Before retrieving greenhouse gas concentrations from spectra of the Thermal and Near Infrared Sensor for Carbon Observation (TANSO)-Fourier Transform Spectrometer (FTS) on board the Greenhouse Gases Observing Satellite (GOSAT), cloud contamination in the fields of view (FOVs) of TANSO-FTS, which could degrade the data quality of the retrieved gas concentrations, is assessed using the TANSO-Cloud and Aerosol Imager (CAI) and the short-wave infrared (SWIR) band of TANSO-FTS in the daytime and the thermal infrared (TIR) band of TANSO-FTS in the nighttime. This study has validated the daytime and nighttime cloud assessments in the FOVs of TANSO-FTS over the ocean in GOSAT data processing by comparing them with cloud assessments based on the reflectance and brightness temperature data of coincident measurements made by the Advanced Himawari Imager (AHI) on board the Himawari-8 satellite. About 90 % of the daytime cloud judgements made by TANSO-CAI and the TANSO-FTS SWIR band and by Himawari-8 in this study agreed with each other. In contrast, agreement between the TANSO-FTS TIR band and Himawari-8 in their nighttime cloud judgements was ～10 % lower than the daytime level of agreement. Due to the larger FOVs of TANSO-FTS (10.5 km), the TANSO-FTS TIR band could not detect subpixel-sized clouds that partly existed in the FOVs of TANSO-FTS. Although the cloud judgements made by Himawari-8 here were “clear conservative,” they suggest that some of the TANSO-FTS observations judged to be “clear” by the GOSAT cloud assessments were contaminated by clouds, especially in the nighttime. We should therefore evaluate the data quality of the GOSAT/TANSO-FTS GHG products from the view point of the accuracy of cloud assessments in the FOVs of TANSO-FTS.

The data obtained by observations of lightning from geostationary orbit are summarized herein based on NOAA Technical Report NESDIS 153, i.e., Geostationary Lightning Mapper (GLM) Value Assessment (VA), Lead author: Dr. Scott Rudlosky, which was published 4 years after the launch of the Geostationary Operational Environmental Satellites-R Series (GOES-R). The GLM onboard the GOES-R is the first operational lightning mapper, and the operational use of the GLM is about to begin after its initial evaluations made during that 4-year period. The benefits of observing lightning from geostationary orbit are (1) improving short-term forecasts through data assimilation, (2) improving the intensity forecasts of tropical cyclones, (3) improving the warnings for severe thunderstorms and tornados, (4) improving precipitation estimations, (5) filling the radar data gap, (6) improving lightning safety, (7) applications for climate science, (8) mitigating aviation hazards, and (9) improving the safety and effectiveness of wildfire responses. Recent studies have also demonstrated that intra-cloud lightning and cloud-to-ground lightning can be identified from satellite observations.

In this study, remote sensing, geographic information system, and analytical hierarchy process (AHP) techniques were combined to delineate the groundwater potential zones (GWPZs) of the Ugii Lake Basin based on six hydrological and hydrogeological factors, a digital elevation model, drainage density, slope, land use/land cover, soil texture, and rainfall. A multi-criteria decision analysis was performed in ArcGIS 10.1, using the assigned weights on each thematic layer by the AHP technique. The GWPZs of the Ugii Lake Basin were delineated and classified into four classes: very high, high, moderate, and poor. Results show that 4.92 km² of the area (1.88 %) indicate very high groundwater potential, followed by 107.40 km² (41.13 %) classified as a high zone, 118.19 km² (45.26 %) as a moderate zone, and 30.62 km² (11.73 %) as a poor zone. Very high to high GWPZs of the basin were delineated surrounding the Ugii Lake due to their geographic location and the tectonic fault that crosses the lake from west to east. The basin’s delineated GWPZs were validated using corresponding well data. According to their classes, 8 wells (42.11 %) were overlaid in the moderate zone, while 11 wells (57.89 %) were overlaid in the high zone. As the weighted overlay analysis indicated satisfactory results, decision-makers can use the GWPZ map of the Ugii Lake Basin for sustainable water management in this remote area.