The effect of doubled CO2 and model basic state biases on the monsoon-ENSO system. I: Mean response and interannual variability

The impact of doubled CO2 concentration on the Asian summer monsoon is studied using a coupled ocean-atmosphere model. Both the mean seasonal precipitation and interannual monsoon variability are found to increase in the future climate scenario presented. Systematic biases in current climate simulations of the coupled system prevent accurate representation of the monsoon-ENSO teleconnection, of prime importance for seasonal prediction and for determining monsoon interannual variability. By applying seasonally varying heat flux adjustments to the tropical Pacific and Indian Ocean surface in the future climate simulation, some assessment can be made of the impact of systematic model biases on future climate predictions. In simulations where the flux adjustments are implemented, the response to climate change is magnified, with the suggestion that systematic biases may be masking the true impact of increased greenhouse gas forcing. The teleconnection between ENSO and the Asian summer monsoon remains robust in the future climate, although the Indo-Pacific takes on more of a biennial character for long periods of the flux-adjusted simulation. Assessing the teleconnection across interdecadal timescales shows wide variations in its amplitude, despite the absence of external forcing. This suggests that recent changes in the observed record cannot be distinguished from internal variations and as such are not necessarily related to climate change

The effect of doubled CO2 and model basic state biases on the monsoon-ENSO system. II: Changing ENSO regimes

Integrations of a fully-coupled climate model with and without flux adjustments in the equatorial oceans are performed under 2×CO2 conditions to explore in more detail the impact of increased greenhouse gas forcing on the monsoon-ENSO system. When flux adjustments are used to correct some systematic model biases, ENSO behaviour in the modelled future climate features distinct irregular and periodic (biennial) regimes. Comparison with the observed record yields some consistency with ENSO modes primarily based on air-sea interaction and those dependent on basinwide ocean wave dynamics. Simple theory is also used to draw analogies between the regimes and irregular (stochastically forced) and self-excited oscillations respectively. Periodic behaviour is also found in the Asian-Australian monsoon system, part of an overall biennial tendency of the model under these conditions related to strong monsoon forcing and increased coupling between the Indian and Pacific Oceans. The tropospheric biennial oscillation (TBO) thus serves as a useful descriptor for the coupled monsoon-ENSO system in this case. The presence of obvious regime changes in the monsoon-ENSO system on interdecadal timescales, when using flux adjustments, suggests there may be greater uncertainty in projections of future climate, although further modelling studies are required to confirm the realism and cause of such changes

The role of the basic state in the ENSO-monsoon relationship and implications for predictability

The impact of systematic model errors on a coupled simulation of the Asian Summer monsoon and its interannual variability is studied. Although the mean monsoon climate is reasonably well captured, systematic errors in the equatorial Pacific mean that the monsoon-ENSO teleconnection is rather poorly represented in the GCM. A system of ocean-surface heat flux adjustments is implemented in the tropical Pacific and Indian Oceans in order to reduce the systematic biases. In this version of the GCM, the monsoon-ENSO teleconnection is better simulated, particularly the lag-lead relationships in which weak monsoons precede the peak of El Nino. In part this is related to changes in the characteristics of El Nino, which has a more realistic evolution in its developing phase. A stronger ENSO amplitude in the new model version also feeds back to further strengthen the teleconnection. These results have important implications for the use of coupled models for seasonal prediction of systems such as the monsoon, and suggest that some form of flux correction may have significant benefits where model systematic error compromises important teleconnections and modes of interannual variability

Designing Black Watch: How Being a Military Spouse Shaped My Creation of the Set Design for a Play about War

This thesis documents the process of designing the set for the play Black Watch by Gregory Burke. This play tells the story of the British Army’s Black Watch Regiment and their deployment to Iraq in 2004. The Black Watch Regiment is a Scottish regiment, and the play focuses on their history, as well as their current operations. Black Watch was first performed on the 5th of August 2006 in Edinburgh, Scotland with the National Theatre of Scotland and received the Laurence Olivier Award for Best New Play. This thesis will focus on two main areas. First, I will highlight the methodology and decision-making process I used in the actual set design. I will explore the technical aspects of design such as drawing a clear ground plan and building a white model of the set. Secondly, I will explore my own experience with war as the wife of an Army Officer who has deployed multiple times during the Operation Iraqi Freedom and Operation Enduring Freedom. I will search for the rationale behind my image of a war zone, and how it differs from my husband’s personal stories of war and the stories of war found in mass media. The intent of this task is to define how and why my idealized image of war may not necessarily represent the reality

The transient response of global-mean precipitation to increasing carbon dioxide levels

