Presented by Limin Zhao, Stan Kidder, and ??????

Outline Introduction Project Requirements Algorithm Review System Design Quality Assurance Operations Concept Risks and Actions Summary 2

Introduction This project builds on the successful operational implementation of the Blended TPW in March 2009 Two products are to be implemented in FY09: Blended Rain Rate product Adding MIRS products, especially SSMIS products, to the Blended TPW product All products are implemented in DPEAS, which was ported to the IBM system in FY08 3

Project Requirements SPSRB # , POES-GOES Blended Hydrometeorological Products; SPSRB # : POES/DMSP Blended Products. Generate operational blended TPW and RR products from POES, MetOP, DMSP, GOES and GPS. Others: (1) NWS AWIPS OB9; (2) NOAA's Hydrometeorological Testbed (HMT); (3) NOAA's Scientific Data Stewardship (SDS) program. User Community NWS WR, NWS SPC, NWS NHC, NWS HPC, NWS WFOs (AWIPS) NESDIS/SAB NOAA Mission Goals Supported Weather and Water, Ecosystems, Climate Commerce and Transportation Goal Wide – Satellite Services; Polar satellites acquisitions Mission Priority: Mission Critical/High- cannot meet operational mission objectives without this requirement. 4

Algorithm Review Enhanced Blended TPW product: MIRS retrievals added Surface type added to algorithm to separate land and ocean TPW blending algorithms. 5

6 Enhanced Blended TPW 15 Jan UTC NOAA 19, MetOp-A, DMSP F16 (MIRS)

7 Enhanced Blended TPW—Close UP 15 Jan UTC DMSP F16 MIRS DMSP F16 SSMIS TPW successfully blended!

Algorithm Review Enhanced Blended TPW product: MIRS retrievals added Surface type added to algorithm to separate land and ocean TPW blending algorithms. Blended Rain Rate product: Blending algorithm developed (see following slides) Test operation implemented at CIRA Blends RR data from NOAA 15, 16, 17, 18, and MetOp-A (does not use MIRS RR because of lower resolution, does not use NOAA 19 RR because of MHS problems). 8

5-Day Histograms (of raining pixels) OCEAN“LAND” PDF PDF 0.25 SSM/I AMSU-B MHS Rain Rate (mm/hr) 0.25 mm/hr bins SSM/I shows expected “lognormal” distribution, but AMSU-B and MHS do not Over “land” all PDFs are similar 9

Cumulative PDF Rain Rate (mm/hr) OCEAN CPDF Input RR Corrected RR Interpolate CPDFs to correct RR 10

The RR Blending Algorithm No correction over land (=“not ocean”) No correction for SSM/I For AMSU-B and MHS over ocean No correction for RR > 5 mm/hr Only negative corrections allowed All scan positions treated the same DMSP F13 SSM/I is the “reference satellite” DMSP F13 histograms were captured before its failure Linearly interpolate the CPDFs to get correction 11

Before All AMSU-B or MHS Note lack of rain rates below 0.5 mm/hr Too much blue and green 12

After AMSU-B or MHS SSM/I AMSU-B and MHS look a lot more like SSM/I than they would have without correction 13

System Design The Operational Blended TPW System The Enhanced Blended TPW and RR System Inside DPEAS TPW processing RR processing 14

15 The Operational Blended TPW Products System Diagram North/Emerald/Diamond DPEAS (Blended TPW) ESPC Diamond AMSU TPW ESPC satepsdist1 GPS & GOES TPW McIDAS Processing AWIPS Processing SOS Image Processing Satepsdist4 ADDE server Satepsdist4 Satepsanone SOS TPW image NAWIPS Satepsdist1 Product Server GINI AWIPS Web Farm Monitoring DDS CLASSSAB Users Cyclone QC/VAL Web Farm Monitoring sftp push sftp push sftp push sftp pull (spider) direct access ANCF/SBN Input Data Includes: AMSU TPW from MSPPS, GOES TPW from SFOV, and GPS from NWS/NOAAPort Processing Server User Data/Product s sftp push

16 The Enhanced Blended TPW and Blended RR Products System Diagram North/Emerald/Diamond DPEAS (Blended TPW & RR) ESPC Diamond AMSU & SSMIS TPW & RR ESPC satepsdist1 GPS & GOES TPW McIDAS Processing AWIPS Processing SOS Image Processing Satepsdist4 ADDE server Satepsdist4 Satepsanone SOS TPW image NAWIPS Satepsdist1 Product Server GINI AWIPS Web Farm Monitoring DDS CLASSSAB Users Cyclone QC/VAL Web Farm Monitoring sftp push sftp push sftp push sftp pull (spider) direct access ANCF/SBN Input Data Includes: AMSU TPW & RR from MSPPS, SSMIS TPW from MIRS, GOES TPW from SFOV, and GPS from NWS/NOAAPort Processing Server User Data/Product s sftp push

17 The Enhanced Blended TPW and Blended RR Products System Diagram ESPC Diamond AMSU & SSMIS TPW & RR ESPC satepsdist1 GPS & GOES TPW McIDAS Processing AWIPS Processing SOS Image Processing Satepsdist4 ADDE server Satepsdist4 Satepsanone SOS TPW image NAWIPS Satepsdist1 Product Server GINI AWIPS Web Farm Monitoring DDS CLASSSAB Users Cyclone QC/VAL Web Farm Monitoring sftp push sftp push sftp push sftp pull (spider) direct access ANCF/SBN Input Data Includes: AMSU TPW & RR from MSPPS, SSMIS TPW from MIRS, GOES TPW from SFOV, and GPS from NWS/NOAAPort Processing Server User Data/Product s sftp push North/Emerald/Diamond DPEAS (Blended TPW & RR) What Happens in DPEAS?

Inside DPEAS 18 ESPC TPW swath data DPEAS TPW Processing Data Ingest (produces augmented HDFEOS data files) Apply blending algorithm Map the data (one swath per map) Composite the maps (produces a global map of TPW over ocean) Data Ingest (already gridded) ESPC GPS TPW data ESPC GOES PW data Data Ingest Objectively analyze the GPS data (Barnes analysis) Blend Land and Ocean TPW to form final product OceanLand NEW: MIRS data ingest NEW: Use surface type to control blending

Inside DPEAS 19 ESPC RR swath data DPEAS RR Processing Data Ingest (produces augmented HDFEOS data files) Apply RR blending algorithm Map the data (one swath per map) Composite the maps

System Design Summary The system design is based on the operational Blended TPW system System modified to handle MIRS data Blended RR added using same technology as operational Blended TPW 20

Quality Assurance System-Level Quality Control Process Quality Assurance Product QC Monitoring 21

22

23

24

25

Operations Concept Product Generation Product Monitoring Product Maintenance Product Dissemination Product Archive 26

27

28

29

30

31

32

33

34

Risks and Actions The new DPEAS code has not yet been implemented at OSDPD However, the code runs in real-time at CIRA, and Last year all of DPEAS was ported to OSDPD, this year only a few modules need to be ported, which should be easy. 35

Summary 36