Zhenya Song

The Flexible Global Ocean-Atmosphere-Land System Model, Grid-point Version 2：FGOALS-g2

This study mainly introduces the development of the Flexible Global Ocean-Atmosphere-Land System Model: Grid-point Version 2 (FGOALS-g2) and the preliminary evaluations of its performances based on results from the pre-industrial control run and four members of historical runs according to the fifth phase of the Coupled Model Intercomparison Project (CMIP5) experiment design. The results suggest that many obvious improvements have been achieved by the FGOALS-g2 compared with the previous version,FGOALS-g1, including its climatological mean states, climate variability, and 20th century surface temperature evolution. For example,FGOALS-g2 better simulates the frequency of tropical land precipitation, East Asian Monsoon precipitation and its seasonal cycle, MJO and ENSO, which are closely related to the updated cumulus parameterization scheme, as well as the alleviation of uncertainties in some key parameters in shallow and deep convection schemes, cloud fraction, cloud macro/microphysical processes and the boundary layer scheme in its atmospheric model. The annual cycle of sea surface temperature along the equator in the Pacific is significantly improved in the new version. The sea ice salinity simulation is one of the unique characteristics of FGOALS-g2, although it is somehow inconsistent with empirical observations in the Antarctic.

The Flexible Global Ocean-Atmosphere-Land system model, Spectral Version 2: FGOALS-s2

The Flexible Global Ocean-Atmosphere-Land System model, Spectral Version 2 (FGOALS-s2) was used to simulate realistic climates and to study anthropogenic influences on climate change. Specifically, the FGOALS-s2 was integrated with Coupled Model Intercomparison Project Phase 5 (CMIP5) to conduct coordinated experiments that will provide valuable scientific information to climate research communities. The performances of FGOALS-s2 were assessed in simulating major climate phenomena, and documented both the strengths and weaknesses of the model. The results indicate that FGOALS-s2 successfully overcomes climate drift, and realistically models global and regional climate characteristics, including SST, precipitation, and atmospheric circulation. In particular, the model accurately captures annual and semi-annual SST cycles in the equatorial Pacific Ocean, and the main characteristic features of the Asian summer monsoon, which include a low-level southwestern jet and five monsoon rainfall centers. The simulated climate variability was further examined in terms of teleconnections, leading modes of global SST (namely, ENSO), Pacific Decadal Oscillations (PDO), and changes in 19th–20th century climate. The analysis demonstrates that FGOALS-s2 realistically simulates extra-tropical teleconnection patterns of large-scale climate, and irregular ENSO periods. The model gives fairly reasonable reconstructions of spatial patterns of PDO and global monsoon changes in the 20th century. However, because the indirect effects of aerosols are not included in the model, the simulated global temperature change during the period 1850–2005 is greater than the observed warming, by 0.6°C. Some other shortcomings of the model are also noted.

The Sunway TaihuLight supercomputer: system and applications

The Sunway TaihuLight supercomputer is the world’s first system with a peak performance greater than 100 PFlops. In this paper, we provide a detailed introduction to the TaihuLight system. In contrast with other existing heterogeneous supercomputers, which include both CPU processors and PCIe-connected many-core accelerators (NVIDIA GPU or Intel Xeon Phi), the computing power of TaihuLight is provided by a homegrown many-core SW26010 CPU that includes both the management processing elements (MPEs) and computing processing elements (CPEs) in one chip. With 260 processing elements in one CPU, a single SW26010 provides a peak performance of over three TFlops. To alleviate the memory bandwidth bottleneck in most applications, each CPE comes with a scratch pad memory, which serves as a user-controlled cache. To support the parallelization of programs on the new many-core architecture, in addition to the basic C/C++ and Fortran compilers, the system provides a customized Sunway OpenACC tool that supports the OpenACC 2.0 syntax. This paper also reports our preliminary efforts on developing and optimizing applications on the TaihuLight system, focusing on key application domains, such as earth system modeling, ocean surface wave modeling, atomistic simulation, and phase-field simulation.

Wave-turbulence interaction-induced vertical mixing and its effects in ocean and climate models.

