Presentation is loading. Please wait.

Presentation is loading. Please wait.

PREPOP Meeting Wednesday, March 23, 2011 10 AM – NOON Room 602 WWB 1.

Similar presentations


Presentation on theme: "PREPOP Meeting Wednesday, March 23, 2011 10 AM – NOON Room 602 WWB 1."— Presentation transcript:

1 PREPOP Meeting Wednesday, March 23, AM – NOON Room 602 WWB 1

2 Agenda 1.Operational Product Status Updates (15 min) a.Hydro-Estimator precipitation products (Kuligowski/Zhao) b.MSPPS/MIRS precipitation products (Zhao/Ferraro/Boukabara) c.Blended TPW products (Zhao/Kidder/Paquette) d.eTRaP (Seybold/Kidder) e.GOES histogram precip product (Schreitz/Xie) 2.Developmental Project Updates (15 min) a.MSPPS snowfall rate (Ferraro/Meng/Zhao) b.MIRS NPP rainfall rate (Boukabara/Iturbide/Zhao) c.eTRaP enhancements (Ma/Kuligowski/Kidder) d.Soil Moisture Products System (Zhan/Zhao) e.POES-GOES-GPS Blended TPW and RR (Zhao/Kidder/Ferraro) f.Satellite Cal/Val efforts for Rainfall Estimates and POES-AMSU Monitoring (Janowiak) g.New satellite data products for TV broadcast market (Ferraro) h.SCaMPR improvements (Kuligowski) 3.Discuss Inactive Projects and Pending PREPOP Projects (All; 5 min) 4.Special Discussion (60 min) a.Impact of MSPPS changes in response to AMSU-B band issues (Zhao/Janowiak; 20 min) b.MIRS Rainfall Rate recalibration (Iturbide-Sanchez; 20 min) c.SMOPS (Zhan; 20 min) 5.New Business (All; 10 min) 6.Review of Action Items (All; 5 min) 7.Adjourn 2

3 a. Operational Hydro-Estimator Update (Zhao/Kuligowski) Operational Global HE User Request (SPSRB ): – SPIWG reviewed NWS user request and requested written assurance of NWS funding support; waiting on signed letter from NWS Multi-Day HE Total Request (SPSRB ) – SPIWG tasked Zhao and Kuligowski to determine if this falls under the OSPO Change Management process ESPC CM Repository – Source code for the HE and SPE have been verified and put in the repository. 3

4 b. MSPPS/MIRS Rainfall Products (1/2) (Zhao / Ferraro / Meng / Boukabara) Upcoming Operational Products – F18 MIRS DAP was received from STAR in June 2010, but its operational implementation is pending IT readiness at OSPO – pending for the new Diamond with the capacity to run MIRS with high resolution, which is now targeted in the June 2011 time frame. – The updated and improved snowfall rate algorithm was received from Huan, but its operational implementation is delayed due to the OSPO IT freeze – the task will be put in the queue to compete for Contractor support resources after the freeze is lifted in April Tailored Products – A netCDF-to-HDF-EOS encoder has been developed and available to users Products Anomaly – No changes for N19, N15 anomalies. – The NOAA-16 AMSU-B channel-18, -19 and -20 are gradually getting very noisy as the instrument is aging. The RR product generation should be evaluated, and might need to be stopped in near future if no alternative works. – NOAA-18 “reduced gyro test” will be conducted on March 23-24, 2011; a geo-location error of km is expected. 4

5 Impacts of ESPC Contractor Transition and IT Freeze – The IT freeze is delaying the readiness of the new operational machine, which consequently impacts the progress to upgrade MIRS to run at the high resolution (at MHS FOVs). – The IT freeze is delaying the implementation of the updated snowfall algorithm. b. MSPPS/MIRS Rainfall Products (2/2) (Zhao / Ferraro / Meng / Boukabara) 5

6 c. Updates on the Operational bTPW Products (1/3) (Zhao / Kidder / Ferraro) Operational Anomalies –No GOES data were being filled in over the outback of Mexico, while no GPS was available. Changes were made in the GOES TPW reader to allow the GOES TPW data be ingested into the system correctly. –A bug was discovered in the GPS TPW analysis, which produced problematic TPW gridded analysis, especially while there are only a few GPS receiver stations. The problem has been fixed and implemented in operations, together with a new GPS station file. BeforeAfter BeforeAfter 6

7 c. Updates on the Operational bTPW Products (2/3) (Zhao / Kidder / Ferraro) Operational Anomalies (cont) – GPS data dropouts have been observed more frequently during the past couple of months Added the option to pick the data file with maximum stations between NOAAPort and FSL ftp site Increased re-visit and also reduced the time latency from 30 min to 60 min when no data are available from the latest hour. – Surface pressure was observed not correct in the GOES West TPW data file – problem reported and fixed. Status of Archive – The archive request is still pending for its final approval at NCDC/CLASS. – The backlog data files will have to be deleted due to the space limits at ESPC if the archive can not be started in two or three months. – Archive assessment for the blended RR product has been provided to NCDC, and also an archive initiation was send to NCDC following the newly developed SPSRB archive guidance. 7

8 Impacts of ESPC Contractor Transition and IT Freeze – The ESPC Contractor Transition put marginal impact on the project schedule. – The ESPC IT freeze is expected to be lift as scheduled on April, 2011, which will allow the transition of the TPW enhancement and blended RR products to start, it will have to compete with all other tasks for Contractor resources. Blended TPW products tailored for TV broadcasters – Set-up the routine support to transfer data for WorldWinds. c. Updates on the Operational bTPW Products (3/3) (Zhao / Kidder / Ferraro) 8

