Non-stationary Modeling of Extreme Precipitation over Monsoon Asia – Role of Teleconnection Time Lags 

2021 ◽  
Author(s):  
Meghana Nagaraj ◽  
Srinivasan Kasturirengan ◽  
Jency Maria Sojan ◽  
Roshan Srivastav
Keyword(s):  
Extreme Precipitation ◽  
Time Lag ◽  
Information Criteria ◽  
Climate Indices ◽  
Time Lags ◽  
Monsoon Asia ◽  
Extreme Precipitation Events ◽  
Large Numbers ◽  
Cross Correlation Analysis ◽  
Time Lagged

<p>Extreme precipitation events are increasing due to climate change and leading to frequent flooding and severe droughts. These events vary in both space and time and are positively correlated with the climate teleconnections representing the oscillations of the ocean-atmospheric system. However, large numbers of climate signals and the precipitation response may vary at certain time lags with each climate indices. This study identifies time lags for climate indices using cross-correlation analysis between extreme precipitation and climate indices. These time-lagged climate indices are used as a covariate to fit a non-stationary generalized extreme value (NS-GEV) model over Monsoon Asia. The best NS-GEV model among non-stationary models is selected based on Akaike information criteria (AICc). Results show that the correlation between precipitation and different climate indices is spatially non-uniform. Incorporating time lag climate indices as covariate improves the performance of the non-stationary models. This study helps in understanding the teleconnections influencing the variation of extreme precipitation in a non-stationary framework and to revise the infrastructure designs and flood risk assessment.</p>

scholarly journals Exploring the Predictability of 30-Day Extreme Precipitation Occurrence Using a Global SST–SLP Correlation Network

2016 ◽  
Vol 29 (3) ◽  
pp. 1013-1029 ◽  
Author(s):  
Mengqian Lu ◽  
Upmanu Lall ◽  
Jaya Kawale ◽  
Stefan Liess ◽  
Vipin Kumar
Keyword(s):  
Extreme Precipitation ◽  
Time Lag ◽  
Principal Component Regression ◽  
Principal Component ◽  
Correlation Network ◽  
Climatic Data ◽  
Wet Season ◽  
Predictive Skill ◽  
Correlation Networks ◽  
Time Lagged

Abstract Correlation networks identified from financial, genomic, ecological, epidemiological, social, and climatic data are being used to provide useful topological insights into the structure of high-dimensional data. Strong convection over the oceans and the atmospheric moisture transport and flow convergence indicated by atmospheric pressure fields may determine where and when extreme precipitation occurs. Here, the spatiotemporal relationship among sea surface temperature (SST), sea level pressure (SLP), and extreme global precipitation is explored using a graph-based approach that uses the concept of reciprocity to generate cluster pairs of locations with similar spatiotemporal patterns at any time lag. A global time-lagged relationship between pentad SST anomalies and pentad SLP anomalies is investigated to understand the linkages and influence of the slowly changing oceanic boundary conditions on the development of the global atmospheric circulation. This study explores the use of this correlation network to predict extreme precipitation globally over the next 30 days, using a logistic principal component regression on the strong global dipoles found between SST and SLP. Predictive skill under cross validation and blind prediction for the occurrence of 30-day precipitation that is higher than the 90th percentile of days in the wet season is indicated for the selected global regions considered.

scholarly journals Analysis and evaluation of the CORDEX simulations and derived extreme precipitation characteristics in European lowlands

2021 ◽  
Author(s):  
Alexandra Berényi ◽  
Judit Bartholy ◽  
Rita Pongrácz
Keyword(s):  
Climate Change ◽  
Extreme Precipitation ◽  
Western Europe ◽  
Climate Model ◽  
Regional Climate ◽  
Mediterranean Area ◽  
Point Of View ◽  
East European Plain ◽  
Climate Indices ◽  
Extreme Precipitation Events

