Large‐scale hydro‐climatology of the terrestrial Arctic drainage system

The large‐scale hydro‐climatology of the terrestrial Arctic drainage system is examined, focusing on the period 1960 onward. Special attention is paid to the Ob, Yenisey, Lena, and Mackenzie watersheds, which provide the bulk of freshwater discharge to the Arctic Ocean. Station data are used to compile monthly gridded time series of gauge‐corrected precipitation (P). Gridded time series of precipitation minus evapotranspiration (P−ET) are calculated from the moisture flux convergence using NCEP reanalysis data. Estimates of ET are obtained as a residual. Runoff (R) is obtained from available discharge records. For long‐term water‐year means, P−ET for the Yenisey, Lena, and Mackenzie watersheds is 16–20% lower than the observed runoff. In the Ob watershed, the two values agree within 9%. Given the uncertainties in P−ET, we consider the atmospheric and surface water budgets to be reasonably closed. Compared to the other three basins, the mean runoff ratio (R/P) is lower in the Ob watershed, consistent with the high fraction of annual precipitation lost through ET. All basins exhibit summer maxima in P and minima in P−ET. Summer P−ET in the Ob watershed is negative due to high ET rates. For large domains in northern Eurasia, about 25% of July precipitation is associated with the recycling of water vapor evapotranspirated within each domain. This points to a significant effect of the land surface on the hydrologic regime. Variability in P and P−ET has generally clear associations with the regional atmospheric circulation. A strong link with the Urals trough is documented for the Ob. Relationships with indices of the Arctic Oscillation and other teleconnections are generally weak. Water‐year time series of runoff and P−ET are strongly correlated in the Lena watershed only, reflecting extensive permafrost. Cold‐season runoff has increased in the Yenisey and Lena watersheds. This is most pronounced in the Yenisey watershed, where runoff has also increased sharply in spring, decreased in summer, but has increased for the year as a whole. The mechanisms for these changes are not entirely clear. While they fundamentally relate to higher air temperatures, increased winter precipitation, and strong summer drying, we speculate links with changes in active layer thickness and thawing permafrost

Climate, seasonal snow cover and permafrost temperatures in Alaska north of the Brooks Range

Thesis (Ph.D.) University of Alaska Fairbanks, 1993Climatological data, active layer and permafrost measurements, and modeling were used to investigate the response of permafrost temperatures to changes in climate in Alaska north of the Brooks Range. Mean annual air temperature (MAAT) from 1987 to 1991 within about 110 km from the Arctic Coast was {-12.4}\pm0.3\sp\circ C, while the mean annual permafrost surface temperature (MAPST) ranged from {-9.0}\sp\circ C along the coast to {-5.2}\sp\circ C inland. Air temperature changes alone can not explain the permafrost warming from the coast to inland. Measurements show that MAPST are about 3\sp\circ C to 6\sp\circ C warmer than MAAT in the region. The interaction of local microrelief and vegetation with snow appears to change the insulating effect of seasonal snow cover and may be the major factor which controls the permafrost temperature during the winter and thus the MAPST. Sensitivity analyses show that for the same MAAT conditions, changes in seasonal snow cover parameters can increase or decrease the MAPST about 7\sp\circ C. Snowfall was greater during the cold years and less during the warm years and was poorly correlated between stations. These results suggest that the effects of changes in air temperatures on permafrost temperatures historically may also have been modified by changes in snow cover. A numerical model was used to investigate the effect of changes in initial permafrost temperature conditions, MAAT, seasonal snow cover and thermal properties of soils on the permafrost temperatures. Permafrost may have started warming about the same time as the atmosphere did in the late 1800's, and the long term mean surface temperature of the permafrost may have been established prior to this time. Variations in the penetration depth of the warming signal may be related to differences in thermal properties of permafrost. Variations in the magnitude of the permafrost surface warming may be due to the effect of local factors such as soil type, vegetation, microrelief, soil moisture, and seasonal snow cover. The effect of the interaction of vegetation and snow cover may amplify the signal of temperature change in the permafrost

An observational 71-year history of seasonally frozen ground changes in the Eurasian high latitudes

Abstract In recent decades, significant changes have occurred in high-latitude areas, particularly to the cryosphere. Sea ice extent and thickness have declined. In land areas, glaciers and ice sheets are experiencing negative mass balance changes, and there is substantial regional snow cover variability. Subsurface changes are also occurring in northern soils. This study focuses on these changes in the soil thermal regime, specifically the seasonally frozen ground region of Eurasia. We use a database of soil temperatures at 423 stations and estimate the maximum annual soil freezing depth at the 387 sites located on seasonally frozen ground. Evaluating seasonal freeze depth at these sites for 1930–2000 reveals a statistically significant trend of −4.5 cm/decade and a net change of −31.9 cm. Interdecadal variability is also evident such that there was no trend until the late 1960s, after which seasonal freeze depths decreased significantly until the early 1990s. From that point forward, likely through at least 2008, no change is evident. These changes in the soil thermal regime are most closely linked with the freezing index, but also mean annual air temperatures and snow depth. Antecedent conditions from the previous warm season do not appear to play a large role in affecting the subsequent cold season’s seasonal freeze depths. The strong decrease in seasonal freeze depths during the 1970s to 1990s was likely the result of strong atmospheric forcing from the North Atlantic Oscillation during that time period.</jats:p

Analysis of dynamic stability for wind turbine blade under fluid-structure interaction

