scholarly journals Improving an Extreme Rainfall Detection System with GPM IMERG data

2019 ◽  
Vol 11 (6) ◽  
pp. 677 ◽  
Author(s):  
Paola Mazzoglio ◽  
Francesco Laio ◽  
Simone Balbo ◽  
Piero Boccardo ◽  
Franca Disabato
Keyword(s):  
Detection System ◽  
Extreme Rainfall ◽  
Rain Gauge ◽  
Probability Of Detection ◽  
Mean Annual Precipitation ◽  
Extreme Rainfall Events ◽  
Rainfall Events ◽  
Time Aggregation ◽  
Spatial Coverage ◽  
Rainfall Detection

Many studies have shown a growing trend in terms of frequency and severity of extreme events. As never before, having tools capable to monitor the amount of rain that reaches the Earth’s surface has become a key point for the identification of areas potentially affected by floods. In order to guarantee an almost global spatial coverage, NASA Global Precipitation Measurement (GPM) IMERG products proved to be the most appropriate source of information for precipitation retrievement by satellite. This study is aimed at defining the IMERG accuracy in representing extreme rainfall events for varying time aggregation intervals. This is performed by comparing the IMERG data with the rain gauge ones. The outcomes demonstrate that precipitation satellite data guarantee good results when the rainfall aggregation interval is equal to or greater than 12 h. More specifically, a 24-h aggregation interval ensures a probability of detection (defined as the number of hits divided by the total number of observed events) greater than 80%. The outcomes of this analysis supported the development of the updated version of the ITHACA Extreme Rainfall Detection System (ERDS: erds.ithacaweb.org). This system is now able to provide near real-time alerts about extreme rainfall events using a threshold methodology based on the mean annual precipitation.

scholarly journals Extreme Rainfall in the Mediterranean: What Can We Learn from Observations?

2013 ◽  
Vol 14 (3) ◽  
pp. 906-922 ◽  
Author(s):  
N. Rebora ◽  
L. Molini ◽  
E. Casella ◽  
A. Comellas ◽  
E. Fiori ◽  
...  
Keyword(s):  
Extreme Rainfall ◽  
Flash Floods ◽  
Rain Gauge ◽  
Extreme Rainfall Events ◽  
Rainfall Events ◽  
Life Threatening ◽  
The Mediterranean ◽  
Moderate Resolution Imaging Spectroradiometer ◽  
Ground Effects

Abstract Flash floods induced by extreme rainfall events represent one of the most life-threatening phenomena in the Mediterranean. While their catastrophic ground effects are well documented by postevent surveys, the extreme rainfall events that generate them are still difficult to observe properly. Being able to collect observations of such events will help scientists to better understand and model these phenomena. The recent flash floods that hit the Liguria region (Italy) between the end of October and beginning of November 2011 give us the opportunity to use the measurements available from a large number of sensors, both ground based and spaceborne, to characterize these events. In this paper, the authors analyze the role of the key ingredients (e.g., unstable air masses, moist low-level jets, steep orography, and a slow-evolving synoptic pattern) for severe rainfall processes over complex orography. For the two Ligurian events, this role has been analyzed through the available observations (e.g., Meteosat Second Generation, Moderate Resolution Imaging Spectroradiometer, the Italian Radar Network mosaic, and the Italian rain gauge network observations). The authors then address the possible role of sea–atmosphere interactions and propose a characterization of these events in terms of their predictability.

 Evaluation of high resolution WRF forecasts for Extreme Rainfall Events over Karnataka against high density in-situ observations 

2021 ◽  
Author(s):  
Ajay Bankar ◽  
Rakesh Vasudevan
Keyword(s):  
Prediction Models ◽  
Initial Conditions ◽  
Weather Prediction ◽  
Wrf Model ◽  
Extreme Rainfall ◽  
Rain Gauge ◽  
Distinct Advantage ◽  
Extreme Rainfall Events ◽  
Rainfall Events ◽  
Synoptic Conditions

