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Satellite Applications in Tropical Weather Forecasting Mark DeMaria Regional and Mesoscale Meteorology Team NESDIS/CIRA Colorado State University, Ft.

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Presentation on theme: "Satellite Applications in Tropical Weather Forecasting Mark DeMaria Regional and Mesoscale Meteorology Team NESDIS/CIRA Colorado State University, Ft."— Presentation transcript:

1 Satellite Applications in Tropical Weather Forecasting Mark DeMaria Regional and Mesoscale Meteorology Team NESDIS/CIRA Colorado State University, Ft. Collins CO Lenny 11/17/99

2 Acknowledgments RAMMT –Roger Phillips, Ray Zehr, Jack Dostalek, John Knaff, Bernadette Connell, Stan Kidder TPC –Jiann-Gwo Jiing (SOO), Richard Pasch, Michelle Huber, Bill Frederick CIMSS –Chris Velden, Gary Wade NESDIS ORA –Roger Weldon

3 Outline General Circulation in the Tropics –ITCZ –Subtropical Ridge –Tropical Upper Tropospheric Trough Synoptic-Scale Weather Systems –Upper-level lows –Tropical Waves Tropical Cyclones –Dvorak method –Environmental interactions –Measurements from Polar orbiting satellites

4 Terminology Channel 1 - Visible -.6  m (.52-.72) Channel 2 - Shortwave IR - 3.9  m (3.78- 4.03) Channel 3 - Water Vapor - 6.7  m (6.47-7.02) Channel 4 - Longwave IR - 10.7  m (10.2-11.2) Channel 5 - Split Window - 12.0  m (11.5-12.5) Microwave frequencies 20-90 Ghz (1.5-0.3 cm) 1 234 5 123

5 Hadley Cell Walker Cells P (mb) -90 -60 -30 0 30 60 90 DJFJJA

6 1979-1996 January Average 200 mb Streamlines

7 1979-1996 July Average 200 mb Streamlines

8 1979-1996 January Average 850 mb Streamlines

9 1979-1996 July Average 850 mb Streamlines

10 GMS, GOES, METEOSAT IR Imagery Composite

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12 Global WV Imagery Composite 22 August 1998 0000 UTC 2100 UTC (Real-time data available from CIMSS web site)

13 Tropical Upper-Level Lows Typically form within TUTT Cold-core systems Shallower circulation than mid-latitude lows (little circulation below 500 mb) Often produce precipitation Can influence intensity and track of tropical cyclones Can be tracked using water vapor imagery

14 300 mb700 mb Cold-low in NCEP Analysis 8/19/96 0000 UTC

15 Perturbation Temperature Cross-Section from NCEP Analysis 8/26/96 0000 UTC

16 Schematic Representation of Cold Low Structure (from Whitfield and Lyons, WF, 1992)

17 Radiation Analysis of WV Imager Channel for Idealized Sounding

18 16-Frame Water Vapor Imagery Loop 7/26/98 02:45 to 7/29/98 20:45 Formation of a Cold-Low

19 TPC Tropical Analysis and Forecast Branch Cold-Low Study Period of Study: Aug. 12-Oct. 1, 1996 Domain: 0-35 N, 110-20 N Cold-low centers tracked using GOES WV imagery 47 lows during 50 days Average Duration of 3 days, Max of 12 days Up to 8 lows in domain at once (average of 3) Vorticity center present in NCEP 200 mb analyses for nearly all cold lows identified by satellite observations –Average NECP analysis location error of 100 nm

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21 NCEP Aviation Model Cold-Low Average Track Error Extrapolation Persistence Cold Lows 1996 Tropical Cyclones 200 400 600

22 Tropical Waves Formation near western Africa –Barotropic/baroclinic instability, PV gradient changes sign –Secondary instability region in Western Caribbean Maximum amplitude near 700 mb Period of 2-5 days, wavelength 2-3000 km, May-Dec Precipitation associated with waves About 2/3 of Atlantic TC genesis associated with waves Role in east Pacific tropical cyclogensis

23 Seasonal Mean PV at 750 mb (Molinari et al, 1997) Mean meridional wind from GATE wave composite (Reed et al, 1977)

24 TAFB Methods for Tracking Waves TAFB tropical surface analysis generated 4 times per day, includes surface wave positions Rawindsone time series Surface data when available Satellite analysis over west Africa –Animation of channels 1, 2 and 4 indicates rotation Hovmoller satellite diagrams for continuity across tropical Atlantic NCEP aviation model analyses and forecasts

25 Dakar Sounding (15 N, 18 W) Time Series August 1995-97 95 96 97

26 20 W40 E20 W40 E 08/01/96 08/15/96 08/16/96 08/31/96 Tropical Strip Time Series 40 E-40 W 0 N-15 N

