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At least 1,585 records · Page 88

Uncertainty, Sensitivity Analysis, and Causal Identification in the Arctic using a Perturbed Parameter Ensemble of the HiLAT Climate Model

Coupled climate models have a large number of input parameters that can affect output uncertainty. We conducted a sensitivity analysis of sea ice proper:es and Arc:c related climate variables to 5 parameters in the HiLAT climate model: air-ocean turbulent exchange parameter (C), conversion of water vapor to clouds (cldfrc_rhminl) and of ice crystals to snow (micro_mg_dcs), snow thermal conduc:vity (ksno), and maximum snow grain size (rsnw_mlt). We used an elementary effect (EE) approach to rank their importance for output uncertainty. EE is an extension of one-at-a-time sensitivity analyses, but it is more efficient in sampling multi-dimensional parameter spaces. We looked for emerging relationships among climate variables across the model ensemble, and used causal discovery algorithms to establish potential pathways for those relationships.

54 ENVIRONMENTAL SCIENCES↗

Final Report on "Collaborative Research to Narrow Uncertainties in Precipitation and the Hydrological Cycle in Climate Models"

The central objectives of this work have been to explore and improve the depiction of precipitation and related processes in climate models by developing and analyzing observations and their gridded analyses, and developing new approaches and metrics. All three groups worked with the NCAR-based Community Earth System Model (CESM) and international community Climate Model Inter-comparison Project version 5 (CMIP5) models in various ways. At NCAR and SUNYA an initial focus was on the observational record, including updating of the river discharge dataset. A major focus at NCAR was extensive work on new datasets of hourly precipitation from CMORPH (observations) and CESM, and commentary on and validation of the CESM. SUNYA contributed to the comparison and evaluation of existing precipitation products widely used in climate research, the analysis of precipitation characteristics in CESM and other CMIP5 models, and decadal precipitation variability associated with decadal variability. At NCAR and SUNYA work was focused on the frequency and intensity of precipitation, including their dependence on the temporal and spatial resolution of the data used to calculate the frequency and intensity, as well as additional analyses on the effects of precipitation data uncertainties on the estimated historical drying trends. LLNL focused on the diurnal cycle. New insights have resulted in the characteristics of precipitation (frequency, intensity, amount, duration, diurnal cycle, covariability in space and time) and evaluation of these in models. In general models perform poorly and this provides a much-needed focus on what aspects of models are greatly in need of improvement. A substantial number of papers have now been published on these topics. The focus on the characteristics of precipitation and not just amount also provides a natural entrée into examining the extremes of precipitation, that are very important to the general public in terms of impacts. Examples are the deluges from Florence and Harvey, and extensive work has been performed on the latter. On the other side of the coin, considerable work has been performed on dry spells and drought, including improvements in a drought index. There has been considerable outreach to the general public, especially through the media, but also via talks and lectures, and a strong educational component at SUNYA. For example, the Harvey paper has an altimetrics rating of 827 and is the highest for any paper from that journal, it is at the 99th percentile of all papers of the same age, and is in the top 95 percent of all papers. The energy cycle and ocean heat content has been another focus. The entire atmospheric energy cycle has been reformulated and applied to the latest data to include effects from the enthalpy of precipitation. Relationships between ocean heat content and sea level rise have also been extensively explored in observations and models, with new insights into the role of Mount Pinatubo volcanic eruption on distorting and hiding the accelerating sea level rise. This work has been also widely featured in news media. The “year without a summer” has also been explored in the past using models, and how changes in the vertical structure and stability of the ocean with a warming climate may influence a future such volcanic event by amplifying the surface temperature response.