<p>As the effects of climate change become more severe, the possible shifts in precipitation patterns can cause severe natural hazards, such as extended drought periods, floods and flash floods, therefore, appropriate risk management is essential. The future adaptation strategies and decisions should definitely consider the results of physically-based climate model simulations, that is why the validation and analysis of these results play a key role in climate change issues.</p><p>            The main goal of this study is to analyse the spatio-temporal changes in main and extreme precipitation indices, and validate the Euro-CORDEX (Coordinated Regional Climate Downscaling Experiment for the Euro-Mediterranean area) simulations from this specific point of view. For the evaluation and analysis, we use the current version of E-OBS database. Both the simulations and the database are available in a 0.11° grid with daily temporal resolution.</p><p>            Since plain regions play an important role in agricultural economy and are more exposed to floods due to their geographic features, our primary goals are (i) to examine temporal and spatial changes in extreme precipitation events, and (ii) to explore possible connections between the different lowlands across Europe. Altogether 14 plain regions were selected with an objective multi-step methodology where the selected plains have to fulfil several criteria.<em> </em>These target regions represent different climatic types within Europe and cover different geographical areas (e.g. near the sea, surrounded by mountains, etc.). More specifically, five plain regions are parts of the East European Plain, two regions are located in the Scandinavian basin, five regions are located in Western Europe, one in Southern Europe, and finally, the Pannonian Plain (including mostly Hungary) is also selected.</p><p>            To analyse and validate the simulations, we calculated 17 climate indices (most of them defined by the Expert Team of Climate Change Indices, ETCCD). These indices are capable to represent the differences and similarities between and within the plains, and measure the changes in the occurrence an intensity of main and extreme precipitation, the lack of precipitation, and dry spells. The validation results serve as a basis of selecting the most suitable simulations for subsequent analysis of extreme conditions predicted for lowlands within Europe under different future scenarios.</p>

scholarly journals Csapadékszélsőségek változása Európa déli alföldi régióiban az 1951–2019 időszakban

2021 ◽  
Vol 16 (4) ◽  
pp. 85-101
Author(s):  
Alexandra Berényi ◽  
◽  
Rita Pongrácz ◽  
Judit Bartholy ◽  
◽  
...  
Keyword(s):  
Extreme Precipitation ◽  
Temporal Trends ◽  
Scientific Basis ◽  
Extreme Weather Events ◽  
Climate Indices ◽  
Po Valley ◽  
Extreme Precipitation Events ◽  
Geographical Regions ◽  
The Difference ◽  
Precipitation Events

The aim of our study is to analyse the spatial patterns and temporal trends of average and extreme precipitation events in a few selected plain regions between 1951 and 2019. Besides the Great Hungarian Plain we chose two plain regions located in the southern part of the continent (i.e. the Po Valley and the Romanian Plain) with the purpose of comparing similar geographical regions, and creating a scientific basis to comprehensively analyse the effects of climate change on economy, society, and nature. For choosing the plains, objective criteria were used, namely, (i) the elevation remains under 200 m throughout the defined area, and (ii) the difference between the neighbouring grid points within the plain region does not exceed 50 m. The analysis of extreme precipitation events was performed for annual periods by calculating 17 climate indices. Based on our research of the past, there is a clear increase in the frequency and intensity of extreme precipitation events, in the length of dry periods as well as in the occurrence of extreme weather events.

Trend in precipitation and drought extremes in southern lowland regions of Europe

2021 ◽  
Author(s):  
Alexandra Berényi ◽  
Rita Pongrácz ◽  
Judit Bartholy
Keyword(s):  
Climate Change ◽  
Extreme Precipitation ◽  
Climate Model ◽  
Regional Scale ◽  
Climate Indices ◽  
Subtropical Climate ◽  
Precipitation Patterns ◽  
Extreme Precipitation Events ◽  
Dry Spells ◽  
Precipitation Events

