Two Decades of Temperature and Specific Humidity Variance Scaling With the Atmospheric Infrared Sounder

A two-decade climatology of height-resolved horizontal variance scaling exponents (𝛼�) for temperature (T) and specific humidity (q) is described using Aqua Atmospheric Infrared Sounder (AIRS) sounding profiles. The AIRS Team Version 6 (V6), Version 7 (V7), and Community Long-term Infrared Microwave Combined Atmospheric Product System (CLIMCAPS) retrieval algorithms are compared to European Centre for Medium-Range Weather Forecasts Reanalysis v5 (ERA5) and Modern-Era Retrospective analysis for Research and Applications, Version 2 (MERRA-2) reanalyses. Large-scale T exponents derived between 600 and 1,200 km (𝛼�L) show close agreement between V6, V7, and CLIMCAPS algorithms. However, small-scale q exponents derived between 150 and 400 km (𝛼�S) are in poor agreement, including an unrealistically steep 𝛼�S in the planetary boundary layer (PBL) in the V7 and CLIMCAPS algorithms that is caused by a combination of algorithm damping and overconstraint by the first guess fields. ERA5 and MERRA-2 reanalyses have large values of 𝛼�L and 𝛼�S for both T and q that indicate reduced small-scale variability in the reanalysis fields. Differences in 𝛼�S between free-running MERRA-2 AMIP and MERRA-2 are negligible, implying that suppressed small-scale variability in reanalyses is imposed by the background model and not caused by the data assimilation process. AIRS has positively skewed T distributions in the tropical-free troposphere that is consistent with positively buoyant air parcels in convection, and negative skewness in the PBL that is related to the existence of cold pools, behavior that is mostly absent in ERA5 and MERRA-2. AIRS provides a global view of scale-dependent variance and skewness that is useful for subgrid parameterization development and validation of weather and climate prediction models. Large volumes of satellite remote sensing and reanalysis data require averages in time and space to investigate weather and climate phenomena. In this work, we preserve instantaneous snapshots of weather variability for temperature and moisture at small spatial resolutions over the two decades of NASA's Aqua Atmospheric Infrared Sounder (AIRS) mission and examine weather variability at horizontal scales from 150 to 1,200 km. The variability is determined from multiple AIRS retrieval algorithms and two reanalysis data sets (ERA5 and MERRA-2) that are widely used in the scientific community. The AIRS algorithms have different magnitudes of horizontal weather variability in the planetary boundary layer, the lowest few kilometers nearest to Earth's surface, with the oldest algorithm version having the closest agreement to aircraft data and theoretical predictions. The two reanalyses have too little temperature and moisture variability in the boundary layer compared to all AIRS algorithms. These results suggest that while satellite and reanalysis data sets have averaged climatologies that agree well with each other, the weather variability is vastly different in the boundary layer. Further progress is necessary to improve temperature and moisture observations near Earth's surface. For over 20 years, the Atmospheric Infrared Sounder (AIRS) instrument has observed height-resolved spatial variability and skewness of Earth's temperature and water vaporDifferent AIRS retrieval algorithms disagree on the magnitude of variability in the planetary boundary layer, particularly for water vaporAIRS observational benchmarks of variability and skewness offer constraints for subgrid physics in climate and weather models