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Comparison of a Very-fine-resolution GCM with RCM Dynamical Downscaling in Simulating Climate in China


doi: 10.1007/s00376-015-5147-y

  • Regional climate simulation can generally be improved by using an RCM nested within a coarser-resolution GCM. However, whether or not it can also be improved by the direct use of a state-of-the-art GCM with very fine resolution, close to that of an RCM, and, if so, which is the better approach, are open questions. These questions are important for understanding and using these two kinds of simulation approaches, but have not yet been investigated. Accordingly, the present reported work compared simulation results over China from a very-fine-resolution GCM (VFRGCM) and from RCM dynamical downscaling. The results showed that: (1) The VFRGCM reproduces the climatologies and trends of both air temperature and precipitation, as well as inter-monthly variations of air temperature in terms of spatial pattern and amount, closer to observations than the coarse-resolution version of the GCM. This is not the case, however, for the inter-monthly variations of precipitation. (2) The VFRGCM captures the climatology, trend, and inter-monthly variation of air temperature, as well as the trend in precipitation, more reasonably than the RCM dynamical downscaling method. (3) The RCM dynamical downscaling method performs better than the VFRGCM in terms of the climatology and inter-monthly variation of precipitation. Overall, the results suggest that VFRGCMs possess great potential with regard to their application in climate simulation in the future, and the RCM dynamical downscaling method is still dominant in terms of regional precipitation simulation.
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  • Collins W., Coauthors, 2004: Description of the NCAR community atmosphere model (CAM 3.0). NCAR Tech Note NCAR/TN-464+STR,214 pp.10.5065/D63N21CH255ddb666d9a21c12a4ac5021116e854http%3A%2F%2Fdx.doi.org%2F10.5065%2FD63N21CHhttp://dx.doi.org/10.5065/D63N21CHThis report presents the details of the governing equations, physical parameterizations, and numerical algorithms defining the version of the NCAR Community Atmosphere Model designated CAM 3.0. The material provides an overview of the major model components,
    Dickinson R. E., R. M. Errico, F. Giorgi, and G. T. Bates, 1989: A regional climate model for the western United States. Climatic Change, 15, 383- 422.10.1007/BF00240465552bf5a7d2091f9921b948564cdb527chttp%3A%2F%2Flink.springer.com%2Farticle%2F10.1007%2FBF00240465http://onlinelibrary.wiley.com/resolve/reference/XREF?id=10.1007/BF00240465We simulate global climate for three years with CCM1/BATS and describe the resulting January surface climatology over the western U.S. The details of the precipitation patterns are unrealistic because of the smooth topography. Selecting five January CCM1 storms that occur over the western U.S. with a total duration of 20 days for simulation with the MM4, we demonstrate that the mesoscale model provides much improved wintertime precipitation patterns. The storms in MM4 are individually much more realistic than those in CCM1. A simple averaging procedure that infers a mean January rainfall climatology calculated from the 20 days of MM4 simulation is much closer to the observed than is the CCM1 climatology. The soil moisture and subsurface drainage simulated over 3-5 day integration periods of MM4, however, remain strongly dependent on the initial CCM1 soil moisture and thus are less realistic than the rainfall. Adequate simulation of surface soil water may require integrations of the mesoscale model over time periods.
    Endris H.S., Coauthors, 2013: Assessment of the performance of CORDEX regional climate models in simulating East African rainfall. J. Climate, 26, 8453- 8475.66a30860ecc9b44ba9403f621f17bc7ehttp%3A%2F%2Fadsabs.harvard.edu%2Fcgi-bin%2Fnph-data_query%3Fbibcode%3D2013JCli...26.8453E%26db_key%3DPHY%26link_type%3DABSTRACT%26high%3D25132/s?wd=paperuri%3A%28da1a7ca88e0a1affd83cc021a7db07f9%29&filter=sc_long_sign&tn=SE_xueshusource_2kduw22v&sc_vurl=http%3A%2F%2Fadsabs.harvard.edu%2Fcgi-bin%2Fnph-data_query%3Fbibcode%3D2013JCli...26.8453E%26db_key%3DPHY%26link_type%3DABSTRACT%26high%3D25132&ie=utf-8
    Gao X., Y. Shi, R. Song, F. Giorgi, Y. Wang, and D. Zhang, 2008: Reduction of future monsoon precipitation over China: Comparison between a high resolution RCM simulation and the driving GCM. Meteor. Atmos. Phys., 100, 73- 86.10.1007/s00703-008-0296-5605435149c1fa535eb78c1049be7faa9http%3A%2F%2Flink.springer.com%2Farticle%2F10.1007%2Fs00703-008-0296-5http://link.springer.com/article/10.1007/s00703-008-0296-5Multi-decadal high resolution climate change simulations over East Asia are performed using the Abdus Salam International Centre for Theoretical Physics (ICTP) Regional Climate Model, RegCM3, nested within the NASA/NCAR global model FvGCM. Two sets of simulations are conducted at 20-km grid spacing for present day and future climate (IPCC A2 scenario). The mean precipitation change during the monsoon season (May to September) over China is analyzed and intercompared between the RegCM and FvGCM. Simulation of the present day precipitation by the RegCM shows a better performance than that of the driving FvGCM in terms of both spatial pattern and amount. The main improvement of the RegCM is the removal of an artificial precipitation center over the eastern edge of the Tibetan Plateau simulated by the FvGCM. The FvGCM simulates a predominant increase of precipitation over the region, whereas the RegCM shows extended areas of decrease. The causes of these differences are investigated and explained in terms of the different topographical forcing on circulation and moisture flux in the two models. We also find that the RegCM-simulated changes are in better agreement with observed precipitation trends over East Asia. It is suggested that high resolution models are needed to better investigate future climate projections over China and East Asia.
    Gao X. J., Y. Shi, D. F. Zhang, and F. Giorgi, 2012: Climate change in China in the 21st century as simulated by a high resolution regional climate model. Chinese Science Bulletin, 57, 1188- 1195.10.1007/s11434-011-4935-8b9b6c9bcba213efe45b79f30df52f093http%3A%2F%2Fwww.cnki.com.cn%2FArticle%2FCJFDTotal-JXTW201210013.htmhttp://www.cnki.com.cn/Article/CJFDTotal-JXTW201210013.htm
    Gao X. J., M. L. Wang, and F. Giorgi, 2013: Climate change over China in the 21st century as simulated by BCC_CSM1.1-RegCM4.0. Atmos. Oceanic Sci. Lett., 6, 381- 386.10.3878/j.issn.1674-2834.13.00294616eec0ee0677e774cb320e63ebaa19http%3A%2F%2Fwww.cqvip.com%2FQK%2F89435X%2F201305%2F47350094.htmlhttp://d.wanfangdata.com.cn/Periodical_dqhhykxkb201305028.aspxDriven by the global model,Beijing Climate Center Climate System Model version 1.1(BCC_CSM1.1),climate change over China in the 21st century is simulated by a regional climate model(RegCM4.0)under the new emission scenarios of the Representative Concentration Pathways-CP4.5 and RCP8.5.This is based on a period of transient simulations from 1950 to2099,with a grid spacing of 50 km.The present paper focuses on the annual mean temperature and precipitation in China over this period,with emphasis on their future changes.Validation of model performance reveals marked improvement of the RegCM4.0 model in reproducing present day temperature and precipitation relative to the driving BCC_CSM1.1 model.Significant warming is simulated by both BCC_CSM1.1 and RegCM4.0,however,spatial distribution and magnitude differ between the simulations.The high emission scenario RCP8.5 results in greater warming compared to RCP4.5.The two models project different precipitation changes,characterized by a general increase in the BCC_CSM1.1,and broader areas with decrease in the RegCM4.0 simulations.
    Giorgi F., 1990: Simulation of regional climate using a limited area model nested in a general circulation model. J. Climate, 3, 941- 964.10.1175/1520-0442(1990)0032.0.CO;2366c9480cd1f7756929e688237ad2fe7http%3A%2F%2Fadsabs.harvard.edu%2Fabs%2F1990JCli....3..941Ghttp://adsabs.harvard.edu/abs/1990JCli....3..941GAbstract A Limited Area Model (LAM) is nested in a General Circulation Model (GCM) to simulate the January climate over the western United States. In the nesting procedure, the GCM output is used to provide the initial and lateral atmospheric boundary conditions necessary to drive the LAM. In this approach, the GCM is used to simulate realistic large-scale atmospheric behavior over an area of interest and the LAM to describe the effect of local, sub-GCM grid scale forcings (such as those induced by the complex western United States topography) on regional patterns of climatic variables. Two versions of the National Center for Atmospheric Research (NCAR) Community Climate Model [the seasonal CCM1 at 4.5 7.5 (R15) and 2.89 2.89 (T42) latitude-longitude resolution] are used to drive a version of the Pennsylvania State University/NCAR mesoscale model (MM4 at 60 km resolution), which includes sophisticated soil hydrology calculations. The CCM1 large-scale January climatology over the region is analyzed first. Comparison with large-scale observations shows that geopotential height, zonal wind, temperature, relative humidity, cloudiness, precipitation and storm frequencies over the western United States and adjacent oceans are realistically simulated by both the T42 and R15 models. The T42 model, however, reproduces storm frequencies and strength and position of the jet stream better than the R15 model. A number of month-long January simulations were performed using both the R15 and T42 model outputs to drive the MM4. The large-scale average circulations over the western United States simulated by the nested MM4 are not substantially different from those of the driving CCM1, both when outputs from the R15 and T42 versions are used to drive the MM4. Owing to the more realistic topography in the MM4, the nested model system produces better regional detail of precipitation and temperature distribution than the CCM1 alone. Temperature and precipitation means, as well as frequencies of daily precipitation intensifies simulated by the nested MM4, compare well with high resolution observations, particularly in their spatial distribution. Also discussed am results of regional snow cover, cloudiness, and soil hydrology calculations included in the MM4.
    Giorgi F., G. T. Bates, 1989: On the climatological skill of a regional model over complex terrain. Mon. Wea. Rev., 117, 2325- 2347.10.1175/1520-0493(1989)117<2325:TCSOAR>2.0.CO;2b4750e21-b75c-4aaf-9c76-6f04130caee7ee6c5a31456c2b641bc7e916d47b9114http%3A%2F%2Fwww.researchgate.net%2Fpublication%2F234177204_The_Climatological_Skill_of_a_Regional_Model_over_Complex_Terrainrefpaperuri:(4448cbef4416f87b403328e0e081a0c8)http://www.researchgate.net/publication/234177204_The_Climatological_Skill_of_a_Regional_Model_over_Complex_TerrainABSTRACT
    Giorgi F., M. R. Marinucci, and G. T. Bates, 1993a: Development of a second-generation regional climate model (RegCM2). Part I: Boundary layer and radiative transfer processes. Mon. Wea. Rev., 121, 2794- 2813.10.1175/1520-0493(1993)1212.0.CO;2a6c529b2-33df-4a0b-a9f3-1f28e6aaaceb21d14709deeac7520a50643b89fd63c5http%3A%2F%2Fadsabs.harvard.edu%2Fabs%2F1993MWRv..121.2794Grefpaperuri:(bf1a89a4dcf40eacfab61db74f692889)http://adsabs.harvard.edu/abs/1993MWRv..121.2794GDuring the last few years the development of a second-generation regional climate modeling system (RegCM2) has been completed at the National Center for Atmospheric Research (NCAR). Based upon the National Center for Atmospheric Research-Pennsylvania State University Mesoscale Model (MM4), RegCM2 includes improved formulations of boundary layer, radiative transfer, surface physics, cumulus convection, and time integration technique, which make it more physically comprehensive and more computationally efficient than the previous regional climate model version. This paper discusses a number of month-long simulations over the European region that were conducted to test the new RegCM2 boundary-layer parameterization (the scheme developed by Holtsag et al.) and radiative transfer formulation [the package developed for the NCAR Community Climate Model 2 (CCM2)]. Both schemes significantly affect the model precipitation, temperature, moisture, and cloudiness climatology, leading to overall more realistic results, while they do not substantially modify the model performance in simulating the aggregated characteristics of synoptic patterns. Description of the convective processes and procedures of boundary condition assimilation included in RegCM2 is presented in companion paper by Giorgi et al. 26 refs., 11 figs., 10 tabs.
    Giorgi F., M. R. Marinucci, G. T. Bates, and G. D. Canio, 1993b: Development of a second-generation regional climate model (RegCM2). Part II: Convective processes and assimilation of lateral boundary conditions. Mon. Wea. Rev., 121, 2814- 2832.b7a9e5b626dff25baaa718226e5f449dhttp%3A%2F%2Fadsabs.harvard.edu%2Fabs%2F1993MWRv..121.2814G/s?wd=paperuri%3A%289ea03fff7b47314084893226a4e6dff1%29&filter=sc_long_sign&tn=SE_xueshusource_2kduw22v&sc_vurl=http%3A%2F%2Fadsabs.harvard.edu%2Fabs%2F1993MWRv..121.2814G&ie=utf-8
    Guo D. L., H. J. Wang, 2013: Simulation of permafrost and seasonally frozen ground conditions on the Tibetan Plateau, 1981-2010. J.Geophys. Res., 118, 5216- 5230.
    Guo D. L., H. J. Wang, 2014: Simulated change in the near-surface soil freeze/thaw cycle on the Tibetan Plateau from 1981 to 2010. Chinese Science Bulletin, 59, 2439- 2448.10.1007/s11434-014-0347-x15718068df91ce5bc5ef5605c9e626a66b8b74eahttp%3A%2F%2Flink.springer.com%2Farticle%2F10.1007%2Fs11434-014-0347-xhttp://www.cnki.com.cn/Article/CJFDTotal-JXTW201420008.htmThe near-surface freeze/thaw cycle in cold regions plays a major role in the surface energy budget,hydrological activity,and terrestrial ecosystems.In this study,the Community Land Model,Version 4 and a suite of high-resolution atmospheric data were used to investigate the changes in the near-surface soil freeze/thaw cycle in response to the warming on the Tibetan Plateau from1981 to 2010.The in situ observations-based validation showed that,considering the cause of scale mismatch in the comparison,the simulated soil temperature,freeze start and end dates,and freeze duration at the near-surface were reasonable.In response to the warming of the Tibetan Plateau at a rate of approximately 0.44C decade-1,the freeze start-date became delayed at an area-mean rate of1.7 days decade-1,while the freeze end-date became advanced at an area-mean rate of 4.7 days decade-1.The delaying of the freeze start-date,which was combined with the advancing of the freeze end-date,resulted in a statistically significant shortening trend with respect to the freeze duration,at an area-mean rate of 6.4 days decade-1.Such changes would strongly affect the surface energy flux,hydrological processes,and vegetation dynamics.We also found that the rate of freeze-duration shortening at the near-surface soil layer was approximately 3.0 days decade-1lower than that at a depth of 1 m.This implied that the changes in soil freeze/thaw cycles at the near surface cannot be assumed to reflect the situation in deeper soil layers.The significant correlations between freeze duration and air temperature indicated that the shortening of the near-surface freeze duration was caused by the rise in air temperature,which occurred especially in spring,followed by autumn.These results can be used to reveal the laws governing the response of the near-surface freeze/thaw cycle to climate change and indicate related changes in permafrost.
    Guo D. L., H. J. Wang, and D. Li, 2012: A projection of permafrost degradation on the Tibetan Plateau during the 21st century. J. Geophys. Res., 117,D05106, doi: 10.1029/2011JD 016545.10.1029/2011JD0165458a7eeb93c4a7d971914738bed33a95b7http%3A%2F%2Fonlinelibrary.wiley.com%2Fdoi%2F10.1029%2F2011JD016545%2Fcitedbyhttp://onlinelibrary.wiley.com/doi/10.1029/2011JD016545/citedby[1] The current distribution and future change of permafrost on the Tibetan Plateau were examined using the Community Land Model version 4 (CLM4) with explicit treatment of frozen soil processes. When forced off-line with archived high-resolution data from The Abdus Salam International Centre for Theoretical Physics Regional Climate Model version 3 nested within the Model for Interdisciplinary Research on Climate 3.2 HiRes, the CLM4 produced a near-surface permafrost area of 122.2 &times; 10 4 km 2 for the Tibetan Plateau. This area compares reasonably with area estimates of 126.7 &times; 10 4 km 2 for the Plateau frozen soil map. In response to the simulated strong Plateau warming (approximately 0.58C per decade over the Tibetan Plateau for the period from 1980 to 2100 under the A1B greenhouse gas emissions scenario), the near-surface permafrost area is projected to decrease by approximately 39% by the mid-21st century and by approximately 81% by the end of the 21st century. The near-surface permafrost area exhibits a significant decreasing linear trend, with a rate of decrease of 9.9 &times; 10 4 km 2 per decade. The simulated deep permafrost area remains longer than the near-surface permafrost for the same period. The active layer thickness of 0.5&ndash;1.5 m found in the present-day increases to approximately 1.5&ndash;2.0 m by the period of 2030&ndash;2050. This increase will continue and reach a level of 2.0&ndash;3.5 m by the period of 2080&ndash;2100. Surface runoff decreases but subsurface runoff increases, both relative to the difference between precipitation and evapotranspiration. This is related to the fact that the decrease in ground ice content, as caused by permafrost degradation, facilitates the percolation of more water to deeper soil layers, thus resulting in the reallocation of runoff. These results provide useful references for evaluating the level of permafrost degradation in response to climate warming on the Tibetan Plateau.
