2016 Vol. 33, No. 7
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2016, 33(7): 795-807.
doi: 10.1007/s00376-016-5234-8
Abstract:
A weakly coupled assimilation system, in which SST observations are assimilated into a coupled climate model (CAS-ESM-C) through an ensemble optimal interpolation scheme, was established. This system is a useful tool for historical climate simulation, showing substantial advantages, including maintaining the atmospheric feedback, and keeping the oceanic fields from drifting far away from the observation, among others. During the coupled model integration, the bias of both surface and subsurface oceanic fields in the analysis can be reduced compared to unassimilated fields. Based on 30 model years of output from the system, the climatology and interannual variability of the climate system were evaluated. The results showed that the system can reasonably reproduce the climatological global precipitation and SLP, but it still suffers from the double ITCZ problem. Besides, the ENSO footprint, which is revealed by ENSO-related surface air temperature, geopotential height and precipitation during El Niño evolution, is basically reproduced by the system. The system can also simulate the observed SST-rainfall relationships well on both interannual and intraseasonal timescales in the western North Pacific region, in which atmospheric feedback is crucial for climate simulation.
A weakly coupled assimilation system, in which SST observations are assimilated into a coupled climate model (CAS-ESM-C) through an ensemble optimal interpolation scheme, was established. This system is a useful tool for historical climate simulation, showing substantial advantages, including maintaining the atmospheric feedback, and keeping the oceanic fields from drifting far away from the observation, among others. During the coupled model integration, the bias of both surface and subsurface oceanic fields in the analysis can be reduced compared to unassimilated fields. Based on 30 model years of output from the system, the climatology and interannual variability of the climate system were evaluated. The results showed that the system can reasonably reproduce the climatological global precipitation and SLP, but it still suffers from the double ITCZ problem. Besides, the ENSO footprint, which is revealed by ENSO-related surface air temperature, geopotential height and precipitation during El Niño evolution, is basically reproduced by the system. The system can also simulate the observed SST-rainfall relationships well on both interannual and intraseasonal timescales in the western North Pacific region, in which atmospheric feedback is crucial for climate simulation.
2016, 33(7): 808-818.
doi: 10.1007/s00376-016-5216-x
Abstract:
Based on the simulations of 31 global models in CMIP5, the performance of the models in simulating the Hadley and Walker circulations is evaluated. In addition, their change in intensity by the end of the 21st century (2080-2099) under the RCP4.5 and RCP8.5 scenarios, relative to 1986-2005, is analyzed from the perspective of 200 hPa velocity potential. Validation shows good performance of the individual CMIP5 models and the multi-model ensemble mean (MME) in reproducing the meridional (zonal) structure and magnitude of Hadley (Walker) circulation. The MME can also capture the observed strengthening tendency of the winter Hadley circulation and weakening tendency of the Walker circulation. Such secular trends can be simulated by 39% and 74% of the models, respectively. The MME projection indicates that the winter Hadley circulation and the Walker circulation will weaken under both scenarios by the end of the 21st century. The weakening amplitude is larger under RCP8.5 than RCP4.5, due to stronger external forcing. The majority of the CMIP5 models show the same projection as the MME. However, for the summer Hadley circulation, the MME shows little change under RCP4.5 and large intermodel spread is apparent. Around half of the models project an increase, and the other half project a decrease. Under the RCP8.5 scenario, the MME and 65% of the models project a weakening of the summer southern Hadley circulation.
Based on the simulations of 31 global models in CMIP5, the performance of the models in simulating the Hadley and Walker circulations is evaluated. In addition, their change in intensity by the end of the 21st century (2080-2099) under the RCP4.5 and RCP8.5 scenarios, relative to 1986-2005, is analyzed from the perspective of 200 hPa velocity potential. Validation shows good performance of the individual CMIP5 models and the multi-model ensemble mean (MME) in reproducing the meridional (zonal) structure and magnitude of Hadley (Walker) circulation. The MME can also capture the observed strengthening tendency of the winter Hadley circulation and weakening tendency of the Walker circulation. Such secular trends can be simulated by 39% and 74% of the models, respectively. The MME projection indicates that the winter Hadley circulation and the Walker circulation will weaken under both scenarios by the end of the 21st century. The weakening amplitude is larger under RCP8.5 than RCP4.5, due to stronger external forcing. The majority of the CMIP5 models show the same projection as the MME. However, for the summer Hadley circulation, the MME shows little change under RCP4.5 and large intermodel spread is apparent. Around half of the models project an increase, and the other half project a decrease. Under the RCP8.5 scenario, the MME and 65% of the models project a weakening of the summer southern Hadley circulation.
