The Resolution Dependence of Contiguous U.S. Precipitation Extremes in Response to CO2 Forcing

2016 ◽  
Vol 29 (22) ◽  
pp. 7991-8012 ◽  
Author(s):  
Karin van der Wiel ◽  
Sarah B. Kapnick ◽  
Gabriel A. Vecchi ◽  
William F Cooke ◽  
Thomas L. Delworth ◽  
...  

Abstract Precipitation extremes have a widespread impact on societies and ecosystems; it is therefore important to understand current and future patterns of extreme precipitation. Here, a set of new global coupled climate models with varying atmospheric resolution has been used to investigate the ability of these models to reproduce observed patterns of precipitation extremes and to investigate changes in these extremes in response to increased atmospheric CO2 concentrations. The atmospheric resolution was increased from 2° × 2° grid cells (typical resolution in the CMIP5 archive) to 0.25° × 0.25° (tropical cyclone permitting). Analysis has been confined to the contiguous United States (CONUS). It is shown that, for these models, integrating at higher atmospheric resolution improves all aspects of simulated extreme precipitation: spatial patterns, intensities, and seasonal timing. In response to 2 × CO2 concentrations, all models show a mean intensification of precipitation rates during extreme events of approximately 3%–4% K−1. However, projected regional patterns of changes in extremes are dependent on model resolution. For example, the highest-resolution models show increased precipitation rates during extreme events in the hurricane season in the U.S. Southeast; this increase is not found in the low-resolution model. These results emphasize that, for the study of extreme precipitation there is a minimum model resolution that is needed to capture the weather phenomena generating the extremes. Finally, the observed record and historical model experiments were used to investigate changes in the recent past. In part because of large intrinsic variability, no evidence was found for changes in extreme precipitation attributable to climate change in the available observed record.

2020 ◽  
Author(s):  
Emma D. Thomassen ◽  
Elisabeth Kendon ◽  
Hjalte J. D. Sørup ◽  
Steven Chan ◽  
Peter L. Langen ◽  
...  

<p>Convection Permitting Models (CPM) are believed to improve the representation of precipitation extremes at sub-daily scale compared to coarser spatial scale Regional Climate Models (RCM). This study seeks to compare how the spatio-temporal characteristics of precipitation extremes differ between a 2.2km CPM and a 12km RCM from the UK Met Office with a pan-European domain.</p><p>Storm data have been re-gridded to a common 12km grid and all events in the period from 1999-2008 are tracked with the DYMECS tracking algorithm. A peak-over-threshold method is used to sample extreme events within a northern European case area. Maximum intensity and maximum area of extremes are sampled based on the maximum intensity and maximum size reached within their lifetime. Evolution in size and intensity, track patterns, and seasonal occurrence of extreme events are compared between the two models.</p><p>For the top 1000 extreme events with the highest maximum intensities, the two models show disagreement in movement direction and spatial and temporal occurrence. While the CPM data are dominated by south-north moving events occurring in summer over central Europe, the RCM data are dominated by west-east moving events occurring over UK and more uniformly distribution over the year. The CPM and RCM however show good agreement in these variables for extreme events instead selected based on largest spatial area. A comparison with the COSMO REA6 reanalysis model continuously nudged towards observations indicates a similar spatial and seasonal distribution of extreme events sampled by maximum intensity as in the CPM. Analysis of the evolution of storms over their lifetime shows on average higher intensities and spatial areas of the most intense storms in the RCM data compared to the most intense storms in the CPM data. Sampling of maximum intensity extreme events in each of the four seasons show larger disagreement between the two models in the evolution in intensity and size in autumn (SON) and winter (DJF) than in spring (MAM) and summer (JJA).</p>


2018 ◽  
Vol 22 (7) ◽  
pp. 3933-3950 ◽  
Author(s):  
Reinhard Schiemann ◽  
Pier Luigi Vidale ◽  
Len C. Shaffrey ◽  
Stephanie J. Johnson ◽  
Malcolm J. Roberts ◽  
...  

