SATELLITE OBSERVATION OF THE DAILY VARIATION OF THIN CIRRUS
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1 SATELLITE OBSERVATION OF THE DAILY VARIATION OF THIN CIRRUS Hermann Mannstein and Stephan Kox ATMOS 2012 Bruges, Folie 1
2 Why cirrus? Folie 2
3 Warum Eiswolken? Folie 3
4 Folie 4
5 Folie 5
6 Folie 6
7 What is missing, what can we do? Daily cycle all satellite data (exept ISCCP) is based on sunsynchronous orbits (NOAA-XX, Aqua,Terra, EPS, A-Train, CALIOP) Observation of the life cycle of clouds Only geostationary satellites can help Folie 7
8 Meteosat Cirrus Detection Algorithm - MeCiDa Cirrus coverage 0.25 x 0.25 Classical algorithm, 6 tests combine spectral and structural information from METEOSAT IR channels Folie 8
9 CALIPSO flies as a part of the NASA afternoon constellation (A-Train), launched in April 2006 polar-orbiting, 705 km altitude carries the Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) CALIOP: Profiles of atmospheric features Optical properties of cirrus clouds Sensitive to cirrus clouds (τ 0.01) Folie 9
10 Folie 10
11 SEVIRI oversampling: Meteorite over Africa Folie 11
12 COCS Dataset Based on a neuronal network During training: CALIOP-measuremts are given as the TRUTH, Containing 8 mio datasets Folie 12
13 Training dataset based on 5 km Cloudlayer product (level 2) of CALIOP Ice optical thickness (IOT) and Cirrus top altitude (TOP) Starting with June 2006, CALIOP delivers almost 4 years of data collocated in space and time to the SEVIRI disc Filter methods to retrieve only cirrus clouds Midlayer temperature -30 Extinction quality flag climatology-dependent threshold (T ): TOP min =4.5 km, TOP max =9.5 km MeCiDA Folie 13
14 Folie 14
15 Folie 15
16 Standarddeviation: IOT = 0.25 COCS Validation with CALIOP TOP = 0.8 km Folie 16 > Optical properties of thin cirrus derived from the infrared channels of SEVIRI > Stephan Kox Folie 16
17 COCS at τ = 0.1 DE = 99.3% FAR = 4.9% Folie 17 > Optical properties of thin cirrus derived from the infrared channels of SEVIRI > Stephan Kox Folie 17
18 New CREW dataset cloud top height / km Ulrich Hamann, hamann@knmi.nl CREW-outlook KNMI 14 June 2012 Folie 18
19 COCS Validation with HSRL measurements PAZI-Campaign: Oct 18, 2008 DLRs Falcon measuring cirrus properties water vapor DIAL system (WALES) A. Ostler Folie 19 > Optical properties of thin cirrus derived from the infrared channels of SEVIRI > Stephan Kox Folie 19
20 COCS Validation Standarddeviation: IOT = 0.18 Detection of thin cirrus with high accuracy Folie 20 > Optical properties of thin cirrus derived from the infrared channels of SEVIRI > Stephan Kox Folie 20
21 COCS Examples 05 April 2009, Golden Day for ACTA (M. Vazquez - Navarro) Contrail-Cirri over Madeira and the Bay of Biskay, t = 15 min Folie 21 > Optical properties of thin cirrus derived from the infrared channels of SEVIRI > Stephan Kox Folie 21
22 COCS Examples 05 April 2009, Golden Day for ACTA (M. Vazquez - Navarro) Contrail-Cirri over Madeira and the Bay of Biskay, t = 15 min Folie 22 > Optical properties of thin cirrus derived from the infrared channels of SEVIRI > Stephan Kox Folie 22
23 COCS Examples 05 April 2009, ACTA detects Contrail Cirrus Rapid Scan Mode on SEVIRI (MSG-8), t = 5 min BTD T10.8-T12.0, ACTA COCS, IOT M. Vazquez-Navarro Folie 23 > Optical properties of thin cirrus derived from the infrared channels of SEVIRI > Stephan Kox Folie 23
24 COCS Examples 05 April 2009, ACTA detects Contrail Cirrus Rapid Scan Mode on SEVIRI (MSG-8), t = 5 min BTD T10.8-T12.0, ACTA COCS results for ACTA M. Vazquez-Navarro Folie 24 > Optical properties of thin cirrus derived from the infrared channels of SEVIRI > Stephan Kox Folie 24
25 COCS Results Folie 25 > Optical properties of thin cirrus derived from the infrared channels of SEVIRI > Stephan Kox Folie 25
26 COCS Results: mean daily cycle Folie 26 > Optical properties of thin cirrus derived from the infrared channels of SEVIRI > Stephan Kox Folie 26
27 COCS Results: Cirrus variations winter summer Folie 27 > Optical properties of thin cirrus derived from the infrared channels of SEVIRI > Stephan Kox Folie 27
28 COCS Next step: The COCS methode is currently expanded to deliver ice water path (IWP) with a new training dataset based on CALIOP s CLayer Products v3.01/3.02. (with no effect on the retrieval-runtime) The effective radius can then be derived by following assumptions (Key et al., 2002 ): COCS version 1 Optical thickness Top altitude COCS version 2 Optical thickness Top altitude - Ice water path - Effective radius Folie 28
29 Conclusions: COCS Outlook & Conclusions COCS is a new, fast method to derive optical properties of cirrus clouds during day and night time COCS is sensitive to thin cirrus, but limited to ice optical depths of 2.5 COCS shows good correlation with CALIOP and HSRL Several options for large and small scale lifetime analysis and intercomparisons Outlook: Analysis of the natural diurnal and seasonal cycle of cirrus clouds and its properties Implementing tracking option Folie 29 > Optical properties of thin cirrus derived from the infrared channels of SEVIRI > Stephan Kox Folie 29
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