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A Methodology for Verifying Cloud Forecasts with VIIRS Imagery and Derived Cloud Products—A WRF Case Study

A methodology is presented to evaluate the accuracy of cloud cover fraction (CCf) forecasts
generated by numerical weather prediction (NWP) and climate models. It is demonstrated with a
case study consisting of simulations from theWeather Research and Forecasting (WRF) model. In this
study, since the WRF CCf forecasts were initialized with reanalysis fields from the North American
Mesoscale (NAM) Forecast System, the characteristics of the NAM CCf products were also evaluated.
The procedures relied extensively upon manually-generated, binary cloud masks created from VIIRS
(Visible Infrared Imager Radiometry Suite) imagery, which were subsequently converted into CCf
truth at the resolution of the NAM and WRF gridded data. The initial results from the case study
revealed biases toward under-clouding in the NAM CCf analyses and biases toward over-clouding in
the WRF CCf products. These biases were evident in images created from the gridded NWP products
when compared to VIIRS imagery and CCf truth data. Thus, additional simulations were completed
to help assess the internal procedures used in the WRF model to translate moisture forecast fields into
layered CCf products. Two additional sets of WRF CCf 24 h forecasts were generated for the region
of interest using WRF restart files. One restart file was updated with CCf truth data and another was
not changed. Over-clouded areas in the updated WRF restart file that were reduced with an update
of the CCf truth data became over-clouded again in the WRF 24 h forecast, and were nearly identical
to those from the unchanged restart file. It was concluded that the conversion of WRF forecast fields
into layers of CCf products deserves closer examination in a future study.

Identiferoai:union.ndltd.org:DRESDEN/oai:qucosa:de:qucosa:84608
Date06 April 2023
CreatorsHutchison, Keith D., Iisager, Barbara D., Dipu, Sudhakar, Jiang, Xiaoyan, Quaas, Johannes, Markwardt, Randy
PublisherMDPI
Source SetsHochschulschriftenserver (HSSS) der SLUB Dresden
LanguageEnglish
Detected LanguageEnglish
Typeinfo:eu-repo/semantics/publishedVersion, doc-type:article, info:eu-repo/semantics/article, doc-type:Text
Rightsinfo:eu-repo/semantics/openAccess
Relation2073-4433, 521

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