Statistical modeling of fire brigade operations with respect to extreme precipitation events over Berlin

2021 ◽  
Author(s):  
Alexander Pasternack ◽  
Ines Langer ◽  
Henning W. Rust ◽  
Uwe Ulbrich
Keyword(s):  
Urban Climate ◽  
Heavy Precipitation ◽  
Radar Data ◽  
Climate Conditions ◽  
Large Cities ◽  
Fire Brigade ◽  
Extreme Precipitation Events ◽  
Highly Sensitive ◽  
Part Modeling ◽  
Precipitation Events

<p>Large cities and urban regions are highly sensitive to impacts caused by extreme events (e.g. heavy rainfall). As problems caused by hazardous atmospheric events are expected to intensify due to the Anthropogenic Climate Change, adequate adaptation planning of urban infrastructure is needed. Planning adaptations not only requires further research on potential impacts under changing climate conditions as a basis, but also a check of the practical feasibility for stakeholders.</p><p>Under the BMBF research program “Urban Climate Under Change” ([UC]²), we relate heavy precipitation events over Berlin to the respective fire brigade operations. Here, the precipitation data are based on temporally high resolved radar data. The fire brigade operation data are available on time and location, but the number of recorded events is small, and their distribution is highly overdispersive compared to a Poisson model. To account for this problem we apply a two part hurdle model with one part modeling the probability of the occurrence of fire brigade operations and one part modeling the actual number of operations given that at least one operation occurs. In the corresponding statistical models the parameters of the distributions are described by additive predictors, which are based on precipitation duration and intensity as well as building density. Based on 10 years of data with a cross validation setup, both the occurrence model and the model for the number of operations significantly outperform the reference climatology for certain areas over Berlin.</p>

Utilization of fire brigade data in the impact analysis of extreme precipitation events over Berlin

2020 ◽  
Author(s):  
Alexander Pasternack ◽  
Ines Langer ◽  
Henning Rust ◽  
Uwe Ulbrich
Keyword(s):  
Impact Analysis ◽  
Global Climate ◽  
Urban Climate ◽  
Heavy Precipitation ◽  
High Temporal Resolution ◽  
Fire Brigade ◽  
Extreme Precipitation Events ◽  
Multiple Data Sets ◽  
The Impact ◽  
Precipitation Events

<p>Large cities and urban regions are highly sensitive to impacts caused by extreme events, e.g. heavy rainfall, since they cause fatalities and economic damages. Moreover, due to regional consequences of global climate change, problems caused by hazardous atmospheric events are expected to intensify in future. Thus adequate adaptation planning of urban infrastructure not only requires further research on potential impacts under changing precipitation patterns, but also practical feasibility for end users like insurances or fire brigades.</p><p>According to this we relate heavy precipitation events over Berlin to the available data on time and location of the respective fire brigade operations, within the research program “Urban Climate Under Change” ([UC]<sup>2</sup>) funded by the BMBF. For this purpose multiple data sets like station, radar and model  based data with a high temporal resolution will be used.  Thus an improved assessment of the spatial and temporal evolution of severe precipitation events can be made,  which is consequently also of aid in the investigation of a connection to related impacts in the urban area.</p>

Statistics of 20 years of heavy precipitation events in Germany from radar data

2021 ◽  
Author(s):  
Katharina Lengfeld ◽  
Ewelina Walawender ◽  
Tanja Winterrath ◽  
Elmar Weigl ◽  
Andreas Becker
Keyword(s):  
Temporal Structure ◽  
Heavy Precipitation ◽  
Radar Data ◽  
Easy Access ◽  
Data Set ◽  
Extreme Precipitation Events ◽  
Radar Networks ◽  
Temporal And Spatial Variability ◽  
Precipitation Estimates ◽  
Precipitation Events

<p>Extreme precipitation events are expected to occur more frequently in a warming climate. Understanding their structure and predicting the exact time and location of precipitation events still remains a challenge because of the high temporal and spatial variability of rainfall. Nationwide weather radar networks are a common tool for investigating precipitation events and their spatial and temporal structure. The German Weather Service (DWD) provides a nationwide climatological radar data set from 2001 to 2020. A reprocessing procedure has been applied to reflectivity measurements in order to obtain precipitation estimates as homogeneous as possible. With an object-oriented analysis, all precipitation events for 11 different durations from 1 to 72 hours exceeding DWD’s official warning level for heavy precipitation have been detected and statistically analysed.</p><p>We will present a comprehensive analysis of all heavy precipitation events that occurred in Germany between 2001 and 2020. We examined their size, duration, location, spatial structure and distribution as well as regional and climatological differences and demonstrate how this information is collected in an online tool for easy access. An assessment of how well these heavy precipitation events were captured by DWD’s network of precipitation stations will be given. Finally, we will present the possibility to use the event detection procedure as an operational tool for assessing and classifying heavy precipitation events and their potential impact in near real-time.</p>

scholarly journals Changes in Intense Precipitation over the Central United States

2012 ◽  
Vol 13 (1) ◽  
pp. 47-66 ◽  
Author(s):  
Pavel Ya. Groisman ◽  
Richard W. Knight ◽  
Thomas R. Karl
Keyword(s):  
United States ◽  
Extreme Precipitation ◽  
Heavy Precipitation ◽  
The Past ◽  
Extreme Precipitation Events ◽  
Intense Precipitation ◽  
Central United States ◽  
Extreme Rain ◽  
Rain Events ◽  
Precipitation Events

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.

