Climate Science and Policy

To inform the sustainable development of offshore wind (OSW) in California, the California Marine Sanctuary Foundation (CMSF), a non-profit with 30 years of experience improving the resilience and stewardship of California’s coastal resources, is developing the Offshore Wind Environmental Monitoring Guidance (EMG) for the California Ocean Protection Council. In support of the EMG, this study reviewed scientific and gray literature and synthesized existing knowledge on fixed bottom and floating OSW’s impacts on marine ecosystems. The primary impacts on marine ecosystems include noise effects, displacement, entanglement and collision with, attraction to, or avoidance of OSW infrastructure, habitat alterations, anthropogenic emissions and pollution, and electromagnetic field (EMF) effects. Identifying knowledge gaps and monitoring priorities is critical for initial OSW development in California. This synthesis reveals that while we have a more developed understanding of OSW's acoustic and EMF impacts on marine megafauna, we lack a similarly complete understanding of OSW’s ecosystem-wide impacts on most taxa.

Marine heat waves (MHWs), extended periods of unusually high ocean temperatures that significantly impact marine ecosystems, are prevalent in the Southern California Bight (SCB), increased thermal stratification has intensified these events over recent decades, affecting California sea lions by disrupting prey availability, leading to malnutrition and higher mortality rates. Rising atmospheric CO2 levels have exacerbated this issue, contributing to the warming of surface waters. Climate models predict that MHWs will continue to increase in frequency, severity, and duration, posing further risks to marine life. Despite the presence of a significant sea lion colony off the coast of San Diego, little research has been conducted on MHWs in the SCB impact on the local sea lion population. This research examines various aspects of MHWs at San Diego, including defining MHWs, historical occurrences, current trends, and their implications for California sea lions, while exploring potential policy and mitigation strategies to protect Southern California's marine ecosystems. Daily sea Surface Temperature (SST) measurements from La Jolla Scripps Pier (1916-2023) are used to quantify local MHWs relative to a shifting baseline (i.e., one that adjusts for the long-term warming trend), and to a fixed baseline (i.e., the warming trend alone increases MHW occurrences). We investigate critical questions about MHW evolution and duration, considering the continuous warming of the oceans. We consider what the two definitions of MHWs imply for upwelling and nutrient supply to the ocean surface, and the implications for California sea lion prey availability. We identify future research priorities, particularly improved measures of sea lion population counts, and the need for better indicators of MHW impacts beyond SST.

The countries within the Nile Basin have become increasingly water stressed with each passing year due to the intensification of climate change, and disagreements about water allocation rights between these countries only exacerbate the issue. For about a century, Ethiopia and Egypt have been quarrelling over rights to the Nile’s waters with no resolution in sight. In 2011, Ethiopia began construction of the Grand Ethiopian Renaissance Dam (GERD), which increased tensions. As of 2023, the dam’s construction was completed but negotiations have made no meaningful progress. The dam worsens political relations but impacts the environment, economy, and society in both positive and negative ways. Considering these impacts and the example of the demolition of the Klamath River dams, it was determined that dam demolition would be the most beneficial and equitable course of action, in the long run, for all the Nile River riparian countries. A policy memo was then constructed advocating for demolition of the GERD.

This study investigates the environmental impacts of college football's 2024 conference realignment, focusing on the increased aviation pollution due to expanded travel requirements for teams. Recent realignments in college football conferences have led to significant changes in team travel schedules, resulting in longer travel distances and a greater reliance on air travel. The research employs a comparative analysis of travel distances and carbon footprint calculations using data from 2024 NCAA team schedules and aviation emission factors. Additionally, the study compares a theoretical model of logical geographically based conferences against the actual 2024 conference alignments, examining just how much grouping schools based on their geography could reduce travel and therefore overall emissions. The analysis reveals a significant increase in travel-related carbon emissions, with certain schools experiencing substantial increases in aviation pollution using the 2024 schedule compared to if they were to use the geographical based model. The study also examines the impact of increased travel on student-athlete mental health, identifying heightened stress and reduced academic performance as significant concerns due to increased cross country travel which was not in place before. Case studies illustrate the varying impacts on different universities and student-athletes. To address these issues, the study suggests a geographical model be put in place in the next ten to fifteen years to avoid the unnecessary increase in aviation pollution, protect student athlete’s mental and academic well being, and keep historic geographically based rivalries strong. The study also highlights sustainability initiatives for stadiums and travel, including the adoption of greener transportation methods and eco-friendly stadium practices. Policy recommendations include regulatory measures to mitigate aviation pollution and support for sustainability initiatives within college athletics. These findings underscore the need for change in comprehensive strategies to 3 manage the environmental and mental health impacts of conference realignment, promoting sustainability and well-being in FBS college football.

