Connection of Quasi-Resonant Amplification to the Delay in Atmospheric Residence Times Over India

Mean monthly Atmospheric Residence Times (ART), deduced from the global climate models of Coupled Model Intercomparison Project 5 (CMIP5) under RCP4.5 and RCP8.5 emission scenarios over Indian landmass, show a perceptible increase by the end of the 21st century. India, being a tropical country, faces prolonged ART, particularly during the June month of Southwest monsoon season (June to September) which will be an indicative measure of the increased frequency of extreme weather events. Here we show a possible connection of quasi-resonant amplification (QRA) to the recent (August 2018) Kerala heavy rains that resulted in severe floods and claimed more than 400 mortalities. Remarkable delay in residence times over India during June is shown to have an association with QRA evidenced by the higher magnitudes of amplitudes at the wavenumbers six and seven from the 19 global climate models of CMIP5 under the RCP4.5 and RCP8.5 scenarios.

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Past and future trends in large-scale atmospheric circulations over Europe: Assessment of the Jenkinson-Collison classification with reanalyses and CMIP6.

10.5194/dkt-12-32 ◽

2020 ◽

Author(s):

Pedro Herrera-Lormendez ◽

Nikolaos Mastrantonas ◽

Jörg Matschullat ◽

Hervé Douville

Keyword(s):

General Circulation ◽

Large Scale ◽

Western Europe ◽

Climate Models ◽

Global Climate ◽

Coupled Model ◽

Global Climate Models ◽

Extreme Weather Events ◽

Dynamical Response ◽

Weather Patterns

Circulation classifications are a simple tool given their ability to portray aspects of day-to-day weather. As we start facing a dynamical response in general circulation patterns due to anthropogenic global warming, circulation changes can enhance or mitigate regional and local behaviour of extreme weather events. A weather type (WT) automatic classification, developed by Jenkinson-Collison (JC), is used to evaluate past and future changes in the seasonal frequencies of synoptic weather patterns over central and western Europe. A set of three reanalyses and four Global Climate Models (GCMs) from the Coupled Model Intercomparison Project Phase 6 (CMIP6) are used, based on daily Sea Level Pressure (SLP) data. Discrepancies are found in the model outputs as they fall short of capturing interannual variabilities when compared to the reanalyses. Cyclonic and westerly circulations tend to be overestimated, whereas anticyclonics are underestimated. The projected frequencies, based on the Shared Socioeconomic Pathway 5 (SSP5) experiment, suggest significant increasing trends for unclassified WT (characterized by weak pressure gradients) during their summer half-year persistency for the coming 21st century. Winter trends indicate a surge in westerlies and a reduction in the events of cyclonic circulations and easterly flows. The results of this study support evidence of emergent changes in the occurrence of major synoptic configurations over Europe.

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Multi-thousand member ensemble atmospheric simulations with global 60km resolution using climateprediction.net

10.5194/egusphere-egu2020-10895 ◽

2020 ◽

Author(s):

Peter Watson ◽

Sarah Sparrow ◽

William Ingram ◽

Simon Wilson ◽

Drouard Marie ◽

...

Keyword(s):

Climate Models ◽

Climate Model ◽

Global Climate ◽

Atmospheric Model ◽

Computing System ◽

Extreme Weather ◽

Global Climate Models ◽

Extreme Weather Events ◽

Weather Events ◽

The Impact

Multi-thousand member climate model simulations are highly valuable for showing how extreme weather events will change as the climate changes, using a physically-based approach. However, until now, studies using such an approach have been limited to using models with a resolution much coarser than the most modern systems. We have developed a global atmospheric model with 5/6&#176;x5/9&#176; resolution (~60km in middle latitudes) that can be run in the climateprediction.net distributed computing system to produce such large datasets. This resolution is finer than that of many current global climate models and sufficient for good simulation of extratropical synoptic features such as storms. It will also allow many extratropical extreme weather events to be simulated without requiring regional downscaling. We will show that this model's simulation of extratropical weather is competitive with that in other current models. We will also present results from the first multi-thousand member ensembles produced at this resolution, showing the impact of 1.5&#176;C and 2&#176;C global warming on extreme winter rainfall and extratropical cyclones in Europe.

