On the opposite relation between extreme precipitation over west Amazon and southeastern Brazil: observations and model simulations

Abstract. Probability estimates of the future change of extreme precipitation events are usually based on a limited number of available global climate model (GCM) or regional climate model (RCM) simulations. Since floods are related to heavy precipitation events, this restricts the assessment of flood risks. In this study a relatively simple method has been developed to get a better description of the range of changes in extreme precipitation events. Five bias-corrected RCM simulations of the 1961–2100 climate for a single greenhouse gas emission scenario (A1B SRES) were available for the Rhine basin. To increase the size of this five-member RCM ensemble, 13 additional GCM simulations were analysed. The climate responses of the GCMs are used to modify an observed (1961–1995) precipitation time series with an advanced delta change approach. Changes in the temporal means and variability are taken into account. It is found that the range of future change of extreme precipitation across the five-member RCM ensemble is similar to results from the 13-member GCM ensemble. For the RCM ensemble, the time series modification procedure also results in a similar climate response compared to the signal deduced from the direct model simulations. The changes from the individual RCM simulations, however, systematically differ from those of the driving GCMs, especially for long return periods.

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Monsoonal Precipitation Over Peninsular Malaysia in the CMIP6 Highresmip Experiments: The Role of Model Resolution

10.21203/rs.3.rs-741632/v1 ◽

2021 ◽

Author(s):

Ju Liang ◽

Mou Leong Tan ◽

Matthew Hawcroft ◽

Jennifer L. Catto ◽

Kevin I. Hodges ◽

...

Keyword(s):

Extreme Precipitation ◽

Monsoon Season ◽

Southwest Monsoon ◽

Peninsular Malaysia ◽

Vertical Resolution ◽

Model Simulations ◽

Extreme Precipitation Events ◽

Different Seasons ◽

Model Ensembles ◽

The Impact

Abstract This study investigates the ability of 20 model simulations which contributed to the CMIP6 HighResMIP to simulate precipitation in different monsoon seasons and extreme precipitation events over Peninsular Malaysia. The model experiments utilize common forcing but are run with different horizontal and vertical resolutions. The impact of resolution on the models’ abilities to simulate precipitation and associated environmental fields is assessed by comparing multi-model ensembles at different resolutions with three observed precipitation datasets and four climate reanalyses. Model simulations with relatively high horizontal and vertical resolution exhibit better performance in simulating the annual cycle of precipitation and extreme precipitation over Peninsular Malaysia and the coastal regions. Improvements associated with the increase in horizontal and vertical resolutions are also found in the statistical relationship between precipitation and monsoon intensity in different seasons. However, the increase in vertical resolution can lead to a reduction of annual mean precipitation compared to that from the models with low vertical resolutions, associated with an overestimation of moisture divergence and underestimation of lower-tropospheric vertical ascent in the different monsoon seasons. This limits any improvement in the simulation of precipitation in the high vertical resolution experiments, particularly for the Southwest monsoon season.

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Return levels of sub-daily extreme precipitation over Europe

10.5194/essd-2020-145 ◽

2020 ◽

Author(s):

Benjamin Poschlod ◽

Ralf Ludwig ◽

Jana Sillmann

Keyword(s):

Observational Data ◽

Extreme Precipitation ◽

Climate Model ◽

Internal Variability ◽

Return Level ◽

Data Set ◽

Model Simulations ◽

Return Levels ◽

Climate Model Simulations ◽

Precipitation Events

Abstract. Information on the frequency and intensity of extreme precipitation is required by public authorities, civil security departments and engineers for the design of buildings and the dimensioning of water management and drainage schemes. Especially for sub-daily resolution, at which many extreme precipitation events occur, the observational data are sparse in space and time, distributed heterogeneously over Europe and often not publicly available. We therefore consider it necessary to provide an impact-orientated data set of 10-year rainfall return levels over Europe based on climate model simulations and evaluate its quality. Hence, to standardize procedures and provide comparable results, we apply a high-resolution single-model large ensemble (SMILE) of the Canadian Regional Climate Model version 5 (CRCM5) with 50 members in order to assess the frequency of heavy precipitation events over Europe between 1980 and 2009. The application of a SMILE enables a robust estimation of extreme rainfall return levels with the 50 members of 30-year climate simulations providing 1500 years of rainfall data. As the 50 members only differ due to the internal variability of the climate system, the impact of internal variability on the return level values can be quantified. We present 10-year rainfall return levels of hourly to 24-hourly duration with a spatial resolution of 0.11° (12.5 km), which are compared to a large data set of observation-based rainfall return levels of 16 European countries. This observation-based data set was newly compiled and homogenized for this study from 32 different sources. The rainfall return levels of the CRCM5 are able to reproduce the general spatial pattern of extreme precipitation for all sub-daily durations with centred Pearson product-moment coefficients of linear correlation > 0.7 for the area covered with observations. Also, the rainfall intensity of the observational data set is in the range of the climate model generated intensities in 52 % (77 %, 79 %, 84 %, 78 %) of the area for hourly (3-hourly, 6-hourly, 12-hourly, 24-hourly) durations. This results in biases between −19.3 % (hourly) to +8.0 % (24-hourly) averaged over the study area. The range, which is introduced by the application of 50 members, shows a spread of −15 % to +18 % around the median. We conclude that our data set shows good agreement with the observations for 3-hourly to 24-hourly durations in large parts of the study area. Though, for hourly duration and topographically complex regions such as the Alps and Norway, we argue that higher-resolution climate model simulations are needed to improve the results. The 10-year return level data are publicly available (Poschlod, 2020; https://doi.org/10.5281/zenodo.3878887).

