Observation of Tropical Cyclone Formation, Growth and Dissipation by SAPHIR Sensor

Proceedings of International Union of Radio Science – 3rd Regional Conference on Radio Science 2017

Vasudha.MP1, G. Raju2 1Research Scholar, Department of Electronics and Communication Engineering (Ph:+91-8050158928; e-mail: [email protected]) 2Professor, Department of Electronics and Communication Engineering School of Engineering and Technology, Jain University, Bangalore, India.

ABSTRACT A critical study of origin and development of Tropical Cyclone (TC) and its intensity is essential for understanding now casting and/or forecasting weather/climate. Evaluation of TC Growth and dissipation also helps in understanding physical properties of earth surface such as land surface emissivity and ocean surface temperature. In this paper a study of i) Genesis, growth/development of TC intensity and ii) Critical analysis of variations in measurement by different wavelengths of Sondeur Atmosphérique du Profil d'Humidité Intertropicale par Radiométrie (SAPHIR) microwave sounder sensors with special reference to the Ashobaa cyclone observed in the Arabian Sea during 2015, and its impact on Indian subcontinent is made by using the SAPHIR Brightness Temperature (TB) patterns at 183±11.0 GHz is relatively more sensitive to ocean. In addition a comparative evaluation of the capabilities of all six channels of SAPHIR in measuring TC development is made with an intention to assess the best channel suitable for detection of TC and its intensity variations. Further, evaluation of capabilities of TB measured by SAPHIR sounder made in our study confirms that orbit position of Megha-Tropiques satellite with more frequent sampling (4-6 times/day) is useful for supporting forecasting and now-casting of tropical cyclone genesis to dissipation and its effects on land. Keywords: Brightness Temperature, Wind Speed, T-Number, Tropical Cyclone, SAPHIR 1. INTRODUCTION Meteorology Department (IMD) relating to tracking TC Tropical cyclone is one of the major natural events intensity [3] is also made. which cause variation in pre-monsoon and post-mansoon SAPHIR images of cyclone region show a climatic condition, besides causing physical disasters and prominent eye encircled by the eye wall and spiral bands of variation in weather phenomena. Forecasting TC genesis convection as defined in Dvorak method and is found useful and TC intensity tracking is essential to analyze climatic for analyzing tropical cyclone genesis and its development condition and atmospheric humidity variation. Tropical followed by its dissipation [12]. The forecasts of cyclone cyclones, has strong impact on atmospheric humidity, indicating its accurate eye location and intensity at 24-hr climate and vegetation. Tropical cyclone over North Indian and/or 48-hr time-steps are useful for all rehabilitation Ocean had caused remarkable variation in monsoon and measures. Our discussion will highlight the importance of climatic condition of Indian sub-continent, besides causing SAPHIR repetitive i.e., 4-6 times in a day in the tropics physical disaster like storm surge, tides, floods, heavy regions with 10km X 10km nadir resolution measurement in rainfall, damages to property and the like. Hence the all atmospheric conditions. It is also seen that BOB region is knowledge about variation of atmospheric humidity due to more prone to tropical cyclone formation than AS region. tropical cyclone is necessary. Satellite data are well Our observation highlights the fact that, i)The SAPHIR is considered to study and understand cyclone-genesis and its well suited for the observation of tropical cyclones because development. Observations of (i) TC genesis and intensities, its measurements are not significantly affected by the ice (ii) Atmospheric humidity and (iii) Land surface emissivity clouds that cover tropical storms. ii)Channel six is best using microwave and/or infrared images obtained by suited for studying tropical cyclone life cycle. sounder onboard satellites enables us to obtain almost real time information relating to the said parameters. Among the 2. BACKGROUND various satellite missions useful to these activities, the For the past four decades passive microwave sensor Advance Microwave Sounding Unit (AMSU) sensors on missions such as SEASAT, Special Sensor Microwave NOAA satellite and SAPHIR sensor on Megha-Tropiques Imager (SSMI), Microwave Humidity Sounder (MHS), satellite with 10km resolution have been considered for our Humidity Sounder for Brazil (HSB), AMSU- A & B, studies [1][16]. The channel-wise TB values have been SAPHIR have been used for oceanographic applications. obtained from the level-1 data over the Bay of Bengal SAPHIR aboard Indian satellite mission is launched for (BOB) region and Arabian Sea (AS) region from ISRO and profiling the atmospheric humidity. Here we made a briefly ICARE data and services center [14]. Channel-wise study of the ocean surface and land features using SAPHIR measured brightness temperature from SAPHIR, relating to data. SAPHIR onboard Megha-Tropiques (MT) satellite has selected cyclone formed in AS and BOB basin has-been a good spatial resolution of 10 to 20 km and a swath of observed and were used to estimate center positions and ~2060 km. Megha-Tropiques carrying SAPHIR sounder intensities of tropical cyclones by the Dvorak method. A was launched in near-circular inclined orbit of 20 degrees on brief comparison of the data provided by the Indian 12 October 2011 [1] and SAPHIR has been providing high-quality data related to ocean surface, atmospheric Proceedings of International Union of Radio Science – 3rd Regional Conference on Radio Science 2017 humidity profile [2] and land-related estimation of two quasi-independent intensity determination application [13]. Its unique features are: (i) frequent and of TC developed a method to observe by using visible and simultaneous observations (up to 6 times a day) and (ii) IR satellite imagery and the same was popularly adopted as good spatial sampling. By using brightness temperature, Dvorak Technique [12]. AMSU sounder data can be used SAPHIR measures the vertical distribution of atmospheric for analysis of TC features. Demuth. JL (2004) [4] water-vapor (from surface to 12 km height) [9]. Although formulated TC intensity and proposed algorithms for wind SAPHIR is primarily meant for atmospheric humidity radii estimation by using AMSU data. Timothy. L and S. profile studies, it has shown interesting results Velden (2007) [12] based on rigorous statistical and demonstrating the possibilities of detection, tracking empirical analysis developed an algorithm to improve movement of the features over the ocean surface. A number pattern recognition which introduced three major changes in of such tropical cyclones have been studied ever since automated storm center determination methodology. C. Megha-Tropiques launch till 2015 (Keila, Thane, Nilam, Balaji, et.al. 2014 [6] again utilized satellite-measured Phailin, Hudhud, Nilofar and Ashobaa). The data from radiances from SAPHIR available in the form of segmented SAPHIR sounder have also compared well with INSAT-3D level-1 data from ICARE Data and Services Center and sounder [3] as well as Indian Meteorological Department then, calculated near-surface rain (NSR) rates with special (IMD) [16] data of the cyclones. This paper brings out a reference to precipitating systems, during the life timeof vivid picture of cyclonic features as observed over a period Tropical cyclones namely (i) cyclone Neelam and (ii) from (from: 0300 UTC 8 June 2015 up to -1200 UTC 12 cyclone Phailin. Shuuji N and others [9], an improved June 2015). The paper also highlights the potentiality of version of dvorak technique for analyzing center positions SAPHIR in studying land features [13]. Dvorak intensity of tropical cyclones using this microwave imagery (from the estimation is the basic step in i) locating TC eye center; ii) AMSR-E system on board the Aqua) analysis is developed.

