Adaptation of NEMO-LIM3 model for multigrid high resolution Arctic simulation

High-resolution regional hindcasting of ocean and sea ice plays an important role in the assessment of shipping and operational risks in the Arctic Ocean. The ice-ocean model NEMO-LIM3 was modified to improve its simulation quality for appropriate spatio-temporal resolutions. A multigrid model setup with connected coarse- (14 km) and fine-resolution (5 km) model configurations was devised. These two configurations were implemented and run separately. The resulting computational cost was lower when compared to that of the built-in AGRIF nesting system. Ice and tracer boundary-condition schemes were modified to achieve the correct interaction between coarse- and fine grids through a long ice-covered open boundary. An ice-restoring scheme was implemented to reduce spin-up time. The NEMO-LIM3 configuration described in this article provides more flexible and customisable tools for high-resolution regional Arctic simulations

Arctic sea ice dynamics forecasting through interpretable machine learning

Machine Learning (ML) has become an increasingly popular tool to model the evolution of sea ice in the Arctic region. ML tools produce highly accurate and computationally efficient forecasts on specific tasks. Yet, they generally lack physical interpretability and do not support the understanding of system dynamics and interdependencies among target variables and driving factors. Here, we present a 2-step framework to model Arctic sea ice dynamics with the aim of balancing high performance and accuracy typical of ML and result interpretability. We first use time series clustering to obtain homogeneous subregions of sea ice spatiotemporal variability. Then, we run an advanced feature selection algorithm, called Wrapper for Quasi Equally Informative Subset Selection (W-QEISS), to process the sea ice time series barycentric of each cluster. W-QEISS identifies neural predictors (i.e., extreme learning machines) of the future evolution of the sea ice based on past values and returns the most relevant set of input variables to describe such evolution. Monthly output from the Pan-Arctic Ice-Ocean Modeling and Assimilation System (PIOMAS) from 1978 to 2020 is used for the entire Arctic region. Sea ice thickness represents the target of our analysis, while sea ice concentration, snow depth, sea surface temperature and salinity are considered as candidate drivers. Results show that autoregressive terms have a key role in the short term (with lag time 1 and 2 months) as well as the long term (i.e., in the previous year); salinity along the Siberian coast is frequently selected as a key driver, especially with a one-year lag; the effect of sea surface temperature is stronger in the clusters with thinner ice; snow depth is relevant only in the short term. The proposed framework is an efficient support tool to better understand the physical process driving the evolution of sea ice in the Arctic region

How tropical Pacific surface cooling contributed to accelerated sea ice melt from 2007 to 2012 as ice is thinned by anthropogenic forcing

Over the past 40 years the Arctic sea ice minimum in September has declined. The period between 2007 and 2012 showed accelerated melt contributed to the record minima of 2007 and 2012. Here, observational and model evidence shows that the changes in summer sea ice since the 2000s reflects a continuous anthropogenically forced melting masked by interdecadal variability of Arctic atmospheric circulation. This variation is partially driven by teleconnections originating from sea surface temperature (SST) changes in the east-central tropical Pacific via a Rossby wave train propagating into the Arctic (hereafter referred to as the “Pacific-Arctic teleconnection (PARC)”), which represents the leading internal mode connecting the pole to lower latitudes. This mode has contributed to accelerated warming and Arctic sea ice loss from 2007 to 2012, followed by slower declines in recent years, resulting in the appearance of a slowdown over the past 11 years. A pacemaker model simulation, in which we specify observed SST in the tropical eastern Pacific, demonstrates a physically plausible mechanism for the PARC mode. However, the model-based PARC mechanism is considerably weaker and only partially accounts for the observed acceleration of sea ice loss from 2007 to 2012. We also explore features of large-scale circulation patterns associated with extreme melting periods in a long (1800-yr) CESM preindustrial simulation. These results further support the role of remote SST forcing originating from the tropical Pacific in exciting significant warm episodes in the Arctic. However, further research is needed to identify the reasons for model limitations in reproducing the observed PARC mode featuring a Cold Pacific - Warm Arctic connection

The efficient global primitive equation climate model SPEEDO V2.0

The efficient primitive-equation coupled atmosphere-ocean model SPEEDO V2.0 is presented. The model includes an interactive sea-ice and land component. SPEEDO is a global earth system model of intermediate complexity. It has a horizontal resolution of T30 (triangular truncation at wave number 30) and 8 vertical layers in the atmosphere, and a horizontal resolution of 2 degrees and 20 levels in the ocean. The parameterisations in SPEEDO are developed in such a way that it is a fast model suitable for large ensembles or long runs (of O(104) years) on a typical current workstation. The model has no flux correction. We compare the mean state and inter-annual variability of the model with observational fields of the atmosphere and ocean. In particular the atmospheric circulation, the midlatitude patterns of variability and teleconnections from the tropics are well simulated. To show the capabilities of the model, we performed a long control run and an ensemble experiment with enhanced greenhouse gases. The long control run shows that the model is stable. CO2 doubling and future climate change scenario experiments show a climate sensitivity of 1.84KW-1m2, which is within the range of state-of-the-art climate models. The spatial response patterns are comparable to state-of-the-art, higher resolution models. However, for very high greenhouse gas concentrations the parameterisations are not valid. We conclude that the model is suitable for past, current and future climate simulations and for exploring wide parameter ranges and mechanisms of variability. However, as with any model, users should be careful when using the model beyond the range of physical realism of the parameterisations and model setup

