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Systematic Evaluation of The Impact of Assimilating A Network of Ground-based Remote Sensing Profilers For Forecasts of Nocturnal Convection Initiation During Pecan

Abstract

Nocturnal convection is often initiated by mechanisms that cannot be easily observed within the large gaps between rawinsondes or by conventional surface networks. To improve forecasts of such events, we evaluate the systematic impact of assimilating a collocated network of high-frequency, ground-based thermodynamic and kinematic profilers collected as part of the 2015 Plains Elevated Convection At Night (PECAN) experiment. For 13 nocturnal convection initiation (CI) events, we find small but consistent improvements when assimilating thermodynamic observations collected by Atmospheric Emitted Radiance Interferometers (AERIs). Through midlevel cooling and moistening, assimilating the AERIs increases the fractions skill score (FSS) for both nocturnal CI and precipitation forecasts. The AERIs also improve various contingency metrics for CI forecasts. Assimilating composite kinematic datasets collected by Doppler lidars and radar wind profilers (RWPs) results in slight degradations to the forecast quality, including decreases in the FSS and traditional contingency metrics. The impacts from assimilating thermodynamic and kinematic profilers often counteract each other, such that we find little impact on the detection of CI when both are assimilated. However, assimilating both datasets improves various properties of the CI events that are successfully detected (timing, distance, shape, etc.). We also find large variability in the impact of assimilating these remote sensing profilers, likely due to the number of observing sites and the strength of the synoptic forcing for each case. We hypothesize that the lack of flow-dependent methods to diagnose observation errors likely contributes to degradations in forecast skill for many cases, especially when assimilating kinematic profilers.

Article / Publication Data
Active/Online
YES
Volume
148
Available Metadata
Accepted On
September 17, 2020
DOI ↗
Fiscal Year
NOAA IR URL ↗
Peer Reviewed
YES
Publication Name
Monthly Weather Review
Published On
November 24, 2020
Publisher Name
American Meteorological Society
Print Volume
148
Print Number
12
Page Range
4703–4728
Issue
12
Submitted On
April 16, 2020
URL ↗

Authors

Authors who have authored or contributed to this publication.