A Comparison of CMIP3 Simulations of Precipitation over North America with Observations: Daily Statistics and Circulation Features Accompanying Extreme Events

2013 ◽  
Vol 26 (10) ◽  
pp. 3209-3230 ◽  
Author(s):  
Anthony M. DeAngelis ◽  
Anthony J. Broccoli ◽  
Steven G. Decker

Abstract Climate model simulations of daily precipitation statistics from the third phase of the Coupled Model Intercomparison Project (CMIP3) were evaluated against precipitation observations from North America over the period 1979–99. The evaluation revealed that the models underestimate the intensity of heavy and extreme precipitation along the Pacific coast, southeastern United States, and southern Mexico, and these biases are robust among the models. The models also overestimate the intensity of light precipitation events over much of North America, resulting in fairly realistic mean precipitation in many places. In contrast, heavy precipitation is simulated realistically over northern and eastern Canada, as is the seasonal cycle of heavy precipitation over a majority of North America. An evaluation of the simulated atmospheric dynamics and thermodynamics associated with extreme precipitation events was also conducted using the North American Regional Reanalysis (NARR). The models were found to capture the large-scale physical mechanisms that generate extreme precipitation realistically, although they tend to overestimate the strength of the associated atmospheric circulation features. This suggests that climate model deficiencies such as insufficient spatial resolution, inadequate representation of convective precipitation, and overly smoothed topography may be more important for biases in simulated heavy precipitation than errors in the large-scale circulation during extreme events.

2020 ◽  
Author(s):  
Sunil Subba ◽  
Yaoming Ma ◽  
Weiqiang Ma

<p>In recent days there have been discussions regarding the impact of climate change and its vagaries of the weather, particularly concerning extreme events. Nepal, being a mountainous country, is more susceptible to precipitation extreme events and related hazards, which hinder the socioeconomic<br>development of the nation. In this regard, this study aimed to address this phenomenon for one of the most naturally and socioeconomically important regions of Nepal, namely, Eastern Nepal. The data were collected for the period of 1997 to 2016. The interdecadal comparison for two periods<br>(1997–2006 and 2007–2016) was maintained for the calculation of extreme precipitation indices as per recommended by Expert Team on Climate Change Detection and Indices. Linear trends were calculated by using Mann‐Kendall and Sen's Slope estimator. The average annual precipitation was found to be decreasing at an alarming rate of −20 mm/year in the last two decades' tenure. In case of extreme precipitation events, consecutive dry days, one of the frequency indices, showed a solo increase in its trend (mostly significant). Meanwhile, all the intensity indices of extreme precipitation showed decreasing trends (mostly insignificant). Thus, it can be concluded that Eastern Nepal has witnessed some significant drier days in the last two decades, as the events of heavy, very heavy, extremely heavy precipitation events, and annual wet day precipitation (PRCPTOT) were found to be decreasing. The same phenomena were also seen in the Tropical Rainfall Measuring Mission 3B42 V7 satellite precipitation product for whole Nepal.</p>


2020 ◽  
Vol 07 (01n02) ◽  
pp. 2050010
Author(s):  
Britta V. Weißer ◽  
Ali Jamshed ◽  
Jörn Birkmann ◽  
Joanna M. McMillan

In 2016, heavy precipitation events in Southern Germany demonstrated that pluvial flooding can cause serious damages, not just in large cities but also in small and medium-sized cities. Hazard-oriented disaster management approaches to better address such spatially ubiquitous extreme events are already being developed. However, integrated strategies to reduce risk and to promote climate-resilient development pathways through both private precautionary measures and integrated urban planning are still underdeveloped. Considering the uncertainties associated with heavy precipitation, analyzing and understanding damages, strengthening people’s preparedness and improving preventative measures are central components of resilience building. This paper complements existing empirical studies on households’ preparedness and provides further insight into how resilience to flooding from heavy precipitation in cities can be strengthened. We do this by analyzing the damages caused by one particular heavy precipitation event, the preparedness of people in the affected city and their perceptions of responsibilities for improving precautionary measures. This paper presents the results from a household survey with a total of 1,128 completed questionnaires which was carried out in Schwäbisch Gmünd, Germany. The findings of the household survey illustrate the variety of damages caused by the heavy precipitation event and reveal important differences between households who experienced damages from pluvial flooding and those who did not. Lastly, findings of people’s perception about who is responsible for improved precautions offer interesting insights into tools that might help to enhance resilience building. Finally, the paper formulates recommendations for an improved assessment of resilience-building processes, individual capacities and planning tools to build climate resilience to extreme precipitation events.


