Synoptic environment associated with heavy rainfall events on the coastland of Northeast Brazil

Abstract. Northeast Brazil (NEB) has an extensive coastal area, often hit by natural disasters that bring many social and economic losses. The objective of this work was to study the synoptic environment associated with a heavy rainfall event (HRE) on the coastland of NEB. We used daily rainfall data for coastal area of NEB between the states of Rio Grande do Norte and Bahia, divided into two subregions: north and south coastland. This data was obtained from the hydrometeorological network managed by the Agência Nacional de Águas and the daily data reanalysis from the ERAInterim. For the selection of HRE the technique of quantiles was used, thus defined HRE where at least one rain gauge recorded rainfall above 95th percentile. The interannual distribution of events showed occurrence maximum in La Niña years and minimal in El Niño years. The results suggest that the HRE were formed mainly due to the action of upper-level cyclonic vortex, in hight levels, and due to the action to South Atlantic convergence zone, in low levels.

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A Comparison Between Global Satellite Mapping of Precipitation Data and High-Resolution Radar Data – A Case Study of Localized Torrential Rainfall over Japan

Journal of Disaster Research ◽

10.20965/jdr.2021.p0786 ◽

2021 ◽

Vol 16 (4) ◽

pp. 786-793

Author(s):

Yoshiaki Hayashi ◽

Taichi Tebakari ◽

Akihiro Hashimoto ◽

◽

Keyword(s):

High Resolution ◽

Heavy Rainfall ◽

Daily Rainfall ◽

Radar Data ◽

Rain Gauge ◽

Hourly Rainfall ◽

The Difference ◽

Microwave Imager ◽

Satellite Mapping

This paper presents a case study comparing the latest algorithm version of Global Satellite Mapping of Precipitation (GSMaP) data with C-band and X-band Multi-Parameter (MP) radar as high-resolution rainfall data in terms of localized heavy rainfall events. The study also obliged us to clarify the spatial and temporal resolution of GSMaP data using high-accuracy ground-based radar, and evaluate the performance and reporting frequency of GSMaP satellites. The GSMaP_Gauge_RNL data with less than 70 mm/day of daily rainfall was similar to the data of both radars, but the GSMaP_Gauge_RNL data with over 70 mm/day of daily rainfall was not, and the calibration by rain-gauge data was poor. Furthermore, both direct/indirect observations by the Global Precipitation Measurement/Microwave Imager (GPM/GMI) and the frequency thereof (once or twice) significantly affected the difference between GPM/GMI data and C-band radar data when the daily rainfall was less than 70 mm/day and the hourly rainfall was less than 20 mm/h. Therefore, it is difficult for GSMaP_Gauge to accurately estimate localized heavy rainfall with high-density particle precipitation.

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Mesoscale Convective Systems: A Case Scenario of the ‘Heavy Rainfall’ Event of 15–20 January 2013 over Southern Africa

Climate ◽

10.3390/cli7060073 ◽

2019 ◽

Vol 7 (6) ◽

pp. 73

Author(s):

Modise Wiston ◽

Kgakgamatso Marvel Mphale

Keyword(s):

