Agricultural and Forest Meteorology最新文献

{"title":"Different responses of Pinus sylvestris L. and Larix decidua Mill. to forest fire in Central England (UK)","authors":"Francesco Niccoli ,&nbsp;Luigi Marfella ,&nbsp;Jerzy P. Kabala ,&nbsp;Jon Rowe ,&nbsp;Rossana Marzaioli ,&nbsp;Flora A. Rutigliano ,&nbsp;Helen C. Glanville ,&nbsp;Giovanna Battipaglia","doi":"10.1016/j.agrformet.2025.110804","DOIUrl":"10.1016/j.agrformet.2025.110804","url":null,"abstract":"<div><div>The United Kingdom (UK) is facing a growing threat due to the increasing frequency of fires attributed to anthropic pressures and activities. This research analysed the impact of a human-induced 2018 wildfire in a mixed woodland of <em>Pinus sylvestris</em> L. and <em>Larix decidua</em> Mill. in The Roaches Nature Reserve (central England). Through a multidisciplinary approach integrating remote sensing, forest surveys, dendrochronology and soil analysis, we compared burned and non-burned (control) trees to assess the eco-physiological responses of two plant species. Remote sensing supported both the strategic planning of field activities and the characterization of vegetation dynamics affected by fire under pre- and post-fire trajectories, while dendrochronological and soil analyses provided crucial information on post-fire forest dynamics. Results showed that, although both species demonstrated good resistance to the immediate impact of the fire, their responses in terms of resilience and recovery were different in the medium-term (5 years). <em>P. sylvestris</em> (Scots pine) showed good resilience and recovery capacity, with surviving trees showing improved growth within five years, though full recovery may still require several years. In contrast, <em>L. decidua</em> (European larch), although a fire-adapted species, experienced nearly total mortality within three years, most likely because of secondary stressors, such as a pathogen outbreak, which potentially compromised its resilience and recovery capacity in the medium-term. According to our results, climate does not seem to have played a determining role in larch tree mortality, as weather conditions were favourable for both species over the years. Likewise, soil properties showed no variation that could decisively influence survival dynamics. This study highlights the importance of understanding species-specific responses to fire and potential secondary stress factors, emphasizing the need to implement effective management strategies for prevention and management of mixed forests in regions where fire incidence is emerging.</div></div>","PeriodicalId":50839,"journal":{"name":"Agricultural and Forest Meteorology","volume":"374 ","pages":"Article 110804"},"PeriodicalIF":5.7,"publicationDate":"2025-08-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144891027","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"The climatic patterns that control regional fire activity in the Brazilian savanna","authors":"Patrícia S. Silva ,&nbsp;Renata Libonati ,&nbsp;Luiz G. Gonçalves ,&nbsp;Carlos C. DaCamara","doi":"10.1016/j.agrformet.2025.110792","DOIUrl":"10.1016/j.agrformet.2025.110792","url":null,"abstract":"<div><div>Fire activity in the Brazilian savanna (Cerrado) is heavily constrained by climate, however the climate patterns that lead to extreme fire seasons are not yet well understood. Climate conditions during the fire season determine fire weather, but climate patterns prior to the fire season months may also modulate fuel availability and condition. In the context of a changing climate, understanding the climatic patterns that lead to extreme fire events, and their mediating factors, is crucial to build resilient landscapes and inform decision-making. In this study, we propose to uncover the nature of these relationships for Cerrado. We evaluate the regional temperature and precipitation patterns that lead to severe and mild fire seasons for each of the 19 ecoregions of Cerrado. We identify two periods that show contrasting behaviours in both extremes: the concurrent climate conditions during the fire season months (August to October) and pre-conditions during the austral autumn (March to May). Despite noteworthy regional discrepancies, in general we find that severe fire seasons are preceded by hot and dry conditions during autumn and associated with hot and dry conditions during the fire season months. Mild fire seasons see the opposite pattern, with colder and wetter conditions both during and prior to the fire season. We further investigate the influence of these climatic patterns in extreme fire activity for each month of the fire season and find that, over most ecoregions, early fire season burned areas are influenced by pre-conditions during autumn, whereas late fire season burned areas rely on concurrent favourable meteorological conditions. These results contribute to the understanding of the regional fire-climate dynamics of the second largest biome in South America and provide a starting point for regional fire outlooks. We further provide regionally tailored information that, considering recent Brazilian policies, may prove useful for fire management.