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

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

Figure 4. A comparison between GOES-11 brightness temperatures and those observed by the AATSR instrument shows large (up to ~0.8K) 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.

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.

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

Figure 6. 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 is larger gain across the board 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 7. Shows the impact of the new calibration relative to the operational 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.

Jonathan Mittaz1, Andy Harris1 & Eileen Maturi2 (GOVERNMENT PRINCIPLE INVESTIGATOR)

1CICS/ESSIC University of Maryland, 2NOAA/NESDIS/STAR

  • The GOES calibration shows large temporally varying biases of up to ~0.8 K (see Fig. 4) which significantly impact analyses based on GOES radiances. For example, the impact of such biases on the GOES SST product is large affecting the cloud mask as well as the SST itself, particularly when using physical retrieval algorithms. We have therefore studied the GOES calibration to better understand such biases to
    • Devise an ad-hoc radiance bias scheme (not the most accurate solution). See the Harris et al. poster.
    • Devise a correction to the GOES calibration if possible (this poster)

Requirement: This provides uniformly consistent information delivered ‘ready-for-use’ in applications world-wide. Thus reducing the cost to the entire user community.


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

meet the requirements of more sophisticated retrieval algorithms as well as provide an accurate climate data record?

Benefit: Improve the accuracy of AVHRR and GOES radiances leading to better derived products supporting the following NOAA Mission Goals.

ecosystems -Develop integrated ecosystem assessments Enabling NOAA for regional management

weather and water-improve forecast capability in coasts, estuaries, and oceans

Climate-• Understand impacts of climate variability and change on marine ecosystems


  • The current AVHRR calibration adds significant biases into the observed radiances and, in particular introduces
    • A strong scene temperature dependent bias (a comparison with IASI is shown in Figure 1). Comparisons with the AATSR and the pre-launch data show a similar effect (see Figure 2).
    • An instrument temperature bias seen in the pre-launch data which is likely to impact long term/climate data records (see Figure 2).
  • There are a number of reasons for these biases in the current calibration
    • Significant contamination of the pre-launch test data by the test environment.
    • An ~1K instrument temperature drift during each calibration run
    • An incorrect parameterization of the calibration equations.
    • The parameterization of the instrument calibration changes significantly between the pre-launch and in-orbit cases.
  • To solve these issues and have derived a new physically meaningful calibration equation which fixes many of the problems with the current calibration.

GOES already has known calibration issues, most notably the need for a so called Midnight Blackbody Calibration Correction (MBCC) used to correct for the contamination of the on-board calibration system around the time of local midnight by a hot radiance source. A correction is currently included in the operational calibration which derives the corrected gain from a correlation between the instrument responsivity (defined as where m is the first order gain and γ is the non-linear coefficient) and the primary mirror temperature. The corrected gain is used during times of contamination. Our analysis of the calibration, however, indicates that the square of the first order gain is a more physically meaning parameter to use (see Figure 5)

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.

α = Bias term

RE = Obs. Radiance

εBB= BB emissivity

ρ = Correction fact.

rScatt= Stray/Scat light

γ = Non-linear term

CS = Space counts

CBB= BB Counts

CE = Obs Counts

Note that the above equation is considerably different from the current calibration equations. The underlined terms are those that are significantly contaminated by stray/scattered light from the pre-launch test environment and will, of course, have different values when the AVHRR is in orbit..

Comparisons between the operational and our new calibration are shown in Fig. 6 and show both the uncorrected and corrected operational gains are under-estimated. Figure 7 shows the impact of this and indicates that the operational calibration does introduce a -0.8K bias with a similar temporal behavior as that seen in Figure 4. Therefore this new calibration could provide a significant improvement to all GOES radiances and hence to GOES products including the SST.

Because of the scattered light problems in the AVHRR pre-launch data some of the calibration parameters have to be determined in orbit using other satellites whose top of atmosphere (TOA) radiances are believed to be accurate such as the (A)ATSR series or IASI As an example we have refitted the MetOp-A AVHRR calibration parameters using IASI and the new calibration is shown in Figure 3 where we only show data which is independent of the fitting process. When compared with the current calibration (Fig. 1) the improvement is significant with only a small residual bias remaining.

Science Challenges: The early AVHRR/1 and AVHRR/2 series lack accurate TOA radiance sources pre-(A)ATSR. For the GOES, the radiances from the new calibration needs to be compared with in-orbit calibration sources.

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

Transition Path: The AVHRR historic data will be re-calibrated to provide a Fundamental Climate Data Record funded through the NOAA Science Data Stewardship program. The new GOES calibration will, if funded, be developed and transitioned through GIMPAP/PSDI.



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.