Vegetation–climate feedbacks across scales

Annals of the New York Academy of Sciences, Год журнала: 2025, Номер unknown

Опубликована: Янв. 24, 2025

Abstract Vegetation is often viewed as a consequence of long‐term climate conditions. However, vegetation itself plays fundamental role in shaping Earth's by regulating the energy, water, and biogeochemical cycles across terrestrial landscapes. It exerts influence consuming water resources through transpiration interception, lowering atmospheric CO 2 concentration, altering surface roughness, controlling net radiation its partitioning into sensible latent heat fluxes. This propagates atmosphere, from microclimate scales to entire boundary layer, subsequently impacting large‐scale circulation global transport moisture. Understanding feedbacks between atmosphere multiple crucial for predicting land use cover changes, accurately representing these processes models. review discusses biophysical mechanisms which modulates spatial temporal scales. Particularly, we evaluate on patterns, precipitation, temperature, considering both trends extreme events, such droughts heatwaves. Our goal highlight state science recent studies that may help advance our collective understanding they play climate.

Язык: Английский

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GLEAM4: global land evaporation and soil moisture dataset at 0.1 resolution from 1980 to near present

Scientific Data, Год журнала: 2025, Номер 12(1)

Опубликована: Март 10, 2025

Terrestrial evaporation plays a crucial role in modulating climate and water resources. Here, we present continuous, daily dataset covering 1980–2023 with 0.1°spatial resolution, produced using the fourth generation of Global Land Evaporation Amsterdam Model (GLEAM). GLEAM4 embraces developments hybrid modelling, learning evaporative stress from eddy-covariance sapflow data. It features improved representation key factors such as interception, atmospheric demand, soil moisture, plant access to groundwater. Estimates are inter-compared existing global products validated against situ measurements, including data 473 sites, showing median correlation 0.73, root-mean-square error 0.95 mm d−1, Kling–Gupta efficiency 0.49. land is estimated at 68.5 × 103 km3 yr−1, 62% attributed transpiration. Beyond actual its components (transpiration, interception loss, evaporation, etc.), also provides potential sensible heat flux, stress, facilitating wide range hydrological, climatic, ecological studies.

Язык: Английский

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Global patterns in observed hydrologic processes

Nature Water, Год журнала: 2025, Номер unknown

Опубликована: Март 31, 2025

Abstract To manage water resources and forecast river flows, hydrologists seek to understand how moves from precipitation, through watersheds, into channels. However, we lack fundamental information on the spatial distribution physical controls global hydrologic processes. This is needed provide theoretical support for large-domain model simulations. Here, address this issue, present a global, searchable database of 400 research watersheds with published descriptions dominant flow pathways. knowledge synthesis approach leverages decades grant funding, fieldwork effort local expertise. We use test longstanding hypotheses about roles climate, biomes landforms in controlling show that aridity predicts depth pathways terrain predict prevalence lateral These new data search capabilities efficient hypothesis testing investigate emergent patterns relate landscape organization function.

Язык: Английский

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Exploring the actual spatial resolution of 1 km satellite soil moisture products

The Science of The Total Environment, Год журнала: 2024, Номер 945, С. 174087 - 174087

Опубликована: Июнь 20, 2024

High-resolution soil moisture data is crucial in the development of hydrological applications as it provides detailed insights into spatiotemporal variability moisture. The emergence advanced remote sensing technologies, alongside widespread adoption machine learning, has facilitated creation continental and global products both at fine spatial (1 km) temporal (daily) scales. Some these rely on several sources input (satellite, situ, modelling), therefore an evaluation their actual resolution required. Nevertheless, absence appropriate ground monitoring networks poses a significant challenge for this assessment. In study, five high-resolution (S1-RT1, S1-COP, SMAP-Planet, SMAP-NSIDC, ESACCI-Zheng) were analysed evaluated throughout Italian territory, together with coarse (12.5 dataset comparison (ASCAT-HSAF). main objective to investigate resolution, accuracy. Firstly, cross-comparison space time carried out, including use triple collocation analysis. Secondly, application-based assessment implemented, considering irrigation, fire, drought, precipitation case studies. results clearly indicate limitations potential each product. Sentinel-1 based (S1-COP S1-RT1) are found able reproduce patterns by detecting localised events precipitation. Their lower leads accuracies than that SMAP-Planet product, comparable SMAP-NSIDC ESACCI-Zheng products. However, have coarser 1 km. study highlights need further research improve products, particularly determine accurately represented At same time, address first opening promising activities operational hydrology water resources management.

