scholarly journals Evaluation of the TRMM product for monitoring drought over Paraíba State, northeastern Brazil: a trend analysis

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Reginaldo Moura Brasil Neto ◽  
Celso Augusto Guimarães Santos ◽  
Jorge Flávio Casé Braga da Costa Silva ◽  
Richarde Marques da Silva ◽  
Carlos Antonio Costa dos Santos ◽  
...  
Keyword(s):  
Standardized Precipitation Index ◽  
Tropical Rainfall Measuring Mission ◽  
Extreme Rainfall ◽  
Rain Gauge ◽  
Rainfall Data ◽  
Northeastern Brazil ◽  
Rainfall Time Series ◽  
Extreme Rainfall Events ◽  
Spatiotemporal Trends ◽  
The Standardized Precipitation Index

AbstractDroughts are complex natural phenomena that influence society's development in different aspects; therefore, monitoring their behavior and future trends is a useful task to assist the management of natural resources. In addition, the use of satellite-estimated rainfall data emerges as a promising tool to monitor these phenomena in large spatial domains. The Tropical Rainfall Measuring Mission (TRMM) products have been validated in several studies and stand out among the available products. Therefore, this work seeks to evaluate TRMM-estimated rainfall data's performance for monitoring the behavior and spatiotemporal trends of meteorological droughts over Paraíba State, based on the standardized precipitation index (SPI) from 1998 to 2017. Then, 78 rain gauge-measured and 187 TRMM-estimated rainfall time series were used, and trends of drought behavior, duration, and severity at eight time scales were evaluated using the Mann–Kendall and Sen tests. The results show that the TRMM-estimated rainfall data accurately captured the pattern of recent extreme rainfall events that occurred over Paraíba State. Drought events tend to be drier, longer-lasting, and more severe in most of the state. The greatest inconsistencies between the results obtained from rain gauge-measured and TRMM-estimated rainfall data are concentrated in the area closest to the coast. Furthermore, long-term drought trends are more pronounced than short-term drought, and the TRMM-estimated rainfall data correctly identified this pattern. Thus, TRMM-estimated rainfall data are a valuable source of data for identifying drought behavior and trends over much of the region.

scholarly journals Evaluation of the TRMM Product for Monitoring Drought over Paraíba State, Northeastern Brazil: A Statistical Analysis

2020 ◽  
Vol 12 (14) ◽  
pp. 2184 ◽  
Author(s):  
Reginaldo Moura Brasil Neto ◽  
Celso Augusto Guimarães Santos ◽  
Thiago Victor Medeiros do Nascimento ◽  
Richarde Marques da Silva ◽  
Carlos Antonio Costa dos Santos
Keyword(s):  
Time Scales ◽  
Standardized Precipitation Index ◽  
Tropical Rainfall Measuring Mission ◽  
Northeastern Brazil ◽  
Natural Phenomenon ◽  
Spatiotemporal Behavior ◽  
The Standardized Precipitation Index ◽  
Statistical Metrics ◽  
Rainfall Estimates ◽  
Different Time Scales

Drought is a natural phenomenon that originates from the absence of precipitation over a certain period and is capable of causing damage to societal development. With the advent of orbital remote sensing, rainfall estimates from satellites have appeared as viable alternatives to monitor natural hazards in ungauged basins and complex areas of the world; however, the accuracies of these orbital products still need to be verified. Thus, this work aims to evaluate the performance of Tropical Rainfall Measuring Mission (TRMM) satellite rainfall estimates in monitoring the spatiotemporal behavior of droughts at multiple temporal scales over Paraíba State based on the standardized precipitation index (SPI) over 20 years (1998–2017). For this purpose, rainfall data from 78 rain gauges and 187 equally spaced TRMM cell grids throughout the region are used, and accuracy analyses are performed at the single-gauge level and in four mesoregions at eight different time scales based on 11 statistical metrics calculations divided into three different categories. The results show that in the mesoregions close to the coast, the satellite-based product is less accurate in capturing the drought behavior regardless of the evaluated statistical metrics. At the temporal scale, the TRMM is more accurate in identifying the pattern of medium-term droughts; however, there is considerable spatial variation in the accuracy of the product depending on the performance index. Therefore, it is concluded that rainfall estimates from the TRMM satellite are a valuable source of data to identify drought behavior in a large part of Paraíba State at different time scales, and further multidisciplinary studies should be conducted to monitor these phenomena more accurately based on satellite data.

