An experiment using the Community Climate System Model(CCSM4), a participant of the Coupled Model Intercomparison Project phase-5(CMIP5), is analyzed to assess the skills of this model in simulating and predicting the...An experiment using the Community Climate System Model(CCSM4), a participant of the Coupled Model Intercomparison Project phase-5(CMIP5), is analyzed to assess the skills of this model in simulating and predicting the climate variabilities associated with the oceanic channel dynamics across the Indo-Pacific Oceans. The results of these analyses suggest that the model is able to reproduce the observed lag correlation between the oceanic anomalies in the southeastern tropical Indian Ocean and those in the cold tongue in the eastern equatorial Pacific Ocean at a time lag of 1 year. This success may be largely attributed to the successful simulation of the interannual variations of the Indonesian Throughflow, which carries the anomalies of the Indian Ocean Dipole(IOD) into the western equatorial Pacific Ocean to produce subsurface temperature anomalies, which in turn propagate to the eastern equatorial Pacific to generate ENSO. This connection is termed the "oceanic channel dynamics" and is shown to be consistent with the observational analyses. However, the model simulates a weaker connection between the IOD and the interannual variability of the Indonesian Throughflow transport than found in the observations. In addition, the model overestimates the westerly wind anomalies in the western-central equatorial Pacific in the year following the IOD, which forces unrealistic upwelling Rossby waves in the western equatorial Pacific and downwelling Kelvin waves in the east. This assessment suggests that the CCSM4 coupled climate system has underestimated the oceanic channel dynamics and overestimated the atmospheric bridge processes.展开更多
Soil moisture is an important state variable for land–atmosphere interactions.It is a vital land surface variable for research on hydrology,agriculture,climate,and drought monitoring.In current study,a soil moisture ...Soil moisture is an important state variable for land–atmosphere interactions.It is a vital land surface variable for research on hydrology,agriculture,climate,and drought monitoring.In current study,a soil moisture data assimilation framework has been developed by using the Community Land Model version 4.5(CLM4.5)and the proper orthogonal decomposition(POD)-based ensemble four-dimensional variational assimilation(PODEn4 DVar)algorithm.Assimilation experiments were conducted at four agricultural sites in Pakistan by assimilating in-situ soil moisture observations.The results showed that it was a reliable system.To quantify further the feasibility of the data assimilation(DA)system,soil moisture observations from the top four soil-depths(0–5,5–10,10–20,and 20–30 cm)were assimilated.The evaluation results indicated that the DA system improved soil moisture estimation.In addition,updating the soil moisture in the upper soil layers of CLM4.5 could improve soil moisture estimation in deeper soil layers[layer 7(L7,62.0 cm)and layer 8(L8,103.8 cm)].To further evaluate the DA system,observing system simulation experiments(OSSEs)were designed for Pakistan by assimilating daily observations.These idealized experiments produced statistical results that had higher correlation coefficients,reduced root mean square errors,and lower biases for assimilation,which showed that the DA system is able to produce and improve soil moisture estimation in Pakistan.展开更多
Two global experiments were carried out to investigate the effects of dynamic vegetation processes on numerical climate simulations from 1948 to 2008.The NCEP Global Forecast System(GFS)was coupled with a biophysical ...Two global experiments were carried out to investigate the effects of dynamic vegetation processes on numerical climate simulations from 1948 to 2008.The NCEP Global Forecast System(GFS)was coupled with a biophysical model,the Simplified Simple Biosphere Model(SSi B)version 2(GFS/SSi B2),and it was also coupled with a biophysical and dynamic vegetation model,SSi B version 4/Top-down Representation of Interactive Foliage and Flora Including Dynamics(TRIFFID)(GFS/SSi B4/TRIFFID).The effects of dynamic vegetation processes on the simulation of precipitation,near-surface temperature,and the surface energy budget were identified on monthly and annual scales by assessing the GFS/SSi B4/TRIFFID and GFS/SSi B2 results against the satellite-derived leaf area index(LAI)and albedo and the observed land surface temperature and precipitation.The results show that compared with the GFS/SSiB2 model,the temporal correlation coefficients between the globally averaged monthly simulated LAI and the Global Inventory Monitoring and Modeling System(GIMMS)/Global Land Surface Satellite(GLASS)LAI in the GFS/SSi B4/TRIFFID simulation increased from 0.31/0.29(SSiB2)to 0.47/0.46(SSiB4).The correlation coefficients between the simulated and observed monthly mean near-surface air temperature increased from 0.50(Africa),0.35(Southeast Asia),and 0.39(South America)to 0.56,0.41,and 0.44,respectively.The correlation coefficients between the simulated and observed monthly mean precipitation increased from 0.19(Africa),0.22(South Asia),and 0.22(East Asia)to 0.25,0.27,and 0.28,respectively.The greatest improvement occurred over arid and semiarid areas.The spatiotemporal variability and changes in vegetation and ground surface albedo modeled by the GFS with a dynamic vegetation model were more consistent with the observations.The dynamic vegetation processes contributed to the surface energy and water balance and in turn,improved the annual variations in the simulated regional temperature and precipitation.The dynamic vegetation processes had the greatest influence on the spatiotemporal changes in the latent heat flux.This study shows that dynamic vegetation processes in earth system models significantly improve simulations of the climate mean status.展开更多
