presented by: zhenglong li, cimss jun li, cimss timothy j. schmit, noaa/nesdis/star

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1 GOES-R AWG Land Surface Emissivity Team: Retrieval of Land Surface Emissivity using Time Continuity June 15, 2011 Presented By: Zhenglong Li, CIMSS Jun Li, CIMSS Timothy J. Schmit, NOAA/NESDIS/STAR

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GOES-R AWG Land Surface Emissivity Team: Retrieval of Land Surface Emissivity using Time Continuity June 15, 2011. Presented By: Zhenglong Li, CIMSS Jun Li, CIMSS Timothy J. Schmit, NOAA/NESDIS/STAR. Executive Summary. - PowerPoint PPT Presentation

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Page 1: Presented By: Zhenglong Li, CIMSS Jun Li, CIMSS Timothy J. Schmit,  NOAA/NESDIS/STAR

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GOES-R AWG Land Surface Emissivity Team:

Retrieval of Land Surface Emissivity using Time Continuity

June 15, 2011

Presented By: Zhenglong Li, CIMSS

Jun Li, CIMSSTimothy J. Schmit, NOAA/NESDIS/STAR

Page 2: Presented By: Zhenglong Li, CIMSS Jun Li, CIMSS Timothy J. Schmit,  NOAA/NESDIS/STAR

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Executive Summary

This ABI Land Surface Emissivity (LSE) retrieval algorithm generates the Option 2 product of LSE

Version 4 was delivered in January. Version 5 and ATBD (100%) are scheduled to be delivered in June.

A physical approach that uniquely takes advantage of time continuity of geostationary satellite, has been developed to generate ABI spectral LSE in window channels; the LSE is assumed to be invariable during a short period of time while LST is variable.

Sensitivity study: the algorithm has been applied to the simulated SEVIRI measurements to test the LSE retrieval sensitivity on the first guess, the local zenith angle (LZA), the radiance bias and instrument noise.

Validation: the LSE retrieval from the SEVIRI measurements are compared with other LSE products such as MODIS, AIRS and IASI.

Page 3: Presented By: Zhenglong Li, CIMSS Jun Li, CIMSS Timothy J. Schmit,  NOAA/NESDIS/STAR

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Algorithm Description

Page 4: Presented By: Zhenglong Li, CIMSS Jun Li, CIMSS Timothy J. Schmit,  NOAA/NESDIS/STAR

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Algorithm Summary

Time continuity: LSE is temporally invariable while LST is variable during a short period of time

Inverse scheme: The quasi-nonlinear iteration

Three IR window channels (8.7, 10.8 and 12 micron) for SEVIRI, and four IR winddow channels (8.5, 10.35, 11.2 and 12.3 micron) for ABI

Three time steps with time difference of 3 hours between two consecutive time steps (e.g., 00 UTC, 03 UTC and 06 UTC)

Page 5: Presented By: Zhenglong Li, CIMSS Jun Li, CIMSS Timothy J. Schmit,  NOAA/NESDIS/STAR

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• The Linearization of the Radiative Transfer Equation yields:

This equation needs to be simplified for accurate and stable LSE retrievals

• The atmospheric correction is achieved by using NWP forecast profiles plus

Greatly simplifies the linearization equation by reducing the unknowns of T/Q profiles to just one hybrid variable of

• The simplified linearized RT Equation:

where

Linearization of RT Equation

R KTsTs K KTT KQ lnQ e

T KT KTT KQ lnQ

T

Page 6: Presented By: Zhenglong Li, CIMSS Jun Li, CIMSS Timothy J. Schmit,  NOAA/NESDIS/STAR

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• Time continuity of LSE: the LSE is assumed to be invariable during a short period of time while LST is variable.

• On SEVIRI, there are three window channels (8.7, 10.8 and 12 micron), and three time steps are recommended.

• The linearized RT equation looks:

or

the number in superscript denotes time steps, and the number in subscript denotes channel index

Time continuity

Y KXe

Page 7: Presented By: Zhenglong Li, CIMSS Jun Li, CIMSS Timothy J. Schmit,  NOAA/NESDIS/STAR

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• A general form of the variational solution for LSE is to minimize the cost function:

Where X: state vector Ym: observed brightness temperature vector Y: radiative transfer model (function of X) E: observation error covariance matrix (diagonal) X0: first guess (initial state) of LSE H: the inverse of the first guess error covariance matrix

• Apply Newtonian iteration

• The quasi-nonlinear iterative form of the solution is

The optimal solution

J(X) [Ym Y(X)]'E 1 [Ym Y(X)] [X X0]'H[X X0]

X n1 X n J ' '(X n) 1 J '(X n)

Xn 1 X0 (Kn' E 1K n H) 1 K n

' E 1[Ym Yn (Xn ) K n (Xn X0)]

Page 8: Presented By: Zhenglong Li, CIMSS Jun Li, CIMSS Timothy J. Schmit,  NOAA/NESDIS/STAR

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ADEB and IV&V Response Summary

ADEB: Land Surface Emissivity -- OK for advance to 100%.  The board commends the team for its use of temporal resolution of ABI.  The board recommends further validation including alternative sources of data and comparison against SeeBor and MODIS emissivities (already done).

