scholarly journals Projections of extreme precipitation events in regional climate simulations for Europe and the Alpine Region

2013 ◽  
Vol 118 (9) ◽  
pp. 3610-3626 ◽  
Author(s):  
J. Rajczak ◽  
P. Pall ◽  
C. Schär
Keyword(s):  
Extreme Precipitation ◽  
Regional Climate ◽  
Alpine Region ◽  
Extreme Precipitation Events ◽  
Climate Simulations ◽  
Precipitation Events

scholarly journals Evaluation of uncertainties in mean and extreme precipitation under climate change for northwestern Mediterranean watersheds from high-resolution Med and Euro-CORDEX ensembles

2018 ◽  
Vol 22 (1) ◽  
pp. 673-687 ◽  
Author(s):  
Antoine Colmet-Daage ◽  
Emilia Sanchez-Gomez ◽  
Sophie Ricci ◽  
Cécile Llovel ◽  
Valérie Borrell Estupina ◽  
...  
Keyword(s):  
Climate Change ◽  
High Resolution ◽  
Extreme Precipitation ◽  
Climate Models ◽  
Regional Climate ◽  
Regional Climate Models ◽  
Historical Period ◽  
Mountainous Regions ◽  
Extreme Precipitation Events ◽  
Precipitation Events

Abstract. The climate change impact on mean and extreme precipitation events in the northern Mediterranean region is assessed using high-resolution EuroCORDEX and MedCORDEX simulations. The focus is made on three regions, Lez and Aude located in France, and Muga located in northeastern Spain, and eight pairs of global and regional climate models are analyzed with respect to the SAFRAN product. First the model skills are evaluated in terms of bias for the precipitation annual cycle over historical period. Then future changes in extreme precipitation, under two emission scenarios, are estimated through the computation of past/future change coefficients of quantile-ranked model precipitation outputs. Over the 1981–2010 period, the cumulative precipitation is overestimated for most models over the mountainous regions and underestimated over the coastal regions in autumn and higher-order quantile. The ensemble mean and the spread for future period remain unchanged under RCP4.5 scenario and decrease under RCP8.5 scenario. Extreme precipitation events are intensified over the three catchments with a smaller ensemble spread under RCP8.5 revealing more evident changes, especially in the later part of the 21st century.

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.

scholarly journals Large-Scale Predictors for Extreme Hourly Precipitation Events in Convection-Permitting Climate Simulations

2018 ◽  
Vol 31 (6) ◽  
pp. 2115-2131 ◽  
Author(s):  
Steven C. Chan ◽  
Elizabeth J. Kendon ◽  
Nigel Roberts ◽  
Stephen Blenkinsop ◽  
Hayley J. Fowler
Keyword(s):  
Extreme Precipitation ◽  
Land Surface ◽  
Large Scale ◽  
Future Climate ◽  
Cumulus Parameterization ◽  
Hourly Precipitation ◽  
Vertical Stability ◽  
Extreme Precipitation Events ◽  
Climate Simulations ◽  
Precipitation Events

Midlatitude extreme precipitation events are caused by well-understood meteorological drivers, such as vertical instability and low pressure systems. In principle, dynamical weather and climate models behave in the same way, although perhaps with the sensitivities to the drivers varying between models. Unlike parameterized convection models (PCMs), convection-permitting models (CPMs) are able to realistically capture subdaily extreme precipitation. CPMs are computationally expensive; being able to diagnose the occurrence of subdaily extreme precipitation from large-scale drivers, with sufficient skill, would allow effective targeting of CPM downscaling simulations. Here the regression relationships are quantified between the occurrence of extreme hourly precipitation events and vertical stability and circulation predictors in southern United Kingdom 1.5-km CPM and 12-km PCM present- and future-climate simulations. Overall, the large-scale predictors demonstrate skill in predicting the occurrence of extreme hourly events in both the 1.5- and 12-km simulations. For the present-climate simulations, extreme occurrences in the 12-km model are less sensitive to vertical stability than in the 1.5-km model, consistent with understanding the limitations of cumulus parameterization. In the future-climate simulations, the regression relationship is more similar between the two models, which may be understood from changes to the large-scale circulation patterns and land surface climate. Overall, regression analysis offers a promising avenue for targeting CPM simulations. The authors also outline which events would be missed by adopting such a targeted approach.

