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Imager and Sounder Fusion

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Five Areas of Imager and Sounder Fusion Research

Fusion of satellite-based imager and sounder data to construct supplementary high spatial resolution narrowband IR radiances

Weisz et al. (2017) demonstrate a method to construct IR water vapor and CO2 absorption band radiances for VIIRS (at 750 m spatial resolution) through fusion with CrIS high spectral resolution radiances (at ~13.5 km at nadir) convolved to the spectral response of the desired missing band. Routine fusion processing has been established on the Atmosphere Science Investigator-led Processing System (SIPS) at SSEC where the VIIRS+CrIS fusion process is used daily to generate MODIS-like infrared (IR) channel radiances and brightness temperatures for VIIRS at M-band (750m) spatial resolution. For example, brightness temperatures are constructed using the Aqua MODIS channel 33 (13.3-micron) spectral response function. Missing IR bands produced by fusion of VIIRS and CrIS data have been compared to collocated MODIS measurements. Regional and global comparisons have been within 0.5 to 1.0 C, where the larger differences are associated with the water vapor sensitive bands. With the fusion approach, it is possible to maintain continuity in derived cloud and moisture products over the generations of polar- orbiting weather satellite sensors and continue applications that require IR absorption bands.

The fusion method consists of two steps: (a) performing a nearest-neighbor search using a k-d tree algorithm on split-window (11 and 12 µm) imager radiances for each VIIRS high-spatial-resolution (M-band data) pixel to find the five nearest in distance and radiance VIIRS low-spatial-resolution FOVs (M-band data averaged over the CrIS FOV), and (b) averaging the convolved sounder radiances at low spatial resolution for the five nearest neighbors selected in the previous step for each imager pixel. The term “convolved sounder radiances” refers to the process of applying a given spectral response function (SRF) to the sounder hyperspectral radiances. The fusion product uses SRFs defined for the MODIS sensor on the NASA Earth Observation System (EOS) Aqua.

The fusion radiances are produced for each 6-minute granule. It is performs best within the CrIS swath but is also produced to full VIIRS swath width. VIIRS/CrIS fusion covers the complete record of Suomi National Polar-orbiting Partnership (S-NPP) and NOAA-20 (the first Joint Polar Satellite System) data and is available at the NASA LAADS DAAC

(https://ladsweb.modaps.eosdis.nasa.gov/missions-and-measurements/products/FSNRAD_L2_VIIRS_CRIS_SNPP/

and

https://ladsweb.modaps.eosdis.nasa.gov/missions-and-measurements/products/FSNRAD_L2_VIIRS_CRIS_NOAA20/)

Fig. 1. CrIS sounder radiance (left), newly constructed fusion radiance (middle), and the observed MODIS radiance differences (right) for MODIS bands 25 (4.5 µm), 27 (6.7 µm) and 35 (13.9µm) in panels a, b and c, respectively, for one granule at 1436 UTC on April 17, 2015 (Weisz et al., 2017).

Daily images comparing brightness temperature of spectral bands from fusion VIIRS/CrIS on SNPP and N20 versus Aqua MODIS can be found at https://sips.ssec.wisc.edu/worldview.

Improvement in cloud retrievals from VIIRS through the use of infrared absorption channels constructed from VIIRS+CrIS data fusion

Retrieval of semitransparent ice cloud properties from the VIIRS on S-NPP and NOAA-20 platforms has been shown to be improved with the addition of IR water vapor and CO2 absorption channels (Li et al., 2020). Using fusion constructed IR spectral bands to supplement the VIIRS IR window measurements, three cloud properties – cloud mask, cloud thermodynamic phase, and cloud top height – have been produced and evaluated through comparison to the Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation/Cloud-Aerosol Lidar with Orthogonal Polarization (CALIPSO/CALIOP) V4-20 cloud layer products and MODIS Collection 6.1 cloud top products. Each of these cloud properties shows improvement with the use of these constructed radiances. The major improvement for the cloud mask is found over polar regions, where the correct cloud detection percentage increases due to a decrease in missed clouds and/or false detection. For cloud thermodynamic phase, the ice cloud fraction increases over nonpolar regions and the combined liquid water and ice cloud discrimination improves in comparison with CALIPSO. The retrieved cloud top height for semitransparent ice clouds increases over non-polar regions and tends to be closer to the true CALIPSO/CALIOP cloud top height. Moreover, the uncertainty of cloud top height retrievals decreases globally for these clouds. Implementation in the CLouds from AVHRR-Extended (CLAVR-x) processing is under study.

