ECPC's Mar. 2000 Forecasts

contributed by J. Roads, S. Chen, J. Ritchie

Experimental Climate Prediction Center Scripps Institution of Oceanography

UCSD, 0224 La Jolla, CA 92093

1. ECPC's Global to Regional Atmospheric Forecast System

As previously discussed by Roads et al. (1999b), the Scripps Experimental Climate Prediction Center (ECPC) currently uses the reanalysis I version (Kalnay et al. 1996) of the National Centers for Environmental Prediction's (NCEP's) medium range forecast (MRF) model or global spectral model (GSM; Roads et al. 1999a). These global forecasts (4xdaily-7 days and weekly to 12-weeks) start from the NCEP operational 00UTC global analysis. The GSM then forces a regional spectral model (RSM; Juang and Kanamitsu, 1994; Juang et al. 1997; Chen et al. 1999, Anderson et al. 1999, Roads and Chen 2000) in order to gain increased spatial resolution (50-25 km resolution) at shorter time scales (4xdaily-7 days and weekly to 4-weeks) for several selected regions (US, CA, SW, Brazil). At even smaller space (2-km resolution) and time scales (8xdaily to 2 days) either the NCEP analysis or GSM can force a corresponding nonhydrostatic mesoscale spectral model (MSM; Juang 1999) for the Hawaiian Islands (Stevens et al. 1999). All atmospheric models are based upon the same physics used in the GSM and can, in principle, be updated as the GSM is updated. Output products from the atmospheric models include a fire weather index (FWI, see Roads et al. 1997) and associated variables such as 2m-temperature, relative humidity and 10m-windspeed as well as precipitation and soil moisture. Since the global and regional atmospheric models are now forcing an ocean model (Auad et al. 1999), forcings and corresponding output from the ocean model will be presented in later ELLFB issues. Land models are also being developed.

2. Preliminary Forecast Skill Evaluations

Two years worth of forecasts (104 forecasts) have been used to develop a GSM forecast climatology dependent upon season as well as lag. This ensemble of forecasts has also been used to evaluate forecast skill. As discussed by Roads et al. (2000), the GSM provides more skillful forecasts of temperature, precipitation, soil moisture, and a fire weather index than persistence, even at long forecast ranges. Although the greatest skill occurs initially and then decays toward zero, daily, weekly or monthly forecast skill does not ever reach zero and forecasts averaged into monthly and seasonal averages demonstrate significant skill, which may be comparable to other long-range forecast methodologies. Similar evaluation efforts are underway for the regional forecasts, which currently use the GSM to start the forecasts and the GSM climatology to derive approximate regional anomalies.

3. Mar. 1 Global Seasonal and US March RSM Forecasts.

Fig.s 1a, 1b ,2a, 2b, 3a, 3b, 4a, 4b,show the GSM seasonal anomaly forecast for Mar.-May 2000 along with the corresponding RSM monthly anomaly forecast for Mar. 2000 of 2-m surface temperature, precipitation, soil moisture and the FWI. It should be noted that both the GSM and the RSM use the same GSM climatology to calculate the anomalies, which may have a deleterious effect on the RSM anomalies discussed below. We are therefore currently trying to develop a more suitable RSM climatology for the RSM simulations to be used in future ELLFB forecasts.

Above normal temperatures (Fig. 1a, 1b) are expected for most places in the Northern Hemisphere, especially in Canada and Russia, along with the lower tropical temperatures which are consistent with the Pacific La Niña. Although somewhat lower temperatures occur over the US West in the RSM, we do expect a somewhat cold RSM bias when using this lower elevation large-scale climatology.

GSM seasonal and RSM monthly precipitation forecasts (Fig. 2a, 2b) have some characteristic features of a cold tropical episode, including below normal precipitation in the tropical Eastern Pacific and above normal precipitation in the tropical western Pacific and western Amazon. The tropical Indian Ocean shows a strong dipole with increased precipitation to the north and decreased precipitation to the south over Madagascar. Over the US, above normal precipitation is expected in the Ohio River Valley. This above normal precipitation is more intense over the Pacific coast and Appalachian range during March in the RSM. In both the GSM and RSM forecasts, dry anomalies are expected over the Rocky Mountains and US Southeast.