Monitoring and Modelling of Soil Moisture in Lower Franconia (Germany)

2020 ◽  
Author(s):  
Julian Krause ◽  
Christian Schäfer ◽  
Birgit Terhorst ◽  
Roland Baumhauer ◽  
Heiko Paeth
Keyword(s):  
Soil Moisture ◽  
Extreme Precipitation ◽  
Regional Climate ◽  
Earth System Model ◽  
System Model ◽  
Future Scenarios ◽  
Earth System ◽  
Extreme Precipitation Events ◽  
Lower Franconia ◽  
Precipitation Events

<p>This research is part of the integrated project “BigData@Geo - Advanced Environmental Technology Using AI In The Web” funded by the European Regional Development Fund (ERDF). The aim of this ERDF-project is to develop a high-resolution regional earth system model for the region of Lower Franconia. One sub-project is dedicated to regional soil moisture modelling created with WaSiM-ETH based on soil moisture monitoring data. The second sub-project aims to improve the resolution of the regional climate model REMO. Both models will be combined to form the earth system model.</p><p>Lower Franconia is amongst the regions in Germany, which will be strongly affected by climate change. Regional climate models show that average temperatures will rise and dry periods as well as extreme precipitation events occur more often. However, it is still not known, what effect the changing climate conditions – especially dry periods and extreme precipitation events – will have on the soils in Lower Franconia.</p><p>Yields of forestry and agriculture (including viticulture and pomiculture) depend very much on the availability of soil water. During the growing season the water retention capacity of soils is therefore highly relevant. Up to present, datasets as well as modelling results of future scenarios on soil moisture are only scarcely available on local as well as on regional scale. In order to generate future scenarios, calculation of the soil moisture regime forms the base in order to evaluate present day conditions as well as to develop prognostic studies. As we intend to obtain most realistic parameters, generation of real-time data with high temporal resolution at selected sites is crucial. They are characteristic for Lower Franconia serving as calibration regions for modelling approaches. The operating monitoring stations record soil moisture and - temperature as well as meteorological parameters.</p><p>In order to obtain data on dynamics and causes of soil moisture fluctuation as well as to understand process flows, soil geographical surveys form an essential component of our research design for selected sites related to the monitoring stations. Furthermore, relevant sedimentological and pedological parameters such as grain size distribution, permeability, and bulk density are analyzed in the laboratory. Thus, our representative test sites combine detailed ground-truth data combining soil moisture and soil quality and thus, form consecutive modules as parts of soil moisture models. These modules drive and control the modelling procedures of the sub-project and they further serve for assessment and calibration of the area-wide hydrological and climate modelling in the “BigData@Geo” ERDF-project.</p>

scholarly journals Future changes in extreme precipitation in the Rhine basin based on global and regional climate model simulations

2012 ◽  
Vol 16 (12) ◽  
pp. 4517-4530 ◽  
Author(s):  
S. C. van Pelt ◽  
J. J. Beersma ◽  
T. A. Buishand ◽  
B. J. J. M. van den Hurk ◽  
P. Kabat
Keyword(s):  
Time Series ◽  
Regional Climate Model ◽  
Extreme Precipitation ◽  
Climate Model ◽  
Regional Climate ◽  
Future Change ◽  
Model Simulations ◽  
Rhine Basin ◽  
Extreme Precipitation Events ◽  
Precipitation Events

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.

scholarly journals Local Enhancement of Extreme Precipitation during Atmospheric Rivers as Simulated in a Regional Climate Model

