Updated real-time website and new products for the 2015 hurricane season Kate Musgrave1, Christopher Slocum2, and Andrea Schumacher1 1CIRA/CSU, Fort Collins, CO 2CSU Dept of Atmospheric Science, Fort Collins, CO HFIP bi-weekly teleconference 09/09/2015 Acknowledgements: John Knaff (NOAA/NESDIS/StAR/RAMMB), Brian McNoldy (UMiami)

Outline CIRA/NESDIS HFIP Products Large-Scale Model Diagnostic Files Updated TC Real-time Site Large-Scale Model Diagnostic Files Hybrid Wind Speed Probabilities Satellite-based Model Evaluation Total Precipitable Water

CIRA/NESDIS HFIP Featured Products Large-Scale Model Diagnostic Files SPICE RII ECMWF SHIPS Real-time Graphics Real-time Verification Seasonal Verification SPICE  Hybrid Wind Speed Probabilities Real-time Graphics Seasonal Verification Satellite-based Model Evaluation Synthetic Infrared Real-time Graphics Real-time Verification Seasonal Verification Total Precipitable Water Synthetic Water-vapor

CIRA/NESDIS HFIP Real-time Product Delivery SPICE delivered to NCAR, and to CIRA ftp site Diagnostic text files delivered to HFIP Product Page Hybrid Wind Speed Probability Plots Model Inter-comparison Plots (GFS, HWRF, GFDL) delivered to HFIP Product Page, and to TC Real-time Page Diagnostic File Skew-T Log-p Plots (GFS, HWRF, GFDL) delivered to TC Real-time Page Diagnostic Storm-based Verification Plots (GFS, HWRF, GFDL) Model Field Animations (GFS, HWRF, GFDL) Blue: HFIP official repository Orange: CIRA public repository

CIRA/RAMMB TC real-time website http://rammb.cira.colostate.edu/products/tc_realtime/

CIRA/RAMMB TC real-time website http://rammb.cira.colostate.edu/products/tc_realtime/ …

CIRA/RAMMB TC real-time website http://rammb.cira.colostate.edu/products/tc_realtime/ Multi-model Diagnostic Plots Single-model Plots GFS, HWRF, GFDL Animation of innermost grid (10° x 10° TC-following box for GFS) Precipitation and SST 850 hPa Vorticity and Vertical Motion 10 m Wind Speed and SLP Diagnostic Skew-T Log-p Animation Diagnostic Verification

Future work with Website Updates Continue real-time product support for 2015 Add synthetic satellite imagery to TC real-time page Synthetic infrared and water-vapor imagery Total precipitable water imagery Evaluate transition of products to HFIP products page

Large-Scale Model Diagnostics

Large-Scale Model Diagnostic Files Purpose TC environment plays large role in intensity, structure Basis of SHIPS, LGEM intensity guidance Input required Model grib files u, v, T, RH, Z at mandatory levels 1000 to 100 hPa SST field if available Model storm track (ATCF format) Output Text file with SHIPS model predictors to 126 hr Code available from CIRA ftp://rammftp.cira.colostate.edu/musgravek/diagcode/ New version released May 2015 Verification GFS, HWRF and GFDL diagnostic files (against GFS analysis) Key parameters are calculated in prescribed areas... This is already done with GFS output to create SHIPS “predictor” files available on NHC's FTP server Sea surface temp (RSST) 850-200 mb shear (SHDC); 200 mb zonal wind (U20C) 200 mb temp (T200); 850-700 mb RH (RHLO) 700-500 mb RH (RHMD); 500-300 mb RH (RHHI) 200 mb divergence (D200); 850 mb vorticity (Z850)

Large-Scale Model Diagnostic Files Diagnostic files available from http://www.hfip.org/products/ Three sections: Storm Data, Sounding Data, and Custom Data Storm Data section contains: LAT, LON, VMAX, RMW, MSLP, shear magnitude and direction, TC speed and heading, SST, OHC, TPW, distance to land, 850 mb tangential winds and vorticity, and 200 hPa divergence Sounding Data section contains: U, V, T, RH, and Z at specified pressure levels, and surface U, V, T, RH, and P

