Santa Ana Winds of Southern California: Historical Variability and Future Climate Projections

Santa Ana Winds of Southern California and Northern Baja California (SoCal) are the primary weather drivers of wildfires that frequently and infamously ravage this topographically and demographically complex region. As the available wind observations are scarce, Santa Ana Winds (SAWs) have not been adequately studied on climate timescales. Yet, wildfire behavior has been changing wildly even during my dissertation work. For example, the largest wildfire in California’s recorded history occurred in December of 2017, well outside the unique fall season for the largest wildfires typical of this region. This dissertation presents results of my efforts to understand Santa Ana wind behavior on climate timescales and in our changing climate. In Chapter 1, I developed and analyzed the longest and most complete record of hourly SAWs heretofore available. These results provide a robust perspective on both high- and low-frequency SAW behavior, uncovering previously unknown climate influences on SAW activity, and laying the groundwork for eventual studies into seasonal SAW predictability. Notably, the 65-year record of hourly SAWs did not manifest clear long-term trends. In Chapter 2, using a dynamically downscaled training data set, I developed an approach to statistically downscale coarsely resolved winds from a global Reanalysis with spatial resolution typical of global climate models (GCMs). The result was an efficient and skillful downscaling of coarse daily surface wind vectors onto a fine grid over the SoCal domain spanning 70 years. From these daily wind fields, I derived SAWs and validated them against my previously validated SAWs derived in Chapter 1 from our dynamical training data set. A capacity to statistically downscale daily winds from reanalyses and global climate models was thus developed and applied, in Chapter 3, to a set of eight GCMs yielding an ensemble of daily 10X10 km wind data sets covering SoCal and spanning a historical and future projected time period from 1950 to 2100. Analyses of these data yielded physically meaningful, robust and clear projections of SAW activity gradually decreasing and constricting around its traditional seasonal peak centered on December. These results provide robustness, nuance and meteorological context to expectations of future SoCal wildfire activity

Santa Ana Winds of Southern California: Historical Variability and Future Climate Projections

Santa Ana Winds of Southern California and Northern Baja California (SoCal) are the primary weather drivers of wildfires that frequently and infamously ravage this topographically and demographically complex region. As the available wind observations are scarce, Santa Ana Winds (SAWs) have not been adequately studied on climate timescales. Yet, wildfire behavior has been changing wildly even during my dissertation work. For example, the largest wildfire in California’s recorded history occurred in December of 2017, well outside the unique fall season for the largest wildfires typical of this region. This dissertation presents results of my efforts to understand Santa Ana wind behavior on climate timescales and in our changing climate. In Chapter 1, I developed and analyzed the longest and most complete record of hourly SAWs heretofore available. These results provide a robust perspective on both high- and low-frequency SAW behavior, uncovering previously unknown climate influences on SAW activity, and laying the groundwork for eventual studies into seasonal SAW predictability. Notably, the 65-year record of hourly SAWs did not manifest clear long-term trends. In Chapter 2, using a dynamically downscaled training data set, I developed an approach to statistically downscale coarsely resolved winds from a global Reanalysis with spatial resolution typical of global climate models (GCMs). The result was an efficient and skillful downscaling of coarse daily surface wind vectors onto a fine grid over the SoCal domain spanning 70 years. From these daily wind fields, I derived SAWs and validated them against my previously validated SAWs derived in Chapter 1 from our dynamical training data set. A capacity to statistically downscale daily winds from reanalyses and global climate models was thus developed and applied, in Chapter 3, to a set of eight GCMs yielding an ensemble of daily 10X10 km wind data sets covering SoCal and spanning a historical and future projected time period from 1950 to 2100. Analyses of these data yielded physically meaningful, robust and clear projections of SAW activity gradually decreasing and constricting around its traditional seasonal peak centered on December. These results provide robustness, nuance and meteorological context to expectations of future SoCal wildfire activity

Santa Ana Winds of Southern California Impact PM2.5 With and Without Smoke From Wildfires.

Fine particulate matter (PM2.5) raises human health concerns since it can deeply penetrate the respiratory system and enter the bloodstream, thus potentially impacting vital organs. Strong winds transport and disperse PM2.5, which can travel over long distances. Smoke from wildfires is a major episodic and seasonal hazard in Southern California (SoCal), where the onset of Santa Ana winds (SAWs) in early fall before the first rains of winter is associated with the region's most damaging wildfires. However, SAWs also tend to improve visibility as they sweep haze particles from highly polluted areas far out to sea. Previous studies characterizing PM2.5 in the region are limited in time span and spatial extent, and have either addressed only a single event in time or short time series at a limited set of sites. Here we study the space-time relationship between daily levels of PM2.5 in SoCal and SAWs spanning 1999-2012 and also further identify the impact of wildfire smoke on this relationship. We used a rolling correlation approach to characterize the spatial-temporal variability of daily SAW and PM2.5. SAWs tend to lower PM2.5 levels, particularly along the coast and in urban areas, in the absence of wildfires upwind. On the other hand, SAWs markedly increase PM2.5 in zip codes downwind of wildfires. These empirical relationships can be used to identify windows of vulnerability for public health and orient preventive measures