2018 ◽  
Vol 19 (9) ◽  
pp. 1429-1446 ◽  
Author(s):  
Raquel Lorente-Plazas ◽  
Todd P. Mitchell ◽  
Guillaume Mauger ◽  
Eric P. Salathé
Keyword(s):  
Extreme Precipitation ◽  
Large Scale ◽  
Regional Climate ◽  
Puget Sound ◽  
Static Stability ◽  
The Other ◽  
Extreme Precipitation Events ◽  
Olympic Mountains ◽  
Synoptic Conditions ◽  
Precipitation Events

Abstract This paper examines the synoptic conditions that yield extreme precipitation in two regions with different orographic features, the Olympic Mountains and Puget Sound. To capture orographic extreme precipitation, a dynamical downscaling is performed, driven by the NCEP–NCAR reanalysis and evaluated for cool-season months from 1970 to 2010. Clustering techniques are applied to the regional climate simulation, which reveals the Olympic Mountains and Puget Sound as regions with distinct temporal variability in precipitation. Results show that approximately one-third of the extreme precipitation events in each region occur without a similarly extreme event in the other, in spite of the fact that the two areas are very closely located and one is downstream of the other. Composites of synoptic conditions for extreme precipitation events show differences in integrated vapor transport (IVT) due to its dynamical component (winds at 850 hPa) and its thermodynamical component [integrated water vapor (IWV)]. For Puget Sound events, IVT is lower compared to Olympic Mountain events because of lower wind speeds. Olympic Mountain events have lower IVT compared to events with extreme precipitation in both regions, but in this case, the difference is due to lower IWV and more southerly winds. These differences in the large-scale conditions promote differences in the mesoscale mechanisms that enhance precipitation in each location. For Puget Sound events, static stability is higher, and there is a weak rain shadow. For Olympic Mountain events, static stability is lower, and a strong rain shadow is present. During extreme events in both regions, orographic modulation is minimized and large-scale effects dominate.

Quantifying the added value of downscaling in extreme precipitation attribution

2020 ◽  
Author(s):  
Jonathan Eden ◽  
Bastien Dieppois
Keyword(s):  
Climate Change ◽  
Global Warming ◽  
Bias Correction ◽  
Extreme Precipitation ◽  
General Circulation ◽  
Regional Climate ◽  
Precipitation Event ◽  
Extreme Precipitation Events ◽  
Statistical Correction ◽  
Precipitation Events

<p>While there is a discernible global warming fingerprint in the increase observed daily temperature extremes, there is far greater uncertainty of the role played by anthropogenic climate change with regard to extreme precipitation. A logical progression of thought is that an increase in extreme precipitation results from the 7% increase in atmospheric moisture per 1°C global temperature increase predicted by the Clausius-Clapeyron (CC) relation.  While this is supported by observations on the global scale, rates of extreme precipitation at smaller spatial and temporal scales are influenced to a far greater extent by atmospheric circulation and vertical stability in addition to local moisture availability. Many of these processes and other features of extreme precipitation events are not sufficiently represented in general circulation model (GCM) simulations. Meanwhile, limited observational networks mean that many short-term convective events are not accurately represented in the observational data.  </p><p>Errors and biases are common to all global and regional climate models, and many users of climate information require some form of statistical correction to improve the usefulness of model output. As so-called bias correction has become commonplace in climate impact research, its development has been hastened by a sustained debate regarding model correction in general leading to techniques that merge statistical correction and downscaling, represent random variability using stochasticity and are explicitly applicable to extremes. To date, attribution of extreme precipitation has not fully utilised the tools available from recent advances in bias correction, stochastic postprocessing and statistical downscaling. In the same way that GCMs are the most important tool in making climate change projections, understanding the degree to which the nature of a particular weather event has changed due to global warming requires long-term simulations of global climate from the pre-industrial era to the present day.  The lack of a correction and/or downscaling step in almost all precipitation event attribution methodologies is therefore surprising. </p><p>Here, we present a multi-scale attribution analysis of a sample of extreme precipitation events across Europe using a blend of observation- and model-based data. Attribution information generated using the raw output of global and regional climate model ensembles will be compared to that generated using the same set of models following a statistical postprocessing and downscaling step. Our conclusions will make recommendations for the value and wider application of downscaling methodologies in attribution science.</p>

scholarly journals Evaluation of uncertainties in mean and extreme precipitation under climate changes for northwestern Mediterranean watersheds from high-resolution Med and Euro-CORDEX ensembles

