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

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

<p>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.</p><p>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.</p>

scholarly journals Managing the effects of extreme sub-daily rainfall and flash floods—a practitioner's perspective

2021 ◽  
Vol 379 (2195) ◽  
pp. 20190550 ◽  
Author(s):  
Murray Dale
Keyword(s):  
Climate Change ◽  
Time Series ◽  
Flood Risk ◽  
Climate Models ◽  
Time Series Data ◽  
Daily Rainfall ◽  
Series Data ◽  
Rainfall Events ◽  
Short Period ◽  
The Uk

Extreme sub-daily rainfall affects flooding in the UK and urban pollution management. Water utilities in the UK need to understand the characteristics of this rainfall, and how it may change in the future in order to plan for and manage these impacts. There is also significant interest from infrastructure owners and urban authorities exposed to flood risk from short-period, intense rainfall events. This paper describes how UK flood risk guidance incorporates allowances for climate change and how recent research using convection-permitting climate models is helping to inform this guidance. The guidance documents are used by engineers and scientists in the modelling of sewer networks, smaller river catchments and urban drainage areas and provide values to ‘uplift' rainfall event data used as model inputs to reflect climate change model projections. With an increasing focus on continuous simulation modelling using time series rainfall, research into adjusting time series data to reflect future rainfall characteristics in convection-permitting climate models is discussed. Other knowledge gaps for practitioners discussed are the potential changing shape (profile) of future rainfall events and future changes in antecedent wetness conditions. The author explains the challenge of developing simple and effective guidance for practitioners from the complex scientific output. This article is part of a discussion meeting issue ‘Intensification of short-duration rainfall extremes and implications for flash flood risks’.

scholarly journals Comparison of regional characteristics of land precipitation climatology projected by an MRI-AGCM multi-cumulus scheme and multi-SST ensemble with CMIP5 multi-model ensemble projections

2020 ◽  
Vol 7 (1) ◽  
Author(s):  
Rui Ito ◽  
Tosiyuki Nakaegawa ◽  
Izuru Takayabu
Keyword(s):  
Climate Change ◽  
High Resolution ◽  
General Circulation ◽  
Annual Precipitation ◽  
Cmip5 Models ◽  
Climate Projections ◽  
The Tibetan Plateau ◽  
Model Ensemble ◽  
Uncertainty Range ◽  
High Performing

AbstractEnsembles of climate change projections created by general circulation models (GCMs) with high resolution are increasingly needed to develop adaptation strategies for regional climate change. The Meteorological Research Institute atmospheric GCM version 3.2 (MRI-AGCM3.2), which is listed in the Coupled Model Intercomparison Project phase 5 (CMIP5), has been typically run with resolutions of 60 km and 20 km. Ensembles of MRI-AGCM3.2 consist of members with multiple cumulus convection schemes and different patterns of future sea surface temperature, and are utilized together with their downscaled data; however, the limited size of the high-resolution ensemble may lead to undesirable biases and uncertainty in future climate projections that will limit its appropriateness and effectiveness for studies on climate change and impact assessments. In this study, to develop a comprehensive understanding of the regional precipitation simulated with MRI-AGCM3.2, we investigate how well MRI-AGCM3.2 simulates the present-day regional precipitation around the globe and compare the uncertainty in future precipitation changes and the change projection itself between MRI-AGCM3.2 and the CMIP5 multiple atmosphere–ocean coupled GCM (AOGCM) ensemble. MRI-AGCM3.2 reduces the bias of the regional mean precipitation obtained with the high-performing CMIP5 models, with a reduction of approximately 20% in the bias over the Tibetan Plateau through East Asia and Australia. When 26 global land regions are considered, MRI-AGCM3.2 simulates the spatial pattern and the regional mean realistically in more regions than the individual CMIP5 models. As for the future projections, in 20 of the 26 regions, the sign of annual precipitation change is identical between the 50th percentiles of the MRI-AGCM3.2 ensemble and the CMIP5 multi-model ensemble. In the other six regions around the tropical South Pacific, the differences in modeling with and without atmosphere–ocean coupling may affect the projections. The uncertainty in future changes in annual precipitation from MRI-AGCM3.2 partially overlaps the maximum–minimum uncertainty range from the full ensemble of the CMIP5 models in all regions. Moreover, on average over individual regions, the projections from MRI-AGCM3.2 spread over roughly 0.8 of the uncertainty range from the high-performing CMIP5 models compared to 0.4 of the range of the full ensemble.