Aiming at improving vibration performance of 1.5 MW wind turbine blades, the theoretical model and the calculation process of vibration problems under geometric nonlinearity and unidirectional fluid-structure interaction (UFSI) were presented. The dynamic stability analysis on a 1.5 MW wind turbine blade was carried out. Both the maximum brandish displacement and the maximum Mises stress increase nonlinearly with the increase of wind speed. The influences of turbulent effect, wind shear effect and their joint effect on displacement and stress increase sequentially. Furthermore, the stability critical curves are calculated and analyzed. As a result, the stability region is established where the wind turbine blade can run safely

RadCloud: Real-Time High-Resolution Point Cloud Generation Using Low-Cost Radars for Aerial and Ground Vehicles

In this work, we present RadCloud, a novel real time framework for directly obtaining higher-resolution lidar-like 2D point clouds from low-resolution radar frames on resource-constrained platforms commonly used in unmanned aerial and ground vehicles (UAVs and UGVs, respectively); such point clouds can then be used for accurate environmental mapping, navigating unknown environments, and other robotics tasks. While high-resolution sensing using radar data has been previously reported, existing methods cannot be used on most UAVs, which have limited computational power and energy; thus, existing demonstrations focus on offline radar processing. RadCloud overcomes these challenges by using a radar configuration with 1/4th of the range resolution and employing a deep learning model with 2.25x fewer parameters. Additionally, RadCloud utilizes a novel chirp-based approach that makes obtained point clouds resilient to rapid movements (e.g., aggressive turns or spins), which commonly occur during UAV flights. In real-world experiments, we demonstrate the accuracy and applicability of RadCloud on commercially available UAVs and UGVs, with off-the-shelf radar platforms on-board.Comment: $\copyright$ 2024 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other work

Permafrost Thermal Responses to Asymmetrical Climate Changes: An Integrated Perspective

An integrated perspective of permafrost dynamics is a key bridge between permafrost and global socioeconomic assessments. This study investigated the air temperature changes (1976&ndash;2020) among permafrost zones in the Northern Hemisphere and their potential impacts on permafrost. We found that continuous permafrost zones experienced faster warming than other regions. The freezing index declined 724&deg;C-day while the thawing index increased only 166&deg;C-day over continuous permafrost zones. This may explain why the temperature of cold permafrost increased rapidly but the active layer thickness changed only slightly. Assuming permafrost carbon emissions arise only from thaw processes may miss a significant source of the emissions. An often-neglected factor is that cold-season snow amplifies permafrost warming caused by summertime air temperature changes. Due to seasonal effects, using mean-annual air temperature to depict permafrost evolution under integrated assessment frameworks may lead to significant errors. &nbsp;</p

Deep Lead Optimization: Leveraging Generative AI for Structural Modification

The idea of using deep-learning-based molecular generation to accelerate discovery of drug candidates has attracted extraordinary attention, and many deep generative models have been developed for automated drug design, termed molecular generation. In general, molecular generation encompasses two main strategies: de novo design, which generates novel molecular structures from scratch, and lead optimization, which refines existing molecules into drug candidates. Among them, lead optimization plays an important role in real-world drug design. For example, it can enable the development of me-better drugs that are chemically distinct yet more effective than the original drugs. It can also facilitate fragment-based drug design, transforming virtual-screened small ligands with low affinity into first-in-class medicines. Despite its importance, automated lead optimization remains underexplored compared to the well-established de novo generative models, due to its reliance on complex biological and chemical knowledge. To bridge this gap, we conduct a systematic review of traditional computational methods for lead optimization, organizing these strategies into four principal sub-tasks with defined inputs and outputs. This review delves into the basic concepts, goals, conventional CADD techniques, and recent advancements in AIDD. Additionally, we introduce a unified perspective based on constrained subgraph generation to harmonize the methodologies of de novo design and lead optimization. Through this lens, de novo design can incorporate strategies from lead optimization to address the challenge of generating hard-to-synthesize molecules; inversely, lead optimization can benefit from the innovations in de novo design by approaching it as a task of generating molecules conditioned on certain substructures

REDCAPP (v1.0): Parameterizing valley inversions in air temperature data downscaled from reanalyses

In mountain areas, the use of coarse-grid reanalysis data for driving fine-scale models requires downscaling of near-surface (e.g., 2 m high) air temperature. Existing approaches describe lapse rates well but differ in how they include surface effects, i.e., the difference between the simulated 2 m and upper-air temperatures. We show that different treatment of surface effects result in some methods making better predictions in valleys while others are better in summit areas. We propose the downscaling method REDCAPP (REanalysis Downscaling Cold Air Pooling Parameterization) with a spatially variable magnitude of surface effects. Results are evaluated with observations (395 stations) from two mountain regions and compared with three reference methods. Our findings suggest that the difference between near-surface air temperature and pressure-level temperature (ΔT) is a good proxy of surface effects. It can be used with a spatially variable land-surface correction factor (LSCF) for

Analysis of dynamic stability for wind turbine blade under fluid-structure interaction

Aiming at improving vibration performance of 1.5 MW wind turbine blades, the theoretical model and the calculation process of vibration problems under geometric nonlinearity and unidirectional fluid-structure interaction (UFSI) were presented. The dynamic stability analysis on a 1.5 MW wind turbine blade was carried out. Both the maximum brandish displacement and the maximum Mises stress increase nonlinearly with the increase of wind speed. The influences of turbulent effect, wind shear effect and their joint effect on displacement and stress increase sequentially. Furthermore, the stability critical curves are calculated and analyzed. As a result, the stability region is established where the wind turbine blade can run safely