</div></div>","PeriodicalId":50839,"journal":{"name":"Agricultural and Forest Meteorology","volume":"374 ","pages":"Article 110792"},"PeriodicalIF":5.7,"publicationDate":"2025-08-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144880313","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Variability and uncertainty in net ecosystem carbon exchange modeling: Systematic estimates at global flux sites via ensemble machine learning","authors":"Nannan Wang ,&nbsp;Zijian Yue ,&nbsp;Yaolin Liu ,&nbsp;Zhaomin Tong ,&nbsp;Yanfang Liu ,&nbsp;Yanchi Lu ,&nbsp;Yongge Shi","doi":"10.1016/j.agrformet.2025.110784","DOIUrl":"10.1016/j.agrformet.2025.110784","url":null,"abstract":"<div><div>Predicting net ecosystem carbon exchange (NEE) is crucial for understanding carbon dynamics. Machine learning (ML) has become pivotal for site-level modeling and spatial upscaling for NEE, yet spatiotemporal variability and uncertainty challenge its reliability and universality. Systematically quantifying variability and uncertainty sources in NEE modeling remains lacking due to the scale-dependent nature of carbon flux variations. Thus, this study established a systematic framework to evaluate how model construction choices and environmental predictors could impact ML-based NEE modeling across timescales with multifaceted evaluation criteria. Using observations from FLUXNET 2015, AmeriFlux, and ICOS, alongside multi-source data, this study conducted separate models for each combination of four timescales (daily, weekly, monthly, and yearly), four tree-based ensemble algorithms, and three data-splitting rules. Multi-faceted assessment included overall, across-site, seasonal, and anomaly perspectives. Key findings include: (1) <em>Model construction.</em> Boosting (LightGBM, XGBoost, and CatBoost) excelled in capturing temporal variability and anomaly, whereas bagging (Random Forest) was effective for spatial variability. Complete-random data splitting increased overfitting risks and should be avoided. (2) <em>Predictors.</em> Environmental controls on accuracy varied with timescales, data situations, and ambient conditions. Predictors for NEE modeling should be selected based on their causal importance (e.g., evapotranspiration, vapor pressure deficit, and air temperature) and statistical relationships (e.g., leaf area index, elevation, and precipitation) with NEE, tailored to specific ambient conditions. Excessive predictors may degrade NEE prediction accuracy, particularly at large scales or in regions with high environment like arid areas. (3) <em>Evaluation criteria.</em> Rigorous multi-metric accuracy assessments proved essential, as reliance on single metrics or overall accuracy could yield contradictory results. For instance, daily models achieved higher anomaly NSE (0.33 vs. 0.25) but lower overall NSE (0.54 vs. 0.59) than monthly models. NEE predictions exhibited greater challenges in accounting for spatial than temporal variability, resulting in lower accuracy for inter-annual than intra-annual predictions. This study advances ML-driven carbon flux modeling with actionable insights.</div></div>","PeriodicalId":50839,"journal":{"name":"Agricultural and Forest Meteorology","volume":"374 ","pages":"Article 110784"},"PeriodicalIF":5.7,"publicationDate":"2025-08-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144880058","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Effects of tree geometry on the aerodynamics of sympodial trees with analysis of extreme gust wind","authors":"Pengfei Lin ,&nbsp;Gang Hu ,&nbsp;K.T. Tse ,&nbsp;Anthony Kwan Leung","doi":"10.1016/j.agrformet.2025.110798","DOIUrl":"10.1016/j.agrformet.2025.110798","url":null,"abstract":"<div><div>Trees are among the species most severely affected in coastal regions when storms strike. However, there remains no definitive explanation how the tree geometry affects wind loading of trees. The wind loading of 3-order sympodial tree models with four distinct tree geometry, were thoroughly investigated through wind tunnel experiments in this study. The results show that the tree model with lower branch angles shows lower drag coefficient, while the tree model with higher branch angles shows a lower overturning moment coefficient. Meanwhile, the tree model with lower surface density or weak branch collisions can lead to a faster reduction in wind loading. Subsequently, the tree model with higher branch orders have been confirmed to have a lower drag coefficient and overturning moment coefficient. Then, the effect of extreme gust wind in urbanized areas on the tree models is investigated. Finally, spectral analysis is adopted to reveal the vibration characteristics under uniform wind flow and extreme-gust wind flow.