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Past and future trends in large-scale atmospheric circulations over Europe: Assessment of the Jenkinson-Collison classification with reanalyses and CMIP6

10.5194/egusphere-egu21-3150 ◽

2021 ◽

Author(s):

Pedro Herrera-Lormendez ◽

Jörg Matschullat ◽

Hervé Douville

Keyword(s):

General Circulation ◽

Large Scale ◽

Western Europe ◽

Climate Models ◽

Global Climate ◽

Coupled Model ◽

Global Climate Models ◽

Extreme Weather Events ◽

Dynamical Response ◽

Weather Patterns

Circulation classifications are a simple tool given their ability to portray aspects of day-to-day weather. As we start facing a dynamical response in general circulation patterns due to anthropogenic global warming, circulation changes can enhance or mitigate regional and local behaviour of extreme weather events.An automatic weather type (WT) classification, developed by Jenkinson-Collison, is used to evaluate past and future changes in seasonal frequencies of synoptic weather patterns over central and western Europe. A set of three reanalyses and eight Global Climate Models (GCMs) from the Coupled Model Intercomparison Project Phase 6 (CMIP6) are used, based on daily Sea Level Pressure (SLP) data.Discrepancies are found in some of the model outputs as some fall short of capturing interannual variabilities when compared to reanalyses. Cyclonic and westerly circulations tend to be overestimated, whereas anticyclonic are underestimated.Based on the historical data and Shared Socioeconomic Pathway 5 (SSP5-8.5) scenario, the evaluated trends suggest more robust signals during the summer half-years given their lesser synoptic-scale variability. During this season, increasing frequencies are found for the WT characterized by weak pressure gradients, mostly at the expense of decreasing frequencies of the westerlies. Our findings indicate that the time of emergence of these signals only occurs towards the end of the 21st century, even in such a high-emission scenario.

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Observation-based selection of climate models projects Arctic ice-free summers around 2035

Communications Earth & Environment ◽

10.1038/s43247-021-00214-7 ◽

2021 ◽

Vol 2 (1) ◽

Author(s):

David Docquier ◽

Torben Koenigk

Keyword(s):

Model Selection ◽

Sea Ice ◽

Climate Models ◽

Global Climate ◽

Coupled Model ◽

Arctic Sea Ice ◽

Global Climate Models ◽

The Arctic ◽

Arctic Sea ◽

Area And Volume

AbstractArctic sea ice has been retreating at an accelerating pace over the past decades. Model projections show that the Arctic Ocean could be almost ice free in summer by the middle of this century. However, the uncertainties related to these projections are relatively large. Here we use 33 global climate models from the Coupled Model Intercomparison Project 6 (CMIP6) and select models that best capture the observed Arctic sea-ice area and volume and northward ocean heat transport to refine model projections of Arctic sea ice. This model selection leads to lower Arctic sea-ice area and volume relative to the multi-model mean without model selection and summer ice-free conditions could occur as early as around 2035. These results highlight a potential underestimation of future Arctic sea-ice loss when including all CMIP6 models.

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Tendency Bias Correction in Coupled and Uncoupled Global Climate Models with a Focus on Impacts over North America

Journal of Climate ◽

10.1175/jcli-d-18-0598.1 ◽

2019 ◽

Vol 32 (2) ◽

pp. 639-661 ◽

Cited By ~ 5

Author(s):

Y. Chang ◽

S. D. Schubert ◽

R. D. Koster ◽

A. M. Molod ◽

H. Wang

Keyword(s):