Adoption of electric vehicles is surging across the state, country, and world, driven by government policies to reduce carbon emissions from the transportation sector. To maximally reduce emissions of EVs, however, drivers must charge their vehicles when clean electricity generation, such as solar and wind power, is abundant. In California, this means charging during the daytime when most people are at work.

Workplace charging plays a pivotal role in this context. Many EV drivers, especially those living in apartments or rented accommodations, lack access to home charging options. For these drivers, workplace charging provides a critical solution, enabling them to charge their vehicles during the day when renewable energy is most available. Moreover, workplace charging can significantly alleviate range anxiety, making EVs a more viable and attractive option for a broader segment of the population. Although the affordability of EVs has improved significantly, the challenge remains in finding reliable and accessible charging stations. Workplace charging addresses this issue, aligns with the goal of equitable access to charging infrastructure, promotes adoption, and supports the wider transition to electric mobility.

This study examines drivers' charging behavior at charging facilities at the University of California San Diego and is extensible to any workplace. The primary motivation is to analyze the heterogeneity in where and how EV drivers charge their vehicles. By mining natural variations in the data, the study aims to inform institutional policies and planning that encourage workplace charging and deliver a positive charging experience for drivers. 

A. Project scope and methodology

Using datasets on drivers’ preferences around charging, charging sessions, and UCSD’s EV charging network, this project conducted a detailed analysis of EV drivers’ charging behavior, focusing on both the spatial and temporal aspects of charging. The data for this study are derived from enrollment surveys of 806 real (anonymized) UCSD EV drivers, alongside more than 55,000 unique charging sessions retrieved from the two main charging service providers at UCSD—ChargePoint and PowerFlex. Key components of the study include:

Imbalances in the demand for charging and the supply of chargers across campus. Understanding the demand-supply imbalance in charging sessions across various campus locations is crucial. The study identifies garages with high demand but relatively few chargers, leading to significant disparities and underutilization of network efficiencies.

Driver preferences for campus charging location vs. what is revealed by their real charging behavior. The study compares drivers’ stated ideal campus charging location with actual charging session data to identify discrepancies and analyze supply-demand imbalances across the campus that may cause deviations in charging location.

The depth, or size, of sessions that drivers’ initiate. Analyzing whether drivers engage in deep or shallow sessions and how these behaviors are distributed spatially across campus. Frequent shallow sessions are identified as a significant factor leading to an underutilized and inefficient charging network.

Identification of driver traits that affect session depth. The study emphasizes identifying commuter traits that influence EV charging infrastructure needs at both micro and macro scales. This includes demographic factors, such as their affiliation, where they live, access to home charging, and commute distances.

The analysis of EV charging behavior at UCSD reveals critical insights into the utilization patterns, demand-supply imbalances, and session depths across different campus zones. By examining the data, several key findings have emerged that highlight the unique challenges and opportunities within the existing charging infrastructure. These findings provide a foundation for targeted improvements to enhance network efficiency, equity, and overall user satisfaction. While the study focuses on behaviors at UCSD, the lessons learned are anticipated to be generalizable to other workplaces outside the campus.

B. Key findings

Supply and demand imbalances:

There are significant disparities in the availability of charging infrastructure across different campus zones. High-demand garages such as Athena, Gilman, and Scholars experience notable supply shortages, leading drivers to frequently deviate from their preferred charging location and charge elsewhere. Six garages with high demand but few forthcoming chargers were identified – Bachman, Campus Point East, Campus Point West, Rady, School of Medicine, and Keck.

