Evidence for trends in heavy rainfall events over the UK

2002 ◽  
Vol 360 (1796) ◽  
pp. 1313-1325 ◽  
Author(s):  
Timothy J. Osborn ◽  
Mike Hulme
Keyword(s):  
Heavy Rainfall ◽  
Rainfall Events ◽  
The Uk ◽  
Heavy Rainfall Events

Subseasonal forecasts for humanitarian decision-making in Kenya: understanding forecast skill and the latest results from the S2S ForPAc real-time pilot study.

2020 ◽  
Author(s):  
Dave MacLeod ◽  
Mary Kilavi ◽  
Emmah Mwangi ◽  
George Otieno ◽  
Richard Graham ◽  
...  
Keyword(s):  
Decision Making ◽  
Pilot Study ◽  
Real Time ◽  
Disaster Preparedness ◽  
Lead Time ◽  
Heavy Rainfall ◽  
Forecast Skill ◽  
Rainfall Events ◽  
The Uk ◽  
Heavy Rainfall Events

<p>In 2018 the long rains season in Kenya (March-May) was the wettest ever recorded. The country experienced several multi-day heavy rainfall episodes, leading to dam collapse, land and mudslides. 186 people died due to flooding and 300,000 were left displaced. </p><p>The Kenya Meteorological Department issued several advisories during the season that warned of heavy rainfall events a few days before their occurrence. Ahead of this no warnings were given.</p><p>However subseasonal forecasts gave strong indications of the heaviest rainfall episodes, several weeks in advance. With this extra lead time, preparedness actions may have been taken in order to reduce flood risk and save lives. </p><p>To this end, the ForPAc project (Toward Forecast-Based Preparedness Action) has been working in partnerships across Kenya and the UK to evaluate and build trust in subseasonal forecasts, and explore preparedness actions which could be taken in response. Most recently ForPAc has been granted access to real-time subseasonal data as part of phase two of the S2S pilot.</p><p>In this presentation we will first show analysis of the S2S hindcasts over East Africa, demonstrating the relatively high levels of subseasonal forecast skill and linking this to a strong MJO teleconnection that models capture relatively well.</p><p>In the second part we will describe work with stakeholders to co-design forecast products derived from the S2S data, concluding with a report on the forecasts for the ongoing 2020 long rains season and an evaluation of the way in which these have influenced disaster preparedness.</p>

scholarly journals Extreme Floods in the Eastern Part of Europe: Large-Scale Drivers and Associated Impacts

Water ◽  
2021 ◽  
Vol 13 (8) ◽  
pp. 1122
Author(s):  
Monica Ionita ◽  
Viorica Nagavciuc
Keyword(s):  
Water Vapor ◽  
Heavy Rainfall ◽  
Large Scale ◽  
Vapor Transport ◽  
Water Vapor Transport ◽  
Flood Events ◽  
Rainfall Events ◽  
Catchment Areas ◽  
Large Scale Atmospheric Circulation ◽  
Heavy Rainfall Events

The role of the large-scale atmospheric circulation in producing heavy rainfall events and floods in the eastern part of Europe, with a special focus on the Siret and Prut catchment areas (Romania), is analyzed in this study. Moreover, a detailed analysis of the socio-economic impacts of the most extreme flood events (e.g., July 2008, June–July 2010, and June 2020) is given. Analysis of the largest flood events indicates that the flood peaks have been preceded up to 6 days in advance by intrusions of high Potential Vorticity (PV) anomalies toward the southeastern part of Europe, persistent cut-off lows over the analyzed region, and increased water vapor transport over the catchment areas of Siret and Prut Rivers. The vertically integrated water vapor transport prior to the flood peak exceeds 300 kg m−1 s−1, leading to heavy rainfall events. We also show that the implementation of the Flood Management Plan in Romania had positive results during the 2020 flood event compared with the other flood events, when the authorities took several precaution measurements that mitigated in a better way the socio-economic impact and risks of the flood event. The results presented in this study offer new insights regarding the importance of large-scale atmospheric circulation and water vapor transport as drivers of extreme flooding in the eastern part of Europe and could lead to a better flood forecast and flood risk management.

scholarly journals Mesoscale Analysis of Heavy Rainfall Episodes from SoWMEX/TiMREX

2012 ◽  
Vol 69 (2) ◽  
pp. 521-537 ◽  
Author(s):  
Christopher A. Davis ◽  
Wen-Chau Lee
Keyword(s):  
Heavy Rainfall ◽  
Southwest Monsoon ◽  
Rainfall Events ◽  
Mesoscale Analysis ◽  
Mesoscale Structure ◽  
Profound Influence ◽  
Moist Condition ◽  
Virtual Temperature ◽  
Convection Initiation ◽  
Heavy Rainfall Events

