The Impact of Dropsonde Data from Dotstar on Tropical Cyclone Track Forecasting
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11A.3 THE IMPACT OF DROPSONDE DATA FROM DOTSTAR ON TROPICAL CYCLONE TRACK FORECASTING Kun-Hsuan Chou1, Chun-Chieh Wu1, * and Po-Hsiung Lin1, Sim Aberson2, Melinda Peng3, Tetsuo Nakazawa4 1Dept. of Atmospheric Sciences, National Taiwan University, Taipei, Taiwan 2Hurricane Research Division, NOAA/AOML, Miami, Florida, USA 3Marine Meteorology Division, Naval Research Laboratory, Monterey, CA 4Meteorological Research Institute, Japan Meteorological Agency, Tokyo, Japan Abstract 1 the track forecast improvement in Atlantic tropical cyclones from surveillance missions. In DOTSTAR, short for Dropwindsonde all, despite the limited number of DOTSTAR Observations for Typhoon Surveillance near the cases in 2004, the overall added value of the Taiwan Region, is an international research dropwindsonde data in improving typhoon track program conducted by meteorologists in Taiwan forecasts over the Northwestern Pacific is partnered with scientists at the Hurricane proven. Research Division (HRD) and the National Centers for Environmental Prediction (NCEP) of the National Oceanic and Atmospheric 1. Introduction Administration (NOAA). The DOTSTAR Taiwan is severely affected by typhoons research team launched their typhoon frequently, and the loss of life and property has surveillance in 2003. During 2004, 10 missions been staggering. Prompted by the National for 8 typhoons were conducted successfully with Science Council's (NSC) sense of social 155 dropwindsondes deployed. In this study, responsibility and its emphasis on typhoon the impact of the dropwindsonde data on tropical research, atmospheric scientists in Taiwan in cyclone track forecasts has been evaluated with July, 2002, initiated an interagency research five models (4 operational and 1 research). project on typhoons, the “National Priority All models, except the Geophysical Fluid Typhoon Research Project.” One key part of Dynamics Laboratory (GFDL) hurricane model, this project involves a field experiment, show positive impact the dropwindsonde data Dropwindsonde Observations for Typhoon have on tropical cyclone track forecasts. Surveillance near the Taiwan Region During the first 72 h, the mean track error (DOTSTAR), marking the beginning of an era of reductions in the NCEP Global Forecast System tropical cyclones surveillance in the western (GFS), the Navy Operational Global North Pacific using GPS dropwindsondes. An Atmospheric Prediction System (NOGAPS) of overview of DOTSTAR is provided in Wu et al. the Fleet Numerical Meteorology and (2005), and targeted observing strategies are Oceanography Center (FNMOC) and the discussed in Wu et al. (2006a). The detailed Japanese Meteorological Agency (JMA) Global results of this work are also shown in Wu et al. Spectral Model (GSM), are 14, 14, and 19%, (2006b). respectively. The track error reduction in the DOTSTAR is a collaboration between Weather Research and Forecasting (WRF) researchers from the National Taiwan University model, in which the initial conditions are directly (NTU) and the Central Weather Bureau (CWB), interpolated from the operational GFS forecast, in partnership with scientists at the Hurricane is 16%. However, the mean track improvement Research Division (HRD) and the National in the GFDL model is a statistically insignificant Centers for Environmental Prediction (NCEP), 3%. The 72-h average track error reduction both part of the National Oceanic and from the ensemble mean of the above three Atmospheric Administration (NOAA), built upon global models is 22%, which is consistent with work pioneered by HRD to improve tropical cyclone track forecasts (Aberson 2003; see more detailed review in section 2). To make the * Corresponding author address: Chun-Chieh, Wu, Dept. of Atmospheric Sciences, National Taiwan maximum use of the DOTSTAR data, they are University, No. 1, Sec. 4, Roosevelt Rd., Taipei, 106, transmitted and assimilated in real time into the Taiwan. E-mail: [email protected] numerical models of CWB, NCEP, the U.S. 1 Navy’s Fleet Numerical Meteorology and throughout the troposphere and over a larger Oceanography Center (FNMOC), and the geographical area than previously available. Japanese Meteorological Agency (JMA). Since 1997, the G-IV has made dropwindsonde With the experience gained from the observations when a TC threatens coastal areas successful first two surveillance flights for of the U.S. in the Atlantic basin, Hawaii, or Typhoons Dujuan and Melor in 2003 (Wu et al. southern California. Along with these 2005), DOTSTAR conducted 10 more enhancements, new satellite measurements and surveillance missions for Typhoons Nida, improved understanding of the atmosphere have Conson, Mindulle, Megi, Aere, Meari, Nock-Ten, resulted in further reduction in TC track error in and Nanmadol in 2004 and released 155 the operational NOAA models. dropwindsondes. The observation time, With the use of the GPS dropwindsondes, position and intensity of the observed tropical the accuracy of wind observations is greatly cyclones are summarized