The Wind-Evaporation-Sea Surface Temperature (WES) feedback is believedto play an important role in the tropics, where climate variability is governed byatmosphere-ocean coupled interactions. This dissertation reports on studies to distinctlyisolate the WES feedback mechanism over tropical oceans using a modiedversion of an NCAR-Community Climate Model (CCM3) thermodynamically coupledto a slab ocean model, where the WES feedback is deliberately suppressed inthe bulk aerodynamic formulation for surface heat uxes. A comparison of coupledintegrations using the modified WES-off CCM3 to those carried out using the standardCCM3 conclusively identifies the role of the WES feedback in enhancing theinter-annual variability over deep tropical oceans and the westward propagation ofthe equatorial annual cycle. An important role for near surface humidity in tropicalclimate variability in enhancing inter-annual variability and in sustaining the equatorialannual cycle is also suggested. Statistical analyses over the tropical Atlanticreveal that the free coupled meridional mode of the Atlantic Ocean is amplified in thepresence of the WES feedback. Similar analyses of coupled model integrations, whenforced with an articial El Ni~no Southern Oscillation (ENSO)-like SST cycle in tropicalPacific, reveal that only in the presence of the WES feedback is the meridionalmode the preferred mode of response of the Atlantic to ENSO forcings. It is also foundthat WES feedback reinforces the tendency of the ITCZ to stay north of the equator over the Atlantic during El-Nino events. Comparative studies between Last GlacialMaximum (LGM) equivalent imposed northern hemispheric sea-ice experiments withthe WES-off model and the standard model indicate a dominant role for the WESfeedback in the southward shift of the ITCZ as indicated by paleo-climate records.However, it is found not to be the sole thermodynamic mechanism responsible for thepropagation of high latitude cold SST anomalies to the tropics, suggesting significantroles for other mechanisms in the tropical response to high latitude changes.

Existing gender inequality is believed to be heightened as a result of weather events and climate-related disasters that are likely to become more common in the future. We show that an already marginalized group-female-headed households in South Africa-is differentially affected by relatively modest levels of variation in rainfall, which households experience on a year-to-year basis. Data from three waves of the National Income Dynamics Survey in South Africa allow us to follow incomes of 4,162 households from 2006 to 2012. By observing how household income is affected by variation in rainfall relative to what is normally experienced during the rainy season in each district, our study employs a series of naturally occurring experiments that allow us to identify causal effects. We find that households where a single head can be identified based on residency or work status are more vulnerable to climate variability than households headed by two adults. Single male-headed households are more vulnerable because of lower initial earnings and, to a lesser extent, other household characteristics that contribute to economic disadvantages. However, this can only explain some of the differential vulnerability of female-headed households. This suggests that there are traits specific to female-headed households, such as limited access to protective social networks or other coping strategies, which makes this an important dimension of marginalization to consider for further research and policy in South Africa and other national contexts. Households headed by widows, never-married women, and women with a non-resident spouse (e.g., "left-behind" migrant households) are particularly vulnerable. We find vulnerable households only in districts where rainfall has a large effect on agricultural yields, and female-headed households remain vulnerable when accounting for dynamic impacts of rainfall on income.

Jellyfish (Phylum Cnidaria, Class Scyphozoa) play important roles in pelagic ecosystems as predators and prey. Seasonally they form blooms facilitating reproductive success, but that are at times problematic for human enterprise. Medusa abundance has been correlated with environmental variables in several instances. However, the direct mechanisms for changes in medusa abundance are unclear. As global sea surface temperatures continue to change there is increasing concern that warming may enhance conditions favourable for the generation of jellyfish medusae. It is important to understand the ways in which temperature affects all life history stages of jellyfish if we are to begin to understand factors associated with jellyfish bloom formations, but how temperature and salinity affects life history stages of scyphozoan jellyfish from British waters remains largely unknown. In Chapter 1 I provide a general introduction to some key issues important to the formation of jellyfish blooms. In Chapter 2 I present results for experiments testing the effects of temperature on settlement and metamorphosis of planulae larvae of Cyanea capillata, Cyanea lamarckii, Chyrsaora hysoscella, and Aurelia aurita. Chapter 3 reports on the effects of temperature and salinity on survival, and asexual reproduction of scyphistomae of the same species. Chapter 4 reports on the effects of temperature and salinity on growth of newly released ephyrae of each of the above mentioned species, as well as the effects of starvation on survivorship on ephyrae of A. aurita originating from two distinct populations of scyphistomae. In Chapter 5 I provide a brief summary of significant findings for each life history stage, their theoretical implications when taken together, and next steps for future research. I also offer recommendations for ecosystem managers with an eye toward affecting the numbers of near-shore jellyfish medusae generated each season in the waters surrounding the British Isles.

