A surface energy perspective on climate change

A surface forcing response framework is developed that enables an understanding of time-dependent climate change from a surface energy perspective. The framework allows the separation of fast responses that are unassociated with global-mean surface air temperature change (ΔT), which is included in the forcing, and slow feedbacks that scale with ΔT. The framework is illustrated primarily using 2 × CO2 climate model experiments and is robust across the models. For CO2 increases, the positive downward radiative component of forcing is smaller at the surface than at the tropopause, and so a rapid reduction in the upward surface latent heat (LH) flux is induced to conserve the tropospheric heat budget; this reduces the precipitation rate. Analysis of the time-dependent surface energy balance over sea and land separately reveals that land areas rapidly regain energy balance, and significant land surface warming occurs before global sea temperatures respond. The 2 × CO2 results are compared to a solar increase experiment and show that some fast responses are forcing dependent. In particular, a significant forcing from the fast hydrological response found in the CO2 experiments is much smaller in the solar experiment. The different fast response explains why previous equilibrium studies found differences in the hydrological sensitivity between these two forcings. On longer time scales, as ΔT increases, the net surface longwave and LH fluxes provide positive and negative surface feedbacks, respectively, while the net surface shortwave and sensible heat fluxes change little. It is found that in contrast to their fast responses, the longer-term response of both surface energy fluxes and the global hydrological cycle are similar for the different forcing agents.

Surface and interstitial Ti diffusion at the rutile TiO2(110) surface

Diffusion of Ti through the TiO2 (110) rutile surface plays a key role in the growth and reactivity of TiO2. To understand the fundamental aspects of this important process, we present an analysis of the diffusion of Ti adspecies at the stoichiometric TiO2(110) surface using complementary computational methodologies of density functional theory corrected for on-site Coulomb interactions (DFT+U) and a charge equilibration (QEq) atomistic potential to identify minimum energy pathways. We find that diffusion of Ti from the surface to subsurface (and vice versa) follows an intersticialcy exchange mechanism, involving exchange of surface Ti with the 6-fold coordinated Ti below the bridging oxygen rows. Diffusion in the subsurface between layers also follows an interstitialcy mechanism. The diffusion of Ti is discussed in light of continued attempts to understand the re-oxidation of non-stoichiometric TiO2(110) surfaces.

Rovibrational energy levels of hydrogen peroxide, studied by MULTIMODE with a reaction path Hamiltonian

Recently. Carter and Handy [J. Chem. Phys. 113 (2000) 987] have introduced the theory of the reaction path Hamiltonian (RPH) [J. Chem. Phys. 72 (1980) 99] into the variational scheme MULTIMODE, for the calculation of the J = 0 vibrational levels of polyatomic molecules, which have a single large-amplitude motion. In this theory the reaction path coordinate s becomes the fourth dimension of the moment-of-inertia tensor, and must be treated separately from the remaining 3N - 7 normal coordinates in the MULTIMODE program. In the modified program, complete integration is performed over s, and the M-mode MULTIMODE coupling approximation for the evaluation of the matrix elements applies only to the 3N - 7 normal coordinates. In this paper the new algorithm is extended to the calculation of rotational-vibration energy levels (i.e. J > 0) with the RPH, following from our analogous implementation for rigid molecules [Theoret. Chem. Acc. 100 (1998) 191]. The full theory is given, and all extra terms have been included to give the exact kinetic energy operator. In order to validate the new code, we report studies on hydrogen peroxide (H2O2), where the reaction path is equivalent to torsional motion. H2O2 has previously been studied variationally using a valence coordinate Hamiltonian; complete agreement for calculated rovibrational levels is obtained between the previous results and those from the new code, using the identical potential surface. MULTIMODE is now able to calculate rovibrational levels for polyatomic molecules which have one large-amplitude motion. (C) 2003 Elsevier B.V. All rights reserved.

A reaction surface Hamiltonian study of malonaldehyde

We report calculations using a reaction surface Hamiltonian for which the vibrations of a molecule are represented by 3N-8 normal coordinates, Q, and two large amplitude motions, s(1) and s(2). The exact form of the kinetic energy operator is derived in these coordinates. The potential surface is first represented as a quadratic in Q, the coefficients of which depend upon the values of s(1),s(2) and then extended to include up to Q(6) diagonal anharmonic terms. The vibrational energy levels are evaluated by solving the variational secular equations, using a basis of products of Hermite polynomials and appropriate functions of s(1),s(2). Our selected example is malonaldehyde (N=9) and we choose as surface parameters two OH distances of the migrating H in the internal hydrogen transfer. The reaction surface Hamiltonian is ideally suited to the study of the kind of tunneling dynamics present in malonaldehyde. Our results are in good agreement with previous calculations of the zero point tunneling splitting and in general agreement with observed data. Interpretation of our two-dimensional reaction surface states suggests that the OH stretching fundamental is incorrectly assigned in the infrared spectrum. This mode appears at a much lower frequency in our calculations due to substantial transition state character. (c) 2006 American Institute of Physics.

