# Presentation: 865655

## APRFC NCEP WX MODEL PROJECT	

- David Streubel and Larry Rundquist
- Alaska Pacific River Forecast Center

## APRFC Objectives

- Assess the value of using NCEP operational models (ETA & GFS) for observed and forecast data within NWSRFS basins in Alaska.
- Evaluate the use of NCEP reanalysis data in the NWSRFS calibration process; specifically determine whether its use provides an unbiased procedure for introducing NCEP data operationally into NWSRFS.

## Previous Work

- Clark et Al. (2004) developed statistical downscale procedure for use with reanalysis 2m temperature and precipitation data and ran a USGS runoff model.
- Significant bias was found with the reanalysis precipitation data and to a lesser extent with the 2m temperature data when compared with observed.
- Temperature driven hydrologic events such as snow melt performed better than precipitation dominated processes.
- CBRFC developed methods in conjunction with Clark et al (2004) to use reanalysis data to create ensembles of 14 day forecasts.  Ongoing project
- Hagemann & Gates (2001) used data from the ECMWF reanalysis project to force a rainfall runoff model.

## What is Reanalysis Data?

- Time series data generated from the NCEP reanalysis project using 1995 frozen MRF model.
- Time series of most major operational model parameters in 6hr or 24hr format since 1948.
- Grid is 1.9 – 2.5 degrees.

## NCEP Operational WX Model Data

- The GEMPAK analysis package supported by UCAR is used for real time extraction of GFS and ETA model output.
- Model run times: GFS 6hrs - ETA 12 hrs
- Data is interpolated by GEMPAK decoders and scripts are used to put data into SHEF for use in NWSRFS.

## Temperature is Initial Focus Area

- Concentrate on extreme snow and ice melt events in data sparse basins.
- Evaluate the effects of including reanalysis temperature data at 700MB, 850MB, Surface, and 2M in the calibration process and its benefit.
- Introduce operational ETA and GFS as both observed and forecast data if confident that significant bias is minimized by using reanalysis data in calibration process.

## Tanana River Basin 

**Tanana River Basin **

- Upper basin 19400 mi^2
- Elevation Range is from 400 to 16390 feet
- 11 real time temperature gauges in basin all below 2700 feet.
- Significant component of water balance is glacier melt.
- Poor simulation  in unusual weather events

## 2004 Lapse Rate Example

**2004 Lapse Rate Example**

## Temperature Bias

- ETA-GFS and reanalysis data bias small
- “Free Air” vs ground temperature bias larger

## Temperature Bias Cont.

**Temperature Bias Cont.**

- GFS-ETA-Reanalysis have significantly less diurnal fluctuations than HRDA2 ground observations.
- Model derived temperatures follow observed relatively well but amount of departure is seasonally dependent.

## Potential Use of Precipitation Data

- Precipitation bias is large when comparing NCEP model, reanalysis, and observed data sets.
- Clark et al (2004) found precipitation bias as “severe” when comparing reanalysis data with observed data and implemented a downscaling procedure to help.

## Precipitation Bias

**Precipitation Bias**

- Usually large accumulation bias are present between models and reanalysis data.
- Timing errors are very dependent on location and season.
- Downscaling methods need to be implemented.

## Conclusions or Initial Thoughts...

- We are just getting started...
- In basins with limited low elevation station data the inclusion of NCEP model temperature data should help during extreme events when standard lapse rates do not apply.
- NCEP reanalysis data likely needs to be included in calibration process of NWSRFS in order to reduce bias when NCEP model data is used operationally .
- Methods for downscaling reanalysis data need to be investigated further

## References

- Clark, M.P., and L. E. Hay 2004.  Use of Medium Range Numerical Weather Prediction Model Output to Produce Forecasts of Streamflow.  The Journal of  Hydrometeorology  5:15-32.
- Hagemann, S., and L. D Gates, 2001.  Validation of hydrological cycle of ECMWF and NCEP reanalyses using the MPI hydrological discharge model.  The Journal of Geophysical .Research 106 D2:1503-1510.