3 resultados para Regional climate models
em Digital Commons - Michigan Tech
Resumo:
This project addresses the potential impacts of changing climate on dry-season water storage and discharge from a small, mountain catchment in Tanzania. Villagers and water managers around the catchment have experienced worsening water scarcity and attribute it to increasing population and demand, but very little has been done to understand the physical characteristics and hydrological behavior of the spring catchment. The physical nature of the aquifer was characterized and water balance models were calibrated to discharge observations so as to be able to explore relative changes in aquifer storage resulting from climate changes. To characterize the shallow aquifer supplying water to the Jandu spring, water quality and geochemistry data were analyzed, discharge recession analysis was performed, and two water balance models were developed and tested. Jandu geochemistry suggests a shallow, meteorically-recharged aquifer system with short circulation times. Baseflow recession analysis showed that the catchment behavior could be represented by a linear storage model with an average recession constant of 0.151/month from 2004-2010. Two modified Thornthwaite-Mather Water Balance (TMWB) models were calibrated using historic rainfall and discharge data and shown to reproduce dry-season flows with Nash-Sutcliffe efficiencies between 0.86 and 0.91. The modified TMWB models were then used to examine the impacts of nineteen, perturbed climate scenarios to test the potential impacts of regional climate change on catchment storage during the dry season. Forcing the models with realistic scenarios for average monthly temperature, annual precipitation, and seasonal rainfall distribution demonstrated that even small climate changes might adversely impact aquifer storage conditions at the onset of the dry season. The scale of the change was dependent on the direction (increasing vs. decreasing) and magnitude of climate change (temperature and precipitation). This study demonstrates that small, mountain aquifer characterization is possible using simple water quality parameters, recession analysis can be integrated into modeling aquifer storage parameters, and water balance models can accurately reproduce dry-season discharges and might be useful tools to assess climate change impacts. However, uncertainty in current climate projections and lack of data for testing the predictive capabilities of the model beyond the present data set, make the forecasts of changes in discharge also uncertain. The hydrologic tools used herein offer promise for future research in understanding small, shallow, mountainous aquifers and could potentially be developed and used by water resource professionals to assess climatic influences on local hydrologic systems.
Resumo:
Northern peatlands are large reservoirs of soil organic carbon (C). Historically peatlands have served as a sink for C since decomposition is slowed primarily because of a raised water table (WT) that creates anoxic conditions. Climate models are predicting dramatic changes in temperature and precipitation patterns for the northern hemisphere that contain more than 90% of the world’s peatlands. It is uncertain whether climate change will shift northern peatlands from C sequestering systems to a major global C source within the next century because of alterations to peatland hydrology. This research investigated the effects of 80 years of hydrological manipulations on peatland C cycling in a poor fen peatland in northern Michigan. The construction of an earthen levee within the Seney National Wildlife Refuge in the 1930’s resulted in areas of raised and lowered WT position relative to an intermediate WT site that was unaltered by the levee. We established sites across the gradient of long-term WT manipulations to examine how decadal changes in WT position alter peatland C cycling. We quantified vegetation dynamics, peat substrate quality, and pore water chemistry in relation to trace gas C cycling in these manipulated areas as well as the intermediate site. Vegetation in both the raised and lowered WT treatments has different community structure, biomass, and productivity dynamics compared to the intermediate site. Peat substrate quality exhibited differences in chemical composition and lability across the WT treatments. Pore water dissolved organic carbon (DOC) concentrations increased with impoundment and WT drawdown. The raised WT treatment DOC has a low aromaticity and is a highly labile C source, whereas WT drawdown has increased DOC aromaticity. This study has demonstrated a subtle change of the long-term WT position in a northern peatland will induce a significant influence on ecosystem C cycling with implications for the fate of peatland C stocks.
Resumo:
Satellite measurement validations, climate models, atmospheric radiative transfer models and cloud models, all depend on accurate measurements of cloud particle size distributions, number densities, spatial distributions, and other parameters relevant to cloud microphysical processes. And many airborne instruments designed to measure size distributions and concentrations of cloud particles have large uncertainties in measuring number densities and size distributions of small ice crystals. HOLODEC (Holographic Detector for Clouds) is a new instrument that does not have many of these uncertainties and makes possible measurements that other probes have never made. The advantages of HOLODEC are inherent to the holographic method. In this dissertation, I describe HOLODEC, its in-situ measurements of cloud particles, and the results of its test flights. I present a hologram reconstruction algorithm that has a sample spacing that does not vary with reconstruction distance. This reconstruction algorithm accurately reconstructs the field to all distances inside a typical holographic measurement volume as proven by comparison with analytical solutions to the Huygens-Fresnel diffraction integral. It is fast to compute, and has diffraction limited resolution. Further, described herein is an algorithm that can find the position along the optical axis of small particles as well as large complex-shaped particles. I explain an implementation of these algorithms that is an efficient, robust, automated program that allows us to process holograms on a computer cluster in a reasonable time. I show size distributions and number densities of cloud particles, and show that they are within the uncertainty of independent measurements made with another measurement method. The feasibility of another cloud particle instrument that has advantages over new standard instruments is proven. These advantages include a unique ability to detect shattered particles using three-dimensional positions, and a sample volume size that does not vary with particle size or airspeed. It also is able to yield two-dimensional particle profiles using the same measurements.