TABLE I. Comparison of SAPHIR, AMSU-B, INSAT-3D and MHS Specifications Features SAPHIR AMSU-B INSAT-3D MHS Orbital Inclination 200 980 820 E 550 No. of Sounding 6 3 5 2 Channels 6000 X 6000 km for 160 Swath Width ~2060 km ~2300 km ~2134 km min Max incidence angle 50.40 58.50 - 49.440 Pixel size across 10-22.7 km 20-64 km 10 km X 40 km 16 km track Pixel size along 10-14.5 km 16-27 km 10km 27.10 km track No. of pixel/scan 10 km E-W every 0.1 182 90 90 line1 sec. Polarization Horizontal Horizontal Linear – Vertical Horizontal 183.31± 0.2 12.66 µm 183.31±1.1 Central Frequency / 183.299 12.02 µm 183.31±2.8 183.311±1.0 Central Wavelength 183.299 7.43 µm 183.31±4.2 183.311±3.0 (GHz/µm ) 183.299 7.02 µm 183.31±6.8 6.51 µm 183.31±11.0 2.35; 1.45; 1.36; 1.06; 0.7; NEΔT (K) 0.3; 0.15; 0.2; 0.2; 0.2. 0.51; 0.4 1.38; 1.03; 1.10 0.6.

