Corrigendum to "High-resolution interpolar difference of atmospheric methane around the Last Glacial Maximum" published in Biogeosciences, 9, 3961–3977, 2012

No abstract available

A Psychometric Study of a Trait and State Assessment of Sexual Pleasure - The Amsterdam Sexual Pleasure Inventory.

We studied the Amsterdam Sexual Pleasure Inventory's (1.0) psychometric properties. The ASPI, a revised self-report battery designed to measure domains of state and trait sexual pleasure in diverse gender, sex, and relationship populations, is based on a recently proposed conceptual framework of sexual pleasure. We collected quantitative (n = 1371) and qualitative data (n = 637) using a cross-sectional multi-method design targeting the general (German-speaking) population. After pre-processing, we conducted analyses on a sample of n = 706 participants. The theory-based 5-factor exploratory structural equation model and the principal component analyses of the two general exploratory index-scales showed good and acceptable structural validity evidence respectively. Measurement invariance was confirmed separately for male and female participants and for those with sexually functional-scoring and dysfunctional-scoring levels. Coefficient omega indicated that all scales, except those of one facet, showed acceptable to very good internal consistency. The ASPI's convergent and discriminant associations with sexological and psychological constructs demonstrated good overall construct validity. Participants understood the items as intended and felt that the ASPI covered relevant facets of sexual pleasure. The ASPI might help understand how individuals differ in experiencing sexual pleasure and how different contexts enable some people to experience pleasure while disadvantaging others

Evaluating atmospheric methane inversion model results for Pallas, northern Finland

A state-of-the-art inverse model, CarbonTracker Data Assimilation Shell (CTDAS), was used to optimize estimates of methane (CH4) surface fluxes using atmospheric observations of CH4 as a constraint. The model consists of the latest version of the TM5 atmospheric chemistry-transport model and an ensemble Kalman filter based data assimilation system. The model was constrained by atmospheric methane surface concentrations, obtained from the World Data Centre for Greenhouse Gases (WDCGG). Prior methane emissions were specified for five sources: biosphere, anthropogenic, fire, termites and ocean, of which bio-sphere and anthropogenic emissions were optimized. Atmospheric CH 4 mole fractions for 2007 from northern Finland calculated from prior and optimized emissions were compared with observations. It was found that the root mean squared errors of the posterior esti - mates were more than halved. Furthermore, inclusion of NOAA observations of CH 4 from weekly discrete air samples collected at Pallas improved agreement between posterior CH 4 mole fraction estimates and continuous observations, and resulted in reducing optimized biosphere emissions and their uncertainties in northern Finland

The relative contribution of orbital forcing and greenhouse gases to the North American deglaciation

Understanding what drove Northern Hemisphere ice sheet melt during the last deglaciation (21–7 ka) can help constrain how sensitive contemporary ice sheets are to greenhouse gas (GHGs) changes. The roles of orbital forcing and GHGs in the deglaciation have previously been modelled, but not yet quantified. Here, for the first time we calculate the relative effect of these forcings on the North American deglaciation by driving a dynamical ice sheet model (GLIMMER-CISM) with a set of un-accelerated transient deglacial simulations with a full primitive equation based ocean atmosphere general circulation model (FAMOUS). We find that by 9 ka, orbital forcing has caused 50% of the deglaciation, GHG 30% and the interaction between the two 20%. Orbital forcing starts affecting the ice volume at 19 ka, 2,000 years before CO2 starts increasing in our experiments, a delay which partly controls their relative effect

Present state of global wetland extent and wetland methane modelling: conclusions from a model inter-comparison project (WETCHIMP)

Global wetlands are believed to be climate sensitive, and are the largest natural emitters of methane (CH4). Increased wetland CH4 emissions could act as a positive feedback to future warming. The Wetland and Wetland CH4 Inter-comparison of Models Project (WETCHIMP) investigated our present ability to simulate large-scale wetland characteristics and corresponding CH4 emissions. To ensure inter-comparability, we used a common experimental protocol driving all models with the same climate and carbon dioxide (CO2) forcing datasets. The WETCHIMP experiments were conducted for model equilibrium states as well as transient simulations covering the last century. Sensitivity experiments investigated model response to changes in selected forcing inputs (precipitation, temperature, and atmospheric CO2 concentration). Ten models participated, covering the spectrum from simple to relatively complex, including models tailored either for regional or global simulations. The models also varied in methods to calculate wetland size and location, with some models simulating wetland area prognostically, while other models relied on remotely sensed inundation datasets, or an approach intermediate between the two. Four major conclusions emerged from the project. First, the suite of models demonstrate extensive disagreement in their simulations of wetland areal extent and CH4 emissions, in both space and time. Simple metrics of wetland area, such as the latitudinal gradient, show large variability, principally between models that use inundation dataset information and those that independently determine wetland area. Agreement between the models improves for zonally summed CH4 emissions, but large variation between the models remains. For annual global CH4 emissions, the models vary by ±40% of the all-model mean (190 Tg CH4 yr−1). Second, all models show a strong positive response to increased atmospheric CO2 concentrations (857 ppm) in both CH4 emissions and wetland area. In response to increasing global temperatures (+3.4 °C globally spatially uniform), on average, the models decreased wetland area and CH4 fluxes, primarily in the tropics, but the magnitude and sign of the response varied greatly. Models were least sensitive to increased global precipitation (+3.9 % globally spatially uniform) with a consistent small positive response in CH4 fluxes and wetland area. Results from the 20th century transient simulation show that interactions between climate forcings could have strong non-linear effects. Third, we presently do not have sufficient wetland methane observation datasets adequate to evaluate model fluxes at a spatial scale comparable to model grid cells (commonly 0.5°). This limitation severely restricts our ability to model global wetland CH4 emissions with confidence. Our simulated wetland extents are also difficult to evaluate due to extensive disagreements between wetland mapping and remotely sensed inundation datasets. Fourth, the large range in predicted CH4 emission rates leads to the conclusion that there is both substantial parameter and structural uncertainty in large-scale CH4 emission models, even after uncertainties in wetland areas are accounted for

Present state of global wetland extent and wetland methane modelling: methodology of a model inter-comparison project (WETCHIMP)

The Wetland and Wetland CH4 Intercomparison of Models Project (WETCHIMP) was created to evaluate our present ability to simulate large-scale wetland characteristics and corresponding methane (CH4) emissions. A multi-model comparison is essential to evaluate the key uncertainties in the mechanisms and parameters leading to methane emissions. Ten modelling groups joined WETCHIMP to run eight global and two regional models with a common experimental protocol using the same climate and atmospheric carbon dioxide (CO2) forcing datasets. We reported the main conclusions from the intercomparison effort in a companion paper (Melton et al., 2013). Here we provide technical details for the six experiments, which included an equilibrium, a transient, and an optimized run plus three sensitivity experiments (temperature, precipitation, and atmospheric CO2 concentration). The diversity of approaches used by the models is summarized through a series of conceptual figures, and is used to evaluate the wide range of wetland extent and CH4 fluxes predicted by the models in the equilibrium run. We discuss relationships among the various approaches and patterns in consistencies of these model predictions. Within this group of models, there are three broad classes of methods used to estimate wetland extent: prescribed based on wetland distribution maps, prognostic relationships between hydrological states based on satellite observations, and explicit hydrological mass balances. A larger variety of approaches was used to estimate the net CH4 fluxes from wetland systems. Even though modelling of wetland extent and CH4 emissions has progressed significantly over recent decades, large uncertainties still exist when estimating CH4 emissions: there is little consensus on model structure or complexity due to knowledge gaps, different aims of the models, and the range of temporal and spatial resolutions of the models