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GOES-R AWG Radiation Team: ABI Absorbed SW Radiation at

surface (ASR) Algorithm

June 14, 2011Presented By: Istvan Laszlo1

1 NOAA/NESDIS/STAR

Team: I. Laszlo (algorithm lead), H-Y. Kim (lead developer), H. Liu, E.G. Dutton and J.A. Augustine (other members)

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Outline

Executive Summary Algorithm Description (2-4 slides) ADEB and IV&V Response Summary (1-2 slides) Requirements Specification Evolution (2 slides) Validation Strategy (3-5 slides) Validation Results (3-5 slides) Summary (1-2 slides)

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Executive Summary

The ABI Absorbed SW Radiation at surface (ASR) Algorithm generates the Option 2 product of absorbed shortwave radiation at surface.

The algorithm combines physical and statistical approaches to estimate ASR depending on the availability of ABI atmosphere products.

Validation & Development Datasets: CERES/ARM Validation Experiment (CAVE), SEVIRI, and MODIS data. Validation indicates spec compliance.

Version 4 was delivered in April 2011. Version 5 and ATBD (100%) is on track for a July and June delivery.

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Algorithm Description

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Algorithm Summary

The ABI absorbed shortwave radiation algorithm is a hybrid algorithm that combines the merits of physical and statistical approaches.

The physical algorithm is used when all inputs needed for describing the state of the atmosphere are available from other ABI products and the statistical algorithm is used otherwise.

Estimation of ASR from the physical algorithm provides consistency with ABI products; while the statistical algorithm permits ASR retrieval even when ABI-derived AOD is not available (over bright surfaces).

Retrievals are performed for all conditions (clear and cloudy) during daytime.

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The ABI ASR (hybrid) algorithm retrieves the radiation absorbed at he surface

» ASR is used e.g., in hydrological and in surface energy budget models

Physical algorithm uses reflectance (R) and transmittance (T) of the surface-atmosphere calculated from radiative transfer and represented by LUT. It estimates ASR using inputs from ABI products directly:

» Solar and sensor zenith angle» Shortwave narrowband reflectance» cloud (fraction, optical depth, effective radius, height, phase)» aerosol (optical depth, model)» total gas amounts (precipitable water and ozone)

Statistical algorithm uses pre-established relationship between surface and TOA solar absorption by regression. It estimates ASR using inputs of

» Solar zenith angle» Shortwave narrowband reflectance» Total column amount of precipitable water

Surface albedo is not needed as input!

ASR Algorithm Description (1)

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ASR Algorithm Description (2)

ASR is determined » for clear and for water and ice cloud scenes separately in the physical

algorithm and the output is the scene fraction weighted average of clear and cloudy estimates

» for combined clear and cloudy scenes in the statistical algorithm

Both algorithms require the TOA broadband albedo, which is obtained from the narrowband ABI reflectances using spectral (NTB) and angular (ADM) transformations.

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Absorbed SW Radiation Algorithm Processing

Schematic

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Example Output: MODIS input

Hybrid algorithm ASR on June 15,

2010 MODIS inputs:

SW narrowband reflectance, location, elevation, geometry, AOD, cloud properties, TPW and ozone, cloud and snow mask

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Example Output: SEVIRI Input

Physical (left) and statistical algorithm (right) on Jan 31 2006 12Z Similar pattern but some difference for clear-sky areas

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Algorithm Changes from 80% to 100%

Added cloud optical depth (COD) as entry in the narrow-to-broadband (NTB) conversion of TOA reflectance. At the 80% version, only surface type was considered for ice cloud.

Increased the number of surface types used in ADM for clear sky from 4 to 10.

Added quality flags indicating status of input. (In the 80% version, QC flags did not tell which input was missing.)

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ADEB and IV&V Response Summary

More complete dataset: added 3 more years of collocated MODIS-ground data (total now is 10 years)

“stretch goals” that approach the state-of-the-art: ASR algorithm is currently state-of-the-art. It is based on radiative transfer and utilizes the best available information on the atmosphere derived from remote sensing.

State plans to meet requirements: The algorithm has already met the accuracy requirements. With the improved NTB transformation in the 100% algorithm the precision requirements are also met.

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Requirements

ProductHorizontal resolution

Accuracy Precision Latency

Absorbed Shortwave Radiation:

Surface (ASR)

Mesoscale: 5 km

• 90 Wm-2 at low value (100 Wm-2);

• 45 Wm-2 at mid value (400 Wm-2);

• 55 Wm-2 at high value (800 Wm-2)

• 75 Wm-2 at low and high values (100 and 800 Wm-2 and

• 95 Wm-2 at mid values (400 Wm-2)

60 min

Qualifiers: Daytime Solar zenith angle < 70 degrees Quantitative for Local Zenith Angle < 70 degrees, qualitative beyond

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Validation Approach

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Validation Approach (1)

Retrieve ASR from MODIS proxy data:» Centered on10 sites» ~ 10 years (03/2000 – 12/2009) » Inputs from MODIS (Terra, Aqua) granule

– SW narrowband reflectance at 1km resolution (MOD021KM)

– Location, surface height, geometry (MOD03)– Aerosol optical depth (MOD04)– Cloud optical depth, size, phase, height (MOD06)– Total precipitable water, ozone (MOD07)– Cloud and snow mask (MOD35)

» TOA albedo input is derived from MODIS reflectances using narrow-to-broadband (NTB) conversions and angular models (ADM)

» Even though this is the best dataset currently available, the estimated TOA albedo may have large errors, and may not be fully consistent with the MODIS atmosphere products

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Validation Approach (2)

Collocate derived ASR with ground truth (and satellite)» in space and time

Compare retrieved ASR to: » Ground measurement of surface flux at 10 sites (SURFRAD, ARM, GMD,

COVE)

Generate comparative statistics » accuracy and precision» histogram

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Validation Results

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Absorbed SW radiation at surface (ASR) Validation

MODIS ~ 10 years data over 10 sites» Overall accuracy: 3%; precision: 20%

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Absorbed SW radiation at surface (ASR) Validation

MODIS ~ 10 years data over 10 sites» Overall accuracy: 15 Wm-2;

precision: 92 Wm-2

Clear and overcast onlyCERES (from CAVE) TOA albedo

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Unit = Wm-2 Accuracy (F&PS) Precision (F&PS)

Low (100) 74 (90) 65 (75)

Medium (400) 24 (45) 93 (95)

High (800) -35 (55) 75 (75)

Overall 15 92

Validation Results Summary

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Summary

The ABI ASR algorithm is state-of-the-art algorithm that utilizes simultaneous atmosphere retrievals and multi-channel measurements offered by ABI.

Version 5 algorithm and 100% ATBD will be delivered soon.

The ASR products meet specifications using the collected 10-year validation dataset.