Abstract. Limited spatial resolution is one of the factors that may hamper applications of global climate models (GCMs), in particular over Europe with its complex coastline and orography. In this study, the representation of European mean and extreme precipitation is evaluated in simulations with an atmospheric GCM (AGCM) at different resolutions between about 135 and 25 km grid spacing in the mid-latitudes. The continent-wide root-mean-square error in mean precipitation in the 25 km model is about 25  % smaller than in the 135 km model in winter. Clear improvements are also seen in autumn and spring, whereas the model's sensitivity to resolution is very small in summer. Extreme precipitation is evaluated by estimating generalised extreme value distributions (GEVs) of daily precipitation aggregated over river basins whose surface area is greater than 50 000 km2. GEV location and scale parameters are measures of the typical magnitude and of the interannual variability of extremes, respectively. Median model biases in both these parameters are around 10 % in summer and around 20 % in the other seasons. For some river basins, however, these biases can be much larger and take values between 50 % and 100 %. Extreme precipitation is better simulated in the 25 km model, especially during autumn when the median GEV parameter biases are more than halved, and in the North European Plains, from the Loire in the west to the Vistula in the east. A sensitivity experiment is conducted showing that these resolution sensitivities in both mean and extreme precipitation are in many areas primarily due to the increase in resolution of the model orography. The findings of this study illustrate the improved capability of a global high-resolution model in simulating European mean and extreme precipitation.


2020 ◽  
Author(s):  
Traute Crueger ◽  
Hauke Schmidt ◽  
Bjorn Stevens

<p>Under present day conditions the observations approximately show a hemispheric symmetry of the top of atmosphere (TOA)  short wave (SW) reflection despite the asymmetry of surface SW reflection. This has been confirmed by climate models. With models in an aqua planet setup, Voigt et al. (2014) found that tropical clouds largely compensate surface SW hemispheric asymmetries, however to a different degree in dependence on the convection scheme.</p><p>In this study, we question, whether there is also a hemispheric symmetry of TOA SW radiation under changed atmospheric radiation conditions. For that reason, we analyze experiments performed with a set of fully coupled general circulation models. The experiments were performed with either a) hemispheric asymmetric incoming radiation, b) increased atmospheric CO2 concentrations, c) increased atmospheric CO2 concentrations combined with increased stratospheric aerosol burden, or d) increased atmospheric CO2 concentration in conjunction with increased ocean albedo.</p><p>We show that generally, a hemispheric symmetry of TOA SW radiation does not occur. Overall, among the group of models, the hemispheric TOA SW radiation budgets are roughly similar for the distinct experiments, although the models utilyze different convection schemes.  We discuss the role of surface and atmospheric feedbacks in the different experiments, especially of tropical and extratropical clouds.</p><p>Reference:<br>Voigt, A., B. Stevens, J. Bader, and T. Mauritsen, 2014: Compensation of Hemispheric Albedo Asymmetries by Shifts of the ITCZ and Tropical Clouds. J. Climate, 27, 1029–1045, https://doi.org/10.1175/JCLI-D-13-00205.1.</p>


2020 ◽  
Author(s):  
Andrew Williams ◽  
Paul O'Gorman

<p>Changes in extreme precipitation are amongst the most impactful consequences of global warming, with potential effects ranging from increased flood risk and landslides to crop failures and impacts on ecosystems. Thus, understanding historical and future changes in extreme precipitation is not only important from a scientific perspective, but also has direct societal relevance.</p><p>However, while most current research has focused on annual precipitation extremes and their response to warming, it has recently been noted that climate model projections show a distinct seasonality to future changes in extreme precipitation. In particular, CMIP5 models suggest that over Northern Hemisphere (NH) land the summer response is weaker than the winter response in terms of percentage changes.</p><p>Here we investigate changes in seasonal precipitation extremes using observations and simulations with coupled climate models. First, we analyse observed trends from the Hadley Centre’s global climate extremes dataset (HadEX2) to investigate to what extent there is already a difference between summer and winter trends over NH land. Second, we use 40 ensemble members from the CESM Large Ensemble to characterize the role played by internal variability in trends over the historical period. Lastly, we use CMIP5 simulations to explore the possibility of a link between the seasonality of changes in precipitation extremes and decreases in surface relative humidity over land.</p>


2021 ◽  
Author(s):  
Emanuele Bevacqua ◽  
Giuseppe Zappa ◽  
Theodore G Shepherd

<p>Wintertime extreme precipitation from cyclone clusters, i.e. consecutive cyclones moving across the same region, can lead to flooding and devastating socio-economic impacts in Europe. Previous studies have suggested that the future direction of the changes in these events are uncertain across climate models. By employing an impact-based metric of accumulated precipitation extremes, we show that projections of cyclone clusters are instead broadly robust, i.e. consistent in sign, across models. A novel physical diagnostic shows that accumulated precipitation extremes are projected to grow by only +1.0 %/K on average across Europe, although the mean precipitation per cyclone increases by +4.7 %/K. This results from a decreased number of clustered cyclones, associated with decreased wintertime storminess, the extent of which varies from northern to southern Europe and depends on the future storyline of atmospheric circulation change. Neglecting the changes in the number of clustered cyclones, i.e. assuming that accumulated precipitation extremes would change as the mean precipitation per cyclone, would lead to overestimating the population affected by increased accumulated wintertime precipitation extremes by 130–490 million across Europe.</p>


