Using a Multiphysics Ensemble for Exploring Diversity in Cloud–Shortwave Feedback in GCMs

2012 ◽  
Vol 25 (15) ◽  
pp. 5416-5431 ◽  
Author(s):  
Masahiro Watanabe ◽  
Hideo Shiogama ◽  
Tokuta Yokohata ◽  
Youichi Kamae ◽  
Masakazu Yoshimori ◽  
...  
Keyword(s):  
Climate Change ◽  
Climate Models ◽  
Global Climate ◽  
Coupled Model ◽  
Cloud Amount ◽  
Global Climate Models ◽  
Intercomparison Project ◽  
The Mean ◽  
Radiative Feedbacks ◽  
The Tropics

Abstract This study proposes a systematic approach to investigate cloud-radiative feedbacks to climate change induced by an increase of CO2 concentrations in global climate models (GCMs). Based on two versions of the Model for Interdisciplinary Research on Climate (MIROC), which have opposite signs for cloud–shortwave feedback (ΔSWcld) and hence different equilibrium climate sensitivities (ECSs), hybrid models are constructed by replacing one or more parameterization schemes for cumulus convection, cloud, and turbulence between them. An ensemble of climate change simulations using a suite of eight models, called a multiphysics ensemble (MPE), is generated. The MPE provides a range of ECS as wide as the Coupled Model Intercomparison Project phase 3 (CMIP3) multimodel ensemble and reveals a different magnitude and sign of ΔSWcld over the tropics, which is crucial for determining ECS. It is found that no single process controls ΔSWcld, but that the coupling of two processes does. Namely, changing the cloud and turbulence schemes greatly alters the mean and the response of low clouds, whereas replacing the convection and cloud schemes affects low and middle clouds over the convective region. For each of the circulation regimes, ΔSWcld and cloud changes in the MPE have a nonlinear, but systematic, relationship with the mean cloud amount, which can be constrained from satellite estimates. The analysis suggests a positive feedback over the subsidence regime and a near-neutral or weak negative ΔSWcld over the convective regime in these model configurations, which, however, may not be carried into other models.

scholarly journals CLIMATE CHANGE AND WATER RESOURCE SUSTAINABILITY INDEX FOR A WATER-STRESSED BASIN IN BRAZIL: THE CASE STUDY OF RIO VERDE GRANDE BASIN

Nativa ◽  
2018 ◽  
Vol 6 (5) ◽  
pp. 480
Author(s):  
Mônica Carvalho de Sá ◽  
Edson De Oliveira Vieira ◽  
Flavia Mazzer Rodrigues ◽  
Lorrana Cavalcanti Albuquerque ◽  
Núbia Ribeiro Caldeira
Keyword(s):  
Climate Change ◽  
Water Resources ◽  
Climate Models ◽  
Global Climate ◽  
Coupled Model ◽  
Minas Gerais ◽  
Global Climate Models ◽  
Climate Projections ◽  
Model Intercomparison ◽  
Intercomparison Project

MUDANÇAS CLIMÁTICAS E A SUSTENTABILIDADES DOS RECURSOS HÍDRICOS EM BACIA HIDROGRÁFICA COM ESCASSEZ HÍDRICA NO BRASIL: O CASO DA BACIA DE RIO VERDE GRANDE A bacia de Rio Verde Grande está localizada 87% na parte norte do estado de Minas Gerais e 13% no estado da Bahia, em uma região com clima semiárido, apresentando longos e intensos períodos de seca. Esta característica climática afeta diretamente a disponibilidade de recursos hídricos e, conseqüentemente, o desenvolvimento das principais atividades da região que são pecuária e agricultura irrigada. Não há estudos que avaliem o efeito das mudanças climáticas na disponibilidade de água e na sustentabilidade de atividades com alta demanda de água na bacia de Rio Verde Grande. O objetivo deste estudo foi analisar as mudanças prováveis na disponibilidade de água na bacia de Rio Verde Grande e a sustentabilidade dos recursos hídricos para as atividades usuárias de água, utilizando séries sintéticas geradas através de programas de modelagem climática e hidrológica. Este estudo realizou as projeções climáticas utilizando os Global Climate Models do Coupled Model Intercomparison Project Phase 5. Com base nos cálculos dos índices de sustentabilidade e na comparação dos cenários atuais e futuros, observou-se que, mesmo com todas as intervenções propostas pelo Plano de Recursos Hídricos da Bacia Rio Verde Grande implementadas, houve uma redução na sustentabilidade da água Recursos em algumas sub-bacias devido à mudança climática.Palavras-chave: CMIP5, modelo WEAP, vulnerabilidade ABSTRACT: The Rio Verde Grande basin is a water-stressed basin, which is 87% in the northern part of Minas Gerais and 13% in Bahia, Brazil. It has a semi-arid climate with long and intense periods of drought. This climatic directly affects the availability of water resources and the development of the main activities in the region. There are presently no studies that evaluate the effect of climate change on the availability of water in the Rio Verde Grande basin and the sustainability of high water demand activities. The objective of this study was to analyze future changes in the availability of water in the Rio Verde Grande basin, and the sustainability of water for the major water users. This was done using a synthetic series generated through climatic and hydrological modeling programs. This study performed climate projections using the Global Climate Models of the Coupled Model Intercomparison Project Phase 5. The calculation of sustainability indexes and a comparison between current and future scenarios, it was observed that even if all the interventions proposed by the Water Resources Plan of the Rio Verde Grande basin are implemented, there will still be a reduction in the sustainability of water resources in some sub-basins, due to climate change.Keywords: CMIP5, WEAP model, vulnerability.

