Hydrometeorological Extremes in a Warmer Climate: A Local Scale Assessment for the Island of Crete

A future warmer atmosphere indicates that precipitation will increase as a consequence of the higher humidity concentrations. According to the Clausius–Clapeyron relationship, precipitation increases by a factor of 7% per degree of warming. However, recent studies have shown that increase in precipitation extremes can exceed this scaling rate. In this regard, we focus on the flash flood prone area of Crete by analyzing high resolution precipitation records form a dense network of meteorological stations to see if the relationship of precipitation and dew point temperature lies within the Clausius–Clapeyron theory. We then use simulation outputs of a “present day event” from a set of very high resolution (about 2 km grid spacing) convective permitting regional climate models (CPRCM) to investigate if the models are able to capture intense convection and thus accurately simulate extreme precipitation events over Crete. A second set of simulations for the present day event, but with a perturbation of +2 °C, is used to examine intensity changes and to see what similar events might look like in a future weather. We finally focus on a high impact flash flood event that occurred on 17 October 2006, and we study changes in hydrological impacts. Information developed in this study can advance local scale knowledge in the context of climate change adaptation and appropriate risk management.

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

Hydrology and Earth System Sciences ◽

10.5194/hess-22-673-2018 ◽

2018 ◽

Vol 22 (1) ◽

pp. 673-687 ◽

Cited By ~ 10

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.

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

10.5194/hess-2017-49 ◽

2017 ◽

Cited By ~ 2

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.

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Antarctic ice shelf thickness change from multimission lidar mapping

The Cryosphere ◽

10.5194/tc-13-1801-2019 ◽

2019 ◽

Vol 13 (7) ◽

pp. 1801-1817 ◽

Cited By ~ 2

Author(s):

Tyler C. Sutterley ◽

Thorsten Markus ◽

Thomas A. Neumann ◽

Michiel van den Broeke ◽

J. Melchior van Wessem ◽

...

Keyword(s):

High Resolution ◽

Climate Models ◽

Regional Climate ◽

Regional Climate Models ◽

Surface Velocity ◽

Ice Thickness ◽

Flux Divergence ◽

Ice Shelf ◽

Thickness Change ◽

Ice Shelves

Abstract. We calculate rates of ice thickness change and bottom melt for ice shelves in West Antarctica and the Antarctic Peninsula from a combination of elevation measurements from NASA–CECS Antarctic ice mapping campaigns and NASA Operation IceBridge corrected for oceanic processes from measurements and models, surface velocity measurements from synthetic aperture radar, and high-resolution outputs from regional climate models. The ice thickness change rates are calculated in a Lagrangian reference frame to reduce the effects from advection of sharp vertical features, such as cracks and crevasses, that can saturate Eulerian-derived estimates. We use our method over different ice shelves in Antarctica, which vary in terms of size, repeat coverage from airborne altimetry, and dominant processes governing their recent changes. We find that the Larsen-C Ice Shelf is close to steady state over our observation period with spatial variations in ice thickness largely due to the flux divergence of the shelf. Firn and surface processes are responsible for some short-term variability in ice thickness of the Larsen-C Ice Shelf over the time period. The Wilkins Ice Shelf is sensitive to short-timescale coastal and upper-ocean processes, and basal melt is the dominant contributor to the ice thickness change over the period. At the Pine Island Ice Shelf in the critical region near the grounding zone, we find that ice shelf thickness change rates exceed 40 m yr−1, with the change dominated by strong submarine melting. Regions near the grounding zones of the Dotson and Crosson ice shelves are decreasing in thickness at rates greater than 40 m yr−1, also due to intense basal melt. NASA–CECS Antarctic ice mapping and NASA Operation IceBridge campaigns provide validation datasets for floating ice shelves at moderately high resolution when coregistered using Lagrangian methods.

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New Approach for Bias Correction and Stochastic Downscaling of Future Projections for Daily Mean Temperatures to a High-Resolution Grid

Journal of Applied Meteorology and Climatology ◽

10.1175/jamc-d-19-0086.1 ◽

2019 ◽

Vol 58 (12) ◽

pp. 2617-2632 ◽

Cited By ~ 1

Author(s):

Qifen Yuan ◽

Thordis L. Thorarinsdottir ◽

Stein Beldring ◽

Wai Kwok Wong ◽

Shaochun Huang ◽

...

