gome-2 cloud top height and optical depth retrieval using...

GOME-2 Cloud top height and opticaldepth retrieval using ROCINN V3.0

Gimeno García1, Sebastián1; Lutz, Ronny1; Romahn, Fabian1; Loyola, Diego1;Spurr, Robert2

1German Aerospace Center (DLR)Remote Sensing Technology Institute

Oberpfaffenhofen, GERMANY

2RT SOLUTIONS Inc.Cambridge, MA, USA

June 10, 2015

ESA ATMOS 2015, Heraklion, 08-12 June 2015 1

Outline

1 Motivation

2 Retrieval strategy

3 OCRA

4 ROCINN – CAL & CRB

5 Results: GOME2-A cloud products

6 Conclusions

7 Outlook

ESA ATMOS 2015, Heraklion, 08-12 June 2015 2

Motivation – 1

Cloud information from spaceborne atmospheric spectrometersprimarily needed for accurate trace gas retrievalCloud effects on gas retrieval (1D):

albedo effect shielding effect multiple scattering

+ other: e.g. multiple cloud layering, . . .

ESA ATMOS 2015, Heraklion, 08-12 June 2015 3

Motivation – 2

Cloud information from spaceborne atmospheric spectrometersprimarily needed for accurate trace gas retrievalCloud effects on gas retrieval (3D):

neighboring pixel effect in-pixel inhomogeneity effect

+ other: e.g. effect of scene variability on spectral calibration

ESA ATMOS 2015, Heraklion, 08-12 June 2015 4

Outline

1 Motivation

2 Retrieval strategy

3 OCRA

4 ROCINN – CAL & CRB

5 Results: GOME2-A cloud products

6 Conclusions

7 Outlook

ESA ATMOS 2015, Heraklion, 08-12 June 2015 5

Retrieval strategy

ROCINN

UVN

Cloud fraction

Cloud-top height

Cloud albedo

O2 A-Band

OCRA

GOME type

Optical thickness),,,,),((},,{ 0 fazsimINVaz cssRNNcc

iBGRi

iiCFiifc,,

2 ))()()(,0max()(

OCRA: Optical Cloud Recognition Algorithm ROCINN: Retrieval Of Cloud Information through Neural Networks

OCRA/ROCINN schematic

ESA ATMOS 2015, Heraklion, 08-12 June 2015 6

Outline

1 Motivation

2 Retrieval strategy

3 OCRA

4 ROCINN – CAL & CRB

5 Results: GOME2-A cloud products

6 Conclusions

7 Outlook

ESA ATMOS 2015, Heraklion, 08-12 June 2015 7

OCRA – in short

OCRA is a RGB color space approach

determine monthly cloud free reflectance maps

map actual reflectance measurements to cloud (radiometric) fraction

radiometric cloud fraction:GOME2-A and GOME2-B merged together

⇒ See poster #47, Lutz et al.:Cloud Fraction Determination for GOME-2 A/B with OCRA V3.0 (!)

ESA ATMOS 2015, Heraklion, 08-12 June 2015 8

Outline

1 Motivation

2 Retrieval strategy

3 OCRA

4 ROCINN – CAL & CRB

5 Results: GOME2-A cloud products

6 Conclusions

7 Outlook

ESA ATMOS 2015, Heraklion, 08-12 June 2015 9

ROCINN – CAL & CRB

Cloud fraction (CF) is retrieved using a RGB color space approach→ OCRA

Cloud Top Height and Albedo (CTH, CTA) and Cloud OpticalThickness (COT) are retrieved in the Oxygen A-band usingregularization theory→ ROCINN

CRB: Clouds are treated as Reflecting BoundariesI Lambertian Equivalent Reflectors (LER)I simple and (numerically) robustI popular in the atmospheric gas retrieval communityI retrieved cloud parameters can greatly deviate from reality

CAL: Clouds are treated As horizontal homogeneous LayersI photon cloud penetration is allowedI multiple scattering is accounted forI modeled radiance contains information below the cloud layerI retrieved CTH is closer to the actual CTH

ESA ATMOS 2015, Heraklion, 08-12 June 2015 10

ROCINN – CAL cloud model

KISS – Keep It Simple Strategy (G. Marsaglia – RNG)

One cloud layer

Liquid water droplets

Spherical particles – Mie scattering theory

Modified gamma particle size distribution (α=6, β=0.11)

⇒ cloud optical propertiesI Single scattering albedoI Scattering phase functionI Optical thickness (not important: to be fit)

