Parameterization of the Spatial Variability of Rain for Large-Scale Models and Remote Sensing

Lebo, Z. J.; Williams, C. R.; Feingold, G.; Larson, V. E.

doi:10.1175/JAMC-D-15-0066.1

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Parameterization of the Spatial Variability of Rain for Large-Scale Models and Remote Sensing

2015
By Lebo, Z. J. ; Williams, C. R. ; Feingold, G. ; ...
Source: J. Appl. Meteor. Climatol. (2015) 54 (10): 2027–2046.

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Journal Title:

Journal of Applied Meteorology and Climatology
Personal Author:

Lebo, Z. J. ; Williams, C. R. ; Feingold, G. ; Larson, V. E.

Lebo, Z. J. ; Williams, C. R. ; Feingold, G. ; Larson, V. E. Less -
NOAA Program & Office:

OAR (Oceanic and Atmospheric Research) ; ESRL (Earth System Research Laboratory) ; CSL (Chemical Sciences Laboratory) ; PSL (Physical Sciences Laboratory) ; CIRES (Cooperative Institute for Research in Environmental Sciences)

OAR (Oceanic and Atmospheric Research) ; ESRL (Earth System Research Laboratory) ; CSL (Chemical Sciences Laboratory) ; PSL (Physical Sciences Laboratory) ; CIRES (Cooperative Institute for Research in Environmental Sciences) Less -
Description:

The spatial variability of rain rate R is evaluated by using both radar observations and cloud-resolving model output, focusing on the Tropical Warm Pool–International Cloud Experiment (TWP-ICE) period. In general, the model-predicted rain-rate probability distributions agree well with those estimated from the radar data across a wide range of spatial scales. The spatial variability in R, which is defined according to the standard deviation of R (for R greater than a predefined threshold Rmin) σ(R), is found to vary according to both the average of R over a given footprint μ(R) and the footprint size or averaging scale Δ. There is good agreement between area-averaged model output and radar data at a height of 2.5 km. The model output at the surface is used to construct a scale-dependent parameterization of σ(R) as a function of μ(R) and Δ that can be readily implemented into large-scale numerical models. The variability in both the rainwater mixing ratio qr and R as a function of height is also explored. From the statistical analysis, a scale- and height-dependent formulation for the spatial variability of both qr and R is provided for the analyzed tropical scenario. Last, it is shown how this parameterization can be used to assist in constraining parameters that are often used to describe the surface rain-rate distribution.
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Atmospheric Science Rain And Rainfall Remote Sensing
Source:

J. Appl. Meteor. Climatol. (2015) 54 (10): 2027–2046.
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https://doi.org/10.1175/JAMC-D-15-0066.1
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Journal Article
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urn:sha256:000fc79f817a907ce1ce93bcde2b3e6d94c8c024e81362c7b6069327c0ae7a02
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Parameterization of the Spatial Variability of Rain for Large-Scale Models and Remote Sensing

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