Temperature scaling of convective cells in present and future conditions

2020 ◽  
Author(s):  
Christopher Purr ◽  
Erwan Brisson ◽  
Bodo Ahrens
Keyword(s):  
High Temperatures ◽  
Extreme Precipitation ◽  
Climate Models ◽  
Climate Model ◽  
Maximum Intensity ◽  
Convective Precipitation ◽  
Slight Reduction ◽  
The Future ◽  
Temperature Scaling ◽  
Convective Cells

<p>Convection permitting climate models (CPMs) agree on an increase in short-term, extreme precipitation in the future. However, different studies using CPM simulations found regionally varying temperature scaling rates of hourly extreme precipitation either close to or above the Clausius-Clapeyron-rate (CC-rate) of 7%/K. These variations suggest that the dynamics of convective events strongly regulate the local scaling rates. In order to understand how the characteristics of convective events change in the future, we apply a tracking algorithm to precipitation data with 5-min temporal resolution from a regional climate model (COSMO-CLM) simulation. The model is run over central Europe at a grid size of 0.025° for an evaluation period (1981-2015) driven by ERA-Interim reanalysis data, as well as a present-day (1976-2005) and a future (2071-2100) period driven by the EC-Earth global model. We investigate the temperature scaling of convective cell characteristics like total precipitation per cell, mean area, lifetime and maximum intensity, as well as changes in the diurnal cycle of convective cells which might explain the overall scaling rates. The cell characteristics precipitation sum, mean area and maximum intensity show an exponential increase with temperature across most of the temperature range with a drop-off at high temperatures very similar to fixed location scaling curves. While the maximum intensity and area scale at rates close to the CC-rate, the precipitation sum scales at a rate close to twice the CC-rate. In contrast to this, the lifetime of convective cells does not increase with temperature but stays constant with a drop-off at high temperatures. The future simulation shows a shift of the scaling curves towards higher peak values at higher temperatures. Convective activity is projected to decrease during daytime and increase during nighttime. While the mean intensity of convective cells increases throughout the whole day, the number of cells is reduced during the afternoon peak and increased during nighttime. This leads to a slight reduction of convective precipitation during daytime and almost a doubling of convective precipitation during nighttime.</p>

scholarly journals Ensemble Projection of Extreme Precipitation Over China Based on Three Dynamical Downscaling Simulations

2021 ◽  
Vol 9 ◽  
Author(s):  
Guangtao Dong ◽  
Ye Xie ◽  
Ya Wang ◽  
Dongli Fan ◽  
Zhan Tian
Keyword(s):  
21St Century ◽  
Extreme Precipitation ◽  
North China ◽  
Climate Models ◽  
Climate Model ◽  
Dynamical Downscaling ◽  
Global Climate Models ◽  
Vapor Flux ◽  
The Future ◽  
Late 21St Century

Based on the outputs of the global climate models (GCMs) HadGEM2-ES, NorESM1-M and MPI-ESM-LR from Coupled Model Intercomparison Project Phase 5 (CMIP5) and the downscaling results with the regional climate model (RCM) REMO, the ability of the climate models to reproduce the extreme precipitation in China during the current period (1986–2005) is evaluated. Then, the future extreme precipitation in the mid (2036–2065) and the late 21st century (2066–2095) is projected under the RCP8.5 scenario. The results show that the RCM simulations have great improvements compared with the GCMs, and the ensemble mean of the RCM results (ensR) outperforms each single RCM simulation. The annual precipitation of the RCM simulations is more consistent with the observation than that of the GCMs, with the overestimation of the peak precipitation reduced, and the ensR further reduces the bias. For the extreme precipitation, the RCM simulations significantly decrease the underestimation of intensity in the GCMs. The RCM simulations and the ensR can greatly improve the simulations of Rx5day and CWD compared with the GCMs, decreasing the wet bias in North China and Northwest China. In the future, the consecutive dry days (CDD) will decrease in the northern arid regions, especially in North China and Northeast China. However, the southern regions will experience longer dry period. Both the amount and the intensity of precipitation will increase in various regions of China. The number of wet days will decrease in the south and increase in the north area. The significantly greater Rx5day and R95t indicate more intensive extreme precipitation in the future, and the intensity in the late 21st century will be stronger than that in the middle. Attribution analysis indicates that the extreme precipitation indices especially the R95t have significant positive temporal and spatial correlations with the water vapor flux.

