scholarly journals Regional Climate Sensitivity of Climate Extremes in CMIP6 Versus CMIP5 Multimodel Ensembles

2020 ◽  
Vol 8 (9) ◽  
Author(s):  
Sonia I. Seneviratne ◽  
Mathias Hauser
2015 ◽  
Vol 46 (7-8) ◽  
pp. 2469-2486 ◽  
Author(s):  
Changyong Park ◽  
Seung-Ki Min ◽  
Donghyun Lee ◽  
Dong-Hyun Cha ◽  
Myoung-Seok Suh ◽  
...  

2015 ◽  
Vol 28 (15) ◽  
pp. 6249-6266 ◽  
Author(s):  
Christian Kerkhoff ◽  
Hans R. Künsch ◽  
Christoph Schär

Abstract A Bayesian hierarchical model for heterogeneous multimodel ensembles of global and regional climate models is presented. By applying the methodology herein to regional and seasonal temperature averages from the ENSEMBLES project, probabilistic projections of future climate are derived. Intermodel correlations that are particularly strong between regional climate models and their driving global climate models are explicitly accounted for. Instead of working with time slices, a data archive is investigated in a transient setting. This enables a coherent treatment of internal variability on multidecadal time scales. Results are presented for four European regions to highlight the feasibility of the approach. In particular, the methodology is able to objectively identify patterns of variability changes, in ways that previously required subjective expert knowledge. Furthermore, this study underlines that assumptions about bias changes have an effect on the projected warming. It is also shown that validating the out-of-sample predictive performance is possible on short-term prediction horizons and that the hierarchical model herein is competitive. Additionally, the findings indicate that instead of running a large suite of regional climate models all forced by the same driver, priority should be given to a rich diversity of global climate models that force a number of regional climate models in the experimental design of future multimodel ensembles.


Author(s):  
Pietro Croce ◽  
Paolo Formichi ◽  
Filippo Landi ◽  
Francesca Marsili

<p>As consequence of global warming extreme weather events might become more frequent and severe across the globe. The evaluation of the impact of climate change on extremes is then a crucial issue for the resilience of infrastructures and buildings and is a key challenge for adaptation planning. In this paper, a suitable procedure for the estimation of future trends of climatic actions is presented starting from the output of regional climate models and taking into account the uncertainty in the model itself. In particular, the influence of climate change on ground snow loads is discussed in detail and the typical uncertainty range is determined applying an innovative algorithm for weather generation. Considering different greenhouse gasses emission scenarios, some results are presented for the Italian Mediterranean region proving the ability of the method to define factors of change for climate extremes also allowing a sound estimate of the uncertainty range associated with different models.</p>


2015 ◽  
Vol 54 (2) ◽  
pp. 370-394 ◽  
Author(s):  
Julia Andrys ◽  
Thomas J. Lyons ◽  
Jatin Kala

AbstractThe authors evaluate a 30-yr (1981–2010) Weather Research and Forecast (WRF) Model regional climate simulation over the southwest of Western Australia (SWWA), a region with a Mediterranean climate, using ERA-Interim boundary conditions. The analysis assesses the spatial and temporal characteristics of climate extremes, using a selection of climate indices, with an emphasis on metrics that are relevant for forestry and agricultural applications. Two nested domains at 10- and 5-km resolution are examined, with the higher-resolution simulation resolving convection explicitly. Simulation results are compared with a high-resolution, gridded observational dataset that provides daily rainfall, minimum temperatures, and maximum temperatures. Results show that, at both resolutions, the model is able to simulate the daily, seasonal, and annual variation of temperature and precipitation well, including extreme events. The higher-resolution domain displayed significant performance gains in simulating dry-season convective precipitation, rainfall around complex terrain, and the spatial distribution of frost conditions. The high-resolution domain was, however, influenced by grid-edge effects in the southwestern margin, which reduced the ability of the domain to represent frontal rainfall along the coastal region. On the basis of these results, the authors feel confident in using the WRF Model for regional climate simulations for the SWWA, including studies that focus on the spatial and temporal representation of climate extremes. This study provides a baseline climatological description at a high resolution that can be used for impact studies and will also provide a benchmark for climate simulations driven by general circulation models.


Atmosphere ◽  
2019 ◽  
Vol 10 (11) ◽  
pp. 675 ◽  
Author(s):  
Almazroui

This paper investigates the temperature and precipitation extremes over the Arabian Peninsula using data from the regional climate model RegCM4 forced by three Coupled Model Intercomparison Project Phase 5 (CMIP5) models and ERA–Interim reanalysis data. Indices of extremes are calculated using daily temperature and precipitation data at 27 meteorological stations located across Saudi Arabia in line with the suggested procedure from the Expert Team on Climate Change Detection and Indices (ETCCDI) for the present climate (1986–2005) using 1981–2000 as the reference period. The results show that RegCM4 accurately captures the main features of temperature extremes found in surface observations. The results also show that RegCM4 with the CLM land–surface scheme performs better in the simulation of precipitation and minimum temperature, while the BATS scheme is better than CLM in simulating maximum temperature. Among the three CMIP5 models, the two best performing models are found to accurately reproduce the observations in calculating the extreme indices, while the other is not so successful. The reason for the good performance by these two models is that they successfully capture the circulation patterns and the humidity fields, which in turn influence the temperature and precipitation patterns that determine the extremes over the study region.


2017 ◽  
Author(s):  
Richard Wartenburger ◽  
Martin Hirschi ◽  
Markus G. Donat ◽  
Peter Greve ◽  
Andy J. Pitman ◽  
...  

Abstract. This article extends a previous study (Seneviratne et al., 2016) to provide regional analyses of changes in climate extremes as a function of projected changes in global mean temperature. We introduce the DROUGHT-HEAT Regional Climate Atlas, an interactive tool to analyse and display a range of well-established climate extremes and water-cycle indices and their changes as a function of global warming. These projections are based on simulations from the 5th phase of the Coupled Model Intercomparison Project (CMIP5). A selection of example results are presented here, but users can visualize specific indices of interest using the online tool. This implementation enables a direct assessment of regional climate changes associated with global temperature targets, such as the 2 degree and 1.5 degree limits agreed within the 2015 Paris Agreement.


2020 ◽  
Author(s):  
Tugba Ozturk ◽  
Dominic Matte ◽  
Jens Hesselbjerg Christensen

&lt;p&gt;&lt;span lang=&quot;EN-US&quot;&gt;The occurrence of extreme weather events and climate extremes over Europe and the Mediterranean region are believed to be associated with changes and variability in the mid-latitude atmospheric circulation. CMIP5 models exhibits a substantial decrease in mid-latitude mean storm track activity for summer under climate change for a variety of scenarios. In this work, we aim to investigate future change in summer circulation and its implication for summer temperature and precipitation extremes over Europe particularly focusing on the Southeastern Mediterranean. EURO-CORDEX regional climate projections at 0.11&amp;#176; grid-mesh are used to analyze future climate projections addressing climate warming targets of 1&amp;#176;C, 2&amp;#176;C and 3&amp;#176;C, respectively. Simple scaling with the global mean temperature change is applied to the regional climate projections for the variables in concern in order to provide robust signals not to be dependent on climate sensitivity. Our focus in this study is on monthly mean geopotential height, winds at mid- and lower-troposphere as indicators of the simulated circulation changes.&lt;/span&gt;&lt;/p&gt;


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