2020 ◽  
Author(s):  
Gustav Strandberg ◽  
Petter Lind

Abstract. Precipitation, and especially extreme precipitation, is a key climate variable as it effects large parts of society. It is difficult to simulate in a climate model because of its large variability in time and space. This study investigates the importance of model resolution on the simulated precipitation in Europe for a wide range of climate model ensembles: from global climate models (GCM) at horizontal resolution of around 300 km to regional climate models (RCM) at horizontal resolution of 12.5 km. The aim is to investigate the differences between models and model ensembles, but also to evaluate their performance compared to gridded observations from E-OBS. Model resolution has a clear effect on precipitation. Generally, extreme precipitation is more intense and more frequent in high-resolution models compared to low-resolution models. Models of low resolution tend to underestimate intense precipitation. This is improved in high-resolution simulations, but there is a risk that high resolution models overestimate precipitation. This effect is seen in all ensembles, and GCMs and RCMs of similar resolution give similar results. The number of precipitation days, which is more governed by large-scale atmospheric flow, is not dependent on model resolution, while the number of days with heavy precipitation is. The difference between different models is often larger than between the low- and high-resolution versions of the same model, which makes it difficult to quantify the improvement. In this sense the quality of an ensemble is depending more on the models it consists of rather than the average resolution of the ensemble. Furthermore, the difference in simulated precipitation between an RCM and the driving GCM depend more on the choice of RCM and less on the down-scaling itself; as different RCMs driven by the same GCM may give different results. The results presented here are in line with previous similar studies but this is the first time an analysis like this is done across such relatively large model ensembles of different resolutions, and with a method studying all parts of the precipitation distribution.


Atmosphere ◽  
2019 ◽  
Vol 10 (3) ◽  
pp. 130 ◽  
Author(s):  
Wenlong Hao ◽  
Zhenchun Hao ◽  
Feifei Yuan ◽  
Qin Ju ◽  
Jie Hao

Extreme events such as rainstorms and floods are likely to increase in frequency due to the influence of global warming, which is expected to put considerable pressure on water resources. This paper presents a regional frequency analysis of precipitation extremes and its spatio-temporal pattern characteristics based on well-known index-flood L-moments methods and the application of advanced statistical tests and spatial analysis techniques. The results indicate the following conclusions. First, during the period between 1969 and 2015, the annual precipitation extremes at Fengjie station show a decreasing trend, but the Wuhan station shows an increasing trend, and the other 24 stations have no significant trend at a 5% confidence level. Secondly, the Hanjiang River Basin can be categorized into three homogenous regions by hierarchical clustering analysis with the consideration of topography and mean precipitation in these areas. The GEV, GNO, GPA and P III distributions fit better for most of the basin and MARE values range from 3.19% to 6.41% demonstrating that the best-fit distributions for each homogenous region is adequate in predicting the quantiles estimates. Thirdly, quantile estimates are reliable enough when the return period is less than 100 years, however estimates for a higher return period (e.g., 1000 years) become unreliable. Further, the uncertainty of quantiles estimations is growing with the growing return periods and the estimates based on R95P series have a smaller uncertainty to describe the extreme precipitation in the Hanjiang river basin (HJRB). Furthermore, In the HJRB, most of the extreme precipitation events (more than 90%) occur during the rainy season between May and October, and more than 30% of these extreme events concentrate in July, which is mainly impacted by the sub-tropical monsoon climate. Finally, precipitation extremes are mainly concentrated in the areas of Du River, South River and Daba Mountain in region I and Tianmen, Wuhan and Zhongxiang stations in region III, located in the upstream of Danjiangkou Reservoir and Jianghan Plain respectively. There areas provide sufficient climate conditions (e.g., humidity and precipitation) responsible for the occurring floods and will increase the risk of natural hazards to these areas.


2020 ◽  
Vol 33 (3) ◽  
pp. 1089-1103 ◽  
Author(s):  
Jean-Luc Martel ◽  
Alain Mailhot ◽  
François Brissette