Santa Ana Winds of Southern California Impact PM2.5 With and Without Smoke From Wildfires

Abstract Fine particulate matter (PM2.5) raises human health concerns since it can deeply penetrate the respiratory system and enter the bloodstream, thus potentially impacting vital organs. Strong winds transport and disperse PM2.5, which can travel over long distances. Smoke from wildfires is a major episodic and seasonal hazard in Southern California (SoCal), where the onset of Santa Ana winds (SAWs) in early fall before the first rains of winter is associated with the region's most damaging wildfires. However, SAWs also tend to improve visibility as they sweep haze particles from highly polluted areas far out to sea. Previous studies characterizing PM2.5 in the region are limited in time span and spatial extent, and have either addressed only a single event in time or short time series at a limited set of sites. Here we study the space‐time relationship between daily levels of PM2.5 in SoCal and SAWs spanning 1999–2012 and also further identify the impact of wildfire smoke on this relationship. We used a rolling correlation approach to characterize the spatial‐temporal variability of daily SAW and PM2.5. SAWs tend to lower PM2.5 levels, particularly along the coast and in urban areas, in the absence of wildfires upwind. On the other hand, SAWs markedly increase PM2.5 in zip codes downwind of wildfires. These empirical relationships can be used to identify windows of vulnerability for public health and orient preventive measures

The health burden of fall, winter and spring extreme heat events in Southern California and contribution of Santa Ana Winds

Background : Extreme heat is associated with increased morbidity but most studies examine this relationship in warm seasons. In Southern California, Santa Ana winds (SAWs) are associated with high temperatures during the fall, winter and spring, especially in the coastal region. Objective s: Our aim was to examine the relationship between hospitalizations and extreme heat events in the fall, winter and spring, and explore the potential interaction with SAWs. Methods: Hospitalizations from 1999–2012 were obtained from the Office of Statewide Health Planning and Development Patient Discharge Data. A time-stratified case crossover design was employed to investigate the association between off-season heat and hospitalizations for various diagnoses. We examined the additive interaction of SAWs and extreme heat events on hospitalizations. Results : Over 1.5 million hospitalizations occurred in the Southern California coastal region during non-summer seasons. The 99th percentile-based thresholds that we used to define extreme heat events varied from a maximum temperature of 22.8 °C to 35.1 °C. In the fall and spring, risk of hospitalization increased for dehydration (OR: 1.23, 95% CI: 1.04, 1.45 and OR: 1.47 95% CI: 1.25, 1.71, respectively) and acute renal failure (OR: 1.35, 95% CI: 1.15, 1.58 and OR: 1.39, 95% CI: 1.19, 1.63, respectively) during 1-day extreme heat events. We also found an association between 1-day extreme heat events and hospitalization for ischemic stroke, with the highest risk observed in December. The results indicate that SAWs correspond to extreme heat events, particularly in the winter. Finally, we found no additive interaction with SAWs. Discussion : Results suggest that relatively high temperatures in non-summer months are associated with health burdens for several hospitalization outcomes. Heat action plans should consider decreasing the health burden of extreme heat events year-round

Ignitions explain more than temperature or precipitation in driving Santa Ana wind fires

Autumn and winter Santa Ana wind (SAW)-driven wildfires play a substantial role in area burned and societal losses in southern California. Temperature during the event and antecedent precipitation in the week or month prior play a minor role in determining area burned. Burning is dependent on wind intensity and number of human-ignited fires. Over 75% of all SAW events generate no fires; rather, fires during a SAW event are dependent on a fire being ignited. Models explained 40 to 50% of area burned, with number of ignitions being the strongest variable. One hundred percent of SAW fires were human caused, and in the past decade, powerline failures have been the dominant cause. Future fire losses can be reduced by greater emphasis on maintenance of utility lines and attention to planning urban growth in ways that reduce the potential for powerline ignitions

Heat, Disparities, and Health Outcomes in San Diego County's Diverse Climate Zones.

Climate variability and change are issues of growing public health importance. Numerous studies have documented risks of extreme heat on human health in different locations around the world. Strategies to prevent heat-related morbidity and reduce disparities are possible but require improved knowledge of health outcomes during hot days at a small-scale level as important within-city variability in local weather conditions, socio-demographic composition, and access to air conditioning (AC) may exist. We analyzed hospitalization data for three unique climate regions of San Diego County alongside temperature data spanning 14 years to quantify the health impact of ambient air temperature at varying exceedance threshold levels. Within San Diego, coastal residents were more sensitive to heat than inland residents. At the coast, we detected a health impact at lower temperatures compared to inland locations for multiple disease categories including heat illness, dehydration, acute renal failure, and respiratory disease. Within the milder coastal region where access to AC is not prevalent, heat-related morbidity was higher in the subset of zip codes where AC saturation is lowest. We detected a 14.6% increase (95% confidence interval [4.5%, 24.6%]) in hospitalizations during hot weather in comparison to colder days in coastal locations where AC is less common, while no significant impact was observed in areas with higher AC saturation. Disparities in AC ownership were associated with income, race/ethnicity, and homeownership. Given that heat waves are expected to increase with climate change, understanding health impacts of heat and the role of acclimation is critical for improving outcomes in the future