scholarly journals Robust increase of Indian monsoon rainfall and its variability under future warming in CMIP-6 models

2020 ◽  
Author(s):  
Anja Katzenberger ◽  
Jacob Schewe ◽  
Julia Pongratz ◽  
Anders Levermann
Keyword(s):  
Climate Change ◽  
Global Warming ◽  
Climate Models ◽  
Monsoon Rainfall ◽  
Global Climate ◽  
Coupled Model ◽  
Global Climate Models ◽  
Future Climate Change ◽  
Global Mean Temperature ◽  
Almost All

Abstract. The Indian summer monsoon is an integral part of the global climate system. As its seasonal rainfall plays a crucial role in India's agriculture and shapes many other aspects of life, it affects the livelihood of a fifth of the world's population. It is therefore highly relevant to assess its change under potential future climate change. Global climate models within the Coupled Model Intercomparison Project Phase 5 (CMIP-5) indicated a consistent increase in monsoon rainfall and its variability under global warming. Since the range of the results of CMIP-5 was still large and the confidence in the models was limited due to partly poor representation of observed rainfall, the updates within the latest generation of climate models in CMIP-6 are of interest. Here, we analyse 32 models of the latest CMIP-6 exercise with regard to their annual mean monsoon rainfall and its variability. All of these models show a substantial increase in June-to-September (JJAS) mean rainfall under unabated climate change (SSP5-8.5) and most do also for the other three Shared Socioeconomic Pathways analyzed (SSP1-2.6, SSP2-4.5, SSP3-7.0). Moreover, the simulation ensemble indicates a linear dependence of rainfall on global mean temperature with high agreement between the models and independent of the SSP; the multi-model mean for JJAS projects an increase of 0.33 mm/day and 5.3 % per degree of global warming. This is significantly higher than in the CMIP-5 projections. Most models project that the increase will contribute to the precipitation especially in the Himalaya region and to the northeast of the Bay of Bengal, as well as the west coast of India. Interannual variability is found to be increasing in the higher-warming scenarios by almost all models. The CMIP-6 simulations largely confirm the findings from CMIP-5 models, but show an increased robustness across models with reduced uncertainties and updated magnitudes towards a stronger increase in monsoon rainfall.

scholarly journals Evaluation of CMIP5 Global Climate Models for Simulating Climatological Temperature and Precipitation for Southeast Asia

2019 ◽  
Vol 2019 ◽  
pp. 1-18 ◽  
Author(s):  
Suchada Kamworapan ◽  
Chinnawat Surussavadee
Keyword(s):  
Southeast Asia ◽  
Climate Models ◽  
Performance Metrics ◽  
Global Climate ◽  
Total Error ◽  
Coupled Model ◽  
Global Climate Models ◽  
Ensemble Average ◽  
Temperature And Precipitation ◽  
Intercomparison Project

