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When a pinch is problematic: Detecting pertechnetate in groundwater

pertechnetate

A PNNL researcher holds a redox sensor in the project’s lab in the Radiochemical Processing Laboratory.  Andrea Starr | PNNL

PNNL develops an effective tool for measuring a tricky contaminant

March 30, 2020
March 30, 2020
Highlight

Imagine trying to detect and measure a pinch of salt in an Olympic-size swimming pool. Now pretend the tools you are using don’t work well. Some can detect the salt but can’t tell you how much is in there, and others confuse salt with chlorine.

Now swap the swimming pool for a source of groundwater and the salt for a radioactive contaminant called pertechnetate.

ACS Journal Pertechnetate
The future of groundwater contamination measurement? The large thiol claws of PNNL’s subsurface probe with custom gold tips detect and measure pertechnetate in aqueous environments. Cover illustration by Rose Perry, PNNL

Pertechnetate is a byproduct of nuclear waste. If it ends up where it is not supposed to be—like, in groundwater—it could impact human health, which is why researchers and regulators keep a close lookout for it. The environmental safety limits for pertechnetate are roughly equivalent to a pinch of salt in an Olympic pool. And there are only a few technologies to measure it, each with limitations.

PNNL research tackles this challenge with new technology to detect and accurately measure pertechnetate at super low levels in groundwater. This research, “Redox-Based Electrochemical Affinity Sensor for Detection of Aqueous Pertechnetate Anion,” was the cover article for the March 2020 edition of ACS Sensors (DOI: 10.1021/acssensors.9b01531). 

Why it matters: The Environmental Protection Agency drinking water standard for pertechnetate is 0.000000052 grams per liter (that’s roughly 1/6000th the weight of a single poppy seed). While techniques exist for detection of pertechnetate in the environment, many have their drawbacks. PNNL’s technology can accurately measure low levels of pertechnetate in groundwater. Additionally, this proof of concept has the potential to be applied to other target contaminants simultaneously, increasing efficiency for environmental sensing.

Summary: The new technology acts like a coin counter, but at a microscopic level. It sorts one type of chemical from another, providing the total amount of a target chemical at the end. The tool uses custom probes with a gold electrode that only allows the target groundwater contaminants to stick while the other chemicals bounce off.

Sulfur likes to bind to gold and it also tends to react with pertechnetate, making sulfur-containing compounds an ideal intermediate in tool development. The sulfur sticks to the gold probe, then reacts with the pertechnetate, which forms a precipitate. The precipitate inhibits an electric current pulsing through the probe, providing an inverse measurement of pertechnetate concentration.

What’s Next: While this work was specifically focused on pertechnetate, there is potential to expand the technology to simultaneous multiple targets with the goal of increasing the efficiency of environmental measurements.

Sponsors: This research was funded by the Laboratory Directed Research and Development program at PNNL and by the Deep Vadose Zone program under the U.S. Department of Energy’s (DOE’s) Office of Environmental Management. Part of this research was performed at the Environmental Molecular Sciences Laboratory, a national user facility at PNNL managed by the DOE Office of Biological and Environmental Research.

PNNL Research Team: Sayandev Chatterjee, Meghan S. Fujimoto, Yingge Du, Gabriel B. Hall, Nabajit Lahiri, Eric D. Walter, Libor Kovarik. ACS Sensors cover illustration by Rose Perry, PNNL.

 

March 27, 2020
MARCH 12, 2020
Web Feature

Tracking Toxics in the Salish Sea

With the help of a diagnostic tool called the Salish Sea Model, researchers found that toxic contaminant hotspots in the Puget Sound are tied to localized lack of water circulation and cumulative effects from multiple sources.

Oxide interfaces in disarray

Microscope image, bright blue background with bright green oxides

Atomic-scale imaging informs interface models for oxygen defect formation during disordering of oxides used in energy and computing.

| PNNL

Exploration of disorder at material interfaces could lead to better device performance

March 3, 2020
March 3, 2020
Highlight

The structure of an interface at which two materials meet helps determine the performance of the computers and other devices we use every day. However, understanding and controlling interface disorder at the atomic level is a difficult materials science challenge.

A research team at PNNL and Texas A&M University combined cutting edge imaging and numerical simulations to examine disordering processes in widely used oxide materials. They found that certain oxide interface configurations remain stable in extreme environments, suggesting ways to build better performing, more reliable devices for fuel cells, space-based electronics, and nuclear energy.

Visualizing the disordering process

As reported in Advanced Materials Interfaces (Asymmetric Lattice Disorder Induced at Oxide Interfaces,” DOI: 10.1002/admi.201901944) the team set out to examine interfaces between pyrochlore-like and perovskite oxides, two common classes of functional materials used in energy and computing technologies. While most past work has focused on individual bulk materials, less attention has been paid to interfaces connecting them, as would be the case in a device. In particular, it is not clear how interface features, such as composition, bonding, and possible defects, govern disordering processes.

