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OVERSHOOTING CONVECTIVE CLOUD TOP HEIGHT ANALYSIS OVER CENTRAL EUROPE , SUMMERS 2009 - 2011

OVERSHOOTING CONVECTIVE CLOUD TOP HEIGHT ANALYSIS OVER CENTRAL EUROPE , SUMMERS 2009 - 2011. J án Kaňák Slovak Hydrometeorological Institute Bratislava Jan .kanak @shmu. sk Kristopher  Bedka Science Systems & Applications, Inc. @ NASA Langley Research Center

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OVERSHOOTING CONVECTIVE CLOUD TOP HEIGHT ANALYSIS OVER CENTRAL EUROPE , SUMMERS 2009 - 2011

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  1. OVERSHOOTING CONVECTIVE CLOUD TOP HEIGHT ANALYSIS OVER CENTRAL EUROPE, SUMMERS 2009-2011 Ján Kaňák Slovak Hydrometeorological InstituteBratislava Jan.kanak@shmu.sk Kristopher Bedka Science Systems & Applications, Inc. @ NASA Langley Research Center kristopher.m.bedka@nasa.gov AloisSokol Faculty of Mathematics, Physics and Informatics, Comenius University Bratislava Lojzo.s@gmail.com EUMETSAT Meteorological Satellite Conference, 3-7 September 2012, Sopot, Poland

  2. Part 1MotivationGeometrical backgroundViewMSG Measurement tool EUMETSAT Meteorological Satellite Conference, 3-7 September 2012, Sopot, Poland

  3. Motivation (1) Photo: 30thMay 2005 18:19 UTC Bratislava Satellite image: MSG channel 12, HRV Start time: 18:15 UTC The storm captured in this photo was located over the borders between north Austria and south Moravia A well-defined shadow was cast on cirrus clouds east of the storm from an overshooting cloud top (OT) According to the satellite image, the storm from was about 80 km to the NW of Bratislava EUMETSAT Meteorological Satellite Conference, 3-7 September 2012, Sopot, Poland

  4. Motivation (2) • Overshooting tops (OTs)indicate the presence of a strong updraft. Severe weather and aviation turbulence often occur in the vicinity of the OT region. • OTscan beobserved or inferred in visible and infrared satellite imagery • Fine temporal (<= 5 min) and spatial resolution (<= 1 km) satellite imagery are needed to highlight important details on OT time evolution and updraft intensity • Polar orbiting satellites provide fine spatial resolution but coarse time resolution • Geostationary satellites can provide sufficient time sampling of OTs in rapid scan operations and, in general, are more suitable for continuous observation and detection of OTs over wide regions • Operational satellite-based cloud top height algorithms will often fail to assign representative heights to OT pixels because they are colder than any temperature represented in a nearby rawinsonde or NWP mode profile • - The tropopause height is used as the default OT height when IR BT < profile temp • Knowledge of the OT height is very important to the aviation industry as pilots face the choice of whether to fly above or around an OT. Satellite-derived cloud heights are one of the few sources of observational guidance in many regions EUMETSAT Meteorological Satellite Conference, 3-7 September 2012, Sopot, Poland

  5. Motivation (3) The shadows cast by OT features upon the surrounding cirrus anvil cloud in low solar elevation angle conditions can be used to estimate the magnitude of OT penetration into the upper troposphere/lower stratosphere (UTLS) region The goal of this study is to utilize a combination of IR spatial gradients near OT signatures and the OT UTLS penetration magnitude observed by MSG SEVIRI to characterize the lapse rate associated with UTLS penetrating convection It is the hope that cloud top height algorithm developers could use IR spatial gradients in combination with lapse rate information to assign more representative heights to OTs EUMETSAT Meteorological Satellite Conference, 3-7 September 2012, Sopot, Poland

  6. To estimate OT height, we have to calculate Sun elevation angle at the OT position and to measure OT shadow length! Additionally we need to know value of Earth radius, mean land surface elevation above the sea level at the point S and cirrus layer height above the Earth surface. Sun elevation is calculated from apparent solar time at the measured point, right ascension and declination. Also parallax shift of OT top in the image should be considered to avoid uncertainties of the result. Geometrical background Sun rays OT Sun elevation angle OT height S (Shadow edge) Cirrus layer Length of OT shadow Cirrus layer height above the Earth surface Method is applicable only in case of low Sun elevation angles (lower then 25°), when the length of shadow is accurately measurable in 1 km HRV imagery Earth surface Earth radius EUMETSAT Meteorological Satellite Conference, 3-7 September 2012, Sopot, Poland

