Climate records exhibit scaling behavior with large exponents, resulting in larger fluctuations at longer timescales. It is unclear whether climate models are capable of simulating these fluctuations, which draws into question their ability to simulate such variability in the coming decades and centuries. Using the latest simulations and data syntheses, we find agreement for spectra derived from observations and models on timescales ranging from interannual to multimillennial. Our results confirm the existence of a scaling break between orbital and annual peaks, occurring around millennial periodicities. That both simple and comprehensive ocean-atmosphere models can reproduce these features suggests that long-range persistence is a consequence of the oceanic integration of both gradual and abrupt climate forcings. This result implies that Holocene low-frequency variability is partly a consequence of the climate system's integrated memory of orbital forcing. We conclude that climate models appear to contain the essential physics to correctly simulate the spectral continuum of global-mean temperature; however, regional discrepancies remain unresolved. A critical element of successfully simulating suborbital climate variability involves, we hypothesize, initial conditions of the deep ocean state that are consistent with observations of the recent past.
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http://dx.doi.org/10.1073/pnas.1809959116 | DOI Listing |
Environ Sci Process Impacts
January 2025
Department of Epidemiology and Biostatistics, College of Public Health, Zhengzhou University, 100 Kexue Avenue, Zhengzhou, Henan, 450001, PR China.
: several adverse effects of ozone (O) and nitrogen dioxide (NO) are assessed using combined oxidant capacity (O) and redox-weighted oxidant capacity (Owtx) as surrogates. However, the associations of oxidant capacity (O and Owtx) with platelet-based inflammatory indicators and the potential modifying role of physical activity (PA) remain unclear. : 31 318 participants were selected from the baseline survey of the Henan Rural Cohort Study.
View Article and Find Full Text PDFGlob Chang Biol
January 2025
Department of Biogeochemical Integration, Max Planck Institute for Biogeochemistry, Jena, Germany.
Terrestrial vegetation is a key component of the Earth system, regulating the exchange of carbon, water, and energy between land and atmosphere. Vegetation affects soil moisture dynamics by absorbing and transpiring soil water, thus modulating land-atmosphere interactions. Moreover, changes in vegetation structure (e.
View Article and Find Full Text PDFPNAS Nexus
January 2025
Southern Research Station, US Forest Service, 320 Green Street, Athens, GA 30602, USA.
Wildfires are growing in destructive power, and accurately predicting the spread and intensity of wildland fire is essential for managing ecological and societal impacts. No current operational models used for fire behavior prediction resolve critical fire-atmospheric coupling or nonlocal influences of the fire environment, rendering them inadequate in accounting for the range of wildland fire behavior scenarios under increasingly novel fuel and climate conditions. Here, we present a new perspective on a dominant fire-atmospheric feedback mechanism, which we term wildland fire entrainment (WFE).
View Article and Find Full Text PDFEstimating the impacts of anthropogenic activities and climate change on species' spatial distributions is crucial for conservation. In this study, based on 62 valid occurrence records of and 24 environmental factors (19 climate factors, 4 topographic factors, and 1 human activity factor), we utilized the biomod2 combined model platform to predict suitable habitats for under two current scenarios (Scenario 1: natural state; Scenario 2: human interference state) and two future climate scenarios (SSP1-2.6 and SSP5-8.
View Article and Find Full Text PDFZhongguo Xue Xi Chong Bing Fang Zhi Za Zhi
December 2024
Yunnan Institute of Endemic Diseases Control and Prevention, Yunnan Provincial Key Laboratory for Zoonosis Control and Prevention, Dali, Yunnan 671000, China.
Objective: To predict the potential geographic distribution of in Yunnan Province using random forest (RF) and maximum entropy (MaxEnt) models, so as to provide insights into surveillance and control in Yunnan Province.
Methods: The snail survey data in Yunnan Province from 2015 to 2016 were collected and converted into snail distribution site data. Data of 22 environmental variables in Yunnan Province were collected, including twelve climate variables (annual potential evapotranspiration, annual mean ground surface temperature, annual precipitation, annual mean air pressure, annual mean relative humidity, annual sunshine duration, annual mean air temperature, annual mean wind speed, ≥ 0 ℃ annual accumulated temperature, ≥ 10 ℃ annual accumulated temperature, aridity and index of moisture), eight geographical variables (normalized difference vegetation index, landform type, land use type, altitude, soil type, soil textureclay content, soil texture-sand content and soil texture-silt content) and two population and economic variables (gross domestic product and population).
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