The prediction of the Earth's climate system is of immediate importance to many decision-makers. Anthropogenic climate change is a key area of public policy and will likely have widespread impacts across the world over the 21st Century. Understanding potential climate changes, and their magnitudes, is important for effective decision making. The principal tools used to provide such climate predictions are physical models, some of the largest and most complex models ever built. Evaluation of state-of-the-art climate models is vital to understanding our ability to make statements about future climate. This Thesis presents a framework for the analysis of climate models in light of their inherent uncertainties and principles of statistical good practice. The assessment of uncertainties in model predictions to-date is incomplete and warrants more attention that it has previously received. This Thesis aims to motivate a more thorough investigation of climate models as fit for use in decision-support. The behaviour of climate models is explored using data from the largest ever climate modelling experiment, the climateprediction.net project. The availability of a large set of simulations allows novel methods of analysis for the exploration of the uncertainties present in climate simulations. It is shown that climate models are capable of producing very different behaviour and that the associated uncertainties can be large. Whilst no results are found that cast doubt on the hypothesis that greenhouse gases are a significant driver of climate change, the range of behaviour shown in the climateprediction.net data set has implications for our ability to predict future climate and for the interpretation of climate model output. It is argued that uncertainties should be explored and communicated to users of climate predictions in such a way that decision-makers are aware of the relative robustness of climate model output.

Developers have an obligation to biodiversity when considering the impact their development may have on the environment, with some choosing to go beyond the legal requirement for planning consent. Climate change projections over the 21st century indicate a climate warming and thus the species selected for habitat creation need to be able to withstand the pressures associated with these forecasts. A process is therefore required to identify resilient plantings for sites subject to climate change. Local government ecologists were consulted on their views on the use of plants of non-native provenance or how they consider resilience to climate change as part of their planting recommendations. There are mixed attitudes towards non-native species, but with studies already showing the impact climate change is having on biodiversity, action needs to be taken to limit further biodiversity loss, particularly given the heavily fragmented landscape preventing natural migration. A methodology has been developed to provide planners and developers with recommendations for plant species that are currently adapted to the climate the UK will experience in the future. A climate matching technique, that employs a GIS, allows the identification of European locations that currently experience the predicted level of climate change at a given UK location. Once an appropriate location has been selected, the plant species present in this area are then investigated for suitability for planting in the UK. The methodology was trialled at one site, Eastern Quarry in Kent, and suitable climate matched locations included areas in north-western France. Through the acquisition of plant species data via site visits and online published material, a species list was created, which considered original habitat design, but with added resilience to climate change.

The most recent transition, from a greenhouse to an icehouse climate state, occurred during the Eocene-Oligocene transition (~34 Ma) and is thought to have been driven by a long-term decline in carbon dioxide concentrations and/or changes in ocean heat redistribution as a result of tectonic gateway reorganisation. In order to determine the primary driving mechanisms responsible, this thesis reconstructs long-term terrestrial and marine temperature change during the Eocene (56.0-33.9 Ma) using an organic biomarker approach. During the descent towards the icehouse (48-34 Ma), high-latitudes (>55°) are characterised by gradual surface water cooling (~6.5 0c). During the same interval, low-latitude settings exhibit ~2.5 °C of cooling. An ensemble of fixed-C02 climate model simulations that span the Eoc'ene indicate that only a small percentage (~5 to 15%) of this reconstructed temperature change can be ascribed to ocean gateway reorganisation or paleogeographic change. As such, this indicates that atmospheric carbon dioxide was the most likely driver of surface water cooling during the middle and late Eocene (48-34 Ma). To explore this further, new terrestrial temperature records were obtained from marginal marine settings and terrestrial lignite deposits. During the early Eocene, terrestrial temperatures remain stable and warm and coincide with a long-term maximum in global surface water temperatures and atmospheric carbon dioxide. Insights from lignite deposits indicate that additional carbon cycle feedback mechanisms (e.g. methane cycling) may have also been important in regulating early Eocene warmth. During the middle and late Eocene, terrestrial temperatures remain stable or exhibit a gradual decline (~3 °C). The magnitude of terrestrial cooling is much smaller than observed in the marine realm and implies significant changes in ocean heat redistribution during the middle and late Eocene. Although changes in ocean heat redistribution are consistent with C02 drawdown, tectonic gateway reorganisation may have also been important in some regions.