    Hasumi H., S. Emori, 2004: K-1 model developers: K-1 coupled model (MIROC) description. K-1 Tech. Rep. 1,Cent. for Clim. Syst. Res., Univ. Tokyo, Tokyo, Japan, 34 pp.
    Hirabayashi Y., S. Kanae, I. Struthers, and T. Oki, 2005: A 100-year (1901-2000) global retrospective estimation of the terrestrial water cycle. J. Geophys. Res., 110,D19101, doi: 10.1029/2004JD005492.10.1029/2004JD005492d39eac2cda5aea9f6dff8bfa98e1f7b4http%3A%2F%2Fonlinelibrary.wiley.com%2Fdoi%2F10.1029%2F2004JD005492%2Ffullhttp://onlinelibrary.wiley.com/doi/10.1029/2004JD005492/full[1] A 100-year off-line simulation using a land surface model (LSM) was completed. The long-term terrestrial water fluxes were estimated well using a LSM driven by long-term atmospheric forcing data that were stochastically estimated from monthly mean time series of precipitation and temperature. While high correlations between predicted and observed annual runoff are obtained at many basins globally, correlations are low in dry areas and in cool-temperate zones. These deficiencies of the simulation point out which model processes should be investigated, which can lead to improved representation of land surface processes in future LSMs from a global viewpoint. Annual snow covered area in North America and northern Europe and annual summer soil moisture in Mongolia were successfully replicated by the model. The descending trend of snow covered area in North America and Europe and the increasing trend of summer soil moisture in Mongolia, that were indicated by previous studies, were also replicated by the simulation. With the benefit of 100-year simulation results for these variables, however, these trends appear to reflect natural long-term variability rather than systematic changes in hydroclimatological condition. The long-term estimation of hydrological components, such as annual and inter-annual variation of runoff, snow and soil moisture, would be useful for examining behaviors of a LSM. The methodology used in this study also has applicability for long-term water resources assessment in poorly gauged basins, where long-term atmospheric data are only available at a monthly scale, by providing predictions of extreme behavior and long-term natural variability in various hydrological components.
    Hong S. Y., J. O. J. Lim, 2006: The WRF single-moment 6-class microphysics scheme (WSM6). Journal of the Korean Meteorological Society, 42, 129- 151.7308c59e0fe08d8147ff5b2869261e63http%3A%2F%2Fwww.dbpia.co.kr%2FJournal%2FArticleDetail%2F773025http://www.dbpia.co.kr/Journal/ArticleDetail/773025This study examines the performance of the Weather Research and Forecasting (WRF)-Single-Moment- Microphysics scheme (WSMMPs) with a revised ice-microphysics of the Hong et al. In addition to the simple (WRF Single-Moment 3-class Microphysics scheme; WSM3) and mixed-phase (WRF Single-Moment 5-class Microphysics scheme; WSM5) schemes of the Hong et al., a more complex scheme with the inclusion of graupel as another predictive variable (WRF Single-Moment 6-class Microphysics scheme; WSM6) was developed. The characteristics of the three categories of WSMMPs were examined for an idealized storm case and a heavy rainfall event over Korea. In an idealized thunderstorm simulation, the overall evolutionary features of the storm are not sensitive to the number of hydrometeors in the WSMMPs; however, the evolution of surface precipitation is significantly influenced by the complexity in microphysics. A simulation experiment for a heavy rainfall event indicated that the evolution of the simulated precipitation with the inclusion of graupel (WSM6) is similar to that from the simple (WSM3) and mixed-phase (WSM5) microphysics in a low-resolution grid; however, in a high-resolution grid, the amount of rainfall increases and the peak intensity becomes stronger as the number of hydrometeors increases.
    Hong S. Y., Y. Noh, and J. Dudhia, 2006: A new vertical diffusion package with an explicit treatment of entrainment processes. Mon. Wea. Rev., 134, 2318- 2341.10.1175/MWR3199.179f98ee85a3853a6bfee0ec84e90c901http%3A%2F%2Fadsabs.harvard.edu%2Fabs%2F2006MWRv..134.2318Hhttp://adsabs.harvard.edu/abs/2006MWRv..134.2318HAbstract This paper proposes a revised vertical diffusion package with a nonlocal turbulent mixing coefficient in the planetary boundary layer (PBL). Based on the study of Noh et al. and accumulated results of the behavior of the Hong and Pan algorithm, a revised vertical diffusion algorithm that is suitable for weather forecasting and climate prediction models is developed. The major ingredient of the revision is the inclusion of an explicit treatment of entrainment processes at the top of the PBL. The new diffusion package is called the Yonsei University PBL (YSU PBL). In a one-dimensional offline test framework, the revised scheme is found to improve several features compared with the Hong and Pan implementation. The YSU PBL increases boundary layer mixing in the thermally induced free convection regime and decreases it in the mechanically induced forced convection regime, which alleviates the well-known problems in the Medium-Range Forecast (MRF) PBL. Excessive mixing in the mixed layer in the presence of strong winds is resolved. Overly rapid growth of the PBL in the case of the Hong and Pan is also rectified. The scheme has been successfully implemented in the Weather Research and Forecast model producing a more realistic structure of the PBL and its development. In a case study of a frontal tornado outbreak, it is found that some systematic biases of the large-scale features such as an afternoon cold bias at 850 hPa in the MRF PBL are resolved. Consequently, the new scheme does a better job in reproducing the convective inhibition. Because the convective inhibition is accurately predicted, widespread light precipitation ahead of a front, in the case of the MRF PBL, is reduced. In the frontal region, the YSU PBL scheme improves some characteristics, such as a double line of intense convection. This is because the boundary layer from the YSU PBL scheme remains less diluted by entrainment leaving more fuel for severe convection when the front triggers it.
    Johns, T. C., Coauthors, 2003: Anthropogenic climate change for 1860 to 2100 simulated with the HadCM3 model under updated emissions scenarios. Climate Dyn., 20, 583- 612.10.1007/s00382-002-0296-yc84c3c119a1a97ba5a90b099cbf60424http%3A%2F%2Fwww.springerlink.com%2Findex%2F4JL70H7CXFQGHLVK.pdfhttp://www.springerlink.com/index/4JL70H7CXFQGHLVK.pdfIn this study we examine the anthropogenically forced climate response over the historical period, 1860 to present, and projected response to 2100, using updated emissions scenarios and an improved coupled model (HadCM3) that does not use flux adjustments. We concentrate on four new Special Report on Emission Scenarios (SRES) namely (A1FI, A2, B2, B1) prepared for the Intergovernmental Panel on Climate Change Third Assessment Report, considered more self-consistent in their socio-economic and emissions structure, and therefore more policy relevant, than older scenarios like IS92a. We include an interactive model representation of the anthropogenic sulfur cycle and both direct and indirect forcings from sulfate aerosols, but omit the second indirect forcing effect through cloud lifetimes. The modelled first indirect forcing effect through cloud droplet size is near the centre of the IPCC uncertainty range. We also model variations in tropospheric and stratospheric ozone. Greenhouse gas-forced climate change response in B2 resembles patterns in IS92a but is smaller. Sulfate aerosol and ozone forcing substantially modulates the response, cooling the land, particularly northern mid-latitudes, and altering the monsoon structure. By 2100, global mean warming in SRES scenarios ranges from 2.6 to 5.3 K above 1900 and precipitation rises by 1%/K through the twenty first century (1.4%/K omitting aerosol changes). Large-scale patterns of response broadly resemble those in an earlier model (HadCM2), but with important regional differences, particularly in the tropics. Some divergence in future response occurs across scenarios for the regions considered, but marked drying in the mid-USA and southern Europe and significantly wetter conditions for South Asia, in June09.uly09.ugust, are robust and significant.
    Ju L. X., H. J. Wang, and D. B. Jiang, 2007: Simulation of the Last Glacial Maximum climate over East Asia with a regional climate model nested in a general circulation model. Palaeogeography, Palaeoclimatology, Palaeoecology, 248, 376- 390.10.1016/j.palaeo.2006.12.0128b7c9752-febd-43b5-80a1-89dc86a2d095e55831a98e3fdd79f17d073b31594ab1http%3A%2F%2Fwww.sciencedirect.com%2Fscience%2Farticle%2Fpii%2FS0031018207000041refpaperuri:(183983d49a63cbaeb93632ce1d7d5777)http://www.sciencedirect.com/science/article/pii/S0031018207000041The East Asian climate at the Last Glacial Maximum (LGM, 21,000 years B.P.) has been simulated using a regional climate model (RegCM2) nested in an atmospheric general circulation model of the Institute of Atmospheric Physics (IAP-AGCM). Boundary conditions for the LGM simulations are consistent with the Paleoclimate Modelling Intercomparison Project (PMIP). The results show that the nested regional model reproduces well the colder LGM climates over East Asia. The simulated annual mean surface temperature is 2 °C–4 °C colder than the present over the East Asian continent, with the coldest anomaly of about 8 °C in the vicinity of current coastal areas, where land is exposed due to lowering sea level at the LGM. The precipitation changes are complex, with general features of drier conditions over eastern China and its neighborhood and wetter conditions over western China than the present. Compared with the driving IAP-AGCM, the RegCM2 results display better agreement with geological reconstructions over East Asia. Especially in the mideastern and southern China, the simulated warming changes by the IAP-AGCM disagree with cooling in paleodata, whereas the RegCM2 reproduces realistic cooler LGM climate. Thus the current work proves that the high-resolution RegCM2 can capture additional regional details in the LGM simulation, produced by improved representation of topography and physics.
    Kain J. S., 2004: The Kain-Fritsch convective parameterization: an update. J. Appl. Meteor., 43, 170- 181.10.1175/1520-0450(2004)0432.0.CO;2ffaf6864-fb52-4cbf-8506-091280c94123244bcc8e65764e4fc4627a1b53bfa036http://www.researchgate.net/publication/280801529_The_Kain_-_Fritsch_convective_parameterization_An_updatehttp://www.researchgate.net/publication/280801529_The_Kain_-_Fritsch_convective_parameterization_An_updateAbstract Numerous modifications to the Kain-ritsch convective parameterization have been implemented over the last decade. These modifications are described, and the motivating factors for the changes are discussed. Most changes were inspired by feedback from users of the scheme (primarily numerical modelers) and interpreters of the model output (mainly operational forecasters). The specific formulation of the modifications evolved from an effort to produce desired effects in numerical weather prediction while also rendering the scheme more faithful to observations and cloud-resolving modeling studies.
    Kiehl J. T., J. J. Hack, G. B. Bonan, B. A. Boville, B. P. Breigleb, D. L. Williamson, and P. J. Rasch, 1996: Description of the NCAR Community Climate Model (CCM3). NCAR Technical Note, NCAR/TN-420+STR, 152 pp.10.5065/D6FF3Q99d167287356dced34ab1b1f9cdc3e5ccdhttp%3A%2F%2Fdx.doi.org%2F10.5065%2FD6FF3Q99http://dx.doi.org/10.5065/D6FF3Q99A Special Library for atmospheric, solar and earth system research.
    Kodama, C., Coauthors, 2015: A 20-year climatology of a NICAM AMIP-type simulation. J. Meteor. Soc. Japan,93, 393-424, doi: 10.2151/jmsj.2015-024.77fc62eab40a2e0c47c4db3683ea05d8http%3A%2F%2Fci.nii.ac.jp%2Flognavi%3Fname%3Dcrossref%26id%3Dinfo%3Adoi%2F10.2151%2Fjmsj.2015-024/s?wd=paperuri%3A%28080296905625b2682e2615a885507889%29&filter=sc_long_sign&tn=SE_xueshusource_2kduw22v&sc_vurl=http%3A%2F%2Fci.nii.ac.jp%2Flognavi%3Fname%3Dcrossref%26id%3Dinfo%3Adoi%2F10.2151%2Fjmsj.2015-024&ie=utf-8
    Lamarque, J. F., Coauthors, 2010: Historical (1850-2000) gridded anthropogenic and biomass burning emissions of reactive gases and aerosols: Methodology and application. Atmos. Chem. Phys., 10, 7017- 7039.
    Lean J., J. Beer, and R. Bradley, 1995: Reconstruction of solar irradiance since 1610: Implications for climate change. Geophys. Res. Lett., 22, 3195- 3198.10.1029/95GL030938e40ecb562da253151cbbedd2063523fhttp%3A%2F%2Fonlinelibrary.wiley.com%2Fdoi%2F10.1029%2F95GL03093%2Fabstracthttp://onlinelibrary.wiley.com/doi/10.1029/95GL03093/abstractSolar total and ultraviolet (UV) irradiances are reconstructed annually from 1610 to the present. This epoch includes the Maunder Minimum of anomalously low solar activity (circa 1645–1715) and the subsequent increase to the high levels of the present Modern Maximum. In this reconstruction, the Schwabe (11‐year) irradiance cycle and a longer term variability component are determined separately, based on contemporary solar and stellar monitoring. The correlation of reconstructed solar irradiance and Northern Hemisphere (NH) surface temperature is 0.86 in the pre‐industrial period from 1610 to 1800, implying a predominant solar influence. Extending this correlation to the present suggests that solar forcing may have contributed about half of the observed 0.55°C surface warming since 1860 and one third of the warming since 1970.
    Lefohn A. S., J. D. Husar, and R. B. Husar, 1999: Estimating historical anthropogenic global sulfur emission patterns for the period 1850-1990. Atmos. Environ., 33, 3435- 3444.10.1016/S1352-2310(99)00112-088489878-db46-4dc4-970c-4201fc338c38796e9e27c5f12a20dcc035aa2a9f727fhttp%3A%2F%2Fwww.sciencedirect.com%2Fscience%2Farticle%2Fpii%2FS1352231099001120refpaperuri:(2109471ef6f08236185ccdcc6ae2ba5b)http://www.sciencedirect.com/science/article/pii/S1352231099001120It is important to establish a reliable regional emission inventory of sulfur as a function of time when assessing the possible effects of global change and acid rain. This study developed a database of annual estimates of national sulfur emissions from 1850 to 1990. A common methodology was applied across all years and countries allowing for global totals to be produced by adding estimates from all countries. The consistent approach facilitates the modification of the database and the observation of changes at national, regional, or global levels. The emission estimates were based on net production (i.e., production plus imports minus exports), sulfur content, and sulfur retention for each country's production activities. Because the emission estimates were based on the above considerations, our database offers an opportunity to independently compare our results with those estimates based on individual country estimates. Fine temporal resolution clearly shows emission changes associated with specific historical events (e.g., wars, depressions, etc.) on a regional, national, or global basis. The spatial pattern of emissions shows that the US, the USSR, and China were the main sulfur emitters (i.e., approximately 50% of the total) in the world in 1990. The USSR and the US appear to have stabilized their sulfur emissions over the past 20 yr, and the recent increases in global sulfur emissions are linked to the rapid increases in emissions from China. Sulfur emissions have been reduced in some cases by switching from high- to low-sulfur coals. Flue gas desulfurization (FGD) has apparently made important contributions to emission reductions in only a few countries, such as Germany.
    Lin S. J., R. B. Rood, 1996: Multidimensional flux-form semi-Lagrangian transport schemes. Mon. Wea. Rev., 124, 2046- 2070.10.1175/1520-0493(1996)1242.0.CO;2a6b5b2f1b8ff9ddd27b0c7311630508dhttp%3A%2F%2Fadsabs.harvard.edu%2Fabs%2F1996MWRv..124.2046Lhttp://adsabs.harvard.edu/abs/1996MWRv..124.2046LABSTRACT An algorithm for extending one-dimensional, forward-in-time, upstream-biased, flux-form transport schemes (e.g., the van Leer scheme and the piecewise parabolic method) to multidimensions is proposed. A method is also proposed to extend the resulting Eulerian multidimensional flux-form scheme to arbitrarily long time steps. Because of similarities to the semi-Lagrangian approach of extending time steps, the scheme is called flux-form semi-Lagrangian (FFSL). The FFSL scheme can be easily and efficiently implemented on the sphere. Idealized tests as well as realistic three-dimensional global transport simulations using winds from data assimilation systems are demonstrated. Stability is analyzed with a von Neuman approach as well as empirically on the 2D Cartesian plane. The resulting algorithm is conservative and upstream biased. In addition, it contains monotonicity constraints and conserves tracer correlations, therefore representing the physical characteristics of constituent transport.
