7 resultados para environmental modeling
em Publishing Network for Geoscientific
Resumo:
Topographic variation, the spatial variation in elevation and terrain features, underpins a myriad of patterns and processes in geography and ecology and is key to understanding the variation of life on the planet. The characterization of this variation is scale-dependent, i.e. it varies with the distance over which features are assessed and with the spatial grain (grid cell resolution) of analysis. A fully standardized and global multivariate product of different terrain features has the potential to support many large-scale basic research and analytical applications, however to date, such technique is unavailable. Here we used the digital elevation model products of global 250 m GMTED and near-global 90 m SRTM to derive a suite of topographic variables: elevation, slope, aspect, eastness, northness, roughness, terrain roughness index, topographic position index, vector ruggedness measure, profile and tangential curvature, and 10 geomorphological landform classes. We aggregated each variable to 1, 5, 10, 50 and 100 km spatial grains using several aggregation approaches (median, average, minimum, maximum, standard deviation, percent cover, count, majority, Shannon Index, entropy, uniformity). While a global cross-correlation underlines the high similarity of many variables, a more detailed view in four mountain regions reveals local differences, as well as scale variations in the aggregated variables at different spatial grains. All newly-developed variables are available for download at http://www.earthenv.org and can serve as a basis for standardized hydrological, environmental and biodiversity modeling at a global extent.
Resumo:
To understand the validity of d18O proxy records as indicators of past temperature change, a series of experiments was conducted using an atmospheric general circulation model fitted with water isotope tracers (Community Atmosphere Model version 3.0, IsoCAM). A pre-industrial simulation was performed as the control experiment, as well as a simulation with all the boundary conditions set to Last Glacial Maximum (LGM) values. Results from the pre-industrial and LGM simulations were compared to experiments in which the influence of individual boundary conditions (greenhouse gases, ice sheet albedo and topography, sea surface temperature (SST), and orbital parameters) were changed each at a time to assess their individual impact. The experiments were designed in order to analyze the spatial variations of the oxygen isotopic composition of precipitation (d18Oprecip) in response to individual climate factors. The change in topography (due to the change in land ice cover) played a significant role in reducing the surface temperature and d18Oprecip over North America. Exposed shelf areas and the ice sheet albedo reduced the Northern Hemisphere surface temperature and d18Oprecip further. A global mean cooling of 4.1 °C was simulated with combined LGM boundary conditions compared to the control simulation, which was in agreement with previous experiments using the fully coupled Community Climate System Model (CCSM3). Large reductions in d18Oprecip over the LGM ice sheets were strongly linked to the temperature decrease over them. The SST and ice sheet topography changes were responsible for most of the changes in the climate and hence the d18Oprecip distribution among the simulations.
Resumo:
A critical problem in radiocarbon dating is the spatial and temporal variability of marine reservoir ages (MRAs). We assessed the MRA evolution during the last deglaciation by numerical modeling, applying a self-consistent iteration scheme in which an existing radiocarbon chronology (derived by Hughen et al., Quat. Sci. Rev., 25, pp. 3216-3227, 2006) was readjusted by transient, 3-D simulations of marine and atmospheric Delta14C. To estimate the uncertainties regarding the ocean ventilation during the last deglaciation, we considered various ocean overturning scenarios which are based on different climatic background states (PD: modern climate, GS: LGM climate conditions). Minimum and maximum MRAs are included in file 'MRAminmax_21-14kaBP.nc'. Three further files include MRAs according to equilibrium simulations of the preindustrial ocean (file 'C14age_preindustrial.nc'; this is an update of our results published in 2005) and of the glacial ocean (files 'C14age_spinupLGM_GS.nc' and 'C14age_spinupLGM_PD.nc').
Resumo:
Fossil shells of planktonic foraminifera serve as the prime source of information on past changes in surface ocean conditions. Because the population size of planktonic foraminifera species changes throughout the year, the signal preserved in fossil shells is biased towards the conditions when species production was at its maximum. The amplitude of the potential seasonal bias is a function of the magnitude of the seasonal cycle in production. Here we use a planktonic foraminifera model coupled to an ecosystem model to investigate to what degree seasonal variations in production of the species Neogloboquadrina pachyderma may affect paleoceanographic reconstructions during Heinrich Stadial 1 (~18-15 cal. ka B.P.) in the North Atlantic Ocean. The model implies that during Heinrich Stadial 1 the maximum seasonal production occurred later in the year compared to the Last Glacial Maximum (~21-19 cal. ka B.P.) and the pre-industrial era north of 30 ºN. A diagnosis of the model output indicates that this change reflects the sensitivity of the species to the seasonal cycle of sea-ice cover and food supply, which collectively lead to shifts in the modeled maximum production from the Last Glacial Maximum to Heinrich Stadial 1 by up to six months. Assuming equilibrium oxygen isotopic incorporation in the shells of N. pachyderma, the modeled changes in seasonality would result in an underestimation of the actual magnitude of the meltwater isotopic signal recorded by fossil assemblages of N. pachyderma wherever calcification is likely to take place.