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Precipitation analysis using the Advanced Microwave Sounding Unit in support of nowcasting applications
SMHI, Research Department, Atmospheric remote sensing.ORCID iD: 0000-0003-2138-4325
SMHI, Core Services.
SMHI, Core Services.ORCID iD: 0000-0001-7370-8788
2002 (English)In: Meteorological Applications, ISSN 1350-4827, E-ISSN 1469-8080, Vol. 9, no 2, 177-189 p.Article in journal (Refereed) Published
Abstract [en]

We describe a method to remotely sense precipitation and classify its intensity over water, coasts and land surfaces. This method is intended to be used in an operational nowcasting environment. It is based on data obtained from the Advanced Microwave Sounding Unit (AMSU) onboard NOAA-15. Each observation is assigned a probability of belonging to four classes: precipitation-free, risk of precipitation, precipitation between 0.5 and 5 mm/h, and precipitation higher than 5 mm/h. Since the method is designed to work over different surface types, it relies mainly on the scattering signal of precipitation-sized ice particles received at high frequencies. For the calibration and validation of the method we use an eight-month dataset of combined weather radar and AMSU data obtained over the Baltic area. We compare results for the AMSU-B channels at 89 GHz and 150 GHz and find that the high frequency channel at 150 GHz allows for a much better discrimination of different types of precipitation than the 89 GHz channel. While precipitation-free areas, as well as heavily precipitating areas (> 5 mm/h), can be identified to high accuracy, the intermediate classes are more ambiguous. This stems from the ambiguity of the passive microwave observations as well as from the non-perfect matching of the different data sources and sub-optimal radar adjustment. In addition to a statistical assessment of the method's accuracy, we present case studies to demonstrate its capabilities to classify different types of precipitation and to work over highly structured, inhomogeneous surfaces.

Place, publisher, year, edition, pages
2002. Vol. 9, no 2, 177-189 p.
National Category
Meteorology and Atmospheric Sciences
Research subject
Remote sensing
Identifiers
URN: urn:nbn:se:smhi:diva-1386DOI: 10.1017/S1350482702002037ISI: 000176325100003OAI: oai:DiVA.org:smhi-1386DiVA: diva2:843983
Available from: 2015-08-03 Created: 2015-07-29 Last updated: 2016-04-08Bibliographically approved

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CiteExportLink to record
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Citation style
  • apa
  • harvard1
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More styles
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