Figure 2. Bias distribution of cloud top height between S-NPP VIIRS and CALIPSO/CALIOP for emissivity range a) 0 to 0.4; b) 0.4 to 0.8; c) 0.8 to 1.0; and d) 0 to 1.0. Solid and dashed lines indicate data with/without fusion channels (Li et al., 2020).

Improvement in tropospheric moisture retrievals from VIIRS through the use of infrared absorption bands constructed from VIIRS and CrIS data fusion

Using the VIIRS high spatial resolution infrared (IR) absorption band radiances (centered at 4.5, 6.7, 7.3, 9.7, 13.3, 13.6, 13.9, and 14.2 µm) generated with the VIIRS+CrIS data fusion method, atmospheric moisture products (e.g., total precipitable water and upper tropospheric humidity) have been generated and evaluated (Borbas et al., 2021). Total precipitable water (TPW) and upper tropospheric humidity (UTH) retrieved from hyperspectral sounder CrIS measurements were provided at the associated VIIRS sensor’s high spatial resolution (750m) and compared to collocated operational Aqua MODIS and Suomi-NPP VIIRS moisture products. Results suggest that the use of VIIRS IR absorption band radiances can provide continuity with Aqua MODIS moisture products. Global comparison for one day is shown below. In a one-month (Jan 2017) study, global mean TPW derived from the VIIRS+CrIS fusion radiances is 0.2 mm higher with a scatter of 1.4 mm when compared to the global MYD08 TPW; without the fusion radiances (VIIRS-only product) the mean is 1.1 mm too high with scatter of 2.7 mm where most of the over-estimation occurs in the tropics. Similar TPW results are also found for one month in each season (Jan, Apr, Jul, Oct) of 2017. VIIRS+CrIS UTH, now possible with the addition of fusion radiances, is found to be within 10% of the MYD08 UTH in mean and scatter for the same four months. Replacing the current VIIRS operational water vapor products with these fusion VIIRS water vapor products is planned.

Figure 3. Geographical distribution of TPW [mm] results derived from the VIIRS+CrIS fusion (top left) and MODIS MYD08_D3 Collect 6.1 (top right) products for 9 April 2018, along with the corresponding difference field (bottom) with mean, standard deviation (std) and root mean square (rms) differences included in the subtitle (Borbas et al., 2021).

Imager and sounder data fusion to generate sounder retrieval products at an improved spatial and temporal resolution

Fusion of high spatial resolution imager (e.g., VIIRS) and a high spectral resolution sounder [e.g., Cross-track Infrared Sounder (CrIS)] data offers the opportunity to construct not only new spectral band radiances (radiance fusion) but also sounder retrieval products (product fusion) at high spatial resolution. Temperature and humidity profiles can also be provided at a high temporal resolution when geostationary imager [Advanced Baseline Imager (ABI)] data are used in combination with polar orbiting sounder (CrIS) data in a fusion approach. Promising results from VIIRS/CrIS and ABI/CrIS fusion have been demonstrated in Weisz and Menzel (2019) and Anheuser et al. (2020).

Fig. 4 ABI band 8 (6.3 µm) radiance (mW m-2 sr -1 cm) is shown in (a), ABI/CrIS 8-band product fusion water vapor (g/kg) at 500 hPa and 850 hPa is shown in (b) and (d), respectively, whereas the 13-km RAP analysis water vapor at 500 hPa is shown in (c). The high (low) moisture feature at 17 UTC inside the red (black) box in (b) and (d) corresponds to the existing cloud development in the red box (new convection in the black box) outlined at 20 UTC in (a) (Weisz and Menzel, 2019).