Atlantic Ocean ◽

Southern Africa ◽

Heavy Rainfall ◽

Rainfall Event ◽

Mesoscale Convective Systems ◽

Heavy Rainfall Event ◽

Convergence Zone ◽

Convective Systems ◽

Mesoscale Convective ◽

Upper Level

Southern east Africa is prone to some extreme weather events and interannual variability of the hydrological cycle, including tropical cyclones and heavy rainfall events. Most of these events occur during austral summer and are linked to shifts in the intertropical convergence zone, changes in El Niño Southern Oscillation signatures, sea surface temperature and sea level pressure. A typical example include mesoscale convective systems (MCSs) that occur between October and March along the eastern part, adjacent to the warm waters of Mozambique Channel and Agulhas Current. In this study we discuss a heavy rainfall event over southern Africa, focusing particularly on the period 15–20 January 2013, the period during which MCSs were significant over the subcontinent. This event recorded one of the historic rainfalls due to extreme flooding and overflows, loss of lives and destruction of economic and social infrastructure. An active South Indian Convergence Zone was associated with the rainfall event sustained by a low-level trough linked to a Southern Hemisphere planetary wave pattern and an upper-level ridge over land. In addition, also noteworthy is a seemingly strong connection to the strength of the African Easterly Jet stream. Using rainfall data, satellite imagery and re-analysis (model processed data combined with observations) data, our analysis indicates that there was a substantial relation between rainfall totals recorded/observed and the presence of MCSs. The low-level trough and upper-level ridge contributed to moisture convergence, particularly from tropical South East Atlantic Ocean, which in turn contributed to the prolonged life span of the rainfall event. Positive temperature anomalies favored the substantial contribution of moisture fluxes from the Atlantic Ocean. This study provides a contextual assessment of rainfall processes and insight into the physical control mechanisms and feedback of large-scale convective interactions over tropical southern Africa.

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Mesoscale and Local Scale Evaluations of Quantitative Precipitation Estimates by Weather Radar Products during a Heavy Rainfall Event

Advances in Meteorology ◽

10.1155/2016/6089319 ◽

2016 ◽

Vol 2016 ◽

pp. 1-9 ◽

Cited By ~ 6

Author(s):

Basile Pauthier ◽

Benjamin Bois ◽

Thierry Castel ◽

D. Thévenin ◽

Carmela Chateau Smith ◽

...

Keyword(s):

High Resolution ◽

Heavy Rainfall ◽

Rain Gauge ◽

Local Scale ◽

Rainfall Event ◽

Heavy Rainfall Event ◽

Preliminary Evaluation ◽

Rainfall Variation ◽

Hourly Rainfall ◽

Rain Gauge Network

A 24-hour heavy rainfall event occurred in northeastern France from November 3 to 4, 2014. The accuracy of the quantitative precipitation estimation (QPE) by PANTHERE and ANTILOPE radar-based gridded products during this particular event, is examined at both mesoscale and local scale, in comparison with two reference rain-gauge networks. Mesoscale accuracy was assessed for the total rainfall accumulated during the 24-hour event, using the Météo France operational rain-gauge network. Local scale accuracy was assessed for both total event rainfall and hourly rainfall accumulations, using the recently developed HydraVitis high-resolution rain gauge network Evaluation shows that (1) PANTHERE radar-based QPE underestimates rainfall fields at mesoscale and local scale; (2) both PANTHERE and ANTILOPE successfully reproduced the spatial variability of rainfall at local scale; (3) PANTHERE underestimates can be significantly improved at local scale by merging these data with rain gauge data interpolation (i.e., ANTILOPE). This study provides a preliminary evaluation of radar-based QPE at local scale, suggesting that merged products are invaluable for applications at very high resolution. The results obtained underline the importance of using high-density rain-gauge networks to obtain information at high spatial and temporal resolution, for better understanding of local rainfall variation, to calibrate remotely sensed rainfall products.

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Improving weather forecasts by means of HPC solutions: the LEXIS approach in the 2020 Bitti flood event

10.5194/ems2021-125 ◽

2021 ◽

Author(s):

Paola Mazzoglio ◽

Paolo Pasquali ◽

Andrea Parodi ◽

Antonio Parodi

Keyword(s):

