Article
Environmental Sciences
Ilias Agathangelidis, Constantinos Cartalis, Anastasios Polydoros, Thaleia Mavrakou, Kostas Philippopoulos
Summary: This study examines heatwave events in the Mediterranean region using surface temperature data and satellite remote sensing technology. The results demonstrate that remotely sensed land surface temperature can effectively indicate heatwave events, with a higher correlation to extremely hot days and long-duration heatwaves.
Article
Agronomy
Lelia Weiland, Cheryl A. Rogers, Camile Sothe, M. Altaf Arain, Alemu Gonsamo
Summary: Soil respiration, a key ecosystem process, can be estimated using satellite-derived land surface temperature and soil moisture. This study evaluated three empirical models and a Random Forest algorithm, which were calibrated using in-situ measurements and validated against soil CO2 fluxes from automatic chambers. The results showed that satellite observations can explain over 70% of the variability in soil respiration and provide comparable accuracy to in-situ measurements.
AGRICULTURAL AND FOREST METEOROLOGY
(2023)
Article
Astronomy & Astrophysics
Yongjie Pan, Yanhong Gao, Suosuo Li
Summary: This study investigated the impact of uncertainty in LULC maps on LST simulation using the CLM4.5 model, revealing that the model can accurately simulate ground temperature but shows large differences compared to MODIS_LST, especially over crop areas. Different LULC products also led to significant dissimilarity in simulated results over forest areas, primarily due to the different identification methods for forest types. Replacing the LAI in the model default data with the MODIS_LAI product greatly reduced the LST simulation biases.
EARTH AND SPACE SCIENCE
(2021)
Article
Geography, Physical
Zefeng Xing, Zhao-Liang Li, Si-Bo Duan, Xiangyang Liu, Xiaopo Zheng, Pei Leng, Maofang Gao, Xia Zhang, Guofei Shang
Summary: This study proposes a practical method to estimate daily mean land surface temperature (LST) using MODIS-derived instantaneous LST products, with reliable results validated through in situ measurements. The method is successfully applied to calculate global annual cycle parameters and shows potential for various applications in global LST trend analysis and climate change.
ISPRS JOURNAL OF PHOTOGRAMMETRY AND REMOTE SENSING
(2021)
Article
Environmental Sciences
Nurul Iman Saiful Bahari, Farrah Melissa Muharam, Zed Zulkafli, Norida Mazlan, Nor Azura Husin
Summary: MODIS land surface temperature data are measured from the earth's surface via satellites and have discrepancies when compared to air temperature data, but a relationship between the two has been established. By applying different correction methods, such as Linear Scaling and Quantile Mapping Mean Bias Correction, the accuracy of MODIS T-s products can be improved, with different methods performing better in station vs. regional analysis.
Article
Geochemistry & Geophysics
Hua Li, Ruibo Li, Yikun Yang, Biao Cao, Zunjian Bian, Tian Hu, Yongming Du, Lin Sun, Qinhuo Liu
Summary: In this study, two MODIS land surface temperature products were evaluated using temperature-based and radiance-based methods over barren surfaces and sand dunes in Northwestern China. The results showed that the C6 MYD21 LST product has better accuracy and consistency than the C6 MYD11 product, especially in sand dune areas.
IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING
(2021)
Article
Environmental Sciences
Yao Xiao, Wei Zhao, Mingguo Ma, Kunlong He
Summary: The proposed method utilizes a linking model with random forest regression and incorporates accumulated solar radiation from sunrise to satellite overpass to represent cloud impact on LST. It successfully generates gap-free LST products for Chongqing City. Visual assessment and validation with in situ observations show that the reconstructed cloud-covered LSTs perform similarly to clear-sky LSTs, with an unbiased root mean squared error of 2.63 K.
Article
Geography, Physical
Junrui Wang, Ronglin Tang, Yazhen Jiang, Meng Liu, Zhao-Liang Li
Summary: A practical angular normalization method was developed to correct the angular anisotropy of MODIS off-nadir LST products over vegetated surfaces. The method was validated using data from 213 sites worldwide and compared to Sentinel-3A nadir LST products. The results showed high accuracy and significance in operationally correcting MODIS LST products for further applications.
ISPRS JOURNAL OF PHOTOGRAMMETRY AND REMOTE SENSING
(2023)
Article
Geochemistry & Geophysics
Kukku Sara, R. Eswar, B. K. Bhattacharya
Summary: This study tested the application of simplified spatial disaggregation models across the temporal domain to obtain higher spatial resolution land surface temperature observations and capture diurnal temperature changes. The results indicated that the DisTrad model performed well in capturing spatiotemporal patterns, while the NL-DisTrad model showed inconsistency.
IEEE GEOSCIENCE AND REMOTE SENSING LETTERS
(2022)
Article
Environmental Sciences
Serkan Kartal, Aliihsan Sekertekin
Summary: The accurate prediction of land surface temperature (LST) is crucial for climate change, ecology, environmental, and industrial studies. This study utilized various machine learning models to predict LST and employed different methods to address the issue of missing pixels. The performance of the models was evaluated through metrics such as root mean square error and mean absolute error, using data from a specific region in Turkey.
ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH
(2022)
Article
Geochemistry & Geophysics
Rui Yao, Lunche Wang, Xin Huang, Liang Sun, Ruiqing Chen, Xiaojun Wu, Wei Zhang, Zigeng Niu
Summary: The study introduced an enhanced hybrid (EH) method for gapfilling, utilizing information from similar LST products to improve accuracy. Results showed that the EH method had higher accuracy compared to other methods, demonstrating the effectiveness of using information from other similar products.
IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING
(2021)
Article
Engineering, Electrical & Electronic
Penghua Hu, Aihui Wang, Yingbao Yang, Xin Pan, Xiejunde Hu, Yuncheng Chen, Xuechun Kong, Yao Bao, Xiangjin Meng, Yang Dai
Summary: This study proposes a novel spatiotemporal fusion model of land surface temperature (LST) based on diurnal variation information (BDSTFM) to predict LST data with high temporal resolution and spatiotemporal continuity. The BDSTFM model achieves a high level of accuracy in downscaling and can obtain realistic and reliable 1-km seamless LST datasets.
IEEE JOURNAL OF SELECTED TOPICS IN APPLIED EARTH OBSERVATIONS AND REMOTE SENSING
(2022)
Article
Environmental Sciences
Bing Li, Shunlin Liang, Xiaobang Liu, Han Ma, Yan Chen, Tianchen Liang, Tao He
Summary: This study proposes a methodology for generating all-sky Land Surface Temperature (LST) products by combining multiple datasets, showing strong model stability and producing more accurate spatial patterns over the contiguous United States compared to existing products.
REMOTE SENSING OF ENVIRONMENT
(2021)
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
Juby Thomas, Manika Gupta, Prashant K. Srivastava, Dharmendra K. Pandey, Rajat Bindlish
Summary: This study proposes a new method to estimate high-resolution Soil Hydraulic Parameters (SHPs) and provide high-resolution rootzone soil moisture (RZSM) products. The method consists of three phases: downsampling satellite soil moisture to estimate surface soil moisture, using downscaled soil moisture to estimate SHPs, and simulating surface soil moisture and RZSM using the derived SHPs.
Article
Environmental Sciences
Andrew J. Newman, Andrew J. Monaghan, Martyn P. Clark, Kyoko Ikeda, Lulin Xue, Ethan D. Gutmann, Jeffrey R. Arnold
Summary: The Arctic is warming faster than the global average, with varying impacts on snowfall and snowpack across different regions. There are significant changes in snow cover and snowfall fractional contributions during spring and fall seasons. Differences in climate reference and future regional climate model simulations are evident, particularly in areas of complex topography.
Article
Meteorology & Atmospheric Sciences
Kyoko Ikeda, Roy Rasmussen, Changhai Liu, Andrew Newman, Fei Chen, Mike Barlage, Ethan Gutmann, Jimy Dudhia, Aiguo Dai, Charles Luce, Keith Musselman
Summary: This study examines current and future western U.S. snowfall and snowpack through climate simulations. The research shows significant impacts of climate change on the water cycle in the western U.S., especially in coastal mountain ranges. The study indicates that snowpack in the Pacific Northwest is predicted to decrease by around 70% by 2100, with most snowpack potentially gone before that time.
Article
Water Resources
Jessica D. Lundquist, Susan Dickerson-Lange, Ethan Gutmann, Tobias Jonas, Cassie Lumbrazo, Dylan Reynolds
Summary: When formulating hydrologic models, scientists often rely on parameterizations from pre-existing models rather than re-evaluating field experiments. Increasing temperatures can lead to a decrease in simulated snow under canopy, but the magnitude of the change varies based on environmental conditions and processes.
HYDROLOGICAL PROCESSES
(2021)
Article
Water Resources
Hannah M. Bonner, Mark S. Raleigh, Eric E. Small
Summary: Understanding the influence of forest canopy on snowpack density and snow water equivalent is crucial for accurate model predictions. The study found that delivery effects have the greatest impact on snowpack density, while mass effects and radiation effects have the greatest impact on the differences in snow water equivalent between forest and open areas.
HYDROLOGICAL PROCESSES
(2022)
Article
Environmental Sciences
Eric J. Smyth, Mark S. Raleigh, Eric E. Small
Summary: Intermittent snow depth observations can be improved with data assimilation, specifically with the implementation of a particle filter technique. This technique reduces errors in snow depth, density, and snow water equivalent at forest locations. The assimilation process also considers the impact of forest canopy on snow accumulation and melt. The study highlights the importance of accurate measurement, estimation, or calibration of canopy-related parameters, which can be reduced through data assimilation.
WATER RESOURCES RESEARCH
(2022)
Article
Environmental Sciences
Mark S. Raleigh, Ethan D. Gutmann, John T. Van Stan, Sean P. Burns, Peter D. Blanken, Eric E. Small
Summary: This study examines the use of monitoring tree sway to detect snow interception and quantify canopy snow water equivalent (SWE). The researchers found that larger changes in tree sway were generally not attributed to thermal effects, and the presence of canopy snow was correlated with total snowstorm amounts.
