Design Review Enhanced Blended TPW and Blended RR

Design Review: Enhanced Blended TPW and Blended RR 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 FY 09: �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 FY 08 3

Project Requirements � SPSRB #0708 -0023, POES-GOES Blended Hydrometeorological Products; SPSRB #9902 -19: POES/DMSP Blended Products. � Generate operational blended TPW and RR products from POES , Met. OP, DMSP, GOES and GPS. � Others: (1) NWS AWIPS OB 9; (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 ocean TPW blending algorithms. 5

Enhanced Blended TPW 15 Jan 2010 1705 UTC NOAA 19, Met. Op-A, DMSP F 16 (MIRS) 6

Enhanced Blended TPW—Close UP 15 Jan 2010 1705 UTC MIRS DMSP F 16 SSMIS TPW successfully blended! DMSP F 16 7

Algorithm Review �Enhanced Blended TPW product: �MIRS retrievals added �Surface type added to algorithm to separate land ocean TPW blending algorithms. �Blended Rain Rate product: �Blending algorithm developed (see following slides) �Test operation implemented at CIRA http: //cat. cira. colostate. edu �Blends RR data from NOAA 15, 16, 17, 18, and Met. Op-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) 1. 0 0. 25 OCEAN “LAND” SSM/I 0. 25 mm/hr bins PDF MHS AMSU-B 0. 0 0 2 4 6 SSM/I shows expected “lognormal” distribution, but AMSU-B and MHS do not 8 10 0. 0 0 2 4 6 8 10 Rain Rate (mm/hr) Over “land” all PDFs are similar 9

Cumulative PDF CPDF 1. 0 Interpolate CPDFs to correct RR OCEAN 0. 0 0 Corrected RR 2 4 6 8 Rain Rate (mm/hr) 10 Input 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 F 13 SSM/I is the “reference satellite” � DMSP F 13 histograms were captured before its failure �Linearly interpolate the CPDFs to get correction 11

Before Note lack of rain rates below 0. 5 mm/hr All AMSU-B or MHS Too much blue and green 12

I SSM/ AMS U-B o r MH S After 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

The Operational Blended TPW Products System Diagram Satepsdist 4 ESPC Diamond AMSU TPW ESPC satepsdist 1 GPS & GOES TPW North/Emerald/Diamond DPEAS (Blended TPW) sftp push Cyclone QC/VAL Web Farm Mc. IDAS Processing Satepsdist 4 ADDE server AWIPS Processing sftp Satepsdist 1 push Product Server SOS Image Processing GINI DDS sftp push CLASS sftp pull sftp push direct access (spider) NAWIPS SAB Monitoring Web Farm Monitoring Users Input Data Includes: AMSU TPW from MSPPS, GOES TPW from SFOV, and GPS from NWS/NOAAPort sftp push Satepsanone SOS TPW image ANCF/SBN AWIPS Data/Product s Processing Server User 15

The Enhanced Blended TPW and Blended RR Products System Diagram ESPC Diamond AMSU & SSMIS TPW & RR ESPC satepsdist 1 GPS & GOES TPW North/Emerald/Diamond DPEAS (Blended TPW & RR) Satepsdist 4 sftp push Cyclone QC/VAL Web Farm Mc. IDAS Processing Satepsdist 4 ADDE server AWIPS Processing sftp Satepsdist 1 push Product Server SOS Image Processing GINI DDS sftp push CLASS sftp push sftp pull sftp push direct access (spider) NAWIPS SAB Monitoring Web Farm Monitoring sftp push Satepsanone SOS TPW image Users Input Data Includes: AMSU TPW & RR from MSPPS, SSMIS TPW from MIRS, GOES TPW from SFOV, and GPS from NWS/NOAAPort ANCF/SBN AWIPS Data/Product s Processing Server User 16

The Enhanced Blended TPW and Blended RR Products System Diagram ESPC Diamond AMSU & SSMIS TPW & RR ESPC satepsdist 1 GPS & GOES TPW North/Emerald/Diamond DPEAS (Blended TPW & RR) Satepsdist 4 sftp push Cyclone QC/VAL Web Farm Mc. IDAS Processing Satepsdist 4 ADDE server AWIPS Processing sftp Satepsdist 1 push Product Server SOS Image Processing GINI DDS What Happens in DPEAS? sftp push CLASS sftp pull sftp push direct access (spider) NAWIPS SAB Monitoring Web Farm Monitoring sftp push Satepsanone SOS TPW image Users Input Data Includes: AMSU TPW & RR from MSPPS, SSMIS TPW from MIRS, GOES TPW from SFOV, and GPS from NWS/NOAAPort sftp push ANCF/SBN AWIPS Data/Product s Processing Server User 17

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

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

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

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

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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