NCEO High Impact Weather and Flooding

Lead Research Organisation: National Centre for Earth Observation

Abstract

The NCEO High Impact Weather and Flooding Programme aims to improve our understanding of the physical and dynamic processes governing storms and floods and to develop capability to forecast these phenomena. Storms, floods and droughts have a major impact on everyday life around the world. An improved ability to forecast, quantify and manage meteorological and hydrological risks, as well as water resources, is essential to protect the public, property and infrastructure, and to maintain a sustainable economy. We will improve methods of assimilating data from meteorological satellites and ground based radar into high resolution atmospheric models, to increase skills in forecasting hazardous weather. We are using EO measurements of soil moisture, snow and flooding to develop hydrological models for flood forecasting, working with operational agencies towards and end-to-end integrated forecasting capability. This theme focuses on the synergistic use of remote sensing data for high resolution predictions of hazardous weather, floods and water resources. Our priorities are: a) to develop assimilation techniques to ingest data from high-resolution satellite and ground based measurements into high-resolution atmospheric models; b) to utilise snow and flood extent measurements from a new generation of satellites to improve models of flooding and water resources; c) to prepare the science base in order to exploit forthcoming missions such as GPM (Global Precipitation Measurement) and Earthcare.

Publications

10 25 50

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Bannister R (2016) Ensemble prediction for nowcasting with a convection-permitting model - II: forecast error statistics in Tellus A: Dynamic Meteorology and Oceanography

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Bengtsson L (2016) The changing atmospheric water cycle in Polar Regions in a warmer climate in Tellus A: Dynamic Meteorology and Oceanography

 
Description 1. Retrievals of global snow mass from remote sensing are flawed in having a strong dependence on physical properties of snow which are generalised, but in reality vary considerably. - I Davenport



2. Snow mass is insensitive to the soil lower boundary condition. Knowledge of mean temperature at soil boundary is sufficient for simulation of soil water profile, but some knowledge of soil moisture is needed at the soil lower boundary. This has implications for the use of satellite sensors SMOS and SMAP in relating the surface soil moisture observations to root zone moisture. - M Sandells



3. "The two papers accepted in 2012 address two important issues for real-time flood forecasting:

a) Mason et al. (2012) develop a method for the automating processing of satellite-based Synthetic Aperture Radar to obtain Water Level Observations than can be assimilated into hydrodynamic models for flood forecast. This includes a top-down clustering approach for optimal subsampling of observations with spatially uncorrelated errors. Overall, the study is an important step toward the operational utilization of remote sensing-supported flood forecast.

b) Marin-Perez et al. (2012) focus on the technical description of a device specially designed to fulfill long-awaited requirements of in-situ hydrologic monitoring for remote areas. This is a low-power and long-range communication device, to support sensor networks, satisfying the requirements in terms of autonomy, sensor hardware compatibility, reliability and long-range communication, for monitoring big hydrologic catchments. Real-time data gathered from these networks can be assimilated along with remote-sensing information." - J Garcia-Pintado



4. "On convective-scale data assimilation (PhD project with Dr. Ruth Petrie): Data assimilation in meteorological weather forecasting is about combining new observations with model forecasts. The 'background error covariance matrix', measures the background forecast's accuracy, and is crucial for successful data assimilation. We were able to show that, by combining physical concepts and mathematical techniques, this matrix could be modelled with reference to the dynamical equations of motion of the atmosphere. This link to dynamics allows the assimilation to adjust the model fields in a way that is consistent with the 'dynamics of the day' allowing the newly assimilated observations to preserve important and relevant dynamical structures present in the background state.



