The aim of this work was to visualise heterogeneous deformation in snow under controlled laboratory conditions. Heterogeneous deformation was observed for both homogenous and heterogeneous loading conditions. Understanding deformation of snow is important in many scientific fields including vehicle traction, avalanche forecasting, and winter sports. This thesis investigates the deformation behaviour of snow on the centimetre scale under moderate strain rates (0.005 to 0.1 s-1) when subject to one-dimensional compression or to indentation. In order to allow controlled and repeatable snow deformation experiments, a new type of artificial snow was developed. This snow type was examined by low temperature scanning electron microscopy and by traditional avalanche observer’s methodology. Penetrometer experiments were conducted on the artificial snow and on natural seasonal snow in Scotland. The two snow types were found to be similar: results obtained on artificial snow are thus applicable to natural snow. A reproducible technique of manufacture and a thorough characterisation of the artificial snow are presented. One-dimensional compression experiments were conducted on the artificial snow. The experiments were in confined compression in a specially constructed apparatus, designed to provide for back-lit photography. Images were taken at 0.25 second intervals and analysed using digital image correlation, thus providing 2D strain fields. With careful control of photographic parameters, it is demonstrated that process of applying tracer substances to the snow is not necessary, thus allowing an unprecedented resolution. Spontaneously-forming strain localisations were observed for the first time, indicating strain softening behaviour. Damage was observed to propagate through the specimen as a moving front, resembling a wave. The force required to propagate the front remained nearly constant until the whole specimen was compacted, at which point a new front formed and the process repeated. The experimental method was extended to 2D indention experiments with a range of sizes and shapes of indenter. Complex deformation fields were observed, extending up to 6 times the width of the indenter on each side. Observed deformation included tensile tearing as well as compression and shear. The maximum local strain achieved in the indentation experiments was similar to that achieved by the first compaction front in one-dimensional compression. The work here presented has implications for snow deformation generally: strain localisation introduces a characteristic length, which may prevent scaling of models or results. The indentation results are particularly relevant to snow penetrometry, where indentation experiments are used to try and extract microstructural information from buried snow layers for the purpose of avalanche prediction. The common assumption that the penetrometer interacts only with snow very close to its tip may need to be reconsidered.

This thesis forms a NERC funded CASE studentship with the Met Office, whose aim is to investigate the treatment of cloud microphysical processes in numerical models, with a particular focus on exploring the impacts and possible benefits of microphysical complexity for the purpose of simulating clouds and precipitation. The issue of complexity is an important one in numerical modelling in order to maintain computational efficiency, particularly in the case of operational models. The latest numerical modelling tools are utilised to perform simulations of cloud types including idealised trade wind cumulus, orographic wave cloud and wintertime shallow convective cloud. Where appropriate, the modelling results are also validated against observations from recent field campaigns. The Factorial Method is employed as the main analysis tool to quantify the effect of microphysical variables in terms of their impact on a chosen metric. Ultimately it is expected that the techniques and results from this thesis will be used to help inform the future development of cloud microphysics schemes for use in both cloud resolving and operational models. This is timely given the current plans to upgrade the microphysics options available for use within the Met Office Unified Model. For an idealised warm cloud, it is shown that different bin microphysics schemes can produce different results, and therefore additional microphysical complexity does not necessarily ensure a more consistent simulation. An intercomparison of bin microphysics schemes in a 1-D column framework is recommended to isolate the origin of the discrepancies. In relation to the mixed-phase wave cloud, model simulations based on an adaptive treatment of ice density and habit struggled to reproduce the observed ice crystal growth rates, highlighting the need for further laboratory work to improve the parameterization of ice growth by diffusion within the sampled temperature regime. The simulations were also found to be largely insensitive to values of the deposition coefficient within the range of 0.1 to 1.0. Results from a mesoscale modelling study of shallow wintertime convection demonstrate the importance of the representation of dynamical factors that control cloud macrostructure, and how this has the potential to overshadow any concerns of microphysical complexity. Collectively, the results of this thesis place emphasis on the need to encourage more synergy between the dynamics and microphysics research communities in order to improve the future performance of numerical models, and to help optimise the balance between model complexity and computational efficiency.

