Cold-ring shaped storms
|
|
- Nancy Ramsey
- 5 years ago
- Views:
Transcription
1 MARTIN SETVÁK CZECH HYDROMETEOROLOGICAL INSTITUTE Cold-ring shaped storms 25 June 2006 (Czech Republic and Austria) EUMeTrain Convection Training Week June 2008
2 Our storms cloud-tops team: 1, Petr Novák 2, Michaela Radová 1, Jindřich Šťástka 1 Pao Wang 3, Daniel Lindsey 4, Robert Rabin 5 1 CHMI, Satellite Dept., Czech Republic 2 CHMI, Radar Dept., Czech Republic 3 University of Wisconsin-Madison, U.S.A. 4 NOAA/NESDIS/RAMMB, CIRA/CSU, U.S.A. 5 NOAA/NSSL, and SSEC, U.S.A. Modified version of presentations given at: and The ECSS2007 (European Conference on Severe Storms), September 2007, Trieste, Italy The EUMETSAT-INMW Convective workshop at Krakow, November 2007, Poland Parts of this research were carried out under support of the Grant Agency of the Czech Republic, project #205/07/0905.
3 What are the cold-ring shaped storms? - appearance, terminology, examples and basic characteristics
4 EXAMPLE: 25 June 2006, Czech Republic and Austria HRV Meteosat-8 (MSG1) 13:45 UTC IR 10.8 BT ENH
5 Necessity to apply suitable image color enhancement!!! This specific brightness temperature range (BT K) of the color enhancement is suitable for typical European storms; however for some cases it may need certain adjustment...
6 Description and examples of cold-ring shaped type of storms Terminology: CENTRAL WARM SPOT (CWS) COLD RING No formal quantitative definition of the cold-rings and CWS in terms of their temperature differences and thresholds, shape and size, duration
7 Description and examples of cold-ring shaped type of storms Terminology: sometimes also called as doughnut-shaped storms Wrong concept!!!
8 Description and examples of cold-ring shaped type of storms Examples:
9 Description and examples of cold-ring shaped type of storms Examples:
10 Description and examples of cold-ring shaped type of storms Examples:
11 Description and examples of cold-ring shaped type of storms Examples:
12 Description and examples of cold-ring shaped type of storms Examples:
13 Description and examples of cold-ring shaped type of storms Examples:
14 Description and examples of cold-ring shaped type of storms Examples:
15 Description and examples of cold-ring shaped type of storms Examples:
16 Description and examples of cold-ring shaped type of storms Main characteristics: temperature difference between the cold ring and CWS: several Kelvins and higher... up to about K (in the MSG imagery) CWS size: typically up to several SEVIRI pixels across CWS duration: from one single scan to several 15-minute MSG repeat cycles (for one single CWS)
17 Description and examples of cold-ring shaped type of storms Other: in some cases difficult to decide whether the observed feature can be classified as a cold-ring shaped storm or not (namely due to its small size or shape), depends also on the level (strength) of the image enhancement; resemblance of the cold-ring shaped storms to the cold-u shaped storms, in some cases difficult to decide between these (no formal distinction between them, absence of formal quantitative definitions); sometimes more accurate to speak generally about a storm exhibiting a distinct enclosed warm spot (area), not mentioning the cold-ring or cold-u shape.
18 Resemblance of the cold-ring shaped storms to the cold-u (enhanced-v) shaped storms - basic characteristics of the cold-u shaped storms, their possible mechanisms, links to the cold-ring shaped storms...
19 Cold-U shaped storms Example of a cold-u shaped storm: 26 May 2007, Germany Meteosat-9 (MSG2) 15:00 UTC DISTANT WARM AREA (DWA) CLOSE-IN WARM AREA (CWA) COLD-U
20 Cold-U shaped storms Originally called as enhanced-v (since observed in enhanced IR imagery), presently stressed the nature of the feature by naming them as cold-u or cold-v shape (or cold-u/v shape). The enhanced-v features documented first in early 1980 s on the basis of GOES and NOAA/AVHRR imagery, showing a very close correlation with severe weather or supercells. However, this feature alone does not automatically classify a storm as a supercell!!! If observed, it indicates a possible severity of the storm, nothing more! Mechanism of the cold-u/v and CWA couplet formation: still not quite well (unambiguously) explained, several different approaches, mechanisms. For details of these see the original papers, addressing this topic.
21 Cold-U shaped storms Wake effects (R.F. Adler, A.F. Hasler, G.M. Heymsfield, R.A. Mack, D.W. McCann, A.J. Negri, R.E. Schlesinger,... ) From: Adler, R. F., and R. A. Mack, Thunderstorm cloud top dynamics as inferred from satellite observations and a cloud top parcel model. J. Atmos. Sci., 43,
22 References: Adler, R. F., M. J. Markus, and D. D. Fenn, Detection of severe Midwest thunderstorms using geosynchronous satellite data. Mon. Wea. Rev., 113, Adler, R. F., and R. A. Mack, Thunderstorm cloud top dynamics as inferred from satellite observations and a cloud top parcel model. J. Atmos. Sci., 43, Hasler, A. F., Stereographic observations from geosynchronous satellites - an important new tool for the atmospheric science. Bull. Amer. Meteor. Soc., 62, Heymsfield, G. M., R. H. Blackmer Jr., and S. Schotz, 1983a. Upper level structure of Oklahoma tornadic storms on 2 May 1979, Pt. 1 radar and satellite observations. J.Atmos.Sci., 40, Heymsfield, G. M., G. Szejwach, S. Schotz, and R. H. Blackmer Jr., 1983b. Upper level structure of Oklahoma tornadic storms on 2 May 1979, Pt. 2 Proposed explanation of "V" pattern and internal warm region in infrared observations. J. Atmos. Sci., 40, Heymsfield, G. M., and R. H. Blackmer Jr., Satellite-observed characteristics of Midwest severe thunderstorm anvils. Mon. Wea. Rev., 116, Heymsfield, G. M., R. Fulton, and J. D. Spinhirne, Aircraft overflight measurements of Midwest severe storms: Implications on geosynchronous satelite interpretations. Mon. Wea. Rev., 119, Mack, R. A., A. F. Hasler, and R. F. Adler, Thunderstorm cloud top observations using satellite stereoscopy. Mon. Wea. Rev., 111, McCann, D. W., The enhanced-v: A satellite observable severe storm signature. Mon. Wea. Rev., 111, Negri, A. J., Cloud-top structure of tornadic storms on 10 April 1979 from rapid scan and stereo satellite observations. Bull. Amer. Meteor. Soc., 63, Schlesinger, R. E., 1984: Mature Thunderstorm Cloud-Top Structure and Dynamics: A Three Dimensional Numerical Simulation Study. J. Atmos. Sci., 41,
23 Cold-U shaped storms Jumping cirrus (T.T. Fujita) From: Fujita T. T., Principle of stereoscopic height computations and their applications to stratospheric cirrus over severe thunderstorms. J. Meteor. Soc. of Japan, 60,
24 Cold-U shaped storms Gravity wake breaking mechanism (P.K. Wang, T.P. Lane,... ) ( Fujita s jumping cirrus & the above-anvil plumes) From: Wang P. K., 2007: The thermodynamic structure atop a penetrating convective thunderstorm. Atmos. Res., 83,
25 Cold-U shaped storms Other possible explanations (discussed either in the past, or recently): Transparency effects... partial IR transparency of the cloud top at the warm area region, thus the radiance originating at the lower, warmer layers inside the cloud; Warm-dome mechanism... higher elevated storm-top dome (not the overshooting tops themselves!!!), residing in the warmer lower stratosphere for a sufficiently long period, thus their skin temperature warmed up by the environmental air; Plume-masking mechanism... warmer above-anvil plume partially masking the downwind parts of the cold anvil cloud top - in combination with the cold-ring feature... (Setvák et al.)