Formation and propagation of great salinity anomalies

North Atlantic/Arctic ocean and sea ice variability for the period 1948–2001 is studied using a global Ocean General Circulation Model coupled to a dynamic/thermodynamic sea ice model forced by daily NCEP/NCAR reanalysis data [Kalnay et al., 1996]. Variability of Arctic sea ice properties is analysed, in particular the formation and propagation of sea ice thickness anomalies that are communicated via Fram Strait into the North Atlantic. These export events led to the Great Salinity Anomalies (GSA) of the 1970s, 1980s and 1990s in the Labrador Sea (LS). All GSAs were found to be remotely excited in the Arctic, rather than by local atmospheric forcing over the LS. Sea ice and fresh water exports through the Canadian Archipelago (CAA) are found to be only of minor importance, except for the 1990s GSA. Part of the anomalies are tracked to the Newfoundland Basin, where they enter the North Atlantic Current. The experiments indicate only a minor impact of a single GSA event on the strength of the North Atlantic Thermohaline Circulation (THC)

Scaling and balancing carbon dioxide fluxes in a heterogeneous tundra ecosystem of the Lena River Delta

The current assessments of the carbon turnover in the Arctic tundra are subject to large uncertainties. This problem can (inter alia) be ascribed to both the general shortage of flux data from the vast and sparsely inhabited Arctic region, as well as the typically high spatiotemporal variability of carbon fluxes in tundra ecosystems. Addressing these challenges, carbon dioxide fluxes on an active flood plain situated in the Siberian Lena River Delta were studied during two growing seasons with the eddy covariance method. The footprint exhibited a heterogeneous surface, which generated mixed flux signals that could be partitioned in such a way that both respiratory loss and photosynthetic gain were obtained for each of two vegetation classes. This downscaling of the observed fluxes revealed a differing seasonality in the net uptake of bushes (−0.89 µmol m−2 s−1) and sedges (−0.38 µmol mm−2 s−1) in 2014. That discrepancy, which was concealed in the net signal, resulted from a comparatively warm spring in conjunction with an early snowmelt and a varying canopy structure. Thus, the representativeness of footprints may adversely be affected in response to prolonged unusual weather conditions. In 2015, when air temperatures on average corresponded to climatological means, both vegetation-class-specific flux rates were of similar magnitude (−0.69 µmol m−2 s−1). A comprehensive set of measures (e.g. phenocam) corroborated the reliability of the partitioned fluxes and hence confirmed the utility of flux decomposition for enhanced flux data analysis. This scrutiny encompassed insights into both the phenological dynamic of individual vegetation classes and their respective functional flux to flux driver relationships with the aid of ecophysiologically interpretable parameters. For comparison with other sites, the decomposed fluxes were employed in a vegetation class area-weighted upscaling that was based on a classified high-resolution orthomosaic of the flood plain. In this way, robust budgets that take the heterogeneous surface characteristics into account were estimated. In relation to the average sink strength of various Arctic flux sites, the flood plain constitutes a distinctly stronger carbon dioxide sink. Roughly 42 % of this net uptake, however, was on average offset by methane emissions lowering the sink strength for greenhouse gases. With growing concern about rising greenhouse gas emissions in high-latitude regions, providing robust carbon budgets from tundra ecosystems is critical in view of accelerating permafrost thaw, which can impact the global climate for centuries

Three-dimensional model study of the Arctic ozone loss in 2002/2003 and comparison with 1999/2000 and 2003/2004

We have used the SLIMCAT 3-D off-line chemical transport model (CTM) to quantify the Arctic chemical ozone loss in the year 2002/2003 and compare it with similar calculations for the winters 1999/2000 and 2003/2004. Recent changes to the CTM have improved the model's ability to reproduce polar chemical and dynamical processes. The updated CTM uses σ-θ as a vertical coordinate which allows it to extend down to the surface. The CTM has a detailed stratospheric chemistry scheme and now includes a simple NAT-based denitrification scheme in the stratosphere. In the model runs presented here the model was forced by ECMWF ERA40 and operational analyses. The model used 24 levels extending from the surface to ~55km and a horizontal resolution of either 7.5° x 7.5° or 2.8° x 2.8°. Two different radiation schemes, MIDRAD and the CCM scheme, were used to diagnose the vertical motion in the stratosphere. Based on tracer observations from balloons and aircraft, the more sophisticated CCM scheme gives a better representation of the vertical transport in this model which includes the troposphere. The higher resolution model generally produces larger chemical O3 depletion, which agrees better with observations. The CTM results show that very early chemical ozone loss occurred in December 2002 due to extremely low temperatures and early chlorine activation in the lower stratosphere. Thus, chemical loss in this winter started earlier than in the other two winters studied here. In 2002/2003 the local polar ozone loss in the lower stratosphere was ~40% before the stratospheric final warming. Larger ozone loss occurred in the cold year 1999/2000 which had a persistently cold and stable vortex during most of the winter. For this winter the current model, at a resolution of 2.8° x 2.8°, can reproduce the observed loss of over 70% locally. In the warm and more disturbed winter 2003/2004 the chemical O3 loss was generally much smaller, except above 620K where large losses occurred due to a period of very low minimum temperatures at these altitudes