    Lucarini V., S. Calmanti, A. Dell'Aquila, P. M. Ruti, and A. Speranza, 2007: Intercomparison of the northern hemisphere winter mid-latitude atmospheric variability of the IPCC models. Climate Dyn., 28, 829- 848.10.1007/s00382-006-0213-x2d5ed8f04f289018fd337b64f3bf1f40http%3A%2F%2Fwww.springerlink.com%2Fcontent%2Fx79862ggl0t15623%2Fhttp://www.springerlink.com/content/x79862ggl0t15623/Abstract: We compare, for the overlapping time frame 1962-2000, the estimate of the northern hemisphere (NH) mid-latitude winter atmospheric variability within the XX century simulations of 17 global climate models (GCMs) included in the IPCC-4AR with the NCEP and ECMWF reanalyses. We compute the Hayashi spectra of the 500hPa geopotential height fields and introduce an integral measure of the variability observed in the NH on different spectral sub-domains. Only two high-resolution GCMs have a good agreement with reanalyses. Large biases, in most cases larger than 20%, are found between the wave climatologies of most GCMs and the reanalyses, with a relative span of around 50%. The travelling baroclinic waves are usually overestimated, while the planetary waves are usually underestimated, in agreement with previous studies performed on global weather forecasting models. When comparing the results of various versions of similar GCMs, it is clear that in some cases the vertical resolution of the atmosphere and, somewhat unexpectedly, of the adopted ocean model seem to be critical in determining the agreement with the reanalyses. The GCMs ensemble is biased with respect to the reanalyses but is comparable to the best 5 GCMs. This study suggests serious caveats with respect to the ability of most of the presently available GCMs in representing the statistics of the global scale atmospheric dynamics of the present climate and, a fortiori, in the perspective of modelling climate change.
    Ma J. H., H. J. Wang, and K. Fan, 2015: Dynamic downscaling of summer precipitation prediction over China in 1998 using WRF and CCSM4. Adv. Atmos. Sci.,32, 577-584, doi: 10.1007/s00376-014-4143-y.10.1007/s00376-014-4143-yab3528ec545a39e57593aed279b0c84ahttp%3A%2F%2Fd.wanfangdata.com.cn%2FPeriodical_dqkxjz-e201505001.aspxhttp://d.wanfangdata.com.cn/Periodical_dqkxjz-e201505001.aspxTo study the prediction of the anomalous precipitation and general circulation for the summer(June-uly-ugust) of1998, the Community Climate System Model Version 4.0(CCSM4.0) integrations were used to drive version 3.2 of the Weather Research and Forecasting(WRF3.2) regional climate model to produce hindcasts at 60 km resolution. The results showed that the WRF model produced improved summer precipitation simulations. The systematic errors in the east of the Tibetan Plateau were removed, while in North China and Northeast China the systematic errors still existed. The improvements in summer precipitation interannual increment prediction also had regional characteristics. There was a marked improvement over the south of the Yangtze River basin and South China, but no obvious improvement over North China and Northeast China. Further analysis showed that the improvement was present not only for the seasonal mean precipitation, but also on a sub-seasonal timescale. The two occurrences of the Mei-yu rainfall agreed better with the observations in the WRF model,but were not resolved in CCSM. These improvements resulted from both the higher resolution and better topography of the WRF model.
    Martynov A., Laprise R., Sushama L., Winger K., šeparović L., andB. Dugas, 2013: Reanalysis-driven climate simulation over CORDEX North America domain using the Canadian Regional Climate Model, version 5: model performance evaluation. Climate Dyn., 41, 2973- 3005.10.1007/s00382-013-1778-9cf75227d-7cc3-4a2c-89dd-14f56e7250726361bcf85653a0453e4b79363f92c6f5http%3A%2F%2Flink.springer.com%2F10.1007%2Fs00382-013-1778-9refpaperuri:(b8df3143ed8e3d64e4156275447fdefc)http://link.springer.com/10.1007/s00382-013-1778-9ABSTRACT The performance of reanalysis-driven Canadian Regional Climate Model, version 5 (CRCM5) in reproducing the present climate over the North American COordinated Regional climate Downscaling EXperiment domain for the 1989&ndash;2008 period has been assessed in comparison with several observation-based datasets. The model reproduces satisfactorily the near-surface temperature and precipitation characteristics over most part of North America. Coastal and mountainous zones remain problematic: a cold bias (2&ndash;6 C) prevails over Rocky Mountains in summertime and all year-round over Mexico; winter precipitation in mountainous coastal regions is overestimated. The precipitation patterns related to the North American Monsoon are well reproduced, except on its northern limit. The spatial and temporal structure of the Great Plains Low-Level Jet is well reproduced by the model; however, the night-time precipitation maximum in the jet area is underestimated. The performance of CRCM5 was assessed against earlier CRCM versions and other RCMs. CRCM5 is shown to have been substantially improved compared to CRCM3 and CRCM4 in terms of seasonal mean statistics, and to be comparable to other modern RCMs.
    Meehl G.A., Coauthors, 2007: Global climate projections. Climate Change 2007: The Physical Science Basis. Contribution of Working Group I to the Fourth Assessment Report of the Intergovernmental Panel on Climate Change, S. Solomon, et al., Eds., Cambridge University Press, Cambridge, United Kingdom and New York,NY, USA, 747- 845.4761652f5a84ef6641e0d523150fbf7bhttp%3A%2F%2Fciteseer.ist.psu.edu%2Fshowciting%3Fcid%3D9113316http://citeseer.ist.psu.edu/showciting?cid=9113316CiteSeerX - Scientific documents that cite the following paper: et al., in Climate Change 2007: The Physical Science Basis. Contribution of Working Group I to the Fourth Assessment Report
    Mizuta R., Coauthors, 2012: Climate simulations using MRI-AGCM3.2 with 20-km grid. J. Meteor. Soc.Japan, 90A, 233- 258.10.2151/jmsj.2012-A120e52d653aa9216f62179d25838a6e23fhttp%3A%2F%2Fci.nii.ac.jp%2Fnaid%2F130004435190%2Fenhttp://ci.nii.ac.jp/naid/130004435190/enA new version of the atmospheric general circulation model of the Meteorological Research Institute (MRI), with a horizontal grid size of about 20 km, has been developed. The previous version of the 20-km model, MRIAGCM3.1, which was developed from an operational numerical weather-prediction model, provided information on possible climate change induced by global warming, including future changes in tropical cyclones, the East Asian monsoon, extreme events, and blockings. For the new version, MRI-AGCM3.2, we have introduced various new parameterization schemes that improve the model climate. Using the new model, we performed a present-day climate experiment using observed sea surface temperature. The model shows improvements in simulating heavy monthly-mean precipitation around the tropical Western Pacific, the global distribution of tropical cyclones, the seasonal march of East Asian summer monsoon, and blockings in the Pacific. Improvements in the model climatologies were confirmed numerically using skill scores (e.g., Taylor's skill score).
    Niu G.Y., Coauthors, 2011: The community Noah land surface model with multiparameterization options (Noah-MP): 1. Model description and evaluation with local-scale measurements. J. Geophys. Res., 116(D12),D12109, doi: 10.1029/ 2010JD015139.10.1029/2010JD015139f363e95e1c0beab3dae85d5aec3482ddhttp%3A%2F%2Fonlinelibrary.wiley.com%2Fdoi%2F10.1029%2F2010JD015139%2Ffullhttp://onlinelibrary.wiley.com/doi/10.1029/2010JD015139/fullThis first paper of the two-part series describes the objectives of the community efforts in improving the Noah land surface model (LSM), documents, through mathematical formulations, the augmented conceptual realism in biophysical and hydrological processes, and introduces a framework for multiple options to parameterize selected processes (Noah-MP). The Noah-MP's performance is evaluated at various local sites using high temporal frequency data sets, and results show the advantages of using multiple optional schemes to interpret the differences in modeling simulations. The second paper focuses on ensemble evaluations with long-term regional (basin) and global scale data sets. The enhanced conceptual realism includes (1) the vegetation canopy energy balance, (2) the layered snowpack, (3) frozen soil and infiltration, (4) soil moisture-groundwater interaction and related runoff production, and (5) vegetation phenology. Sample local-scale validations are conducted over the First International Satellite Land Surface Climatology Project (ISLSCP) Field Experiment (FIFE) site, the W3 catchment of Sleepers River, Vermont, and a French snow observation site. Noah-MP shows apparent improvements in reproducing surface fluxes, skin temperature over dry periods, snow water equivalent (SWE), snow depth, and runoff over Noah LSM version 3.0. Noah-MP improves the SWE simulations due to more accurate simulations of the diurnal variations of the snow skin temperature, which is critical for computing available energy for melting. Noah-MP also improves the simulation of runoff peaks and timing by introducing a more permeable frozen soil and more accurate simulation of snowmelt. We also demonstrate that Noah-MP is an effective research tool by which modeling results for a given process can be interpreted through multiple optional parameterization schemes in the same model framework.
    Nozawa T., J. Kurokawa, 2006: Historical and future emissions of sulfur dioxide and black carbon for global and regional climate change studies. CGER-Report, CGER/NIES, Tsukuba, Japan.
    Nozawa T., T. Nagashima, T. Ogura, T. Yokohata, N. Okada, H. Shiogama, 2007: Climate change simulations with a coupled ocean-atmosphere GCM called the model for interdisciplinary research on climate: MIROC. CGER-Report, CGER/NIES, Tsukuba, Japan, 79 pp.e6a4dcf64a2031b7b00e1c437fc640f1http%3A%2F%2Fwww.researchgate.net%2Fpublication%2F242573669_Climate_Change_Simulations_with_a_Coupled_Ocean-Atmosphere_GCM_Called_the_Model_for_Interdisciplinary_Research_on_Climate_MIROChttp://www.researchgate.net/publication/242573669_Climate_Change_Simulations_with_a_Coupled_Ocean-Atmosphere_GCM_Called_the_Model_for_Interdisciplinary_Research_on_Climate_MIROC
    Pal, J. S., Coauthors, 2007: Regional climate modeling for the developing world: The ICTP RegCM3 and RegCNET. Bull. Amer. Meteor. Soc., 88, 1395- 1409.778ff4532ac62bb38eeb56de13cfcf2fhttp%3A%2F%2Fadsabs.harvard.edu%2Fabs%2F2007BAMS...88.1395P/s?wd=paperuri%3A%28b6290093ecf04d721f21562eb74a8b47%29&filter=sc_long_sign&tn=SE_xueshusource_2kduw22v&sc_vurl=http%3A%2F%2Fadsabs.harvard.edu%2Fabs%2F2007BAMS...88.1395P&ie=utf-8
    Rand el, W. J., F. Wu, 1999: A stratospheric ozone trends data set for global modeling studies. Geophys. Res. Lett., 26, 3089- 3092.10.1029/1999GL900615d87850adf640dd33feaa97cb47fcc91bhttp%3A%2F%2Fonlinelibrary.wiley.com%2Fdoi%2F10.1029%2F1999GL900615%2Fcitedbyhttp://onlinelibrary.wiley.com/doi/10.1029/1999GL900615/citedbyA global stratospheric ozone trends data set is described, providing monthly profile trend estimates derived for the period 1979&ndash;1997. SAGE I/II profile trends are used above 20 km outside of polar regions, and results between the tropopause and 20 km are derived by differencing SAGE and TOMS column ozone trends. In polar regions trends are derived from ozone sonde data up to 27 km, using the near-complete profile records at Syowa (69S) and Resolute (75N). While these polar ozonesonde trends agree well with TOMS outside of polar night, the Arctic data furthermore indicate significant ozone losses beginning in midwinter (January) that are not observable in TOMS data.
    Sakamoto, T. T., Coauthors, 2012: MIROC4h閳ユ柡锟芥摐 new high-resolution atmosphere-ocean coupled general circulation model. J. Meteor. Soc.Japan, 90, 325- 359.
    Sato M., J. E. Hansen, M. P. McCormick, and J. B. Pollack, 1993: Stratospheric aerosol optical depths, 1850-1990. J. Geophys. Res., 98, 22 987- 22 994.10.1029/93JD025531c0959ae-8b23-4095-ae80-5c69292845791a35d79335fffcd6899699c7cea8dfd4http%3A%2F%2Fonlinelibrary.wiley.com%2Fdoi%2F10.1029%2F93JD02553%2Ffullrefpaperuri:(acfddcd885208da9b97a849bf84d2e41)http://onlinelibrary.wiley.com/doi/10.1029/93JD02553/fullABSTRACT A global stratospheric aerosol database employed for climate simulations is described. For the period 1883-1990, aerosol optical depths are estimated from optical extinction data, whose quality increases with time over that period. For the period 1850-1882, aerosol optical depths are more crudely estimated from volcanological evidence for the volume of ejecta from major known volcanoes. The data set is available over Internet.
    Shi Y., 2010: A high resolution climate change simulation of the 21st century over East Asia by RegCM3. Ph. D dissertation, Institute of Atmospheric Physics, Chinese Academy of Science, 117 pp. (in Chinese)81ad1f54d057d2fc3babaf0eb2162719http%3A%2F%2Fadsabs.harvard.edu%2Fabs%2F2010eguga..12.7611ghttp://adsabs.harvard.edu/abs/2010eguga..12.7611gTo meet the increasing demands from the climate change impact assessment studies, a high resolution climate change simulation over East Asia region has being performed in the National Climate Center of the China Meteorological Administration. The model employed in the study is the Abdus Salam International Centre for Theoretical Physics (ICTP) Regional Climate Model (RegCM3). A global model of the CCSR/NIES/FRCGC MIROC3.2_hires is selected to drive RegCM3 because of its high resolution (T106) and its good performances in simulating the present day climate over the region. The simulation is conducted at 25-km grid spacing for the period of 1951-2100. Observed CO2 concentration are used for the present day simulation of 1951-2000 and the emission scenario of IPCC SRES A1B is used as the GHG (greenhouse gases) forcing. Simulations of present day climate over China by RegCM3 and MIROC3.2_hires are compared against observation to valid the model performances. Results show that both models reproduced the general pattern of surface air temperature and precipitation well over the region. Compared to the driving MIROC3.2_hires, RegCM3 provides with more spatial details of the surface fields. Differed from previous GCM-RegCM3 simulations, the RegCM3 did not improves the general pattern of the precipitation due to the good performances of MIROC3.2_hires. Preliminary analysis of the future changes simulated by the two models' show difference, in particular during June-July-August. For example while the MIROC3.2_hires projected a prevailing increase of precipitation in JJA over China, the RegCM3 projected extended areas of decreased precipitation. The data are available for those interested from the community of climate change impacts studies.
    Skamarock, W. C., Coauthors, 2008: A description of the advanced research WRF Version 3. NCAR Tech. Note,TN-475+STR, 113 pp.133fdf5edd3fc85654e5fe959ecf2a0ahttp%3A%2F%2Fntis.library.gatech.edu%2Fhandle%2F123456789%2F2086http://ntis.library.gatech.edu/handle/123456789/2086The development of the Weather Research and Forecasting (WRF) modeling system is a multi-agency effort intended to provide a next-generation mesoscale forecast model and data assimilation system that will advance both the understanding and prediction of mesoscale weather and accelerate the transfer of research advances into operations. The model is being developed as a collaborative effort among the NCAR Mesoscale and Microscale Meteorology (MMM) Division, the National Oceanic and Atmospheric Administration's (NOAA) National Centers for Environmental Prediction (NCEP) and Forecast System Laboratory (FSL), the Department of Defense's Air Force Weather Agency (AFWA) and Naval Research Laboratory (NRL), the Center for Analysis and Prediction of Storms (CAPS) at the University of Oklahoma, and the Federal Aviation Administration (FAA), along with the participation of a number of university scientists. The WRF model is designed to be a flexible, state-of-the-art, portable code that is efficient in a massively parallel computing environment. A modular single-source code is maintained that can be configured for both research and operations. It offers numerous physics options, thus tapping into the experience of the broad modeling community. Advanced data assimilation systems are being developed and tested in tandem with the model. WRF is maintained and supported as a community model to facilitate wide use, particularly for research and teaching, in the university community. It is suitable for use in a broad spectrum of applications across scales ranging from meters to thousands of kilometers. Such applications include research and operational numerical weather prediction (NWP), data assimilation and parameterized-physics research, downscaling climate simulations, driving air quality models, atmosphere-ocean coupling, and idealized simulations (e.g boundary-layer eddies, convection, baroclinic waves). With WRF as a common tool in the university and operational centers, closer ties will be promoted between these communities, and research advances will have a direct path to operations. These hallmarks make the WRF modeling system unique in the history of NWP in the United States.
    Sudo K., M. Takahashi, J. Kurokawa, and H. Akimoto, 2002: CHASER: A global chemical model of the troposphere: 1. Model description. J. Geophys. Res., 107,4339, doi: 10.1029/ 2001JD001113.10.1029/2001JD001113da8b9705-75c4-4504-b9c3-49987336adc3a5cc06ba70906cf57bbf80a4f9fb29eehttp%3A%2F%2Fonlinelibrary.wiley.com%2Fdoi%2F10.1029%2F2001JD001113%2Fcitedbyrefpaperuri:(bc8ccf608f9383a83b1f2f0ee2c9f984)http://onlinelibrary.wiley.com/doi/10.1029/2001JD001113/citedbyABSTRACT We present a new global three-dimensional chemical model for the troposphere, named chemical atmospheric general circulation model (AGCM) for study of atmospheric environment and radiative forcing (CHASER). This model, developed in the framework of the Center for Climate System Research/National Institute for Environment Studies (CCSR/NIES) AGCM, is aimed to study tropospheric photochemistry and its influences on climate. The chemical component of the model simulates the O3-HOx-NOx-CH4-CO photochemical system and oxidation of nonmethane hydrocarbons through 88 chemical and 25 photolytic reactions with 47 chemical species in its present configuration. The model includes emission sources, dry and wet deposition, as well as chemical transformations. Meteorological processes such as transport due to advection, convection, and other subgrid-scale mixing are simulated ``on-line'' by the dynamical component of the CCSR/NIES AGCM. A detailed evaluation of the model results is presented in a companion paper [Sudo et al., 2002]. An evaluation of the transport scheme adopted in the model suggests that the model is capable of simulating transport associated with convection and boundary layer mixing as well as large-scale advection. The model capability to simulate dry and wet deposition was also evaluated by conducting a simulation of atmospheric lead. The simulated lead distributions are consistent with those observed at the surface, showing the validity of the deposition parameterization adopted in the model.
