The global climate is changing due to the accumulation of greenhouse gases (GHGs) in the atmosphere, primarily due to anthropogenic activity. The dominant GHG is CO₂ which originates from combustion of fossil fuels, land use change and management. The terrestrial biosphere is a key driver of climate and biogeochemical cycles at regional and global scales. Furthermore, the response of the Earth system to future drivers of climate change will depend on feedbacks between biogeochemistry and climate. Therefore, understanding these processes requires a mechanistic approach in any model simulation framework. However ecosystem processes are complex and nonlinear and consequently models need to be validated against observations at multiple spatial scales. In this thesis the weather research and forecasting model (WRF) has been coupled to the mechanistic terrestrial ecosystem model soil-plant-atmosphere (SPA), creating WRF-SPA. The thesis is split into three main chapters: i. WRF-SPA model development and validation at multiple spatial scales, scaling from surface fluxes of CO₂ and energy to aircraft profiles and tall tower observations of atmospheric CO₂ concentrations. ii. Investigation of ecosystem contributions to observations of atmospheric CO₂ concentrations made at tall tower Angus, Dundee, Scotland using ecosystem specific CO₂ tracers at seasonal and interannual time scales. iii. An assessment of detectability of a policy relevant national scale afforestation by observations made at a tall tower. Detectability of changes in atmospheric CO₂ concentrations was assessed through a comparison of a control simulation, using current day forest extent, and an experimentally afforested simulation using WRF-SPA. WRF-SPA performs well at both site and regional scales, accurately simulating aircraft profiles of CO₂ concentration magnitudes (error <+- 4 ppm), indicating appropriate source sink distribution and realistic atmospheric transport. Hourly observations made at tall tower Angus were also well simulated by WRF-SPA (R² = 0.67, RMSE = 3.5 ppm, bias = 0.58 ppm). Analysis of CO₂ tracers at tall tower Angus show an increase in the seasonal error between WRF-SPA simulated atmospheric CO₂ and observations, which coincides with simulated cropland harvest. WRF-SPA does not simulate uncultivated land associated with agriculture, which in Scotland represents 36 % of agricultural holdings. Therefore, uncultivated land components may provide an explanation for the increase in model-data error. Interannual variation in weather is indicated to have a greater impact on ecosystem specific contributions to atmospheric CO₂ concentrations at Angus than variation in surface activity. In a model experiment, afforestation of Scotland was simulated to test the impact on Scotland’s carbon balance. The changes were shown to be potentially detectable by observations made at tall tower Angus. Afforestation results in a reduction in atmospheric CO₂ concentrations by up to 0.6 ppm at seasonal time scales at tall tower Angus. Detection of changes in forest surface net CO₂ uptake flux due to afforestation was improved through the use of a network of tall towers (R² = 0.83) compared to tall tower Angus alone (R² = 0.75).

The launch of large stratospheric balloons is highly dependant on the meteorological conditions at ground level, including wind speed. The balloon launch base Esrange Space Center in northern Sweden currently uses forecasts delivered through the Swedish Meteorological and Hydrological Institute to predict opportunities for balloon launches. However the staff at Esrange Space Center experience that the current forecasts are not accurate enough. For that reason the Weather Research and Forecasting model is used to improve the forecast. The model performs a Large Eddy Simulation over the area closest to Esrange Space Center to predict wind speed and turbulence. During twelve hypothetical launch days the improved forecast have an overall accuracy of 93% compared to the old forecast accuracy of 69%. With some improvements and the right computational power the system is thought to be operationally viable.

abstract: This research work uses the Weather Research and Forecasting Model to study the effect of large wind farms with an area of 900 square kilometers and a high power density of 7.58 W/m2 on regional climate. Simulations were performed with a wind farm parameterization scheme turned on in south Oregon. Control cases were also run with the parameterization scheme turned off. The primary emphasis was on offshore wind farms. Some analysis on onshore wind farms was also performed. The effects of these wind farms were studied on the vertical profiles of temperature, wind speed, and moisture as well as on temperature and on wind speed near the surface and at hub height. The effects during the day and at night were compared. Seasonal variations were also studied by performing simulations in January and in July. It was seen that wind farms produce a reduction in wind speed at hub height and that the downward propagation of this reduction in wind speed lessens as the atmosphere becomes more stable. In all the cases studied, the wind farms produced a warming effect near the surface, with greater atmospheric stability leading to higher near-surface temperatures. It was also observed that wind farms caused a drying effect below the hub height and a moistening effect above it, because they had facilitated vertical transport of moisture in the air from the lower layers of the atmosphere to the layers of the atmosphere above the wind farm. / Dissertation/Thesis / Masters Thesis Mechanical Engineering 2016