26 References: Levizzani, V., and M. Setvák, 1996: Multispectral, high-resolution satellite observations of plumes on top of convective storms. J. Atmos. Sci., 53, Luderer, G., J. Trentmann, K. Hungershöfer, M. Herzog, M. Fromm, and M. O. Andreae, 2007: Small-scale mixing processes enhancing troposphere-to-stratosphere transport by pyro cumulonimbus storms. Atmos. Chem. Phys., 7, Setvák M., Doswell III C.A., 1991: The AVHRR Channel 3 Cloud Top Reflectivity of Convective Storms. Mon. Wea. Rev. 119, Setvák M., Rabin R.M., Doswell C.A., Levizzani V., 2003: Satellite observations of convective storm top features in the 1.6 and 3.7/3.9 m spectral bands. Atmos. Research, 67-68C, Setvák M., Rabin R.M., 2003: MODIS observations of deep convective cloud tops. Proc. The 2003 EUMETSAT Meteorological Satellite Conference, Weimar, Germany. EUM P39, ISBN , ISSN , Setvák M., Rabin R.M., Wang P.K., 2007: Contribution of the MODIS instrument to observations of deep convective storms and stratospheric moisture detection in GOES and MSG imagery. Atmos. Research, 83, Wang, P. K., 2007: The thermodynamic structure atop a penetrating convective thunderstorm. Atmos. Res., 83,
27 Link between storms exhibiting the cold-ring or cold-u features Transition of a cold-ring into a cold-u shaped storm: 26 May 2007, Germany 13:30 UTC 15:00 UTC
28 Link between storms exhibiting the cold-ring or cold-u features If a cold-ring shaped storm can transform itself into a cold-u shaped storm, could it be that the mechanisms forming the CWS and CWA are the same? Are the cold-ring and cold-u shaped storms a result of the same or similar processes? What may force the storm to transform itself from one form into another????
29 Link between storms exhibiting the cold-ring or cold-u features Model studies (Pao Wang et al.) indicate that decreasing or removing the wind shear results into a storm resembling a cold-ring, while higher shear forms a cold-u/v shape This might explain the fact that the cold-u shaped storms seem to be more common in the United States, while the cold-ring shaped storms are more common in Europe... possible impact of the wind-shear climatology?
30 Link between storms exhibiting the cold-ring or cold-u features However, possible problem (???) storms above Bulgaria and Romania, 22 April 2008 B A The cold-ring shaped storm B has developed in the track of cold-u shaped storm A, shortly after the storm A has dissipated. Several possible explanations of this: (1) different height of the cloud top of the two storms (thus different cloud-top relative winds); (2) different environment behind the storm A, (3) some mechanism related to the storm A forming its plume, in combination with consequent plume-masking effect...
31 Link between storms exhibiting the cold-ring or cold-u features If the future proves that the CWA of cold-u shaped storms and CWS of cold-ring shaped storms result from the same mechanism, then their naming should (and most likely will) be unified...
32 Cold-ring shaped storms of the 25 June 2006: - comparison of the MSG and radar data
33 25 June cold ring shaped storms, Czech Republic and Austria 14 km 10 km 5 km CZRAD radar composite 14:10 UTC
34 25 June cold ring shaped storms, Czech Republic and Austria Radar (Skalky) cross-section along the line A-B from the previous slide: 20 km Tropopause, km 15 km 10 km A 5 km B Experimental cross-section, extended up to 20 km, based on CAPPI products (step 0.5 km) derived from the radar reflectivity volume data (radar Skalky only!) Active parts of both storms penetrating high above the tropopause, up to about km!!!
35 25 June cold ring shaped storms, Czech Republic and Austria Sounding Praha Libuš (11520), 12:00 UTC
36 25 June cold ring shaped storms, Czech Republic and Austria Sounding Praha Libuš (11520), 18:00 UTC
37 25 June cold ring shaped storms, Czech Republic and Austria IR :00 UTC Evolution of the cold-ring feature
38 25 June cold ring shaped storms, Czech Republic and Austria IR :15 UTC Evolution of the cold-ring feature
39 25 June cold ring shaped storms, Czech Republic and Austria IR :30 UTC Evolution of the cold-ring feature
40 25 June cold ring shaped storms, Czech Republic and Austria IR :45 UTC Evolution of the cold-ring feature
41 25 June cold ring shaped storms, Czech Republic and Austria IR :00 UTC Evolution of the cold-ring feature
42 25 June cold ring shaped storms, Czech Republic and Austria IR :15 UTC Evolution of the cold-ring feature
43 25 June cold ring shaped storms, Czech Republic and Austria IR :30 UTC Evolution of the cold-ring feature
44 25 June cold ring shaped storms, Czech Republic and Austria IR :45 UTC Evolution of the cold-ring feature
45 25 June cold ring shaped storms, Czech Republic and Austria IR :00 UTC Evolution of the cold-ring feature
46 Discussion of the central warm spot (CWS) Meteosat-8 (MSG1) 14:00 UTC IR 10.8 Highest temperatures within the warm spot: 218 K Lowest temperatures within the cold ring: K
47 Discussion of the central warm spot (CWS) Meteosat-8 (MSG1) 14:00 UTC HRV Outline of the warm spot (from the IR 10.8 image) Area of the overshooting tops The warm spot is located at the downwind side of the overshooting tops and in their lee!!!
48 Discussion of the central warm spot (CWS) In principle, three possible explanations of the warm area: Partial IR transparency of the area, thus the radiance originating at the lower warmer layers; Wake effects, or gravity wave breaking effects, similar to those assumed to be the explanation of the cold-u/v shapes and CWA couplets; Higher elevated tops, residing in the warmer lower stratosphere for a sufficiently long period of time, warmed by the environmental air warm dome mechanism (or any combination of these)
49 Discussion of the central warm spot (CWS) To decide among these, it is necessary to know (as accurately as possible) the cloud top height and its microphysical composition Necessitates the use of radar (and lidar) cloud-top observations
50 Radar study of the 25 June 2006 storm top (radar echo tops) 14:10 radar Skalky Tropopause, km 20 km 15 km 10 km A 5 km B Praha-Libus Observations at 12Z 25 Jun PRES HGHT TEMP DWPT hpa m C C tropopause
51 Radar study of the 25 June 2006 storm top (radar echo tops) The fact that these tops are indeed well above the tropopause, in the warmer lower stratosphere, is important; however the crucial question is what is the location of these elevated tops relative to the features observed in the satellite images, with respect to the location of CWA and the cold ring When comparing the satellite and radar data, it is necessary to take into account the parallax shift (for the given location and height of the cloud top).