5. On balance in the atmosphere at small scales: Ensembles of forecasts contain a wealth of information about forecast uncertainty, but also about the key balances that operate (or do not operate) for the particular meteorological conditions of the day (balance includes the idea of 'geostrophic balance' which is seen as flow in an anti-clockwise direction about a low pressure system (in the northern hemisphere) and 'hydrostatic balance' which requires that the atmospheric pressure at a given height must be able to support the weight of the atmosphere above it. Both of these balances are exploited in contemporary data assimilation (as used in weather forecasting) but theory expects these balances to not hold so strongly for scales of atmospheric motion that are short (so-called convective-scales of a few kms to tens of kms). Failing to account for this is likely to degrade the quality of data assimilation for convective scale models (such as the Met Office's new 1.5 km resolution model). We have analysed the forecast ensembles and have found that these balances are not always well obeyed. We have also considered a different balance (called anelastic balance) to see if this can be used as an alternative.



6. On ensemble data assimilation: There are many approaches to data assimilation, and one modern approach is called ensemble data assimilation where the assimilation process is informed by the spread in an ensemble of forecasts. Even though it has many benefits, one major drawback is related to the small number of forecast members (constituent forecasts) that can be afforded to be run on costly supercomputers. Small ensemble sizes lead to statistical issues (sampling errors) that need to be accounted for by filtering sampling noise (a process called 'localization'). The usual ways of doing localization are effective but are known to destroy key balance properties of the ensemble (using the balance properties is very important in data assimilation in fluid dynamical systems to avoid data assimilation 'shocks'). We have evaluated the effect of localization on balance with standard and new ways of doing data assimilation. Preliminary results hint that one of the new 'adaptive' localization methods may well preserve the balance proprties of the ensemble." - R Bannister



7. The ensemble of high-resolution weather forecasts developed by the NCEO/Met Office/DIAMET partnership has been used as a tool to investigate many useful and interesting aspects. 1. The forecasts for our case study were found to increase in spread for most variables when the capability of model error variability is added to the ensemble. 2. The forecasts were found to increase in skill for the first few hours, and decrease in skill after that as a result of model error variability. 3. The ensemble was used for a study of ensemble localization techniques (methods of reducing sampling noise in small ensembles). All localization methods were found to have a negative effect on ensemble balance, but one adaptive method is shown to be slightly superior to traditional (non-adaptive) methods.

R Bannister, 2014



8.Modelled snow grain size from meteorological data has shown strong correlation to actual grain size, which is important for using remote sensing to estimate global snow mass. I Davenport, 2014



9. Snow grain size obtained by optical reflectance methods cannot be used directly in microwave emission models. Some form of scaling is required between optical and microwave grain sizes, and the scaling factor is frequency and polarization dependent. Ice lenses within snow have a higher density than previously estimated or measured in the literature, but microwave emission models give similar brightness temperatures whether ice lenses are represented as pure ice or high density snow layers. A review of snow data assimilation systems showed that assimilation of snow extent data gives information at the start and end of snow seasons, whereas more useful information is obtained by assimilation of radiance data, particularly at multiple frequencies, which provides indirect information on snow grain size. M Sandells, 2014
Exploitation Route 1, More accurate snow mass measurements incorporating the modelling of physical characteristics will be a potential indicator of climate change and allow better management of water resources. - I Davenport



6. May be useful to operational forecast agencies for future data assimilation developments. - R Bannister



7. Potential use in Numerical Weather Prediction. - R Bannister



8. The distribution of snow mass is a potential indicator of climate change, and changes will directly impact on the one-sixth of the World's population who rely on snowmelt water. - I Davenport



9. Snow retrievals are of significant value to the energy, insurance and agricultural sectors. The contribution of snow to US manufacturing is 1.6 trillion dollars per year. - M Sandells


6. To inform operational forecast agencies. - R Bannister

7. To inform other assimilation studies of the pros and cons of localization - R Bannister

8. It is likely to be used in a data assimilation framework, and will have an influence on the next snow mass measurement mission. - I Davenport

9. This research will influence future satellite retrievals, and provide input for a future snow observation satellite mission not yet proposed, but under discussion. - M Sandells
Sectors Aerospace/ Defence and Marine,Agriculture/ Food and Drink,Communities and Social Services/Policy,Education,Energy,Environment,Leisure Activities/ including Sports/ Recreation and Tourism

