Jordan Gerth Jordan Gerth, Ph.D.
Associate Researcher
Cooperative Institute for Meteorological Satellite Studies
Space Science and Engineering Center
University of Wisconsin — Madison
Madison, Wisconsin, USA
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My curriculum vitae as of January 2018, and a short biography as of September 2016

Summary of Work

NWS Forecaster
GOES-R and JPSS Proving Grounds
Bridging the gap from research to operations
Role: Co-Investigator

The Geostationary Operational Environmental Satellite R-Series (GOES-R) and Joint Polar Satellite System (JPSS) Proving Grounds are an orchestrated effort among several cooperative institutes, including CIMSS, and the National Oceanic and Atmospheric Administration (NOAA) to prepare the primary users of geostationary and polar satellite data, forecasters at the National Weather Service (NWS), for the launch and operational activation of GOES-R and JPSS. Compared to the current GOES series, the amount of raw GOES-R data processed will increase by 60, with additional products derived from the increase in spatial, temporal, and spectral resolutions. This continuing multi-year effort includes conducting training at NWS units and constructing virtual learning activities, finding new ways to use existing space-based resources for emulating GOES-R and JPSS imagery and science products, such as exploiting the capabilities of the Suomi National Polar-orbiting Partnership (NPP), readying GOES-R and JPSS Proving Ground products for operations through incorporation into the Advanced Weather Interactive Processing System (AWIPS), and building a close relationship between algorithm developers and users to ensure a two-way dialogue that results in the best possible transition from current GOES to GOES-R deployment, and from NPP to JPSS.
Satellite Data Assimilation
Improving weather forecasts for the Great Lakes
Role: Investigator

The National Aeronautics and Space Administration (NASA) operate a series of polar-orbiting satellites which are used to make atmospheric measurements. These space-based observations have been shown useful in improving numerical weather prediction simulations. This work includes using the Weather Research and Forecast (WRF) Model with initial conditions modified by data from two NASA satellites equipped with a MODerate Resolution Imaging Spectroradiometer (MODIS) to assess the impact of space-based data on mesoscale weather simulations (occurring on a horizontal grid of 20-kilometer spacing or less) over regional sectors. A particularly notable region is the Great Lakes, where the marine-modified atmosphere plays a significant role in the weather of coastal communities. The end goal is to show improved temperature and moisture forecasts and provide this data to the NWS in real-time.

Sky Cover
Toward a better analysis and short-term forecasts
Role: Investigator

NWS meteorologists are required to produce gridded sky cover forecasts as part of their routine duties and submit them to the National Digital Forecast Database (NDFD). Discrepancies in the NDFD sky cover forecast remain despite progress with other weather elements since the inception of the NDFD. There are two causes for this. First, a suitable sky cover analysis does not exist for validation purposes. Second, the diagnostic sky cover formulation currently used in numerical weather prediction models, which provide input to the NDFD, does not adequately represent some cloud patterns. This research devises a methodology to incorporate both geostationary satellite and in-situ observations of cloud into a single sky cover analysis. Using an optimization methodology, this analysis is then compared to numerical weather model fields to establish a linear correlation between sky cover and prognostic model variables. The objective is to improve short-term sky cover forecasts.

Current Support Activities

  • Advanced Weather Interactive Processing System (AWIPS)
  • Common Operations and Development Environment (CODE) Radar Product Generator (RPG) and Level II Radar Ingest
  • Local Data Manager (LDM) and Unidata, other Decoders
  • L/X-Band Antenna Network
  • Common Satellite Processing Package (CSPP)
  • Satellite Information Familiarization Tool (SIFT) – Download
  • CIMSS Regional Assimilation System (CRAS) Model – Recent Runs
  • Weather Research and Forecast (WRF) Model

Previous Projects

  • Convectively Induced and Clear Air Turbulence via MODIS
  • Volcanic Ash and Clouds from AVHRR Extended (CLAVR-X)

Scientific and Technical Computing Expertise

  • C/C++
  • Eclipse Software Development Kit (SDK)
  • Fortran
  • General Algebraic Modeling System (GAMS)
  • GEneral Meteorology PAcKage (GEMPAK/N-AWIPS)
  • GRIdded Binary (GRIB) and GRIB2 data formats
  • Hierarchical Data Format (HDF)
  • Integrated Data Viewer (IDV)
  • Java
  • Linux scripting (bash, csh, ksh, tcsh)
  • Man computer Interactive Data Access System (McIDAS) X and V
  • Mathworks' MATLAB
  • Network Common Data Format (NetCDF)
  • Perl
  • PHP
  • PostgreSQL
  • Python
Jordan Gerth (L) and Marsha Mailick (C)

Additional Information

Jordan Gerth, Ph.D.

1225 W. Dayton St. #431
Madison, WI 53706

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October 16, 2018