The effect of climate change on urban drainage: an evaluation based on regional climate model simulations

2006 ◽  
Vol 54 (6-7) ◽  
pp. 9-15 ◽  
Author(s):  
M. Grum ◽  
A.T. Jørgensen ◽  
R.M. Johansen ◽  
J.J. Linde
Keyword(s):  
Climate Change ◽  
Extreme Precipitation ◽  
Climate Model ◽  
Regional Climate ◽  
Rain Gauge ◽  
Urban Drainage ◽  
Extreme Precipitation Events ◽  
Rainfall Extremes ◽  
The Future ◽  
Precipitation Events

That we are in a period of extraordinary rates of climate change is today evident. These climate changes are likely to impact local weather conditions with direct impacts on precipitation patterns and urban drainage. In recent years several studies have focused on revealing the nature, extent and consequences of climate change on urban drainage and urban runoff pollution issues. This study uses predictions from a regional climate model to look at the effects of climate change on extreme precipitation events. Results are presented in terms of point rainfall extremes. The analysis involves three steps: Firstly, hourly rainfall intensities from 16 point rain gauges are averaged to create a rain gauge equivalent intensity for a 25 × 25 km square corresponding to one grid cell in the climate model. Secondly, the differences between present and future in the climate model is used to project the hourly extreme statistics of the rain gauge surface into the future. Thirdly, the future extremes of the square surface area are downscaled to give point rainfall extremes of the future. The results and conclusions rely heavily on the regional model's suitability in describing extremes at time-scales relevant to urban drainage. However, in spite of these uncertainties, and others raised in the discussion, the tendency is clear: extreme precipitation events effecting urban drainage and causing flooding will become more frequent as a result of climate change.

Change in thunderstorm activity in a projected warmer future climate over Bangladesh

2021 ◽  
Author(s):  
Shahana Akter Esha ◽  
Nasreen Jahan
Keyword(s):  
Climate Model ◽  
Convective Available Potential Energy ◽  
Thunderstorm Activity ◽  
Future Climate ◽  
Convective Precipitation ◽  
Severe Thunderstorms ◽  
Wide Range ◽  
The Future ◽  
Rcp 8.5 ◽  
Increasing Risk

<p>Thunderstorms can have a wide range of impacts on modern societies and their assets. Severe thunderstorms associated with thunder squall, hail, tornado, and lightning cause extensive damage and losses to lives, especially in the densely populated sub-tropical countries like Bangladesh. In this study the future changes in thunderstorm conducive environments, in terms convective available potential energy (CAPE), have been assessed under the RCP 8.5 scenario for the selected major cities of Bangladesh. Results show an increase in CAPE for all the selected cities and in the range of 44%–106%. Later, a statistical thunderstorm frequency prediction model has been developed based on CAPE and convective precipitation and the probable scenario of thunderstorm frequency in the 21st century under future climate has been projected. The simulations were carried out for three different time slices (Early, Mid and Late 21<sup>st</sup> century) with CMCC-CM (Centro Euro-Mediterraneo per Cambiamenti Climatici Climate Model) model data. The future projection of thunderstorm shows an increase in thunderstorm frequency for all the season in a warmer future climate. But pre-monsoon and monsoon are found to be the most thunderstorm frequent season. Given the substantial damage from severe thunderstorms in the current climate, such increases imply an increasing risk of thunderstorm-related damage in this disaster-prone region of the world.</p>

scholarly journals Fidelity of the Observational/Reanalysis Datasets and Global Climate Models in Representation of Extreme Precipitation in East China

2018 ◽  
Vol 32 (1) ◽  
pp. 195-212 ◽  
Author(s):  
Sicheng He ◽  
Jing Yang ◽  
Qing Bao ◽  
Lei Wang ◽  
Bin Wang
Keyword(s):  
Extreme Precipitation ◽  
Climate Models ◽  
Climate Model ◽  
Global Climate ◽  
Yangtze River Basin ◽  
Global Climate Model ◽  
Global Climate Models ◽  
Global Ocean ◽  
East China ◽  
Cmip5 Models

