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2016 Vol. 21, No. 5

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Spatial-Temporal Variation and Abrupt Analysis of Evapotranspiration over the Yellow River Source Region
LIU Rong, WEN Jun, WANG Xin
2016, 21(5): 503-511. doi: 10.3878/j.issn.1006-9585.2015.15202
Abstract(1716) PDF (4250KB)(2267)
Evapotranspiration (ET) is a key factor in the eco-hydrological process on basin scale. However, it is hard to obtain long-term and reliable ET measurement data for a specific watershed. In this study, ET reanalysis products from the European Centre for Medium Range Weather Forecasts (ECMWF) and the U.S. National Centers for Environmental Prediction (NCEP) were compared to eddy covariance measurements in the Yellow River source region on daily scale. The ERA-Interim reanalysis data was found to have a good agreement with ET measurements in the Yellow River source region with the root mean square error (RMSQ) of 0.63; the NCEP reanalysis data was found to overestimate ET from April to July and from October to December with the RMSQ of 0.81. The Mann Kendall test and Sen's slope estimator test were then applied to quantify the changing trend of ET during 1979-2014 based on the Interim-ET reanalysis products. In general ET increased over the northern region and decreased in the south during the study period. The most rapid increase of 1.5-2.5 mm/a was found in the northern region in Xinhai-Gonghe-Guide, and the most rapid decrease of -1.0--0.5 mm/a was found in the southwestern region in Qumalai-Zhidu-Yushu. In the southeastern region in Maqin-Maqu-Jiuzhi, ET also increased by 0.5-1.0 mm/a. Abrupt ET changes over Yellow River source region mainly occurred in the 1980s based on results of both the moving t test and the sequential Mann Kendall test.
Simulation and Evaluation of Statistical Downscaling of Regional Daily Precipitation over Yangtze-Huaihe River Basin Based on Self-Organizing Maps
ZHOU Pu, JIANG Zhihong
2016, 21(5): 512-524. doi: 10.3878/j.issn.1006-9585.2016.16097
Abstract(1547) PDF (1847KB)(3000)
Based on the ERA-40 daily reanalysis data from 1961-2002 and observed daily precipitation data at 56 meteorological stations located in the Yangtze-Huaihe River basin, this study applies a new downscaling method based on Self-Organizing Maps (SOMs) to produce downscaled summer precipitation estimates at each station. The simulation capability of the statistical downscaling approach for monsoon precipitation and extreme precipitation over East China have been assessed. The downscaling model is then applied to simulate daily precipitation at the same 56 stations for the period 1986-2005 using predictor sets simulated by BCC-CSM1.1(m) (Climate System Model of the Beijing Climate Center). Results show that the downscaling approach can realistically reproduce the observed probability distribution and temporal variability of precipitation. The Brier scores are almost zero and the significance scores are above 0.8 for all stations. Average biases of the downscaled number of days with precipitation greater than 1 mm and 10 mm, the summer total precipitation, the simple daily intensity index, the extreme daily precipitation threshold, and the fraction of total precipitation due to events exceeding the 95th percentile of the climatological wet-day precipitation distribution all are below 11%. Furthermore, the downscaling approach is, to a certain extent, able to reproduce the temporal variability characteristics of precipitation. Compared with that for the raw outputs of BCC-CSM1.1(m), the biases of the above indices for the downscaled results reduce by 40% to 60%. The spatial correlation coefficients increase to 0.9, and the root mean square errors are below 0.5. Overall, the downscaling model significantly improves the simulation of the probability distribution of daily precipitation, particularly the simulation of extreme precipitation. Thereby it can be applied for the projection of future precipitation changes.
