ECPC's current atmospheric forecast system was previously described by Roads et al. (1998a,b,c). At the largest space and time scales, ECPC’s atmospheric modeling system uses the National Centers for Environmental Prediction’s (NCEP’s) medium range forecast (MRF) model or global spectral model (GSM; Kalnay et al. 1996). A high resolution regional spectral model (RSM; Juang et al. 1994,1997; Chen et al. 1998; Anderson et al. 1998a,b), is nested within the global model by first integrating the GSM, which provides initial and low spatial resolution global model parameters for the RSM. A mesoscale spectral model (Juang 1998), which uses the nonhydrostatic equations, can then be nested within the RSM or can be initialized and bounded by the global model. The MSM is being used to display high-resolution products for the Hawaii Islands (see Roads et al. 1999 and http://www.mhpcc.edu/~wswx).

Several products from these global to regional and daily to seasonal forecasts are currently displayed at ECPC's site (http://meteora.ucsd.edu/ecpc/). Output includes products from the global (200-km), U.S. (50km), U.S. Southwest (25 km), and California (25 km) models. Products include a fire weather index (FWI, see Roads et al. 1997a,b) and associated variables such as 2m-temperature, relative humidity and 10m windspeed as well as precipitation and soil moisture for several regions. Since the atmospheric models are now forcing ocean and land surface models, we are also beginning to display surface water and energy forcings. Separate displays of weather (twice daily up to 7 days) and climate forecasts (weekly up to 12 weeks) are provided. For both the weather and climate forecasts, combinations (4xdaily for the weather forecasts and weekly for the 12 week forecasts) of all the latest forecasts can be seen in a virtual VCR.

As discussed by Roads et al. (1998b) the GSM provides more skillful forecasts of temperature, precipitation and fire weather index than persistence. (Soil moisture is forecast initially better by persistence.) Many additional forecasts need to be made. Because of the limited numbers of currently available forecasts, it is unlikely, at least after the first few weeks, that the dynamical forecasts are significantly better than the persistence forecasts. It is important that we eventually evaluate many additional years of forecasts to get the appropriate background climatologies for the pattern correlations. The climatology chosen here is the average over the forecast period. Additional years of forecasts could provide significant skill increases since particular years will have initialized states, which are significantly different than long term climatologies.

It should first be noted that there are a number of significant biases in the forecasts. Over the US there is a negative forecast temperature bias, on the order of a few degrees, that is comparable to the standard deviation of the temperature variations. This negative temperature bias is also reflected in a high relative humidity bias (forecast RH > than observed RH) and a low FWI bias (forecast FWI > analysis FWI). We are considering making an empirical correction to these forecasts. However, we should mention that with the introduction (beginning in July 1998) of NCEP's higher resolution global forecasts (T170L31), the forecast biases became much larger for both the GSM and the persistence forecasts. We are thus waiting to see if the systematic biases will decrease now that NCEP has moved back to the previous lower resolution analysis system. It should also be mentioned that our forecasts and skill evaluations will soon be moving toward the winter season and we may thus soon see other seasonal biases. Precipitation biases appear less sensitive to the NCEP resolution change, perhaps because precipitation has much less skill. Somewhat puzzling is that besides being less skillful, initial model soil moisture appears wetter than the corresponding analysis. Only with increased forecast time does the model dry out. Since we know that this forecast model has a tendency to dry (Roads et al. 1998a), we are a little worried now that the GSM may be drying out too much.

Separating out the systematic biases as well as evaluating the true forecast skill from a limited number of forecasts is frustrating and we have to be patient in developing evaluations from the still limited number of forecasts. However, despite the limited sample size, there are indications that there is limited forecast skill at long ranges. In particular, although the greatest skill occurs initially and then decays toward zero at long forecast ranges, daily or weekly or monthly forecast skill does not ever reach absolute zero and the residual weekly forecast skill when averaged into monthly and seasonal averages shows a skill level that may be significant and comparable to other long-range forecast methodologies.