  7. ViewMSG Measurement tool Manual estimation of OT height above the anvil in two steps: a) Set Pointer elevation: 8055m a.s.l. Result: 1464m (height of OT) b) Adjust Pointer length Results: Sun elevation: 4,81° Shadow length: 59 pixels = 17 km OT height: 1464 m EUMETSAT Meteorological Satellite Conference, 3-7 September 2012, Sopot, Poland

  8. Part 2Description of statistical data setData distributionsRelations between Minimum OT BT, Anvil BT and OT Height EUMETSAT Meteorological Satellite Conference, 3-7 September 2012, Sopot, Poland

  9. Description of statistical data set Part 1 We worked with two independent statistical data sets: • OTs detectedby the Bedka et al (JAMC, 2010) algorithm - Detection is based on localization of the minimum OT BT, calculation of mean anvil BT (brightness temperature), calculation and thresholding of Min OT – anvil BT difference (OTs detected by IR). • OTs detected with ViewMSG measurement tool developed by Ján Kaňák - Detection is based on visual inspection of MSG HRV imagery, localization of OTs with well visible shadows over the anvils during low Sun elevation angles, calculation of shadow length and OT height (OTs detected by HRV). Both data sets represent June-August 2009, 2010 and 2011. 15-minute operational MSG SEVIRI IR 10,8µm and HRV channel observations were used EUMETSAT Meteorological Satellite Conference, 3-7 September 2012, Sopot, Poland

  10. Description of statistical data set Part 2 Month Num 200906 4450 200907 2353 200908 1442 201006 3262 201007 1839 201008 1110 201106 3421 201107 1126 201108 1897 Total 20900 OTs by HRV algorithm: Date and time Latitude Longitude Apparent solar time Sun elevation OT height Month Num 200906 776 200907 714 200908 830 201006 704 201007 463 201008 242 201106 611 201107 376 201108 361 Total 5077 Data processing: Co-location of OTs limited to 10 km Resulting co-located pairs were further analyzed with the aim to find relations between anvil BT, OT BT, Sun elevation and OT height. OTs by IR algorithm: Date and time Latitude Longitude Minimum OT brightness temp Minimum OT – Anvil BT difference Relative number of anvil pixels EUMETSAT Meteorological Satellite Conference, 3-7 September 2012, Sopot, Poland

  11. Data distributions (co-location difference) During first co-location attempt 15km co-location difference was used (blank columns). Distribution tail over 9,5km belongs to range out of MSG IR pixel native resolution. We decided to cut off this tail with co-location threshold of 10km. Distribution became more symmetric with mean co-location difference about 4,5km Averaged co-location distance of selected data pairs finallyreached MSG native resolution over the region of central Europe for all processed months. MSG IR pixel native resolution in CE Europe Coarse visual OT identification approach was used for months July, August 2010, 2011. For the rest of months identification methodology was more precise.It is evident from lower mean co-location differences. EUMETSAT Meteorological Satellite Conference, 3-7 September 2012, Sopot, Poland

  12. Data distributions Important note: The next part of presentation will deal only with subset of co-located data cases. In chart below such cases are represented by green columns. Final co-located dataset was filteredby: OT height < 3000m Sun Elevation <15° Fraction of pixels surrounding OT considered anvil by Bedka method > 70% Ratio of IR-HRV pairs number and total HRV detections is quite low. Reasons are not only filtering, but also low efficiency of manual selection of OT with good visible shadows. EUMETSAT Meteorological Satellite Conference, 3-7 September 2012, Sopot, Poland

  13. Data distributions (anvil BT and Minimum OT BT) HRV method (blue) selects systematically colder anvils then IR method (red), shift is about 2K. 218 K 220 K HRV method (blue) selects systematically colder OTs then IR method (red), Shift is about 2K. 210 K 212 K In average OT is 8 degrees colder then anvil: (220-212 = 218-210 = 8K) Relative counting rate was used because of different total number of items in IR and HRV datasets. EUMETSAT Meteorological Satellite Conference, 3-7 September 2012, Sopot, Poland

