# Presentation: 515334

## The NOAA Hydrometeorological Testbed and theNWS Office of Hydrologic Development

**David Kitzmiller, Michael Smith,**
**Pedro Restrepo, Dong-Jun Seo**

- Hydrology Laboratory
- Office of Hydrologic Development

- NOAA National Weather Service
- March 3, 2004

## OHD efforts related to the NOAA HMT:

- Distributed Hydrologic Modeling
- Snowpack Modeling
- Precipitation Estimation
- Multisensor analysis
- Remote sensing
- Rain gauge observation quality control
- Surface Radiation Budgets
- Soil Moisture Estimation
- Data assimilation
- Combined River/Estuary Modeling
- Ensemble and Probabilistic Streamflow prediction

## DMIP 2 and HMT

- An exciting linkage providing:
- Multi-institutional evaluation of HMT data products in an end-to-end test
- Advanced data products for evaluating important science questions for RFC river forecasting
- soil moisture
- precipitation
- streamflow

**Notes:**
The linkage of DMIP and HMT is a win-win situation for both. DMIP gets high quality data, and HMT gets a multi-institutional evaluation in an end to end test. Thus, DMIP will allow HMT to know how much its new data improves model simulations in an unprecedented manner.

## Phase 2 Scope

- Intercomparison
- Project (DMIP)

_**Additional Tests in DMIP 1 Basins**_
- Routing
- Soil Moisture
- Lumped vs. Distributed

_**Tests with Complex Hydrology**_
- Snow, Rain/snow events
- Soil Moisture
- Lumped vs. Distributed

**ETL HMT**

**Notes:**
The second phase of DMIP proposes to use the North Fork of the American River as one of its test basins. DMIP 2 will also contain additional tests on the basins forming DMIP 1. 

 ETL HMT data collection activities will be an exciting component of DMIP 2.  Also, HMT will benefit from a multi-institutional evaluation of HMT products in an end-to-end fashion. 

## Precipitation Analysis and Assimilation

- The California/Nevada observational testbed will provide valuable ground-truth observations for comparison with operational remote sensing systems
- The impact of improved, high-resolution radar and gauge observations on modeling and prediction of streamflow will be assessed
- Methods for automated quality control will be tested

**Notes:**
Precipitation includes snow, soil moisture...

## CNRFC 24-Hour Precipitation 17 Dec 2002

- Gauge Only

- Gauge-Radar-Hydroestimator

## Ensemble Streamflow Prediction

- Ensemble streamflow prediction requires knowledge of statistical properties related to spatial distribution of temperature and precipitation
- High-resolution observations from HMT could provide valuable information on small-scale variability in this meteorological forcing

## Future Ensemble Streamflow Prediction System with Data Assimilation and Explicit Uncertainty Processors

**Notes:**
For uncertainty in initial conditions, must know both mean and distribution for input temperature and precipitation to a high degree of reliability.

## Modeling of the Tar Basin River-Estuary System

- Ongoing effort to estimate precipitation, runoff, river channel flow, and river-estuary interactions in the Tar River Basin of North Carolina
- Joint effort among NSSL, NCSU, NOAA NWS
- Major goals are refinement of multisensor precipitation algorithms, river channel model, estuary model
- Experiments will benefit from intensive observations in the testbed area; models can provide validation of observations

## Channel Routing 

- Channel Routing
- and
- Flood Mapping
- Of Tar River below
- Rocky Mount

- QPE-SUMS
- Rainfall Data

- Distributed
- Model of Tar
- River Basin

- rain depth

- Tarboro

- Estuary Model

- Rocky
- Mount

**Notes:**
Basic purpose of project is to show linkage of models
QPESUMS data will be generate on a grid and used a direct input to the distributed model
The distributed model will be set up over entire Tar Basin Domain. It will generate lateral inflows for direct input into the Flood Wave model. This is a new and important development: a distributed model directly linked to an advanced channel routing model in an operational setting. Very few instances of this as far as I know.
The Flood Wave model will be able to generate flood inundation maps for the Tar River Below Rocky mount. Flood Wave will have a two way linkage to the Estuary model.  Floodwave provides flows into the Estuary model, while the Estuary model provides the down stream boundary condition for Flood Wave. 

## Summary

- OHD has carried out extensive intercomparisons of hydrologic models, precipitation estimation systems, and remote sensing systems
- Inhouse expertise will be devoted to evaluation of observations from HMT systems

**Notes:**
Some evaluation might also be carried out with university collaborators

## Estimates of Freezing Level Height and Surface Precipitation Type

- Particularly in mountainous terrain, real-time estimation of freezing level height and snow level are crucial to effective modeling of runoff
- Profiler and WSR-88D observations can provide physical evidence of level at which snow begins to melt, and lowest level at which precipitation remains frozen

## WSR-88D and Profiler

**WSR-88D and Profiler**
**Estimates of Freezing**
**Level Height**

- Circles: Profiler    Crosses: WSR-88D
- Upper figure: SNR
- Lower figure: vertical velocity
- Data from Astoria OR profiler and Portland OR WSR-88D
- 28 Jan 2004

**Notes:**
WSR-88D estimates based on areal-mean vertical profile of reflectivity
Thanks to Allen White for profiler data and figures.