CRN Workshop, March 3-5, 2009 1 An Attempt to Evaluate Satellite LST Using SURFRAD Data Yunyue Yu a,...
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Transcript of CRN Workshop, March 3-5, 2009 1 An Attempt to Evaluate Satellite LST Using SURFRAD Data Yunyue Yu a,...
CRN Workshop, March 3-5, 2009 1
An Attempt to Evaluate An Attempt to Evaluate Satellite LST Using Satellite LST Using
SURFRAD DataSURFRAD Data
Yunyue YuYunyue Yuaa, Jeffrey L. Privette, Jeffrey L. Privettebb, Mitch Goldberg, Mitch Goldbergaa
a a NOAA/NESDIS/StARNOAA/NESDIS/StARb b NOAA/NESDIS/NCDCNOAA/NESDIS/NCDC
CRN Workshop, March 3-5, 2009 2
OutlinesOutlines
Motivation
Data Sources
Method
Results
Summary
CRN Workshop, March 3-5, 2009 3
MotivationMotivation
Satellite LST Validation Needs NeedsSatellite LST Validation Needs Needs» Over 30 years LST development at NOAA – Climate Over 30 years LST development at NOAA – Climate
Data RecordData Record
» Validation Needs for NPOESS/VIIRS LST ProductValidation Needs for NPOESS/VIIRS LST Product– Five years Cal/Val plan: 2009 – 2013Five years Cal/Val plan: 2009 – 2013– Core ground data source : 20 SURFRAD/CRN sitesCore ground data source : 20 SURFRAD/CRN sites
» Validation Needs for GOES-R/ABI LST ProductValidation Needs for GOES-R/ABI LST Product– Pre-launch validation plan: 2009 – 2013Pre-launch validation plan: 2009 – 2013– Core ground data source : 10-15 SURFRAD/CRN Core ground data source : 10-15 SURFRAD/CRN
sitessites
» Validation Needs for GIMPAP LST productValidation Needs for GIMPAP LST product
SURFRAD/CRN data plays critical role in NPOESS and GOES-R Programs !!SURFRAD/CRN data plays critical role in NPOESS and GOES-R Programs !!
CRN Workshop, March 3-5, 2009 4
Motivation (2)Motivation (2)
LST Validation DifficultiesLST Validation Difficulties» In Situ data limitationIn Situ data limitation
– measurement difficulty: emissivitymeasurement difficulty: emissivity
» Effect of cloud contaminationEffect of cloud contamination– Partial or thin cloudy pixels Partial or thin cloudy pixels
» Spatial and temporal variationsSpatial and temporal variations » Angle effectAngle effect
New Method ExplorationNew Method Exploration
CRN Workshop, March 3-5, 2009 5
Data SourcesData Sources
No.No. Site LocationSite Location Lat/LonLat/Lon Surface Type*Surface Type*
11 Pennsylvania State University, PAPennsylvania State University, PA 40.72/77.9340.72/77.93 Mixed ForestMixed Forest
22 Bondeville, ILBondeville, IL 40.05/88.3740.05/88.37 Crop LandCrop Land
33 Goodwin Creek, MSGoodwin Creek, MS 34.25/89.8734.25/89.87 Evergreen Needle Evergreen Needle Leaf ForestLeaf Forest
44 Fort Peck, MTFort Peck, MT 48.31/105.1048.31/105.10 Grass LandGrass Land
55 Boulder, COBoulder, CO 40.13/105.2440.13/105.24 Crop LandCrop Land
66 Desert Rock, NVDesert Rock, NV 36.63/116.0236.63/116.02 Open Shrub LandOpen Shrub Land
Down-looking PIR at 8 meter height from the ground
UP-looking PIR
Diffuse Radiometer
Down-looking PIR on the towerAt 8-m from ground
Thermometer
Anemometer
Duration of Data: Jan 1 – Dec 31, 2001
GOES-8 and GOES-10 Imager data were applied in validating the LST algorithm using ground data from SURFace RADiation (SURFRAD) budget network stations
Satellite and Ground DatasetsSatellite and Ground Datasets
CRN Workshop, March 3-5, 2009 6
Data Source (2)Data Source (2)
GeolocationMatch-up
SURFRADData
SatelliteData
TimeMatch-up(<15 mins)
Time SeriesSmoothness Check:Upwelling, Downwelling
Irradiances
SpatialDifference Test:T4 -- 3X3 pix STD,Visual -- 0.5 deg
Channel BTDifference Test:
(Ts, T4), (T4, T2)(T4, T5)
MatchedDataset
ManualTuning
Match-up Flow Chart
CRN Workshop, March 3-5, 2009 7
Data Sources (3)Data Sources (3)
» The difference between the top of the atmosphere channel 4 brightness temperature from GOES satellite for the spatially closest pixel and the land surface temperature derived from SURFRAD measurements should be generally 5 K or less for clear sky conditions.
