Article
Environmental Sciences
Hossein Zare, Tobias K. D. Weber, Joachim Ingwersen, Wolfgang Nowak, Sebastian Gayler, Thilo Streck
Summary: This study proposes a method for early forecasting of winter wheat yields in low-information systems, which integrates satellite and in-situ green leaf area index (LAI) data using a particle filtering method. The results show that assimilating even noisy LAI data substantially improves the accuracy and precision of yield prediction, reducing errors caused by uncertainties in weather data, incomplete knowledge about management, and model calibration uncertainty.
Article
Energy & Fuels
Celio Maschio, Joao Carlos von Hohendorff Filho, Denis Jose Schiozer
Summary: Numerical reservoir simulation is a crucial tool for production forecast and decision-making in the petroleum industry. This study proposed a methodology for dynamic data assimilation to reduce uncertainty in reservoir and production system models. The results showed that uncertainties in both systems can cause variability in production forecast, and multiple solutions should be considered for more realistic forecasts.
JOURNAL OF PETROLEUM SCIENCE AND ENGINEERING
(2021)
Article
Agriculture, Multidisciplinary
Jan Top, Sander Janssen, Hendrik Boogaard, Rob Knapen, Gorkem Simsek-Senel
Summary: Data generated by the global food system plays a crucial role in achieving sustainable, resilient, and high-quality food production. The operationalization of FAIR principles in agriculture and food requires conditions such as the availability of automated tools, community-based approach in developing tools and vocabularies, not relying solely on open-by-default policy for data sharing, and scientific insight into how data is (re)used in scientific communities.
COMPUTERS AND ELECTRONICS IN AGRICULTURE
(2022)
Article
Geosciences, Multidisciplinary
Vasily Titov, Christopher Moore
Summary: A modeling study successfully simulated the 2013 U.S. East Coast meteotsunami event using numerical simulation and weather radar reflection imagery, showing promise for accurately predicting coastal tsunami impacts based on measurements and real-time data assimilation.
Article
Biochemistry & Molecular Biology
Yu Watanabe, Kiyoko F. Aoki-Kinoshita, Yasushi Ishihama, Shujiro Okuda
Summary: The principle of FAIRness is crucial for the reproducibility and sustainability of scientific research, and the development of the GlycoPOST repository for glycomics MS data has already attracted researchers from around the world and significantly contributed to the future FAIRness of the field.
NUCLEIC ACIDS RESEARCH
(2021)
Article
Environmental Sciences
Zeyi Niu, Lei Zhang, Peiming Dong, Fuzhong Weng, Wei Huang
Summary: Assimilating FY-3D MWTS-2 data into the WRF model can improve the forecast performance and reduce the average track error for typhoon Lekima. The assimilation of satellite radiances plays a crucial role in forecasting the landfall of typhoon Lekima three days in advance.
Article
Environmental Sciences
Haoliang Wang, Shuangqi Yuan, Yubao Liu, Yang Li
Summary: This study evaluates and compares the performance of radar reflectivity and lightning data assimilation in short-term precipitation and lightning forecasts. Both assimilation methods improved the accuracy of forecasts, with radar reflectivity assimilation performing better for precipitation and lightning data assimilation performing better for lightning forecasts, especially in the analysis period and 1-hour forecast.
Article
Environmental Sciences
Yineng Li, Shaotian Li, Shiqiu Peng, Yuhang Zhu, Fenghua Zhou, Shilin Tang
Summary: This study introduces an updated version of the real-time Experimental Platform of Marine Environment Forecasting system for the North Indian Ocean, called EPMEF-NIO. The updates include adding the western Indian Ocean to the regions for weather, surge, and wave forecasts, increasing the horizontal resolutions for the two-domain weather forecast, adding a three-domain-nested wave forecast, and extending the length of the forecast time. The assessment based on substantial observations shows that the EPMEF-NIO performs well in weather, wave, and storm surge forecasts, thanks to the spectacular techniques employed in the system.