Real Time ◽

Spatial Resolution ◽

Early Warning ◽

Heavy Rainfall ◽

Large Scale ◽

Detection System ◽

Daily Rainfall ◽

Early Warning Systems ◽

Flood Event ◽

Heavy Rainfall Event

In the framework of LEXIS (Large-scale EXecution for Industry & Society) H2020 project, CIMA Research Foundation is running a 3 nested domain WRF (Weather Research and Forecasting) model with European coverage and weather radar data assimilation over Italy. Forecasts up to 48 hours characterized by a 7.5 km resolution are then processed by ITHACA ERDS (Extreme Rainfall Detection System), an early warning system for the heavy rainfall monitoring and forecasting. This type of information is currently managed by ERDS together with two global-scale datasets. The first one is provided by NASA/JAXA GPM (Global Precipitation Measurement) Mission through the IMERG (Integrated Multi-satellitE Retrievals for GPM) Early run data, a near real-time rainfall information with hourly updates, 0.1&#176; spatial resolution and a 4 hours latency. The second one is instead provided by GFS (Global Forecast System) at a 0.25&#176; spatial resolution. The entire WRF-ERDS workflow has been tested and validated on the heavy rainfall event that affected the Sardinia region between 27 and 29 November 2020. This convective event significantly impacted the southern and eastern areas of the island, with a daily rainfall depth of 500.6 mm recorded at Oliena and 328.6 mm recorded at Bitti. During the 28th, the town of Bitti (Nuoro province) was hit by a severe flood event. Near real-time information provided by GPM data allowed us to issue alerts starting from the late morning of the 28th. The first alert over Sardinia based on GFS data was provided in the late afternoon of the 27th, about 40 km far from Bitti. In the early morning of the 28th, a new and more precise alert was issued over Bitti. The first alert based on WRF data was instead provided in the morning of the 27th and the system continued to issue alerts until the evening of the 29th, confirming that, for this type of event, precise forecasts are needed to provide timely alerts. Obtained results show how, taking advantage of HPC resources to perform finer weather forecast experiments, it is possible to significantly improve the capabilities of early warning systems. By using WRF data, ERDS was able to provide heavy rainfall alerts one day before than with the other data. The integration within the LEXIS platform will help with the automatization by data-aware orchestration of our workflow together with easy control of data and workflow steps through a user-friendly web interface.

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Increase in the frequency of heavy rainfall events over the UK in the light of climate change.

10.5194/egusphere-egu2020-11025 ◽

2020 ◽

Author(s):

Daniel Cotterill ◽

Peter Stott ◽

Elizabeth Kendon

Keyword(s):

Climate Change ◽

High Resolution ◽

Heavy Rainfall ◽

Daily Rainfall ◽

Heavy Rainfall Event ◽

Climate Projections ◽

Intense Rainfall ◽

Rainfall Events ◽

Climate Forcings ◽

The Uk

We investigate the attribution of the flooding in Northern England that saw at least 500 homes flooded and over 1000 properties evacuated in flooded areas in 2019. This occurred during the wettest Autumn on record in some areas and also contained some very high daily rainfall totals. In the light of climate change, it is expected that intense rainfall events are to become more intense as a result of increased global average temperatures and the Clausius-Clapeyron relationship, but here we investigate quantitatively how much climate change has increased the risk of such an event to date.We use results from the 2.2km convective permitting high resolution local UK Climate Projections (UKCP) and observations to show that more intense rainfall events may already be occurring in Autumn in the UK. This work shows using this high resolution UKCP data that a heavy rainfall event exceeding 50mm in one day in Autumn was 33-40% more likely to occur in 2019 than 1985. Further work that looks at the HadGEM3-A simulations shows that these heavy rainfall days are more likely to occur in a climate impacted by human activity than one with just natural climate forcings.

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Development and Evaluation of Mei-Yu Season Quantitative Precipitation Forecasts in Taiwan River Basins Based on a Conceptual Climatology Model

Weather and Forecasting ◽

10.1175/waf-d-11-00098.1 ◽

2012 ◽

Vol 27 (3) ◽

pp. 586-607 ◽

Cited By ~ 5

Author(s):

Chung-Chieh Wang ◽

Chu-Ying Kung ◽

Cheng-Shang Lee ◽

George Tai-Jen Chen

Keyword(s):