Abstract The authors analyze the mesoscale structure accompanying two multiday periods of heavy rainfall during the Southwest Monsoon Experiment and the Terrain-Induced Mesoscale Rainfall Experiment conducted over and near Taiwan during May and June 2008. Each period is about 5–6 days long with episodic heavy rainfall events within. These events are shown to correspond primarily to periods when well-defined frontal boundaries are established near the coast. The boundaries are typically 1 km deep or less and feature contrasts of virtual temperature of only 2°–3°C. Yet, owing to the extremely moist condition of the upstream conditionally unstable air, these boundaries appear to exert a profound influence on convection initiation or intensification near the coast. Furthermore, the boundaries, once established, are long lived, possibly reinforced through cool downdrafts and prolonged by the absence of diurnal heating over land in generally cloudy conditions. These boundaries are linked phenomenologically with coastal fronts that occur at higher latitudes.

scholarly journals An Improved Weighting Method of Time-Lag-Ensemble Averaging for Hourly Precipitation Forecasts and Its Application in a Typhoon-Induced Heavy Rainfall Event

Atmosphere ◽  
2021 ◽  
Vol 12 (7) ◽  
pp. 875
Author(s):  
Li Zhou ◽  
Lin Xu ◽  
Mingcai Lan ◽  
Jingjing Chen
Keyword(s):  
Heavy Rainfall ◽  
Time Lag ◽  
Probability Of Detection ◽  
Precipitation Forecast ◽  
Ensemble Averaging ◽  
Weighting Method ◽  
Prediction Ability ◽  
Rainfall Events ◽  
Hourly Precipitation ◽  
Heavy Rainfall Events

Heavy rainfall events often cause great societal and economic impacts. The prediction ability of traditional extrapolation techniques decreases rapidly with the increase in the lead time. Moreover, deficiencies of high-resolution numerical models and high-frequency data assimilation will increase the prediction uncertainty. To address these shortcomings, based on the hourly precipitation prediction of Global/Regional Assimilation and Prediction System-Cycle of Hourly Assimilation and Forecast (GRAPES-CHAF) and Shanghai Meteorological Service-WRF ADAS Rapid Refresh System (SMS-WARR), we present an improved weighting method of time-lag-ensemble averaging for hourly precipitation forecast which gives more weight to heavy rainfall and can quickly select the optimal ensemble members for forecasting. In addition, by using the cross-magnitude weight (CMW) method, mean absolute error (MAE), root mean square error (RMSE) and correlation coefficient (CC), the verification results of hourly precipitation forecast for next six hours in Hunan Province during the 2019 typhoon Bailu case and heavy rainfall events from April to September in 2020 show that the revised forecast method can more accurately capture the characteristics of the hourly short-range precipitation forecast and improve the forecast accuracy and the probability of detection of heavy rainfall.

Diverse synoptic weather patterns of warm-season heavy rainfall events in South Korea

2021 ◽  
Author(s):  
Chanil Park ◽  
Seok-Woo Son ◽  
Joowan Kim ◽  
Eun-Chul Chang ◽  
Jung-Hoon Kim ◽  
...  
Keyword(s):  
North Pacific ◽  
Moisture Transport ◽  
Heavy Rainfall ◽  
Eastern China ◽  
Warm Season ◽  
Sea Level Pressure ◽  
Rainfall Events ◽  
Weather Patterns ◽  
Synoptic Weather ◽  
Heavy Rainfall Events

AbstractThis study identifies diverse synoptic weather patterns of warm-season heavy rainfall events (HREs) in South Korea. The HREs not directly connected to tropical cyclones (TCs) (81.1%) are typically associated with a midlatitude cyclone from eastern China, the expanded North Pacific high and strong southwesterly moisture transport in between. They are frequent both in the first (early summer) and second rainy periods (late summer) with impacts on the south coast and west of the mountainous region. In contrast, the HREs resulting from TCs (18.9%) are caused by the synergetic interaction between the TC and meandering midlatitude flow, especially in the second rainy period. The strong south-southeasterly moisture transport makes the southern and eastern coastal regions prone to the TC-driven HREs. By applying a self-organizing map algorithm to the non-TC HREs, their surface weather patterns are further classified into six clusters. Clusters 1 and 3 exhibit frontal boundary between the low and high with differing relative strengths. Clusters 2 and 5 feature an extratropical cyclone migrating from eastern China under different background sea-level pressure patterns. Cluster 4 is characterized by the expanded North Pacific high with no organized negative sea-level pressure anomaly, and cluster 6 displays a development of a moisture pathway between the continental and oceanic highs. Each cluster exhibits a distinct spatio-temporal occurrence distribution. The result provides useful guidance for predicting the HREs by depicting important factors to be differently considered depending on their synoptic categorization.

