IMPROVING HURRICANE INTENSITY FORECASTS IN A MESOSCALE MODEL VIA MICROPHYSICAL PARAMETERIZATION METHODS By Cerese Albers & Dr. TN Krishnamurti- FSU Dept. of Meteorology Objectives: Model Options Chosen- Dennis 2005 The main focus of this study is how improved microphysical parameterization in mesoscale models can positively affect intensity forecasting out to 48 hours while more accurately simulating the real storm environment. Recognizing the many facets involved in intensity prediction, what is shown here is a procedure, and by no means a final solution. The same options were chosen for Dennis 2005, the only difference is: Timestep= 12 sec. and Grid size: Outermost domain: 25km; Middle domain: 8.3km; Innermost domain: 2.7km Final Microphysical Parameterization Coefficients Selected Running and Post-Processing Each Experiment Erin: Melting of Snow= Red. by 25% Melting of Graupel= Red. by 75% Evaporation of Rain Water= Red. by 25% Fall Speed of Snow= Red. by 50% Fall Speed of Graupel= Red. by 25% No alteration to graupel intercept parameter: remains =4.e6 Datasets: Each of the 36 total experiments was run for a full uninterrupted 48 hours. Model output was generated and processed by the WRF2GrADS post-processing package. To accurately compare each microphysical parameterization experiment, key benchmarks are used to determine the best runs from the rest: Simulated Storm Intensity plotted for Predicted Sea Level Pressure (slp) Predicted 10-meter Surface Winds (magnitude of u10 & v10) Root Mean Square Errors (as compared to FNL) for Slp and mag(u10;v10) Anomaly Correlation for Intensity based on All were produced 6-hourly for every experiment, as well as for the control runs which did not include any alterations to mp. The datasets for the initial state and time-varying boundary conditions for the numerical experiments were obtained from the NCEP FNL analyses for the respective model domains for Erin(2001) and Dennis(2005). They are Global Final Analyses available from NCEP-NCAR at one degree grids every 6 hours. HWIND datasets for comparison of the structural characteristics of the model-produced surface wind speed. Dennis: Melting of Snow= Red. by 75% Melting of Graupel= Red. by 50% Evaporation of Rain Water= Red. by 25% Fall Speed of Snow= Red. by 75% Fall Speed of Graupel= Red. by 75% No alteration to graupel intercept parameter: remains =4.e6 NASA TRMM 3B42 GSFC obtained datasets of gridded 3-hourly rain-rate estimates at a horizontal resolution of 0.25° X 0.25° in a global latitude expanse from 50.0°N to 50.0°S. These datasets were interpolated for every 1-min interval, the time step of the WRF model, for the 24 hours of RRI. Later these data sets were averaged over a 24 hour period and used for observational comparisons to model forecasts. Hurricane Erin Intensity- 48 Hour Forecast Period Analysis Track Microphysical Parameterization Experimentation Methodology Pressure (hPa) v. Day & Time (UTC) Max Winds (m/s) v. Day & Time (UTC) A few studies have found that alterations to particular species of hydrometeors have impacts, large and small, on the intensity, structure of precipitation and vertical make-up of a hurricane. It has been shown that there is a need for improved microphysical parameterization, which is a proven factor of intensity prediction. First Rain Rate Initialization is applied for the 24 hours prior the model forecast start time. The initialized WRF model is allowed to spin up (on average takes about 12-18 hrs to have a good degree of skill) and produce a simulated storm for Erin or Dennis for 48 hours, with only one microphysical parameterization altered at a time in the WSM 6-class graupel scheme. These alterations take place according to the following table: Best Combination for Each Storm is Chosen First the experiment resultant slp is computed and plotted against the control run, and NHC values. Based on how it performs during the maturation and intensification stages of the hurricane, with respect to the other runs and observations, it is decided if this is a potential candidate for the OPTMP run. Next the simulated hurricane’s resultant intensity values for slp and winds at 10 m are subjected to skill score testing. The RMSE and ANOMCOR values are grouped by experiment series number (ex. Experiment Series 1 varied reduction of the melting of snow in the model), and evaluated for the lowest RMSE and highest ANOMCOR values in each category. The best-performing experiment, in terms of these intensity guiding parameters, is chosen to be simulated in the OPTMP run. Hurricane Dennis Intensity- 48 Hour Forecast Period Analysis Track Pressure (hPa) v. Day & Time (UTC) Max Winds (m/s) v. Day & Time (UTC) Parameters are chosen & altered based on prior literature studies. For example, notice there is no 100% reduction of a variable because this is not physically realistic in a hurricane. Selected Results HWIND v. Simulated Winds (kt)at 10m for Hurricane Erin Sept. 09 ~18:00 UTC This set of figures shows the RMSE and Anomaly Correlations for Hurricane Erin in the top figures for slp and winds, while the bottom figures show ETS for Erin and Dennis on Day 2 Model Options Chosen- Erin 2001 Run time = 48 hours: 0000 UTC Sept 09 through 0000 UTC Sept 11, 2001 Timestep = 60 sec. Grid size: Outer domain: 25km Inner domain: 5km Options/Schemes chosen: WSM 6-class graupel scheme, Longwave (RRTM) scheme, Shortwave Radiation Dudhia scheme, Surface-layer Monin-Obukhov (Janjic) scheme, Land-surface thermal diffusion scheme, Boundary-layer physics: Mellor-Yamada Janjic TKE scheme, Cumulus Option 0 for Innermost domain- turned off b/c <10km, N-down option between domains and inclusion of nested boundary conditions Variations in parameterizations to WSM 6-class graupel mp scheme: Melting of Snow, Melting of Graupel, Evaporation of Rain Water, Fall Speed of Snow, Fall Speed of Graupel, Intercept Parameter for Graupel Hurricane Erin 24 Hr Accumulated Rainfall: Simulated v TRMM CTRL OPTMP TRMM 24 Hour totals show that the model tends to overestimate the total precipitation. However, the OPTMP better simulates the location of the rainfall avg center and total area than the CTRL run (tilt). ETS =