2017 ◽  
Author(s):  
Antoine Colmet-Daage ◽  
Emilia Sanchez-Gomez ◽  
Sophie Ricci ◽  
Cécile Llovel ◽  
Valérie Borrell Estupina ◽  
...  
Keyword(s):  
High Resolution ◽  
Extreme Precipitation ◽  
Climate Models ◽  
Regional Climate ◽  
Regional Climate Models ◽  
Mountainous Regions ◽  
Extreme Precipitation Events ◽  
Change Impact ◽  
Model Precipitation ◽  
Precipitation Events

Abstract. The climate change impact on mean and extreme precipitation events in the northern Mediterranean region is assessed over high resolution EuroCORDEX and MedCORDEX simulations. The focus is made on three regions, the Lez and the Aude located in France, and the Muga, located in northeastern Spain and eight pairs of global and regional climate models are analyzed with respect to the SAFRAN product. First the model skills are evaluated in terms of bias for the precipitation annual cycle over past period. Then future changes in extreme precipitation, under two emission scenarios, are estimated through the computation of past/future change coefficients of quantile-ranked model precipitation outputs. Over past period, the cumulative precipitation is overestimated for most models over the mountainous regions and underestimated over the coastal regions in autumn and higher order quantile. The ensemble mean and the spread for future period remain unchanged under RCP4.5 scenario and decrease under RCP8.5 scenario. Extreme precipitation events are intensified over the three catchments with a smaller ensemble spread under RCP8.5 revealing more evident changes, especially in the last part of the 21th century.

scholarly journals Falling Trend of Western Disturbances in Future Climate Simulations

2019 ◽  
Vol 32 (16) ◽  
pp. 5037-5051 ◽  
Author(s):  
Kieran M. R. Hunt ◽  
Andrew G. Turner ◽  
Len C. Shaffrey
Keyword(s):  
Extreme Precipitation ◽  
Meridional Wind ◽  
Winter Precipitation ◽  
Future Climate ◽  
Northern India ◽  
Western Disturbances ◽  
Extreme Precipitation Events ◽  
Climate Simulations ◽  
The Impact ◽  
Precipitation Events

Abstract Western disturbances (WDs) are synoptic-scale cyclonic weather systems advected over Pakistan and northern India by the subtropical westerly jet stream. There, they are responsible for most of the winter precipitation, which is crucial for agriculture of the rabi crop as well for as more extreme precipitation events, which can lead to local flooding and avalanches. Despite their importance, there has not yet been an attempt to objectively determine the fate of WDs in future climate GCMs. Here, a tracking algorithm is used to build up a catalog of WDs in both CMIP5 historical and representative concentration pathway (RCP) experiments of the future. It is shown that in business-as-usual (RCP8.5) future climate simulations, WD frequency falls by around 15% by the end of the twenty-first century, with the largest relative changes coming in pre- and postmonsoon months. Meanwhile, mean WD intensity will decrease, with central vorticity expected to become less cyclonic by about 12% over the same period. Changes in WD frequency are attributed to the projected widening and weakening of the winter subtropical jet as well as decreasing meridional wind shear and midtropospheric baroclinic vorticity tendency, which also explain the changes in intensity. The impact of these changes on regional precipitation is explored. The decline in WD frequency and intensity will cause a decrease in mean winter rainfall over Pakistan and northern India amounting to about 15% of the mean—subject to the ability of the models to represent the responsible processes. The effect on extreme precipitation events, however, remains unclear.

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