<p><span>Extreme Rainfall Events (EREs) in India has increased many folds in recent decades. These severe weather events are generally destructive in nature causing flash floods, catastrophic loss of life and property over densely populated urban cities. Various cities in Karnataka, a southern state in India, witnessed many EREs recently. Appropriate advanced warning systems to predict these events are crucial for preparedness of mitigation strategy to reduce human casualty and socio economic loss. Mesoscale models are essential tools for developing an integrated platform for disaster warning and management. From a stakeholder/user pint of view, primary requirement to tackle ERE related damages is accurate prediction of the observed rainfall location, coverage and intensity in advance. Weather prediction models have inherent limitations imposed primarily by approximations in the model and inadequacies in data. Hence, it is important to evaluate the skill of these models for many cases under different synoptic conditions to quantify model skill before using them for operational applications. The objective of the study is to evaluate performance of the Weather Research and Forecasting (WRF) model for several ERE cases in Karnataka at different model initial conditions. The EREs were identified from the distribution of rainfall events over different regions in Karnataka and those events comes under 1% probability were considered. We examined 38 ERE’s distributed over Karnataka for the period June to November for the years 2015-2019. WRF model is configured with 3 nested domains with outer, inner and innermost domains having resolution of 12 km, 9 km and 3 km respectively. Two sets of simulations are conducted in this study, i) staring at 12 hours prior to the ERE day (i.e. -1200 UTC) & ii) starting at 0000 UTC of the ERE day. Performance of the WRF model forecast is validated against 15 minutes rainfall observations from ~6000 rain gauge stations over Karnataka. During initial hours forecasts initiated at 1200 UTC has distinct advantage in terms of accuracy compared to those initiated at 0000 UTC for most of the cases. In general, model underpredict EREs and underprediction is relatively low for forecasts initiated at 12 00 UTC.</span></p>

scholarly journals Verification of APHRODITE Precipitation Data Set in Bangladesh

2021 ◽  
Vol 12 (1) ◽  
pp. 51-56
Author(s):  
Md Atiqul Islam ◽  
Asif Ahmed ◽  
Md Munirujjaman Munir ◽  
Zarif Zaman Khandakar
Keyword(s):  
Extreme Rainfall ◽  
Absolute Error ◽  
Rain Gauge ◽  
Probability Of Detection ◽  
False Alarms ◽  
Data Set ◽  
Study Region ◽  
Rainfall Events ◽  
Rain Gauges ◽  
Precipitation Threshold

We investigated the preformance of Asian Precipitation-Highly-Resolved Observational Data Integration Towards Evaluation (APHRODITE) of water resources precipitation products in Bangladesh taking rain gauge data as reference for a 3-year period (2003-2005). Various statistical and categorical indices such as coefficient of correlation (CC), bias, relative bias (RB), mean absolute error (MAE), root mean square error (RMSE), probability of detection (POD), and false alarm ratio (FAR), were applied to measure the performance of the product. With CC value of 0.85, bias of 0.91, RB of -9.5%, MAE of 7.7 mm, and RMSE of 15.2 mm the product tended to underestimate rainfall values during the study period. Although, the POD score of 1.00 demonstrated very good skill in detecting the occurrence of rainfall events, FAR value of 0.25 indicated a considerable amount of false alarms. Moreover, as the precipitation threshold increased, the underestimation became more prominent over the study region. Analysis on the basis of location of the rain gauges also showed that APHRODITE consistently underestimated rainfall values with the increase of extreme rainfall thresholds. Journal of Engineering Science 12(1), 2021, 51-56

scholarly journals On the Epochal Strengthening in the Relationship between Rainfall of East Africa and IOD

2013 ◽  
Vol 26 (15) ◽  
pp. 5655-5673 ◽  
Author(s):  
Desmond Manatsa ◽  
Swadhin K. Behera
Keyword(s):  
East Africa ◽  
Rainfall Variability ◽  
Spatial Coherence ◽  
Principal Component ◽  
Extreme Rainfall ◽  
Rain Gauge ◽  
Monthly Precipitation ◽  
Extreme Rainfall Events ◽  
Rainfall Events ◽  
Global Precipitation Climatology Centre

Abstract Variability of the equatorial East Africa “short rains” (EASR) has intensified significantly since the turn of the twentieth century. This increase toward more extreme rainfall events has not been gradual but is strongly characterized by epochs. The rain gauge–based Global Precipitation Climatology Centre (GPCC) monthly precipitation dataset for the period 1901–2009 is used to demonstrate that the epochal changes were dictated by shifts in the Indian Ocean dipole (IOD) mode. These shifts occurred during 1961 and 1997. In the pre-1961 period, there was virtually no significant linear link between the IOD and the EASR. But a relatively strong coupling between the two occurred abruptly in 1961 and was generally maintained at that level until 1997, when another sudden shift to even a greater level occurred. The first principal component (PC1) extracted from the EASR spatial domain initially merely explained about 50% of the rainfall variability before 1961, and then catapulted to about 73% for the period from 1961 to 1997, before eventually shifting to exceed 82% after 1997. The PC1 for each successive epoch also displayed loadings with notably improved spatial coherence. This systematic pattern of increase was accompanied by both a sharp increase in the frequency of rainfall extremes and spatial coherence of the rainfall events over the region. Therefore, it is most likely that the 1961 and 1997 IOD shifts are responsible for the epochal modulation of the EASR in both the spatial and temporal domain.