58 GEOSCIENCES↗

Climate Change Science Review 2018 and Associated Social and Economic Impacts

Climate change and its impacts on average temperature, water supply, agriculture, coastal flooding, biodiversity, social and economic stability, human migration, and overall global stability is one of the leading threats emerging for humanity, and is likely to increase as a threat for decades to come. This report represents a snapshot of climate change data, information, and understanding, as of 2018, and can serve as a kind of benchmark for changes going forward in time. This report covers temperature change and heat effects, atmospheric and ocean circulation, freshwater supply changes, sea level rise and flooding, extreme climate events, oceanic deoxygenation, land degredation, social and economic changes, migration, and food. Data and information on all these issues represent a compelling body of knowledge supporting the scientific hypothesis describing climate change, and an important mile marker in our effort to track the unfolding nature of the problem. A slide presentation that summarizes the content of this report is in Appendix A and can serve as an executive summary for the report.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Quasi-stationary Planetary Scale Waves in Modern Climate Models

We evaluate climate model simulations of geopotential height at the largest space-time scales, considering the first Fourier components (in longitude) of long-term climatological means. Quasi-stationary planetary scale waves emerge from this analysis. Variations of these waves are important components of climate change, for example associated with regional drought. Systematic examination of their long-term climatology provides context for understanding their evolution in time. We compare four reanalysis datasets with “historical runs” from the latest version of the Coupled Model Intercomparison Project (CMIP) and find general agreement, but we also identify model errors outside the range of both observational uncertainty and the uncertainty implied by interannual variability. Errors in wave phase have possible implications for climate model projections of regional climate and of shifting weather patterns. One model in the set we examine, originally created nearly 20 years before the others, exhibits noticeably greater errors.

54 ENVIRONMENTAL SCIENCES↗

US Climate Variability and Predictability Project. Final Report

The primary goal of the US Climate Variability and Predictability (CLIVAR) Project Office is to enable science community planning and implementation of research activities to advance the program mission to understand and predict climate variability and change on intraseasonal-to-centennial timescales, through observations and modeling, with emphasis on the role of the ocean and its interaction with other elements of the Earth system, and to serve the climate community and society through the coordination and facilitation of research on outstanding climate questions.

54 ENVIRONMENTAL SCIENCES↗

Co-Evolving Climate Models under Uncertainty to Improve Predictive Skill

Focal Area: Predictive modeling through the use of AI techniques and AI-derived model components; the use of AI and other tools to design a prediction system comprising of a hierarchy of models Science Challenge: Advances in modeling of climate and improved observational capabilities have led to great improvements in understanding large-scale historical climate effects. It however remains a challenge to reliably predict the risk of fine-scale regional climate events on human systems even as such risks are on the rise because warmer and wetter climates are more prone to hydrometeorological extremes,

54 ENVIRONMENTAL SCIENCES↗

Separating Climate Signals with Machine Learning

To better prepare for future changes in the water cycle, it is vital to understand the regional effects of anthropogenic climate change and internal climate variability on precipitation. With existing methods, there is uncertainty regarding the regional patterns of these climate processes. We propose using machine learning to decompose seasonal total and extreme precipitation (calculated by Risser et. al., 2019) into components caused by each of the following signals: anthropogenic forcing, internal variability, and modes of natural climate variability (such as El Niño/ Southern Oscillation, Atlantic Multidecadal Oscillation, and the Pacific North American teleconnection).

54 ENVIRONMENTAL SCIENCES↗

Cost-Optimized Cold Climate Heat Pump Development and Field Test

Cold climate heat pumps (CCHPs) expand the heat pump market to climates where heating demand is dominant. They can achieve more than 70% energy savings compared with electric resistance heating and operate at lower cost than using tank-stored propane to fuel a furnace. A high-efficiency heat pump with a heating seasonal performance factor (HSPF)—as defined by the Air-Conditioning, Heating, and Refrigeration Institute (AHRI 2008)—greater than 10.0 would be more efficient than gas heating in terms of source energy. However, developing a cost-effective CCHP involves some challenges. A typical single-speed, air-source heat pump (ASHP) with an HSPF of 7.7 Btu/Wh does not work well under cold outdoor temperature conditions typical of cold climate locations for four major reasons: 1. Discharge temperature is too high—The low suction pressure and high compression pressure ratio at low ambient temperatures causes high compressor discharge temperatures in excess of the maximum limit for many of the compressors on the market. Furthermore, system charge of a heat pump is usually optimized in the cooling mode, which leads to overcharge conditions in the heating mode, further increasing the discharge temperature. 2. Heating capacity is insufficient if sized to meet the building design cooling load— Heating capacity of a single-speed heat pump decreases with ambient temperature. The heating capacity at -13°F (-25°C) typically decreases to 20%–40% of the rated heating capacity at 47°F (8.3°C) (~equivalent to the rated cooling capacity at 95°F [35°C]). Therefore, a single-speed heat pump, typically sized to match the building design cooling load, cannot provide adequate heating capacity to match the building heating load at low ambient temperatures. The capacity deficit is filled by inefficient resistance heat, thus lowering the system efficiency and significantly increasing power demand. 3. Cyclic loss is significant if sized to meet the building design heating load—If a single-speed heat pump is sized to meet the heating load, it will be significantly oversized relative to the cooling load in many cold climates. This will cause excessive on/off cyclic loss during the cooling and heating operations at moderately low ambient temperatures. Thus, capacity modulation capability (e.g., using a variable-speed or multi-stage compressor) is necessary for a CCHP, which uses its full capacity to meet the peak heating load and partial capacity to meet the cooling and part-load heating loads. 4. Coefficient of performance (COP) is low—Heating COP degrades significantly at low ambient temperatures owing to the large temperature difference between the heat source and sink. A target CCHP should be sized to meet the building design heating load while minimizing the cyclic loss for the cooling and heating operations at moderate ambient temperatures.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