Charging session depth:

Data reveal that garages with lower demand-supply ratios have higher rates of shallow charging sessions. These shallow sessions are less efficient and can contribute to congestion at charging stations. Encouraging deeper charging sessions can improve network efficiency and parking garage utilization.

Influencing factors:

Access to home charging, commute distance, and driver demographics significantly impact charging behavior. Drivers without home charging access, particularly those from lower-income groups, face greater challenges in finding available charging spots and have higher deviation sessions. Temporal patterns show peak usage times coinciding with typical work hours, stressing the need for optimal charger placement and availability.

C. Conclusion and recommendations

This study on workplace EV charging behavior at UCSD provides crucial insights into the significant disparities and heterogeneity in the demand for charging and supply of charging infrastructure across different campus zones. The findings reveal prevalent shallow charging sessions and high demand-supply imbalances in specific garages, leading to network inefficiencies and driver inconveniences. To address these issues, the following strategies are recommended:

Prioritize installing new charging stations where supply-demand imbalances are greatest:

Prioritizing the installation of new charging stations in garages with high demand-supply imbalances, such as Athena, Gilman, and Scholars, to address current imbalances is crucial for mitigating deviation sessions and encouraging deeper sessions. It is important to focus on maximizing kWh sales, EV throughput, and charger cost recovery while also considering goals of access and equity.

Encourage deeper charging sessions:

Implementing incentives such as kWh-based pricing may encourage deeper charging sessions, reducing the frequency of shallow sessions and optimizing charger usage. Additionally, developing targeted support programs for drivers lacking home charging options, including dedicated charging slots for long-hour charging.

Optimize charging schedules:

Introducing a reservation system or time-based access to manage peak usage times, distributing the charging load more evenly and reducing congestion during peak hours may influence behavior heterogeneity.

Continuous monitoring and adaptation:

Establishing a continuous monitoring system to assess the performance and utilization of the charging infrastructure will inform decisions on future expansions and improvements. Preferably, focus on those parking garages where actions are most required. The enrollment survey-led incentive mechanism already exists as an effective method to communicate behavioral benefits directly to users.

Expand public awareness and education:

Awareness campaigns to inform drivers about the benefits of optimal charging practices and the impact of their behavior on network efficiency may increase emphasis on deeper charging sessions, including improved commute efficiency and potential incentives.

By adopting these recommendations, UCSD can enhance the performance and user satisfaction of its charging network, supporting the broader adoption of electric vehicles and contributing to sustainable transportation initiatives on campus.

In the last decade, research on atmospheric rivers (ARs) has surged due to their potential to cause extreme flooding and alleviate drought stress in the Western United States. Concurrently, wildfires in Southern California have become increasingly costly and destructive. While the timing of the first fall AR is known to influence wildfire risk in Southern California, the impact of ARs on spring vegetation growth and subsequent fall wildfire risk remains poorly understood, especially at the fine scale of Southern California ecosystems.

To investigate this link, we analyzed forty years of AR-associated Integrated Vapor Transport (IVT) and winter precipitation data across ten Level IV Ecoregions in Southern California. We examined the correlations between these metrics and the Enhanced Vegetation Index (EVI) and the Evaporative Demand Drought Index (EDDI). Our analysis revealed that productivity during the growing season is linked to the previous winter's total AR-associated IVT, and even more strongly to winter precipitation totals. We found positive correlations between AR-associated IVT and precipitation with EVI in early peak fire season (defined as August through October), particularly in chaparral-dominated areas, while conifer forests and grassland ecosystems displayed weaker correlations. 

We also found that the 90-day EDDI in early peak fire season was influenced by winter precipitation in some ecoregions, and that EDDI also had significant correlations with early peak fire season EVI. 