This thesis develops an innovative process-based analysis of contemporary model performance of precipitation over southern Africa. This region is typically understudied and not fully understood due to the complexity of various influences and drivers of precipitation. Historical simulations of precipitation are assessed including principal drivers, sources of biases and dominant modes of interannual variability. The South Indian Ocean Convergence Zone (SIOCZ), a large-scale, austral summer rainfall feature extending across southern Africa into the south-west Indian Ocean, is evaluated as the feature of interest in historical simulations. Most CMIP5 models simulate an SIOCZ feature, but are typically too zonally oriented and discontinued between land and the adjacent Indian Ocean. Excessive precipitation over the continent is likely associated with excessively high low-level moisture flux around the Angola Low, which is almost entirely due to model circulation biases. Drivers of precipitation over southern Africa include three dominant moisture flux transport pathways which originate from flow around the SIOHP and SAOHP and monsoon winds. Interannual variability in the SIOCZ is shown by a clear dipole pattern, indicative of a northeast-southwest movement of the SIOCZ. Drivers of this shift are significantly related to the El Niño Southern Oscillation and the subtropical Indian Ocean dipole in observations. However models do not capture these teleconnections well, limiting confidence in model representation of variability. A large majority of the population rely heavily on precipitation over southern Africa for agricultural purposes. Therefore spatial and temporal changes in precipitation are crucial to identify and understand with intentions to ultimately provide useful climate information regarding water security over the region. Key climate change signals over southern Africa are established in this thesis (OND and DJF), in which the dominant regional mechanisms of precipitation change over southern Africa are quantified. Robustness and credibility of these changes are additionally quantified. The most notable projected change in precipitation over southern Africa is the distinct drying signal evident in the pre-summer season (OND). This has the implication of delaying the onset of the rainy season affecting planting and harvesting times. Future projections of the SIOCZ are determined, which indicate a northward shift of approximately 200km. A dipole pattern of precipitation wetting/drying is evident, where wetting occurs to the north of the climatological axis of maximum rainfall, hence implying a northward shift of the ITCZ, consistent with the SIOCZ shift. Using a decomposition method it is established that ΔP's dipole pattern emerges largely from the dynamic component, which holds most uncertainty, particularly over the south-west Indian Ocean. Changes in precipitation over land are not solely driven by dynamical changes but additionally driven by thermodynamic contributions, implying projected changes over land and ocean regions require different approaches. SST patterns of warming over the Indian Ocean corroborate the warmest-get-wetter mechanism driving wetting over the south-west Indian Ocean, which is robust in both key seasons. Coherent model behaviour is understood via across model correlation plots of principal components, whereby patterns of coherent warming patterns are identified. Composite analyses of diagnostic variables across models illustrate patterns driving projected precipitation changes. Drying is more robust over land than over the south-west Indian Ocean. Clear robust drying signal in OND, however magnitude is uncertain. Drivers of uncertainty include SST pattern changes, which modulate atmospheric circulation patterns. Therefore reductions in uncertainty rely on the accurate representation of these processes within climate models to become more robust. There is a desire from both climate scientists and policy-makers to reduce uncertainty in future projections. No one particular methodology is unanimously agreed upon, however one approach is analysed in this thesis. Uncertainties of future precipitation projections are addressed using a process-based model ranking framework. Several metrics most applicable to southern African climate are selected and ranked, which include aspects of both mean state and variability. A sensitivity test via a Monte Carlo approach is performed for various sub-samples of “top” performing models within the CMIP5 model dataset. Uncertainty is significantly reduced when particular sub-sets of “top” performing models are selected, however only for austral summer over the continent. The result has the implication that potential value is established in performing a process-based model ranking over southern Africa. However additional investigation is required before such an approach may become viable and sufficiently credible and robust. Reductions in model spread are additionally established in SIOCZ projections, whereby model processes of change exhibit agreement, despite differing initial SIOCZ conditions. Therefore model process convergence and coherence is established with respect to projected changes in the SIOCZ, irrespective of initial climatology biases.