The Arctic is an important region in the study of climate change, but monitoring surface temperatures in this region is challenging, particularly in areas covered by sea ice. Here in situ, satellite and reanalysis data were utilised to investigate whether global warming over recent decades could be better estimated by changing the way the Arctic is treated in calculating global mean temperature. The degree of difference arising from using five different techniques, based on existing temperature anomaly dataset techniques, to estimate Arctic SAT anomalies over land and sea ice were investigated using reanalysis data as a testbed. Techniques which interpolated anomalies were found to result in smaller errors than non-interpolating techniques. Kriging techniques provided the smallest errors in anomaly estimates. Similar accuracies were found for anomalies estimated from in situ meteorological station SAT records using a kriging technique. Whether additional data sources, which are not currently utilised in temperature anomaly datasets, would improve estimates of Arctic surface air temperature anomalies was investigated within the reanalysis testbed and using in situ data. For the reanalysis study, the additional input anomalies were reanalysis data sampled at certain supplementary data source locations over Arctic land and sea ice areas. For the in situ data study, the additional input anomalies over sea ice were surface temperature anomalies derived from the Advanced Very High Resolution Radiometer satellite instruments. The use of additional data sources, particularly those located in the Arctic Ocean over sea ice or on islands in sparsely observed regions, can lead to substantial improvements in the accuracy of estimated anomalies. Decreases in Root Mean Square Error can be up to 0.2K for Arctic-average anomalies and more than 1K for spatially resolved anomalies. Further improvements in accuracy may be accomplished through the use of other data sources.

During the Miocene, the Earth's climate transitioned from an extended phase of global warmth (Miocene climatic optimum) into a colder mode with the establishment of a permanent and stable East Antarctic Ice Sheet (EAIS). The mechanisms which drove this extreme climate shift are still poorly understood, because continuous, well-dated Miocene sedimentary archives are still scarce. Reliable sea surface temperature estimates are crucial to any reconstruction and modelling of past ocean salinity and density, water column stratification, thermohaline circulation, and ice volume. Despite extensive studies of benthic foraminifera, existing planktonic foraminiferal records for this interval are extremely scarce and of low resolution. Consequently, the impact of global warming and cooling on tropical surface waters and the propagation of orbital cycles in the Earth System are unknown. The overarching aim of this thesis is to investigate the nature and variability of early-middle Miocene climate and the relationship to orbital variations in solar insolation, in order to better understand the extent and magnitude of the global middle Miocene Climate Transition (MMCT) and the subsequent cooling/EAIS events. Furthermore, this study aims to investigate changes in the thermal structure of the Pacific Ocean during the development of MMCT to examine Pacific Ocean circulation across the middle Miocene climatic events. This is achieved through high resolution planktonic foraminiferal stable isotope analysis, spectral analysis and wavelet transform analysis. The first ever high-resolution (3 kyr) astronomically-tuned record of δ18O and δ13C from planktonic foraminifera for the eastern equatorial Pacific Ocean (15.56–13.35 Myr) is presented here. These data provide vital new information on sea surface temperatures and primary productivity changes at the tropics during the middle Miocene, at a resolution not achieved in any previous study, which sheds new light on the extent and magnitude of the MMCT and associated carbon-isotope excursion. In order to assess the reliability of these new records this thesis also goes on to document the taxonomy and palaeobiology of Miocene tropical planktonic foraminifera and their response to times of climatic stress. Finally the data from Site U1338 is compared to Site 1146 in the western equatorial Pacific Ocean, to reconstruct bottom and surface water conditions and changes in ocean dynamics across the equatorial Pacific during this highly complex interval of climate history.