Our findings suggest that wet winters may increase wildfire risk in fuel-limited ecosystems like grasslands due to higher biomass accumulation, whereas in chaparral-dominated areas, increased moisture may reduce wildfire risk via maintaining higher fuel moistures in the fire season. These results underscore the need for further research to clarify the importance of fuel abundance versus fuel dryness, especially in conifer forest and sage scrub ecoregions for accurate Southern California wildfire risk assessment.

Microclimates can behave differently from the larger regional climate, and it is essential to consider various spatiotemporal scales when studying how climate change affects local ecosystems. This research identifies small-scale climate variations within Channel Islands National Park (CINP), particularly in areas where species might find refuge to adapt to climate change. The study identifies different climate characteristics in this region by creating a microclimate framework and analyzing historical data accordingly. It also explains the need for scaling down climate information to the ecosystem level and provides a literature review of all known criteria necessary. The goal is to help inform park managers of local conditions and potential threats to prioritize areas for conservation and restoring biodiversity and natural resources. While global and regional climate models help understand broad trends, they often need more detail to grasp ecological changes at the community or individual species level. Scaling down climate information can enhance the accuracy of predictive models used in environmental assessments and impact studies, and identifying existing microclimates can help assess the overall health of an ecosystem. The research categorizes the scaling process into four levels: macro, meso, topo, and micro. It outlines the procedure for identifying microclimates, analyzes model predictions, illustrates future climate scenarios, and highlights correlations between various physical factors using recent climatological observations. The study starts with a review of existing literature to provide context for each climate variable's impact on the overall ecosystem, explains the research methods, presents the results, and concludes with a discussion of the findings and suggestions for future research beyond the scope of this study. The research was conducted in collaboration with The Nature Conservancy and the National Park Service to address the specific needs of the park.

Climate change and over-allocation of the Colorado River have resulted in difficult negotiations amongst the seven states (Arizona, California, Colorado, New Mexico, Nevada, Utah, and Wyoming) that rely on the river. The Lower Basin and Federal Government recently came to an agreement (May 2023) for voluntary users to conserve water in trade for financial compensation, resulting in an estimated 3 million acre-feet (MAF) of total conserved water by the end of 2026. Southern California imports more water from the Colorado River than any other user. The majority (80%) of California’s 4.4 MAF allotment from the Colorado River is used to irrigate the region’s $11.6 billion agriculture industry, and only 20% is used for municipal water. This study examines the annual consumptive use of the four largest importers of Colorado River water in California from 1964 – 2021 to identify extreme variations and understand the effect that precipitation plays in those variations. This study also focuses on the time period of 2002 – 2003, in which Southern California’s imports were reduced by 1 MAF due to the Quantification Settlement Agreement (QSA), as a proxy to understand what major cuts in imports will mean to California’s agriculture industry today. The study finds that local precipitation had a negative moderate-strong correlation with consumptive use prior to the 2003 QSA in three of the water districts, but a negative weak correlation following the 2003 QSA in all but one district. Reductions from the QSA were widespread but unevenly distributed; Metropolitan Water District decreased its consumptive use by nearly 50% (~0.5 MAF) while Imperial Irrigation District, the largest user of Colorado River water, decreased by less than 6% (0.2 MAF). Irrigated crop acreage (ICA) of all crops decreased by <1% between 2002 and 2003, with the largest decrease in alfalfa at 51,000 acres. Irrigated crop acreage of all crops increased, on average, in the years following the 2003 QSA, even though consumptive use decreased >12%; the ICA of alfalfa had an overall decrease of ~4% while common produce crops increased by ~3%. Similarly, the total water consumed water by alfalfa decreased >13% in the years following the QSA, while the consumptive use of common produce increased nearly 3%. Overall, alfalfa accounted for ~30% of the total irrigated crop acreage and ~44% of total water consumed within the water districts.

