Evaluating CMIP6 Model Fidelity at Simulating Non-Gaussian Temperature Distribution Tails

Under global warming, changes in extreme temperatures will manifest in more complex ways in locations where temperature distribution tails deviate from Gaussian. For example, uniform warming applied to a temperature distribution with a shorter-than-Gaussian warm tail would lead to greater exceedances in warm-side temperature extremes compared with a Gaussian distribution. Confidence in projections of future temperature extremes and associated impacts under global warming therefore relies on the ability of global climate models (GCMs) to realistically simulate observed temperature distribution tail behavior. This presentation examines the ability of the latest state-of-the-art ensemble of GCMs from the Coupled Model Intercomparison Project phase six (CMIP6) to capture historical global surface temperature distribution tail shape in hemispheric winter and summer seasons. Comparisons between the multi-model ensemble mean and a reanalysis product reveal strong agreement on coherent spatial patterns of longer- and shorter-than-Gaussian tails for the cold and warm sides of the temperature distribution, suggesting that CMIP6 is broadly capturing tail behavior for plausible physical and dynamical reasons. Most individual GCMs are also reasonably skilled at capturing historical tail shape on a global scale, but a division of the domain into sub-regions reveals considerable model and spatial variability. To explore potential mechanisms driving these differences, a back trajectory analysis examining patterns in the origin of air masses on days experiencing extreme temperatures is also discussed.

Download Full-text

Varying soil moisture-atmosphere feedbacks explain divergent temperature extremes and precipitation projections in Central Europe

10.5194/esd-2018-24 ◽

2018 ◽

Cited By ~ 1

Author(s):

Martha M. Vogel ◽

Jakob Zscheischler ◽

Sonia I. Seneviratne

Keyword(s):

Climate Change ◽

Soil Moisture ◽

Central Europe ◽

Climate Models ◽

Global Climate ◽

Summer Precipitation ◽

Global Climate Models ◽

Temperature Extremes ◽

Extreme Temperatures

Abstract. The frequency and intensity of climate extremes is expected to increase in many regions due to anthropogenic climate change. In Central Europe extreme temperatures are projected to change more strongly than global mean temperatures and soil moisture-temperature feedbacks significantly contribute to this regional amplification. Because of their strong societal, ecological and economic impacts, robust projections of temperature extremes are needed. Unfortunately, in current model projections, temperature extremes in Central Europe are prone to large uncertainties. In order to understand and potentially reduce uncertainties of extreme temperatures projections in Europe, we analyze global climate models from the CMIP5 ensemble for the business-as-usual high-emission scenario (RCP8.5). We find a divergent behavior in long-term projections of summer precipitation until the end of the 21st century, resulting in a trimodal distribution of precipitation (wet, dry and very dry). All model groups show distinct characteristics for summer latent heat flux, top soil moisture, and temperatures on the hottest day of the year (TXx), whereas for net radiation and large-scale circulation no clear trimodal behavior is detectable. This suggests that different land-atmosphere coupling strengths may be able to explain the uncertainties in temperature extremes. Constraining the full model ensemble with observed present-day correlations between summer precipitation and TXx excludes most of the very dry and dry models. In particular, the very dry models tend to overestimate the negative coupling between precipitation and TXx, resulting in a too strong warming. This is particularly relevant for global warming levels above 2 °C. The analysis allows for the first time to substantially reduce uncertainties in the projected changes of TXx in global climate models. Our results suggest that long-term temperature changes in TXx in Central Europe are about 20 % lower than projected by the multi-model median of the full ensemble. In addition, mean summer precipitation is found to be more likely to stay close to present-day levels. These results are highly relevant for improving estimates of regional climate-change impacts including heat stress, water supply and crop failure for Central Europe.

Download Full-text

Regions of intensification of extreme snowfall under future warming

Scientific Reports ◽

10.1038/s41598-021-95979-4 ◽

2021 ◽

Vol 11 (1) ◽

Author(s):

Lennart Quante ◽

Sven N. Willner ◽

Robin Middelanis ◽

Anders Levermann

Keyword(s):

Climate Change ◽

Global Warming ◽

Observational Data ◽

Climate Models ◽

Hydrological Cycle ◽

Global Climate ◽

Global Climate Models ◽

Average Intensity ◽

High Latitudes ◽

Future Warming

AbstractDue to climate change the frequency and character of precipitation are changing as the hydrological cycle intensifies. With regards to snowfall, global warming has two opposing influences; increasing humidity enables intense snowfall, whereas higher temperatures decrease the likelihood of snowfall. Here we show an intensification of extreme snowfall across large areas of the Northern Hemisphere under future warming. This is robust across an ensemble of global climate models when they are bias-corrected with observational data. While mean daily snowfall decreases, both the 99th and the 99.9th percentiles of daily snowfall increase in many regions in the next decades, especially for Northern America and Asia. Additionally, the average intensity of snowfall events exceeding these percentiles as experienced historically increases in many regions. This is likely to pose a challenge to municipalities in mid to high latitudes. Overall, extreme snowfall events are likely to become an increasingly important impact of climate change in the next decades, even if they will become rarer, but not necessarily less intense, in the second half of the century.