AbstractRealistic reproduction of historical extreme precipitation has been challenging for both reanalysis and global climate model (GCM) simulations. This work assessed the fidelities of the combined gridded observational datasets, reanalysis datasets, and GCMs [CMIP5 and the Chinese Academy of Sciences Flexible Global Ocean–Atmospheric Land System Model–Finite-Volume Atmospheric Model, version 2 (FGOALS-f2)] in representing extreme precipitation over East China. The assessment used 552 stations’ rain gauge data as ground truth and focused on the probability distribution function of daily precipitation and spatial structure of extreme precipitation days. The TRMM observation displays similar rainfall intensity–frequency distributions as the stations. However, three combined gridded observational datasets, four reanalysis datasets, and most of the CMIP5 models cannot capture extreme precipitation exceeding 150 mm day−1, and all underestimate extreme precipitation frequency. The observed spatial distribution of extreme precipitation exhibits two maximum centers, located over the lower-middle reach of Yangtze River basin and the deep South China region, respectively. Combined gridded observations and JRA-55 capture these two centers, but ERA-Interim, MERRA, and CFSR and almost all CMIP5 models fail to capture them. The percentage of extreme rainfall in the total rainfall amount is generally underestimated by 25%–75% in all CMIP5 models. Higher-resolution models tend to have better performance, and physical parameterization may be crucial for simulating correct extreme precipitation. The performances are significantly improved in the newly released FGOALS-f2 as a result of increased resolution and a more realistic simulation of moisture and heating profiles. This work pinpoints the common biases in the combined gridded observational datasets and reanalysis datasets and helps to improve models’ simulation of extreme precipitation, which is critically important for reliable projection of future changes in extreme precipitation.

scholarly journals Selection of Bias Correction Methods to Assess the Impact of Climate Change on Flood Frequency Curves

Water ◽  
2019 ◽  
Vol 11 (11) ◽  
pp. 2266 ◽  
Author(s):  
Enrique Soriano ◽  
Luis Mediero ◽  
Carlos Garijo
Keyword(s):  
Climate Change ◽  
Bias Correction ◽  
Climate Models ◽  
Climate Model ◽  
Control Period ◽  
Flood Frequency ◽  
Climate Projections ◽  
The Future ◽  
Flood Quantiles ◽  
The Impact

Climate projections provided by EURO-CORDEX predict changes in annual maximum series of daily rainfall in the future in some areas of Spain because of climate change. Precipitation and temperature projections supplied by climate models do not usually fit exactly the statistical properties of the observed time series in the control period. Bias correction methods are used to reduce such errors. This paper seeks to find the most adequate bias correction techniques for temperature and precipitation projections that minimizes the errors between observations and climate model simulations in the control period. Errors in flood quantiles are considered to identify the best bias correction techniques, as flood quantiles are used for hydraulic infrastructure design and safety assessment. In addition, this study aims to understand how the expected changes in precipitation extremes and temperature will affect the catchment response in flood events in the future. Hydrological modelling is required to characterize rainfall-runoff processes adequately in a changing climate, in order to estimate flood changes expected in the future. Four catchments located in the central-western part of Spain have been selected as case studies. The HBV hydrological model has been calibrated in the four catchments by using the observed precipitation, temperature and streamflow data available on a daily scale. Rainfall has been identified as the most significant input to the model, in terms of its influence on flood response. The quantile mapping polynomial correction has been found to be the best bias correction method for precipitation. A general reduction in flood quantiles is expected in the future, smoothing the increases identified in precipitation quantiles by the reduction of soil moisture content in catchments, due to the expected increase in temperature and decrease in mean annual precipitations.

scholarly journals Quantification of the Expected Changes in Annual Maximum Daily Precipitation Quantiles under Climate Change in the Iberian Peninsula

Proceedings ◽  
2018 ◽  
Vol 7 (1) ◽  
pp. 23 ◽  
Author(s):  
Carlos Garijo ◽  
Luis Mediero
Keyword(s):  
Climate Change ◽  
Iberian Peninsula ◽  
Climate Models ◽  
Climate Model ◽  
Global Climate ◽  
Global Climate Model ◽  
Regional Climate ◽  
Control Period ◽  
Regional Climate Models ◽  
The Future