Fig. 1(a). SAPHIR Scanning Geometry Fig. 1(b). Weighting Function of SAPHIR & AMSU-B

Proceedings of International Union of Radio Science – 3rd Regional Conference on Radio Science 2017 3. SENSOR DETAILS sampling of L1A (180 pixels) data brightness temperature to The SAPHIR is the only instrument as on date produce de-correlated non-overlapping 130 pixels for all which can provide atmospheric humidity profile using six channels. channels with high temporal receptivity. It is ranging from 4.2. Tropical Cyclone Tracking by Intensity Estimation surface 1000 hpa to the stratosphere 86 hpa (layer 1: 1000 – (i) Dvorak technique (TC eye detection and 850 hpa; layer 2: 850 – 700 hpa; layer 3: 700 – 550 hpa; tracking method) has been adopted to detect and track TC layer 4: 550 – 400 hpa; layer 5: 400 – 250 hpa; layer 6: 250 Ashobaa from brightness temperature data as – 100 hpa), as compared to 3 layers of AMSU-B and derived/obtained from all the six channels of SAPHIR. Fig additionally some more layer supplementing these data with 3(a) illustrates the organized Cloud System Center (CSC) INSAT-3D. Table I shows the comparison of technical formation to determine the cyclone intensity are:The cloud 0 specifications of SAPHIR [15], AMSU-B [5], INSAT-3D system has a CSC within the diameter 2.5 latitude or less [3] and MHS sounder [2]. and CSC lasts for 6 hours or more; The cloud system has an 0 SAPHIR sounder performing cross track scanning area of dense, cold that appears less then 2 latitude from 0 when satellite is moving ahead offers 10 km at nadir center and 1.5 latitude in diameter. If CSC satisfied above resolution and 22.9 km at edge spatial resolution, number of features, it is determined as T-number T1.0, otherwise pixels per each scan is 182 per scan (130 per scan without consider the T-number of less than T1.0. Figure 3(b) shows overlap) and for one complete orbit 4187 scans as shown in the dvorak model of tropical cyclone development using Figure 1(a). curved band type intensity analysis. SAPHIR provides the vertical distribution of atmospheric water-vapour 6 channels provide relatively narrow weighting functions from the surface to about 12 km as shown in Figure 1(b) which shows the normalized weighting function of SAPHIR (S3, S4 and S5) that are similar to AMSU-B (M3, M4 and M5) channels [5].

4. METHODOLOGY

4.1. Data source Megha-Tropiques SAPHIR metadata products named as “MT1SAPSL1A” contains all the parameters of brightness temperature temporal, humidity profile of all 6 Fig. 3(a). Cyclone Intensity Number Determination channels and also INSAT-3D dataset available from 2011 to 2015 from MOSDAC (ISRO Ahmedabad) and ICARE (France) [18].