» The standard deviation of the 3 by 3 pixel array GOES channel 4 brightness temperature should no exceed 1.5 K.
» The absolute difference between GOES channel 4 and channel 2 brightness temperatures should not exceed 5 K.
» The absolute difference between GOES channel 4 and channel 5 brightness temperatures should not exceed 1 K.
» The time series curves of solar irradiance should be smoothly varying without distortions.
» The time series curves of down-welling infrared irradiance also should be smoothly varying in time without any significant enhancement.
» The average reflectance for the spatially closest GOES-pixel should be generally less than 40% except for snow conditions which can be mostly identified from sequence of hourly GOES images. Snow is more static than clouds.
» Finally the 0.5 degree by 0.5 degree around the SURFRAD site must be visually clear of clouds to form coincident pairs of cloud-free SURFRAD and GOES data.
Match-up Data Processing
CRN Workshop, March 3-5, 2009 8
Data Sources (4)Data Sources (4)
Atmosphericprofiles
TOAradiances
MODTRAN
Input (looping)parameters
Start
Surface Type Configuration
AlgorithmCoeffs.
Sensor SpectralResponse Funs
SensorBrightness
Temperatures
Sensor Brightness
TemperatureCalculation
Regression of LST
Algorithms
STD ErrorOf
Algorithms
Input parameters
Filter ofData
Distribution
AlgorithmSelected
AccuracyAnalysis
Sensitivities Analysis
tables
plots
Simulation Process
Regression Process
Analyzing Process
Developing for Satellite LST Algorithm
CRN Workshop, March 3-5, 2009 9
Data Sources (5)Data Sources (5)
MonthSite 1 Site 2 Site 3 Site 4 Site 5 Site 6
Day Night Day Night Day Night Day Night Day Night Day Night
1 16 33 46 69 76 154 57 124 84 157 113 245
2 17 45 9 28 36 86 78 139 35 95 96 135
3 0 0 33 92 70 94 77 125 23 58 145 141
4 66 84 28 42 63 89 25 64 44 67 112 74
5 40 69 21 31 107 134 90 64 51 43 158 190
6 26 39 37 54 37 83 27 32 49 64 235 189
7 1 8 34 56 31 48 14 22 48 34 250 226
8 16 33 35 69 12 47 106 106 39 64 188 195
9 46 83 70 110 84 102 69 76 97 123 226 257
10 56 77 66 101 156 213 39 67 28 75 96 152
11 59 118 84 148 47 112 32 94 110 176 85 147
12 25 54 35 99 61 148 38 133 73 124 58 72
Number of Match-up Dataset: Number of Match-up Dataset: GOES-8 and SURFRAD and SURFRAD
Overall: Large number for statistical significance.Overall: Large number for statistical significance.
