Article
Water Resources
Vinayak Huggannavar, J. Indu
Summary: This study evaluates the simulated soil moisture of WRF-NoahMP model using two different configurations and finds that the GW model improves soil moisture and latent heat flux in the Ganga River basin. However, the model overestimates the groundwater table depth and lacks consideration of anthropogenic factors such as groundwater pumping.
HYDROLOGICAL PROCESSES
(2023)
Article
Meteorology & Atmospheric Sciences
Chunhui Jia, Ping Zhao, Jingfeng Wang, Yi Deng, Na Li, Yingchun Wang, Shiguang Miao
Summary: The coupling of the maximum entropy production (MEP) model with the Noah land surface model (LSM) in the Weather Research and Forecasting (WRF) model improves the calculation of surface sensible heat (SH) and latent heat (LE) fluxes, particularly in complex terrains. The MEP model reduces the overestimation of SH and LE, and the underestimation of the surface ground heat flux. It also reduces the cold and wet biases and improves the accuracy of soil temperature and daily precipitation estimations.
JOURNAL OF GEOPHYSICAL RESEARCH-ATMOSPHERES
(2023)
Article
Meteorology & Atmospheric Sciences
K. Warrach-Sagi, J. Ilgwersen, T. Schwitalla, C. Troost, J. Aurbacher, L. Jach, T. Berger, T. Streck, V Wulfmeyerl
Summary: This paper couples a crop growth model with a weather model and conducts an impact study at a small scale in Germany. The results demonstrate that weather driven crop growth significantly influences land-atmosphere feedback, improving temperature biases and enhancing distributed added value.
JOURNAL OF GEOPHYSICAL RESEARCH-ATMOSPHERES
(2022)
Article
Meteorology & Atmospheric Sciences
Marc J. Alessi, Dimitris A. Herrera, Colin P. Evans, Arthur T. DeGaetano, Toby R. Ault
Summary: The strengthening land-atmosphere coupling in the northeastern United States, along with a positive soil moisture-rainfall feedback, may contribute to an increase in drought. This study indicates that future summers in the region may see drier soil conditions and a higher occurrence of droughts.
JOURNAL OF GEOPHYSICAL RESEARCH-ATMOSPHERES
(2022)
Article
Environmental Sciences
Sachin Budakoti, Tejasvi Chauhan, Raghu Murtugudde, Subhankar Karmakar, Subimal Ghosh
Summary: The study examines the impact of interannual variations of vegetation on Indian Summer Monsoon Rainfall (ISMR) and suggests that representing time-varying leaf area index (LAI) is crucial for accurate predictions of ISMR, particularly during drought years. Using numerical experiments and information theory-based analysis, the research highlights the importance of regional land-atmosphere feedbacks in influencing the variability of ISMR.
WATER RESOURCES RESEARCH
(2021)
Article
Green & Sustainable Science & Technology
Igor Gomez, Sergio Molina, Juan Jose Galiana-Merino, Maria Jose Estrela, Vicente Caselles
Summary: This study evaluates the ability of the WRF model to forecast surface energy fluxes in Eastern Spain and finds that Noah-MP physics options strongly impact energy partitioning in short-timescale simulations, with simulated surface skin temperature by Noah-MP being colder than that obtained by the original Noah LSM.
Article
Agronomy
Trevor F. Partridge, Jonathan M. Winter, Anthony D. Kendall, David W. Hyndman
Summary: Integrating dynamic crop growth into climate models can reduce biases in simulated leaf area index over croplands, but does not lead to significant differences in evapotranspiration, temperature, and precipitation simulations. Errors in simulating crop yield vary depending on year and spatial resolution, with the use of observed climate data helping to reduce the range of errors.
AGRICULTURAL AND FOREST METEOROLOGY
(2021)
Article
Geosciences, Multidisciplinary
Chia-Jeng Chen, Min-Hung Chi, Jing-Ru Ye
Summary: Modeling techniques are used in this study to analyze the response of regional hydroclimate in central Taiwan to changes in land use conditions. The results show that land use/cover change significantly affects heat fluxes, surface variables, and precipitation. These changes also influence runoff characteristics, with an increase in average peak flow and total runoff volume. The study emphasizes the importance of comprehensive model physics in regional hydroclimate modeling.
