Details:

Journal Title:
Monthly Weather Review
Personal Author:
Hamill, Thomas M.
NOAA Program & Office:
OAR (Oceanic and Atmospheric Research) ; PSL (Physical Sciences Laboratory)
OAR (Oceanic and Atmospheric Research) ; PSL (Physical Sciences Laboratory) Less -
Description:
High-quality, high-resolution, hourly unbiased surface (2 m) temperature analyses are needed for many applications, including training and validation of statistical postprocessing applications. These temperature analyses are often generated through data assimilation procedures, whereby a background short-range gridded forecast is adjusted to newly available observations. Even with frequent updates to newly available observations, surface-temperature analysis errors and biases can be comparatively large relative to errors and biases of midtropospheric variables, especially over land, despite more near-surface in situ observations. Larger near-surface errors may have several causes, including biased background forecasts and the spatial heterogeneity of surface temperatures that results from subgrid-scale surface, vegetation, land-use, and terrain variations. Are biased raw background forecasts the predominant cause of surface temperature analysis errors? Part I of this two-part series describes a simple benchmark for evaluating the error characteristics of short-term (1 h) raw model background surface temperature forecasts. For stations with a relatively complete time series of data, it is possible to generate an hourly, diurnally, and seasonally dependent observation climatology at a station. The deviation of the current hour’s temperature observation with respect to this hour’s and Julian day’s climatology is added to the climatology for the next hour. For contiguous U.S. stations in July 2015, the station benchmark was lower in error than interpolated 1-h high-resolution numerical predictions of surface temperature from NOAA’s High-Resolution Rapid Refresh (HRRR) system, although not including full postprocessing. For August 2018, 1-h HRRR forecasts were much improved when tested against the station benchmark.
Keywords:
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Forecast Verification Model Initialization Nowcasting Statistical Forecasting Surface Observations
Source:
Monthly Weather Review, 148(2), 689-700.
DOI:
https://doi.org/10.1175/MWR-D-19-0027.1
Document Type:
Journal Article
Rights Information:
Other
Compliance:
Submitted
Main Document Checksum:
[+]
urn:sha256:cd3df39c603d52741b91014b7a5fa4ed096e56a7b448a19f4dd3481499cf9933
Download URL:
https://repository.library.noaa.gov/view/noaa/31117/noaa_31117_DS1.pdf
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