Quantifying Dynamical Proxy Potential Through Shared Adjustment Physics in the North Atlantic. Issue 9 (26th August 2020)

• Record Type: Journal Article
• Authors: Loose, N.; Heimbach, P.; Pillar, H. R.; Nisancioglu, K. H.
• Is Part Of: Journal of geophysical research. Volume 125:Issue 9(2020)
• Page Start: n/a
• Page End: n/a
• Publication Date: 2020-08-26
• Subjects: North Atlantic -- teleconnection -- proxy -- observing system design -- uncertainty quantification -- adjoint model; Oceanography -- Periodicals; 551.4605
• DOI: 10.1029/2020JC016112
• Languages: English
• ISSNs: 2169-9275

Abstract

Abstract: Oceanic quantities of interest (QoIs), for example, ocean heat content or transports, are often inaccessible to direct observation, due to the high cost of instrument deployment and logistical challenges. Therefore, oceanographers seek proxies for undersampled or unobserved QoIs. Conventionally, proxy potential is assessed via statistical correlations, which measure covariability without establishing causality. This paper introduces an alternative method: quantifying dynamical proxy potential. Using an adjoint model, this method unambiguously identifies the physical origins of covariability. A North Atlantic case study illustrates our method within the ECCO (Estimating the Circulation and Climate of the Ocean) state estimation framework. We find that wind forcing along the eastern and northern boundaries of the Atlantic drives a basin‐wide response in North Atlantic circulation and temperature. Due to these large‐scale teleconnections, a single subsurface temperature observation in the Irminger Sea informs heat transport across the remote Iceland‐Scotland ridge (ISR), with a dynamical proxy potential of 19%. Dynamical proxy potential allows two equivalent interpretations: Irminger Sea subsurface temperature (i) shares 19% of its adjustment physics with ISR heat transport and (ii) reduces the uncertainty in ISR heat transport by 19% (independent of the measured temperature value), if the Irminger Sea observation is added without noise to the ECCO state estimate. With its two interpretations, dynamical proxy potential is simultaneously rooted in (i) ocean dynamics and (ii) uncertainty quantification and optimal observing system design, the latter being an emerging branch in computational science. The new method may therefore foster dynamics‐based, quantitative ocean observing system design in the coming years. Plain Language Summary: To understand the Earth's changing climate, it is important to estimate how much heat the ocean takes up from the atmosphere and how the ocean recirculates the heat around the globe. Directly obtaining these estimates from measurements is complicated because oceanographers cannot measure the ocean everywhere. Ocean measurements taken from ships or freely drifting instruments are expensive and difficult to obtain, especially in regions with ice cover or rough weather conditions. To analyze how existing measurements can be used to estimate unmeasured aspects of the ocean, past studies have used statistical correlations, although it is usually unclear whether correlations have a real, physical origin. This paper introduces a new method: We replace statistical correlations by correlations that have an underlying physical mechanism. As an example, the paper reveals that (A) a subsurface ocean temperature measurement in the Irminger Sea helps to better estimate (B) poleward ocean heat transport across the Iceland‐Scotland ridge, hundreds of kilometers away. (A) and (B) are related by physics‐based correlation, which is created by a similar dynamical response of (A) and (B) to changes in the near‐ and far‐field wind. The new method can be used to plan effective instrument placements in the future. Key Points: Sensitivities of key metrics, representing observed and desirable quantities in the ocean, are computed using an adjoint model Similar sensitivity distributions indicate proxy potential through shared ocean adjustment physics In contrast to conventional statistical methods, our quantification of proxy potential is rigorously dynamics‐based