scholarly journals Selection of CMIP6 GCM With Projection of Climate Over The Amu Darya River Basin

2021 ◽  
Author(s):  
Obaidullah Salehie ◽  
Mohammed Magdy Hamed ◽  
Tarmizi Ismail ◽  
Tze Huey Tam ◽  
Shamsuddin Shahid
Keyword(s):  
River Basin ◽  
Climate Models ◽  
Global Climate ◽  
Coupled Model ◽  
Global Climate Models ◽  
Future Climate Change ◽  
Amu Darya ◽  
Intercomparison Project ◽  
Far Future ◽  
Amu Darya River

Abstract Global Climate Models (GCMs) are considered the most feasible tools to estimate future climate change. The objective of this study was to assess the interpretation of 19 GCMs of Coupled Model Intercomparison Project 6 (CMIP6) in replicating the historical precipitation and temperature of climate prediction center data for the Amu Darya river basin (ADRB) and the projection of climate of the basin using the selected GCMs. The Kling Gupta efficiency (KGE) metric was used to assess the effectiveness of GCMs to simulate the annual geographic variability of precipitation, maximum and minimum temperature (Pr, Tmx and Tmn). A multi-criteria decision-making approach (MCDMA) was used to integrate the KGE values to rank GCMs. The results revealed that MPI-ESM1-2-LR, CMCC-ESM2, INM-CM4-8 and AWI-CM-1-1-MR are the best in replicating observed Pr, Tmx and Tmn in ADRB. Projection of climate employing the selected GCMs indicated an increase in precipitation (9.9-12.4%) and temperature (1.3-5.5⁰C) in the basin for all the shared socioeconomic pathways (SSPs), particularly for the far future (2060-2099). A significant variation can be seen in temperature over the different climatic zone. However, the intercomparison of selected GCM projected revealed high uncertainty in the projected climate. The uncertainty is higher in the far future and higher SSPs compared to the near future and lower SSPs.

scholarly journals Projection of Droughts in Amu Darya River Basin for Shared Socioeconomic Pathways

2021 ◽  
Author(s):  
Obaidullah Salehie ◽  
Mohammed Magdy Hamed ◽  
Tarmizi bin Ismail ◽  
Shamsuddin Shahid
Keyword(s):  
River Basin ◽  
Climate Models ◽  
Potential Evapotranspiration ◽  
Global Climate ◽  
Global Climate Models ◽  
Multimodel Ensemble ◽  
Amu Darya ◽  
Near Future ◽  
Far Future ◽  
Amu Darya River

Abstract Droughts significantly affect socioeconomic and the environment primarily by decreasing the water availability of a region. This study aims to assess the changes in drought characteristics in Central Asia's transboundary Amu Darya river basin for four shared socioeconomic pathways (SSP1-2.6, SSP2-4.5, SSP3-7.0, and SSP5-8.5). The precipitation, maximum and minimum temperature (Pr, Tmx and Tmn) simulations of 19 global climate models (GCMs) of the coupled model intercomparison project phase 6 (CMIP6) were used to select the best models to prepare the multimodel ensemble (MME). The standard precipitation evapotranspiration index (SPEI) was used to estimate droughts for multiple timescales from Pr and potential evapotranspiration (PET) derived from Tmx and Tmn. The changes in the frequency and spatial distribution of droughts for different severities and timescales were evaluated for the two future periods, 2020–2059 and 2060-2099, compared to the base period of 1975-2014. The study revealed four GCMs, AWI-CM-1-1-MR, CMCC-ESM2, INM-CM4-8 and MPI-ESM1-2-LR, as most suitable for projections of droughts in the study area. The multimodel ensemble (MME) mean of the selected GCMs showed a decrease in Pr by -3 to 12% in the near future and a change in the range of 3 to -9% in the far future in most parts of the basin for different SSPs. The PET showed almost no change in most parts of the basin in the near future and an increase in the range of 10 to 70% in the far future. The change (%) in projected drought occurrence showed to noticeably decrease in the near future, particularly for moderate droughts by up to ≤-50% for SSP5-8.5 and an increase in the far future by up to ≥30% for SSP3-7.0. The increase in all severities of droughts was projected mostly in the center and northwest of the basin. Overall, the results showed a drought shift from the east to the northwest of the basin in the future.

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.

scholarly journals Hydroclimatic Extremes in the Limpopo River Basin, South Africa, under Changing Climate

Water ◽  
2020 ◽  
Vol 12 (12) ◽  
pp. 3299
Author(s):  
Christina M. Botai ◽  
Joel O. Botai ◽  
Nosipho N. Zwane ◽  
Patrick Hayombe ◽  
Eric K. Wamiti ◽  
...  
Keyword(s):  
South Africa ◽  
River Basin ◽  
Climate Models ◽  
Research Study ◽  
Global Climate ◽  
Regional Climate ◽  
Coupled Model ◽  
Global Climate Models ◽  
Trend Test ◽  
Changing Climate

This research study evaluated the projected future climate and anticipated impacts on water-linked sectors on the transboundary Limpopo River Basin (LRB) with a focus on South Africa. Streamflow was simulated from two CORDEX-Africa regional climate models (RCMs) forced by the 5th phase of the Coupled Model Inter-Comparison Project (CMIP5) Global Climate Models (GCMs), namely, the CanESM2m and IPSL-CM5A-MR climate models. Three climate projection time intervals were considered spanning from 2006 to 2099 and delineated as follows: current climatology (2006–2035), near future (2036–2065) and end of century future projection (2070–2099). Statistical metrics derived from the projected streamflow were used to assess the impacts of the changing climate on water-linked sectors. These metrics included streamflow trends, low and high flow quantile probabilities, the Standardized Streamflow Index (SSI) trends and the proportion (%) of dry and wet years, as well as drought monitoring indicators. Based on the Mann-Kendall (MK) trend test, the LRB is projected to experience reduced streamflow in both the near and the distant future. The basin is projected to experience frequent dry and wet conditions that can translate to drought and flash floods, respectively. In particular, a high proportion of dry and a few incidences of wet years are expected in the basin in the future. In general, the findings of this research study will inform and enhance climate change adaptation and mitigation policy decisions and implementation thereof, to sustain the livelihoods of vulnerable communities.

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.

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