www.le.ac.uk requirements consolidation of the near- infrared channel of the gmes-sentinel-5 uvns...
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Requirements Consolidation of the Near-Infrared Channel of the GMES-Sentinel-5 UVNS Instrument
Scattering profile characterisation for SWIR
Leif Vogel, Hartmut BoeschUniversity Leicester
Approach for Retrieval Simulations
• Spectra are simulated using the forward model of UoL FP retrieval algorithm for a range of geophysical scenarios
• Sensitivity tests for retrievals w.r.t. scattering profiles, i.e. the retrieval applies
• the same a priori trace gas profiles, temperature profile, surface albedo
• different setup for aerosol and cirrus a priori
• Maximal sensitivity to scattering induced errors
• Bias given by difference between true and retrieved XCH4
The UoL Retrieval Algorithm
• Measured radiance spectra are non-linear function of atmospheric parameters• retrieval is performed iteratively by
alternating calls to FW and IM
• Forward Model describes physics of measurement: • Multiple-scattering RT• Instrument Model• Solar Model
• Inverse Method estimates state: • Rodger’s optimal estimation
technique
• XCH4, XCO and its error is computed from retrieved state after iterative retrieval has converged
Names Quantity Notes
CO and CH4 1 Multiplier to a priori profile
H2O, HDO, CO2 1 Multiplier to a priori profile
Temperature 1 Additive offset to a priori profile
2 Aerosols AOD, height and width
Gauss profile
Cirrus clouds AOD, height and width
Gauss profile
Surface Albedo #bands x 2para Albedo at band centre and slope
Typical State Vector
Retrieved properties
Concept A Bands NIR (685 – 773 nm)* SWIR 1 SWIR3
NIR 1 NIR 2
Wavelengths [nm] 685 - 700 750 – 773 1590 - 1675 2305 - 2385
Numbers of pixel 116 177 850 800
FWHM ISF 0.39 0.39 0.25 0.25
*) Simulated retrievals do not use full range due to strongly changing surface albedo
Concept B
Instrumental setup
Instrumental errors (ECHAM Scenarios)
• Aerosol profiles originating from ECHAM 5 model simulations (Stier et al 2005)
• Global coverage for one day (April 15th, 2015)
• Atmosphere: 18-level profile
• SZA: noon local time (27º- 87º)
• Total AOD given by MODIS measurements
• Surface albedo determined by MODIS and Sciamacy data
Geophysical scenario described in Butz et al. 2010, Butz et al. 2012
ECHAM Kahn et al. 2001
Mode Aerosols Base/Mixt. Aerosols
Nucleation SU Base SU land
Aitken SU, BC, POM Mix 5a SU, acc.DU, BC, Carb
Accumulation SU, BC, POM, SS, DU Mix 3a SU, SS, BC, Carb
Coarse SU, BC, POM, SS, DU Mix 4a SU, acc.DU, coarse DU, Carb
Aitken BC, POM Mix 3b BC, Carb, SU, SS
Accumulation DU Base Acc. DU
Coarse DU Base Coarse DU
Cirrus clouds
Calipso data, Gaussian profile, optical properties from Baum et al. (2005) for reff = 60µm
ECHAM Desaster
Simulated ECHAM scenarios
Sensitivity to radiometric accuracy
• Linear mapping of errors has been used to determine additive and multiplicative ARA errors – Additive gain: 3% of trop dark scenario in
respective band– Multiplicative gain: 3% for NIR1 and 2
• RSRA/ESRA errors determined by SWIR study
Simulated ECHAM scenarios
additive ARA
Error source
ECHAM Scenarios; Concept A
Instrumental
Std dev mean
ARA-additive
NIR 1 0.703 -0.207
NIR 2 1.072 0.881
NIR
1N
IR 2
Simulated ECHAM scenarios
multiplicative ARA
Error source
ECHAM Scenarios; Concept A
Instrumental
Std dev mean
ARA-multiplicative
NIR 1 0.750 -0.258
NIR 2 0.946 0.494
NIR
1N
IR 2
Simulated ECHAM scenarios
Sensitivity to ISRF
ISF
nominal Gaussian function convolved with a box-car, fitted to the ESA supplied function
asy1pc