Soil moisture (Fig.3a, 3b) is generally coincident with the global and US precipitation anomalies, which reflects the strong influence of precipitation on soil moisture as well as potential feedbacks by the soil moisture on precipitation. Many potential drought areas in the US southeast, southern Brazil, and central Africa are indicated.

The FWI (Fig. 4a, 4b) is generally coincident with the precipitation and soil moisture over the western Amazon, northern Australia, China, Afghanistan. Over the US, the FWI is relatively high along the Rocky Mountain Front Range and low over the Rocky Mountains during March. Again, this RSM pattern may be affected by our use of our GSM climatology, which we will eventually replace with an RSM climatology.

Other experimental GSM and RSM forecast fields (wind speed, relative humidity) and additional forecast months) can be found at http://ecpc.ucsd.edu/projects/ellfb/. Other forecast ranges and regions can be found at http://ecpc.ucsd.edu/m2s/m2s_ECPC_forecasts.html.

References

Anderson, B.T., J. O. Roads, S. -C. Chen, and H. -M. Huang, 1999: Regional Modeling of the Low-level Monsoon Winds Over the Gulf of California and Southwest United States: Simulation and Validation, (submitted).

Auad, G., J. Roads, A. Miller, D. Cayan, W. White, 1999: Comparison of wind stresses and surface heat fluxes from the COADS, FSU and NCEP data sets. (submitted)

Chen, S.-C., J.O. Roads, H.-M. H. Juang, M. Kanamitsu, Global to regional simulation of California's wintertime precipitation. J. Geophys. Res., 104(24), 31517-31532, 1999.

Juang, H. -M. H., and M. Kanamitsu, 1994: The NMC nested regional spectral model. Mon. Wea. Rev., 122, 3-26.

Juang, H.-M. H., S.-Y. Hong and M. Kanamitsu, 1997: The NCEP regional spectral model: an update. Bulletin Amer. Meteor. Soc., 78, 2125-2143.

Juang, H. -M. H., 1999: The EMC/NCEP mesoscale spectral model: A revised version of the nonhydrostatic regional spectral model. Mon. Wea. Rev., submitted.

Kalnay, E. et al., 1996: The NMC/NCAR reanalysis project, Bull. Am. Meteor. Soc., 77, 437- 471, 1996.

Roads, J.O., S. -C. Chen, F.M. Fujioka, H. Juang, and M. Kanamitsu. 1997. Global to Regional Fire Weather Forecasts. Int. Forest Fire News, 33-37.

Roads, J., S. Chen, M. Kanamitsu, H. Juang, Surface water characteristics in NCEP global spectral model reanalysis. J. Geophys. Res., 104, 19307-19327, 1999a.

Roads, J., S. -C. Chen, J. Ritchie, 1999b: ECPC's Weekly to Seasonal U.S. Forecasts of FWI, Soil Moisture, and Precipitation. ELLFB bulletin, Dec. 1999

Roads, J. and S. Chen, 2000: Surface Water and Energy Budgets in the NCEP Regional Spectral Model. J. Geophys. Res. (to be accepted)

Roads, J., Chen, S. -C., Ritchie, J., 2000: Evaluation of the Experimental Climate Prediction Center's global forecasts. (in preparation)

Stevens, D. D. Funayama, J. Roads, S. Chen, W. Smith, C. McCord, H. Juang, F. Fujioka, 1999: Experimental short-term weather forecasts for Hawaii. MHPCC application briefs 1999. (Available from MHPCC, Kihei, Maui, HI 96753), 19.

Fig. 1a, 1b, Temperature (C) anomalies: (upper) Mar.-May GSM forecast anomalies: (lower) Mar. RSM forecast anomalies.

Fig. 2a, 2b, Precipitation (mm/day) anomalies: (upper) Mar.-May GSM forecast anomalies: (lower) Mar. RSM forecast anomalies.

Fig. 3a, 3b, Soil Moisture anomalies: (upper) Mar.-May GSM forecast anomalies: (lower) Mar. RSM forecast anomalies.

Fig. 4a, 4b, FWI anomalies: (upper) Mar.-May GSM forecast anomalies: (lower) Mar. RSM forecast anomalies.