SIRTA Cloud and Radiation Observatory

Cloudnet meeting 18-19 Oct 2004 - Martial Haeffelin

SIRTASIRTASIRTASIRTA Cloud and Radiation ObservatorySIRTA Cloud and Radiation Observatory

M. Haeffelin, A. Armstrong, L. Barthès, O. Bock, C. Boitel, D. Bouniol, M. Chiriaco, J. Delanoe, P. Drobinski, J-L. Dufresne, C. Flamant, M. Grall, F. Hourdin, F. Lapouge, Y. Lemaître, A. Mathieu, Y. Morille, V. Noel, J. Pelon, C. Pietras, A. Protat, B. Romand, G. Scialom, R. Vautard, Y. Wanherdrick

Institut Pierre Simon LaplaceInstitut Pierre Simon Laplace

AlgorithmsAlgorithms


SIRTASIRTASIRTA

LIDAR Cloud and aerosol vertical structure

Multi-test algorithm applied on 532-nm channel to identify cloud layers, aerosol layers, molecular layers, and boundary layer height (Morille et al., 2004)

Optical depth Multi-retrieval algorithm applied on 532-nm channel to retrieve optical depth of cloud or aerosol layers (Cadet et al., 2004)

Depolarization and

color ratio

Multi-wavelength algorithms using linear and cross-polarized 532-nm and linear 1064-nm channels to discriminate particle shape (Noel et al., 2002)

RADAR Cloud structure

Ice/water content

Particle size distribution

Mean particle diameter from radar reflectivity and doppler velocity

Size distribution related to mean diameter

Extinction and ice water content function of reflectivity and size distribution

Retrieval uncertainties estimated 50%

CEILOMETER

Cloud-base height

Vaisala proprietary algorithm

RADIATI-VE FLUX STATION

Fraction of cloud cover

Shortwave and longwave clear-sky fluxes

Clear-sky models derived from measurements. Threshold to identify cloud cover fraction.

(Long and Ackerman 2000)

MWR Integrated water vapor and liquid water content

Brightness temperatures simulated from radiosonde profiles to calibrate MWR. Water vapor and liquid water contents inverted using the Kummerow and Weinman (1988) algorithm.

Data ProductsData Products


SIRTASIRTASIRTA Lidar Data ProductsLidar Data Products

Wavelet transform method:

• Search for high correlation between a wavelet and the lidar signal

• Mexican hat for particle layers in the free troposphere

• Step function for boundary layer

Cloud / aerosol separation based on PR2 peak-to-base ratio

Distinction between true noise (no more photons) and apparent noise (no more scatterers)

Cloud and aerosol vertical structure



L0:• Lidar back-scattered powerL1:• Quality flag• Monitoring noiseL2: • Atmospheric Mask (Clouds, aerosols, Boundary layer, Particle-free zone, Noise• Cloud thermodynamic phase• Cloud and aerosol layer optical depthL3:• Time and layer -average data


SIRTASIRTASIRTA Radar-Lidar Cloud ProductsRadar-Lidar Cloud ProductsCombine Reading classification with LNA classification


SIRTASIRTASIRTA Cloud Product Dataset Analysis Cloud Product Dataset Analysis

Processed LNA Lidar data: 10/2002 - 09/2004

• Cloud, aerosol mask

• Time averaged data

20040830 7.0 10005 11655 10020040830 8.0 01515 01995 100 10170 11700 08320040830 9.0 10710 11790 10020040830 10.0 01620 01995 030 10545 11865 10020040830 11.0 01815 02220 100 09435 12000 10020040830 12.0 01650 02325 100 09150 12150 10020040830 13.0 02055 02490 086 09990 12135 10020040830 14.0 02085 02550 100 09675 12060 09520040830 15.0 01875 02760 100 09390 11565 07020040830 17.0 08550 11715 100



Frequency of occurrence of cloud fraction and vertical distribution of cloud layers

Palaiseau 10/2002-09/2004 LNA Lidar



Frequency of occurrence of single and multiple cloud layers




Frequency of occurrence of cloud thickness and vertical distribution





Relative occurrence of cloud altitude (monthly variations)




Relative occurrence of cloud altitude (seasonal variations)

Vertical Extent of Clouds



Relative occurrence of cloud-base altitude (seasonal variations)


Occurrence of Cloud

Base



Mixed phaseLiquid water

Ice water

Normalization problem

Cloud thermodynamic phase• Based on lidar depolarization ratio + threshold• Requires normalization in particle-free zone (2.74%)



Molecular Integration method: = ∫ (z)dz

Integrated extinction = power loss between theoretical molecular return below the cloud and molecular return above the cloud

Cloud optical depth

Particle Integration method:

= LReff ∫ (R(z)-1)m(z)dz

where R(z)=(m(z)+c(z))/m(z)

LReff prescribed: 18 sr

LReffopt derived from MI method

Cadet et al. 2004


SIRTASIRTASIRTA Lidar Data ProductsLidar Data ProductsCloud optical depth

Cadet et al. 2004


SIRTASIRTASIRTA Radiative Flux StationRadiative Flux Station

LWSW

Operations:• 18 months of Global SW + LW• SW Direct + Diffuse missing 12/03-02/04


SIRTASIRTASIRTA Radiative Flux Dataset Analysis Radiative Flux Dataset Analysis

SW Direct

May 2004

SW Diffuse

SW Global

LW Down


SIRTASIRTASIRTA Radiative Flux Dataset Analysis Radiative Flux Dataset Analysis

Shortwave radiative impact of cloud layers

Clear-sky reference from F = a cos()b

May 2004

Single-layer high-altitude

clouds


SIRTASIRTASIRTA

• Produce 2-year radar-lidar L3 products

• Pursue analysis of vertical structure

• Pursue developments of lidar-only retrievals and combination

• Develop clear-sky flux and radiative forcing products, and analyse in relation to the cloud data base

PerspectivesPerspectives

Institutes and programs supporting SIRTA:

SIRTA Cloud and Radiation Observatory

Documents

Transcript of SIRTA Cloud and Radiation Observatory