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Sensitivities of Extreme Precipitation to Global Warming Are Lower over Mountains than over Oceans and Plains

Journal of Climate ◽

10.1175/jcli-d-15-0576.1 ◽

2016 ◽

Vol 29 (13) ◽

pp. 4779-4791 ◽

Cited By ~ 20

Author(s):

Xiaoming Shi ◽

Dale Durran

Keyword(s):

Global Warming ◽

Extreme Precipitation ◽

Climate Model ◽

Static Stability ◽

Induced Response ◽

Model Simulations ◽

Fractional Rate ◽

Rate Of Increase ◽

Climate Model Simulations ◽

Almost All

Abstract Climate-model simulations predict an intensification of extreme precipitation in almost all areas of the world under global warming. Local variations in the magnitude of this intensification are evident in these simulations, but most previous efforts to understand the factors responsible for the changes in extreme precipitation focused on zonal averages and neglected zonal variations, leading to uncertainties in the understanding and estimation of regional responses. Here the spatial heterogeneity of the warming-induced response of midlatitude extreme precipitation is studied in climate-model simulations with idealized orography on the western margins of otherwise flat continents. It is shown that the sensitivity of extreme precipitation to warming (i.e., its fractional rate of increase in intensity with global-mean surface temperature) is ~3% K−1 lower over the mountains than the oceans and plains. This difference in sensitivity is primarily produced by differences in the dynamics governing vertical ascent over the three regions. In these extreme events, mountain-wave dynamics control the moist ascent over the mountains, and the sensitivity of this ascent to global warming is mainly controlled by changes in upper-level dry static stability and the cross-mountain winds. In contrast, midlatitude cyclone dynamics govern moist ascent over the oceans and plains. Ascending motions in intense midlatitude cyclones are sensitive to the ratio of the moist static stability in their saturated cores to the dry stability in surrounding regions. This ratio decreases in the warmer world, intensifying the maximum vertical velocities while reducing the horizontal extent of the regions of the rising air within the cyclone.

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Changing seasonality of moderate and extreme precipitation events in the Alps

Natural Hazards and Earth System Science ◽

10.5194/nhess-18-2047-2018 ◽

2018 ◽

Vol 18 (7) ◽

pp. 2047-2056 ◽

Cited By ~ 20

Author(s):

Stefan Brönnimann ◽

Jan Rajczak ◽

Erich M. Fischer ◽

Christoph C. Raible ◽

Marco Rohrer ◽

...

Keyword(s):

Extreme Precipitation ◽

Climate Model ◽

Global Climate Model ◽

Model Simulations ◽

Extreme Precipitation Events ◽

Rate Of Increase ◽

Decadal Scale ◽

The Future ◽

The Impact ◽

Precipitation Events

Abstract. The intensity of precipitation events is expected to increase in the future. The rate of increase depends on the strength or rarity of the events; very strong and rare events tend to follow the Clausius–Clapeyron relation, whereas weaker events or precipitation averages increase at a smaller rate than expected from the Clausius–Clapeyron relation. An often overlooked aspect is seasonal occurrence of such events, which might change in the future. To address the impact of seasonality, we use a large ensemble of regional and global climate model simulations, comprising tens of thousands of model years of daily temperature and precipitation for the past, present, and future. In order to make the data comparable, they are quantile mapped to observation-based time series representative of the Aare catchment in Switzerland. Model simulations show no increase in annual maximum 1-day precipitation events (Rx1day) over the last 400 years and an increase of 10 %–20 % until the end of the century for a strong (RCP8.5) forcing scenario. This fits with a Clausius–Clapeyron scaling of temperature at the event day, which increases less than annual mean temperature. An important reason for this is a shift in seasonality. Rx1day events become less frequent in late summer and more frequent in early summer and early autumn, when it is cooler. The seasonality shift is shown to be related to summer drying. Models with decreasing annual mean or summer mean precipitation show this behaviour more strongly. The highest Rx1day per decade, in contrast, shows no change in seasonality in the future. This discrepancy implies that decadal-scale extremes are thermodynamically limited; conditions conducive to strong events still occur during the hottest time of the year on a decadal scale. In contrast, Rx1day events are also limited by other factors. Conducive conditions are not reached every summer in the present, and even less so in the future. Results suggest that changes in the seasonal cycle need to be accounted for when preparing for moderately extreme precipitation events and assessing their socio-economic impacts.