 
Description This research investigates the sensitivity of a snow microwave emission model heterogeneity in the snow. This research introduced new field methods to measure snow structure in 2-D, and relate it to microwave emission across a 4.5m transect. New techniques developed include how to relate vertical profile observations to snow layers derived from near infra-red images. This showed that microwave scatters from particles larger than the size of individual snow grains.
Sector Cultural
Impact Types Cultural

 
Description DIAbatic influences on Mesoscale structures in ExTratropical storms (DIAMET)
Amount £336,353 (GBP)
Funding ID NE/I005234/1 
Organisation Natural Environment Research Council 
Sector Public
Country United Kingdom
Start 04/2010 
End 03/2013
 
Description DIAbatic influences on Mesoscale structures in ExTratropical storms (DIAMET)
Amount £336,353 (GBP)
Funding ID NE/I005234/1 
Organisation Natural Environment Research Council 
Sector Public
Country United Kingdom
Start 04/2010 
End 03/2017
 
Description Extinction of Microwave Radiation in Snow
Amount £51,467 (GBP)
Organisation Finnish Meteorological Institute 
Sector Public
Country Finland
Start 10/2013 
End 09/2016
 
Description Extinction of Microwave Radiation in Snow
Amount £51,467 (GBP)
Organisation Finnish Meteorological Institute 
Sector Public
Country Finland
Start  
 
Description Forecasting Rainfall exploiting new data Assimilation techniques and Novel observations of Convection
Amount £200,272 (GBP)
Funding ID NE/K008900/1 
Organisation Natural Environment Research Council 
Sector Public
Country United Kingdom
Start 04/2013 
End 03/2017
 
Description Forecasting Rainfall exploiting new data Assimilation techniques and Novel observations of Convection
Amount £200,272 (GBP)
Funding ID NE/K008900/1 
Organisation Natural Environment Research Council 
Sector Public
Country United Kingdom
Start 04/2013 
End 03/2017
 
Description Software Sustainability Institute Fellowship
Amount £3,000 (GBP)
Organisation University of Edinburgh 
Department UK Software Sustainability Institute
Sector Academic/University
Country United Kingdom
Start 01/2014 
End 12/2014
 
Description Software Sustainability Institute Fellowship
Amount £3,000 (GBP)
Organisation University of Edinburgh 
Department UK Software Sustainability Institute
Sector Academic/University
Country United Kingdom
Start 01/2014 
End 12/2014
 
Description Software Sustainabiliy Institute Fellowship
Amount £3,000 (GBP)
Organisation University of Edinburgh 
Department UK Software Sustainability Institute
Sector Academic/University
Country United Kingdom
Start 01/2013 
End 12/2013
 
Description Software Sustainabiliy Institute Fellowship
Amount £3,000 (GBP)
Organisation University of Edinburgh 
Department UK Software Sustainability Institute
Sector Academic/University
Country United Kingdom
Start 01/2013 
End 12/2013
 
Description ASMEx: Arctic Snow Microstructure Experiment - Finland 
Organisation Finnish Meteorological Institute
Country Finland 
Sector Public 
PI Contribution Field experiment to measure snow microstructure and relate it to microwave radiation scattering measurements
Start Year 2012
 
Description ASMEx: Arctic Snow Microstructure Experiment - Switzerland 
Organisation WSL Institute for Snow and Avalanche Research SLF
Country Switzerland 
Sector Academic/University 
PI Contribution Field experiment to measure snow microstructure and relate it to microwave radiation scattering measurements
Start Year 2014
 
Description Academic 
Organisation British Antarctic Survey
Country United Kingdom 
Sector Academic/University 
PI Contribution iSTAR-D
Start Year 2012
 
Description Academic 
Organisation International Space Science Institute (ISSI)
Country Switzerland 
Sector Academic/University 
PI Contribution Workshop on the Hydrological Cycle
Start Year 2012
 
