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Grant: Collaborative Research and Development Grants

York University

$66,000.00

Virtual weather observations, forecasting and validation

FY 2015-16

Summary
Pelmorex Media Inc. via The Weather Network provide high quality weather information to consumers and commercial clients across Canada and in other parts of the world. Forecasts for approximately 20,000 sites in Canada are distributed via TV, internet and mobile phones with an emphasis on timely delivery. While current observations are available for about 1,000 of these forecast locations there are many more without in-situ observations. The aim of our research is to provide a methodology to generate best estimates with a ""Virtual Observation Engine"" (VOE). Pelmorex have a prototype engine using interpolations from available data (including about 1,000 weather stations in Canada and 7,000 world wide) coupled with numerical weather prediction forecasts. We will aim to improve the virtual observation engine through the use of data assimilation techniques, and careful down-scaling using simple guidelines or high resolution boundary-layer flow models. In addition York University (Dr Chen's group) are currently using the WRF (Weather Research and Forecasting) model and assimilating a range of data, including radar wind profiler data, in a joint, MITACS supported, project with Pelmorex. This is currently focused on Southern Ontario but will be expanded to test the use of this approach as a VOE for critical locations or areas across the country where other techniques have difficulty in predicting reliable virtual observations. Dr Taylor's group have worked with Pelmorex to assess the performance of their prototype VOE. In areas of even moderately complex terrain the effects of local topography and variations in surface properties (such as roughness and albedo) can play a significant role in determining local wind and temperature. The aim is to develop approaches which take better account of these factors within the Virtual Observation Engine approach.
Program
Collaborative Research and Development Grants
Location
Ontario, Canada
Recipient Type
Academia
Type
Grant
Source
NSERC's Awards Data

As published

Application id
477772-2014
Name nom
Taylor, Peter
Department département
Earth and Space Science and Engineering
Organization id
38
Institution établissement
York University
Province en
Ontario
Province fr
Ontario
Country en
CANADA
Country fr
CANADA
Fiscal year exercice financier
2015
Competition year année de concours
2014
Award amount
66000
Program id
CRDPJ
Program name en
Collaborative Research and Development Grants
Program name fr
Subventions de recherche et développement coopérative
Group en
Research partnerships programs
Group fr
Programmes de partenariat
Committee code
96
Committee name en
RPP Internal Decision Cttee
Committee name fr
Cté de décision interne - PPR
Area of application code
401
Area of application group en
Environment
Area of application group fr
Environnement
Area of application en
Climate and atmosphere
Area of application fr
Climat et atmosphère
Research subject code
4401
Research subject group en
Atmospheric science
Research subject group fr
Étude de l'atmosphère
Research subject en
Dynamic meteorology
Research subject fr
Météorologie dynamique
Partie
1
Nb partie
2
Application title
Virtual weather observations, forecasting and validation
Keyword
NSERC
Application summary
Pelmorex Media Inc. via The Weather Network provide high quality weather information to consumers and commercial clients across Canada and in other parts of the world. Forecasts for approximately 20,000 sites in Canada are distributed via TV, internet and mobile phones with an emphasis on timely delivery. While current observations are available for about 1,000 of these forecast locations there are many more without in-situ observations. The aim of our research is to provide a methodology to generate best estimates with a ""Virtual Observation Engine"" (VOE). Pelmorex have a prototype engine using interpolations from available data (including about 1,000 weather stations in Canada and 7,000 world wide) coupled with numerical weather prediction forecasts. We will aim to improve the virtual observation engine through the use of data assimilation techniques, and careful down-scaling using simple guidelines or high resolution boundary-layer flow models. In addition York University (Dr Chen's group) are currently using the WRF (Weather Research and Forecasting) model and assimilating a range of data, including radar wind profiler data, in a joint, MITACS supported, project with Pelmorex. This is currently focused on Southern Ontario but will be expanded to test the use of this approach as a VOE for critical locations or areas across the country where other techniques have difficulty in predicting reliable virtual observations. Dr Taylor's group have worked with Pelmorex to assess the performance of their prototype VOE. In areas of even moderately complex terrain the effects of local topography and variations in surface properties (such as roughness and albedo) can play a significant role in determining local wind and temperature. The aim is to develop approaches which take better account of these factors within the Virtual Observation Engine approach.