This study evaluates the performances of all forty different global climate models (GCMs) that participate in the Coupled Model Intercomparison Project Phase 5 (CMIP5) for simulating climatological temperature and precipitation for Southeast Asia. Historical simulations of climatological temperature and precipitation of the 40 GCMs for the 40-year period of 1960–1999 for both land and sea and those for the century of 1901–1999 for land are evaluated using observation and reanalysis datasets. Nineteen different performance metrics are employed. The results show that the performances of different GCMs vary greatly. CNRM-CM5-2 performs best among the 40 GCMs, where its total error is 3.25 times less than that of GCM performing worst. The performance of CNRM-CM5-2 is compared with those of the ensemble average of all 40 GCMs (40-GCM-Ensemble) and the ensemble average of the 6 best GCMs (6-GCM-Ensemble) for four categories, i.e., temperature only, precipitation only, land only, and sea only. While 40-GCM-Ensemble performs best for temperature, 6-GCM-Ensemble performs best for precipitation. 6-GCM-Ensemble performs best for temperature and precipitation simulations over sea, whereas CNRM-CM5-2 performs best over land. Overall results show that 6-GCM-Ensemble performs best and is followed by CNRM-CM5-2 and 40-GCM-Ensemble, respectively. The total errors of 6-GCM-Ensemble, CNRM-CM5-2, and 40-GCM-Ensemble are 11.84, 13.69, and 14.09, respectively. 6-GCM-Ensemble and CNRM-CM5-2 agree well with observations and can provide useful climate simulations for Southeast Asia. This suggests the use of 6-GCM-Ensemble and CNRM-CM5-2 for climate studies and projections for Southeast Asia.

The Double-ITCZ Bias in CMIP6 Models

2020 ◽  
Author(s):  
Baijun Tian
Keyword(s):  
Climate Models ◽  
Global Climate ◽  
Coupled Model ◽  
Global Climate Models ◽  
Cmip5 Models ◽  
Tropical Precipitation ◽  
Double Itcz ◽  
Intercomparison Project ◽  
Fully Coupled

<p>The double-Intertropical Convergence Zone (ITCZ) bias is one of the most outstanding problems in climate models. This study seeks to examine the double-ITCZ bias in the latest state-of-the-art fully coupled global climate models that participated in Coupled Model Intercomparison Project (CMIP) Phase 6 (CMIP6) in comparison to their previous generations (CMIP3 and CMIP5 models). To that end, we have analyzed the long-term annual mean tropical precipitation distributions and several precipitation bias indices that quantify the double-ITCZ biases in 75 climate models including 24 CMIP3 models, 25 CMIP3 models, and 26 CMIP6 models. We find that the double-ITCZ bias and its big inter-model spread persist in CMIP6 models but the double-ITCZ bias is slightly reduced from CMIP3 or CMIP5 models to CMIP6 models.</p>

scholarly journals Climate Projections Over Different Climatic Regions of Afghanistan for Shared Socioeconomic Scenarios

2022 ◽  
Author(s):  
Mohammad Naser Sediqi ◽  
Vempi Satriya Adi Hendrawan ◽  
Daisuke Komori
Keyword(s):  
Climate Models ◽  
Global Climate ◽  
Coupled Model ◽  
Global Climate Models ◽  
Maximum Temperature ◽  
Climate Projections ◽  
Climatic Regions ◽  
Temperature And Precipitation ◽  
Intercomparison Project ◽  
Precipitation And Temperature

Abstract The global climate models (GCMs) of Coupled Model Intercomparison Project phase 6 (CMIP6) were used spatiotemporal projections of precipitation and temperature over Afghanistan for three shared socioeconomic pathways (SSP1-2.6, 2-4.5 and 5-8.5) and two future time horizons, early (2020-2059) and late (2060-2099). The Compromise Programming (CP) approach was employed to order the GCMs based on their skill to replicate precipitation and temperature climatology for the reference period (1975-2014). Three models, namely ACCESS-CM2, MPI-ESM1-2-LR, and FIO-ESM-2-0, showed the highest skill in simulating all three variables, and therefore, were chosen for the future projections. The ensemble mean of the GCMs showed an increase in maximum temperature by 1.5-2.5oC, 2.7-4.3 oC, and 4.5-5.3 oC and minimum temperature by 1.3-1.8 oC, 2.2-3.5 oC, and 4.6-5.2 oC for SSP1-2.6, SSP2-4.5, and SSP5-8.5, respectively in the later period. Meanwhile, the changes in precipitation in the range of -15-18%, -36-47% and -40-68% for SSP1-2.6, SSP2-4.5, and SSP5-8.5, respectively. The temperature and precipitation were projected to increase in the highlands and decrease over the deserts, indicating dry regions would be drier and wet regions wetter.

