Performance assessment of general circulation models: application of compromise programming method and global performance indicator technique

2021 ◽  
Author(s):  
B. Deepthi ◽  
Bellie Sivakumar
Keyword(s):  
Performance Assessment ◽  
General Circulation ◽  
Performance Indicator ◽  
General Circulation Models ◽  
Compromise Programming ◽  
Programming Method ◽  
Global Performance

RANKING OF CMIP5-BASED GENERAL CIRCULATION MODELS USING COMPROMISE PROGRAMMING AND TOPSIS FOR PRECIPITATION: A CASE STUDY OF UPPER GODAVARI BASIN, INDIA

2020 ◽  
pp. 2050007
Author(s):  
B. DEEPTHI ◽  
AKSHAY SUNIL ◽  
SARANYA C. NAIR ◽  
A. B. MIRAJKAR ◽  
S. ADARSH
Keyword(s):  
Decision Making ◽  
Group Decision Making ◽  
Performance Indicators ◽  
General Circulation ◽  
Group Decision ◽  
Performance Indicator ◽  
General Circulation Models ◽  
Entropy Method ◽  
Compromise Programming ◽  
Grid Points

This study determines the suitable general circulation models (GCMs) for the prediction of future precipitation of Upper Godavari sub-basin, India. Five performance indicators (PIs) namely correlation coefficient (CC), normalized root mean square deviation (NRMSD), absolute normalized mean biased deviation (ANMBD), skill score (SS), Nash Sutcliffe efficiency (NSE), and three different combinations (Case 1: all performance indicators, Case 2: CC, SS and ANMBD, and Case 3: CC, SS, and NRMSD) were considered to evaluate the performance of 38 GCM models for the study area. The observed precipitation data for 12 grid points covering the Upper Godavari sub-basin along with eight districts of Maharashtra were used for the selection of the suitable GCMs. The weights of the indicators were determined by the entropy method. Compromise programming (CP) and the technique for order preference to the similarity to ideal solution (TOPSIS) methods were used for ranking the GCMs. The group decision-making approach was employed to make a collective decision about the rank of 38 GCMS considering all the grid points. In view of all the three combinations of PIs, the study suggests that the effect of the performance indicator NSE on the ranking of GCM models is the most significant (weights for the grid points varying in the range 22.75%–78%) followed by ANMBD, CC, NRMSD, and SS. Including the maximum number of PIs and considering their combinations is found to be much helpful to enhance the credibility of the ranking of GCMs. From the group decision-making approach, it was observed that the ensemble of MPI-ESM-P, CNRM-CM5-2, and CNRM-CM5 is suitable for the prediction of precipitation for the study area.

scholarly journals An effective parameter optimization with radiation balance constraint in CAM5 (version 5.3)

2019 ◽  
Author(s):  
Li Wu ◽  
Tao Zhang ◽  
Yi Qin ◽  
Wei Xue
Keyword(s):  
Parameter Optimization ◽  
General Circulation ◽  
Performance Indicator ◽  
Optimization Problems ◽  
Model Performance ◽  
Optimization Methods ◽  
General Circulation Models ◽  
Atmospheric Model ◽  
Radiation Balance ◽  
Performance Metric

Abstract. Uncertain parameters in physical parameterizations of General Circulation Models (GCMs) greatly impact model performance. In recent years, automatic parameter optimization has been introduced for tuning model performance of GCMs but most of the optimization methods are unconstrained optimization methods under a given performance indicator, so that the calibrated model may break through essential constraints that models have to keep, such as the radiation balance at top of model, which is known for its importance to the conservation of model energy. In this study, an automated and efficient parameter optimization with the radiation balance constraint is presented and applied in Community Atmospheric Model (CAM5) in terms of a synthesized performance metric using global means of radiation, precipitation, relative humidity, and temperature. The tuned parameters are from the parameterization schemes of convection and cloud. And the radiation constraint is defined as the deviation of the net longwave flux at top of model (FLNT) and net solar flux at top of model (FSNT) less than 1 W m−2. Results show that the synthesized performance under the optimal parameters is 6.3 % better than the control run (CNTL) as well as the radiation imbalance is as low as 0.1 W m−2. The proposed method provides the insight for physics-guided optimization under the premise of a profound understanding of models and it can be easily applied to optimization problems with other prerequisite constraints in GCMs.

scholarly journals An effective parameter optimization with radiation balance constraint in CAM5 (version 5.3)

2020 ◽  
Vol 13 (1) ◽  
pp. 41-53
Author(s):  
Li Wu ◽  
Tao Zhang ◽  
Yi Qin ◽  
Wei Xue
Keyword(s):  
Parameter Optimization ◽  
General Circulation ◽  
Performance Indicator ◽  
Optimization Problems ◽  
Model Performance ◽  
Optimization Methods ◽  
General Circulation Models ◽  
Atmospheric Model ◽  
Absolute Difference ◽  
Radiation Balance

