Impact of Higher Spatial Atmospheric Resolution on Precipitation Extremes Over Land in Global Climate Models

Bador, Margot; Boé, Julien; Terray, Laurent; Alexander, Lisa V.; Baker, Alexander J.; Bellucci, Alessio; Haarsma, Reindert J.; Köenigk, Torben; Moine, Marie‐Pierre; Lohmann, Katja; Putrasahan, Dian; Roberts, C. D.; Roberts, Malcolm; Scoccimarro, Enrico; Schiemann, R.; Seddon, Jon; Senan, Retish; Valcke, Sophie; Vannière, Benoît

doi:10.1029/2019jd032184

Cited by 107 publications

(83 citation statements)

References 57 publications

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“…For wind, Willison et al (2015) find a larger response of the North Atlantic storm track to global warming with higher resolution in the regional WRF model. Furthermore, Baker et al (2019) find that in winter the polar jet, storm tracks, and associated precipitation shift further north over the Euro-Atlantic region in the future with increased resolution in the same HadGEM3-A set-up as used here. The sensitivity of projections to resolution nevertheless remains an area that needs further research.…”

Section: Discussionmentioning

confidence: 69%

The benefits of increasing resolution in global and regional climate simulations for European climate extremes

et al. 2020

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Abstract. Many climate extremes, including heatwaves and heavy precipitation events, are projected to worsen under climate change, with important impacts for society. Future projections required for adaptation are often based on climate model simulations. Given finite resources, trade-offs must be made concerning model resolution, ensemble size, and level of model complexity. Here we focus on the resolution component. A given resolution can be achieved over a region using either global climate models (GCMs) or at lower cost using regional climate models (RCMs) that dynamically downscale coarser GCMs. Both approaches to increasing resolution may better capture small-scale processes and features (downscaling effect), but increased GCM resolution may also improve the representation of the large-scale atmospheric circulation (upscaling effect). The size of this upscaling effect is therefore important for deciding modelling strategies. Here we evaluate the benefits of increased model resolution for both global and regional climate models for simulating temperature, precipitation, and wind extremes over Europe at resolutions that could currently be realistically used for coordinated sets of climate projections at the pan-European scale. First we examine the benefits of regional downscaling by comparing EURO-CORDEX simulations at 12.5 and 50 km resolution to their coarser CMIP5 driving simulations. Secondly, we compare global-scale HadGEM3-A simulations at three resolutions (130, 60, and 25 km). Finally, we separate out resolution-dependent differences for HadGEM3-A into downscaling and upscaling components using a circulation analogue technique. Results suggest limited benefits of increased resolution for heatwaves, except in reducing hot biases over mountainous regions. Precipitation extremes are sensitive to resolution, particularly over complex orography, with larger totals and heavier tails of the distribution at higher resolution, particularly in the CORDEX vs. CMIP5 analysis. CMIP5 models underestimate precipitation extremes, whilst CORDEX simulations overestimate compared to E-OBS, particularly at 12.5 km, but results are sensitive to the observational dataset used, with the MESAN reanalysis giving higher totals and heavier tails than E-OBS. Wind extremes are somewhat stronger and heavier tailed at higher resolution, except in coastal regions where large coastal grid boxes spread strong ocean winds further over land. The circulation analogue analysis suggests that differences with resolution for the HadGEM3-A GCM are primarily due to downscaling effects.

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Section: Discussionmentioning

confidence: 69%

The benefits of increasing resolution in global and regional climate simulations for European climate extremes

et al. 2020

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“…Because core precipitation occurs over a small area, it relates more directly to extreme precipitation metrics defined at the gridpoint scale than precipitation averaged in the whole tropical cyclone does. Interestingly, Bador et al (2020) found that HadGEM3-GC3.1 and CMCC-CM2 produce the largest change with resolution of the following extreme precipitation metrics: maximum 1-day precipitation (rx1day), maximum 5-day precipitation (rx5day), and total precipitation from extremely wet days (r99p), over both land and ocean, suggesting that tropical cyclone core precipitation in these models share essential physics with processes that contribute to set the extreme precipitation captured by those three metrics.…”

