M. Collins | Geology Reports

USGS2013

A computational- And storage-cloud for integration of biodiversity collections

A core mission of the Integrated Digitized Biocollections (iDigBio) project is the building and deployment of a cloud computing environment customized to support the digitization workflow and integration of data from all U.S. nonfederal biocollections. iDigBio chose to use cloud computing technologies to deliver a cyberinfrastructure that is flexible, agile, resilient, and scalable to meet the needs of the biodiversity community. In this context, this paper describes the integration of open source cloud middleware, applications, and third party services using standard formats, protocols, and services. In addition, this paper demonstrates the value of the digitized information from collections in a broader scenario involving multiple disciplines.

Conference Paper↗

USGS2011

Quantifying Uncertainty in Model Predictions for the Pliocene (Plio-QUMP): Initial results

Examination of the mid-Pliocene Warm Period (mPWP; ~ 3.3 to 3.0 Ma BP) provides an excellent opportunity to test the ability of climate models to reproduce warm climate states, thereby assessing our confidence in model predictions. To do this it is necessary to relate the uncertainty in model simulations of mPWP climate to uncertainties in projections of future climate change. The uncertainties introduced by the model can be estimated through the use of a Perturbed Physics Ensemble (PPE). Developing on the UK Met Office Quantifying Uncertainty in Model Predictions (QUMP) Project, this paper presents the results from an initial investigation using the end members of a PPE in a fully coupled atmosphere–ocean model (HadCM3) running with appropriate mPWP boundary conditions. Prior work has shown that the unperturbed version of HadCM3 may underestimate mPWP sea surface temperatures at higher latitudes . Initial results indicate that neither the low sensitivity nor the high sensitivity simulations produce unequivocally improved mPWP climatology relative to the standard. Whilst the high sensitivity simulation was able to reconcile up to 6 °C of the data/model mismatch in sea surface temperatures in the high latitudes of the Northern Hemisphere (relative to the standard simulation), it did not produce a better prediction of global vegetation than the standard simulation. Overall the low sensitivity simulation was degraded compared to the standard and high sensitivity simulations in all aspects of the data/model comparison. The results have shown that a PPE has the potential to explore weaknesses in mPWP modelling simulations which have been identified by geological proxies, but that a ‘best fit’ simulation will more likely come from a full ensemble in which simulations that contain the strengths of the two end member simulations shown here are combined.

Palaeogeography, Palaeoclimatology, Palaeoecology↗