NCEO High Impact Weather and Flooding
Lead Research Organisation:
National Centre for Earth Observation
Department Name: UNLISTED
Abstract
Abstracts are not currently available in GtR for all funded research. This is normally because the abstract was not required at the time of proposal submission, but may be because it included sensitive information such as personal details.
Organisations
- National Centre for Earth Observation (Lead Research Organisation)
- National Aeronautics and Space Administration (NASA) (Collaboration)
- Government of Canada (Collaboration)
- Finnish Meteorological Institute (Collaboration)
- National Science Foundation (NSF) (Collaboration)
- NORTHUMBRIA UNIVERSITY (Collaboration)
- European Centre for Medium Range Weather Forecasting ECMWF (Collaboration)
- National Institute for Space Research Brazil (Collaboration)
- International Space Science Institute (ISSI) (Collaboration)
- Meteorological Office UK (Collaboration)
- U.S. Department of Agriculture USDA (Collaboration)
- Bjerknes Centre for Climate Research (Collaboration)
- Universität Hamburg (Collaboration)
- University of Sherbrooke (Collaboration)
- Swiss Federal Institute for Forest, Snow and Landscape Research (Collaboration)
- British Antarctic Survey (Collaboration)
- Monash University (Collaboration)
People |
ORCID iD |
| Peter Jan Van Leeuwen (Principal Investigator) |
Publications
Bannister R
(2011)
Ensemble prediction for nowcasting with a convection-permitting model - II: forecast error statistics
in Tellus A: Dynamic Meteorology and Oceanography
Bengtsson L
(2011)
The changing atmospheric water cycle in Polar Regions in a warmer climate
in Tellus A: Dynamic Meteorology and Oceanography
Mesquita M
(2011)
Sea-ice anomalies in the Sea of Okhotsk and the relationship with storm tracks in the Northern Hemisphere during winter
in Tellus A: Dynamic Meteorology and Oceanography
Fowler A
(2011)
A new floating model level scheme for the assimilation of boundary-layer top inversions: the univariate assimilation of temperature
in Quarterly Journal of the Royal Meteorological Society
Troccoli A
(2011)
Storm surge frequency reduction in Venice under climate change
in Climatic Change
Hawcroft M
(2012)
How much Northern Hemisphere precipitation is associated with extratropical cyclones?
in Geophysical Research Letters
Carbonneau PE
(2012)
Fluvial Remote Sensing for Science and Management
Mason D
(2012)
Near Real-Time Flood Detection in Urban and Rural Areas Using High-Resolution Synthetic Aperture Radar Images
in IEEE Transactions on Geoscience and Remote Sensing
Harvey B
(2012)
How large are projected 21st century storm track changes?
in Geophysical Research Letters
Migliorini S
(2012)
On the Equivalence between Radiance and Retrieval Assimilation
in Monthly Weather Review
| 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 | 03/2010 |
| 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 | 03/2010 |
| End | 03/2017 |
| Description | Extinction of Microwave Radiation in Snow |
| Amount | £51,467 (GBP) |
| Organisation | Finnish Meteorological Institute |
| Sector | Public |
| Country | Finland |
| Start | |
| Description | Extinction of Microwave Radiation in Snow |
| Amount | £51,467 (GBP) |
| Organisation | Finnish Meteorological Institute |
| Sector | Public |
| Country | Finland |
| Start | 09/2013 |
| End | 09/2016 |
| 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 | 03/2013 |
| 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 | 03/2013 |
| 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 | Swiss Federal Institute for Forest, Snow and Landscape Research |
| Department | 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 | Academic/University |
| 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 | United Kingdom |
| 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 | Academic/University |
| 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 |