Here we analyze climate variability using instrumental, paleoclimate (proxy), and the latest climate model data to understand more about the sources and impacts of low-frequency climate variability. Understanding the drivers of climate variability at interannual to century timescales is important for studies of climate change, including analyses of detection and attribution of climate change impacts. Additionally, correctly modeling the sources and impacts of variability is key to the simulation of abrupt change (Alley et al., 2003) and extended drought (Seager et al., 2005; Pelletier and Turcotte, 1997; Ault et al., 2014). In Appendix A, we employ an Earth system model (GFDL-ESM2M) simulation to study the impacts of a weakening of the Atlantic meridional overturning circulation (AMOC) on the climate of the American Tropics. The AMOC drives some degree of local and global internal low-frequency climate variability (Manabe and Stouffer, 1995; Thornalley et al., 2009) and helps control the position of the tropical rainfall belt (Zhang and Delworth, 2005). We find that a major weakening of the AMOC can cause large-scale temperature, precipitation, and carbon storage changes in Central and South America. Our results suggest that possible future changes in AMOC strength alone will not be sufficient to drive a large-scale dieback of the Amazonian forest, but this key natural ecosystem is sensitive to dry-season length and timing of rainfall (Parsons et al., 2014). In Appendix B, we compare a paleoclimate record of precipitation variability in the Peruvian Amazon to climate model precipitation variability. The paleoclimate (Lake Limón) record indicates that precipitation variability in western Amazonia is ‘red’ (i.e., increasing variability with timescale). By contrast, most state-of-the-art climate models indicate precipitation variability in this region is nearly'‘white' (i.e., equally variability across timescales). This paleo-model disagreement in the overall structure of the variance spectrum has important consequences for the probability of multi-year drought. Our lake record suggests there is a significant background threat of multi-year, and even decade-length, drought in western Amazonia, whereas climate model simulations indicate most droughts likely last no longer than one to three years. These findings suggest climate models may underestimate the future risk of extended drought in this important region. In Appendix C, we expand our analysis of climate variability beyond South America. We use observations, well-constrained tropical paleoclimate, and Earth system model data to examine the overall shape of the climate spectrum across interannual to century frequencies. We find a general agreement among observations and models that temperature variability increases with timescale across most of the globe outside the tropics. However, as compared to paleoclimate records, climate models generate too little low-frequency variability in the tropics (e.g., Laepple and Huybers, 2014). When we compare the shape of the simulated climate spectrum to the spectrum of a simple autoregressive process, we find much of the modeled surface temperature variability in the tropics could be explained by ocean smoothing of weather noise. Importantly, modeled precipitation tends to be similar to white noise across much of the globe. By contrast, paleoclimate records of various types from around the globe indicate that both temperature and precipitation variability should experience much more low-frequency variability than a simple autoregressive or white-noise process. In summary, state-of-the-art climate models generate some degree of dynamically driven low-frequency climate variability, especially at high latitudes. However, the latest climate models, observations, and paleoclimate data provide us with drastically different pictures of the background climate system and its associated risks. This research has important consequences for improving how we simulate climate extremes as we enter a warmer (and often drier) world in the coming centuries; if climate models underestimate low-frequency variability, we will underestimate the risk of future abrupt change and extreme events, such as megadroughts.

