The Evolution and Evaluation of CIMSS’ AWIPS-related efforts since May 2008

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The Evolution and Evaluation of CIMSS’ AWIPS- related efforts since May 2008 Jordan Gerth In coordination with Scott Bachmeier Wayne Feltz Tim Schmit and others 1

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The Evolution and Evaluation of CIMSS’ AWIPS-related efforts since May 2008. Jordan Gerth In coordination with Scott Bachmeier Wayne Feltz Tim Schmit and others. Involved Weather Forecast Offices. - PowerPoint PPT Presentation

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The Evolution and Evaluation of CIMSS AWIPS-related effortssince May 2008Jordan Gerth

In coordination withScott BachmeierWayne FeltzTim Schmitand others1

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SMGAberdeen, South Dakota (ABR)Amarillo, Texas (AMA)Boulder, Colorado (BOU)Dallas/Fort Worth, Texas (FWD)Davenport, Iowa (DVN)Des Moines, Iowa (DMX)Duluth, Minnesota (DLH)El Paso, Texas (EPZ)Glasgow, Montana (GGW)Indianapolis, Indiana (IND)Kansas City, Missouri (EAX) Midland, Texas (MAF)Minneapolis, Minnesota (MPX)Norman, Oklahoma (OUN)Pendleton, Oregon (PDT)Reno, Nevada (REV)Riverton, Wyoming (RIW)Springfield, Missouri (SGF)Tulsa, Oklahoma (TSA)Spaceflight Meteorology GroupMilwaukee, Wisconsin (MKX)Billings, Montana (BYZ)Chicago, Illinois (LOT)Green Bay, Wisconsin (GRB)La Crosse, Wisconsin (ARX)Las Vegas, Nevada (VEF)Marquette, Michigan (MQT)Northern Indiana (IWX)Spokane, Washington (OTX)Wichita, Kansas (ICT)Kansas City, Missouri (CRH)Fort Worth, Texas (SRH)Salt Lake City, Utah (WRH)Involved Weather Forecast OfficesDistribution Node25 MODIS AFDs Issued1 AFD IssuedReceive MODIS Imagery

in AWIPS31920

Last updated on Jan 20, 200933TOTAL2

Boulder, Colorado (BOU)Fargo, North Dakota (FGF)Indianapolis, Indiana (IND)Kansas City, Missouri (EAX)La Crosse, Wisconsin (ARX)Nashville, Tennessee (OHX)Rapid City, South Dakota (UNR)Springfield, Missouri (SGF)Milwaukee, Wisconsin (MKX)Aberdeen, South Dakota (ABR)Burlington, Vermont (BTV)Minneapolis, Minnesota (MPX) Northern Indiana (IWX)Riverton, Wyoming (RIW)Bohemia, New York (ERH)Fort Worth, Texas (SRH)Kansas City, Missouri (CRH)Salt Lake City, Utah (WRH)Involved Weather Forecast OfficesDistribution Node50 CRAS AFDs Issued1 AFD IssuedReceive CRAS Imageryin AWIPS4167

Last updated on Jan 20, 200918TOTAL

Introduction of GRIB2fields in August 20083

4None so far this May

527 January 2009 at CIMSS with theme Catering to the satellite needs of operational meteorology17 February 2009 at NWS WFO MKX with theme Building on a collaborative foundation for success in operational satellite meteorologySurvey conducted to assess presentations and content based on applicability and pertinence to the field of operational meteorology (1, not applicable; 5, immediately applicable):GOES-R Proving Ground and Overview of Simulated ABI Datasets: 4.4A primer on the use of the current GOES Sounder: 3.4Using GOES Sounder products to improve regional NWP: 4.4 (CRAS), 4.0 (Nearcasting)Providing Research Satellite Products to NWS Operations: 4.7Convective Initiation and Aviation Applications to Forecasting: 4.0Overall, including organization and subject matter: 4.7Meetings with NWS WFO MKX6CIMSS Regional Assimilation System

CRAS is unique in that, since 1996, its development was guided by validating forecasts using information from GOES.CRASThe Cooperative Institute for Meteorological Satellite Studies (CIMSS) uses the CIMSS Regional Assimilation System (CRAS) to assess the impact of space-based observations on numerical forecast accuracy.Slide credit: Robert Aune, NOAA/NESDIS7

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http://cimss.ssec.wisc.edu/cras/NOAA Collaborator: Robert Aune

Web Transitioning

10Sky Cover Prediction

Pre-release commentary from National Weather Service Science Operations Officers:

[The] field really does need something to help with the sky grids.

