scholarly journals Evaluation of Climate in CMIP6 Models over Two Third Pole Subregions with Contrasting Circulation Systems

2021 ◽  
pp. 1-64
Author(s):  
Ying Li ◽  
Chenghao Wang ◽  
Fengge Su
Keyword(s):  
Coupled Model ◽  
Warming Trend ◽  
Climate Projections ◽  
Future Period ◽  
Temperature And Precipitation ◽  
Model Average ◽  
Global Trend ◽  
Monsoon System ◽  
Drying Trend ◽  
Intercomparison Project

AbstractReliable simulations of historical and future climate are critical to assessing ecological and hydrological responses over the Third Pole (TP). In this study, we evaluate the historical and future temperature and precipitation simulations of 18 models from the Coupled Model Intercomparison Project Phase 6 (CMIP6) in southeastern TP (SETP) and the upstream of the Amu Darya and Syr Darya (UAS) regions, two typical TP subregions dominated by the Indian summer monsoon system and westerlies, respectively. Comparison against station observations suggests that CMIP6 models generally capture the intra-annual variability and spatial pattern of historical climate over both subregions. However, the wetting and cold biases observed in CMIP5 still persist in CMIP6; annual temperature is underestimated by most models and annual precipitation is overestimated by all models. Multi-model average cold biases in SETP and UAS are 1.18°C and 0.32°C, respectively, and wet biases in SETP and UAS are 119% and 46%, respectively. We further analyze climate projections under SSP1-2.6, SSP2-4.5, and SSP5-8.5 scenarios. Both SETP and UAS subregions are projected to experience significant warming in 2015–2100, with warming trends 34%–42% and 40%–50% higher than the global trend, respectively. Model projections suggest that the warming trend will slow down under SSP1-2.6 and SSP2-4.5 but further intensify under SSP5-8.5 in 2050–2100. Monsoon-dominated SETP is projected to experience a significant wetting trend stronger than UAS over the entire future period, especially in summer (cf. winter in westerlies-dominated UAS). Concurrently, a significant drying trend in summer is found in UAS during 2050–2100 under SSP5-8.5, suggesting the intensified uneven distributions of seasonal precipitation based on projections.

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 Diagnosis of Multiyear Predictability on Continental Scales

2011 ◽  
Vol 24 (19) ◽  
pp. 5108-5124 ◽  
Author(s):  
Liwei Jia ◽  
Timothy DelSole
Keyword(s):  
Time Scales ◽  
Air Temperature ◽  
Climate Models ◽  
Coupled Model ◽  
Surface Air Temperature ◽  
Optimization Method ◽  
First Year ◽  
Temperature And Precipitation ◽  
Regional Prediction ◽  
Intercomparison Project

A new statistical optimization method is used to identify components of surface air temperature and precipitation on six continents that are predictable in multiple climate models on multiyear time scales. The components are identified from unforced “control runs” of the Coupled Model Intercomparison Project phase 3 dataset. The leading predictable components can be calculated in independent control runs with statistically significant skill for 3–6 yr for surface air temperature and 1–3 yr for precipitation, depending on the continent, using a linear regression model with global sea surface temperature (SST) as a predictor. Typically, lag-correlation maps reveal that the leading predictable components of surface air temperature are related to two types of SST patterns: persistent patterns near the continent itself and an oscillatory ENSO-like pattern. The only exception is Europe, which has no significant ENSO relation. The leading predictable components of precipitation are significantly correlated with an ENSO-like SST pattern. No multiyear predictability of land precipitation could be verified in Europe. The squared multiple correlations of surface air temperature and precipitation for nonzero lags on each continent are less than 0.4 in the first year, implying that less than 40% of variations of the leading predictable component can be predicted from global SST. The predictable components describe the spatial structures that can be predicted on multiyear time scales in the absence of anthropogenic and natural forcing, and thus provide a scientific rationale for regional prediction on multiyear time scales.

scholarly journals Simulations of changes to Glaciar Zongo, Bolivia (16° S), over the 21st century using a 3-D full-Stokes model and CMIP5 climate projections

2015 ◽  
Vol 56 (70) ◽  
pp. 89-97 ◽  
Author(s):  
Marion Réveillet ◽  
Antoine Rabatel ◽  
Fabien Gillet-Chaulet ◽  
Alvaro Soruco
Keyword(s):  
Mass Balance ◽  
21St Century ◽  
Coupled Model ◽  
Cmip5 Models ◽  
Climate Projections ◽  
Surface Mass Balance ◽  
Equilibrium Line Altitude ◽  
Surface Mass ◽  
Temperature Changes ◽  
Intercomparison Project

