Characterization of the Climate Absolute Radiance and Refractivity Observatory (CLARREO) ability to serve as an infrared satellite intercalibration reference

Abstract

Climate Absolute Radiance and Refractivity Observatory (CLARREO) is a future mission employing an infrared spectrometer with unprecedented calibration accuracy and the ability to assess its calibration on‐orbit using a novel verification system. Utilizing this capability for satellite intercalibration is a primary objective of the mission. This paper presents a new infrared intercalibration methodology that minimizes the intercalibration uncertainties and provides uncertainty estimates resulting from the scene variability and instrument noise. Results of a simulation study to characterize realistic spatial and temporal matching differences for simultaneous nadir overpasses (SNOs) of CLARREO and existing hyperspectral sounders are presented. This study, along with experience with intercalibration of real data, finds that intercalibration uncertainties are minimized when the SNOs are not screened for sky conditions but instead weighted based on the observed scene variability. Intercalibration performance is investigated for a 90° polar orbit mission and for a Pathfinder mission on the International Space Station, for various potential CLARREO footprint sizes, and as a function of mission length, scene brightness temperature, and wavelength. The results are encouraging and suggest that biases between CLARREO and sounder observations can be determined with low uncertainty and with high time frequency during a CLARREO mission. For example, the simulations suggest that a CLARREO footprint of 50 to 100 km in diameter is optimal for intercalibration, and that the 3 sigma intercalibration uncertainty is less than 0.1 K for channels at infrared window wavelengths using 2 months of accumulated SNOs, and for more absorbing channels with less scene variability the uncertainties are less than 50 mK.

Intercomparison Between VIIRS and CrIS by Taking Into Account the CrIS Subpixel Cloudiness and Viewing Geometry

“…The results in Figure show that the uniformity has little impact on the radiance biases, as long as a statistically large sample is used for analysis. The results are also consistent with previous studies (Tobin, Revercomb, Knuteson, Best, et al, ; Tobin et al, ). However, the uniformity does have a substantial impact on the STDs.…”

“…In most previous studies (Moeller et al, ; Tobin, Revercomb, Knuteson, Best, et al, ; Tobin et al, ; Wang et al, ), uniform scenes are usually selected to avoid potential uncertainties caused by geolocation errors and the collocation method. While the unique aspect of this study is the focus on the CrIS subpixel impact, it is important to include both uniform and nonuniform scenes, and understand how the results are affected by the uniformity.…”

“…The geolocation correction is important for VIIRS/CrIS intercomparisons (Tobin et al, ; Wang, Zhang, et al, ). As mentioned, the results presented in Figure are after the simplified geolocation error correction.…”

Assessment of COSMIC radio occultation and AIRS hyperspectral IR sounder temperature products in the stratosphere using observed radiances

“…These benchmark measurements, which have higher accuracy requirements than current operational instruments, would provide the ability to more accurately record upper air temperature. Though current hyperspectral IR and GPS RO measurements do not meet the CLARREO requirements, they already play an important role in the global space-based intercalibration system which plays a vital role in monitoring instrument accuracies [Tobin et al, 2006a, Smith et al, 2009Hilton et al, 2012;Tobin et al, 2016;Zou et al, 2014;Ho et al, 2009;Goldberg et al, 2011].…”

How long do satellites need to overlap? Evaluation of climate data stability from overlapping satellite records

“…These high-accuracy instrument systems will provide two fundamental products of great value to the climate science community: (1) reliable long-term records of basic climate forcings, response and feedback for analysis and climate model verification, and (2) in-flight calibration standards for environmental operational satellite sensors including weather satellites that do not have a rigorous pre-flight radiometric calibration requirement or the ability to perform degradation corrections on orbit. These ideas have been formulated in the visions of CLARREO and TRUTHS but may be tested in other reconfigurations (Wielicki et al, 2013;Best et al, 2008;Fox et al, 2013;Tobin et al, 2016). Until such techniques are developed and tested, ground-based and in situ observations continue to offer some of our best ways of tying satellite observations to traceable standards.…”