Funded by PNNL’s Nuclear Process Science Initiative (NPSI), the team employed experimental and theoretical methods to study the interface at different stages of disorder introduced through ion irradiation. They imaged the local structure of the material using high-resolution scanning transmission electron microscopy and convergent beam electron diffraction, which showed that the bulk of the two materials disordered (amorphized) before the interface. After further irradiating the material, they found that a band region near the interface had remained crystalline, while the rest of the structure had become amorphous.

To understand this behavior, the team turned to a technique called electron energy loss spectroscopy, which allowed them to examine the atomic-scale chemistry and defects formed at the interface. Their measurements revealed the presence of substantial amounts of defects called oxygen vacancies, which can greatly affect properties such as magnetism and conductivity. Based on these observations, the team constructed a theoretical model of the interface and explored the effect of different interface configurations on the tendency to form vacancies.

“In our model we are able to systematically vary interface features, such as crystal structure, intermixing, and strain, to see their effect on defect formation. We found that the structure of the materials on both sides of the interface can influence where defects are likely to form first,” explained Steven R. Spurgeon, a PNNL materials scientist. “Our model suggests that by selecting appropriate crystal structures and controlling how they connect, it may be possible to dictate the sequence of defect formation, which would allow us to enhance the properties of these materials.”

The team is exploring other interface structures and chemistries, with an eye toward improving the performance of oxides used in extreme environments.

The study was conducted as part of the NPSI project, “Damage Mechanisms and Defect Formation in Irradiated Model Systems,” led by Spurgeon.

Research Team

Steven Spurgeon (PNNL), Tiffany Kaspar (PNNL), Vaithiyalingam Shutthanandan (Environmental Molecular Sciences Laboratory at PNNL), Jonathan Gigax (Texas A&M), Lin Shao (Texas A&M), Michel Sassi (PNNL).
February 20, 2020

Improving nuclear waste storage models by studying the chemistry of material interactions

A female researcher wearing a blue lab coat and heat-resistant safety gloves pours molten glass out of a metal crucible onto a metal tray.

PNNL conducts research into glass, glass-ceramic, grout, metal, and metal-ceramic wasteforms that will withstand corrosion over geologic time.

PNNL | Andrea Starr

WastePD EFRC research on the glass-steel interface was published in Nature Materials

February 3, 2020
February 3, 2020
Highlight

New research unravels the chemistry of how materials in the waste packages used for the disposal of high-level radioactive waste interact in deep geologic repository environments. Having a better understanding of the interactions between materials under various conditions provides more information to make waste storage performance models more robust.

“Many performance models use conservative approaches such as assuming that the steel canister walls don’t even exist or that they dissolve very fast. This study provides the opportunity to better incorporate the canister barrier in the models,” said Joseph Ryan, a PNNL materials scientist and coauthor on the paper, “Self-accelerated corrosion of nuclear waste forms at material interfaces,” published in Nature Materials.

The United States is converting highly radioactive nuclear waste, also known as high-level waste, into glass. The molten glass is poured into steel canisters for long-term storage and ultimate disposal in a geologic repository. The goal is to design waste storage and disposal systems that would remain safe for hundreds of thousands of years to come, even if they are exposed to water. Because of the extensive time span of waste storage, researchers turn to cutting-edge science to project what will happen during that time period. The data is used to inform extensive safety analyses—helping make sure the system is engineered to be compatible with the natural system so that waste remains separate from the environment.

“We can’t just do a test on a material and say, ‘That material corroded this much in 30 days and extrapolate that to a million years.’ It doesn’t work that way,” Ryan said. “At the most basic level, we try to understand the underlying chemistry of corrosion. Then, we feed that information into computer models to calculate the expected release over time.”

In this study, led by the WastePD Energy Frontier Research Center based at Ohio State University, researchers unpacked the chemistry that occurs when two materials are close together, focusing on glass-steel along with ceramic-steel interactions. This chemical situation could occur when water has percolated into the repository and has breached the steel canister, exposing the glass-steel interface to water.

When water finally breaches the waste package container, it will fill the microscopic space that forms between the solid glass and the steel canister. Chemical reactions that happen in localized and tiny microenvironments such as these can be quite different than those happening in a more open setting. In this case, this localized area can have a different chemistry than the surrounding solution, causing more corrosion than would be expected.

The researchers tested their theory in the laboratory. They pressed glass and steel together in salty liquid and kept it at 90° C (194° F) for a month. At the end of the experiment, they found differences in the width of thin layers that indicated higher corrosion between the glass-steel couple interface than in a control sample.