</div></div>","PeriodicalId":50839,"journal":{"name":"Agricultural and Forest Meteorology","volume":"373 ","pages":"Article 110798"},"PeriodicalIF":5.7,"publicationDate":"2025-08-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144864254","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Threshold-governed insulating and cooling effects of snow cover on alpine permafrost: evidence from the Qinghai–Tibet Plateau","authors":"Yao Xiao ,&nbsp;Guojie Hu ,&nbsp;Ren Li ,&nbsp;Tonghua Wu ,&nbsp;Xiaodong Wu ,&nbsp;Guangyue Liu ,&nbsp;Defu Zou ,&nbsp;Zanpin Xing ,&nbsp;Jimin Yao ,&nbsp;Chong Wang ,&nbsp;Lin Zhao","doi":"10.1016/j.agrformet.2025.110802","DOIUrl":"10.1016/j.agrformet.2025.110802","url":null,"abstract":"<div><div>Snow cover critically influences ground thermal regimes and surface energy fluxes in alpine permafrost regions. However, its depth-dependent effects remain poorly understood, particularly on the Qinghai–Tibet Plateau (QTP), where snow is typically thin and short-lived. Using multi-year, high-resolution observations from two contrasting sites (TGL, 5100 m; XDT, 4538 m), we analyzed snow cover characteristics, ground surface temperature (GST) responses, and energy flux dynamics. Piecewise regression revealed site-specific insulation thresholds at 4.1 cm (TGL) and 6.9 cm (XDT). Above these depths, GST variability declined, the difference between GST and air temperature (ΔT) increased, and net radiation and soil heat flux decreased, indicating stronger thermal buffering. Below the thresholds, especially under snow &lt;2 cm, GST amplitude remained high and ΔT low, suggesting enhanced cooling via albedo and melt-induced latent heat loss. Energy fluxes exhibited similarly nonlinear responses, with stronger radiative loss and variability under thin snowpacks, especially at XDT. Transient events missed by daily datasets were captured by high-frequency sensors. Compared to Arctic regions, the QTP’s snow–ground coupling is dominated by shallow-snow processes and strong surface–atmosphere exchange. These findings underscore the need for threshold-aware, depth-sensitive snow parameterizations in cold-region models to better simulate thermal transitions and permafrost responses under changing snow regimes.</div></div>","PeriodicalId":50839,"journal":{"name":"Agricultural and Forest Meteorology","volume":"373 ","pages":"Article 110802"},"PeriodicalIF":5.7,"publicationDate":"2025-08-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144864255","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Mapping range-wide budburst gradients in 22 temperate tree species across the eastern U.S. using quantile regression","authors":"Liang Liang","doi":"10.1016/j.agrformet.2025.110790","DOIUrl":"10.1016/j.agrformet.2025.110790","url":null,"abstract":"<div><div>Phenology plays a pivotal role in ecosystem functioning, and shifts in the timing of phenological events are a key indicator of climate change impacts on the biosphere. However, the sparseness of species-specific observations limits our ability to track phenological changes and their ecological consequences comprehensively. This study addresses this gap by developing a gradient-based spatial prediction approach to map range-wide budburst patterns of temperate tree species in the eastern U.S. Using sparse yet extensive observations from the USA National Phenology Network, I mapped range-wide phenological gradients for 22 species using quantile regression models driven by mean spring temperatures (1991–2020). Despite the simplicity of the modeling approach, the predicted gradients were highly consistent within each species between training and testing datasets, achieving prediction accuracy within 2 to 7 days. The predicted budburst gradients confirm established phenology-climate relationships across space, while revealing species-level variations. Gradients of phenological variability (inter-decile range) revealed decreasing plasticity in budburst timing toward colder climates, potentially due to local adaptation to narrower windows of frost-safe temperatures. This approach also supported quantifying phenological shifts with geographic factors, highlighting species-specific effects of latitude and elevation. Moreover, I demonstrated how interspecific comparisons of phenological surfaces in overlapping ranges could be made to help identify climate-driven mismatches, which may inform studies of species interactions. By integrating range-wide, intra- and interspecific variation across a climatic gradient, this study advances the understanding of phenological patterns in temperate tree species and provides an approach to tracking species-specific phenological changes in a geographically complete manner.