Article
Environmental Sciences
Hamid Dashti, William K. Smith, Xueli Huo, Andrew M. Fox, Mostafa Javadian, Charles J. Devine, Ali Behrangi, David J. P. Moore
Summary: The Arctic and Boreal Region (ABR) undergoes extensive land cover change (LCC) due to factors such as wildfire, permafrost thaw, and shrubification. These LCCs alter important biophysical variables including land surface temperature (LST), albedo, and evapotranspiration (ET), which have a significant impact on the warming trend over the ABR. The sensitivity of these variables to different types of LCC in heterogeneous systems like ABR remains uncertain.
ENVIRONMENTAL RESEARCH LETTERS
(2023)
Article
Geochemistry & Geophysics
Yaxuan Chang, Ziti Jiao, Xiaoning Zhang, Linlu Mei, Yadong Dong, Siyang Yin, Lei Cui, Anxin Ding, Jing Guo, Rui Xie, Zidong Zhu, Sijie Li
Summary: This study assessed a series of hotspot-corrected Ross-Li models in fitting POLDER data sets and estimating albedo, especially at large solar zenith angles. The results indicate that BRDF models with appropriately selected kernels are likely to retrieve albedo more accurately at large SZAs, providing guidance for selecting suitable combinations of multiple kernels.
IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING
(2021)
Article
Meteorology & Atmospheric Sciences
Jun Ge, Bo Qiu, Bowen Chu, Duzitian Li, Lingling Jiang, Weidan Zhou, Jianping Tang, Weidong Guo
Summary: This study evaluates the performance of three regional climate models in representing the local biophysical effects of afforestation over continental China. The models do a poor job in describing afforestation-induced changes in surface biophysical properties such as albedo and leaf area index, as well as changes in latent and sensible heat fluxes. However, they are generally reasonable in representing the impact of afforestation on temperature.
JOURNAL OF CLIMATE
(2021)
Article
Geochemistry & Geophysics
Xingwen Lin, Shengbiao Wu, Dalei Hao, Jianguang Wen, Qing Xiao, Qinhuo Liu
Summary: The study assessed the performance of three types of surface reflectance on driving satellite-based albedo, with results showing that sloping reflectance is the best option for retrieval in mountainous areas.
IEEE GEOSCIENCE AND REMOTE SENSING LETTERS
(2022)
Article
Meteorology & Atmospheric Sciences
Xing Luo, Jun Ge, Weidong Guo, Yipeng Cao, Yu Liu, Chaorong Chen, Limei Yang
Summary: This study comprehensively evaluates the performance of four Earth System Models (ESMs) in representing the effects of deforestation. The results show that while the models can capture the general temperature response, they tend to over- or underestimate the magnitude. Biases in the simulated responses of albedo and heat fluxes contribute to these discrepancies. The models consistently overestimate the albedo response under snow-covered conditions and fail to fully reproduce the observed responses of heat fluxes. Model biases in surface temperature responses mainly result from biases related to surface energy partitioning. These findings highlight the need for caution when interpreting simulated results using CMIP6 models and have implications for model improvement.
JOURNAL OF GEOPHYSICAL RESEARCH-ATMOSPHERES
(2023)
Article
Environmental Sciences
Tiffany M. Wei, Ana P. Barros
Summary: The study examines the hydro-climatic resilience of the miombo ecosystem in Southern Africa, highlighting its adaptive traits to water stress and the effectiveness of conserving its spatial structure for increasing crop yields. The grass savanna's high vulnerability to water stress emphasizes the potential severe impacts of miombo deforestation.
Article
Geochemistry & Geophysics
Qing Cheng, Weifeng Hao, Chao Ma, Fan Ye, Jie Luo, Ying Qu
Summary: In this study, a new algorithm called MBRI is proposed to estimate the albedo of Arctic sea ice using MODIS data. The algorithm uses an iteration procedure with multiband spectral reflectance data to retrieve the bidirectional reflectance distribution function of sea ice and calculates the broadband albedo. The generated daily albedo product shows good agreement with in situ sea-ice measurements and reveals a decreasing trend in Arctic sea-ice albedo over the past two decades.
IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING
(2023)
Article
Ecology
Jan Pisek, Angela Erb, Lauri Korhonen, Tobias Biermann, Arnaud Carrara, Edoardo Cremonese, Matthias Cuntz, Silvano Fares, Giacomo Gerosa, Thomas Gruenwald, Niklas Hase, Michal Heliasz, Andreas Ibrom, Alexander Knohl, Johannes Kobler, Bart Kruijt, Holger Lange, Leena Leppanen, Jean-Marc Limousin, Francisco Ramon Lopez Serrano, Denis Loustau, Petr Lukes, Lars Lundin, Riccardo Marzuoli, Meelis Molder, Leonardo Montagnani, Johan Neirynck, Matthias Peichl, Corinna Rebmann, Eva Rubio, Margarida Santos-Reis, Crystal Schaaf, Marius Schmidt, Guillaume Simioni, Kamel Soudani, Caroline Vincke
Summary: The study suggests that accurate retrievals of forest understory NDVI can be obtained using MODIS data and a specific method, with better performance in forest types with open canopies, but limitations in forests with closed canopies and high foliage cover.
Article
Environmental Studies
Jiaxing Xin, Jun Yang, Dongqi Sun, Tianyu Han, Chunrui Song, Zhipeng Shi
Summary: The process of urbanization is accelerating, and land surface temperature (LST) is increasing, posing a serious threat to human health. This study explores the differences in LST of different land use/land cover (LULC) types from the perspective of different climate zones. Results show that urban and built-up lands, as well as barren lands, have higher LSTs compared to forests, grasslands, and water bodies during the day, while the LSTs of urban and built-up lands decrease at night, and barren lands show a significant decrease to LSTs even lower than those of water bodies.
Article
Engineering, Electrical & Electronic
Yijie Tang, Qunming Wang, Peter M. M. Atkinson
Summary: This article proposes a filling then spatio-temporal fusion (FSTF) method to address the challenge of large gaps in MODIS LST data. By utilizing the CLDAS LST product, the FSTF method can more accurately reconstruct the MODIS LST images. The results of the study demonstrate the potential of FSTF for updating the current MODIS LST product globally.
IEEE JOURNAL OF SELECTED TOPICS IN APPLIED EARTH OBSERVATIONS AND REMOTE SENSING
(2023)
Article
Environmental Sciences
Sarchil Hama Qader, Rhorom Priyatikanto, Nabaz R. Khwarahm, Andrew J. Tatem, Jadunandan Dash
Summary: This study provides a comprehensive characterization of the vegetation phenological characteristics of major vegetation types in the Middle East at a fine spatial resolution of 30 m. The results show a progressive pattern in phenophases from low to high latitude, with the earliest start of the season concentrated in the central and east of the region and a significantly delayed end of the season in northern Turkey and Iran. There is a significant positive correlation between phenological parameters and latitude.
Article
Multidisciplinary Sciences
Antoine Saint-Amand, Jonathan Lambrechts, Emmanuel Hanert
Summary: Estimating connectivity between coral reefs is essential for conservation efforts. Researchers assessed the impact of biophysical models resolution on connectivity estimates and found that higher resolution models produced more complex dispersal patterns with weaker connections. Fine-resolution models showed larger clusters of well-connected reefs and increased local retention. As a result, reef management recommendations should be made at scales coarser than the model resolution, not exceeding about 500 m.
SCIENTIFIC REPORTS
(2023)
Article
Environmental Sciences
Richard Massey, Brendan M. Rogers, Logan T. Berner, Sol Cooperdock, Michelle C. Mack, Xanthe J. Walker, Scott J. Goetz
Summary: Deciduous tree cover is expected to increase in North American boreal forests with climate warming and wildfire, potentially generating biophysical cooling. However, recent decades have seen a small net decrease in deciduous fraction and near-neutral net biophysical change in radiative forcing associated with albedo, indicating no systematic negative feedbacks to climate warming.