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Sub-daily temporal reconstruction of extreme precipitation events using NWP model simulations

Atmospheric Research ◽

10.1016/j.atmosres.2019.03.019 ◽

2019 ◽

Vol 224 ◽

pp. 65-80 ◽

Cited By ~ 4

Author(s):

Vojtěch Bližňák ◽

Marek Kašpar ◽

Miloslav Müller ◽

Petr Zacharov

Keyword(s):

Extreme Precipitation ◽

Model Simulations ◽

Extreme Precipitation Events ◽

Nwp Model ◽

Precipitation Events

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Changing seasonality of moderate and extreme precipitation events in the Alps

10.5194/nhess-2018-55 ◽

2018 ◽

Author(s):

Stefan Brönnimann ◽

Jan Rajczak ◽

Erich Fischer ◽

Christoph C. Raible ◽

Marco Rohrer ◽

...

Keyword(s):

Extreme Precipitation ◽

Climate Model ◽

Global Climate Model ◽

Model Simulations ◽

Extreme Precipitation Events ◽

Rate Of Increase ◽

Decadal Scale ◽

The Future ◽

The Impact ◽

Precipitation Events

Abstract. The intensity of precipitation events is expected to increase in the future. The rate of increase depends on the strength or rarity of the events; very strong and rare events tend to follow the Clausius-Clapeyron relation, whereas weaker events or precipitation averages do not. An often overlooked aspect is seasonal occurrence of such events, which might change in the future. To address the impact of seasonality, we use a large ensemble of regional and global climate model simulations, comprising tens of thousands of model years of daily temperature and precipitation for the past, present and future. In order to make the data comparable, they are quantile-mapped to observation-based time series representative of the Aare catchment in Switzerland. Model simulations show no increase in annual maximum 1-day precipitation events (Rx1day) over the last 400 yrs and an increase of 10–20 % until the end of the century for a strong (RCP8.5) forcing scenario. This fits with a Clausius-Clapeyron scaling of temperature at the event day, which increases less than annual mean temperature. An important reason for this is a shift in seasonality. Rx1day events become less frequent in late summer and more frequent in early summer and early fall, when it is cooler. The seasonality shift is shown to be related to summer drying. Models with decreasing annual mean or summer mean precipitation show this behavior more strongly. The highest Rx1day per decade, in contrast, shows no change in seasonality in the future. This discrepancy implies that decadal-scale extremes are thermodynamically limited; conditions conducive to strong events still occur during hottest time of the year on a decadal scale. In contrast, Rx1day events are also limited by other factors. Conducive conditions are not reached every summer in the present, and even less so in the future. Results suggest that changes in the seasonal cycle need to be accounted for when preparing for moderately extreme precipitation events and assessing their socio-economic impacts.

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Blasts from the past: Reimagining historical storms with model simulations to modernize dam safety and flood risk assessment

Bulletin of the American Meteorological Society ◽

10.1175/bams-d-21-0133.1 ◽

2021 ◽

pp. 1-35

Author(s):

Kelly Mahoney ◽

Chesley McColl ◽

Douglas M. Hultstrand ◽

William D. Kappel ◽

Bill McCormick ◽

...

Keyword(s):

Risk Assessment ◽

Water Resources ◽

Flood Risk ◽

Extreme Precipitation ◽

Historical Event ◽

Accurate Estimation ◽

Dam Safety ◽

Model Simulations ◽

Upper Limit ◽

Safety Rules

AbstractAccurate estimation of the potential “upper limit” for extreme precipitation is critical for dam safety and water resources management, as dam failures pose significant risks to life and property. Methods used to estimate the theoretical “upper limit” of precipitation are often outdated and in need of updating. The rarity of extreme events means that old storms with limited observational data are often used to define the upper bound of precipitation. Observations of many important old storms are limited in spatial and temporal coverage, and sometimes of dubious quality. This reduces confidence in flood hazard assessments used in dam safety evaluations and leads to unknown or uncertain societal risk.This paper describes a method for generating and applying ensembles of high-resolution, state-of-the-art numerical model simulations of historical past extreme precipitation events to meet contemporary stakeholder needs. The method was designed as part of a research-to-application-focused partnership project to update state dam safety rules in Colorado and New Mexico. The results demonstrated multiple stakeholder and user benefits which were applied directly into storm analyses utilized for extreme rainfall estimation, and diagnostics were developed and ultimately used to update Colorado state dam safety rules, officially passed in January 2020. We discuss how what started as a prototype research foray to meet a specific user need may ultimately inform wider adoption of numerical simulations for water resources risk assessment, and how the historical event downscaling method performed offers near-term, implementable improvements to current dam safety flood risk estimates that can better serve society today.

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