Session 19 Calibration/Validation for Environmental Remote Sensing, Numerical Weather Prediction, and Climate Change Detection


Description:

Calibration/Validation and Verification are essential parts of data quality assurance and is critically important for operational radiance assimilation in numerical weather prediction (NWP), climate change detection, generation of all environmental data records, and retrieval continuity across multiple overlapping sensor records, including atmospheric soundings, aerosols, fire, trace gas, cloud, sea surface temperature, ocean color, land, vegetation, and cryosphere. For example, understanding the error characteristics of satellite observations and reconciling the biases are important for data assimilation in NWP models; interpreting the small changes in the time series of temperature, trace gas, aerosols, ocean color, and other products depends on the stability of the underlining reprocessed fundamental data records; analysis of the trend of global climate change highly relies on the assumption that the data used are extremely stable and accurate. As more small satellites are launched into space with new technologies in passive and active sensors providing an unprecedented, large volume of data and covering almost the entire electromagnetic spectrum, data consistency, latency, usability, and sustainability may become challenges for operational forecasters, who need to become prepared to expand the algorithms and skills to take full advantages of the new observations. This session will highlight ongoing calibration and validation research that will aid the operational use of the data to explore opportunities and meet challenges of the evolving multitude of Earth and atmospheric observations from satellites, in-situ, and other platforms in the coming years to benefit the society.

Conveners: Changyong Cao, NOAA/NESDIS/STAR, David Robert Doelling,

          NASA LaRC, and Stephen A. Mango, NOAA/NESDIS/OSAAP Affiliate and ISS, Inc.


Papers:
Hyperspectral Remote Sensing: Ground-based Calibration/Validation for Air Quality and Atmospheric Composition Satellite Missions
Brianna Hauke, Northland College, Ashland, WI; NOAA/Center for Satellite Applications and Research, College Park, MD; and C. Cao, L. Wolf, X. Shao, P. Dulaca, S. Uprety, F. Zhang, and Y. Bai

Exploration of a Statistical Approach for the Calibration of the NOAA CrIS Sensors Using Machine Learning
Jonathan David Starfeldt, University of Wisconsin-Madison, Madison, WI; STAR, College Park, MD

CLARREO Pathfinder (CPF) Mission Overview and its Intercalibration Capabilities
Rajendra Bhatt, NASA, Hampton, VA; and Y. L. Shea, W. Wu, Q. Yang, D. Goldin, M. Little, X. Liu, and N. M. Smith

Evaluating GOES ABI Band-to-Band Co-registration Accuracy at Sub-Satellite Point
Fangfang Yu, Univ. of Maryland, College Park, MD; and X. Wu, Dr., V. Kondratovich, and J. Zhou

Exploring GOES-R ABI Lunar Image Registration with AI
Linfred Kingston, University of Maryland, College Park, MD; and F. Yu and X. Wu, Dr.

Evaluation of VIIRS thermal emissive bands long-term stability and inter-sensor consistency with radiative transfer modeling
Feng Zhang, University of Maryland, College Park, MD; and X. Shao, Y. Chen, T. C. Liu, X. Jing, and W. Wang

First Year Performance of GOES-18 ABI Calibration
Xiangqian Wu, Dr., NOAA/NESDIS, College Park, MD; and F. Yu, V. Kondratovich, D. Lindsey, and E. M. Kline

Consistent Pixel Resolution Characterization of Deep Convective Clouds for Calibration
Conor O. Haney, Analytical Mechanics Associates, Hampton, VA; and D. R. Doelling, R. Bhatt, P. Khakurel, B. R. Scarino, and A. Gopalan

Universal Instrument Simulation Wrapper (UISW): A Lightweight and Flexible Observation Simulation Library in Support of Cal/Val, Data Assimilation and Digital Twin Projects
Cheng Da, University of Maryland, College Park, College Park, MD; and A. Farguell, S. Mote, E. Kalnay, M. Halem, J. Mandel, A. K. Kochanski, S. Chiao, B. Demoz, Z. Yang, and M. Weldegaber

Submission Deadline: Thursday, 31 August 2023