Katherine J. Evans

CAM-SE: A scalable spectral element dynamical core for the Community Atmosphere Model

The Community Atmosphere Model (CAM) version 5 includes a spectral element dynamical core option from NCAR’s High-Order Method Modeling Environment. It is a continuous Galerkin spectral finite-element method designed for fully unstructured quadrilateral meshes. The current configurations in CAM are based on the cubed-sphere grid. The main motivation for including a spectral element dynamical core is to improve the scalability of CAM by allowing quasi-uniform grids for the sphere that do not require polar filters. In addition, the approach provides other state-of-the-art capabilities such as improved conservation properties. Spectral elements are used for the horizontal discretization, while most other aspects of the dynamical core are a hybrid of well-tested techniques from CAM’s finite volume and global spectral dynamical core options. Here we first give an overview of the spectral element dynamical core as used in CAM. We then give scalability and performance results from CAM running with three different dynamical core options within the Community Earth System Model, using a pre-industrial time-slice configuration. We focus on high-resolution simulations, using 1/4 degree, 1/8 degree, and T341 spectral truncation horizontal grids.

Climate, environmental and socio-economic change: weighing up the balance in vector-borne disease transmission

Arguably one of the most important effects of climate change is the potential impact on human health. While this is likely to take many forms, the implications for future transmission of vector-borne diseases (VBDs), given their ongoing contribution to global disease burden, are both extremely important and highly uncertain. In part, this is owing not only to data limitations and methodological challenges when integrating climate-driven VBD models and climate change projections, but also, perhaps most crucially, to the multitude of epidemiological, ecological and socio-economic factors that drive VBD transmission, and this complexity has generated considerable debate over the past 10–15 years. In this review, we seek to elucidate current knowledge around this topic, identify key themes and uncertainties, evaluate ongoing challenges and open research questions and, crucially, offer some solutions for the field. Although many of these challenges are ubiquitous across multiple VBDs, more specific issues also arise in different vector–pathogen systems.

AMIP Simulation with the CAM4 Spectral Element Dynamical Core

AbstractThe authors evaluate the climate produced by the Community Climate System Model, version 4, running with the new spectral element atmospheric dynamical core option. The spectral element method is configured to use a cubed-sphere grid, providing quasi-uniform resolution over the sphere and increased parallel scalability and removing the need for polar filters. It uses a fourth-order accurate spatial discretization that locally conserves mass and total energy. Using the Atmosphere Model Intercomparison Project protocol, the results from the spectral element dynamical core are compared with those produced by the default finite-volume dynamical core and with observations. Even though the two dynamical cores are quite different, their simulated climates are remarkably similar. When compared with observations, both models have strengths and weaknesses but have nearly identical root-mean-square errors and the largest biases show little sensitivity to the dynamical core. The spectral element core does an ...

Progress towards accelerating HOMME on hybrid multi-core systems

The suitability of a spectral element based dynamical core (HOMME) within the Community Atmospheric Model (CAM) for GPU-based architectures is examined and initial performance results are reported. This work was done within a project to enable CAM to run at high resolution on next-generation, multi-petaflop systems. The dynamical core is the present focus because it dominates the performance profile of our target problem. HOMME enjoys good scalability due to its underlying cubed-sphere mesh with full two-dimensional decomposition and the localization of all computational work within each element. The thread blocking and code changes that allow HOMME to effectively use GPUs are described along with a rewritten vertical remapping scheme, which improves performance on both CPUs and GPUs. Validation of results in the full HOMME model is also described. We demonstrate that the most expensive kernel in the model executes more than three times faster on the GPU than the CPU. These improvements are expected to provide improved efficiency when incorporated into the full model that has been configured for the target problem. Remaining issues affecting performance include optimizing the boundary exchanges for the case of multiple spectral elements being computed on the GPU.

Accuracy Analysis of a Spectral Element Atmospheric Model Using a Fully Implicit Solution Framework

Abstract A fully implicit (FI) time integration method has been implemented into a spectral finite-element shallow-water equation model on a sphere, and it is compared to existing fully explicit leapfrog and semi-implicit methods for a suite of test cases. This experiment is designed to determine the time step sizes that minimize simulation time while maintaining sufficient accuracy for these problems. For test cases without an analytical solution from which to compare, it is demonstrated that time step sizes 30–60 times larger than the gravity wave stability limits and 6–20 times larger than the advective-scale stability limits are possible using the FI method without a loss in accuracy, depending on the problem being solved. For a steady-state test case, the FI method produces error within machine accuracy limits as with existing methods, but using an arbitrarily large time step size.