Description Academic 
Organisation National Aeronautics and Space Administration (NASA)
Department Jet Propulsion Laboratory
Country United States 
Sector Public 
PI Contribution SMAP Science Definition Team
Start Year 2012
 
Description Academic 
Organisation National Science Foundation (NSF)
Country United States 
Sector Public 
PI Contribution Workshop to define Earthcube Initiative
Start Year 2012
 
Description Bjerknes Centre for Climate Research (Norway) 
Organisation Bjerknes Centre for Climate Research
Country Norway 
Sector Academic/University 
PI Contribution Dr Kevin Hodges is a visiting scientist at the Bjerknes Centre for Climate Research (Norway)
Start Year 2013
 
Description Calculating the contribution of observation and background errors in vertical wind profilers for numerical weather models 
Organisation Meteorological Office UK
Country United Kingdom 
Sector Public 
PI Contribution This project was connected with an MSc student project. It used the 'analysis of innovations' method to help determine the error statistics (variances and decorrelation lengthscales) of forecasts and wind profiler observations. These error statistics are essential in data assimilation.
Start Year 2012
 
Description Centro de Previsão de Tempo e Estudos Climáticos 
Organisation National Institute for Space Research Brazil
Department Weather Forecasting and Climate Studies Centre (CPTEC)
Country Brazil 
Sector Public 
PI Contribution Dr Kevin Hodges is a visiting scientist at the Centro de Previsão de Tempo e Estudos Climáticos, Brazil
Start Year 2013
 
Description Evaluation of snow remote sensing studentship - Canada 
Organisation Government of Canada
Department Environment Canada
Country Canada 
Sector Public 
PI Contribution Joint PhD supervision for student based in Northumbria University
Start Year 2010
 
Description Evaluation of snow remote sensing studentship - Northumbria 
Organisation Northumbria University
Country United Kingdom 
Sector Academic/University 
PI Contribution Joint PhD supervision for student based in Northumbria University
Start Year 2010
 
Description Joint project on LiDAR vegetation characterisation 
Organisation Monash University
Country Australia 
Sector Academic/University 
PI Contribution Collaborative research on determining vegetation structure from airborne laser altimetry data, using fieldwork and aerial acquisitions carried out in New South Wales.
Start Year 2008
 
Description Meteorologisches Institut 
Organisation University of Hamburg
Department Meteorologisches Institute
Country Germany 
Sector Academic/University 
PI Contribution Project Partnership
Start Year 2013
 
Description Snow and soil model development 
Organisation U.S. Department of Agriculture USDA
Country United States 
Sector Public 
PI Contribution Development and validation of physically-based snow and soil model
Start Year 2000
 
Description Snow microwave emission modelling 
Organisation Finnish Meteorological Institute
Country Finland 
Sector Public 
PI Contribution Development of field measurement methodology, evaluation of snow microwave emission model
Start Year 2010
 
Description Snow microwave emission modelling 
Organisation Government of Canada
Department Environment Canada
Country Canada 
Sector Public 
PI Contribution Development of field measurement methodology, evaluation of snow microwave emission model
Start Year 2010
 
Description Snow microwave emission modelling 
Organisation Northumbria University
Country United Kingdom 
Sector Academic/University 
PI Contribution Development of field measurement methodology, evaluation of snow microwave emission model
Start Year 2006
 
Description Snow microwave emission modelling 
Organisation University of Sherbrooke
Country Canada 
Sector Academic/University 
PI Contribution Development of field measurement methodology, evaluation of snow microwave emission model
Start Year 2010
 
Description Staff secondment to ECMWF 
Organisation European Centre for Medium Range Weather Forecasting ECMWF
Country European Union (EU) 
Sector Public 
PI Contribution Dr Stefano Migliorini was seconded to ECMWF for Research activity in the ECMWF Satellite Section
Start Year 2013
 