52 Parallax effect Parallax shift Nadir view, or surface observations (e.g. radar) Geostationary view Projection of various cloud-top features to surface ("georeferencing these) strongly depends on their height above ground and on scanning geometry
53 Radar study of the 25 June 2006 storm top (radar echo tops) Parallax shift (for the area of the storm) (LAT = N, LON = 14.3 E) h height of the top (above sea level) P... parallax total Pe parallax, eastward component Pn parallax, northward component
54 Radar study of the 25 June 2006 storm top (radar echo tops) Parallax shift (correction) usually applied to satellite imagery, according to the cloud top height, derived typically from IR BT. In the following case, the parallax shift was applied to the radar CAPPI images, as if these were viewed from the geostationary orbit. Reason for this approach is in the fact that the real cloud top height is difficult to retrieve from satellite data when overshooting tops and possible wake effects (CWS, CWA) are involved.
55 Radar study of the 25 June 2006 storm top (radar echo tops) Position of the cross-section A-B in standard radar projection.
56 Radar study of the 25 June 2006 storm top (radar echo tops) Position of the cross-section A-B in the radar projection (bottom left line) and after parallax shift for a level at 15.5 km (upper right line), shown in the IR10.8 BT image.
57 Radar study of the 25 June 2006 storm top (radar echo tops) A B Position of the cross-section A-B in the radar projection, shown in the IR10.8 BT image.
58 Radar study of the 25 June 2006 storm top (radar echo tops) A Overshooting tops at CAPPI 15.5 km B Position of the cross-section A-B and CAPPI 15.5 km, shown in the IR10.8 BT image.
59 Radar study of the 25 June 2006 storm top (radar echo tops) A B Position of the cross-section A-B and CAPPI 15.5 km in the radar projection (bottom left line) and after parallax shift for a level at 15.5 km (upper right line), shown in the IR10.8 BT image.
60 Radar study of the 25 June 2006 storm top (radar echo tops) A B Position of the cross-section A-B and CAPPI 15.5 km, both after parallax shift, shown in the IR10.8 BT image.
61 Radar study of the 25 June 2006 storm top (radar echo tops) These elevated tops appear to be a part of the cold ring area, not of the CWS!!! In the IR10.8 image continuous cloud shield, not a gap like here, in the radar data >>> the radar sees less of the cloud then the IR10.8 satellite band 20 km Tropopause, km 15 km 10 km A 5 km B
62 Radar study of the 25 June 2006 storm top (radar echo tops) Radar cross-section C-D and CAPPI 15.5 km after parallax shift shown in the IR10.8 BT image. The C-D plane was chosen to intersect the CWS; also it is oriented in the direction of parallax shift.
63 Radar study of the 25 June 2006 storm top (radar echo tops) Radar cross-section C-D and CAPPI 13.0 km (just above the tropopause) after parallax shift shown in the IR10.8 BT image.
64 Radar cross-sections (along line C-D) of the 25 June 2006 storm top
65 Radar cross-sections (along line C-D) of the 25 June 2006 storm top (CWS according to IR10.8)
66 Radar cross-sections (along line C-D) of the 25 June 2006 storm top
67 Radar cross-sections (along line C-D) of the 25 June 2006 storm top Since the CWS was located for most of its existence also above the cloud (echo) tops close to the tropopause, the warm dome mechanism can be most likely excluded.
68 Possible problems and errors: radar echo top and real cloud top (as seen by satellite in the IR10.8 band) are not the same, radar fails to detect smaller particles => possible underestimation of the cloud top height by the radar; radar beam width ambiguity of the echo top height of about ± 1.5 km (at 200 km distance and 15 km height); additional possible errors as a result of the CAPPI computation method (PPI => volume data => CAPPI => cross sections)
69 Possible problems and errors: Echo-top height uncertainty related to the beam width and distance from a radar
70 Summary In this case, the wave effect or gravity wave breaking mechanism seem to be more likely than the warm dome mechanism; Exceptional cloud-top heights for Central Europe of the storms from 25 June however, how many similar storms do occur here? Necessity to apply the parallax shift correction for similar studies; Storms exhibiting cold-ring or cold-u features appear in average much warmer than ordinary storms; however their tops may actually be significantly higher than those of the regular storms, thus these storms are likely to be more severe than the regular ones; Derived satellite products (namely CTH), and also storm tracking algorithms or rain estimates based on satellite IR data are likely to fail when treating storms with cold-ring or cold-u shapes (strongly underestimate these).
71 What next? Studies of other similar storm cases (satellites, ground radar, ) on national basis, depending on radar data availability; also utilizing the MSG rapid-scan data (might significantly help thanks to its 5-minute repeat cycle; Modeling of similar cases... cold-ring versus cold-u shaped storms (the role of storm environment, wind shear); RTM studies; Special attention to shape transitions and to the effect of plumemasking mechanism Use of CloudSat and CALIPSO observations: might significantly help, but a timing problem overpass of these satellites is too close to local noon, before the onset of any significant convection; Perhaps use of polarimetric research radars (where available);
72 21/22 June cold ring shaped storms, Austria Another example of CWS developing in the wake of overshooting tops: MSG IR10.8 warm spot (CWS) Parallax-shifted overshooting tops at radar CAPPI levels ~ km Due to storm s location and reach of it by radars in Austria, Czech Republic, Slovakia and Hungary, a good case for a possible joint study of the storm, for tests of merging the satellite and radar data (and parallax correction)...???
