Operational Issues from NCDC Perspective Steve Del Greco, Brian Nelson, Dongsoo Kim NOAA/NESDIS/NCDC Dongjun Seo – NOAA/NWS/OHD 1 st Q2 Workshop Archive,

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Presentation transcript:

Operational Issues from NCDC Perspective Steve Del Greco, Brian Nelson, Dongsoo Kim NOAA/NESDIS/NCDC Dongjun Seo – NOAA/NWS/OHD 1 st Q2 Workshop Archive, Access and Service Assessment and Stewardship

1 st Q2 Workshop Incorporating Q2 products into NOAA’s NCDC Archive, Operations and Customer Service Plan:  Archive Q2 products on the NCDC robotic mass storage system  Provide dissemination/visualization capabilities for Q2 products  Prepare for implementation of higher resolution data, new products, and new data streams (Dual Pol QPE, Phase Array)  Implement Q2 products into spatial algorithms to be used to QC precipitation point data  Pilot Study on Regional Multisensor Precipitation Reanalysis

WSR-88D Radar Data Services Operations: WSR-88D Radar Data Services Operations: NOAA NCDC transitioned from receiving WSR-88D data on hard media to real time electronic ingest (NGI for base data (Level II) & dedicated line for products (level III)) NOAA NCDC transitioned from receiving WSR-88D data on hard media to real time electronic ingest (NGI for base data (Level II) & dedicated line for products (level III)) The NCDC Mass Storage System holds over 1000 terabytes of NEXRAD data and grows at a rate of ~ 80 terabytes per year The NCDC Mass Storage System holds over 1000 terabytes of NEXRAD data and grows at a rate of ~ 80 terabytes per year Annual data receipt of 80 terabytes may, in ~ three years, increase to 2,080 terabytes per year or 4,160 terabytes per year with backup Annual data receipt of 80 terabytes may, in ~ three years, increase to 2,080 terabytes per year or 4,160 terabytes per year with backup

WSR-88D Radar Data Services Potential Growth NCDC Radar Archives: Implementation of new radar technologies, such as dual polarization may increase the growth of the radar digital archive by a factor of 26 Implementation of new radar technologies, such as dual polarization may increase the growth of the radar digital archive by a factor of 26 With Phase Array Radar in 15 years ~ 20,800 terabytes per year With Phase Array Radar in 15 years ~ 20,800 terabytes per year Possibly incorporate the FAA Terminal Doppler WR (TDWR) Network into the NCDC Archives Possibly incorporate the FAA Terminal Doppler WR (TDWR) Network into the NCDC Archives Plans to archive multi-sensor (QPE) products Plans to archive multi-sensor (QPE) products 4.1 Minute Volume Coverage Pattern 4/ m, vice 1 km, Reflectivity Data Dual Polarization, 4 New Moments

An Automated, Multi-Layer, Precipitation Estimator using GIS and Spatial Interpolation DPA(s) RUC Model Stage IV Satellite (6) In-Situ Merged Layer NESDIS NCEP NWS QPE? PRECIPVAL Uses remotely sensed gridded data, and point data to estimate hourly precipitation for any point in the continental US

PrecipVal Current Data Sources In-Situ: Automated Surface Observing System (ASOS) Climate Reference Network (CRN) Climate Reference Network (CRN) Radar: Stage IV (Replace with QPE?) Digital Precipitation Array (DPA) Digital Precipitation Array (DPA) Model: Rapid Update Cycle (RUC) Satellite: GOES Multispectral Rainfall Algorithm (GMSRA) GMSRA with Night Screen GMSRA with Night Screen Auto Estimator Auto Estimator Hydro Estimator Hydro Estimator Blended GOES / Blended GOES / Microwave Estimator Microwave Estimator

1 st Q2 Workshop Assessment and Stewardship Pilot Study on Regional Multisensor Precipitation Reanalysis Objective: Provision of high resolution (5km), high frequency (1 hr) precipitation climate database Input to Distributed Hydrologic Models Input to Regional Climate Models

NCDC NEXRAD Resources Level II and Level III products Level II and Level III products Some sites have 10 years of data Some sites have 10 years of data

In-Situ Data Sources HADS (not ASOS yet) HADS (not ASOS yet) Hourly Precipitation (TD3240) Hourly Precipitation (TD3240) Daily COOP (TD3200) Daily COOP (TD3200)

In-Situ Data Sources Importance of Gauge Quality and Density Importance of Gauge Quality and Density MPR Algorithm Parameters for GMosaic RI=160 km Neighbors = ~10 April 2004

In-Situ Data Sources Gauge Climatology - MPR TD 3240 & 3200 only, no HADS Gauge Climatology - MPR TD 3240 & 3200 only, no HADS Warm Season Totals

Radar Data Sources Radar Climatology Radar Climatology Enhanced radar merging based on MPE algorithm Improvement on Stage III Significant inter radar calibration differences

Reprocessing of HADS Precip Ongoing historic HADS (1996-) archive will be completed by Aug 2006 Ongoing historic HADS (1996-) archive will be completed by Aug 2006 Sub-hourly PC will be converted to hourly PP Sub-hourly PC will be converted to hourly PP HADS precip will be included in Health of Network* for user feedback HADS precip will be included in Health of Network* for user feedback Add QA/QC and data recovery under Scientific Data Stewardship discipline Add QA/QC and data recovery under Scientific Data Stewardship discipline *

Quality Assurance of HADS The Physical Element HG (Stream Gauge Height) should have been PC (Accumulated Precipitation)

Quality Assurance of HADS These zeroes should have been reported as missings

Future of MPR (CONUS) ? Stage III Improvements MPE QPE-SUMS Dual Pol Reanalysis Additional Data Sources Parameter Estimation Uncertainty Estimation Additional Data Sources Parameter Estimation Uncertainty Estimation New Algorithms NCDC Archive

“Data Stewardship” NOAA Observing System Council definition: A subset of Data Management and consists of the application of rigorous analyses and oversight to ensure that data sets meet the needs of users. This includes documenting measurement practices and processing practices (metadata); providing feedback on observing system performance; intercomparison of data sets for validation; reprocessing (incorporate new data, apply new algorithms, perform bias corrections, integrate/blend data sets from different sources or observing systems); and recommending corrective action for errant or non-optimal operations.