This thesis examines the relationship between synoptic meteorology and particulate matter (PM10). PM10 is a pollutant of high interest to UK health policy (DEFRA, 2016) and this study evaluates the importance of Rossby wave breaking (RWB) on UK PM10 concentration ([PM10]). RWB can result in atmospheric blocking, which is one extreme of mid-latitude synoptic meteorological variability that favours the accumulation of PM10. This study finds significant increases (p < 0.01) in UK Midlands [PM10] resulting from winter-time northeast Atlantic/ European RWB. Furthermore, this study shows that northeast Atlantic/ European RWB increases the probability of exceeding a hazardous [PM10] threshold. We have identified the Omega block as the most hazardous RWB subset, with a probability of exceeding a hazardous [PM10] threshold (0.383) over three times that for days without RWB (0.129). We have implemented a tracer framework within a Hadley centre Met-Office climate model (HADGEM3-GA4) to identify flow regimes influencing the UK throughout northeast Atlantic/European RWB events. A present-day HADGEM3-GA4 simulation, nudged to ERA-Interim reanalysis data, is used to verify the tracer framework and to identify the flow regimes influencing Omega block events. This study finds that the advection of European tracer and the accumulation of locally sourced tracer contribute to hazardous [PM10] throughout Omega block events. This study’s principal aim is to determine climatic shifts in both the frequency of synoptic meteorological conditions conducive to UK PM10 accumulation and in the corresponding flow regimes. Using a further two HADGEM3-GA4 simulations, we find a north-eastward climate shift in northeast Atlantic/European RWB, with an overall reduction in events. Additionally, we find that uture RWB events result in significantly (p<0.01) increased European and reduced stagnant air masses within the UK. This result indicates a reduced frequency of UK [PM10] exceedances, however a tendency for increased transport of toxic particles from Europe.

Undisputable evidence of global warming is accumulating from direct observations. Unfortunately, for some unanalysed regions of the world, the data coverage is still sparse (IPCC, 2007). This study aims to assess the changing patterns of precipitation and temperature across Mexico and the direct influence of EI Nino-Southern Oscillation. A network of 175 stations with precipitation and 52 with temperature of monthly data were built for the Principal Component Analysis (PCA) and the ENSO modulation assessments. A set of 35 stations with daily data for weather extremes analyses was also developed. Oblique-rotated (promax, k=2) solutions have been applied to the monthly datasets to regionalise groups of stations that are varying coherently. Extreme indices are calculated using the RClimDex in the daily time-series of rainfall and temperature. Finally, linear (Kendall's tau-b) and lag correlations have been applied to establish relationships between three different ENSO indices, the precipitation regional averages (resulting from PCA) and also with the weather extreme indices. A clear latitudinal transition is observed when the annual and wet (May-Oct) seasons of regional precipitation averages and extreme rainfall indices are correlated with the ENSO indices: wetter c.onditions are observed north of the tropic of cancer and below normal precipitation is dominant in the southern part of the country. Meanwhile, a national climatic picture of wetter conditions is observed when the standardised versions of the dry (Nov-Apr) season of the regional precipitation averages and the extreme precipitation indices are correlated with the ENSO indices; precipitation responds mainly close to the peak of EI Nino-like conditions. Warmer temperatures are observed when the extreme temperature indices are correlated with the ENSO indices. Nevertheless, the most significant results are seen in the minimum temperature related indices, although timing of response to the ENSO modulation is not as clear as in the case of precipitation.

This thesis assesses regional and temporal dependent biases in several microwave rainfall climatologies and considers their implications for monitoring the El Nino Southern Oscillation. Seasonal rainfall climatologies from the Tropical Rainfall Measuring Mission (TRMM) are evaluated during the transition from the 1997/1998 El Nino to the 1998/2000 La Nina. The satellite algorithms include version 5 TRMM rainfall products (GPROF (2A12), COMBINED (2B31) and PR (2A25», several passive microwave algorithms and GPCP (Global Precipitation Climatology Project) satellite-gauge estimates. All are compared to GPCC (Global Precipitation Climatology Centre) gauge estimates and two benchmark climatologies. The passive microwave algorithms are spatially and temporally calibrated to the Precipitation Radar using the histogram matching approach, which minimises spatial and temporal algorithm biases. Each algorithm detects seasonal and inter-annual variations in the rainfall distributions, although absolute values are shown to be significantly different. Despite three year quasiglobal averages converging to within -20%, zonal averages show large variations in the magnitude of the biases, e.g. >55% (-30%) for the austral (boreal) summer over land and >40% (-20-25%) during El Nifio (La Nina) over the ocean. Fine-scale comparisons show regional differences vary from <20% to >200%. Biases are attributed to variations in cloud microphysical characteristics, sampling problems and passive microwave coastal and surface artefacts. Unless temporal and spatial algorithm biases are accounted for, all satellite retrievals should be restricted to qualitative assessments of climatic rainfall.