AbstractBolivian glaciers are an essential source of fresh water for the Altiplano, and any changes they may undergo in the near future due to ongoing climate change are of particular concern. Glaciar Zongo, Bolivia, located near the administrative capital La Paz, has been extensively monitored by the GLACIOCLIM observatory in the last two decades. Here we model the glacier dynamics using the 3-D full-Stokes model Elmer/Ice. The model was calibrated and validated over a recent period (1997–2010) using four independent datasets: available observations of surface velocities and surface mass balance were used for calibration, and changes in surface elevation and retreat of the glacier front were used for validation. Over the validation period, model outputs are in good agreement with observations (differences less than a small percentage). The future surface mass balance is assumed to depend on the equilibrium-line altitude (ELA) and temperature changes through the sensitivity of ELA to temperature. The model was then forced for the 21st century using temperature changes projected by nine Coupled Model Intercomparison Project phase 5 (CMIP5) models. Here we give results for three different representative concentration pathways (RCPs). The intermediate scenario RCP6.0 led to 69 ± 7% volume loss by 2100, while the two extreme scenarios, RCP2.6 and RCP8.5, led to 40 ± 7% and 89 ± 4% loss of volume, respectively.

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 Prediction of Droughts in the Mongolian Plateau Based on the CMIP5 Model

Water ◽  
2020 ◽  
Vol 12 (10) ◽  
pp. 2774
Author(s):  
Yongzhen Li ◽  
Siqin Tong ◽  
Yongbin Bao ◽  
Enliang Guo ◽  
Yuhai Bao
Keyword(s):  
21St Century ◽  
Function Analysis ◽  
Coupled Model ◽  
Mongolian Plateau ◽  
Early 21St Century ◽  
Temperature And Precipitation ◽  
Mode Decomposition ◽  
Drought Pattern ◽  
Intercomparison Project ◽  
Simulated Drought

Understanding the variations of future drought under climate warming can provide the basis for mitigation efforts. This study utilized the standardized precipitation evapotranspiration index (SPEI), empirical mode decomposition (EMD) and empirical orthogonal function analysis (EOF) to predict the spatiotemporal variation of future drought under the representative concentration pathway RCP4.5 and RCP8.5 scenarios within the Mongolian Plateau over the period 2020–2100. The SPEI was computed using temperature and precipitation data generated by the fifth stage of the Coupled Model Intercomparison Project (CMIP5). The results under both the RCP4.5 and RCP8.5 scenarios showed increasing changes in temperature and precipitation. Both scenarios indicated increases in drought, with those under RCP8.5 much more extreme than that under RCP4.5. Under both scenarios, the climate showed an abrupt change to become drier, with the change occurring in 2041 and 2054 for the RCP4.5 and RCP8.5 scenarios, respectively. The results also indicated future drought to be more extreme in Mongolia than in Inner Mongolia. The simulated drought pattern showed an east–west antiphase and a north–south antiphase distribution based on EOF. The frequency of drought was higher under RCP8.5 compared to that under RCP4.5, with the highest frequencies under both scenarios occurring by the end of the 21st century, followed by the mid-21st century and early 21st century. The findings of this research can provide a solid foundation for the prevention, early warning and mitigation of drought disasters within the context of climate change in the Mongolian Plateau.

scholarly journals Bias-corrected climate projections for South Asia from Coupled Model Intercomparison Project-6

2020 ◽  
Vol 7 (1) ◽  
Author(s):  
Vimal Mishra ◽  
Udit Bhatia ◽  
Amar Deep Tiwari
Keyword(s):  
Climate Change ◽  
Impact Assessment ◽  
South Asia ◽  
General Circulation ◽  
Coupled Model ◽  
General Circulation Models ◽  
River Basins ◽  
Climate Projections ◽  
Model Intercomparison ◽  
Intercomparison Project

Abstract Climate change is likely to pose enormous challenges for agriculture, water resources, infrastructure, and livelihood of millions of people living in South Asia. Here, we develop daily bias-corrected data of precipitation, maximum and minimum temperatures at 0.25° spatial resolution for South Asia (India, Pakistan, Bangladesh, Nepal, Bhutan, and Sri Lanka) and 18 river basins located in the Indian sub-continent. The bias-corrected dataset is developed using Empirical Quantile Mapping (EQM) for the historic (1951–2014) and projected (2015–2100) climate for the four scenarios (SSP126, SSP245, SSP370, SSP585) using output from 13 General Circulation Models (GCMs) from Coupled Model Intercomparison Project-6 (CMIP6). The bias-corrected dataset was evaluated against the observations for both mean and extremes of precipitation, maximum and minimum temperatures. Bias corrected projections from 13 CMIP6-GCMs project a warmer (3–5°C) and wetter (13–30%) climate in South Asia in the 21st century. The bias-corrected projections from CMIP6-GCMs can be used for climate change impact assessment in South Asia and hydrologic impact assessment in the sub-continental river basins.

scholarly journals Global Warming Will Aggravate Ozone Pollution in the U.S. Mid-Atlantic

