scholarly journals Which Temperature and Precipitation Extremes Best Explain the Variation of Warm versus Cold Years and Wet versus Dry Years?

2017 ◽  
Vol 31 (1) ◽  
pp. 45-59 ◽  
Author(s):  
Jian-Sheng Ye ◽  
Yan-Hong Gong ◽  
Feng Zhang ◽  
Jiao Ren ◽  
Xiao-Ke Bai ◽  
...  
Keyword(s):  
Climate Change ◽  
Climate Model ◽  
Extreme Temperature ◽  
Climate Extremes ◽  
Heavy Precipitation ◽  
Ecosystem Response ◽  
Temperature And Precipitation ◽  
Extreme Cold ◽  
Precipitation Records ◽  
Precipitation Events

Abstract Intensifying climate extremes are one of the major concerns with climate change. Using 100-yr (1911–2010) daily temperature and precipitation records worldwide, 28 indices of extreme temperature and precipitation are calculated. A similarity percentage analysis is used to identify the key indices for distinguishing how extreme warm and cold years (annual temperature above the 90th and below the 10th percentile of the 100-yr distribution, respectively) differ from one another and from average years, and how extreme wet and dry years (annual precipitation above the 90th and below the 10th percentile of the 100-yr distribution, respectively) differ from each other and from average years. The analysis suggests that extreme warm years are primarily distinguished from average and extreme cold years by higher occurrence of warm nights (annual counts when night temperature >90th percentile), which occur about six more counts in extreme warm years compared with average years. Extreme wet years are mainly distinguished from average and extreme dry years by more occurrences of heavy precipitation events (events with ≥10 mm and ≥20 mm precipitation). Compared with average years, heavy events occur 60% more in extreme wet years and 50% less in extreme dry years. These indices consistently differ between extreme and average years across terrestrial ecoregions globally. These key indices need to be considered when analyzing climate model projections and designing climate change experiments that focus on ecosystem response to climate extremes.

Signals of Climate Change and Spatio-temporal Analysis of Climate Extremes in the Homogeneous Climatic Zones of Pakistan During 1962-2019

2021 ◽  
Author(s):  
Firdos Khan ◽  
Shaukat Ali ◽  
Christoph Mayer ◽  
Hamd Ullah ◽  
Sher Muhammad
Keyword(s):  
Climate Change ◽  
Climate Extremes ◽  
Heavy Precipitation ◽  
Temporal Analysis ◽  
Significance Level ◽  
Temperature And Precipitation ◽  
Increasing Trend ◽  
North Pakistan ◽  
Spatio Temporal ◽  
Increasing Temperature

Abstract This study investigates contemporary climate change and spatio-temporal analysis of climate extremes in Pakistan (divided into five homogenous climate zones) using observed data, categorized between 1962–1990 and 1991–2019. The results show that on the average, the changes in temperature and precipitation are significant at 5 % significance level throughout Pakistan in most of the seasons. The spatio-temporal trend analysis of consecutive dry days (CDD) shows an increasing trend during 1991–2019 except in zone 4 indicating throughout decreasing trend. PRCPTOT (annual total wet-day precipitation), R10 (number of heavy precipitation days), R20 (number of very heavy precipitation days) and R25mm (extremely heavy precipitation days) are significantly decreasing (increasing) during 1962–1990 (1991–2019) in North Pakistan. Summer days (SU25) increased across the country, except in zone 4 with a decrease. TX10p (Cool days) decreased across the country except an increase in zone 1 and zone 2 during 1962–1990. TX90p (Warm days) has an increasing trend during 1991–2019 except zone 5 and decreasing trend during 1962–1990 except zone 2 and 5. The Mann-Kendal test indicates increasing precipitation (DJF) and decreasing maximum and minimum temperature (JJA) in the Karakoram region during 1962–1990. The decadal analysis suggests decreasing precipitation during 1991–2019 and increasing temperature (maximum and minimum) during 2010–2019 which is in line with the recently confirmed slight mass loss of glaciers against Karakoram Anomaly.

scholarly journals The risks of warm nights and wet days in the context of climate change: assessing road safety outcomes in Boston, USA and Santo Domingo, Dominican Republic

