Battelle’s Post

Excited to share new developments for measuring atmospheric fluxes with slow-response sensors! I developed a new easy-to-implement, highly-accurate, and direct variant of relaxed eddy accumulation method. Paper out today in Agricultural and Forest Meteorology: https://lnkd.in/e_2iVVHc Using a technique from computer graphics, the new method improves the accuracy of relaxed eddy accumulation (REA), an important technique to measure atmospheric exchange, by more than 100 times without imposing any additional requirements. Measuring exchange of trace gases and aerosols is crucial for climate science. It reveals how pollutants spread or how ecosystems respond to change. But for many atmospheric constituents, we lack fast-response analyzers, making accurate measurements a persistent challenge. REA is one of the simplest and most common flux measurement methods. It estimates atmospheric exchange using an approximation factor β. However, uncertainty in β estimates can contribute up to 20% error in measured fluxes, making it a key challenge in applying REA. A key insight in this paper: REA is similar to quantizing wind velocity. The main source of error in REA stems from this quantization process. Specifically, biases arise from the correlation between quantization error and the measured scalar. How can we minimize these errors? The solution: feed back previous quantization errors into the wind velocity before the next quantization step. This randomizes the quantization error, minimizing its correlation with the scalar. This process is known as "error diffusion." Error diffusion is commonly used in computer graphics to improve image quality. Quantized 1-bit images, can be improved by distributing the error to neighboring pixels to reduce the overall error. The integration of error diffusion proved to be surprisingly good. It allowed us to reach flux estimates within 0.1% of the reference eddy covariance measurement, completely eliminating the need for β, and enabling an increase in the signal-to-noise ratio. But how can adding noise improve flux estimates? The key is in how error diffusion shapes the noise. While the total variance of the quantization error increases, its correlation with our scalar of interest decreases. Improved measurements lead to more reliable data for climate models and environmental monitoring, advancing our understanding of ecosystem-atmosphere interactions. The new method has potential applications for a wide range of atmospheric constituents. These include stable isotopes, VOCs, ammonia, NOx, methane, oxygen, bio-aerosols, and trace metals among others. I want to thank my colleagues at the Bioclimatology group at The University of Göttingen, the editor, and the reviewers. A full code implementation is available on GitHub: https://lnkd.in/efPG2CTs. Happy to discuss further!

MSI Bulletin [Updates on the MT Terra Nova Oil Spill] Bulletin #02 (July 29, 2024): Oil spill trajectory model forecasts that spill will reach Metro Manila by July 30 An oil spill trajectory model was run to forecast the transport of the slick based on prevailing ocean currents and weather patterns. From the location of the oil slick based on the satellite image dated July 27, 6:07PM, oil may be transported to the following coastal areas and are projected to landfall at these times: Noveleta, Rosario, Tanza - 7/29/2024 8:00AM Naic - 7/29/2024 9:30AM Ternate - 7/29/2024 1:00PM Metro Manila - 7/30/2024 1:00AM Models are generated to inform the public on the potential direction of transport of the oil spill and help direct response efforts on the ground. However, models have some levels of uncertainty due to assumptions and limitations, and thus, should be used with caution. *Description of the Oil Spill Trajectory Model: The model used is the General NOAA Operational Modeling Environment (GNOME) for predicting the fate and transport of pollutants, such as oil, spilled into the ocean. The model for the MT Terra Nova spill uses surface velocity fields from Global Ocean Physics Analysis and Forecast and surface winds from the National Center for Environmental Prediction Global Forecast System. Spill location was specified based on the oil spill extent map provided by Copernicus and PhilSA dated 7/27/2024 18:07 PHT. Information about the model is available at https://lnkd.in/gtEx4p-x.

Open access paper: Well Control Strategies for Effective CO2 Subsurface Storage: Optimization and Policies by  Ismail Ismail  Vassilis Gaganis Abstract To combat the detrimental impacts of climate change and meet the obligations outlined in the 2015 Paris Agreement, Carbon Capture, Utilization, and Storage (CCUS) has emerged as a crucial technology with significant potential for achieving climate targets. CCUS involves the capture, storage, and utilization of carbon dioxide (CO2) emissions from existing energy infrastructure, hard-to-abate industries, or directly from the atmosphere, presenting a promising solution for emission reduction. However, fully harnessing the benefits of carbon storage requires the development of technically robust, safe, and cost-effective well control strategies that align with fundamental subsurface policies. This study aims to offer a comprehensive reference guide for carbon storage applications by reviewing relevant research in the field and establishing key subsurface storage policies for carbon storage in saline aquifer formation along with their practical implementation in carbon storage development plans. Additionally, we explore the utilization of optimization techniques employed thus far in the development of effective well control strategies in saline aquifers, presenting mathematical tools utilized and the achieved results. Figure: An overview of the characterization and assessment of the potential storage complex and surrounding area Keywords: #CCUS #CCS #injectionpolicies  #climatechange #geomechanics #WellControl #risk Source: https://lnkd.in/dDJy9xSi Figure credit: //lnkd.in/dDJy9xSi

