You-Soon Chang

Intercomparison of the Arctic sea ice cover in global ocean–sea ice reanalyses from the ORA-IP project

AbstractOcean–sea ice reanalyses are crucial for assessing the variability and recent trends in the Arctic sea ice cover. This is especially true for sea ice volume, as long-term and large scale sea ice thickness observations are inexistent. Results from the Ocean ReAnalyses Intercomparison Project (ORA-IP) are presented, with a focus on Arctic sea ice fields reconstructed by state-of-the-art global ocean reanalyses. Differences between the various reanalyses are explored in terms of the effects of data assimilation, model physics and atmospheric forcing on properties of the sea ice cover, including concentration, thickness, velocity and snow. Amongst the 14 reanalyses studied here, 9 assimilate sea ice concentration, and none assimilate sea ice thickness data. The comparison reveals an overall agreement in the reconstructed concentration fields, mainly because of the constraints in surface temperature imposed by direct assimilation of ocean observations, prescribed or assimilated atmospheric forcing and assimilation of sea ice concentration. However, some spread still exists amongst the reanalyses, due to a variety of factors. In particular, a large spread in sea ice thickness is found within the ensemble of reanalyses, partially caused by the biases inherited from their sea ice model components. Biases are also affected by the assimilation of sea ice concentration and the treatment of sea ice thickness in the data assimilation process. An important outcome of this study is that the spatial distribution of ice volume varies widely between products, with no reanalysis standing out as clearly superior as compared to altimetry estimates. The ice thickness from systems without assimilation of sea ice concentration is not worse than that from systems constrained with sea ice observations. An evaluation of the sea ice velocity fields reveals that ice drifts too fast in most systems. As an ensemble, the ORA-IP reanalyses capture trends in Arctic sea ice area and extent relatively well. However, the ensemble can not be used to get a robust estimate of recent trends in the Arctic sea ice volume. Biases in the reanalyses certainly impact the simulated air–sea fluxes in the polar regions, and questions the suitability of current sea ice reanalyses to initialize seasonal forecasts.

A Review of the Quality Control of Global Ocean Temperature and Salinity Data

High-density temperature and salinity profiles from the successful international Argo project made it possible to reproduce the three-dimensional global ocean state in near-real time, which also increased much attention on the data analysis studies of global ocean. This paper reviewed several important issues on the recent data analysis studies such as systematic biases of XBT (eXpendable BathyThermograph) and Argo data, sea level budget discrepancy between steric height and satellite observed data, heat content change, and the current status of the development of objective analysis fields. This study also emphasized that it is required to carry out very cautious ocean data quality control and understand global-scale ocean variability prior to analyzing the regional-scale ocean climate change, particularly, in the East Asian marginal Seas.

Vertical gradient correction for the oceanographic Atlas of the East Asian Seas

Regional climatology around the East Asian Seas has been developed by an international collaboration between the National Oceanic Data Center and the Korea Oceanic Data Center. It provides reliable information on temperature and salinity climatological fields with high resolution (0.1° × 0.1° by 137 levels). However, there is a problem around near-bottom areas where topographic change is steep and observations are not available near the bottom. This study resolves this problem using a vertical gradient correction method when the profile is statically unstable. The stability is determined based on the Brunt-Vaisala frequency with individual temperature and salinity profiles. Topographic-following mapping technique employing the potential vorticity constraint term is used to construct a vertical gradient database for the temperature and salinity at every grid point. The results show that the correction is effective for eliminating large erroneous vertical gradients around near-bottom areas. In addition, we show the importance of the optimal length scale to construct a precise vertical gradient database in a particular area such as the northern shelf of Taiwan. We expect that our revised high-resolution climatological mean fields will serve as important data for relevant studies around the East Asian Seas.

An OSSE Study for Deep Argo Array using the GFDL Ensemble Coupled Data Assimilation System

An observing system simulation experiment (OSSE) using an ensemble coupled data assimilation system was designed to investigate the impact of deep ocean Argo profile assimilation in a biased numerical climate system. Based on the modern Argo observational array and an artificial extension to full depth, “observations” drawn from one coupled general circulation model (CM2.0) were assimilated into another model (CM2.1). Our results showed that coupled data assimilation with simultaneous atmospheric and oceanic constraints plays a significant role in preventing deep ocean drift. However, the extension of the Argo array to full depth did not significantly improve the quality of the oceanic climate estimation within the bias magnitude in the twin experiment. Even in the “identical” twin experiment for the deep Argo array from the same model (CM2.1) with the assimilation model, no significant changes were shown in the deep ocean, such as in the Atlantic meridional overturning circulation and the Antarctic bottom water cell. The small ensemble spread and corresponding weak constraints by the deep Argo profiles with medium spatial and temporal resolution may explain why the deep Argo profiles did not improve the deep ocean features in the assimilation system. Additional studies using different assimilation methods with improved spatial and temporal resolution of the deep Argo array are necessary in order to more thoroughly understand the impact of the deep Argo array on the assimilation system.

Development and Application of an Experimental Program for Mapping Temperature and Salinity Distribution around the Korean Marginal Seas Using Ocean Data View

This study developed an experimental program for mapping temperature and salinity distribution around the Korean marginal seas using Ocean Data View (ODV) software. Serial ocean observational data have been analyzed after being converted to the ODV compatible format using a separated program newly developed for this study. When this new experimental program was applied to 65 pre-service teachers, it was found that the quality of assignment completion with a new program improved compared with that of the same group who used the existing program. A questionnaires was employed to delve into participants` satisfaction of the new program. Findings depicted that accurate and quick drawing of isoline drew the highest responses of satisfaction, and confirmed positive responses to the understanding and application of this new experimental program.