Why it matters: This research allows scientists to improve models that project how a disposal canister could perform in a deep geologic environment. Having a better understanding of the interactions between materials under various conditions provides more information to make the models more robust. Currently, some models project what happens to waste under the assumption that the steel canister walls do not exist. Operating under this pretext can result in higher projections of waste degradation than would likely occur when taking a conservative approach. But better understanding the chemistry of how the solid waste and the steel canister interact allows a scientifically based understanding of how the canisters behave and interact with the glass to be included in performance assessment models.

Summary: High-level waste is immobilized as glass in stainless steel canisters. On cooling, a confined crevice space forms at the stainless steel-glass interface. If the disposal canister is breached and if water can enter the steel-glass interface, it could result in anodic dissolution of the stainless steel, generating metal cations, which hydrolyze to form protons and strongly increase the local acidity. This acidic environment may locally enhance the corrosion of both the stainless steel and the glass, which leads to the release of cations from the glass. Further, the coupled corrosion may trigger the precipitation of additional secondary phases that may impact subsequent canister corrosion or nuclear glass durability.

What’s Next: While this study sheds light on the chemical interactions that occur at the stainless steel-glass interface, there are more interactions to explore. Ultimately, a better understanding of different chemical mechanisms will improve the overall performance model.

Acknowledgements

Sponsors: This work was supported as part of the Center for Performance and Design of Nuclear Waste Forms and Containers, an Energy Frontier Research Center funded by the US Department of Energy, Office of Science, Basic Energy Sciences under Award no. DESC0016584.

Research Team: Xiaolei Guo, Gerald S. Frankel, Gopal Viswanathan, Tianshu Li (Ohio State University); Stéphane Gin (CEA, France); Penghui Lei, Tiankai Yao, Jie Lian (Rensselaer Polytechnic Institute); Hongshen Liu, Dien Ngo, Seong H. Kim (Pennsylvania State University); Daniel K. Schreiber, John D. Vienna, Joseph V. Ryan (PNNL); Jincheng Du (University of North Texas)

January 27, 2020
JANUARY 10, 2020
Web Feature

Clark Recognized for Nuclear Chemistry Research

The world’s largest scientific society honored Sue B. Clark, a PNNL and WSU chemist, for contributions toward resolving our legacy of radioactive waste, advancing nuclear safeguards, and developing landmark nuclear research capabilities.
DECEMBER 6, 2019
Web Feature

Converging on Coastal Science

Advancing a more collective understanding of coastal systems dynamics and evolution is a formidable scientific challenge. PNNL is meeting the challenge head on to inform decisions for the future.

Moments Matter When It Comes to Modeling Rain

Rain

Getting rain properties correct in atmospheric models is critical for accurately representing the structure and evolution of cloud systems.

Improved representation of rain microphysics led to more accurate simulations of surface precipitation

March 12, 2019
October 22, 2019
Highlight

The Science
In atmospheric models, raindrop properties such as rainfall rate are usually described based on the raindrop size distribution. For example, heavy rain rates may have a wider raindrop size distribution than light rain. To improve predictions of rain that reaches the surface, the primary question has been, how can models better represent the evolution of raindrop size distribution in space and time in the atmosphere? A team led by researchers at the U.S. Department of Energy’s (DOE) Pacific Northwest National Laboratory improved the representation of rain microphysics by predicting the shape parameter of raindrop size distributions in a recently developed cloud microphysics scheme. They found that under a wide range of atmospheric conditions, their advanced representation delivered surface rain properties similar to those produced by a benchmark scheme, but with less computational resources.

The Impact
Because raindrops play a major role in the vertical redistribution of heat and moisture in the atmosphere, they are a critical component for modeling the structure and evolution of cloud systems such as mesoscale convective systems. These systems are major sources of heavy rain in the central United States. A proper representation of rain in numerical models is not only vital to predict surface precipitation, but also to accurately simulate environmental conditions and circulation patterns. The advanced rain microphysics representation from this study improves simulations of rain properties under various atmospheric conditions, and it can be used to increase accuracy of weather and climate models. The scheme will be implemented in DOE’s Energy Exascale Earth System Model (E3SM).

Summary
Cloud microphysics schemes in weather and climate models usually predict two moments—the total number and mass—of the raindrop size distribution. Researchers upgraded the Predicted Particle Properties (P3) cloud scheme by adding another predicted variable—shape parameter—for raindrop size distribution, turning the two-moment scheme into a three-moment scheme for raindrop representation. They also developed and incorporated a new parameterization for drop-drop collisions—when two drops collide—and the breakup of large drops into smaller ones. 
To evaluate those new developments, the research team tested them with an idealized rain model. The model simulated 450 rain scenarios that were initialized by different raindrop size distributions and environmental conditions. Researchers compared the simulated surface rain properties against those from a detailed and computationally costly reference scheme. The team found that, depending on initial rain intensity, up to 95 percent of simulations with the new developments produced raindrop sizes and surface rain rates within ±20 percent biases from the reference results. This was a considerable improvement from the original two-moment scheme, which only reached 4 percent using the same criteria for comparisons with the reference results. Sensitivity tests showed that both the added degree of freedom—the additional variable for raindrop size distribution—and the new process parameterization contributed to the improvements.

