Dataset Information

Synoptic-Scale Precursors of Extreme U.K. Summer 3-Hourly Rainfall.

ABSTRACT: The synoptic-scale meteorological conditions leading up to the 30 most extreme subdaily summer rain events for two regions of the United Kingdom (northwest and southeast) were examined for the period 1979-2013. Using a recently available, quality controlled, national hourly rain gauge data set, we were able to identify extreme 3-hr rainfall accumulations that may be indicative of flash flooding. Composites of the state of the atmosphere leading up to these dates were produced to investigate synoptic-scale processes, thus potentially allowing for them to be identified in coarse resolution reanalyses and in climate models. The results show that the two regions have different dominant synoptic-scale conditions leading to extreme 3-hr rainfall, which is thought to be related to the type of rainfall typically experienced in each region. In particular, positive anomalies in mean sea level pressure and the geopotential height at 200 hPa over the United Kingdom are associated with extreme rainfall in the northwest, where the position of the westerly jet is also important. For the southeast, no clear anomalous synoptic-scale conditions could be identified; however, localized moisture sources and unstable air masses were observed in association with extremes. These results indicate the importance of better understanding of both synoptic-scale and thermodynamic drivers of short-duration extreme rainfall, with potential implications in forecasting and flood warning, as well as for understanding the representation of key processes by regional climate models.

SUBMITTER: Champion AJ

PROVIDER: S-EPMC6582617 | biostudies-literature | 2019 Apr

REPOSITORIES: biostudies-literature

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Synoptic-Scale Precursors of Extreme U.K. Summer 3-Hourly Rainfall.

Champion Adrian J AJ Blenkinsop Stephen S Li Xiao-Feng XF Fowler Hayley J HJ

Journal of geophysical research. Atmospheres : JGR 20190429 8

The synoptic-scale meteorological conditions leading up to the 30 most extreme subdaily summer rain events for two regions of the United Kingdom (northwest and southeast) were examined for the period 1979-2013. Using a recently available, quality controlled, national hourly rain gauge data set, we were able to identify extreme 3-hr rainfall accumulations that may be indicative of flash flooding. Composites of the state of the atmosphere leading up to these dates were produced to investigate syno ...[more]

PMID: 31245232

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Project description:Sub-daily rainfall extremes may be associated with flash flooding, particularly in urban areas but, compared with extremes on daily timescales, have been relatively little studied in many regions. This paper describes a new, hourly rainfall dataset for the UK based on ?1600 rain gauges from three different data sources. This includes tipping bucket rain gauge data from the UK Environment Agency (EA), which has been collected for operational purposes, principally flood forecasting. Significant problems in the use of such data for the analysis of extreme events include the recording of accumulated totals, high frequency bucket tips, rain gauge recording errors and the non-operation of gauges. Given the prospect of an intensification of short-duration rainfall in a warming climate, the identification of such errors is essential if sub-daily datasets are to be used to better understand extreme events. We therefore first describe a series of procedures developed to quality control this new dataset. We then analyse ?380 gauges with near-complete hourly records for 1992-2011 and map the seasonal climatology of intense rainfall based on UK hourly extremes using annual maxima, n-largest events and fixed threshold approaches. We find that the highest frequencies and intensities of hourly extreme rainfall occur during summer when the usual orographically defined pattern of extreme rainfall is replaced by a weaker, north-south pattern. A strong diurnal cycle in hourly extremes, peaking in late afternoon to early evening, is also identified in summer and, for some areas, in spring. This likely reflects the different mechanisms that generate sub-daily rainfall, with convection dominating during summer. The resulting quality-controlled hourly rainfall dataset will provide considerable value in several contexts, including the development of standard, globally applicable quality-control procedures for sub-daily data, the validation of the new generation of very high-resolution climate models and improved understanding of the drivers of extreme rainfall.

Project description:BackgroundThe southeastern United States consistently has high salmonellosis incidence, but disease drivers remain unknown. Salmonella is regularly detected in this region's natural environment, leading to numerous exposure opportunities. Rainfall patterns may impact the survival/transport of environmental Salmonella in ways that can affect disease transmission.ObjectivesThis study investigated associations between short-term precipitation (extreme rainfall events) and longer-term precipitation (rainfall conditions antecedent to these extreme events) on salmonellosis counts in the state of Georgia in the United States.MethodsFor the period 1997-2016, negative binomial models estimated associations between weekly county-level extreme rainfall events (≥90th percentile of daily rainfall) and antecedent conditions (8-week precipitation sums, categorized into tertiles) and weekly county-level salmonellosis counts.ResultsIn Georgia's Coastal Plain counties, extreme and antecedent rainfall were associated with significant differences in salmonellosis counts. In these counties, extreme rainfall was associated with a 5% increase in salmonellosis risk (95% CI: 1%, 10%) compared with weeks with no extreme rainfall. Antecedent dry periods were associated with a 9% risk decrease (95% CI: 5%, 12%), whereas wet periods were associated with a 5% increase (95% CI: 1%, 9%), compared with periods of moderate rainfall. In models considering the interaction between extreme and antecedent rainfall conditions, wet periods were associated with a 13% risk increase (95% CI: 6%, 19%), whereas wet periods followed by extreme events were associated with an 11% increase (95% CI: 5%, 18%). Associations were substantially magnified when analyses were restricted to cases attributed to serovars commonly isolated from wildlife/environment (e.g., Javiana). For example, wet periods followed by extreme rainfall were associated with a 34% risk increase (95% CI: 20%, 49%) in environmental serovar infection.ConclusionsGiven the associations of short-term extreme rainfall events and longer-term rainfall conditions on salmonellosis incidence, our findings suggest that avoiding contact with environmental reservoirs of Salmonella following heavy rainfall events, especially during the rainy season, may reduce the risk of salmonellosis. https://doi.org/10.1289/EHP4621.

Dataset Information

Synoptic-Scale Precursors of Extreme U.K. Summer 3-Hourly Rainfall.

Publications

Synoptic-Scale Precursors of Extreme U.K. Summer 3-Hourly Rainfall.

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