GEOSCIENCE LETTERS
(2023)
Article
Environmental Sciences
Chenxiang Ju, Huoqing Li, Man Li, Zonghui Liu, Yufen Ma, Ali Mamtimin, Mingjing Sun, Yating Song
Summary: By evaluating the Noah and Noah-MP land surface schemes in the Central Asia arid region, it was found that the Noah-MP model performs better in simulating soil temperature and soil moisture compared to the Noah model, but has decreased performance in simulating 10-m wind speed and 2-m air temperature.
Article
Meteorology & Atmospheric Sciences
Liang Qiao, Zhiyan Zuo, Dong Xiao
Summary: This study evaluates global shallow and deep soil moisture in CMIP6 simulations using multiple reanalysis datasets. The multimodel ensemble mean produces generally reasonable simulations, but significant discrepancies exist at high elevations and latitudes and in extreme arid areas.
JOURNAL OF CLIMATE
(2022)
Article
Agriculture, Multidisciplinary
Lingxue Yu, Ye Liu, Tingxiang Liu, Entao Yu, Kun Bu, Qingyu Jia, Lidu Shen, Xingming Zheng, Shuwen Zhang
Summary: This study examines the simulation of crop growth and yield in Northeast China by coupling crop models with climate models. The results show that the coupled model improves the accuracy of crop phenology simulation and enhances the performance of crop growth simulation. Adjusting crop parameters further improves the simulation results. This research is important for ensuring future crop growth and food security.
COMPUTERS AND ELECTRONICS IN AGRICULTURE
(2022)
Article
Geosciences, Multidisciplinary
Yingzuo Qin, Dashan Wang, Ye'er Cao, Xitian Cai, Shijing Liang, Hylke E. Beck, Zhenzhong Zeng
Summary: Understanding the regional climate response to land cover change requires an accurate sub-grid representation of vegetation cover in climate models. The Community Land Model (CLM) is advanced and shows better performance in simulating surface air temperature and precipitation compared to other land surface schemes. By reactivating the theoretical sub-grid vegetation cover representation in the Weather Research and Forecasting (WRF)-CLM model, it was found to successfully capture the sensitivity of evapotranspiration (ET) and temperature to deforestation, improving the spatial pattern responses of simulated ET and temperature to regional deforestation.
GEOPHYSICAL RESEARCH LETTERS
(2023)
Article
Geosciences, Multidisciplinary
Yu Cheng, Kaighin A. Mccoll
Summary: Deforestation, urbanization and construction of wind farms can change land surface roughness and influence surface heat fluxes, weather and climate. Anomalies in land surface roughness can trigger convergence and cause mesoscale circulations and anomalous precipitation. This mechanism is not present in climate models and may be relevant to storm formation over wind farms, cities and forests.
GEOPHYSICAL RESEARCH LETTERS
(2023)
Article
Environmental Sciences
Natthachet Tangdamrongsub
Summary: Hydrology and land surface models are important tools for estimating global terrestrial water storage. This study compares the performance of six global TWS models using GRACE and GRACE-FO satellite data. The results show that Noah-MP and PCR-GLOBWB perform the best at a global scale, while CABLE performs the best in Australia. Additionally, ensemble models yield more accurate results than individual models. The findings of this study are important for future model development and scientific advancements in hydrology.
Article
Environmental Sciences
Xiaohang Wen, Xian Zhu, Maoshan Li, Mei Chen, Shaobo Zhang, Xianyu Yang, Zhiyuan Zheng, Yikun Qin, Yu Zhang, Shihua Lv
Summary: The Qinghai-Tibet Plateau plays a crucial role in the global climate system and is highly sensitive to climate change. However, the challenging environmental conditions and limited observation stations make it difficult to accurately study the land-atmosphere interactions and their effects. To address this, we used the WRF model and a 3DVAR assimilation method to create a high-resolution assimilated dataset (HRAD), which has been validated and can be utilized for further studies on land-atmosphere interactions, water cycling, radiation energy transfer, and extreme weather events in the region.