Eastern Kentucky is a 35-county region that is a part of the Cumberland Plateau of the Appalachian Mountains. With mountaintop removal and associated land cover change (LCC) (primarily deforestation), it is hypothesized that there would be changes in various atmospheric boundary layer parameters and precipitation. In this research, we have conducted sensitivity experiments of atmospheric response of a significant flash flood-producing rainfall event by modifying land cover and topography. These reflect recent LCC, including mountaintop removal (MTR). We have used the Weather Research and Forecasting (WRF) model for this purpose. The study found changes in amount, location, and timing of precipitation. LCC also modified various surface fluxes, moist static energy, planetary boundary layer height, and local-scale circulation wind circulation. The key findings were the modification in fluxes and precipitation totals. With respect to sensible heat flux (H), there was an increase to bare soil (post-MTR) in comparison to pre-MTR conditions (increased elevation with no altered land cover). Allowing for growth of vegetation, the grass simulation resulted in a decrease in H. H increased when permitting the growth of forest land cover (LC) but not to the degree of bare soil. In regards to latent heat flux (LE), there was a dramatic decrease transitioning from pre-MTR to post-MTR simulations. Then with the subsequent grass and forest simulations, there was an increase in LE comparable to the pre-MTR simulation. Under pre-MTR conditions, the total precipitation was at its highest level overall. Then with the simulated loss of vegetation and elevation, there was a dramatic decrease in precipitation. With the grass LC, the precipitation increased in all areas of interest. Then forest LC was simulated allowing overall slightly higher precipitation than grass.

In the current study, we have presented a systematic analysis of the diurnal cycle of rainfall over the Indian region using satellite observations, and evaluated the ability of the Weather Research and Forecasting Model (WRF) to simulate some of the salient features of the observed diurnal characteristics of rainfall. Using high resolution simulations, we also investigate the underlying mechanisms of some of the observed diurnal signatures of rainfall. Using the Tropical Rain-fall Measuring Mission (TRMM) 3-hourly, 0.25 ×0.25 degree 3B42 rainfall product for nine years (1999-2007), we extract the finer spatial structure of the diurnal scale signature of Indian summer monsoon rainfall. Using harmonic analysis, we construct a signal corresponding to diurnal and sub-diurnal variability. Subsequently, the 3-hourly time-period or the octet of rain-fall peak for this filtered signal, referred to as the “peak octet,” is estimated with care taken to eliminate spurious peaks arising out of Gibbs oscillations. Our analysis suggests that over the Bay of Bengal, there are three distinct modes of the peak octet of diurnal rainfall corresponding to 1130, 1430 and 1730 IST, from north central to south Bay. This finding could be seen to be consistent with southward propagation of the diurnal rainfall pattern reported by earlier studies. Over the Arabian sea, there is a spatially coherent pattern in the mode of the peak octet (1430 IST), in a region where it rains for more than 30% of the time. In the equatorial Indian Ocean, while most of the western part shows a late night/early morning peak, the eastern part does not show a spatially coherent pattern in the mode of the peak octet, owing to the occurrence of a dual maxima (early morning and early/late afternoon). The Himalayan foothills were found to have a mode of peak octet corresponding to 0230 IST, whereas over the Burmese mountains and the Western Ghats (west coast of India) the rainfall peaks during late afternoon/early evening (1430-1730 IST). This implies that the phase of the diurnal cycle over inland orography (e.g., Himalayas) is significantly different from coastal orography (e.g., Western Ghats). We also find that over the Gangetic plains, the peak octet is around 1430 IST, a few hours earlier compared to the typical early evening maxima over land. The second part of our study involves evaluating the ability of the Weather Research and Fore-casting Model (WRF) to simulate the observed diurnal rainfall characteristics. It also includes conducting high resolution simulations to explore the underlying physical mechanisms of the observed diurnal signatures of rainfall. The model (at 54km resolution) is integrated for the month of July 2006 since this period was particularly favourable for the study of diurnal cycle. We first evaluate the sensitivity of the model to the prescribed sea surface temperature (SST) by using two different SST datasets, namely Final Analyses (FNL) and Real-time Global (RTG). The overall performance of RTG SST was found to be better than FNL, and hence it was used for further model simulations. Next, we investigated the impact of different parameterisations (convective, microphysical, boundary layer, radiation and land surface) on the simulation of diurnal cycle of rainfall. Following this sensitivity study, we identified the suite of physical parameterisations in the model that “best” reproduces the observed diurnal characteristics of Indian monsoon rainfall. The “best” model configuration was used to conduct two nested simulations with one-way, three-level nesting (54-18-6km) over central India and Bay of Bengal. While the 54km and 18km simulations were conducted for July 2006, the 6km simulation was carried out for the period 18-24 July 2006. This period was chosen for our study since it is composed of an active period (19-21 July 2006), followed by a break period (22-24 July 2006). At 6km grid-spacing the model is able to realistically simulate the active and break phases in rainfall. During the chosen active phase, we find that the observed rainfall over central India tends to reach a maximum in the late night/early morning hours. This is in contrast to the observed climatological diurnal maxima of late evening hours. Interestingly, the 6km simulation for the active phase is able to reproduce this late night/early morning maxima. Upon further analysis, we find that this is because of the strong moisture convergence at the mid-troposphere during 2030-2330 IST, leading to the rainfall peak seen during 2330-0230 IST. Based on our analysis, we conclude that during both active and break phases of summer monsoon, mid-level moisture convergence seems to be one of the primary factors governing the phase of the diurnal cycle of rainfall. Over the Bay of Bengal, the 6km model simulation is in very good agreement with observations, particularly during the active phase. The southward propagation observed during 19-20 July 2006, which was not captured by the coarse resolution simulation (54km), is exceedingly well captured by the 6km simulation. The positive anomalies in specific humidity attain a maxima during 2030-0230 IST in the north and during 0830-1430 IST in the south. This confirms the role of moisture convergence in the southward propagation of rainfall. Equally importantly we find that while low level moisture convergence is dominant in the north Bay, it is the mid-level moisture convergence that is predominant in the south Bay.