Measuring large scale Earth system change: a process-oriented approach to satellite data

Earth system processes, whether physical or biogeochemical, exist at all scales in a constant state of flux. As a result, system change is not expressed as a single instance in space-time but instead as dynamic, evolving, inter-connected states. The question is how best to make use of satellite measurements to gain insight into changing states and thus improve upon a predictive understanding of global change. Infrared-microwave sounder pairs onboard the EOS and Suomi NPP (SNPP) platforms have been making measurements of a wide range of Earth system parameters for more than a decade. There is the AIRS-AMSU on EOS operational since 2002 and the CrIS-ATMS on SNPP operational since 2012. The NOAA Unique Combined Atmospheric Processing System (NUCAPS) is the operational SNPP retrieval algorithm and an implementation of the heritage EOS algorithm to continue this long-standing record. In addition to profiles of temperature and water vapor, NUCAPS also retrieves trace gas species (CO, CH4, O3) under clear-sky and party-cloudy conditions. Satellite measurements from polar-orbiting platforms such as EOS and SNPP allow two snapshots per day (am and pm) of the global atmospheric state. The challenge remains in how to stack snapshots together to form a coherent characterization of dynamic Earth system change. Given the specific strengths (space-time regularity of global measurements) and weaknesses (variable quality and an inability to measure below uniform cloud fields) of satellite soundings, we demonstrate the value in adopting process-oriented methods, such as variance scaling, that can adequately capture dynamic processes at a range of scales.