scholarly journals Comparison of Precipitation Projections of CMIP5 and CMIP6 Global Climate Models over Yulin, China

2021 ◽  
Author(s):  
Mohammed Sanusi Shiru ◽  
Eun-Sung Chung ◽  
Shamsuddin Shahid ◽  
Xiao-Jun Wang
Keyword(s):  
Climate Models ◽  
Global Climate ◽  
Coupled Model ◽  
Global Climate Models ◽  
Precipitation Climatology ◽  
Global Precipitation Climatology Centre ◽  
Intercomparison Project ◽  
Yulin City ◽  
Global Precipitation ◽  
Precipitation Projections

Abstract This study compared precipitation projections of Coupled Model Intercomparison Project 5 (CMIP5) and 6 (CMIP6) GCMs over Yulin City, China. The performance of CMIP5 and CMIP6 GCMs in replicating Global Precipitation Climatology Centre (GPCC) precipitation climatology of the city was evaluated using different statistical metrics. The best performing GCMs common to both CMIP5 and CMIP6 were selected and subsequently downscaled to GPCC resolution using linear scaling method to spatiotemporal changes in precipitation. The study revealed BCC.CSM1.1(m), IPSL.CM5A.LR, MRI.CGCM3 and MIROC5 of CMIP5 and their equivalents BCC-CSM2-MR, IPSL-CM6A-LR, MRI.ESM2.0 and MIRCO6 of CMIP6 as the most suitable GCMs for the projection of rainfall in Yulin. Changes in precipitation were in the range of -14.0 − 0.0% and − 22.0 − 0.2% during 2021−2060 for RCP4.5 and SSP2-4.5 respectively. The highest decrease of -29.7 ̶ -22.0% was projected by MRI-ESM-2-0 for SSP2-4.5, while − 28.0 − -20.0% by MIROC5 for RCP4.5. For RCP8.5 and SSP5-8.5, precipitation was projected to decrease in the range of -17.0 ̶ -2.0% and − 32.0 ̶ 0.0%, respectively during 2021 ̶ 2060 by most of the GCMs. An increase in precipitation up to 12.3% was projected only by IPSL-CM5A-LR for RCP8.5 for this period. The highest decrease was projected by MIROC5 (-40.2 − -29.0%) for RCP8.5 and IPSL-CM6A-LR (-40.2 − -26.0%) for SSP5-8.5. Overall, the results revealed a higher decrease in precipitation in Yulin city by CMIP6 GCMs compared to those projected by their corresponding GCMs of CMIP5 for both scenarios.

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 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.

scholarly journals A Regime-Oriented Approach to Observationally Constraining Extratropical Shortwave Cloud Feedbacks

2020 ◽  
Vol 33 (23) ◽  
pp. 9967-9983
Author(s):  
Daniel T. McCoy ◽  
Paul Field ◽  
Alejandro Bodas-Salcedo ◽  
Gregory S. Elsaesser ◽  
Mark D. Zelinka
Keyword(s):  
Climate Models ◽  
Global Climate ◽  
Coupled Model ◽  
Moisture Flux ◽  
Global Climate Models ◽  
Sea Surface ◽  
Liquid Water Path ◽  
Cloud Feedbacks ◽  
Intercomparison Project ◽  
Cloud Liquid Water Path

AbstractThe extratropical shortwave (SW) cloud feedback is primarily due to increases in extratropical liquid cloud extent and optical depth. Here, we examine the response of extratropical (35°–75°) marine cloud liquid water path (LWP) to a uniform 4-K increase in sea surface temperature (SST) in global climate models (GCMs) from phase 5 of the Coupled Model Intercomparison Project (CMIP5) and variants of the HadGEM3-GC3.1 GCM. Compositing is used to partition data into periods inside and out of cyclones. The response of extratropical LWP to a uniform SST increase and associated atmospheric response varies substantially among GCMs, but the sensitivity of LWP to cloud controlling factors (CCFs) is qualitatively similar. When all other predictors are held constant, increasing moisture flux drives an increase in LWP. Increasing SST, holding all other predictors fixed, leads to a decrease in LWP. The combinations of these changes lead to LWP, and by extension reflected SW, increasing with warming in both hemispheres. Observations predict an increase in reflected SW over oceans of 0.8–1.6 W m−2 per kelvin SST increase (35°–75°N) and 1.2–1.9 W m−2 per kelvin SST increase (35°–75°S). This increase in reflected SW is mainly due to increased moisture convergence into cyclones because of increasing available moisture. The efficiency at which converging moisture is converted into precipitation determines the amount of liquid cloud. Thus, cyclone precipitation processes are critical to constraining extratropical cloud feedbacks.

scholarly journals Cambios proyectados de los recursos hídricos bajo escenarios de emisiones RCP4.5 y 8.5 de modelos climáticos globales del CMIP5 en el Altiplano Peruano

