Browsing by Subject "Precipitation"

Light rainfall is the baseline input to the annual water budget in mountainous landscapes through the tropics and at mid-latitudes. In the Southern Appalachians, the contribution from light rainfall ranges from 50-60% during wet years to 80-90% during dry years, with convective activity and tropical cyclone input providing most of the interannual variability. The Southern Appalachians is a region characterized by rich biodiversity that is vulnerable to land use/land cover changes due to its proximity to a rapidly growing population. Persistent near surface moisture and associated microclimates observed in this region has been well documented since the colonization of the area in terms of species health, fire frequency, and overall biodiversity. The overarching objective of this research is to elucidate the microphysics of light rainfall and the dynamics of low level moisture in the inner region of the Southern Appalachians during the warm season, with a focus on orographically mediated processes. The overarching research hypothesis is that physical processes leading to and governing the life cycle of orographic fog, low level clouds, and precipitation, and their interactions, are strongly tied to landform, land cover, and the diurnal cycles of flow patterns, radiative forcing, and surface fluxes at the ridge-valley scale. The following science questions will be addressed specifically: 1) How do orographic clouds and fog affect the hydrometeorological regime from event to annual scale and as a function of terrain characteristics and land cover?; 2) What are the source areas, governing processes, and relevant time-scales of near surface moisture convergence patterns in the region?; and 3) What are the four dimensional microphysical and dynamical characteristics, including variability and controlling factors and processes, of fog and light rainfall? The research was conducted with two major components: 1) ground-based high-quality observations using multi-sensor platforms and 2) interpretive numerical modeling guided by the analysis of the in situ data collection. Findings illuminate a high level of spatial – down to the ridge scale - and temporal – from event to annual scale - heterogeneity in observations, and a significant impact on the hydrological regime as a result of seeder-feeder interactions among fog, low level clouds, and stratiform rainfall that enhance coalescence efficiency and lead to significantly higher rainfall rates at the land surface. Specifically, results show that enhancement of an event up to one order of magnitude in short-term accumulation can occur as a result of concurrent fog presence. Results also show that events are modulated strongly by terrain characteristics including elevation, slope, geometry, and land cover. These factors produce interactions between highly localized flows and gradients of temperature and moisture with larger scale circulations. Resulting observations of DSD and rainfall patterns are stratified by region and altitude and exhibit clear diurnal and seasonal cycles.

Previously, we usually analyze climate responses to all the climate drivers combined. However, the climate responses to individual climate drivers are far from well-known, as it is nearly impossible to separate the climate responses to individual climate drivers from the pure observational records. In this dissertation, I analyzed the responses of effective radiative forcing (ERF), precipitation and clouds to five individual climate drivers by using the model output from the Precipitation and Driver Response Model Inter-comparison Project (PDRMIP, consisting of five core experiments: CO2x2, CH4x3, Solar+2%, BCx10, and SO4x5). Firstly, I compared the ERF values estimated by six different methods and demonstrated that the values estimated using fixed sea-surface temperature and linear regression methods are fairly consistent for most climate drivers. For each individual driver, multi-model mean ERF values vary by 10-50% with different methods, and this difference may reach 70-100% for BC. Then, I analyzed the dynamical responses of precipitation in Mediterranean to well-mixed greenhouse gases (WMGHGs) and aerosols and found that precipitation in Mediterranean is more sensitive to BC forcing. When scaled to historical forcing level, WMGHG contributed roughly two-thirds to the Mediterranean drying during the past century and BC aerosol contributed the remaining one-third by causing a northward shift of the jet streams and storm tracks. Lastly, I explored the responses of shortwave cloud radiative effect (SWCRE) to CO2 and the two aerosol species and found that CO2 causes positive SWCRE changes over most of the Northern Hemisphere during boreal summer, and BC causes similar positive responses over North America, Europe and East China but negative SWCRE over India and tropical Africa. When normalized by global ERF, the change of SWCRE from BC forcing is roughly 3-5 times larger than that from CO2. SWCRE change is mainly due to cloud cover changes resulting from the changes in relative humidity, and to a lesser extent, changes in circulation and stability. The SWCRE response to sulfate aerosols, however, is negligible compared to that from CO2 and BC, because the radiation scattered by clouds under all-sky conditions will also be scattered by aerosols under clear-sky conditions. As SW is in effect only during daytime, positive (negative) SWCRE could amplify (dampen) daily maximum temperature (Tmax). Using a multi-linear regression model, I found that Tmax increases by 0.15 K and 0.13 K given unit increase in local SWCRE under the CO2 and BC experiments, respectively. When domain-averaged, SWCRE changes contributed to summer mean Tmax changes by 10-30% under CO2 forcing and by 30-50% under BC forcing, varying by regions, which can have important implications extreme climatic events and socio-economic activities.

Topography, vegetation, nutrient dynamics, soil features and hydroclimatic forcing are inherently coupled, with feedbacks occurring over a wide range of temporal and spatial scales. Vegetation growth may be limited by soil moisture, nutrient or solar radiation availability, and in turn influences both soil moisture and nutrient balances at a point. These dynamics are further complicated in a complex terrain, through a series of spatial interactions. A number of experiments has characterized the feedbacks between soil moisture and vegetation dynamics, but a theoretical framework linking short-term leaf-level to interannual plot-scale dynamics has not been fully developed yet. Such theory is needed for optimal management of water resources in natural ecosystems and for agricultural, municipal and industrial uses. Also, it complements the current knowledge on ecosystem response to the predicted climate change.

In this dissertation, the response of vegetation dynamics to unpredictable environmental fluctuations at multiple space-time scales is explored in a modeling framework from sub-daily to interannual time scales. At the hourly time scale, a simultaneous analysis of photosynthesis, transpiration and soil moisture dynamics is carried out to explore the impact of water stress on different photosynthesis processes at the leaf level, and the overall plant activity. Daily soil moisture and vegetation dynamics are then scaled up to the growing season using a stochastic model accounting for daily to interannual hydroclimatic variability. Such stochastic framework is employed to explore the impact of rainfall patterns and different irrigation schemes on crop productivity, along with their implications in terms of sustainability and profitability. To scale up from point to landscape, a probabilistic representation of local landscape features (i.e., slope and aspect) is developed, and applied to assess the effects of topography on solar radiation. Finally, a minimalistic ecosystem model, including soil moisture, vegetation and nutrient dynamics at the year time scale, is outlined; when coupled to the proposed probabilistic topographic description, the latter model can serve to assess the relevance of spatial interactions and to single out the main biophysical controls responsible for ecohydrological variability at the landscape scale.