Obviously great potential for (the) NDFD!11Sky Cover Prediction

The Problem:What is 100% sky cover? Both celestial domes are completely covered with cloud. Do we use an incoming light standard? If so, what do we do at night?Photos courtesy of National Weather Service Southern Region Headquarters

12The most recent advances in numerical weather prediction have come with the advent and widespread distribution to the Weather Research and Forecast (WRF) model to both the field and academia. The WRF has two dynamical cores, one with customizable physics, and a 3-dimensional variational (3DVAR) assimilation system. The goal is flexibility.Concurrently, increases in personal computer capabilities and innovations in parallel processing have led to a realistic ability to run regional simulations on increasingly high-resolution mesoscale spatial and temporal grids with relative ease.An effort is underway to create initial conditions for the WRF using data from the GOES Sounder in a satellite-focused real-time mesoscale analysis system. WRF domains could then be provided boundary conditions from the CRAS to extend the analysis of satellite data in numerical weather predictions.Transitioning to the WRF

13Specific Objective:Expand the benefits of valuable moisture Information contained in GOES Sounder Derived Product Images (DPI)GOES Sounder products images already are available to forecasters. Products currently available include: - Total column Precipitable Water (TPW) - Stability Indices (LI, CAPE) - 3-layers Precipitable Water (PW) . . . Build upon GOES Strengths: + Derived Product Images (DPI) of soundings speeds comprehension of information + Data improves upon model first guess

HOWEVER, some operational realities exist: - DPIs used primarily as observations - No predictive component - 3-layer DPIs not used in current NWP models - Products often obscured when needed most - Cloud development/expansion obscures IR observations

Improvement of GOES DPI over NWP guessNeed to add a DPI predictive capability toclose these information gaps

10 Feb 2009, 1700 UTC 900-700 hPa GOES PW 6-Hr nearcastSlide credit: Robert Aune, NOAA/NESDIS14

http://cimss.ssec.wisc.edu/model/nrc/NOAA Collaborator: Robert AuneCIMSS Collaborator: Ralph Peterson15

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Common AWIPS Visualization Environment (CAVE)

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22Questions or [email protected]1231122025271126814941324612315538538415134471123510161741511232574115510628213381111162756113811000

CRASMODISCombinedMonthNumber of AFDsCRAS and MODIS in Area Forecast Discussions at NWS Forecast Offices through 5/10/2009

Chart21665114522131211311

CRAS and MODIS in Area Forecast Discussions by NWS Forecast Offices through 2/28/2009

Chart3975004100000011300

CRAS in Area Forecast Discussions by NWS Forecast Offices through 2/28/2009

Chart4690110422131200011

MODIS in Area Forecast Discussions by NWS Forecast Offices through 2/28/2009

Chart50781516172022243133476066818997102106117122123130135137142153163171174185212223234234

0MonthCumulative Total Number of AFDsCRAS and MODIS in Area Forecast Discussions at NWS Forecast Offices through 5/10/2009