  14. Relations between Minimum OT BT, Anvil BT and OT Height Part 1 Colder anvils produce also colder OTs. An average OT is 8 degrees colder then anvil. If dry adiabatic lapse rate is 9.8 K/km, averaged OT height = 8[K]/9.8[K/km]=816m. The average OT height based on shadows is 1800m, which is due to missing measurements for OT height < 1000m and subjective preference of higher OT cases. Averaged height = 1800m Missing measurements for OT < 1000m due to limitation of manual shadow technique Dry adiabatic lapse rate = 9.8 K/km (http://en.wikipedia.org/wiki/Lapse_rate) EUMETSAT Meteorological Satellite Conference, 3-7 September 2012, Sopot, Poland

  15. Relations between Minimum OT BT, Anvil BT and OT Height Part 2 Gain the Height dependence on both Min OT and Anvil BTs: Colder anvil produce colder and higher OT according lapse rate, which can be expressed by polynomial form but with strong bias from adiabatic theory (9.8K/km) y = -0,0118x2 + 0,4695x + 2,5899 EUMETSAT Meteorological Satellite Conference, 3-7 September 2012, Sopot, Poland

  16. Relations between Minimum OT BT, Anvil BT and OT Height Part 3 Dependence of OT height(BT diff) distribution on Sun elevation angle: Sun elevation angle The sequence of data filtered on Sun elevation to show how to obtain the most realistic dataset of co-located OTs.Finally all detections with Sun elevation higher then 15° were removed from processing. EUMETSAT Meteorological Satellite Conference, 3-7 September 2012, Sopot, Poland

  17. Error in OT-anvil IR BT difference resulting from low image resolution Courtesy of Scott Bachmeier (UW-CIMSS) Resolution of left image (~5.5 km GOES) is lower then right (~1 km MODIS), therefore the fine structuresandalso extremely low BT spotsare not resolved in the GOES image. It is the reason why Minimum OT BT can be higher then real value, mainly when horizontal size of OT is lower then pixel resolution. Recent studies have found a warm bias of ~9 K when OTs are examined in in geostationary vs. polar orbiting data Adding the 9 K bias to the OT-anvil BT vs HRV penetration height analysis would yield a lapse rate of 9.1 to 9.4 K/km that is much more realistic EUMETSAT Meteorological Satellite Conference, 3-7 September 2012, Sopot, Poland

  18. Part 3Sources of errors resulting from shadows location sun elevation anvil layer height and parallax shift low image resolutionExamples of correct and failed cases EUMETSAT Meteorological Satellite Conference, 3-7 September 2012, Sopot, Poland

  19. Sources of errors in OT penetration height estimation by HRV method • Error of visual location of shadow start at OT center (shadow head) (error is substantial) • OT center is not touching the shadow directly, set subjectively, no IR data used • Error of visual location of shadow end on the anvil (shadow tail)(error is substantial) • Shadow of one OT can be broken by another OT • Shadow tail is located out of anvil (out of projection area) • Anvil is too transparent or is not a plain • Observed cloud structures are not regular OTs and/or cirrus clouds • Error resulting from Sun elevation(error is substantial) • Too long shadows when elevation is very low (<2°), shadow beyond terminator • Too short shadows when elevation is very high (>25°) • Error resulting from parallax shift (error is negligible) • Correction implemented in the tool; necessity of manual adjustment • In some cases it is hard to allocate proper cloud structure to the shadow • Error resulting from absolute anvil layer height above Earth surface • Error can be compensated visually(error is negligible) Some mentioned errors are relative to native MSG HRV image resolution and some relate to subjective evaluation by observer. EUMETSAT Meteorological Satellite Conference, 3-7 September 2012, Sopot, Poland

  20. Error resulting from Sun elevation This plot was created using algorithm implemented in ViewMSGProcmeasurement tool. This error includes uncertainty in location of shadow headand shadow tail with assumption that shadow can be localized within the precision of MSG native resolution. Valid for central European region. EUMETSAT Meteorological Satellite Conference, 3-7 September 2012, Sopot, Poland