NATURE CLIMATE CHANGE
(2023)
Article
Geochemistry & Geophysics
Han Ma, Shunlin Liang, Zhiliang Zhu, Tao He
Summary: This article introduces an inversion framework called LoVE-Landsat for estimating spatiotemporal continuous land surface variables from Landsat data. The framework incorporates data assimilation approach, artificial neural networks, and 4DVar and EnKF algorithms. Experimental results demonstrate the effectiveness of the proposed framework in estimating daily land surface variables.
IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING
(2022)
Article
Environmental Sciences
Tianci Guo, Tao He, Shunlin Liang, Jean-Louis Roujean, Yuyu Zhou, Xin Huang
Summary: Surface albedo is a crucial parameter in the surface energy balance and plays a significant role in understanding climate change in urban areas. This study analyzed spatial and temporal changes in surface albedo in Chinese cities to identify the impact of increasing urbanization on regional climate. The results showed an increase in albedo, indicating a cooling effect, and revealed the relationship between surface albedo and landscape transformation.
REMOTE SENSING OF ENVIRONMENT
(2022)
Article
Agronomy
Wenyi Xu, Bo Elberling, Per Lennart Ambus
Summary: The frequency and extent of wildfires in the Arctic have been increasing due to climate change. In this study, researchers conducted experiments in West Greenland to investigate the long-term impacts of climate warming on post-fire carbon dioxide exchange in arctic tundra ecosystems. They found that fire increased soil organic phosphorus concentrations and burned areas remained a net CO2 source five years after the fire. However, with four to five years of summer warming, the burned areas turned into a net CO2 sink.
AGRICULTURAL AND FOREST METEOROLOGY
(2024)
Article
Agronomy
Yuanhang Yang, Jiabo Yin, Shengyu Kang, Louise J. Slater, Xihui Gu, Aliaksandr Volchak
Summary: This study investigates the impacts of water and heat stress on carbon uptake in China and explores the driving mechanisms of droughts using a machine learning model. The results show that droughts are mostly driven by atmospheric dryness, with precipitation, relative humidity, and temperature playing dominant roles. Water and heat stress have negative impacts on carbon assimilation, and drought occurrence is projected to increase significantly in the future. Improving ecosystem resilience to climate warming is crucial in mitigating the negative effects of droughts on carbon uptake.
AGRICULTURAL AND FOREST METEOROLOGY
(2024)
Article
Agronomy
Ningbo Cui, Shunsheng Zheng, Shouzheng Jiang, Mingjun Wang, Lu Zhao, Ziling He, Yu Feng, Yaosheng Wang, Daozhi Gong, Chunwei Liu, Rangjian Qiu
Summary: This study proposes a method to partition evapotranspiration (ET) into its components in agroforestry systems. The method is based on water-carbon coupling theory and flux conservation hypothesis. The results show that the partitioned components agree well with measurements from other sensors. The study also finds that atmospheric evaporation demand and vegetation factors greatly influence the components of ET, and increased tree leaf area limits understory grass transpiration.
AGRICULTURAL AND FOREST METEOROLOGY
(2024)
Article
Agronomy
Xinhao Li, Tianshan Zha, Andrew Black, Xin Jia, Rachhpal S. Jassal, Peng Liu, Yun Tian, Chuan Jin, Ruizhi Yang, Feng Zhang, Haiqun Yu, Jing Xie
Summary: With the rapid increase of urbanization, evapotranspiration (ET) in urban forests has become increasingly important in urban hydrology and climate. However, there is still a large uncertainty regarding the factors that regulate ET in urban areas. This study investigates the temporal variations of ET in an urban forest park in Beijing using the eddy-covariance technique. The results show that daily ET is close to zero during winter but reaches 3-6 mm day-1 in summer. Daily ET increases with vapor pressure deficit (VPD) and soil water content (SWC). Monthly ET increases linearly with normalized difference vegetation index and shows a strong correlation with surface conductance (gs), while exhibiting saturated responses to increasing monthly precipitation (PPT). Annual ET ranges from 326 to 566 mm, and soil water replenishment through PPT from the previous year is responsible for the generally higher monthly ET in spring relative to PPT. Biotic factors and PPT seasonality play essential roles in regulating ET at different scales.
