Potentially dangerous consequences for biodiversity of solar geoengineering implementation and termination.

Solar geoengineering is receiving increased policy attention as a potential tool to offset climate warming. While climate responses to geoengineering have been studied in detail, the potential biodiversity consequences are largely unknown. To avoid extinction, species must either adapt or move to track shifting climates. Here, we assess the effects of the rapid implementation, continuation and sudden termination of geoengineering on climate velocities-the speeds and directions that species would need to move to track changes in climate. Compared to a moderate climate change scenario (RCP4.5), rapid geoengineering implementation reduces temperature velocities towards zero in terrestrial biodiversity hotspots. In contrast, sudden termination increases both ocean and land temperature velocities to unprecedented speeds (global medians >10 km yr-1) that are more than double the temperature velocities for recent and future climate change in global biodiversity hotspots. Furthermore, as climate velocities more than double in speed, rapid climate fragmentation occurs in biomes such as temperate grasslands and forests where temperature and precipitation velocity vectors diverge spatially by >90°. Rapid geoengineering termination would significantly increase the threats to biodiversity from climate change.

An efficient multistage algorithm for full calibration of the hemodynamic model from BOLD signal responses.

We propose a computational strategy that falls into the category of prediction/correction iterative-type approaches, for calibrating the hemodynamic model. The proposed method is used to estimate consecutively the values of the two sets of model parameters. Numerical results corresponding to both synthetic and real functional magnetic resonance imaging measurements for a single stimulus as well as for multiple stimuli are reported to highlight the capability of this computational methodology to fully calibrate the considered hemodynamic model.

Northern Hemisphere Winter Warming and Summer Monsoon Reduction after Volcanic Eruptions over the Last Millennium.

Observations show that all recent large tropical volcanic eruptions (1850-present) were followed by surface winter warming in the first Northern Hemisphere (NH) winter after the eruption. Recent studies show that climate models produce a surface winter warming response in the first winter after the largest eruptions, but require a large ensemble of simulations to see significant changes. It is also generally required that the eruption be very large, and only two such eruptions occurred in the historical period: Krakatau in 1883 and Pinatubo in 1991. Here we examine surface winter warming patterns after the 10 largest volcanic eruptions between 850 and 1850 in the Paleoclimate Modeling Intercomparison Project 3 last millennium simulations and in the Community Earth System Model Last Millennium Ensemble. These eruptions were all larger than those since 1850. Though the results depend on both the individual models and the forcing data set used, we have found that models produce a surface winter warming signal in the first winter after large volcanic eruptions, with higher temperatures over NH continents and a stronger polar vortex in the lower stratosphere. We also examined NH summer precipitation responses in the first year after the eruptions, and find clear reductions of summer Asian and African monsoon rainfall.

Efficient solution methodology for calibrating the hemodynamic model using functional Magnetic Resonance Imaging (fMRI) measurements.

Our aim is to propose a numerical strategy for retrieving accurately and efficiently the biophysiological parameters as well as the external stimulus characteristics corresponding to the hemodynamic mathematical model that describes changes in blood flow and blood oxygenation during brain activation. The proposed method employs the TNM-CKF method developed in [1], but in a prediction/correction framework. We present numerical results using both real and synthetic functional Magnetic Resonance Imaging (fMRI) measurements to highlight the performance characteristics of this computational methodology.