2020 ◽  
Author(s):  
Nikolaos Mastrantonas ◽  
Linus Magnusson ◽  
Florian Pappenberger ◽  
Jörg Matschullat

<p>The Mediterranean region is an area with half a billion population, about 10 percent contribution to the world’s GDP, and locations of global natural, historical and cultural significance. In this context, natural hazards in the area have the potential for severe negative impacts on society, economy, and environment. </p><p>Some of the most frequent and devastating natural hazards that affect the Mediterranean relate to extreme precipitation events causing flash floods and landslides. Thus, given their adverse consequences, it is of immense importance to better understand their statistical characteristics and connection to large-scale atmospheric patterns. Such advances can substantially support the accurate and early identification of these extreme events, improve early warning systems, and contribute to mitigating related risks. </p><p>This work focuses on the characteristics and spatiotemporal variability of extreme precipitation events of large spatial coverage across the Mediterranean region. The study uses the ERA5 dataset, the latest, state of the art, reanalysis dataset from Copernicus/ECMWF. Initially, exploratory analysis is performed to assess the different characteristics at various subdomains within the study area. Furthermore, composite analysis is used to understand the connection of extreme events with large-scale atmospheric patterns. Finally, the Empirical Orthogonal Function (EOF) analysis is implemented to quantify the importance of weather regimes with respect to the frequency of extreme precipitation events. </p><p>Preliminary results indicate that there is a spatial division in the occurrence of identified events. Winter and autumn are the seasons of the highest frequency of extreme precipitation for the east and west Mediterranean respectively. Troughs and cut-off lows in the lower and middle-level troposphere have a strong association with such extreme events, and the effect is modulated by other parameters, such as local orography. Results of this work are in accordance with previous studies in the region and provide information that can be utilized by future research for improving the predictability of such events in the medium- and extended-range forecasts. </p><p>This work is part of the Climate Advanced Forecasting of sub-seasonal Extremes (CAFE) project. The project has received funding from the European Union’s Horizon 2020 research and innovation programme under the Marie Skłodowska-Curie grant agreement No 813844.</p>


2013 ◽  
Vol 26 (21) ◽  
pp. 8671-8689 ◽  
Author(s):  
Kelly Mahoney ◽  
Michael Alexander ◽  
James D. Scott ◽  
Joseph Barsugli

Abstract A high-resolution case-based approach for dynamically downscaling climate model data is presented. Extreme precipitation events are selected from regional climate model (RCM) simulations of past and future time periods. Each event is further downscaled using the Weather Research and Forecasting (WRF) Model to storm scale (1.3-km grid spacing). The high-resolution downscaled simulations are used to investigate changes in extreme precipitation projections from a past to a future climate period, as well as how projected precipitation intensity and distribution differ between the RCM scale (50-km grid spacing) and the local scale (1.3-km grid spacing). Three independent RCM projections are utilized as initial and boundary conditions to the downscaled simulations, and the results reveal considerable spread in projected changes not only among the RCMs but also in the downscaled high-resolution simulations. However, even when the RCM projections show an overall (i.e., spatially averaged) decrease in the intensity of extreme events, localized maxima in the high-resolution simulations of extreme events can remain as strong or even increase. An ingredients-based analysis of prestorm instability, moisture, and forcing for ascent illustrates that while instability and moisture tend to increase in the future simulations at both regional and local scales, local forcing, synoptic dynamics, and terrain-relative winds are quite variable. Nuanced differences in larger-scale and mesoscale dynamics are a key determinant in each event's resultant precipitation. Very high-resolution dynamical downscaling enables a more detailed representation of extreme precipitation events and their relationship to their surrounding environments with fewer parameterization-based uncertainties and provides a framework for diagnosing climate model errors.