Independently scaling the width of the nominal function on either side of the peak. Asymmetry is introduced with a maximum impact of 1% of the peak value of the nominal function
homm Scene inhomogeneityGradient in along-slit illumination (10% of the mean illumination, direction of assumed gradient “…m” or “…p”)homp
idisp-1 Spectrally offset versions of the nominal slit function are added to the slit function itself; ISRF with the same centre of mass and FWHM as the original pattern. (error falls with then 1% enveloped of the requirement)
idisp1
idisp-2
idisp2
idisp-3
idisp3
wid1pc The effect of perturbing the width of the nominal function by 1%
• Linear mapping of errors has been used to determine sensitivity to ISRF
• 11 different slit functions are studied
asymmetry
Scene inhom
Spectral offset
width
Simulated ECHAM scenarios
Sensitivity to ISRF
R. Siddans
Simulated ECHAM scenarios
Sensitivity to ISRF
Sensitivity to ISRF
• Greatest CH4 error via idisp-3
• NIR 1 channel much less sensitive
• Allowing for the retrieval algorithm to spectrally shift and squeeze may mitigate (or mask) effects
ISFCH4 bias
NIR1 mean [%]
NIR1 std [%]
NIR2 mean [%]
NIR2 std [%]
Total mean [%]
Total std [%]
asy1pc -0.006 0.007 -0.007 0.024 0.010 0.025idisp-1 -0.003 0.084 0.163 0.298 0.163 0.309idisp1 -0.013 0.082 0.121 0.232 0.122 0.246idisp-2 0.005 0.096 0.207 0.358 0.207 0.371idisp2 -0.009 0.092 0.120 0.234 0.120 0.251idisp-3 0.014 0.107 0.236 0.402 0.237 0.416idisp3 -0.002 0.106 0.120 0.264 0.120 0.285wid1pc -0.018 0.099 0.172 0.342 0.173 0.356
Total range (asy1pc – idisp-3)
-0.006 – 0.14
0.007 – 0.107
-0.007 – 0.120
0.024 – 0.402
0.010 – 0.237
0.025 – 0.416
Simulated ECHAM scenarios
ISFCH4 bias
NIR1 mean [%]
NIR1 std [%]
NIR2 mean [%]
NIR2 std [%]
Total mean [%]
Total std [%]
homm0.035 0.071 -0.033 0.464
0.048
0.469
homp-0.035 0.071 0.034 0.465
0.048
0.470
Scene Inhomogeneity
homm; homp0.035 0.071 0.034 0.465
0.048
0.469
Sensitivity to ISRF, Scene inhomogeniety
• NIR 1 channel much less sensitive
• Homm; homp slit function errors are not independent– Error of scene inhomogeneity is given as absolute mean
• Introduced bias is very low with 0.048%
• A greater variability in the NIR2 channel leads to total standard deviation of 0.469%.
Simulated ECHAM scenarios
Instrumental errors (ECHAM)
ConclusionsError source ECHAM Scenarios; Concept A
Instrumental Std dev mean
ARA-multiplicative 1)
NIR 1 0.750 -0.258
NIR 2 0.946 0.494
ARA-additive 2)NIR 1 0.703 -0.207
NIR 2 1.072 0.881
RSRA or ESRA 3) Done by SWIR study group
1 0
ISRF variations 4)
NIR 1 0.007 - 0.107 -0.006 - 0.014
NIR 2 0.024 - 0.402 -0.007 - 0.237
Scene inhomogeneity 5)
NIR 1 0.071 0.035
NIR 2 0.465 0.034
Total Instrumental 6)
NIR1 and NIR2 2.0791 - 2.120 1.064 - 1.090
Only NIR 2 1.780 - 1.787 0.814 - 0.816
ARA requirements: Mean CH4 accuracy meets requirements, but standard deviation is rather high.
Reduction would be beneficial
Simulated MACC scenarios
Simulations with ECHAM 5 model simulations as described in Stier et al 2005, Butz et al 2010, Butz et al 2012
Description of atmospheric parameters and aerosol optical properties not directly transferable to the UoL algorithm.
Calculated aerosol optical properties are either dust or sulphate dominated
ECHAM 5 aerosols replaced with aerosols from MACC, ECWMF integrated forecasting system (IFS), 12h GMT April 14th 2010
Use atmospheric data from the previous scenarios in combination with ECMWF aerosols to increase number of successful retrievals
ECHAM Desaster
MACC vs. ECHAM Scenarios
Replace only aerosols All other scenario
information remains unchanged
Cirrus clouds, atmosphere, pressure levels, surface albedo, etc.