Keyword(s):

High Resolution ◽

Bias Correction ◽

Climate Models ◽

Regional Climate ◽

Regional Climate Models ◽

Climate Change Signal ◽

Climate Projections ◽

Data Product ◽

Temporal Features ◽

Stochastic Downscaling

AbstractIn applications of climate information, coarse-resolution climate projections commonly need to be downscaled to a finer grid. One challenge of this requirement is the modeling of subgrid variability and the spatial and temporal dependence at the finer scale. Here, a postprocessing procedure for temperature projections is proposed that addresses this challenge. The procedure employs statistical bias correction and stochastic downscaling in two steps. In the first step, errors that are related to spatial and temporal features of the first two moments of the temperature distribution at model scale are identified and corrected. Second, residual space–time dependence at the finer scale is analyzed using a statistical model, from which realizations are generated and then combined with an appropriate climate change signal to form the downscaled projection fields. Using a high-resolution observational gridded data product, the proposed approach is applied in a case study in which projections of two regional climate models from the Coordinated Downscaling Experiment–European Domain (EURO-CORDEX) ensemble are bias corrected and downscaled to a 1 km × 1 km grid in the Trøndelag area of Norway. A cross-validation study shows that the proposed procedure generates results that better reflect the marginal distributional properties of the data product and have better consistency in space and time when compared with empirical quantile mapping.

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Using convection-permitting climate models and a high-resolution distributed hydrological model to assess future changes in Alpine flash floods.

10.5194/egusphere-egu21-11484 ◽

2021 ◽

Author(s):

Marjanne Zander ◽

Pety Viguurs ◽

Frederiek Sperna Weiland ◽

Albrecht Weerts

Keyword(s):

High Resolution ◽

Natural Hazards ◽

Climate Models ◽

Flash Flood ◽

Regional Climate ◽

Flash Floods ◽

Flood Frequency ◽

Climate Dynamics ◽

Future Climate ◽

European Climate

Flash Floods are damaging natural hazards which often occur in the European Alps. Precipitation patterns and intensity may change in a future climate affecting their occurrence and magnitude. For impact studies, flash floods can be difficult to simulate due the complex orography and limited extent & duration of the heavy rainfall events which trigger them. The new generation convection-permitting regional climate models improve the intensity and frequency of heavy precipitation (Ban et al., 2021).Therefore, this study combines such simulations with high-resolution distributed hydrological modelling to assess changes in flash flood frequency and occurrence over the Alpine terrain. We use the state-of-the-art Unified Model (Berthou et al., 2018) to drive a high-resolution distributed hydrological wflow_sbm model (e.g. Imhoff et al., 2020) covering most of the Alpine mountain range on an hourly resolution. Simulations of the future climate RCP 8.5 for the end-of-century (2096-2105) and current climate (1998-2007) are compared.First, the wflow_sbm model was validated by comparing ERA5 driven simulation with streamflow observations (across Rhone, Rhine, Po, Adige and Danube). Second, the wflow_sbm simulation driven by UM simulation of the current climate was compared to a dataset of historical flood occurrences (Paprotny et al., 2018, Earth Syst. Sci. Data) to validate if the model can accurately simulate the location of the flash floods and to determine a suitable threshold for flash flooding. Finally, the future run was used to asses changes in flash flood frequency and occurrence. Results show an increase in flash flood frequency for the Upper Rhine and Adige catchments. For the Rhone the increase was less pronounced. The locations where the flash floods occur did not change much.This research is embedded in the EU H2020 project EUCP (EUropean Climate Prediction system) (https://www.eucp-project.eu/), which aims to support climate adaptation and mitigation decisions for the coming decades by developing a regional climate prediction and projection system based on high-resolution climate models for Europe.&#160;N. Ban, E. Brisson, C. Caillaud, E. Coppola, E. Pichelli, S. Sobolowski, &#8230;, M.J. Zander (2021): &#8220;The first multi-model ensemble of regional climate simulations at the kilometer-scale resolution, Part I: Evaluation of precipitation&#8221;, manuscript accepted for publication in Climate Dynamics.S. Berthou, E.J. Kendon, S. C. Chan, N. Ban, D. Leutwyler, C. Sch&#228;r, and G. Fosser, 2018, &#8220;Pan-european climate at convection-permitting scale: a model intercomparison study.&#8221; Climate Dynamics, pages 1&#8211;25, DOI: 10.1007/s00382-018-4114-6Imhoff, R.O., W. van Verseveld, B. van Osnabrugge, A.H. Weerts, 2020. &#8220;Scaling point-scale pedotransfer functions parameter estimates for seamless large-domain high-resolution distributed hydrological modelling: An example for the Rhine river.&#8221; Water Resources Research, 56. Doi: 10.1029/2019WR026807Paprotny, D., Morales Napoles, O., & Jonkman, S. N., 2018. "HANZE: a pan-European database of exposure to natural hazards and damaging historical floods since 1870". Earth System Science Data, 10, 565&#8211;581, https://doi.org/10.5194/essd-10-565-2018