North America ◽

Bias Correction ◽

Climate Models ◽

Global Climate ◽

Storm Track ◽

Coupled Model ◽

Global Climate Models ◽

Forecast Skill ◽

Boreal Summer ◽

Transient Wave

Abstract We revisit the bias correction problem in current climate models, taking advantage of state-of-the-art atmospheric reanalysis data and new data assimilation tools that simplify the estimation of short-term (6 hourly) atmospheric tendency errors. The focus is on the extent to which correcting biases in atmospheric tendencies improves the model’s climatology, variability, and ultimately forecast skill at subseasonal and seasonal time scales. Results are presented for the NASA GMAO GEOS model in both uncoupled (atmosphere only) and coupled (atmosphere–ocean) modes. For the uncoupled model, the focus is on correcting a stunted North Pacific jet and a dry bias over the central United States during boreal summer—long-standing errors that are indeed common to many current AGCMs. The results show that the tendency bias correction (TBC) eliminates the jet bias and substantially increases the precipitation over the Great Plains. These changes are accompanied by much improved (increased) storm-track activity throughout the northern midlatitudes. For the coupled model, the atmospheric TBCs produce substantial improvements in the simulated mean climate and its variability, including a much reduced SST warm bias, more realistic ENSO-related SST variability and teleconnections, and much improved subtropical jets and related submonthly transient wave activity. Despite these improvements, the improvement in subseasonal and seasonal forecast skill over North America is only modest at best. The reasons for this, which are presumably relevant to any forecast system, involve the competing influences of predictability loss with time and the time it takes for climate drift to first have a significant impact on forecast skill.

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

10.5194/esd-2020-80 ◽

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.

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

Advances in Meteorology ◽

10.1155/2019/1067365 ◽

2019 ◽

Vol 2019 ◽

pp. 1-18 ◽

Cited By ~ 9

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.

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

Water ◽

10.3390/w12123299 ◽

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.

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Projected increases in magnitude and socioeconomic exposure of global droughts in 1.5 and 2 °C warmer climates

Hydrology and Earth System Sciences ◽

10.5194/hess-24-451-2020 ◽

2020 ◽

Vol 24 (1) ◽

pp. 451-472 ◽

Cited By ~ 9

Author(s):

Lei Gu ◽

Jie Chen ◽

Jiabo Yin ◽

Sylvia C. Sullivan ◽

Hui-Min Wang ◽

...

Keyword(s):

Global Warming ◽

Climate Models ◽

Global Climate ◽

Coupled Model ◽

Global Climate Models ◽

Drought Severity ◽

Copula Functions ◽

Infrastructure Failure ◽

Potential Risks ◽

Socioeconomic Consequences

Abstract. The Paris Agreement sets a long-term temperature goal to hold global warming to well below 2.0 ∘C and strives to limit it to 1.5 ∘C above preindustrial levels. Droughts with either intense severity or a long persistence could both lead to substantial impacts such as infrastructure failure and ecosystem vulnerability, and they are projected to occur more frequently and trigger intensified socioeconomic consequences with global warming. However, existing assessments targeting global droughts under 1.5 and 2.0 ∘C warming levels usually neglect the multifaceted nature of droughts and might underestimate potential risks. This study, within a bivariate framework, quantifies the change in global drought conditions and corresponding socioeconomic exposures for additional 1.5 and 2.0 ∘C warming trajectories. The drought characteristics are identified using the Standardized Precipitation Evapotranspiration Index (SPEI) combined with the run theory, with the climate scenarios projected by 13 Coupled Model Inter-comparison Project Phase 5 (CMIP5) global climate models (GCMs) under three representative concentration pathways (RCP 2.6, RCP4.5 and RCP8.5). The copula functions and the most likely realization are incorporated to model the joint distribution of drought severity and duration, and changes in the bivariate return period with global warming are evaluated. Finally, the drought exposures of populations and regional gross domestic product (GDP) under different shared socioeconomic pathways (SSPs) are investigated globally. The results show that within the bivariate framework, the historical 50-year droughts may double across 58 % of global landmasses in a 1.5 ∘C warmer world, while when the warming climbs up to 2.0 ∘C, an additional 9 % of world landmasses would be exposed to such catastrophic drought deteriorations. More than 75 (73) countries' populations (GDP) will be completely affected by increasing drought risks under the 1.5 ∘C warming, while an extra 0.5 ∘C warming will further lead to an additional 17 countries suffering from a nearly unbearable situation. Our results demonstrate that limiting global warming to 1.5 ∘C, compared with 2 ∘C warming, can perceptibly mitigate the drought impacts over major regions of the world.

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The Double-ITCZ Bias in CMIP6 Models

10.5194/egusphere-egu2020-21375 ◽

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

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.

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