>Magister Scientiae - MSc / This work aimed at assessing the response of wetland vegetation productivity to the 2014-2017 climate-induced drought at the Soetendalsvlei wetland system in the Western Cape province of South Africa. To achieve this objective, firstly a literature review on the progress of remotely sensed data applications in assessing and monitoring wetland vegetation productivity was conducted. The review elaborates on the role of remote sensing in monitoring and assessing wetland vegetation productivity, with a detailed discussion of the climate change and variability impacts on wetland vegetation productivity. Accurate assessment results are produced when suitable processing techniques are selected as well as appropriate spatial and spectral resolution for extracting spectral information of wetland vegetation productivity. Secondly, wetland vegetation changes and productivity status was assessed using multi-temporal resolution Landsat series imagery and Normalized Difference Vegetation Index (NDVI) during the wet and dry seasons for the period between 2014 and 2018.

Climate variability threatens agricultural productivity and household food security, amongst small-scale farmers of South Africa. Managing climate variability is challenging due to the variation of climate parameters and the difficulty in making decisions under such conditions. Integrated seasonal forecast information and crop models have been used as a tool that enhances decision making in some countries. Utilization of such an approach in South Africa can enhance decision making in climate variability management. The study therefore sought to formulate a decision-making approach to enhance climate variability management in small-scale farming systems of South Africa through integrating seasonal forecast information and crop models. Current practices, challenges and opportunities for climate variability management by different small-scale farmer types were identified using focus group discussions and local agricultural extension officers. The Climate Forecast System version 2 (CFSv2) model-based forecasts were integrated with the Decision Support System for Agrotechnology Transfer (DSSAT) v4.7, a mechanistic crop model based on the Global Climate Model (GCM) approach. The GCM approach was the most appropriate technique for integrating seasonal forecast information and the crop model due to the compatibility in the forecast and crop model format. The decision-making process was formulated through assessing the simulation yield patterns under a range of farm management practices and seasonal forecasts for different cropping seasons, crops and farmer types for Limpopo and Eastern Cape, South Africa for 2017/18 season. The study assessed 48 different potential combinations of farm management practices: organic amendments, varieties, fertilizers and irrigation. Benefits of the decision formulation process and specific seasonal forecast-based recommendations were then assessed in the context of the performance of the practices under historical measured data for the conditions; 2011-2017, using percentile ranking. Assessing the yield response patterns under different farm management practices and seasonal forecasts (2017/2018), the study realized a range of decision scenarios. These are (1) low decision capacity and low climate sensitivity where there is low value for decision due to the homogeneous performance of the different management practices given climate forecasts. (2) high decision capacity and low climate sensitivity, where there is higher potential value for decision making as the different practices have uniform performance across climate forecasts. (3) High decision capacity and high climate sensitivity, where the good response to change in practices under changing climate forecasts. Confidence in the decision formulation process v was re-enforced as some of the decision scenarios were also realized under different conditions in the period; 2011-17. The scenario (2): High decision capacity and low climate sensitivity was predominant in locations with low forecast skill. In contrast the scenario (3): High decision capacity and high climate sensitivity was predominant in locations with high forecast skill. The decision formulation process allows for assessment of farm management practices in the seasonal forecast decision space. Although the case study realized some scenarios ahead of others, the process is robust and repeatable under any conditions. Although the process does not always offer recommendation with improved value for decision making, the value of recommendations is greater under decision scenarios with greater decision capacity. Such benefits are crop and location dependent. Improved seasonal forecasting skill increases reliability of the decision-making process, decision scenarios and associated recommendations. Such assertions need to be tested on the field scale to assess their practical feasibility.

Wind patterns in the Pacific Ocean fluctuate seasonally, annually, and decadally, resulting in changes in the dispersal of volcanic smog (vog) across the Hawaiian Islands. A variety of synoptic-scale weather patterns can affect the Islands, creating variability in the direction and intensity of wind patterns. Recent changes in wind profiles were analyzed to identify possible patterns that could influence and increase the dispersion of vog over time on Hawai’i Island and the other Hawaiian Islands to the northwest. Historically, Northeast Trade Winds prevailed for much of the year, shifting vog into the Pacific Ocean southwest of Hawaii and away from the state’s principal population centers, but Northeast Trade Winds have shown a 20+% reduction over the past several decades. An increase in the southerly source of prevailing wind increased the frequency and intensity of vog and its impacts on the environment and health and well-being of people across the Islands.

