Proxy calibration on two sedimentary sequences off Lisbon

High-resolution proxy data analyzed on two high-sedimentation shallow water sedimentary sequences (PO287-26B and PO287-28B) recovered off Lisbon (Portugal) provide the means for comparison to long-term instrumental time series of marine and atmospheric parameters (sea surface temperature (SST), precipitation, total river flow, and upwelling intensity computed from sea level pressure) and the possibility to do the necessary calibration for the quantification of past climate conditions. XRF Fe is used as proxy for river flow, and the upwelling-related diatom genus Chaetoceros is our upwelling proxy. SST is estimated from the coccolithophore-synthesized alkenones and Uk'37 index. Comparison of the Fe record to the instrumental data reveals its similarity to a mean average run of the instrumentally measured winter (JFMA) river flow on both sites. The upwelling diatom record concurs with the upwelling indices at both sites; however, high opal dissolution, below 20-25 cm, prevents its use for quantitative reconstructions. Alkenone-derived SST at site 28B does not show interannual variation; it has a mean value around 16°C and compares quite well with the instrumental winter/spring temperature. At site 26B the mean SST is the same, but a high degree of interannual variability (up to 4°C) appears to be determined by summer upwelling conditions. Stepwise regression analyses of the instrumental and proxy data sets provided regressions that explain from 65 to 94% of the variability contained in the original data, and reflect spring and summer river flow, as well as summer and winter upwelling indices, substantiating the relevance of seasons to the interpretation of the different proxy signals. The lack of analogs and the small data set available do not allow quantitative reconstructions at this time, but this might be a powerful tool for reconstructing past North Atlantic Oscillation conditions, should we be able to find continuous high-resolution records and overcome the analog problem.

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.