Utilizing PBL Height Data From Multiple Observing Systems in the GEOS System. Part II: Assessment of PBL Height Data
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Yang, E. G., Y. Zhu, N. P. Arnold, et al. “Utilizing PBL Height Data From Multiple Observing Systems in the GEOS System. Part II: Assessment of PBL Height Data.” Journal of Geophysical Research: Atmospheres 131, no. 3 (2026): e2025JD044701. https://doi.org/10.1029/2025JD044701.
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This work was written as part of one of the author's official duties as an Employee of the United States Government and is therefore a work of the United States Government. In accordance with 17 U.S.C. 105, no copyright protection is available for such works under U.S. Law.
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Abstract
This sequel study continues to develop a strategic framework for the global Planetary Boundary Layer Height (PBLH) analysis and monitoring using the National Aeronautics and Space Administration (NASA) Goddard Earth Observing System (GEOS) data assimilation (DA) system. The framework supports the assessment of PBLH from multiple observing systems, including radiosonde, Global Navigation Satellite System-Radio Occultation (GNSS-RO), spaceborne lidars: Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) and Cloud-Aerosol Transport System (CATS), ground-based lidar: NASA Micro-Pulse Lidar Network (MPLNET), and ground-based radar: networks of radar wind profilers (GRWP), using either consistent or inconsistent PBLH definitions from the GEOS model. A comprehensive evaluation over a 27-day period (23 August –18 September 2015) is performed to quantify the PBLH Observation minus Forecast bias and Root Mean Square Deviation across data types. Although radiosonde, GNSS-RO, and GRWP PBLH are assessed using consistent model definitions, lidar-based PBLH is compared using inconsistent ones due to current model limitations. The results underscore the importance of using physically and instrumentally consistent model PBLH with corresponding PBLH observations. They further demonstrate that robust quality control and thinning procedures tailored to each observation type are critical, particularly when model definition and PBLH observations are inconsistent. The results also highlight notable discrepancies among two space-based lidar PBLH data sets, especially over the ocean, which the implementation of corresponding lidar-based model PBLH and advanced PBLH retrieval algorithms are expected to reduce. The developed framework enables a robust evaluation of current and future PBLH data sets and serves as a foundation for an effective assimilation strategy.