2016, 33(7): 819-828.
doi: 10.1007/s00376-016-5193-0
Abstract:
This study simulates the effective radiative forcing (ERF) of tropospheric ozone from 1850 to 2013 and its effects on global climate using an aerosol-climate coupled model, BCC_AGCM2.0.1_CUACE/Aero, in combination with OMI (Ozone Monitoring Instrument) satellite ozone data. According to the OMI observations, the global annual mean tropospheric column ozone (TCO) was 33.9 DU in 2013, and the largest TCO was distributed in the belts between 30°N and 45°N and at approximately 30°S; the annual mean TCO was higher in the Northern Hemisphere than that in the Southern Hemisphere; and in boreal summer and autumn, the global mean TCO was higher than in winter and spring. The simulated ERF due to the change in tropospheric ozone concentration from 1850 to 2013 was 0.46 W m-2, thereby causing an increase in the global annual mean surface temperature by 0.36°C, and precipitation by 0.02 mm d-1 (the increase of surface temperature had a significance level above 95%). The surface temperature was increased more obviously over the high latitudes in both hemispheres, with the maximum exceeding 1.4°C in Siberia. There were opposite changes in precipitation near the equator, with an increase of 0.5 mm d-1 near the Hawaiian Islands and a decrease of about -0.6 mm d-1 near the middle of the Indian Ocean.
This study simulates the effective radiative forcing (ERF) of tropospheric ozone from 1850 to 2013 and its effects on global climate using an aerosol-climate coupled model, BCC_AGCM2.0.1_CUACE/Aero, in combination with OMI (Ozone Monitoring Instrument) satellite ozone data. According to the OMI observations, the global annual mean tropospheric column ozone (TCO) was 33.9 DU in 2013, and the largest TCO was distributed in the belts between 30°N and 45°N and at approximately 30°S; the annual mean TCO was higher in the Northern Hemisphere than that in the Southern Hemisphere; and in boreal summer and autumn, the global mean TCO was higher than in winter and spring. The simulated ERF due to the change in tropospheric ozone concentration from 1850 to 2013 was 0.46 W m-2, thereby causing an increase in the global annual mean surface temperature by 0.36°C, and precipitation by 0.02 mm d-1 (the increase of surface temperature had a significance level above 95%). The surface temperature was increased more obviously over the high latitudes in both hemispheres, with the maximum exceeding 1.4°C in Siberia. There were opposite changes in precipitation near the equator, with an increase of 0.5 mm d-1 near the Hawaiian Islands and a decrease of about -0.6 mm d-1 near the middle of the Indian Ocean.
2016, 33(7): 829-840.
doi: 10.1007/s00376-016-5284-y
Abstract:
Environmental changes are expected to shift the distribution and abundance of vegetation by determining seedling establishment and success. However, most current ecosystem models only focus on the impacts of abiotic factors on biogeophysics (e.g., global distribution, etc.), ignoring their roles in the population dynamics (e.g., seedling establishment rate, mortality rate, etc.) of ecological communities. Such neglect may lead to biases in ecosystem population dynamics (such as changes in population density for woody species in forest ecosystems) and characteristics. In the present study, a new establishment scheme for introducing soil water as a function rather than a threshold was developed and validated, using version 1.0 of the IAP-DGVM as a test bed. The results showed that soil water in the establishment scheme had a remarkable influence on forest transition zones. Compared with the original scheme, the new scheme significantly improved simulations of tree population density, especially in the peripheral areas of forests and transition zones. Consequently, biases in forest fractional coverage were reduced in approximately 78.8% of the global grid cells. The global simulated areas of tree, shrub, grass and bare soil performed better, where the relative biases were reduced from 34.3% to 4.8%, from 27.6% to 13.1%, from 55.2% to 9.2%, and from 37.6% to 3.6%, respectively. Furthermore, the new scheme had more reasonable dependencies of plant functional types (PFTs) on mean annual precipitation, and described the correct dominant PFTs in the tropical rainforest peripheral areas of the Amazon and central Africa.