Biogeophysical effects of land use and land cover （LULC） changes play a significant role in modulating climate on various spatial scales. In this study, a set of recent LULC products with a spatial resolution of 500...Biogeophysical effects of land use and land cover （LULC） changes play a significant role in modulating climate on various spatial scales. In this study, a set of recent LULC products with a spatial resolution of 500 m was developed in China for update in RegCM4 （regional climate model version 4）. Two sets of comparative numerical experiments were conducted to study the effects of LULC changes on near-surface temperature simulation. The results show that after LULC changes, areas of crops and mixed woodlands as well as urban areas increase over entire China, accom- panied with greatly expanded mixed farming and forests/field mosaics in southern China, and reduced areas of 1） ir- rigated crops and short grasses in northern China and the Tibetan Plateau, and 2） semi-desert and desert in northwest-em China. Improvements in the LULC data clearly result in more accurate simulations of the near-surface temperat-ure. Specifically, increasing latent heat and longwave albedo due to enhanced LULC in certain areas lead to reduc-tion in land surface temperature （LST）, while changes in shortwave albedo and sensible heat also exert a great influ- ence on the LST. Overall, these parameter adjustments reduce the biases in near-surface temperature simulation.展开更多
The NCAR community climate model was run for 20 years and the simulated East Asian climate was analyzed and checked against the observation data.It is found that the large-scale features of the East Asia climate were ...The NCAR community climate model was run for 20 years and the simulated East Asian climate was analyzed and checked against the observation data.It is found that the large-scale features of the East Asia climate were simulated pretty well by the model,though there are still some discrepancies between the model output and the observation.The simulated geopotential height,wind and temperature fields are very close to the observations.The large scale systems such as subtropical high.Mongolia high,Indian low which have important influence on the East Asia monsoon also simulated pretty well.It is also found that the moisture field is not simulated so well as those fields mentioned above.The simulated precipitation is rather different from the observations.These suggest that some physical processes in the CCM2 need to be improved.展开更多
基金the National Basic Research Program of China(973 Program)(No.2012CB956000)the Strategic Priority Project of Chinese Academy of Sciences(No.XDA11010301)+2 种基金the National Natural Science Foundation of China(Nos.41421005,U1406401)the Public Welfare Grant of China Meteorological Administration(No.GYHY201306018)the Global Change and Air-Sea Interactions of State Oceanic Administration(No.GASI-03-01-01-05)
文摘An experiment using the Community Climate System Model(CCSM4), a participant of the Coupled Model Intercomparison Project phase-5(CMIP5), is analyzed to assess the skills of this model in simulating and predicting the climate variabilities associated with the oceanic channel dynamics across the Indo-Pacific Oceans. The results of these analyses suggest that the model is able to reproduce the observed lag correlation between the oceanic anomalies in the southeastern tropical Indian Ocean and those in the cold tongue in the eastern equatorial Pacific Ocean at a time lag of 1 year. This success may be largely attributed to the successful simulation of the interannual variations of the Indonesian Throughflow, which carries the anomalies of the Indian Ocean Dipole(IOD) into the western equatorial Pacific Ocean to produce subsurface temperature anomalies, which in turn propagate to the eastern equatorial Pacific to generate ENSO. This connection is termed the "oceanic channel dynamics" and is shown to be consistent with the observational analyses. However, the model simulates a weaker connection between the IOD and the interannual variability of the Indonesian Throughflow transport than found in the observations. In addition, the model overestimates the westerly wind anomalies in the western-central equatorial Pacific in the year following the IOD, which forces unrealistic upwelling Rossby waves in the western equatorial Pacific and downwelling Kelvin waves in the east. This assessment suggests that the CCSM4 coupled climate system has underestimated the oceanic channel dynamics and overestimated the atmospheric bridge processes.
基金Supported by the National Key Basic Research and Development Program of China(2018YFC1506602)National Natural Science Foundation of China(41830967)Key Research Program of Frontier Sciences,Chinese Academy of Sciences(QYZDY-SSWDQC012).
