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Mesoscale Convective Systems Observed by CloudSat

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Presentation on theme: "Mesoscale Convective Systems Observed by CloudSat"— Presentation transcript:

1 Mesoscale Convective Systems Observed by CloudSat
Robert A. Houze, PI Study 1: Jasmine Cetrone Study 2: Jian Yuan CloudSat Science Team Meeting, Seattle, 20 August 2008

2 Goal: Structure and composition of MCS Anvils
AC AS

3 Study 1: Identify MCSs by tracking
West Africa Maritime Continent Bay of Bengal

4 Find MCS Anvils Find potential MCS signal in CPR data
Track cloud systems in geostationary satellite data to decide if MCS Tb<208K over 100-km scale at some point in its lifetime Find anvil portion of CPR signal Non-precipitating anvil if less than -10 dBZ at all levels below 5 km

5 Analysis of Anvils Number of cases: Anvils stratified by thickness
82 over West Africa 78 over the Maritime Continent 42 over the Bay of Bengal Anvils stratified by thickness Thin (0-2 km), Medium (2-6 km) and Thick (>6 km) Plotted CFADs

6 All Anvil CFADs Thin, medium, thick combined Diagonal mode
West Africa Thin, medium, thick combined Diagonal mode Not as high over West Africa Even though convection more intense TRMM shows rain echoes higher! Large ice particles? Mar. Cont. Bay Bengal

7 Thick Anvil Results West Africa thick anvils
High reflectivity peak ~8 km another indication of larger ice Bimodal structure at low-reflectivity values Confirmed by ARM ground-based cloud radars Lower maximum may be a result aggregation Mar. Cont. Bay Bengal

8 ARM Thick Anvil Results
Niamey Darwin

9 Study 2: Objective Identification of MCSs
Rain Rate: AMSR-E Aqua L2B Global Swath Rain Rate (AE_Rain). Horizontal Cloud Structure: MODIS MODIS/Aqua Clouds 1km and 5km 5-Min L2 Wide Swath Subset along CloudSat V2 at GES DISC(GES_DISC_MAC06S1_v2) Vertical Cloud Structure: CloudSat Products 2B-GEOPROF; 2B-CWC-RO; 2B-FLXHR; …

10 Identification of High Cloud Features
MODIS Tb11 (K) AMSR/E Rain (mm/h) COMBINED Cloud Element Rain Core FEATURE MASK

11 Further Analysis Identify MCSs: Stratify MCSs
Rain area 2,000-40,000 km2 Mean Tb11 <235 K Rain area with R>10 mm/hr > 200km2 Stratify MCSs Cold: Tb11_min<208 K Warm: 208 Ko<Tb11_min<220 K Subdivide Cold and Warm by size

12 Global-seasonal distribution of MCS
Largest 20 % of “Cold” MCSs (>14,000 km2) Latitude Nº 50% of cold MCS precip

13 Combined Analysis (CPR data in MCSs)
CFAD of thick and Thin Anvils of Cold MCS The color map shows the fraction (number of occurrence at each height-reflectivity bin normalized by the total number of valid sample at 11 km).

14 Combined Analysis Thickness-Distance Distribution for Anvils of Cold MCSs
West Pacific ( E)

15 Conclusions & Future Work
Temporally tracked MCSs Used manual tracking to identify MCSs CFADs suggest larger ice particles over Africa Thick anvils show a bimodal signature at low reflectivity confirmed by ARM cloud radars Objective identification of MCSs Used MODIS and AMSR E to identify MCSs Reasonable global patterns of MCS types Vertical structure agrees with manually tracked MCSs Next work Statistics of structure, composition, and radiative heating in MCS anvils

16 Thank You

17 Thank You

18 Study 2: Data AMSR-E/Aqua L2B Global Swath Rain Rate (AE_Rain).
MODIS/Aqua Clouds 1km and 5km 5-Min L2 Wide Swath Subset along CloudSat V2 at GES DISC(GES_DISC_MAC06S1_v2) CloudSat products (2B-GEOPROF;2B- CWC-RO; 2B-FLXHR…)

19 Global-seasonal distribution of MCS
Smallest 40 % of “Cold” MCSs ( km2) Latitude Nº 15% of precip in cold MCS category

20 Vertical Structure Categories From CloudSat
54 % 9 % 3% 5% 7% 45% Overlapping within each type of cloud has been considered. Overlapping between different types are not taken into account.

21 Methodology Build the data base of deep cloud system (precipitating and non precipitating) basd on AMSR-E rain rate and MODIS Tb11. Group deep cloud systems into different categories based on their properties(size of the raining area, coldest Tb11, intense raining area etc. Co-locate CloudSat data with the cloud database and determine their parenting MCSs. Composite cloud structures according to their parenting MCSs.

22 High Cloud System identification
Co-location of different datasets 'Nearest neighbor' matching, convert AE-Rain to MODIS resolution Picking high cloud systems Determining high cloud boundary based on Tb11 gradients and rain fall pattern Determining cloud cores (raining or non-raining cold cores) in multi-core systems

23 MCS Definition MCS1:Size>2000km2; Tb11_min<208Ko; Tb11_mean<235Ko; area with R>10mm/hr bigger than 200km2 MCS2:Size>2000km2,208Ko<Tb11_min<228Ko, Tb11_mean<235Ko; area with R>10mm/hr bigger than 200km2

24 Global-seasonal distribution of MCS Large “Warm” MCSs (10000-21360km2)

25 Thick Anvil Results Bimodal structure at low-reflectivity values
West Africa Bimodal structure at low-reflectivity values Confirmed by ARM ground-based cloud radars Lower maximum may be a result aggregation West Africa thick anvils Reach lower heights than other regions despite having tallest precipitation echoes High reflectivity peak ~8 km may indicate larger ice Mar. Cont. Bay Bengal

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