Suman Goyal Sc E /In-charge SYNOPTIC Application Unit Satellite Meteorology Davison

Transcription

1 Suman Goyal Sc E /In-charge SYNOPTIC Application Unit Satellite Meteorology Davison

2 Introduction What is ForTraCC? It is an algorithm for tracking and forecasting radiative and morphological characteristics of mesoscale convective systems (MCSs) through their entire life cycles using geostationary satellite thermal channel information (10.8 µm).

3 ForTraCC is a nowcasting software developed by Brazilian Meteorologist for the purpose of convective cell identification tracking and nowcasting by using developed convective cells from the Satellite Data. The Software is originally designed for GOES data Satellite Application unit with the help of SAC, Ahmedabad implemented this software partially on INSAT-3D data The verification of software is in process for Indian region Some verification Results for a particular event are shown.

4 Algorithm of ForTraCC The main steps of the algorithm are the following: A cloud cluster detection method based on a size and temperature threshold A statistical module to identify morphological and radiative parameters of each MCS A tracking technique based on MCS overlapping areas between successive images A forecast module based on MCS evolution in previous time steps In ForTraCC Vila (2005) method are used and In this case a minimum of 150 pixels considering the image resolution of 4X4 km is taken i.e. minimum size should be km

5 Tracking technique of ForTraCC The tracking methodology is based on tracking algorithm presented in Mathon & Laurent (2001) The tracking of convective clouds is based on area overlapping method and assumes that there are common pixels in two consecutive images A brightness temperature threshold of 235 K has been chosen for MCS detection because this threshold seems to be suitable for detecting clouds associated with convection. In this technique simply assumes that a cloud at a later time corresponds to that at an earlier time when, considering the previous constraints of size and temperature, there are common pixels in consecutive images.

6 Tracking methodology Continuity Spliting Merger Situation of Convective clouds obtain during algorithm

7 MCS center of mass displacement estimation V(t-1) = estimated displacement vector in the previous time VP(t) = predicted displacement vector for next 30 min (considering no change in displacement vector) ΔV(t)= V(t)-VP(t) V(t) is the real MCS displacement The estimation/prediction of vector displacement of MCS for next 30 min is Limitation: Applicable for continuity condition VE(t+1)=V(t) + ΔV(t) Not applicable for merging and splitting Conserve MCS s shape and size

8 Mesoscale convective system displacement estimation

9 MCS life cycle Phase (Growth and Decay)

10 Verification of Satellite based nowcasting technique The thunderstorm event reported by Met Office Event Date : 03-MAY-2014 Event: Thunder Squall reported at Safdarjung (New Delhi) at 03/ /1355 UTC & Alipore (Kolkata) from 03/ UTC

11 Procedure for generating forecast files At least 4 consecutive HDF files are taken for generation of forecast up to 6hrs. Hdf5 Data taken for the generation of forecast file for this case For this case the data of 1130 UTC is taken as last for which the forecast up to 1730 UTC are generate for every 30 min. The verification of forecast with actual observation by min CTT of the convective cell are shown

12 2 hour Fortracc forecast verification 2 Hr. forecast Actual 1330 UTC , , , , Hr. forecast Actual 1400 UTC , , , ,88.2

13 3 hour Fortracc forecast verification 3 Hr. forecast Actual 1330 UTC , , , , Hr. forecast Actual 1400 UTC , , , ,87.4

14 4 hour Fortracc forecast verification 4 Hr. forecast Actual 1330 UTC , , , , Hr. forecast , , , ,88.2

15 CTT comparison over Delhi area Time/fcst hr. fcst actual Min. CTT Position Min CTT Position 1330/ 2 hr , , / 2.5 hr , , / 3 hr , , / 3.5 hr , , / 4 hr , , / 4.5 hr , ,75.5

16 Min CTT comparison over Alipore area Time/fcst hr. fcst actual Min. CTT Position Min CTT Position 1330/ 2 hr , , / 2.5 hr , , / 3 hr , , / 3.5 hr , , / 4 hr , , / 4.5 hr , ,88.2

17 Forecast using animation

18 J & K Disaster

19 Procedure for implementation Possible ways to do this: To put the information of area, min CTT, centroid and extent by using locally developed algorithm named FLOODFILL. METHODOLOGY of Floodfill Extracting pixels with given temperature value (here it is 243 K(-30 C)) Run flood fill algorithm for 243 K (-30 C) 223 K (-50 C) 203 K (-70 C) to separate cells Output cell characteristics: Latitude range Longitude range Centre Area Min. temperature

20 Validation of Nowcasting Technique The correlation graph of Min cloud top brightness temperature for 120 (2hrs) and 150 (2.5 hrs) forecast with actual BT.

21 Consequences of Convective activity Uttarakhand Disaster J & K Disaster

22 धन यव द