Figure 2. Left hand panels show the AVHRR pre-launch data for NOAA-17 using the Walton et al. (1998)...
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A New Approach To The Calibration of The Broadband Infrared Sensors Onboard NOAA Satellites - PowerPoint PPT Presentation


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Figure 2. Left hand panels show the AVHRR pre-launch data for NOAA-17 using the Walton et al. (1998) calibration where the different instrument temperatures (10ºC, 15ºC, 20ºC, 25ºC, 30ºC shown by different symbols and colors). Both significant scene temperature and instrument temperature trends can be seen. The right hand panels show same data where the Mittaz et al. calibration has been applied which has removed the trends seen in the left hand panels from the data.

Figure 3. The IASI/AVHRR BT difference with the new calibration applied. Unlike Fig. 1 this time there are no strong scene temperature trends and the final AVHRR calibration matches the IASI BTs to within < 0.1K

A New Approach To The Calibration of The Broadband Infrared Sensors Onboard NOAA Satellites

E. Maturi, J.P.D. Mittaz & A.R. Harris

AVHRR Calibration

Requirement: Provide a Continuous Stream of Satellite Data and Information with the

Quality and Accuracy to Meet Users’ Requirements for Spatial and Temporal Sampling

and Timeliness of Delivery

Science:To improve the calibration of the AVHRR and GOES sensors to

meet the requirements of an accurate climate data record

Benefit: Will improve the accuracy of AVHRR and GOES derived products

including the SST products

GOES Calibration

The current AVHRR calibration is known to introduce significant biases into the observed radiances with most noticeably, a strong scene temperature dependent bias when compared to accurate top-of-atmosphere (TOA) radiance calibration sources. Fig. 1 shows a comparison between the IR brightness temperatures from the AVHRR flown on MetOp-A and its companion

The GOES Calibration Algorithm

instrument IASI and shows a distinct scene dependent bias caused by errors in the AVHRR calibration. Comparisons with the AATSR show a similar effect (e.g. Mittaz & Harris 2008).

Two effects are at play that cause the scene temperature dependent bias in the AVHRR. Firstly significant contamination of the pre-launch test data by the test environment coupled with an incorrect parameterization of the calibration added significant biases into the pre-launch analysis (Mittaz, Harris & Sullivan 2009). Secondly the parameterization of the instrument calibration changes significantly between the pre-launch and in-orbit cases due to differences in the thermal environments (see for example Mittaz & Harris 2009). Both of these effects are discussed below

Like the AVHRR the GOES calibration also shows evidence of large biases (see Fig. 4). However, unlike the AVHRR where there were problems with the calibration algorithm which was made significantly worse by the scattered light problems, the fundamental GOES calibration algorithm is correct. GOES, however, has other problems, most notably the need for a so called Midnight Blackbody Calibration Correction (MBCC) which is used to correct for the contamination of the on-board calibration system around the time of local midnight by a hot radiance source. The current GOES calibration does include a correction for this effect which is derived by correlating the responsivity (defined as where m is the first order gain and γ is the non-linear coefficient) with the primary mirror temperature when the midnight blackbody contamination is not in effect. Then during times when the calibration is corrupted the MBCC model is used to derive the instrument gain instead of using the observed blackbody measurements.

Figure 4 shows that even with the MBCC active there is still a significant bias implying that there are unresolved issues that need to be addressed in the GOES calibration. We have used the same principles used to derive the AVHRR calibration and have derived a new MBCC correction where instead of using the responsivity as is currently done we correlate the square of the first order gain with the primary mirror temperature. Comparisons between the old and new gains are shown in Fig. 5 and show that for GOES-11 around the time of local midnight both the uncorrected and corrected gains are under-estimated relative to the new calibration. The impact of this under-estimation is shown in Fig. 6 where the example of a pixel at 300K Is used and shows that the old calibration can introduce an up -0.8K bias into the data. Both the scale and timing of this bias matches what is seen in the GOES-11/AATSR comparison shown in Fig. 4 and indicates that the new calibration may giving more accurate radiances.

Figure 4. A comparison between GOES-11 brightness temperatures and those observed by the AATSR instrument shows large (up to 1K) biases which are a strong function of time and which seem to be centered close to local midnight.