Sheet1National Weather Service Usage StatisticsCRASMODISTotalPositionRankOfficeCRASMODISTotalKapela303WCMMKXMKX9769166Craven325SOOMKXRIW505Zajdel-Y19019LeadMKXARX011Hentz313061LeadMOSTMKXICT011S.Davis224LeadMKXABR404Kavinsky131427LeadMKXIWX145McMahon15520LeadMKXLOT022Kochis-Y202GeneralMKXGRB022Collar303GeneralMKXOTX011Gehring314LeadMKXMQT033Wood134GeneralMKXVEF011Borghoff033InternMKXBYZ022Unknown101T-LEASTMKXBTV101Meunier101LeadT-LEASTRIWEAX101Skrbac202LeadRIWMPX303Smith101GeneralT-LEASTRIWREV011Baumgardt011SOOT-LEASTARXBUF011Cox011LeadT-LEASTICTTotal11288200Fowle-X2810SOOABRJJG 2/8/2009Tarver303GeneralABRMurphy033UnknownIWXChamberlain101UnknownT-LEASTIWXRatzer022UnknownLOTKurimski011GeneralT-LEASTGRBSkowronski011LeadT-LEASTGRBFox011UnknownT-LEASTOTXGuenther022GeneralMQTAlumbaugh011GeneralT-LEASTMQTRunk011MICT-LEASTVEFRichmond022UnknownBYZGoff101GeneralT-LEASTBTVLipson101GeneralT-LEASTRIWDux101GeneralT-LEASTEAXEffertz303GeneralMPXJordan011GeneralT-LEASTREVLudington011UnknownT-LEASTIWXCronce011GeneralT-LEASTMKXHitchcock011GeneralT-LEASTBUFTotal11288200JJG 2/8/2009X - Previously Journey at MKXYellow designates highest scoreY - Now Resigned or RetiredNumber in each column represents the number of Area Forecast Discussions which match the headerCRASMODISTotalSeasonRankTotalRunningJul-060Summer0Aug-06257Summer77Sep-06101FallT-LEAST8Oct-06527Fall15Nov-06101FallT-LEAST916Dec-06011WinterT-LEAST17Jan-07123Winter20Feb-07112Winter622Mar-07202Spring24Apr-07527Spring31May-07112Spring1133Jun-076814Summer47Jul-079413Summer60Aug-07246Summer3366Sep-0712315Fall81Oct-07538Fall89Nov-07538Fall3197Dec-07415Winter102Jan-08134Winter106Feb-084711Winter20117Mar-08235Spring122Apr-08101SpringT-LEAST123May-08617Spring13130Jun-08415Summer135Jul-08112Summer137Aug-08325Summer12142Sep-087411Fall153Oct-085510Fall163Nov-08628Fall29171Dec-08213Winter174Jan-093811Winter185Feb-09111627WinterMOST41212Mar-095611Spring223Apr-093811Spring234May-09000Spring22234Total126108234JJG 5/10/2009Number in each column represents the number of Area Forecast Discussions which match the header

Sheet2

Chart1388990388992571015271010111231122025271126814941324612315538538415134471123510161741511232574115510628213381111162756113811000

CRASMODISCombinedMonthNumber of AFDsCRAS and MODIS in Area Forecast Discussions at NWS Forecast Offices through 5/10/2009

Chart21665114522131211311

CRAS and MODIS in Area Forecast Discussions by NWS Forecast Offices through 2/28/2009

Chart3975004100000011300

CRAS in Area Forecast Discussions by NWS Forecast Offices through 2/28/2009

Chart4690110422131200011

MODIS in Area Forecast Discussions by NWS Forecast Offices through 2/28/2009

Chart50781516172022243133476066818997102106117122123130135137142153163171174185212223234234

0MonthCumulative Total Number of AFDsCRAS and MODIS in Area Forecast Discussions at NWS Forecast Offices through 5/10/2009

Sheet1National Weather Service Usage StatisticsCRASMODISTotalPositionRankOfficeCRASMODISTotalKapela303WCMMKXMKX9769166Craven325SOOMKXRIW505Zajdel-Y19019LeadMKXARX011Hentz313061LeadMOSTMKXICT011S.Davis224LeadMKXABR404Kavinsky131427LeadMKXIWX145McMahon15520LeadMKXLOT022Kochis-Y202GeneralMKXGRB022Collar303GeneralMKXOTX011Gehring314LeadMKXMQT033Wood134GeneralMKXVEF011Borghoff033InternMKXBYZ022Unknown101T-LEASTMKXBTV101Meunier101LeadT-LEASTRIWEAX101Skrbac202LeadRIWMPX303Smith101GeneralT-LEASTRIWREV011Baumgardt011SOOT-LEASTARXBUF011Cox011LeadT-LEASTICTTotal11288200Fowle-X2810SOOABRJJG 2/8/2009Tarver303GeneralABRMurphy033UnknownIWXChamberlain101UnknownT-LEASTIWXRatzer022UnknownLOTKurimski011GeneralT-LEASTGRBSkowronski011LeadT-LEASTGRBFox011UnknownT-LEASTOTXGuenther022GeneralMQTAlumbaugh011GeneralT-LEASTMQTRunk011MICT-LEASTVEFRichmond022UnknownBYZGoff101GeneralT-LEASTBTVLipson101GeneralT-LEASTRIWDux101GeneralT-LEASTEAXEffertz303GeneralMPXJordan011GeneralT-LEASTREVLudington011UnknownT-LEASTIWXCronce011GeneralT-LEASTMKXHitchcock011GeneralT-LEASTBUFTotal11288200JJG 2/8/2009X - Previously Journey at MKXYellow designates highest scoreY - Now Resigned or RetiredNumber in each column represents the number of Area Forecast Discussions which match the headerCRASMODISTotalSeasonRankTotalRunningJul-060Summer0Aug-06257Summer77Sep-06101FallT-LEAST8Oct-06527Fall15Nov-06101FallT-LEAST916Dec-06011WinterT-LEAST17Jan-07123Winter20Feb-07112Winter622Mar-07202Spring24Apr-07527Spring31May-07112Spring1133Jun-076814Summer47Jul-079413Summer60Aug-07246Summer3366Sep-0712315Fall81Oct-07538Fall89Nov-07538Fall3197Dec-07415Winter102Jan-08134Winter106Feb-084711Winter20117Mar-08235Spring122Apr-08101SpringT-LEAST123May-08617Spring13130Jun-08415Summer135Jul-08112Summer137Aug-08325Summer12142Sep-087411Fall153Oct-085510Fall163Nov-08628Fall29171Dec-08213Winter174Jan-093811Winter185Feb-09111627WinterMOST41212Mar-095611Spring223Apr-093811Spring234May-09000Spring22234Total126108234JJG 5/10/2009Number in each column represents the number of Area Forecast Discussions which match the header