Bio-energy retains its mitigation potential under elevated CO2

Background If biofuels are to be a viable substitute for fossil fuels, it is essential that they retain their potential to mitigate climate change under future atmospheric conditions. Elevated atmospheric CO2 concentration [CO2] stimulates plant biomass production; however, the beneficial effects of increased production may be offset by higher energy costs in crop management. Methodology/Main findings We maintained full size poplar short rotation coppice (SRC) systems under both current ambient and future elevated [CO2] (550 ppm) and estimated their net energy and greenhouse gas balance. We show that a poplar SRC system is energy efficient and produces more energy than required for coppice management. Even more, elevated [CO2] will increase the net energy production and greenhouse gas balance of a SRC system with 18%. Managing the trees in shorter rotation cycles (i.e. 2 year cycles instead of 3 year cycles) will further enhance the benefits from elevated [CO2] on both the net energy and greenhouse gas balance. Conclusions/significance Adapting coppice management to the future atmospheric [CO2] is necessary to fully benefit from the climate mitigation potential of bio-energy systems. Further, a future increase in potential biomass production due to elevated [CO2] outweighs the increased production costs resulting in a northward extension of the area where SRC is greenhouse gas neutral. Currently, the main part of the European terrestrial carbon sink is found in forest biomass and attributed to harvesting less than the annual growth in wood. Because SRC is intensively managed, with a higher turnover in wood production than conventional forest, northward expansion of SRC is likely to erode the European terrestrial carbon sink.

Energy-dependent cancellation of diffraction spots due to surface roughening

The low-energy electron diffraction (LEED) pattern of the step-kinked Pt{531} surface at 200 K shows energy-dependent cancellation of diffraction spots over unusually large energy ranges, up to 100 eV. This cannot be reproduced theoretically when a flat surface geometry is assumed. A relatively simple model of roughening, however, involving 0.25 ML of vacancies and adatoms leads to very good agreement with the experiment. The cancellation of intensities within a very narrow range of adatom or vacancy coverages is caused by the interference of electrons emerging from different heights but similar local environments. This is a rare example where the energy dependence of integrated LEED spot intensities is dramatically affected by the long-range arrangement of atoms.

Evaluating the potential for statistical decadal predictions of sea surface temperatures with a perfect model approach

We explore the potential for making statistical decadal predictions of sea surface temperatures (SSTs) in a perfect model analysis, with a focus on the Atlantic basin. Various statistical methods (Lagged correlations, Linear Inverse Modelling and Constructed Analogue) are found to have significant skill in predicting the internal variability of Atlantic SSTs for up to a decade ahead in control integrations of two different global climate models (GCMs), namely HadCM3 and HadGEM1. Statistical methods which consider non-local information tend to perform best, but which is the most successful statistical method depends on the region considered, GCM data used and prediction lead time. However, the Constructed Analogue method tends to have the highest skill at longer lead times. Importantly, the regions of greatest prediction skill can be very different to regions identified as potentially predictable from variance explained arguments. This finding suggests that significant local decadal variability is not necessarily a prerequisite for skillful decadal predictions, and that the statistical methods are capturing some of the dynamics of low-frequency SST evolution. In particular, using data from HadGEM1, significant skill at lead times of 6–10 years is found in the tropical North Atlantic, a region with relatively little decadal variability compared to interannual variability. This skill appears to come from reconstructing the SSTs in the far north Atlantic, suggesting that the more northern latitudes are optimal for SST observations to improve predictions. We additionally explore whether adding sub-surface temperature data improves these decadal statistical predictions, and find that, again, it depends on the region, prediction lead time and GCM data used. Overall, we argue that the estimated prediction skill motivates the further development of statistical decadal predictions of SSTs as a benchmark for current and future GCM-based decadal climate predictions.

Urban microclimate and renewable energy use in cities

This paper presents an experimental measurement campaign of urban microclimate for a building complex located in London, the United Kingdom. The experiment was carried out between 19 July and 16 August, 2010 at the Elephant & Castle site. The wind and solar energy distributions within the London urban experimental site were assessed in detail for their potential use in areas of high-rise urban building complexes. The climatic variables were measured at every five minutes for the air temperature, the wind speed and direction, the air humidity and the global solar radiation for a period of four weeks. The surface temperatures were also measured on the asphalt road, pavement and building walls at every hour for the first week of the campaign period. The effect of the building complex on the urban microclimate has been analyzed in terms of the solar radiation, the air temperature and velocity. The information and observation obtained from this campaign will be useful to the analysis of renewable energy implementations in dense urban situations.