CRN Workshop, March 3-5, 2009 10
Data Source (6)Data Source (6)
LST estimation from SURFRAD measurementLST estimation from SURFRAD measurementThe LST values were derived through Stefan-Boltzmann (SB) Law from up-welling irradiance measured by the down-looking broad band PIR in the spectral range from 3 to 50 microns. Stefan-Boltzmann Law can be stated as
e = T4
e -- surface emitted irradiance
-- emissivity of the surface
-- the Stefan-Boltzmann constant
T -- temperature of the surface in degree Kelvin
To obtain the surface emitted irradiance e from the SURFRAD upwelling irradiance
measurements, we first subtract the reflected portion of the down-welling irradiance from the PIR
irradiance value. It is done as in equation (2) given below
pir = e – (1-)d pir -- the up-welling irradiance at the SURFRAD down-looking PIR
d -- the down-welling irradiance at the SURFRAD up-looking PIR
CRN Workshop, March 3-5, 2009 11
MethodMethod
Direct ComparisonDirect Comparison» Scatter PlotsScatter Plots
» Table of StatisticsTable of Statistics Correlation AnalysesCorrelation Analyses
» Two-measurement ComparisonsTwo-measurement Comparisons
CRN Workshop, March 3-5, 2009 12
Down-looking PIR at 8 meter height from the ground
UP-looking PIR
Diffuse Radiometer
Down-looking PIR on the towerAt 8-m from ground
Thermometer
Anemometer
Satellite LST: Algorithms applied to GOES-8/10 dataGround LST: Derived from SURFRAD site measurements
Duration: Jan 1 – Dec 31, 2001
SURFRADradiance
Temperature :
emitupdown
emit
Spectral Correction:
T=T+dTpir - dT
dTpir=(dpir/ )(T/4)
dT=(T/4)(d)
GOES 8/10data
Cloud filter
Match-up and Comparison
Statistics
Algorithm:LST Calculation
Plots & Tables
Method (2)Method (2)
Procedure of of Direct Comparison
CRN Workshop, March 3-5, 2009 13Comparison of SURFRAD Estimated LSTs and GOES Retrieved LSTs
Validation Results: FORT PECK, 2001
Results for GOES-8 Results for GOES-10
Results Results ---- Direct Comparison---- Direct Comparison
CRN Workshop, March 3-5, 2009 14Comparison of SURFRAD Estimated LSTs and GOES Retrieved LSTs
Validation Results: Boulder, 2001
Results for GOES-8 Results for GOES-10
Results Results ---- Direct Comparison (2)---- Direct Comparison (2)
CRN Workshop, March 3-5, 2009 15
Validation Results: direct comparison summary
Good:● Statistical significance● Two satellite validations● Accuracy satisfaction (average RMS=2.1 K)
Issues:● Point-pixel difference● Emissivity inaccuracy● Cloud screen effectiveness
ResultsResults
---- Direct Comparison (3)---- Direct Comparison (3)
SiteGOES-8 GOES-10
Bias (K) STD (K) Bias (K) STD (K)
1 1.47 1.87 N/A N/A
2 1.06 2.26 -0.41 2.27
3 0.15 1.31 -0.84 1.53
4 -0.27 2.10 -0.97 1.87
5 -0.59 1.67 -1.37 1.91
6 -1.63 1.69 -1.69 1.30
Total -0.37 1.76 -1.23 1.69
RMS 1.80/2.07* 2.09/2.17*
*weighted through each site*weighted through each site
CRN Workshop, March 3-5, 2009 16
Method (3)Method (3)
Two-Measurement MethodLinear Approach Model
goesgoesgoes aLSTLST
surfradsurfradsurfrad bLSTLST
LST -- True LST
LSTgoes – The GOES LST measurement
LSTsurfrad – the SUFRAD LST estimation
goes – random noise of the GOES LST measurement
surfrad – random noise of the SURFRAD LST estimation
Perform Variation/Co-variation Computation
)(),()()( 2goesgoesgoesgoesgoes VARLSTCOVLSTVARLSTVAR
)(),()()( 2surfradsurfradsurfradsurfradsurfrad VARLSTCOVLSTVARLSTVAR
),(),(
),()(),(
surfradgoessurfradgoes
goessurfradsurfradgoessurfradgoes
COVLSTCOV
LSTCOVLSTVARLSTLSTCOV
CRN Workshop, March 3-5, 2009 17
Method (3)Method (3)
Two-Measurement Method
Primary Assumptions
COV(goes, surfrad)COV(LST, goes) = 0,
COV(LST, surfrad) = 0,
Therefore
surfradgoes
surfradgoes LSTLSTCOVLSTVAR
),(
)(
),()(2surfradgoes
surfrad
goesgoesgoes LSTLSTCOVLSTVAR
),()(2surfradgoes
goes
surfradsurfradsurfrad LSTLSTCOVLSTVAR
CRN Workshop, March 3-5, 2009 18
Results Results ---- Correlation Analyses---- Correlation Analyses
Relative bias V(goes) V(surfrad) V (goes-surfrad) CV(goes, surfrad) ( goes, surfrad)
0.0017 39.971 34.645 2.096 36.260 0.974
No goessurfrad goes surfrad
1 1.05 1.378 0.334
2 1.06 1.239 0.661
3 1.07 1.083 0.870
4 1.08 0.900 1.035
5 1.09 0.669 1.174
6 1.10 0.293 1.230
Samples for GOES-8 LST vs SURFRAD: Bondeville Site Case StudyBondeville Site Case Study
In the table, the Relative bias is defined as
Relative bias = surfradgoes
surfradgoes
LSTLST
LSTLST
0.2 ;
Pearson Linear correction coefficient, defined as
)()(
),(
surfradgoes
surfradgoes
LSTVARLSTVAR
LSTLSTCOV . (
Using Flynn’s estimation for the ratio ,
BAAB 1/m ,m surfrad
goes
(
where mAB=COV(LSTsurfrad,,LSTgoes)/VAR(LSTsurfrad) and
mBA= COV(LSTgoes, LSTsurfrad )/VAR(LSTgoes),rspectively.
