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DECEMBER 6, 2019
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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
Highlight

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
Highlight

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.

Improving Projections of Future Hydropower Changes in the Western United States

Dam

One-quarter of the total electricity produced in the western United States comes from hydropower, including electricity generated by Glen Canyon Dam in northern Arizona. Further exploration of coupled energy and water system dynamics using a two-step multiscale calibration enables researchers to produce more accurate projections of future hydropower changes in the western United States, which will be of value to regional power system planners.

Integrated modeling system with a new, process-based hydropower module accounts for both electric grid operations and environmental constraints

March 22, 2019
October 22, 2019
Highlight

The Science
Hydropower currently accounts for more than one-quarter of the electricity produced in the western United States, so there is considerable interest in understanding how this resource may evolve under changing environmental conditions. Previous estimates of future hydropower generation have generally been based either on statistical relationships deduced from historical hydropower production or on simplified process-based models. In this study, researchers at the U.S. Department of Energy’s Pacific Northwest National Laboratory enhanced a large-scale river-routing and water management model with a process-based hydropower module that accounts for reservoir operation constraints, grid operation constraints, and hydrometeorological simulation biases. The results of the study are generally consistent with previous assessments of how hydropower generation may change in the future, but with slightly weaker seasonal shifts and reduced uncertainties. 

The Impact
By adding operational constraints on hydropower generation and using a two-step multiscale calibration, the approach used in this study produces more accurate projections of future hydropower changes in the western United States, which will be of value to regional power system planners. The design of the model, with explicit attention to operational constraints, also provides a platform for further exploration of coupled energy and water system dynamics. 

Summary
In this study, the authors enhanced an integrated hydrological model (MOSART-WM) with an enhanced process-based hydropower module to predict future hydropower generation. The new module addresses several commonly underrepresented constraints, including (1) ecological spills, (2) penstock constraints to provide flexibility in electricity operations, and (3) biases in hydrometeorological simulations. By evaluating projections based on two radiative forcing scenarios (RCP4.5 and RCP8.5) and ten downscaled global Earth system models, the authors found that (1) potential hydropower generation is not projected to change substantially on an annual time scale in most of the study region; (2) at the seasonal time scale, systematic shifting of generation patterns can be observed in snowmelt-dominated regions; and (3) including more complex operations and constraints tends to reduce uncertainties, especially at the seasonal time scale. In the Pacific Northwest, where hydropower is the dominant electricity source, the predicted future shift in hydropower generation toward the spring season is about 10% lower than in regression-based projections. These results demonstrate the value of using a multisector, multiscale modeling approach to investigate complex system dynamics under time-evolving boundary conditions.  

PI Contact
Nathalie Voisin, Pacific Northwest National Laboratory, nathalie.voisin@pnnl.gov 
Ian Kraucunas,Pacific Northwest National Laboratory, ian.kraucunas@pnnl.gov 

Funding
The integrated hydrologic simulations were conducted under the Laboratory Directed Research and Development Program at Pacific Northwest National Laboratory. The regional analysis and writing of the paper were supported by the U.S. Department of Energy, Office of Science, as part of the Multisector Dynamics, Earth and Environmental Modeling Program. 

T. Zhou, N. Voisin, and T. Fu, “Non-stationary hydropower generation projections constrained by environmental and electricity grid operations over the western United States.” Environmental Research Letters 13(7):074035 (2018). https://doi.org/10.1088/1748-9326/aad19f

Implications of water constraints on electricity capacity expansion in the United States

Water supplies

If water supplies are stretched thin, conventional power plants may need to be replaced with generation technologies that are less dependent on water.

Water limitations are projected to increase electricity costs

May 3, 2019
October 21, 2019
Highlight

The Science
Most of the electricity we use is generated by methods that require water, either for cooling or as steam to turn a generator. Researchers at the U.S. Department of Energy’s Pacific Northwest National Laboratory set out to quantify the implications of limited water availability for electricity capacity expansion in the U.S., by adding state-level water data to a global model that links the economy, energy, land use, water, and climate systems. Results indicated different effects of water constraints across states, with limitations more likely in the drier West than in the East.


The Impact
Concerns about water availability could affect decisions on where to build new power plants as well as whether to switch to generation methods that use less water, which could further influence the ability of existing plants to meet growing electricity demand. Accounting for water availability in electricity capacity planning is critical to make sure that strategic resource planning can be accomplished with minimum economic losses. This work highlights state-level challenges to facilitate regional strategic resource planning.