9 d. eTRaP Ma / Seybold / Kuligowski / Kidder (SPSRB ) Liqun Ma replaced Matt Seybold as OSPO Tropical PAL User survey by Mike Turk (SAB); key findings: – Broad awareness of product – Greatest benefit to operations in Eastern / Southern Hemispheres – Equally divided on point vs. area probabilities B. Ebert proposed both (gridded point values overlaid with contourd area values); discussion ongoing 9

10 e. GOES histogram precip product (Schreitz / Xie) Quarterly Critical Infrastructure Protection (CIP) testing was successfully completed. 10

11 Agenda 1.Operational Product Status Updates (15 min) a.Hydro-Estimator precipitation products (Kuligowski/Zhao) b.MSPPS/MIRS precipitation products (Zhao/Ferraro/Boukabara) c.Blended TPW products (Zhao/Kidder/Paquette) d.eTRaP (Seybold/Kidder) e.GOES histogram precip product (Schreitz/Xie) 2.Developmental Project Updates (15 min) a.MSPPS snowfall rate (Ferraro/Meng/Zhao) b.MIRS NPP rainfall rate (Boukabara/Iturbide/Zhao) c.eTRaP enhancements (Ma/Kuligowski/Kidder) d.Soil Moisture Products System (Zhan/Zhao) e.POES-GOES-GPS Blended TPW and RR(Zhao/Kidder/Ferraro) f.Satellite Cal/Val efforts for Rainfall Estimates and POES-AMSU Monitoring (Janowiak) g.New satellite data products for TV broadcast market (Ferraro) h.SCaMPR improvements (Kuligowski) 3.Discuss Inactive Projects and Pending PREPOP Projects (All; 5 min) 4.Special Discussion (60 min) a.Impact of MSPPS changes in response to AMSU-B band issues (Zhao/Janowiak; 20 min) b.MIRS Rainfall Rate recalibration (Iturbide-Sanchez; 20 min) c.SMOPS (Zhan; 20 min) 5.New Business (All; 10 min) 6.Review of Action Items (All; 5 min) 7.Adjourn 11

12 12 Active PREPOP R2O Projects SPSRB # Product End User POC NESDIS LeadCurrent Phase Status (G/Y/R) Issue(s)Funding POES/AMSU Rain Rate (SSMIS and NPP rain rates from MIRS only—not part of SPSRB request, but for supporting continuity of operations). MSPPS snowfall rate – extending AMSU RR to solid precipitation. Xie, Heil (NWS); Kusselson (SAB); Wang (FNMOC ) MSPPS: Ferraro (STAR), Zhao (OSPO) MIRS: Boukabara (STAR), Zhao (OSPO), Meng (STAR) Operational (Development for MSPPS snowfall rate / NPP ATMS RR, TPW, CLS) G MSPPS snowfall rate submitted but IT freeze delays its operational implementation. The implementation of full-resolution MIRS F18 retrievals is still pending IT capacity. P-PSDI and OSPO base; NDE (SSMIS and NPP only) POES/AMSU TPW (also SSMIS and NPP TPW from MIRS only) Operational (Development for NPP RR) G POES/AMSU CLW (also SSMIS and NPP TPW from MIRS only) Operational (Development for NPP RR) G Operational Implementation of an Ensemble Tropical Rainfall Potential (eTRaP) [justification under TRaP for HPC/TPC/CPHC/CPC] Kusselson (SAB) Seybold (OSPO), Kuligowski (STAR), Kidder (CIRA) Operational (eTRaP); Development (upgrades) Y OSPO IT freeze delaying operational implementation; development delays. P-PSDI 12

13 13 Active PREPOP R2O Projects SPSRB # Product End User POC NESDIS LeadCurrent Phase Status (G/Y/R) Issue(s)Funding Soil Moisture Products SystemEk, Xie (NWS) Zhan (STAR) Zhao (OSPO) Development G OSPO IT freeze might have impact on its final operational implementation. P-PSDI POES-GOES-GPS Blended Hydrometeorological Products [TPW and RR] Schrab (NWS) Zhao, Paquette, Kidder (CIRA), Ferraro (STAR) Operational (TPW) Development (RR) Y OSPO IT freeze delays the project schedule and operational implementation. G-PSDI / 0005/ 0006/ 0007 Megha-Tropiques Data and Products Ferraro (STAR); Zhao (OSPO) Development G Plan modified due to launch delay. P-PSDI Multi-day (more than 24hrs) NESDIS Hydro-Estimator Rain Estimates Eckert (NWS) Kuligowski (STAR); Zhao (OSPO) Development G After OSPO IT freeze is lifted OSPO base 13

14 a. MSPPS Snowfall Rate Meng / Yan / Ferraro / Zhao (SPSRB /6) Project Overview – The project will develop an operational surface snowfall rate algorithm using passive microwave data from AMSU/MHS. Recent Accomplishments – Limited case studies Next Steps – Algorithm validation 14

15 MIRS NPP Rain Rate Boukabara / Iturbide / Zhao (SPSRB /6) Project Overview – Adaptation of MiRS to NPOESS Preparatory Project (NPP) ATMS and integration within NPOESS Data Exploitation (NDE). Recent Accomplishments – Developed a netCDF-to-HDF-EOS encoder – Provided the NDE team the algo description for the MIRS Level-3 mapped products. – Analyzed the impact of a Hydrometeor Background Covariance Matrix based on WRF simulations Next Steps – Preparing the detailed documentation for the MIRS Level-3 products – Analyze new strategies to improve the quality of the MiRS rainfall rate. 15