Multi-Model Diagnostic Comparison Plots Model inter-comparison available from http://www.hfip.org/products/ Panel Design 5 panels: Intensity (top left) Track (bottom left) Deep-Layer Shear (850-200 hPa , top right) SST (middle right) Mid-Level RH (700-500 hPa , bottom right) Non-track panels show previous and next 5 days, centered at current time Vertical lines indicate the initial time of the most recent available forecast, color-coded by model Previous times are analysis values Track panel shows five day forecasts and recent best track Models Selected Intensity: GFS, HWRF, GFDL, DSHP, LGEM, OFCL, BEST Upcoming: SPC3 will be re-introduced Track: GFS, HWRF, GFDL, OFCL, BEST Deep-Layer Shear: GFS, HWRF, GFDL SST: GFS, HWRF, GFDL Mid-Level RH: GFS, HWRF, GFDL Purpose Provides overview of TC environment Comparison of model track, intensity, and basic dynamic and thermodynamic environment

Diagnostic File Skew-T Log-p Plots Purpose Provide vertical view of model TC environment Design Uses “Sounding Data” section of diagnostic files Highlight features not captured in multi-model comparison plots: Vertical wind shear not shown in 850-200 hPa shear calculation Dry layers not included in 700-500 hPa relative humidity Contains “Storm Data” variables in text box, for compact view of the diagnostics for an individual forecast time Animation of all forecast hours for each forecast cycle

Diagnostic Verification Plots Panels (CW from top left): Intensity, Deep-Layer Shear, Mid-Level RH, SST Dashed Line: RMSE; Solid Line: MAE (left-hand axis) Avg. track error indicated in MAE line shading [<100, 100 to 200, >200 nmi] Gray Shaded Bars: Bias (right-hand axis)

Future work with Model Diagnostic Files Implement upgraded diagnostic code at EMC Assess utility of current and new diagnostic-based products Provide Python code upon request Investigate verification metrics and guidance-on-guidance Update seasonal verification in late 2015 The seasonal verification code for the diagnostic files is being re-written to be consistent with the updated diagnostic file code includes support for all global basins includes an expanded parameter set incorporates the histogram code provided by Ryan Torn The updated verification code will be made available to the HFIP community

Hybrid wind speed probabilities

Hybrid statistical-dynamical wind speed probabilities Overview The Monte Carlo wind speed model estimates the probability of 34-, 50-, and 64-kt winds out to 5 days Generates 1000 realizations based on the official forecast by sampling from past official track and intensity errors and using a persistence and climatology radii model. Version of Monte Carlo wind speed probability model where the statistical track realizations are replaced with global model ensemble tracks Intensity and radii come from same method as statistical MC model Motivation: global model track models have been found to be well-dispersed, can they improve WSPs? (internal guidance, not meant to replace public product) Up to 133 tracks used: GFS (20), CMC (20), EMCWF (50), FNMOC (20), and UKMET (23)

Hybrid statistical-dynamical wind speed probabilities Status Available since 21 Aug 2012 for Atlantic, NE Pacific, and NW Pacific TCs Runs at 0 and 12 Z: Ensemble data latency differs (6-12 hrs), so provisional versions of hybrid WSPs are run using all data available Displayed in real-time on HFIP experimental products web page: http://www.hfip.org/products/, “Ensemble Model Output” tab

Hybrid vs. Statistical - Example Hurricane Isaac (2012) made landfall along the Louisiana coast at 0000 UTC 29 August Statistical: Largest coastal probabilities focused along FL panhandle Hybrid: Largest coastal probabilities smaller, spread from FL to LA

Hybrid vs. Statistical - Verification Sample: 2013-2014 (only full seasons hybrid WSPs have run) Overall, hybrid WSPs had improved Brier scores over the statistical version in all basins (although NE Pacific is marginal)