As rising sea levels are anticipated to threaten coastal communities around the world within the next century, many low-lying coastlines are already experiencing threats of coastal flooding. The scientific research community is contributing to our understanding of these hazards by collecting data on historically significant flood events, developing short-term flood forecasting models, and projecting future coastal flood risks and vulnerabilities that combine with rising sea levels. For coastal leaders, hazard managers, planners, and residents, effective communication of this data is important to how well it is applied to local impacts, policies, and adaptive measures. A number of U.S. government agencies (e.g., NOAA, NASA) have developed educational guidelines and data mapping tools to enhance understanding of science and coastal flood risks. However, these resources often require a general understanding of flood science, coastal oceanography, or climatic influences. Accessible online communication tools can provide a public benefit by increasing community risk perception and engagement, but these resources should understand their specific audience needs to ensure that relevant language, data, and local priorities are incorporated. In Imperial Beach, California, the low-lying coastal city currently experiences occasional coastal flooding during periods of high tides concurrent with winter storms or large wave events. To better prepare and mitigate the impacts of these events, the City of Imperial Beach has become a longstanding collaborator with the Scripps Institution of Oceanography. This partnership has led to increased technical guidance and support, as well as an abundance of Imperial Beach coastal flood data. Utilizing the flood risk science available in Imperial Beach, this research project sought to work with city staff to identify opportunities and limitations of communicating flood risk in Imperial Beach. The research design included four components. First, a review of flood risk literature and three types of flood risk communication available for Imperial Beach: historical flooding, short-term flood forecasting, and projections of future flood frequency. An ArcGIS storymap was then developed compiling and demonstrating potential methods for communicating Imperial Beach flood risk data in a centralized and publicly accessible format. The storymap was used to facilitate an informal interview and survey with Imperial Beach staff to obtain input on the utility and effectiveness of flood risk communication formats. Finally, an analysis of limitations and opportunities was conducted based on climate risk communication literature and input received from Imperial Beach government staff. This assessment found that communicating historical flood data that could be validated using in-situ observations such as images, videos, or other media was effective for communicating past events. However, historical flood risk communication could be improved if it better described what the different coastal flood drivers were. The short-term flood forecasting system was found to be useful in increasing collaboration between researchers and city officials, as well as increasing hazard response capabilities. However, future workshops between specialists and the public could increase public understanding and engagement, while offering feedback and validation of forecasting models and warning systems. Future projections of sea level rise and coastal flooding communication often relies too much on projections of worst-case scenarios in the long term (100+ years into the future). Additionally, flood frequency projection tools were useful for establishing a future timeline of increasing flood events, but inconsistent vocabulary defining flood days and events may complicate communication. Future coastal flood research projects could significantly benefit from increased stakeholder engagement, and relying on a bottom-up approach to communication and educational resource development.

Sea level rise resulting from human-induced global warming poses a grave threat to our planet, particularly endangering low-lying coastal areas susceptible to flooding. Effective beach monitoring can help vulnerable coastal communities anticipate the adverse impacts of sea level rise. CoastSnap, a worldwide beach monitoring program, collects and analyses coastline photos contributed by smartphone users. The primary objective is to study how beaches change over time while engaging and educating communities about the dynamic nature of their coastlines. CoastSnap employs community science, which empowers communities to actively participate in the scientific data collection and inquiry process, catering to the unique needs of each community. This capstone project focuses on establishing CoastSnap stations in and around the City of Imperial Beach, an exceptionally vulnerable coastal region within San Diego County. Three locations, including two on Imperial Beach Pier and one at Border Field State Park, have been identified as suitable sites for new stations. Additionally, an analysis of CoastSnap data from the Torrey Pines station explored the accuracy of image-derived beach width measurements in comparison to data obtained through physical beach surveying (in-situ), to demonstrate CoastSnap’s suitability for monitoring coastlines in Southern California. The comparison of CoastSnap measurements with in-situ measurements revealed an overall mean deviation of 1.35 meters, with CoastSnap measurements tending slightly more seaward. When considering tide levels, low tide events resulted in a lower mean deviation (mean = 0.94 meters) compared to high tides (mean = 1.78 meters). The analysis also found that CoastSnap-derived shorelines from Winter showed the strongest seaward deviation (mean = 4.30 meters), while Fall measurements tended to deviate slightly landward on average (mean = -0.61 meters).