AGRICULTURAL AND FOREST METEOROLOGY
(2024)
Article
Agronomy
Zhaogang Liu, Zhi Chen, Meng Yang, Tianxiang Hao, Guirui Yu, Xianjin Zhu, Weikang Zhang, Lexin Ma, Xiaojun Dou, Yong Lin, Wenxing Luo, Lang Han, Mingyu Sun, Shiping Chen, Gang Dong, Yanhong Gao, Yanbin Hao, Shicheng Jiang, Yingnian Li, Yuzhe Li, Shaomin Liu, Peili Shi, Junlei Tan, Yakun Tang, Xiaoping Xin, Fawei Zhang, Yangjian Zhang, Liang Zhao, Li Zhou, Zhilin Zhu
Summary: This study investigates the responses of temperate grassland (TG) and alpine grassland (AG) to climate change by studying carbon (C) fluxes across different regions in China. The results reveal that water factors consistently increase C fluxes, while temperature factors have opposite effects on TG and AG. The study enhances our understanding of C sinks and grassland sensitivity to climate change.
AGRICULTURAL AND FOREST METEOROLOGY
(2024)
Article
Agronomy
Peng Li, Huijie Li, Bingcheng Si, Tao Zhou, Chunhua Zhang, Min Li
Summary: This study mapped the distribution of forest age on the Chinese Loess Plateau using the LandTrendr algorithm. The results show that the LT algorithm is a convenient, efficient, and reliable method for identifying forest age. The findings have important implications for assessing and quantifying biomass and carbon sequestration in afforestation efforts on the Chinese Loess Plateau.
AGRICULTURAL AND FOREST METEOROLOGY
(2024)
Review
Agronomy
Yean-Uk Kim, Heidi Webber, Samuel G. K. Adiku, Rogerio de S. Noia Junior, Jean-Charles Deswarte, Senthold Asseng, Frank Ewert
Summary: As climate change is expected to increase the intensity and frequency of extreme weather events, it is crucial to assess their impact on cropping systems and explore adaptation options. Process-based crop models (PBCMs) have improved in simulating the impacts of major extreme weather events, but still struggle to reproduce low crop yields under wet conditions. This article provides an overview of the yield-loss mechanisms of excessive rainfall in cereals and the associated modelling approaches, aiming to guide improvements in PBCMs.
AGRICULTURAL AND FOREST METEOROLOGY
(2024)
Article
Agronomy
Xiaodong Liu, Yingjie Feng, Xinyu Zhao, Zijie Cui, Peiling Liu, Xiuzhi Chen, Qianmei Zhang, Juxiu Liu
Summary: Understanding the impact of climate on litterfall production is crucial for simulating nutrient cycling in forest ecosystems. This study analyzed a 14-year litterfall dataset from two subtropical forests in South China and found that litterfall was mainly influenced by wind speed during the wet season and by temperature during the dry season. These findings have potential significance in improving our understanding of carbon and nutrient cycling in subtropical forest ecosystems under climate change conditions.
AGRICULTURAL AND FOREST METEOROLOGY
(2024)
Article
Agronomy
Ruonan Chen, Liangyun Liu, Zhunqiao Liu, Xinjie Liu, Jongmin Kim, Hyun Seok Kim, Hojin Lee, Genghong Wu, Chenhui Guo, Lianhong Gu
Summary: Solar-induced chlorophyll fluorescence (SIF) has the potential to estimate gross primary production (GPP), but the quantitative relationship between them is not constant. In this study, a mechanistic model for SIF-based GPP estimation in evergreen needle forests (ENF) was developed, considering the seasonal variation in a key parameter of the model. The GPP estimates from this model were more accurate compared to other benchmark models, especially in extreme conditions.