Future work with Hybrid WSPs Continue running in real-time for 2015 Display will remain on HFIP products webpage Update verification in early 2016 Improvements to statistical WSPs Update serial correlation method Incorporate intensity GPCE Investigate other hybrid approaches Preliminary work has begun on developing model-based WSPs that use forecasts and error statistics from global models

Total Precipitable Water (TPW)

Verification of large-scale HWRF synthetic total precipitable water Purpose: Environmental moisture plays a critical role in TC evolution Validate HWRF synthetic total precipitable water using the NESDIS operational blended product (Kidder & Jones 2007) Metrics: Mean absolute error (MAE) Mean bias Mean square error (MSE) skill score (SS) with climatology as a reference Potential extensions to work: Correlate MSE SS from the analysis to 24/48 hour intensity error Perform outlier analysis Comparison and difference plots and normalized histograms for each forecast. Kidder, S. Q., and A. S. Jones, 2007: A Blended Satellite Total Precipitable Water Product for Operational Forecasting. J. Atmos. Oceanic Technol., 24, 74–81.

Mean absolute error and bias for 2015 Atlantic and East Pacific HWRF model runs (12Z June 9 onward) calculated on a 40°x40° storm-relative box Relatively constant positive bias MAE grows with time Similar trend to 2014 season for parent grid and inner nest Atlantic E. Pacific

Shifting to a Mean Square Error Skill Score MAE and bias do not provide insight into the divergence in observations and forecast Correlation is unbiased by construct but forecasts are not Adding climatology tames spurious skill given to a forecast predicting climatology Phase association: Measure of forecast feature location, shape, and relative magnitude Conditional bias: Amplitude error Unconditional bias: Map error (bias) MSE SS: 1 = perfect; 0 = no skill;  – ∞   2 2 y = forecast o = observation s = std dev [ ]’ = [ ] - clim Livezey, R. E., 1995a. Field intercomparison. In: H. von Storch and A. Navarra, eds., Analysis of Climate Variability. Springer, 159-176. Livezey, R. E., 1995b. The evaluation of forecasts. In: H. von Storch and A. Navarra, eds., Analysis of Climate Variability. Springer, 159-176. Murphy, A. H., and E. S. Epstein, 1989: Skill Scores and Correlation Coefficients in Model Verification. Mon. Wea. Rev., 117, 572–582. Wilks, D.S., 2011. Statistical Methods in the Atmospheric Sciences, 563-582.

MSE SS with climatology for 2015 Atlantic: MSE SS rapidly deteriorates By forecast hour 90, Mean MSE SS < 0 Indication of more land influence and track deviations E. Pacific: Mean MSE SS stays positive Note: Violin plots are similar to box plots but include probability density. The marker denotes the mean. Atlantic E. Pacific

MSE SS term contributions Atlantic: Phase association (large = higher MSE SS) drops over forecast period indicating shape, location, relative magnitude differences Unconditional bias relatively steady East Pacific: Better phase association Small unconditional bias Atlantic E. Pacific

Potential application to guidance-on-guidance Can the 6 hr forecast MSE SS provide insight into intensity error? MSE SS potentially correlated to 48 hr intensity error in the Atlantic Weaker relationship in the East Pacific Outlier analysis may provide more insight Atlantic E. Pacific

Total precipitable water summary Conclusions: Atlantic and East Pacific HWRF model runs have a positive bias and increasing MAE MSE Skill Score contextualizes error sources Phase association dominates at early forecast hours Growing conditional biases at end of forecast Unconditional bias is a minor factor in the MSE SS Potential future applications: Explore using 6 hr forecast to provide guidance on guidance for the 24/48/72 hr intensity error Perform outlier analysis to identify what poor precipitable water initializations indicate

CIRA/NESDIS HFIP Products Large-Scale Model Diagnostic Files SPICE RII ECMWF SHIPS Real-time Graphics Real-time Verification Seasonal Verification SPICE  Hybrid Wind Speed Probabilities Real-time Graphics Seasonal Verification Satellite-based Model Evaluation Synthetic Infrared Real-time Graphics Real-time Verification Seasonal Verification Total Precipitable Water Synthetic Water-vapor

Questions?