2012 ◽  
Vol 13 (1) ◽  
pp. 47-66 ◽  
Author(s):  
Pavel Ya. Groisman ◽  
Richard W. Knight ◽  
Thomas R. Karl

Abstract In examining intense precipitation over the central United States, the authors consider only days with precipitation when the daily total is above 12.7 mm and focus only on these days and multiday events constructed from such consecutive precipitation days. Analyses show that over the central United States, a statistically significant redistribution in the spectra of intense precipitation days/events during the past decades has occurred. Moderately heavy precipitation events (within a 12.7–25.4 mm day−1 range) became less frequent compared to days and events with precipitation totals above 25.4 mm. During the past 31 yr (compared to the 1948–78 period), significant increases occurred in the frequency of “very heavy” (the daily rain events above 76.2 mm) and extreme precipitation events (defined as daily and multiday rain events with totals above 154.9 mm or 6 in.), with up to 40% increases in the frequency of days and multiday extreme rain events. Tropical cyclones associated with extreme precipitation do not significantly contribute to the changes reported in this study. With time, the internal precipitation structure (e.g., mean and maximum hourly precipitation rates within each preselected range of daily or multiday event totals) did not noticeably change. Several possible causes of observed changes in intense precipitation over the central United States are discussed and/or tested.


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.


Author(s):  
Olivia VanBuskirk ◽  
Paulina Ćwik ◽  
Renee A. McPherson ◽  
Heather Lazrus ◽  
Elinor Martin ◽  
...  

AbstractHeavy precipitation events and their associated flooding can have major impacts on communities and stakeholders. There is a lack of knowledge, however, about how stakeholders make decisions at the sub-seasonal to seasonal (S2S) timescales (i.e., two weeks to three months). To understand how decisions are made and S2S predictions are or can be used, the project team for “Prediction of Rainfall Extremes at Sub-seasonal to Seasonal Periods” (PRES2iP) conducted a two-day workshop in Norman, Oklahoma, during July 2018. The workshop engaged 21 professionals from environmental management and public safety communities across the contiguous United States in activities to understand their needs for S2S predictions of potential extended heavy precipitation events. Discussions and role-playing activities aimed to identify how workshop participants manage uncertainty and define extreme precipitation, the timescales over which they make key decisions, and the types of products they use currently. This collaboration with stakeholders has been an integral part of PRES2iP research and has aimed to foster actionable science. The PRES2iP team is using the information produced from this workshop to inform the development of predictive models for extended heavy precipitation events and to collaboratively design new forecast products with our stakeholders, empowering them to make more-informed decisions about potential extreme precipitation events.


2021 ◽  
Vol 14 (2) ◽  
Author(s):  
Nathan Felipe da Silva Caldana ◽  
Leonardo Rodrigues ◽  
Luis Gustavo Batista Ferreira ◽  
Marcelo Augusto De Aguiar e Silva

Extreme precipitation events cause severe damage in both urban and rural areas. The objective of this work was to analyze rainfall variability, understand the dynamics of extreme precipitation events and to find out the occurrence of floods, runoff and inundation in the Metropolitan Region of Curitiba (MRC). Data from 39 rainfall stations distributed in the MRC area were used, as well as data by municipality of occurrence of flooding, runoff or inundation, from 1976 to 2018. Extreme precipitation events were identified in all months, most frequently in the summer. Totaling 48 decrees of emergency or public calamity and 397,516 people affected by one of the three socioenvironmental disasters.


2021 ◽  
Author(s):  
Jérôme Kopp ◽  
Pauline Rivoire ◽  
S. Mubashshir Ali ◽  
Yannick Barton ◽  
Olivia Martius

<p>Temporal clustering of extreme precipitation events on subseasonal time scales is a type of compound event, which can cause large precipitation accumulations and lead to floods. We present a novel count-based procedure to identify subseasonal clustering of extreme precipitation events. Furthermore, we introduce two metrics to characterise the frequency of subseasonal clustering episodes and their relevance for large precipitation accumulations. The advantage of this approach is that it does not require the investigated variable (here precipitation) to satisfy any specific statistical properties. Applying this methodology to the ERA5 reanalysis data set, we identify regions where subseasonal clustering of annual high precipitation percentiles occurs frequently and contributes substantially to large precipitation accumulations. Those regions are the east and northeast of the Asian continent (north of Yellow Sea, in the Chinese provinces of Hebei, Jilin and Liaoning; North and South Korea; Siberia and east of Mongolia), central Canada and south of California, Afghanistan, Pakistan, the southeast of the Iberian Peninsula, and the north of Argentina and south of Bolivia. Our method is robust with respect to the parameters used to define the extreme events (the percentile threshold and the run length) and the length of the subseasonal time window (here 2 – 4 weeks). The procedure could also be used to identify temporal clustering of other variables (e.g. heat waves) and can be applied on different time scales (e.g. for drought years). <span>For a complementary study on the subseasonal clustering of European extreme precipitation events and its relationship to large-scale atmospheric drivers, please refer to Barton et al.</span></p>


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