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2681
Turbulent heat flux dynamics along the Dotson and Getz ice-shelf fronts (Amundsen Sea, Antarctica)
Published 2025-02-01“…Consequently, we rely on models and reanalysis that are un-validated against observations to study the effect of atmospheric forcing on polynya dynamics. We use austral summer 2022 shipboard data to understand the turbulent heat flux dynamics in the Amundsen Sea Polynya and evaluate our ability to represent these dynamics in ERA5. …”
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2682
Intensification of Hurricane Idalia by a river plume in the eastern Gulf of Mexico
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2683
HIDRA3: a deep-learning model for multipoint ensemble sea level forecasting in the presence of tide gauge sensor failures
Published 2025-02-01“…A recently proposed deep-learning model, HIDRA2 (HIgh-performance Deep tidal Residual estimation method using Atmospheric data, version 2), avoids numerical simulations while delivering competitive forecasts. …”
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2684
Tropical Cyclone Size Prediction and Development of An Error Correction Method
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2685
The effects of vessel speed and size on the lethality of strikes of large whales in U.S. waters
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2686
Assessing and optimizing the potential for climate change mitigation and carbon sequestration in urban residential green spaces: energizing sustainable cities
Published 2025-01-01“…IntroductionUrban green spaces play a crucial role in mitigating climate change by sequestering atmospheric carbon dioxide. This study aimed to evaluate the carbon sequestration potential of common plant species in urban residential areas and provide recommendations for optimizing green space design and management.MethodsThe research was conducted in four residential areas of Nanjing, China, where key growth parameters of 20 plant species, including evergreen trees, deciduous trees, evergreen shrubs, and deciduous shrubs, were measured. …”
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2687
Impact of wave–current coupling on the bottom boundary layer in Bohai Bay
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2691
Assessment of WRF Land Surface Model Performance over West Africa
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2692
Compensatory effects conceal large uncertainties in the modelled processes behind the relationship between the El Niño–Southern Oscillation (ENSO) and CO<sub>2</sub>
Published 2025-01-01“…The increasing availability of carbon flux data from atmospheric inversions and remote sensing products makes this a tangible goal that could lead to a better representation of the processes driving interannual variability in the global carbon cycle.…”
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HOLSEA-NL: a Holocene water level and sea level indicator dataset for the Netherlands
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2696
Nitrous Oxide Emissions from Smallholders’ Cropping Systems in Sub-Saharan Africa
Published 2021-01-01“…Increased concentration of atmospheric nitrous oxide (N2O), a potent greenhouse gas (GHG), is of great concern due to its impact on ozone layer depletion leading to climate change. …”
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OH 89: A newly described ~1.8-million-year-old hominid clavicle from Olduvai Gorge
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2698
SuessR: Regional corrections for the effects of anthropogenic CO2 on δ13C data from marine organisms
Published 2021-08-01“…In 2020, net corrections (Suess + Laws corrections) were as follows—Bering Sea: 1.29‰; Aleutian Islands: 1.30‰, Gulf of Alaska: 1.30‰; and Subpolar North Atlantic: 1.31‰ (compared to a global atmospheric CO2 change of ~2.43‰ across the same period). …”
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2699
Health and economic cost estimates of short-term total and wildfire PM2.5 exposure on work loss: using the consecutive California Health Interview Survey (CHIS) data 2015–2018
Published 2024-07-01“…Instruction To help determine the health protectiveness of government regulations and policies for air pollutant control for Americans, our study aimed to investigate the health and economic impacts of work loss due to sickness associated with daily all-source and wildfire-specific PM2.5 (particulate matter with an aerodynamic diameter smaller than 2.5 μm) exposures in California.Methods We linked the 2015–2018 California Health Interview Survey respondents’ geocoded home addresses to daily PM2.5 estimated by satellites and atmospheric modelling simulations and wildfire-related PM2.5 from Community Multiscale Air Quality models. …”
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Enhancing Soil Moisture Prediction in Drought-Prone Agricultural Regions Using Remote Sensing and Machine Learning Approaches
Published 2025-01-01“…Analysis of spatial covariates showed that atmospheric forcing factors, particularly temperature and evaporation, had the most substantial impact on model performance, followed by static factors such as latitude, longitude, and soil texture. …”
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