Sheet2

Chart10.26086956520.85454545450.0809523810.2608695652

900-700 hPa700-300 hPaVertical Layer% Reduction with GOES-12TPW NWP Guess Error Reduction using GOES-12

Sheet1BIAS(mm)SD(mm)AVGY(mm)TPW,G120.483.6822.76GS wrt RB,OPS 5x5-0.753.2222.76RT wrt RB,OPS 5x5G120.343.6120.71GS wrt RB,CMS 3x3-0.433.1320.71RT wrt RB,CMS 3x3TPW,G10-0.843.6516.14GS wrt RB,OPS 5x5-1.043.4616.14RT wrt RB,OPS 5x5G10-0.323.4413.75GS wrt RB,CMS 3x30.232.8113.75RT wrt RB,CMS 3x3WV1,G12-0.691.468.83GS wrt RB,OPS 5x5-0.641.58.83RT wrt RB,OPS 5x5G12-0.71.458.1GS wrt RB,CMS 3x3-0.691.418.1RT wrt RB,CMS 3x3WV1,G10-1.581.75.95GS wrt RB,OPS 5x5-0.741.535.95RT wrt RB,OPS 5x5G10-1.081.424.8GS wrt RB,CMS 3x3-0.631.314.8RT wrt RB,CMS 3x3WV2,G120.52.110.03GS wrt RB,OPS 5x50.211.9710.03RT wrt RB,OPS 5x5G120.462.19.05GS wrt RB,CMS 3x30.341.939.05RT wrt RB,CMS 3x3WV2,G100.292.16.97GS wrt RB,OPS 5x50.132.176.97RT wrt RB,OPS 5x5G100.281.896.09GS wrt RB,CMS 3x30.491.736.09RT wrt RB,CMS 3x3WV3,G120.641.453.84GS wrt RB,OPS 5x5-0.331.113.84RT wrt RB,OPS 5x5G120.551.383.51GS wrt RB,CMS 3x3-0.081.023.51RT wrt RB,CMS 3x3WV3,G100.441.263.18GS wrt RB,OPS 5x5-0.441.093.18RT wrt RB,OPS 5x5G100.461.182.82GS wrt RB,CMS 3x30.370.952.82RT wrt RB,CMS 3x3Geos 12 - Eastern USError reductions900-700 hPaG125.08%23.20%9.05GS wrt RB,CMS 3x33.76%21.33%9.05RT wrt RB,CMS 3x326.09%8.10%700-300 hPaG1215.67%39.32%3.51GS wrt RB,CMS 3x3-2.28%29.06%3.51RT wrt RB,CMS 3x385.45%26.09%

Sheet1000000

Raob-GuessGEOS12-RaobStatisticPercipitable WaterMid-Level (900-700 hPa) DPI fits

Sheet2000000

Raob-GuessGEOS12-RaobStatisticPercipitable WaterHigh-Level (700-300 hPa) DPI fits

Sheet30000

900-700 hPa700-300 hPaVertical Layer% Reduction with GOES-12TPW Error Reduction u sing GOES-12

0000

Raob-GuessGEOS12-RaobStatisticPercipitable WaterHigh-Level (700-300 hPa) DPI fits

0000

Raob-GuessGEOS12-RaobStatisticPercipitable WaterMid-Level (900-700 hPa) DPI fits