</div></div>","PeriodicalId":50839,"journal":{"name":"Agricultural and Forest Meteorology","volume":"373 ","pages":"Article 110790"},"PeriodicalIF":5.7,"publicationDate":"2025-08-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144864337","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Using sentinel-2 data to quantify the impacts of drought on crop yields at local and regional scales in Sweden","authors":"Mitro Müller ,&nbsp;Shangharsha Thapa ,&nbsp;El houssaine Bouras ,&nbsp;Per-Ola Olsson ,&nbsp;Sadegh Jamali ,&nbsp;Lars Eklundh ,&nbsp;Jonas Ardö","doi":"10.1016/j.agrformet.2025.110789","DOIUrl":"10.1016/j.agrformet.2025.110789","url":null,"abstract":"<div><div>A causal inference framework was developed to investigate crop responses to agricultural drought by integrating meteorological data, Sentinel-2-derived data, and soil property maps. To account for crop rotation, soil, and topographical variables, propensity score matching was employed to estimate drought-induced yield losses at the field level for selected periods. The Plant Phenology Index (PPI) and the derived Total Productivity (TPROD) parameter enabled monitoring of crop development and productivity. TPROD showed high regional accuracy (R² = 0.93) and field-level accuracy for estimating crop yields (R² = 0.42–0.73, varying by crop type). The monitoring of common production crops in Sweden during the 2018 drought revealed that all crops had a shortened growing season, with spring-sown crops experiencing greater yield losses. The influence of soil texture variables, which act as indicators of water holding capacity, on the variability of drought-induced yield losses was assessed, and seasonal dynamics were examined, thereby improving the comprehension of the interactions among soil-plant-atmosphere dynamics at a local scale. We conclude that applying propensity score matching combined with satellite remote sensing can provide site-specific information on crop selection and timing and facilitate economically efficient irrigation planning. Nevertheless, further improvements are recommended, such as incorporating more detailed field-level data on yields and management practices, to enhance the approach's robustness and applicability for drought preparedness and adaptive agricultural management.</div></div>","PeriodicalId":50839,"journal":{"name":"Agricultural and Forest Meteorology","volume":"373 ","pages":"Article 110789"},"PeriodicalIF":5.7,"publicationDate":"2025-08-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144864253","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Identifying individual drivers of damage to oak during severe UK storms in winter 2021","authors":"Kate Halstead ,&nbsp;Roy Sanderson ,&nbsp;Salvatore Bonomo ,&nbsp;Christopher Quine ,&nbsp;Andrew Suggitt ,&nbsp;Rachel Gaulton","doi":"10.1016/j.agrformet.2025.110797","DOIUrl":"10.1016/j.agrformet.2025.110797","url":null,"abstract":"<div><div>There has been an increase in windstorm disturbance events in European forests over the past ∼50 years, exacerbated by anthropogenic climate change. In this study, we examined the factors influencing storm damage to oak tree species native to Great Britain (<em>Quercus robur</em> and <em>Quercus petraea</em>) following two successive and severe <em>Storms, Arwen</em> and <em>Barra</em>, in the UK in winter 2021. A combination of novel data collection methods, dendrochronology and remote sensing, and data analysis models, Structural Equation Modelling (SEM) and Random Forest, are used to evaluate storm impacts at both individual tree and site-wide scales. This research directly compares a well-established but data-driven machine-learning method, Random Forest, with a novel, untested approach for wind risk modelling, SEM, to determine whether SEM is a viable method for identifying predictors of storm damage. SEM is a hypothesis-driven method which allows testing of relationships based on prior ecological knowledge. This analysis investigates whether pre-existing health conditions, such as disease and structural defects, influence an oak tree’s vulnerability to storm damage. Both models indicated that individual tree characteristics, notably structural defects and growth rate, were stronger predictors of storm damage than topographic factors. Disease symptoms were also important at the site-wide scale. SEM enabled identification of indirect pathways - for example, showing that disease symptoms were associated with reduced growth, which in turn increased susceptibility to damage - relationships not detected in Random Forest outputs. Furthermore, oak trees with faster growth rates were more prone to storm impacts; across all sites, cumulative growth rates (2000–2015) of storm-damaged trees were 22.8% greater than those of undamaged trees. Our findings contribute to the understanding of wind risk, aiding the parameterisation of risk models for oak, whilst also providing site managers with insights to support conservation efforts. Identifying drivers of damage is crucial given increasing climate-induced storm risk.