    Takata K., S. Emori, and T. Watanabe, 2003: Development of the minimal advanced treatments of surface interaction and runoff. Globat Planet Change, 38, 209- 222.10.1016/S0921-8181(03)00030-49e1916fd-b701-44d0-a22c-e5c75a493fc245d71c6ad3cf64ab26a77188f48aafebhttp%3A%2F%2Fci.nii.ac.jp%2Fnaid%2F10013125540%2Frefpaperuri:(eb1963e8a8c40b3ed49452dee8273c75)http://ci.nii.ac.jp/naid/10013125540/Development of the minimal advanced of the surface interaction and runoff TAKATA K. Global Planet. Change 39, 209-222, 2003
    Wang S. Z., E. T. Yu, 2013a: Simulation and projection of changes in rainy season precipitation over China using the WRF model. Acta Meteorologica Sinica, 27, 577- 584.10.1007/s13351-013-0406-216ee3a6163195ffd078c32634eca496dhttp%3A%2F%2Fwww.cnki.com.cn%2FArticle%2FCJFDTotal-QXXW201304011.htmhttp://d.wanfangdata.com.cn/Periodical_qxxb-e201304010.aspx
    Wang S. Z., E. T. Yu, 2013b: Dynamical downscaling simulation over China using the nested MIROC/WRF model. Climatic and Environmental Research, 18, 681- 692. (in Chinese)2cac4fad-800c-4228-857d-3435f40a4db7945d1b52042f5158d42a1b12b729e0e6http%3A%2F%2Fen.cnki.com.cn%2FArticle_en%2FCJFDTotal-QHYH201306001.htmhttp://en.cnki.com.cn/Article_en/CJFDTotal-QHYH201306001.htmA dynamic downscaling simulation experiment based on the WRF(Weather Research and Forecasting) model was conducted to examine the performance of the model in simulating the climate in China. The following results were found. MIROC(Model for Interdisciplinary Research on Climate) and the WRF model can reproduce the observed spatial patterns of surface air temperature well. The WRF model provides more detailed descriptions of the temperature, with both high temperatures in the Sichuan Basin and low temperatures in North China simulated well.The annual and seasonal spatial correlation coefficient between the MIROC simulated and observed precipitation ranges from 0.79 to 0.83, indicating that MIROC can simulate precipitation well. Overall, the WRF model can reproduce the observed precipitation distribution more accurately than the MIROC. Both the MIROC and the WRF models simulate precipitation better in South and East China than in North and West China. The WRF model can remove the artificial precipitation center over the eastern edge of the Tibetan Plateau simulated by the MIROC. Both models do a poor job of simulating the interannual variations in annual mean temperature and total precipitation,although the WRF model performs better.
    Wu J., X. J. Gao, 2013: A gridded daily observation dataset over China region and comparison with the other datasets. Chinese Journal of Geophysics, 56, 1102- 1111. (in Chinese)10.6038/cjg20130406985e209292a1f5241b8f12261847dbd0http%3A%2F%2Fen.cnki.com.cn%2FArticle_en%2FCJFDTOTAL-DQWX201304008.htmhttp://en.cnki.com.cn/Article_en/CJFDTOTAL-DQWX201304008.htmA new gridded daily dataset with the resolution of 0.25latitude by 0.25longitude,CN05.1,is constructed for the purpose of high resolution climate model validation over China region.The dataset is based on the interpolation from over 2400observing stations in China,includes 4variables : daily mean,minimum and maximum temperature,daily precipitation.The " anomaly approach " is applied in this interpolation.The climatology is first interpolated by thinplate smoothing splines and then a gridded daily anomaly derived from angular distance weighting method is added to climatology to obtain the final dataset.Intercomparison of the dataset with other three daily datasets,CN05for temperature,and EA05and APHRO for precipitation is conducted.The analysis period is from 1961to 2005.For multi-annual mean temperature variables,results show small differences over eastern China with dense observation stations,but larger differences(warmer) over western China with less stations between CN05.1and CN05.The temperature extremes are measured by TX3D(mean of the 3greatest maximum temperatures in a year) and TN3D(mean of the 3lowest minimum temperatures).CN05.1in general shows a warmer TX3Dover China,while a lower TN3Din the east and greater TN3Din the west are found compared to CN05.A greater value of annual mean precipitation compared to EA05and APHRO,especially to the latter,is found in CN05.1.For precipitation extreme of R3D(mean of the 3largest precipitations in a year),CN05.1presents lower value of it in western China compared to EA05.
    Wu, T. W., Coauthors, 2010: The Beijing Climate Center atmospheric general circulation model: Description and its performance for the present-day climate. Climate Dyn., 34, 123- 147.10.1007/s00382-008-0487-2ed67c5acfd5a67cd1c2a184e1c216ab0http%3A%2F%2Fonlinelibrary.wiley.com%2Fresolve%2Freference%2FXREF%3Fid%3D10.1007%2Fs00382-008-0487-2http://onlinelibrary.wiley.com/resolve/reference/XREF?id=10.1007/s00382-008-0487-2The Beijing Climate Center atmospheric general circulation model version 2.0.1 (BCC_AGCM2.0.1) is described and its performance in simulating the present-day climate is assessed. BCC_AGCM2.0.1 originates from the community atmospheric model version 3 (CAM3) developed by the National Center for Atmospheric Research (NCAR). The dynamics in BCC_AGCM2.0.1 is, however, substantially different from the Eulerian spectral formulation of the dynamical equations in CAM3, and several new physical parameterizations have replaced the corresponding original ones. The major modification of the model physics in BCC_AGCM2.0.1 includes a new convection scheme, a dry adiabatic adjustment scheme in which potential temperature is conserved, a modified scheme to calculate the sensible heat and moisture fluxes over the open ocean which takes into account the effect of ocean waves on the latent and sensible heat fluxes, and an empirical equation to compute the snow cover fraction. Specially, the new convection scheme in BCC_AGCM2.0.1, which is generated from the Zhang and McFarlane- scheme but modified, is tested to have significant improvement in tropical maximum but also the subtropical minimum precipitation, and the modified scheme for turbulent fluxes are validated using EPIC2001 in situ observations and show a large improvement than its original scheme in CAM3. BCC_AGCM2.0.1 is forced by observed monthly varying sea surface temperatures and sea ice concentrations during 1949-2000. The model climatology is compiled for the period 1971-2000 and compared with the ERA-40 reanalysis products. The model performance is evaluated in terms of energy budgets, precipitation, sea level pressure, air temperature, geopotential height, and atmospheric circulation, as well as their seasonal variations. Results show that BCC_AGCM2.0.1 reproduces fairly well the present-day climate. The combined effect of the new dynamical core and the updated physical parameterizations in BCC_AGCM2.0.1 leads to an overall improvement, compared to the original CAM3.
    Xu Y., X. J. Gao, Y. Shen, C. H. Xu, Y. Shi, and F. Giorgi, 2009: A daily temperature dataset over China and its application in validating a RCM simulation. Adv. Atmos. Sci.,26, 763-772, doi: 10.1007/s00376-009-9029-z.10.1007/s00376-009-9029-z1f1341eab9bde9f710b2a22cc78220fbhttp%3A%2F%2Flink.springer.com%2F10.1007%2Fs00376-009-9029-zhttp://d.wanfangdata.com.cn/Periodical_dqkxjz-e200904016.aspxThis paper describes the construction of a 0.5°×0.5° daily temperature dataset for the period of 1961-2005 over mainland China for the purpose of climate model validation.The dataset is based on the interpolation from 751 observing stations in China and comprises 3 variables:daily mean,minimum,and maximum temperature.The "anomaly approach" is applied in the interpolation.The gridded climatology of 1971-2000 is first calculated and then a gridded daily anomaly for 1961-2005 is added to the climatology to obtain the final dataset.Comparison of the dataset with CRU (Climatic Research Unit) observations at the monthly scale shows general agreement between the two datasets.The differences found can be largely attributed to the introduction of observations at new stations.The dataset shows similar interannual variability as does CRU data over North China and eastern part of the Tibetan Plateau,but with a slightly larger linear trend.The dataset is employed to validate the simulation of three extreme indices based on daily mean,minimum,and maximum temperature by a high-resolution regional climate model.Results show that the model reproduces these indices well.The data are available at the National Climate Center of China Meteorological Administration,and a coarser resolution (1°×1°) version can be accessed via the World Wide Web.
    Yang B., Y. C. Zhang, Y. Qian, A. N. Huang, and H. P. Yan, 2015a: Calibration of a convective parameterization scheme in the WRF model and its impact on the simulation of East Asian summer monsoon precipitation. Climate Dyn., 44, 1661- 1684.10.1007/s00382-014-2118-4a79f16bd7b3bd422d2ecae2bd21bbd2fhttp%3A%2F%2Flink.springer.com%2F10.1007%2Fs00382-014-2118-4http://link.springer.com/10.1007/s00382-014-2118-4Reasonably modeling the magnitude, south-搉orth gradient and seasonal propagation of precipitation associated with the East Asian summer monsoon (EASM) is a challenging task in the climate community. In this study we calibrate five key parameters in the Kain-ritsch convection scheme in the WRF model using an efficient importance-sampling algorithm to improve the EASM simulation. We also examine the impacts of the improved EASM precipitation on other physical process. Our results suggest similar model sensitivity and values of optimized parameters across years with different EASM intensities. By applying the optimal parameters, the simulated precipitation and surface energy features are generally improved. The parameters related to downdraft, entrainment coefficients and CAPE consumption time (CCT) can most sensitively affect the precipitation and atmospheric features. Larger downdraft coefficient or CCT decrease the heavy rainfall frequency, while larger entrainment coefficient delays the convection development but build up more potential for heavy rainfall events, causing a possible northward shift of rainfall distribution. The CCT is the most sensitive parameter over wet region and the downdraft parameter plays more important roles over drier northern region. Long-term simulations confirm that by using the optimized parameters the precipitation distributions are better simulated in both weak and strong EASM years. Due to more reasonable simulated precipitation condensational heating, the monsoon circulations are also improved. By using the optimized parameters the biases in the retreating (beginning) of Mei-yu (northern China rainfall) simulated by the standard WRF model are evidently reduced and the seasonal and sub-seasonal variations of the monsoon precipitation are remarkably improved.
    Yang B., Y. C. Zhang, Y. Qian, T. W. Wu, A. N. Huang, and Y. J. Fang, 2015b: Parametric sensitivity analysis for the Asian summer monsoon precipitation simulation in the Beijing Climate Center AGCM version 2.1. J. Climate, 28, 5622- 5644.10.1175/JCLI-D-14-00655.109d87415-c5d5-4801-b01d-a08b3e5017743b99f0fa310c1cef7f2ebf66fa858b71http%3A%2F%2Fcpfd.cnki.com.cn%2FArticle%2FCPFDTOTAL-ZGQX201510008050.htmhttp://cpfd.cnki.com.cn/Article/CPFDTOTAL-ZGQX201510008050.htmAbstract In this study, the authors apply an efficient sampling approach and conduct a large number of simulations to explore the sensitivity of the simulated Asian summer monsoon (ASM) precipitation, including the climatological state and interannual variability, to eight parameters related to the cloud and precipitation processes in the Beijing Climate Center AGCM, version 2.1 (BCC_AGCM2.1). The results herein show that BCC_AGCM2.1 has large biases in simulating the ASM precipitation. The precipitation efficiency and evaporation coefficient for deep convection are the most sensitive parameters in simulating the ASM precipitation. With optimal parameter values, the simulated precipitation climatology could be remarkably improved, including increased precipitation over the equatorial Indian Ocean, suppressed precipitation over the Philippine Sea, and more realistic mei-yu distribution over eastern China. The ASM precipitation interannual variability is further analyzed, with a focus on the ENSO impacts. It is shown that simulations with better ASM precipitation climatology can also produce more realistic precipitation anomalies during El Ni帽o-揹ecaying summer. In the low-skill experiments for precipitation climatology, the ENSO-induced precipitation anomalies are most significant over continents (vs over ocean in observations) in the South Asian monsoon region. More realistic results are derived from the higher-skill experiments with stronger anomalies over the Indian Ocean and weaker anomalies over India and the western Pacific Ocean, favoring more evident easterly anomalies forced by the tropical Indian Ocean warming and stronger Indian Ocean-搘estern Pacific teleconnection as observed. The model results reveal a strong connection between the simulated ASM precipitation climatological state and interannual variability in BCC_AGCM2.1 when key parameters are perturbed.
    Yu E. T., H. J. Wang, and J. Q. Sun, 2010: A quick report on a dynamical downscaling simulation over China using the nested model. Atmos. Oceanic Sci. Lett., 3, 325- 329.10.1080/16742834.2010.11446886a3bb608314f05ac1a6fb104b43273915http%3A%2F%2Fwww.cqvip.com%2FMain%2FDetail.aspx%3Fid%3D37257289http://d.wanfangdata.com.cn/Periodical_dqhhykxkb201006007.aspxThis paper describes a dynamical downscaling simulation over China using the nested model system,which consists of the modified Weather Research and Forecasting Model(WRF)nested with the NCAR Community Atmosphere Model(CAM).Results show that dynamical downscaling is of great value in improving the model simulation of regional climatic characteristics.WRF simulates regional detailed temperature features better than CAM.With the spatial correlation coefficient between the observation and the simulation increasing from 0.54 for CAM to 0.79 for WRF,the improvement in precipitation simulation is more perceptible with WRE Furthermore,the WRF simulation corrects the spatial bias of the precipitation in the CAM simulation.
    Yu E. T., H. J. Wang, Y. Q. Gao, and J. Q. Sun, 2011: Impacts of cumulus convective parameterization schemes on summer monsoon precipitation simulation over China. Acta Meteorologica Sinica, 25, 581- 592.10.1007/s13351-011-0504-y7ceeaebafb7695b8f51e12fc334d667fhttp%3A%2F%2Fwww.cqvip.com%2FQK%2F88418X%2F201105%2F40187611.htmlhttp://d.wanfangdata.com.cn/Periodical_qxxb-e201105004.aspx
    Yu E. T., J. Q. Sun, H. P. Chen, and W. L. Xiang, 2015: Evaluation of a high-resolution historical simulation over China: Climatology and extremes. Climate Dyn., 45, 2013- 2031.10.1007/s00382-014-2452-6dac4a1d66ac62eb068a74e331c6ed7c7http%3A%2F%2Flink.springer.com%2F10.1007%2Fs00382-014-2452-6http://link.springer.com/10.1007/s00382-014-2452-6China faces an increasing challenge in water resources in the coming decades; thus high-confidence climate projection is of particular importance for the country- future. In this paper, we evaluate the performance of a long high-resolution continuous simulation over China based on multiple observations and the corresponding historical simulation. The simulation is completed using the Weather Research and Forecasting (WRF) model driven by the Model for Interdisciplinary Research on Climate version 5 (MIROC5) in the context of the Coupled Model Intercomparison Project Phase 5. The results show that both MIROC5 and WRF can capture the distribution and variability of temperature over China, whereas WRF shows improvements, particularly for simulation of regional features. Compared with MIROC5, WRF can reproduce the spatial distribution, annual cycle, probability distribution, and seasonal evolution of the precipitation over mainland China and the sub-regions with better performance. The trend is of fundamental importance in the future projection estimations, and WRF shows better skill in simulating the annual mean precipitation trend. However, there is overestimation of precipitation in Southeast China while negative one in the middle latitude of China in WRF simulation, which can be traced back to model bias in atmospheric circulation and water vapor transportation in these regions. Several extreme climate indices are selected to further assess the model- performance in simulating climate extremes, WRF can well reproduce the main features with better model skill compared with MIROC5. The better performance of WRF indicates the necessity of the dynamical downscaling technique and the robustness of regional climate simulation in future regional climate projection聽over China.
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Manuscript received: 15 June 2015
Manuscript revised: 28 September 2015
Manuscript accepted: 29 September 2015
通讯作者: 陈斌, bchen63@163.com
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Comparison of a Very-fine-resolution GCM with RCM Dynamical Downscaling in Simulating Climate in China

