A Barotropic Solver for High-Resolution Ocean General Circulation Models

High-resolution global ocean general circulation models (OGCMs) play a key role in accurate ocean forecasting. However, the models of the operational forecasting systems are still not in high resolution due to the subsequent high demand for large computation, as well as the low parallel efficiency barrier. Good scalability is an important index of parallel efficiency and is still a challenge for OGCMs. We found that the communication cost in a barotropic solver, namely, the preconditioned conjugate gradient (PCG) method, is the key bottleneck for scalability due to the high frequency of the global reductions. In this work, we developed a new algorithm—a communication-avoiding Krylov subspace method with a PCG (CA-PCG)—to improve scalability and then applied it to the Nucleus for European Modelling of the Ocean (NEMO) as an example. For PCG, inner product operations with global communication were needed in every iteration, while for CA-PCG, inner product operations were only needed every eight iterations. Therefore, the global communication cost decreased from more than 94.5% of the total execution time with PCG to less than 63.4% with CA-PCG. As a result, the execution time of the barotropic modes decreased from more than 17,000 s with PCG to less than 6000 s with CA-PCG, and the total execution time decreased from more than 18,000 s with PCG to less than 6200 s with CA-PCG. Besides, the ratio of the speedup can also be increased from 3.7 to 4.6. In summary, the high process count scalability when using CA-PCG was effectively improved from that using the PCG method, providing a highly effective solution for accurate ocean simulation.

Characteristics and robustness of Agulhas Leakage estimates: an inter-comparison study of Lagrangian methods

<p>The exchange of water between the Indian Ocean and South Atlantic with their different thermohaline properties via Agulhas Leakage is important for the meridional overturning circulation. Agulhas Leakage as well as the output of ocean general circulation models in general can be analysed using a Lagrangian approach with a variety of different tools available. Here, Agulhas Leakage is estimated with both the newly developed tool Parcels and the well established tool Ariane, and different designs of the Lagrangian experiment are analysed. In a hindcast simulation with the eddy-rich ocean sea-ice model INALT20 (1/20° horizontal resolution) under the new JRA55-do forcing, Agulhas Leakage increases from the early 1960s to mid 1980s, but there is no clear trend afterwards, which is in contrast to earlier studies using hindcast simulations under the CORE forcing. During the transit from the Agulhas Current at 32°S to the Cape Basin, a cooling and freshening of Agulhas Leakage waters occurs especially in the western part of the Retroflection, resulting in a density increase as the thermal effect dominates. The average transport, its variability, trend and the transit time from the Agulhas Current to the Cape Basin of Agulhas Leakage is simulated equally with the Lagrangian tools Ariane and Parcels, emphasising the robustness of our method.</p>

Climate change effects Management with the approach of the uncertainty of Atmosphere-Ocean General Circulation Models in Hamadan Province, Iran

INTRODUCTION: Since Iran is located in the semi-arid belt, it has faced such issues as drought, dust crisis, and intensified migration. The assessment of the effects of climate change includes identifying some key aspects of uncertainties used to estimate its impacts, such as uncertainties in the context of Atmosphere-Ocean General Circulation Models (AOGCMs): in regional-scale climatology, in statistical or dynamic downscaling methods, and parametric and structural uncertainties in different models. One of the most important sources of uncertainty in climate change is the use of different AOGCMs that produce different outputs for climate variables. METHODS: In this study, to investigate the uncertainty of AOGCM models, the downscaled data of the NASA Earth Exchange Global Daily Downscaled Projections dataset obtained from 21 AOGCMs with medium Representative Concentration Pathway4.5 scenario were downloaded from the NASA site for 81 cells in Hamadan Province, Iran. After the validation of the models, they were evaluated against the criteria of the coefficient of determination and model efficiency coefficient in comparison with the data of the Hamedan synoptic station in the statistical period of 1976-2005. To reduce the uncertainty of AOGCMs, the ensemble performance (EP) of models was used in Climate Data Operators software. FINDINGS: It was revealed that MRI-CGCM3, MPI-ESM-LR, BNU-ESM, ACCESS1-0, MIROC-ESM, MIROC-ESM-CHEM, and MPI-ESM-MR models had better performance than similar models. It was also found that IPSL-CM5A-LR, CNRM-CM5, CSIRO-Mk3-6-0, CESM1-BGC, and GFDL-ESM2M had the lowest correlation between observational and simulation data of mean monthly precipitation. CONCLUSION: According to the results, this method could provide a good estimate in the base period (1976-2005), compared to the data of the Hamedan synoptic station, and was more accurate compared to the single implementation method of each AOGCM model. The results of EP of models in the future period (2020-2049) showed that precipitation will not change considerably in the future and will increase by 0.23 mm. In addition, the average, maximum, and minimum annual temperatures will increase by 1.54°C, 1.7°C, and 1.40°C, respectively.

Visualizador dinámico de modelos climáticos numéricos en México, basado en estructuras de datos NetCDF

Para enfrentar el cambio y variabilidad climáticas, las instituciones públicas necesitan el manejo de información científica sustentada en una gran cantidad de observaciones confiables, y a la vez una estrategia de comunicación para permitir la utilización de la información por sectores claves de la sociedad. Presentamos la visualización cartográfica dinámica de imágenes diarias de variables climáticas básicas (precipitación, temperatura mínima, temperatura máxima) adaptadas de los modelos numéricos “Atmosphere Ocean General Circulation Models” (AOGCM). La estructura NetCDF (“cubo de datos”) permitió una alta escalabilidad en cuanto a la conformación de series temporales, su visualización y su descarga. Esta plataforma fue aceptada por el INEGI para estar incorporada en el Mapa Digital de México.

On the future role of the most parsimonious climate module in integrated assessment

In the following, we test the validity of a one-box climate model as an emulator for atmosphere–ocean general circulation models (AOGCMs). The one-box climate model is currently employed in the integrated assessment models FUND, MIND, and PAGE, widely used in policy making. Our findings are twofold. Firstly, when directly prescribing AOGCMs' respective equilibrium climate sensitivities (ECSs) and transient climate responses (TCRs) to the one-box model, global mean temperature (GMT) projections are generically too high by 0.5 K at peak temperature for peak-and-decline forcing scenarios, resulting in a maximum global warming of approximately 2 K. Accordingly, corresponding integrated assessment studies might tend to overestimate mitigation needs and costs. We semi-analytically explain this discrepancy as resulting from the information loss resulting from the reduction of complexity. Secondly, the one-box model offers a good emulator of these AOGCMs (accurate to within 0.1 K for Representative Concentration Pathways, RCPs, namely RCP2.6, RCP4.5, and RCP6.0), provided the AOGCM's ECS and TCR values are universally mapped onto effective one-box counterparts and a certain time horizon (on the order of the time to peak radiative forcing) is not exceeded. Results that are based on the one-box model and have already been published are still just as informative as intended by their respective authors; however, they should be reinterpreted as being influenced by a larger climate response to forcing than intended.