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Using high-resolution regional climate models to estimate return levels of daily extreme precipitation over Bavaria

Natural Hazards and Earth System Science ◽

10.5194/nhess-21-3573-2021 ◽

2021 ◽

Vol 21 (11) ◽

pp. 3573-3598

Author(s):

Benjamin Poschlod

Keyword(s):

High Resolution ◽

Climate Models ◽

Regional Climate ◽

Daily Rainfall ◽

Regional Climate Models ◽

Reanalysis Data ◽

Extreme Value ◽

Return Level ◽

Gev Distribution ◽

Return Levels

Abstract. Extreme daily rainfall is an important trigger for floods in Bavaria. The dimensioning of water management structures as well as building codes is based on observational rainfall return levels. In this study, three high-resolution regional climate models (RCMs) are employed to produce 10- and 100-year daily rainfall return levels and their performance is evaluated by comparison to observational return levels. The study area is governed by different types of precipitation (stratiform, orographic, convectional) and a complex terrain, with convective precipitation also contributing to daily rainfall levels. The Canadian Regional Climate Model version 5 (CRCM5) at a 12 km spatial resolution and the Weather and Forecasting Research (WRF) model at a 5 km resolution both driven by ERA-Interim reanalysis data use parametrization schemes to simulate convection. WRF at a 1.5 km resolution driven by ERA5 reanalysis data explicitly resolves convectional processes. Applying the generalized extreme value (GEV) distribution, the CRCM5 setup can reproduce the observational 10-year return levels with an areal average bias of +6.6 % and a spatial Spearman rank correlation of ρ=0.72. The higher-resolution 5 km WRF setup is found to improve the performance in terms of bias (+4.7 %) and spatial correlation (ρ=0.82). However, the finer topographic details of the WRF-ERA5 return levels cannot be evaluated with the observation data because their spatial resolution is too low. Hence, this comparison shows no further improvement in the spatial correlation (ρ=0.82) but a small improvement in the bias (2.7 %) compared to the 5 km resolution setup. Uncertainties due to extreme value theory are explored by employing three further approaches. Applied to the WRF-ERA5 data, the GEV distributions with a fixed shape parameter (bias is +2.5 %; ρ=0.79) and the generalized Pareto (GP) distributions (bias is +2.9 %; ρ=0.81) show almost equivalent results for the 10-year return period, whereas the metastatistical extreme value (MEV) distribution leads to a slight underestimation (bias is −7.8 %; ρ=0.84). For the 100-year return level, however, the MEV distribution (bias is +2.7 %; ρ=0.73) outperforms the GEV distribution (bias is +13.3 %; ρ=0.66), the GEV distribution with fixed shape parameter (bias is +12.9 %; ρ=0.70), and the GP distribution (bias is +11.9 %; ρ=0.63). Hence, for applications where the return period is extrapolated, the MEV framework is recommended. From these results, it follows that high-resolution regional climate models are suitable for generating spatially homogeneous rainfall return level products. In regions with a sparse rain gauge density or low spatial representativeness of the stations due to complex topography, RCMs can support the observational data. Further, RCMs driven by global climate models with emission scenarios can project climate-change-induced alterations in rainfall return levels at regional to local scales. This can allow adjustment of structural design and, therefore, adaption to future precipitation conditions.

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