73 At least one mystery solved THE END
74
COLD-RING AND COLD-U/V SHAPED STORMS
MARTIN SETVÁK setvak@chmi.cz Czech Hydrometeorological Institute, Prague COLD-RING AND COLD-U/V SHAPED STORMS Version : 18 May 2009 What are the cold-ring and cold-u/v shaped storms? Appearance and terminology
More informationCHARACTERISTICS OF EMBEDDED WARM AREAS AND SURROUNDING COLD RINGS AND COLD-US
CHARACTERISTICS OF EMBEDDED WARM AREAS AND SURROUNDING COLD RINGS AND COLD-US Michaela Radová 1,2, Jindřich Šťástka 1,2, Jakub Seidl 3 (1) Department of Meteorology and Environment Protection, Faculty
More informationCzech Hydrometeorological Institute, Na Šabatce 17, CZ Praha 4, Czech Republic. 3
MOISTURE DETECTION ABOVE CONVECTIVE STORMS UTILIZING THE METHOD OF BRIGHTNESS TEMPERATURE DIFFERENCES BETWEEN WATER VAPOR AND IR WINDOW BANDS, BASED ON 2008 MSG RAPID SCAN SERVICE DATA Jindřich Šťástka1,2,
More informationOVERSHOOTING TOPS CHARACTERISTICS AND PROPERTIES
OVERSHOOTING TOPS CHARACTERISTICS AND PROPERTIES Michaela Valachová 1,2, Martin Setvák 2, Jindřich Šťástka 1,2 1 Charles University in Prague, Faculty of Mathematics and Physics, Department of Meteorology
More informationSATELLITE MONITORING OF THE CONVECTIVE STORMS
SATELLITE MONITORING OF THE CONVECTIVE STORMS FORECASTERS POINT OF VIEW Michaela Valachová, EUMETSAT Workshop at ECMWF User Meeting Reading, 13 June 2017 Central Forecasting Office, Prague michaela.valachova@chmi.cz
More informationJason C. Brunner * Cooperative Institute for Meteorological Satellite Studies (CIMSS)/University of Wisconsin, Madison, Wisconsin
P3.16 A QUANTITATIVE ANALYSIS OF THE ENHANCED-V FEATURE Jason C. Brunner * Cooperative Institute for Meteorological Satellite Studies (CIMSS)/University of Wisconsin, Madison, Wisconsin Steven A. Ackerman
More informationDetection and Monitoring Convective Storms by. Using MSG SEVIRI Image. Aydın Gürol ERTÜRK. Contents
Detection and Monitoring Convective Storms by 1 Using MSG SEVIRI Image Contents MSGView Software Cold U/V and Ring Shape Storm Tops Case Study, 2nd April 2011 Antalya, Türkiye Conclusion Aydın Gürol ERTÜRK
More informationEUMETSAT/15 TH AMS SATELLITE CONFERENCE
EUMETSAT/15 TH AMS SATELLITE CONFERENCE Toward An Objective Enhanced-V Detection Algorithm University of Wisconsin-Madison/CIMSS Jason Brunner, Wayne Feltz, John Moses, Robert Rabin, and Steven Ackerman
More informationMSG Indian Ocean Data Coverage (IODC) Jochen Grandell & Sauli Joro
MSG Indian Ocean Data Coverage (IODC) Jochen Grandell & Sauli Joro 1 EUM/STG-SWG/42/17/VWG/03 v1, 7 8 Mach 2017 Topics Introduction MSG-IODC Overall Project Schedule Status Product validation Products
More informationNowcasting of Severe Weather from Satellite Images (for Southern
Nowcasting of Severe Weather from Satellite Images (for Southern Europe) Petra Mikuš Jurković Forecasting/ nowcasting of convective storms NWP models cannot well predict the exact location and intesity
More informationCASE STUDY OF THE 20 MAY 2008 TORNADIC STORM IN HUNGARY
CASE STUDY OF THE 20 MAY 2008 TORNADIC STORM IN HUNGARY Mária Putsay 1, Jochen Kerkmann 2 and Ildikó Szenyán 1 1 Hungarian Meteorological Service, H-1525 Budapest, P. O. Box 38, Hungary 2 EUMETSAT, am
More informationREPORT ON THE ACTIVITIES OF THE EUMETSAT-ESSL CONVECTION WORKING GROUP
REPORT ON THE ACTIVITIES OF THE EUMETSAT-ESSL CONVECTION WORKING GROUP Marianne König EUMETSAT, Eumetsat Allee 1, 64295 Darmstadt, Germany Abstract The focus of the Convection Working Group is to have
More informationThe thermodynamic structure atop a penetrating convective thunderstorm
Atmospheric Research 83 (2007) 254 262 www.elsevier.com/locate/atmos The thermodynamic structure atop a penetrating convective thunderstorm Pao K. Wang Department of Atmospheric and Oceanic Sciences, University
More informationGEOMETRIC CLOUD HEIGHTS FROM METEOSAT AND AVHRR. G. Garrett Campbell 1 and Kenneth Holmlund 2
GEOMETRIC CLOUD HEIGHTS FROM METEOSAT AND AVHRR G. Garrett Campbell 1 and Kenneth Holmlund 2 1 Cooperative Institute for Research in the Atmosphere Colorado State University 2 EUMETSAT ABSTRACT Geometric
More informationYELLOW SPOT IN THE CONVECTIVE STORMS RGB IMAGE CAUSED BY A PILEUS CLOUD
YELLOW SPOT IN THE CONVECTIVE STORMS RGB IMAGE CAUSED BY A PILEUS CLOUD André Simon, Mária Putsay, Ildikó Szenyán and Ákos Horváth Hungarian Meteorological Service, Kitaibel Pál u. 1, H-1024 Budapest,
More informationSTATISTICAL ANALYSIS ON SEVERE CONVECTIVE WEATHER COMBINING SATELLITE, CONVENTIONAL OBSERVATION AND NCEP DATA
12.12 STATISTICAL ANALYSIS ON SEVERE CONVECTIVE WEATHER COMBINING SATELLITE, CONVENTIONAL OBSERVATION AND NCEP DATA Zhu Yaping, Cheng Zhoujie, Liu Jianwen, Li Yaodong Institute of Aviation Meteorology
More informationSatellite observations of convective storm tops in the 1.6, 3.7 and 3.9 Am spectral bands
Atmospheric Research 67 68 (2003) 607 627 www.elsevier.com/locate/atmos Satellite observations of convective storm tops in the 1.6, 3.7 and 3.9 Am spectral bands Martin Setvák a, *, Robert M. Rabin b,
More informationSatellite-based Convection Nowcasting and Aviation Turbulence Applications
Satellite-based Convection Nowcasting and Aviation Turbulence Applications Kristopher Bedka Cooperative Institute for Meteorological Satellite Studies (CIMSS), University of Wisconsin-Madison In collaboration
More informationThis article appeared in a journal published by Elsevier. The attached copy is furnished to the author for internal non-commercial research and
This article appeared in a journal published by Elsevier. The attached copy is furnished to the author for internal non-commercial research and education use, including for instruction at the authors institution
More informationObjective Satellite-Based Detection of Overshooting Tops Using Infrared Window Channel Brightness Temperature Gradients
VOLUME 49 J O U R N A L O F A P P L I E D M E T E O R O L O G Y A N D C L I M A T O L O G Y FEBRUARY 2010 Objective Satellite-Based Detection of Overshooting Tops Using Infrared Window Channel Brightness
More informationValidation of Satellite-Based Objective Overshooting Cloud-Top Detection Methods Using CloudSat Cloud Profiling Radar Observations