2019 ◽  
Vol 58 (6) ◽  
pp. 1267-1278 ◽  
Author(s):  
Cristina L. Archer ◽  
Joseph F. Brodie ◽  
Sara A. Rauscher
Keyword(s):  
Global Warming ◽  
Air Quality ◽  
Coupled Model ◽  
Historical Period ◽  
Climate Projections ◽  
Ozone Pollution ◽  
Near Surface ◽  
Weather Patterns ◽  
Temperature And Precipitation ◽  
The U.S

AbstractThe goal of this study is to evaluate the effects of anthropogenic climate change on air quality, in particular on ozone, during the summer in the U.S. mid-Atlantic region. First, we establish a connection between high-ozone (HO) days, defined as those with observed 8-h average ozone concentration greater than 70 parts per billion (ppb), and certain weather patterns, called synoptic types. We identify four summer synoptic types that most often are associated with HO days based on a 30-yr historical period (1986–2015) using NCEP–NCAR reanalysis. Second, we define thresholds for mean near-surface temperature and precipitation that characterize HO days during the four HO synoptic types. Next, we look at climate projections from five models from phase 5 of the Coupled Model Intercomparison Project (CMIP5) for the early and late midcentury (2025–34 and 2045–54) and analyze the frequency of HO days. We find a general increasing trend, weaker in the early midcentury and stronger in the late midcentury, with 2 and 5 extra HO days per year, respectively, from 16 in 2015. These 5 extra days are the result of two processes. On one hand, the four HO synoptic types will increase in frequency, which explains about 1.5–2 extra HO days. The remaining 3–3.5 extra days are explained by the increase in near-surface temperatures during the HO synoptic types. Future air quality regulations, which have been successful in the historical period at reducing ozone concentrations in the mid-Atlantic, may need to become stricter to compensate for the underlying increasing trends from global warming.

scholarly journals Setup of the PMIP3 paleoclimate experiments conducted using an Earth System Model, MIROC-ESM

2012 ◽  
Vol 5 (3) ◽  
pp. 2527-2569 ◽  
Author(s):  
T. Sueyoshi ◽  
R. Ohgaito ◽  
A. Yamamoto ◽  
M. O. Chikamoto ◽  
T. Hajima ◽  
...  
Keyword(s):  
Climate Model ◽  
Coupled Model ◽  
Earth System Model ◽  
Future Climate ◽  
System Model ◽  
Climate Feedback ◽  
Climate Projections ◽  
Earth System ◽  
Intergovernmental Panel ◽  
Intercomparison Project

Abstract. The importance of climate model evaluation using paleoclimate simulations for better future climate projections has been recognized by the Intergovernmental Panel on Climate Change. In recent years, Earth System Models (ESMs) were developed to investigate carbon-cycle climate feedback, as well as to project the future climate. Paleoclimate events, especially those associated with the variations in atmospheric CO2 level or land vegetation, provide suitable benchmarks to evaluate ESMs. Here we present implementations of the paleoclimate experiments proposed by the Coupled Model Intercomparison Project phase 5/Paleoclimate Modelling Intercomparison Project phase 3 (CMIP5/PMIP3) using an Earth System Model, MIROC-ESM. In this paper, experimental settings and procedures of the mid-Holocene, the Last Glacial Maximum, and the Last Millennium experiments are explained. The first two experiments are time slice experiments and the last one is a transient experiment. The complexity of the model requires various steps to correctly configure the experiments. Several basic outputs are also shown.

scholarly journals Reducing uncertainties in projections of Antarctic ice mass loss

2015 ◽  
Vol 9 (2) ◽  
pp. 2625-2654 ◽  
Author(s):  
G. Durand ◽  
F. Pattyn
Keyword(s):  
Mass Loss ◽  
Climate Model ◽  
Drainage Basin ◽  
Ice Sheet ◽  
Coupled Model ◽  
Model Average ◽  
Grounding Line ◽  
Polar Ice Sheets ◽  
Order Of Magnitude ◽  
Intercomparison Project

Abstract. Climate model projections are often aggregated into multi-model averages of all models participating in an Intercomparison Project, such as the Coupled Model Intercomparison Project (CMIP). A first initiative of the ice-sheet modeling community, SeaRISE, to provide multi-model average projections of polar ice sheets' contribution to sea-level rise recently emerged. SeaRISE Antarctic numerical experiments aggregate results from all models willing to participate without any selection of the models regarding the processes implemented in. Here, using the experimental set-up proposed in SeaRISE we confirm that the representation of grounding line dynamics is essential to infer future Antarctic mass change. We further illustrate the significant impact on the ensemble mean and deviation of adding one model with a known biais in its ability of modeling grounding line dynamics. We show that this biased model can hardly be discriminated from the ensemble only based on its estimation of volume change. However, tools are available to test parts of the response of marine ice sheet models to perturbations of climatic and/or oceanic origin (MISMIP, MISMIP3d). Based on recent projections of the Pine Island Glacier mass loss, we further show that excluding ice sheet models that do not pass the MISMIP benchmarks decreases by an order of magnitude the mean contribution and standard deviation of the multi-model ensemble projection for that particular drainage basin.

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