The impact of Argo observations in a global weakly coupled ocean–atmosphere data assimilation and short‐range prediction system

Abstract

The Argo array is a large component of the ocean observing system on which operational ocean forecasts rely. Global observations of the sub‐surface temperature and salinity from Argo enables the accurate initialisation of ocean forecasts, improving the position of currents and the overall energy available for air–sea interactions. Such constraints on the sub‐surface ocean are important for coupled initialisation for seasonal forecasting where the atmosphere is coupled to the upper ocean. As operational centres move toward using coupled atmosphere–ocean models for numerical weather prediction (NWP), it is useful to understand how ocean observations contribute to short‐range coupled forecasts. Using the Met Office Weakly Coupled Data Assimilation system, we have run Observing System Experiments (OSEs) to investigate the effect of withholding Argo observations on short‐range coupled ocean–atmosphere analyses and forecasts. Withholding Argo significantly increases the sub‐surface temperature and salinity RMS errors with consequent changes in the upper ocean heat content and positions of currents. Overall, there is little systematic impact of these ocean differences on global atmosphere analyses. However, in a case‐study over the period of hurricane Sandy (October 2012), we do see that Argo observations have some impact on atmospheric forecasts. The assimilation of Argo observations affects the position of the Gulf Stream leading to a small effect on the position and intensity of hurricane Sandy as it made landfall. As the resolution of the system is quite low compared to operational NWP systems, seeing even a small impact is encouraging. We might expect with future increased‐resolution coupled models that this influence of ocean observations on the atmosphere would only increase.

Assessing the role and consistency of satellite observation products in global physical–biogeochemical ocean reanalysis

“…These are intended to explore physical-biogeochemical relationships in the model and observations, and the impact of data assimilation on these, rather than simply validating the accuracy of the reanalyses. For validation of the underlying system, the reader is referred to Blockley et al (2014) for the physical model and assimilation, Ford and Barciela (2017) for the biogeochemical model and assimilation, and Lea et al (2014) and King et al (2020) for data withholding experiments performed with the physics-only system.…”

“…For the 1 • runs, the eddy-induced velocity parameterisation of Gent and McWilliams (1990) was turned on, and Laplacian rather than bi-Laplacian lateral iso-level diffusion was used on momentum, with associated mixing coefficients varying in 3D rather than 2D. Furthermore, the special treatment of tidal mixing in the Indonesian throughflow, as developed by Koch-Larrouy et al (2008), was only used at 1/4 • resolution.…”

Benchmarking of automatic quality control checks for ocean temperature profiles and recommendations for optimal sets

“…Chassignet et al, 2009;Blockley et al, 2014;King et al, 2018;Lellouche et al, 2018;Schiller et al, 2020) and numerical weather prediction from coupled atmosphere-ocean models (e.g. Dong et al, 2017;King et al, 2020). Ocean applications that require observations with less stringent timeliness requirements but a higher level of quality control include climate applications such as decadal forecasting (e.g.…”

Assessing the Potential Impact of Changes to the Argo and Moored Buoy Arrays in an Operational Ocean Analysis System

“…The aims of this study are two-fold: 1. assess the impact of additional (or fewer) observations on the ability of the assimilative system to reproduce the ocean state and 2. assess the effectiveness of an ocean system to using ocean observations and identify areas for future model and assimilation development. Previous studies have proved that the Argo floats and mooring arrays are crucial in constraining the ocean forecasting system at various temporal and spatial scales (Lea et al, 2014;Oke et al, 2015;Xue et al, 2017b;Fujii et al, 2019;King et al, 2020). Therefore, in this study we focus on the impact of global Argo floats and the tropical mooring arrays on the Met Office Forecasting Ocean Assimilation Model (FOAM) (Blockley et al, 2014).…”