A Review of Water and Climate Change Analysis in Electric Utility Integrated Resource Planning

The purpose of this paper is to examine the extent to which electric utility integrated resource plans (IRPs) evaluate the impact of water constraints on electric generation resource portfolios and the extent to which IRPs consider the impacts of climate change to generation and loads. This white paper reviewed 30 IRPs to determine best practices with respect to analyzing and reporting on potential water-based and climate change risks within the integrated resource planning process. Best practices from electric utility IRPs are identified and additional recommendations and considerations are put forth. In recent years, thermal generating facilities have experienced challenges with water availability: a shortage of cooling water, conditions in which incoming cooling water is too warm for optimal operation, and/or water discharge temperatures exceeding permit limits. S&P Global Market Intelligence recently reported on a study that identified for the year 2030, 98.2 gigawatts (GW) of coal capacity at risk due to water stress. Climate change effects on hydrological cycles may adjust the timing, temperature, and volume of water availability for thermal electric cooling and for hydropower generation, which could further exacerbate the frequency and duration of operational constraints. Climate change can also impact the timing and intensity of electric loads that utilities must serve, most notably for heating and cooling.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Model Advancements to Enable Impact Analysis of Climate Change on Streamflow Temperature

With support from the Department of Energy’s Water Power Technologies Office, Pacific Northwest National Laboratory (PNNL) has developed new tools that incorporate cutting-edge climate and hydrological science capabilities to assess the potential long-term impacts of future climate conditions on unregulated streamflow and water temperature within watershed-river-reservoir systems. The objectives of this project were achieved by enhancing key hydrologic and hydrodynamic models and transferring them to a high-performance computing environment to provide a high-spatiotemporal resolution, multi-scale modeling framework. The new modeling framework has the potential to quantify risks related climate change impacts on runoff, unregulated streamflow, and water temperature. Initial development and demonstration of the modeling framework was conducted under historical and future climate conditions in the Columbia River Basin in the Pacific Northwest and the Connecticut River Basin in New England.

13 HYDRO ENERGY↗

Puerto Rico Historical Climate Analysis: A closer look at complex tropical terrain

Small tropical islands like Puerto Rico are especially vulnerable to climate change impacts, yet are often underrepresented in most datasets because the spatial resolution is too coarse to sufficiently cover their complex terrain. This study was done to better understand how the climate has changed in the various regions of Puerto Rico, which will support a transition to renewable energy and aid in projecting future climate impacts on the residents and land they live on. This study used multiple datasets including Daymet, a daily surface weather and climatological summary; European Centre for Medium-Range Weather Forecasts Reanalysis version 5 (ERA5); and station observations. The climate variables examined here include minimum and maximum near-surface air temperature, daily precipitation, incident shortwave radiation, and large-scale upper atmosphere conditions. The time periods cover the years 1950–2019. Results in both Daymet and station observations show long-term warming trends throughout every season. In particular, the minimum winter temperatures increased the most compared with maximum and mean air temperature. Northeast Puerto Rico, where the majority of the island’s population is located, experienced the largest warming. Summertime precipitation has decreased over time, and spring and fall precipitation has increased. The largest increase in fall is because there has been more available precipitable water, lower sea-level pressure, and favorable cyclonic circulations from the trade winds over the past seven decades. Overall, wet days are getting wetter, while dry days are getting drier. While there are good solar energy potential, we see a long-term decreasing trend in shortwave radiation over time in all seasons across entire island, possibly due to the increase of cloud cover.