PI Contact
Jiwen Fan, Pacific Northwest National Laboratory, jiwen.fan@pnnl.gov  

Funding
This research was supported by the Climate Model Development and Validation program funded by the Office of Biological and Environmental Research in the U.S. Department of Energy Office of Science. Model simulations were performed using PNNL Institutional Computing.

Paukert M, J Fan, PJ Rasch, H Morrison, JA Milbrandt, J Shpund, and A. Khain. 2019. “Three-Moment Representation of Rain in a Bulk Microphysics Model.” Journal of Advances in Modeling Earth Systems 11(1):257−277, https://doi.org/10.1029/2018MS001512.

Influence of Groundwater Extraction Costs and Resource Depletion Limits on Simulated Global Nonrenewable Water Withdrawals over the 21st Century

Groundwater

Recent PNNL research suggests that rising groundwater extraction costs will force users to turn to other sources of water.

Global groundwater depletion is projected to peak and then decline during this century as costs of using it change

April 16, 2019
October 22, 2019
Highlight

The Science
Because water is a fundamental human need, estimating future supplies is important. Researchers at the U.S. Department of Energy’s Pacific Northwest National Laboratory (PNNL) coupled regionally varying groundwater availability and extraction cost estimates with continually adjusted demands for water in a simulation that covered multiple sectors around the world. As groundwater levels dropped, imposing greater capital and energy costs to bring water to the surface, modeled water use sectors responded by drawing from other water resources. These behaviors resulted in a marked peak and decline in the rate of global groundwater depletion.

The Impact
Previously it was assumed that the rate of global groundwater depletion would increase steadily over the 21st century as humans demanded more water—particularly for crop production. This work suggests that groundwater depletion may actually decline, because the increasing costs of pumping will force water users to adapt by turning to less expensive sources, which are often in regions where renewable water remains plentiful.

Summary
In many regions of the world, groundwater reserves are being depleted rapidly. This raises concerns for the sustainability of irrigated agriculture and global food supplies. It is therefore important to study groundwater depletion and possible exhaustion of water resources at a global scale. A problem for such analysis is the lack of detailed understanding of when a depleting resource becomes unviable for further exploitation. The question is not simply how much water is physically available; we need to know when the financial costs and environmental effects of extracting more groundwater render the resource unviable for human applications. To study these effects, PNNL researchers employed a global, gridded data set that specifies the cost of groundwater extraction as a function of depletion. Then, using the Global Change Assessment Model (GCAM), they simulated water users as economic decision makers to understand how they would adapt as extraction costs increased. Results indicated that future rates of global groundwater depletion would be heavily moderated by increasing extraction costs. Regions that depleted water to costly levels lost competitive advantage for crop production, which shifted to regions where water resources were less costly and more plentiful. The team concluded that extraction costs must be included in simulations for projections of global groundwater depletion to be reliable.

PI Contact
Leon Clarke, Pacific Northwest National Laboratory, leon.clarke@pnnl.gov

PNNL Contact
Mohamad Hejazi, Pacific Northwest National Laboratory, Mohamad.Hejazi@pnnl.gov  

Funding
This research was supported by the U.S. Department of Energy Office of Science, Biological and Environmental Research through the Multisector Dynamics, Earth and Environmental System Modeling Program. 

Turner SWD, M Hejazi, C Yonkofski, SH Kim, and P Kyle. 2019. “Influence of Groundwater Extraction Costs and Resource Depletion Limits on Simulated Global Nonrenewable Water Withdrawals Over the Twenty-First Century.” Earth’s Future 7(2):123−135. https://doi.org/10.1029/2018ef001105.

Calibrating Building Energy Demand Models to Refine Long-Term Energy Planning

Bend

The BEND model can combine information on building technologies, climate, and population to forecast hourly building energy demand for regions the size of electric power balancing authorities. This calibration aligns the results with historical data to make them more accurate.

A new, flexible calibration approach improved model accuracy in capturing year-to-year changes in building energy demand

June 6, 2019
October 22, 2019
Highlight

The Science
Aggregated building energy demand models, which are based on combining the outcomes of many individual building simulations, are an emerging tool for long-term energy planning at multiple spatial scales. They can be used to understand and project changes in building energy demand due to changes in population, climate, and building technologies. However, these models can be hard to calibrate because real-world data availability at the appropriate temporal, spatial, and sectoral scales is often limited. A new approach developed at the U.S. Department of Energy’s (DOE’s) Pacific Northwest National Laboratory (PNNL) allows these aggregate models to be calibrated at multiple scales. Researchers used this new method to calibrate PNNL’s Building ENergy Demand (BEND) aggregate model. Once calibrated, BEND successfully captured year-to-year changes in building energy demand due to changes in weather.