  21. Error resulting fromanvil layer height and parallax shift Measured shadow length Anvil layer Parallax shift Sea level Real shadow length Because parallax shift is too small in comparison to shadow length in prevalent number of cases, error resulting from parallax shift is negligible. In extreme case it is source of overestimation of shadow length. Can be corrected subjectively. Because anvil layer height is too small in comparison to Earth radius,error resulting from anvil layer height is negligible. Nevertheless correction of this error is implemented in measuring tool. EUMETSAT Meteorological Satellite Conference, 3-7 September 2012, Sopot, Poland

  22. Example 1 Failed 4.8.2009 07:15 UTC; Sun elevation: 38,5°; Estimated height: 5793m Estimation error: 2900m Comment: Sun elevation is very high; Error of estimation is around 3000m. EUMETSAT Meteorological Satellite Conference, 3-7 September 2012, Sopot, Poland

  23. Example 2 Failed 12.6.2010 16:15 UTC; Sun elevation: 19,4°; Estimated height: 5292m Estimation error: 1300m Comment: Shadow of OT is interrupted by another cloud structure. EUMETSAT Meteorological Satellite Conference, 3-7 September 2012, Sopot, Poland

  24. Example 3 Failed 16.6.2010 16:30 UTC; Sun elevation: 14,6°; Estimated height: 6090m Estimation error: 970m Comment: Shadow of OT is interrupted by another cloud structure. EUMETSAT Meteorological Satellite Conference, 3-7 September 2012, Sopot, Poland

  25. Example 4 Failed 13.7.2011 05:00 UTC; Sun elevation: 11,4°; Estimated height: 6494m Estimation error: 770m Comment: Structure of anvil is not a plain. Height of Cb over mid-level clouds was measured instead of OT. EUMETSAT Meteorological Satellite Conference, 3-7 September 2012, Sopot, Poland

  26. Example 5 Success 5.7.2009 17:45 UTC; Sun elevation: 4,3°; Estimated height: 1371m Estimation error: 250m Comment: Well depicted OT with shadow. Length of shadow well measureable. EUMETSAT Meteorological Satellite Conference, 3-7 September 2012, Sopot, Poland

  27. Example 6 Success 2.6.2010 18:00 UTC; Sun elevation: 3,6°; Estimated height: 1670m Estimation error: 205m Comment: Quite well depicted OT with shadow. Length of shadow well measureable. EUMETSAT Meteorological Satellite Conference, 3-7 September 2012, Sopot, Poland

  28. Example 7 Success 3.6.2010 17:45 UTC; Sun elevation: 5,1°; Estimated height: 1590m Estimation error: 315m Comment: OT shadowis measureable, case was added into processed data set. EUMETSAT Meteorological Satellite Conference, 3-7 September 2012, Sopot, Poland

  29. Example 8 Success 12.6.2010 17:30 UTC; Sun elevation: 10,6°; Estimated height: 2893m Estimation error: 730m Comment: Well depicted OT with shadow. Length of shadow well measureable. EUMETSAT Meteorological Satellite Conference, 3-7 September 2012, Sopot, Poland

  30. ConclusionsWe used significant dataset of OTs, more then 20000 detections from IR and 5000 from HRV SEVIRI imagery with the aim to show whether OTpenetration height is measurable by shadow technique and if some relations between IR BT and height parameters can be found.We identified some problems of shadow technique and their influence on the results. Thereafter we processed datasets to show relations. Only subset of IR and HRV data were coupled – co-located successfully. Main reasons are limited resources of manual shadow technique and different IR and HRV channels resolution.The trend line between OT penetration height and Min OT BT and Anvil BT difference we derived possible lapse rate of OT cooling above the anvil level from 3 to 7.3K/km, which is too low in comparison to generally valid value of 9.8K/kmWe assume that two factors – low IR resolution of SEVIRI imager and inability to detect very low OTs by shadow technique are the reasons of bias for lapse rate derived from statistical data set.We assume that comparison of time matched SEVIRI and early evening NOAA-17 AVHRR HRPT observations over Europe could help quantitatively show the bias and its relation to OT heightThis work was based only on 15-minute SEVIRI observations and it is not enough to estimate at what point in OT lifecycle was sampled.Rapid scan imagery with higher frequency (< 2.5 min from SEVIRI, 30 seconds from GOES-R ABI) can help to show where IR-Height relationfor OTs starts to break down from adiabatic theory as OTs warm via mixing with the stratospheric air EUMETSAT Meteorological Satellite Conference, 3-7 September 2012, Sopot, Poland

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