ESRL Integrating Research and Technology Themes

Hydrometeorology Testbed

Goal and Scope

The goal is to develop, test and demonstrate new methods and tools that are able to improve NOAA's hydrometeorological services, including quantitative precipitation estimation (QPE) and forecasting (QPF) as well as streamflow predictions, flood warnings and drought monitoring. Those prototypes that prove effective in focused demonstrations, both technically and practically, are then transitioned into NOAA forecast operations and information services. Accurate, high resolution precipitation and soil moisture information are common denominators required for each of these services and is a major focus of Hydrometeorology Testbed (HMT), along with improved understanding of the physical processes governing precipitation.

The scope of this effort engages expertise that resides both within and outside Earth System Research Laboratory (ESRL). The Physical Sciences Division is well suited to provide research leadership of this effort, with NWS providing leadership of forecasting elements in QPF (NCEP/HPC) and Hydrology (OHD). HMT integrates ESRL capabilities in the following areas: use of experimental field data to diagnose errors in operational models, forecaster training, observing systems, mesoscale numerical modeling and weather-climate connections. Other partners in OAR, NWS and NESDIS complement these capabilities. There is a critical need for coordination of these diverse capabilities and roles across NOAA. The existence of HMT as an integrating theme at ESRL helps fill this gap, through both leadership and technical expertise, and provides an important capability to help NOAA address the critical area of water resources.

Rationale and Payoffs

NOAA's hydrometeorological services provide a vital foundation for numerous applications and users, including transportation, agriculture, water supply and flood control. Improvements and extensions of these services from NOAA are needed for many of these users to reach their goals. Two current examples where NOAA is extending its suite of services are the development of water quality forecasts (jointly with EPA) and a debris-flow watch-warning system (jointly with USGS). A common denominator of these needs is the requirement for accurate water quantity information, a need that HMT helps NOAA meet.

The payoffs include:

Accelerated development of those prototype methods and tools that hold the greatest promise to improve NOAA's hydrological and hydrometeorological services.
Pilot studies accelerate the transition of proven methods into forecast operations and information services. The tests and demonstrations are planned and conducted jointly by research and operations partners, in collaboration with external forecast users.
Improvements in scores on NOAA's operational Government Performance Requirements Act (GPRA) goals in QPF and flood warnings, after operationalization.
Socio-economic benefits accrued through improved decision-making, e.g., better QPF can help reservoir operators balance flood control against competing needs for water resources. Development of forecast-based reservoir operations on one key watershed alone is projected to save 60,000 acre feet of water for later use, without compromising flood control.

Major Collaborators and Their Research Foci

Physical Sciences Division: QPE, QPF, observing systems, model diagnostics, physical processes, Weather-Climate Connection, extreme events research and microphysics.
Global Systems Division: Data assimilation and coupling with models.

National Severe Storms Lab: QPE, observing systems.
NWS/Office of Hydrologic Development: Distributed Model Intercomparison Project.
NCEP/Hydrometeorological Prediction Center, Environmental Modeling Center: QPF.
California/Nevada River Forecast Center: QPE/QPF, observing system evaluation.
San Francisco WFO: Watch-warning program/flash flooding.
NGDC: Satellite data records for model initialization: clouds, radiation, ice phase.
NMFS and NOS: QPE, QPF, observing systems, model diagnostics, physical processes, extreme events research in coastal areas associated with impacts studies.

Contributions to NOAA Goals

HMT helps NOAA achieve its goals in transitioning research to operations in the area of hydrometeorology.
The NOAA Strategic Plan, the NOAA Research Plan, and the Annual Guidance Memos have identified improvements in Water Resource Information as a priority for the agency, and this has been reflected in the PPBES process through the ST&I Matrix Program and the Weather & Water Mission Goal.
QPE and QPF improvements directly impact NOAA's ability to provide the information needed for the Nation's Commerce and Transportation system.

Major Information Products, Customers, and Linkages

HMT yields research findings and field-tested methods that can be implemented into NOAA's operational forecast and information services. These include improved algorithms, better models, new observations or better use of existing observations, and forecaster training modules describing new tools or physical understanding. A key output of HMT is an accurate description of the spatio-temporal distribution of precipitation over carefully selected pilot study watersheds. These observations are then used to evaluate existing and new forecast models (e.g., the WRF model; being developed for use at ERSL, NCEP and elsewhere) and other forecast tools (e.g., Mountain Mapper; used at River Forecast Centers to downscale NCEP/HPC's QPF products over mountains), as well as those needed for the NWS Watch-Warning System (e.g., QPE SUMS; being tested at River Forecast Centers) and streamflow forecasting system (e.g., DMIP; a study to assess candidates for NOAA's next-generation streamflow forecast model).

HMT is linked to research activities external to NOAA, including partners in Joint Institutes, such as the "Water-in-the-West" effort at CIRES, and through interagency partners such as in the USWRP (e.g., the USWRP Cool-Season QPF Implementation Plan identifies establishment of a national HMT Infrastructure at NOAA as a leading priority) and USGS.