Western Antarctica has been experiencing significant warming for at least the past fifty years. While higher Net Surface Mass Balance (SMB) over West Antarctica during this period of warming is expected, SMB reconstructions from ice cores reveal a more complex pattern during the period of warming. The mechanisms giving rise to SMB variability over the West Antarctic Ice Sheet (WAIS) are not well understood due to lack of instrumental data. The Southern Annular Mode (SAM) and El Niño Southern Oscillation (ENSO) are believed to contribute to WAIS SMB variability but the assumption has not been rigorously tested. SMB during years where SAM and ENSO are in extreme phases is compared to average SMB from the period 1979-2010. Additionally, atmospheric circulation anomalies are used to assess what circulation patterns accompany extreme modes of climate during the same period. The results suggest that significantly lower SMB occurs when SAM is in an extremely positive phase or ENSO is in an extremely negative phase. Additionally, atmospheric circulation anomalies show that certain circulation patterns accompany extreme modes of climate, which contribute to SMB variability over the WAIS. Ultimately, the location of low and high pressure cells is the best predictor for extreme accumulation events over the WAIS. These results are verified by assessing observed net SMB trends from a network of firn cores located from the central WAIS. Seven new firn cores are added to improve the spatial network of regional net SMB measurements. Reconstructed net SMB is calculated from new firn core records, and compared to the existing cores. The new suite of preliminary firn core records show the same significant decreasing trend that is observed in existing cores. This represents a negative region-wide SMB trend that is likely in part due to trends in SAM and ENSO.

No description available.

Understanding forest carbon uptake and associated growth response is important for carbon sequestration and water management practices given the large quantities of carbon stored in forest ecosystems. Climate variability and forest management practices influence the magnitude and rate of soil CO2 efflux; however, their combined effects are complex and not well understood. This study investigated the response of soil CO2 efflux to the combined effects of climate variability, including those caused by climate oscillations, and shelterwood harvesting in a mature temperate white pine (Pinus strobes L.) forest, located near Lake Erie in southern Ontario, Canada. Analyses indicated that local winter temperatures and precipitation were influenced by climate oscillations, which affected forest carbon dynamics. After the shelterwood harvest removed approximately a third of the overstory canopy, no significant differences were found for soil temperature and soil moisture between the pre-harvesting (2008 to 2011) and post-harvesting (2012 to 2014) periods. Despite similar climate conditions pre- and post-harvesting, soil CO2 effluxes post-harvesting were lower. A Gaussian-Gamma specification model determined that heterotrophic (autotrophic) respiration decreased (increased) between pre- and post-harvesting, respectively. Mineral-soil respiration were similar pre- and post-harvesting. Soil CO2 efflux accounted for 78±9% of the annual ecosystem respiration (RE), derived using eddy-covariance fluxes. However, the overall net ecosystem productivity showed no significant difference between pre- and post-harvesting. This was attributed to an increase in the gross ecosystem productivity post-harvesting, compensating for the increased losses (i.e. increased RE). This study highlights the complexities of measuring various components of ecosystem respiration after a disturbance, such as a harvest. The knowledge gained from this study provides a better understanding of climate variability and shelterwood harvesting influences on ecosystem respiration and can be useful for forest managers focused on carbon sequestration and forest conservation. / Dissertation / Doctor of Science (PhD) / Coniferous forest plantations in eastern North America are undergoing silvicultural management to enhance their carbon sequestration capabilities and native-tree species diversity. This study investigated the combined influence of climate oscillations and shelterwood harvesting on soil carbon dynamics of a planted pine forest in southern Ontario, Canada. Between pre- and post-harvesting, soil temperature and soil moisture did not show any significant differences. However, soil CO2 effluxes in post-harvesting years were lower than pre-harvesting years. A Gaussian-Gamma specification model determined that heterotrophic (autotrophic) respiration decreased (increased) post-harvesting and mineral-soil respiration was similar between pre- and post-harvesting. An increase in ecosystem respiration post-harvesting, despite soil CO2 efflux decreasing and being the largest component, was primarily caused by the increase in autotrophic respiration due to enhancement in forest growth. This study improved the understanding of forest carbon dynamics by highlighting the importance of accounting for all components, which may contribute to ecosystem respiration. Results can be useful for forest management practitioners, specifically those focused on carbon sequestration and forest conservation.