文摘Soil moisture is an important state variable for land–atmosphere interactions.It is a vital land surface variable for research on hydrology,agriculture,climate,and drought monitoring.In current study,a soil moisture data assimilation framework has been developed by using the Community Land Model version 4.5(CLM4.5)and the proper orthogonal decomposition(POD)-based ensemble four-dimensional variational assimilation(PODEn4 DVar)algorithm.Assimilation experiments were conducted at four agricultural sites in Pakistan by assimilating in-situ soil moisture observations.The results showed that it was a reliable system.To quantify further the feasibility of the data assimilation(DA)system,soil moisture observations from the top four soil-depths(0–5,5–10,10–20,and 20–30 cm)were assimilated.The evaluation results indicated that the DA system improved soil moisture estimation.In addition,updating the soil moisture in the upper soil layers of CLM4.5 could improve soil moisture estimation in deeper soil layers[layer 7(L7,62.0 cm)and layer 8(L8,103.8 cm)].To further evaluate the DA system,observing system simulation experiments(OSSEs)were designed for Pakistan by assimilating daily observations.These idealized experiments produced statistical results that had higher correlation coefficients,reduced root mean square errors,and lower biases for assimilation,which showed that the DA system is able to produce and improve soil moisture estimation in Pakistan.
基金Supported by the National Key Research and Development Program of China(2018YFC1507700)National Natural Science Foundation of China(41905083)the United States National Science Foundation(AGS-1419526)。
文摘Two global experiments were carried out to investigate the effects of dynamic vegetation processes on numerical climate simulations from 1948 to 2008.The NCEP Global Forecast System(GFS)was coupled with a biophysical model,the Simplified Simple Biosphere Model(SSi B)version 2(GFS/SSi B2),and it was also coupled with a biophysical and dynamic vegetation model,SSi B version 4/Top-down Representation of Interactive Foliage and Flora Including Dynamics(TRIFFID)(GFS/SSi B4/TRIFFID).The effects of dynamic vegetation processes on the simulation of precipitation,near-surface temperature,and the surface energy budget were identified on monthly and annual scales by assessing the GFS/SSi B4/TRIFFID and GFS/SSi B2 results against the satellite-derived leaf area index(LAI)and albedo and the observed land surface temperature and precipitation.The results show that compared with the GFS/SSiB2 model,the temporal correlation coefficients between the globally averaged monthly simulated LAI and the Global Inventory Monitoring and Modeling System(GIMMS)/Global Land Surface Satellite(GLASS)LAI in the GFS/SSi B4/TRIFFID simulation increased from 0.31/0.29(SSiB2)to 0.47/0.46(SSiB4).The correlation coefficients between the simulated and observed monthly mean near-surface air temperature increased from 0.50(Africa),0.35(Southeast Asia),and 0.39(South America)to 0.56,0.41,and 0.44,respectively.The correlation coefficients between the simulated and observed monthly mean precipitation increased from 0.19(Africa),0.22(South Asia),and 0.22(East Asia)to 0.25,0.27,and 0.28,respectively.The greatest improvement occurred over arid and semiarid areas.The spatiotemporal variability and changes in vegetation and ground surface albedo modeled by the GFS with a dynamic vegetation model were more consistent with the observations.The dynamic vegetation processes contributed to the surface energy and water balance and in turn,improved the annual variations in the simulated regional temperature and precipitation.The dynamic vegetation processes had the greatest influence on the spatiotemporal changes in the latent heat flux.This study shows that dynamic vegetation processes in earth system models significantly improve simulations of the climate mean status.
基金Supported by the China Meteorological Administration Special Public Welfare Research Fund(GYHY201506001)Gansu Provincial Meteorological Bureau Key Research Project(GSMAZd2017-10)
文摘Biogeophysical effects of land use and land cover （LULC） changes play a significant role in modulating climate on various spatial scales. In this study, a set of recent LULC products with a spatial resolution of 500 m was developed in China for update in RegCM4 （regional climate model version 4）. Two sets of comparative numerical experiments were conducted to study the effects of LULC changes on near-surface temperature simulation. The results show that after LULC changes, areas of crops and mixed woodlands as well as urban areas increase over entire China, accom- panied with greatly expanded mixed farming and forests/field mosaics in southern China, and reduced areas of 1） ir- rigated crops and short grasses in northern China and the Tibetan Plateau, and 2） semi-desert and desert in northwest-em China. Improvements in the LULC data clearly result in more accurate simulations of the near-surface temperat-ure. Specifically, increasing latent heat and longwave albedo due to enhanced LULC in certain areas lead to reduc-tion in land surface temperature （LST）, while changes in shortwave albedo and sensible heat also exert a great influ- ence on the LST. Overall, these parameter adjustments reduce the biases in near-surface temperature simulation.
文摘The NCAR community climate model was run for 20 years and the simulated East Asian climate was analyzed and checked against the observation data.It is found that the large-scale features of the East Asia climate were simulated pretty well by the model,though there are still some discrepancies between the model output and the observation.The simulated geopotential height,wind and temperature fields are very close to the observations.The large scale systems such as subtropical high.Mongolia high,Indian low which have important influence on the East Asia monsoon also simulated pretty well.It is also found that the moisture field is not simulated so well as those fields mentioned above.The simulated precipitation is rather different from the observations.These suggest that some physical processes in the CCM2 need to be improved.
