The use of QBO, ENSO, and NAO perturbations in the evaluation of GOME-2 MetOp A total ozone measurements

In this work we present evidence that quasi-cyclical perturbations in total ozone (quasi-biennial oscillation - QBO, El Niño-Southern Oscillation - ENSO, and North Atlantic Oscillation - NAO) can be used as independent proxies in evaluating Global Ozone Monitoring Experiment (GOME) 2 aboard MetOp A (GOME-2A) satellite total ozone data, using ground-based (GB) measurements, other satellite data, and chemical transport model calculations. The analysis is performed in the frame of the validation strategy on longer time scales within the European Organisation for the Exploitation of Meteorological Satellites (EUMETSAT) Satellite Application Facility on Atmospheric Composition Monitoring (AC SAF) project, covering the period 2007-2016. Comparison of GOME-2A total ozone with ground observations shows mean differences of about <span classCombining double low lineinline-formula><math xmlnsCombining double low linehttp://www.w3.org/1998/Math/MathML idCombining double low lineM1 displayCombining double low lineinline overflowCombining double low linescroll dspmathCombining double low linemathml><mrow><mo>-</mo><mn mathvariantCombining double low linenormal>0.7</mn><mo>±</mo><mn mathvariantCombining double low linenormal>1.4</mn></mrow></math><span><svg:svg xmlns:svgCombining double low linehttp://www.w3.org/2000/svg widthCombining double low line52pt heightCombining double low line10pt classCombining double low linesvg-formula dspmathCombining double low linemathimg md5hashCombining double low linedba8c66e297c0601baccc6ab115a0086><svg:image xmlns:xlinkCombining double low linehttp://www.w3.org/1999/xlink xlink:hrefCombining double low lineamt-12-987-2019-ie00001.svg widthCombining double low line52pt heightCombining double low line10pt srcCombining double low lineamt-12-987-2019-ie00001.png/></svg:svg></span></span> % in the tropics (0-30<span classCombining double low lineinline-formula>ĝ</span>), about <span classCombining double low lineinline-formula><math xmlnsCombining double low linehttp://www.w3.org/1998/Math/MathML idCombining double low lineM3 displayCombining double low lineinline overflowCombining double low linescroll dspmathCombining double low linemathml><mrow><mo>+</mo><mn mathvariantCombining double low linenormal>0.1</mn><mo>±</mo><mn mathvariantCombining double low linenormal>2.1</mn></mrow></math><span><svg:svg xmlns:svgCombining double low linehttp://www.w3.org/2000/svg widthCombining double low line52pt heightCombining double low line10pt classCombining double low linesvg-formula dspmathCombining double low linemathimg md5hashCombining double low line63d75ddfa7d430e7ceb7a4033cb0075f><svg:image xmlns:xlinkCombining double low linehttp://www.w3.org/1999/xlink xlink:hrefCombining double low lineamt-12-987-2019-ie00002.svg widthCombining double low line52pt heightCombining double low line10pt srcCombining double low lineamt-12-987-2019-ie00002.png/></svg:svg></span></span> % in the mid-latitudes (30-60<span classCombining double low lineinline-formula>ĝ</span>), and about <span classCombining double low lineinline-formula><math xmlnsCombining double low linehttp://www.w3.org/1998/Math/MathML idCombining double low lineM5 displayCombining double low lineinline overflowCombining double low linescroll dspmathCombining double low linemathml><mrow><mo>+</mo><mn mathvariantCombining double low linenormal>2.5</mn><mo>±</mo><mn mathvariantCombining double low linenormal>3.2</mn></mrow></math><span><svg:svg xmlns:svgCombining double low linehttp://www.w3.org/2000/svg widthCombining double low line52pt heightCombining double low line10pt classCombining double low linesvg-formula dspmathCombining double low linemathimg md5hashCombining double low linecc8aa294436c6f7026458ba098d8c81e><svg:image xmlns:xlinkCombining double low linehttp://www.w3.org/1999/xlink xlink:hrefCombining double low lineamt-12-987-2019-ie00003.svg widthCombining double low line52pt heightCombining double low line10pt srcCombining double low lineamt-12-987-2019-ie00003.png/></svg:svg></span></span> % and <span classCombining double low lineinline-formula>0.0±4.3</span> % over the northern and southern high latitudes (60-80<span classCombining double low lineinline-formula>ĝ</span>), respectively. In general, we find that GOME-2A total ozone data depict the QBO-ENSO-NAO natural fluctuations in concurrence with the co-located solar backscatter ultraviolet radiometer (SBUV), GOME-type Total Ozone Essential Climate Variable (GTO-ECV; composed of total ozone observations from GOME, SCIAMACHY - SCanning Imaging Absorption SpectroMeter for Atmospheric CHartographY, GOME-2A, and OMI - ozone monitoring instrument, combined into one homogeneous time series), and ground-based observations. Total ozone from GOME-2A is well correlated with the QBO (highest correlation in the tropics of <span classCombining double low lineinline-formula>+</span>0.8) in agreement with SBUV, GTO-ECV, and GB data which also give the highest correlation in the tropics. The differences between deseazonalized GOME-2A and GB total ozone in the tropics are within <span classCombining double low lineinline-formula>±1</span> %. These differences were tested further as to their correlations with the QBO.<span idCombining double low linepage988/> The differences had practically no QBO signal, providing an independent test of the stability of the long-term variability of the satellite data. Correlations between GOME-2A total ozone and the Southern Oscillation Index (SOI) were studied over the tropical Pacific Ocean after removing seasonal, QBO, and solar-cycle-related variability. Correlations between ozone and the SOI are on the order of <span classCombining double low lineinline-formula>+</span>0.5, consistent with SBUV and GB observations. Differences between GOME-2A and GB measurements at the station of Samoa (American Samoa; 14.25<span classCombining double low lineinline-formula>ĝ</span> S, 170.6<span classCombining double low lineinline-formula>ĝ</span> W) are within <span classCombining double low lineinline-formula>±1.9</span> %. We also studied the impact of the NAO on total ozone in the northern mid-latitudes in winter. We find very good agreement between GOME-2A and GB observations over Canada and Europe as to their NAO-related variability, with mean differences reaching the <span classCombining double low lineinline-formula>±1</span> % levels. The agreement and small differences which were found between the independently produced total ozone datasets as to the influence of the QBO, ENSO, and NAO show the importance of these climatological proxies as additional tool for monitoring the long-term stability of satellite-ground-truth biases. © 2019. This work is distributed under the Creative Commons Attribution 4.0 License

A generalized joint inference approach for citation matching

Citation matching is the problem of extracting bibliographic records from citation lists in technical papers, and merging records that represent the same publication. Generally, there are three types of data- sets in citation matching, i.e., sparse, dense and hybrid types. Typical approaches for citation matching are Joint Segmentation (Jnt-Seg) and Joint Segmentation Entity Resolution (Jnt-Seg-ER). Jnt-Seg method is effective at processing sparse type datasets, but often produces many errors when applied to dense type datasets. On the contrary, Jnt-Seg-ER method is good at dealing with dense type datasets, but insufficient when sparse type datasets are presented. In this paper we propose an alternative joint inference approach&ndash;Generalized Joint Segmentation (Generalized-Jnt-Seg). It can effectively deal with the situation when the dataset type is unknown. Especially, in hybrid type datasets analysis there is often no a priori information for choosing Jnt-Seg method or Jnt-Seg-ER method to process segmentation and entity resolution. Both methods may produce many errors. Fortunately, our method can effectively avoid error of segmentation and produce well field boundaries. Experimental results on both types of citation datasets show that our method outperforms many alternative approaches for citation matching.<br /