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The 5-year Ocean Regulation of Climate by Heat and Carbon Sequestration and Transports (ORCHESTRA) programme and its 1-year extension ENCORE (ENCORE is the National Capability ORCHESTRA Extension) was an approximately 11-million-pound programme involving seven UK research centres that finished in March 2022. The project sought to radically improve our ability to measure, understand and predict the exchange, storage and export of heat and carbon by the Southern Ocean. It achieved this through a series of milestone observational campaigns in combination with model development and analysis. Twelve cruises in the Weddell Sea and South Atlantic were undertaken, along with mooring, glider and profiler deployments and aircraft missions, all contributing to measurements of internal ocean and air–sea heat and carbon fluxes. Numerous forward and adjoint numerical experiments were developed and supported by the analysis of coupled climate models. The programme has resulted in over 100 peer-reviewed publications to date as well as significant impacts on climate assessments and policy and science coordination groups. Here, we summarize the research highlights of the programme and assess the progress achieved by ORCHESTRA/ENCORE and the questions it raises for the future. This article is part of a discussion meeting issue ‘Heat and carbon uptake in the Southern Ocean: the state of the art and future priorities’.

The turbulent exchanges, or fluxes, of heat, moisture and momentum between the atmosphere and the ocean play a crucial role in the Earth’s climate system. Direct measurements of turbulent fluxes are very challenging and sparse, and do not span the full range of environmental conditions that exist over the ocean. This means that empirical “bulk formulae” parameterizations that relate direct flux observations to concurrent measurements of the mean meteorological and sea surface variables contain considerable uncertainty. In this paper, we present a Python 3.6 (or higher) open-source software package “AirSeaFluxCode” for the computation of the heat (latent and sensible) and momentum fluxes. Ten different parameterizations are included, each based on published descriptions or code and each derived from a different set of observations, or different assumptions about the turbulent exchange processes. They represent a range of current expert opinion on how the fluxes depend on mean properties and can be used to explore uncertainty in calculated fluxes. AirSeaFluxCode also allows the adjustment of the mean meteorological input parameters (air temperature, humidity and wind speed) from the height at which they are obtained to a user-defined output height. This height adjustment enables the comparison of measurements, or model-derived values, made at different heights above sea-level. The parameterizations calculate the fluxes using input parameters that are relatively easily to measure, or are available as model output: wind speed, air temperature, sea surface temperature, atmospheric pressure and humidity. Where original code is available we have compared its output with that of AirSeaFluxCode. Any changes made to increase consistency across algorithms by standardizing computational methods or calculation of meteorological variables, for example, are discussed and the impacts quantified: these are shown to be insignificant except for a few cases where conditions were extrem

Low-level easterly winds encircling Antarctica help drive coastal currents which modify transport of circumpolar deep water to ice shelves, and the formation and distribution of sea ice. Reanalysis datasets are especially important at high southern latitudes where observations are few. Here, we investigate the representation of the mean state and short-term variability of coastal easterlies in three recent reanalyses, ERA5, MERRA-2 and JRA-55. Reanalysed winds are compared with summertime marine near-surface wind observations from the Advanced Scatterometer (ASCAT) and surface and upper air measurements from coastal stations. Reanalysis coastal easterlies correlate highly with ASCAT (r= 0.91, 0.89 and 0.85 for ERA5, MERRA-2 and JRA-55, respectively) but notable wind speed biases are found close to the coastal margins, especially near complex orography and at high wind speeds. To characterise short-term variability, 12-hourly reanalysis and coastal station winds are composited using self-organising maps (SOMs), which cluster timesteps under similar synoptic and mesoscale influences. Reanalysis performance is sensitive to the flow configuration at stations near steep coastal slopes, where they fail to capture the magnitude of near-surface wind speed variability when synoptic forcing is weak and conditions favour katabatic forcing. ERA5 exhibits the best overall performance, has more realistic orography, and a more realistic jet structure and temperature profile. These results demonstrate the regime behaviour of Antarctica's coastal winds and indicate important features of the coastal winds which are not well characterised by reanalysis datasets.

The exchanges, or fluxes, of heat, moisture and momentum between the atmosphere and the Earth's surface play a crucial role in the Earth's climate system, but the quantification of these fluxes remains challenging due to the non-linearity of surface dynamics and turbulent processes. Bulk formulae are frequently used to estimate surface turbulent fluxes from observed mean (or bulk) meteorological quantities. Uncertainties are inherent in the parameterisations as they rely on observations that are themselves uncertain and may not sample the full range of important conditions or include all of the variables that may affect the fluxes. As a consequence, different parameterisations of the bulk formulae may give different estimates of the fluxes. AirSeaFluxCode is an open-source software package implemented in Python 3.6 for the computation of surface turbulent fluxes of heat (latent and sensible) and momentum. It includes ten different parameterisations, each based on published algorithms. The parameterisations implemented in the new package can be used to caclulate the fluxes using a small number of input parameters that are typically observed or available as model output: wind speed; air temperature; sea surface temperature; atmospheric pressure; and humidity. Some parameterisations require the input of a "skin" sea surface temperature so code to relate skin temperature to temperature at depth is included. In addition the code can be used to do height corrections of mean parameters. This open-source software package is intended to be accessible, easy to use in its default implementation, and to provide a more informed choice of suitable parameterisations for particular applications.

The exchanges, or fluxes, of heat, moisture and momentum between the atmosphere and the Earth's surface play a crucial role in the Earth's climate system, but the quantification of these fluxes remains challenging due to the non-linearity of surface dynamics and turbulent processes. Bulk formulae are frequently used to estimate surface turbulent fluxes from observed mean (or bulk) meteorological quantities. Uncertainties are inherent in the parameterisations as they rely on observations that are themselves uncertain and may not sample the full range of important conditions or include all of the variables that may affect the fluxes. As a consequence, different parameterisations of the bulk formulae may give different estimates of the fluxes. AirSeaFluxCode is an open-source software package implemented in Python 3.6 for the computation of surface turbulent fluxes of heat (latent and sensible) and momentum. It includes ten different parameterisations, each based on published algorithms. The parameterisations implemented in the new package can be used to caclulate the fluxes using a small number of input parameters that are typically observed or available as model output: wind speed; air temperature; sea surface temperature; atmospheric pressure; and humidity. Some parameterisations require the input of a "skin" sea surface temperature so code to relate skin temperature to temperature at depth is included. In addition the code can be used to do height corrections of mean parameters. This open-source software package is intended to be accessible, easy to use in its default implementation, and to provide a more informed choice of suitable parameterisations for particular applications.