Section: B Tropical Cyclone Core Precipitationmentioning

confidence: 99%

The Moisture Budget of Tropical Cyclones in HighResMIP Models: Large-Scale Environmental Balance and Sensitivity to Horizontal Resolution

et al. 2020

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Previous studies have shown that the number, intensity and structure of simulated tropical cyclones (TCs) in climate models get closer to the observations as the horizontal resolution is increased. However, the sensitivity of tropical cyclone precipitation and moisture budget to changes in resolution has received less attention. In this study, we use the five-model ensemble from project PRIMAVERA/HighResMIP to investigate the systematic changes of the water budget of tropical cyclones in a range of horizontal resolutions of 1° to 0.25°. Our results show that, despite a large change in the distribution of TC intensity with resolution, the distribution of precipitation per TC (i.e. averaged in a 5° radial cap) does not change significantly. This result is explained by the large-scale balance that characterises the moisture budget of TCs, with the radius of the moisture source extending to ∼ 15°, well beyond the TC edge, and that low and high resolution models represent equally well. The wind profile is found to converge between low and high resolutions for radii > 5 °, resulting in a moisture flux convergence into the TC of similar magnitude at low and high resolutions. In contrast to precipitation per TC, the larger TC intensity at higher resolution is explained by the larger surface latent heat flux near the center of the storm, which leads to an increase in equivalent potential temperature and warmer core anomalies, despite representing a negligible contribution to the overall moisture budget. We discuss the complication arising from the choice of the tracking algorithm when assessing the impact of model resolution.

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“…This suggests that the models overestimate the correlation between precipitation and wind. Nevertheless, given previous assessments that found CMIP6 models simulate heavy rainfall relatively poorly (Bador et al., 2020; Kim et al., 2020) and the relative lack of analyses of strong winds, many CMIP6 models capture WP‐CEs surprisingly well. However, there are areas where individual models fail to reflect the observations well.…”

Section: Resultsmentioning

confidence: 99%

“…(2013) note that CMIP5 models generally capture observed trends in temperature extremes, but rainfall extremes are more challenging, although this might be partly due to higher observational uncertainty. Since this assessment, extensive literature has emerged demonstrating the improved skill of climate models in simulating temperature (e.g., Di Luca et al., 2020) and rainfall extremes (Bador et al., 2020), particularly in hot and cold extremes (Di Luca et al., 2020) and the intensity of heavy rainfall (Kim et al., 2020). The evaluation of wind extremes is more limited, but Kumar et al.…”

Section: Introductionmentioning

confidence: 99%

Do CMIP6 Climate Models Simulate Global or Regional Compound Events Skillfully?

Ridder

Pitman

Ukkola

2021

Geophysical Research Letters

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Global climate models are used to simulate climate and weather extremes, including extreme rainfall, high and low temperatures, droughts, and winds. Analyses of observations, historical simulations, and projections of extremes (Alexander, 2016; Bindoff et al., 2013; Sillman et al., 2013) have provided major advances in understanding how the statistics of extremes respond to natural variability and global warming. Many analyses of extremes focus on single hazards, such as how hot is the hottest day each year, or how much rain fell during the rainiest 5-day stretch of the year. An evaluation of models included in the fifth phase of the Coupled Model Intercomparison Project (CMIP5) highlights that extremes are generally more difficult to represent realistically than the average (Flato et al., 2013; Sillman et al., 2013b). For instance, Flato et al. (2013) note that CMIP5 models generally capture observed trends in temperature extremes, but rainfall extremes are more challenging, although this might be partly due to higher observational uncertainty. Since this assessment, extensive literature has emerged demonstrating the improved skill of climate models in simulating temperature (e.g., Di Luca et al., 2020) and rainfall extremes (Bador et al., 2020), particularly in hot and cold extremes (Di Luca et al., 2020) and the intensity of heavy rainfall (Kim et al., 2020). The evaluation of wind extremes is more limited, but Kumar et al. (2015) noted that CMIP5 models simulated the multimodel mean (MMM) of spatial patterns of extreme winds with 25-100-year return periods (RPs) well. In the last decade, compound events (CEs) have emerged as a focus for understanding the link between changes in weather and climate and impacts on vulnerable systems (

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Impact of Higher Spatial Atmospheric Resolution on Precipitation Extremes Over Land in Global Climate Models

Cited by 107 publications

References 57 publications

The benefits of increasing resolution in global and regional climate simulations for European climate extremes

The benefits of increasing resolution in global and regional climate simulations for European climate extremes

The Moisture Budget of Tropical Cyclones in HighResMIP Models: Large-Scale Environmental Balance and Sensitivity to Horizontal Resolution

Do CMIP6 Climate Models Simulate Global or Regional Compound Events Skillfully?

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