27 Tropical Cyclogenesis Eastern Pacific –Interaction of tropical waves/monsoon trough –Includes region of maximum global storm formation Atlantic –2/3 of storms from tropical waves –Some baroclinic, subtropical and monsoon trough developments –Very “peaked” season –Experimental genesis parameter under development

28 Climtological Tropical Cyclone Frequency (From WMO Global Guide To TC Forecasting)

29 (Tropical Atlantic: 0-20 N, 0-60 W)

30 Tropical Atlantic Genesis Parameter Developed from cases since 1991 Genesis variables –zonal shear (NCEP analyses) –vertical stability (NCEP analyses) –Mid-level moisture (Cloud-cleared GOES-8 water vapor brightness temperature, 1996-99) –5-day running means 8-18 N, 30-50 W Variables scaled from -1 to 1 Genesis parameter = shear x stability x moisture

31 Tropical Atlantic Genesis Locations 1991-99 45 Total Cases: 7 Un-named TDs 13 TS 9 Non-major Hurricanes 16 Major Hurricanes

32 Climatological Shear, Stability, WVBT (Scaled) Marginal Unfavorable Favorable

33 Genesis Parameter in 1999 ShearStability WVBTGP (www.cira.colostate.edu/ramm/gparm/genesis.asp)

34 5-Day Running Mean Cloud Cleared Water Vapor Imagery for August 1999 LOOP

35 Tropical Cyclone Classification NHC has responsibility for Atlantic and east Pacific basins –Atlantic: 10 storms, 6 hurricanes –East Pacific: 16 storms, 10 hurricanes Aircraft recon available only for Atlantic west of 55 W Majority of center and intensity estimates from GOES satellite data TAFB, SAB, AFWA provide classifications

36 Overview of the Dvorak Technique Visible and Infrared Technique Simplified Visible Technique given here (See Technical Report for full details) Uses patterns and measurements as seen on satellite imagery to assign a number (T number) representative of the cyclone’s strength. The T number scale runs from 0 to 8 in increments of 0.5.

37 Overview of the Dvorak Technique Cont’d In the following examples, only the Data T Number (DT) will be calculated, the final (official) T number assigned to a tropical cyclone includes further considerations. DT computations familiarize one to various tropical cyclone patterns.

38 Four Basic Patterns Curved Band Pattern Shear Pattern Central Dense Overcast (CDO) Pattern Eye Pattern –Pattern is not always obvious –Pattern typically varies with time

39 Patterns and Associated T Numbers

40 Empirical relationship between T number and wind speed

41 Finding the Cloud System Center (CSC) First step in the Dvorak technique From Dvorak (1985): “The cloud system center is defined as the focal point of all the curved lines or bands of the cloud system. It can also be thought of as the point toward which the curved lines merge or spiral.” Center not always obvious, especially at night TPC technique combines channel 2 and 4

42 T.S. Lisa Channel 4

43 T.S. Lisa

44 Curved Band Pattern TS Ivan 9/23/98 11:15 UTC

45 Curved Band Pattern Cont’d 1.0 2.0 2.5 3.0 3.5 4.0 4.5 DT Number

46 Shear Pattern Hurricane Bertha 7/11/96 2015 UTC

47 Shear Pattern DT Numbers 1° latitude = 60 nautical miles (nmi) = 111 km

48 Central Dense Overcast (CDO) Hurricane Georges 9/21/98 1545 UTC

49 CDO No eye DT number determined by CF+BF=DT –CF=CENTRAL FEATURE –BF=BANDING FEATURE –DT=DATA T NUMBER

50 CDO Central Feature (CF) Measure Diameter of CDO in degrees latitude For a well defined CDO –3/4 °CF=2 –1 1/4 °CF=3 –1 3/4 °CF=4 –>2 1/4 °CF=5 For an irregular CDO –1° to 1 1/2 °CF=2 –>1 1/2 °CF=3

51 CDO - Banding Feature (BF)

52 Eye Pattern Hurricane Georges 9/19/98 1345 UTC

53 Eye Pattern DT number determined by CF+BF=DT –CF=CENTRAL FEATURE –BF=BANDING FEATURE –DT=DATA T NUMBER

54 Banding Eye Hurricane Bonnie 8/25/98 2131 UTC

55 Infrared (IR) Technique Can be used during night as well as during day At times, more objective than visible technique Fully objective version developed at CIRA Updated objective technique from CIMSS

56 Example Digital IR: Hurricane Erika 1515 UTC 8 September 1997 Warmest eye pixel 16 °C Warmest pixel 30 nmi (55 km) from center -71 °C Nomogram gives Eye no. =7

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59 Operational Dvorak Technique Verification for 1997-98 Atlantic Seasons

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62 Input for NHC Track and Intensity Forecasts Track –70 % Numerical model guidance –15 % Synoptic reasoning –15 % Recent trends Intensity –50 % Recent trends –40 % Synoptic reasoning –10 % Numerical model guidance