scholarly journals Extreme rainfall events in the Northeastern USA become more frequent with rising temperatures, but their intensity distribution remains stable

2021 ◽  
pp. 1-51
Author(s):  
Helga Kristin Olafsdottir ◽  
Holger Rootzén ◽  
David Bolin
Keyword(s):  
Extreme Rainfall ◽  
Rain Gauge ◽  
Series Data ◽  
Extreme Rainfall Events ◽  
Rainfall Events ◽  
Daily Data ◽  
Extreme Value Model ◽  
Value Model ◽  
Increasing Trends ◽  
Northeastern Usa

AbstractBoth intensities of individual extreme rainfall events and the frequency of such events are important for infrastructure planning. We develop a new statistical extreme value model, the PGEV model, which makes it possible to use high quality annual maximum series data instead of lesswell checked daily data to estimate trends in intensity and frequency separately. The method is applied to annual maxima data from the NOAA Atlas 14, Volume 10, dating from approximately 1900 to 2014, showing that in the majority of 333 rain gauge stations in the Northeastern USA the frequency of extreme rainfall events increases as mean temperature increases, but that there is little evidence of trends in the distribution of the intensities of individual extreme rainfall events. The median of the frequency trends corresponds to extreme rainfalls becoming 83% more frequent for each centigrade degree of temperature increase. Naturally, increasing trends in frequency also increase the yearly or 10-yearly risks of very extreme rainfall events. Three other large areas in the contiguous USA, the Midwest, the Southeast, and Texas, are also studied, and show similar but weaker trends than those in the Northeast.

The Influence of Geographical Factors on Extreme Rainfalls in Lampung Province

2019 ◽  
Vol 1 (1) ◽  
pp. 33
Author(s):  
M Welly
Keyword(s):  
Geographical Location ◽  
Daily Rainfall ◽  
Extreme Rainfall ◽  
Design Flood ◽  
Extreme Rainfall Events ◽  
Rainfall Events ◽  
Ungauged Basin ◽  
Flood Discharge ◽  
Design Rainfall ◽  
Geographical Factors

Many people in Indonesia calculate design rainfall before calculating the design flooddischarge. The design rainfall with a certain return period will eventually be convertedinto a design flood discharge by combining it with the characteristics of the watershed.However, the lack of a network of rainfall recording stations makes many areas that arenot hydrologically measured (ungauged basin), so it is quite difficult to know thecharacteristics of rain in the area concerned. This study aims to analyze thecharacteristics of design rainfall in Lampung Province. The focus of the analysis is toinvestigate whether geographical factors influence the design rainfall that occurs in theparticular area. The data used in this study is daily rainfall data from 15 rainfallrecording stations spread in Lampung Province. The method of frequency analysis usedin this study is the Gumbel method. The research shows that the geographical location ofan area does not have significant effect on extreme rainfall events. The effect of risingearth temperatures due to natural exploitation by humans tends to be stronger as a causeof extreme events such as extreme rainfall.Keywords: Influence, geographical, factors, extreme, rainfall.

CLIMATOLOGY OF EXTREME RAINFALL EVENTS IN EASTERN AND NORTHERN SANTA CATARINA STATE, BRAZIL: PRESENT AND FUTURE CLIMATE

2013 ◽  
Vol 31 (3) ◽  
pp. 413 ◽  
Author(s):  
André Becker Nunes ◽  
Gilson Carlos Da Silva
Keyword(s):  
Climate Model ◽  
Climate Modeling ◽  
Linear Trend ◽  
Extreme Rainfall ◽  
Eastern Region ◽  
Santa Catarina ◽  
Extreme Rainfall Events ◽  
Rainfall Events ◽  
History Of ◽  
Santa Catarina State

