Marilyn M. Wolfson

TL;DR: In this paper, the authors proposed a sequential variational approach that possesses advantages of both a standard statistical analysis [such as with a three-dimensional variational data assimilation (3DVAR) or Kalman filter] and a traditional objective analysis (such as the Barnes analysis).

TL;DR: In this article, the authors studied the behavior of a one-dimensional radiative-convective model with two types of cloud variation: (1) variable cloud cover with constant optical thickness and (2) variable optical thickness with constant cloud cover.

TL;DR: In this paper, an image filter approximating the envelope of the organized storm radar image is applied to a pixel in a received weather radar image to generate a processed pixel value and a variability value is determined from the variation in the pixel values of the neighboring pixels which lie within the image filter.

TL;DR: In this article, an image filter is used to identify areas of interest within a meteorological image that are likely to contain convective weather, and an image difference processor is applied to identify sub-image regions within the image that experience a growth and/or decay of weather events.

TL;DR: In this paper, a study designed to accumulate statistics on the gust frontal signature in Doppler radar data, nine gust front cases were analyzed and data were collected on those characteristics thought to be most important in developing rules for automatic gust-front detection such as gust front length and height, maximum and minimum values of reflectivity, velocity and spectrum width, and estimates of radial shear.