Environmental changes are expected to shift the distribution and abundance of vegetation by determining seedling establishment and success. However, most current ecosystem models only focus on the impacts of abiotic factors on biogeophysics (e.g., global distribution, etc.), ignoring their roles in the population dynamics (e.g., seedling establishment rate, mortality rate, etc.) of ecological communities. Such neglect may lead to biases in ecosystem population dynamics (such as changes in population density for woody species in forest ecosystems) and characteristics. In the present study, a new establishment scheme for introducing soil water as a function rather than a threshold was developed and validated, using version 1.0 of the IAP-DGVM as a test bed. The results showed that soil water in the establishment scheme had a remarkable influence on forest transition zones. Compared with the original scheme, the new scheme significantly improved simulations of tree population density, especially in the peripheral areas of forests and transition zones. Consequently, biases in forest fractional coverage were reduced in approximately 78.8% of the global grid cells. The global simulated areas of tree, shrub, grass and bare soil performed better, where the relative biases were reduced from 34.3% to 4.8%, from 27.6% to 13.1%, from 55.2% to 9.2%, and from 37.6% to 3.6%, respectively. Furthermore, the new scheme had more reasonable dependencies of plant functional types (PFTs) on mean annual precipitation, and described the correct dominant PFTs in the tropical rainforest peripheral areas of the Amazon and central Africa.
2016, 33(7): 841-851.
doi: 10.1007/s00376-016-5238-4
Abstract:
This paper investigates the possible sources of errors associated with tropical cyclone (TC) tracks forecasted using the Global/Regional Assimilation and Prediction System (GRAPES). The GRAPES forecasts were made for 16 landfalling TCs in the western North Pacific basin during the 2008 and 2009 seasons, with a forecast length of 72 hours, and using the default initial conditions ("initials", hereafter), which are from the NCEP-FNL dataset, as well as ECMWF initials. The forecasts are compared with ECMWF forecasts. The results show that in most TCs, the GRAPES forecasts are improved when using the ECMWF initials compared with the default initials. Compared with the ECMWF initials, the default initials produce lower intensity TCs and a lower intensity subtropical high, but a higher intensity South Asia high and monsoon trough, as well as a higher temperature but lower specific humidity at the TC center. Replacement of the geopotential height and wind fields with the ECMWF initials in and around the TC center at the initial time was found to be the most efficient way to improve the forecasts. In addition, TCs that showed the greatest improvement in forecast accuracy usually had the largest initial uncertainties in TC intensity and were usually in the intensifying phase. The results demonstrate the importance of the initial intensity for TC track forecasts made using GRAPES, and indicate the model is better in describing the intensifying phase than the decaying phase of TCs. Finally, the limit of the improvement indicates that the model error associated with GRAPES forecasts may be the main cause of poor forecasts of landfalling TCs. Thus, further examinations of the model errors are required.
This paper investigates the possible sources of errors associated with tropical cyclone (TC) tracks forecasted using the Global/Regional Assimilation and Prediction System (GRAPES). The GRAPES forecasts were made for 16 landfalling TCs in the western North Pacific basin during the 2008 and 2009 seasons, with a forecast length of 72 hours, and using the default initial conditions ("initials", hereafter), which are from the NCEP-FNL dataset, as well as ECMWF initials. The forecasts are compared with ECMWF forecasts. The results show that in most TCs, the GRAPES forecasts are improved when using the ECMWF initials compared with the default initials. Compared with the ECMWF initials, the default initials produce lower intensity TCs and a lower intensity subtropical high, but a higher intensity South Asia high and monsoon trough, as well as a higher temperature but lower specific humidity at the TC center. Replacement of the geopotential height and wind fields with the ECMWF initials in and around the TC center at the initial time was found to be the most efficient way to improve the forecasts. In addition, TCs that showed the greatest improvement in forecast accuracy usually had the largest initial uncertainties in TC intensity and were usually in the intensifying phase. The results demonstrate the importance of the initial intensity for TC track forecasts made using GRAPES, and indicate the model is better in describing the intensifying phase than the decaying phase of TCs. Finally, the limit of the improvement indicates that the model error associated with GRAPES forecasts may be the main cause of poor forecasts of landfalling TCs. Thus, further examinations of the model errors are required.
2016, 33(7): 852-864.
doi: 10.1007/s00376-016-5138-7
Abstract:
The spatiotemporal variability of the greenhouse gas methane (CH4) in the atmosphere over the Amazon is studied using data from the space-borne measurements of the Atmospheric Infrared Sounder on board NASA's AQUA satellite for the period 2003-12. The results show a pronounced variability of this gas over the Amazon Basin lowlands region, where wetland areas occur. CH4 has a well-defined seasonal behavior, with a progressive increase of its concentration during the dry season, followed by a decrease during the wet season. Concerning this variability, the present study indicates the important role of ENSO in modulating the variability of CH4 emissions over the northern Amazon, where this association seems to be mostly linked to changes in flooded areas in response to ENSO-related precipitation changes. In this region, a CH4 decrease (increase) is due to the El Niño-related (La Niña-related) dryness (wetness). On the other hand, an increase (decrease) in the biomass burning over the southeastern Amazon during very dry (wet) years explains the increase (decrease) in CH4 emissions in this region. The present analysis identifies the two main areas of the Amazon, its northern and southeastern sectors, with remarkable interannual variations of CH4. This result might be useful for future monitoring of the variations in the concentration of CH4, the second-most important greenhouse gas, in this area.
