Northern Eurasia Future Initiative (NEFI): facing the challenges and pathways of global change in the 21st century

During the past several decades, the Earth system has changed significantly, especially across Northern Eurasia. Changes in the socio-economic conditions of the larger countries in the region have also resulted in a variety of regional environmental changes that can have global consequences. The Northern Eurasia Future Initiative (NEFI) has been designed as an essential continuation of the Northern Eurasia Earth Science Partnership Initiative (NEESPI), which was launched in 2004. NEESPI sought to elucidate all aspects of ongoing environmental change, to inform societies and, thus, to better prepare societies for future developments. A key principle of NEFI is that these developments must now be secured through science-based strategies co-designed with regional decision makers to lead their societies to prosperity in the face of environmental and institutional challenges. NEESPI scientific research, data, and models have created a solid knowledge base to support the NEFI program. This paper presents the NEFI research vision consensus based on that knowledge. It provides the reader with samples of recent accomplishments in regional studies and formulates new NEFI science questions. To address these questions, nine research foci are identified and their selections are briefly justified. These foci include: warming of the Arctic; changing frequency, pattern, and intensity of extreme and inclement environmental conditions; retreat of the cryosphere; changes in terrestrial water cycles; changes in the biosphere; pressures on land-use; changes in infrastructure; societal actions in response to environmental change; and quantification of Northern Eurasia's role in the global Earth system. Powerful feedbacks between the Earth and human systems in Northern Eurasia (e.g., mega-fires, droughts, depletion of the cryosphere essential for water supply, retreat of sea ice) result from past and current human activities (e.g., large scale water withdrawals, land use and governance change) and potentially restrict or provide new opportunities for future human activities. Therefore, we propose that Integrated Assessment Models are needed as the final stage of global change assessment. The overarching goal of this NEFI modeling effort will enable evaluation of economic decisions in response to changing environmental conditions and justification of mitigation and adaptation efforts

Parallel Algorithms for Semi-Lagrangian Advection

Numerical time-step limitations associated with the explicit treatment of advection-dominated problems in computational fluid dynamics are often relaxed by employing Eulerian-Lagrangian methods. These are also known as semi-Lagrangian methods in the atmospheric sciences. Such methods involve backward time integration of a characteristic equation to find the departure point of a fluid particle arriving at an Eulerian grid point. The value of an advected field at the departure point is obtained by interpolation. Both the trajectory integration and repeated interpolation influence accuracy. We compare the accuracy and performance of interpolation schemes based on piecewise cubic polynomials and cubic B-splines in the context of a distributed-memory, parallel computing environment. The computational cost and inter-processor communication requirements for both methods are reported. Spline interpolation has better conservation properties but requires the solution of a global linear system, i..

A New Dynamics Kernel For The MC2 Model II: Flexible GMRES Elliptic Solver

The Mesoscale Compressible Community (MC2) model is an extension of a fully compressible limited area model developed by Monique Tanguay, Andre Robert and Rene Laprise in the mid-1980's. The model employs a three-time-level semi-implicit, semi-Lagrangian time discretisation with modified terrain following Gal-Chen coordinates. The semi-implicit scheme results in an elliptic boundary value problem with first-order derivative terms in the vertical direction and thus the resulting discretised system of equations has a large sparse nonsymmetric coefficient matrix. To build a massively parallel implemenation of the model, the original alternating direction implicit (ADI) elliptic solver has been replaced with a flexible Generalised Minimum Residual (GMRES) Krylov method with variable preconditioning. We report on the performance of successive over relaxation (SOR) and vertical line relaxation (ADI) as preconditioners to improve the convergence rate of GMRES. A meteorological comparison base..

Shared And Distributed Memory Implementations Of The Canadian MC2 Model

The Mesoscale Compressible Community (MC2) model is an extension of a fully compressible limited area model developed by Monique Tanguay, Andre Robert and Rene Laprise in the mid-1980's. The model employs a three-timelevel semi-implicit, semi-Lagrangian time discretisation with modified terrain following Gal-Chen coordinates. The semi-implicit scheme results in an elliptic boundary value problem with first-order derivative terms in the vertical direction and thus the resulting discretised system of equations has a large sparse nonsymmetric coefficient matrix. The original alternating direction implicit (ADI) elliptic solver has been replaced with a flexible Generalised Minimum Residual (GMRES) Krylov method with variable preconditioning. We report on the performance of successive over relaxation (SOR) and vertical line relaxation (ADI) as parallel preconditioners to improve the convergence rate of GMRES. Parallelisation of the model for a distributed-memory computing environment has be..