# Presentation: 487598

## NCEP Production Suite Review  NOAA/NWS Alaska Region 

- NCEP Production Suite Review  NOAA/NWS Alaska Region

- Carven A Scott
- Chief, Environmental Scientific Services Division
- Alaska Region Headquarters

## Topics

- Comments
- GFS
- RTMA
- Local Modeling

## Comments

- ECMWF – Similar experiences to CR and ER. The field reports that the ECMWF's skill appears to be superior to both the GFS and NAM.
- GFS 06Z/18Z runs – As with SR, AR field offices would prefer to eliminate the runs, or eliminate distribution on the SBN.
- NAM – Real issues beyond 36 hours, especially with systems in the southwest and west portions of domain. Often accelerates lows and frontal systems.

## Comments

- Short Range Ensembles (SREF)  - Problematic in the mountainous West. The 13 km NAM-WRF cannot adequately capture many terrain details.  The lower resolution SREF does even more poorly.
- The models cannot resolve most of the valleys, and the downslope and channeled flow effects in the narrow valleys.
- Thus all the ensemble members may forecast precipitation at a given valley locations in moist southwest flow leading to guidance that indicates a 100% chance of precipitation.  Yet, in reality the valleys may only have a 20-30% chance of precipitation.
- A general example from IC4D.  We receive SREF ceiling/cloud top/visibilities products based on the ensemble means.
- Given the difficulties and unknowns in modeling moisture, especially in the boundary layer over water/ or land in winter, the ceiling grids in particular forecast ceilings that are often much too low.
- All the ensemble members show this same error.  The error is partly due to errors in modeling moisture, and due to unknowns in formulating the algorithms to calculate these fields.

## GFS – Cold Bias

- Cold surface temps “polluted” GFS surface temp grids for two years (fix in January 2009?)
- GFS appears to erroneously sense there are glaciers (or some other permanently snow-covered surface) in certain areas.
- It’s not an issue in the winter since there is snow in those locations. However, in the summer these places fail to warm up, with the following consequences to our operations:
- GFS temperature grids are difficult to use in the GFE.
- The bias corrected grids are less problematic, but still does not completely cure the problem.
- A variety of other temperature dependent fields (such as RH, CAPE, BL, etc.) are also “polluted”.

## GFS – Cold Bias

## Alaska RTMA

- An NCEP-AR success story! Several iterations since initial introduction. RTMA is now a part of forecast operations. Still a work in progress (marine environment).
- RTMA performance seemed better during the night (05z-13z) than day (14z-04z) as compared to the MatchObs errors.
- No significant differences based upon elevations (since 1000ft could correspond to a top of a hill or a broad valley).
- Broad plains tend to have minimal variations between RTMA and MatchObs as compared to steep terrain locations.
- No experience with the parallel version.

## Local Modeling - WFO AnchorageWRF

- Local Modeling - WFO AnchorageWRF

- A varied-model multianalysis ensemble up to 18 members at an 8km resolution out to 36 hours, producing guidance twice a day.
- Purpose is to provide insight into model variance at the mesoscale in complex terrain.
- Generate ensemble spread and statistics for D2D.
- Promising research (U of W).
- Utilize the ensemble mean to initialize and nudge a high resolution (nested 2 km/1 km) deterministic run.
- Varying perturbation schemes via physics packages.
- Working towards a GFE procedure that will provide detailed ensemble statistics such as a correlation between ensemble spread and forecast error, variance, and some measure of forecast probability that will allow us to give the probability that an event will occur.

## Local Modeling – WFO AnchorageAnchorage -Turnagain Arm

- Local Modeling – WFO AnchorageAnchorage -Turnagain Arm

## Local Modeling – WFO AnchorageSWAN

- Local Modeling – WFO AnchorageSWAN

- Problem: Forecasting sea state at Kennedy Entrance
- Solution: High Resolution SWAN Model driven by a high resolution atmospheric model.
- Ingesting WWIII (AKWAVE) for nudging and initialization
- High Resolution WRF (2 km)
- Tide and current data
- High resolution bathymetry

## Beaufort Sea Mesoscale WRF

**Beaufort Sea Mesoscale WRF**

- The University of Alaska, Fairbanks (Dr. Jing Zhang and Don Morton) have been working on improving the WRF for the Beaufort and Chukchi seas.
- Specifically land use, air-ocean-sea ice coupling.

## A new WRF/Chem Wildfire Smoke Forecast System for Alaska

- Carven Scott1 and Martin Stuefer21: Chief, Environmental and Scientific Services Division    NOAA/NWS Alaska Region Headquarters2: GEOPHYSICAL INSTITUTE &    ARCTIC REGION SUPERCOMPUTING CENTER    UNIVERSITY OF ALASKA FAIRBANKS**International Air Quality Advisory Board****Expert Consultation **Anchorage, September 2008

**A new WRF/Chem Wildfire Smoke Forecast System for Alaska**

- A development at the University of Alaska, _Arctic Region Supercomputing Center_ in collaboration with _Georg Grell_ from the Global System Division, NOAA, _Saulo Freitas_ from the Brazil Center for Weather Forecasting and Climate Studies (CPTEC/INPE) and the US Forest Service (USFS) Fire Sciences Lab in Missoula

## Questions?