학술논문
Bias Correction of Long-Path CO2 Observations in a Complex Urban Environment for Carbon Cycle Model Inter-Comparison and Data Assimilation.
Document Type
Article
Source
Subject
*CARBON cycle
*GAS lasers
*TRACE gases
*PARIS Terrorist Attacks, Paris, France, 2015
*DATA modeling
URBAN ecology (Sociology)
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Language
ISSN
1867-8610
Abstract
The Greenhouse gas Laser Imaging Tomography Experiment (GreenLITE™) trace gas measurement system, jointly designed and developed by Atmospheric and Environmental Research, Inc. and Spectral Sensor Solutions LLC, provides high-precision, long-path measurements of atmospheric trace gases including CO2 and CH4 over extended (0.04 km²-25 km²) areas of interest. In 2015, a prototype unit was deployed in Paris, France to demonstrate its ability to provide continuous observations of CO2 concentrations along horizontal air segments and two-dimensional (2-D) maps of time-varying CO2 concentrations over a complex urban environment. Subsequently, these data have been adapted to create a physically consistent set of horizontal segment mean concentrations for: 1) Comparisons to highly accurate in situ point measurements obtained for coincident times within the Greater Paris area, 2) Inter-comparisons with results from high-spatial and temporal regional carbon cycle model data, and 3) Potential assimilation of these data to constrain and inform regional carbon cycle modeling frameworks. To achieve these ends, the GreenLITE™ data are calibrated against precise in situ point measurements to reconcile constant systematic as well as slowly varying temporal differences that exist between in situ and GreenLITE™ measurements to provide unbiased comparisons, and the potential for long-term co-assimilation of both measurements into urban-scale emission models. While both the constant systematic biases and the slowly varying differences may have different impacts on the measurement accuracy and/or precisions, they are in part due to a number of potential common terms that include limitation in the instrument design, uncertainties in spectroscopy and imprecise knowledge of the atmospheric state. This work provides a brief overview of the system design and the current gas concentration retrieval and 2-D reconstruction approaches, a description of the bias correction approach, the results as applied to data collected in Paris, France, and an analysis of the inter-comparison between collocated in situ measurements and GreenLITE™ observations. [ABSTRACT FROM AUTHOR]