AbstractMany studies have reported projected increases in the frequency and intensity of extreme precipitation events in a warmer future climate. These results challenge the assumption of climate stationarity, a standard hypothesis in the estimation of extreme precipitation quantiles (e.g., 100-yr return period) often used as key design criteria for many infrastructures. In this work, changes in hourly to 5-day precipitation extremes occurring between the 1980–99 and 2080–99 periods are investigated using three large ensembles (LE) of climate simulations. The first two are the global CanESM2 50-member ensemble at a 2.8° resolution and the global CESM1 40-member ensemble at a 1° resolution. The third is the regional CRCM5 50-member ensemble at a 0.11° resolution, driven at its boundaries by the 50-member CanESM2 ensemble over the northeastern North America (NNA) and Europe (EU) domains. Results indicate increases in the frequency of future extreme events, and, accordingly, a reduction of the return period of current extreme events for all tested spatial resolutions and temporal scales. Agreement between the three ensembles suggests that extreme precipitations, corresponding to the 100-yr return period over the reference period, become 4–5 (2–4) times more frequent on average for the NNA (EU) domain for daily and 5-day annual maximum precipitation. Projections by CRCM5-LE show even larger increases for subdaily precipitation extremes. Considering the life-span of many public infrastructures, these changes may have important implications on service levels and the design of many water infrastructures and for public safety, and should therefore be taken into consideration in establishing design criteria.


2007 ◽  
Vol 20 (8) ◽  
pp. 1419-1444 ◽  
Author(s):  
Viatcheslav V. Kharin ◽  
Francis W. Zwiers ◽  
Xuebin Zhang ◽  
Gabriele C. Hegerl

Abstract Temperature and precipitation extremes and their potential future changes are evaluated in an ensemble of global coupled climate models participating in the Intergovernmental Panel on Climate Change (IPCC) diagnostic exercise for the Fourth Assessment Report (AR4). Climate extremes are expressed in terms of 20-yr return values of annual extremes of near-surface temperature and 24-h precipitation amounts. The simulated changes in extremes are documented for years 2046–65 and 2081–2100 relative to 1981–2000 in experiments with the Special Report on Emissions Scenarios (SRES) B1, A1B, and A2 emission scenarios. Overall, the climate models simulate present-day warm extremes reasonably well on the global scale, as compared to estimates from reanalyses. The model discrepancies in simulating cold extremes are generally larger than those for warm extremes, especially in sea ice–covered areas. Simulated present-day precipitation extremes are plausible in the extratropics, but uncertainties in extreme precipitation in the Tropics are very large, both in the models and the available observationally based datasets. Changes in warm extremes generally follow changes in the mean summertime temperature. Cold extremes warm faster than warm extremes by about 30%–40%, globally averaged. The excessive warming of cold extremes is generally confined to regions where snow and sea ice retreat with global warming. With the exception of northern polar latitudes, relative changes in the intensity of precipitation extremes generally exceed relative changes in annual mean precipitation, particularly in tropical and subtropical regions. Consistent with the increased intensity of precipitation extremes, waiting times for late-twentieth-century extreme precipitation events are reduced almost everywhere, with the exception of a few subtropical regions. The multimodel multiscenario consensus on the projected change in the globally averaged 20-yr return values of annual extremes of 24-h precipitation amounts is that there will be an increase of about 6% with each kelvin of global warming, with the bulk of models simulating values in the range of 4%–10% K−1. The very large intermodel disagreements in the Tropics suggest that some physical processes associated with extreme precipitation are not well represented in models. This reduces confidence in the projected changes in extreme precipitation.


2018 ◽  
Vol 31 (17) ◽  
pp. 6711-6727 ◽  
Author(s):  
Xiaolong Chen ◽  
Peili Wu ◽  
Malcolm J. Roberts ◽  
Tianjun Zhou

The amount of rainfall during June and July along the mei-yu front contributes about 45% to the total summer precipitation over the Yangtze River valley. How it will change under global warming is of great concern to the people of China because of its particular socioeconomic importance, but climate model projections from phase 5 of the Coupled Model Intercomparison Project (CMIP5) show large uncertainties. This paper examines model resolution sensitivity and reports large differences in projected future summer rainfall along the mei-yu front between a low-resolution (Gaussian N96 grid, ~1.5° latitude–longitude) and a high-resolution (N216, ~0.7°) version of the Hadley Centre’s latest climate model, the HadGEM3 Global Coupled Configuration 2.0 (HadGEM3-GC2). The high-resolution model projects large increases of summer rainfall under two representative concentration pathway scenarios (RCP8.5 and RCP4.5) whereas the low-resolution model shows a decrease. A larger increase of projected mei-yu rainfall in higher-resolution models is also observed across the CMIP5 ensemble. These differences can be explained in terms of enhanced moist static energy advection and moisture convergence by stationary eddies in the high-resolution model. A large-scale manifestation of the anomalous stationary eddies is the contrasting response to the same warming scenario by the western North Pacific subtropical high, which is almost unchanged in N216 but retreats evidently eastward in N96, reducing the southwesterly flow and consequently moisture supply to the mei-yu front. Further increases in model resolution to resolve parameterized processes and detailed orographic features will hopefully reduce the spread in future climate projections.


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