Linearity of Climate Response to Increases in Black Carbon Aerosols

AbstractThe impacts of absorbing aerosols on global climate are not completely understood. This paper presents the results of idealized experiments conducted with the Community Atmosphere Model, version 4 (CAM4), coupled to a slab ocean model (CAM4–SOM) to simulate the climate response to increases in tropospheric black carbon aerosols (BC) by direct and semidirect effects. CAM4-SOM was forced with 0, 1×, 2×, 5×, and 10× an estimate of the present day concentration of BC while maintaining the estimated present day global spatial and vertical distribution. The top-of-atmosphere (TOA) radiative forcing of BC in these experiments is positive (warming) and increases linearly as the BC burden increases. The total semidirect effect for the 1 × BC experiment is positive but becomes increasingly negative for higher BC concentrations. The global-average surface temperature response is found to be a linear function of the TOA radiative forcing. The climate sensitivity to BC from these experiments is estimated to be...

Development of a 2-D algorithm to simulate convection and phase transition efficiently

We develop a Jacobian-Free Newton-Krylov (JFNK) method for the solution of a two-dimensional convection phase change model using the incompressible Navier-Stokes equation set and enthalpy as the energy conservation variable. The SIMPLE algorithm acts as a physics-based preconditioner to JFNK. This combined algorithm is compared to solutions using SIMPLE as the main solver. Algorithm performance is assessed for two benchmark problems of phase change convection of a pure material, one melting and one freezing. The JFNK-SIMPLE method is shown to be more efficient per time step and more robust at larger time steps. Overall CPU savings of more than an order of magnitude are realized.

Intermediate frequency atmospheric disturbances: A dynamical bridge connecting western U.S. extreme precipitation with East Asian cold surges

In this study, an atmospheric river (AR) detection algorithm is developed to investigate the downstream modulation of the eastern North Pacific ARs by another weather extreme, known as the East Asian cold surge (EACS), in both reanalysis data and high-resolution global model simulations. It is shown that following the peak of an EACS, atmospheric disturbances of intermediate frequency (IF; 10–30 day period) are excited downstream. This leads to the formation of a persistent cyclonic circulation anomaly over the eastern North Pacific that dramatically enhances the AR occurrence probability and the surface precipitation over the western U.S. between 30°N and 50°N. A diagnosis of the local geopotential height tendency further confirms the essential role of IF disturbances in establishing the observed persistent anomaly. This downstream modulation effect is then examined in the two simulations of the National Center for Atmospheric Research Community Climate System Model version 4 with different horizontal resolutions (T85 and T341) for the same period (1979–2005). The connection between EACS and AR is much better captured by the T341 version of the model, mainly due to a better representation of the scale interaction and the characteristics of IF atmospheric disturbances in the higher-resolution model. The findings here suggest that faithful representations of scale interaction in a global model are critical for modeling and predicting the occurrences of hydrological extremes in the western U.S. and for understanding their potential future changes.

A case study of CUDA FORTRAN and OpenACC for an atmospheric climate kernel

Abstract The porting of a key kernel in the tracer advection routines of the Community Atmosphere Model – Spectral Element (CAM-SE) to use Graphics Processing Units (GPUs) using OpenACC is considered in comparison to an existing CUDA FORTRAN port. The development of the OpenACC kernel for GPUs was substantially simpler than that of the CUDA port. Also, OpenACC performance was about 1.5× slower than the optimized CUDA version. Particular focus is given to compiler maturity regarding OpenACC implementation for modern FORTRAN, and it is found that the Cray implementation is currently more mature than the PGI implementation. Still, for the case that ran successfully on PGI, the PGI OpenACC runtime was slightly faster than Cray. The results show encouraging performance for OpenACC implementation compared to CUDA while also exposing some issues that may be necessary before the implementations are suitable for porting all of CAM-SE. Most notable are that GPU shared memory should be used by future OpenACC implementations and that derived type support should be expanded.

Toward a science of tumor forecasting for clinical oncology.

We propose that the quantitative cancer biology community makes a concerted effort to apply lessons from weather forecasting to develop an analogous methodology for predicting and evaluating tumor growth and treatment response. Currently, the time course of tumor response is not predicted; instead, response is only assessed post hoc by physical examination or imaging methods. This fundamental practice within clinical oncology limits optimization of a treatment regimen for an individual patient, as well as to determine in real time whether the choice was in fact appropriate. This is especially frustrating at a time when a panoply of molecularly targeted therapies is available, and precision genetic or proteomic analyses of tumors are an established reality. By learning from the methods of weather and climate modeling, we submit that the forecasting power of biophysical and biomathematical modeling can be harnessed to hasten the arrival of a field of predictive oncology. With a successful methodology toward tumor forecasting, it should be possible to integrate large tumor-specific datasets of varied types and effectively defeat one cancer patient at a time.