Thermodynamic efficiencies of an idealized global climate model

We employ the heat engine framework to derive a simple method for assessing the strength of irreversible processes in global climate models (GCMs). Using the explicit energy budget of an idealized GCM, we show that the thermodynamic efficiencies based on the net heating rate and frictional work rate provides a measure of physical and numerical irreversibilities present in either open (e.g., the Hadley circulation) or closed (e.g., the general circulation) circulations. In addition, we show that the Carnot efficiency is useful for assessing the maximum possible efficiency attained by closed circulations. Comparison of the work-based efficiency with that based on the net heating rate and the Carnot efficiency provides a gauge of how close to reversible and ideal the circulations are. A series of experiments with the idealized GCM demonstrate the usefulness of our method and show the sensitivity of an essentially reversible model to changes in physical and numerical parameters such as rotation period and resolution.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/47143/1/382_2005_Article_71.pd

Fluorescent amino acids as versatile building blocks for chemical biology

Fluorophores have transformed the way we study biological systems, enabling non-invasive studies in cells and intact organisms, which increase our understanding of complex processes at the molecular level. Fluorescent amino acids have become an essential chemical tool because they can be used to construct fluorescent macromolecules, such as peptides and proteins, without disrupting their native biomolecular properties. Fluorescent and fluorogenic amino acids with unique photophysical properties have been designed for tracking protein–protein interactions in situ or imaging nanoscopic events in real time with high spatial resolution. In this Review, we discuss advances in the design and synthesis of fluorescent amino acids and how they have contributed to the field of chemical biology in the past 10 years. Important areas of research that we review include novel methodologies to synthesize building blocks with tunable spectral properties, their integration into peptide and protein scaffolds using site-specific genetic encoding and bioorthogonal approaches, and their application to design novel artificial proteins, as well as to investigate biological processes in cells by means of optical imaging. [Figure not available: see fulltext.]

Geodesy and the problem of ice sheets

In recent years, great improvements have been made toward understanding the modern dynamics and recent history of the ice sheets. Several recently-launched satellite missions promise to make geodesy the most powerful tool for investigation of the changing ice sheets, including their past history and their present behavior. Mathematical description of ice sheet behavior from geodetic data requires accurate modeling of all the processes which may affect the measurements. Most geodetic tools measure changes in elevation of the ice sheets, which can include Post Glacial Rebound (PGR), the current Ice Mass Trend (IMT) consisting of both accumulation and glacial outflux, and processes of compaction within the firn column. Consequently it is necessary for mathematical models of geodetic data to separate the effects of IMT, PGR, and compaction. Satellite measurements of the time-variable geoid are insensitive to compaction effects and depend on IMT and PGR differently than do height measurements. Two methodological approaches have been proposed to separate these effects using measurements of height and time-variable geoid: 1- direct inversion for ice mass variability (Wu et al., 2002), which requires a priori assumptions about either the Earth’s rheology or the ice load history; 2- iterative solution for the fields, which theoretically is more approximate but is computationally much simpler and less dependent on a priori assumptions. In this paper we analyze how we can learn about IMT and PGR by combining geodetic measurements, and we assess the conditions required to optimally combine satellite and ground-based data sets

Importance of background climate in determining impact of land-cover change on regional climate

International audienc

Uncertainties due to transport-parameter sensitivity in an efficient 3-D ocean-climate model

A simplified climate model is presented which includes a fully 3-D, frictional geostrophic (FG) ocean component but retains an integration efficiency considerably greater than extant climate models with 3-D, primitive-equation ocean representations (20k years of integration can be completed in about a day on a PC). The model also includes an Energy and Moisture Balance atmosphere and a dynamic and thermodynamic sea-ice model. Using a semi-random ensemble of 1,000 simulations, we address both the inverse problem of parameter estimation, and the direct problem of quantifying the uncertainty due to mixing and transport parameters. Our results represent a first attempt at tuning a 3-D climate model by a strictly defined procedure, which nevertheless considers the whole of the appropriate parameter space. Model estimates of meridional overturning and Atlantic heat transport are well reproduced, while errors are reduced only moderately by a doubling of resolution. Model parameters are only weakly constrained by data, while strong correlations between mean error and parameter values are mostly found to be an artefact of single-parameter studies, not indicative of global model behaviour. Single-parameter sensitivity studies can therefore be misleading. Given a single, illustrative scenario of CO2 increase and fixing the polynomial coefficients governing the extremely simple radiation parameterisation, the spread of model predictions for global mean warming due solely to the transport parameters is around one degree after 100 years forcing, although in a typical 4,000-year ensemble-member simulation, the peak rate of warming in the deep Pacific occurs 400 years after the onset of the forcing. The corresponding uncertainty in Atlantic overturning after 100 years is around 5 Sv, with a small, but non-negligible, probability of a collapse in the long term