scholarly journals Statistically Downscaled CMIP6 Projections Show Stronger Warming for Germany

Atmosphere ◽  
2020 ◽  
Vol 11 (11) ◽  
pp. 1245
Author(s):  
Frank Kreienkamp ◽  
Philip Lorenz ◽  
Tobias Geiger
Keyword(s):  
Climate Change ◽  
Climate Models ◽  
Global Climate ◽  
Regional Scale ◽  
Coupled Model ◽  
Global Climate Models ◽  
Climate Projections ◽  
Climate Modelling ◽  
Climate Signal ◽  
Temperature Signal

Climate modelling output that was provided under the latest Coupled Model Intercomparison Project (CMIP6) shows significant changes in model-specific Equilibrium Climate Sensitivity (ECS) as compared to CMIP5. The newer versions of many Global Climate Models (GCMs) report higher ECS values that result in stronger global warming than previously estimated. At the same time, the multi-GCM spread of ECS is significantly larger than under CMIP5. Here, we analyse how the differences between CMIP5 and CMIP6 affect climate projections for Germany. We use the statistical-empirical downscaling method EPISODES in order to downscale GCM data for the scenario pairs RCP4.5/SSP2-4.5 and RCP8.5/SSP5-8.5. We use data sets of the GCMs CanESM, EC-Earth, MPI-ESM, and NorESM. The results show that the GCM-specific changes in the ECS also have an impact at the regional scale. While the temperature signal under regional climate change remains comparable for both CMIP generations in the MPI-ESM chain, the temperature signal increases by up to 3 °C for the RCP8.5/SSP5-8.5 scenario pair in the EC-Earth chain. Changes in precipitation are less pronounced and they only show notable differences at the seasonal scale. The reported changes in the climate signal will have direct consequences for society. Climate change impacts previously projected for the high-emission RCP8.5 scenario might occur equally under the new SSP2-4.5 scenario.

scholarly journals Characterizing and Understanding Cloud Ice and Radiation Budget Biases in Global Climate Models and Reanalysis

2016 ◽  
Vol 56 ◽  
pp. 13.1-13.20 ◽  
Author(s):  
J.-L. F. Li ◽  
D. E. Waliser ◽  
G. Stephens ◽  
Seungwon Lee
Keyword(s):  
Climate Models ◽  
Global Climate ◽  
Coupled Model ◽  
Global Climate Models ◽  
Model Intercomparison ◽  
Convective Core ◽  
Intercomparison Project ◽  
Annual Means ◽  
Cloud Ice ◽  
Ice Water

Abstract The authors present an observationally based evaluation of the vertically resolved cloud ice water content (CIWC) and vertically integrated cloud ice water path (CIWP) as well as radiative shortwave flux downward at the surface (RSDS), reflected shortwave (RSUT), and radiative longwave flux upward at top of atmosphere (RLUT) of present-day global climate models (GCMs), notably twentieth-century simulations from the fifth phase of the Coupled Model Intercomparison Project (CMIP5), and compare these results to those of the third phase of the Coupled Model Intercomparison Project (CMIP3) and two recent reanalyses. Three different CloudSat and/or Cloud–Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) combined ice water products and two methods are used to remove the contribution from the convective core ice mass and/or precipitating cloud hydrometeors with variable sizes and falling speeds so that a robust observational estimate can be obtained for model evaluations. The results show that, for annual mean CIWC and CIWP, there are factors of 2–10 (either over- or underestimate) in the differences between observations and models for a majority of the GCMs and for a number of regions. Most of the GCMs in CMIP3 and CMIP5 significantly underestimate the total ice water mass because models only consider suspended cloud mass, ignoring falling and convective core cloud mass. For the annual means of RSDS, RLUT, and RSUT, a majority of the models have significant regional biases ranging from −30 to 30 W m−2. Based on these biases in the annual means, there is virtually no progress in the simulation fidelity of RSDS, RLUT, and RSUT fluxes from CMIP3 to CMIP5, even though there is about a 50% bias reduction improvement of global annual mean CIWP from CMIP3 to CMIP5. It is concluded that at least a part of these persistent biases stem from the common GCM practice of ignoring the effects of precipitating and/or convective core ice and liquid in their radiation calculations.