The transient response of global-mean precipitation to an increase in atmospheric carbon dioxide levels of 1% yr(-1) is investigated in 13 fully coupled atmosphere-ocean general circulation models (AOGCMs) and compared to a period of stabilization. During the period of stabilization, when carbon dioxide levels are held constant at twice their unperturbed level and the climate left to warm, precipitation increases at a rate of similar to 2.4% per unit of global-mean surface-air-temperature change in the AOGCMs. However, when carbon dioxide levels are increasing, precipitation increases at a smaller rate of similar to 1.5% per unit of global-mean surface-air-temperature change. This difference can be understood by decomposing the precipitation response into an increase from the response to the global surface-temperature increase (and the climate feedbacks it induces), and a fast atmospheric response to the carbon dioxide radiative forcing that acts to decrease precipitation. According to the multi-model mean, stabilizing atmospheric levels of carbon dioxide would lead to a greater rate of precipitation change per unit of global surface-temperature change

Modelling monsoons: understanding and predicting current and future behaviour

The global monsoon system is so varied and complex that understanding and predicting its diverse behaviour remains a challenge that will occupy modellers for many years to come. Despite the difficult task ahead, an improved monsoon modelling capability has been realized through the inclusion of more detailed physics of the climate system and higher resolution in our numerical models. Perhaps the most crucial improvement to date has been the development of coupled ocean-atmosphere models. From subseasonal to interdecadal time scales, only through the inclusion of air-sea interaction can the proper phasing and teleconnections of convection be attained with respect to sea surface temperature variations. Even then, the response to slow variations in remote forcings (e.g., El Niño—Southern Oscillation) does not result in a robust solution, as there are a host of competing modes of variability that must be represented, including those that appear to be chaotic. Understanding the links between monsoons and land surface processes is not as mature as that explored regarding air-sea interactions. A land surface forcing signal appears to dominate the onset of wet season rainfall over the North American monsoon region, though the relative role of ocean versus land forcing remains a topic of investigation in all the monsoon systems. Also, improved forecasts have been made during periods in which additional sounding observations are available for data assimilation. Thus, there is untapped predictability that can only be attained through the development of a more comprehensive observing system for all monsoon regions. Additionally, improved parameterizations - for example, of convection, cloud, radiation, and boundary layer schemes as well as land surface processes - are essential to realize the full potential of monsoon predictability. A more comprehensive assessment is needed of the impact of black carbon aerosols, which may modulate that of other anthropogenic greenhouse gases. Dynamical considerations require ever increased horizontal resolution (probably to 0.5 degree or higher) in order to resolve many monsoon features including, but not limited to, the Mei-Yu/Baiu sudden onset and withdrawal, low-level jet orientation and variability, and orographic forced rainfall. Under anthropogenic climate change many competing factors complicate making robust projections of monsoon changes. Absent aerosol effects, increased land-sea temperature contrast suggests strengthened monsoon circulation due to climate change. However, increased aerosol emissions will reflect more solar radiation back to space, which may temper or even reduce the strength of monsoon circulations compared to the present day. Precipitation may behave independently from the circulation under warming conditions in which an increased atmospheric moisture loading, based purely on thermodynamic considerations, could result in increased monsoon rainfall under climate change. The challenge to improve model parameterizations and include more complex processes and feedbacks pushes computing resources to their limit, thus requiring continuous upgrades of computational infrastructure to ensure progress in understanding and predicting current and future behaviour of monsoons

Extreme weather and climate events with ecological relevance : a review

Author Posting. © The Author(s), 2017. This is the author's version of the work. It is posted here under a nonexclusive, irrevocable, paid-up, worldwide license granted to WHOI. It is made available for personal use, not for redistribution. The definitive version was published in Philosophical Transactions of the Royal Society of London.Series B, Biological Sciences, 372 (2017): 2016.0135, doi: 10.1098/rstb.2016.0135.Robust evidence exists that certain extreme weather and climate events, especially daily temperature and precipitation extremes, have changed in regard to intensity and frequency over recent decades. These changes have been linked to human-induced climate change, while the degree to which climate change impacts an individual extreme climate event (ECE) is more difficult to quantify. Rapid progress in event attribution has recently been made through improved understanding of observed and simulated climate variability, methods for event attribution and advances in numerical modelling. Attribution for extreme temperature events is stronger compared with other event types, notably those related to the hydrological cycle. Recent advances in the understanding of ECEs, both in observations and their representation in state-of-the-art climate models, open new opportunities for assessing their effect on human and natural systems. Improved spatial resolution in global climate models and advances in statistical and dynamical downscaling now provide climatic information at appropriate spatial and temporal scales. Together with the continued development of Earth System Models that simulate biogeochemical cycles and interactions with the biosphere at increasing complexity, these make it possible to develop a mechanistic understanding of how ECEs affect biological processes, ecosystem functioning and adaptation capabilities. Limitations in the observational network, both for physical climate system parameters and even more so for long-term ecological monitoring, have hampered progress in understanding bio-physical interactions across a range of scales. New opportunities for assessing how ECEs modulate ecosystem structure and functioning arise from better scientific understanding of ECEs coupled with technological advances in observing systems and instrumentation.Portions of this study were supported by the Regional and Global Climate Modeling Program (RGCM) of the U.S. Department of Energy's Office of Biological & Environmental Research (BER) Cooperative Agreement #DE-FC02-97ER62402, and the National Science Foundation