<p>The effects of climate change on precipitation patterns can be observed on global scale, however, global climate change affects different regions more or less severely. Because of the high variability of precipitation in particular, future changes related to precipitation can be very different, even opposite on continental/regional scale. Even within Europe, the detected trends in precipitation patterns and extremes differ across the continent. According to climate model simulations for the future, Northern Europe is projected to become wetter, while the southern parts of the continent will tend to become drier by the end of the 21st century. The frequency and intensity of extreme precipitation will also increase in the whole continent. The possible shifts in precipitation patterns from wetter to drier conditions with fewer but increased extreme precipitation events can cause severe natural hazards, such as extended drought periods, water scarcity, floods and flash floods, therefore appropriate risk management is essential. For this purpose the analysis of possible hazards associated to specific precipitation-related weather phenomena is necessary and serves as key input.</p><p>Since plain regions play an important role in agricultural economy and are more exposed to floods because of their geographic features and the gravitational movement of surface water, our primary goal was to examine temporal and spatial changes in extreme precipitation events and dry spells in three European lowlands, located in the southern part of the continent. We selected the following regions: the Po-Valley located in Italy with humid subtropical climate; the Romanian Plain in Romania, and the Pannonian Plain covering different parts of Hungary, Serbia, Slovakia, Croatia, Romania and Ukraine with humid continental climatic conditions.</p><p>Precipitation time series were used from the E-OBS v.22 dataset on a 0.1° regular grid. The dataset is based on station measurements from Europe and are available from 1950 onward with daily temporal resolution. For the analysis of main precipitation patterns, dry spells and extreme events, we use 17 climate indices (most of them are defined by the Expert Team on Climate Change Detection and Indices, ECCDI). The analysis focuses on annual and seasonal changes in the three regions. The selected indices are capable to represent the differences and similarities between and within the plains. Our preliminary results show that the occurrence and intensity of extreme precipitation events increased in all regions, while the trends of duration and frequency of dry spells show both intra- and inter regional variability across the plains.</p>

Spatiotemporal Changes in Precipitation Extremes over Canada and Their Teleconnections to Large-Scale Climate Patterns

2019 ◽  
Vol 20 (2) ◽  
pp. 275-296 ◽  
Author(s):  
Yang Yang ◽  
Thian Yew Gan ◽  
Xuezhi Tan
Keyword(s):  
Extreme Precipitation ◽  
Large Scale ◽  
Specific Humidity ◽  
Climate Indices ◽  
Extreme Precipitation Events ◽  
Daily Precipitation Data ◽  
Climate Patterns ◽  
Extreme Precipitation Indices ◽  
Precipitation Indices ◽  
Precipitation Events

Abstract In the past few decades, there have been more extreme climate events occurring worldwide, including Canada, which has also suffered from many extreme precipitation events. In this paper, trend analysis, probability distribution functions, principal component analysis, and wavelet analysis were used to investigate the spatial and temporal patterns of extreme precipitation events of Canada. Ten extreme precipitation indices were calculated using long-term daily precipitation data (1950–2012) from 164 Canadian gauging stations. Several large-scale climate patterns such as El Niño–Southern Oscillation (ENSO), Pacific decadal oscillation (PDO), Pacific–North American (PNA), and North Atlantic Oscillation (NAO) were selected to analyze the relationships between extreme precipitation and climate indices. Convective available potential energy (CAPE), specific humidity, and surface temperature were employed to investigate potential causes of trends in extreme precipitation. The results reveal statistically significant positive trends for most extreme precipitation indices, which means that extreme precipitation of Canada has generally become more severe since the mid-twentieth century. The majority of indices display more increasing trends along the southern border of Canada while decreasing trends dominated the central Canadian Prairies. In addition, strong teleconnections are found between extreme precipitation and climate indices, but the effects of climate patterns differ from region to region. Furthermore, complex interactions of climate patterns with synoptic atmospheric circulations can also affect precipitation variability, and changes to the summer and winter extreme precipitation could be explained more by the thermodynamic impact and the combined thermodynamic and dynamic effects, respectively. The seasonal CAPE, specific humidity, and temperature are correlated to Canadian extreme precipitation, but the correlations are season dependent, which could be positive or negative.

scholarly journals The Connection between Extreme Precipitation Variability over Monsoon Asia and Large-Scale Circulation Patterns

Atmosphere ◽  
2021 ◽  
Vol 12 (11) ◽  
pp. 1492
Author(s):  
Sunilkumar Khadgarai ◽  
Vinay Kumar ◽  
Prabodha Kumar Pradhan
Keyword(s):  
Climate Change ◽  
Surface Temperature ◽  
Temporal Variability ◽  
Extreme Precipitation ◽  
Precipitation Variability ◽  
The Philippines ◽  
Positive Trend ◽  
Monsoon Asia ◽  
Extreme Precipitation Events ◽  
Circulation Patterns