FRONTIERS IN MARINE SCIENCE
(2022)
Article
Computer Science, Interdisciplinary Applications
Yuying Wei, Adrian Wing-Keung Law, Chun Yang
Summary: In this study, a new framework called Probabilistic Optimal Interpolation (POI) is proposed for Data Assimilation (DA). It combines predictions from Machine Learning (ML) models trained with historical data and real-time observations to improve system state estimation. The framework integrates the heteroscedastic uncertainty of ML predictions and the residual-based uncertainty of observations through optimal interpolation.
JOURNAL OF COMPUTATIONAL SCIENCE
(2023)
Article
Mathematics
Cristina Georgiana Calancea, Lenuta Alboaie
Summary: Sharing data along the economic supply/demand chain is crucial for improving the performance of a digitized business sector. Designing automatic mechanisms for structured data exchange and implementing FAIR principles are necessary for ensuring the proper development of B2B processes in a regulated environment.
Editorial Material
Multidisciplinary Sciences
Stephanie Russo Carroll, Edit Herczog, Maui Hudson, Keith Russell, Shelley Stall
Summary: Advances in big data and open data have limited Indigenous Peoples' rights to control and access their data. By combining the FAIR Principles with the CARE Principles, machine actionability can be enhanced to address Indigenous Peoples' rights and interests in data.
Article
Meteorology & Atmospheric Sciences
Yuxin Zhang, Zhixiong Chen, Xian Xiao, Xiushu Qie, Min Chen, Jingyu Lu, Dongfang Wang, Shanfeng Yuan, Huimin Lyu, Jin Feng, Shuiyong Fan, Dongxia Liu
Summary: In this study, a lightning data assimilation (LDA) method was examined using the Weather Research and Forecasting (WRF) model and WRF Data Assimilation (WRFDA). The LDA method retrieves pseudo vertical velocity profiles from total lightning observations and improves wind convergence over lightning regions. Comparisons were made with radar data assimilation (RDA), and it was found that RDA improves long-term forecasts, while LDA corrects precipitation intensity and location.
ATMOSPHERIC RESEARCH
(2023)
Article
Geosciences, Multidisciplinary
Stanley G. Benjamin, Tatiana G. Smirnova, Eric P. James, Eric J. Anderson, Ayumi Fujisaki-Manome, John G. W. Kelley, Greg E. Mann, Andrew D. Gronewold, Philip Chu, Sean G. T. Kelley
Summary: The accurate initialization of lake temperatures is crucial for the application of lake models in earth-system prediction models. Traditional methods have limitations in capturing the temporal characteristics of lake temperatures, and an alternative lake-initialization method using a two-way coupled cycling approach has been developed. This method has been found to decrease errors in lake surface temperature and improve accuracy compared to other estimates.
GEOSCIENTIFIC MODEL DEVELOPMENT
(2022)
Article
Astronomy & Astrophysics
Jingjing Wang, Bingxian Luo, Siqing Liu, Yue Zhang
Summary: This study investigates the temporal and spatial features of active regions (ARs) in solar magnetic field observations to understand the evolution process from quiet to active states. The researchers find that these features can effectively predict strong-flare occurrences and reduce false alarms.
ASTROPHYSICAL JOURNAL SUPPLEMENT SERIES
(2023)
Article
Environmental Sciences
Miranti Indri Hastuti, Ki-Hong Min, Ji-Won Lee
Summary: Assimilating satellite and radar data into numerical weather prediction models improves the accuracy of rainfall forecasts and enhances the simulation of moisture distribution and atmospheric fields. The integration of satellite and GPSRO data reduces initial errors associated with the estimation of water vapor in radar reflectivity. Additionally, the assimilation of satellite atmospheric motion vectors improves wind information and atmospheric dynamics, leading to more accurate moisture convergence and fluxes.
