Manually-Digitized Radar Data for the Midwest and Eastern United States
d840000
The former Techniques Development Laboratory (TDL) of the U.S. National Weather Service began collecting Manually-Digitized Radar (MDR) data in November 1973 from teletype reports. The MDR data were then archived in Model Output Statistics (MOS) predictand tape format to be used for thunderstorm prediction. The data were intended for both general and severe thunderstorm prediction using MOS which related the radar data to large-scale predictors from operational numerical models. Other uses of the data included development of improved initial moisture fields in TDL numerical models and verification of convective weather forecasts. The MDR data were archived for a pseudo-grid covering roughly the eastern two-thirds of the United States. This pseudo-grid was a subset of the 47 by 51 (octagonal) polar-stereographic grid that was used for numerical weather output at the time.
dataset
https://rda.ucar.edu/datasets/d840000/
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https://rda.ucar.edu/datasets/d840000/dataaccess/
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applicationProfile: browser
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function: download
climatologyMeteorologyAtmosphere
dataset
revision
2014-10-16
WEATHER STATIONS > WEATHER STATIONS
revision
2024-07-23
WEATHER RADARS
revision
2024-06-28
EARTH SCIENCE > SPECTRAL/ENGINEERING > RADAR > RADAR REFLECTIVITY
revision
2024-07-24
-130.0637
-60.1448
57.8226
17.9164
1973-11-01
1977-09-05
publication
1980-01-11
notPlanned
Creative Commons Attribution 4.0 International License
None
UCAR/NCAR - Research Data Archive
National Center for Atmospheric Research
CISL/DECS
P.O. Box 3000
Boulder
80307
U.S.A.
(303)-497-1825
303-497-1291
pointOfContact
NCAR Research Data Archive
National Center for Atmospheric Research
CISL/DECS
P.O. Box 3000
Boulder
80307
U.S.A.
303-497-1291
name: NCAR Research Data Archive
description: The Research Data Archive (RDA), managed by the Data Engineering and Curation Section (DECS) of the Computational and Information Systems Laboratory (CISL) at NCAR, contains a large and diverse collection of meteorological and oceanographic observations, operational and reanalysis model outputs, and remote sensing datasets to support atmospheric and geosciences research, along with ancillary datasets, such as topography/bathymetry, vegetation, and land use.
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pointOfContact
2024-08-04T02:11:46Z