OCTOBER 2012 B E D K A E T A L. 1811 Validation of Satellite-Based Objective Overshooting Cloud-Top Detection Methods Using CloudSat Cloud Profiling Radar Observations KRISTOPHER M. BEDKA Science Systems
More informationPICTURE OF THE MONTH. Some Frequently Overlooked Severe Thunderstorm Characteristics Observed on GOES Imagery: A Topic for Future Research
1529 PICTURE OF THE MONTH Some Frequently Overlooked Severe Thunderstorm Characteristics Observed on GOES Imagery: A Topic for Future Research JOHN F. WEAVER AND DAN LINDSEY NOAA/NESDIS/RAMM Team, Cooperative
More information6A.4 REFLECTIVE STORM TOPS: A SATELLITE METHOD FOR INFERRING THUNDERSTORM TOP MICROPHYSICAL STRUCTURE. Fort Collins, Colorado. Fort Collins, Colorado
6A.4 REFLECTIVE STORM TOPS: A SATELLITE METHOD FOR INFERRING THUNDERSTORM TOP MICROPHYSICAL STRUCTURE Daniel T. Lindsey 1* and Louie Grasso 2 1 NOAA/NESDIS/ORA/RAMMB Fort Collins, Colorado 2 Cooperative
More informationMSGVIEW: AN OPERATIONAL AND TRAINING TOOL TO PROCESS, ANALYZE AND VISUALIZATION OF MSG SEVIRI DATA
MSGVIEW: AN OPERATIONAL AND TRAINING TOOL TO PROCESS, ANALYZE AND VISUALIZATION OF MSG SEVIRI DATA Aydın Gürol Ertürk Turkish State Meteorological Service, Remote Sensing Division, CC 401, Kalaba Ankara,
More informationT-re Plots Generated from MSG Data in Severe Storms Forecasting Testing in Central Europe
WDS'11 Proceedings of Contributed Papers, Part III, 88 92, 2011. ISBN 978-80-7378-186-6 MATFYZPRESS T-re Plots Generated from MSG Data in Severe Storms Forecasting Testing in Central Europe M. Pokorný
More informationThunderstorm Downburst Prediction: An Integrated Remote Sensing Approach. Ken Pryor Center for Satellite Applications and Research (NOAA/NESDIS)
Thunderstorm Downburst Prediction: An Integrated Remote Sensing Approach Ken Pryor Center for Satellite Applications and Research (NOAA/NESDIS) Topics of Discussion Thunderstorm Life Cycle Thunderstorm
More informationClimatologies of ultra-low clouds over the southern West African monsoon region
Climatologies of ultra-low clouds over the southern West African monsoon region Andreas H. Fink 1, R. Schuster 1, R. van der Linden 1, J. M. Schrage 2, C. K. Akpanya 2, and C. Yorke 3 1 Institute of Geophysics
More informationCHARACTERISTICS OF LIGHTNING ACTIVITY IN DEEP CONVECTIVE CLOUDS WITH THE OVERSHOOTING TOPS
CHARACTERISTICS OF LIGHTNING ACTIVITY IN DEEP CONVECTIVE CLOUDS WITH THE OVERSHOOTING TOPS Petra Mikuš, Nataša Strelec Mahović Meteorological and Hydrological Service, Grič 3, Zagreb, Croatia Abstract
More informationRGB Experts and Developers Workshop 2017 Tokyo, Japan
"Application of the Sandwich Product and variations to this as used by Australian Forecasters and as presented during training at the Australian VLab Centre of Excellence". RGB Experts and Developers Workshop
More informationAOMSUC-6 Training Event
Effective use of high temporal and spatial resolution Himawari-8 data AOMSUC-6 Training Event Bodo Zeschke Australian Bureau of Meteorology Training Centre Australian VLab Centre of Excellence Content
More informationCHARACTERISATION OF STORM SEVERITY BY USE OF SELECTED CONVECTIVE CELL PARAMETERS DERIVED FROM SATELLITE DATA
CHARACTERISATION OF STORM SEVERITY BY USE OF SELECTED CONVECTIVE CELL PARAMETERS DERIVED FROM SATELLITE DATA Piotr Struzik Institute of Meteorology and Water Management, Satellite Remote Sensing Centre
More informationRGB Products: an easy and practical way to display multispectral satellite data (in combination with derived products)
RGB Products: an easy and practical way to display multispectral satellite data (in combination with derived products) Dr. Jochen Kerkmann Training Officer EUMETSAT Multi-channel GEO satellites today Him-08
More informationTHE FEASIBILITY OF EXTRACTING LOWLEVEL WIND BY TRACING LOW LEVEL MOISTURE OBSERVED IN IR IMAGERY OVER CLOUD FREE OCEAN AREA IN THE TROPICS
THE FEASIBILITY OF EXTRACTING LOWLEVEL WIND BY TRACING LOW LEVEL MOISTURE OBSERVED IN IR IMAGERY OVER CLOUD FREE OCEAN AREA IN THE TROPICS Toshiro Ihoue and Tetsuo Nakazawa Meteorological Research Institute
More informationHail nowcast exploiting radar and satellite observations
Federal Department of Home Affairs FDHA Federal Office of Meteorology and Climatology MeteoSwiss Hail nowcast exploiting radar and satellite observations Ulrich Hamann, Elena Leonarduzzi, Kristopher Bedka,
More informationMeteosat Third Generation (MTG): Lightning Imager and its products Jochen Grandell
1 Go to View menu and click on Slide Master to update this footer. Include DM reference, version number and date Meteosat Third Generation (MTG): Lightning Imager and its products Jochen Grandell Topics
More informationSATELLITE SIGNATURES ASSOCIATED WITH SIGNIFICANT CONVECTIVELY-INDUCED TURBULENCE EVENTS
SATELLITE SIGNATURES ASSOCIATED WITH SIGNIFICANT CONVECTIVELY-INDUCED TURBULENCE EVENTS Kristopher Bedka 1, Wayne Feltz 1, John Mecikalski 2, Robert Sharman 3, Annelise Lenz 1, and Jordan Gerth 1 1 Cooperative
More informationFigure 1: Tephigram for radiosonde launched from Bath at 1100 UTC on 15 June 2005 (IOP 1). The CAPE and CIN are shaded dark and light gray,
Figure 1: Tephigram for radiosonde launched from Bath at 1100 UTC on 1 June 200 (IOP 1). The CAPE and CIN are shaded dark and light gray, respectively; the thin solid line partially bounding these areas
More informationMETEOSAT CONVECTIVE INITIATION PRODUCT WITH AND WITHOUT CLOUD TRACKING - EXPERIENCES
METEOSAT CONVECTIVE INITIATION PRODUCT WITH AND WITHOUT CLOUD TRACKING - EXPERIENCES Mária Putsay 1, Zsófia Kocsis 1, Marianne König 2, Ildikó Szenyán 1, Márta Diószeghy 1, André Simon 1 and Márk Rajnai
More informationTHE ATMOSPHERIC MOTION VECTOR RETRIEVAL SCHEME FOR METEOSAT SECOND GENERATION. Kenneth Holmlund. EUMETSAT Am Kavalleriesand Darmstadt Germany
THE ATMOSPHERIC MOTION VECTOR RETRIEVAL SCHEME FOR METEOSAT SECOND GENERATION Kenneth Holmlund EUMETSAT Am Kavalleriesand 31 64293 Darmstadt Germany ABSTRACT The advent of the Meteosat Second Generation
More informationINTERPRETATION OF CLOUD. Tetsuya Theodore Fujita. The University of Chicago 5734 Ellis Avenue Chicago, Illinois U.S.A.