Article
Ecology
Abigail S. L. Lewis, Christine R. Rollinson, Andrew J. Allyn, Jaime Ashander, Stephanie Brodie, Cole B. Brookson, Elyssa Collins, Michael C. Dietze, Amanda S. Gallinat, Noel Juvigny-Khenafou, Gerbrand Koren, Daniel J. McGlinn, Hassan Moustahfid, Jody A. Peters, Nicholas R. Record, Caleb J. Robbins, Jonathan Tonkin, Glenda M. Wardle
Summary: This article introduces a conceptual framework that describes how ecological forecasting can energize and advance ecological theory. The authors emphasize the potential for future progress through increased forecast development, comparison, and synthesis. They envision a future where forecasting is integrated as part of the toolset used in fundamental ecology, and aim to decrease barriers to entry and broaden the community of researchers using forecasting for fundamental ecological insight.
METHODS IN ECOLOGY AND EVOLUTION
(2023)
Review
Biodiversity Conservation
Mary E. Lofton, Dexter W. Howard, R. Quinn Thomas, Cayelan C. Carey
Summary: Near-term freshwater forecasts are urgently needed to mitigate freshwater risks and improve water quality management. Currently, freshwater forecasting mainly focuses on water quantity, while water quality forecasts are fewer and in the early stages of development. However, recent progress in forecasting methodology and end-user engagement suggests that near-term water quality forecasting is poised to make substantial advances.
GLOBAL CHANGE BIOLOGY
(2023)
Article
Environmental Sciences
Whitney M. M. Woelmer, Alexandria G. G. Hounshell, Mary E. E. Lofton, Heather L. L. Wander, Abigail S. L. Lewis, Durelle Scott, Cayelan C. C. Carey
Summary: Significant quantities of carbon (C), nitrogen (N), and phosphorus (P) enter freshwater reservoirs annually and can undergo various processes within the reservoirs. However, there is limited knowledge on the spatial and temporal variability of biogeochemistry within reservoirs. To address this, a study examined surface water biogeochemistry in two small reservoirs throughout a thermally stratified season. The study found that heterogeneity in biogeochemical concentrations was greater over time than space, and certain locations within the reservoirs acted as hotspots of change. The results suggest that spatially explicit metrics of biogeochemical processing can help understand the role of reservoirs in carbon, nitrogen, and phosphorus cycles.
Article
Ecology
R. Quinn Thomas, Ryan P. McClure, Tadhg N. Moore, Whitney M. Woelmer, Carl Boettiger, Renato J. Figueiredo, Robert T. Hensley, Cayelan C. Carey
Summary: The standardized monitoring program of the US National Ecological Observatory Network (NEON) provides an unprecedented opportunity to compare ecosystem predictability. In this study, we developed a near-term, iterative water temperature forecasting system for all six NEON lakes in the conterminous US. Using a process-based hydrodynamic model updated with observations, we generated 1-day-ahead to 35-days-ahead forecasts. The forecast accuracy was positively associated with lake depth and water clarity, while negatively associated with fetch and catchment size.
FRONTIERS IN ECOLOGY AND THE ENVIRONMENT
(2023)
Editorial Material
Ecology
R. Quinn Thomas, Carl Boettiger, Cayelan C. Carey, Michael C. Dietze, Leah R. Johnson, Melissa A. Kenney, Jason S. McLachlan, Jody A. Peters, Eric R. Sokol, Jake F. Weltzin, Alyssa Willson, Whitney M. Woelmer
FRONTIERS IN ECOLOGY AND THE ENVIRONMENT
(2023)
Article
Biology
J. W. Smith Jr, L. R. Johnson, R. Q. Thomas
Summary: Hierarchical probability models are increasingly being used in environmental prediction and forecasting, with Bayesian approaches becoming popular. This study focuses on ecosystem models that can be treated as statistical state space models (SSMs). Using simulated data, the effects of changing the temporal resolution of observations and state processes on parameter estimates are examined. The study also introduces a method of tuning the time resolution of latent states to improve estimates.
JOURNAL OF AGRICULTURAL BIOLOGICAL AND ENVIRONMENTAL STATISTICS
(2023)
Article
Ecology
Alyssa M. Willson, Hayden Gallo, Jody A. Peters, Antoinette Abeyta, Nievita Bueno Watts, Cayelan C. Carey, Tadhg N. Moore, Georgia Smies, R. Quinn Thomas, Whitney M. Woelmer, Jason S. McLachlan
Summary: Conducting ecological research requires a diverse and quantitatively trained workforce. Understanding the current landscape of ecology and environmental sciences undergraduate curriculum allows for targeted interventions to improve educational opportunities. Ecological forecasting can contribute to restructuring the curriculum and enhancing inclusivity.
