Session Q30: The Physics of Climate

Stochastic Stommel box models for the thermohaline structure of the oceans

Bistability of the thermohaline circulation of the oceans has been implicated in various climate shifts in the past. The origin of the bistability lies in ocean-atmosphere interactions, as can be understood from a simple, deterministic two-box model proposed by H. Stommel (1961). Because of the rapidly varying nature of the atmosphere relative to the ocean it is more appropriate to treat the interactions stochastically, but, studies of stochastic Stommel models have been limited. Stochastic Stommel models have the further potential of explaining the features of the global temperature-salinity distribution in the oceans. We propose several such models, of varying complexity, which provide the blueprints to understand both empirical data and general circulation models.   

Nonequilibrium life-cycles in Ocean Heat Content

Natural climate variability can be considered as fluctuations in a nonequilibrium steady state. A fundamental property of nonequilibrium steady states is the phase space current which provides a preferred direction for fluctuations, and is manifested as preferred life-cycles for climate fluctuations. We propose a new quantity, the phase space angular momentum, to quantify the phase space rotation. In analogy with traditional angular momentum, which quantifies the rotation of mass in physical space, the phase space angular momentum quantifies the rotation of probability in phase space. It has the additional advantage that it is straightforward to calculate from a time series. We investigate the phase space angular momentum for fluctuations in ocean heat content in both observations and ocean general circulation models.   

Sensitivity of deep tropical convection to changes in the thermodynamic environment

Accurately modeling the effects of climate change using global models relies heavily on the representation of unresolved convection. This is because a major uncertainty in models is due to the effect of clouds and water vapor. Reducing this uncertainty requires a better understanding of convective processes. Deep tropical convection is especially important since it simultaneously drives global circulation and evolves as a result in changes to the convective environment induced by the general circulation. We investigate how changes to the thermodynamic environment--specifically changes in temperature and moisture--modify tropical convection. Unsurprisingly, increases in environmental moisture result in convection with higher precipitation rates. However, a counter-intuitive result is that increases atmospheric stability associated with a cooling in the lower troposphere and a warming aloft also produce higher precipitation rates. Understanding this result has provided significant insight to tropical cyclogenesis, and may be important for understanding other types of large scale organization of tropical convection.   

Uncertainties and complexities in small-scale ocean surface mixing processes

Ocean mixing and dispersion processes are intermittent in time, nonlinear, and inhomogeneous in space. Much is known about processes with a spatial scale of a few tens of km (that can be studied using satellite data) and about very fine-scale processes (turbulent motions of milimeters to meters that can be studied using microstructure turbulence profilers). However, there is a lack of both observations and understanding of the so-called ``submesoscale'' processes, composed of motions on a scale of a few kilometers. It is well recognized that submesoscale processes play a critical role in modulating large-scale circulation, ecological functioning, and the dispersion of pollutants. Due to limited computer power, present day ocean and climate models resolve processes on scales down to a few tens of km, so submesoscale processes have to be parameterized. Accurate parameterizations of these processes are critical in simulating and predicting ocean circulation and changes in the climate. In this talk, I will focus on submesoscale horizontal mixing. Recent advances in ocean observation systems enable us to reconstruct quasi-synoptic maps of the ocean surface velocity field, over large areas and at high spatial (100s of meter) and temporal (30 min) resolutions. These surface current observations allow the computation of Lagrangian trajectories of many virtual particles. Based on these trajectories, one can compute various measures for mixing and identify Lagrangian Coherent Structures (LCS) using various methods (such as Finite Time and Finite Size Lyapunov Exponents). I will demonstrate, using surface current measurements by High Frequency radar, the existence of temporary submesoscale barriers to mixing. This has important implications for a wide range of predictions. We were also able to verify the existence of these barriers using aerial-photographs. Using a non-stationary Lagrangian stochastic model, I will present a method for estimating the upper bound of the horizontal eddy diffusivity based on the existence of such barriers.   

Atomic-scale mechanism of incorporation of carbon dioxide in coal

Global warming is attributed to the rise of CO$_{2}$ concentration in the atmosphere. Sequestration of CO$_{2}$ into geological formations has been suggested for mitigating this phenomenon. Coalbeds are investigated as potential storage sites. Numerous experimental studies have demonstrated that coal swelling occurs after the injection of CO$_{2}$ into coal seams. However, the atomic-scale mechanism of such a phenomenon has not been well established. We report first-principles density-functional-theory calculations for the interaction between CO$_{2}$ and the coal network. The calculations show that the activation energies for incorporation of CO$_{2}$ into the coal bonding network are low at $\sim$ 0.9-1.3 eV depending on the bonding sites. We have found that the incorporated configurations are stable at low temperatures. However, high temperatures could stimulate the dissociation of CO$_{2}$ from such configurations as the activation energies are low at $\sim$ 0.5-0.9 eV, suggesting that coal swelling is reversible at high temperatures.   

Calibration of cavity ring-down spectrometry, integrating nephelometery, and condensation particle counting for distinguishing aerosol scattering/absorption properties

Aerosol optical depth, Angstrom exponent, size distribution are critical for radiative forcing models and are necessary to adequately parameterize biomass aerosols and dust in RCMs to improve our understanding of the impacts of aerosols on regional climate. Recent studies on the impact of atmospheric heating by dust and black carbon in the Tibetan Plateau (TP) showed that the heating will lead to enhanced pre-summer monsoon surface warming and early snow melts the TP region.. As a first step to characterize biomass aerosols we use completely scattering particles (polystyrene latex (PSL) spheres) and absorbing spheres to compare three techniques: cavity ring-down spectrometry (CRDS), integrating nephelometery, and Mie and T-Matrix theory; along with ancillary techniques, including condensation particle counting (CPC) and differential mobility analysis (DMA). In this work we compare the values and uncertainties of the scattering and backscattering cross section at 589 nm, scattering efficiency, and scattering {\AA}ngstrom coefficient determined from CRDS, nephelometery, and Mie theory and T-matrix theory. This is applied to PSL spheres 100-300 $\mu $m diameter and extended to 400 $\mu $m absorbing PSL spheres.   