scholarly journals Changing Rainfall Patterns in an Era of Climate Change: A Multiparameter Spatiotemporal Analysis of Trends & Impacts for India

2020 ◽  
Author(s):  
Praharsh Patel ◽  
Adeel Khan
Keyword(s):  
Climate Change ◽  
Hydrological Cycle ◽  
Daily Rainfall ◽  
Water Security ◽  
Extreme Rainfall ◽  
Spatiotemporal Analysis ◽  
Rainfall Data ◽  
Extreme Rainfall Events ◽  
Spatiotemporal Trends ◽  
Rainfall Patterns

Abstract The hydrological cycle that starts with rainfall has been under major threat from the global temperature rise and climatic changes. In India, rainfall changes not only jeopardize water security but also have a major set-back for socio-economic stability. There have been attempts to decode the changing rainfall patterns in India but most of them conducted at wider spatial resolution (such as national, state, or sub-divisional level) fail to capture the essence of spatial variation in rainfall characteristics. To get a clearer understanding of change in key rainfall parameters, this paper analyses more than 197 million 0.25˚ x 0.25˚ gridded rainfall data points. The fine resolution 117 years (1901-2017) of daily rainfall data is utilized to test significant spatiotemporal trends in the quantum of rainfall and other key rainfall parameters such as rainy days, monsoon onset and withdrawal dates, occurrences of extreme rainfall events, and frequency of drought and high rainfall years. With an emphasis on changing climatic patterns since perceived climate change onset in the 1970s, the study identifies the regions with significant changes in rainfall patterns by comparing key parameters pre- & post- 1970s. The paper also highlights the major repercussions and challenges for the identified regions with significant changing rainfall patterns.

Changing Rainfall Patterns in India: A Spatiotemporal Analysis of Trends & Impacts

2020 ◽  
Author(s):  
Praharsh Patel ◽  
Adeel Khan
Keyword(s):  
Hydrological Cycle ◽  
Daily Rainfall ◽  
Water Security ◽  
Extreme Rainfall ◽  
Spatiotemporal Analysis ◽  
Rainfall Data ◽  
Extreme Rainfall Events ◽  
Spatiotemporal Trends ◽  
Rainfall Patterns ◽  
Fine Resolution

Abstract The hydrological cycle that starts with rainfall has been under major threat from the global temperature rise and climatic changes. In India, rainfall changes not only jeopardize water security but also have a major set-back for socio-economic stability. There have been attempts to decode the changing rainfall patterns in India but most of them conducted at wider spatial resolution (such as national, state, or sub-divisional level) fail to capture the essence of spatial variation in rainfall characteristics. To get a clearer understanding of change in key rainfall parameters, this paper analyses more than 197 million 0.25˚ x 0.25˚ gridded rainfall data points. The fine resolution 117 years (1901-2017) of daily rainfall data is utilized to test significant spatiotemporal trends in the quantum of rainfall and other key rainfall parameters such as rainy days, monsoon onset and withdrawal dates, occurrences of extreme rainfall events, and frequency of drought and high rainfall years. With an emphasis on changing climatic patterns since perceived climate change onset in the 1970s, the study identifies the regions with significant changes in rainfall patterns by comparing key parameters pre- & post- 1970s. The paper also highlights the major repercussions and challenges for the identified regions with significant changing rainfall patterns.

