Wavelet analysis of airborne CO 2 measurements and related meteorological parameters over heterogeneous landscapes

Abstract

In this study, we focus on the spatial variations in CO 2 and related meteorological parameters quantified in the planetary boundary layer (PBL) from airborne measurements over Illinois, Ohio and Nebraska, USA during the INTEX-NA campaign, July 8th, 2004. The airborne measurements were conducted during morning hours (8:47 a.m) in Nebraska whereas mostly during afternoon hours (1:00 pm and 1:50 pm) in Illinois and Ohio respectively. We perform wavelet analysis using a continuous wavelet transform and wavelet coherence functions for the CO 2 data and underlying meteorological variables to interpret the airborne observations. In addition, we also used LANDSAT derived land use/cover information to relate to CO 2 variations observed in the PBL. Maximum CO 2 mixing ratios were observed over Nebraska and the lowest CO 2 mixing ratios over Illinois followed by Ohio. Spectral decomposition of the CO 2 data using scalograms revealed lower frequency signals of shorter duration over Illinois compared to Ohio and Nebraska. Further, the high frequency CO 2 data for Illinois showed good cyclicity. The high frequency data in Illinois corresponded to low CO 2 values of less than 354 ppm, and the time localization of these frequencies closely matched with corn/soybeans mixed agricultural land use suggesting significant CO 2 uptake. Results from the wavelet coherence analysis between the CO 2 time series and meteorological parameters (potential temperature, relative humidity, water vapor partial pressure, water vapor mixing ratio, wind speed and infrared surface temperature) revealed significant differences in coherences as a function of sampling time. The scale and time dependent wavelet coherence variations observed for CO 2 and meteorological data over three different states were attributed to mesoscale variability including variations in the type of vegetation, topography, land-vegetation contrast, cloud cover, and overall landscape heterogeneity.