This article reviews existing and planned contributions of spaceborne microwave radiometry from P to S band to new measurements of key geophysical variables with a particular focus on the polar regions. It summarizes the current state of spaceborne microwave radiometry to measure ice sheet thermal states, sea ice thickness (SIT), salinity, and sea surface salinity (SSS). Then, this article discusses the potential of wideband radiometry, with continuous sampling in the range of 0.4-2 GHz, as a breakthrough for enhancing the estimation of geophysical variables such as SSS and the geothermal heat flux beneath the polar ice sheets, which are currently monitored primarily using L-band radiometry satellites. Furthermore, this article describes opportunities for new unique observations that cannot be achieved with the current constellation of satellite sensors. In addition, this article demonstrates the advantages of using low-frequency radiometry in sensing soil moisture and biomass from space due to the great sensing depth. This article concludes with a discussion of mission concepts highlighting the CryoRad mission, which has been selected as one of the four candidates for European Space Agency Earth Explorer 12 competition and is now conducting Phase 0 feasibility studies, envisions a 0.4-2-GHz dedicated spaceborne radiometer operated with circular polarization.
The wave-induced breakup of sea ice contributes to the formation of the marginal ice zone in the polar oceans. Understanding how waves fragment the ice cover into individual ice floes is thus instrumental for accurate numerical simulations of the sea ice extent and its evolution, both for operational and climate research purposes. Yet, there is currently no consensus on the appropriate fracturing criterion, which should constitute the starting point of a physically sound wave–ice model. While fracture by waves is commonly treated within a hydroelastic framework and parametrised with a maximum strain-based criterion, in this study we explore a different, energy-based, approach to fracturing. We introduce SWIIFT (Surface Wave Impact on sea Ice – Fracture Toolkit), a one-dimensional model based on linear plate theory, that can produce time-domain simulations of wave-induced fracture, into which we incorporate this energy fracture criterion. We demonstrate SWIIFT with simple simulations that reproduce existing laboratory experiments of the fracture by waves of an analogue material, allowing qualitative comparisons and validations of the energy fracture criterion. We find that under some wave conditions, identified by a dimensionless wavenumber, corresponding to in situ or laboratory wave-induced fracture, the model does not predict fracture at constant curvature; thereby calling into question the appropriateness of parametrising sea ice fracture with a maximum strain criterion.
Anthropogenic forcing not only exacerbates the severity of compound high-temperature and drought events (CHTDE) but also amplifies their impact on maize yield reduction in Northeast China (NEC). Although the statistical linkage between compound events and yield has been extensively documented, the critical thresholds beyond which losses remain poorly constrained. Therefore, this study employs the Copula function to quantify the probability of maize yield loss under CHTDE on basis of the Standardized Dry-and-Hot Index (SDHI) corresponding to different yield loss levels. The anthropogenic influence on these probabilities and thresholds are then assessed, and the expected changes in response to future warming are also evaluated using the DSSAT-CERES-Maize model. Results indicate that the probabilities of >= 40% yield loss under light-to-extreme CHTDE rise from 69.7% to 80.3%; the increments for >= 60% and >= 80% losses are from 49.8% to 64.0% and from 26.7% to 38.0%, respectively. Overall, the probability of yield loss decreases with a higher loss level and increases with the CHTDE intensity amplification. Correspondingly, the SDHI thresholds triggering yield losses from >= 40% to >= 80% decrease from -0.50 to -2.07, indicating that the CHTDE required to trigger yield loss become increasingly extreme. Anthropogenic forcing amplifies these probabilities and thresholds, and its effect is expected to further increase the risk of maize yield loss under future warming. Particularly under SSP5-8.5, the SDHI threshold for >= 70% yield loss is -1.36 in the short-term and -0.91 in the long-term of the 21th century, both lower than the historical -1.60, implying that yield loss can be induced by less severe CHTDE. These findings provide a crucial basis for future risk warning and adaptive strategies for maize production in Northeast China.
The Marginal Ice Zone (MIZ) forms a critical transition region between the ocean and sea ice cover, as it protects the close ice further in from the effect of the steepest and most energetic open ocean waves. As waves propagate through the MIZ, they become exponentially attenuated. Unfortunately, the associated attenuation coefficient is difficult to accurately estimate and model, and there are still large uncertainties around which attenuation mechanisms dominate depending on the conditions. This makes it difficult to predict waves in ice attenuation, as well as sea ice breakup and dynamics. Here, we report in situ observations of strongly modulated waves in ice amplitude, with a modulation period of around 12 h. We show that simple explanations, such as changes in the incoming open water waves or the direct effect of tides and currents and bathymetry on the propagating waves, cannot explain the observed modulation. Therefore, the wave height modulation observed in the ice comes from a modulation of the waves in ice attenuation coefficient. We gather evidence that sea ice convergence and divergence is likely the factor driving this modulation in the attenuation coefficient, through its influence on the ice “closedness”. This implies that the level of sea ice “closedness” needs to be taken into account by future dissipation parameterizations.
In the context of increasing Arctic warming, it is essential to predict changes in Arctic sea ice area (SIA) and the onset of ice-free conditions. The main sources of uncertainty in the projections are internal variability, large variability in the model structures and uncertainty in future emission scenarios. To reduce the uncertainty, we evaluated 27 CMIP6 models over the historical period and selected the nine best performing models using a percentile-based method. For the three considered scenarios (SSP1-2.6, SSP2-4.5 and SSP5-8.5), the respective total reductions in March SIA by the end of the century are 5 CMIP6 models evaluated (1979-2014); 9 selected for reliable Arctic ice projections. Projections are analysed for three Shared Socioeconomic Pathways (SSP). SSP1-2.6: no ice-free Arctic. SSP2-4.5: 2 ice-free months by 2100. SSP5-8.5: 5 months. Models vary in projecting ice-free timing despite good historical performance. Research improves Arctic sea ice projections by stepwise reduction of uncertainty.
