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Browsing by Author "O'Dell, Christopher, committee member"

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    Time-filtered inverse modeling of land-atmosphere carbon exchange
    (Colorado State University. Libraries, 2015) Geyer, Nicholas M., author; Denning, Scott, advisor; Hoeting, Jennifer, committee member; O'Dell, Christopher, committee member
    The sources and sinks of biospheric carbon dioxide represent one of the least understood and most critical processes in carbon science. Since the 1990's, carbon dioxide inversion models have estimated the magnitude, location, and uncertainty of carbon sources and sinks. These inversions are underconstrained statistical problems that employ aggressive statistical regularizations in both space and time to estimate quantities like net ecosystem exchange (NEE) on weekly timescales over fine spatial scales. This study developed and tested a new regularization that leverages the available observational information toward a small number of estimates associated with the longer-lived slowly varying biospheric processes, which control time-averaged sources and sinks of carbon dioxide. This approach multiplicatively adjusts the longer lived component fluxes, gross primary production (GPP) and total respiration (RESP), using several timescale harmonics. This methodology was tested by estimating adjustments to either net or component fluxes from Simple Biosphere Model 4 (SiB4) using observational data from 8 different eddy-covariance flux towers selected from the North American Carbon Program (NACP) site synthesis dataset. The time-filtering methodology was robustly capable of accurately estimating both net and component fluxes given high observational uncertainty. Furthermore, the methodology was flexible of correctly producing estimates of all three fluxes when given a component flux as an additional observational constraint.
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    Using remotely sensed fluorescence and soil moisture to better understand the seasonal cycle of tropical grasslands
    (Colorado State University. Libraries, 2017) Smith, Dakota Carlysle, author; Denning, A. Scott, advisor; Smith, Melinda, committee member; O'Dell, Christopher, committee member; Kummerow, Christian, committee member
    Seasonal grasslands account for a large area of Earth's land cover. Annual and seasonal changes in these grasslands have profound impacts on Earth's carbon, energy, and water cycles. In tropical grasslands, growth is commonly water-limited and the landscape oscillates between highly productive and unproductive. As the monsoon begins, soils moisten providing dry grasses the water necessary to photosynthesize. However, along with the rain come clouds that obscure satellite products that are commonly used to study productivity in these areas. To navigate this issue, we used solar induced fluorescence (SIF) products from OCO-2 along with soil moisture products from the Soil Moisture Active Passive satellite (SMAP) to "see through" the clouds to monitor grassland productivity. To get a broader understanding of the vegetation dynamics, we used the Simple Biosphere Model (SiB4) to simulate the seasonal cycles of vegetation. In conjunction with SiB4, the remotely sensed SIF and soil moisture observations were utilized to paint a clearer picture of seasonal productivity in tropical grasslands. The remotely sensed data is not available for every place at one time or at every time for one place. Thus, the study was focused on a large area from 15° E to 35° W and from 8°S to 20°N in the African Sahel. Instead of studying productivity relative to time, we studied it relative to soil moisture. Through this investigation we found soil moisture thresholds for the emergence of grassland growth, near linear grassland growth, and maturity of grassland growth. We also found that SiB4 overestimates SIF by about a factor of two for nearly every value of soil moisture. On the whole, SiB4 does a surprisingly good job of predicting the response of seasonal growth in tropical grasslands to soil moisture. Future work will continue to integrate remotely sensed SIF & soil moisture with SiB4 to add to our growing knowledge of carbon, water, and energy cycling in tropical grasslands.