Agricultural and Forest Meteorology最新文献

{"title":"Microclimate variations in the roughness sublayer above European forests: assessing theories using ICOS network data","authors":"Klara Bouwen, Yves Brunet, Sébastien Lafont, Jean-Christophe Domec, Marie Charru, Christophe Chipeaux, Daniel Berveiller, Matthias Cuntz, Guillaume Simioni, Pasi Kolari, Maarten Krol, Michiel van der Molen, Anne Klosterhalfen, Alexander Knohl, Jérôme Ogée","doi":"10.1016/j.agrformet.2026.111442","DOIUrl":"https://doi.org/10.1016/j.agrformet.2026.111442","url":null,"abstract":"Forests are aerodynamically rough surfaces above which turbulent exchange is enhanced, generating smaller vertical gradients in windspeed and air temperature than those predicted by the Monin-Obukhov Similarity Theory (MOST). Roughness sublayer (RSL) corrections, based on canopy structure, have been proposed to account for this enhancement in turbulent exchange, but evaluation of these RSL corrections above a range of forest types is still lacking. In this study, we mobilised multiyear datasets of canopy structure, turbulent fluxes and microclimate gradients from the ICOS European network to evaluate two widely-used RSL corrections in a range of climates, forest structures and atmospheric conditions. As expected, observed windspeed gradients above these forest sites were smaller than MOST predictions. The two RSL corrections improved the windspeed gradient predictions with similar accuracy, irrespective of atmospheric stability conditions. The need of RSL corrections for predicting air temperature gradients above forests was more contrasted than for windspeed, and depended on the site and the atmospheric stability conditions. Overall, the RSL corrections at canopy height remained relatively small, around 0.5°C for air temperature and 0.5 m s<ce:sup loc=\"post\">-1</ce:sup> for windspeed on average, and were most pronounced under stable atmospheric conditions. Based on the evaluation of the simplifying assumptions behind each RSL correction, we built recommendations to implement those corrections in models. We also discussed the potential impact of wind sensor positions to estimate aerodynamic parameters needed to apply MOST and RSL corrections and provide recommendations for improvement of the ICOS network. Our results highlight the difficulty to estimate displacement height and relate it to canopy structure, and question the idea that the drag coefficient does not change with leaf area or clumping.","PeriodicalId":50839,"journal":{"name":"Agricultural and Forest Meteorology","volume":"5 1","pages":""},"PeriodicalIF":6.2,"publicationDate":"2026-08-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148883917","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":"Corrigendum to “Simultaneous estimation of soil moisture and soil organic matter from in situ dielectric measurements - part 1: Optimal estimation strategy” [Agricultural and Forest Meteorology 386 (2026) 111196]","authors":"Chang-Hwan Park, Ankur Desai, Jingyi Huang, Andreas Colliander, Hyunglok Kim, Thomas Jagdhuber, Venkataraman Lakshmi, Michael H. Cosh, Aaron Berg, Jean-Pierre Wigneron","doi":"10.1016/j.agrformet.2026.111434","DOIUrl":"https://doi.org/10.1016/j.agrformet.2026.111434","url":null,"abstract":"","PeriodicalId":50839,"journal":{"name":"Agricultural and Forest Meteorology","volume":"43 1","pages":""},"PeriodicalIF":6.2,"publicationDate":"2026-08-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148883918","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":"Corrigendum to “Evaluating surface fluxes in WRF using eddy-covariance flux measurements in the Western and Eastern U.S.” [Agricultural and Forest Meteorology 379 (2026) 111029]","authors":"Fan Wu","doi":"10.1016/j.agrformet.2026.111415","DOIUrl":"https://doi.org/10.1016/j.agrformet.2026.111415","url":null,"abstract":"","PeriodicalId":50839,"journal":{"name":"Agricultural and Forest Meteorology","volume":"51 1","pages":"111415"},"PeriodicalIF":6.2,"publicationDate":"2026-08-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148756218","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":"Erratum to “Differential responses of trees to heatwaves in a desert-oasis ecotone: the role of