Intelligent pointing increases the fraction of cloud-free CO2 and CH4 observations from space - Nassar, Ray; MacDonald, Cameron G.; Kuwahara, Bruce; Fogal, Alexander; Issa, Joshua; Girmenia, Anthony; Khan, Safwan; Sioris, Chris E. (Frontiers in Remote Sensing, 2023)
For most CO2 and CH4 satellites, only a small percentage (~10%) of observations yield successful retrievals, with the remaining ~90% rejected, primarily due to the effects of clouds. Discarding this large fraction of data is an inefficient strategy worth reconsidering due to the costs involved in developing, launching and operating the satellites to make these observations. However, if real-time cloud data are available together with pointing capability, cloud data can guide the instrument pointing in an "intelligent pointing" strategy for cloud avoidance. In this work, multiple intelligent pointing simulations were conducted, demonstrating the significant advantages of this approach for satellites in a highly elliptical orbit (HEO), from which nearly the whole Earth disk can be observed. Multiple factors are shown to contribute to intelligent pointing efficiency such as the size and shape (or aspect ratio) of the field-of-view (FOV). For the current baseline orbit and Imaging Fourier Transform Spectrometer (IFTS) observing characteristics for the proposed Arctic Observing Mission (AOM), the monthly fraction of cloud-free observations is roughly a factor of 2 (ranging from ~1.5-2.5) more than obtained with standard pointing (in which cloud information is not used). A similar efficiency is expected in a geostationary orbit (GEO) with an IFTS, however, for a dispersive instrument in HEO or GEO, the gain is more modest. This result is primarily attributed to the ~1:1 aspect ratio of the IFTS FOV, since it is more efficient for cloud avoidance and scanning irregularlyshaped land masses than the long and narrow slit projection of a typical dispersive spectrometer. These results have implications for the design of future CO2 or CH4 monitoring satellites and constellation architectures, as well as other fields of satellite earth observation in which clouds significantly impact observations.