land surface temperature and its interaction with atmospheric circulation in different scales 5 th SALGEE Workshop 2017 18 20 September 2017 itamarlenskybiuacil Itamar M ID: 1044262
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1. MSG & MODIS observations ofland surface temperature and its interaction with atmospheric circulation in different scales5th SALGEE Workshop 2017, 18 ‐ 20 September 2017itamar.lensky@biu.ac.ilItamar M. Lensky, Shilo ShiffandUri Dayan
2. ScaleExampletemporalspatialMicrobuildingminmeters2Atmospheric scales
3. ScaleExampletemporalspatialMicrobuildingminmetersTopovalleyhoursFew km3Atmospheric scales
4. ScaleExampletemporalspatialMicrobuildingminmetersTopovalleyhoursFew kmMesocountry< 1 day10-100 km4Atmospheric scales
5. ScaleExampletemporalspatialMicrobuildingminmetersTopovalleyhoursFew kmMesocountry< 1 day10-100 kmSynopticcontinentFew days500-5000 km5Atmospheric scales
6. ScaleExampletemporalspatialMicrobuildingminmetersTopovalleyhoursFew kmMesocountry< 1 day10-100 kmSynopticcontinentFew days500-5000 kmGlobalplanet> weeks6Atmospheric scales
7. ScaleExampletemporalspatialMicrobuildingminmetersTopovalleyhoursFew kmMesocountry< 1 day10-100 kmSynopticcontinentFew days500-5000 kmGlobalplanet> weeks7Atmospheric scales
8. Radiative cooling at clear winter nights causes stable stratification.Topographic depressions are filled with cold air.Cold air pool formation
9. Met stationsDetecting Finescale Climatic Features
10. Met stationsMODIS10705 km, 10:30 AM/PMLensky and Dayan, BAMS 2011Detecting Finescale Climatic Features
11. Warm lowlandsCold mountains- 200 m+1000 mJJAJJAJJASummer Nights - LST controlled by altitude
12. Longer winter clear-sky nights.Stable atmosphere suppresses turbulence.Drainage flow from the mountains.DJFDJFWinter Nights - Detecting cold patches
13. GDD accumulatedFast growthSlow growthGrowing Day DegreeImplications for Agricultural Planning:Simulation of corn growth
14. PupaeMothA 3-week delay in pest population expansion is expected in cold poolsImplication for pest management:Predicting timing of pest population expansion
15. amplitude difference between winter & summer LST Radiative cooling @ winter nights in valleys
16. ALSTmean fTemporal Fourier Analysis (TFA)LST(t) = LSTmean + Acos(wt+f)R – LSTmeanG – fB – A
17. LST(t) = LSTmean + Acos(wt+f)ALSTmean fTemporal Fourier Analysis (TFA)R – LSTmeanG – fB – A
18. Google Earth Engine
19. ScaleExampletemporalspatialMicrobuildingminmetersTopovalleyhoursFew kmMesocountry< 1 day10-100 kmSynopticcontinentFew days500-5000 kmGlobalplanet> weeks19Atmospheric scales
20. MesoscaleSynoptic scale Sea Breeze: summer mesoscale system
21. SB detection is based on the contrast between cool marine-air and underlying warm terrain Resolution: 15 min; 4 km MSG9:00July 312005
22. 9:30July 312005
23. 10:00July 312005
24. 10:30July 312005
25. 11:00July 312005
26. 11:30July 312005
27. 12:00July 312005
28. 12:30July 312005
29. 13:00July 312005
30. 13:30July 312005
31. 14:00July 312005
32. 14:30July 312005
33. 15:00July 312005
34. 34DeepWeakSB best observed when synoptics is weak an extension of the Indian monsoonPersian Trough prevails at Summer over the EM
35. Meso signalSynoptic signalJuly 7 2010July 21 2010weak windsstrong windssteady directionDeepWeakclimactualSB variable direction
36. רוחות חלשותTiming of the SB: 11:00, 13:00, 15:00.SBSynopticJuly 7 2010July 21 2010DeepWeakLensky and Dayan, ACP 2012Timing of the Sea Breeze
37. ScaleExampletemporalspatialMicrobuildingminmetersTopovalleyhoursFew kmMesocountry< 1 day10-100 kmSynopticcontinentFew days500-5000 kmGlobalplanet> weeks37Atmospheric scales
38. surface temperature patterns induced by synoptic circulationover the Eastern Mediterranean
39. the seasonal & diurnal cycles, seasonality10:30 LT2400 X 2400 1km pixelsMODIS 10:30 LT LST productLST is controlled by:
40. the seasonal & diurnal cycles, topography, land cover, mineralogyLSTOct 1020002400 X 2400 1km pixelsMODIS 10:30 LT LST productLST is controlled by:
41. the seasonal & diurnal cycles, topography, land cover, mineralogy and circulation Seasonality masks the effect of circulation on LSTseasonalitycirculationpositive anomalycirculationnegative anomaly10:30 LT2400 X 2400 1km pixelsMODIS 10:30 LT LST productLST is controlled by:
42. ActualOct 102000ClimatologicalOct. 102000-12anomalyOct. 102000abc=a-bThe anomaly removes the effects of:seasonality, topography, land cover, and mineralogy
43. Synoptic categorydaysRed Sea Trough with eastern axis558Red Sea trough with western axis56Red Sea trough with central axis 263Weak Persian trough 674Median Persian trough379Deep Persian trough163high to the east184high to the west627high to the north372high over Israel298deep low to the east56deep Cyprus low to the south4shallow Cyprus low to the south15deep Cyprus low to the north35shallow Cyprus low to the north148cold low to the west29shallow low to the east 232sharav low to the west35sharav low over Israel23SLP 12 UTC (2000-2012) HLWinter18456Synoptic effect on LST in the same season (winter)
44. Deep Low to the east High to the east T995 (NCEP/NCAR)MeanLST (MODIS)Lensky and Dayan, IJoC 2014Winter – The effect of seasonality
45. T995 (NCEP/NCAR)AnomalyLST (MODIS)Deep Low to the east High to the east Lensky and Dayan, IJoC 2014Winter – The effect of synoptics
46. ScaleExampletemporalspatialMicrobuildingminmetersTopovalleyhoursFew kmMesocountry< 1 day10-100 kmSynopticcontinentFew days500-5000 kmGlobalplanet> weeks46Atmospheric scales
47. 47combining 1 km resolution MODIS Land Surface Temperature with 25 km Climate Forecast System Version 2 (CFSv2) modeled surface temperatureto provide continuous LST at a spatial resolution of 1 km in cloudy pixelsMODISCFSv2combining MODIS & CFSv2 data
48. 48MODISCFSV2
49. High to the east ObservationMODIS LSTClimatologyMODIS TFA LSTModel anomalyCFSv2Continuous LSTMODIS + CFSv2
50. Deep Low to the east ObservationMODIS LSTClimatologyMODIS TFA LSTModel anomalyCFSv2Continuous LSTMODIS + CFSv2
51. The effect of different atmospheric scales on land surface temperature can be detected from satelliteThis together with model data was used to achieve a continuous LST dataset at 1 km resolutionUseful for agricultural planning and managementSummary and conclusionsTHANK YOU!