WATER RESOURCES RESEARCH
(2022)
Article
Meteorology & Atmospheric Sciences
Ethan D. Gutmann, Joseph. J. Hamman, Martyn P. Clark, Trude Eidhammer, Andrew W. Wood, Jeffrey R. Arnold
Summary: Statistical processing of numerical model output has been widely used in weather forecasting and climate applications for decades. This study proposes a unified framework to evaluate the decisions made in the methods used to statistically postprocess output from weather and climate models. The Ensemble Generalized Analog Regression Downscaling (En-GARD) method is introduced, which allows users to select input variables, predictors, mathematical transformations, and combinations for downscaling approaches. The study applies En-GARD to regional climate model simulations to evaluate the impact of different downscaling method choices on current and future climate.
JOURNAL OF HYDROMETEOROLOGY
(2022)
Article
Environmental Sciences
Hannah M. Bonner, Eric Smyth, Mark S. Raleigh, Eric E. Small
Summary: This study presents meteorology and snow observation data collected in the southwestern Colorado Rocky Mountains over three water years with different amounts of snow water equivalent accumulation. The dataset focuses on open-forest sites in a continental snow climate and includes measurements of snow pits, snow depth, and meteorological variables. The data is available for download and can be used to improve model representation of snow processes.
WATER RESOURCES RESEARCH
(2022)
Article
Environmental Sciences
Liza J. Wernicke, Clara C. Chew, Eric E. Small, Narendra N. Das
Summary: This study developed an algorithm to downscale the SMAP data using CYGNSS reflectivity data in order to reveal the spatial details of the SMAP data. The 3 km SMAP/CYGNSS TBs are more spatially heterogeneous than the 9 km SMAP TBs and capture the expected NSSM patterns.
Article
Environmental Sciences
Cameron Wobus, Eric Small, Jared C. Carbone, Parthkumar Modi, Hannah Kamen, William Szafranski, Ben Livneh
Summary: Water allocation is governed by complex water laws in many parts of the world, including the western United States. However, these laws may not maximize economic value across the entire economy. A study using a simplified MATLAB model found that the total economic value generated from water-dependent users depends primarily on the total water available in the system. Economic value is not necessarily maximized when all water is allocated to the user with the highest willingness to pay (WTP). Instead, it depends on the amount of water available, the relative WTP between users, and the return flows generated from each sector's water use.
Article
Biology
John T. Van Stan, Scott T. Allen, Douglas P. Aubrey, Z. Carter Berry, Matthew Biddick, Miriam A. M. J. Coenders-Gerrits, Paolo Giordani, Sybil G. Gotsch, Ethan D. Gutmann, Yakov Kuzyakov, Donat Magyar, Valentina S. A. Mella, Kevin E. Mueller, Alexandra G. Ponette-Gonzalez, Philipp Porada, Carla E. Rosenfeld, Jack Simmons, Kandikere R. Sridhar, Aron Stubbins, Travis Swanson
Summary: Stormwater is a crucial resource and plays a dynamic role in terrestrial ecosystem processes. However, the processes during and after storms are often not well understood when relying solely on technological observations. Human observations can complement technological ones by revealing ephemeral storm-related phenomena, which can then be further investigated using sensors and virtual experiments. Storm-related phenomena have significant impacts on hydrologic and biogeochemical processes, organismal traits and functions, and ecosystem services at all scales.
Article
Geosciences, Multidisciplinary
A. Rugg, E. D. Gutmann, R. R. McCrary, F. Lehner, A. J. Newman, J. H. Richter, M. R. Tye, A. W. Wood
Summary: This paper presents a method to adjust precipitation estimates from climate models, using sub-grid-scale topography and modeled wind direction. Results show that mitigating grid-scale biases is critical for regions with wet biases, and the new method produces more realistic sub-grid-scale variability in runoff. The method also brings the timing of runoff centroid closer to observed values for all examined subregions.
GEOPHYSICAL RESEARCH LETTERS
(2023)
Article
Geosciences, Multidisciplinary
Esteban Alonso-Gonzalez, Ethan Gutmann, Kristoffer Aalstad, Abbas Fayad, Marine Bouchet, Simon Gascoin
Summary: The snowpack over the Mediterranean mountains is a key water resource for downstream populations. A detailed study on the dynamics of the snowpack in the Lebanese mountain ranges was carried out using a 1 km regional-scale snow reanalysis (ICAR_assim) covering the period 2010-2017, showing high agreement with MODIS gap-filled snow products and in situ observations.
HYDROLOGY AND EARTH SYSTEM SCIENCES
(2021)
Article
Water Resources
Hannah M. Bonner, Mark S. Raleigh, Eric E. Small
Summary: This study investigates the influence of forest canopy on snow density and snow water equivalent. Results show that forest processes have some impact on snow density and water content, with delivery effects having the greatest impact on density and mass effects and radiation effects having the greatest impact on differences in snow water equivalent between forest and open areas.
HYDROLOGICAL PROCESSES
(2022)