Heated from above, the oceans are stably stratified. Therefore, the performance of general ocean circulation models and climate studies through coupled atmosphere–ocean models depends critically on vertical mixing of energy and momentum in the water column. Many of the traditional general circulation models are based on total kinetic energy (TKE), in which the roles of waves are averaged out. Although theoretical calculations suggest that waves could greatly enhance coexisting turbulence, no field measurements on turbulence have ever validated this mechanism directly. To address this problem, a specially designed field experiment has been conducted. The experimental results indicate that the wave–turbulence interaction-induced enhancement of the background turbulence is indeed the predominant mechanism for turbulence generation and enhancement. Based on this understanding, we propose a new parametrization for vertical mixing as an additive part to the traditional TKE approach. This new result reconfirmed the past theoretical model that had been tested and validated in numerical model experiments and field observations. It firmly establishes the critical role of wave–turbulence interaction effects in both general ocean circulation models and atmosphere–ocean coupled models, which could greatly improve the understanding of the sea surface temperature and water column properties distributions, and hence model-based climate forecasting capability.

Water Vapor Transport and Cross-Equatorial Flow over the Asian-Australia Monsoon Region Simulated by CMIP5 Climate Models

The summer mean water vapor transport (WVT) and cross-equatorial flow (CEF) over the Asian-Australian monsoon region simulated by 22 coupled atmospheric-oceanic general circulation models (AOGCMs) from the World Climate Research Programme’s Coupled Model Intercomparison Project Phase 5 (CMIP5) were evaluated. Based on climatology of the twentieth-century simulations, most of models have a reasonably realistic representation of summer monsoon WVT characterized by southeast water vapor conveyor belt over the South Indian Ocean and southwest belt from the Arabian Sea to the East Asian. The correlation coefficients between NCEP reanalysis and simulations of BCC-CSM1-1, BNU-ESM, CanESM2, FGOALS-s2, MIROC4h and MPI-ESM-LR are up to 0.8. The simulated CEF depicted by the meridional wind along the equator includes the Somali jet and eastern CEF in low atmosphere and the reverse circulation in upper atmosphere, which were generally consistent with NCEP reanalysis. Multi-model ensemble means (MME) can reproduce more reasonable climatological features in spatial distribution both of WVT and CEF. Ten models with more reasonable WVT simulations were selected for future projection studies, including BCCCSM1-1, BNU-ESM, CanESM2, CCSM4, FGOALS-s2, FIO-ESM, GFDL-ESM2G, MRIOC5, MPI-ESM-LR and NorESM-1M. Analysis based on the future projection experiments in RCP (Representative Concentration Pathway) 2.6, RCP4.5, RCP6 and RCP8.5 show that the global warming forced by different RCP scenarios will results in enhanced WVT over the Indian area and the west Pacific and weaken WVT in the low latitudes of tropical Indian Ocean.

The prediction on the 2015/16 El Niño event from the perspective of FIO-ESM

Recently atmospheric and oceanic observations indicate the tropical Pacific is at the El Niño condition. However, it’s not clear whether this El Niño event of this year is comparable to the very strong one of 1997/98 which brought huge influence on the whole world. In this study, based on the Ensemble Adjusted Kalman Filter (EAKF) assimilation scheme and First Institute of Oceanography-Earth System Model (FIO-ESM), the assimilation system is setup, which can provide reasonable initial conditions for prediction. And the hindcast results suggest the skill of El Niño-Southern Oscillation (ENSO) prediction is comparable to other dynamical coupled models. Then the prediction for 2015/16 El Niño by using FIO-ESM is started from 1 November 2015. The ensemble results indicate that the 2015/16 El Niño will continue to be strong. By the end of 2015, the strongest strength is very like more than 2.0°C and the ensemble mean strength is 2.34°C, which indicates 2015/16 El Niño event will be very strong but slightly less than that of 1997/98 El Niño event (2.40°C) calculated relative a climatology based on the years 1992–2014. The prediction results also suggest 2015/16 El Niño event will be a transition to ENSO-neutral level in the early spring (FMA) 2016, and then may transfer to La Niña in summer 2016.

Data Reduction Analysis for Climate Data Sets

Global climate modeling not only requires computation capabilities, but also brings tough challenges for data storage systems. The input and output data sets generally require hundreds or even thousands of terabytes storage. Therefore, storage reduction methods, such as content deduplication and various data compression methods, are extremely important for reducing the storage size requirement in climate modeling. However, little work has been done on investigating the effectiveness of these data reduction methods for climate data sets. In this paper, the potential benefit of data reduction for climate data is studied by investigating a total of 46.5 TB climate data sets, including 3 observation data sets (14.1 TB) and 3 climate model output data sets (32.4 TB). Five different data compression algorithms and two types of content deduplication mechanisms are applied to these data sets to study the possible data reduction effectiveness. Further more, the compressibility of different climate component data is also examined. Our work demonstrates the potential of applying data reduction methods in climate modeling platforms, and provides guidance for selecting the suitable methods for different kinds of climate data sets. We find that the compression method

A comparison of two global ocean-ice coupled models with different horizontal resolutions

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