isohydric/anisohydric stomatal regulation” [Agricultural and Forest Meteorology 388 (2026) 111362]","authors":"Hao Huang, Xuewei Gong, Hengfang Wang, Zhengxian Mo, Li Sun, Shengtao Wei","doi":"10.1016/j.agrformet.2026.111400","DOIUrl":"https://doi.org/10.1016/j.agrformet.2026.111400","url":null,"abstract":"","PeriodicalId":50839,"journal":{"name":"Agricultural and Forest Meteorology","volume":"720 1","pages":""},"PeriodicalIF":6.2,"publicationDate":"2026-08-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148716508","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":"Genotype-specific calibration and uncertainty quantification in oil palm modeling: developing a probabilistic framework for tropical American conditions","authors":"Carlos Ricardo Bojacá, Cristihian Bayona, Iván Ayala-Díaz, Alexandre Cooman","doi":"10.1016/j.agrformet.2026.111160","DOIUrl":"https://doi.org/10.1016/j.agrformet.2026.111160","url":null,"abstract":"","PeriodicalId":50839,"journal":{"name":"Agricultural and Forest Meteorology","volume":"17 1","pages":""},"PeriodicalIF":6.2,"publicationDate":"2026-04-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147620307","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":"Similarity of wind speed in the Roughness Sublayer above vegetation","authors":"Raoni Aquino Silva de Santana, Leandro dos Reis Biase Gomes, Marcelo Chamecki, Jose D. Fuentes, Flávio Augusto Farias D’Oliveira, Denisi Holanda Hall, Bruno Takeshi Tanaka Portela, Cléo Quaresma Dias-Júnior","doi":"10.1016/j.agrformet.2026.111155","DOIUrl":"https://doi.org/10.1016/j.agrformet.2026.111155","url":null,"abstract":"","PeriodicalId":50839,"journal":{"name":"Agricultural and Forest Meteorology","volume":"1 1","pages":""},"PeriodicalIF":6.2,"publicationDate":"2026-04-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147620309","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":"Robust estimation of daily photosynthesis from instantaneous observations through machine-learning integration of radiation and environmental drivers","authors":"Yanan Zhou,&nbsp;Xing Li,&nbsp;Jingyu Lin,&nbsp;Xi Liu","doi":"10.1016/j.agrformet.2026.111064","DOIUrl":"10.1016/j.agrformet.2026.111064","url":null,"abstract":"<div><div>Remote sensing (RS) facilitates large-scale estimation of vegetation carbon and water fluxes, yet temporal mismatches persist between its instantaneous observations and the daily flux mean or sum required for ecological modeling. Traditional upscaling methods typically convert instantaneous flux observations to daily values through assuming that diurnal flux patterns are mainly driven by solar radiation, failing to capture real dynamics induced by other environmental factors (e.g., temperature and moisture). This introduces substantial errors, particularly in daily carbon flux estimation. To address this issue, we focus on gross primary production (GPP) and develop a new conversion factor model that integrates solar radiation and other key environmental drivers, enabling robust upscaling from instantaneous to daily scales. Using the FLUXNET2015 dataset, the conversion factor <span><math><msub><mi>γ</mi><mrow><mi>e</mi><mi>n</mi><mi>v</mi></mrow></msub></math></span>, defined as the ratio of instantaneous to daily GPP, was modeled using random forest, with vapor pressure deficit, soil water content, air temperature, and shortwave radiation as predictors. SHapley Additive exPlanations (SHAP) analysis was used to evaluate predictors’ contribution and response mechanisms. Results show that the proposed model outperformed traditional upscaling methods in daily GPP estimation, improving R² by up to 39% and reducing RMSE by up to 82%. Validation across diverse ecosystems, environmental stress levels, and drought conditions further confirmed its superior generalizability over conventional methods. Critically, <span><math><msub><mi>γ</mi><mrow><mi>e</mi><mi>n</mi><mi>v</mi></mrow></msub></math></span> retained high accuracy when driven by ERA5-Land reanalysis data instead of site-level tower measurements and reliably upscaled satellite-based instantaneous GPP snapshots to daily estimates, demonstrating scalability for large-scale applications. Moreover, <span><math><msub><mi>γ</mi><mrow><mi>e</mi><mi>n</mi><mi>v</mi></mrow></msub></math></span> effectively captured complex diurnal dynamics of vegetation photosynthesis under environmental stress, and through SHAP, revealed the growing role of water or temperature-related drivers in regulating GPP diurnal patterns as stress intensified. Overall, this study presents a structurally simple yet ecologically grounded solution to the temporal mismatch in RS-based GPP estimation, and offers valuable insights for upscaling other ecosystem fluxes.