2021 ◽  
Vol 8 (1) ◽  
Author(s):  
José Ignacio Nazif-Munoz ◽  
Pablo Martínez ◽  
Augusta Williams ◽  
John Spengler
Keyword(s):  
Climate Change ◽  
Dominican Republic ◽  
Road Safety ◽  
Warm Season ◽  
Weather Conditions ◽  
Heavy Precipitation ◽  
Traffic Fatalities ◽  
Santo Domingo ◽  
Temperature And Precipitation ◽  
Precipitation Events

Abstract Background There remains a dearth of cross-city comparisons on the impact of climate change through extreme temperature and precipitation events on road safety. We examined trends in traffic fatalities, injuries and property damage associated with high temperatures and heavy rains in Boston (USA) and Santo Domingo (Dominican Republic). Methods Official publicly available data on daily traffic outcomes and weather conditions during the warm season (May to September) were used for Boston (2002–2015) and Santo Domingo (2013–2017). Daily maximum temperatures and mean precipitations for each city were considered for classifying hot days, warm days, and warm nights, and wet, very wet, and extremely wet days. Time-series analyses were used to assess the relationship between temperature and precipitation and daily traffic outcomes, using a quasi-Poisson regression. Results In Santo Domingo, the presence of a warm night increased traffic fatalities with a rate ratio (RR) of 1.31 (95% CI [confidence interval]: 1.00,1.71). In Boston, precipitation factors (particularly, extremely wet days) were associated with increments in traffic injuries (RR 1.25, 95% CI: 1.18, 1.32) and property damages (RR 1.42, 95% CI: 1.33, 1.51). Conclusion During the warm season, mixed associations between weather conditions and traffic outcomes were found across Santo Domingo and Boston. In Boston, increases in heavy precipitation events were associated with higher traffic injuries and property damage. As climate change-related heavy precipitation events are projected to increase in the USA, the associations found in this study should be of interest for road safety planning in a rapidly changing environment.

scholarly journals Changes in the Risk of Extreme Climate Events over East Asia at Different Global Warming Levels

Water ◽  
2019 ◽  
Vol 11 (12) ◽  
pp. 2535
Author(s):  
Jintao Zhang ◽  
Fang Wang
Keyword(s):  
Global Warming ◽  
East Asia ◽  
Cost Benefit Analysis ◽  
Extreme Temperature ◽  
Coupled Model ◽  
Cost Benefit ◽  
Climate Extremes ◽  
Heavy Precipitation ◽  
Mitigation Measures ◽  
Temperature And Precipitation

Limiting the global temperature increase to a level that would prevent “dangerous anthropogenic interference with the climate system” is the focus of intergovernmental climate negotiations, and the cost-benefit analysis to determine this level requires an understanding of how the risk associated with climate extremes varies with different warming levels. We examine daily extreme temperature and precipitation variances with continuous global warming using a non-stationary extreme value statistical model based on the Coupled Model Intercomparison Project Phase 5 (CMIP5). Our results show the probability of extreme warm and heavy precipitation events over East Asia (EA) will increase, while that of cold extremes over EA will decrease as global warming increases. A present-day 1-in-20-year heavy precipitation extreme in EA is projected to increase to 1.3, 1.6, 2.5, and 3.4 times more frequently of the current climatology, at the global mean warming levels of 1.5 °C, 2 °C, 3 °C, and 4 °C above the preindustrial era, respectively. Moreover, the relative changes in probability are larger for rarer events. These results contribute to an improved understanding of the future risk associated with climate extremes, which helps scientists create mitigation measures for global warming and facilitates policy-making.

scholarly journals Land surface model influence on the simulated climatologies of temperature and precipitation extremes in the WRF v3.9 model over North America

2020 ◽  
Vol 13 (11) ◽  
pp. 5345-5366
Author(s):  
Almudena García-García ◽  
Francisco José Cuesta-Valero ◽  
Hugo Beltrami ◽  
Fidel González-Rouco ◽  
Elena García-Bustamante ◽  
...  
Keyword(s):  
Land Surface ◽  
Climate Model ◽  
Regional Climate ◽  
Extreme Temperature ◽  
Wrf Model ◽  
Land Surface Model ◽  
Surface Model ◽  
Temperature And Precipitation ◽  
Model Ensembles ◽  
Precipitation Events

