The real-time Arctic MM5 modeling system: Characteristics and performance for short-range Alaska regional and local forecast applications

Over the past year, we have developed an integrated experimental real-time mesoscale modeling and forecast system based on the so-called ‘Arctic MM5’ developed in-house over the past year. The integrated system ingests Alaskan meteorological observations plus NCEP Eta-model analyses twice daily in real-time and incorporates this data into a quintuple-grid hierarchy of numerical forecasts. The forecasts extend to a maximum duration of 39 hours and utilize a minimum grid resolution of 5 km over local domains encompassing Fairbanks, Anchorage, and Barrow-ARM/CART. Post-processed products include an integrated aircraft icing forecast algorithm that also incorporates observed data of numerous types, and other aviation impact variables.

The intent of the system is to provide additional short-range forecast information to not only NWS forecasters, who receive the forecast data in a format suitable for ingestion into AWIPS, but also to the Alaska transportation department, other state agencies, and the general public at-large. As such, our system is deliberately designed as an enhancement to, rather than a substitute for, existing NWS information, and focuses on Web-based forecast product delivery.

The real-time system provides an appropriate platform for in-depth evaluation of the adequacy of the Arctic MM5 as well as changes to the model configuration developed in our ongoing NWP research efforts. As part of the real-time system, we have implemented verification routines based upon domain-averaged skill score statistics, similar to those presented at the 2001 polar conference (e.g., RMSE, bias, S1 skill score, etc.).

In our presentation, we will describe the characteristics of the real-time system in detail, including improvements/changes not yet implemented at the time of this writing. We will also discuss the short-range forecast performance of the modeling system on the various scales, including changes in performance resulting from incorporation of new physical parameterizations/processes. Strengths and weaknesses of the current system will be highlighted using selected forecast examples.