CRESTNOAA Nowcasting Project

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CREST/NOAA Nowcasting Project

• Reza Khanbilvardi, Arnold Gruber, Shayesteh
  Mahani, Margarita Mihailidi,
• Viviana Crespo and Ryan HutchinsonCREST, City
  University of New York

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Status of the CREST/NOAA Nowcasting Project

• CREST has recently initiated a nowcasting project
  (30-90 minute forecasts of high impact rain and
  weather events) in partnership with NOAA.
• NOAA partners are
• National Environmental Satellite and Data and
  Information Service, Office of Research and
  Applications
• National Weather Service, Meteorological
  Development Laboratory
• Office of Oceanic and Atmospheric Research,
  National Severe Storms Laboratory
• The goal is to implement a geostationary
  satellite based nowcasting model for the New York
  City Metropolitan Area
• Collaboration with the European Organisation for
  the Exploitation of Meteorological Satellites
  (EUMETSAT)
• Beta tester for EUMETSAT Rapidly Developing
  Thunderstorm (RDT) nowcasting model
• RDT is used operationally by EUMETSAT for
  identification and tracking of developing
  thunderstorms
• First model to be implemented at CREST

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Status of the CREST/NOAA Nowcasting Project

• Other models under consideration
• Hydro-Nowcaster NESDIS Geostationary model
• Warning Decision Support System Integrated
  Information (WDSSII) Multiscale Storm
  Identification and Forecast Algorithm OAR/NSSL
  model uses radar will be modified to use
  satellite data
• CREST will utilize the nowcasting project to
• Train students in applications of satellite
  remote sensing observations to severe weather and
  rainfall nowcasts
• Rainfall estimation, cloud screening and
  identification, atmospheric moisture and
  temperature structure and wind
• Provide experimental nowcasts on the web to
  increase public awareness in applications of
  remote sensing to the environment.
• This project helps NOAA in achieving its
  strategic planning goals in Weather and Water,
  specifically
• Improve predictability of the onset, duration,
  and impact of hazardous and severe weather and
  water events
• enhance environmental literacy and improve
  understanding, value, and use of weather and
  water information and services.

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Plan

• Initial
• Implement RDT model on CREST computer system
• Run model for case studies of warm season heavy
  rain events and evaluate nowcasts
• Evaluation will use data from the CREST weather
  station, volunteer stations, NWS stations and
  radar data
• Set up web page
• Establish an archive of all input data and
  outputs.

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NOAA sites
28 NOAA Stations in NE
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Number of Stations
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CCNY website Northeast

• http//earth.engr.ccny.cuny.edu/noaa/wc/Stations/W
  eatherStations.html

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PLAN (Cont.)

• Future
• Work with partners in evaluating RDT, Hydro
  Nowcaster and WDSSII Multiscale Storm
  Identification and Forecast Algorithm for NYC
  Metro Area
• Extend to cool season extreme rain events
• Utilize meso-scale Weather Research Forecasting
  Model (WRF) output to help in nowcasts,
  initiation and dissipation ( e.g., winds,
  vorticity, boundary layer convergence. etc)
• Make routine nowcasts for NYC metro available on
  web.

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Current Status

• Downloaded RDT software from EUMETSAT
• Working on implementation and checkout of
  software using EUMETSAT data
• Two students Ryan Hutchinson and Viviana Crespo
  being trained to work on project.
• Survey of severe weather and heavy rainfall being
  conducted by students for 2003-2005 for case
  studies

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Concluding Remarks

• This project is in its initial phase
• We have established a strong working relationship
  with NESDIS, NWS and OAR that blends research and
  operational activities.
• This combination will enhance CRESTs educational
  and research goals and help NOAA achieve its
  strategic planning goals
• The team is actively pursuing funding from the
  GOES R program for continued support. Focused
  GOES R Risk Reduction tasks include
• Utilize MODIS, AIRS, National Lightning Detection
  Network Data to investigate possible use of new
  data available from GOES R ( ABI, HES, GLM) for
  improving existing nowcasting models, e.g., storm
  development and decay
• Investigate impact of increased refresh rates,
  i.e., from 15 min to 5 min
• Investigate improved water vapor wind fields
  expected from GOES R for upper level divergence
  fields and use in initiation, intensity and
  duration of convective storms
• ABI-Advanced baseline Imager, HES- Hyperspectral
  Environmental Suite, GLM- GOES Lightning Mapper

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New York City Metropolitan Area as defined by US
Census Bureau ( NY, Northern NJ, Southern
Conn., and a small part of Pa.)
NYC Metro area is largest in Nation and has about
22 million people
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