54 ENVIRONMENTAL SCIENCES↗

ARM data-oriented metrics and diagnostics package for climate model evaluation (ARM-DIAGS-V3) version 3

A Python-based metrics and diagnostics package is currently being developed by the ARM Infrastructure Team at Lawrence Livermore National Laboratory to facilitate the use of long-term high frequency measurements from the ARM program in evaluating the regional climate simulation of clouds, radiation, precipitation, and aerosols. This metrics and diagnostics package computes climatological means of targeted climate model simulation and generates tables and plots for comparing the model simulation with ARM observational data. The CMIP model data sets are also included in the package to enable model inter-comparison as demonstrated in Zhang et al. (2018) and Zhang et al. (2020). The mean of the CMIP model can be served as a reference for individual models. Basic performance metrics are computed to measure the accuracy of mean state and variability of climate models. The evaluated physical quantities include cloud fraction, temperature, relative humidity, cloud liquid water path, total column water vapor, precipitation, sensible and latent heat fluxes, aerosol optical depth, and radiative fluxes, with plan to extend to more fields, such as the evaluation of model simulated aerosol physicochemical properties and cloud microphysics properties. Process-oriented diagnostics focusing on aerosol, cloud, and precipitation-related phenomena are also being developed for the evaluation and development of specific model physical parameterizations. In addition to the Southern Great Plains (SGP), North Slope of Alaska (NSA) and Tropical Western Pacific (TWP) atmospheric observatories in the ARMDIAGS version 2.0, the version 3.0 package have extended to the data collected at the ARM Eastern North Atlantic (ENA) atmospheric observatory and the Observation and Modeling of the Green Ocean Amazon (GOAMAZON) field campaign. The metrics and diagnostics package are currently built upon standard Python libraries and additional Python packages developed by DOE (CDAT). The ARM metrics and diagnostic package is available publicly with the hope that it can serve as an easy entry point for climate modelers to compare their models with ARM data. In this report, we first provide an overview of major metrics in section 2. The input data, which constitutes the core content of the metrics and diagnostics package, is summarized in section 3. A user's guide documenting the workflow/structure of the version 3.0 codes and including step-by-step instruction for running the package is described in section 4.

54 ENVIRONMENTAL SCIENCES↗

Cold Climate Air-Source Heat Pump Demonstration and Analysis: Experimental Study on Cold Temperature Performance

Space heating energy is the largest end use for U.S. residential buildings, accounting for nearly 45% of residential building energy consumption nationwide, and approximately 51% of space heating energy is consumed on-site by combusting natural gas (EIA 2020a). In Colorado, approximately 53% of the statewide residential building energy consumption goes to space heating, 76% of which is provided by natural gas (EIA 2020a). Heat pumps are an efficient, electric alternative space heating technology and have been proven viable for decades. However, historically air-source heat pumps (ASHPs) have been limited to temperate climates because of (1) subpar performance at extremely cold outdoor air temperatures, (2) the need for air conditioning in summer months, and (3) the availability of natural gas in colder climates. Relatively recent advances to cold climate ASHP technology, which typically relies on inverter-driven, variable-speed compressors and variable-speed fans, have significantly improved low-temperature heat pump performance, enabling the technology to potentially save energy for many homes in cold climates.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Energy Transitions: Local Water Concerns and Climate Impacts

This report summarizes important nuances in local water concerns and potential climate impacts that could influence the roll-out of technologies associated with energy transitions. Current investments in clean energy technologies are very high, which is driving a lot of investments in related manufacturing (i.e., hydrogen, solar, wind, and batteries) and mining (e.g., lithium, copper, and graphite) around the world. To understand how water and climate dynamics could be influencing these activities, we conducted a phased literature review for three countries: China, Germany, and France. China was selected due to its global dominance in manufacturing of solar panels, batteries, and electrolyzers as well as production of rare earth elements while Germany and France were selected due to their emerging leadership in energy transitions-related manufacturing within the European Union. For each of these three nations, we identified areas where manufacturing is occurring within the country and then evaluated relevant water resources and climate impacts. Multiple sources were consulted for this review, including BloombergNEF, international reports, industry sources, peer-reviewed literature, climate data, and media coverage.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Dynamics of Water, Climate, and Infrastructure