Heavy Rainfall ◽

Statistical Tests ◽

River Basins ◽

Short Wave ◽

Rain Gauge ◽

Quantitative Precipitation Forecasts ◽

Southern Taiwan ◽

Upper Level ◽

Central Weather Bureau ◽

Rainfall Climatology

Abstract Using rain gauge data during 134 mei-yu frontal cases in May–June 1991–2006, a rainfall climatology in relation to the positions of fronts every 0.5° in Taiwan is obtained, showing widespread precipitation with maxima over windward mountain slopes associated with frontal passages. For six major river basins, rainfall characteristics and synoptic factors are further analyzed to build a conceptual climatology model for short-term quantitative precipitation forecasts (QPFs). The four basins in central–southern Taiwan exhibit increased heavy-rainfall frequencies (>25%) roughly from 2° south to 1° north of the front, while the two basins in northern Taiwan have lower frequencies with different characteristics mainly due to the differences in their topography. The synoptic factors in the checklist employed by the Central Weather Bureau and important to heavy rainfall are identified for each of the six basins through statistical tests and their threat score (TS). These factors include those related to mei-yu fronts, low-level jets and moisture, upper-level divergence–diffluence, and short-wave troughs. A conceptual climatology model that uses both synoptic and probability forecasting guidance is developed, and in practice the average rainfall climatology is replaced by one obtained for heavy-rainfall periods if either of the two guidance schemes indicates heavy-rainfall possibility. This model for 0–6- and 0–12-h QPFs is also evaluated for its usefulness using cases during the 2007–08 seasons. With typical TSs of 0.2–0.3 (for heavy rainfall), this approach outperforms simple climatology in all six basins especially toward higher thresholds (about 20–50 mm) and for 12-h events, where it also shows advantages over model QPFs in southern Taiwan. Thus, the model can provide useful information for operational use.

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Rainfall Regime of a Mountainous Mediterranean Region: Statistical Analysis at Short Time Steps

Journal of Applied Meteorology and Climatology ◽

10.1175/2011jamc2691.1 ◽

2012 ◽

Vol 51 (3) ◽

pp. 429-448 ◽

Cited By ~ 31

Author(s):

Gilles Molinié ◽

Davide Ceresetti ◽

Sandrine Anquetin ◽

Jean Dominique Creutin ◽

Brice Boudevillain

Keyword(s):

Daily Rainfall ◽

Large River ◽

Rain Gauge ◽

Heavy Rainfall Event ◽

Rainfall Regime ◽

Study Region ◽

Rain Gauge Data ◽

Rain Gauges ◽

Gauge Data ◽

The Difference

AbstractThis paper presents an analysis of the rainfall regime of a Mediterranean mountainous region of southeastern France. The rainfall regime is studied on temporal scales from hourly to yearly using daily and hourly rain gauge data of 43 and 16 years, respectively. The domain is 200 × 200 km2 with spatial resolution of hourly and daily rain gauges of about 8 and 5 km, respectively. On average, yearly rainfall increases from about 0.5 m yr−1 in the large river plain close to the Mediterranean Sea to up to 2 m yr−1 over the surrounding mountain ridges. The seasonal distribution is also uneven: one-third of the cumulative rainfall occurs during the autumn season and one-fourth during the spring. At finer time scales, rainfall is studied in terms of rain–no-rain intermittency and nonzero intensity. The monthly intermittency (proportion of dry days per month) and the daily intermittency (proportion of dry hours per day) is fairly well correlated with the relief. The higher the rain gauges are, the lower the monthly and daily intermittencies are. The hourly and daily rainfall intensities are analyzed in terms of seasonal variability, diurnal cycle, and spatial pattern. The difference between regular and heavy-rainfall event is depicted by using both central parameters and maximum values of intensity distributions. The relationship between rain gauge altitudes and rainfall intensity is grossly inverted relative to intermittency and is also far more complex. The spatial and temporal rainfall patterns depicted from rain gauge data are discussed in the light of known meteorological processes affecting the study region.

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Frequency Trend Analysis of Heavy Rainfall Days for Germany

Water ◽

10.3390/w12071950 ◽

2020 ◽

Vol 12 (7) ◽

pp. 1950

Author(s):

Detlef Deumlich ◽

Andreas Gericke

Keyword(s):

Heavy Rainfall ◽

Coastal Region ◽

Daily Rainfall ◽

Recent Change ◽

Trend Test ◽

Time Interval ◽

Regional Patterns ◽

Daily Data ◽

Hourly Data ◽

Regional Analyses

Climate change is expected to affect the occurrence of heavy rainfall. We analyzed trends of heavy rainfall days for the last decades in Germany. For all available stations with daily data, days exceeding daily thresholds (10, 20, 30 mm) were counted annually. The Mann–Kendall trend test was applied to overlapping periods of 30 years (1951–2019). This period was extended to 1901 for 111 stations. The stations were aggregated by natural regions to assess regional patterns. Impacts of data inconsistencies on the calculated trends were evaluated with the metadata and recent hourly data. Although the trend variability depended on the chosen exceedance threshold, a general long-term trend for the whole of Germany was consistently not evident. After 1951, stable positive trends occurred in the mountainous south and partly in the northern coastal region, while parts of Central Germany experienced negative trends. The frequent location shifts and the recent change in the time interval for daily rainfall could affect individual trends but were statistically insignificant for regional analyses. A case study supported that heavy rains became more erosive during the last 20 years. The results showed the merit of historical data for a better understanding of recent changes in heavy rainfall.

