In the land surface models predicting vegetation growth and decay, representation of the seasonality of land surface energy and mass fluxes largely depends on how to describe the vegetation dynamics. In this study, we developed a new parameterization scheme to characterize allocation of the assimilated carbon to plant parts, including leaves and fine roots. The amount of carbon allocation in this scheme depends on the climatological net primary production (NPP) of the plants. The newly developed scheme is implemented in the augmented Noah land surface model with multiple parameterization options (Noah‐MP) along with other biophysical processes related to variations in photosynthetic capacity. The scheme and the augmented biophysical processes are evaluated against tower measurements of vegetation from four forest sites in various regions—two for the deciduous broadleaf and two for the needleleaf evergreen forest. Results from the augmented Noah‐MP showed good agreement with the observations and demonstrated improvements in representing the seasonality of leaf area index (LAI), gross primary production (GPP), ecosystem respiration (ER), and latent heat flux. In particular, significant improvements are found in simulating amplitudes and phase shift timing in the LAI seasonal cycle, and the amount of GPP and ER in the growing season. Furthermore, the augmented Noah‐MP performed reasonably well in simulating the spatial distributions of LAI, GPP, and NPP in East Asia, consistent with the satellite observations.

Nighttime correction of CO 2 flux is one of the most important and challenging tasks in eddy covariance measurements over a complex mountainous terrain. In this study, we have scrutinized the quality and the credibility of the CO 2 flux datasets which were produced by employing three different methods of nighttime correction, i.e., (1) friction velocity (u * ) correction, (2) light response curve (LRC) correction, and (3) advection-based van Gorsel (VG) correction. The whole year datasets used in our analysis were collected at the two KoFlux tower sites (i.e., GDK deciduous forest site at the upper hill and GCK coniferous forest site at the lower hill) located in the valley of Gwangneung National Arboretum in central Korea. The resultant magnitudes and patterns of ecosystem respiration (R E ), gross primary productivity (GPP), and net ecosystem exchange (NEE) of CO 2 showed marked differences among the datasets produced with three different correction methods, which were also site-specific. The examination from micrometeorological and ecological perspectives suggests that the major cause of some inconsistency seems to be associated with the advection of CO 2 along the sloping terrain and the inappropriate selection of the correction data that might have been

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Abstract. The continuous measurement of H 2 O fluxes using the eddy covariance (EC) technique is still challenging for forests because of large amounts of wet canopy evaporation (E WC ), which occur during and following rain events when the EC systems rarely work correctly. We propose a new gap-filling and partitioning technique for the H 2 O fluxes: a model-statistics hybrid (MSH) method. It enables the recovery of the missing E WC in the traditional gap-filling method and the partitioning of the evapotranspiration (ET) into transpiration and (wet canopy) evaporation. We tested and validated the new method using the data sets from two flux towers, which are located at forests in hilly and complex terrains. The MSH reasonably recovered the missing E WC of 16-41 mm yr −1 and separated it from the ET (14-23 % of the annual ET). Additionally, we illustrated certain advantages of the proposed technique which enable us to understand better how ET responds to environmental changes and how the water cycle is connected to the carbon cycle in a forest ecosystem.

In this study, attention has been focused on the climatology of some variables linked to the turbulent exchanges of heat and water vapor in the surface layer during a summer monsoon in Korea. In particular, the turbulent fluxes of sensible and latent heat, the hydrologic budget, and the soil temperatures and moistures have been analyzed. At large scale, because the measurements of those data are not only fragmentary and exiguously available but also infeasible for the execution of climatologic analyses, the outputs of a land surface scheme have been used as surrogate of observations to analyze surface layer processes [this idea is based on the methodology Climatology of Parameters at the Surface (CLIPS)] in the Korean monsoonal climate. Analyses have been made for the summer of 2005. As a land surface scheme, the land surface process model (LSPM) developed at the University of Torino, Italy, has been employed, along with the data collected from 635 Korean meteorological stations. The LSPM predictions showed good agreement with selected observations of soil temperature. Major results show that, during the rainfall season, soil moisture in the first tenths of centimeters frequently exceeds the field capacity, whereas most of the rainfall is ''lost'' as surface runoff. Evapotranspiration is the dominant component of the energy budget, sometimes even exceeding net radiation, especially during the short periods between the precipitation events; in these periods, daily mean soil temperatures are about 288C or even more. The Gyeonggi-do region, the metropolitan area surrounding Seoul, shows some particularities when compared with the neighboring regions: solar radiation and precipitations are lower, causing high values of sensible heat flux and soil temperatures, and lower values of latent heat flux and soil moistures.