Figure 1.A comparison between the AVHRR sensor flown on-board MetOp-A and IASI. A significant scene temperature dependent trend is clearly seen.

In-orbit data

Pre-launch data

Because of the significant problems with scattered light in the AVHRR pre-launch data some of the calibration derived parameters will have been contaminated and will not be applicable for an accurate in-orbit calibration. We have therefore refitted the MetOp-A AVHRR calibration parameters using IASI as an accurate TOA calibration source. Figure 3 shows the new AVHRR calibration compared to IASI where the data shown is independent of the data used for the fitting. When compared with the current calibration (Fig. 1) the improvement is significant. See Mittaz & Harris (2009) for details.

Figure 5. Shows the correlation between the square of the gain and the primary mirror temperature for GOES-11 for a five day period where the times around local midnight have been excluded. In general the correlation is very good although there are problems with the detector 1 of the 3.9µm which are being investigated.

The pre-launch data was taken by ITT with AVHRR observing a cold (70K) target to simulate observations of space together with an external calibration target (ECT) which simulated Earth views and provide a range of different scene temperatures. The left hand panels of Fig. 2 show the pre-launch data where the current operational (Walton et al. 1998) calibration has been applied and significant trends both as a function of scene temperature (similar to the trends shown in Fig. 1) and of operating (instrument) temperature bias are apparent.

The right hand panels of Fig. 2 show the same data where a new calibration from Mittaz, Harris & Sullivan (2009) has been applied. The calibration equation is shown above is physically based which enables the inclusion of extra stray light/scattered radiation into the calibration. This turns out to be crucial for obtaining an accurate calibration since a detailed analysis of the AVHRR pre-launch data shows a significant amount of stray light contamination caused by radiance from the test chamber being scattered from the internal blackbody into the calibration data. The new calibration corrects for such effects and the improvement can be seen in Fig. 2.

Figure 5. Shows the GOES gains with the uncorrected gain (crosses), current GOES gain (blue) and new gain derived using the square of the gain predictor (red). Note that the MBCC effect can be clearly seen in the uncorrected 3.9 and 6.75 µm channels. What is also clear is that the new gain gives rise to a larger gain during the MBCC than the current calibration which will give rise to significant differences in the observed radiances around the time of local midnight.

Figure 6. Shows the impact of the new calibration relative to the old one for a scene temperature of 300K. The data shows the difference in temperature between a data point calibrated using the current calibration and the new one and shows that the old calibration would introduce a time dependent bias of up to 0.8K around local midnight – a result remarkably similar to the GOES/AATSR comparison shown in Fig. 4.

Science Challenges: The early AVHRR/1 and AVHRR/2 series lack accurate TOA radiance sources pre-(A)ATSR and so other proxies must be found. For the GOES the new calibration needs to be implemented as part of a GOES ingestor.

Next Steps:Analysis of the pre-launch AVHRR/2 series and comparisons of AVHRR/3 data with IASI/(A)ATSR. Obtain funding to continue to look at the GOES calibration.

Transition Path: AVHRR re-calibration funded by SDS FY2009 to produce algorithms for creating an AVHRR FCDR. No path yet for a new GOES calibration.

Conclusion

The GOES calibration shows evidence of significant time dependent biases which remain in the current calibration. We have developed a new calibration which uses a different predictive model for the instrument gain and show that the new calibration should be able to reduce the GOES-11 time dependent biases. What remains is to use the new methodology to re-calibrate complete GOES images and re-derive the GOES/AATSR matches in order to evaluate how well the new calibration works in an operational sense.

Conclusion

The current AVHRR is clearly sub-optimal with biases of >0.5K at some scene temperatures. The use of a new physically based calibration whose parameters have been determined in-orbit can correct many of the current biases and yield accurate (<0.1K) AVHRR radiances.

Walton et al., 1998, J. Geophys. Res., 103, 3323-3357

Mittaz, Harris & Walton, 2009, J. Atmos. Ocean. Technol., 26, 996-1019

Mittaz & Harris, 2008, 2nd MERIS/(A)ATSR Users Workshop held in Frascati, Italy, 22-26 Sept 2008, ESA SP-666 Paper 869

Mittaz & Harris, 2009, EUMETSAT Meteorological Satellite Conference held in Bath, UK, 21-25 Sept. 2009


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