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Extreme Rainfall Events in the Hawaiian Islands

Journal of Applied Meteorology and Climatology ◽

10.1175/2008jamc1829.1 ◽

2009 ◽

Vol 48 (3) ◽

pp. 502-516 ◽

Cited By ~ 39

Author(s):

Pao-Shin Chu ◽

Xin Zhao ◽

Ying Ruan ◽

Melodie Grubbs

Keyword(s):

Return Period ◽

Heavy Rainfall ◽

Hawaiian Islands ◽

Daily Rainfall ◽

Extreme Rainfall ◽

Generalized Extreme Value Distribution ◽

Economic Losses ◽

Return Periods ◽

Extreme Rainfall Events ◽

Rainfall Events

Abstract Heavy rainfall and the associated floods occur frequently in the Hawaiian Islands and have caused huge economic losses as well as social problems. Extreme rainfall events in this study are defined by three different methods based on 1) the mean annual number of days on which 24-h accumulation exceeds a given daily rainfall amount, 2) the value associated with a specific daily rainfall percentile, and 3) the annual maximum daily rainfall values associated with a specific return period. For estimating the statistics of return periods, the three-parameter generalized extreme value distribution is fit using the method of L-moments. Spatial patterns of heavy and very heavy rainfall events across the islands are mapped separately based on the aforementioned three methods. Among all islands, the pattern on the island of Hawaii is most distinguishable, with a high frequency of events along the eastern slopes of Mauna Kea and a low frequency of events on the western portion so that a sharp gradient in extreme events from east to west is prominent. On other islands, extreme rainfall events tend to occur locally, mainly on the windward slopes. A case is presented for estimating return periods given different rainfall intensity for a station in Upper Manoa, Oahu. For the Halloween flood in 2004, the estimated return period is approximately 27 yr, and its true value should be no less than 13 yr with 95% confidence as determined from the adjusted bootstrap resampling technique.

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Changing Frequency of Heavy Rainfall over the Central United States

Journal of Climate ◽

10.1175/jcli-d-12-00043.1 ◽

2013 ◽

Vol 26 (1) ◽

pp. 351-357 ◽

Cited By ~ 110

Author(s):

Gabriele Villarini ◽

James A. Smith ◽

Gabriel A. Vecchi

Keyword(s):

United States ◽

Heavy Rainfall ◽

Daily Rainfall ◽

Rain Gauge ◽

First Century ◽

Temperature Record ◽

Central United States ◽

Increasing Trends ◽

Surface Temperature Record ◽

Threshold Approach

Abstract Records of daily rainfall accumulations from 447 rain gauge stations over the central United States (Minnesota, Wisconsin, Michigan, Iowa, Illinois, Indiana, Missouri, Kentucky, Tennessee, Arkansas, Louisiana, Alabama, and Mississippi) are used to assess past changes in the frequency of heavy rainfall. Each station has a record of at least 50 yr, and the data cover most of the twentieth century and the first decade of the twenty-first century. Analyses are performed using a peaks-over-threshold approach, and, for each station, the 95th percentile is used as the threshold. Because of the count nature of the data and to account for both abrupt and slowly varying changes in the heavy rainfall distribution, a segmented regression is used to detect changepoints at unknown points in time. The presence of trends is assessed by means of a Poisson regression model to examine whether the rate of occurrence parameter is a linear function of time (by means of a logarithmic link function). The results point to increasing trends in heavy rainfall over the northern part of the study domain. Examination of the surface temperature record suggests that these increasing trends occur over the area with the largest increasing trends in temperature and, consequently, with an increase in atmospheric water vapor.

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