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The time-series shows surface conditions for the closest point to The City College of New York. Shown below are the 2 meter temperature (F) and relative humidity (%), 8-hr accumulated precipitation (in mm, 1-hr accunmulated), and 10 meter wind speed (m/s) and wind direction (degrees from North with vectors pointing where the wind is moving towards; up is North). The 72 hr (3 days) forecast is produced on a daily basis.

The prediction is generated by the research group Coastal-Urban Environmental Research Group (CUERG) from City College of New York.

For the assessment, diagnostic meteorological variables are outputted at every time-step for the closest model point to the location of interest. The meteorological variables used are temperature (K), wind speed (m/s), and wind direction (degrees North).

The locations of interest are the weather stations located at John F. Kennedy International Airport (JFK), LaGuardia Airport (LGA) and Central Park, NYC (NYC). The stations are part of the Automatic Surface Observing System (ASOS) which is publicly available. We have a modified a tool developed at Iowa State University for automating the downloading of ASOS station data (for more information: https://mesonet.agron.iastate.edu/request/download.phtml ). Once the model and observations are downloaded, a time-matching algorithm matches WRF results closest in time to the observations. This allows us to use observations that may be reported inconsistently or at finer-than-hourly time scales without having to calculate means. The urban-WRF model is initialized every day using the 00-UTC NAM forecast and runs for 84 hours. Therefore, the previous day is modeled at least 3 times. WRF D-0 (“Day minus 0”) are the WRF results for the previous day for which the forecast was initialized on that day, WRF-D-1 (“Day minus one”) are the results for the same day but using data that was initialized one day before, and WRF D-2 (“Day minus two”) are the results of the previous day with a forecast initialized two days before the date of interest.

The code used for the Evaluation System is available through a public repository (https://github.com/thedmv/uwrf_evaluation_system/ ).

uWRF Evaluation

The Support for this work and corresponding data product was provided by the National Oceanic and Atmospheric Administration – Cooperative Science Center for Earth System Sciences and Remote Sensing Technologies (NOAA-CESSRST) under the Cooperative Agreement Grant #: NA16SEC4810008. We gratefully acknowledge support to The City College of New York, NOAA-CESSRST program and NOAA Office of Education, Educational Partnership Program.

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