  • 1. Nansen-Zhu International Research Center, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing 100029
  • 2. Climate Change Research Center, Chinese Academy of Sciences, Beijing 100029
  • 3. Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters, Nanjing University of Information Science & Technology, Nanjing 210044

Abstract: Regional climate simulation can generally be improved by using an RCM nested within a coarser-resolution GCM. However, whether or not it can also be improved by the direct use of a state-of-the-art GCM with very fine resolution, close to that of an RCM, and, if so, which is the better approach, are open questions. These questions are important for understanding and using these two kinds of simulation approaches, but have not yet been investigated. Accordingly, the present reported work compared simulation results over China from a very-fine-resolution GCM (VFRGCM) and from RCM dynamical downscaling. The results showed that: (1) The VFRGCM reproduces the climatologies and trends of both air temperature and precipitation, as well as inter-monthly variations of air temperature in terms of spatial pattern and amount, closer to observations than the coarse-resolution version of the GCM. This is not the case, however, for the inter-monthly variations of precipitation. (2) The VFRGCM captures the climatology, trend, and inter-monthly variation of air temperature, as well as the trend in precipitation, more reasonably than the RCM dynamical downscaling method. (3) The RCM dynamical downscaling method performs better than the VFRGCM in terms of the climatology and inter-monthly variation of precipitation. Overall, the results suggest that VFRGCMs possess great potential with regard to their application in climate simulation in the future, and the RCM dynamical downscaling method is still dominant in terms of regional precipitation simulation.

