The Arctic has experienced much greater warming than the global average in recent decades. Current climate models project that this Arctic warming trend will continue in this century. At present, one quarter of its land is underlain with permafrost and contains a large amount of vulnerable carbon.
Extensive seasonal biomass burning over southern Africa results in the transport of massive amounts of smoke aerosols over the adjacent Atlantic Ocean. These aerosols are of increasing interest due to their strong absorption of incoming solar radiation and the associated impact on the regional energy budget and the atmosphere thermodynamical structure. Interactions between the overlying smoke aerosols and low-level cloud microphysics and the subsequent albedo perturbation are, however, generally ignored in biomass burning radiative assessments.
Accurate prediction of high resolution (1-10 km) regional convection and rainfall is vital for a wide variety of meteorological applications. To improve the understanding and the model simulation of the regional convection and precipitation, a three-pronged strategy was undertaken. This include studying the impacts of heterogeneous land surface, (ii) land-atmosphere surface coupling strength, and (iii) an improvement to the Kain-Fritsch (KF) convective parameterization scheme (CPS), on short-term precipitation forecasting using the Weather Research and Forecasting (WRF) model.
As our values evolve and the world changes, we sometimes face problems of increasing complexity where status quo solutions are no longer acceptable or applicable. Computational and geospatial models provide an opportunity to investigate new ideas amidst an uncertain future, and to help us more fully understand potential effects and explore alternative solutions.
The spatial heterogeneity of land surface affects energy, moisture, and greenhouse gas exchanges with the atmosphere. However, representing heterogeneity of terrestrial hydrological and biogeochemical processes in earth system models remains a critical scientific challenge.
There is wide consensus among scientific community that anthropogenic greenhouse gases are changing global climate, and those changes may involve not only changes in climatic means but also in extremes. It is thus of great interest to determine how the tail behavior of temperature may be affected by increased atmospheric CO2 concentrations. However, this inquiry is complicated by the fact that the observational data records are not adequate to robustly detect possible changes in this behavior that may have already occurred.
The Nordic countries have a long tradition of networking weather radar data in a de-centralized manner, and also having a common system with which data are processed locally in real time according to each organization's needs. The legacy collaboration is called NORDRAD. Using funding from the EU's Baltic Sea Region (BSR) programme, this Nordic concept was extended to the whole BSR through two projects, BALTRAD and BALTRAD+, which were carried out 2009-2014. This presentation will outline the BALTRAD and BALTRAD+ projects, what was achieved technically, scientifically and politically, and it will give an outlook for the coming years.
In an environment of rising energy consumption and a setting of climate change, our challenge as concerned scientists is to be proactive during a period of rapid renewable energy expansion in order to reduce global biodiversity loss from high magnitude warming and address the potential for harm to animal and plant populations.
The vast amount of organic carbon stored in soils of the northern circumpolar permafrost region is a potentially vulnerable component of the global carbon cycle. Yet, estimates of the quantity, decomposability, and combustibility of the carbon contained in permafrost-region soils remain highly uncertain, limiting our ability to predict the release of greenhouse gases due to permafrost thawing.
Nearly 80% of all structural failures are due to mechanical fatigue, which often results in catastrophic, dangerous, and costly failure events. However, a comprehensive model to predict fatigue remains an elusive goal. One of the major challenges is that fatigue is intrinsically a multiscale process that is dependent on the macroscale geometry (i.e., shape) of a device as well as its microscale structural features (e.g., the non-metallic inclusions, crystal grains, or voids found in metal alloys). The presented work will develop a novel multiscale method for fatigue prediction by simulating macroscale geometries explicitly while concurrently calculating the simplified local response of microscale inclusions.
The Geospatial Research Laboratory (GRL) providers the warfighter and Nation with superior knowledge of the battlefield through innovative basic and applied research in geospatial and related sciences.
GRL conducts geospatial research, development, technology and evaluation of current and emerging geospatial technologies that will help characterize and measure phenomena within the physical (terrain) and social (cultural) environment encountered by the Army.
A transient Mixing Cell Model (MCM) was developed for assessing groundwater fluxes in complex hydro-geological basins prevailing transient groundwater flow system. It is aimed for complex systems with vague sub-aquifer structure, lack of hydro-geological information.