Anthropogenic changes (e.g., deforestation and climate change) can impact both the tropical forest itself and extratropical regions (D. Energy exchanges between the land and the atmosphere are enhanced by low albedo and high evaporative cooling (Bonan, 2008 Wohl et al., 2012). In humid tropical regions, hydrological processes are also markedly categorized by uniform warm temperatures, large inter-annual and spatial variability of moisture cycle, and high annual rainfall. While tropical forests comprise only 16% of the global surface, they produce 33% of terrestrial evapotranspiration (ET, 1,000–2,200 mm per year), 70% of which comes from transpiration (Fisher et al., 2009 Kume et al., 2011 Loescher et al., 2005 Schlesinger & Jasechko, 2014 Sheil, 2018). In the terrestrial biosphere, tropical forests house 25% of the carbon stocks and account for 33% of net primary production (NPP) (Bonan, 2008). Zhang et al., 2010) and climate cycles (Beer et al., 2010 Huntingford et al., 2013), improved modeling of tropical regions is vital for the accurate prediction of future climate and for the assessment of its impact on climate change. Due to their significance for the global water cycles (Choudhury & DiGirolamo, 1998 K. Tropical forests play a key role in determining global and regional climate, and their associated land-surface processes are critical to the Earth system. Further observations and model developments, aimed at reflecting surface heterogeneity, will be necessary to adequately capture the complexity and the features of the tropical montane rainforest. More importantly, unlike single layer models, the results that CLM-ml produces can be compared to variables measured within the canopy to provide far more detailed diagnostic information. Sub-canopy considerations, such as canopy shapes and turbulent transfer parameters, also played a significant role in model performance. In the single-layer models (CLM4.5 and CLM5), excessive day-to-night differences in leaf temperature and leaf wetness were originally noted, but CLM-ml significantly improved these issues, decreasing the amplitudes of diurnal cycles by 67% and 47%. Test results indicate that the modified multi-layer CLM model can successfully replicate the shape of various micrometeorological profiles (humidity, CO 2, temperature, and wind speed) under the canopy. Modifications are made in order to capture a wider array of vertical leaf area distributions, predict CO 2 profiles, account for soil respiration, and adjust wind forcings for difficult topographic settings. This study updates the multi-layered Community Land Model (CLM-ml) for hillslopes and compares predictions from against observations collected in tropical montane rainforest, Costa Rica.
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