Land surface processes play an important role when modeling weather and climate, and understanding and representing such processes in South America is a particular challenge because of the large variations in regional climate and surface features such as vegetation and soil. Numerical models have been used to explore the climate and weather of continental South America, but without appropriate initiation of land surface conditions model simulations can rapidly diverge from reality. This initiation problem is exacerbated by the fact that conventional surface observations over South America are scarce and biased towards the urban centers and coastal areas. This dissertation explores issues related to the apt representation of land surface processes and their impacts in numerical simulations with a regional atmospheric model (specifically the Eta model) over South America. The impacts of vegetation heterogeneity in regional weather forecast were first investigated. A South American Land Data Assimilation System (SALDAS) was then created analogous to that currently used in North America to estimate soil moisture fields for initializing regional atmospheric models. The land surface model (LSM) used in this SALDAS is the Simplified Simple Biosphere (SSiB). Precipitation fields are critical when calculating soil moisture and, because conventional surface observations are scarce in South America, some of the most important remote sensed precipitation products were evaluated as potential precipitation forcing for the SALDAS. Spin up states for SSiB where then compared with climatological estimates of land surface fields and significant differences found. Finally, an assessment was made of the value of SALDAS-derived soil moisture fields on Eta model forecasts. The primary result was that model performance is enhanced over the entire continent in up to 72h forecasts using SALDAS surface fields

The interaction between climate and land-surface hydrology is extremely important in relation to long term water resource planning. This is especially so in the presence of global warming and massive land use change, issues which seem likely to have a disproportionate impact on developing countries. This thesis develops tools aimed at the study and prediction of climate effects on land-surface hydrology (in particular streamflow), which require a minimum amount of site specific data. This minimum data requirement allows studies to be performed in areas that are data sparse, such as the developing world. ¶ A simple lumped dynamics-encapsulating conceptual rainfall-runoff model, which explicitly calculates the evaporative feedback to the atmosphere, was developed. It uses the linear streamflow routing module of the rainfall-runoff model IHACRES, with a new non-linear loss module based on the Catchment Moisture Deficit accounting scheme, and is referred to as CMD-IHACRES. In this model, evaporation can be calculated using a number of techniques depending on the data available, as a minimum, one to two years of precipitation, temperature and streamflow data are required. The model was tested on catchments covering a large range of hydroclimatologies and shown to estimate streamflow well. When tested against evaporation data the simplest technique was found to capture the medium to long term average well but had difficulty reproducing the short-term variations. ¶ A comparison of the performance of three limited area climate models (MM5/BATS, MM5/SHEELS and RegCM2) was conducted in order to quantify their ability to reproduce near surface variables. Components of the energy and water balance over the land surface display considerable variation among the models, with no model performing consistently better than the other two. However, several conclusions can be made. The MM5 longwave radiation scheme performed worse than the scheme implemented in RegCM2. Estimates of runoff displayed the largest variations and differed from observations by as much as 100%. The climate models exhibited greater variance than the observations for almost all the energy and water related fluxes investigated. ¶ An investigation into improving these streamflow predictions by utilizing CMD-IHACRES was conducted. Using CMD-IHACRES in an 'offline' mode greatly improved the streamflow estimates while the simplest evaporation technique reproduced the evaporative time series to an accuracy comparable to that obtained from the limited area models alone. The ability to conduct a climate change impact study using CMD-IHACRES and a stochastic weather generator is also demonstrated. These results warrant further investigation into incorporating the rainfall-runoff model CMD-IHACRES in a fully coupled 'online' approach.

In semiarid regions, where water resources are limited and precipitation dynamics are changing, understanding land surface-atmosphere interactions that regulate the coupled soil moisture-precipitation system is key for resource management and planning. We present a modeling approach to study soil moisture and albedo controls on planetary boundary layer height (PBLh). We used Santa Rita Creosote Ameriflux and Tucson Airport atmospheric sounding data to generate empirical relationships between soil moisture, albedo, and PBLh. Empirical relationships showed that similar to 50% of the variation in PBLh can be explained by soil moisture and albedo with additional knowledge gained by dividing the soil profile into two layers. Therefore, we coupled these empirical relationships with soil moisture estimated using a two-layer bucket approach to model PBLh under six precipitation scenarios. Overall we observed that decreases in precipitation tend to limit the recovery of the PBL at the end of the wet season. However, increases in winter precipitation despite decreases in summer precipitation may provide opportunities for positive feedbacks that may further generate more winter precipitation. Our results highlight that the response of soil moisture, albedo, and the PBLh will depend not only on changes in annual precipitation, but also on the frequency and intensity of this change. We argue that because albedo and soil moisture data are readily available at multiple temporal and spatial scales, developing empirical relationships that can be used in land surface-atmosphere applications have great potential for exploring the consequences of climate change.

Uncertainty of predicted change in precipitation frequency and intensity motivates the scientific community to better understand, quantify, and model the possible outcome of dryland ecosystems. In pulse dependent ecosystems (i.e. monsoon driven) soil moisture is tightly linked to atmospheric processes. Here, I analyze three overarching questions; Q1) How does soil moisture presence or absence in a shallow or deep layer influence the surface energy budget and planetary boundary layer characteristics?, Q2) What is the role of vegetation on ecosystem albedo in the presence or absence of deep soil moisture?, Q3) Can we develop empirical relationships between soil moisture and the planetary boundary layer height to help evaluate the role of future precipitation changes in land surface atmosphere interactions?. To address these questions I use a conceptual framework based on the presence or absence of soil moisture in a shallow or deep layer. I define these layers by using root profiles and establish soil moisture thresholds for each layer using four years of observations from the Santa Rita Creosote Ameriflux site. Soil moisture drydown curves were used to establish the shallow layer threshold in the shallow layer, while NEE (Net Ecosystem Exchange of carbon dioxide) was used to define the deep soil moisture threshold. Four cases were generated using these thresholds: Case 1, dry shallow layer and dry deep layer; Case 2, wet shallow layer and dry deep layer; Case 3, wet shallow layer and wet deep layer, and Case 4 dry shallow and wet deep layer. Using this framework, I related data from the Ameriflux site SRC (Santa Rita Creosote) from 2008 to 2012 and from atmospheric soundings from the nearby Tucson Airport; conducted field campaigns during 2011 and 2012 to measure albedo from individual bare and canopy patches that were then evaluated in a grid to estimate the influence of deep moisture on albedo via vegetation cover change; and evaluated the potential of using a two-layer bucket model and empirical relationships to evaluate the link between deep soil moisture and the planetary boundary layer height under changing precipitation regime. My results indicate that (1) the presence or absence of water in two layers plays a role in surface energy dynamics, (2) soil moisture presence in the deep layer is linked with decreased ecosystem albedo and planetary boundary layer height, (3) deep moisture sustains vegetation greenness and decreases albedo, and (4) empirical relationships are useful in modeling planetary boundary layer height from dryland ecosystems. Based on these results we argue that deep soil moisture plays an important role in land surface-atmosphere interactions.