scholarly journals Historical and future trends in wetting and drying in 291 catchments across China

2017 ◽  
Vol 21 (4) ◽  
pp. 2233-2248 ◽  
Author(s):  
Zhongwang Chen ◽  
Huimin Lei ◽  
Hanbo Yang ◽  
Dawen Yang ◽  
Yongqiang Cao
Keyword(s):  
Climate Changes ◽  
Climate Models ◽  
Potential Evapotranspiration ◽  
Global Climate ◽  
Coupled Model ◽  
Global Climate Models ◽  
Future Trends ◽  
Wetting And Drying ◽  
Intercomparison Project ◽  
Streamflow Data

Abstract. An increasingly uneven distribution of hydrometeorological factors related to climate change has been detected by global climate models (GCMs) in which the pattern of changes in water availability is commonly described by the phrase dry gets drier, wet gets wetter (DDWW). However, the DDWW pattern is dominated by oceanic areas; recent studies based on both observed and modelled data have failed to verify the DDWW pattern on land. This study confirms the existence of a new DDWW pattern in China after analysing the observed streamflow data from 291 Chinese catchments from 1956 to 2000, which reveal that the distribution of water resources has become increasingly uneven since the 1950s. This pattern can be more accurately described as drier regions are more likely to become drier, whereas wetter regions are more likely to become wetter. Based on a framework derived from the Budyko hypothesis, this study estimates runoff trends via observations of precipitation (P) and potential evapotranspiration (Ep) and predicts the future trends from 2001 to 2050 according to the projections of five GCMs from the Coupled Model Intercomparison Project Phase 5 (CMIP5) under three scenarios: RCP2.6, RCP4.5, and RCP8.5. The results show that this framework has a good performance for estimating runoff trends; such changes in P play the most significant role. Most areas of China, including more than 60 % of catchments, will experience water resource shortages under the projected climate changes. Despite the differences among the predicted results of the different models, the DDWW pattern does not hold in the projections regardless of the model used. Nevertheless, this conclusion remains tentative owing to the large uncertainties in the GCM outputs.

scholarly journals Large-scale features and evaluation of the PMIP4-CMIP6 <i>midHolocene</i> simulations

2020 ◽  
Vol 16 (5) ◽  
pp. 1847-1872 ◽  
Author(s):  
Chris M. Brierley ◽  
Anni Zhao ◽  
Sandy P. Harrison ◽  
Pascale Braconnot ◽  
Charles J. R. Williams ◽  
...  
Keyword(s):  
Large Scale ◽  
Climate Models ◽  
Hydrological Cycle ◽  
Global Climate ◽  
Coupled Model ◽  
Global Climate Models ◽  
Current Phase ◽  
Model Intercomparison ◽  
Global Mean Temperature ◽  
Intercomparison Project

Abstract. The mid-Holocene (6000 years ago) is a standard time period for the evaluation of the simulated response of global climate models using palaeoclimate reconstructions. The latest mid-Holocene simulations are a palaeoclimate entry card for the Palaeoclimate Model Intercomparison Project (PMIP4) component of the current phase of the Coupled Model Intercomparison Project (CMIP6) – hereafter referred to as PMIP4-CMIP6. Here we provide an initial analysis and evaluation of the results of the experiment for the mid-Holocene. We show that state-of-the-art models produce climate changes that are broadly consistent with theory and observations, including increased summer warming of the Northern Hemisphere and associated shifts in tropical rainfall. Many features of the PMIP4-CMIP6 simulations were present in the previous generation (PMIP3-CMIP5) of simulations. The PMIP4-CMIP6 ensemble for the mid-Holocene has a global mean temperature change of −0.3 K, which is −0.2 K cooler than the PMIP3-CMIP5 simulations predominantly as a result of the prescription of realistic greenhouse gas concentrations in PMIP4-CMIP6. Biases in the magnitude and the sign of regional responses identified in PMIP3-CMIP5, such as the amplification of the northern African monsoon, precipitation changes over Europe, and simulated aridity in mid-Eurasia, are still present in the PMIP4-CMIP6 simulations. Despite these issues, PMIP4-CMIP6 and the mid-Holocene provide an opportunity both for quantitative evaluation and derivation of emergent constraints on the hydrological cycle, feedback strength, and potentially climate sensitivity.

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