</div></div>","PeriodicalId":50839,"journal":{"name":"Agricultural and Forest Meteorology","volume":"380 ","pages":"Article 111064"},"PeriodicalIF":5.7,"publicationDate":"2026-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146147528","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":"Coupling data assimilation and machine learning to improve land surface conditions and near-surface temperature and humidity forecasts","authors":"Xinlei He ,&nbsp;Shaomin Liu ,&nbsp;Tongren Xu ,&nbsp;Fei Chen ,&nbsp;Zhitao Wu ,&nbsp;Ziwei Xu ,&nbsp;Xiang Li ,&nbsp;Rui Liu","doi":"10.1016/j.agrformet.2026.111063","DOIUrl":"10.1016/j.agrformet.2026.111063","url":null,"abstract":"<div><div>Enhancing the representation of land surface conditions and improving the accuracy of near-surface weather forecasts remain critical challenges for numerical weather prediction (NWP). This study coupled a hybrid data assimilation-machine learning framework (DL) with the Weather Research and Forecasting (WRF) model to quantify the impacts of incorporating soil moisture (SM) and vegetation data on land surface initialization and near-surface weather forecast accuracy. This was achieved by integrating satellite-based leaf area index (LAI) and multi-source SM data into the WRF model in the Southern Great Plains (SGP) of the United States. The results indicate that optimizing LAI and SM significantly improves the simulation of water table depth, evapotranspiration (ET), air temperature and humidity in the WRF model. In addition to SM, LAI optimization provides additional benefits to the WRF model in dry years. A series of comparison experiments were conducted across both dry and wet years to evaluate the accuracy of air temperature and humidity forecasts. The optimized vegetation and SM conditions from the DL method were used as initial conditions for the early days of the forecast period. The results confirm that the DL method effectively refines the land surface initial conditions at the beginning of the forecast period. This effect improves the estimation of near-surface atmospheric conditions (e.g., air temperature and humidity) and alters precipitation patterns during the forecast period. In addition, the integration of LAI and SM is more effective in improving forecasts in wet/normal years than dry years. Analysis of the forecast results illustrates that the DL method can optimize initial conditions and improve near-surface weather forecasts over the next month.</div></div>","PeriodicalId":50839,"journal":{"name":"Agricultural and Forest Meteorology","volume":"380 ","pages":"Article 111063"},"PeriodicalIF":5.7,"publicationDate":"2026-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146147527","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":"Warm and wet spring compensated for the reduction in carbon sinks due to an extreme summer heatwave-drought event in 2022 in southern China","authors":"Yuanyuan Zhang ,&nbsp;Fei Jiang ,&nbsp;Yanlian Zhou ,&nbsp;Guanyu Dong ,&nbsp;Dongqiao Wu ,&nbsp;Wei He ,&nbsp;Jun Wang ,&nbsp;Mousong Wu ,&nbsp;Hengmao Wang ,&nbsp;Lingyu Zhang ,&nbsp;Mengwei Jia ,&nbsp;Weimin Ju ,&nbsp;Jing M. Chen","doi":"10.1016/j.agrformet.2026.111060","DOIUrl":"10.1016/j.agrformet.2026.111060","url":null,"abstract":"<div><div>During the July-September (JAS) of 2022, a record-breaking heatwave-drought (DH2022) hit southern China, especially in the middle and lower reaches of the Yangtze River basin (MLYR). It caused an unprecedented decline in vegetation photosynthesis, however, its impact on the regional carbon budget remains unclear. Here, we assessed the response of regional terrestrial carbon fluxes to DH2022 using the Global Carbon Assimilation System (GCAS v2) by assimilating OCO-2 