The cause-effect relationship is not always possible to trace in GCMs because of the simultaneous inclusion of several highly complex physical processes. Furthermore, the inter-GCM differences are large and there is n...The cause-effect relationship is not always possible to trace in GCMs because of the simultaneous inclusion of several highly complex physical processes. Furthermore, the inter-GCM differences are large and there is no simple way to reconcile them. So, simple climate models, like statistical-dynamical models (SDMs), appear to be useful in this context. This kind of models is essentially mechanistic, being directed towards understanding the dependence of a particular mechanism on the other parameters of the problem. In this paper, the utility of SDMs for studies of climate change is discussed in some detail. We show that these models are an indispensable part of hierarchy of climate models.展开更多
A quantitative description of the processes taking place among the atmosphere, vegetation and soil is needed for studying air-land interaction and interrelation between the geosphere and the biosphere. In this paper, ...A quantitative description of the processes taking place among the atmosphere, vegetation and soil is needed for studying air-land interaction and interrelation between the geosphere and the biosphere. In this paper, a simple land surface process model is proposed. Through transfers and exchanges of heat and water, the therrnal and moisture states of the atmosphere, vegetation and soil are linked in a coupled system, in which vegetation is considered as a horizontally uniform layer, soil is divided into three layers and the horizontal differences of variables in the system are neglected. The preliminary results of the experiment indicate that the model is capable of predicting the thermal and moisture conditions of the land surface and suitable to climate study.展开更多
According to the nonlinear basic theory that a forced dissipative nonlinear system in a higher dimensional state space can be evolved into an attractor set of the descending dimension, a new method of reducing the deg...According to the nonlinear basic theory that a forced dissipative nonlinear system in a higher dimensional state space can be evolved into an attractor set of the descending dimension, a new method of reducing the degrees of freedom of the general circulation model (GCM) is given. The concrete way of it is: the time-dependent integral series of the model is decomposed through empirical orthogonal functions (EOFs), therefore the small number of the degrees of freedom supporting the attractor set of GCM can be formed, and then a simplified model can be derived when the EOFs are used as basis. The numerical simulation experiment has been done by using a theoretical model, and we are sure that the feasibility and effectiveness of the method can be proved.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
Based on the results of the complex climate model BCC-CSM,the Beijing Climate Center Simple Earth System Model(BCC-SESM)was developed for climate system simulations in Integrated Assessment Models(IAMs).The first vers...Based on the results of the complex climate model BCC-CSM,the Beijing Climate Center Simple Earth System Model(BCC-SESM)was developed for climate system simulations in Integrated Assessment Models(IAMs).The first version of the BCC-SESM model was based on a high-emissions scenario(ESMRCP8.5)and tends to overestimate the temperatures in low and medium emissions scenarios.To address this problem,this study uses three CO_(2)-concentration-driven simulations under different RCP scenarios of complex climate models to evaluate parameters sensitivity and their impacts on projection efficacy.The results show that the new version of the BCC-SESM(denoted as BCC-SESM1.1)model based on a medium-emissions scenario experiment(RCP4.5)is more suitable for temperature projections for various climate scenarios.It can well reproduce the original value of complex climate model.At the same time,it also has high predictive efficacies for medium(RCP4.5)and low(RCP2.6)emissions scenarios,although it tends to underestimate for high emissions scenario(RCP8.5).The sensitivity tests for different RCP scenarios shows that the BCC-SESM1.1 has higher efficacy in projections of future climate change than those model versions based on the other scenarios.The projection deviations for the global average temperature by the BCC-SESM1.1(<2%)are better than the previous BCC-SESM(<5%).In light of recent progress in climate policy,the BCC-SESM1.1 is hence more suitable for coupling with IAMs for the purposes of assessing climate outcomes.展开更多
In this paper, by using a simple climate model (SCM), a numerical simulationstudy has been conducted on the scientific and methodological aspects of Brazilian Proposal. Firstthe initial check of simple climate model h...In this paper, by using a simple climate model (SCM), a numerical simulationstudy has been conducted on the scientific and methodological aspects of Brazilian Proposal. Firstthe initial check of simple climate model has been done, then we do some sensitivity studies ontimeframes (attribution start and end dates, and evaluation date), and three attribution methods(marginal attribution method, proportional attribution method, and time-sliced attribution method),at last we get the main conclusions as follows: The simple climate model can represent the resultsof more complex climate model (e.g., HadCM3), and it is thus used to study the scientific andmethodological aspects of the Brazilian Proposal. Because of the limited knowledge of science anddata, although attributing a part of temperature increase to different GHG (greenhouse gas) emissionsource, there is considerable temperature increase unattributed to regional emissions. Therefore itis uncertain to make Brazilian Proposal as the method for the responsibility share of future GHGdecrease emission. The choices of different timeframes (attribution start and end dates, andevaluation date) and future emission SRES (Special Report on Emission Scenarios) make greatinfluence on the regional contributions to global climate changes, but different attribution methodshave only a little influence.展开更多
文摘The cause-effect relationship is not always possible to trace in GCMs because of the simultaneous inclusion of several highly complex physical processes. Furthermore, the inter-GCM differences are large and there is no simple way to reconcile them. So, simple climate models, like statistical-dynamical models (SDMs), appear to be useful in this context. This kind of models is essentially mechanistic, being directed towards understanding the dependence of a particular mechanism on the other parameters of the problem. In this paper, the utility of SDMs for studies of climate change is discussed in some detail. We show that these models are an indispensable part of hierarchy of climate models.