Spatial and temporal variability in precipitation has been dramatically changed due to climate variability and climate change over the global domain. Increasing in extreme precipitation events are pronounced in various regions, including monsoon Asia (MA) in recent decades. The present study evaluated precipitation variability in light of intensity, duration, and frequency with several extreme precipitation climate change indices developed by the Expert Team on Climate Change Detection Indices (ETCCDI) over the MA region. This study uses an improved version (APHRO_V1901) of the Asian Precipitation Highly Resolved Observation Data Integration Towards Evaluation of extreme events (APHRODITE-2) gridded rainfall product. Results showed that the spatial variability of the extreme precipitation climate change indices is reflected in the annual mean rainfall distribution in MA. Maximum one-day precipitation (R × 1) and precipitation contributed from extremes (R95) depict a peak in decadal mean rainfall values over topography regions. A significant positive trend in R × 1 (with a slope of 0.3 mm/yr) and precipitation greater than the 95th percentile (R95: with a slope of 0.5 mm/yr) are predominantly observed in decadal trends in regional average extreme precipitation climate change indices over MA. Maritime continental countries exhibit an inclined trend in R10, whereas central Asian arid regions show a decreasing tendency in continuous dry days (CDD). The positive trend in R95 is observed over central India, the monsoon region in China, countries that reside over the equator and some parts of Japan, and the Philippines. When comparing the influence of surface temperature (T) and total column water vapor (TCW) on precipitation climate change indices, TCW seems to be a crucial attributor to climate change indices meridional variability. The mutual correlation analysis depicts that precipitation contributed from extremes (R95) strongly correlates in terms of temporal variability with all extreme precipitation indices. Among various global circulation patterns, the prevalent conditions of sea surface temperature (SST) over the equatorial Pacific Ocean have a significant influence on decadal variability in extreme precipitation climate change indices. R10 and R95 possess a relatively significant correlation (0.86 and 0.91) with the Southern Oscillation Index. The maximum number of consecutive dry days (CDD) shows an increasing trend with a positive phase of the North Atlantic Oscillation Index.

scholarly journals Semiarid grasslands and extreme precipitation events: Do experimental results scale to the landscape?

Ecology ◽  
2021 ◽  
Author(s):  
Alison K. Post ◽  
Kristin P. Davis ◽  
Jillian LaRoe ◽  
David L. Hoover ◽  
Alan K. Knapp
Keyword(s):  
Extreme Precipitation ◽  
Experimental Results ◽  
Extreme Precipitation Events ◽  
Precipitation Events

scholarly journals Quantifying the influence of natural climate variability on in situ measurements of seasonal total and extreme daily precipitation

2021 ◽  
Author(s):  
Mark D. Risser ◽  
Michael F. Wehner ◽  
John P. O’Brien ◽  
Christina M. Patricola ◽  
Travis A. O’Brien ◽  
...  
Keyword(s):  
Climate Variability ◽  
Extreme Precipitation ◽  
Southern Oscillation ◽  
Statistical Significance ◽  
In Situ Measurements ◽  
Climate Indices ◽  
Natural Climate Variability ◽  
Modes Of Variability ◽  
Natural Climate

AbstractWhile various studies explore the relationship between individual sources of climate variability and extreme precipitation, there is a need for improved understanding of how these physical phenomena simultaneously influence precipitation in the observational record across the contiguous United States. In this work, we introduce a single framework for characterizing the historical signal (anthropogenic forcing) and noise (natural variability) in seasonal mean and extreme precipitation. An important aspect of our analysis is that we simultaneously isolate the individual effects of seven modes of variability while explicitly controlling for joint inter-mode relationships. Our method utilizes a spatial statistical component that uses in situ measurements to resolve relationships to their native scales; furthermore, we use a data-driven procedure to robustly determine statistical significance. In Part I of this work we focus on natural climate variability: detection is mostly limited to DJF and SON for the modes of variability considered, with the El Niño/Southern Oscillation, the Pacific–North American pattern, and the North Atlantic Oscillation exhibiting the largest influence. Across all climate indices considered, the signals are larger and can be detected more clearly for seasonal total versus extreme precipitation. We are able to detect at least some significant relationships in all seasons in spite of extremely large (> 95%) background variability in both mean and extreme precipitation. Furthermore, we specifically quantify how the spatial aspect of our analysis reduces uncertainty and increases detection of statistical significance while also discovering results that quantify the complex interconnected relationships between climate drivers and seasonal precipitation.

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