XCO₂ retrievals. Our results indicate that, relative to 2015-2021, the MLYR region experienced a 45.8 TgC reduction in land sink during JAS, consistent with the TRENDYv13 simulations. Combining our inverse results with satellite proxies for GPP, we find that an unusually wet spring in 2022 boosted vegetation growth in the MLYR, increasing gross primary productivity (GPP) by 46.1 TgC and strengthening the land sink by 24.0 TgC, thereby substantially offsetting the carbon sink reductions observed during JAS. Outside the MLYR region in southern China, annual land sink increased by 49.9 TgC in remaining areas (RAS), also greatly mitigating the impact of the DH2022 on the regional carbon balance. Overall, the annual land sink in MLYR decreased by only 7.1 TgC, whereas in southern China, it increased by 42.8 TgC. During JAS, the decreased land sink in MLYR was primarily driven by a decline in GPP in forests and grass/shrub, coupled with an increase in total ecosystem respiration in croplands. Our study provides a comprehensive assessment of land carbon dynamics in southern China under the influence of DH2022, enhancing our understanding of the impacts of climate extremes on the regional carbon cycle.</div></div>","PeriodicalId":50839,"journal":{"name":"Agricultural and Forest Meteorology","volume":"379 ","pages":"Article 111060"},"PeriodicalIF":5.7,"publicationDate":"2026-03-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146129312","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":"Sensitivity of diaheliotropic leaf movement is enhanced in field-grown cotton under moderate water deficit","authors":"Yuan Shi,&nbsp;Fubin Liang,&nbsp;Shuhao Lv,&nbsp;Huijun Song,&nbsp;Jingshan Tian,&nbsp;Yali Zhang,&nbsp;Ling Gou,&nbsp;Wangfeng Zhang","doi":"10.1016/j.agrformet.2026.111028","DOIUrl":"10.1016/j.agrformet.2026.111028","url":null,"abstract":"<div><div>Diaheliotropic leaf movement is pronounced in cotton (<em>Gossypium hirsutum</em> L.) leaves, affecting the interception of photosynthetically active radiation and thus leaf photosynthetic capacity. The leaf movement state is related to soil water content. However, the relationship between diaheliotropic leaf movement characteristics and soil water content in cotton leaves, as well as its effect on leaf photosynthetic capacity is still unclear. In this study, cotton (<em>Gossypium hirsutum</em> L. cv. Xinluzao 45) was subjected to three water treatments: well-watered (control), moderate, and severe water deficit, with the relative soil water content in the 0–60 cm soil layer maintained at 75 ± 5 %, 55 ± 5 %, and 35 ± 5 % of the field capacity, respectively. The cotton leaves were categorized into two groups, free-moving and restrained leaves, to measure diurnal variations in midrib angle, incident photosynthetic photon flux density (PPFD), net photosynthetic rate (Pn), and sucrose and starch content under different water treatments. The results showed that the degree of diaheliotropic leaf movement reached its maximum in the morning (before 12:00). Under water deficit conditions, the time of peak variation in leaf midrib angle was advanced by 0.5–2 h compared to the control. Under moderate water deficit, the rate of midrib angle change in free-moving leaves was 27.9 %–44.3 % higher than that of the control. Accordingly, their incident PPFD was 26.7 %–31.4 % higher and Pn was 19.3 %–35.1 % higher than those in restrained leaves. Free-moving leaves exhibited synergistic changes in sucrose accumulation and water potential under moderate water deficit, and the vascular tissue at the junction of leaf and petiole changed less than that under severe water deficit. Therefore, the production and transport of photoassimilates were not affected under moderate water deficit. The stabilized accumulation of photoassimilates mitigated water stress and enhanced the sensitivity of diaheliotropic leaf movement through sucrose-dominated osmotic adjustment.</div></div>","PeriodicalId":50839,"journal":{"name":"Agricultural and Forest Meteorology","volume":"379 ","pages":"Article 111028"},"PeriodicalIF":5.7,"publicationDate":"2026-03-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146015039","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}