Earth Radiation Budget from NISTAR

DSCOVR Workshop

NASA Langley Research Center / Atmospheric Sciences

Earth Radiation Budget from NISTAR

Patrick Minnis

NASA Langley Research Center

May 11, 2007

- With help from Dave Doelling & Rabi Palikonda, SSAI

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Why measure ERB from L1?

• NISTAR is an active cavity sensor - absolute calibrations

• New approach to an old problem that requires more stitching of data and interpolation, etc.– Minimizes correction for missing hours

• DSCOVR albedo and daytime OLR can serve as constraints on CERES & serve as a calibration source -

a complementary approach

– CERES is out of balance by 6 Wm-2

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How do we measure ERB with DSCOVR?

• NISTAR measures TOT & SW radiances of entire disk, LW = SW-TOT

- Viewing & illumination geometry varies slowly over time within a narrow range of angles near the backscatter position

- Can only determine global albedo & daytime OLR

- Nocturnal OLR is an educated guess

• Radiance observations must be converted to irradiance (flux)

- Apply anisotropic directional models (ADMs)

- Need cloud information

- Other considerations

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March 21, 1986, 15° east from L1 April 15, 1986, 15°E of L1

Changing View of Earth With Season

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CORRECTION MODELS

SW albedo

• Small (2% to 8%) but variable sliver of sunlight is always out of view, depends on offset from L1

- Missing light correction

• To determine albedo, a set of SW ADM correction models needed

- Bidirectional reflectance correction

OLR

• Most of darkside Earth is never seen

- Nightside correction

• To determine OLR from LW radiance, a set of LW ADM correction models needed

- Limb-darkening correction

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Development of Correction Models & Analysis Approach

• Initial study used ERBE scanner data - monthly averages

• Most recent (2002) used ISCCP & ERBE combined - 3 hr => 1 hr

- developed simulated NISTAR radiances

- constructed correction factors for range of DSCOVR views

- determined variability & estimated error in albedo

- developed correction models: seasonal & L1 dependence

=> set of algorithms that can utilize cloud information to compute correction factors for any time & L1

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• TRIANA GLOBAL BIDIRECTIONAL FACTOR triana (utc) = REF triana (utc) / triana(utc) • TRIANA GLOBAL MISSING LIGHT ALBEDO CORRECTION

FACTOR

FACTOR (utc) = [earth

∑ erbe ( i) i cos (lat i) / earth

∑ i cos( lat i) ] / [ triana (utc ) ]

• TRIANA GLOBAL LIMB DARKENING FACTOR triana (utc ) = RADtriana (utc ) / OLRtriana (utc ) • TRIANA GLOBAL NIGHTSIDE OLR CORRECTION FACTOR

OLRFACTOR (utc) = [earth

∑ OLRerbe (tT) cos( lat i) / earth

∑ cos( lat i) ] / [OLRtriana (utc )]

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DSCOVR Simulator• Construct hourly global radiation and cloud field

- Convert 3-hr ISCCP GEO radiances to BB albedo (< 60° lat)

- monthly NB-BB conversion ERBS/GEO

- use ISCCP clouds to select ERBE ADM

- normalize to ERBE (CERES TISA GEO method)

- Use NOAA-9/10 ERBE data > 60° latitude

- Interpolate to hourly using CERES TISA interpolations

• Compute global ERB every hour

• Use ISCCP clouds & regional albedos w/ ERBE ADMs to compute NISTAR radiances at specified UTC & L1 position, 1985-88

• Calculate correction factors for monthly mean radiance conversion

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Narrowband-broadband conversion

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Testing Interpolation

• normalize to ERBS, compare to NOAA-9 ERBE fluxes

• RMS error least for all categories, but CS

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March 21, 1986, 15° east from L1

Simulated albedo/reflectance field

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Mean SW parameters as function of L1 orbit position, March 1986

Missing light factorBDR Factor

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Daily variability in missing light correction is small < 0.5%

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Variation of monthly mean missing light factor as function of L1, 00 UTC

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Mean LW parameters as function of L1 orbit position, March 1986LD variability < 0.2%

OLR (nightside) correction factor

var < 1.1%

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Variation of monthly mean nightside OLR factor as function of L1, 00 UTC

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SUMMARY

• Both diurnal and seasonal variability are significant for all DSCOVR correction parameters