Variability of Aerosol Optical Properties Based on Particle Size, Concentration and Origin

This work provides time series of size segregated aerosol optical depth (AOD), absorption angstrom exponent, single scattering albedo, aerosol size distribution observed over Tudor Hill, Bermuda. Aerosol optical properties (absorption and scattering) are compared with corresponding chemical compositions. It is observed that coarse particle light scattering is dominated by sea salt particles and fine aerosol light scattering is dominated by non-sea salt sulfate. The concentration of coarse sea salt aerosols shows a strong correlation with the wind speed however chemical composition observed in fine particles did not show any connection with the wind speed. The possibility of different origins of aerosol particles such as from continental, oceanic, industrial etc. will be presented based on the back trajectory analyses and the chemical composition.   

Multiscale Atmospheric Physics Modeled by Cumulant Expansions

We investigate a systematic and physically based approach to modeling subgrid physics statistically with the use of an expansion in equal-time cumulants. To accomplish this we replace the zonal average employed in previous work\footnote{S. M. Tobias and J. B. Marston, Phys. Rev. Lett. {\bf 101}, 104502 (2013).} with a low-pass filter that separates small and large scales in the zonal direction. The statistics are non-local, inhomogeneous, and anisotropic; the sole approximation is the neglect of 3-point and higher correlation functions. The closure respects the conservation of energy, enstrophy, and angular momentum. An advantage of the formulation is that correlations between large and small scale processes are treated explicitly without the introduction of phenomenological parameterizations. The approach is tested against full numerical simulation of idealized 1- and 2-layer models of the atmospheric general circulation\footnote{J. B. Marston, Ann. Rev. Cond. Matt. Phys. {\bf 3}, 285 (2012).} and shown to yield accurate low-order statistics. (The computer model used to perform these tests runs on OS X and is publicly available.\footnote{URL http://appstore.com/mac/gcm}) We identify important multiscale interactions and discuss the computational cost of the new scheme.   

Can We Eliminate the Major Tornado Threats in Tornado Alley?

The recent devastating tornado attacks in Oklahoma, Iowa, Nebraska, and South Dakota raise an important question: can we do something to eliminate the major tornado threats in Tornado Alley? Violent tornado attacks in Tornado Alley are starting from intensive encounters between the northbound warm air flow and southbound cold air flow. As there is no mountain in Tornado Alley ranging from west to east to weaken or block such air flows, some encounters are violent, creating instability: The strong wind changes direction and increases in speed and height. As a result, it creates a supercell, violent vortex, an invisible horizontal spinning motion in the lower atmosphere. When the rising air tilts the spinning air from horizontal to vertical, tornadoes with radii of miles are formed and cause tremendous damage. Here we show that if we build three east-west great walls in the American Midwest, 300m high and 50m wide, one in North Dakota, one along the border between Kansas and Oklahoma to east, and the third one in the south Texas and Louisiana, we will diminish the tornado threats in the Tornado Alley forever. We may also build such great walls at some area with frequent devastating tornado attacks first, then gradually extend it.   

How can you tell whether Earth is warming Up?

How does one determine whether the high summer temperatures in Moscow of a few years ago was an extreme climatic fluctuation or the result of a systematic global warming trend? How does one perform an analysis of the causes of this summer's high temperatures in the US, if climate variability is poorly constrained? It is only under exceptional circumstances that one can determine whether a climate signal belongs to a particular statistical distribution. In fact, climate signals are rarely ``statistical.'' It is thus often the case that one relies on statistical assumptions in order to compute a trend. There are other challenges in obtaining a trend: inherent multi-scale manifestations, and nonlinearities/non-Gaussianity, incomplete knowledge of climate variability. We propose a non-parametric notion of a trend, we call the tendency, that can handle multi-scale time series and that does not rely on statistical assumptions. Its primary utility lies in the analysis of time series with the aim of discerning structure from processes that could be modeled as noise.   

Iceberg capsize hydrodynamics and the source of glacial earthquakes

Accelerated warming in the past few decades has led to an increase in dramatic, singular mass loss events from the Greenland and Antarctic ice sheets, such as the catastrophic collapse of ice shelves on the western antarctic peninsula, and the calving and subsequent capsize of cubic-kilometer scale icebergs in Greenland's outlet glaciers. The latter has been identified as the source of long-period seismic events classified as glacial earthquakes, which occur most frequently in Greenland's summer months. The ability to partially monitor polar mass loss through the Global Seismographic Network is quite attractive, yet this goal necessitates an accurate model of a source mechanism for glacial earthquakes. In addition, the detailed relationship between iceberg mass, geometry, and the measured seismic signal is complicated by inherent difficulties in collecting field data from remote, ice-choked fjords. To address this, we use a laboratory scale model to measure aspects of the post-fracture calving process not observable in nature. Our results show that the combination of mechanical contact forces and hydrodynamic pressure forces generated by the capsize of an iceberg adjacent to a glacier's terminus produces a dipolar strain which is reminiscent of a single couple seismic source.