16 c. eTRaP Enhancements Ma / Seybold / Kuligowski / Kidder (SPSRB ) Project Overview – Improve the eTRaP product by calibrating probabilities against observations to remove bias determining the optimal product format (point vs. area probabilities) adding new ensemble members (H-E, SSMIS, R-CLIPER) adding enhancements (shear, topography, storm rotation) Recent Accomplishments – Delays in getting the project started; agreed to schedule regular conference calls to track progress Next Steps – Finish and implement probability calibration – Incorporate H-E and SSMIS data into ensemble 16

17 d. Soil Moisture Products System Zhan / Zhao (SPSRB ) (To be covered in Special Discussion) 17

18 e. POES-GOES-GPS Blended TPW Zhao / Kidder / Ferraro (SPSRB ) Project Overview – To develop an enhanced Blended TPW product which Includes SSMIS TPW and MIRS TPW Has a higher resolution (8 km vs 16km for the current operational bTPW) Uses an enhanced blending technique to fully utilize the capabilities of GOES PW, MIRS TPW, and GPS TPW Recent Accomplishments – Added MIRS TPW over land and water – Added SSMIS TPW – Improved handling of GPS TPW – Filtering of “eyeball” problem; Fixed Barnes analysis bug; Added land mask capability; Updated GPS station list – Developed an enhanced blending algorithm to fully utilize the strength of each dataset, including AMSU, SSMIS, GPS and GOES TPWs – Experimental products have been developed and runs hourly at CIRA: - Blended TPW with SSMIS and MIRS TPW over land - Blended TPW with the enhanced merging algorithm Next Steps – Continue working on the fine tune of the new merging algorithm – Operational implementation of the enhanced TPW products after the OSPO IT freeze is lift – Investigating some apparently anomalous behavior of over-land MIRS TPW (conference call scheduled 31 March) – Reworking scripting code to allow script-level control of Blending algorithm Data sources 18

19 e. POES-GOES-GPS Blended RR Zhao / Kidder / Ferraro (SPSRB ) Project Overview – To develop a blended Rain Rate product for NWS forecasters Recent Accomplishments – The blended RR product from MSPPS, MIRS, and FNMOC SSMIS are generated and made available for evaluation on Internet – Worked with John Janowiak for validation – Upgraded the histogram correction with options to allow different corrections over land and ocean choose any satellite as the reference satellite, including DMSP F13 specify the “strength” of correction as none, light, and strong – The product has been developed and runs hourly at CIRA (http://cat.cira.colostate.edu)http://cat.cira.colostate.edu – Provided archive assessment for the blended RR product to NCDC, and submitted an archive initiation following the newly developed SPSRB archive guidance. Next Steps – A delta CDR for the blended RR, which is delayed due the Contractor transition, and is planning to be completed by April, – Operational implementation of the blended RR products 19

20 20 Active PREPOP Development Projects ProductKey CapabilitiesEnd User POCNESDIS LeadIssue(s)Funding Satellite Cal / Val Efforts for Rainfall Estimates and POES-AMSU Monitoring Develop real-time STAR precipitation product validation Kuligowski and Zhao; PREPOP John Janowiak (STAR/CORP) None.STAR Cal/Val funds New Satellite Data Products for TV Broadcast Market (Phase I) Port “emerging” NESDIS satellite products to TV broadcast community Dave Gilhousen (WorldWinds), Dan Gallagher (Baron) Ralph Ferraro (STAR) None.NOAA SBIR SCaMPR Improvements Add TRMM data, visible data, moisture correction Kuligowski (STAR)Contractor support ended; implementation is now “out of hide”. Working to incorporate MWCOMB into real-time version, followed by adaptation of GOES-R version (with current Imager bands) in summer to support the GOES-R Proving Ground. None

21 f. Satellite Cal/Val efforts for Rainfall Estimates and POES-AMSU Monitoring Janowiak Project Overview – Provide routine and (as requested) case-study validation of MW-based rain rate products Recent Accomplishments – Added SON 2010 validation to Web page at – Evaluated impact of AMSU-B band issues on MSPPS changes (see upcoming presentation) Next Steps – Continue routine validation and case study validation as requested 21

22 g. New Satellite Data Products for TV Broadcast Market Ferraro Project Overview – Funded through NOAA’s FY10 SBIR Program – Develop prototype method to deliver new NOAA satellite products to TV broadcasters Recent Accomplishments – Phase I project completed Dec 31, 2010 – Blended TPW delivered through Baron Systems package Was used by three west coast markets on the air during December heavy precipitation event! – Both WorldWinds and Baron great to work with. Next Steps – Phase II proposal submitted by WorldWinds Inc. Enhanced product list – Reviews due April – They will brief NOAA SBIR in May 22

23 h. SCaMPR Improvements Kuligowski Project Overview – Improve the SCaMPR algorithm by incorporating TRMM data (short-term) and implementing the GOES-R version (medium-term) Recent Accomplishments – Evaluating the impact of the TRMM data and working on a journal article – Working on a real-time version of SCaMPR that will use MWCOMB as the MW input Next Steps – Finalize parallel real-time runs of MWCOMB SCaMPR – Implement real-time version of GOES-R SCaMPR (also driven by MWCOMB) to support GOES-R Proving Ground beginning in summer 23

