Mesoscale eddies play an important role in both momentum and heat balances in the Southern Ocean. Previous studies have documented an increasing intensity of the Southern Ocean eddy field during recent decades; however, it is still unclear whether the mesoscale eddies with different lifetimes have different temporal variations. Using satellite altimeter observations from 1993 to 2020, we find that the increasing trend in the intensity of eddies is dominated by long-lived eddies (with lifetimes ≥ 90 days), whose amplitude has increased at a rate of ~2.8% per decade; the increase is concentrated downstream of topography. In contrast, short-lived eddies (with lifetimes < 90 days) do not appear to have a significant trend in their amplitudes since the early 1990s. An energy conversion analysis indicates that the increased baroclinic instabilities of the mean flows associated with topography are responsible for the amplitude increase of the long-lived eddies.

The non-linear reliance of channel steepness on erosion rates can be reconciled by the stochastic-threshold incision model that incorporates river incision threshold and discharge probability distribution into erosion efficiency. Here, we explored the usage of the model in river longitudinal profile inversion, by assuming time-dependent tectonic forcing and a linear exponent that relates channel incision to slope. We developed an analytical solution to the model equation and an inverse scheme to retrieve relative uplift rate history, whose validity was based on the theoretical demonstration on knickpoint preservation. Application of the inverse scheme to the main trunks of the Dadu River basin in the eastern Tibetan Plateau produced a history with two-phase increases in the uplift/incision rates, which is similar to the results from low-temperature thermochronology. Thus, our analytical procedures provide new insights into the link of tectonic uplift and river profile evolution, when channel steepness depends on erosion rates non-linearly. 

Products derived from remote sensing reflectances ($R_{rs}(\lambda)$), e.g. chlorophyll, phytoplankton carbon, euphotic depth, or particle size, are widely used in oceanography. Problematically, $R_{rs}(\lambda)$ may have fewer degrees of freedom (DoF) than measured wavebands or derived products. A global sea surface hyperspectral $R_{rs}(\lambda)$ dataset has DoF=4. MODIS-like multispectral equivalent data also have DoF=4, while their SeaWiFS equivalent has DoF=3. Both multispectral-equivalent datasets predict individual hyperspectral wavelengths’ $R_{rs}(\lambda)$ within nominal uncertainties. Remotely sensed climatological multispectral $R_{rs}(\lambda)$ have DoF=2, as information is lost by atmospheric correction, shifting to larger spatiotemporal scales, and/or more open-ocean measurements, but suites of $R_{rs}(\lambda)$-derived products have DoF=1. These results suggest that remote sensing products based on existing satellites’ $R_{rs}(\lambda)$ are not independent and should not be treated as such, that existing $R_{rs}(\lambda)$ measurements hold unutilized information, and that future multi- or especially hyper-spectral algorithms must rigorously consider correlations between $R_{rs}(\lambda)$ wavebands.

Ice cliff distribution plays a major role in determining the melt of debris-covered glaciers but its controls are largely unknown. We assembled a dataset of 37537 ice cliffs and determined their characteristics across 86 debris-covered glaciers within High Mountain Asia (HMA). We complemented this dataset with the analysis of 202 cliff formation events from multi-temporal UAV observations for a subset of glaciers. We find that 38.9% of the cliffs are stream-influenced, 19.5% pond-influenced and 19.7% are crevasses. Surface velocity is the main predictor of cliff distribution at both local and glacier scale, indicating its dependence on the dynamic state and hence evolution stage of debris-covered glacier tongues. Supraglacial ponds contribute to maintaining cliffs in areas of thicker debris, but this is only possible if water accumulates at the surface. Overall, total cliff density decreases exponentially with debris thickness as soon as debris gets thicker than 10 cm.

A document by Linying Gao. Click on the document to view its contents.