The Impact
Unlike more traditional statistical methods, physically based aggregate models such as BEND can fully capture the dynamic relationships between hourly building energy demand and population, climate, and building technologies. As a result, these models are valuable tools for understanding multisectoral dynamics. The new approach allows BEND and other aggregate models to be calibrated at the scale at which they will be applied, overcoming a key limitation of this class of models. Models such as BEND will improve model projections of future building energy demand at different scales and refine long-term energy planning through integration with grid operations and resource planning models.

Summary
PNNL’s BEND model is one of an emerging class of models designed to capture total and hourly building energy demand resulting from the aggregation of tens to hundreds of thousands of individual building simulations. Historically, these aggregate models have proven difficult to calibrate because there is a limited amount of target data available at relevant space, time, and sectoral scales. Researchers developed and demonstrated a novel approach to calibrate BEND, using approximately 100,000 individual simulations of DOE’s EnergyPlus model, against the best available data at the geographic scale of balancing authorities (electricity management subregions). Once calibrated, BEND captured year-to-year changes in total and peak building energy demand due to variations in weather within these areas. The study applied PNNL’s new calibration approach to the western United States, but the method can be applied to regions across the world with similar data and scale challenges. Researchers also suggested areas in which improved data collection and sharing would help to further refine these emerging models.

PI Contact
Jennie Rice, Pacific Northwest National Laboratory, jennie.rice@pnnl.gov
Ian Kraucunas, Pacific Northwest National Laboratory, ian.kraucunas@pnnl.gov 

Funding
This research was supported by the DOE Office of Science as part of research in the MultiSector Dynamics, Earth and Environmental System Modeling Program. A portion of the research was performed using PNNL’s Institutional Computing resources. 

Taylor ZT, Y Xie, CD Burleyson, N Voisin, and I Kraucunas. 2019. “A multi-scale calibration approach for process-oriented aggregated building energy demand models.” Energy and Buildings 191:82‒94. https://doi.org/10.1016/j.enbuild.2019.02.018.

A Global Hydrologic Framework to Accelerate Scientific Discovery

Hydro

A new version of the Xanthos global hydrology model enables researchers to rapidly address complex multisector dynamics science challenges, such as determining water scarcity impacts on land use, and could help accelerate energy-water-land research even more.

A new version of the Xanthos model enables researchers to rapidly address evolving energy-water-land science challenges

June 11, 2019
October 22, 2019
Highlight

The Science
Research in energy-water-land systems—and understanding how water scarcity can affect these systems—is rapidly progressing. To quantify changes in—and the effects of—future freshwater availability, a team from the U.S. Department of Energy’s Pacific Northwest National Laboratory (PNNL) developed the Xanthos global hydrology model, which can be used independently or as a part of a coupled modeling system. Researchers can use Xanthos to explore how different climate, socioeconomic, or energy scenarios affect regional and global water availability over the 21st century. In version 2 of the model, the PNNL team built a component-based framework to rapidly incorporate and test new hydrologic process modules—or code—within a robust environment, complete with diagnostics and calibration capabilities.

The Impact
Within Xanthos version 2, scientists can easily incorporate and test evolving hydrologic process models as components, or selectable, compatible parts of the Xanthos framework. For example, researchers can customize a specific configuration of components to address the role of snowmelt in characterizing drought or to explore the role of model assumptions in characterizing the uncertainty of complex coupled energy-water-land systems. The process of incorporating and testing models within the component-based framework is faster than what it would take to reproduce an entire configuration of models if users added their own from scratch. The usability of Xanthos version 2 enables researchers to rapidly address complex multisector dynamics science challenges, such as determining water scarcity impacts on land use, and could help accelerate energy-water-land research even more.

Summary
Xanthos, an open-source model written in Python, provides a solid foundation for continued advances in global water dynamics science. The model simulates historical and future global water availability on a monthly time step at a spatial resolution of 0.5 geographic degrees. Xanthos also can serve as the freshwater supply component of the Global Change Assessment Model (GCAM), also developed at PNNL. 
For Xanthos version 2, the PNNL team built upon the original version by creating a component-based framework in which users can swap out or extend previously existing core components of the model—potential evapotranspiration (PET), runoff generation, and river routing—without starting from scratch. For example, users can now swap out the potential evapotranspiration core component with one they think captures the dynamics of the systems and processes they are trying to model. The component-style architecture of Xanthos version 2 enables researchers to quickly incorporate and test the latest energy-water-land research in a stable modeling environment with prebuilt diagnostics. The PNNL team also created a robust default configuration that includes a calibration module, hydropower modules, and new PET modules. These enhancements are now available to the scientific community in Xanthos version 2, which can be downloaded from GitHub.