Summary
Effects of potential water constraints on U.S. electricity generation have been studied previously, but past studies have been limited in terms of scale and robustness. This work extended previous studies by including physical water constraints within a state-level model of the U.S. energy system embedded in the GCAM model (GCAM-USA) that integrates both supply and demand effects under a consistent framework. Results indicate that water constraints have two general effects across the U.S.: (1) electricity generation becomes more costly, which results in less electricity usage, and (2) water-intensive technologies, such as coal- and gas-fired generators, may need to be retired before the end of their designed lifetimes, while investment shifts to less water-dependent technologies, such as wind and solar photovoltaic. The western states, such as Texas and Arizona, are more likely than the eastern U.S. to face the need to abandon usable generators and invest in new equipment that uses less water.

PI Contact
Mohamad Hejazi, Pacific Northwest National Laboratory and Joint Global Change Research Institute, Mohamad.Hejazi@pnnl.gov
Leon Clarke, Pacific Northwest National Laboratory, leon.clarke@pnnl.gov

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

Liu L, M Hejazi, G Iyer, and B Forman. 2019. “Implications of water constraints on electricity capacity expansion in the United States.” Nature Sustainability 2:206−213. doi: 10.1038/s41893-019-0235-0.

Looking at Monsoon Rainfall Through a New Lens

Monsoon

Researchers discovered different hydrological characteristics between Indian and East/Southeast Asian monsoon systems in a warmer climate

December 20, 2018
October 21, 2019
Highlight

The Science


Summer monsoon rainfall provides the lifeline for agriculture in many tropical and subtropical countries. How monsoon precipitation and hydrological extremes could respond to climate warming is of great social and societal importance. Working with university collaborators, researchers from the U.S. Department of Energy’s Pacific Northwest National Laboratory developed and applied a new analysis method—called local water vapor wave activity, or LWA—to examine how hydrological extremes over Asian monsoon regions will change in the future. They found that a metric for precipitation extremes derived from LWA analysis increased in both the Indian and East/Southeast Asian monsoon regions. Meanwhile, the rate at which water vapor cycled through the atmosphere strengthened in the latter, but not the former, region.


The Impact
This research showcases the application of LWA analysis to tropical monsoon systems. This LWA diagnostic allows for more rigorous study of hydrological extremes at a regional scale, with the resultant LWA sink as a useful metric for precipitation extremes. The distinct characteristics in the hydrological cycling rate imply differing dynamical mechanisms governing precipitation extremes between Indian and East/Southeast Asian monsoons.


Summary
Globally, the atmosphere may be treated as a “reservoir” of moisture, with precipitation acting as a moisture sink and evaporation a moisture source, and thus the concept of hydrological cycle is well suited for globally integrated moisture. However, this global perspective cannot be readily carried over to regional atmospheric hydrological cycles. In a changing climate, the amount of precipitation that reaches Earth’s surface could fluctuate greatly by region compared to historical trends. Researchers developed an LWA diagnostic method for water vapor to represent local hydrological cycles. They then applied the method to explore the response of hydrological extremes over Asian monsoon systems to a climate warming scenario. Results showed that future water vapor wave activity over the broad Asian monsoon region increased by about 35 percent, largely due to the increase in background moisture. The analysis also found that precipitation extremes measured by the LWA sink of the budget strongly increased in both the Indian and East/Southeast Asian monsoon regions. The hydrological cycling rate, measured by the inverse of the residence time of the column moisture, showed distinct features between the two regions, suggesting different dynamical effects. 


PI Contact
L. Ruby Leung, Pacific Northwest National Laboratory, Ruby.Leung@pnnl.gov 


Funding
The U.S. Department of Energy Office of Science, Biological and Environmental Research supported this research as part of the Regional and Global Climate Modeling program. The National Natural Science Foundation of China (Grants 41475092, 41621005, and 41775073), China Scholarship Council, and Jiangsu Collaborative Innovation Center for Climate Change supported D.X. The National Natural Science Foundation of China (Grants 41475092 and 41621005) supported Y.Z.
 

D. Xue, J. Lu, L.R. Leung, and Y. Zhang, “Response of the Hydrological Cycle in Asian Monsoon Systems to Global Warming Through the Lens of Water Vapor Wave Activity Analysis.” Geophysical Research Letters 45(21), 11,904−11,912 (2018). [https://doi.org/10.1029/2018GL078998].