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Enhance Low Level Temperature and Moisture Profiles Through Combining NUCAPS, ABI Observations, and RTMA Analysis

Journal Article · · Earth and Space Science
DOI:https://doi.org/10.1029/2020ea001402· OSTI ID:1784267
 [1];  [2];  [2];  [3];  [4];  [5];  [6]
  1. Chinese Academy of Sciences (CAS), Beijing (China); Univ. of Wisconsin, Madison, WI (United States); Univ. of Chinese Academy of Sciences (CAS), Beijing (China)
  2. Univ. of Wisconsin, Madison, WI (United States)
  3. NEDIS/NOAA, Madison, WI (United States)
  4. National Oceanic and Atmospheric Administration (NOAA), Miami, FL (United States)
  5. Univ. of Maryland Baltimore County (UMBC), Baltimore, MD (United States); National Oceanic and Atmospheric Administration (NOAA), Miami, FL (United States)
  6. National Oceanic and Atmospheric Administration (NOAA), College Park, MD (United States)
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Thermodynamic information from low levels in the atmosphere is crucial for operational weather forecasts and meteorological researchers. The NOAA Unique Combined Atmospheric Processing System (NUCAPS) sounding products have been proven beneficial to fill the data gap between synoptic radiosonde observations (RAOBs). However, compared with the upper troposphere, the accuracy of NUCAPS soundings in the low levels still needs improvement. In this study, a deep neural network (DNN) is applied to fuse multiple data sources to enhance the NUCAPS temperature and moisture profiles in the lower atmosphere. The network is developed by combining satellite observations, including NUCAPS sounding retrievals and high resolution geostationary satellite observations from the Advanced Baseline Imager, and surface analysis from the Real-Time Mesoscale Analysis (RTMA) as inputs, while collocated soundings from ECMWF re-analysis version 5 are used as the benchmark for the training. The performance of the model is evaluated by using the independent testing data set, data from a different year, as well as collocated RAOBs, showing improvement to the temperature and moisture profiles by reducing the root-mean-squared-error (RMSE) by more than 30% in the lower atmosphere (from 700 hPa to surface) in both clear sky and partially cloudy conditions. A convective event from June 18, 2017 is presented to illustrate the application of the enhanced low level soundings on high impact weather events. The enhanced soundings from fused data capture the large surface-based convective available potential energy structures in the preconvection environment, which is very useful for severe storm nowcasting and forecasting applications.
Research Organization:
Oak Ridge National Laboratory (ORNL), Oak Ridge, TN (United States). Atmospheric Radiation Measurement (ARM) Data Center
Sponsoring Organization:
USDOE Office of Science (SC), Biological and Environmental Research (BER)
Grant/Contract Number:
AC05-76RL01830
OSTI ID:
1784267
Journal Information:
Earth and Space Science, Journal Name: Earth and Space Science Journal Issue: 6 Vol. 8; ISSN 2333-5084
Publisher:
American Geophysical Union (AGU)Copyright Statement
Country of Publication:
United States
Language:
English

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Related Subjects

54 ENVIRONMENTAL SCIENCES
ABI
NUCAPS
low level
sounding
surface observation