In our case, the range is calculated as [1.047 to 1.102].
CRN Workshop, March 3-5, 2009 19
SummarySummary
SURFRAD ground station data were used for GOES-R LST SURFRAD ground station data were used for GOES-R LST algorithm evaluation.algorithm evaluation.
GOES-8, -10 Imager data were used as proxies of GOES-R GOES-8, -10 Imager data were used as proxies of GOES-R ABI.ABI.
LST algorithm coefficients were derived from a radiative LST algorithm coefficients were derived from a radiative transfer simulation model (MODTRAN).transfer simulation model (MODTRAN).
Match-up dataset of satellite and ground data were created Match-up dataset of satellite and ground data were created carefully.carefully.
Direct comparisons indicate a promising algorithm accuracy.Direct comparisons indicate a promising algorithm accuracy. Correlation analyses showed good algorithm precision Correlation analyses showed good algorithm precision Further works will be performed using three-measurement Further works will be performed using three-measurement
comparison comparison
CRN Workshop, March 3-5, 2009 20
Backup slidesBackup slides
CRN Workshop, March 3-5, 2009 21
Two-directions from GOES SatellitesTwo-directions from GOES Satellites
135° W 75°W
CRN Workshop, March 3-5, 2009 22
Difference of LSTs observed by GOES-10 and GOES-8 imager at the same location of SURFRAD station Desert Rock, NV, 36.63ºN, 116.02ºW. The simultaneous observation pairs are about 2096.
View zenith of GOES-8: 60.140
View zenith of GOES-10: 46.810
LST Directional Effect in LST Directional Effect in GOES-8 and -10 ImagerGOES-8 and -10 Imager
CRN Workshop, March 3-5, 2009 23
Goodwin Creek, MS, observation pairs are about 510. View Zenith of GOES-8/-10: 42.680/61.890
LST Directional Effect in LST Directional Effect in GOES-8 and -10 Imager (2)GOES-8 and -10 Imager (2)
CRN Workshop, March 3-5, 2009 24
Boulder, CO, observation pairs are about 510. View Zenith of GOES-8/-10: 42.680/61.890
LST Directional Effect in LST Directional Effect in GOES-8 and -10 Imager (3)GOES-8 and -10 Imager (3)
CRN Workshop, March 3-5, 2009 25
LST Directional Effect in LST Directional Effect in GOES-8 and -10 Imager (4)GOES-8 and -10 Imager (4)
Bondville, IL. Data pairs: 710 Fort Peck, MT. Data pairs: 912
View Zenith of GOES-8: 48.120
View Zenith of GOES-10: 66.140
View Zenith of GOES-8: 62.420
View Zenith of GOES-10: 62.360
Note the difference of the two sites
CRN Workshop, March 3-5, 2009 26Daytime Scatter plot comparison of the GOES LST and the SURFRAD
LST for all the match-up data in 2001, within 6 SURFRAD sites.
CRN Workshop, March 3-5, 2009 27Nighttime scatter plot comparison of the GOES LST and the SURFRAD LST for all the scatter plot comparison of the GOES LST and the SURFRAD LST for all the match-up data in 2001, within 6 SURFRAD sites.match-up data in 2001, within 6 SURFRAD sites.
CRN Workshop, March 3-5, 2009 28Dry atmos condition scatter plot comparison of the GOES LST and the SURFRAD LST scatter plot comparison of the GOES LST and the SURFRAD LST for all the match-up data in 2001, within 6 SURFRAD sites.for all the match-up data in 2001, within 6 SURFRAD sites.
CRN Workshop, March 3-5, 2009 29Moist atmos condition scatter plot comparison of the GOES LST and the SURFRAD LST scatter plot comparison of the GOES LST and the SURFRAD LST for all the match-up data in 2001, within 6 SURFRAD sites.for all the match-up data in 2001, within 6 SURFRAD sites.