24 Agenda 1.Operational Product Status Updates (15 min) a.Hydro-Estimator precipitation products (Kuligowski/Zhao) b.MSPPS/MIRS precipitation products (Zhao/Ferraro/Boukabara) c.Blended TPW products (Zhao/Kidder/Paquette) d.eTRaP (Seybold/Kidder) e.GOES histogram precip product (Schreitz/Xie) 2.Developmental Project Updates (15 min) a.MSPPS snowfall rate (Ferraro/Meng/Zhao) b.MIRS NPP rainfall rate (Boukabara/Iturbide/Zhao) c.eTRaP enhancements (Ma/Kuligowski/Kidder) d.Soil Moisture Products System (Zhan/Zhao) e.POES-GOES-GPS Blended RR (Zhao/Kidder/Ferraro) f.Satellite Cal/Val efforts for Rainfall Estimates and POES-AMSU Monitoring (Janowiak) g.New satellite data products for TV broadcast market (Ferraro) h.SCaMPR improvements (Kuligowski) 3.Discuss Inactive Projects and Pending PREPOP Projects (All; 5 min) 4.Special Discussion (60 min) a.Impact of MSPPS changes in response to AMSU-B band issues (Zhao/Janowiak; 20 min) b.MIRS Rainfall Rate recalibration (Iturbide-Sanchez; 20 min) c.SMOPS (Zhan; 20 min) 5.New Business (All; 10 min) 6.Review of Action Items (All; 5 min) 7.Adjourn 24

25 25 Inactive PREPOP R2O Projects SPSRB # ProductEnd User POC NESDIS Lead Current Phase Issue(s)Funding Operational GPROF-6 [GPROF-2004] Precip Estimates Dropped from SPSRB User Request List High Temporal Satellite Precipitation Estimates Dropped from SPSRB User Request List GOES Mesoscale Convective System Index Eckert (NWS)Lindsey (STAR), Hanna (OSPO) DevelopmentDevelopment on hold for the time being. None.

26 26 Inactive PREPOP Development Projects ProductKey CapabilitiesEnd User POCNESDIS LeadIssue(s)Funding AMSR-E ProductsRainfall and cloud properties from AMSR-E Kusselson, Turk (SAB); Heil (NWS) Ferraro (STAR), Ding (OSPO), Zhao (OSPO) The products are supported as “it is”, and no resource available for making improvements at NESDIS. None; however, under OSPO EOS “umbrella”. McIDAS application is on OSPO base SSMIS Rain Rates from GPROF Rain rates from DMSP F-16/17 SSMIS using GPROF Xie (CPC), Huffman (NASA), Kummerow (GEWEX) Ferraro (STAR), Zhao (OSDPD) Produced in real time, but no funding available for operational transition. May be difficult to fund since MIRS plans to produce SSMIS rain rates also. None Intercomparison of H-E, QMORPH, and SCaMPR Decision tool for determining how best to operationally support SAB during the pre-GOES-R era Kusselson (SAB)Kuligowski (STAR)Will begin when new version of SCaMPR starts running in real time, which should begin in summer 2011 to support the GOES-R Proving Ground. None

27 27 Pending PREPOP R2O Projects PriorityKey CapabilitiesLeadSPSRB#SPSRB Project Plan TitleUser(s) Product Team Status 1NPP NOAA- Unique Products (NUP) Heidinger (STAR); TBD (OSDPD) TBDPOES-consistent VIIRS Cloud Products NCEP EMC; NWS WFO’s accessing CIMSS feed; NESDIS IASI processing system; climate community TBDProposing for funding through JPSS 2Global (60S- 60N) coverage of Hydro-Estimator rain rates Kuligowski (STAR); Zhao (OSDPD) Global Hydro-Estimator Satellite Rainfall Estimates NWS (provide to Hydrologic Research Center as part of MOU) TBDSPIWG requested written guarantee of NWS funding; still waiting to receive. 3Real-time GCOM-W products Ferraro (STAR); Zhao (OSDPD) Part of JPSS TBDSAB, NWS field offices and CPC TBDProject being incorporated within JPSS; efforts underway to get funding. 27

28 Agenda 1.Operational Product Status Updates (15 min) a.Hydro-Estimator precipitation products (Kuligowski/Zhao) b.MSPPS/MIRS precipitation products (Zhao/Ferraro/Boukabara) c.Blended TPW products (Zhao/Kidder/Paquette) d.eTRaP (Seybold/Kidder) e.GOES histogram precip product (Schreitz/Xie) 2.Developmental Project Updates (15 min) a.MSPPS snowfall rate (Ferraro/Meng/Zhao) b.MIRS NPP rainfall rate (Boukabara/Iturbide/Zhao) c.eTRaP enhancements (Ma/Kuligowski/Kidder) d.Soil Moisture Products System (Zhan/Zhao) e.POES-GOES-GPS Blended TPW and RR(Zhao/Kidder/Ferraro) f.Satellite Cal/Val efforts for Rainfall Estimates and POES-AMSU Monitoring (Janowiak) g.New satellite data products for TV broadcast market (Ferraro) h.SCaMPR improvements (Kuligowski) 3.Discuss Inactive Projects and Pending PREPOP Projects (All; 5 min) 4.Special Discussion (60 min) a.Impact of MSPPS changes in response to AMSU-B band issues (Zhao/Janowiak; 20 min) b.MIRS Rainfall Rate recalibration (Iturbide-Sanchez; 20 min) c.SMOPS (Zhan; 20 min) 5.New Business (All; 10 min) 6.Review of Action Items (All; 5 min) 7.Adjourn 28

