Abstract. The tropical cyclone (TC) track and intensity predictions over Bay of Bengal (BOB) using the Advanced Research Weather Research and Forecasting (ARW) model are evaluated for a number of data assimilation experiments using various types of data. Eight cyclones that made landfall along the east coast of India during 2008-2013 were simulated. Numerical experiments included a control run (CTL) using the National Centers for Environmental Prediction (NCEP) 3-hourly 0.5 × 0.5 • resolution Global Forecasting System (GFS) analysis as the initial condition, and a series of cycling mode variational assimilation experiments with Weather Research and Forecasting (WRF) data assimilation (WRFDA) system using NCEP global PrepBUFR observations (VARPREP), Atmospheric Motion Vectors (VARAMV), Advanced Microwave Sounding Unit (AMSU) A and B radiances (VARRAD) and a combination of PrepBUFR and RAD (VARPREP+RAD). The impact of different observations is investigated in detail in a case of the strongest TC, Phailin, for intensity, track and structure parameters, and finally also on a larger set of cyclones. The results show that the assimilation of AMSU radiances and Atmospheric Motion Vectors (AMV) improved the intensity and track predictions to a certain extent and the use of operationally available NCEP PrepBUFR data which contains both conventional and satellite observations produced larger impacts leading to improvements in track and intensity forecasts. The forecast improvements are found to be associated with changes in pressure, wind, temperature and humidity distributions in the initial conditions after data assimilation. The assimilation of mass (radiance) and wind (AMV) data showed different impacts. While the motion vectors mainly influenced the track predictions, the radiance data merely influenced forecast intensity. Of various experiments, the VARPREP produced the largest impact with mean errors (India Meteorological Department (IMD) observations less the model values) of 78, 129, 166, 210 km in the vector track position, 10.3, 5.8, 4.8, 9.0 hPa deeper than IMD data in central sea level pressure (CSLP) and 10.8, 3.9, −0.2, 2.3 m s −1 stronger than IMD data in maximum surface winds (MSW) for 24, 48, 72, 96 h forecasts respectively. An improvement of about 3-36 % in track, 6-63 % in CSLP, 26-103 % in MSW and 11-223 % in the radius of maximum winds in 24-96 h lead time forecasts are found with VARPREP over CTL, suggesting the advantages of assimilation of operationally available PrepBUFR data for cyclone predictions. The better predictions with PrepBUFR could be due to quality-controlled observations in addition to containing different types of data (conventional, satellite) covering an effectively larger area. The performance degradation of VARPREP+RAD with the assimilation of all available observations over the domain after 72 h could be due to poor area coverage and bias in the radiance data.
The sensitivity of tropical cyclone simulations in a coupled ocean-atmospheric model WRF-3DPWP to surface roughness parameterizations is investigated. Six cyclones, Hudhud, Phailin, Helen, Jal, Nilam and Khaimuk, which occurred in the North Indian Ocean (NIO) during 2008-2014, are simulated. Three schemes for drag and enthalpy co-efficients (control (CNTL): Garrett C d and C k , Opt1: Donelan C d + Constant C k , Opt2: Donelan C d + Garret C k ) are used. India Meteorological Department (IMD) best track parameters are used for comparison. The results indicate that the simulated cyclone intensity is highly sensitive to the formulation of drag and enthalpy co-efficients in all cyclone categories, whereas the simulated tracks for strong cyclones only are affected by these schemes. The results showed that CNTL produced better predictions for track and Opt2 for intensity for the three cyclones. An improvement of 12.3, 35.2 and 34.9% in central sea level pressure (CSLP) and 2.9, 31.5 and 45.9% in maximum surface winds (MSW) at 24, 48 and 72 hr respectively are found with Opt2 over Opt1. Simulations showed the model enthalpy co-efficients mainly affected the intensity of the cyclones by producing a wind-induced surface heat exchange (WISHE)-type of feedback through heat and moisture fluxes and warm-core structure. Opt1 produced highly intensified cyclones due to simulating large enthalpy fluxes associated with a high C k /C d ratio. The stronger wind-induced moisture fluxes, higher vorticity and strong vertical motion associated with large enthalpy fluxes all support stronger simulated cyclones in Opt1 compared with CNTL and Opt2. The study shows that the decreasing C k for higher winds in Opt2 produced realistic intensity predictions. K E Y W O R D Sintensity, surface roughness, tropical cyclone, WRF-3DPWP
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