Application of Cloudnet data in the validation of SCIAMACHY cloud height products

Ping Wang Piet Stammes

KNMI, De Bilt, The Netherlands

CESAR Science day, 19 June, 2013

Overview• SCIAMACHY cloud products• Cloud retrieval algorithms from O2 A band • Validation data sets • Results• Summary

SCIAMACHY cloud products• ESA L2 (v5.02)Cloud top height and Cloud optical thickness are retrieved from SACURA. Cloud optical thickness is only retrieved for thick clouds, > 5. Cloud fraction is retrieved from PMDs (OCRA).

• FRESCO (v6)Effective cloud fraction and cloud height are retrieved from FRESCO. The cloud height is close to the middle of the cloud. FRESCO: Fast Retrieval Scheme for Clouds from the Oxygen A band

FRESCO cloud algorithms

Lambertian cloud model

Cloud data sets of SCIAMACHYData: ESA level-2, version 5.02, FRESCO, version 6

• Intercomparison data set - one orbit per month from 2002 to 2012, including 4 full day of data (~160 orbits).

• Validation data set - SCIAMACHY overpass pixels at Cabauw (2003- 2005) and Lindenberg (2005-2012). (~700 measurements)

Distributions of the differences (L2 –FRESCO)

Mean difference -0.0225 Standard deviation 0.100

Mean difference 0.609 km Standard deviation 2.16 km

Cloud fraction Cloud height

Cloudnet dataInstruments:

Radar : large particles such as rain and drizzle drops, ice particles, and insectsLidar : higher concentrations of smaller particles, such as cloud droplets, aerosol, supercooled liquid layers Microwave radiometer: liquid water pathRain gauge: precipitation

Cloudnet cloud top height, cloud base height and target categorization data are selected for one hour, centered at SCIAMACHY overpass time.

Illingworth et al., BAMS, 2007. http://www.cloud-net.org

Cloudnet categorization product

Ice cloud

Water cloud

height grid time resolutionCabauw: 0.253-11.5km, 90m (126 levels), 15s (240 /hr) Lindenberg: 0.355-15.2km, 30m (495 levels), 30s (120 /hr)

Cloud top

Cloud base

Cloudnet categorization product

Ice cloud

Water cloud

height grid time resolutionCabauw: 0.253-11.5km, 90m (126 levels), 15s (240 /hr) Lindenberg: 0.355-15.2km, 30m (495 levels), 30s (120 /hr)

Cloud top

Cloud base

Cloud top of ESA L2 vs. Cloudnet: single layer clouds

All clouds

water clouds

ice clouds

Color scale: ESA L2 cloud fraction

All clouds

ice clouds

water clouds

Cloud height of FRESCO vs. Cloudnet cloud top: single layer clouds

Color scale: FRESCO effective cloud fraction

SCIA cloud heights and Cloudnet cloud boundaries: single layer clouds, ceff>0.1

SCIAMACHY and Cloudnet cloud heights: single layer clouds, ceff>0.1

SCIAMACHY cloud height vs. Cloudnet cloud top: multi-layer clouds

ESA L2 cloud top height

FRESCO cloud height

SCIAMACHY and Cloudnet cloud heights: Multi-layer clouds

Summary (1)SCIAMACHY ESA L2 v5.02 cloud fractions are similar to FRESCO v6 effective cloud fractions. For the selected data from 200210 to 201204, the mean difference is -0.0225 and the standard deviation is 0.10.

SCIAMACHY ESA L2 v5.02 cloud top height is higher than FRESCO cloud height. The mean difference of cloud heights is 0.609 km with a standard deviation of 2.16 km for pixels without snow/ice.

Summary (2)We compared ESA L2 and FRESCO cloud heights with Cloudnet products for 220 single layer cloud cases in 2003-2011.

For single layer clouds, ESA L2 cloud top height is close to lidar/radar cloud top height for clouds at 3-7 km.FRESCO cloud height is close to lidar/radar cloud middle height for clouds below 5 km.

Acknowledgment

We would like to thank Henk Klein-Baltink (KMNI) for helpful discussions.

We acknowledge the Cloudnet project (European Union contract EVK2-2000-00611) for providing the target classification and cloud boundaries, which was produced by the University of Reading using measurements from Cabauw and Lindenberg.