Abstract
The visible band of satellite sensors is of limited use during the night due to a lack of solar reflection. This study presents an improved conditional generative adversarial networks (CGANs) model to generate virtual nighttime visible imagery using infrared (IR) multiband satellite observations and the brightness temperature difference between the two IR bands in the communication, ocean, and meteorological satellite. For the summer daytime case study with visible band imagery, our multiband CGAN model showed better statistical results [correlation coefficient (CC) = 0.952, bias = −1.752 (in a digital number (DN) unit from 0 to 255, converted from reflectance from 0 to 1), and root-mean-square-error (RMSE) = 26.851 DN] than the single-band CGAN model using a pair of visible and IR bands (CC = 0.916, bias = −4.073 DN, and RMSE = 35.349 DN). The proposed multiband CGAN model performed better than the single-band CGAN model, particularly, in convective clouds and typhoons, because of the sounding effects from the water vapor band. In addition, our multiband CGAN model provided detailed patterns for clouds and typhoons at twilight. Therefore, our results could be used for visible-based nighttime weather analysis of convective clouds and typhoons, using data from next-generation geostationary meteorological satellites.
Highlights
W EATHER satellites have been playing important roles in observing the Earth’s surface and atmosphere, from their geostationary (GEO) and low orbits, using sensors thatManuscript received February 11, 2020; revised June 5, 2020 and July 8, 2020; accepted July 22, 2020
This work frame is very similar to image-to-image translation [24], in which one representative where G is a mapping function from Z to YAI, Z is the noise dataset with the sample noise image zi, i denotes the number of samples from 1 to n in the noise dataset Z, n is the total number of noise samples, YAI is the dataset with the output image yj,artificial intelligence (AI) generated from G, j denotes the number of output images from 1 to m in the output dataset YAI, and m is the total number of output images
The orange color denotes an underestimation of the conditional generative adversarial networks (CGANs)-model, and purple denotes the overestimation of the CGAN model relative to the real COMS VIS observation
Summary
W EATHER satellites have been playing important roles in observing the Earth’s surface and atmosphere, from their geostationary (GEO) and low orbits, using sensors that. Manuscript received February 11, 2020; revised June 5, 2020 and July 8, 2020; accepted July 22, 2020. Date of publication August 3, 2020; date of current version August 21, 2020. The properties of different spectral sensor bands onboard these satellites help in determining the different types of targets. Various spectral bands in weather satellites detect hazardous weather systems, such as typhoons, heavy rainfall, and yellow dust, or provide information about weather elements, such as aerosols, fog, and precipitation.
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