The global energy balance from a surface perspective

In the framework of the global energy balance, the radiative energy exchanges between Sun, Earth and space are now accurately quantified from new satellite missions. Much less is known about the magnitude of the energy flows within the climate system and at the Earth surface, which cannot be directly measured by satellites. In addition to satellite observations, here we make extensive use of the growing number of surface observations to constrain the global energy balance not only from space, but also from the surface. We combine these observations with the latest modeling efforts performed for the 5th IPCC assessment report to infer best estimates for the global mean surface radiative components. Our analyses favor global mean downward surface solar and thermal radiation values near 185 and 342Wm−2, respectively, which are most compatible with surface observations. Combined with an estimated surface absorbed solar radiation and thermal emission of 161 and 397Wm−2, respectively, this leaves 106 Wm−2 of surface net radiation available globally for distribution amongst the non-radiative surface energy balance components. The climate models overestimate the downward solar and underestimate the downward thermal radiation, thereby simulating nevertheless an adequate global mean surface net radiation by error compensation. This also suggests that, globally, the simulated surface sensible and latent heat fluxes, around 20 and 85Wm−2 on average, state realistic values. The findings of this study are compiled into a new global energy balance diagram, which may be able to reconcile currently disputed inconsistencies between energy and water cycle estimate

Development of Aerosol Models for Radiative Flux Calculations at ARM Sites

The direct radiative forcing (DRF) of aerosols, the change in net radiative flux due to aerosols in non-cloudy conditions, is an essential quantity for understanding the human impact on climate change. Our work has addressed several key issues that determine the accuracy, and identify the uncertainty, with which aerosol DRF can be modeled. These issues include the accuracy of several radiative transfer models when compared to measurements and to each other in a highly controlled closure study using data from the ARM 2003 Aerosol IOP. The primary focus of our work has been to determine an accurate approach to assigning aerosol properties appropriate for modeling over averaged periods of time and space that represent the observed regional variability of these properties. We have also undertaken a comprehensive analysis of the aerosol properties that contribute most to uncertainty in modeling aerosol DRF, and under what conditions they contribute the most uncertainty. Quantification of these issues enables the community to better state accuracies of radiative forcing calculations and to concentrate efforts in areas that will decrease uncertainties in these calculations in the future

Remote sensing data from CLARET: A prototype CART data set

The data set containing radiation, meteorological , and cloud sensor observations is documented. It was prepared for use by the Department of Energy's Atmospheric Radiation Measurement (ARM) Program and other interested scientists. These data are a precursor of the types of data that ARM Cloud And Radiation Testbed (CART) sites will provide. The data are from the Cloud Lidar And Radar Exploratory Test (CLARET) conducted by the Wave Propagation Laboratory during autumn 1989 in the Denver-Boulder area of Colorado primarily for the purpose of developing new cloud-sensing techniques on cirrus. After becoming aware of the experiment, ARM scientists requested archival of subsets of the data to assist in the developing ARM program. Five CLARET cases were selected: two with cirrus, one with stratus, one with mixed-phase clouds, and one with clear skies. Satellite data from the stratus case and one cirrus case were analyzed for statistics on cloud cover and top height. The main body of the selected data are available on diskette from the Wave Propagation Laboratory or Los Alamos National Laboratory

Illuminating hydrological processes at the soil-vegetation-atmosphere interface with water stable isotopes

Funded by DFG research project “From Catchments as Organised Systems to Models based on Functional Units” (FOR 1Peer reviewedPublisher PDFPublisher PD

Justice from an interdisciplinary perspective: the impact of the revolution in Human Sciences on Peace Research and International Relations

Peace and justice have been a preferred couple in theoretical writings - but what do we know about their empirical relationship? Insights from other disciplines suggest that humans are highly sensitive to violations of justice and that justice concerns permeate social relations. Neuroscientists have located the parts of the brain responsible for negative reactions to violation of claims for justice. Evolutionary biologists have identified rules of distribution and retribution not only in early human societies but among other socially living species as well. Psychologists have observed the emergence of a sense of justice in very early childhood, while behavioral economists have identified behavior of average persons in experiments that deviated significantly from the model of the "economic man" and could only be explained by a sense of justice. The chapter summarizes these findings and outlines their implications for peace research. It highlights the ambivalent nature of justice for social relations. Justice concerns can exacerbate conflicts between individuals and groups but justice can also provide standards for arriving at durable peaceful solutions to conflicts. Understanding these ambivalences and their repercussions for international and intrastate relations provides a promising path towards understanding conflict dynamics

The meaning of my feelings depends on who I am: work-related identifications shape emotion effects in organizations

Theory and research on affect in organizations has mostly approached emotions from a valence perspective, suggesting that positive emotions lead to positive outcomes and negative emotions to negative outcomes for organizations. We propose that cognition resulting from emotional experiences at work cannot be assumed based on emotion valence alone. Instead, building on appraisal theory and social identity theory, we propose that individual responses to discrete emotions in organizations are shaped by, and thus depend on, work-related identifications. We elaborate on this proposition specifically with respect to turnover intentions, theorizing how three discrete emotions - anger, guilt, and pride - differentially affect turnover intentions, depending on two work-related identifications - organizational and occupational identification. A longitudinal study involving 135 pilot instructors reporting emotions, work-related identifications, and turnover intentions over the course of one year provides general support for our proposition. Our theory and findings advance emotion and identity theories by explaining how the effects of emotions are dependent on the psychological context in which they are experienced