The spatiotemporal variability of the greenhouse gas methane (CH4) in the atmosphere over the Amazon is studied using data from the space-borne measurements of the Atmospheric Infrared Sounder on board NASA's AQUA satellite for the period 2003-12. The results show a pronounced variability of this gas over the Amazon Basin lowlands region, where wetland areas occur. CH4 has a well-defined seasonal behavior, with a progressive increase of its concentration during the dry season, followed by a decrease during the wet season. Concerning this variability, the present study indicates the important role of ENSO in modulating the variability of CH4 emissions over the northern Amazon, where this association seems to be mostly linked to changes in flooded areas in response to ENSO-related precipitation changes. In this region, a CH4 decrease (increase) is due to the El Niño-related (La Niña-related) dryness (wetness). On the other hand, an increase (decrease) in the biomass burning over the southeastern Amazon during very dry (wet) years explains the increase (decrease) in CH4 emissions in this region. The present analysis identifies the two main areas of the Amazon, its northern and southeastern sectors, with remarkable interannual variations of CH4. This result might be useful for future monitoring of the variations in the concentration of CH4, the second-most important greenhouse gas, in this area.
2016, 33(7): 865-874.
doi: 10.1007/s00376-016-5201-4
Abstract:
Radiative transfer model simulations were used to investigate the erythemal ultraviolet (EUV) correction factors by separating the UV-A and UV-B spectral ranges. The correction factor was defined as the ratio of EUV caused by changing the amounts and characteristics of the extinction and scattering materials. The EUV correction factors (CFEUV) for UV-A [CFEUV(A)] and UV-B [CFEUV(B)] were affected by changes in the total ozone, optical depths of aerosol and cloud, and the solar zenith angle. The differences between CFEUV(A) and CFEUV(B) were also estimated as a function of solar zenith angle, the optical depths of aerosol and cloud, and total ozone. The differences between CFEUV(A) and CFEUV(B) ranged from -5.0% to 25.0% for aerosols, and from -9.5% to 2.0% for clouds in all simulations for different solar zenith angles and optical depths of aerosol and cloud. The rate of decline of CFEUV per unit optical depth between UV-A and UV-B differed by up to 20% for the same aerosol and cloud conditions. For total ozone, the variation in CFEUV(A) was negligible compared with that in CFEUV(B) because of the effective spectral range of the ozone absorption band. In addition, the sensitivity of the CFEUVs due to changes in surface conditions (i.e., surface albedo and surface altitude) was also estimated by using the model in this study. For changes in surface albedo, the sensitivity of the CFEUVs was 2.9%-4.1% per 0.1 albedo change, depending on the amount of aerosols or clouds. For changes in surface altitude, the sensitivity of CFEUV(B) was twice that of CFEUV(A), because the Rayleigh optical depth increased significantly at shorter wavelengths.
Radiative transfer model simulations were used to investigate the erythemal ultraviolet (EUV) correction factors by separating the UV-A and UV-B spectral ranges. The correction factor was defined as the ratio of EUV caused by changing the amounts and characteristics of the extinction and scattering materials. The EUV correction factors (CFEUV) for UV-A [CFEUV(A)] and UV-B [CFEUV(B)] were affected by changes in the total ozone, optical depths of aerosol and cloud, and the solar zenith angle. The differences between CFEUV(A) and CFEUV(B) were also estimated as a function of solar zenith angle, the optical depths of aerosol and cloud, and total ozone. The differences between CFEUV(A) and CFEUV(B) ranged from -5.0% to 25.0% for aerosols, and from -9.5% to 2.0% for clouds in all simulations for different solar zenith angles and optical depths of aerosol and cloud. The rate of decline of CFEUV per unit optical depth between UV-A and UV-B differed by up to 20% for the same aerosol and cloud conditions. For total ozone, the variation in CFEUV(A) was negligible compared with that in CFEUV(B) because of the effective spectral range of the ozone absorption band. In addition, the sensitivity of the CFEUVs due to changes in surface conditions (i.e., surface albedo and surface altitude) was also estimated by using the model in this study. For changes in surface albedo, the sensitivity of the CFEUVs was 2.9%-4.1% per 0.1 albedo change, depending on the amount of aerosols or clouds. For changes in surface altitude, the sensitivity of CFEUV(B) was twice that of CFEUV(A), because the Rayleigh optical depth increased significantly at shorter wavelengths.