Abstract. The representation and projection of extreme temperature and precipitation events in regional and global climate models are of major importance for the study of climate change impacts. However, state-of-the-art global and regional climate model simulations yield a broad inter-model range of intensity, duration and frequency of these extremes. Here, we present a modeling experiment using the Weather Research and Forecasting (WRF) model to determine the influence of the land surface model (LSM) component on uncertainties associated with extreme events. First, we analyze land–atmosphere interactions within four simulations performed by the WRF model from 1980 to 2012 over North America, using three different LSMs. Results show LSM-dependent differences at regional scales in the frequency of occurrence of events when surface conditions are altered by atmospheric forcing or land processes. The inter-model range of extreme statistics across the WRF simulations is large, particularly for indices related to the intensity and duration of temperature and precipitation extremes. Our results show that the WRF simulation of the climatology of heat extremes can be 5 ∘C warmer and 6 d longer depending on the employed LSM component, and similarly for cold extremes and heavy precipitation events. Areas showing large uncertainty in WRF-simulated extreme events are also identified in a model ensemble from three different regional climate model (RCM) simulations participating in the Coordinated Regional Climate Downscaling Experiment (CORDEX) project, revealing the implications of these results for other model ensembles. Thus, studies based on multi-model ensembles and reanalyses should include a variety of LSM configurations to account for the uncertainty arising from this model component or to test the performance of the selected LSM component before running the whole simulation. This study illustrates the importance of the LSM choice in climate simulations, supporting the development of new modeling studies using different LSM components to understand inter-model differences in simulating extreme temperature and precipitation events, which in turn will help to reduce uncertainties in climate model projections.

scholarly journals Atmospheric Rivers in CMIP5 climate ensembles downscaled with a high resolution regional climate model

2021 ◽  
Author(s):  
Matthias Gröger ◽  
Christian Dieterich ◽  
Cyril Dutheil ◽  
Markus Meier ◽  
Dmitry Sein
Keyword(s):  
Climate Change ◽  
Regional Climate Model ◽  
Eastern Europe ◽  
Central Europe ◽  
Climate Model ◽  
Global Climate ◽  
Regional Climate ◽  
Heavy Precipitation ◽  
Atmospheric Rivers ◽  
Precipitation Events

Abstract. Atmospheric rivers (AR) are important drivers of heavy precipitation events in western and central Europe and often associated with intense floods. So far, the ARs response to climate change in Europe has been investigated by global climate models within the CMIP5 framework. However, their spatial resolution between 1 and 3° is too coarse for an adequate assessment of local to regional precipitation patterns. Using a regional climate model with 0.22° resolution we downscale an ensemble of 24 global climate simulations following the greenhouse gas scenarios RCP2.6, RCP4.5, RCP8.5. The performance of the model was tested against ER-I reanalysis data. The downscaled simulation notably better represents small-scale spatial characteristics which is most obvious over the terrain of the Iberian Peninsula where the AR induced precipitation pattern clearly reflect eat-west striking topographical elements resulting in zonal bands of high and low AR impact. Over central Europe the model simulates a less far propagation of ARs toward eastern Europe compared to ERA-I but a higher share of AR forced heavy precipitation events especially Norway where 60 % of annual precipitation maxima are related to ARs. We find ARs more frequent and more intense in a future warmer climate especially in the higher emission scenarios whereas the changes are mostly mitigated under the assumption of RCP2.6. They also propagate further inland to eastern Europe in a warmer climate. In the high emission scenario RCP8.5 AR induced precipitation rates increase between 20 and 40 % in western central Europe while mean precipitation rates increase by maximal 12 %. Over the Iberian Peninsula AR induced precipitation rates slightly decrease around −6 % but mean rates decrease around −15 %. The result of these changes is an overall increased contribution of ARs to heavy precipitation with greatest impact over Iberia (15–30 %). Over Norway average AR precipitation rates decline between −5 to −30 %. These reductions most likely the originate from regional dynamical changes. In fact, over Norway we find ARs originating from > 60° N are reduced by up to 20 % while those originating south of 45° N are increased. Also, no clear climate change signal is seen for AR related heavy precipitation and annual maximum precipitation over Norway where the uncertainty of the ensemble is quite large.

scholarly journals Approaches to attribution of extreme temperature and precipitation events using multi-model and single-member ensembles of general circulation models