PI Contact
Mohamad Hejazi, Pacific Northwest National Laboratory, Mohamad.Hejazi@pnnl.gov

Funding
This research was supported by the U.S. Department of Energy Office of Science as part of research in the MultiSector Dynamics, Earth and Environmental System Modeling program.

Vernon CR, MI Hejazi, SWD Turner, Y Liu, CJ Braun, X Li, and RP Link. 2019. “A Global Hydrologic Framework to Accelerate Scientific Discovery.” Journal of Open Research Software 7(1):1, http://doi.org/10.5334/jors.245.

Making 1+1 Bigger than 2

modules

A study highlighted progress and pitfalls in coupling different modules within weather, climate, and Earth system models, demonstrating the pervasiveness of coupling problems in current models as well as highlighting recent progress.

A state-of-the-science review highlighted progress and pitfalls in coupling different modules within weather, climate, and Earth system models

February 18, 2019
October 22, 2019
Highlight

The Science
Modern computer models for weather, climate, and Earth systems contain numerous modules that simulate the complex workings of distinct physical and dynamical phenomena, such as ocean currents, atmospheric winds, clouds, and river flows. These individual modules are typically developed by separate groups of researchers and then connected to form a comprehensive model system. The two-step approach can lead to inaccurate results in current model simulations. An international team of researchers, including scientists from the U.S. Department of Energy’s Pacific Northwest National Laboratory, reviewed the state of the science in module coupling and identified possible ways to address some key challenges.

The Impact
Most model development work typically focuses on individual modules, resulting in a research gap in the simulation of weather and climate, which are the sum of many processes. This review paper demonstrates the pervasiveness of coupling problems in current models and highlights recent progress in module coupling. The paper also provides illustrative examples of coupling issues, such as insufficient frequency of information exchange between modules and double counting of processes by multiple modules. Such issues could, for example, strongly affect how much rain is predicted in a simulation of storms. The coupling issues must be overcome for each module to realize its full potential and improve the overall predictive skill of the entire model system. This is needed for the improvement of existing modules as well as in the design of new modules or model systems. 

Summary
The compartmentalization of model codes and development teams is natural and also necessary to manage the endeavor of modeling complex weather, climate, and Earth systems, which are influenced by many processes. As a result, three types of issues can occur: First, the artificial distinction between physical phenomena based on whether they can be spatially resolved or not can lead to double counting or undercounting of processes. Second, infrequent information exchange between interacting modules can result in biases, or offsets from observations, in the balance between them. Third, inconsistent approximations employed by different modules can lead to unintended violation of basic physical principles. The topic of coupling typically receives little attention during model development, and more evidence suggests that this gap in research is becoming a bottleneck in further improving the corresponding models.
Aimed at increasing awareness of such issues, this review describes the symptoms of coupling problems using examples from existing literature and discusses their root causes and possible methods for analyzing the problems. The paper reflects the findings of many research highlights from an international biennial workshop series on physics-dynamics coupling. Since the first workshop in 2014, this small but evolving event series has gained attention from international weather, climate and Earth system model development groups and research sponsors to join forward-thinking discussions and address the ubiquitous coupling problems. Topics discussed in the workshop series and the paper include: conceptual inconsistencies in model equations; numerical methods for solving the equations with computers; sensitivities of model results to choices made for the numerical calculations and strategies for analyzing such sensitivities; and methods for making the computations more efficient on supercomputers.

PNNL Contacts
Hui Wan, Pacific Northwest National Laboratory, Hui.Wan@pnnl.gov
L. Ruby Leung, Pacific Northwest National Laboratory, Ruby.Leung@pnnl.gov

Funding
The U.S. Department of Energy (DOE) Office of Science funded Hui Wan’s, Peter M. Caldwell’s, and Philip J. Rasch’s contributions to the paper as part of the Scientific Discovery through Advanced Computing (SciDAC) program. PNNL’s Linus Pauling Distinguished Postdoctoral Fellowship partially supported earlier contributions by Hui Wan. DOE Office of Science Grants DE-SC0006684 and DE-SC0003990 supported Christiane Jablonowski and Diana R. Thatcher. The DOE Office of Science, Biological and Environmental Research funded Koichi Sakaguchi’s and L. Ruby Leung’s contribution to this work as part of the Regional and Global Model Analysis, Earth and Environmental System Modeling program. Part of the numerical simulations presented in the paper used computational resources from the National Energy Research Scientific Computing Center (NERSC), a DOE user facility supported by the Office of Science under Contract DE-AC02-05CH11231, and PNNL Institutional Computing.