scholarly journals Brief communication "Climatic covariates for the frequency analysis of heavy rainfall in the Mediterranean region"

2011 ◽  
Vol 11 (9) ◽  
pp. 2463-2468 ◽  
Author(s):  
Y. Tramblay ◽  
L. Neppel ◽  
J. Carreau
Keyword(s):  
Extreme Events ◽  
Heavy Rainfall ◽  
Climate Models ◽  
Extreme Event ◽  
Generalized Pareto Distribution ◽  
Climatic Conditions ◽  
Extreme Rainfall Events ◽  
Rainfall Events ◽  
The Future ◽  
Heavy Rainfall Events

Abstract. In Mediterranean regions, climate studies indicate for the future a possible increase in the extreme rainfall events occurrence and intensity. To evaluate the future changes in the extreme event distribution, there is a need to provide non-stationary models taking into account the non-stationarity of climate. In this study, several climatic covariates are tested in a non-stationary peaks-over-threshold modeling approach for heavy rainfall events in Southern France. Results indicate that the introduction of climatic covariates could improve the statistical modeling of extreme events. In the case study, the frequency of southern synoptic circulation patterns is found to improve the occurrence process of extreme events modeled via a Poisson distribution, whereas for the magnitude of the events, the air temperature and sea level pressure appear as valid covariates for the Generalized Pareto distribution scale parameter. Covariates describing the humidity fluxes at monthly and seasonal time scales also provide significant model improvements for the occurrence and the magnitude of heavy rainfall events. With such models including climatic covariates, it becomes possible to asses the risk of extreme events given certain climatic conditions at monthly or seasonal timescales. The future changes in the heavy rainfall distribution can also be evaluated using covariates computed by climate models.

scholarly journals Spatiotemporal patterns of synchronous heavy rainfall events in East Asia during the Baiu season

2021 ◽  
Author(s):  
Frederik Wolf ◽  
Ugur Ozturk ◽  
Kevin Cheung ◽  
Reik V. Donner
Keyword(s):  
System Dynamics ◽  
East Asia ◽  
Heavy Rainfall ◽  
Spatial Organization ◽  
Monsoon Season ◽  
Spatiotemporal Patterns ◽  
Extreme Weather Events ◽  
Earth System ◽  
Rainfall Events ◽  
Heavy Rainfall Events

<p>Investigating the synchrony and interdependency of heavy rainfall occurrences is crucial to understand the underlying physical mechanisms and reduce physical and economic damages by improved forecasting strategies. In this context, studies utilizing functional network representations have recently contributed to significant advances in the understanding and prediction of extreme weather events.</p><p>To thoroughly expand on previous works employing the latter framework to the East Asian Summer Monsoon (EASM) system, we focus here on changes in the spatial organization of synchronous heavy precipitation events across the monsoon season (April to August) by studying the temporal evolution of corresponding network characteristics in terms of a sliding window approach. Specifically, we utilize functional climate networks together with event coincidence analysis for identifying and characterizing synchronous activity from daily rainfall estimates with <span>a spatial resolution of 0.25° </span>between 1998 and 2018. Our results demonstrate that the formation of the Baiu front as a main feature of the EASM is reflected by a double-band structure of synchronous heavy rainfall with two centers north and south of the front. Although the two separated bands are strongly related to either low- or high-level winds which are commonly assumed to be independent, we provide evidence that it is rather their mutual interconnectivity that changes during the different phases of the EASM season in a characteristic way.</p><p>Our findings shed some new light on the interplay between tropical and extratropical factors controlling the EASM intraseasonal evolution, which could potentially help improving future forecasts of the Baiu onset in different regions of East Asia.</p><p> </p><p>Further details: F. Wolf, U. Ozturk, K. Cheung, R.V. Donner: Spatiotemporal patterns of synchronous heavy rainfall events in East Asia during the Baiu season. Earth System Dynamics (in review). Discussion Paper: Earth System Dynamics Discussions, (2020)</p>

Analysis of heavy rainfall events in North Rhine–Westphalia with radar and raingauge data

2005 ◽  
Vol 77 (1-4) ◽  
pp. 337-346 ◽  
Author(s):  
Markus Jessen ◽  
Thomas Einfalt ◽  
André Stoffer ◽  
Bernd Mehlig
Keyword(s):  
Heavy Rainfall ◽  
Rainfall Events ◽  
Raingauge Data ◽  
Heavy Rainfall Events
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