Evaluation of a high‐resolution numerical weather prediction model's simulated clouds using observations from CloudSat, GOES‐13 and in situ aircraft Journal Articles uri icon

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  • This study aimed to assess tropical cloud properties predicted by Environment and Climate Change Canada's Global Environmental Multiscale (GEM) model when 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 16 May 2015 over French Guiana. Data from CloudSat'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.


  • Qu, Zhipeng
  • Barker, Howard
  • Korolev, Alexei V
  • Milbrandt, Jason A
  • Heckman, Ivan
  • Bélair, Stéphane
  • Leroyer, Sylvie
  • Vaillancourt, Paul A
  • Wolde, Mengistu
  • Schwarzenböck, Alfons
  • Leroy, Delphine
  • Strapp, J Walter
  • Cole, Jason NS
  • Nguyen, Louis
  • Heidinger, Andrew

publication date

  • July 2018