scholarly journals Role of land state in a high resolution mesoscale model for simulating the Uttarakhand heavy rainfall event over India

2016 ◽  
Vol 125 (3) ◽  
pp. 475-498 ◽  
Author(s):  
P V Rajesh ◽  
S Pattnaik ◽  
D Rai ◽  
K K Osuri ◽  
U C Mohanty ◽  
...  
Keyword(s):  
High Resolution ◽  
Heavy Rainfall ◽  
Mesoscale Model ◽  
Rainfall Event ◽  
Heavy Rainfall Event

scholarly journals A high-resolution downscaled CMIP6 projections dataset of essential surface climate variables over the globe coherent with the ERA5-Land reanalysis for climate change impact assessments

2021 ◽  
Author(s):  
Thomas Noël ◽  
Harilaos Loukos ◽  
Dimitri Defrance
Keyword(s):  
Climate Change ◽  
High Resolution ◽  
Climate Models ◽  
Mapping Method ◽  
Cumulative Distribution ◽  
Climate Projections ◽  
Climate Modelling ◽  
Temperature And Precipitation ◽  
Surface Climate ◽  
Emissions Scenarios

A high-resolution climate projections dataset is obtained by statistically downscaling climate projections from the CMIP6 experiment using the ERA5-Land reanalysis from the Copernicus Climate Change Service. This global dataset has a spatial resolution of 0.1°x 0.1°, comprises 5 climate models and includes two surface daily variables at monthly resolution: air temperature and precipitation. Two greenhouse gas emissions scenarios are available: one with mitigation policy (SSP126) and one without mitigation (SSP585). The downscaling method is a Quantile Mapping method (QM) called the Cumulative Distribution Function transform (CDF-t) method that was first used for wind values and is now referenced in dozens of peer-reviewed publications. The data processing includes quality control of metadata according to the climate modelling community standards and value checking for outlier detection.

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

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.

Simulation of a heavy rainfall event during southwest monsoon using high-resolution NCUM-modeling system: a case study

2018 ◽  
Vol 131 (4) ◽  
pp. 1035-1054 ◽  
Author(s):  
Devajyoti Dutta ◽  
A. Routray ◽  
D. Preveen Kumar ◽  
John P. George ◽  
Vivek Singh
Keyword(s):  
High Resolution ◽  
Heavy Rainfall ◽  
Southwest Monsoon ◽  
Rainfall Event ◽  
Heavy Rainfall Event ◽  
System A

Identification and Synoptic Analysis of the Highest Precipitation Linked to Ars in Iran

2021 ◽  
Vol 3 (2) ◽  
pp. 20-32
Author(s):  
Hassan Lashkari ◽  
Neda Esfandiari ◽  
Abbas Kashani
Keyword(s):  
Water Vapour ◽  
Heavy Rainfall ◽  
Daily Rainfall ◽  
Horn Of Africa ◽  
Maximum Rainfall ◽  
Rainfall Events ◽  
Atmospheric Rivers ◽  
Factors Affecting ◽  
North West ◽  
Integral Data

Atmospheric rivers are long, narrow, concentrated structures of water vapour that are highly associated with rainfall and floods. To identify and introduce the highest rainfall occurring during the presence of atmospheric rivers from November to April (2007-2018) while showing the importance of this phenomenon in creating super heavy rainfall and introducing the areas affected by it, analyzed the synoptic factors affecting them slowly. In order to identify atmospheric rivers, vertical integral data of water vapour flow were used and thresholds were documented on them. The date of occurrence of each atmospheric river with their daily rainfall was examined and ten of the highest rainfall events Station (equivalent to the 95th percentile of maximum rainfall) related to atmospheric rivers was introduced and analyzed. It is found that the South Gram has been directly and indirectly the main source of atmospheric rivers associated with heavy rainfall. The source of most of these atmospheric rivers is at the peak of the Red Sea, the Gulf of Aden and the Horn of Africa. Synonymously, the origins of 7 cases from Atmospheric rivers have been of the Sudanese low pressure and in the remaining three cases have been integrated systems. In Sudanese systems, the predominant structure of the meridional inclination jet and in Integration systems has been oriented. Due to the dominance of a strong upstream current in the vicinity of the highest flux, moisture of heavy convective currents has caused super heavy rainfall and the station with the highest rainfall in the east and North West of the negative omega field or upstream streams.

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

2016 ◽  
Vol 2016 ◽  
pp. 1-9 ◽  
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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