Tropical montane cloud forests (TMCFs) depend on predictable, frequent, and prolonged immersion in cloud. Clearing upwind lowland forest alters surface energy budgets in ways that influence dry season cloud fields and thus the TMCF environment. Landsat and Geostationary Operational Environmental Satellite imagery show that deforested areas of Costa Rica's Caribbean lowlands remain relatively cloud-free when forested regions have well-developed dry season cumulus cloud fields. Further, regional atmospheric simulations show that cloud base heights are higher over pasture than over tropical forest areas under reasonable dry season conditions. These results suggest that land use in tropical lowlands has serious impacts on ecosystems in adjacent mountains.

This article summarizes the changes in landscape structure because of human land management over the last several centuries, and using observed and modeled data, documents how these changes have altered biogeophysical and biogeochemical surface fluxes on the local, mesoscale, and regional scales. Remaining research issues are presented including whether these landscape changes alter large-scale atmospheric circulation patterns far from where the land use and land cover changes occur. We conclude that existing climate assessments have not yet adequately factored in this climate forcing. For those regions that have undergone intensive human landscape change, or would undergo intensive change in the future, we conclude that the failure to factor in this forcing risks a misalignment of investment in climate mitigation and adaptation. (C) 2011 John Wiley & Sons, Ltd

Land cover changes (LCCs) play an important role in the climate system. Research over recent decades highlights the impacts of these changes on atmospheric temperature, humidity, cloud cover, circulation, and precipitation. These impacts range from the local-and regional-scale to sub-continental and global-scale. It has been found that the impacts of regional-scale LCC in one area may also be manifested in other parts of the world as a climatic teleconnection. In light of these findings, this article provides an overview and synthesis of some of the most notable types of LCC and their impacts on climate. These LCC types include agriculture, deforestation and afforestation, desertification, and urbanization. In addition, this article provides a discussion on challenges to, and future research directions in, assessing the climatic impacts of LCC.

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[1] The current study provides new insights into the coupling of land use in lowland and premontane regions (i.e., regions below 1000 m) and orographic cloud formation over the Monteverde cloud forests. Rawinsondes launched during the Land Use Cloud Interaction Experiment (LUCIE) together with those from the National Centers for Environmental Prediction (NCEP) provided profiles that were used to drive the Colorado State University Regional Atmospheric Modeling System (CSU RAMS) model, which simulated three realistic land use scenarios (pristine forests, current conditions and future deforestation). For current conditions, the model-simulated clouds were compared against those observed at hourly intervals by the Geostationary Environmental Observational Satellite-East (GOES E) satellite. The model performed best on 6 different days. The model-simulated profiles of dew point and air temperatures were compared with the observed profiles from rawinsondes for these days. There was generally very good agreement below 700 mb, the region of the atmosphere most crucial to the cloud forests. The average model simulations for the 6 days show that when the lowland and premontane regions were completely forested, the orographic cloud bank intersected the mountains at the lowest elevations, covered the largest land surface area and remained longest on the surface in the montane regions. Deforestation has decreased the cloud forest area covered with fog in the montane regions by around 5-13% and raised the orographic cloud bases by about 25-75 m in the afternoon. The model results show that further deforestation in the lowland and premontane regions would lead to around 15% decrease in the cloud forest area covered with fog and also raise the orographic cloud base heights by up to 125 m in the afternoon. The simulations show that deforestation in the lowland and premontane regions raises surface sensible heat fluxes and decreases latent heat fluxes. This warms the air temperature and results in a lower dew point temperature of air masses that blow over the lowland and premontane regions. These air masses when lifted form the orographic cloud bank at higher elevations.

