Pollen abundances, and temperature and precipitation reconstruction for the Eocene to Oligocene transition in northern high latitudes

A profound global climate shift took place at the Eocene-Oligocene transition (~33.5 million years ago) when Cretaceous/early Palaeogene greenhouse conditions gave way to icehouse conditions (Zachos et al., 2001, doi:10.1126/science.1059412; Coxall et al., 2005, doi:10.1038/nature03135; Lear et al., 2008, doi:10.1130/G24584A.1). During this interval, changes in the Earth's orbit and a long-term drop in atmospheric carbon dioxide concentrations (Pagani et al., 2005, doi:10.1126/science.1110063; Pearson and Palmer, 2000, doi:10.1038/35021000; DeConto and Pollard, 2003, doi:10.1038/nature01290) resulted in both the growth of Antarctic ice sheets to approximately their modern size (Coxall et al., 2005, doi:10.1038/nature03135; Lear et al., 2008, doi:10.1130/G24584A.1) and the appearance of Northern Hemisphere glacial ice (Eldrett et al., 2007, doi:10.1038/nature05591; Moran et al., 2006, doi:10.1038/nature04800). However, palaeoclimatic studies of this interval are contradictory: although some analyses indicate no major climatic changes (Kohn et al., 2004, doi:10.1130/G20442.1; Grimes et al., 2005, doi:10.1130/G21019.1), others imply cooler temperatures (Zanazzi et al., 2007, doi:10.1038/nature05551), increased seasonality (Ivany et al., 2000, doi:10.1038/35038044; Terry, 2001, doi:10.1016/S0031-0182(00)00248-0) and/or aridity (Ivany et al., 2000, doi:10.1038/35038044; Terry, 2001, doi:10.1016/S0031-0182(00)00248-0; Sheldon et al., 2002, doi:10.1086/342865; Dupont-Nivet et al., 2007, doi:10.1038/nature05516). Climatic conditions in high northern latitudes over this interval are particularly poorly known. Here we present northern high-latitude terrestrial climate estimates for the Eocene to Oligocene interval, based on bioclimatic analysis of terrestrially derived spore and pollen assemblages preserved in marine sediments from the Norwegian-Greenland Sea. Our data indicate a cooling of ~5 °C in cold-month (winter) mean temperatures to 0-2 °C, and a concomitant increased seasonality before the Oi-1 glaciation event. These data indicate that a cooling component is indeed incorporated in the d18O isotope shift across the Eocene-Oligocene transition. However, the relatively warm summer temperatures at that time mean that continental ice on East Greenland was probably restricted to alpine outlet glaciers.

High-resolution dynamical downscaling products for the North Slope of Alaska and surrounding areas, links to model result files

Climatic changes are most pronounced in northern high latitude regions. Yet, there is a paucity of observational data, both spatially and temporally, such that regional-scale dynamics are not fully captured, limiting our ability to make reliable projections. In this study, a group of dynamical downscaling products were created for the period 1950 to 2100 to better understand climate change and its impacts on hydrology, permafrost, and ecosystems at a resolution suitable for northern Alaska. An ERA-interim reanalysis dataset and the Community Earth System Model (CESM) served as the forcing mechanisms in this dynamical downscaling framework, and the Weather Research & Forecast (WRF) model, embedded with an optimization for the Arctic (Polar WRF), served as the Regional Climate Model (RCM). This downscaled output consists of multiple climatic variables (precipitation, temperature, wind speed, dew point temperature, and surface air pressure) for a 10 km grid spacing at three-hour intervals. The modeling products were evaluated and calibrated using a bias-correction approach. The ERA-interim forced WRF (ERA-WRF) produced reasonable climatic variables as a result, yielding a more closely correlated temperature field than precipitation field when long-term monthly climatology was compared with its forcing and observational data. A linear scaling method then further corrected the bias, based on ERA-interim monthly climatology, and bias-corrected ERA-WRF fields were applied as a reference for calibration of both the historical and the projected CESM forced WRF (CESM-WRF) products. Biases, such as, a cold temperature bias during summer and a warm temperature bias during winter as well as a wet bias for annual precipitation that CESM holds over northern Alaska persisted in CESM-WRF runs. The linear scaling of CESM-WRF eventually produced high-resolution downscaling products for the Alaskan North Slope for hydrological and ecological research, together with the calibrated ERA-WRF run, and its capability extends far beyond that. Other climatic research has been proposed, including exploration of historical and projected climatic extreme events and their possible connections to low-frequency sea-atmospheric oscillations, as well as near-surface permafrost degradation and ice regime shifts of lakes. These dynamically downscaled, bias corrected climatic datasets provide improved spatial and temporal resolution data necessary for ongoing modeling efforts in northern Alaska focused on reconstructing and projecting hydrologic changes, ecosystem processes and responses, and permafrost thermal regimes. The dynamical downscaling methods presented in this study can also be used to create more suitable model input datasets for other sub-regions of the Arctic.

(Figure 2) Mean discharge per day (total and baseflow part) of the San Francisco River and daily precipitation at station ECPL (Planta), in 2007

We investigated controls on the water chemistry of a South Ecuadorian cloud forest catchment which is partly pristine, and partly converted to extensive pasture. From April 2007 to May 2008 water samples were taken weekly to biweekly at nine different subcatchments, and were screened for differences in electric conductivity, pH, anion, as well as element composition. A principal component analysis was conducted to reduce dimensionality of the data set and define major factors explaining variation in the data. Three main factors were isolated by a subset of 10 elements (Ca2+, Ce, Gd, K+, Mg2+, Na+, Nd, Rb, Sr, Y), explaining around 90% of the data variation. Land-use was the major factor controlling and changing water chemistry of the subcatchments. A second factor was associated with the concentration of rare earth elements in water, presumably highlighting other anthropogenic influences such as gravel excavation or road construction. Around 12% of the variation was explained by the third component, which was defined by the occurrence of Rb and K and represents the influence of vegetation dynamics on element accumulation and wash-out. Comparison of base- and fast flow concentrations led to the assumption that a significant portion of soil water from around 30 cm depth contributes to storm flow, as revealed by increased rare earth element concentrations in fast flow samples. Our findings demonstrate the utility of multi-tracer principal component analysis to study tropical headwater streams, and emphasize the need for effective land management in cloud forest catchments.