We often attribute the problem of the sensitivity of wave modelling to the forcing wind fields especially under severe wind conditions that significantly affects the accuracy of modelled extreme waves. The ERA5 reanalysis is one of the most widely used datesets for wave climate modelling. Given that it underestimates modelled extreme waves as reported in several recent studies, a correction of its high winds is mandatory for the proper modelling and representation of stormy wave conditions. It is a pleasure to share with you our recent paper published in Ocean Engineering where a new parameterization has been developed for the correction of ERA5 severe winds for extreme ocean wave modelling. The new parameterization has been implemented in the source code of the WAVEWATCH III spectral wind wave model and the model has been applied at a global scale. The developed parameterization has improved the extreme wave modelling accuracy at the global scale and in most ocean basins for significant wave heights reaching~ 14m. It has clearly reduced the underestimation of extreme waves to properly capture the peaks of the storms. This study has been carried out in collaboration with my colleagues at IHCantabria Raúl Medina (general director of IHCantabria) and Melisa Menéndez García (director of the marine climate and climate change group of IHCantabria). The following link provides an open access to the article:

Dryland ecosystems are challenging when it comes to modeling plant water use through surface energy balance theory. Our recent work led by Yun Bai 白雲 (https://lnkd.in/eyUxqhuJ) developed a hybrid method that integrates the strengths of machine learning with a theory-driven thermal evaporation model. Global evaluation demonstrated that the improvement in vegetation water use retrieval under water-scarce conditions is attributed to the more accurate simulation of canopy-surface conductance and its responses to water stress. The enhanced representation of canopy-surface conductance effectively captures variations in physiological traits across global ecosystems, reflecting how plants adapt to seasonal temperature changes. Thus, the new method could additionally contribute in understanding terrestrial ecosystem responses to global change.

📣 New Research: Improving Geological Carbon Capture & Storage Safety Geological carbon capture and storage (CCS) offers a critical pathway to reducing greenhouse gas emissions. However, ensuring long-term, secure CO2 storage requires careful assessment of potential leakage routes through subsurface faults and fractures. In our recent paper, published in the International Journal of Greenhouse Gas Control, we present a new integrated approach for modelling geological leakage in fault zones. https://lnkd.in/dahWcvUF Andreas Busch Nathaniel Forbes Inskip Kim Senger Peter Betlem Kevin Bisdom Key Findings: 📍We combined laboratory stress-permeability measurements of individual fractures with detailed fracture analysis from an outcrop in Svalbard, Norway (an analog for various caprock formations). 📍Through digitisation and analysis of the natural fracture network, we showed how fracture pattern variations across a fault zone result in distinct permeability models. 📍This integrated approach allows for more accurate and realistic simulations of potential CO2 leakage pathways. Implications: 📌 Our work provides a valuable framework for incorporating detailed geological information into CCS risk assessments, potentially improving site selection and long-term monitoring strategies. A special thanks goes to Università degli Studi di Firenze for covering the publication costs. Please feel free to reach out if you have questions or would like to discuss the work! #CCS #CarbonCapture #ClimateSolutions #GeologicalStorage

Geoengineering - the fundamentally wrong (but enticingly simple) answer to a very complex problem: https://lnkd.in/eSb__csZ

The present study aims to: 1 - Examine the influence of dynamical downscaling options (direct versus one-way nesting) and boundary layer schemes (HOLT versus UW) on the simulated PET in comparison with ERA5 reanalysis product as the ground truth of observations of the PET. 2 - Examine the dependence of the simulated PET on the global incident solar radiation and daily mean air temperature (as inputs of the HS equation) by constructing a regional map of the Pearson correlation coefficient in each case. The significant correlation was calculated using student t-test of alpha equals to 5%. 3 - Investigate the performance of the RegCM4 concerning the climatological annual cycle of the PET with respect to ERA5. Presentation link: https://lnkd.in/d98qv8XK Manuscript link: https://lnkd.in/dGwyurvE

ESPO-G6-R2 v1.0 is a set of statistically downscaled and bias-adjusted climate simulations based on the Coupled Model Intercomparison Project 6 (CMIP6) models. The dataset is composed of daily timeseries of three variables: daily maximum temperature, daily minimum temperature and daily precipitation. Data are available from 1950 to 2100 over North America. The simulation ensemble is comprised of 14 models driven by two emissions scenarios (SSP2-4.5 and SSP3-7.0). In this paper, we describe the workflow used for the bias-adjustment, which relies on the detrended quantile mapping method and the Regional Deterministic Reforecast System (RDRS) v2.1 reference dataset. Using the framework defined in the VALUE project, we show the improvements made by the bias-adjustment on marginal, temporal and multivariate aspects of the data. We also verify that the bias-adjusted climate data have similar climate change signal to the original climate model simulations. Finally, we provide guidance to users on how to use this dataset. Article link: https://lnkd.in/dZbSfrDH

Fascinating video by the folk at the British Geological Survey on using remote digital technology to literally see the earth moving. "The techniques (instrumentation, software and methodologies) developed by GTom are used to underpin studies in infrastructure monitoring, waste management, contaminated land remediation and the protection of groundwater and soils, as well as the detection and mitigation of natural hazards. Our PRIME technology permits complex earth systems and processes to be monitored remotely using permanent, in situ sensor networks and wireless telemetry." https://lnkd.in/eXzQ96jM