Climate and its impacts on the natural environment, and on the ability of the natural environment to support population and the built environment, stands as a threat multiplier that impacts national and global security. The Water Intersections with Climate Systems Security (WICSS) Strategic Initiative is designed to improve understanding of water’s role in, among other topics, the connection of critical infrastructure to climate in light of competing national and global security interests (including transboundary issues and stability), and identifying research gaps aligned with Sandia, and Federal agency priorities. With this impetus in mind, the WICSS Strategic Initiative team conceptualized a causal loop diagram (CLD) of the relationship between and among climate, the natural environment, population, and the built environment, with an understanding that any such regionally focused system must have externalities that influence the system from beyond its’ control, and metrics for better understanding the consequences of the set of interactions. These are discussed in light of a series of worldviews that focus on portions of the overall systems relationship. The relationships are described and documented in detail. A set of reinforcing and balancing loops are then highlighted within the context of the model. Finally, forward-looking actions are highlighted to describe how this conceptual model can be turned into modeling to address multiple problems described under the purview of the Strategic Initiative.

54 ENVIRONMENTAL SCIENCES↗

Gap Analysis of Global Climate Agreements

As climate change progresses, there will be greater pressure on state and nonstate actors to mitigate associated harms. This pressure will encourage aggressive action on climate change, including more ambitious emissions reduction goals and the use of both conventional and novel environmental modification techniques. Existing international agreements—including the Paris Agreement and the Environmental Modification Convention (ENMOD)—are critical to ensuring that climate change mitigation is achieved through peaceful, meaningful, and sustainable methods. With this in mind, this paper provides an overview of the Paris Agreement and ENMOD and identifies updates required for these agreements to meet the evolving challenges of climate change.

54 ENVIRONMENTAL SCIENCES↗

Performance Results from DOE Cold Climate Heat Pump Challenge Field Validation

Space conditioning and water heating consume over 40% of the nation’s primary energy use and represent a significant component of many homeowners’ monthly energy bill. However, in cold climates, performance of heat pumps has traditionally suffered as the units have been unable to efficiently transfer heat from colder outdoor air temperatures to warm the interior space of homes. Optimizing heat pumps for cold climates (5 °F and below) requires coordinated effort to ensure heat pump technologies can be enjoyed by Americans living in these regions. The DOE Cold Climate Heat Pump (CCHP) Challenge sought to address this challenge by partnering with industry to develop, test, and validate the performance of new, highly efficient heat pumps in real homes. The Challenge, launched in 2021, brought together leading heating, ventilation, and air conditioning (HVAC) manufacturers to develop prototype units optimized for performance at cold climates. This report summarizes results from the field validation that occurred 2022-2024.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Aerosol-Cloud Interactions and the Intersection of Climate Forcing and Feedback

The goal of this project has been to understand at the process level how the interaction of aerosols and cloud microphysics may alter the cloud response to climate change from the scale of turbulence to the global scale. Atmospheric aerosols (suspended particulates) have a unique role to play in the climate system. Anthropogenic aerosols may be an air pollution hazard and degrade human health. Their presence also results in the direct scattering or absorption of sunlight, with small net impacts on climate. But aerosols are also a key part of cloud formation, as the locations on which cloud droplets and ice crystals form. Understanding these Aerosol Cloud Interactions (ACI) is a critical uncertainty for climate models, including the Energy Exascale Earth System Model (E3SM), and affects how well models like E3SM can simulate the past and future. This work aims to understand cloud microphysics as well as the interaction of aerosol forcing and cloud feedback through improving our understanding of aerosol-cloud interactions (ACI) by looking at their uncertainty in critical environments at the process level. It will also contribute to the development of E3SM. Specific goals include: first, high level analysis of Perturbed Parameter Ensemble (PPE) simulations already available from the Community Earth System Model (CESM) and E3SM. Second, detailed analysis of recent changes to temperature and the role of aerosols.

54 ENVIRONMENTAL SCIENCES↗