Fig. 3(b). Tropical Cyclone Development Model [12]

(ii) The results so obtained are compared with the

Fig. 2 Data Flow Structure actual/observed data obtained from Indian Meteorological Department (IMD) at an interval of 3 hours prediction to Fig. 2 shows the selection processes of data product predict the accuracy in the application of sounder data. type orbit-wise or segment-wise of respective level will be (iii) TC detection and tracking from Dvorak archived in HDF5 format. Level-1 products generate two technique using brightness temperature data obtained from types of files are segment-wise (possibly exceeding one all six channels of SAPHIR is compared with AMSU-B revolution, variable in size) and orbit-wise (i.e., one sounder images with an intention to establishing the best revolution). The L1 products that are available to the users efficient satellite data that can be used to identify the genesis are L1A and L1A2. Level 1A (L1A) is the brightness and tracking of TC over Indian sub-continent. temperature geo-tagged product and along the scan line, samples of all the 6 channels are collocated and have exactly 5. OBSERVATION AND ANALYSIS the same footprint dimensions projected on ground as well A number of cyclone observations have been the same geo-location [19]. Level 1A2 (L1A2) is the re- considered to study the impact of ocean surface features and 3

Proceedings of International Union of Radio Science – 3rd Regional Conference on Radio Science 2017 atmospheric humidity. Apart from As an example the Dvorak technique has been several cyclones a few severe cyclones that occurred in the applied to Ashobaa cyclone that occurred from 7 June to 12 Indian geographical region have been listed in Table II. As a June 2015 as highlighted in Fig.5 and when the cyclone eye preliminary study qualitative analysis of tropical cyclone (Deep depression area) has been surrounded by cloud band features over Arabian Sea and Bay of Bengal surrounding at least halfway around the eye, the cyclone intensity T- the Indian sub-continent from 2011 to 2015 are observed number is assigned as T1.0. If the cloud area is more during October to December of every year. organized than at the previous analysis, 0.5 is added to the previous T-number and CSC increase along with their T- TABLE II. Cyclones Occurred During 2011 to 2015 number. Year Cyclone Name Duration Ocean 2011 Keila 29 Oct 2011 to Arabian Sea 4 Nov 2011 2011 Thane 25 Dec 2011 to Bay of Bengal 31 Dec 2011 2012 Nilam 28 Oct 2012 to Bay of Bengal 3 Nov 2012 2013 Phailin 4 Oct 2013 to Bay of Bengal 14 Oct 2013 2014 Hudhud 7 Oct 2014 to Bay of Bengal 14 Oct 2014 2014 Nilofar 25 Oct 2014 to Arabian Sea 31 Oct 2014 2015 Ashobhaa 7 June 2015 to Arabian Sea 12 June 2015 Fig.6. Development and movement of Ashobaa Cyclone over Arabian Sea from Day1 to Day7 where Day3 shown in enlarged image [source ICARE france SAPHIR data].

Fig. 6 shows the progressive development of Ashobaa cyclone (7 June to 12 June 2015) based on cyclone eye pattern method of Dvorak technique for the lead time of 24 hrs observation based on cyclonic rotation of cloud area. A CSC is observed with respect to time variation from Day- 1 to Day-7 as the curvature and length of cloud bands rotation area increased. The mean error (variation/difference) between actual observations and estimation of wind speed (MSSLP) reported by IMD is shown in Table III. Estimated latitude and longitude positional error of Ashobaa cyclone IMD is shown in Table IV. Further, the graphical representation of variation Fig. 5. Ashobaa Cyclone Development. between observed and estimated wind speed is shown in Fig. 7.