29 Impact of AMSU-B band issues on the MSPPS rain rate product Limin Zhao 3/23/

30 Status of Sensor Health and Product Availability N15 AMSU-B – The 183 GHz moisture channels failed on Sep 20, 2010 (local oscillator failed), all data are flagged missing. – The 89 GHz and 150 GHz window channels are providing good quality data – No MSPPS Rain Rate is produced with the current algorithm N16 AMSU-B – The 183 GHz moisture channels are getting much noisy as the sensor is aging out although the sensor is still operated operationally. – The 89 GHz and 150GHz GHz window channels are providing good quality data – MSPPS rain rate products are been producing with the CI-correction off for light rain over land N17 AMSU-B – The 183 GHz moisture channels failed on Dec 16, 2009 (local oscillator failed), all data are flagged missing. – The 89 GHz and 150 GHz window channels are providing good quality data – No MSPPS rain rate is produced with the current algorithm N18 MHS – All MHS channels are good – MSPPS rain rate product are available N19 MHS – Channel 3 (183±1GHz) and its NDET exceeded spec started from Aug 27, 2009, and stabilized around 3.0 K (exceeding 1.0 K specification) since Oct 7, 2009 – Channel 4 (183±3GHz) and its NDET exceeded spec starting from Aug 27, 2009, and stabilized around 0.61 K (back within 1.0 K specification) since Oct 7, 2009, which is back within 1.0 K specification – MSPPS are being produced, no quality issue observed/reported so far Metop-A MHS – All MHS channels are good – MSPPS rain rate product are available 30

31 Use of AMSU-B 183 GHz Channels in MSPPS Ice Water Path Retrieval – Conditions for existence of detectable precipitating cloud – Criteria for adding correction over costal lines to recover ice water path that are missed due to lack of large precipitating ice particles – 183±7 GHz channel for screening false alarm over desert Rain Rate Retrieval – Used in deriving the Convective Index for separating convective cores from stratiform regimes – Criteria for adding correction over ocean and costal to recover light rain that are missed due to lack of large precipitating ice particles 31

32 Convective Index (CI) CI algorithm The CI, which reflects the vertical convection strength of precipitation systems, is calculated using the MHS moisture channels (183  1, 183  3 and 190) as follows: CI = 1 for  2 >-3 and  2 >  1 and  2 >  3 CI = 2 for  2 > 0 and  1 > 0 and  3 > 0 and  1 >  3 and  2 >  3 CI = 3 for  2 > 0 and  1 > 0 and  3 > 0 and  1 >  3 and  2 <  3 where  1 = 183  ,  2 = 183  ,  3 = 183   3 and the values of 1, 2 and 3 represent the exist of weak, moderate and strong vertical convection. A different IWP - RR relation is applied for these pixels with CI=3. 32

33 Responses to AMSU-B Moisture Channels Issues Without Action – No AMSU rain rate products available from N15, N16 and N17 – Users have to live with degraded temporal sampling or global refresh rate, which increases from 2.5 ~ 4.0 hr → 6.0 hr while rain rate products are only available from N18, N19 and Metop-A. Alternative – Disable the classification of convective and stratiform to allow the products be generated with slightly degraded quality – Exploring the possibility of retrieving rain rate without using AMSU-B moisture channels 33

34 First Attempt Alternative CI – Made an attempt to use only 89 GHZ and 150 GHz channels over land for defining the strong convective cores CI=3 for BT150 < 173 and BT89 < 220 and land_stag=1 Changes in the IWP algo – Conditions for existence of detectable precipitating cloud Replace (BT176 3) – Disable the correction over costal lines – Replace BT176 with BT150 for screening dessert, and adjust the threshold value according Changes in the RR algo – Use the alternative CI over land – Disable the use of CI over ocean – Disable the correction over costal lines 34

35 With AMSU-B Moisture ChannelsWithout AMSU-B Moisture Channels 35

36 Validation of MSPPS Changes in Response to AMSU-B Issues John Janowiak 3/21/

37 Evaluation of Changes Approaches – Verify that the alternative algorithms can generate reasonable retrievals without using AMSU-B moisture channels – Satellite retrievals are matched with the closest radar hourly rainfall estimate: – N18 is used as the reference to compare the retrievals with and without using AMSU-B moisture channel Performed with Limited Cases – Two weeks worth of data on November, 2010 – Two weeks worth of data on March,

38 RADAR (N15 match) “N15_new” “N15_new” - RADAR RADAR (N18 match) “N18_new” “N18_new” - RADAR “N18_ops” “N18_ops” - RADAR Time-space matched satellite & precipitation during March 3-14, 2011 NOTE: time sampling difference between NOAA-15/18 (radar matched for each satellite, separately) “mm” accumulated over period Difference Maps 38

39 March 3-14, 2011 Nov 15-30, 2010 Swath Rain rate Histograms (light rain) 39

40 March 3-14, 2011 Nov 15-30, 2010 Swath Rain rate Histograms (moderate-heavy rain) Note Y-axis range differences 40

41 PDFs over global oceans 41

42 Evaluation of Changes Approaches spatially, all 3 satellite estimates exhibit very similar patterns and, in general, they underestimate precipitation (relative to radar) in the eastern 1/3 of the nation and overestimate in much of the West. -- Slide 9 Histograms of precipitation rates in the 0.5 to 2 mm hr -1 range during the March 2011 case are very similar to the Nov 2010 data, with very good agreement among the satellite estimates and with the radar data in the 1.25 to 2 mm hr -1 range. -- Slide 10 Histograms of precipitation rates in the 2 to 5 mm hr -1 range during the March 2011 period for the modified NOAA-15 algorithm are closer to the radar data than the NOAA-18 algorithms, and are in better agreement with radar compared to the Nov 2010 case. -- Slide 10 For precipitation rates of 10 to 20 mm hr -1, the modified NOAA-15 results are in very good agreement with the radar data (particularly for rates in the mm hr -1 range), and all 3 satellite estimates perform better during this period compared to the Nov 2010 case. -- Slide 11 All of the satellite estimates exhibit considerably more events with precipitation rates of 25 to 30 mm hr -1 compared to radar – although this may be because the radar data are integrated hourly data while the satellite estimates are ‘snapshots’. Note, that while the radar data indicate 0 to 0.03% of the events with precip. >25 mm hr -1 during both Nov and Mar, the satellite %’s are much higher in March than November. -- Slide 11 42