Download Full-text

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.

Download Full-text

Assessing the impact of global warming on worldwide open field tomato cultivation through CSIRO-Mk3·0 global climate model

The Journal of Agricultural Science ◽

10.1017/s0021859616000654 ◽

2016 ◽

Vol 155 (3) ◽

pp. 407-420 ◽

Cited By ~ 7

Author(s):

R. S. SILVA ◽

L. KUMAR ◽

F. SHABANI ◽

M. C. PICANÇO

Keyword(s):

Climate Change ◽

Global Warming ◽

Open Field ◽

Climate Models ◽

Climate Model ◽

Global Climate ◽

Global Climate Model ◽

Current Model ◽

Global Climate Models ◽

The Impact

SUMMARYTomato (Solanum lycopersicum L.) is one of the most important vegetable crops globally and an important agricultural sector for generating employment. Open field cultivation of tomatoes exposes the crop to climatic conditions, whereas greenhouse production is protected. Hence, global warming will have a greater impact on open field cultivation of tomatoes rather than the controlled greenhouse environment. Although the scale of potential impacts is uncertain, there are techniques that can be implemented to predict these impacts. Global climate models (GCMs) are useful tools for the analysis of possible impacts on a species. The current study aims to determine the impacts of climate change and the major factors of abiotic stress that limit the open field cultivation of tomatoes in both the present and future, based on predicted global climate change using CLIMatic indEX and the A2 emissions scenario, together with the GCM Commonwealth Scientific and Industrial Research Organisation (CSIRO)-Mk3·0 (CS), for the years 2050 and 2100. The results indicate that large areas that currently have an optimum climate will become climatically marginal or unsuitable for open field cultivation of tomatoes due to progressively increasing heat and dry stress in the future. Conversely, large areas now marginal and unsuitable for open field cultivation of tomatoes will become suitable or optimal due to a decrease in cold stress. The current model may be useful for plant geneticists and horticulturalists who could develop new regional stress-resilient tomato cultivars based on needs related to these modelling projections.

Download Full-text

Increased water vapour lifetime due to global warming

10.5194/acp-2019-121 ◽

2019 ◽

Cited By ~ 1

Author(s):

Øivind Hodnebrog ◽

Gunnar Myhre ◽

Bjørn H. Samset ◽

Kari Alterskjær ◽

Timothy Andrews ◽

...

Keyword(s):

Global Warming ◽

Water Vapour ◽

Solar Irradiance ◽

Climate Models ◽

Hydrological Cycle ◽

Global Climate ◽

Global Climate Models ◽

Climate Projections ◽

Surface Temperature Change ◽

Surface Warming

Abstract. The relationship between changes in integrated water vapour (IWV) and precipitation can be characterized by quantifying changes in atmospheric water vapour lifetime. Precipitation isotope ratios correlate with this lifetime, a relationship that helps understand dynamical processes and may lead to improved climate projections. We investigate how water vapour and its lifetime respond to different drivers of climate change, such as greenhouse gases and aerosols. Results from 11 global climate models have been used, based on simulations where CO2, methane, solar irradiance, black carbon (BC), and sulphate have been perturbed separately. A lifetime increase from 8 to 10 days is projected between 1986–2005 and 2081–2100, under a business-as-usual pathway. By disentangling contributions from individual climate drivers, we present a physical understanding of how global warming slows down the hydrological cycle, due to longer lifetime, but still amplifies the cycle due to stronger precipitation/evaporation fluxes. The feedback response of IWV to surface temperature change differs somewhat between drivers. Fast responses amplify these differences and lead to net changes in IWV per degree surface warming ranging from 6.4±0.9 %/K for sulphate to 9.8±2 %/K for BC. While BC is the driver with the strongest increase in IWV per degree surface warming, it is also the only driver with a reduction in precipitation per degree surface warming. Consequently, increases in BC aerosol concentrations yield the strongest slowdown of the hydrological cycle among the climate drivers studied, with a change in water vapour lifetime per degree surface warming of 1.1±0.4 days/K, compared to less than 0.5 days/K for the other climate drivers (CO2, methane, solar irradiance, sulphate).