• Varibilities also sensitive to DSCOVR offset phase angle (from L1)

• One year correction factors computed:

– BRF 1.1216 -- 1.1616 SD 0.0018 -- 0.0176 (1.5%)

– MLCF 1.0063 -- 1.0259 SD 0.0008 -- 0.0048 (0.5%)

– LDC 1.0354 -- 1.0519 SD 0.0002 -- 0.0012 (0.2%)

– NSCF 0.9448 -- 1.0083 SD 0.0021 -- 0.0106 (1.1%)

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APPLICATIONS

• Correction factors can be used independently to correct NISTAR measurements

- will not account for dramatic scene changes

- Need updating with CERES data and models

• Same analysis approach can be used if cloud data and narrowband radiances available (CERES TISA approach)

- should yield same radiance as CERES, on average, bias would indicate differences in calibration

- Cloud data from EPIC insufficient

- Cloud data from GEO + MODIS best option

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Use Canned Correction Models

• Perform fits to simulated data as function of month/day, L1 position, UTC, Fourier or EO fits

• Apply to NISTAR observations

• Unless drastic changes in scene distributions occur,

monthly means should be extremely accurate

– Night side?

– ADM uncertainties?

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Global Albedo Correction Model

This model is designed to predict the corrected global mean albedo for given GMT and day:

global (tg,td) triana (L1L1tg,td)·F(L1L1tg,td)

where tg is the GMT and td is the day of the year.

F(L1L1tg,td) is the missing light albedo correction function.

F(L1L1tg,td)=mnTmn(tg,td)·nL1m

L1

where m, n=0, 1, 2, 3 and

Tmn(tg,td)= ijCij tjg ti

d

where i, j=0, 1, 2, 3.

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Global OLR Correction Model

This model is designed to predict the corrected global mean albedo for given GMT and day:

OLRglobal

(tg,td) OLRtriana(L1L1tg,td)·FS(L1L1tg,td)

where tg is the GMT and td is the day of the year.

Folr (L1L1tg,td) is the OLR correction function.

Folr(L1L1tg,td)=mnTmn(tg,td)·nL1m

L1

where m, n=0, 1, 2, 3 and

Tmn(tg,td)= ijCij tjg ti

d

where i, j=0, 1, 2, 3.

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Modeled & observed night side correction

factors1986

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Use External Cloud Data

• CERES already performs a similar analysis, not real time- TISA algorithms the basis for simulation

• CERES algorithms applied in real time GEO data subsets

- global application only computer/manpower limited

• Accounts for changes in climate, yields better daily values

– Parallax problems?

– ADM uncertainties?

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Using GEO-LEO Data

• Intercalibrate all GEOs and LEO imagers to a single source

- done & ongoing

• Apply common cloud retrieval algorithm

- ongoing for subsets

• Fusion: GEO-LEO can provide cloud clearing for aerosol & surface property retrievals

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Example: real-time cloud retrievals at 4 km resolution, 18 UTC, 7 Nov 2006Cloud properties are derived every 30 minutes from GOES-11 & 12 over CONUS and merged - these include all of the same properties derived from MODIS for CERES

http://www-angler.larc.nasa.gov/satimage/products.html

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Example: real-time cloud retrievals from MTSAT, 02 UTC, 7 Nov 2006

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Example: full-disk cloud retrievals from Meteosat, 12 UTC, 26 April 2007

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Example: full-disk cloud retrievals from GOES, 8 May 2007

GOES-11 (W) GOES-12 (E)

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Parallax Problems: What size regions with VZA?

Would we need to worry about this in making corrections? Will be a factor at all high VZA/SZA.

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Summary

• Capability to monitor global albedo/ERB globally from NISTAR- Estimate night side OLR, not true climate monitor

- Cannot get regional scale ERB

• Corrections do not appear to be highly variable interannually - need more data + new CERES models

• Explicit corrections can be made using GEO-LEO data- Is this approach too redundant with CERES?

- Or is it the means to constrain/compare CERES?

• Basic algorithms developed for either approach

- Need to be refined, streamlined, & documented

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EPIC Notes

• EPIC could be a good calibration reference

- always has another imager with proper geometry

• EPIC view angles, when matched with LEO/GEO imagers provide capability to estimate cloud particle habit/shape, aerosol & surface properties

Earth Radiation Budget from NISTAR

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