TABLE III. Comparison of Observed and Estimated Parameters for Ashobaa Cyclone Tracking Estimated Observed Estimated Ref- Time Surface Observed Ref- Date Category Surface Wind Category Issued (UTC) Wind speed Issued speed (kmph) (kmph) DEMS-RSMC DEMS-RSMC 08 06 50-60 60-70 1 03.00 UTC 08 06.00 DD 0900 UTC 08 06 CS 2015 Gust: 70 Gust: 80 06 2015 2015 DEMS-RSMC 90-100 DEMS-RSMC 09 06 80-90 kmph 2 09 00 UTC 08 12.00 kmph Gust: CS 15 00 UTC 09 CS 2015 Gust: 100 kmph 06 2015 120 kmph 06 2015 DEMS-RSMC 95-105 DEMS-RSMC 10 06 80-90 kmph 3 21 00 UTC 09 12.00 kmph Gust: SCS 15 00 UTC 10 CS 2015 Gust: 100 kmph 06 2015 120 Kmph 06 2015 DEMS-RSMC 65-75 kmph DEMS-RSMC 11 06 60-70 kmph 4 1500 UTC 10 06 12.00 Gust: 85 CS 15 00 UTC 11 CS 2015 Gust: 80 kmph 2015 kmph 06 2015 DEMS-RSMC 25-35 kmph DEMS-RSMC 12 06 35-45 kmph 5 0600 UTC 11 06 12.00 Gust 45 L 0300 UTC 12 06 D 2015 Gust 55 kmph 2015 kmph 2016 D – Depression; DD – Deep Depression; CS – Cylone Storm; SCS – Sever Cyclone Storm; L – Low Pressure 4

Proceedings of International Union of Radio Science – 3rd Regional Conference on Radio Science 2017

A verification of the forecast TC positions, Maximum Sustained Surface Wind Speed (MSSWS) and Gust made by the IMD (using NWP models)with the observed positions reported by the Regional Specialized Meteorological Centre (RSMC) New Delhi has been carried out. Verification of forecast and observed positions of TC Ashobaa is performed by using 121 samples for the lead time 12 hr, 15 hr, 18 hr, 21 hr, 24 hr, 33 hr, 36 hr, 45 hr and 48 hr, which includes verification of increase and decrease between average track forecast and observed positions. The average mean error detected after verification is summarized as: i) 0.750 N – 1.160 E average forecast errors in TC positions; ii) 4.59 knots average forecast error of MSSWS during cyclone period and iii) average forecast error of 4.81 knots gust during cyclone period. We have Fig.7 Error in Wind Speed (kmph) of Ashobaa Cyclone made graphical representation shown in Fig. 9 positional Tracking error detection of Ashobaa cyclone from 7 to 12 June 2015 as well as statistical representation in Table V of mean track forecast error corresponding to lead time 12 hr, 15 hr, 18 hr, 21 hr, 24 hr, 33 hr, 36 hr, 45 hr and 48 hr respectively and the abstract of the same is given below.

(a) 48hr Earlier Long (b) 48hr Earlier Lat

Fig.8 Ashobaa cyclone eye center detected from BT measurement made by SAPHIR Sounder, on same day at lead time: (a) 1:40 to 3:33pm; (b) 3:28 to 5:22pm; (c) 5:17 to 7:12pm; (d) 7:17 to 9:02 and (e) 23:37 to 1:31am.

(c) 33hr Earlier (d) 24hr Earlier TABLE IV Estimated Positional Error (Latitude and Longitude) of Ashobaa Cyclone Estimated Estimated Observed Observed Date Latitude Longitude Latitude Longitude 08 06 2015 18.2 67.1 18.6 66.5 09 06 2015 19.7 66 21 63 09 06 2015 21.1 63.8 21.2 62.5 10 06 2015 21.4 62.2 21.3 62.1 (e) 21hr Earlier (f) 18hr Earlier 10 06 2015 21.4 62.1 21.3 62.1 11 06 2015 20.7 60.5 20.8 60.5 11 06 2015 22.2 60 20.8 60 11 06 2015 20.8 59.6 20.8 59.7 12 06 2015 20.8 58.9 20.8 59.5 On 8 June 2015 at different time intervals cyclone eye center intensity has been calculated using brightness temperature parameter and same shown in Fig. 8 (a) to (e) (g) 15hr Earlier (h) 12hr Earlier of Ashobhaa cyclone. Estimated positional tracking of Fig. 9. Positional Error Detection. Ashobaa cyclone (Latitude and Longitude) variation from IMD has been compared with SAPHIR observed data shown in Table IV from 8 June 2015 to 12 June 2015.