Climate model projections can be used to assess the expected behaviour of extreme precipitations in the future due to climate change. The European part of the Coordinated Regional Climate Downscalling Experiment (EURO-CORDEX) provides precipitation projections for the future under various representative concentration pathways (RCPs) through regionalised Global Climate Model (GCM) outputs by a set of Regional Climate Models (RCMs). In this work, 12 combinations of GCM and RCM under two scenarios (RCP 4.5 and RCP 8.5) supplied by the EURO-CORDEX are analysed for the Iberian Peninsula. Precipitation quantiles for a set of probabilities of non-exceedance are estimated by using the Generalized Extreme Value (GEV) distribution and L-moments. Precipitation quantiles expected in the future are compared with the precipitation quantiles in the control period for each climate model. An approach based on Monte Carlo simulations is developed in order to assess the uncertainty from the climate model projections. Expected changes in the future are compared with the sampling uncertainty in the control period. Thus, statistically significant changes are identified. The higher the significance threshold, the fewer cells with significant changes are identified. Consequently, a set of maps are obtained in order to assist the decision-making process in subsequent climate change studies.

Investigating the seasonal response of precipitation extremes to global warming using observations and large-ensembles of coupled climate models

2020 ◽  
Author(s):  
Andrew Williams ◽  
Paul O'Gorman
Keyword(s):  
Global Warming ◽  
Extreme Precipitation ◽  
Climate Models ◽  
Climate Model ◽  
Global Climate ◽  
Precipitation Extremes ◽  
Cmip5 Models ◽  
Historical Period ◽  
Societal Relevance ◽  
Coupled Climate Models

<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>

Future extreme precipitation frequency in the eastern Mediterranean: a new approach exploiting climate model projections

2020 ◽  
Author(s):  
Francesco Marra ◽  
Moshe Armon ◽  
Davide Zoccatelli ◽  
Osama Gazal ◽  
Chaim Garfinkel ◽  
...  
Keyword(s):  
Extreme Precipitation ◽  
Climate Models ◽  
Climate Model ◽  
Eastern Mediterranean ◽  
Regional Climate ◽  
Coastal Region ◽  
Climatic Conditions ◽  
Synoptic Scale ◽  
Precipitation Frequency ◽  
Extreme Quantiles

<p>Understanding extreme precipitation under changing climatic conditions is crucial to manage weather- and flood-related hazards. Global and regional climate models are able to provide coarse scale information on future conditions under different emission scenarios, but large uncertainties affect the projected precipitation amounts, extremes in particular, so that frequency analyses cannot be quantitatively trusted. This study uses, for the first time, the Simplified Metastatistical Extreme Value (SMEV) approach to directly exploit synoptic scale information, better represented by climate models, for obtaining projections of future extreme precipitation frequency.</p><p>We use historical rainfall data from >400 stations in Israel and Jordan to (a) provide a climatology of extreme daily precipitation (e.g., the 100-year return period amounts) in the steep climatic gradients of the region and (b) improve understanding of the SMEV description under changing climate. We demonstrate that, using SMEV, it is possible to (c) present the sensitivity of extreme quantiles to occurrence and intensity of Mediterranean lows and other synoptic systems, and (d) project future extreme quantiles starting from synoptic scale information generated by earlier climate-model-based studies. Under our working hypotheses, we project a general decrease of extreme precipitation quantiles for the RCP8.5 scenario; an increase is detected in the coastal region and the Negev arid lands. We discuss the apparent contrast of these results with previous findings.</p>

scholarly journals Shorter cyclone clusters modulate changes in European wintertime precipitation extremes

2021 ◽  
Author(s):  
Emanuele Bevacqua ◽  
Giuseppe Zappa ◽  
Theodore G Shepherd
Keyword(s):  
Atmospheric Circulation ◽  
Extreme Precipitation ◽  
Climate Models ◽  
Precipitation Extremes ◽  
Southern Europe ◽  
Circulation Change ◽  
The Future ◽  
The Mean ◽  
Future Direction ◽  
Atmospheric Circulation Change

<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>

scholarly journals The importance of model resolution on simulated precipitation in Europe – from global to regional model

2020 ◽  
Author(s):  
Gustav Strandberg ◽  
Petter Lind
Keyword(s):  
High Resolution ◽  
Extreme Precipitation ◽  
Climate Models ◽  
Climate Model ◽  
Horizontal Resolution ◽  
Model Resolution ◽  
Simulated Precipitation ◽  
The Difference ◽  
Model Ensembles ◽  
High Resolution Models

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.

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