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Tides are proved to have a significant effect on the ocean and climate. Previous modelling research either adds a tidal mixing parameterisation or an explicit tidal forcing to the ocean models. However, no research compares the two approaches in the same framework. Here we implement both schemes in a general ocean circulation model and assess both methods by comparing the results. The aspects for comparison involve hydrography, sea ice, meridional overturning circulation (MOC), vertical diffusivity, barotropic streamfunction and energy diagnostics. We conclude that although the mesh resolution is poor in resolving internal tides in most mid-latitude and shelf-break areas, explicit tidal forcing still shows stronger tidal mixing at the Kuril–Aleutian Ridge and the Indonesian Archipelago than the tidal mixing parameterisation. Beyond that, the explicit tidal forcing method leads to a stronger upper cell of the Atlantic MOC by enhancing the Pacific MOC and the Indonesian Throughflow. Meanwhile, the tidal mixing parameterisation leads to a stronger lower cell of the Atlantic MOC due to the tidal mixing in deep oceans. Both methods maintain the Antarctic Circumpolar Current at a higher level than the control run by increasing the meridional density gradient. We also show several phenomena that are not considered in the tidal mixing parameterisation, for example, the changing of energy budgets in the ocean system, the bottom drag induced mixing on the continental shelves and the sea ice transport by tidal motions. Due to the limit of computational capacity, an internal-tide-resolving simulation is not feasible for climate studies. However, a high-resolution short-term tidal simulation is still required to improve parameters and parameterisation schemes in climate studies.

The ocean mixed layer is the interface between the ocean interior and the atmosphere or sea ice, and plays a key role in climate variability. It is thus critical that numerical models used in climate studies are capable of a good representation of the mixed layer, especially its depth. Here we evaluate the mixed layer depth (MLD) in six pairs of non-eddying (1° resolution) and eddy-rich (up to 1/16°) models from the Ocean Model Intercomparison Project (OMIP), forced by a common atmospheric state. For model validation, we use an updated MLD dataset computed from observations using the OMIP protocol (a constant density threshold). In winter, low resolution models exhibit large biases in the deep water formation regions. These biases are reduced in eddy-rich models but not uniformly across models and regions. The improvement is most noticeable in the mode water formation regions of the northern hemisphere. Results in the Southern Ocean are more contrasted, with biases of either sign remaining at high resolution. In eddy-rich models, mesoscale eddies control the spatial variability of MLD in winter. Contrary to a hypothesis that the deepening of the mixed layer in anticyclones would make the MLD larger globally, eddy-rich models tend to have a shallower mixed layer at most latitudes than coarser models do. In addition, our study highlights the sensitivity of the MLD computation to the choice of a reference level and the spatio-temporal sampling, which motivates new recommendations for MLD computation in future model intercomparison projects.

An oral presentation at () ISDA online event. Topic: Ocean Data Assimilation

Oral presentation at EGU GA 2023 (EGU23 14227)

Using transient climate forcing based on simulations from the Alfred Wegener Institute Earth System Model (AWI-ESM), we simulate the evolution of the Greenland Ice Sheet (GrIS) from the last interglacial (125 ka, kiloyear before present) to 2100 AD with the Parallel Ice Sheet Model (PISM). The impact of paleoclimate, especially Holocene climate, on the present and future evolution of the GrIS is explored. Our simulations of the past show close agreement with reconstructions with respect to the recent timing of the peaks in ice volume and the climate of Greenland. The maximum and minimum ice volume at around 18–17 ka and 6–5 ka lag the respective extremes in climate by several thousand years, implying that the ice volume response of the GrIS strongly lags climatic changes. Given that Greenland’s climate was getting colder from the Holocene Thermal Maximum (i.e., 8 ka) to the Pre-Industrial era, our simulation implies that the GrIS experienced growth from the mid-Holocene to the industrial era. Due to this background trend, the GrIS still gains mass until the second half of the 20th century, even though anthropogenic warming begins around 1850 AD. This is also in agreement with observational evidence showing mass loss of the GrIS does not begin earlier than the late 20th century. Our results highlight that the present evolution of the GrIS is not only controlled by the recent climate changes, but is also affected by paleoclimate, especially the relatively warm Holocene climate. We propose that the GrIS was not in equilibrium throughout the entire Holocene and that the slow response to Holocene climate needs to be represented in ice sheet simulations in order to predict ice mass loss, and therefore sea level rise, accurately.