ECOLOGY AND EVOLUTION
(2023)
Article
Multidisciplinary Sciences
Jacob H. Wynne, Whitney Woelmer, Tadhg N. Moore, R. Quinn Thomas, Kathleen C. Weathers, Cayelan C. Carey
Summary: Freshwater ecosystems are at risk from global change, particularly in relation to lake thermal dynamics. Uncertainty in future lake conditions is influenced by climate model and lake model selection. A study of a dimictic lake in the USA found that surface water temperature and total ice duration were primarily affected by climate model selection uncertainty, while bottom water temperature and stratification duration were dominated by lake model selection uncertainty.
Article
Environmental Sciences
Alexandria G. G. Hounshell, Brenda M. M. D'Acunha, Adrienne Breef-Pilz, Mark S. S. Johnson, R. Quinn Thomas, Cayelan C. C. Carey
Summary: Small freshwater reservoirs play an important role in global GHG budgets, but quantifying their annual GHG fluxes is challenging due to their limited surface area. We deployed an EC system in a small reservoir in Virginia, USA and found that the reservoir is a significant source of CO2 and CH4 to the atmosphere, with substantial variability at different timescales. We identified several key environmental variables that drive GHG fluxes in the reservoir.
JOURNAL OF GEOPHYSICAL RESEARCH-BIOGEOSCIENCES
(2023)
Article
Environmental Sciences
Christopher M. M. Clark, R. Quinn Thomas, Kevin J. J. Horn
Summary: Analyzing data from a tree inventory and growth for the contiguous US, researchers found that long-term nitrogen deposition may not continue to stimulate tree carbon storage. Changes in nitrogen availability can affect the ability of forest ecosystems to store carbon. Their analysis showed that the effect of nitrogen deposition on aboveground carbon varies among species and regions in the US. In the Northeastern US, the recent estimate of this effect is weaker than in the 1980s-90s, suggesting a weakening of the US forest carbon sink.
COMMUNICATIONS EARTH & ENVIRONMENT
(2023)
Article
Environmental Sciences
John W. Smith, R. Quinn Thomas, Leah R. Johnson
Summary: In this paper, a novel method for parameterizing Lognormal state space models using moment matching is proposed. The method enforces the positivity constraint, allows for arbitrary mean evolution and variance structure, and has a closed-form Markov transition density. Experimental results show that the method performs well under model misspecification and fixing the observation variance improves both estimation and forecasting performance. The method also outperforms its competitor in predicting leaf area index over a 151-day horizon.
ENVIRONMENTAL AND ECOLOGICAL STATISTICS
(2023)
Correction
Environmental Sciences
John W. Smith, R. Quinn Thomas, Leah R. Johnson
ENVIRONMENTAL AND ECOLOGICAL STATISTICS
(2023)
Article
Biodiversity Conservation
Christopher M. Clark, Jennifer Phelan, Jeremy Ash, John Buckley, James Cajka, Kevin Horn, R. Quinn Thomas, Robert D. Sabo
Summary: Climate change and nitrogen and sulfur deposition have significant impacts on forest demography. The study projects changes in forest composition based on future scenarios of temperature, precipitation, and deposition. Results show that the effects of climate change and deposition vary among species, with potential shifts in the abundance of 60 species declining and 20 species increasing. The study suggests that reducing deposition alone may not be sufficient to offset the impacts of climate change on forest composition.
GLOBAL CHANGE BIOLOGY
(2023)
Article
Ecology
Whitney M. Woelmer, Tadhg N. Moore, Mary E. Lofton, R. Quinn Thomas, Cayelan C. Carey
Summary: This study developed a teaching module to introduce ecological forecasting and uncertainty communication to undergraduate students. By embedding forecasting activities in an R Shiny application, students were able to actively engage in learning data science, ecological modeling, and forecasting concepts without advanced computational or programming skills.