1. Introduction
  • Following the development of RCM dynamical downscaling (Dickinson et al., 1989; Giorgi and Bates, 1989; Giorgi, 1990), the method is now widely used to simulate regional climate in many different regions worldwide. This is mainly due to its more realistic topographic forcings, comprehensive physical processes, and the related improvement in simulation results relative to the driving GCM (Ju et al., 2007; Yu et al., 2010, 2015; Gao et al., 2012; Endris et al., 2013; Martynov et al., 2013). The method appears to be more effective for regions with complex topography, such as China, characterized by its wide variety of highly different landscapes, with the Tibetan Plateau and various mountain chains in the west and the north and lower lands in the east (Gao et al., 2008). (Ju et al., 2007) simulated the East Asian climate at the Last Glacial Maximum (LGM) using RegCM2 (Giorgi et al., 1993a, 1993b) nested within an atmospheric GCM, and proved that the high-resolution RegCM2 can capture additional regional details of the LGM climate. When RegCM3 (Pal et al., 2007) was nested within the global model FvGCM [finite volume general circulation model (Lin and Rood, 1996; Kiehl et al., 1996)], (Gao et al., 2008) found that it showed a better performance in both the spatial pattern and amount of precipitation over East Asia than FvGCM alone, with the most marked improvement being the removal of an artificial precipitation center over the eastern edge of the Tibetan Plateau. Recently, the WRF model (Skamarock et al., 2008) model was employed to simulate changes in climate extremes over China. Driven by MIROC5 (Hasumi and Emori, 2004) from CMIP5 (Coupled Model Intercomparison Phase 5) (Yu et al., 2015), it was found that WRF can better reproduce the main features of the climate extremes compared with MIROC5 (Yu et al., 2015).

