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Evolution of energy, water, and carbon cycles due to land use change at Calhoun critical zone

This study investigates the evolution of energy, water, and carbon cycles due to land-use change at Calhoun critical zone (CCZ). Land-use change such as deforestation and reforestation alters energy, water, and carbon cycles by changing the land surface energy balance, evapotranspiration, soil moisture storage, soil porosity, and carbon storage. CCZ is an ideal platform for investigating the proposed issue as Calhoun has experienced a huge land-use change including severe deforestation in the 18th century, intensive cultivation before the Great Depression, and tremendous reforestation in the 20th century. This study selects current CCZ’s ecosystems such as cropland, young pine forests, and mature forests as CCZ’s historic ecosystems in a chronological order, and designs thorough instrumentations to measure energy, water, and carbon fluxes among other micrometeorological variables at the selected ecosystems. Using the field observations from different ecosystems, the evolution of energy, water, and carbon cycles at CCZ is quantitatively analyzed. Half-order derivative model and maximum entropy production model are applied to estimate unmeasured variables, crosscheck estimated and measured variables, and fill the missing records, because these two independent models can estimate fluxes accurately without using gradient variables or wind speed. This study also investigates the evolution of runoff ratios at Calhoun Watersheds using historic and contemporary records of streamflow and rainfall. Results of this study should broaden our knowledge of CCZ’s evolution, and provide valuable reference to other ecosystems under land-use pressure.

 

Keywords: critical zone science; Calhoun critical zone observatory; land-use change; energy, water, and carbon cycles; micrometeorology

A non-gradient model to estimate turbulent gas fluxes over land surfaces                            

A novel non-gradient model is proposed for estimating turbulent gas fluxes from single-level time-series data of near-surface gas concentration. Based on a diffusion equation describing the one-dimensional turbulent transport process in the atmospheric boundary layer, a gas flux is expressed as a weighted average of the time-history of the corresponding gas concentration at the same level. Eddy-diffusivity in the diffusion equation is formulated as a function of sensible heat flux according to the Monin-Obukhov similarity theory. Sensible heat flux may be derived from surface net radiation and air temperature using the maximum entropy production model to facilitate the use of remote sensing data. The proposed model is parsimony in model parameters without using wind speed, surface roughness, or vegetation specific data. The model is tested for water vapor and CO2 at several sites with contrasting vegetation covers, and geographic and climatic conditions. The encouraging results demonstrate its usefulness and potential for modeling gas fluxes at diurnal and seasonal scales, and justify further tests for modeling greenhouse gas fluxes at regional and global scales using remote sensing observations.

Keywords: Surface gas fluxes; non-gradient model; half-order derivative

Friction velocity estimated from sensible heat flux over land surfaces

Based on a unique extreme solution of the well-known Monin-Obukhov similarity theory, we propose a new model for estimating friction velocity from sensible heat flux over land surfaces. The new model of friction velocity does not require surface wind speed as an input and thus avoids the circular dependence of friction velocity and surface wind speed in most atmospheric surface layer models. Sensible heat flux is parameterized using the Maximum Entropy Production model in terms of net radiation, surface temperature, and/or relative humidity, which may be obtained from remote sensing observations, ground-based observations, and modern reanalysis products. The new model is tested using field observations with contrasting vegetation covers, and geographic and climatic conditions. The modeled friction velocities agree well with the observed ones at all site at diurnal and seasonal time scales. The encouraging results demonstrate the approach’s usefulness and potential for modeling friction velocity over different land covers at local sites, and justify further applications of this approach in estimating friction velocity and surface wind speed over land surfaces at regional and global spatial scales, particularly in weather and climate models.

Keywords: Friction velocity; Monin-Obukhov similarity theory; Atmospheric surface layer

Dynamics of precipitation recycling

The precipitation recycling ratio is defined as the contribution of precipitation originated from evaporation in the region of interest to the total precipitation. Conventional bulk models of precipitation recycling have several drawbacks: (1) they are applicable only on large temporal and spatial scales; (2) they cannot resolve the dependence of precipitation recycling ratio on the length scale of the region of interest; and (3) most of them cannot provide spatial distribution of precipitation recycling ratio. With the concept of the local precipitation recycling, we describe the physical and mathematical problem of the precipitation recycling, and propose an instantaneous, non-stationary, and distributed model of precipitation recycling. Our novel model directly relates the spatial-temporal variation of the local recycling ratio to those of evaporation, specific humidity and atmospheric circulation. By selecting the region of interest as each continent using the land-sea mask data, we resolve the second drawback and suggest the local precipitation recycling on a continental scale. We further expand the region of interest to all continents. The precipitation recycling ratio on global scale can be useful to understand not only land surface-atmosphere interaction but also land surface-ocean interaction in the global hydrological cycle. National Centers for Environmental Prediction (NCEP) Reanalysis-I (R-I) data are used in the numerical analysis of precipitation recycling on continental scale during 2001-2010. For each continent independently, the spatial distributions of the local precipitation recycling ratio using the new model agree qualitatively very well with the existed studies over Russia, Unite States, and India. On the global scale, the overall spatial distribution is consistent with the results from both a stationary bulk model and GCM simulations. The analysis indicates that the evaporation from land surface is essential in the global hydrological cycle.

Keywords: Precipitation Recycling, Dynamic Model, Continental Scale Analysis.

 

 

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