scholarly journals Robustness of Future Changes in Local Precipitation Extremes

2008 ◽  
Vol 21 (17) ◽  
pp. 4280-4297 ◽  
Author(s):  
Elizabeth J. Kendon ◽  
David P. Rowell ◽  
Richard G. Jones ◽  
Erasmo Buonomo

Abstract Reliable projections of future changes in local precipitation extremes are essential for informing policy decisions regarding mitigation and adaptation to climate change. In this paper, the extent to which the natural variability of the climate affects one’s ability to project the anthropogenically forced component of change in daily precipitation extremes across Europe is examined. A three-member ensemble of the Hadley Centre Regional Climate Model (HadRM3H) is used and a statistical framework is applied to estimate the uncertainty due to the full spectrum of climate variability. In particular, the results and understanding presented here suggest that annual to multidecadal natural variability may contribute significant uncertainty. For this ensemble projection, extreme precipitation changes at the grid-box level are found to be discernible above climate noise over much of northern and central Europe in winter, and parts of northern and southern Europe in summer. The ability to quantify the change to a reasonable level of accuracy is largely limited to regions in northern Europe. In general, where climate noise has a significant component varying on decadal time scales, single 30-yr climate change projections are insufficient to infer changes in the extreme tail of the underlying precipitation distribution. In this context, the need for ensembles of integrations is demonstrated and the relative effectiveness of spatial pooling and averaging for generating robust signals of extreme precipitation change is also explored. The key conclusions are expected to apply more generally to other models and forcing scenarios.

2006 ◽  
Vol 54 (6-7) ◽  
pp. 9-15 ◽  
Author(s):  
M. Grum ◽  
A.T. Jørgensen ◽  
R.M. Johansen ◽  
J.J. Linde

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.


New Medit ◽  
2021 ◽  
Vol 20 (5) ◽  
Author(s):  
Houda Rjili ◽  
Mohamed JAOUAD

Climate change is a global environmental threat to all economic activities, especially the livestock activity. The South of Tunisia, where animal husbandry is a fundamental element of the domestic economy, is more influenced by these negatives effects due to the arid climate. The objective of this study is to identify strategies and levers mitigation and adaptation to climate change developed by breeders on based on available factors. For this purpose, a survey conducted among 73 breeders on the rangelands of El Ouara, in the South of Tunisia. Results emerges that breeders use various adaptation strategies principally, supplementation, integration agriculture-livestock and conduct’s mode through different types such as association. The result of the model reveal that age of breeder, herd size, agricultural area, member of an association, subsidies and well ownerships are the most factors which significantly influence the adaptation choices of breeders to cope to climate change. The results proved too that adaptation to climate change was inhibited by many factors such as luck of workforce labor, lack of water and financial resources as well the degradation of the rangelands.


Water ◽  
2020 ◽  
Vol 12 (10) ◽  
pp. 2784 ◽  
Author(s):  
Wenping Xu ◽  
Lingli Xiang ◽  
David Proverbs

While various measures of mitigation and adaptation to climate change have been taken in recent years, many have gradually reached a consensus that building community resilience is of great significance when responding to climate change, especially urban flooding. There has been a dearth of research on community resilience to urban floods, especially among transient communities, and therefore there is a need to conduct further empirical studies to improve our understanding, and to identify appropriate interventions. Thus, this work combines two existing resilience assessment frameworks to address these issues in three different types of transient community, namely an urban village, commercial housing, and apartments, all located in Wuhan, China. An analytic hierarchy process–back propagation neural network (AHP-BP) model was developed to estimate the community resilience within these three transient communities. The effects of changes in the prioritization of key resilience indicators under different environmental, economic, and social factors was analyzed across the three communities. The results demonstrate that the ranking of the indicators reflects the connection between disaster resilience and the evaluation units of diverse transient communities. These aspects show the differences in the disaster resilience of different types of transient communities. The proposed method can help decision makers in identifying the areas that are lagging behind, and those that need to be prioritized when allocating limited and/or stretched resources.


Water ◽  
2019 ◽  
Vol 11 (3) ◽  
pp. 587 ◽  
Author(s):  
Evdokia Tapoglou ◽  
Anthi Vozinaki ◽  
Ioannis Tsanis

Frequency analysis on extreme hydrological and meteorological events under the effect of climate change is performed in the island of Crete. Data from Regional Climate Model simulations (RCMs) that follow three Representative Concentration Pathways (RCP2.6, RCP4.5, RCP8.5) are used in the analysis. The analysis was performed for the 1985–2100 time period, divided into three equal-duration time slices (1985–2010, 2025–2050, and 2075–2100). Comparison between the results from the three time slices for the different RCMs under different RCP scenarios indicate that drought events are expected to increase in the future. The meteorological and hydrological drought indices, relative Standardized Precipitation Index (SPI) and Standardized Runoff index (SRI), are used to identify the number of drought events for each RCM. Results from extreme precipitation, extreme flow, meteorological and hydrological drought frequency analysis over Crete show that the impact of climate change on the magnitude of 100 years return period extreme events will also increase, along with the magnitude of extreme precipitation and flow events.


2020 ◽  
Author(s):  
Erika Toivonen ◽  
Danijel Belušić ◽  
Emma Dybro Thomassen ◽  
Peter Berg ◽  
Ole Bøssing Christensen ◽  
...  

<p>Extreme precipitation events have a major impact upon our society. Although many studies have indicated that it is likely that the frequency of such events will increase in a warmer climate, little has been done to assess changes in extreme precipitation at a sub-daily scale. Recently, there is more and more evidence that <span>high-resolution convection-permitting models </span><span>(CPMs)</span> (grid-mesh typically < 4 km) can represent especially short-duration precipitation extremes more accurately when compared with coarser-resolution <span>regional climate model</span><span>s </span><span>(RCMs)</span><span>.</span></p><p>This study investigates sub-daily and daily precipitation characteristics based on hourly <span>output data from the HARMONIE-Climate model </span>at 3-km and 12-km grid-mesh resolution over the Nordic region between 1998 and 2018. The RCM modelling chain uses the ERA-Interim reanalysis to drive a 12-km grid-mesh simulation which is further downscaled to 3-km grid-mesh resolution using a non-hydrostatic model set-up.</p><p>The statistical properties of the modeled extreme precipitation are compared to several sub-daily and daily observational products, including gridded and in-situ gauge data, from April to September. We investigate the skill of the model to represent different aspects of the frequency and intensity of extreme precipitation as well as intensity–duration–frequency (IDF) curves that are commonly used to investigate short duration extremes from an urban planning perspective. The high grid resolution combined with the 20-year-long simulation period allows for a robust assessment at a climatological time scale <span>and enables us to examine the added value of high-resolution </span><span>CPM</span><span> in reproducing precipitation extremes over the Nordic </span><span>region</span><span>. </span><span>Based on the tentative results, the high-resolution CPM can realistically capture the </span><span>characteristics </span><span>of precipitation extremes, </span><span>for instance, </span><span>in terms of improved diurnal cycle and maximum intensities of sub-daily precipitation.</span></p>


2020 ◽  
Author(s):  
Andrew Williams ◽  
Paul O'Gorman

<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>


Sign in / Sign up

Export Citation Format

Share Document