The Significance of the Long-Wavelength Correction for Studies of Baroclinic Tides With SWOT

IF 2.9 3区 地球科学 Q2 ASTRONOMY & ASTROPHYSICS Earth and Space Science Pub Date : 2024-10-10 DOI:10.1029/2024EA003677
Edward D. Zaron
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Abstract

The long-wavelength correction (LWC) of SWOT data is intended to reduce errors related to the stability of the SWOT antenna and its attitude in orbit. The algorithms used to compute the LWC utilize SWOT KaRIn sea surface-height (SSH) measurements and additional data, and the LWC may absorb geophysical SSH into the correction. Different LWC algorithms are used on the L2 and L3 SWOT products, which are analyzed here during the 1 day repeat (Cal/Val) mission phase lasting approximately 100 days. During this mission phase the SSH anomaly (SSHA) computed using the L3 LWC is much more realistic than the L2 LWC, as shown here by comparing spatial statistics of the L2 and L3 products. The L3 LWC algorithm is nonlinear insofar as it depends on second-order statistics of the SSHA and multi-satellite SSHA differences, making it difficult to quantify the extent to which it could absorb baroclinic tidal signals. To overcome this difficulty, a proxy L3 LWC algorithm is developed which mimics the L3 LWC but is strictly linear in the SSHA. The proxy LWC is applied to both idealized waveforms and to the predicted internal tide available on the products, and it is found to absorb 1% or less of the signal variance, leading to corresponding pointwise errors of 10% or less. Because the errors are at longer wavelengths and are significantly smaller amplitude than internal tide signals, the LWC impact on the measurement and interpretation of internal tides with SWOT is expected to be negligible in most applications.

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长波校正对利用 SWOT 研究巴氏潮汐的意义
SWOT 数据的长波校正(LWC)旨在减少与 SWOT 天线的稳定性及其在轨姿态有关的误差。用于计算长波校正的算法利用 SWOT KaRIn 海面高度(SSH)测量值和附加数据,长波校正可能会将地球物理 SSH 吸收到校正中。L2 和 L3 SWOT 产品使用了不同的 LWC 算法,这里分析的是在大约 100 天的 1 天重复(Cal/Val)任务阶段。在这一任务阶段,使用 L3 低纬度预报算法计算的 SSH 异常(SSHA)比 L2 低纬度预报算法更真实,这里通过比较 L2 和 L3 产品的空间统计数据来说明这一点。L3 LWC 算法是非线性的,因为它依赖于 SSHA 和多卫星 SSHA 差异的二阶统计量,因此很难量化它能在多大程度上吸收气压潮汐信号。为了克服这一困难,开发了一种替代 L3 LWC 算法,该算法模仿 L3 LWC,但与 SSHA 严格成线性关系。代用 LWC 既适用于理想化波形,也适用于产品上的预测内潮,结果发现它能吸收 1%或更少的信号方差,导致 10%或更少的相应点误差。由于误差发生在较长的波长上,且振幅明显小于内潮信号,因此预计在大多数应用中,LWC 对使用 SWOT 测量和解释内潮的影响可以忽略不计。
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来源期刊
Earth and Space Science
Earth and Space Science Earth and Planetary Sciences-General Earth and Planetary Sciences
CiteScore
5.50
自引率
3.20%
发文量
285
审稿时长
19 weeks
期刊介绍: Marking AGU’s second new open access journal in the last 12 months, Earth and Space Science is the only journal that reflects the expansive range of science represented by AGU’s 62,000 members, including all of the Earth, planetary, and space sciences, and related fields in environmental science, geoengineering, space engineering, and biogeochemistry.
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