Variogram Stability Analysis Tim Hewison, Rob Roebeling EUMETSAT

HIRS Data – Objectives Prerequisites and Benefits To recalibrate time-series Meteosat First Generation and Meteosat Second Generation infrared radiances from 1982 till date using a superior instrument as reference. Prerequisites: Inter-calibration back to 1982 Target accuracy over the time-series better than 1 K Inter-calibration with uncertainty estimate Method Select reference instrument Assess the uncertainties through systematic review of spectral conversion functions Define the inter-calibration approach Reprocess and validate the Data processing and verification Instrument drift is SRF shifts & sensor degradation

METEOSAT 1984-2005 Archive evaluation using radiosondes Upgrade of calibration technique (van de Berg, et al., 95) Upgrade of calibration technique (Schmetz, 1989) ISCCP DX Normalized Instead of nominal Comparisons between the METEOSAT BTs and the simulated BTs from radoisoundings: (+) represent the raw data, (◊) represent the homogeneised data. The histogram shows the nb of soundings used for comparison. Can we do better than that and extend to SEVIRI? Courtesy of Helene Brogniez and Rémy Roca, LMD

Traditional inter-calibration approach Slide: 4

Proposed GSICS inter-calibration approach Delta Correction to transfer from one reference to another Defined as differences between inter-calibration functions Defined in channel-space of monitored instrument No need for direct comparisons of references More explanation needed Delta Slide: 5 5

Proposed GSICS inter-calibration approach Delta time steps inserted for illustration only In practice, deltas defined from simultaneous double-differences Make lines transparent Delta Slide: 6 6

Uncertainties of Meteosat-HIRS inter-calibration Uncertainties introduced due to: SBA due to SRF differences Systematic and Random: Spatial Temporal Radiometric Noise Aliasing diurnal cycle variation Due to orbital drift Radiometric calibration drift - Quantified with SBAF } }- GEO-IASI Unc Anal Negligible? Quantified by Tett et al. Quantified here!

Method Can quantify instrument calibration drift wrt IASI Using 4-year time series of inter-comparisons Meteosat7/MVIRI-MetopA/IASI MetopA/HIRS-MetopA/IASI (MetopA has been in stabilised 21:30 orbit 2006-2013) Weighted Regression of collocated radiance Evaluation of standard radiance bias (for 1976 US Std Atm) As brightness temperature bias, ΔTb Calculate temporal variogram from ΔTb time series:

Time Series of MetopA/HIRS Bias wrt MetopA/IASI MetopA/HIRS Ch12 & Ch8 ~ Meteosat/MVIRI “WV” and “IR” Processed using GSICS GEO-IASI ATBD GSICS RA Correction coeff Evaluated Bias for Standard Scene radiance Expressed as Tb Ch12: small, irregular var Ch8: small annual cycle Time Series of Standard Biases for Ch12 and Ch8 of Metop-A/HIRS calculated with reference to Metop-A/IASI.

Variograms for MetopA/HIRS Ch12 & Ch8 “WV” and “IR” channels of Meteosat/MVIRI Variograms increase with time interval 1-29d Averaging period used in GSICS Correction “WV” Maximum at Δt=1yr: (2γt)1/2=33.8±2.2 mK “IR” Minimum at Δt=1yr: (2γt)1/2=9.0±0.6 mK Error budget contributions Negligible wrt SBAF Temporal variograms [(2γt)1/2] calculated as RMS differences in Standard Biases for Ch12 and Ch8 of Metop-A/HIRS calculated with reference to Metop-A/IASI. Vertical lines show periods of 29d and 1yr.

Time Series of Meteosat7/MVIRI Bias wrt IASI Meteosat7/MVIRI “WV” and “IR” Processed using GSICS GEO-IASI ATBD GSICS RA Correction coeff Evaluated Bias for Standard Scene radiance Expressed as Tb WV: strong yearly cycle IR: twice-yearly cycle + long-term drift (ice contamination?) Time Series of Standard Biases for “WV” and “IR” channels of Meteosat7/MVIRI calculated with reference to Metop-A/IASI.

Variograms for Meteosat-7/MVIRI “WV” and “IR” “WV” and “IR” channels of Meteosat/MVIRI Variograms increase with time interval 1-29d Averaging period used in GSICS Correction “WV” Minimum at Δt=1yr: (2γt)1/2=65±4 mK “IR” Minimum at Δt=1yr: (2γt)1/2=187±12 mK Higher “nugget values” More collocation noise Higher “sill values” Faster calibration drift Temporal variograms [(2γt)1/2] calculated as RMS differences in Standard Biases for “WV” and “IR” channels of Meteosat-7/MVIRI calculated with reference to Metop-A/IASI. Vertical lines show periods of 29d and 1yr.

Conclusions Calibration drift of MetopA/HIRS channels: Ch12 (“WV”): 34mK over 1yr << SBAF uncertainty (~0.74K) Ch8 (“IR”): 9mK over 1yr << SBAF uncertainty (~34mK) HIRS may serve as stable inter-calibration reference for WV+IR But HIRS on other platforms suffer from orbital drift Changing instrument environment (temperature, stray light) Aliasing diurnal cycle Calibration drift of Meteosat7/MVIRI channels: “WV”: 65mK over 1yr << SBAF uncertainty (~0.74K) “IR”: 187mK over 1yr > SBAF uncertainty (~34mK) Better to use HIRS to bridge time periods between Meteosats? Or apply bridge at same time of year to minimise variance?