Spatio-temporal surface soil heat flux estimates from satellite data: results for the AMMA experiment at the Fakara (Niger) supersite

This paper describes a method that employs Earth Observation (EO) data to calculate spatiotemporal estimates of soil heat flux, G, using a physically-based method (the Analytical Method). The method involves a harmonic analysis of land surface temperature (LST) data. It also requires an estimate of near-surface soil thermal inertia; this property depends on soil textural composition and varies as a function of soil moisture content. The EO data needed to drive the model equations, and the ground-based data required to provide verification of the method, were obtained over the Fakara domain within the African Monsoon Multidisciplinary Analysis (AMMA) program. LST estimates (3 km × 3 km, one image 15 min−1) were derived from MSG-SEVIRI data. Soil moisture estimates were obtained from ENVISAT-ASAR data, while estimates of leaf area index, LAI, (to calculate the effect of the canopy on G, largely due to radiation extinction) were obtained from SPOT-HRV images. The variation of these variables over the Fakara domain, and implications for values of G derived from them, were discussed. Results showed that this method provides reliable large-scale spatiotemporal estimates of G. Variations in G could largely be explained by the variability in the model input variables. Furthermore, it was shown that this method is relatively insensitive to model parameters related to the vegetation or soil texture. However, the strong sensitivity of thermal inertia to soil moisture content at low values of relative saturation (<0.2) means that in arid or semi-arid climates accurate estimates of surface soil moisture content are of utmost importance, if reliable estimates of G are to be obtained. This method has the potential to improve large-scale evaporation estimates, to aid land surface model prediction and to advance research that aims to explain failure in energy balance closure of meteorological field studies.

Land-atmosphere energy exchange in Arctic tundra and boreal forest: available data and feedbacks to climate

This paper summarizes and analyses available data on the surface energy balance of Arctic tundra and boreal forest. The complex interactions between ecosystems and their surface energy balance are also examined, including climatically induced shifts in ecosystem type that might amplify or reduce the effects of potential climatic change. High latitudes are characterized by large annual changes in solar input. Albedo decreases strongly from winter, when the surface is snow-covered, to summer, especially in nonforested regions such as Arctic tundra and boreal wetlands. Evapotranspiration (QE) of high-latitude ecosystems is less than from a freely evaporating surface and decreases late in the season, when soil moisture declines, indicating stomatal control over QE, particularly in evergreen forests. Evergreen conifer forests have a canopy conductance half that of deciduous forests and consequently lower QE and higher sensible heat flux (QH). There is a broad overlap in energy partitioning between Arctic and boreal ecosystems, although Arctic ecosystems and light taiga generally have higher ground heat flux because there is less leaf and stem area to shade the ground surface, and the thermal gradient from the surface to permafrost is steeper. Permafrost creates a strong heat sink in summer that reduces surface temperature and therefore heat flux to the atmosphere. Loss of permafrost would therefore amplify climatic warming. If warming caused an increase in productivity and leaf area, or fire caused a shift from evergreen to deciduous forest, this would increase QE and reduce QH. Potential future shifts in vegetation would have varying climate feedbacks, with largest effects caused by shifts from boreal conifer to shrubland or deciduous forest (or vice versa) and from Arctic coastal to wet tundra. An increase of logging activity in the boreal forests appears to reduce QE by roughly 50% with little change in QH, while the ground heat flux is strongly enhanced.

Characterization of energy flux partitioning in urban environments: links with surface seasonal properties

A better understanding of links between the properties of the urban environment and the exchange to the atmosphere is central to a wide range of applications. The numerous measurements of surface energy balance data in urban areas enable intercomparison of observed fluxes from distinct environments. This study analyzes a large database in two new ways. First, instead of normalizing fluxes using net all-wave radiation only the incoming radiative fluxes are used, to remove the surface attributes from the denominator. Second, because data are now available year-round, indices are developed to characterize the fraction of the surface (built; vegetation) actively engaged in energy exchanges. These account for shading patterns within city streets and seasonal changes in vegetation phenology; their impact on the partitioning of the incoming radiation is analyzed. Data from 19 sites in North America, Europe, Africa, and Asia (including 6-yr-long observation campaigns) are used to derive generalized surface–flux relations. The midday-period outgoing radiative fraction decreases with an increasing total active surface index, the stored energy fraction increases with an active built index, and the latent heat fraction increases with an active vegetated index. Parameterizations of these energy exchange ratios as a function of the surface indices [i.e., the Flux Ratio–Active Index Surface Exchange (FRAISE) scheme] are developed. These are used to define four urban zones that characterize energy partitioning on the basis of their active surface indices. An independent evaluation of FRAISE, using three additional sites from the Basel Urban Boundary Layer Experiment (BUBBLE), yields accurate predictions of the midday flux partitioning at each location.