Download Full-text

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.

Download Full-text

Projected precipitation changes over China for global warming levels at 1.5°C and 2°C in an ensemble of regional climate simulations: Impact of bias-correction algorithms

10.5194/egusphere-egu2020-4811 ◽

2020 ◽

Author(s):

Lianyi Guo

Keyword(s):

Global Warming ◽

Bias Correction ◽

Climate Models ◽

Dynamical Downscaling ◽

Comprehensive Evaluation ◽

Global Climate ◽

Regional Climate ◽

Global Climate Models ◽

Cumulative Distribution ◽

Mathematical Framework

Four bias-correction methods, i.e. Gamma Cumulative Distribution Function (GamCDF), Quantile-Quantile Adjustment (QQadj), Equidistant CDF Matching (EDCDF) and Transform CDF (CDF-t), were applied to five daily precipitation datasets over China produced by LMDZ4-regional that was nested into five global climate models (GCMs), BCC-CSM1-1m, CNRM-CM5, FGOALS-g2, IPSL-CM5A-MR and MPI-ESM-MR, respectively. A unified mathematical framework can be used to define the four methods, which helps understanding their nature and essence in identifying the most reliable probability distributions of projected climate. CDF-t is shown to be the best bias-correction algorithm based on a comprehensive evaluation of different rainfall indices. Future precipitation projections corresponds to the global warming levels of 1.5&#176;C and 2&#176;C under RCP8.5 were obtained using the bias correction methods. The multi-algorithm and multi-model ensemble characteristics allow to explore the spreading of results, considered as a surrogate of climate projection uncertainty, and to attribute such uncertainties to different sources. It was found that the spread among bias-correction methods is smaller than that among dynamical downscaling simulations. The four bias-correction methods with CDF-t at the top all reduce the spread among the downscaled results. Future projection using CDF-t is thus considered having higher credibility.

Download Full-text

Intensification characteristics of hydroclimatic extremes in the Asia monsoon region under 1.5 and 2.0 °C of global warming

10.5194/hess-2019-643 ◽

2020 ◽

Author(s):

Jeong-Bae Kim ◽

Deg-Hyo Bae

Keyword(s):

Global Warming ◽

Climate Models ◽

Global Climate ◽

Regional Climate ◽

Global Climate Models ◽

Monsoon Region ◽

Infiltration Capacity ◽

Meteorological Forcing ◽

Climate Zones ◽

Global Mean Temperature

Abstract. The changes in hydroclimatic extremes are assessed over the Asia monsoon region under 1.5 and 2.0 °C warming targets of global mean temperature above preindustrial levels based on a representative concentration pathway (RCP) 4.5 scenario. The subregions in this domain are defined by the Köppen climate classification method to identify regional climate characteristics. The change patterns of long-term hydroclimatic mean and hydroclimatic extreme among subregions are compared based on the multimodel ensemble (MME) of selected five global climate models (GCMs). Each GCM is bias corrected and then used as a meteorological forcing for a hydrological model. To simulate how the hydrologic system responds to 1.5 and 2.0 °C global warming targets, we select the variable infiltration capacity (VIC) model. The results of temperature extremes show significant change patterns over all climate zones. As the globe warms, the increasing warm extremes and the decreasing cold extremes with a high robustness occur more frequently over Asia. Meanwhile, changes in precipitation and runoff averages (and low runoff extremes) show large spatial variations in change patterns with little robustness based on intermodel agreement. Global warming is expected to significantly intensify maximum precipitation extremes in all climate zones. Regardless of regional climate characteristics, this behavior is expected to be enhanced under 2.0 °C compare to 1.5 °C warming scenario and cause the likelihood of flood risk. The spatial extent and magnitude of change patterns in runoff are modulated by those of change patterns in precipitation. More importantly, an extra 0.5 °C of global warming also leads to amplified change signals and more robust change patterns in hydroclimatic extremes, especially in cold (and polar) climate zones. The results of this study demonstrate that the clear changes in regional hydroclimatic extremes under warmer conditions over Asia, and hydroclimatic sensitivities differ based on regional climate characteristics.