[1] As is typical in the Northern Hemisphere spring, during 20 April to 21 May 2003, significant biomass burning smoke from Central America was transported to the southeastern United States (SEUS). A coupled aerosol, radiation, and meteorology model that is built upon the heritage of the Regional Atmospheric Modeling System (RAMS), having newly developed capabilities of Assimilation and Radiation Online Modeling of Aerosols (AROMA) algorithm, was used to simulate the smoke transport and quantify the smoke radiative impacts on surface energetics, boundary layer, and other atmospheric processes. This paper, the first of a two-part series, describes the model and examines the ability of RAMS-AROMA to simulate the smoke transport. Because biomass-burning fire activities have distinct diurnal variations, the FLAMBE hourly smoke emission inventory that is derived from the geostationary satellite (GOES) fire products was assimilated into the model. In the ''top-down'' analysis, ground-based observations were used to evaluate the model performance, and the comparisons with model-simulated results were used to estimate emission uncertainties. Qualitatively, a 30-day simulation of smoke spatial distribution as well as the timing and location of the smoke fronts are consistent with those identified from the PM 2.5 observation network, local air quality reports, and the measurements of aerosol optical thickness (AOT) and aerosol vertical profiles from the Southern Great Plains (SGP) Atmospheric Radiation Measurements (ARM) site in Oklahoma. Quantitatively, the model-simulated daily mean near-surface dry smoke mass correlates well with PM 2.5 mass at 34 locations in Texas and with the total carbon mass and nonsoil potassium mass (KNON) at three IMPROVE sites along the smoke pathway (with linear correlation coefficients R = 0.77, 0.74, and 0.69 at the significance level larger than 0.99, respectively). The top-down sensitivity analysis indicates that the total smoke particle emission during the study period is about 1.3 ± 0.2 Tg. The results further indicate that the simulation with a daily smoke emission inventory provides a slightly better correlation with measurements in the downwind region on daily scales but gives an unrealistic diurnal variation of AOT in the smoke source region. This study suggests that the assimilation of emission inventories from geostationary satellites is superior to that of polar orbiting satellites and has important implications for the modeling of air quality in areas influenced by fire-related pollutants from distant sources.

A B S T R A C T This paper documents the diverse role of land-use/land-cover change on precipitation. Since land conversion continues at a rapid pace, this type of human disturbance of the climate system will continue and become even more significant in the coming decades.

[1] Recent studies have shown that there has been a reduction in dry season moisture input from direct interception of cloud water and wind-blown mist at the lee edge of the Monteverde cloud forest, Costa Rica, since the mid 1970s. This reduction of moisture could be responsible for the population crashes of anurans observed in the region. It has been hypothesized that this behavior is a result of increases in cloud base height, linked to increased sea surface temperatures. In this study we present a complementary hypothesis, that deforestation upwind of the Monteverde cloud forest preserve is responsible for the observed changes in cloud base height. An automated cumulus cloud classification scheme extracts monthly spatial maps of the frequency of occurrence of cumulus cloudiness over Costa Rica from GOES 8 visible channel satellite imagery. We find that cumulus cloud formation in the morning hours over deforested regions is suppressed compared to forested areas. The degree of suppression appears to be related to the extent of deforestation. This difference in cloud formation between forested and deforested areas is a clear signal of land use change influencing the regional climate. Regional Atmospheric Modeling System numerical modeling simulations are used to explore the differences in cloud field characteristics over the lowland pasture and forest landscapes. Statistically significant differences in cloud base height and cloud thickness occur between the forest and pasture simulations. Clouds have higher base heights and are thinner over pasture landscapes than over forested ones. On the other hand, these simulations show no statistically significant differences in cloud top heights, cloud cover, mean cloud water mixing ratio, or cloud liquid water path between pasture and forest simulations. However, in the simulations there are enhanced sensible heat fluxes and reduced latent heat fluxes over pasture compared to forest. It is the drier and warmer air over pasture surfaces that results in the formation of elevated thinner clouds. This study suggests that deforestation results in warmer, drier air upwind of the Monteverde cloud forests and that this could influence the base height of orographic cloudbanks crucial to the region during the dry season.