Heavy precipitating events in satellites and rain-gauge products over the Sahel

2021 ◽  
Author(s):  
Sidiki Sanogo ◽  
Philippe Peyrillé ◽  
Romain Roehrig ◽  
Françoise Guichard ◽  
Ousmane Ouedraogo
Keyword(s):  
Burkina Faso ◽  
West African Monsoon ◽  
Extreme Rainfall ◽  
Rain Gauge ◽  
Reference Dataset ◽  
Extreme Rainfall Events ◽  
Microwave Sensor ◽  
Sahel Region ◽  
Distribution Intensity ◽  
Rain Gauge Network

<p>The Sahel has experienced an increase in the frequency and intensity of extreme rainfall events over the recent decades. These trends are expected to continue in the future. However the properties of these events have so far received little attention. In the present study, we define a heavy precipitating event (HPE) as the occurrence of daily-mean precipitation exceeding a given percentile (e.g., 99<sup>th</sup> and higher) over a 1°x1° pixel and examine their spatial distribution, intensity, seasonality and interannual variability. We take advantage of an original reference dataset based on a rather high-density rain-gauge network over Burkina Faso (142 stations) to evaluate 22 precipitation gridded datasets often used in the literature, based on rain-gauge-only measurements, satellite measurements, or both. Our reference dataset documents the HPEs over Burkina Faso. The 99<sup>th</sup> percentile identifies events greater than 26 mm d<sup>-1</sup> with a ~2.5 mm confidence interval depending on the number of stations within a 1°x1° pixel. The HPEs occur in phase with the West African monsoon annual cycle, more frequently during the monsoon core season and during wet years. The evaluation of the gridded rainfall products reveals that only two of the datasets, namely the rain-gauge-only based products GPCC-DDv1 and REGENv1, are able to properly reproduce all of the HPE features examined in the present work. A subset of the remaining rainfall products also provide satisfying skills over Burkina Faso, but generally only for a few HPE features examined here. In particular, we notice a general better performance for rainfall products that include rain-gauge data in the calibration process, while estimates using microwave sensor measurements are prone to overestimate the HPE intensity. The agreement among the 22 datasets is also assessed over the entire Sahel region. While the meridional gradient in HPE properties is well captured by the good performance subset, the zonal direction exhibit larger inter-products spread. This advocates for the need to continue similar evaluation with the available rain-gauge network available in West Africa, both to enhance the HPE documentation and understanding at the scale of the region and to help improve the rainfall dataset quality.</p>

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.

scholarly journals Data analysis reveals that extreme events have increased the flood inundations in the Taquari River´s Valley, southern Brazil

2021 ◽  
Vol 1 (1) ◽  
pp. 16-25
Author(s):  
Francisco Manoel Wohnrath Tognoli ◽  
Sabrina Deconti Bruski ◽  
Thiago Peixoto de Araujo
Keyword(s):  
Extreme Events ◽  
Extreme Rainfall ◽  
Maximum Level ◽  
Data Series ◽  
Rainfall Time Series ◽  
Southern Brazil ◽  
Human Occupation ◽  
Extreme Rainfall Events ◽  
Starting Point ◽  
The City

Flood inundations represent more than 62% of the deaths caused by natural disasters in Brazil. The dataset comprises the records of the Encantado´s pluviometric station, a municipality located beside the margin of the Taquari River in southern Brazil, which comprises the rainfall time series (n = 36,466) over 78 years, from April 1943 to December 2020. Complementary datasets also include the annual volume of precipitation per year and the level reached by the Taquari River during 44 flood inundations since 1941. The number of events is subsampled because only 32 years have the complete record of the river level. Three of the five major flood inundations at Encantado occurred after 2001, and the more severe flood recorded the maximum level of the Taquari River (20,27 meters) on July 8th, 2020. Thirty-four percent of all flood inundations in the city were recorded between 2011 and 2020. The months of July to October record 70% of all the events, but there is no record of floods in February and December throughout the data series. The human occupation of the floodplain has been fast in the last decades, and most of the urban area has a potential risk of being affected by flood inundations. Moreover, extreme rainfall events and flood events have been more frequent in the last 30 years. This database can contribute as a starting point for developing predictive models and verifying a possible correlation of floods with extreme events and global climatic changes.