Download Full-text

Impact of Global Warming on Extreme Heavy Rainfall in the Present Climate: Case Study of Heavy Rainfall in Kinugawa, Japan (2015)

Atmosphere ◽

10.3390/atmos11020220 ◽

2020 ◽

Vol 11 (2) ◽

pp. 220

Author(s):

Kenji Taniguchi ◽

Yuto Minobe

Keyword(s):

Global Warming ◽

Heavy Rainfall ◽

Climate Models ◽

Initial Conditions ◽

Atmospheric Temperature ◽

Global Climate Models ◽

Extreme Weather Events ◽

Heavy Rainfall Event ◽

Simulated Rainfall ◽

Total Rainfall

Hazardous heavy rainfall and wide-scale inundation occurred in the Kinugawa River basin, north of Tokyo, in 2015. In this study, ensemble hindcast and non-global warming (NGW) simulations of this heavy rainfall event were implemented. In the NGW simulations, initial and boundary conditions were generated by using the outputs of natural forcing historical experiments by twelve different global climate models. The results of the hindcast and NGW simulations indicated the high likelihood of the generation of linear heavy rainfall bands and the intensification of Kinugawa heavy rainfall due to anthropogenic greenhouse gas emissions. However, in some NGW simulations, the total rainfall was greater than in the hindcast. In addition, the maximum total rainfall was greater in many NGW simulations. Lower atmospheric temperature, sea surface temperature (SST), and precipitable water content (PWC) under the initial conditions can cause less rainfall in the NGW simulations. However, some discrepancies were found in the initial conditions and simulated rainfall; less rainfall with higher atmospheric temperature, SST and PWC, and vice versa. A detailed investigation of simulated atmospheric conditions explained the simulated rainfall. These results indicate that it is not sufficient to examine climatological anomalies to understand individual extreme weather events, but that detailed simulations are useful.

Download Full-text

Climate engineering to mitigate the projected 21st-century terrestrial drying of the Americas: a direct comparison of carbon capture and sulfur injection

10.5194/egusphere-egu21-7926 ◽

2021 ◽

Author(s):

Yangyang Xu ◽

Lei Lin ◽

Simone Tilmes ◽

Katherine Dagon ◽

Lili Xia ◽

...

Keyword(s):

Global Warming ◽

South America ◽

21St Century ◽

Carbon Capture ◽

Model Comparison ◽

Climate Models ◽

Global Climate ◽

Low Cost ◽

Amazon Region ◽

Global Climate Models

To mitigate the projected global warming in the 21st century, it is well-recognized that society needs to cut CO2 emissions and other short-lived warming agents aggressively. However, to stabilize the climate at a warming level closer to the present day, such as the &#8220;well below 2 &#9702;C&#8221; aspiration in the Paris Agreement, a net-zero carbon emission by 2050 is still insufficient. The recent IPCC special report calls for a massive scheme to extract CO2 directly from the atmosphere, in addition to decarbonization, to reach negative net emissions at the mid-century mark. Another ambitious proposal is solar-radiation-based geoengineering schemes, including injecting sulfur gas into the stratosphere. Despite being in public debate for years, these two leading geoengineering schemes have not been directly compared under a consistent analytical framework using global climate models.Here we present the first explicit analysis of the hydroclimate impacts of these two geoengineering approaches using two recently available large-ensemble model experiments conducted by a family of state-of-the-art Earth system models. Our analysis focuses on the projected aridity conditions over the Americas in the 21st century in detailed terms of the potential mitigation benefits, the temporal evolution, the spatial distribution (within North and South America), the relative efficiency, and the physical mechanisms. We show that sulfur injection, in contrast to previous notions of leading to excessive terrestrial drying (in terms of precipitation reduction) while offsetting the global mean greenhouse gas (GHG) warming, will instead mitigate the projected drying tendency under RCP8.5. The surface energy balance change induced by sulfur injection, in addition to the well-known response in temperature and precipitation, plays a crucial role in determining the overall terrestrial hydroclimate response. However, when normalized by the same amount of avoided global warming in these simulations, sulfur injection is less effective in curbing the worsening trend of regional land aridity in the Americas under RCP8.5 when compared with carbon capture. Temporally, the climate benefit of sulfur injection will emerge more quickly, even when both schemes are hypothetically started in the same year of 2020. Spatially, both schemes are effective in curbing the drying trend over North America. However, for South America, the sulfur injection scheme is particularly more effective for the sub-Amazon region (southern Brazil), while the carbon capture scheme is more effective for the Amazon region. We conclude that despite the apparent limitations (such as an inability to address ocean acidification) and potential side effects (such as changes to the ozone layer), innovative means of sulfur injection should continue to be explored as a potential low-cost option in the climate solution toolbox, complementing other mitigation approaches such as emission cuts and carbon capture (Cao et al., 2017). Our results demonstrate the urgent need for multi-model comparison studies and detailed regional assessments in other parts of the world.

Download Full-text