INTERPRETATION OF CLOUD WINDS Tetsuya Theodore Fujita The University of Chicago 5734 Ellis Avenue Chicago, Illinois 60637 U.S.A. A B S T R A C T Since the mid 1960s, when geostationary satellite data became
More informationApplications of multi-spectral satellite data
Applications of multi-spectral satellite data Jochen Kerkmann EUMETSAT, Satellite Meteorologist, Training Officer Adjusted by E de Coning South African Weather Service Content 1. Why should we use RGBs?
More informationTHE WISCONSIN DYNAMICAL/MICROPHYSICAL MODEL (WISCDYMM) AND THE USE OF IT TO INTERPRET SATELLITE OBSERVED STORM DYNAMICS
THE WISCONSIN DYNAMICAL/MICROPHYSICAL MODEL (WISCDYMM) AND THE USE OF IT TO INTERPRET SATELLITE OBSERVED STORM DYNAMICS Pao K. Wang Department of Atmospheric and Oceanic Sciences University of Wisconsin-Madison
More informationRain rate retrieval using the 183-WSL algorithm
Rain rate retrieval using the 183-WSL algorithm S. Laviola, and V. Levizzani Institute of Atmospheric Sciences and Climate, National Research Council Bologna, Italy (s.laviola@isac.cnr.it) ABSTRACT High
More informationSmall-scale mixing processes enhancing troposphere-to-stratosphere transport by pyro-cumulonimbus storms
Author(s) 2007. This work is licensed under a Creative Commons License. Atmospheric Chemistry and Physics Small-scale mixing processes enhancing troposphere-to-stratosphere transport by pyro-cumulonimbus
More informationMSG system over view
MSG system over view 1 Introduction METEOSAT SECOND GENERATION Overview 2 MSG Missions and Services 3 The SEVIRI Instrument 4 The MSG Ground Segment 5 SAF Network 6 Conclusions METEOSAT SECOND GENERATION
More informationThe origin of the gullwing-shaped cirrus above an Argentinian thunderstorm as seen in CALIPSO images
PUBLICATIONS Journal of Geophysical Research: Atmospheres RESEARCH ARTICLE Key Points: CALIPSO satellite images show gullwing-shaped cirrus above the anvil of some thunderstorms Gullwing cirrus indicates
More informationUsing McIDAS-V for Satellite-Based Thunderstorm Research and Product Development
Using McIDAS-V for Satellite-Based Thunderstorm Research and Product Development Kristopher Bedka UW-Madison, SSEC/CIMSS In Collaboration With: Tom Rink, Jessica Staude, Tom Whittaker, Wayne Feltz, and
More informationMcIDAS Activities Within The NASA Langley Research Center Clouds And Radiation Group
McIDAS Activities Within The NASA Langley Research Center Clouds And Radiation Group Kristopher Bedka Science Systems and Applications Inc @ NASA LaRC In Collaboration With (in alphabetical order) J. K.
More informationRapidly Developing Thunderstorm (RDT)
Rapidly Developing Thunderstorm (RDT) Jean-Marc Moisselin, Frédéric Autones Météo-France Nowcasting Department 42, av. Gaspard Coriolis 31057 Toulouse France jean-marc.moisselin@meteo.fr EUMETRAIN Convection
More informationAtmospheric Motion Vectors: Product Guide
Atmospheric Motion Vectors: Product Guide Doc.No. Issue : : EUM/TSS/MAN/14/786435 v1a EUMETSAT Eumetsat-Allee 1, D-64295 Darmstadt, Germany Tel: +49 6151 807-7 Fax: +49 6151 807 555 Date : 9 April 2015
More informationTool for Storm Analysis Using Multiple Data Sets
Tool for Storm Analysis Using Multiple Data Sets Robert M. Rabin 1,2 and Tom Whittaker 2 1 NOAA/National Severe Storms Laboratory, Norman OK 73069, USA 2 Cooperative Institute for Meteorological Satellite
More informationSevere storms over the Mediterranean Sea: A satellite and model analysis
National Research Council of Italy Severe storms over the Mediterranean Sea: A satellite and model analysis V. Levizzani, S. Laviola, A. Malvaldi, M. M. Miglietta, and E. Cattani 6 th International Precipitation
More informationQUALITY OF MPEF DIVERGENCE PRODUCT AS A TOOL FOR VERY SHORT RANGE FORECASTING OF CONVECTION
QUALITY OF MPEF DIVERGENCE PRODUCT AS A TOOL FOR VERY SHORT RANGE FORECASTING OF CONVECTION C.G. Georgiev 1, P. Santurette 2 1 National Institute of Meteorology and Hydrology, Bulgarian Academy of Sciences
More informationFor the operational forecaster one important precondition for the diagnosis and prediction of
Initiation of Deep Moist Convection at WV-Boundaries Vienna, Austria For the operational forecaster one important precondition for the diagnosis and prediction of convective activity is the availability
More informationThe water vapour channels of SEVIRI (Meteosat). An introduction
The water vapour channels of SEVIRI (Meteosat). An introduction jose.prieto@eumetsat.int Cachoeira P. July 2006 Formats 1.5 1 Objectives 2 Describe the characteristics of WV channels on board of SEVIRI
More informationJudit Kerényi. OMSZ - Hungarian Meteorological Service, Budapest, Hungary. H-1525 Budapest, P.O.Box 38, Hungary.
SATELLITE-DERIVED PRECIPITATION ESTIMATIONS DEVELOPED BY THE HYDROLOGY SAF PROJECT CASE STUDIES FOR THE INVESTIGATION OF THEIR ACCURACY AND FEATURES IN HUNGARY Judit Kerényi OMSZ - Hungarian Meteorological
More informationLecture 19: Operational Remote Sensing in Visible, IR, and Microwave Channels
MET 4994 Remote Sensing: Radar and Satellite Meteorology MET 5994 Remote Sensing in Meteorology Lecture 19: Operational Remote Sensing in Visible, IR, and Microwave Channels Before you use data from any
More information4/18/2010. National Weather Service. Severe Weather Forecasting: A Western North Carolina Case Study
National Weather Service Severe Weather Forecasting: A Western North Carolina Case Study Laurence G. Lee Science and Operations Officer National Weather Service Greer, SC Plus 13 River Forecast Centers
More information1. INTRODUCTION. investigating the differences in actual cloud microphysics.