Seasonality in the Amazon Rainforest is predicted to become more extreme, with dry seasons increasing in length and severity, while severe episodic droughts are expected to occur with greater frequency. Drought stress can reduce the capacity of the rainforest to sequester carbon, and severe drought events can switch the region from being a net sink to a temporary source of carbon to the atmosphere. A key component in the drought-induced carbon flux is tree mortality, and there is evidence of strong feedbacks globally and regionally in the Amazon with climate change. Although the exact cause of drought-induced mortality in trees is difficult to ascertain, recent data suggests that reduced functionality of the water transport pathway (hydraulic failure) is an important factor. Hydraulic vulnerability in trees is often assessed using measurements of the capacity of stems and branches to cope with the strongly negative internal water pressures associated with drought. However, leaves play a vital role in protecting the integrity of the ‘upstream’ hydraulic pathway by influencing the rate of transpiration and thus the tension in the water column. Therefore, the physiology of leaves can be informative of, and influence, tree species’ sensitivity to drought. This thesis uses a long-term large-scale rainfall exclusion experiment in the Eastern Amazon to examine the possible link between leaf physiology and drought sensitivity (or tolerance) by different taxa, and the capacity of mature, upper canopy Amazonian trees to respond to drought via plastic changes in leaf physiology. The plasticity in response to experimental drought and the differences between taxa classed as drought-sensitive and drought-resistant based on drought induced mortality records were tested by the study of leaf water relations (Chapter 2), leaf anatomy (Chapter 3) and foliar water uptake (Chapter 4). No consistent differences were found between drought-resistant and drought-sensitive species suggesting that the sensitivity of these species to drought may be due to other aspects of plant physiology. However, a limited response to the imposed drought conditions was detected across all taxa and included reductions of osmotic potential at full turgor and turgor loss point (Chapter 2), and increases in the thickness of the upper epidermis and the leaf internal cavity volume (Chapter 3). Interestingly, drought-sensitive taxa showed more seasonal osmotic adjustment than drought-resistant taxa, indicating that short-term responses to drought (e.g. season) are not representative of the capacity for adjustment in response to long-term water deficits. No significant changes occurred in leaf size, thickness, stomatal and vein density, the quantity of the inner leaf tissues (i.e. the palisade and spongy mesophyll) and mesophyll cell size, in response to the experimental drought. The experiments on foliar water uptake in Chapter 4 revealed that this rarely-considered process occurs in all taxa, but the response to the drought treatment differed among taxa. Using a simple model, foliar water uptake was scaled up to canopy level. Under normal conditions (i.e. no drought) canopy foliar uptake was calculated to be 29.9 ± 2.3 mm year-1 from rainfall alone, but this increased to a maximum of 51.9 ± 2.3 mm year-1 when including the input of dew in the dry season. However, lower water potential in the drought plot causing increased rates of foliar water uptake, led to estimates of 38.7 ± 3.0 mm year-1 (rainfall only) and 68.9 ± 2.9 mm year-1 (including dry season dew). Taken together, these results demonstrate that Amazonian trees show some limited capacity for acclimation to drought through the changes in leaf physiology measured in this thesis. Low turgor loss point is associated with dry climate-adapted plants, so the finding that this parameter reduced in response to the drought reveals some potential for Amazonian trees to acclimate with the predicted changes in moisture availability. However, the limited response of leaf anatomy to long-term drought might suggest that acclimation may only occur within a narrow range. The finding that six common Amazonian tree genera can take water up through their leaves has considerable implications for understanding the Amazon water budget, in terms of the contribution of dew and light rainfall to canopy water status, but also the implications it has for the hydraulic vulnerability of trees in rainforests right across the Amazon basin.

Copies of author's previously published articles inserted. / Bibliography: p. 223-244. / xx, 244 p. : ill. (some col.) ; 30 cm. / Title page, contents and abstract only. The complete thesis in print form is available from the University Library. / Thesis (Ph.D.)--University of Adelaide, Dept. of Physics and Mathematical Physics, 1994

This thesis seeks to investigate the changes in the characteristics of 20th and 21st century meteorological droughts in the UK to address the following lines of inquiry: 1) How credible are rainfall-based indices in representing hydrological droughts, 2) How coherent are droughts?, 3) Can alternative method of analysis provide new (or additional) information on the uncertainties in climate models?, and 4) Will future drought characteristics change?. Key results, respectively, are summarized as follows: • The drought severity index (DSI), can be considered a good proxy for assessing hydrological droughts as can be seen in its ability to capture the major hydrological events. The main caveat of the DSI is that there is often an underestimation of drought intensity and duration, • Drought covariance is higher for the (i) wet season, (ii) moderate and (iii) shorter duration droughts, • Evaluating climate models using drought statistics produces contrasting results compared with that using the model's precipitation fields. Drought statistics show biases which are largely negative, more intense, and have a greater spatial coverage. • The projected ensemble-mean change is generally greater (and more widespread) for (i) moderate droughts and (ii) wet season compared with extreme droughts and the dry season, respectively with increases in drought intensity, drought covariance index, frequency of drought months and frequency of drought events for a given duration shown for England.