in Table 1, and the enhanced as compared to previous technology best tracks are shown in Fig. 1. The impact of (Hock and Franklin 1999). The first-year result the dropwindsonde data obtained during 2004 with the G-IV surveillance in 1997 revealed that on global numerical models from three GPS dropwindsonde observations improved the operational centers (NCEP, FNMOC, and JMA) Geophysical Fluid Dynamics Laboratory (GDFL) is evaluated. The impact on two other regional track and intensity forecasts by as much as 32% models, i.e. the GFDL hurricane model (Kurihara and 20%, respectively, in the period within 48 h et al. 1998; Wu et al. 2000) and the Weather of projected landfall (Aberson and Franklin Research and Forecasting model (WRF, 1999). Skamarock et al. 2005), are also discussed. Recently, a strategy for identifying potential Note that the CWB global model is not used due dropwindsonde release locations (targets) to to the problem with its tracking TCs. optimize the likelihood that the additional observations would impact the global model TC track forecasts has been developed (Aberson 2. Background of NOAA Hurricane 2003). This strategy employs estimates of Surveillance initial condition uncertainty and potential error In 1982, HRD began research flights to growth from the NCEP operational global explore possible improvements to numerical ensemble forecasting system and ensures tropical cyclone track forecasts that result from adequate sampling of the target regions. the assimilation of dropwindsonde observations During 2003, thirteen missions were conducted. made in the data-sparse TC environment. The dropwindsonde data improved the 24- and From 1982 to 1996, the crews of NOAA's WP-3D 48-h NCEP global model track forecasts by an aircraft operated by the Aircraft Operations average of 18% to 32% through five days. Center (AOC), made dropwindsonde Over the last three years, the missions have observations in the environments of TCs for 19 improved the critical 36 to 60-h global model synoptic times. The observations, coupled with track forecasts by more than 20%. These the improved modeling and data assimilation, forecast times are critical to issuing watches or helped the Environmental Modeling Center warnings to alert the public to the threat of TCs. (EMC) of NCEP to reduce track forecast errors Some evidence suggests that the significantly (Burpee et al. 1996; Tuleya and dropwindsondes produce larger forecast Lord 1997). According to Burpee et al. (1996), improvements for strong or rapidly intensifying the increase of observational data made storms (Aberson, personal communication statistically significant contributions to the 2005). operational numerical model forecasts The improvements have increased year by (improvement by 16%-30% for 12-60-h year as the sampling technique has been refined forecasts). Additionally, the data have been and are approaching the values seen in Burpee used in research, such as identifying beta gyres et al. (1996). The annual percentage and their effects on TC motion (Franklin et al. improvements to the NCEP Global Forecast 1996). System (GFS) range from 10% to 30% for 5-day These encouraging results led to the track forecasts (Aberson 2004). development of a new generation of Global Positioning System (GPS) dropwindsondes and the purchase by NOAA of a Gulfstream-IV (G-IV) 3. The Model Descriptions jet aircraft that flies higher and covers a larger To evaluate the impact of dropwindsonde area than a P-3, enabling data to be acquired 2 data on numerical forecasts, three global models valid at the analysis time. NOGAPS, like the [The NCEP GFS, the FNMOC NOGAPS, and GFS, uses a three-dimensional variational (3-D the JMA GSM] and two regional models [NCEP VAR) assimilation scheme on a Gaussian grid. GFDL hurricane model and WRF model] are c. JMA GSM used. The data from the 10 DOTSTAR The JMA GSM has a horizontal resolution missions were assimilated into the global models on a Gaussian grid of T213 with 40 sigma levels in real time (the control runs, i.e., GFS-D, from the surface to 0.4 hPa. (The corresponding NOGAPS-D, and GSM-D 1). The denial transform grids are spaced about 0.5625 degree experiments (without the dropwindsonde data, in both longitude and latitude) The JMA i.e., GFS-N, NOGAPS-N, and GSM-N) are 3D-VAR data assimilation system is run four retrospective reruns. times a day. Typhoon bogus data are The two regional models (GFDL and WRF) embedded in the first guess fields of surface were run with the initial and boundary conditions pressure, temperature, and wind. A more provided by the GFS-D for the control (i.e., detailed description of the model can be found in GFDL-D and WRF-D), and by the GFS-N for the JMA’s website denial runs (GFDL-N and WRF-N). (http://www.jma.go.jp/JMA_HP/jma/jma-eng/jma a. NCEP GFS -center/nwp/outline-nwp/index.htm). The NCEP GFS (Surgi et al. 1998) is d. GFDL hurricane model an operational global data assimilation and The GFDL hurricane model is a model system providing forecasts four times per limited-area gridded model developed day. During 2004, the horizontal resolution was specifically for hurricane prediction.