    However, as funding sources to develop climate models have increased, the horizontal resolutions of GCMs have become finer. For instance, in CMIP5, some modeling centers have provided higher resolution simulation results relative to in CMIP3, such as the results from MIROC4h (Sakamoto et al., 2012) and BCC_CSM1.1(m) (Wu et al., 2010). The horizontal resolution of MIROC4h is approximately 0.5625°× 0.5625°, which is close to the level of RCM dynamical downscaling methods (Gao et al., 2013; Wang and Yu, 2013a). In the AMIP (Atmospheric Model Intercomparison Project), some models have a horizontal resolution less than 50 km, e.g., MRI-AGCM (Mizuta et al., 2012) and NICAM [Non-hydrostatic Icosahedral Atmospheric Model (Kodama et al., 2015)]. Thus, the question arises as to whether these very-fine-resolution GCMs (VFRGCMs) threaten the advantage of high-resolution RCM dynamical downscaling. Attempting to address this question is highly important for understanding and using these two kinds of simulation approaches in the future.

    The objectives of the present study were to: (1) compare the simulation of a VFRGCM with that of its coarse-resolution version over China, and (2) compare the VFRGCM simulation to an RCM dynamical downscaling simulation over China under an almost equal horizontal resolution. Observational data were also used for comparison purposes. In section 2, brief descriptions of the data and models are provided. Section 3 compares the climatologies, trends, and inter-monthly variations of temperature and precipitation in the three simulations. Further discussion on the discrepancies between the RCM dynamical downscaling and VFRGCM simulations is provided in section 4. A summary of the key findings is presented in section 5.

2. Model, observations, and methods
  • The coarse-resolution GCM used in this study was MIROC3.2 (hires) (hereafter, M3H), developed by the Center for Climate System Research, National Institute for Environmental Studies, and Frontier Research Center for Global Change of Japan (Hasumi and Emori, 2004). The horizontal resolution of the atmospheric model is approximately 1.125°×1.125°. The height of the model top is about 40 km, having 56 vertical σ layers with relatively finer vertical resolution in the planetary layer and around the tropopause. The land surface model is MATSIRO (Minimal Advanced Treatments of Surface Interaction and RunOff) (Takata et al., 2003). The model has one canopy layer, five soil layers, and a variable number (0-3) of snow layers. The total thickness of the soil layer is 2 m. The ocean model has 47 vertical levels, and the vertical coordinate is a hybrid of σ and z. The horizontal resolution of the ocean model is approximately 0.28125° (lon) × 0.1875° (lat). As a component of CMIP3, M3H has carried out historical simulations of the period 1850-2000, using observed natural and anthropogenic forcings (Nozawa et al., 2007): changes in total solar irradiance (Lean et al., 1995), volcanic aerosols (Sato et al., 1993), well-mixed greenhouse gases (Johns et al., 2003), tropospheric and stratospheric ozone (Randel and Wu, 1999; Sudo et al., 2002), surface emissions of anthropogenic carbonaceous aerosols (Nozawa and Kurokawa, 2006) and precursors of sulfate aerosols (Lefohn et al., 1999), and land use (Hirabayashi et al., 2005). The simulation results have been widely used to analyze global or regional climate change and to drive RCMs (Lucarini et al., 2007; Gao et al., 2012; Guo et al., 2014).

    The VFRGCM used in this study was MIROC4h (hereafter, M4H), which was developed as an improved version of M3H (Sakamoto et al., 2012). The height of the atmospheric model top and its vertical σ layers and resolution are the same as those of M3H. The land surface model as well as the vertical coordinate, vertical levels and horizontal resolution of the ocean model are also the same as those in M3H. The most fundamental change in M4H, compared to M3H, is a doubling of the horizontal resolution of the atmospheric model to approximately 0.5625°. Additionally, a minor change from M3H to M4H is the difference in the latitude where the isopycnal layer thickness diffusion is applied in the Northern Hemisphere (Sakamoto et al., 2012). As a component of CMIP5, M4H has carried out historical simulations of the period 1950-2006 using almost the same observed natural and anthropogenic forcings as M3H, except for surface emissions of anthropogenic carbonaceous aerosols and sulfate aerosols [M3H used the data from (Lefohn et al., 1999) and (Nozawa and Kurokawa, 2006) while M4H used the data from (Lamarque et al., 2010)]. (Sakamoto et al., 2012) found that M4H achieves many improvements in climate simulation compared with M3H, including not only smaller errors in the reproducibility of the surface variables, but also more realistic results for the interannual effects of events such as ENSO. These improvements are mostly due to the use of a higher resolution atmospheric model in M4H (Sakamoto et al., 2012).

    The RCM dynamical downscaling simulation was carried out using WRF-ARW, version 3.3.1 (Skamarock et al., 2008), driven by the output of M3H. The microphysics scheme was WSM6 (Hong and Lim, 2006). The atmospheric radiation transfer schemes for longwave and shortwave radiation were calculated by CAM3.0 (Collins et al., 2004). The cumulus convective precipitation was parameterized by the Kain-Fritsch scheme (Kain, 2004). The planetary boundary layer was depicted by the Yonsei University scheme (Hong et al., 2006). The land surface model employed the Noah land surface model with multi-parameterization options (Niu et al., 2011). Notably, different sets of physical options may produce different simulated results (Yu et al., 2011). In this study, the above set was chosen because it can produce highly reasonable results for both air temperature and precipitation in China (Wang and Yu, 2013b). The period of simulation was 1980 to 2000, and the first year of the period was taken as the spin-up phase. The horizontal resolution of the simulation was 50 km (approximately 0.5°), with 23 vertical layers from the surface up to a model top at 50 hPa. The simulation domain covered all of China and its surrounding areas, including 164× 128 (east-west × north-south) grid points, with the center at (35° N, 102° E) (Fig. 1c). More detailed information can be found in the works of Wang and Yu (2013a, b).

    Figure 1.  The topographies (m) used in (a) M3H, (b) M4H, (c) WRF, and (d) CN05.1. The simulation domain for WRF is also shown in (c).

  • The CN05.1 dataset is an upgraded version of the previous dataset, CN05 (Xu et al., 2009), and was used as the observation in this study to compare with the simulation results. The dataset contains daily mean temperature, maximum temperature, minimum temperature, precipitation, evaporation, mean wind speed, and relative humidity, at a horizontal resolution of 0.25°× 0.25°, and covers the period from 1961 to 2012. The product was developed by increasing the number of stations, in China, used in the interpolation of observations, from 751 in CN05 to 2416 in CN05.1, and was obtained from the China Meteorological Administration (Wu and Gao, 2013). The data are reliable and have been widely used as an appropriate reference for comparisons with simulation results (Guo and Wang, 2013, 2014; Ma et al., 2015; Yu et al., 2015).

  • In order to perform a homogenous comparison, all data from M3H, M4H and WRF were interpolated into a common resolution of 0.25°× 0.25°, which is the same as that of the CN05.1 data. The influence of topography on simulated temperature were corrected during the process of interpolation. The specific method for the correction was that the original coarser resolution simulated temperature was firstly converted into values at sea level (0 m height), based on the corresponding coarser resolution topography and vertical temperature lapse rate [(0.65°C (100 m)-1], and then those values were horizontally interpolated into the higher resolution data using a bilinear interpolation method. Finally, they were again converted into the temperature at the corresponding higher resolution topography, based on the vertical temperature lapse rate. The trend was calculated using ordinary least-squares regression by deriving the slope of the linear fit, and its statistical significance was assessed using the Student's t-test method.

3. Results
  • In this section, the impact of topographic correction on the simulation results is firstly given, and then the simulation results from M3H, M4H and WRF are compared to the CN05.1 data in terms of the climatologies averaged for the period 1981-2000, trends during the period 1981-2000, and inter-monthly variations averaged for the period 1981-2000, for air temperature and precipitation, separately.

  • The topographies used in M3H, M4H, WRF and CN05.1 are shown in Figs. 1a-d. It can be seen that the differences in the four sets of topographies are mainly situated on the Tibetan Plateau. The topography used in M3H is much higher on the Tibetan Plateau than that used in CN05.1; moreover, it fails to show some detailed information due to its coarser resolution. The topography used in M4H is still higher on the Tibetan Plateau than that used in CN05.1, but it shows greater regional detail relative to M3H. The topography used in WRF is quite similar to that used in CN05.1. These differences in topography indicate that topographic correction is necessary during the process of interpolating coarser resolution data into a higher resolution.

    Figure 2.  Climatology of air temperature ($^\circ$C) during the period 1981-2000 from (a) CN05.1, (b, c) MIROC3h, (d, e) MIROC4h, and (f, g) WRF. Panels (b, d, f) refer to the results without topographic correction, while (c, e, g) refer to the results with topographic correction. China was divided into four sub-regions [shown in (a)] for analysis, based on Shi (2010): northwestern China (NW); northeastern China (NE); the Tibetan Plateau (TP); South China (SC).

    Figure 2 compares the results with and without topographic correction during the process of interpolation. It can clearly be seen that the air temperature from M3H becomes closer to observations after topographic correction is performed. The cold bias on the Tibetan Plateau becomes smaller, and many regional details in the Tibetan Plateau and northwestern China are present. For the entire region of China, the spatial correlation coefficient increases from 0.94 to 0.97 and the spatial RMSE decreases from 3.34°C to 2.80°C, after the topographic correction. The improvement is especially evident on the Tibetan Plateau; the spatial correlation coefficient increases from 0.88 to 0.92 and the spatial RMSE decreases from 6.28°C to 5.47°C (Table 1). The air temperature from M4H also improves after topographic correction. The spatial correlation coefficient increases from 0.96 to 0.97 and the spatial RMSE decreases from 2.87°C to 2.48°C (Table 1). In contrast, the air temperature from WRF shows very small changes after topographic correction, due to its close topography to that of CN05.1. These results suggest that topographic correction is necessary before comparing model results to observations.

  • As shown in Figs. 2c, e and g, all three models capture the spatial pattern of the climatology of air temperature well, such as the high air temperature in southeastern China, low air temperature in the Tibetan Plateau, and transitional temperature in northwestern, northeastern, and central China. Clearly, all three models give a lower temperature in the Tibetan Plateau compared to observations. This is especially true for WRF, which gives a distinctly lower temperature not only in the Tibetan Plateau but also in northwestern China (Fig. 2g). Relative to both M3H and WRF, M4H reproduces more realistic air temperature on the Tibetan Plateau, which is confirmed by the RMSE (root-mean-square error) of 5.23°C, relative to 6.28°C for M3H and 7.63°C for WRF (Table 1). For the entire region of China, M4H has an equal correlation coefficient of 0.97 with M3H and WRF, but the lowest RMSE of 2.48°C compared with 2.8°C for M3H and 3.99°C for WRF (Table 1). These results indicate that M4H is superior in simulating the climatology of air temperature in China.

    For precipitation, all three models capture the gradually decreasing pattern from southeastern to northwestern China shown in observations (Figs. 3a-d). However, M3H and M4H yield an artificial precipitation center over the eastern edge of the Tibetan Plateau, although the center is smaller in M4H due to its more realistic topography (Figs. 3b and c). The center can also be seen in the WRF simulation results, but it is quite weak (Fig. 3d). Compared to M3H, the bias in the amount of precipitation is less in M4H because of the improved horizontal resolution. Compared to M4H, the WRF simulation is closer to observations in terms of both the spatial pattern and amount in all sub-regions except northeastern China, where M4H shows better performance (Table 1).