Recommend #1 -- Continue to pursue more complete data sets. Measurement validation must be conducted with thoroughness and completeness within a sustained validation/verification framework and should consider using “human in the loop.” This recommendation was made previously but has rarely been adopted.

Response: Surface emissivity will not only be compared to MODIS and SeeBor, but other datasets, such as from AIRS/IASI/CrIS (when available). Again, there is the 'direct' comparison to other LSE products and also the 'indirect' method of using the LSE in the forward calculations to then compare to observations. Another option to indirectly validate LSE is to investigate its impacts on sounding retrievals. One unique method is to use satellite radiance measurements to objectively quantify LSE precision. More information about this method can be found in Li, Zhenglong; Li, Jun; Jin, Xin; Schmit, Timothy J.; Borbas, Eva E. and Goldberg, Mitchell D. An objective methodology for infrared land surface emissivity evaluation. Journal of Geophysical Research, Volume 115, 2010, Doi:10.1029/2010JD014249.

Page 9: Presented By: Zhenglong Li, CIMSS Jun Li, CIMSS Timothy J. Schmit,  NOAA/NESDIS/STAR

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ADEB and IV&V Response Summary-cont

Recommend #3 -- In most cases the requirements are conservative. Most of the products, especially the legacy ones, have requirements that do not extend the capabilities.

Response: As far as a 'stretch' goal for LSE, there is a limit to what can be done with low spectral resolution data. That said, the LSE current requirement is ONLY for the CONUS region. At some point, this should be extended to cover the Full Disk regions (within the LZA cut-off). This will help other products, such as OLR and LST.

Recommend #4 -- The many advantages of geostationary orbit are rarely exploited.

Response: As mentioned by the ADEB, the LSE already uses the temporal resolution. There may be the other product, other that winds, that uses the temporal component. The implementation of time continuity in LSE algorithm improves LSE products quality.

Page 10: Presented By: Zhenglong Li, CIMSS Jun Li, CIMSS Timothy J. Schmit,  NOAA/NESDIS/STAR

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ADEB and IV&V Response Summary-cont

Recommend #5 -- The board recommends this issue be addressed thoroughly before launch. The IPR team and the ADEB were asked to consider graceful degradation, however the teams rarely discussed it and then only with regard to ancillary data. Impacts due to sensor/channel degradation or loss were not addressed, and there was no quantitative assessment of impact to product quality as input data degrade. 

Response: wrt graceful degradation, how much is needed to be done by the teams, as opposed to the AIT running more 'system' level tests? For LSE products, no discussion is made WRT graceful degradation. However, the discussion of radiance biases (which could comes from cloud/dust contamination, forward calculation or instrument degradation) should apply here. Our study indicates the LSE products are sensitive to radiance biases in a complex way. Therefore, radiance bias adjustment is needed if there is any.

Recommend #6 – plans to reach 100% should be clearly stated.

Response: Compared with 80 %, the 100 % will include more quality control, which makes it easier for users to understand the quality of the products.  

Page 11: Presented By: Zhenglong Li, CIMSS Jun Li, CIMSS Timothy J. Schmit,  NOAA/NESDIS/STAR

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Requirements Surface Emissivity

M – Mesoscale FD – Full Disk

Nam

e

User &

Priority

Geographic

Coverage

(G, H

, C, M

)

Vertical

Resolution

Horizontal

Resolution

Mapping

Accuracy

Measurem

ents

Range

Measurem

ents

Accuracy

Refresh

Rate/C

overage Tim

e Option (M

ode 3)

Refresh R

ate Option (M

ode 4)

Vendor A

llocated Ground

Latency (M

ode 3)

Vendor A

llocated Ground L

atency (Mode

4) Product M

easurement P

recision

Surface Emissivity

GOES-R C N/A 10 km 5 km 0.6 to 1.0 (unitless)

0.05 (unitless)

60 min 60 min 3236 sec 3236 sec 0.005*

*Pending to relax to 0.05, due to lack of HES.

