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GFS MOS Wind Guidance: Problem Solved?. Eric Engle and Kathryn Gilbert MDL/Statistical Modeling Branch 15 May 2012. Overview. Reason for Refresh Development Sample Predictand Definition Predictors and Equation Development Independent Test Systems Verification Impact on Gridded MOS.
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GFS MOS Wind Guidance: Problem Solved? Eric Engle and Kathryn Gilbert MDL/Statistical Modeling Branch 15 May 2012
Overview Reason for Refresh Development Sample Predictand Definition Predictors and Equation Development Independent Test Systems Verification Impact on Gridded MOS
Reason for Refresh • GFS Model “bugfix” implemented in May 2011 • Set new thermal roughness length to address a low level warm bias over land • Affected the behavior of the low level wind fields • Usually chosen as predictors (10-m u, v, speed)
GFS Vegetation Type Vegetation Type Description 7: Groundcover only (perennial) 8: Broadleaf shrubs with perennial groundcover 9: Broadleaf shrubs with bare soil 11: Bare soil • Roughness length change has most impact in these vegetation type areas. • Verifications show this is true (not shown) VEGETATION TYPES (DORMAN AND SELLERS, 1989; JAM)
Reason for Refresh • GFS Model “bugfix” implemented in May 2011 • Set new thermal roughness length to address a low level warm bias over land • Affected the behavior of the low level wind fields • Usually chosen as predictors (10-m u, v, speed) • Had a direct impact on GFS MOS wind speed guidance • Large guidance errors (strong positive biases) • Western CONUS (low vegetation/desert areas) • Most pronounced in warm season, during daytime hours
Implementation 32.2 knot error
2011 Jan-Apr 2009 2010 2011 May-July Credit: Dr. Yun Fan
Reason for Refresh • GFS Model “bugfix” implemented in May 2011 • Set new thermal roughness length to address a low level warm bias over land • Affected the behavior of the low level wind fields • Usually chosen as predictors (10-m u, v, speed) • Had a direct impact on GFS MOS wind speed guidance • Large forecast busts (strong positive biases) • Western CONUS (low vegetation/desert areas) • Most pronounced in warm season, during daytime hours • Complaints from NWS forecasters and private sector • GFS MOS wind guidance “unusable”
Responses from Users “Our workload has increased due to this problem” “…we continue to deal with serious fire weather conditions…” “The forecaster stated that this issue makes the point and gridded MOS…typically used to populate GFE…unusable and times.” “The situation with the MAV guidance winds has become a source of frustration and a workload issue for our office.”
Solutions Investigated • Turning off partial inflation (PI) • Many stations benefit from PI • Development without boundary layer model predictors • Many stations benefit from these • Bias correction • Big project…significant MOS production overhead • The solution…collect sufficient mixed sample and redevelop • Most timely
Development Sample • Balance the influence of “new” model data (version 9.0.1) with a sufficient sample size • 64% “new” / 36% “old” • Previous two warm seasons available • April through September, 2010 and 2011. • Comprised of three different versions of GFS model.
Predictand Definition • Predictands: • 10-m U-wind • 10-m V-wind • 10-m Wind Speed • Derived from hourly observed 10-m wind speed and direction • Wind data are quality controlled via MDL software • Regression equations for predictands are developed simultaneously • Predictors selected that best fit all 3 predictands • Different coefficient • 3-hourly guidance to 192-h • 6-hourly guidance from 204-h to 264-h
Predictors Offered • U, V, Speed at 1000, 925, 850, 700, and 500 hPa; and 10-m • Mass divergence, relative vorticity, vertical velocity at 925, 850, 700, and 500 hPa • Mean Layer RH 1000-850; 850-700 hPa; and 1-0.44 sigma • Temperature Difference between 1000-925, 1000-800, and 1000-700 hPa levels • K index • Sine and cosine DOY (harmonic functions) • PBL mixing parameter • Bilinear interpolation • Observed predictors offered out to 15-h (persistence)
Regression and Equation Development • Single station equation development • Multiple linear regression (forward selection) • Maximum number of predictors: 10 (no forcing) • 100 “cases” required equation to be developed • Three independent test systems were developed • Determine the best mix of “old” and “new” GFS model sample
Independent Test Systems • TEST1 • Only GFS v9.0.1 “new” used • July-Sept. 2010 (reforecast); May 10 – Sept. 2011 • TEST2 • Same as TEST1, but includes April 1 – May 9, 2011 (GFS v9.0.0) • TEST3 • All data from previous 2 warm seasons included • April-Sept. 2010 and 2011
Independent Testing • Cross-validation “leave one out” technique used • Each of the 3 test systems comprised of 8 equation sets • 7 out of 8 months of “new” GFS model data included in each equation set • Withheld month is used to verify the equation set in which it was held back. • End up with 8 fully independent months of guidance to verify against
Compare Equations for KPHX (24-h)00Z New (awaiting implementation) Operational (as of 5/14/2012)
Verification Summary • Verifications show TEST3 being the most accurate/skillful system • Attributethis to a longer sample • New equations have similar skill in wind direction guidance as the old equations • Guidance in Alaska degraded with test developments • Existing equations will remain in place
Summary • Change in GFS thermal roughness length • Negative impact on GFS MOS • Wind equations redeveloped using previous 2 warm seasons • Except for Alaska • Large wind speed guidance errors removed • Positive impact on Gridded MOS • Future work? • Bias correction • Redevelop again with longer sample • Implementation in June 2012
See the New Equations in Action… • http://www.mdl.nws.noaa.gov/~mos/mos/gfsmos_wind/index.php