43 Summary No MSPPS rain rate products are available from N15 and N17 due to the fail of AMSU-B moisture channels. N16 rain rate product is degraded due to increased noise in AMSU-B moisture channels A preliminary attempt is made to recover the MSPPS rain rate product without using AMSU-B moisture channels. The comparisons with limited data sets show that the retrievals with a-CI in general look good and agree well with that from the operation. No obvious problems have cropped up during the two evaluation periods. More detailed analysis and evaluation are needed to fully understand the impact of these changes. Looking for comments/suggestions/recommendations from POP and/or Users – Any requirement or desires to recover the RR products from these aged satellites? – Should we make efforts to improve and implement the changes to operation? 43

44 Agenda 1.Operational Product Status Updates (15 min) a.Hydro-Estimator precipitation products (Kuligowski/Zhao) b.MSPPS/MIRS precipitation products (Zhao/Ferraro/Boukabara) c.Blended TPW products (Zhao/Kidder/Paquette) d.eTRaP (Seybold/Kidder) e.GOES histogram precip product (Schreitz/Xie) 2.Developmental Project Updates (15 min) a.MSPPS snowfall rate (Ferraro/Meng/Zhao) b.MIRS NPP rainfall rate (Boukabara/Iturbide/Zhao) c.eTRaP enhancements (Ma/Kuligowski/Kidder) d.Soil Moisture Products System (Zhan/Zhao) e.POES-GOES-GPS Blended TPW and RR (Zhao/Kidder/Ferraro) f.Satellite Cal/Val efforts for Rainfall Estimates and POES-AMSU Monitoring (Janowiak) g.New satellite data products for TV broadcast market (Ferraro) h.SCaMPR improvements (Kuligowski) 3.Discuss Inactive Projects and Pending PREPOP Projects (All; 5 min) 4.Special Discussion (60 min) a.Impact of MSPPS changes in response to AMSU-B band issues (Zhao/Janowiak; 20 min) b.MIRS Rainfall Rate recalibration (Iturbide-Sanchez; 20 min) c.SMOPS (Zhan; 20 min) 5.New Business (All; 10 min) 6.Review of Action Items (All; 5 min) 7.Adjourn 44

45 Present Efforts to Improve and Extend the MiRS Rainfall Rate 45

46 MiRS Atmospheric Background Covariance Matrix based on ECMWF 60 and WRF simulations Temp. and Water Vapor based on ECMWF 60 Hydrometeors based on WRF simulations Implementation of a New Hydrometeor Background Covariance Matrix based of WRF Simulations WRF Simulation over Middle Latitude Land Surfaces for SON season CONUS South America Australia 46

47 CorrelationProbability of Detection Validation of the New Hydrometeor Covariance Matrix Using Stage IV Rainfall Rate Dark Line: Based on Current Hydrometeor Covariance Matrix Blue Line: Based on New Hydrometeor Covariance Matrix 47

48 False Alarm RateHeidke Skill Score Validation of the New Hydrometeor Covariance Matrix Using Stage IV Rainfall Rate Dark Line: Based on Current Hydrometeor Covariance Matrix Blue Line: Based on New Hydrometeor Covariance Matrix 48

49 Current Covariance MatrixNew Covariance Matrix Estimation of more high rainfall rate cases Impact of the New Hydrometeor Covariance Matrix on the Rainfall Rate Distribution 49

50 Current Covariance MatrixNew Covariance Matrix Estimation of more high rainfall rate cases Impact of the New Hydrometeor Covariance Matrix on the Estimation of Rainfall Rate 50

51 51 Cumulative Validation and Consolidation of MIRS MIRS is applied to a number of microwave sensors, each time gaining robustness and improving validation for Future New Sensors POES N18,N19  DMSP SSMIS F16, F18  AQUA AMSR-E  NPP/NPOESS ATMS, MIS   : Applied Daily  : Applied occasionally  : Tested in Simulation Metop-A  The exact same executable, forward operator, covariance matrix used for all sensors MiRS: A System that is Being Applied to Multiple Sensors TRMM-TMI 

52 Extension of MiRS Rainfall Rate to TRMM-TMI Observations. Comparison to N18 Rainfall Rate MiRS N18 Rainfall RateMiRS TRMM-TMI Rainfall Rate ~5.0 km spatial resolution ~50.0 km spatial resolution 52

53 Extension of MiRS Rainfall Rate to TRMM-TMI Observations. Comparison to TRMM-2A12 Rainfall Rate 1/2 TRMM-2A12 Rainfall RateMiRS TRMM-TMI Rainfall Rate 53

54 TRMM-2A12 Rainfall RateMiRS TRMM-TMI Rainfall Rate Extension of MiRS Rainfall Rate to TRMM-TMI Observations. Comparison to TRMM-2A12 Rainfall Rate 2/2 Major efforts to the improvement of the MiRS TRMM-TMI rainfall rate are related to the improvement of the background covariance matrix and bias correction. 54

