Quantifying Observational Variability and Inverse Model Biases of Planetary Boundary Layer Depths and Their Impact on the Calculation of Carbon Fluxes in CarbonTracker

The goals of this project are 1) to evaluate the performance of atmospheric transport models that drive global carbon inverse models in their simulation of Planetary Boundary Layer (PBL) depths, 2) to improve the representation of PBL depths in these models, and 3) to assess the impact of an improved representation on the calculation of the North American carbon budget. To accomplish these goals, efforts will focus on the detailed evaluation and modeling of spatial and temporal variability of PBL depths. Observations combined with numerical models, including the community model WRF and the carbon data assimilation system CarbonTracker will be used. Observations will come from surface-based, airborne, and spaceborne measurements, including those from radar wind profilers, ceilometers, lidars, radiosondes, aircraft profiles, and spaceborne remote sensors. Existing methodologies will be used to determine the PBL depths from these measurements. Several case studies that coincide with the largest amount of available data and data-rich field studies will serve as a focus. This project will deliver a thorough data set of PBL depths with which current and future transport models can be evaluated, an improved simulation of CO2 transport, and a framework to investigate the effect of the improved representation of vertical transport and mixing in carbon exchange estimates. It will thereby contribute to ongoing efforts to monitor the global and North American carbon cycle.