Different retrievals for MACC simulationsAerosol parameterization:
• Use two linear combination of aerosol types to approximate true type
• 2 generic Gaussian aerosol extinction profiles (altitude =2km agl, width = 1.5km, aod = 0.1)
• Cirrus (altitude 10km agl, width =1km, cod = 0.05
In total 8 global retrievals to study representation errors`
Representation errors(MACC scenarios)
Forwardsimulations
Retrieval
Without fluorescence With fluorescence
2 aerosols NIR1 and NIR2 Only NIR2 NIR1 and NIR2 Only NIR2
2 aerosls with zero level offset (fluorescence mitigation)
NIR1 and NIR2 Only NIR2 NIR1 and NIR2 Only NIR2
Simulation of fluorescene
• Fluorescence data supplied by L. Guanter
• FS Spectra added to simulated Spectra taking into account respective aerosol load and viewing direction
NIR 1&2 NIR 1&2NIR 2 NIR 2without fluorescence with fluorescence
with
out o
ffset
with
offs
etRepresentation errors
(MACC scenarios)
Some regional differences can be observed:• effect of fluorescence (without offset correction)• Indication that zero level offset may couple unfavourably with
cirrus clouds• Similar coverage of NIR 1&2 and NIR 2 only retrievals
CH4 bias [%]NIR 1&2 NIR 1&2NIR 2 NIR 2
without fluorescence with fluorescence
with
out o
ffset
with
offs
etRepresentation errors
(MACC scenarios)
Blue: converged retrievals over ice-free landGreen: a-posteriori filter is applied
NIR 1&2 NIR 1&2NIR 2 NIR 2without fluorescence with fluorescence
with
out o
ffset
with
offs
et
CH4 retrieval error [%]
Blue: converged retrievals over ice-free landGreen: a-posteriori filter is applied
Representation errors(MACC scenarios)
MACC scenarios
Converged MACC Scenarios
Error sourceNIR1 and NIR2(O2-A and O2-B band)
NIR2(O2-A band)
Error CH4 [%] std dev mean bias Mean precision
# retrievals 1) std dev mean bias Mean
precision# retrievals 1)
No FS, no offset 0.609 -0.067 0.127 1269 (65%) 0.864 -0.168 0.162 1419
(74%)
No FS, offset 0.838 -0.052 0.196 1429 (74%) 1.039 -0.116 0.224 1659
(86%)
FS, no offset 0.874 0.000 0.129 1069 (55%) 0.793 -0.108 0.162 1353
(70%)
FS, offset 0.831 -0.049 0.197 1395 (72%) 1.066 -0.129 0.226 1623
(84%)
1) Number of converged retrievals out of a total of 1933 simulated measurements over land and ice free surface.
All retrievals fulfill requirements• Less converged retrievals for NIR 1&2 than for only NIR2
<->Tighter boundary conditions due to O2-B band• Retrievals with NIR 1&2 show better performance in random and systematic errors
• Fluorescence leads to higher errors, but its effect can be mitigated• Indication that aerosol information in the O2-B band constrains the retrievals at cost
of lesser coverage <-> filtering effect
SummaryInstrumental errors from ECHAM ScenariosInstrumental Systematic 1) Pseudo random 2) Random 3)
ARA-multiplicativeNIR 1 -0.258 0.750
NIR 2 0.494 0.946
ARA-additiveNIR 1 -0.207 0.703
NIR 2 0.881 1.072
RSRA or ESRA 4) Done by SWIR study group
0 1
ISRF variations 5)NIR 1 -0.006 - 0.014 0.007 - 0.107
NIR 2 -0.007 - 0.237 0.024 - 0.402
Sceneinhomogeneity
NIR 1 0.035 0.071
NIR 2 0.034 0.465
Total Instrumental 6)NIR1 and NIR2 1.064 - 1.090 2.0791 - 2.120
Only NIR 2 0.814 - 0.816 1.780 - 1.787
Representation errors from MACC scenariosConverged but not filtered results
Systematic 1) Pseudo random 2) Random 3)
Simulation with Fluorescence, retrieval with 2 aerosols and zero level offset
NIR1 and NIR2(1395, 72%)
0.049 0.831 0.197
Only NIR 2(1623, 84%)
0.129 1.066 0.226
Total error 9)
NIR1 and NIR2 1.065 - 1.091 2.239 - 2.277 0.197
Only NIR 2 0.824 - 0.826 2.075 - 2.081 0.2261) Systematic is described here by the mean bias2) Pseudo random is described as the standard deviation of the mean bias 3) Random is given by the mean of the retrieval error where applicable.4) 50% of user requirement5) Minimum and maximum values from the ILS variations. Min. variations are taken from asy1pc, max. values from idisp-36) The two values result from the assumed minimum and maximum error of the ILS
Conclusion:• Retrievals have been performed with two geophysical
Scenarios based on ECHAM and MACC aerosol distributions for instrumental and representation errors.
• Most error sources lead to results inline with the requirements. However, additive and multiplicative ARA induced errors are high. Reduction of these error sources is desirable.
• Representation errors meet the requirements. • Using a two NIR (O2-A & B) band retrieval increases
accuracy at the cost of slightly diminished coverage, and its use is beneficial to prevent erroneous results.
• The effect of fluorescence can be mitigated using a zero level offset.
• Further potential lies in improved aerosol representations (regional dependencies, climatology, improved optical properties), which may also lead to increased coverage.