FY13 Final GIMPAP Progress Report
Reporting Period: February 2014—June 2014 (2nd half of second year funding cycle)
1. Project Title: WRF Cloud and Moisture Verification with GOES
2. PIs: Dan Lindsey (STAR/RAMMB) and Louie Grasso (CIRA)
3. Participants: Bob Rabin (NSSL), Jack Kain (NSSL), Steve Weiss (SPC), Curtis
Seaman (CIRA)
4. Brief Project Summary: The purpose of this project is to leverage CIRA’s ability to
generate synthetic satellite imagery using output from the 4-km NSSL WRF model to
valid cloud and moisture forecasts from the NSSL with observed GOES data.
Quantitative validation statistics will be provided to the model developers, who will then
use this information to make future model improvements.
5. FY13 Milestones

Compute validation statistics for the 1+ years of archived data and provide the results
to NSSL

Explore object-based verification

Begin working toward a real-time verification system

Compute validation statistics for the fog forecasts using METARS from the select
airport locations

Prepare a publication to a peer-reviewed journal
6. Progress toward FY13 Milestones

Compute validation statistics for the 1+ years of archived data and provide the results
to NSSL
Since this is the final report, our main findings will be discussed. One of our first
findings was that synthetic GOES-13 imagery at 10.7 µm of the 4 km NSSL WRFARW with the WSM6 micropyhysics contained thunderstorm tops that were too
small and too warm compared to observed GOES-13 imagery at 10.7 µm (see Figure
1).
1
Figure 1: (a) Observed and (b) synthetic GOES-13 imagery at 10.7 µm valid at 0300
UTC on 6 Julyl 2013. Histograms of observed (solid contour) and synthetic (dotted
contour) brightness temperatures corresponding to the images over (c) all brightness
temperatures and (d) zoomed in the denoted box for brightness temperatures between
190 K and 250 K. The synthetic image is based on a 27 hour forecast from the 4 km
NSSL WRF-ARW.
In order to ensure that this bias is consistent at other times, histograms were created
using all forecasts from July 2011 to September 2012 (see Figure 2). As indicated in
Figure 2, there are more cold pixels (200 – 230 K) in the observed imagery compared
to those in the synthetic imagery, confirming a warm bias in the NSSL WRF-ARW
with the WSM6 microphysics.
2
Figure 2: Similar to the histograms in Figure 1, except for all 9- to 36-hour forecast images
from July 2011 to September 2012.
Following up on this potentially important finding, the PIs worked with Kyo-Sun Lim
(Pacific Northwest National Laboratory), Scott Dembek (CIMMS), and Adam Clark
(NSSL) to test changes to the WSM6 microphysics. Many sensitivity test suggested
that the conversion of ice to snow (PSACI) was too aggressive. As a result,
precipitation settling of snow transferred solid water mass out of the anvil top. A final
test was conducted in which the conversion of ice to snow was reduced BY 50 % (see
Figure 3). Histograms from these two simulations also indicate an improvement (See
Figure 4).
See below for publication details.
3
Figure 3: Synthetic GOES-13 image at 10.7 µm valid 00Z 26 July 2013 for (a) a
100% PSACI simulation and (b) a new run with 50% PSACI.
4
Figure 4: Histograms of the synthetic GOES-13 images shown in Figure 3 and
observed GOES-13. Observed data is indicated by a solid black contour; the dotted
black contour represents data from the original simulation while the red dotted
contour represent data from the new simulation. In (a) brightness temperatures from
160 K to 320 K is shown while in (b) brightness temperatures between 190 K and 250
K are displayed.

Explore object-based verification
Object-based verification was explored, but it was determined that it is beyond the
scope of this project. If EMC or other operational modeling groups decide that this
type of verification would be beneficial, then this could be a future project (assuming
funding could be secured.)

Begin working toward a real-time verification system
After getting increasingly involved in this project, we have concluded that a real-time
verification system will not benefit forecasters as much as simply viewing the
synthetic imagery side-by-side with the corresponding observed imagery (up to the
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current time), and qualitatively noting areas in which the model has
correctly/incorrectly placed the clouds, short waves, jet streaks, etc. A real-time
verification system would provide large-scale statistics such as a domain average root
mean square error, but knowing the areas in which the model is more on track is far
more beneficial.

Compute validation statistics for the fog forecasts using METARS from the select
airport locations
Some validation statistics have been computed, but this portion of the project is not
completed sufficiently to report those results. Given that this milestone was added to
the project long after the project was first approved for funding, we will continue to
work on this (unfunded) and may eventually write a paper on the results.

Prepare a publication to a peer-reviewed journal
As noted below, a paper has been written, submitted, accepted, and is currently in
press.
7. Real-Time Demonstrations and User Feedback (if applicable)
The nature of this validation project does not make it applicable for real-time
demonstrations.
8. Operational Transition Plans (if applicable)
This is also not applicable.
9. Publications and Presentations
Grasso, L., 2014: Evaluation of and Suggested Improvements to the WSM6 Microphysics
in WRF-ARW Using Synthetic and Observed GOES-13 Imagery. Oral presentation
delivered at the 4th Hazardous Weather Workshop, 1-3 April 2014, Norman, OK.
Grasso, L., D. T. Lindsey, K-S Lim, A. Clark, S. Dembek, and Dan Bikos, 2014:
Evaluation of and Suggested Improvements to the WSM6 Microphysics in WRF-ARW
Using Synthetic and Observed GOES-13 Imagery. Mon. Wea. Rev. In Press.
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