2019 ◽  
Vol 5 (2) ◽  
pp. 133-146 ◽  
Author(s):  
Sophie C. Lewis ◽  
Sarah E. Perkins-Kirkpatrick ◽  
Andrew D. King
Keyword(s):  
General Circulation ◽  
Climate Model ◽  
Extreme Event ◽  
Extreme Temperature ◽  
General Circulation Models ◽  
Cmip5 Models ◽  
Spatial And Temporal Scales ◽  
Temperature And Precipitation ◽  
Event Attribution ◽  
Precipitation Events

Abstract. Extreme temperature and precipitation events occurring in Australia in recent decades have caused significant socio-economic and environmental impacts, and thus determining the factors contributing to these extremes is an active area of research. Many recently occurring record-breaking temperature and rainfall events have now been examined from an extreme event attribution (EEA) perspective. This paper describes a set of studies that have examined the causes of extreme climate events using various general circulation models (GCMs), presenting a comprehensive methodology for GCM-based attribution of extremes of temperature and precipitation observed on large spatial and temporal scales in Australia. First, we review how Coupled Model Intercomparison Project Phase 5 (CMIP5) models have been used to examine the changing odds of observed extremes. Second, we review how a large perturbed initial condition ensemble of a single climate model (CESM) has been used to quantitatively examine the changing characteristics of Australian heat extremes. For each approach, methodological details and applications are provided and limitations highlighted. The conclusions of this methodological review discuss the limitations and uncertainties associated with this approach and identify key unexplored applications of GCM-based attribution of extremes. Ideally, this information will be useful for the application of the described extreme event attribution approaches elsewhere.

scholarly journals Contribution of climatic changes in mean and variability to monthly temperature and precipitation extremes

2021 ◽  
Vol 2 (1) ◽  
Author(s):  
Karin van der Wiel ◽  
Richard Bintanja
Keyword(s):  
Climate Variability ◽  
Climate Model ◽  
Climate Extremes ◽  
Heavy Precipitation ◽  
Precipitation Extremes ◽  
Probability Ratio ◽  
Temperature And Precipitation ◽  
Climate Simulations ◽  
Individual Contributions ◽  
Mean Climate

AbstractThe frequency of climate extremes will change in response to shifts in both mean climate and climate variability. These individual contributions, and thus the fundamental mechanisms behind changes in climate extremes, remain largely unknown. Here we apply the probability ratio concept in large-ensemble climate simulations to attribute changes in extreme events to either changes in mean climate or climate variability. We show that increased occurrence of monthly high-temperature events is governed by a warming mean climate. In contrast, future changes in monthly heavy-precipitation events depend to a considerable degree on trends in climate variability. Spatial variations are substantial however, highlighting the relevance of regional processes. The contributions of mean and variability to the probability ratio are largely independent of event threshold, magnitude of warming and climate model. Hence projections of temperature extremes are more robust than those of precipitation extremes, since the mean climate is better understood than climate variability.

scholarly journals Unpacking future climate extremes and their sectoral implications in western Nepal

2021 ◽  
Vol 168 (1-2) ◽  
Author(s):  
Dipesh Chapagain ◽  
Sanita Dhaubanjar ◽  
Luna Bharati
Keyword(s):  
Climate Models ◽  
Regional Climate ◽  
Extreme Temperature ◽  
Climate Extremes ◽  
Climate Indices ◽  
Climate Projections ◽  
Temperature And Precipitation ◽  
Extreme Precipitation Events ◽  
The Impact ◽  
Precipitation Events

AbstractExisting climate projections and impact assessments in Nepal only consider a limited number of generic climate indices such as means. Few studies have explored climate extremes and their sectoral implications. This study evaluates future scenarios of extreme climate indices from the list of the Expert Team on Sector-specific Climate Indices (ET-SCI) and their sectoral implications in the Karnali Basin in western Nepal. First, future projections of 26 climate indices relevant to six climate-sensitive sectors in Karnali are made for the near (2021–2045), mid (2046–2070), and far (2071–2095) future for low- and high-emission scenarios (RCP4.5 and RCP8.5, respectively) using bias-corrected ensembles of 19 regional climate models from the COordinated Regional Downscaling EXperiment for South Asia (CORDEX-SA). Second, a qualitative analysis based on expert interviews and a literature review on the impact of the projected climate extremes on the climate-sensitive sectors is undertaken. Both the temperature and precipitation patterns are projected to deviate significantly from the historical reference already from the near future with increased occurrences of extreme events. Winter in the highlands is expected to become warmer and dryer. The hot and wet tropical summer in the lowlands will become hotter with longer warm spells and fewer cold days. Low-intensity precipitation events will decline, but the magnitude and frequency of extreme precipitation events will increase. The compounding effects of the increase in extreme temperature and precipitation events will have largely negative implications for the six climate-sensitive sectors considered here.