55 Agenda 1.Operational Product Status Updates (15 min) a.Hydro-Estimator precipitation products (Kuligowski/Zhao) b.MSPPS/MIRS precipitation products (Zhao/Ferraro/Boukabara) c.Blended TPW products (Zhao/Kidder/Paquette) d.eTRaP (Seybold/Kidder) e.GOES histogram precip product (Schreitz/Xie) 2.Developmental Project Updates (15 min) a.MSPPS snowfall rate (Ferraro/Meng/Zhao) b.MIRS NPP rainfall rate (Boukabara/Iturbide/Zhao) c.eTRaP enhancements (Ma/Kuligowski/Kidder) d.Soil Moisture Products System (Zhan/Zhao) e.POES-GOES-GPS Blended TPW and RR (Zhao/Kidder/Ferraro) f.Satellite Cal/Val efforts for Rainfall Estimates and POES-AMSU Monitoring (Janowiak) g.New satellite data products for TV broadcast market (Ferraro) h.SCaMPR improvements (Kuligowski) 3.Discuss Inactive Projects and Pending PREPOP Projects (All; 5 min) 4.Special Discussion (60 min) a.Impact of MSPPS changes in response to AMSU-B band issues (Zhao/Janowiak; 20 min) b.MIRS Rainfall Rate recalibration (Iturbide-Sanchez; 20 min) c.SMOPS (Zhan; 20 min) 5.New Business (All; 10 min) 6.Review of Action Items (All; 5 min) 7.Adjourn 55

56 NOAA-NESDIS Global Soil Moisture Operational Product System (SMOPS) Xiwu Zhan, Jicheng Liu, Limin Zhao, Mitch Goldberg NOAA-NESDIS Center for Satellite Applications and Research, Camp Springs, MD, USA Ken Jensen Raytheon Technical Service Company, Landover, MD, USA Raytheon Technical Service Company, Landover, MD, USA Acknowledgment: Slides about, USDA-ARS & SCAN networks, NOAA-USCRN, ALEXI and NOAA-OHD are borrowed from Drs. P. Houser, G. Scheffner, T. Jacksonn, B. Baker, M. Anderson and B. Cosgrove 56

57 OUTLINE  Why Soil Moisture  Current Data Products  NOAA-NESDIS SMOPS  Future Plans 57

58 24-Hours Ahead Atmospheric Model Forecasts Observed Rainfall 0000Z to 0400Z 13/7/96 (Chen et al., NCAR) Buffalo Creek Basin "The strong motivation for this land data assimilation and land- monitoring space missions such as Hydros is that the land states of soil moisture, soil ice, snowpack, and vegetation exert a strong control on...the heating and moistening of the lower atmosphere…forecast of tomorrow's heat index, precipitation, and severe thunderstorm likelihood." Louis Uccellini, NCEP “The experience of the last ten years at ECMWF has shown the importance of soil moisture...Soil moisture is a major player on the quality of weather parameters such as precipitation, screen-level temperature and humidity and low-level clouds." Anthony Hollingworth, ECMWF Soil Moisture Data Will Improve Numerical Weather Prediction (NWP) Over the Continents by Accurately Initializing Land Surface States With Realistic Soil Moisture Without Realistic Soil Moisture Observed Rainfall from intense storm in Colorado: Model forecasts with and w/o soil moisture: Actual storm event is forecasted accurately only if soil moisture information is available. Soil Moisture Impacts on Weather Forecasting 58

59 Current NWS Operational 30 km Flash Flood Guidance (FFG) is Based on Model Surface Soil Moisture Deficit Current NOAA and National Drought Mitigation Center (NDMC) Operational Drought Index is also based on Modeled Soil Moisture Data. Soil moisture Observational data will replace model or proxy SM Soil Moisture Data for Flood & Drought Monitoring 59

60 VUT ESCAT (Wagner et al, 1999) VUT ESCAT (Wagner et al, 1999) GSFC SMMR (Owe et al, 2001) GSFC SMMR (Owe et al, 2001) USDA TMI (Bindlish et al, 2003) USDA TMI (Bindlish et al, 2003) Princeton TMI (Gao et al, 2006) Princeton TMI (Gao et al, 2006) NASA AMSR-E (Njoku et al, 2003) NASA AMSR-E (Njoku et al, 2003) USDA AMSR-E (Jackson et al, 2007) USDA AMSR-E (Jackson et al, 2007) VUA AMSR-E (Owe et al, 2008) VUA AMSR-E (Owe et al, 2008) USDA WindSat (Jackson et al, 2008) USDA WindSat (Jackson et al, 2008) NRL WindSat (Li et al, 2008) NRL WindSat (Li et al, 2008) Current Satellite Soil Moisture Data Products: 60

61 T B,i cmp = T skin {e r,p exp (-  i /cos  ) + (1 –  ) [1 – exp (-  i /cos  )] [1 + R r,i exp (-  i /cos  )]}  i = b *VWC R r,i = R s exp(h cos 2 θ) R s = f(ε) -- Fresnel Equation ε = g(SM) -- Mixing model T B,i obs = T B06h, T B06v, T B10h, T B10v, T B18h, T B18v Multi-channel Inversion Algorithm (MCI): Soil Moisture Retrieval Algorithms: 61

62 T B10h = T s [1 –R r exp (-2  /cos  )] R r = R s exp(h cos 2 θ) R s = f(ε) -- Fresnel Equation ε = g(SM) -- Mixing model T s = reg 1 (T B37v ) or T s LSM  = b * VWC VWC= reg 2 (NDVI) Single Channel Retrieval (SCR) Algorithm: SCR can be applied to different sensors for a consistent satellite soil moisture data product. Soil Moisture Retrieval Algorithms: 62