Daily Maximum Height of Atmospheric Boundary Layer in Beijing: Climatology and Environmental Meaning
WANG Jian, CAI Xuhui, SONG Yu
2016, 21(5): 525-532. doi: 10.3878/j.issn.1006-9585.2016.15178
Abstract(1576) PDF (2825KB)(2130)
The dry adiabatic method was applied to analyze sounding data and normal maximum surface temperatures collected at Beijing observatory during 1984-2013 and calculate daily maximum height of atmospheric boundary layer (MABL) in Beijing area. The mean wind speed and ventilation were obtained simultaneously. Characteristics of the three boundary layer variables and the air pollution index (API) were analyzed to investigate the relationship between the boundary layer variables and air pollution. The results showed that: (1) Monthly mean MABL of about 1600 m is the highest in the spring and early summer (March to June), following by that in the summer and early autumn (July to October), which is about 1300 m; the monthly mean MABL is low in the winter (November, December, and January) with a value of about 1000-1200 m; (2) in the summer, the frequency distribution of the MABL is roughly symmetric with the peak value within the range of 1000-1600 m; in the autumn and winter, the frequency distribution is skewed to the lower side with the largest frequency for the MABL within the range of 600-800 m; the MABL frequency varies greatly in the spring; (3) the mean wind speed in the boundary layer is lowest in the summer; (4) ventilation reaches maximum in the spring, followed by that in the autumn and summer, and it is minimum in the winter; (5) in the autumn and winter, heavy pollution (API>200) is often accompanied with weak winds, low boundary layer height and low ventilation, reflecting the cumulative effect of local pollutants. In the spring, more than half of the pollution events are characterized by high wind speeds and high ventilation, reflecting the dust pollution by external inputs.
Evaluation and Projection of the Climatic Characteristics of Aleutian Low Based on CMIP5 Models
LI Kailin, ZHI Hai, BAI Wenrong
2016, 21(5): 533-546. doi: 10.3878/j.issn.1006-9585.2016.15161
Abstract(1368) PDF (8772KB)(1439)
The observed sea surface temperature, sea level pressure and multi-model simulations of the Coupled Model Inter-comparison Project 5 (CMIP5) are explored to analyze the temporal and spatial variation of the Aleutian Low (AL) index in the North Pacific. Furthermore, the decadal cycle variability is evaluated and the long-term trend is estimated based on simulations of the CMIP5. Results show that the CMIP5 multi-model simulations can well reproduce the climatology and variability of the AL circulation. Specifically, the simulated AL is sensitive to simulated sea surface temperature in the East Pacific. However, the comparison of the CMIP5 multi-model ensemble results and observations indicates that the intensity of the standard deviation of the ensemble mean is stronger than that of the observation, while the model ability for standard deviation simulation is worse than that for mean climate state simulation. Also, 16 out of the 22 CMIP5 models can reproduce the decadal oscillation cycle of the AL. In the Historical experiment, there is a large disagreement over the long-term trend of AL among the model results. It is suggested that the AL strengthens and extends northward under two typical Representation Concentration Pathway scenarios (i.e. RCP4.5 and RCP8.5), particularly under the RCP8.5 scenario. More significant annual and inter-decadal variations are found under the RCP8.5 scenario. It is also noted that the ensemble mean and most of the models can forecast the AL intensity and its northward extension. However, the reason for the eastward extension of AL is still controversial.
Horizontal and Vertical Distributions of Clouds of Different Types Based on CloudSat-CALIPSO Data
FANG Lexin, LI Yunying, SUN Guorong, GAO Cuicui, LU Zhixian
2016, 21(5): 547-556. doi: 10.3878/j.issn.1006-9585.2016.15240
Abstract(1530) PDF (9489KB)(1539)
Global mean total amount of clouds is 66.7%. The total cloud fraction of Cirrus (Ci) and Stratocumulus (Sc) clouds is comparable to the sum of clouds of other six types, indicating that Ci and Sc clouds are two most frequently occurring cloud types over the globe. The amount of cumuliform clouds decreases from tropical to subtropical, while the amount of stratiform clouds changes in the opposite direction, indicating different environments for the formation of cumuliform and stratiform clouds. The topography and synoptic systems can affect cloud occurrence too. The cloud height and thickness of eight types of clouds are significantly different in different regions. Ci clouds, with higher cloud base and top, are very thin. Altostratus (As) clouds and Altocumulus (Ac) clouds are mid-level clouds, but As clouds are thicker and located at higher levels than Ac clouds. Stratus (St), Sc, and Cumulus (Cu) clouds are thin clouds occurring in the lower atmosphere. Nimbostratus (Ns) and deep convective (DC) clouds are thick clouds with lower cloud base and higher cloud top. Overall, the height of the cloud base over the ocean is lower than that over the land. The cloud base is higher and the cloud depth is thicker in relatively unstable atmosphere such as over the equator than in stable atmosphere. Clouds over the Plateau are characterized by the features that high-clouds are not high and low-clouds are not low while the cloud depth is usually thin.
