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  • Author or Editor: Min Chen x
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Yu Zhang
,
Min Chen
, and
Jiqin Zhong

Abstract

A wind profiler network with a total of 65 profiling radar systems was operated by the China Meteorological Observation Center (MOC) of the China Meteorological Administration (CMA) until July 2015. In this study, a quality control procedure is constructed to incorporate the profiler data from the wind-profiling network into the local data assimilation and forecasting systems. The procedure applies a blacklisting check that removes stations with gross errors and an outlier check that rejects data with large deviations from the background. As opposed to the biweight method, which has been commonly implemented in outlier elimination for univariate observations, the outlier elimination method is developed based on the iterated reweighted minimum covariance determinant (IRMCD) for multivariate observations, such as wind profiler data. A quality control experiment is performed separately for subsets containing profiler data tagged with/without rain flags in parallel every 0000 and 1200 UTC from 20 June to 30 September 2015. The results show that with quality control, the frequency distributions of the differences between the observations and the model background meet the requirements of a Gaussian distribution for data assimilation. A further intensive assessment of each quality control step reveals that the stations rejected by the blacklisting contained poor data quality and that the IRMCD rejects outliers in a robust and physically reasonable manner. Detailed comparisons between the IRMCD and the biweight method are performed, and the IRMCD is demonstrated to be more efficient and more comprehensive regarding the dataset used in this study.

Full access
Min Gan
,
Yongping Chen
,
Shunqi Pan
,
Jiangxia Li
, and
Zijun Zhou

Abstract

Influenced by river discharge, the tidal properties of estuarine tides can be more complex than those of oceanic tides, which makes the tidal prediction less accurate when using a classical tidal harmonic analysis approach, such as the T_TIDE model. Although the nonstationary tidal harmonic analysis model NS_TIDE can improve the accuracy for the analysis of tides in a river-dominated estuary, it becomes less satisfactory when applying the NS_TIDE model to a mesotidal estuary like the Yangtze estuary. Through the error source analysis, it is found that the main errors originate from the low frequency of tidal fluctuation. The NS_TIDE model is then modified by replacing the stage model with the frequency-expanded tidal–fluvial model so that more subtidal constituents, especially the “atmospheric tides,” can be taken into account. The results show that the residuals from tidal harmonic analysis are significantly reduced by using the modified NS_TIDE model, with the yearly root-mean-square-error values being only 0.04–0.06 m for the Yangtze estuarine tides.

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Boyin Huang
,
Xungang Yin
,
James A. Carton
,
Ligang Chen
,
Garrett Graham
,
Chunying Liu
,
Thomas Smith
, and
Huai-Min Zhang

Abstract

Our study shows that the intercomparison among sea surface temperature (SST) products is influenced by the choice of SST reference, and the interpolation of SST products. The influence of reference SST depends on whether the reference SSTs are averaged to a grid or in pointwise in situ locations, including buoy or Argo observations, and filtered by first-guess or climatology quality control (QC) algorithms. The influence of the interpolation depends on whether SST products are in their original grids or preprocessed into common coarse grids. The impacts of these factors are demonstrated in our assessments of eight widely used SST products (DOISST, MUR25, MGDSST, GAMSSA, OSTIA, GPB, CCI, CMC) relative to buoy observations: (i) when the reference SSTs are averaged onto 0.25° × 0.25° grid boxes, the magnitude of biases is lower in DOISST and MGDSST (<0.03°C), and magnitude of root-mean-square differences (RMSDs) is lower in DOISST (0.38°C) and OSTIA (0.43°C); (ii) when the same reference SSTs are evaluated at pointwise in situ locations, the standard deviations (SDs) are smaller in DOISST (0.38°C) and OSTIA (0.39°C) on 0.25° × 0.25° grids; but the SDs become smaller in OSTIA (0.34°C) and CMC (0.37°C) on products’ original grids, showing the advantage of those high-resolution analyses for resolving finer-scale SSTs; (iii) when a loose QC algorithm is applied to the reference buoy observations, SDs increase; and vice versa; however, the relative performance of products remains the same; and (iv) when the drifting-buoy or Argo observations are used as the reference, the magnitude of RMSDs and SDs become smaller, potentially due to changes in observing intervals. These results suggest that high-resolution SST analyses may take advantage in intercomparisons.

Significance Statement

Intercomparisons of gridded SST products be affected by how the products are compared with in situ observations: whether the products are in coarse (0.25°) or original (0.05°–0.10°) grids, whether the in situ SSTs are in their reported locations or gridded and how they are quality controlled, and whether the biases of satellite SSTs are corrected by localized matchups or large-scale patterns. By taking all these factors into account, our analyses indicate that the NOAA DOISST is among the best SST products for the long period (1981–present) and relatively coarse (0.25°) resolution that it was designed for.

Open access