ESD climate scientists Jinyun Tang and Bill Riley have developed a climate model that quantifies interactions between soil microbes and their surroundings.
Using some of the most powerful supercomputers now available, a team of Lawrence Berkeley National Laboratory (Berkeley Lab) climate scientists headed by Michael Wehner (and including ESD Climate Science Head Bill Collins) was able to complete a run a high resolution global-climate-model simulation in just three months.
ESD’s David Romps recently led a team of climate scientists in looking at predictions of cloud buoyancy in 11 different climate models—the combined effect of which (they concluded) will generate more frequent lightning strikes.
ESD’s Giovanni Birarda and others recently investigated the microbiome relatedness of subsurface biofilms within two sulfidic springs in Germany—the results of which provide insight into the dynamics of subsurface microbial life.
ESD’s Dan Feldman and Bill Collins have identified a mechanism that could turn out to be a big contributor to warming in the Arctic region and melting sea ice—in the far infrared region of the electromagnetic spectrum.
ESD’s Jie Niu helped to quantify water-budget components and storage changes for two of the largest watersheds in Michigan, using remotely sensed data and a process-based hydrologic model representing subsurface and land surface processes.
Website Teaser: Ken Williams and Phil Long were part of a team that recently compared two types of organic-rich sediments to better understand uranium release mechanisms at contaminated sites.
ESD’s Harry Beller, Peter Nico, and colleagues studied chromate bioremediation and found that the bulk redox status and biogeochemical regime do not necessarily control the final product of Cr(VI) reduction.
ESD’s Javier Ceja-Navarro and others have characterized the gut microbiome of a wood-feeding beetle native to the eastern US, finding in its gut a metabolic capability permitting both aerobic and anaerobic activity, as well as N2 fixation.
Daniele Rosa and Bill Collins compared precipitation data from Southeastern U.S. rain-gauge measurements with GCMs, finding that GCMs overestimate the impact of medium rainfall while underestimating the impact of no, low, or heavy rain.