Three dimensional adaptive mesh refinement on a spherical shell for atmospheric models with lagrangian coordinates

One of the most important advances needed in global climate models is the development of atmospheric General Circulation Models (GCMs) that can reliably treat convection. Such GCMs require high resolution in local convectively active regions, both in the horizontal and vertical directions. During previous research we have developed an Adaptive Mesh Refinement (AMR) dynamical core that can adapt its grid resolution horizontally. Our approach utilizes a finite volume numerical representation of the partial differential equations with floating Lagrangian vertical coordinates and requires resolving dynamical processes on small spatial scales. For the latter it uses a newly developed general-purpose library, which facilitates 3D block-structured AMR on spherical grids. The library manages neighbor information as the blocks adapt, and handles the parallel communication and load balancing, freeing the user to concentrate on the scientific modeling aspects of their code. In particular, this library defines and manages adaptive blocks on the sphere, provides user interfaces for interpolation routines and supports the communication and load-balancing aspects for parallel applications. We have successfully tested the library in a 2-D (longitude-latitude) implementation. During the past year, we have extended the library to treat adaptive mesh refinement in the vertical direction. Preliminary results are discussed. This research project is characterized by an interdisciplinary approach involving atmospheric science, computer science and mathematical/numerical aspects. The work is done in close collaboration between the Atmospheric Science, Computer Science and Aerospace Engineering Departments at the University of Michigan and NOAA GFDL.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/58181/2/jpconf7_78_012072.pd

Combustibility of biomass from wet fens in Belarus and its potential as a substitute for peat in fuel briquettes

Peatland drainage has caused enormous environmental problems at global scale; in particular, ongoing greenhouse gas emissions and soil degradation. In Belarus, which is rich in peatlands and a hotspot of emissions from drained peatlands, several thousand hectares have already been re-wetted but are not used productively. Moreover, vast areas of wet (undrained) peatland that are designated for nature conservation are in need of mowing and biomass removal. Plants such as common reed (Phragmites australis), reed canary grass (Phalaris arundinacea) and sedges (Carex spp.) which frequently dominate these areas could be harvested and used as fuel, potentially as a substitute for peat. In this study we analysed the yield and combustibility of late harvests in March/April 2009 and 2010. The yields of 3.7–11.7 t DM ha-1 were within the range reported from other studies on wetland plants. Concentrations of Cl, S, N, P, C, Ca, K, Mg and Na, as well as water and ash contents, indicated similar or better combustibility when compared to other straw-like (graminaceous) plants such as Miscanthus. The full replacement of peat fuel by biomass from wet peatlands in Belarus would require an area of 680,000 ha, i.e. 'only' half of the peatland that has been drained for agriculture

Development of an atmospheric climate model with self-adapting grid and physics

An adaptive grid dynamical core for a global atmospheric climate model has been developed. Adaptations allow a smooth transition from hydrostatic to non-hydrostatic physics at small resolution. The adaptations use a parallel program library for block-wise adaptive grids on the sphere. This library also supports the use of a reduced grid with coarser resolution in the longitudinal direction as the poles are approached. This permits the use of a longer time step since the CFL number restriction (CFL < 1) in a regular longitude-latitude grid is most severe in the zonal direction at high latitudes. Several tests show that our modelling procedures are stable and accurate.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/49004/2/jpconf5_16_049.pd

The Earth System Prediction Suite: Toward a Coordinated U.S. Modeling Capability

The Earth System Prediction Suite (ESPS) is a collection of flagship U.S. weather and climate models and model components that are being instrumented to conform to interoperability conventions, documented to follow metadata standards, and made available either under open source terms or to credentialed users.The ESPS represents a culmination of efforts to create a common Earth system model architecture, and the advent of increasingly coordinated model development activities in the U.S. ESPS component interfaces are based on the Earth System Modeling Framework (ESMF), community-developed software for building and coupling models, and the National Unified Operational Prediction Capability (NUOPC) Layer, a set of ESMF-based component templates and interoperability conventions. This shared infrastructure simplifies the process of model coupling by guaranteeing that components conform to a set of technical and semantic behaviors. The ESPS encourages distributed, multi-agency development of coupled modeling systems, controlled experimentation and testing, and exploration of novel model configurations, such as those motivated by research involving managed and interactive ensembles. ESPS codes include the Navy Global Environmental Model (NavGEM), HYbrid Coordinate Ocean Model (HYCOM), and Coupled Ocean Atmosphere Mesoscale Prediction System (COAMPS); the NOAA Environmental Modeling System (NEMS) and the Modular Ocean Model (MOM); the Community Earth System Model (CESM); and the NASA ModelE climate model and GEOS-5 atmospheric general circulation model