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>

Extreme precipitating events in satellite and rain-gauge products over the Sahel

2022 ◽  
pp. 1-60
Keyword(s):  
Burkina Faso ◽  
West African Monsoon ◽  
Rain Gauge ◽  
Data Availability ◽  
Reference Dataset ◽  
Full Data ◽  
Global Precipitation Climatology Centre ◽  
Extreme Precipitation Events ◽  
Infrared Measurements ◽  
Precipitation Gauge

Abstract Over the recent decades, Extreme Precipitation Events (EPE) have become more frequent over the Sahel. Their properties, however, have so far received little attention. In this study the spatial distribution, intensity, seasonality and interannual variability of EPEs are examined, using both a reference dataset, based on a high-density rain-gauge network over Burkina Faso and 24 precipitation gridded datasets. The gridded datasets are evaluated in depth over Burkina Faso while their commonalities are used to document the EPE properties over the Sahel. EPEs are defined as the occurrence of daily-accumulated precipitation exceeding the all-day 99th percentile over a 1°x1° pixel. Over Burkina Faso, this percentile ranges between 21 and 33 mm day-1. The reference dataset show that EPEs occur in phase with the West African monsoon annual cycle, more frequently during the monsoon core season and during wet years. These results are consistent among the gridded datasets over Burkina Faso but also over the wider Sahel. The gridded datasets exhibit a wide diversity of skills when compared to the Burkinabe reference. The Global Precipitation Climatology Centre Full Data Daily version 1 (GPCC-FDDv1) and the Global Satellite Mapping of Precipitation gauge Reanalysis version 6.0 (GSMaP-gauge-RNL v6.0) are the only products that properly reproduce all of the EPE features examined in this work. The datasets using a combination of microwave and infrared measurements are prone to overestimate the EPE intensity, while infrared-only products generally underestimate it. Their calibrated versions perform than their uncalibrated (near-real-time) versions. This study finally emphasizes that the lack of rain-gauge data availability over the whole Sahel strongly impedes our ability to gain insights in EPE properties.

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 A New Land Surface Hydrology within the Noah-WRF Land-Atmosphere Mesoscale Model Applied to Semiarid Environment: Evaluation over the Dantiandou Kori (Niger)

2009 ◽  
Vol 2009 ◽  
pp. 1-13 ◽  
Author(s):  
B. Decharme ◽  
C. Ottlé ◽  
S. Saux-Picart ◽  
N. Boulain ◽  
B. Cappelaere ◽  
...  
Keyword(s):  
Land Surface ◽  
Mesoscale Model ◽  
West African Monsoon ◽  
Radar Data ◽  
Rain Gauge ◽  
Surface Energy Budget ◽  
Surface Hydrology ◽  
Land Surface Hydrology ◽  
Rain Gauge Network

Land-atmosphere feedbacks, which are particularly important over the Sahel during the West African Monsoon (WAM), partly depend on a large range of processes linked to the land surface hydrology and the vegetation heterogeneities. This study focuses on the evaluation of a new land surface hydrology within the Noah-WRF land-atmosphere-coupled mesoscale model over the Sahel. This new hydrology explicitly takes account for the Dunne runoff using topographic information, the Horton runoff using a Green-Ampt approximation, and land surface heterogeneities. The previous and new versions of Noah-WRF are compared against a unique observation dataset located over the Dantiandou Kori (Niger). This dataset includes dense rain gauge network, surfaces temperatures estimated from MSG/SEVIRI data, surface soil moisture mapping based on ASAR/ENVISAT C-band radar data and in situ observations of surface atmospheric and land surface energy budget variables. Generally, the WAM is reasonably reproduced by Noah-WRF even if some limitations appear throughout the comparison between simulations and observations. An appreciable improvement of the model results is also found when the new hydrology is used. This fact seems to emphasize the relative importance of the representation of the land surface hydrological processes on the WAM simulated by Noah-WRF over the Sahel.

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 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 The Contribution of Orographically Driven Banded Precipitation to the Rainfall Climatology of a Mediterranean Region

2011 ◽  
Vol 50 (11) ◽  
pp. 2235-2246 ◽  
Author(s):  
Angélique Godart ◽  
Sandrine Anquetin ◽  
Etienne Leblois ◽  
Jean-Dominique Creutin
Keyword(s):  
Deep Convection ◽  
Regional Climate ◽  
Extreme Rainfall ◽  
Rain Gauge ◽  
Western Mediterranean ◽  
Small Scale ◽  
Shallow Convection ◽  
Extreme Rainfall Events ◽  
Atmospheric Flow ◽  
Rainfall Climatology

AbstractStudies carried out worldwide show that topography influences rainfall climatology. As in most western Mediterranean regions, the mountainous Cévennes–Vivarais area in France regularly experiences extreme precipitation that may lead to devastating flash floods. Global warming could further aggravate this situation, but this possibility cannot be confirmed without first improving the understanding of the role of topography in the regional climate and, in particular, for extreme rainfall events. This paper focuses on organized banded rainfall and evaluates its contribution to the rainfall climatology of this region. Stationary rainfall systems made up of such bands are triggered and enhanced by small-scale interactions between the atmospheric flow and the relief. Rainbands are associated with shallow convection and are also present in deep-convection events for specific flux directions. Such precipitation patterns are difficult to observe both with operational weather radar networks, which are not designed to observe low-level convection within complex terrain, and with rain gauge networks, for which gauge spacing is typically larger than the bandwidth. A weather class of banded orographic shallow-convection events is identified, and the contribution of such events to annual or seasonal precipitation over the region is assessed. Moreover, a method is also proposed to quantify the contribution of banded convection during specific deep-convection events. It is shown that even though these orographically driven banded precipitation events produce moderate precipitation intensities they have long durations and therefore represent a significant amount of the rainfall climatology of the region, producing up to 40% of long-term total precipitation at certain locations.

 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 Analysis of predicted and observed accumulated convective precipitation in the area with frequent split storms

2011 ◽  
Vol 15 (12) ◽  
pp. 3651-3658 ◽  
Author(s):  
M. Ćurić ◽  
D. Janc
Keyword(s):  
Cloud Model ◽  
Extreme Rainfall ◽  
Rain Gauge ◽  
Convective Precipitation ◽  
Spatial And Temporal Variability ◽  
Extreme Rainfall Events ◽  
Small Areas ◽  
Convective Clouds ◽  
Rain Gauges ◽  
Cloud Resolving Model

Abstract. Convective clouds generate extreme rainfall events and flash floods in small areas with both large spatial and temporal variability. For this reason, the monitoring of the total accumulated precipitation fields at the surface with rain gauges and meteorological radars has both strengths and weakness. Alternatively, a numerical cloud model may be a useful tool to simulate convective precipitation for various analyses and predictions. The main objective of this paper is to show that the cloud-resolving model reproduces well the accumulated convective precipitation obtained from the rain gauge network data in the area with frequent split storms. We perform comparisons between observations and model samples of the areal accumulated convective precipitation for a 15-year period over treated area. Twenty-seven convective events have been selected. Statistical analyses reveal that the model areal accumulated convective precipitation closely match their observed values with a correlation coefficient of 0.80.

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.

Sign in / Sign up

Export Citation Format

Share Document