Extreme Rainfall Events in the Macro-Metropolis of São Paulo: trends and connection with climate oscillations

2021 ◽  
Author(s):  
Carolyne B. Machado ◽  
Thamiris L. O. B. Campos ◽  
Sameh A. Abou Rafee ◽  
Jorge A. Martins ◽  
Alice M. Grimm ◽  
...  
Keyword(s):  
Urban Areas ◽  
Extreme Rainfall ◽  
Kendall Test ◽  
Rain Gauge ◽  
Sao Paulo ◽  
Annual Rainfall ◽  
São Paulo ◽  
Wet Season ◽  
Extreme Rainfall Events ◽  
Climatic Indices

AbstractIn the present work, the trend of extreme rainfall indices in the Macro-Metropolis of São Paulo (MMSP) was analyzed and correlated with largescale climatic oscillations. A cluster analysis divided a set of rain gauge stations into three homogeneous regions within MMSP, according to the annual cycle of rainfall. The entire MMSP presented an increase in the total annual rainfall, from 1940 to 2016, of 3 mm per year on average, according to Mann-Kendall test. However, there is evidence that the more urbanized areas have a greater increase in the frequency and magnitude of extreme events, while coastal and mountainous areas, and regions outside large urban areas, have increasing rainfall in a better-distributed way throughout the year. The evolution of extreme rainfall (95th percentile) is significantly correlated with climatic indices. In the center-north part of the MMSP, the combination of Pacific Decadal Oscillation (PDO) and Antarctic Oscillation (AAO) explains 45% of the P95th increase during the wet season. In turn, in southern MMSP, the Temperature of South Atlantic (TSA), the AAO, the El Niño South Oscillation (ENSO) and the Multidecadal Oscillation of the North Atlantic (AMO) better explain the increase in extreme rainfall (R2 = 0.47). However, the same is not observed during the dry season, in which the P95th variation was only negatively correlated with the AMO, undergoing a decrease from the ‘70s until the beginning of this century. The occurrence of rainy anomalous months proved to be more frequent and associated with climatic indices than dry months.

scholarly journals Analysis of Drought in the Northern Region of Bangladesh Using Standardized Precipitation Index (SPI)

2019 ◽  
Vol 11 (1-2) ◽  
pp. 199-216
Author(s):  
R Afrin ◽  
F Hossain ◽  
SA Mamun
Keyword(s):  
Standardized Precipitation Index ◽  
Extended Period ◽  
Northern Region ◽  
Precipitation Index ◽  
Rainfall Data ◽  
Extreme Drought ◽  
Severe Drought ◽  
Drought Analysis ◽  
Dry Conditions ◽  
The Standardized Precipitation Index

Drought is an extended period when a region notes a deficiency in its water supply. The Standardized Precipitation Index (SPI) method was used in this study to analyze drought. Northern region of Bangladesh was the area of study. Monthly rainfall data of northern region of Bangladesh was obtained from the Meteorological Department of Bangladesh. Obtained rainfall data was from 1991 to 2011 and values from 2012 to 2026 were generated using Markov model. Then SPI values from 1991 to 2026 were calculated by using SPI formula for analyzing drought. Analysis with SPI method showed that droughts in northern region of Bangladesh varied from moderately dry to severely dry conditions and it may vary from moderately dry to severely dry conditions normally in future but in some cases extreme drought may also take place. From the study, it is observed that the northern region of Bangladesh has already experienced severe drought in 1991, 1992, 1994, 1995, 1997, 1998, 2000, 2003, 2005, 2007, 2009 and 2010. The region may experience severe drought in 2012, 2015, 2016, 2018, 2019, 2021, 2022, 2023, 2024, 2025 and 2026 and extreme drought in 2012, 2014, 2016, 2023 and 2024. J. Environ. Sci. & Natural Resources, 11(1-2): 199-216 2018

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.

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