Altitude dependence of atmospheric temperature trends: Climate models versus observation

As a consequence of greenhouse forcing, all state of the art general circulation models predict a positive temperature trend that is greater for the troposphere than the surface. This predicted positive trend increases in value with altitude until it reaches a maximum ratio with respect to the surface of as much as 1.5 to 2.0 at about 200 to 400 hPa. However, the temperature trends from several independent observational data sets show decreasing as well as mostly negative values. This disparity indicates that the three models examined here fail to account for the effects of greenhouse forcings.Comment: 9 pages, 3 figure

Reproduction of Twentieth Century Intradecadal to Multidecadal Surface Temperature Variability in Radiatively Forced Coupled Climate Models

[1] Coupled Model Intercomparison Project 3 simulations that included time-varying radiative forcings were ranked according to their ability to consistently reproduce twentieth century intradecadal to multidecadal (IMD) surface temperature variability at the 5° by 5° spatial scale. IMD variability was identified using the running Mann-Whitney Z method. Model rankings were given context by comparing the IMD variability in preindustrial control runs to observations and by contrasting the IMD variability among the ensemble members within each model. These experiments confirmed that the inclusion of time-varying external forcings brought simulations into closer agreement with observations. Additionally, they illustrated that the magnitude of unforced variability differed between models. This led to a supplementary metric that assessed model ability to reproduce observations while accounting for each model\u27s own degree of unforced variability. These two metrics revealed that discernable differences in skill exist between models and that none of the models reproduced observations at their theoretical optimum level. Overall, these results demonstrate a methodology for assessing coupled models relative to each other within a multimodel framework

Overview of the Coupled Model Intercomparison Project (CMIP)

The Coupled Model Intercomparison Project (CMIP) involves study and intercomparison of multimodel simulations of present and future climate. The simulations of the future use idealized forcing in which CO, increase is compounded 1% yr(-1) until it doubles (near year 70) with global coupled models that contain, typically, components representing atmosphere, ocean, sea ice, and land surface. Results from CMIP diagnostic sub-projects were presented at the Second CMIP Workshop held at the Max Planck Institute for Meteorology in Hamburg, Germany, in September 2003. Significant progress in diagnosing and understanding results from global coupled models has been made since the time of the First CMIP Workshop in Melbourne, Australia, in 1998. For example, the issue of flux adjustment is slowly fading as more and more models obtain stable multicentury surface climates without them. El Nino variability, usually about half the observed amplitude in the previous generation of coupled models, is now more accurately simulated in the present generation of global coupled models, though there are still biases in simulating the patterns of maximum variability. Typical resolutions of atmospheric component models contained in coupled models are now usually around 2.5degrees latitude-longitude, with the ocean components often having about twice the atmospheric model resolution, with even higher resolution in the equatorial Tropics. Some new-generation coupled models have atmospheric resolutions of around 1.5degrees latitude - longitude. Modeling groups now routinely run the CMIP control and 1% CO2 simulations in addition to twentieth- and twenty-first-century climate simulations with a variety of forcings e.g., volcanoes, solar variability, anthropogenic sulfate aerosols, ozone, and greenhouse gases, with the anthropogenic forcings for future climate as well. However, persistent systematic errors noted in previous generations of global coupled models are still present in the current generation (e.g., overextensive equatorial Pacific cold tongue, double ITCZ). This points to the next challenge for the global coupled climate modeling community. Planning and commencement of the Intergovernmental Panel on Climate Change Fourth Assessment Report (AR4) has prompted rapid coupled model development, which is leading to an expanded CMIP-like activity to collect and analyze results for the control, 1% CO2, and twentieth-, twenty-first, and twenty-second-century simulations performed for the AR4. The international climate community is encouraged to become involved in this analysis effort