AGRICULTURAL AND FOREST METEOROLOGY
(2024)
Article
Agronomy
Jingyi Zhu, Yanzheng Yang, Nan Meng, Ruonan Li, Jinfeng Ma, Hua Zheng
Summary: This study developed a random forest model using climate station and satellite data to generate high-precision precipitation datasets for the Qinghai-Tibet Plateau. By incorporating multisource satellite data, the model achieved a significant enhancement in precipitation accuracy and showed promising results in regions with limited meteorological stations and substantial spatial heterogeneity in precipitation patterns.
AGRICULTURAL AND FOREST METEOROLOGY
(2024)
Article
Agronomy
Yulin Yan, Youngryel Ryu, Bolun Li, Benjamin Dechant, Sheir Afgen Zaheer, Minseok Kang
Summary: Sustainable rice farming practices are urgently needed to meet increasing food demand, cope with water scarcity, and mitigate climate change. Traditional farming methods that prioritize a single objective have proven to be insufficient, while simultaneously optimizing multiple competing objectives remains less explored. This study optimized farm management to increase rice yield, reduce irrigation water consumption, and tackle the dilemma of reducing GHG emissions. The results suggest that the optimized management can maintain or even increase crop yield, while reducing water demand and GHG emissions by more than 50%.
AGRICULTURAL AND FOREST METEOROLOGY
(2024)
Article
Agronomy
Sasha D. Hafner, Jesper N. Kamp, Johanna Pedersen
Summary: This study compared micrometeorological and wind tunnel measurements using a semi-empirical model to understand wind tunnel measurement error. The results showed differences in emission estimates between the two methods, but the ALFAM2 model was able to reproduce emission dynamics for both methods when considering differences in mass transfer. The study provides a template for integrating and comparing measurements from different methods, suggesting the use of wind tunnel measurements for model evaluation and parameter estimation.
AGRICULTURAL AND FOREST METEOROLOGY
(2024)
Article
Agronomy
Wenfang Xu, Wenping Yuan, Donghai Wu, Yao Zhang, Ruoque Shen, Xiaosheng Xia, Philippe Ciais, Juxiu Liu
Summary: In the summer of 2022, China experienced record-breaking heatwaves and droughts, which had a significant impact on plant growth. The study also found that heatwaves were more critical than droughts in limiting vegetation growth.
AGRICULTURAL AND FOREST METEOROLOGY
(2024)
Article
Agronomy
Jiaqi Guo, Xiaohong Liu, Wensen Ge, Liangju Zhao, Wenjie Fan, Xinyu Zhang, Qiangqiang Lu, Xiaoyu Xing, Zihan Zhou
Summary: Vegetation photosynthetic phenology is an important indicator for understanding the impacts of climate change on terrestrial carbon cycle. This study evaluated and compared the abilities of different spectral indices to model photosynthetic phenology, and found that NIRv and PRI are effective proxies for monitoring photosynthetic phenology.
AGRICULTURAL AND FOREST METEOROLOGY
(2024)
Article
Agronomy
Arango Ruda Elizabeth, M. Altaf Arain
Summary: Temperate deciduous forests have significant impacts on regional and global water cycles. This study examined the effects of climate change and extreme weather events on the water use and evapotranspiration of a temperate deciduous forest in eastern North America. The results showed that photosynthetically active radiation and air temperature were the primary drivers of evapotranspiration, while vapor pressure deficit regulated water use efficiency. The study also found a changing trend in water use efficiency over the years, influenced by extreme weather conditions.
AGRICULTURAL AND FOREST METEOROLOGY
(2024)