A Severe Weather Quick Observing System Simulation Experiment (QuickOSSE) of Global Navigation Satellite System (GNSS) Radio Occultation (RO) Superconstellations

Leidner, S. Mark; Nehrkorn, Thomas; Henderson, John; Mountain, Marikate; Yunck, Tom; Hoffman, Ross N.

doi:10.1175/mwr-d-16-0212.1

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A Severe Weather Quick Observing System Simulation Experiment (QuickOSSE) of Global Navigation Satellite System (GNSS) Radio Occultation (RO) Superconstellations

2017
By Leidner, S. Mark ; Nehrkorn, Thomas ; Henderson, John ; ...
Source: Monthly Weather Review, 145(2), 637-651.

[PDF-2.51 MB]

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Journal Title:

Monthly Weather Review
Personal Author:

Leidner, S. Mark ; Nehrkorn, Thomas ; Henderson, John ; Mountain, Marikate ; Yunck, Tom ; ... More +

Leidner, S. Mark ; Nehrkorn, Thomas ; Henderson, John ; Mountain, Marikate ; Yunck, Tom ; Hoffman, Ross N. Less -
NOAA Program & Office:

OAR (Oceanic and Atmospheric Research) ; AOML (Atlantic Oceanographic and Meteorological Laboratory) ; CIMAS (Cooperative Institute for Marine and Atmospheric Studies)

OAR (Oceanic and Atmospheric Research) ; AOML (Atlantic Oceanographic and Meteorological Laboratory) ; CIMAS (Cooperative Institute for Marine and Atmospheric Studies) Less -
Description:

Global Navigation Satellite System (GNSS) radio occultations (RO) over the last 10 years have proved to be a valuable and essentially unbiased data source for operational global numerical weather prediction. However, the existing sampling coverage is too sparse in both space and time to support forecasting of severe mesoscale weather. In this study, the case study or quick observing system simulation experiment (Quick-OSSE) framework is used to quantify the impact of vastly increased numbers of GNSS RO profiles on mesoscale weather analysis and forecasting. The current study focuses on a severe convective weather event that produced both a tornado and flash flooding in Oklahoma on 31 May 2013. The WRF Model is used to compute a realistic and faithful depiction of reality. This 2-km "nature run'' (NR) serves as the "truth'' in this study. The NR is sampled by two proposed constellations of GNSS RO receivers that would produce 250 thousand and 2.5 million profiles per day globally. These data are then assimilated using WRF and a 24-member, 18-km-resolution, physics-based ensemble Kalman filter. The data assimilation is cycled hourly and makes use of a nonlocal, excess phase observation operator for RO data. The assimilation of greatly increased numbers of RO profiles produces improved analyses, particularly of the lower-tropospheric moisture fields. The forecast results suggest positive impacts on convective initiation. Additional experiments should be conducted for different weather scenarios and with improved OSSE systems.
Source:

Monthly Weather Review, 145(2), 637-651.
DOI:

https://doi.org/10.1175/mwr-d-16-0212.1
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Journal Article
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urn:sha256:3365145b6a7eb3d4dfcdc5e008480f5b4e9edd2f574b127639a655c07eaca41d
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A Severe Weather Quick Observing System Simulation Experiment (QuickOSSE) of Global Navigation Satellite System (GNSS) Radio Occultation (RO) Superconstellations

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