2016 ◽  
Vol 18 (2) ◽  
Author(s):  
Efrain Lujano-Laura ◽  
Liz S. Hidalgo-Sanchez ◽  
Bernardino Tapia-Aguilar ◽  
Apolinario Lujano-Laura
Keyword(s):  
Water Resources ◽  
Climate Models ◽  
Global Climate ◽  
Coupled Model ◽  
Global Climate Models ◽  
Annual Rainfall ◽  
Palabras Clave ◽  
Australian Community ◽  
Intercomparison Project ◽  
Spatio Temporal

<p>La investigación, se realizó en el ámbito del altiplano Peruano, con el objetivo de evaluar los cambios en la disponibilidad del recurso hídrico bajo escenarios de emisiones de Modelos Climáticos Globales (MCG) del Proyecto de Intercomparación de Modelos Acoplados Fase 5 (CMIP5). La distribución espacio-temporal de la precipitación, se tomó como referencia la climatología 1971 – 2000 y sus proyecciones para el horizonte 2071 – 2100, así mismo para la simulación de caudales se utilizó el modelo hidrológico conceptual de Ingeniería Rural de 2 parámetros, cuyas evaluaciones estadísticas se midieron a través de la eficiencia de Nash y Sutcliffe. El Simulador del Sistema Terrestre y el Clima de la Comunidad Australiana versiones 1.0 y 1.3 (ACCESS1.0 y 1.3) y el Modelo para la Investigación Interdisciplinaria sobre el Clima versión 5 (MIROC5), simularon adecuadamente el ciclo estacional de la precipitación y en base a los resultados, los cambios de precipitaciones para los caminos de concentración representativas (RCP4.5 y 8.5) a finales del siglo XXI, indican un ligero incremento de la precipitación anual en la cuenca Ramis y una disminución para la cuenca Ilave. Es así que las variaciones de las precipitaciones son también reflejadas en los caudales, concluyéndose que las mayores disminuciones del recurso hídrico se darían para la cuenca Ilave, con incrementos ligeros en promedio anual para la cuenca Ramis.</p><p><strong>Palabras clave:</strong> Altiplano Peruano, cambio climático, escenarios climáticos, disponibilidad hídrica.</p><p align="center"><strong>ABSTRACT</strong></p><p>The research was conducted in the area of the Peruvian altiplano with the aim to assess changes in the availability of water resources under emission scenarios Global Climate Models (GCMs) of the Coupled Model Intercomparison Project phase 5 (CMIP5). The spatio-temporal precipitation distribution was taken as reference climatology 1971 - 2000 and its projections for the horizon 2071 - 2100, also for simulating flows conceptual hydrological model of Rural Engineering 2 parameters are used, whose evaluations statistics were measured through efficiency Nash and Sutcliffe. The Australian Community Climate and Earth System Simulator versions 1.0 and 1.3 (ACCESS1.0 and 1.3) and Model for Interdisciplinary Research on Climate version 5 (MIROC5), adequately simulated the seasonal cycle of precipitation and based results, changes in rainfall for Representative Concentration Pathways (RCP4.5 and 8.5) at the end of the XXI century, indicate a slight increase of annual rainfall of the basin Ramis and a decrease for the Ilave basin. Is thus that variations in rainfall are also reflected in the flows, concluding that the largest decreases of water resources would be given for the Ilave basin, with slight increases in annual average for the basin Ramis.</p><p><strong>Keywords: </strong>Peruvian altiplano,<strong> </strong>climate change, climate scenarios, water availability.</p>

scholarly journals Combining Emergent Constraints for Climate Sensitivity

2020 ◽  
Vol 33 (17) ◽  
pp. 7413-7430 ◽  
Author(s):  
Christopher S. Bretherton ◽  
Peter M. Caldwell
Keyword(s):  
Climate Sensitivity ◽  
Climate Models ◽  
Global Climate ◽  
Coupled Model ◽  
Global Climate Models ◽  
Climate Feedback ◽  
Feedback Parameter ◽  
Emergent Constraints ◽  
Intercomparison Project ◽  
Special Case

AbstractA method is proposed for combining information from several emergent constraints into a probabilistic estimate for a climate sensitivity proxy Y such as equilibrium climate sensitivity (ECS). The method is based on fitting a multivariate Gaussian PDF for Y and the emergent constraints using an ensemble of global climate models (GCMs); it can be viewed as a form of multiple linear regression of Y on the constraints. The method accounts for uncertainties in sampling this multidimensional PDF with a small number of models, for observational uncertainties in the constraints, and for overconfidence about the correlation of the constraints with the climate sensitivity. Its general form (Method C) accounts for correlations between the constraints. Method C becomes less robust when some constraints are too strongly related to each other; this can be mitigated using regularization approaches such as ridge regression. An illuminating special case, Method U, neglects any correlations between constraints except through their mutual relationship to the climate proxy; it is more robust to small GCM sample size and is appealingly interpretable. These methods are applied to ECS and the climate feedback parameter using a previously published set of 11 possible emergent constraints derived from climate models in the Coupled Model Intercomparison Project (CMIP). The ±2σ posterior range of ECS for Method C with no overconfidence adjustment is 4.3 ± 0.7 K. For Method U with a large overconfidence adjustment, it is 4.0 ± 1.3 K. This study adds confidence to past findings that most constraints predict higher climate sensitivity than the CMIP mean.

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