The Surface Water Ocean Topography (SWOT) mission significantly improves on the capabilities of current nadir altimeters by enabling two-dimensional mapping. Assimilating this advanced data into high-resolution models poses challenges. To address this, Observing System Simulation Experiments (OSSEs) were conducted to evaluate the effects of both simulated and actual SWOT data on the Regional Ice Ocean Prediction System (RIOPS). This study examines the OSSEs’ design, focusing on the simulated observations and assimilation systems used. The validity of the OSSE designs is confirmed by ensuring the deviations between the assimilation system and the Nature Run (NR) align with discrepancies observed between actual oceanic data and OSSE simulations. The study measures the impact of assimilating SWOT and two nadir altimeters by calculating root mean square forecast error for sea surface height (SSH), temperature, and velocities, along with performing wave-number spectra and coherence analyses of SSH errors. The inclusion of SWOT data is found to reduce RMS SSH errors by 16% and RMS velocity errors by 6% in OSSEs. The SSH error spectrum shows that the most notable improvements are for scales associated with the largest errors in the range of 200-400 km, with a 33% reduction compared to traditional data assimilation. Additionally, spectral coherence analysis shows that the limit of constrained scales is reduced from 280 km for conventional observations to 195 km when SWOT is assimilated as well. This study also represents our first attempt at assimilating early-release SWOT data. A set of Observing System (data denial) experiments using early-release SWOT measurements shows similar (but smaller) responses to OSSE experiments in a two nadir-altimeter context. In a six-altimeter constellation setup, a positive impact of SWOT is also noted, but of significantly diminished amplitude. These findings robustly advocate for the integration of SWOT observations into RIOPS and similar ocean analysis and forecasting frameworks.

中文翻译：

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使用区域冰海预报系统同化北大西洋和加拿大东海岸的合成和真实 SWOT 观测


表层水海洋地形 （SWOT） 任务通过实现二维测绘，显著提高了当前最低点高度计的能力。将这些高级数据同化到高分辨率模型中会带来挑战。为了解决这个问题，进行了观测系统模拟实验 （OSSEs），以评估模拟和实际 SWOT 数据对区域冰海预报系统 （RIOPS） 的影响。本研究检查了 OSSE 的设计，重点是使用的模拟观察和同化系统。通过确保同化系统和自然运行 （NR） 之间的偏差与实际海洋数据和 OSSE 模拟之间观察到的差异保持一致，可以确认 OSSE 设计的有效性。该研究通过计算海面高度 （SSH）、温度和速度的均方根预报误差，以及对 SSH 误差进行波数谱和相干分析，来衡量同化 SWOT 和两个最低点高度的影响。发现包含 SWOT 数据可以将 OSSE 中的 RMS SSH 错误减少 16%，RMS 速度错误减少 6%。SSH 误差谱显示，最显着的改进是与 200-400 公里范围内最大误差相关的尺度，与传统数据同化相比减少了 33%。此外，光谱相干分析表明，当 SWOT 也被同化时，约束尺度的限制从常规观测的 280 公里减少到 195 公里。这项研究也代表了我们首次尝试吸收早期发布的 SWOT 数据。一组使用早期发布 SWOT 测量的观测系统（数据否认）实验在两个最低高度计环境中显示出对 OSSE 实验的相似（但较小）响应。 在六高度计星座设置中，还注意到了 SWOT 的积极影响，但振幅显着减小。这些发现有力地倡导将 SWOT 观测整合到 RIOPS 和类似的海洋分析和预报框架中。