Fig. 1 shows the anomalous FWI forecast (from the global model) for the U.S. for the period Aug. 29-Sept. 26 and Sept. 26-Oct. 24, 1998. Increased fire weather potential is found over the U.S. West. This increased potential is largely due to increased wind speed and reduced relative humidity (which can be seen at (http://meteora.ucsd.edu/ecpc/projects/ellfb). Temperature effects have less influence on FWI variations. The anomalies are calculated here with respect to the NCEP reanalysis anomalies (Kalnay et al. 1996) and could thus contain some influence of systematic forecast model bias. Eventually, the forecast bias of the model will be removed, which will provide a better forecast of anomalous values. Fig. 2 shows the anomalous soil moisture forecast for the U.S. for the same periods. The soil moisture anomalies are quite similar to the FWI anomalies. Windy and dry atmospheric conditions in the U.S. west correspond to dry soil moisture in these regions. Fig. 3 displays the precipitation anomalies, which are also similar to the forecast soil moisture and FWI in the US west. Above normal precipitation is indicated in the Canadian region. This increased precipitation is consistent with past La Ninas. However, this increased precipitation has not yet shown up in the model soil moisture which is still relatively dry in the Canadian region.

Anderson, B.T., J. O. Roads, S. -C. Chen, and H. -M. Huang, 1998a: Regional Modeling of the Low-level Monsoon Winds Over the Gulf of California and Southwest United States: Simulation and Validation, (submitted).

Anderson, B.T., J. O. Roads, S. -C. Chen, and H. -M. Huang, 1998b: Model Dynamics of Low Level Monsoon Winds and Surge Events over the Gulf of California and Northwest Mexico. (submitted).

Chen, S. -C., J. O. Roads, H. H. -M. Juang, and M. Kanamitsu, 1998 Global to Regional Simulations of California Wintertime Precipitation. J. Geophys. Res. (in press, precipitation special issue)

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 of AMS, 78,2125-2143.

Juang, H. –M., 1998: The NCEP Mesoscale Spectral Model. (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. Fujioka, M. Kanamitsu and H. Juang, 1997a: Global to Regional Fire Weather Forecasts, U.N. Int’l Decade for Natural Disaster Reduction. J. Goldammer, Ed.

Roads, J.O., S. -C. Chen, F.M. Fujioka, H. Juang, and M. Kanamitsu. 1997b. Global to Regional Fire Weather Forecasts. Int. Forest Fire News No.17, 33-37.

Roads, J. O., S. -C. Chen, M. Kanamitsu, H. Juang, 1998a: Surface Water Characteristics in NCEP’s Reanalysis and Global Spectral Model. J. Geophys. Res.-Atmos. (in press, special GCIP Issue)

Roads, J., Chen, S. -C., Ritchie, J., 1998b: Evaluation of the Experimental Climate Prediction Center’s Global to Regional and Daily to Seasonal Prediction System. Proceedings of the 23^rd Annual Climate Diagnostics Meeting. Miami, Florida

Roads, J., S. -C. Chen, J. Ritchie, 1998c: ECPC’s Weekly to Seasonal U.S. Forecasts of FWI, Soil Moisture, and Precipitation. ELLFB bulletin, Sept. 1998

Roads, J., S. Chen, D. Stevens, C. McCord, H. Juang, F. Fujioka, 1999: Weather and climate analyses and forecasts at MHPCC. Seventh International Conference on High Performance Computing and Networking. Amsterdam, The Netherlands, April 12-14, 1999.

Fig. 1. Monthly FWI anomaly forecast for the U.S. region for Nov. 28-Dec. 26, 1998 and Dec.26, 1998-Jan. 23, 1998.

Fig. 2 Monthly soil moisture anomaly forecasts for the U.S. region Nov. 28-Dec. 26, 1998 and Dec.26, 1998-Jan. 23, 1998.

Fig. 3. Monthly precipitation and vertically integrated moisture flux forecasts for the U.S. region for Nov. 28-Dec. 26, 1998 and Dec.26, 1998-Jan. 23, 1998.