Proceedings of International Union of Radio Science – 3rd Regional Conference on Radio Science 2017 TABLE V. Mean Track Forecast Error Corresponding to Lead Time of Ashobaa Cyclone Lead LAT(Degree- LONG (Degree- Verified MSSWS (knots) GUST (knots) time North) East) Samples UTC Incr Decr Avg Incr Decr Avg Incr Decr Avg Incr Decr Avg 12 hr - 121 0.41 0.99 0.75 1.05 1.17 1.16 1.77 7.05 4.59 2.78 8.95 4.81 48hr

of SAPHIR are more prominent and clear when compared to AMSU images.

(a) 7 June SAPHIR (b) 7 June AMSU

Fig. 11(a). Channel 1 Fig. 11(b). Channel 2

Fig. 11(c). Channel 3Fig. 11(d). Channel 4

(e) 10 June SAPHIR (f) 10 June AMSU

Fig. 11(e). Channel 5 Fig. 11(f). Channel 6

(g) 11 June SAPHIR (h) 11 June AMSU Fig.11(a) to (f) shows the comparison of Ashobaa cyclone eye occurred on 8 June 2015 all 6 channels of SAPHIR sensor. It is observed that Channel 6 of SAPHIR sounder is more accurate in showing the cloud formation area and cloud cyclonic region compared to other channels.

(i) 12 June SAPHIR (j) 12 June AMSU Fig. 10(a) to (j) Comparison of two different sensor SAPHIR sounder and AMSU sounder observed on Ashobaa cyclone from 7 June to 12 June 2015 occurred in Arabian Sea.

A comparison of brightness temperature profiles of select images of SAPHIR and AMSU is shown in Fig. 10(a) to 10(j), which present the day to day variation of Ashobaa cyclone from genesis on 7 June to dissipation 12 June 2015 in terms of brightness temperature. It also shows that images 6

Proceedings of International Union of Radio Science – 3rd Regional Conference on Radio Science 2017 (a). Channel 1 (b). Channel 2

(c). Channel 3 (d). Channel 4 (c). Channel 3 (d). Channel 4

(e). Channel 5 (f). Channel 6 (e). Channel 5 (f). Channel 6 Fig. 14 Tropical Cyclone NILOFAR of different SAPHIR Fig. 12 Tropical Cyclone PHAILIN of different SAPHIR channels[formed: 25Oct 2014; dissipated: 31 Oct 2014] channels[formed: 8 Oct 2013; dissipated: 14 Oct 2013]

(a). Channel 1 (b). Channel 2

(c). Channel 3 (d). Channel 4 Fig.13. Development and movement of Phailin Cyclone over Bay Of Bengal from Day1 to Day6 where Day3 shown in enlarged image [source ICARE France SAPHIR data].

(e). Channel 5 (f). Channel 6 Fig. 15 Tropical Cyclone HUDHUD of different SAPHIR channels[formed: 7Oct 2014; dissipated: 14 Oct 2014]

(a). Channel 1 (b). Channel 2

TABLE VI. Mean Error Detection Estimation of Tropical Cyclone Position and Intensity TC Lead verified LAT(Degree-North) LONG (Degree-East) MSSWS (Kts) Names time Increase Decrease Avg Increase Decrease Avg Increase Decrease Avg UTC Samples 0N 0N 0N 0E 0E 0E KEILA 12-45 19 0.64 0.00 0.64 2.1 0.00 2.1 0.3 7.33 3.81 THANE 12-48 89 1.46 0.64 1.05 0.95 0.62 0.78 13.24 10.71 11.97 NILAM 12-48 28 045 0.32 0.38 0.71 1.67 1.19 1.66 6.69 4.17 PHAILIN 12-48 70 0.3 0.52 0.41 0.56 0.17 0.36 19.62 23.53 21.57 NILOFAR 12-48 136 0.24 0.68 0.46 0.54 1.08 0.81 12.85 25.28 19.06 HUDHUD 12-48 114 0.23 0.44 0.33 0.31 0.60 0.45 9.48 5.96 7.72 ASHOBAA 12-48 121 0.41 0.99 0.75 1.05 1.17 1.16 1.77 7.05 4.59