2016, 33(7): 875-888.
doi: 10.1007/s00376-016-5249-1
Abstract:
A four-dimensional variational (4D-Var) data assimilation method is implemented in an improved intermediate coupled model (ICM) of the tropical Pacific. A twin experiment is designed to evaluate the impact of the 4D-Var data assimilation algorithm on ENSO analysis and prediction based on the ICM. The model error is assumed to arise only from the parameter uncertainty. The "observation" of the SST anomaly, which is sampled from a "truth" model simulation that takes default parameter values and has Gaussian noise added, is directly assimilated into the assimilation model with its parameters set erroneously. Results show that 4D-Var effectively reduces the error of ENSO analysis and therefore improves the prediction skill of ENSO events compared with the non-assimilation case. These results provide a promising way for the ICM to achieve better real-time ENSO prediction.
A four-dimensional variational (4D-Var) data assimilation method is implemented in an improved intermediate coupled model (ICM) of the tropical Pacific. A twin experiment is designed to evaluate the impact of the 4D-Var data assimilation algorithm on ENSO analysis and prediction based on the ICM. The model error is assumed to arise only from the parameter uncertainty. The "observation" of the SST anomaly, which is sampled from a "truth" model simulation that takes default parameter values and has Gaussian noise added, is directly assimilated into the assimilation model with its parameters set erroneously. Results show that 4D-Var effectively reduces the error of ENSO analysis and therefore improves the prediction skill of ENSO events compared with the non-assimilation case. These results provide a promising way for the ICM to achieve better real-time ENSO prediction.
2016, 33(7): 889-904.
doi: 10.1007/s00376-016-5223-y
Abstract:
This paper describes a strategy for merging daily precipitation information from gauge observations, satellite estimates (SEs), and numerical predictions at the global scale. The strategy is designed to remove systemic bias and random error from each individual daily precipitation source to produce a better gridded global daily precipitation product through three steps. First, a cumulative distribution function matching procedure is performed to remove systemic bias over gauge-located land areas. Then, the overall biases in SEs and model predictions (MPs) over ocean areas are corrected using a rescaled strategy based on monthly precipitation. Third, an optimal interpolation (OI)-based merging scheme (referred as the HL-OI scheme) is used to combine unbiased gauge observations, SEs, and MPs to reduce random error from each source and to produce a gauge—satellite-model merged daily precipitation analysis, called BMEP-d (Beijing Climate Center Merged Estimation of Precipitation with daily resolution), with complete global coverage. The BMEP-d data from a four-year period (2011-14) demonstrate the ability of the merging strategy to provide global daily precipitation of substantially improved quality. Benefiting from the advantages of the HL-OI scheme for quantitative error estimates, the better source data can obtain more weights during the merging processes. The BMEP-d data exhibit higher consistency with satellite and gauge source data at middle and low latitudes, and with model source data at high latitudes. Overall, independent validations against GPCP-1DD (GPCP one-degree daily) show that the consistencies between BMEP-d and GPCP-1DD are higher than those of each source dataset in terms of spatial pattern, temporal variability, probability distribution, and statistical precipitation events.
This paper describes a strategy for merging daily precipitation information from gauge observations, satellite estimates (SEs), and numerical predictions at the global scale. The strategy is designed to remove systemic bias and random error from each individual daily precipitation source to produce a better gridded global daily precipitation product through three steps. First, a cumulative distribution function matching procedure is performed to remove systemic bias over gauge-located land areas. Then, the overall biases in SEs and model predictions (MPs) over ocean areas are corrected using a rescaled strategy based on monthly precipitation. Third, an optimal interpolation (OI)-based merging scheme (referred as the HL-OI scheme) is used to combine unbiased gauge observations, SEs, and MPs to reduce random error from each source and to produce a gauge—satellite-model merged daily precipitation analysis, called BMEP-d (Beijing Climate Center Merged Estimation of Precipitation with daily resolution), with complete global coverage. The BMEP-d data from a four-year period (2011-14) demonstrate the ability of the merging strategy to provide global daily precipitation of substantially improved quality. Benefiting from the advantages of the HL-OI scheme for quantitative error estimates, the better source data can obtain more weights during the merging processes. The BMEP-d data exhibit higher consistency with satellite and gauge source data at middle and low latitudes, and with model source data at high latitudes. Overall, independent validations against GPCP-1DD (GPCP one-degree daily) show that the consistencies between BMEP-d and GPCP-1DD are higher than those of each source dataset in terms of spatial pattern, temporal variability, probability distribution, and statistical precipitation events.
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