. There is now overwhelming evidence that the stratosphere and troposphere behave as a two-way dy- namically coupled system, such that changes in temperature and wind in the stratosphere can influence the tropospheric circulation and vice versa. This has motivated interest in the role of the stratosphere in determining the climate response to forcing. Observations show that stratospheric water vapour (SWV) increased by ",30% between 1980 and 2000. Despite this, few studies have assessed the tropospheric dynamical response to SWV trends; this is the main aim of this thesis. The first part of the thesis focuses on modelling the radiative response to changes in SWV. It is shown that there are differences of up to ",70% in the magnitude of the temperature response to a given SWV perturbation between two different broad-band radiation codes. The physical basis for the structure of the purely radiative temperature response to an increase in SWV is then considered. The largest cooling occurs in the lower stratosphere and is enhanced in the extratropics compared to the tropics. The typically low concentration of SWV (a few ppmv) and the horizontal gradient in tropopause height are shown to be the dominant drivers of this structure. The second part of the thesis considers the response to SWV perturbations in global climate models (GCMs). An advanced GCM (H~dGAM I) is used to test the response to changes in SWV in the absence of changes in sea surface temperatures (SSTs). A uniform doubling in SWV results in a poleward shift in the rnidlatitude jets, a more positive annular mode index and an increase in the strength of the Brewer- Dobson circulation. In the more simplified Reading IGCM, the inclusion of the changes in SSTs causes a negative feedback, which reduces the amplitude of the tropospheric circulation response to a uniform SWV perturbation.

The Indian Ocean plays an important role in modulating climate over the surrounding region and around the globe, particularly through its major mode of climate variability, the Indian Ocean dipole (IOD). In this thesis, the representation of the Indian Ocean mean state and the IOD in the HiGEM high resolution coupled climate model has been investigated. To understand air-sea coupled processes during the IOD, it is first necessary to evaluate the representation of the Indian Ocean mean state in HiGEM. Although HiGEM has a very good representation of the tropical Indian Ocean, there are some regional biases in the model. Firstly biases in the Arabian Sea. HiGEM has biases in various parameters over the northern Arabian Sea during boreal winter. A major result of this thesis is that a winter cold SST bias in the Arabian Sea in HiGEM is shown to be common among most of the CMIP3 models, relating to cold dry air advection from north-west India! Pakistan during the winter monsoon. This also feeds enhanced convergence over the western equatorial Indian Ocean, potentially interacting with biases along the equator and the IOD. Secondly biases in mean equatorial winds, reversing the tilt of the equatorial thermocline during SON and DJF, which may lead to biases in the evolution of the IOD. To test the impact of the equatorial mean state biases in HiGEM on the IOD, an ensemble experiment correcting ocean surface wind stress over the equatorial Indian Ocean has been performed. When applied the wind stress correction to the ocean wind stress, it reduced the biases in the Cold SST and thermocline depth in the east equatorial Indian Ocean (EElO). This suggests that the seasonal evolution of the IOD is sensitive to the model mean state. As the anthropogenic warming can spin down the tropical circulations, the impact of climate change on the IOD in HiGEM is also investigated. Analysis showed an earlier initiation and termination of the roD in HiGEM in a warm climate compared to the HiGEM control run. This shift in initiation and termination in the seasonal evolution of the IOD is consistent with the change in the Indian Ocean mean state in a wann climate. This study shows the importance of understanding the Indian Ocean processes and their representation in models for regional climate studies.