Tuesday, 28 June 2016
Green Mountain Ballroom (Hilton Burlington )
Handout (1.9 MB)
The difficulty of modeling atmospheric transport and mixing processes introduces significant uncertainties in the fluxes estimated with inverse carbon transport models. Of particular importance for a correct estimation of carbon fluxes is the simulation of vertical transport and mixing within the planetary boundary layer (PBL) and between the PBL and the free troposphere. An important diagnostic for vertical transport and mixing is the PBL depth, the height above the surface up to which surface fluxes of heat, moisture, momentum, and trace gases such as CO2 are transported and mixed on a diurnal time scale. Despite its importance, there is large uncertainty in how well current transport models simulate PBL depths and how biases in PBL depths translate to uncertainties in CO2 fluxes. The diurnal and seasonal cycle of CO2 concentrations near the surface and in the PBL is strongly dependent on vertical mixing within the PBL, and if we are to have confidence in inverse modeling estimates of continental CO2 fluxes, then the transport models driving the inverse models must also be capable of predicting the variation in PBL depth and structure. In this poster, we demonstrate the importance of understanding spatio-temporal variability and representativeness of planetary boundary layer depths over complex terrain for carbon cycle studies. To this end, we evaluate the performance of the atmospheric transport model TM5 that drives global carbon inverse models in its simulation of regional scale PBL depths for a case study in complex terrain that coincided with a large amount of available data. Simulations with the Weather Research and Forecasting (WRF) model are also performed to investigate the spatial PBL depth variability and to illustrate the challenges of evaluating simulated PBL depths with local scale observations.
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