Uncertainty of slope length derived from digital elevation models of the Loess Plateau,China

Although many studies have investigated slope gradient uncertainty derived from Digital Elevation Models（DEMs）, the research concerning slope length uncertainty is far from mature. This discrepancy affects the availability and accuracy of soil erosion as well as hydrological modeling. This study investigates the formation and distribution of existing errors and uncertainties in slope length derivation based on 5-m resolution DEMs of the Loess Plateau in the middle of China. The slope length accuracy in three different landform areas is examined to analyse algorithm effects. The experiments indicate that the accuracy of the flat test area is lower than that of the rougher areas. The value from the specific contributing area（SCA） method is greater than the cumulative slope length（CSL）, and the differences between these two methods arise from the shape of the upslope area. The variation of mean slope length derived from various DEM resolutions and landforms. The slope length accuracy decreases with increasing grid size and terrain complexity at the six test sites. A regression model is built to express the relationship of mean slope length with DEM resolution less than 85 m and terrain complexity represented by gully density. The results support the understanding of the slope length accuracy, thereby aiding in the effective evaluation of the modeling effect of surface process.     

Modelling ocean waves in ice-covered seas

Over the past decade there has been a rapid growth of interest in wave propagation through ice covers. This paper summarizes the author’s observation of the modeling efforts on this topic. Models can be theory-based, data-driven, or a combination of the two. A pure data-driven model relies on a large amount of observations and is only becoming available recently. Theory-based models on the other hand have a long history. They are always a simplified version of the reality. As our knowledge grows, theories become more complicated. A theory for waves-in-ice that captures all possible processes does not exist. However, when integrated with observation through calibration, these combined theory + data-based models may be used with some confidence. In this paper, different models, their basic concepts, their calibration and validation are discussed. The present theory-based models do not have the correct spectral attenuation trend as observed from field or laboratory experiments. Hence, through calibration they may fit different parts of the wave spectra but not all. Pure data-driven models can reproduce the correct trend, but its dependability outside the situation where the data are collected is uncertain. In addition to offering tools to forecast waves-in-ice, these model building and validating efforts point to missing mechanisms that should be carefully studied. Despite the many challenges towards building a satisfactory general waves-in-ice model, significant progress has been made for models that work reasonably well in the marginal ice zone. We anticipate much more data will become available in the coming years to help us improve the existing models.     

IPCC emission scenarios: How did critiques affect their quality and relevance 1990–2022?

Long-term global emission scenarios enable the analysis of future climate change, impacts, and response strategies by providing insight into possible future developments and linking these different climate research elements. Such scenarios play a crucial role in the climate change literature informing the Intergovernmental Panel on Climate Change’s (IPCC) Assessment Reports (ARs) and support policymakers. This article reviews the evolution of emission scenarios, since 1990, by focusing on scenario critiques and responses as published in the literature. We focus on the issues raised in the critiques and the possible impact on scenario development. The critique (280) focuses on four areas: 1) key scenario assumptions (40%), 2) the emissions range covered by the scenarios and missing scenarios (25%), 3) methodological issues (24%), and 4) the policy relevance and handling of uncertainty (11%). Scenario critiques have become increasingly influential since 2000. Some areas of critique have decreased or become less prominent (probability, development process, convergence assumptions, and economic metrics). Other areas have become more dominant over time (e.g., policy relevance & implications of scenarios, transparency, Negative Emissions Technologies (NETs) assumptions, missing scenarios). Several changes have been made in developing scenarios and their content that respond to the critique.