MICROPHYSICAL PROPERTIES OF DEVELOPING VERSUS NON-DEVELOPING CLOUD CLUSTERS DURING TROPICAL CYCLOGENESIS 4B.5 Nathan D. Johnson,* William C. Conant, and Elizabeth A. Ritchie Department of Atmospheric Sciences,
More informationComparison of cloud statistics from Meteosat with regional climate model data
Comparison of cloud statistics from Meteosat with regional climate model data R. Huckle, F. Olesen, G. Schädler Institut für Meteorologie und Klimaforschung, Forschungszentrum Karlsruhe, Germany (roger.huckle@imk.fzk.de
More informationNear Real-time Cloud Classification, Mesoscale Winds, and Convective Initiation Fields from MSG Data
Near Real-time Cloud Classification, Mesoscale Winds, and Convective Initiation Fields from MSG Data Wayne Feltz *, J. Mecikalski, and K. Bedka * Cooperative Institute of Meteorological Satellite Studies
More informationThe development and evolution of deep convection and heavy rainfall
The development and evolution of deep convection and heavy rainfall Unique in spectra, space and time The spatial and temporal domains of the phenomena being investigated drive the satellite s spectral
More informationDetailed Cloud Motions from Satellite Imagery Taken at Thirty Second One and Three Minute Intervals
Detailed Cloud Motions from Satellite Imagery Taken at Thirty Second One and Three Minute Intervals James F.W. Purdom NOAA/NESDIS/RAMM Branch CIRA Colorado State University W. Laporte Avenue Fort Collins,
More informationSUPER-RAPID SCAN SATELLITE IMAGERY ANALYSIS OF TWO HAILSTORMS SAMPLED BY HAILSTONE
SUPER-RAPID SCAN SATELLITE IMAGERY ANALYSIS OF TWO HAILSTORMS SAMPLED BY HAILSTONE Jennifer M. Laflin* and Scott F. Blair NOAA/NWS Kansas City/Pleasant Hill, Missouri Chad Gravelle NOAA/NWS Operations
More informationCombining Polar Hyper-spectral and Geostationary Multi-spectral Sounding Data A Method to Optimize Sounding Spatial and Temporal Resolution
Combining Polar Hyper-spectral and Geostationary Multi-spectral Sounding Data A Method to Optimize Sounding Spatial and Temporal Resolution W. L. Smith 1,2, E. Weisz 1, and J. McNabb 2 1 University of
More informationHow to display RGB imagery by SATAID
How to display RGB imagery by SATAID Akihiro SHIMIZU Meteorological Satellite Center (MSC), Japan Meteorological Agency (JMA) Ver. 2015110500 RGB imagery on SATAID SATAID software has a function of overlapping
More informationA HIGH RESOLUTION EUROPEAN CLOUD CLIMATOLOGY FROM 15 YEARS OF NOAA/AVHRR DATA
A HIGH RESOLUTION EUROPEAN CLOUD CLIMATOLOGY FROM 15 YEARS OF NOAA/AVHRR DATA R. Meerkötter 1, G. Gesell 2, V. Grewe 1, C. König 1, S. Lohmann 1, H. Mannstein 1 Deutsches Zentrum für Luft- und Raumfahrt
More informationCloud analysis from METEOSAT data using image segmentation for climate model verification
Cloud analysis from METEOSAT data using image segmentation for climate model verification R. Huckle 1, F. Olesen 2 Institut für Meteorologie und Klimaforschung, 1 University of Karlsruhe, 2 Forschungszentrum
More informationMeteorological product extraction: Making use of MSG imagery
Meteorological product extraction: Making use of MSG imagery Kenneth Holmlund, Simon Elliott, Leo van de Berg, Stephen Tjemkes* Meteorological Operations Division *Meteorological Division EUMETSAT Am Kavalleriesand
More informationDetection of convective overshooting tops using Himawari-8 AHI, CloudSat CPR, and CALIPSO data
Detection of convective overshooting tops using Himawari-8 AHI, CloudSat CPR, and CALIPSO data Miae Kim¹, Jungho Im¹, Seonyoung Park¹ ¹Ulsan National Institute of Science and Technology (UNIST), South
More informationPRECIPITATION ESTIMATION FROM INFRARED SATELLITE IMAGERY
PRECIPITATION ESTIMATION FROM INFRARED SATELLITE IMAGERY A.M. BRASJEN AUGUST 2014 1 2 PRECIPITATION ESTIMATION FROM INFRARED SATELLITE IMAGERY MASTER S THESIS AUGUST 2014 A.M. BRASJEN Department of Geoscience
More informationLecture 4b: Meteorological Satellites and Instruments. Acknowledgement: Dr. S. Kidder at Colorado State Univ.
Lecture 4b: Meteorological Satellites and Instruments Acknowledgement: Dr. S. Kidder at Colorado State Univ. US Geostationary satellites - GOES (Geostationary Operational Environmental Satellites) US
More informationNUMERICAL EXPERIMENTS USING CLOUD MOTION WINDS AT ECMWF GRAEME KELLY. ECMWF, Shinfield Park, Reading ABSTRACT
NUMERICAL EXPERIMENTS USING CLOUD MOTION WINDS AT ECMWF GRAEME KELLY ECMWF, Shinfield Park, Reading ABSTRACT Recent monitoring of cloud motion winds (SATOBs) at ECMWF has shown an improvement in quality.
More informationMike Fromm, Naval Research Laboratory Washington, DC
a b c Mike Fromm, Naval Research Laboratory Washington, DC d Particlelarly Interesting Science: the Meaning, Marvels and Mysteries of Pyrocumulonimbus Grimsvötn (Iceland) volcano June 2011 Warm Fire (Arizona)
More informationDetailed flow, hydrometeor and lightning characteristics of an isolated, hail producing thunderstorm during COPS
Detailed flow, hydrometeor and lightning characteristics of an isolated, hail producing thunderstorm during COPS, Martin Hagen, Hartmut Höller, Hans Volkert Institut für Physik der Atmosphäre, DLR Oberpfaffenhofen
More informationChapter 14 Thunderstorm Fundamentals
Chapter overview: Thunderstorm appearance Thunderstorm cells and evolution Thunderstorm types and organization o Single cell thunderstorms o Multicell thunderstorms o Orographic thunderstorms o Severe
More informationSatellite-based Convective Initiation Nowcasting System Improvements Expected from the MTG FCI Meteosat Third Generation Capability.
