Application of cloudnet data in the validation of sciamachy cloud height products
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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 O 2 A band Validation data sets Results

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

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Application of cloudnet data in the validation of sciamachy cloud height products

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

Overview

  • SCIAMACHY cloud products

  • Cloud retrieval algorithms from O2 A band

  • Validation data sets

  • Results

  • Summary


Sciamachy cloud products

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

FRESCO cloud algorithms

Lambertian cloud model


Cloud data sets of sciamachy

Cloud data sets of SCIAMACHY

Data: 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

Distributions of the differences (L2 –FRESCO)

Cloud fraction

Cloud height

Mean difference -0.0225 Standard deviation 0.100

Mean difference 0.609 km Standard deviation 2.16 km


Cloudnet data

Instruments:

Radar : large particles such as rain and drizzle drops, ice particles, and insects

Lidar : higher concentrations of smaller particles, such as

cloud droplets, aerosol, supercooled liquid layers

Microwave radiometer: liquid water path

Rain gauge: precipitation

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

Cloudnet data

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


Cloudnet categorization product

Cloudnet categorization product

Ice cloud

Cloud top

Water cloud

Cloud base

height grid time resolution

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


Cloudnet categorization product1

Cloudnet categorization product

Ice cloud

Cloud top

Water cloud

Cloud base

height grid time resolution

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


Cloud top of esa l2 vs cloudnet single layer clouds

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

ice clouds

water clouds

All clouds

Color scale: ESA L2 cloud fraction


Cloud height of fresco vs cloudnet cloud top single layer clouds

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

ice clouds

water clouds

All clouds

Color scale: FRESCO effective cloud fraction


Scia cloud heights and cloudnet cloud boundaries single layer clouds ceff 0 1

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


Sciamachy cloud height vs cloudnet cloud top multi layer clouds

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

FRESCO cloud height

ESA L2 cloud top height


Sciamachy and cloudnet cloud heights multi layer clouds

SCIAMACHY and Cloudnet cloud heights: Multi-layer clouds


Summary 1

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

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

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.


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