The Exploitation of new data sources, data assimilation and ensemble techniques for storm and flood forecasting Project is a NERC Flood Risk for Extreme Events (FREE) Research Programme project (Round 1 - NE/E002137/1 - Duration January 2007 - April 2010) led by Prof AJ Illingworth, University of Reading. This project investigates possible methods of producing ensemble weather forecasts at high-resolution. These ensembles will be used with raingauge and river flow to improve methods of flood forecasting. The dataset includes radiosonde and wind profiles in England and Wales derived using Doppler radar returns from insects. The radial velocity measurements from insects were converted into VAD profiles by fitting a sinusoid to radial velocities at constant range. All measured profiles have been interpolated to the instrument location.
This dataset contains wind profiler measurements.
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Public data: access to these data is available to both registered and non-registered users.
Use of these data is covered by the following licence: http://www.nationalarchives.gov.uk/doc/open-government-licence/version/3/. When using these data you must cite them correctly using the citation given on the CEDA Data Catalogue record.
Data were collected using Doppler radar in England and Wales. All measured profiles have been interpolated to the instrument location.
Data are netCDF formatted
- units: m
- long_name: model level height in m
- standard_name: height
- var_id: height
- names: height, model level height in m
- standard_name: eastward_wind
- units: m s-1
- var_id: u
- long_name: observed eastward_wind
- names: eastward_wind, observed eastward_wind
- units: m s-1
- long_name: observed northward_wind
- var_id: v
- standard_name: northward_wind
- names: northward_wind, observed northward_wind
- standard_name: latitude
- units: degree_north
- var_id: lat
- long_name: latitude
- names: latitude
- var_id: lon
- units: degree_east
- standard_name: longitude
- long_name: longitude
- names: longitude
- long_name: time
- standard_name: time
- var_id: time
- names: time