scholarly journals Enhancing the Accessibility of Unified Modeling Systems: GFDL SHiELD v2021b in a Container

2021 ◽  
Author(s):  
Kai-Yuan Cheng ◽  
Lucas M. Harris ◽  
Yong Qiang Sun
Keyword(s):  
High Resolution ◽  
Model Development ◽  
Seasonal Prediction ◽  
Atmospheric Model ◽  
Regional Model ◽  
Easy Access ◽  
Unified Modeling ◽  
Modeling Systems ◽  
Cross Platform ◽  
Study Performance

Abstract. Container technology provides a pathway to facilitate easy access to unified modeling systems and opens opportunities for collaborative model development and interactive learning. In this paper, we present the implementation of software containers for the System for High‐resolution prediction on Earth‐to‐Local Domains (SHiELD), a unified atmospheric model for weather-to-seasonal prediction. The containerized SHiELD is cross-platform and easy to install. Flexibility of the containerized SHiELD is demonstrated as it can be configured as a global, a global-nest, and a regional model. Bitwise reproducibility is achieved on various x86 systems tested in this study. Performance and scalability of the containerized SHiELD are evaluated and discussed.

scholarly journals Multimodel Prediction Skills of the Somali and Maritime Continent Cross-Equatorial Flows

2018 ◽  
Vol 31 (6) ◽  
pp. 2445-2464 ◽  
Author(s):  
Chen Li ◽  
Jing-Jia Luo ◽  
Shuanglin Li ◽  
Harry Hendon ◽  
Oscar Alves ◽  
...  
Keyword(s):  
High Resolution ◽  
Walker Circulation ◽  
Seasonal Prediction ◽  
Atmospheric Model ◽  
Precipitation Anomaly ◽  
Boreal Summer ◽  
Maritime Continent ◽  
Anomaly Correlation Coefficient ◽  
The Difference ◽  
The Individual

Predictive skills of the Somali cross-equatorial flow (CEF) and the Maritime Continent (MC) CEF during boreal summer are assessed using three ensemble seasonal forecasting systems, including the coarse-resolution Predictive Ocean Atmospheric Model for Australia (POAMA, version 2), the intermediate-resolution Scale Interaction Experiment–Frontier Research Center for Global Change (SINTEX-F), and the high-resolution seasonal prediction version of the Australian Community Climate and Earth System Simulator (ACCESS-S1) model. Retrospective prediction results suggest that prediction of the Somali CEF is more challenging than that of the MC CEF. While both the individual models and the multimodel ensemble (MME) mean show useful skill (with the anomaly correlation coefficient being above 0.5) in predicting the MC CEF up to 5-month lead, only ACCESS-S1 and the MME can skillfully predict the Somali CEF up to 2-month lead. Encouragingly, the CEF seesaw index (defined as the difference of the two CEFs as a measure of the negative phase relation between them) can be skillfully predicted up to 4–5 months ahead by SINTEX-F, ACCESS-S1, and the MME. Among the three models, the high-resolution ACCESS-S1 model generally shows the highest skill in predicting the individual CEFs, the CEF seesaw, as well as the CEF seesaw index–related precipitation anomaly pattern in Asia and northern Australia. Consistent with the strong influence of ENSO on the CEFs, the skill in predicting the CEFs depends on the model’s ability in predicting not only the eastern Pacific SST anomaly but also the anomalous Walker circulation that brings ENSO’s influence to bear on the CEFs.

A new ensemble-based statistical methodology to verify changes in weather and climate models

2021 ◽  
Author(s):  
Christian Zeman ◽  
Christoph Schär
Keyword(s):  
Climate Models ◽  
Climate Model ◽  
Numerical Models ◽  
Hypothesis Test ◽  
Model Development ◽  
Atmospheric Model ◽  
Statistical Hypothesis ◽  
Model Parameters ◽  
Rounding Errors ◽  
Weather And Climate

<p>Since their first operational application in the 1950s, atmospheric numerical models have become essential tools in weather and climate prediction. As such, they are a constant subject to changes, thanks to advances in computer systems, numerical methods, and the ever increasing knowledge about the atmosphere of Earth. Many of the changes in today's models relate to seemingly unsuspicious modifications, associated with minor code rearrangements, changes in hardware infrastructure, or software upgrades. Such changes are meant to preserve the model formulation, yet the verification of such changes is challenged by the chaotic nature of our atmosphere - any small change, even rounding errors, can have a big impact on individual simulations. Overall this represents a serious challenge to a consistent model development and maintenance framework.</p><p>Here we propose a new methodology for quantifying and verifying the impacts of minor atmospheric model changes, or its underlying hardware/software system, by using ensemble simulations in combination with a statistical hypothesis test. The methodology can assess effects of model changes on almost any output variable over time, and can also be used with different hypothesis tests.</p><p>We present first applications of the methodology with the regional weather and climate model COSMO. The changes considered include a major system upgrade of the supercomputer used, the change from double to single precision floating-point representation, changes in the update frequency of the lateral boundary conditions, and tiny changes to selected model parameters. While providing very robust results, the methodology also shows a large sensitivity to more significant model changes, making it a good candidate for an automated tool to guarantee model consistency in the development cycle.</p>

Seasonal-to-Decadal Predictability and Prediction of North American Climate—The Atlantic Influence

2006 ◽  
Vol 19 (23) ◽  
pp. 6005-6024 ◽  
Author(s):  
H. M. Van den Dool ◽  
Peitao Peng ◽  
Åke Johansson ◽  
Muthuvel Chelliah ◽  
Amir Shabbar ◽  
...  
Keyword(s):  
North American ◽  
Seasonal Prediction ◽  
Atmospheric Model ◽  
The United States ◽  
Seasonal Forecast ◽  
Ocean Model ◽  
Prediction Skill ◽  
Basic Material ◽  
Atlantic Sector ◽  
The Impact

Abstract The question of the impact of the Atlantic on North American (NA) seasonal prediction skill and predictability is examined. Basic material is collected from the literature, a review of seasonal forecast procedures in Canada and the United States, and some fresh calculations using the NCEP–NCAR reanalysis data. The general impression is one of low predictability (due to the Atlantic) for seasonal mean surface temperature and precipitation over NA. Predictability may be slightly better in the Caribbean and the (sub)tropical Americas, even for precipitation. The NAO is widely seen as an agent making the Atlantic influence felt in NA. While the NAO is well established in most months, its prediction skill is limited. Year-round evidence for an equatorially displaced version of the NAO (named ED_NAO) carrying a good fraction of the variance is also found. In general the predictability from the Pacific is thought to dominate over that from the Atlantic sector, which explains the minimal number of reported Atmospheric Model Intercomparison Project (AMIP) runs that explore Atlantic-only impacts. Caveats are noted as to the question of the influence of a single predictor in a nonlinear environment with many predictors. Skill of a new one-tier global coupled atmosphere–ocean model system at NCEP is reviewed; limited skill is found in midlatitudes and there is modest predictability to look forward to. There are several signs of enthusiasm in the community about using “trends” (low-frequency variations): (a) seasonal forecast tools include persistence of last 10 years’ averaged anomaly (relative to the official 30-yr climatology), (b) hurricane forecasts are based largely on recognizing a global multidecadal mode (which is similar to an Atlantic trend mode in SST), and (c) two recent papers, one empirical and one modeling, giving equal roles to the (North) Pacific and Atlantic in “explaining” variations in drought frequency over NA on a 20 yr or longer time scale during the twentieth century.

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