ABSTRACT. The eastern region of Santa Catarina State (Brazil) has an important history of natural disasters due to extreme rainfall events. Floods and landslides are enhancedby local features such as orography and urbanization: the replacement of natural surface coverage causing more surface runoff and, hence, flooding. Thus, studies of this type of events – which directly influence life in the towns – take on increasing importance. This work makes a quantitative analysis of occurrences of extreme rainfall events in the eastern and northern regions of Santa Catarina State in the last 60 years, through individual analysis, considering the history of floods ineach selected town, as well as an estimate through to the end of century following regional climate modeling. A positive linear trend, in most of the towns studied, was observed in the results, indicating greater frequency of these events in recent decades, and the HadRM3P climate model shows a heterogeneous increase of events for all towns in the period from 2071 to 2100.Keywords: floods, climate modeling, linear trend. RESUMO. A região leste do Estado de Santa Catarina tem um importante histórico de desastres naturais ocasionados por eventos extremos de precipitação. Inundações e deslizamentos de terra são potencializados pelo relevo acidentado e pela urbanização das cidades da região: a vegetação nativa vem sendo removida acarretando um maior escoamento superficial e, consequentemente, em inundações. Desta forma, torna-se de suma importância os estudos acerca deste tipo de evento que influencia diretamente a sociedade em geral. Neste trabalho é realizada uma análise quantitativa do número de eventos severos de precipitação ocorridos nas regiões leste e norte de Santa Catarina dos últimos 60 anos, por meio de uma análise pontual, considerandoo histórico de inundações de cada cidade selecionada, além de uma projeção para o fim do século de acordo com modelagem climática regional. Na análise dos resultados observou-se uma tendência linear positiva na maioria das cidades, indicando uma maior frequência deste tipo de evento nas últimas décadas, e o modelo climático HadRM3P mostra um aumento heterogêneo no número de eventos para todas as cidades no período de 2071 a 2100.Palavras-chave: inundações, modelagem climática, tendência linear.

Comparing vulnerability and institutional capacities in three Latin American coastal localities in response to extreme rainfall events

2021 ◽  
Vol 25 (1) ◽  
Author(s):  
Arturo Ruiz-Luna ◽  
Claudia Martínez-Peralta ◽  
Patricia P. B. Eichler ◽  
Leonardo R. Teixeira ◽  
Montserrat Acosta-Morel ◽  
...  
Keyword(s):  
Latin American ◽  
Extreme Rainfall ◽  
Extreme Rainfall Events ◽  
Rainfall Events

scholarly journals Tropical cyclone contribution to extreme rainfall over southwest Pacific Island nations

2021 ◽  
Author(s):  
Anil Deo ◽  
Savin S. Chand ◽  
Hamish Ramsay ◽  
Neil J. Holbrook ◽  
Simon McGree ◽  
...  
Keyword(s):  
Tropical Cyclone ◽  
El Niño ◽  
El Nino ◽  
Extreme Rainfall ◽  
Pacific Island ◽  
Extreme Rainfall Events ◽  
Rainfall Events ◽  
Southwest Pacific ◽  
Inactive Phase ◽  
Pacific Island Nations

AbstractSouthwest Pacific nations are among some of the worst impacted and most vulnerable globally in terms of tropical cyclone (TC)-induced flooding and accompanying risks. This study objectively quantifies the fractional contribution of TCs to extreme rainfall (hereafter, TC contributions) in the context of climate variability and change. We show that TC contributions to extreme rainfall are substantially enhanced during active phases of the Madden–Julian Oscillation and by El Niño conditions (particularly over the eastern southwest Pacific region); this enhancement is primarily attributed to increased TC activity during these event periods. There are also indications of increasing intensities of TC-induced extreme rainfall events over the past few decades. A key part of this work involves development of sophisticated Bayesian regression models for individual island nations in order to better understand the synergistic relationships between TC-induced extreme rainfall and combinations of various climatic drivers that modulate the relationship. Such models are found to be very useful for not only assessing probabilities of TC- and non-TC induced extreme rainfall events but also evaluating probabilities of extreme rainfall for cases with different underlying climatic conditions. For example, TC-induced extreme rainfall probability over Samoa can vary from ~ 95 to ~ 75% during a La Niña period, if it coincides with an active or inactive phase of the MJO, and can be reduced to ~ 30% during a combination of El Niño period and inactive phase of the MJO. Several other such cases have been assessed for different island nations, providing information that have potentially important implications for planning and preparing for TC risks in vulnerable Pacific Island nations.

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