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Evaluation of a High-Resolution Numerical Weather Prediction Model’s Simulated Clouds Using Observations from CloudSat, GOES-13 and in Situ AircraftThis study aimed to assess tropical cloud properties predicted by Environment and Climate Change Canada’s Global Environmental Multiscale (GEM)modelwhen run with the Milbrandt–Yau double-moment cloud microphysical scheme and one-way nesting that culminated at a (∼300 km)2 inner domain with 0.25 km horizontal grid spacing. The assessment utilized satellite and in situ data collected during the High Ice Water Content (HIWC) and High Altitude Ice Crystals (HAIC) projects for a mesoscale convective system on 16May 2015 over French Guiana.Data fromCloud- Sat’s cloud-profiling radar and GOES-13’s imager were compared to data either simulated directly by GEM or produced by operating on GEM’s cloud data with both the CFMIP (Cloud Feedback Model Intercomparison Project) Observation Simulator Package (COSP) instrument simulator and a three-dimensional Monte Carlo solar radiative transfer model. In situ observations were made from research aircraft – Canada’s National Research Council Convair-580 and the French SAFIRE Falcon-20 – whose flight paths were aligned with CloudSat’s ground-track. Spatial and temporal shifts of clouds simulated by GEM compared well to GOES-13 imagery. There are, however, differences between simulated and observed amounts of high and low cloud. While GEM did well at predicting ranges of ice-water content (IWC) near 11 km altitude (Falcon-20), it produces too much graupel and snow near 7 km (Convair-580). This produced large differences between CloudSat’s and COSP-generated radar reflectivities and two-way attenuations. On the other hand, CloudSat’s inferred values of IWC agree well with in situ samples at both altitudes. Generally, GEM’s visible reflectances exceeded GOES-13’s on account of having produced too much low-level liquid cloud. It is expected that GEM’s disproportioning of cloud hydrometeors will improve once it includes a better representation of secondary ice production.


Document ID
20200002640
Acquisition Source
Langley Research Center
Document Type
Reprint (Version printed in journal)
External Source(s)
Authors
Qu, Zhipeng
(Environment and Climate Change Canada (ECCC) Toronto, Ontario, Canada)
Barker, Howard W.
(Environment and Climate Change Canada (ECCC) Toronto, Ontario, Canada)
Korolev, Alexei V.
(Environment and Climate Change Canada (ECCC) Toronto, Ontario, Canada)
Milbrandt, Jason A.
(Environment and Climate Change Canada (ECCC) Dorval, Quebec, Canada)
Heckman, Ivan
(Environment and Climate Change Canada (ECCC) Toronto, Ontario, Canada)
Bélair, Stéphane
(Environment and Climate Change Canada (ECCC) Dorval, Quebec, Canada)
Leroyer, Sylvie
(Environment and Climate Change Canada (ECCC) Dorval, Quebec, Canada)
Vaillancourt, Paul A.
(Environment and Climate Change Canada (ECCC) Dorval, Quebec, Canada)
Wolde, Mengistu
(National Research Council of Canada (HQ) Ottawa, Ontario, Canada)
Schwarzenböck, Alfons
(Université Blaise-Pascal Clermont-Ferrand, France)
Leroy, Delphine
(Université Blaise-Pascal Clermont-Ferrand, France)
Strapp, J. Walter
(Met Analytics Aurora, Ontario, Canada)
Cole, Jason N. S.
(Environment and Climate Change Canada (ECCC) Toronto, Ontario, Canada)
Nguyen, Louis
(NASA Langley Research Center Hampton, VA, United States)
Heidinger, Andrew
(National Oceanic and Atmospheric Administration (NOAA) Madison, WI, United States)
Date Acquired
April 17, 2020
Publication Date
April 27, 2018
Publication Information
Publication: Quarterly Journal of the Royal Meteorological Society
Publisher: Wiley
Volume: 144
Issue: 715
ISSN: 0035-9009
e-ISSN: 1477-870X
Subject Category
Earth Resources And Remote Sensing
Report/Patent Number
NF1676L-31651
ISSN: 0035-9009
E-ISSN: 1477-870X
Report Number: NF1676L-31651
Funding Number(s)
WBS: 652528.02.01
Distribution Limits
Public
Copyright
Other

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