Study on the Ensemble Mean Method in Reducing the Numerical Error in Chaotic Dynamical System
WANG Pengfei, BI Shuting
2016, 21(5): 557-566. doi: 10.3878/j.issn.1006-9585.2016.16003
Abstract(1672) PDF (3745KB)(1804)
Five groups (each includes 20 samples) of numerical experiments are implemented and the solutions are compared with reliable solutions of the Lorenz chaotic system. Results indicate that the ensemble mean method is not as good as the high precision scheme in reducing the numerical error. 1) When a general scheme and double-precision are used in computing, the truncation error will be dominant, and the ensemble mean solution will not converge to the real solution but approach to a solution with the truncation error. 2) When the initial error is dominant compared to the truncation error, the error will increase exponentially, and the solution will converge to an error-induced solution that is mainly affected by the initial error. 3) When the initial error and the truncation error are comparable, neither of them can be eliminated. The probability density function (PDF) of the numerical solutions is also analyzed for the ensemble mean dynamical system. Results indicate that the PDF is significantly different to that in the original system. This difference further indicates that the ensemble mean method cannot yield a true numerical solution. The PDF study also suggests that a correct PDF distribution of the numerical solution cannot guarantee a correct solution.
Statistical Downscaling of Monthly Mean Temperature for Kazakhstan Using Ridge Regression
LI Yafei, WANG Leibin, MAO Huiqin, YAN Xiaodong
2016, 21(5): 567-576. doi: 10.3878/j.issn.1006-9585.2016.16027
Kazakhstan is the largest landlocked country in the world with a typical continental climate, and its natural environment and human society are sensitive and vulnerable to climate change. In climate change impact studies, one widely-used approach to obtain future climate change scenario at regional or local scale is to downscale future climate projection from General Circulation Model (GCM). So far, to our knowledge, no statistical downscaling study has been carried out in Kazakhstan region. In this study, the authors explored and validated the ability of a statistical downscaling model that is based on ridge regression to predict monthly mean temperatureat of 11 stations in Kazakhstan from NCEP/ NCAR monthly mean reanalysis. The 30-year dataset for the period from 1960 to 1989 was used to train the downscaling model and the next 20-year data for the period of 1990-2009 was used for validation of the downscaling model. The result shows that despite certain disagreements with observations at several stations, the ridge regression model generally is able to reasonably reproduce monthly mean temperature over Kazakhstan region. The authors also find that the performance of the ridge regression model is better in the summer than in the winter and better in flat terrain areas than in complex terrain areas.
The Relationship between the Ural Blocking in Boreal Winter and the East Asian Winter Monsoon
WU Jing, DIAO Yina, ZHUANG Xuzong
2016, 21(5): 577-585. doi: 10.3878/j.issn.1006-9585.2016.15172
Abstract(1393) PDF (1522KB)(1743)
Based on the National Centers for Environmental Prediction/National Center for Atmospheric Research (NCEP/NCAR) gridded reanalysis data during 1948-2013, the relationship between the Ural blocking in boreal winter and the East Asian winter monsoon was investigated on both interannual and intraseasonal time scales. Results show that the integrated index of the East Asian winter monsoon is highly correlated with the Ural blocking frequency. In addition, they share the same linear tendency and period. The Ural blockings exert significant influences on the East Asian winter monsoon on interannual time scale. Further analyses suggest that in the winter with frequent occurrence of the Ural blocking, the anti-cyclone over Siberia at 500 hPa tends to intensify and the East Asian trough becomes deeper than normal. There are also significant signals in the lower troposphere. High frequency of the Ural blocking potentially promotes a cold EAWM (East Asia Winter Monsoon) and equatorward wind anomalies over Lake Baikal and the coastal region of East Asia. As such, a link is established between the EAWM and the Ural blocking. The intensification and eastward migration of Siberia High correspond to the peak and decaying of the Ural blocking. Meanwhile, equatorward wind anomalies develop and gradually affect a large area from Lake Baikal to the east of the Philippines.