Listening to Stakeholders: Initiating Research on Sub-seasonal to Seasonal Heavy Precipitation Events in the Contiguous U.S. by First Understanding What Stakeholders Need

2021 ◽  
pp. 1-35
Author(s):  
Olivia VanBuskirk ◽  
Paulina Ćwik ◽  
Renee A. McPherson ◽  
Heather Lazrus ◽  
Elinor Martin ◽  
...  
Keyword(s):  
United States ◽  
Environmental Management ◽  
Predictive Models ◽  
Extreme Precipitation ◽  
Heavy Precipitation ◽  
Role Playing ◽  
Extreme Precipitation Events ◽  
Rainfall Extremes ◽  
Actionable Science ◽  
Precipitation Events

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.

scholarly journals Short-Range Numerical Weather Prediction of Extreme Precipitation Events Using Enhanced Surface Data Assimilation

Atmosphere ◽  
2019 ◽  
Vol 10 (10) ◽  
pp. 587
Author(s):  
Magnus Lindskog ◽  
Tomas Landelius
Keyword(s):  
Data Assimilation ◽  
Numerical Weather Prediction ◽  
Short Range ◽  
Weather Prediction ◽  
Heavy Precipitation ◽  
Numerical Weather ◽  
Extreme Precipitation Events ◽  
Surface Data ◽  
Enhanced Surface ◽  
Precipitation Events

A limited-area kilometre scale numerical weather prediction system is applied to evaluate the effect of refined surface data assimilation on short-range heavy precipitation forecasts. The refinements include a spatially dependent background error representation, use of a flow-dependent data assimilation technique, and use of data from a satellite-based scatterometer instrument. The effect of the enhancements on short-term prediction of intense precipitation events is confirmed through a number of case studies. Verification scores and subjective evaluation of one particular case points at a clear impact of the enhanced surface data assimilation on short-range heavy precipitation forecasts and suggest that it also tends to slightly improve them. Although this is not strictly statistically demonstrated, it is consistent with the expectation that a better surface state should improve rainfall forecasts.

scholarly journals Trends, change points and spatial variability in extreme precipitation events from 1961 to 2017 in China

2020 ◽  
Vol 51 (3) ◽  
pp. 484-504 ◽  
Author(s):  
Linchao Li ◽  
Yufeng Zou ◽  
Yi Li ◽  
Haixia Lin ◽  
De Li Liu ◽  
...  
Keyword(s):  
Extreme Precipitation ◽  
Extreme Event ◽  
Heavy Precipitation ◽  
Kendall Test ◽  
Temporal Variations ◽  
Change Points ◽  
Monthly Precipitation ◽  
Flood Peak ◽  
Extreme Precipitation Events ◽  
Precipitation Events

Abstract Extreme precipitation events vary with different sub-regions, sites and years and show complex characteristics. In this study, the temporal variations, trends with significance and change points in the annual time series of 10 extreme precipitation indices (EPIs) at 552 sites and in seven sub-regions were analyzed using the modified Mann–Kendall test and sequential Mann–Kendall analysis. Three representative (extremely wet, normal and extremely dry) years from 1961 to 2017 were selected by the largest, 50%, and smallest empirical frequency values in China. The spatiotemporal changes in the EPIs during the three representative years were analyzed in detail. The results showed that during 1961–2017, both the consecutive wet or dry days decreased significantly, while the number of heavy precipitation days had no significant trend, and the other seven wet EPIs increased insignificantly. The abrupt change years of the 10 EPIs occurred 32 and 40 times from 1963 to 1978 and from 1990 to 2016, respectively, regardless of sub-region. The extremely dry (or wet) events mainly occurred in western (or southwestern) China, implying a higher extreme event risk. The extremely wet, normal and extremely dry events from 1961 to 2017 occurred in 2016, 1997 and 2011 with empirical frequencies of 1.7%, 50% and 98.3%, respectively. In addition, 1998 was the second-most extremely wet year (empirical frequency was 3.7%). The monthly precipitation values were larger from February to August in 1998, forming a much earlier flood peak than that of 2016. The 10 EPIs had close connections with Normalized Difference Vegetation Indexes during the 12 months of 1998 and 2016. This study provides useful references for disaster prevention in China.

scholarly journals How Well Can IMERG Products Capture Typhoon Extreme Precipitation Events over Southern China?