Ecosystems undergo permanent alteration and degradation as a result of the pressure exerted upon them by anthropogenic activities and natural causes. Amongst the natural causes, drought can have considerable impacts on vegetation productivity; these impacts include biomass reduction and changes in vegetation cycles, growth, and vitality. Such impacts have important implications for society, and understanding the impacts of drought in natural systems will help minimise vulnerability to it. The Yucatan Peninsula is a vulnerable area in climate change scenarios, where increased intensity and frequency of droughts is already occurring. This thesis aims to analyse how droughts impact upon vegetation on the Yucatan Peninsula, Mexico using both remotely sensed data (in particular the Advanced Very High Resolution Radiometer – AVHRR - data) and meteorological data (in situ precipitation data). Three major elements are addressed: (1) spatial and temporal precipitation variability, and the occurrence of droughts during the period 1980-2011; (2) vegetation productivity trends, focusing on the persistence and resilience of the different vegetation types present across the Yucatan Peninsula using remotely sensed data sets, specifically, the Normalised Difference Vegetation Index (NDVI) from the National Oceanic and Atmosphere Administration Advanced Very High Resolution Radiometer (NOAA-AVHRR) as a proxy for productivity in the period 1982 to 2011; and (3) the relationship between vegetation productivity and rainfall and the lack of it (i.e. droughts) at a more detailed temporal scale (monthly) with two vegetation indices (NDVI from AVHRR and MTCI from the MEdium Resolution Imaging Spectrometer (MERIS)). The main findings indicate that precipitation in the area follows a gradient from north to south which is linked to vegetation types in the area, from deciduous forest to evergreen forest. NDVI trends in the Yucatan Peninsula are generally stable during the period 1980-2011; however, negative trends are persistent in areas where human impacts and intensive agriculture are present. Analysis of resilience also shows that deciduous forest and grasslands are much less resilient to disturbance and have a longer recovery period compared to other vegetation types. Per-pixel regression analysis between precipitation and vegetation productivity shows high explained variances between NDVI and rainfall with a time-lag of 1 and 2 months and tropical dry forest is the biome most affected by droughts. These results are valuable for decreasing the vulnerability of the Yucatan Peninsula and they could be used for increasing the understanding of the area and therefore go further in the creation of warning and management programmes.

No description available.

This work tests the validity of using a commercial cloud condensation nuclei (CCN) counter (CCNc) on the Facility for Airborne Atmospheric Measurements (FAAM) research aircraft. The CCNc was suitable for aircraft work with sta- ble and repeatable supersaturation, temperature and pressure relationships. The sample architecture of the aircraft fitted CCNc was found to transmit particles with acceptable losses in the diameter range of interest as was a pressure control device designed for airborne work. Rosemount inlets, used to sample aerosol, were found to be sensitive to particle density resulting in disparate aerosol being sam- pled with different efficiencies. In dust dominated aerosol inlet efficiency peaks at 10.24 at an optical diameter of 2.91 μm, with a minimum inlet efficiency between 1.78 and 1.51 at 0.28μm. In less dense aerosol inlets sample representatively below 0.6 μm and comparably below 1.0 μm. The thorough testing of the CCNc, associated sampling architecture and mea- surement strategies, enabled vertical and horizontal CCN to be investigated along with other aerosol and cloud microphysical properties in the Southern Equato- rial Pacific (SEP). The primary source of particulates was the South American continent, with sulphate dominating composition. There were strong gradients in aerosol and gas phase chemistry concentration with distance from the coast and in the cloud microphysics measurements where highest droplet numbers and smallest diameters were close to the coast. These data represent an important validatory and parameterisation data set for models of all scales. CCN data were used to calculate the aerosol hygroscopicity parameter, the mean project value, κ, was 0.21 ± 0.18 . There was no evident variation in hygroscopicity with distance from the Chilean coastline suggesting a single dominant source and a well mixed boundary layer up to 907km to the west. CCN measurements were also com- pared to predictions from multiple models of different composition and mixing state assumptions. The best CCN closure used an external mixture of inorganic and organic aerosol components, with a modelled to observed ratio of 1.37 ± 0.32. It was hypothesised that this large ratio and the relatively low bulk hy- groscopicity was influenced by an external mixture. Incorporating this external mixture is imperative if CCN are to be accurately modelled and any subsequent cloud processes accurately captured.

Der Bericht aus der Luftreinhaltung untersucht die Partikelzusammensetzung in der Außenluft. An vier Messorten in und um Leipzig wurden ultrafeine und feine Partikel nach Wetterlagen charakterisiert. Rund 90.000 Einzelanalysen führten zu den Verursachern. Bei östlicher Anströmung im Winter entstanden hohe Feinstaubwerte zu 80 % durch Kohle- und Holzheizungen und Sekundär-Partikel. Dabei lag meist überregionaler Ferntransport vor. Verkehrsemissionen dominierten bei westlicher Anströmung. Ruß, Metalle und polyzyklische Kohlenwasserstoffe reduzierten sich gegenüber 2000 deutlich.