Characteristics of Seasonal Variations of Energy and Water Cycles over the Complex Underlying Surface of the Tibetan Plateau
CHEN Yuhang, FAN Guangzhou, LAI Xin, HUA Wei, ZHANG Yongli, WANG Bingyun, ZHU Lihua
2016, 21(5): 586-600. doi: 10.3878/j.issn.1006-9585.2016.15068
Abstract(1626) PDF (1232KB)(2329)
Using multiple daily data of GSWP (Global Soil Wetness Project), GLDAS (Global Land Data Assimilation System), AMSR-E (Advance Microwave Scanning Radiometer-EOS) soil moisture, and in-situ observations, the method of the sliding t test is applied to analyze characteristics of seasonal variations of the underlying surface variables for the purpose to better understand energy and water cycles over the Tibetan Plateau (TP). The analysis reveals that the seasonal variations of underlying surface physical variables are significant and closely related with each other. The seasonal variations of surface net shortwave radiation and sensible heat flux are significant and both start to increase in January. Their annual maximum values appear in May and June. Net long wave radiation is also high in May but low during the summer. Latent heat flux starts to grow remarkably in January and reaches its annual maximum value in the summer. Heat is transferred from the ground surface to the atmosphere since March, and then from the atmosphere to soil in September. Snow starts melting since March and decreases from March to May. Precipitation and vegetation water content begin to increase significantly in February. Rainfall increases sharply in May and June, leading to the peak value of 1-cm soil moisture. Precipitation, vegetation water content, plant transpiration, and total evapotranspiration all reach their highest values in July and August. During this time, the 1-cm soil moisture content is low but reaches its second peak in September. In October, with the underlying surface temperature turning cold, snow cover increases and 1-cm soil moisture decreases.
Cluster Analysis of the Circulation Situation Occurring during Fog and Haze Weather in North China
SUN Yu, NIU Tao, QIAO Lin, MA Zhenfeng, WU Wei
2016, 21(5): 601-613. doi: 10.3878/j.issn.1006-9585.2016.15119
Abstract(1897) PDF (7807KB)(1389)
40 in situ measurements of fog and haze over North China from 2000 through 2013 were used and cluster analysis is applied in the geopotential height field from the same period of NCEP daily reanalysis data. Results show that surface circulation situations can be respectively divided into four and five clusters when fog or haze weather occurs. Clustering results reveal that the atmospheric circulation has different characteristics when fog and haze occurs, weak high pressure is the only common type for both. The transportation of the humidity field and cold (warm) advection are also significantly different in fog and haze weather. In addition, the analysis results show that fog and haze conversion exists on the same day and fog coexists with haze at the same moment. The authors also analyze the circulation characteristics of these two scenarios, and provide explanations for the phenomena.
A Quality Control Algorithm for Surface Temperature Observations Based on Improved Kriging Method
YE Xiaoling, SHEN Yunpei, XIONG Xiong
2016, 21(5): 614-620. doi: 10.3878/j.issn.1006-9585.2016.15264
Abstract(1358) PDF (404KB)(2096)
A method called Ordinary Kriging (OK) in Geostatistics was introduced for quality control of surface temperature observations based on spatial correlation of temperature. Due to the continuity of temperature, Gaussian model was chosen as the semi-variogram model. Because of some possible disadvantages in applying Gaussian model, it is necessary to improve Gaussian model. A quality control method based on Improved Ordinary Kriging (IOK) was developed in this study. In order to assess the effectiveness and applicability of the proposed method, daily mean surface temperature observations collected at 67 stations in Jiangsu Province were used for quality control, and the results were compared with that from OK and Inverse Distance Weighted (IDW) methods. It was found that IOK performs better than IDW and OK in error checking, and the proposed method can effectively identify errors in temperature data. In addition, IOK also has higher stability and applicability.