</div></div>","PeriodicalId":50839,"journal":{"name":"Agricultural and Forest Meteorology","volume":"373 ","pages":"Article 110797"},"PeriodicalIF":5.7,"publicationDate":"2025-08-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144864252","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Climate at play: Norway spruce responses to weather and climate conditions across latitudinal and elevational gradients of Eastern Europe","authors":"Andrei Popa ,&nbsp;Ionel Popa ,&nbsp;Āris Jansons ,&nbsp;Oskars Krišāns ,&nbsp;Pauls Zeltiņs ,&nbsp;Roberts Matisons","doi":"10.1016/j.agrformet.2025.110795","DOIUrl":"10.1016/j.agrformet.2025.110795","url":null,"abstract":"<div><div>During the last decades, Norway spruce has been severely affected by climate change and disturbances, hence substantial alterations in species abundance are anticipated. Although substitution of Norway spruce is considered in Central and Western Europe, in vast parts of Northern and Eastern Europe, the species is still of high economic and ecological importance. To better understand population responses in terms of adaptability in relation to climatic sensitivity, this study aimed to identify and compare sensitivity to the main climatic drivers of Norway spruce from different populations in Europe across comparable climatic gradients. The responses of radial increment of Norway spruce to weather (locally) and climate (regionally) across the extended latitudinal and elevational gradients represented by 61 sites from three distinct populations, i.e., the eastern Baltic region, the Carpathians, as well as Central Europe, were assessed using a dendroclimatological approach and multiple regression techniques (generalized additive mixed models). Nonlinear, multi-month meteorological effects cumulatively explained 18% of interannual variability in radial increment. The responses, however, revealed some population specifics, with distinct sensitivities to water availability and winter and summer temperature. A clear drought signal was evident, particularly through June-July climatic water balance, with increment being highly sensitive to water deficits exceeding 100 mm (two-month scale) and variable responses to moisture excess among the populations. Temperatures in spring and summer had positive effects, yet optimal temperature ranges and response shapes (bell-shaped or sigmoid) varied among the populations. Accordingly, climate change will have disproportional, yet population-specific effects on Norway spruce across Europe, thus suggesting potential for the between-population assisted gene transfer for improvement of local breeding populations.</div></div>","PeriodicalId":50839,"journal":{"name":"Agricultural and Forest Meteorology","volume":"373 ","pages":"Article 110795"},"PeriodicalIF":5.7,"publicationDate":"2025-08-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144860412","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Using reflectance to reduce solar angle effects on the scattering of far-red solar-induced chlorophyll fluorescence to better track the diurnal dynamics of gross primary productivity","authors":"Xuhui Lu ,&nbsp;Peiqi Yang ,&nbsp;Alasdair Mac Arthur ,&nbsp;Christiaan van der Tol","doi":"10.1016/j.agrformet.2025.110794","DOIUrl":"10.1016/j.agrformet.2025.110794","url":null,"abstract":"<div><div>Solar-induced chlorophyll fluorescence (SIF) is linked to photosynthesis and provides reliable estimation of Gross Primary Productivity (GPP). However, SIF observed (SIF_obs) at the top-of-canopy is theoretically less accurate in predicting GPP compared with the total emitted SIF (SIF_total). Converting remotely sensed SIF_obs to SIF_total is therefore crucial for improving GPP estimation. SIF_obs is a portion of SIF_total and their ratio is termed the fluorescence escape ratio (<em>f</em>_esc), describing the scattering and re-absorption processes. <em>f</em>_esc is affected by canopy structure and sun-observer geometry. Vegetation indices, such as the Fluorescence Correction Vegetation Index (FCVI) and the near-infrared reflectance of vegetation (NIR_v), have been developed to estimate <em>f</em>_esc and SIF_total with reasonable accuracy particularly under varying viewing angles scenarios. However, their performance in estimating <em>f</em>_esc and SIF_total has not been well-studied for a diurnal scale, in which solar angles vary. Solar angles affect both <em>f</em>_esc and SIF_total, while viewing angles affect <em>f</em>_esc but not SIF emission. In this study, we analyzed the solar angle effects on far-red SIF scattering and mitigated the effects by leveraging these indices to estimate <em>f</em>_esc, facilitating the derivation of SIF_total for improving GPP estimation. Numerical experiments were employed to support the use of FCVI and NIR_v for <em>f</em>_esc estimation under varying chlorophyll content (<em>C</em>_ab), leaf angle distribution (LAD) and leaf area index (LAI) conditions. SIF_total was derived to enhance the accuracy of GPP estimation at the diurnal scale in filed measurements. Our results indicated that both FCVI and NIR_v reliably estimated <em>f</em>_esc under varying solar angles. Moreover, SIF_total improved the SIF-GPP relationship, with <em>R</em>² increasing to 0.43 – 0.80, compared to SIF_obs (0.12 &lt; <em>R</em>² &lt;0.52), and its diurnal pattern was more consistent with that of GPP. Our study suggested that the use of FCVI and NIR_v for <em>f</em>_esc mitigates solar angle effects on SIF_obs and thus improves GPP estimation.</div></div>","PeriodicalId":50839,"journal":{"name":"Agricultural and Forest Meteorology","volume":"373 ","pages":"Article 110794"},"PeriodicalIF":5.7,"publicationDate":"2025-08-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144864875","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}