Abstract. Uncertain parameters in physical parameterizations of general circulation models (GCMs) greatly impact model performance. In recent years, automatic parameter optimization has been introduced for tuning model performance of GCMs, but most of the optimization methods are unconstrained optimization methods under a given performance indicator. Therefore, the calibrated model may break through essential constraints that models have to keep, such as the radiation balance at the top of the model. The radiation balance is known for its importance in the conservation of model energy. In this study, an automated and efficient parameter optimization with the radiation balance constraint is presented and applied in the Community Atmospheric Model (CAM5) in terms of a synthesized performance metric using normalized mean square error of radiation, precipitation, relative humidity, and temperature. The tuned parameters are from the parameterization schemes of convection and cloud. The radiation constraint is defined as the absolute difference of the net longwave flux at the top of the model (FLNT) and the net solar flux at the top of the model (FSNT) of less than 1 W m−2. Results show that the synthesized performance under the optimal parameters is 6.3 % better than the control run (CNTL) and the radiation imbalance is as low as 0.1 W m−2. The proposed method provides an insight for physics-guided optimization, and it can be easily applied to optimization problems with other prerequisite constraints in GCMs.

scholarly journals Evaluation of the CMIP5 general circulation models for simulating the precipitation and temperature of the Koshi River Basin in Nepal

2021 ◽  
Author(s):  
Pragya Pradhan ◽  
Sangam Shrestha ◽  
S. Mohana Sundaram ◽  
Salvatore G. P. Virdis
Keyword(s):  
River Basin ◽  
General Circulation ◽  
Performance Indicator ◽  
Extreme Temperature ◽  
General Circulation Models ◽  
Climate Impact ◽  
Climate Indices ◽  
Extreme Precipitation Events ◽  
Koshi River Basin ◽  
Precipitation And Temperature

Abstract This study evaluates the performance of 12 different general circulation models (GCMs) from the Coupled Model Intercomparison Project Phase 5 (CMIP5) to simulate precipitation and temperature in the Koshi River Basin, Nepal. Four statistical performance indicators: correlation coefficient, normalised root-mean-square deviation (NMRSD), absolute NMRSD, and average absolute relative deviation are considered to evaluate the GCMs using historical observations. Seven different climate indices: consecutive dry days, consecutive wet days, cold spell duration index, warm spell duration index, frost days, very wet days, and simple daily intensity index are considered to identify the most suitable models for the basin and future climate impact assessment studies. Weights for each performance indicator are determined using the entropy method, with compromise programming applied to rank the GCMs based on the Euclidian distant technique. The results suggest that CanESM2 and CSIRO-MK3.6.0 are the most suitable for predicting extreme precipitation events, and BCC-CSM 1.1, CanESM2, NorESM1-M, and CNRM-CM5 for extreme temperature events in Himalayan river basins. Overall, IPSL-CM5A-MR, CanESM2, CNRM-CM5, BCC-CSM 1.1, NorESM1-M, and CSIRO-Mk3.6.0 are deemed suitable models for predicting precipitation and temperature in the Koshi River Basin, Nepal.

Ranking general circulation models for India using TOPSIS

2014 ◽  
Vol 6 (2) ◽  
pp. 288-299 ◽  
Author(s):  
K. Srinivasa Raju ◽  
D. Nagesh Kumar
Keyword(s):  
General Circulation ◽  
Climate Models ◽  
Performance Indicator ◽  
Global Climate ◽  
Evaluation Criteria ◽  
General Circulation Models ◽  
Skill Score ◽  
Global Climate Models ◽  
Climate Conditions ◽  
Grid Points

Eleven general circulation models/global climate models (GCMs) – BCCR-BCCM2.0, INGV-ECHAM4, GFDL2.0, GFDL2.1, GISS, IPSL-CM4, MIROC3, MRI-CGCM2, NCAR-PCMI, UKMO-HADCM3 and UKMO-HADGEM1 – are evaluated for Indian climate conditions using the performance indicator, skill score (SS). Two climate variables, temperature T (at three levels, i.e. 500, 700, 850 mb) and precipitation rate (Pr) are considered resulting in four SS-based evaluation criteria (T500, T700, T850, Pr). The multicriterion decision-making method, technique for order preference by similarity to an ideal solution, is applied to rank 11 GCMs. Efforts are made to rank GCMs for the Upper Malaprabha catchment and two river basins, namely, Krishna and Mahanadi (covered by 17 and 15 grids of size 2.5° × 2.5°, respectively). Similar efforts are also made for India (covered by 73 grid points of size 2.5° × 2.5°) for which an ensemble of GFDL2.0, INGV-ECHAM4, UKMO-HADCM3, MIROC3, BCCR-BCCM2.0 and GFDL2.1 is found to be suitable. It is concluded that the proposed methodology can be applied to similar situations with ease.

