The basis for our work came on a breakthrough achieved by Prof. Irina Gladkova and her graduate student (James Cross III) at the City College of New York to merge high spectral resolution IR data (specifically AIRS) with broadband imager data (specifically MODIS). This work is detailed in Cross et al. (2013). They constructed a high spatial resolution (1 km) 13.3-µm CO2 channel for MODIS by building a relationship between the MODIS 11- and 12-µm window radiances at high spatial resolution and the same radiances averaged to low spatial resolution coincident with the AIRS fields of view (FOV). Each high spatial resolution pixel was associated with five nearby low spatial resolution FOVs.  Based on this relationship, they demonstrated that it was possible to construct high spatial resolution 13.3-µm radiances from AIRS spectral data. Since MODIS measures radiances at 13.3 µm (band 33), it serves as an ideal platform to test and analyze their method. The “fusion” constructed radiances were within 1% of the measured radiances where MODIS and AIRS both collect measurements. Cross et al. (2013) provided results for a MODIS granule (5 min) and demonstrated a positive impact on cloud top height retrievals using the Heidinger optimal estimation method (Heidinger et al. 2010). The initial application of this approach was to build such a channel for VIIRS, which lacks any IR absorption channels.

The MODerate resolution Imaging Spectroradiometer (MODIS) sensors on the Terra and Aqua platforms provide measurements in the infrared (IR) water vapor (at 6.7 µm) and carbon dioxide (4.3- and 15-µm) sensitive bands, as shown in Fig. 1a. The current polar-orbiting imager is the Visible Infrared Imaging Radiometer Suite (VIIRS). VIIRS has several major improvements to the earlier imagers, including pixel spatial resolution that remains essentially constant across the scan.  One of the primary limitations for determining cloud properties with VIIRS is that it has only IR window bands, as shown in Fig. 1b.   The information content provided by the VIIRS radiance measurements lies between the AVHRR and MODIS sensors. Without even a single IR carbon dioxide or water vapor sensitive band, the MODIS-like cloud top pressure/height and phase algorithms cannot be transitioned to VIIRS because of a fundamental loss of information. The lack of any sounding channels primarily impacts the inference of cloud properties including cloud-top height/pressure/temperature and IR thermodynamic phase. We developed an innovative solution to this problem by using V IIRS and CrIS data to construct high spatial resolution spectral bands for VIIRS in the CO2 (MODIS bands 24, 25 and 33-36), the O3 (MODIS band 30), and the H2O (MODIS bands 27 and 28) spectrally sensitive regions. The approach is described in Weisz et al. (2017) and also in our ATBD.

Our software for constructing IR radiance bands is mature and has been transitioned into Atmosphere SIPS (Science Investigator-led Processing System) operations. A benefit of our approach is that we can also construct n ew spectral band radiances for VIIRS that exclude strong trace gas absorption lines or fulfill other criteria, e.g., water vapor bands with narrower bandwidths. That is, we can construct radiances assuming either continuous or discrete spectral response functions. A further bonus from fusion is the mitigation of detector-to-detector radiometric differences and response-versus-scan mirror issues that increase product retrieval uncertainties.

Figure 1: (a) AIRS infrared brightness temperature spectrum (black) with main absorbers indicated, with the MODIS spectral response functions (SRFs; green) superimposed. (b) CrIS infrared brightness temperature spectrum with the VIIRS SRFs superimposed. The spectral response functions are scaled to fit the brightness temperature range. From Weisz et al. (2017).