Generation and Assessment of ARGO Sea Surface Temperature Climatology for the Indian Ocean Region

IF 2.6 3区 地球科学 Q2 OCEANOGRAPHY
Ravi Kumar Jha, T.V.S. Udaya Bhaskar
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引用次数: 0

Abstract

ARGO program was conceived with an aim to generate near real-time ocean observations as the primary in-situ sources for use in operational oceanography studies. Two decades-long ARGO near-surface temperature data set was used for generating monthly gridded ARGO sea surface temperature (ASST) product on a climatological scale. Data interpolating variational analysis (DIVA) method was employed for generating the product with a spatial resolution of 0.25° x 0.25° for the Tropical Indian Ocean. This monthly ASST product was evaluated using five different climatological SST products derived from in-situ and satellite measurements. Various statistics such as BIAS, RMSE, coefficient of correlation, and skill scores were generated to evaluate the reliability of the ASST product. Further, the ASST product was validated with climatological in-situ SST obtained from RAMA and OMNI moorings deployed in the Indian Ocean. Statistical comparisons showed low BIAS and RMSE, and high correlation and skill scores with most of the buoys locations and the gridded SST products. Results concluded that the near-surface temperature data from ARGO can be used along with other SST data sets in the generation of high-resolution blended SST products.

印度洋地区ARGO海温气候学的生成和评估
ARGO计划的目的是产生接近实时的海洋观测,作为业务海洋学研究中使用的主要现场资源。利用20年ARGO近地表温度数据集,在气候尺度上生成ARGO月格网海面温度产品。采用数据插值变分分析(DIVA)方法生成了热带印度洋空间分辨率为0.25°x 0.25°的产品。每月的海温产品是用五种不同的气候海温产品进行评估的,这些产品来自于现场和卫星测量。产生各种统计数据,如BIAS、RMSE、相关系数和技能分数,以评估该产品的可靠性。此外,用部署在印度洋的RAMA和OMNI系泊所获得的气候原位海温验证了该产品。统计比较显示,大多数浮标位置和网格化海表温度产品具有较低的偏差和RMSE,且具有较高的相关性和技能得分。结果表明,ARGO的近地表温度数据可以与其他海温数据集一起用于高分辨率混合海温产品的生成。
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来源期刊
Oceanologia
Oceanologia 地学-海洋学
CiteScore
5.30
自引率
6.90%
发文量
63
审稿时长
146 days
期刊介绍: Oceanologia is an international journal that publishes results of original research in the field of marine sciences with emphasis on the European seas.
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