Successive Modulation of ENSO to the Future Greenhouse Warming

2008 ◽  
Vol 21 (1) ◽  
pp. 3-21 ◽  
Author(s):  
Soon-Il An ◽  
Jong-Seong Kug ◽  
Yoo-Geun Ham ◽  
In-Sik Kang
Keyword(s):  
General Circulation ◽  
Southern Oscillation ◽  
General Circulation Models ◽  
Tropical Pacific ◽  
Greenhouse Warming ◽  
Delayed Response ◽  
Subsurface Temperature ◽  
Climate System Model ◽  
The Mean ◽  
The Tropical Pacific

Abstract The multidecadal modulation of the El Niño–Southern Oscillation (ENSO) due to greenhouse warming has been analyzed herein by means of diagnostics of Intergovernmental Panel on Climate Change (IPCC) Fourth Assessment Report (AR4) coupled general circulation models (CGCMs) and the eigenanalysis of a simplified version of an intermediate ENSO model. The response of the global-mean troposphere temperature to increasing greenhouse gases is more likely linear, while the amplitude and period of ENSO fluctuates in a multidecadal time scale. The climate system model outputs suggest that the multidecadal modulation of ENSO is related to the delayed response of the subsurface temperature in the tropical Pacific compared to the response time of the sea surface temperature (SST), which would lead a modulation of the vertical temperature gradient. Furthermore, an eigenanalysis considering only two parameters, the changes in the zonal contrast of the mean background SST and the changes in the vertical contrast between the mean surface and subsurface temperatures in the tropical Pacific, exhibits a good agreement with the CGCM outputs in terms of the multidecadal modulations of the ENSO amplitude and period. In particular, the change in the vertical contrast, that is, change in difference between the subsurface temperature and SST, turns out to be more influential on the ENSO modulation than changes in the mean SST itself.

scholarly journals Contributors to linkage between Arctic warming and East Asian winter climate

2021 ◽  
Author(s):  
Xinping Xu ◽  
Shengping He ◽  
Yongqi Gao ◽  
Botao Zhou ◽  
Huijun Wang
Keyword(s):  
Sea Ice ◽  
General Circulation ◽  
Initial Conditions ◽  
Wave Train ◽  
East Asian ◽  
Surface Air Temperature ◽  
General Circulation Models ◽  
The Arctic ◽  
Winter Climate ◽  
Arctic Warming

AbstractPrevious modelling and observational studies have shown discrepancies in the interannual relationship of winter surface air temperature (SAT) between Arctic and East Asia, stimulating the debate about whether Arctic change can influence midlatitude climate. This study uses two sets of coordinated experiments (EXP1 and EXP2) from six different atmospheric general circulation models. Both EXP1 and EXP2 consist of 130 ensemble members, each of which in EXP1 (EXP2) was forced by the same observed daily varying sea ice and daily varying (daily climatological) sea surface temperature (SST) for 1982–2014 but with different atmospheric initial conditions. Large spread exists among ensemble members in simulating the Arctic–East Asian SAT relationship. Only a fraction of ensemble members can reproduce the observed deep Arctic warming–cold continent pattern which extends from surface to upper troposphere, implying the important role of atmospheric internal variability. The mechanisms of deep Arctic warming and shallow Arctic warming are further distinguished. Arctic warming aloft is caused primarily by poleward moisture transport, which in conjunction with the surface warming coupled with sea ice melting constitutes the surface-amplified deep Arctic warming throughout the troposphere. These processes associated with the deep Arctic warming may be related to the forcing of remote SST when there is favorable atmospheric circulation such as Rossby wave train propagating from the North Atlantic into the Arctic.

scholarly journals Simulation of Extreme Precipitation in Four Climate Regions in China by General Circulation Models (GCMs): Performance and Projections

Water ◽  
2021 ◽  
Vol 13 (11) ◽  
pp. 1509
Author(s):  
Mengru Zhang ◽  
Xiaoli Yang ◽  
Liliang Ren ◽  
Ming Pan ◽  
Shanhu Jiang ◽  
...  
Keyword(s):  
Extreme Precipitation ◽  
General Circulation ◽  
Global Climate ◽  
Summer Precipitation ◽  
General Circulation Models ◽  
Cumulative Distribution ◽  
Extreme Precipitation Events ◽  
Increasing Trend ◽  
The Future ◽  
Semi Arid

In the context of global climate change, it is important to monitor abnormal changes in extreme precipitation events that lead to frequent floods. This research used precipitation indices to describe variations in extreme precipitation and analyzed the characteristics of extreme precipitation in four climatic (arid, semi-arid, semi-humid and humid) regions across China. The equidistant cumulative distribution function (EDCDF) method was used to downscale and bias-correct daily precipitation in eight Coupled Model Intercomparison Project Phase 5 (CMIP5) general circulation models (GCMs). From 1961 to 2005, the humid region had stronger and longer extreme precipitation compared with the other regions. In the future, the projected extreme precipitation is mainly concentrated in summer, and there will be large areas with substantial changes in maximum consecutive 5-day precipitation (Rx5) and precipitation intensity (SDII). The greatest differences between two scenarios (RCP4.5 and RCP8.5) are in semi-arid and semi-humid areas for summer precipitation anomalies. However, the area of the four regions with an increasing trend of extreme precipitation is larger under the RCP8.5 scenario than that under the RCP4.5 scenario. The increasing trend of extreme precipitation in the future is relatively pronounced, especially in humid areas, implying a potential heightened flood risk in these areas.

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