Proceedings of International Union of Radio Science – 3rd Regional Conference on Radio Science 2017

Comparative study of observed cyclone tabulated in 5. Julie L. Demuth et al., “Evaluation of Advanced Table VI, it is observed that 579 samples related to 7 Microwave Sounding Unit Tropical-Cyclone Intensity cyclones from 2011 to 2015 near Indian sub-continent were and Size Estimation Algorithms,” Journal of Applied chosen and the average increase or decrease variation in TC Meteorological and Climatology, vol. 23, issue. 2, pp. position and MSSWS speed (kts). 282-296, 2004. 6. C. Balaji et al., “On the Possibility of Retrieving Near- 6. CONCLUSION Surface Rain-rate from the Microwave Sounder This paper aims at qualitative and Quantitative SAPHIR of the Megha-Tropiques Mission,” Current analysis of the capabilities of the SAPHIR humidity sounder Science, vol.106, issue. 4, pp. 587-593, 2014. on board Megha-Tropiques satellite in providing adequate 7. Kidder .SQ, WM. Gray and TH. Vonder Haar, and accurate data useful for determining the humidity “Tropical Cyclone Outer Surface Winds Derived from variations at various altitudes. Considering its frequent Satellite Microwave Sounder Data,”Journal of temporal observations the SAPHIR sounder data can be Monthly Weather Review, vol. 108, pp. 144-152, applied for near real-time applications such as weather 1980. forecasting and cyclone track monitoring. 8. N. Karouche et al., “Megha-Tropiques Satellite A comparison of brightness temperature profile of Mission: In Flight Performances Results,” Proce. of selected images of SAPHIR obtained from all six channels IEEE Int. Con. Geosci. Remote Sensing Symp., pp. shows i) The images of SAPHIR is capable of providing 4684-4687, 2012. comparatively more adequate qualitative and quantitative 9. Randhir Singh et al., “Quality Assessment and information relating to TC genesis and development Assimilation of Megha-Tropiques Saphir Radiances ii)compared to AMSU observed data, SAPHIR data can also into WRF Assimilation System,” Journal of Geophy. be used for tracking life cycle of tropical cyclones Res. Atmos.,vol. 118, pp. 6957-6969, 2013. originated over selected area; iii) SAPHIR has relatively 10. Shuuji Nishimura, et.al., “Analysis of Tropical higher spatial resolution, is observed that it has more clear Cyclones using Microwave Satellite Imagery,” Techn. contrast near real-time image. Rev. JMA., vol. 10, pp. 30-70, 2008. Our study also proves that Dvorak’s technique of 11. Timothy L. Olander and Christopher S. Velden, “The interpretation of satellite observation is still useful for Advanced Dvorak Technique: Continued determining the TC storm intensity. From the comparison of Development of an Objective Scheme to Estimate brightness temperature profiles of all six channels Tropical Cyclone Intensity using Geostationary of SAPHIR it is found that channel six is found to be the Infrared Satellite Imagery,” J. Wea. Forecas., vol. 22, the best one suitable for detection of TC and its intensity issue. 2, pp.287-298, 2007. variations. 12. Vernon F. Dvorak, “Tropical Cyclone Intensity Analysis and Forecasting from Satellite Imagery,” J. ACKNOWLEDGEMENT Mon. Wea. Rev., vol. 103, pp. 420-430, 1975. The authors would like to express their sincere 13. Velden C et al., “The Digital Dvorak Tropical Cyclone gratitude to Indian Space Research Organization (ISRO) Intensity Estimation Technique,” J. Ame. Mete. MOSDAC for providing SAPHIR sensor dataset and Soci.,pp. 1195-1210, 2006. ICARE France. The authors acknowledge the necessary 14. C. 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