Язык: Английский

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Digital twin approach for the soil-plant-atmosphere continuum: think big, model small

Frontiers in Science, Год журнала: 2024, Номер 2

Опубликована: Март 5, 2024

Keywords: Digital twin Earth, soil-plant-atmosphere continuum, soil-plant hydraulics, leaf water potential, cellular scale, turbulence length scale

Язык: Английский

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Precipitation data merging via machine learning: Revisiting conceptual and technical aspects

Journal of Hydrology, Год журнала: 2024, Номер 637, С. 131424 - 131424

Опубликована: Май 25, 2024

The development of accurate precipitation products with wide spatio-temporal coverage is crucial for a range applications. In this context, data merging (PDM) that entails the blending satellite-based estimates ground-based measurements holds prominent position, while currently there an increasing trend in deployment machine learning (ML) algorithms such endeavors. light recent advances field, work discusses key aspects PDM problem associated with: a) conceptual formulation problem, closely related to training ML models and their predictive capacity, b) selection fused, latency final product operational applicability method, c) efficiency single-step two-step approaches, former one treating via only regression latter combined use classification algorithms. By formulating as prediction we define assess two different strategies models, termed full per time step strategy, which entail building single or several respectively. Furthermore, performance allows predictions both spatial temporal dimensions, assessed context merging. each three scenarios, popular ensemble tree-based algorithms, i.e., random forest, gradient boosting extreme algorithm, are employed resulting nine merged products. To provide empirical evidence, employ datacube composed by daily observations, reanalysis estimates, well auxiliary covariates, from 1009 uniformly distributed cells (representative sampling area 25 × km), over four countries around world (Australia, USA, India Italy). large-scale experiment indicates that: (i) strategy competitive alternative since it enables methods improved accuracy, respect metrics reproduction statistics, but also higher capability applicability, (ii) much better occurrence characteristics, reflected improvement relevant categorical metrics, probability autocorrelation coefficient, (iii) no significant difference was noticed

Язык: Английский

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Rainfall estimation in the West African Sahel: comparison and cross-validation of top-down vs. bottom-up precipitation products in Burkina Faso

Geocarto International, Год журнала: 2024, Номер 39(1)

Опубликована: Янв. 1, 2024

Язык: Английский

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A novel approach for estimating groundwater recharge leveraging high-resolution satellite soil moisture

Journal of Hydrology, Год журнала: 2025, Номер unknown, С. 132678 - 132678

Опубликована: Янв. 1, 2025

Язык: Английский

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Monitoring and Modeling the Soil‐Plant System Toward Understanding Soil Health

Reviews of Geophysics, Год журнала: 2025, Номер 63(1)

Опубликована: Янв. 25, 2025

Abstract The soil health assessment has evolved from focusing primarily on agricultural productivity to an integrated evaluation of biota and biotic processes that impact properties. Consequently, shifted a predominantly physicochemical approach incorporating ecological, biological molecular microbiology indicators. This shift enables comprehensive exploration microbial community properties their responses environmental changes arising climate change anthropogenic disturbances. Despite the increasing availability indicators (physical, chemical, biological) data, holistic mechanistic linkage not yet been fully established between functions across multiple spatiotemporal scales. article reviews state‐of‐the‐art monitoring, understanding how soil‐microbiome‐plant contribute feedback mechanisms causes in properties, as well these have functions. Furthermore, we survey opportunities afforded by soil‐plant digital twin approach, integrative framework amalgamates process‐based models, Earth Observation data assimilation, physics‐informed machine learning, achieve nuanced comprehension health. review delineates prospective trajectory for monitoring embracing systematically observe model system. We further identify gaps opportunities, provide perspectives future research enhanced intricate interplay hydrological processes, hydraulics, microbiome, landscape genomics.

Язык: Английский

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Doing better rather than promising more: A basic principle applicable to both climate modelling and climate policies

PLOS Climate, Год журнала: 2025, Номер 4(1), С. e0000466 - e0000466

Опубликована: Янв. 30, 2025

A growing number of scientists are expressing concerns about the inadequacy climate change policies. Fewer questionning dominant modelling paradigm and IPCC’s success to prevent humanity from venturing unprepared into hitherto unknown territories. However, in view an urgent need provide readily available data on constraining uncertainty local regional impacts next few years, there is a debate most suitable path inform both mitigation adaptation strategies. Examples given how common statistical methods emerging technologies can be used exploit wealth existing knowledge drive policy. Parsimonious equitable approaches promoted that combine various lines evidence, including model diversity, large ensembles, storylines, novel applied well-calibrated, global regional, Earth System simulations, deliver more reliable information. As examplified by Paris agreement desirable warming targets, it argued display unrealistic ambitions may not best way for modellers accomplish their long-term objectives, especially consensus emergency allocated short time delivered applied.

Язык: Английский

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