Gross M, H Wan, PJ Rasch, PM Caldwell, DL Williamson, D Klocke, C Jablonowski, DR Thatcher, N Wood, M Cullen, B Beare, M Willett, F Lemarié, E Blayo, S Malardel, P Termonia, A Gassmann, PH Lauritzen, H Johansen, CM Zarzycki, K Sakaguchi, and R Leung. 2018. “Physics–Dynamics Coupling in Weather, Climate, and Earth System Models: Challenges and Recent Progress.” Monthly Weather Review 146:3505–3544, https://doi.org/10.1175/MWR-D-17-0345.1.

The Nonlinear Response of Storm Surge to Sea-Level Rise: A Modeling Approach

Sea

With sea-level rise, storm surge will reach farther inland, but by different amounts in different places.

Maximum storm surge will not increase at the same rate as sea-level rise in all locations

January 20, 2019
October 22, 2019
Highlight

The Science
Future storm surges will be amplified by sea-level rise, but the spatial variability of this amplification has not been systematically addressed, in part due to nonlinear interactions that take place in different parts of a hurricane track. In this study, scientists from the Department of Energy’s Pacific Northwest National Laboratory evaluated the nonlinear response of storm surge to sea-level rise using a high-resolution model of Hurricane Katrina under five different sea-level rise scenarios. They found that storm surge heights in the lower floodplain region can increase more than twice as much as sea-level rise as a result of nonlinear amplification effects. 

The Impact
Hurricane-driven storm surges are among the most damaging and costliest natural disasters, so it is critical to understand how sea-level rise may be influencing storm surges. This study identified specific portions of coastal topography that may experience increases in storm surges that are even larger than the rate of sea-level rise, which is valuable for assessing coastal infrastructure resilience. The study also highlights the need for dynamic modeling in order to account for complex interactions associated with coastal storm surge in the context of long-term sea-level rise. 

Summary
The study team used the unstructured-grid, finite-volume, coastal ocean model known as FVCOM (Finite-Volume Coastal Ocean Model) to simulate the effect of Hurricane Katrina on the Gulf Coast under five different scenarios of sea-level rise, ranging from 0 to 2.0 meters. The model was driven by the observed Katrina wind field, and includes a wetting and drying process to accurately simulate storm surge heights across complex coastal topographies. To assess the nonlinear interaction between surge height and sea-level rise, the team looked at three different regions across the land-ocean boundary near the hurricane track: the offshore coastal area, the upper floodplain, and the lower floodplain. Although maximum storm surge height increased with sea-level rise in all three regions, the response under larger sea-level rise scenarios was muted in the upper floodplain and exacerbated in the lower floodplain. These results highlight the need for additional research with dynamic, high-resolution models to better understand the interactions between sea-level rise and storm surge in different regions, for different storm patterns, and under different sea-level rise scenarios. 

PI Contact
Ian Kraucunas, Pacific Northwest National Laboratory, Ian.Kraucunas@pnnl.gov 
Zhaoqing Yang, Pacific Northwest National Laboratory, Zhaoqing.Yang@pnnl.gov 

Funding
This study was funded by the U.S. Department of Energy, Office of Science, Office of Biological and Environmental Research, as part of the Regional Integrated Assessment Modeling Project under the Multisector Dynamics research program. 

Wang T and Z Yang. 2019. “The Nonlinear Response of Storm Surge to Sea-Level Rise: A Modeling Approach.” Journal of Coastal Research 35(2):287-294. https://doi.org/10.2112/jcoastres-d-18-00029.1 

The Many Shapes of Reservoirs

reservoir

A key challenge in modeling the influence of reservoirs on streamflows and other water cycle processes is accounting for the relationship between reservoir depth, surface area, and storage. By deriving optimal geometric shapes for more than 6,800 reservoirs worldwide, researchers developed a data set that provides more accurate storage-area-depth relationships. 

Researchers developed a new global data set for better representing reservoirs in Earth system models

March 11, 2019
October 22, 2019
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The Science
Reservoirs store and release water for flood control, navigation, and water supplies for the domestic, industrial, agricultural, and energy sectors. A key challenge in modeling the influence of reservoirs on streamflows and other water cycle processes is accounting for the relationship between reservoir depth, surface area, and storage. To address this challenge, a team including scientists at the U.S. Department of Energy’s Pacific Northwest National Laboratory developed a new global reservoir storage-area-depth data set by deriving an optimal geometric shape for more than 6,800 reservoirs worldwide. This new data set is critical for accurately representing reservoir processes in Earth system models, including the influence of reservoirs on regional hydrology, ecology, and biogeochemistry.

The Impact
Approaches used in previous studies to model reservoir storage-area-depth relationships are either difficult to generalize beyond a specific site or too simplified to account for fluctuations in reservoir surface area and storage over time. The new global reservoir storage-area-depth data set developed in this study will improve the ability to simulate reservoir dynamics in Earth system models. These details are critical for understanding how water management interacts with energy production and other sectors.
 