Numerical modeling enables a comprehensive understanding not only of the Earth's system today, but also of the past. To date, a significant amount of time and effort has been devoted to paleoclimate modeling and analysis, which involves the latest and most advanced Paleoclimate Modelling Intercomparison Project phase 4 (PMIP4). The definition of seasonality, which is influenced by slow variations in the Earth's orbital parameters, plays a key role in determining the calculated seasonal cycle of the climate. In contrast to the classical calendar used today, where the lengths of the months and seasons are fixed, the angular calendar calculates the lengths of the months and seasons according to a fixed number of degrees along the Earth's orbit. When comparing simulation results for different time intervals, it is essential to account for the angular calendar to ensure that the data for comparison are from the same position along the Earth's orbit. Most models use the classical calendar, which can lead to strong distortions of the monthly and seasonal values, especially for the climate of the past. Here, by analyzing daily outputs from multiple PMIP4 model simulations, we examine calendar effects on surface air temperature and precipitation under mid-Holocene, Last Interglacial, and pre-industrial climate conditions. We came to the following conclusions. (a) The largest cooling bias occurs in boreal autumn when the classical calendar is applied for the mid-Holocene and Last Interglacial, due to the fact that the vernal equinox is fixed on 21 March. (b) The sign of the temperature anomalies between the Last Interglacial and pre-industrial in boreal autumn can be reversed after the switch from the classical to angular calendar, particularly over the Northern Hemisphere continents. (c) Precipitation over West Africa is overestimated in boreal summer and underestimated in boreal autumn when the classical seasonal cycle is applied. (d) Finally, month-length adjusted values f

The North Atlantic subpolar gyre influences the climate in many different ways. Here, we identified that it is also responsible for a recent extreme event of Arctic Ocean freshwater export west of Greenland. A shift in climate regimes occurred in the mid-2000s, with a significant negative trend in the dynamic sea level in the subpolar gyre since then. We found that the dynamic sea level drop induced a strong increase in freshwater export west of Greenland, in particular from 2015 to 2017, when the sea level was close to the minimum. Sea ice melting and atmospheric variability in the Arctic had only a small contribution to this event. As the exported water from the Arctic Ocean has low salinity and constituents of chemical tracers very different from those in the North Atlantic, such events might have impacts on the North Atlantic ecosystem and the climate as well. Our study suggests that such events might be predictable if the subpolar gyre sea level has certain predictability.

Being a vast carbon pool, ocean is an important component of the climate system. It absorbs not only the heat trapped by the greenhouse gasses in the atmosphere, but also a quarter of the anthropogenic carbon dioxide (CO2) emissions itself. Ocean carbon uptake, however, decreases the pH in seawater that has negative implications for marine life. Despite the progress over the last decades, observational data is still sparse in the global oceans. Moreover, there are still gaps in understanding key processes and relevant feedbacks of global ocean carbon source/sink in response to atmospheric CO2 scenarios. Marine biogeochemical models are helpful tools to bridge these gaps. In this study we coupled the Finite-volumE Sea ice-Ocean Model (FESOM2.1) to the Regulated Ecosystem Model (REcoM2). Compared to the previous version FESOM1.4-REcoM2, the model utilizes a new dynamical core based on a finite volume discretization instead of finite elements, but retains the biogeochemical part. Mocsy2.0 computes carbonate chemistry including water vapor correction. It operates on variable mesh resolution. Unlike standard structured-mesh ocean models, the mesh flexibility allows for a realistic representation of small-scale dynamics in key regions at affordable computational cost. Here we present an assessment of the ocean and biogeochemical states simulated with FESOM2.1-REcoM2 in a relatively low spatial resolution global configuration forced with JRA55-do atmospheric reanalysis. A bias present in the previous model version FESOM1.4-REcoM2 in annual mean global ocean-atmosphere CO2 flux can be significantly reduced. Besides, the computational efficiency is about 2-3 times higher than FESOM1.4-REcoM2. Thus, the new coupled model is a promising tool for ocean biogeochemical modelling applications.