Approach to enhance trace gas determinations through multi-satellite data fusion

The imaging instruments on the polar-orbiting S-NPP and NOAA-20 satellite platforms [e.g., VIIRS] and on geostationary GOES and Himawari platforms [e.g., Advanced Baseline Imager (ABI) and Advanced Himawari Imager (AHI)] have high horizontal spatial resolution but coarse vertical information about tropospheric gases and temperatures. Fusing high spatial resolution imager (e.g., VIIRS, ABI, and AHI) and a high information content sounder or trace gas monitor [e.g.,CrIS and TROPOspheric Monitoring Instrument (TROPOMI)] data offers the opportunity to construct retrieval products (e.g., trace gas concentrations of CO, SO2, and NH3) via product fusion at high spatial resolution. Furthermore, these products can also be provided at high temporal resolution when geostationary imager (ABI and AHI) data are used in the product fusion. Promising results from VIIRS/CrIS, VIIRS/TROPOMI, and AHI/TROPOMI fusion are shown in Weisz and Menzel (2020). The potential for nowcasting applications is under study.

Fig. 5 (a) TROPOMI CO [DU] over NE China on 23 March 2020 at 12:43 China Standard Time (CST) or 0443 UTC; (b)-(f) AHI/TROPOMI fusion results at 7, 10, 13, 16 and 19 CST on 23 March 2020. Selected cities (Beijing, Baicheng, Handan, Xingtai) are marked and labeled in panel (a) (Weisz and Menzel, 2020).

Publications

Anheuser, J., E. Weisz, and W. P. Menzel, 2020: Low earth orbit sounder retrieval products at geostationary Earth orbit spatial and temporal scales, J. Appl. Remote Sens. 14(4), 048502 (2020), doi: 10.1117/1.JRS.14.048502.

Borbas, E. E., E. Weisz, C. Moeller, W. P. Menzel, and B. A. Baum, 2021: Improvement in tropospheric moisture retrievals from VIIRS through the use of infrared absorption bands constructed from VIIRS and CrIS data fusion, Atmospheric Measurement Techniques. 14, 1191–1203, doi.org/10.5194/amt-14-1191-2021, 2021.

Cross, J., I. Gladkova, W. P. Menzel, A.Heidinger, and M. D. Grossberg, 2013: Statistical estimation of a 13.3 µm Visible Infrared Imaging Radiometer Suite channel using multisensor data fusion. J. Appl. Remote Sens. 7 (1), 073473, doi: 10.1117/1.JRS.7.073473

Li, Yue, B. A. Baum, A. K. Heidinger, W. P. Menzel, E. Weisz, 2020: Improvement in cloud retrievals from VIIRS through the use of infrared absorption channels constructed from VIIRS-CrIS data fusion, Atmospheric Measurement Techniques. 13, 4035–4049, doi.org/10.5194/amt-13-4035-2020, 2020.

Weisz, E., B. A. Baum, and W. P. Menzel, 2017: Fusion of satellite-based imager and sounder data to construct supplementary high spatial resolution narrowband IR radiances. J. Appl. Remote Sens. 11(3), 036022, doi: 10.1117/1.JRS.11.036022.

Weisz, E., and W. P. Menzel, 2019: Imager and sounder data fusion to generate sounder retrieval products at an improved spatial and temporal resolution, J. Appl. Remote Sens. 13(3), 034506, doi: 10.1117/1.JRS.13.034506.

Weisz, E., and W. P. Menzel, 2020: An Approach to Enhance Trace Gas Determinations through Multi-Satellite Data Fusion, J. Appl. Remote Sens. 14(4), 044519 (2020), doi: 10.1117/1.JRS.14.044519.