Description UK Met Office 
Organisation Meteorological Office UK
Country United Kingdom 
Sector Public 
PI Contribution Collaboration
Start Year 2013
 
Description Cafe Scientifique Reading 
Form Of Engagement Activity A talk or presentation
Part Of Official Scheme? No
Geographic Reach Regional
Primary Audience Public/other audiences
Results and Impact Dr Melody Sandells gave a science talk to Cafe Scientifique Reading in December 2013

Increase in requests for further information.
Year(s) Of Engagement Activity 2013
 
Description Live Interview on BBC Radio Berkshire 
Form Of Engagement Activity A press release, press conference or response to a media enquiry/interview
Part Of Official Scheme? No
Geographic Reach Regional
Primary Audience Public/other audiences
Results and Impact Advice on why densely packed snow melts slower in response to suggestion by the Environment Agency that building snowmen will help prevent flooding.

Increase in requests for further information.
Year(s) Of Engagement Activity 2013
 
Description National Science and Engineering Week Careers Event March 2014 
Form Of Engagement Activity A talk or presentation
Part Of Official Scheme? No
Geographic Reach National
Primary Audience Schools
Results and Impact Dr Melody Sandells attended the National Science and Engineering Week Careers Event on behalf of the NCEO.

Increased the school children's knowledge and understanding of NCEO's science, and encouraged them to study science.
Year(s) Of Engagement Activity 2014
 
Description Polar regions: the weather, clothing, transport and wildlife 
Form Of Engagement Activity A talk or presentation
Part Of Official Scheme? No
Geographic Reach Local
Primary Audience Schools
Results and Impact Talk with primary school children about polar regions: the weather, clothing, transport and wildlife.

No description available.
Year(s) Of Engagement Activity 2012
 
Description Primary School Talks on the Polar Regions 
Form Of Engagement Activity A talk or presentation
Part Of Official Scheme? No
Geographic Reach Regional
Primary Audience Schools
Results and Impact Dr Melody Sandells gave talks to year 1-2 primary school children in Wiltshire on the Polar Regions

Increased the school children's knowledge and understanding of NCEO's science.
Year(s) Of Engagement Activity 2014
 
Description Quoted in David Mitchell's column in the Guardian newspaper 
Form Of Engagement Activity A magazine, newsletter or online publication
Part Of Official Scheme? No
Geographic Reach International
Primary Audience Public/other audiences
Results and Impact A response to the Environment Agency regarding their suggestion that building snowmen will help prevent flooding regarding the physics behind why more densely packed snow melts slower.

Increase in requests for further information.
Year(s) Of Engagement Activity 2013
 
Description Science Slam 
Form Of Engagement Activity A talk or presentation
Part Of Official Scheme? No
Geographic Reach Local
Primary Audience Schools
Results and Impact 22 March 2014; Dr Melody Sandells gave a science presentation to school students.

Increased the school children's knowledge and understanding of science.
Year(s) Of Engagement Activity 2014
 
Description Snow Mass satellite retrievals 
Form Of Engagement Activity A talk or presentation
Part Of Official Scheme? No
Geographic Reach Regional
Primary Audience Schools
Results and Impact Visit to a secondary school: Dr Melody Sandells developed an activity for AS-level physics students to look at snow mass satellite retrievals, derive snow mass using existing techniques and compare with ground-based observations, construct an energy balance for the snowpack and compute snow temperature and mass change over a diurnal cycle.

Increased school pupils' understanding of science.
Year(s) Of Engagement Activity 2013
 
Description Times Newspaper Interview 
Form Of Engagement Activity A press release, press conference or response to a media enquiry/interview
Part Of Official Scheme? No
Geographic Reach International
Primary Audience Public/other audiences
Results and Impact Advice on why densely packed snow melts slower in response to suggestion by the Environment Agency that building snowmen will help prevent flooding.

Increase in requests for further information.
Year(s) Of Engagement Activity 2013