Summary
This study focused on the development of representative storage-area-depth relationships for more than 6,800 reservoirs around the world. The research team identified a small number of representative reservoir geometries defined by a combination of horizontal surface shapes (parabolic, rectangular, elliptical) and vertical cross-section shapes (wedge, bowl, prism). For each reservoir, researchers used an optimization algorithm to select the geometric shape that best represented the effective reservoir length and width values derived from the Global Reservoir and Dam (GRanD) database. The team then calculated reservoir storage-area-depth relationships based on the optimal geometry. Using this method, about 70 percent of reservoirs included in GRanD had errors in total storage of less than 5 percent, and about 85 percent had errors less than 25 percent. Researchers validated the storage-depth relationship using both remote-sensing data for 40 major reservoirs globally and ground-based measurements for 34 reservoirs in the United States and China. 
The more accurate storage-area-depth relationships in this new data set will improve the representation of reservoir dynamics in global hydrological and Earth system models. For example, the relationships can be used to calculate physical reservoir characteristics needed for modeling heat transfer, mass balance, or nutrient concentration. The team is using the global data set to model reservoir stratification, or the separation of water into layers of varying temperatures. Accurate representation of stratification is vital for improving the simulation of stream temperature—an important consideration for thermoelectric power plant performance and aquatic habitats.

PI Contacts
Ian Kraucunas, Pacific Northwest National Laboratory, ian.kraucunas@pnnl.gov
Jennie Rice, Pacific Northwest National Laboratory, jennie.rice@pnnl.gov

Funding
The U.S. Department of Energy Office of Science, Biological and Environmental Research supported this research as part of the Multisector Dynamics, Earth and Environmental System Modeling Program. 

Yigzaw W, H-Y Li, Y Demissie, MI Hejazi, LR Leung, N Voisin, and R Payn. 2018. “A New Global Storage-Area-Depth Data Set for Modeling Reservoirs in Land Surface and Earth System Models.” Water Resources Research 54(12):10,372−10,386, https://doi.org/10.1029/2017WR022040.

Projecting Global Urban Area Growth through 2100 Based on Historical Time Series Data and Future Scenarios

Urban

Researchers gathered data on worldwide urban growth, and used it to project urbanization for each country to the year 2100. The newly created data set can serve as the foundation for studies on the effects of urban growth.

Study provides country-specific urban area growth models and the first data set on country-level urban extents under five future scenarios of socioeconomic change

May 24, 2019
October 22, 2019
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The Science
Researchers created a data set on historic urban area growth using satellite observations and then developed models that project future growth at the country level. They used the models to project country-level urban extents under five different future scenarios of socioeconomic change through 2100.

The Impact
This new data set can be the foundation for various global change studies; for example, simulating urban sprawl, modeling multisector dynamics, and investigating the effects of urbanization on air quality, and human health.

Summary
Better understanding of the potential growth of urban areas at the national and global levels is important for exploring the linkages between urban systems, other human systems, and the environment. In this study, researchers at the Department of Energy’s Pacific Northwest National Laboratory and Iowa State University developed urban area growth models for each country using the time‐series dataset of global urban extents (1992–2013), and projected the future growth of urban areas under five Shared Socioeconomic Pathways (SSPs), which are reference pathways depicting plausible alternative trends in the evolution of society and ecosystems through 2100. Global urban area is projected to increase by roughly 40–67% under the five scenarios by 2050 relative to the base year of 2013, and this trend would continue to a growth ratio of more than 200% by 2100. Although developing countries would remain leading contributors to the increase of global urban areas in the future, they may exhibit different temporal patterns, i.e., plateaued or monotonically increasing trends. Our urban area dataset is the first country‐level urban area projection consistent with the five SSPs, between 2013 and 2100. Several types of predictive global change studies can be built on this dataset, e.g., urban sprawl simulation, multisector dynamics modeling, and investigating the effects of urban growth on air pollution and public health.

PI Contact
Mohamad Hejazi, Pacific Northwest National Laboratory, Mohamad.Hejazi@pnnl.gov  

Funding
This work was supported by the U.S. Department of Energy Office of Science, as part of research in the MultiSector Dynamics Earth and Environmental System Modeling Program, the NASA ROSES LULC Program and the NASA ROSES INCA Program. Jiyong Eom was also supported by the Ministry of Environment of Korea through the Climate Change Correspondence Program.

Li X, Y Zhou, J Eom, S Yu, and GR Asrar. 2019. “Projecting global urban area growth through 2100 based on historical time‐series data and future Shared Socioeconomic Pathways.” Earth's Future, 7, 351–362.  https://doi.org/10.1029/2019ef001152.