    Figure 3.  Climatology of precipitation (mm yr$^{-1}$) during the period 1981-2000 from (a) CN05.1, (b) MIROC3h, (c) MIROC4h, and (d) WRF.

  • Observations show that almost all areas of China experienced an increasing trend in air temperature during the period 1981-2000, especially in the northern part of China (Fig. 4a). However, M3H yields a decreasing trend in many areas of China, such as in eastern and southern parts (Fig. 4c). The WRF dynamical downscaling based on M3H also yields a decreasing trend, in more areas of China than M3H (Fig. 4g). Notably, M4H shows a distinctly more reasonable result than M3H and WRF; the decreasing trends shown in many areas in M3H and WRF shift to increasing trends in M4H, closer to observations (Fig. 4e). For the entire region of China, the spatial RMSE of M4H is 0.28°C (10 yr)-1, which is much lower than the values of 0.57 and 0.65°C (10 yr)-1 for M3H and WRF, respectively (Table 1).

    Figure 4.  Trends in (a, c, e, g) air temperature [$^\circ$C (10 yr)$^{-1}$] and (b, d, f, h) precipitation [mm (10 yr)$^{-1}$] during the period 1981-2000 from (a, b) CN05.1, (c, d) MIROC3h, (e, f) MIROC4h, and (g, h) WRF. Areas with statistical significance exceeding the 95% confidence level are denoted by black dots.

    Figure 5.  Yearly time series of air temperature (T) and precipitation (P) change from CN05.1, MIROC3h (M3H), MIROC4h (M4H), and WRF during the period 1981-2000, as averaged over China and the four sub-regions indicated in Fig. 2a. The trends [units: $^\circ$C (10 yr)$^{-1}$ for temperature and mm d$^{-1}$ (10 yr)$^{-1}$ for precipitation] of each series are labelled at the top of each subgraph, and asterisks indicate statistical significance at the greater than 95% confidence level. Note: CH, NW, NE, TP, and SC denote China, northwestern China, northeastern China, the Tibetan Plateau, and South China, respectively.

    Figure 6.  Annual cycle of monthly averaged air temperature (T) and precipitation (P) from CN05.1, MIROC3h (M3H), MIROC4h (M4H), and WRF, as averaged during the period 1981-2000 over China and the four sub-regions indicated in Fig. 2a. The temporal correlation coefficients between the three simulated results and CN05.1 are labelled at the top of each panel, and all the correlation coefficients are statistically significant at the greater than 95% confidence level. Note: CN, NW, NE, TP, and SC denote China, northwestern China, northeastern China, the Tibetan Plateau, and South China, respectively.

    For precipitation, a clear north-south oriented pattern of positive-negative-positive change was observed in southern China (Fig. 4b). Of the three models, WRF is the most successful in reproducing this pattern (Fig. 4h). However, it fails to capture the positive center in central China [approximately (33° N, 107° E)], as well as the positive trend in northeastern China. In contrast, M4H successfully captures these two features shown in observations (Fig. 4f). For all regions of China, both M4H and WRF have equal spatial correlation coefficients with observations, but M4H has lower RMSE than WRF (Table 1). For four sub-regions, M4H also performs better than WRF in terms of the spatial correlation coefficient and RMSE, except for the Tibetan Plateau.

    Area-averaged yearly time series of air temperature and precipitation from CN05.1 and the three models, as averaged over the entire region of China and four sub-regions during the period 1981-2000, are presented in Fig. 5. Because atmosphere-ocean coupled GCMs generally cannot reproduce past interannual variations of air temperature and precipitation, it may not be reasonable to directly compare the interannual variation of model results with observations. Therefore, only trends and biases of the area-averaged yearly time series were analyzed. For the entire region of China, the trend of air temperature from M4H is 0.39°C (10 yr)-1, which is in closest agreement with the observed result of 0.50°C (10 yr)-1, relative to 0.06 and -0.05°C (10 yr)-1 for M3H and WRF, respectively (Fig. 5). As for bias, apparently, WRF shows a considerable cold bias in spite of relatively small biases in M3H and M4H, compared to observations. For the four sub-regions, the trends of air temperature produced by M4H is the most consistent with observations. Notably, the air temperature produced by WRF shows a weaker performance than that of M3H, in terms of both trend and bias, in China as a whole and in the four sub-regions except for northwest China. In other words, RCM dynamical downscaling seems to increase the deviation between the driving GCM and observations. The possible reasons for this are discussed in section 4.

    As shown in Fig. 5, M4H shows reduced bias and a closer trend with the observed time series of precipitation compared to M3H. In spite of this, WRF produces time series of precipitation that are in closest agreement with observations among the three models, in terms of both trend and bias, over all regions except northeastern China. These results indicate that the dynamical downscaling method can better improve the trend and bias of area-average time series of precipitation than a fine-resolution GCM.

  • Figure 6 shows time series of monthly air temperature and precipitation, as averaged during the period 1981-2000, from CN05.1 and the three models over the entire region of China and four sub-regions. All three models reproduce the observed inter-monthly variation of air temperature well over the entire region of China, as well as in northwestern, northeastern and southern China. The correlation coefficients are above 0.898. Over the Tibetan Plateau, the correlation coefficients are still high, but significant cold biases are apparent. M4H shows the closest agreement with the observed inter-monthly variation of air temperature among the three models, in terms of both correlation and bias, followed by M3H and WRF. These results are also true for all four sub-regions.

    For precipitation, the correlations between the simulated monthly time series and observations are also high for all three models, over the entire region of China and the four sub-regions, but with emerging large biases, relative to air temperature. Also, similar to the interannual variation of precipitation, WRF shows the closest agreement with the observed inter-monthly variation of precipitation among the three models, in terms of both correlation and bias, over all regions except northeastern China (Fig. 6). M4H shows distinctly lower correlation and larger bias with observations than WRF over all regions except northeastern China. Compared to M3H, M4H shows a reduced bias with observations over the entire region of China and the four sub-regions, but a lower correlation with observations over all regions except southern China (Fig. 6). The lower correlation of M4H with observations than M3H is a primary cause of the large discrepancy in correlations between M4H and WRF with observations.

4. Discussion
  • China is characterized by complex topography and unique weather and climate systems. A coarse-resolution GCM will usually produce considerable discrepancies against observations when simulating the climate in China, such as significantly lower air temperature but more precipitation over the Tibetan Plateau, an artificial precipitation center over the eastern edge of the Tibetan Plateau, and poor reproduction of regional details of climatic variables (Gao et al., 2008, 2013). With its advantages of more realistic topographic forcings and comprehensive physical processes, RCM dynamical downscaling is a method that offers great improvements to simulation results, such as a significant decrease in bias, better reproduction of regional details, and removal of the aforementioned artificial precipitation center (Gao et al., 2008; Wang and Yu, 2013b; Yu et al., 2015). The present study found that the simulation of climate in China can also be significantly improved by the direct use of a VFRGCM, i.e., a GCM that has a resolution almost equal to that of RCM dynamical downscaling. However, some differences between these two simulation approaches remain. The possible reasons for these differences are discussed in this section.

    The VFRGCM used in the present work produced a more realistic climatology of air temperature than RCM dynamical downscaling. Furthermore, RCM dynamical downscaling showed a colder bias on average than the driving GCM. The high-resolution model might capture some land cover types, such as snow cover, glaciers, and permafrost. These land cover types melted and absorbed heat, thus resulting in cool air temperature. Because these land cover types may be small in area or isolated, they would not be captured by the coarse-resolution GCM, thus not resulting in the cool air temperature. This may partly explain the colder bias of RCM dynamical downscaling compared to the coarse-resolution GCM. However, if this is true, the VFRGCM should also show a colder bias than the coarse-resolution GCM, but this was not the case in our results. A further explanation could be that the cold bias of the VFRGCM may be offset by the heat from the wider region, such as the ocean. RCM dynamical downscaling is restricted to a smaller region and prescribed boundary conditions from coarse-resolution GCM, and thus its cold bias would not be adequately offset.

    The VFRGCM used in the present work also produced a more realistic trend of air temperature than RCM dynamical downscaling. A reason for this difference may relate to the different data sources of anthropogenic carbonaceous aerosol and sulfate aerosol emissions used in M3H and M4H. As described in section 2.1, M3H uses the aerosol data from Lefohn et al. (2005) and (Nozawa and Kurokawa, 2006), while M4H uses aerosol data from (Lamarque et al., 2010). This may also contribute to the differences in the air temperature trends between the VFRGCM and RCM. Another reason for this difference may relate to the higher climate sensitivity of M4H. (Sakamoto et al., 2012) found that M4H has an effective climate sensitivity to a doubling CO2 of 5.69°C, which is higher than the value 3.68°C for MIROC 3.2 (midres), and the range (2°C-4.5°C) of climate sensitivity reported in IPCC AR4 (Meehl et al., 2007). The higher climate sensitivity may also be one of the reasons for the differences between the air temperature trends from the VFRGCM and RCM. In addition, compared to VFRGCM, RCM has more complex model physical parameterizations, which will inevitably induce large model uncertainty. The uncertainty in model physics can evidently affect the simulated results (Yang et al., 2015a, 2015b). This may be one of the reasons for the more realistic trend of air temperature produced by the VFRGCM compared with RCM dynamical downscaling.

    For precipitation, both the VFRGCM and RCM dynamical downscaling results showed reduced bias compared with the coarse-resolution GCM, due to their finer resolutions. However, RCM dynamic downscaling produced a smaller bias than the VFRGCM despite their almost equal horizontal resolutions. The differences may be attributable to the more comprehensive physical processes of the RCM dynamical downscaling approach compared with the VFRGCM (Yang et al., 2015a, 2015b).

    Notably, all three models give a cold bias on the Tibetan Plateau compared to observations. This is especially true in the western part of the Tibetan Plateau. In general, it is thought that the cold bias results from the climate model. However, it should be noted that the CN05.1 data, used for comparison, include very sparse meteorological station data in the western part of the Tibetan Plateau (Wu and Gao, 2013). Therefore, it is possible that the CN05.1 data are somewhat inaccurate in the western part of the Tibetan Plateau, and this may contribute to the cold bias.

5. Conclusions
  • Climate simulations in China using a VFRGCM were compared to those based on RCM dynamical downscaling, each possessing almost equal horizontal resolution. Topographic correction can evidently improve GCM air temperature, and thus it should be required before comparing GCM air temperature to observations. Given the fine resolution of the GCM, the climatology, trend, and inter-monthly variation of air temperature, as well as the climatology and trend of precipitation, obtained more reasonable results relative to its coarse-resolution version. However, the situation in terms of the inter-monthly variation of precipitation was different; the fine-resolution GCM showed a reduced bias but a lower correlation with observations compared to its coarse-resolution version. Compared to RCM dynamical downscaling, the VFRGCM better captured the climatology, trend, and inter-monthly variation of air temperature, as well as the trend in precipitation, in terms of the spatial pattern and amount, but showed weaker performance in simulating the climatology and inter-monthly variation of precipitation. As indicated by the results, for simulations of regional precipitation, RCM dynamical downscaling is still the dominant approach, but VFRGCMs possess great potential with regard to their application in climate simulations in the future.

    The present reported results provide information on the differences between using GCMs with coarse and fine resolutions, which have same dynamical and physical processes, and dynamical downscaling from the same coarse-resolution GCM to simulate climate in China. They will be useful for understanding and using GCMs and RCMs to improve such simulations of climate in China in the future. Nevertheless, it should be stressed that these results are limited to the model chosen for use in this study, and differences may be found in the results of other models. Therefore, continued work is needed to compare the results from other models, and to explore the reasons for discrepancies between the simulations of VFRGCMs and RCM dynamical downscaling.

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