63 Spatial Map Soil Moisture Retrieval Comparison: 63

64 SCRSCR MCIMCI Soil Moisture Retrieval Comparison: 64

65 NASA and USDA AMSR-E Compared with In Situ Measurements Soil Moisture Retrieval Comparison: 65

66 NOAA-NESDIS SMOPS Structure: 66

67 NOAA-NESDIS SMOPS Structure: 67

68 NOAA-NESDIS SMOPS Data Processing Steps: 68

69 NOAA Global Soil Moisture Data Portal: 69

70 NOAA NESDIS SM Data Research Plan Bayesian or other Merging Method Cubist, ALEXI, etc. Low Rez Soil Moisture Data High Rez Soil Moisture Proxy TMI/AMSR-E/WindSat/ SMOS/SMAP/Aquarius/ MIS/ASCAT Obs TM/AVHRR/MODIS/VIIRS/Radar/ GOES Obs Soil Moisture Ground Obs Meteorological Forcing & Land Surface Obs LIS/EnKF Data Assimilation Agriculture DSS Drought Monitoring/ Forecast Flood Monitoring/ Forecast Military Applications Water Resources Management Numerical Weather Predictions High Rez/Quality Soil Moisture Data Products Retrieval Alg. X. Zhan, NOAA/NESDIS/STAR 2007/04/ km, Low accuracy km, Higher accuracyAncillary Data 70

71 Potential Role of Passive Microwave Remote Sensing in Flood Forecasting R. Bindlish, W.T. Crow & T.J. Jackson USDA ARS Hydrology and Remote Sensing Lab (funded by NASA EOS/ ) 71

72 AMSR 6.6 H GHz observations 72

73 Correlation Coefficients ParameterPrecipitation6.6H Bowen Downs 0.80 (4)0.36 (4) Longreach 0.64 (6)0.36 (6) Stonehenge 0.70 (4)0.31 (6) Retreat 0.63 (8)0.30 (8) Nappa Merrie 0.11 (15)0.43 (16) * Numbers in parenthesis donate lag times in days for maximum correlation coefficient 73

74 Bowen Downs (Thomson River km 2 ) 74

75 SUMMARY  Current satellite soil moisture products may not meet the needs for NWP applications  A one-stop global soil moisture data production and distribution system (SMOPS) is being built at NOAA-NESDIS  Soil moisture signal from MW satellite may have the potential to assist flood forecasting 75

76 THANKS for Listening ! I’ll listen to you anywhere anytime from now at or x

77 Agenda 1.Operational Product Status Updates (15 min) a.Hydro-Estimator precipitation products (Kuligowski/Zhao) b.MSPPS/MIRS precipitation products (Zhao/Ferraro/Boukabara) c.Blended TPW products (Zhao/Kidder/Paquette) d.eTRaP (Seybold/Kidder) e.GOES histogram precip product (Schreitz/Xie) 2.Developmental Project Updates (15 min) a.MSPPS snowfall rate (Ferraro/Meng/Zhao) b.MIRS NPP rainfall rate (Boukabara/Iturbide/Zhao) c.eTRaP enhancements (Ma/Kuligowski/Kidder) d.Soil Moisture Products System (Zhan/Zhao) e.POES-GOES-GPS Blended TPW and RR(Zhao/Kidder/Ferraro) f.Satellite Cal/Val efforts for Rainfall Estimates and POES-AMSU Monitoring (Janowiak) g.New satellite data products for TV broadcast market (Ferraro) h.SCaMPR improvements (Kuligowski) 3.Discuss Inactive Projects and Pending PREPOP Projects (All; 5 min) 4.Special Discussion (60 min) a.Impact of MSPPS changes in response to AMSU-B band issues (Zhao/Janowiak; 20 min) b.MIRS Rainfall Rate recalibration (Iturbide-Sanchez; 20 min) c.SMOPS (Zhan; 20 min) 5.New Business (All; 10 min) 6.Review of Action Items (All; 5 min) 7.Adjourn 77

78 78 Review of October 2010 Action Items DescriptionPOCStatus Brief PREPOP on the result of the MIRS Rainfall Rate recalibration Iturbide- Sanchez Completed at this meeting. Provide PREPOP with a systematic evaluation of the impact of the MSPPS changes in response to the AMSU-B band issues JanowiakCompleted at this meeting.

79 Agenda 1.Operational Product Status Updates (15 min) a.Hydro-Estimator precipitation products (Kuligowski/Zhao) b.MSPPS/MIRS precipitation products (Zhao/Ferraro/Boukabara) c.Blended TPW products (Zhao/Kidder/Paquette) d.eTRaP (Seybold/Kidder) e.GOES histogram precip product (Schreitz/Xie) 2.Developmental Project Updates (15 min) a.MSPPS snowfall rate (Ferraro/Meng/Zhao) b.MIRS NPP rainfall rate (Boukabara/Iturbide/Zhao) c.eTRaP enhancements (Ma/Kuligowski/Kidder) d.Soil Moisture Products System (Zhan/Zhao) e.POES-GOES-GPS Blended TPW and RR(Zhao/Kidder/Ferraro) f.New satellite data products for TV broadcast market (Ferraro) g.SCaMPR improvements (Kuligowski) 3.Discuss Inactive Projects and Pending PREPOP Projects (All; 5 min) 4.Special Discussion (60 min) a.Impact of MSPPS changes in response to AMSU-B band issues (Zhao/Janowiak; 20 min) b.MIRS Rainfall Rate recalibration (Iturbide-Sanchez; 20 min) c.SMOPS (Zhan; 20 min) 5.New Business (All; 10 min) 6.Review of Action Items (All; 5 min) 7.Adjourn 79


Download ppt "PREPOP Meeting Wednesday, March 23, 2011 10 AM – NOON Room 602 WWB 1."

Similar presentations


Ads by Google