文摘A quantitative description of the processes taking place among the atmosphere, vegetation and soil is needed for studying air-land interaction and interrelation between the geosphere and the biosphere. In this paper, a simple land surface process model is proposed. Through transfers and exchanges of heat and water, the therrnal and moisture states of the atmosphere, vegetation and soil are linked in a coupled system, in which vegetation is considered as a horizontally uniform layer, soil is divided into three layers and the horizontal differences of variables in the system are neglected. The preliminary results of the experiment indicate that the model is capable of predicting the thermal and moisture conditions of the land surface and suitable to climate study.
基金This work was supported by Higher Learning Institution Doctoral Unit Sciences Foundation of the National Educational Committee
文摘According to the nonlinear basic theory that a forced dissipative nonlinear system in a higher dimensional state space can be evolved into an attractor set of the descending dimension, a new method of reducing the degrees of freedom of the general circulation model (GCM) is given. The concrete way of it is: the time-dependent integral series of the model is decomposed through empirical orthogonal functions (EOFs), therefore the small number of the degrees of freedom supporting the attractor set of GCM can be formed, and then a simplified model can be derived when the EOFs are used as basis. The numerical simulation experiment has been done by using a theoretical model, and we are sure that the feasibility and effectiveness of the method can be proved.
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funded by National Natural Science Foundation of China(42175171)National Key R&D Program of China(2016YFA0602602)Public Welfare Meteo-rology Research Project(GYHY201506023).
文摘Based on the results of the complex climate model BCC-CSM,the Beijing Climate Center Simple Earth System Model(BCC-SESM)was developed for climate system simulations in Integrated Assessment Models(IAMs).The first version of the BCC-SESM model was based on a high-emissions scenario(ESMRCP8.5)and tends to overestimate the temperatures in low and medium emissions scenarios.To address this problem,this study uses three CO_(2)-concentration-driven simulations under different RCP scenarios of complex climate models to evaluate parameters sensitivity and their impacts on projection efficacy.The results show that the new version of the BCC-SESM(denoted as BCC-SESM1.1)model based on a medium-emissions scenario experiment(RCP4.5)is more suitable for temperature projections for various climate scenarios.It can well reproduce the original value of complex climate model.At the same time,it also has high predictive efficacies for medium(RCP4.5)and low(RCP2.6)emissions scenarios,although it tends to underestimate for high emissions scenario(RCP8.5).The sensitivity tests for different RCP scenarios shows that the BCC-SESM1.1 has higher efficacy in projections of future climate change than those model versions based on the other scenarios.The projection deviations for the global average temperature by the BCC-SESM1.1(<2%)are better than the previous BCC-SESM(<5%).In light of recent progress in climate policy,the BCC-SESM1.1 is hence more suitable for coupling with IAMs for the purposes of assessing climate outcomes.
基金The work is supported by Climate Change Special Funds of China Meteorological Administration (CCSF2005-2-QH11).
文摘In this paper, by using a simple climate model (SCM), a numerical simulationstudy has been conducted on the scientific and methodological aspects of Brazilian Proposal. Firstthe initial check of simple climate model has been done, then we do some sensitivity studies ontimeframes (attribution start and end dates, and evaluation date), and three attribution methods(marginal attribution method, proportional attribution method, and time-sliced attribution method),at last we get the main conclusions as follows: The simple climate model can represent the resultsof more complex climate model (e.g., HadCM3), and it is thus used to study the scientific andmethodological aspects of the Brazilian Proposal. Because of the limited knowledge of science anddata, although attributing a part of temperature increase to different GHG (greenhouse gas) emissionsource, there is considerable temperature increase unattributed to regional emissions. Therefore itis uncertain to make Brazilian Proposal as the method for the responsibility share of future GHGdecrease emission. The choices of different timeframes (attribution start and end dates, andevaluation date) and future emission SRES (Special Report on Emission Scenarios) make greatinfluence on the regional contributions to global climate changes, but different attribution methodshave only a little influence.