Land Surface Model influence on the simulated climatologies of extreme temperature and precipitation events within the WRF model over North America

2020 ◽  
Author(s):  
Almudena García-García ◽  
Francisco José Cuesta-Valero ◽  
Hugo Beltrami ◽  
J. Fidel González-Rouco ◽  
Elena García-Bustamante ◽  
...  
Keyword(s):  
Land Surface ◽  
Climate Model ◽  
Regional Climate ◽  
Extreme Temperature ◽  
Wrf Model ◽  
Land Surface Model ◽  
Surface Model ◽  
Model Simulations ◽  
Temperature And Precipitation ◽  
Precipitation Events

<p class="western"><span>The representation and projection of extreme temperature and precipitation events in climate models are of major importance for developing polices to build communities’ resilience in the face of climate change. However, state-of-the-art global and regional climate model simulations yield a broad inter-model range of intensities, durations and frequencies of these extremes. </span></p> <p class="western"><span>Here, we present a modeling experiment using the Weather Research and Forecasting (WRF) Regional Climate Model (RCM) to determine the influence of the choice of land surface model (LSM) component on the uncertainty in the simulation of extreme event statistics. First, we evaluate land-atmosphere interactions within four simulations performed with the WRF model coupled to three different LSMs from 1980 to 2012 over North America. Results show regional differences among simulations for the frequency of events when surface conditions are altered by atmospheric forcing or by land surface processes. Second, we find a large inter-model range of extreme statistics across the ensemble of WRF-LSM simulations. This is particularly the case for indices related to the intensity and duration of temperature and precipitation extremes. </span></p> <p class="western"><span>Regions displaying large uncertainty in the WRF simulation of extreme events are also identified in a model ensemble experiment carried out with three different RCMs participating in the Coordinated Regional Climate Downscaling Experiment (CORDEX) project. This agreement between the model simulations performed in this work and the set of CORDEX simulations suggests that the implications of our results are valid for other model ensembles. This study illustrates the importance of supporting the development of new multi-LSM modeling studies to understand inter-model differences in simulating extreme events, ultimately helping to narrow down the range across climate model projections.</span></p>

scholarly journals Unpacking Future Climate Extremes and their Sectoral Implications in Western Nepal

2021 ◽  
Author(s):  
Dipesh Chapagain ◽  
Sanita Dhaubanjar ◽  
Luna Bharati
Keyword(s):  
Climate Models ◽  
Regional Climate ◽  
Extreme Temperature ◽  
Climate Extremes ◽  
Climate Indices ◽  
Climate Projections ◽  
Temperature And Precipitation ◽  
Extreme Precipitation Events ◽  
The Impact ◽  
Precipitation Events

Abstract Existing climate projections and impact assessments in Nepal only consider a limited number of generic climate indices such as means. Few studies have explored climate extremes and their sectoral implications. This study evaluates future scenarios of extreme climate indices from the list of Expert Team on Sector-specific Climate Indices (ET-SCI) and their sectoral implications in the Karnali Basin in western Nepal. First, future projections of 26 climate indices relevant to six climate-sensitive sectors in Karnali were made for the near (2021–2045), mid (2046–2070), and far (2071–2095) future for low- and high-emission scenarios (RCP4.5 and RCP8.5, respectively) using bias-corrected ensembles of 19 regional climate models from the COordinated Regional Downscaling EXperiment for South Asia (CORDEX-SA). Second, a qualitative analysis based on expert interviews and a literature review on the impact of the projected climate extremes on the climate-sensitive sectors was undertaken. Both the temperature and precipitation patterns are projected to deviate significantly from the historical reference already from the near future with increased occurrences of extreme events. Winter in the highlands is expected to become warmer and dryer. The hot and wet tropical summer in the lowlands will become hotter with longer warm spells and fewer cold days. Low-intensity precipitation events will decline, but the magnitude and frequency of extreme precipitation events will increase. The compounding effects of the increase in extreme temperature and precipitation events will have largely negative implications for the six climate-sensitive sectors considered here.

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