Satellite-based Convective Initiation Nowcasting System Improvements Expected from the MTG FCI Meteosat Third Generation Capability Final Report EUM/CO/07/4600000405/JKG Technical Report John R. Mecikalski
More informationInner core dynamics: Eyewall Replacement and hot towers
Inner core dynamics: Eyewall Replacement and hot towers FIU Undergraduate Hurricane Internship Lecture 4 8/13/2012 Why inner core dynamics is important? Current TC intensity and structure forecasts contain
More informationGOES Climatology and Analysis of Thunderstorms with Enhanced 3.9- m Reflectivity
2342 M O N T H L Y W E A T H E R R E V I E W VOLUME 134 GOES Climatology and Analysis of Thunderstorms with Enhanced 3.9- m Reflectivity DANIEL T. LINDSEY AND DONALD W. HILLGER NOAA/NESDIS/ORA/RAMMB, Fort
More informationNEFODINA: A TOOL FOR AUTOMATIC DETECTION OF SEVERE CONVECTIVE PHENOMENA
NEFODINA: A TOOL FOR AUTOMATIC DETECTION OF SEVERE CONVECTIVE PHENOMENA Davide MELFI IAFMS, Centro Operativo per la Meteorologia, Pomezia (Rome), Italy Abstract The NEFODINA (DYNAmic NEFOanalisys) product
More informationA new Approach to the Detection and Tracking of Mesoscale Convective Systems in the Tropics using MSG
new pproach to the Detection and Tracking of Mesoscale Convective Systems in the Tropics using MSG Courtesy of STMOS LMD Thomas Fiolleau Rémy Roca Outline of the talk Introduction the Hydrological and
More informationGENERATION OF HIMAWARI-8 AMVs USING THE FUTURE MTG AMV PROCESSOR
GENERATION OF HIMAWARI-8 AMVs USING THE FUTURE MTG AMV PROCESSOR Manuel Carranza 1, Régis Borde 2, Masahiro Hayashi 3 1 GMV Aerospace and Defence S.A. at EUMETSAT, Eumetsat Allee 1, D-64295 Darmstadt,
More informationGlobal Instability Index: Product Guide
Doc.No. Issue : : EUM/TSS/MAN/15/802106 v1c e-signed EUMETSAT Eumetsat-Allee 1, D-64295 Darmstadt, Germany Tel: +49 6151 807-7 Fax: +49 6151 807 555 Date : 2 September 2015 http://www.eumetsat.int WBS/DBS
More informationIntroduction of the Hyperspectral Environmental Suite (HES) on GOES-R and beyond
Introduction of the Hyperspectral Environmental Suite (HES) on GOES-R and beyond 1 Timothy J. Schmit, 2 Jun Li, 3 James Gurka 1 NOAA/NESDIS, Office of Research and Applications, Advanced Satellite Products
More informationTitle: The Impact of Convection on the Transport and Redistribution of Dust Aerosols
Authors: Kathryn Sauter, Tristan L'Ecuyer Title: The Impact of Convection on the Transport and Redistribution of Dust Aerosols Type of Presentation: Oral Short Abstract: The distribution of mineral dust
More informationAtmospheric Motions Derived From Space Based Measurements: A Look To The Near Future. James F.W. Purdom
Atmospheric Motions Derived From Space Based Measurements: A Look To The Near Future James F.W. Purdom Director, Office of Research and Applications NOAA/NESDIS 1. Introduction This short note addresses
More informationRemote Sensing in Meteorology: Satellites and Radar. AT 351 Lab 10 April 2, Remote Sensing
Remote Sensing in Meteorology: Satellites and Radar AT 351 Lab 10 April 2, 2008 Remote Sensing Remote sensing is gathering information about something without being in physical contact with it typically
More informationNEW SCHEME TO IMPROVE THE DETECTION OF RAINY CLOUDS IN PUERTO RICO
NEW SCHEME TO IMPROVE THE DETECTION OF RAINY CLOUDS IN PUERTO RICO Joan Manuel Castro Sánchez Advisor Dr. Nazario Ramirez UPRM NOAA CREST PRYSIG 2016 October 7, 2016 Introduction A cloud rainfall event
More informationOn the Satellite Determination of Multilayered Multiphase Cloud Properties. Science Systems and Applications, Inc., Hampton, Virginia 2
JP1.10 On the Satellite Determination of Multilayered Multiphase Cloud Properties Fu-Lung Chang 1 *, Patrick Minnis 2, Sunny Sun-Mack 1, Louis Nguyen 1, Yan Chen 2 1 Science Systems and Applications, Inc.,
More informationMeasurements from Geostationary Satellite
The Fifth Asia/Oceania Meteorological Satellite Users' Conference (2014) Characteristics of Multi-spectral Measurements from Geostationary Satellite during Convections over North China Lin Yinjing Severe
More informationThunderstorm: a cumulonimbus cloud or collection of cumulonimbus clouds featuring vigorous updrafts, precipitation and lightning
Thunderstorm: a cumulonimbus cloud or collection of cumulonimbus clouds featuring vigorous updrafts, precipitation and lightning Thunderstorm: a cumulonimbus cloud or collection of cumulonimbus clouds
More informationEUMETSAT Satellite Programmes Use of McIDAS at EUMETSAT
EUMETSAT Satellite Programmes Use of McIDAS at EUMETSAT Marianne König Peter Miu McIDAS Users' Group Meeting, 07-10 May 2012 Slide 1 EUMETSAT Headquarters Darmstadt McIDAS Users' Group Meeting, 07-10 May
More informationA statistical approach for rainfall confidence estimation using MSG-SEVIRI observations
A statistical approach for rainfall confidence estimation using MSG-SEVIRI observations Elisabetta Ricciardelli*, Filomena Romano*, Nico Cimini*, Frank Silvio Marzano, Vincenzo Cuomo* *Institute of Methodologies
More informationObservations needed for verification of additional forecast products
Observations needed for verification of additional forecast products Clive Wilson ( & Marion Mittermaier) 12th Workshop on Meteorological Operational Systems, ECMWF, 2-6 November 2009 Additional forecast
More informationSAFNWC/MSG SEVIRI CLOUD PRODUCTS
SAFNWC/MSG SEVIRI CLOUD PRODUCTS M. Derrien and H. Le Gléau Météo-France / DP / Centre de Météorologie Spatiale BP 147 22302 Lannion. France ABSTRACT Within the SAF in support to Nowcasting and Very Short
More informationMESOSCALE WINDS IN VICINITY OF CONVECTION AND WINTER STORMS. Robert M. Rabin
MESOSCALE WINDS IN VICINITY OF CONVECTION AND WINTER STORMS Robert M. Rabin NOAA/National Severe Storms Lab (NSSL), Norman, OK Cooperative Institute for Meteorological Satellite Studies (CIMSS), Madison,
More informationSatellite Meteorology. Protecting Life and Property Around the World
Satellite Meteorology Protecting Life and Property Around the World The Value of Forecasting Severe Weather Flooding events across Europe in August 2002 cost in the region of 20 billion; 20,000 people
More informationTitle Slide: AWIPS screengrab of AVHRR data fog product, cloud products, and POES sounding locations.
Title Slide: AWIPS screengrab of AVHRR data fog product, cloud products, and POES sounding locations. Slide 2: 3 frames: Global tracks for NOAA19 (frame 1); NOAA-19 tracks over CONUS (frame 2); NOAA-19
More informationOCND Convective Cloud Heights
OCND Convective Cloud Heights NRL Satellite Meteorological Applications Monterey, CA Outline: I. Background II. Outline of Method a. North/South Domains b. Strengths/Weaknesses III. Protocols of the Aviation
More informationImpact of the 2002 stratospheric warming in the southern hemisphere on the tropical cirrus clouds and convective activity
The Third International SOWER meeting,, Lake Shikotsu,, July 18-20, 2006 1 Impact of the 2002 stratospheric warming in the southern hemisphere on the tropical cirrus clouds and convective activity Eguchi,
More information