ESA ATMOS 2015, Heraklion, 08-12 June 2015 11

Outline

1 Motivation

2 Retrieval strategy

3 OCRA

4 ROCINN – CAL & CRB

5 Results: GOME2-A cloud products

6 Conclusions

7 Outlook

ESA ATMOS 2015, Heraklion, 08-12 June 2015 12

ROCINN_CRB: UPAS GDP 4.8 – 01 Jul 2009

Cloud Fraction Cloud Top Height

Cloud Fraction (CF) product nicely captures cloud systemmacroscopic structureCRB cloud top height (CTH) captures variability inside cloudsystem

ESA ATMOS 2015, Heraklion, 08-12 June 2015 13

ROCINN_CRB: UPAS GDP 4.8 – 01 Jul 2009

Cloud Top Albedo Cloud Top Height

CRB cloud top albedo (CTA) is less variable than CFCRB cloud top height (CTH) captures variability inside cloudsystems

ESA ATMOS 2015, Heraklion, 08-12 June 2015 14

ROCINN_CAL: UPAS GDP 4.8 – 01 Jul 2009

Cloud Optical Thickness Cloud Top Height

CAL cloud optical thickness (COT) captures more variability thanCRB_CTACAL cloud top height (CTH) higher than CRB_CTH

ESA ATMOS 2015, Heraklion, 08-12 June 2015 15

ROCINN_CAL: UPAS GDP 4.8 – 01 Jul 2009

Cloud Optical Thickness MODIS MOD08 COT

@ NASA GES DISC: data generated with Giovanni tool

CRB CAL_COT shows similar patterns than MODIS total COT

Equatorial crossing times:

I GOME-2 on EPS/MetOp-A: ∼ 9:30 AM local timeI MODIS on NASA-EOS/Terra: ∼ 10:30 AM local time

ESA ATMOS 2015, Heraklion, 08-12 June 2015 16

Outline

1 Motivation

2 Retrieval strategy

3 OCRA

4 ROCINN – CAL & CRB

5 Results: GOME2-A cloud products

6 Conclusions

7 Outlook

ESA ATMOS 2015, Heraklion, 08-12 June 2015 17

Conclusions

ROCINN3.0 CAL and CRB algorithms have been successfullyimplemented in UPAS (GDPv4.8 –GOME-2)

ROCINN3.0 CAL and CRB ready for operational processing

CAL and CRB cloud top height (CTH) captures the variabilityinside cloud systems

CRB delivers systematic lower CTH than CAL

CRB CTA is much smoother than CF

CAL COT shows much more variability than the related quantityCTA (due to the CAL cloud model)

A preliminary comparison with MODIS total COT shows a goodqualitative agreement

ESA ATMOS 2015, Heraklion, 08-12 June 2015 18

Outline

1 Motivation

2 Retrieval strategy

3 OCRA

4 ROCINN – CAL & CRB

5 Results: GOME2-A cloud products

6 Conclusions

7 Outlook

ESA ATMOS 2015, Heraklion, 08-12 June 2015 19

Outlook

Verification activities: compare OCRA/ROCINN with otherGOME-2 cloud products

I SACURA: CTH, COTI FRESCO: CF, CHI HICRU: CF

Compare OCRA/ROCINN with external cloud products:I AVHRR Patmos-XI MODIS MOD08I . . .

Reprocess GOME-2 on MetOp-A and MetOp-B

Setup UPAS for Sentinel-5 Precursor processing

ESA ATMOS 2015, Heraklion, 08-12 June 2015 20

MoCaRT

Thank you for your attention!

ESA ATMOS 2015, Heraklion, 08-12 June 2015 21

OCRA – method

OCRA is a RGB color space approachI OCRA RGB-bands for different sensors

determine monthly cloud free reflectance mapsmap actual reflectance measurements to cloud (radiometric)fraction

ESA ATMOS 2015, Heraklion, 08-12 June 2015 22

ROCINN – Forward model

CRB radiance forward model

ICRB = CF · Iclr (CH,CA;α) + (1− CF ) · Iclr (SH,SA;α)

CAL radiance forward model

ICAL = CF · Icld (CTH,COT ,CGT ,SH,SA;α) + (1−CF ) · Iclr (SH,SA;α)

whereI CF: cloud fractionI SH: surface heightI SA: surface albedoI C(T)H: cloud (top) heightI C(T)A: cloud (top) albedoI COT: cloud optical thicknessI CGT: cloud geometrical thicknessI α: auxiliary parameters (observation geometry, . . . )

ESA ATMOS 2015, Heraklion, 08-12 June 2015 23

ROCINN – Inversion

Tikhonov regularization

minx‖y− F(x)‖2 + ‖Γ(x− x0)‖2

whereI x: state vectorI x0: expected value of the state vectorI y: observationsI F: forward modelI Γ: Tikhonov regularization matrix

ESA ATMOS 2015, Heraklion, 08-12 June 2015 24