Improved Hyperspectral IR/Microwave Sounding of Boundary Layer Inversions: Final Report

Abstract

Improved understanding of thermodynamics within the Planetary Boundary Layer (PBL), including its structure and PBL height (PBLH) over land and water as a function of time of day, is of great importance to NASA, as recommended by the National Academy of Sciences in the 2017 Decadal Survey for Earth Science and Applications from Space ("ESAS 2017") [3, 4] and subsequently by the NASA PBL Incubation Study Team Report (STR; [5]). During the ESAS 2017 process, improved PBL monitoring from space was identified as a high priority across multiple interdisciplinary panels and science and application questions, leading to the current NASA PBL Decadal Survey Incubation (DSI) program that will invest in future spaceborne PBL mission development. [2]In recent decades, spaceborne microwave and hyperspectral infrared (HIR) sounding instruments on Aqua, Suomi NPP, and JPSS have significantly improved weather forecasting [6, 7]. However, existing retrievals of lower troposphere temperature and water vapor profiles from HIR and microwave sounders have limitations in vertical resolution, and often cannot accurately represent key features such as the mixed layer thermodynamic structure and the inversion at the PBL top, the latter of which appears as a sharp gradient in or potential temperature as illustrated in Figure 1. With the mixed layer itself being tilde 1-3 km thick, previously reported AIRS T and q profile resolution (and resultant PBLH) errors on the order of tilde 1-2 km [8] are not sufficient, and, alone, fall well short of the ESAS recommendation of tilde 100-300 m vertical resolution for new PBL observing systems. Because of the existing limitations in PBL remote sensing from space, there is an urgent need to improve routine, global observations of the PBL and enable advances in scientific understanding and weather and climate prediction.

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Document Details

Document Type
Technical Report
Publication Date
Feb 02, 2024
Accession Number
AD1230208

Entities

People

  • Adam B. Milstein

Organizations

  • Massachusetts Institute of Technology

Tags

Fields of Study

  • Environmental science

Readers

  • Atmospheric Remote Sensing.
  • Mathematics or Statistics
  • Ocean-Atmosphere Mesoscale Modeling, Data Assimilation, and Flux Boundary Layers

Technology Areas

  • Space