Page 12: Presented By: Zhenglong Li, CIMSS Jun Li, CIMSS Timothy J. Schmit,  NOAA/NESDIS/STAR

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Surface Emissivity Product Qualifiers

FD – CONUS M - Mesoscale

Nam

e

User &

Priority

Geograp

hic

Coverage

(G, H

, C, M

)

Tem

poral C

overage Qu

alifiers

Prod

uct E

xtent Q

ualifier

Clou

d C

over Con

dition

s Q

ualifier

Prod

uct S

tatistics Qu

alifier

Surface Emissivity GOES-R C Sun at less than 67 degree daytime solar zenith angle *

Quantitative out to at least 70 degrees LZA and qualitative at larger LZA **

Clear conditions associated with threshold accuracy

Over specified geographic area

* This IR technique is independent of the solar illumination.** Quantitative out to at least 67 degrees LZA and qualitative at larger LZA (out to soundings limit).

Page 13: Presented By: Zhenglong Li, CIMSS Jun Li, CIMSS Timothy J. Schmit,  NOAA/NESDIS/STAR

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Validation Strategy

Page 14: Presented By: Zhenglong Li, CIMSS Jun Li, CIMSS Timothy J. Schmit,  NOAA/NESDIS/STAR

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Validation Approach Direct validation of LSE retrievals using laboratory measurements are

difficult due to » Measurement scale inconsistency (point versus area); very few areas are

homogeneous enough for this comparison.

» Naturally temporal variation of LSE

» Expensive

Practical way to evaluate LSE retrievals include

» Simulation study: validate the LSE retrieval algorithm in simplified conditions

» Inter-comparison: compare with other LSE databases, such as MODIS, SeeBor, AIRS and IASI

» Indirect: apply the LSE database to see if they draw positive impacts, i.e. on sounding retrievals and radiative transfer calculations as compared to observations

» Indirect: apply the objective method to quantitatively evaluate LSE precisions using satellite observations

» Indirect: apply the algorithm to GOES Sounder over ocean to see if the retrieved LSE and LST are temporally consistent

Page 15: Presented By: Zhenglong Li, CIMSS Jun Li, CIMSS Timothy J. Schmit,  NOAA/NESDIS/STAR

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Validation Results

Page 16: Presented By: Zhenglong Li, CIMSS Jun Li, CIMSS Timothy J. Schmit,  NOAA/NESDIS/STAR

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The retrievals with LZA of 0 degree are compared with the true

Validation of the retrievals using simulated SEVIRI

radiances

The algorithm successfully brings the retrieval parameters closer to the true values, especially for LSE of 8.7 micrometer and LST.

Page 17: Presented By: Zhenglong Li, CIMSS Jun Li, CIMSS Timothy J. Schmit,  NOAA/NESDIS/STAR

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The algorithm is applied to SEVIRI observations on August 1 2006. The retrievals are compared with MODIS (collection 4.1), AIRS and IASI monthly LSE databases.

Inter-comparison:SEVIRI LSE products----8.7 um

8.7 um

Page 18: Presented By: Zhenglong Li, CIMSS Jun Li, CIMSS Timothy J. Schmit,  NOAA/NESDIS/STAR

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Using MODIS monthly LSE database as reference, other three databases are quantitatively evaluated

Inter-comparison:Compared with MODIS----8.7

um

8.7 um

Using MODIS as a reference, SEVIRI > IASI > operational AIRS for 8.7 µm in this particular case

Page 19: Presented By: Zhenglong Li, CIMSS Jun Li, CIMSS Timothy J. Schmit,  NOAA/NESDIS/STAR

2020

The retrieved SSE/SST from GOES Sounder (coarser spatial resolution) with GOES-R LSE algorithm is temporally consistent, although there seems to be cloud contamination.

Indirect:Apply to GOES Sounder

April 29, 2010

12.66 um SSE

11.03 um SSE

12.02 um SSE

SST

Page 20: Presented By: Zhenglong Li, CIMSS Jun Li, CIMSS Timothy J. Schmit,  NOAA/NESDIS/STAR

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Summary The ABI land surface emissivity algorithm provides LSE

products that uniquely utilizes the time continuity offered by the ABI

Version 4 is delivered, version 5 and the 100% ATBD is coming.

These products are being validated, and will be useful for other products.

The validation strategy includes objective method, direct comparison and indirect evaluation

Page 21: Presented By: Zhenglong Li, CIMSS Jun Li, CIMSS Timothy J. Schmit,  NOAA/NESDIS/STAR

References

Li, J., Z. Li, X. Jin, T. Schmit, L. Zhou, and M. Goldberg, 2011: Land surface emissivity from high temporal resolution geostationary infrared imager radiances: Methodology and simulation studies, Journal of Geophysical Research - Atmospheres, 116, D01304, doi:10.1029/2010JD014637.

Li, Z., J. Li, X. Jin, T. J. Schmit, E. Borbas, and M. D. Goldberg, 2010: An objective methodology for infrared land surface emissivity evaluation, Journal of Geophysical Research - Atmospheres, 115, D22308, doi:10.1029/2010JD014249.

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