2019 ◽  
Vol 11 (1) ◽  
pp. 70 ◽  
Author(s):  
Chaoying Huang ◽  
Junjun Hu ◽  
Sheng Chen ◽  
Asi Zhang ◽  
Zhenqing Liang ◽  
...  
Keyword(s):  
Extreme Precipitation ◽  
Southern China ◽  
Correlation Coefficients ◽  
Heavy Precipitation ◽  
Spatiotemporal Variability ◽  
Bias Analysis ◽  
Extreme Precipitation Events ◽  
Precipitation Measurement ◽  
Global Precipitation ◽  
Precipitation Events

This study assesses the performance of the latest version 05B (V5B) Integrated Multi-Satellite Retrievals for Global Precipitation Measurement (GPM) (IMERG) Early and Final Runs over southern China during six extremely heavy precipitation events brought by six powerful typhoons from 2016 to 2017. Observations from a dense network composed of 2449 rain gauges are used as reference to quantify the performance in terms of spatiotemporal variability, probability distribution of precipitation rates, contingency scores, and bias analysis. The results show that: (1) both IMERG with gauge calibration (IMERG_Cal) and without gauge correction (IMERG_Uncal) generally capture the spatial patterns of storm-accumulated precipitation with moderate to high correlation coefficients (CCs) of 0.57–0.87, and relative bias (RB) varying from −17.21% to 30.58%; (2) IMERG_Uncal and IMERG_Cal capture well the area-average hourly series of precipitation over rainfall centers with high CCs ranging from 0.78 to 0.94; (3) IMERG_Cal tends to underestimate precipitation especially the rainfall over the rainfall centers when compared to IMERG_Uncal. The IMERG Final Run shows promising potentials in typhoon-related extreme precipitation storm applications. This study is expected to give useful feedbacks about the latest V5B Final Run IMERG product to both algorithm developers and the scientific end users, providing a better understanding of how well the V5B IMERG products capture the typhoon extreme precipitation events over southern China.

Spatial and Temporal Analysis of Precipitation Extremities of Eastern Nepal in the Last Two Decades (1997–2016)

2020 ◽  
Author(s):  
Sunil Subba ◽  
Yaoming Ma ◽  
Weiqiang Ma
Keyword(s):  
Climate Change ◽  
Extreme Events ◽  
Extreme Precipitation ◽  
Tropical Rainfall Measuring Mission ◽  
Heavy Precipitation ◽  
Temporal Analysis ◽  
Extreme Precipitation Events ◽  
Slope Estimator ◽  
The Impact ◽  
Precipitation Events

<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>

scholarly journals Multi-Indicator Evaluation for Extreme Precipitation Events in the Past 60 Years over the Loess Plateau

Water ◽  
2020 ◽  
Vol 12 (1) ◽  
pp. 193 ◽  
Author(s):  
Chaoxing Sun ◽  
Guohe Huang ◽  
Yurui Fan
Keyword(s):  
Loess Plateau ◽  
Return Period ◽  
Extreme Precipitation ◽  
Precipitation Amount ◽  
Heavy Precipitation ◽  
The Loess Plateau ◽  
Extreme Precipitation Events ◽  
Daily Precipitation Data ◽  
Joint Return ◽  
Precipitation Events

The unique characteristics of topography, landforms, and climate in the Loess Plateau make it especially important to investigate its extreme precipitation characteristics. Daily precipitation data of Loess Plateau covering a period of 1959–2017 are applied to evaluate the probability features of five precipitation indicators: the amount of extreme heavy precipitation (P95), the days with extreme heavy precipitation, the intensity of extreme heavy precipitation (I95), the continuous dry days, and the annual total precipitation. In addition, the joint risk of different combinations of precipitation indices is quantitatively evaluated based on the copula method. Moreover, the risk and severity of each extreme heavy precipitation factor corresponding to 50-year joint return period are achieved through inverse derivation process. Results show that the precipitation amount and intensity of the Loess Plateau vary greatly in spatial distribution. The annual precipitation in the northwest region may be too concentrated in several rainstorms, which makes the region in a serious drought state for most of the year. At the level of 10-year return period, more than five months with no precipitation events would occur in the Northwest Loess Plateau. While, P95 or I95 events of 100-year level may be encountered in a 50-year return period and in the southeastern region, which means there are foreseeable long-term extreme heavy precipitation events.

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
Keyword(s):  
North America ◽  
Extreme Events ◽  
Extreme Precipitation ◽  
Large Scale ◽  
Climate Model ◽  
Heavy Precipitation ◽  
Convective Precipitation ◽  
Southern Mexico ◽  
Extreme Precipitation Events ◽  
Precipitation Events

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.

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