Improving Retrievals by the Stepped Frequency Microwave Radiometer in Midlatitude Winter Storms

Jezabel Vilardell Sanchez, Joseph W. Sapp, Zorana Jelenak, Paul S. Chang, Stephen J. Frasier

Research output: Contribution to journalArticlepeer-review

Abstract

We consider the radiative transfer model (RTM) employed by the stepped frequency microwave radiometer (SFMR) and its application in airborne wintertime observations of midlatitude storms and extratropical cyclones. We find that the current RTM, developed and tuned for use in tropical cyclones (TCs), does not adequately model the observed brightness temperatures typically encountered in these cold conditions. While the brightness temperatures observed at several frequencies across the C band are lower, they are more spread apart from each other than the TC RTM predicts. We consider two hypotheses to explain the differences between the measurements and model. One hypothesis assumes the presence of a melting layer between the aircraft and the surface, which imparts enhanced attenuation and emission, which would result in an enhanced spreading of brightness temperatures. The properties of the melting layer scale with rain rate. The other hypothesis is a wind-dependent excess emissivity possibly due to the surface-based layer of mixed-phase droplets lofted from the surface. The latter hypothesis is most consistent with observations when the freezing level, as deduced from the flight-level temperature and an assumed lapse rate, is at or below the surface. We find that the latter hypothesis better represents the observations compared to the first, in large part because there is often little to no rain present in the observations. An excess emissivity model for winter conditions is provided.

Original languageEnglish
Pages (from-to)815-826
Number of pages12
JournalJournal of Atmospheric and Oceanic Technology
Volume42
Issue number7
DOIs
StatePublished - Jul 2025
Externally publishedYes

Keywords

  • Aircraft observations
  • Instrumentation/sensors
  • Microwave observations
  • Remote sensing

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