63 Applications of Satellite Data to TC Forecasting Track –Inclusion of remotely sensed data in NWP models –Diagnosis of model initial state –Evaluation of synoptic situation Intensity –Evaluation of factors affecting intensity SST changes vertical shear (especially cloud track winds) trough interaction –Inclusion in NWP models

64 300 mb AVN Winds and WV Image 19 Sept 1998

65 NEW GOES WINDS PRODUCTS ARE BEING PRODUCED BY CIMSS/NESDIS: - HIGH - DENSITY WINDS DERIVED FROM IR AND HIGH-RESOLUTION VISIBLE CLOUD MOTIONS AS WELL AS WATER VAPOR MOTIONS, USING AUTOMATED ALGORITHMS - DISPLAYS OF THESE WINDS FOR UPPER- & LOWER-LEVEL LAYERS OVER THE TROPICS ARE ROUTINELY AVAILABLE VIA THE INTERNET -UWISC/CIMSS TC WEB SITE: http://cimss.ssec.wisc.edu/tropic/tropic.html

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67 Vertical Wind Shear Analysis from GOES High Density Winds

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69 Hurricane-Trough PV Interaction During Hurricane Elena 1985 (Molinari et al 1995)

70 8-Frame Water Vapor Imagery Loop 9/20/98 23:45 to 9/21/98 23:45 Hurricane/Trough Interaction

71 Storm-Scale Structure Convective transients, asymmetries –Velden and Olander (1998) technique IR BT usually warmer than WV Deep convection transport into stratosphere WV BT warmer than IR Concentric eye walls, eye wall cycles Mesovortices within the eye –High spatial and time resolution imagery (RSO, SRSO) –Extra-high density satellite winds

72 Channel 3, 4 Convective Parameter (CP) for Hurricane Opal 1995 (From Bosart, et al 1999) Min P P (mb) CP

73 GOES-East Scanning Strategies Routine Scanning –Conus hr+01,31 –Extended NH hr+15,45 –(2 or 4 per hr) Rapid Scan –Conus, NH 5-10 min –(8 per hr) Super Rapid Scan –Selected Sector 1-5 min –(22 per hr)

74 10-frame Rapid-Scan Visible Imagery Loop 9/21/98 19:02 to 20:10 Hurricane Georges Approaching Puerto Rico

75 Comparison of Operational and SRSO Winds for Hurricane Floyd

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77 Hurricane Luis 9/6/95 1345 UTC

78 TC Measurements from Microwave Frequencies Special Sensor Microwave Imager (SSM/I) –DMSP polar orbiting satellites –19, 22, 37, 85 GHz, 25 km resolution Advanced Microwave Sounding Unit (AMSU) –NOAA polar orbiting satellites (NOAA 15 +) –15 channels 23-89 GHz, 50 km resolution Can see “through” clouds Depicts rainband, eye structure Rainfall and surface wind algorithms AMSU temperature retrievals

79 Hurricane Jeanne 9/23/98 1021 UTC From NRL web site

80 SSM/I Imagery for Hurricane Floyd 13-14 September 1999

81 IR Imagery March 1, 1999 AMSU Temperature Retrieval (570 mb)

82 Hurricane Floyd Analysis 14 Sept 1999 12 UTC AMSU Swath IR Image Liquid Water (www.cira.colostate.edu/ramm/tropic/amsustrm.asp)

83 Without Correction With Correction TaTa V TaTa V

84 Applications of Balanced Winds: Asymmetric Vortex Structure 850 mb Isotachs (m/s) from Floyd 14 Sept 99 12 UTC -0 -10 -20 -30 -40

85 Gale Force (34 kt) Wind Radii Prediction 5 predictors selected, AE=18 nm, r 2 =83% AMSU Variable Normalized Coefficient 0-100 km Liquid water 29.1 Max Temp anomaly 26.5 Storm latitude 25.3 600-0 km pressure drop -17.2 Radius of 15 kt wind at 3 km 8.1

86 AMSU-A Rainfall Rate for Hurricane Georges (.01 inches/hr) TRaP for Key West = 6.7 inches

87 GOES IR and SSM/I 85 GHz Huricane Floyd 10 UTC 11 Sep 1999 (from NRL web site) IR 85 GHz

88 Auto-Estimator> <Multi-Spectral Rainfall Estimation From GOES

89 Summary Multispectral GOES imagery provides synoptic overview –ITCZ, Subtropical Ridges, TUTT and cold lows, waves, TCs WV Imagery is especially useful for tracking cold lows Continuity in imagery is primary tool for tropical waves Dvorak method provides quantitative intensity estimates –Also provides framework for operational forecasting –Shortwave IR aids center location, especially at night Sat. winds: environmental interactions, model intialization WV- IR difference isolates tropical deep convection Rapid-scan imagery: storm-scale fluctuations Microwave imagery is useful for low-level storm structure New AMSU data shows promise for hurricane analysis


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