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This study investigates the predictability of downslope windstorms located in Santa Barbara County, California, locally referred to as Sundowner winds, from both observed relationships and a high-resolution, operational numerical weather prediction model. We focus on April 2022, during which the Sundowner Winds Experiment (SWEX) was conducted. We further refine our study area to the Montecito region owing to some of the highest wind measurements occurring at or near surface station MTIC1, situated on the coast-facing slope overlooking the area. Fires are not uncommon in this area, and the difficulty of egress makes the population particularly vulnerable. Area forecasters often use the sea-level pressure difference (ΔSLP) between Santa Barbara Airport (KSBA) and locations to the north such as Bakersfield (KBFL) to predict Sundowner windstorm occurrence. Our analysis indicates that ΔSLP by itself is prone to high false alarm rates and offers little information regarding downslope wind onset, duration, or magnitude. Additionally, our analysis shows that the high-resolution rapid refresh (HRRR) model has limited predictive skill overall for forecasting winds in the Montecito area. The HRRR, however, skillfully predicts KSBA-KBFL ΔSLP, as does GraphCast, a machine learning weather prediction model. Using a logistic regression model we were able to predict the occurrence of winds exceeding 9 m s−1 with a high probability of detection while minimizing false alarm rates compared to other methods analyzed. This provides a refined and easily computed algorithm for operational applications. 

We analyzed meteorological conditions that occurred during the December 2021 Boulder, Colorado, downslope windstorm. This event is of particular interest due to the ignition and spread of the Marshall Fire, which quickly became the most destructive wildfire in Colorado history. Observations indicated a rapid onset of fast winds with gusts as high as 51 m/s that generally remained confined to the east-facing slopes and foothills of the Rockies, similar to previous Boulder windstorms. After about 12 h, the windstorm shifted into a second, less intense phase. Midtropospheric winds above northwestern Colorado weakened prior to the onset of strong surface winds and the event strength started waning as stronger winds moved back into the area. Forecasts from NOAA high-resolution operational models initialized more than a few hours prior to windstorm onset did not simulate the start time, development rate and/or maximum strength of the windstorm correctly, and day-ahead runs even failed to develop strong downslope windstorms at all. Idealized modeling confirmed that predictability was limited by errors on the synoptic scale affecting the midtropospheric wind conditions representing the Boulder windstorm’s inflow environment. Gust forecasts for this event were critically evaluated. 

Abstract Coastal Santa Barbara is among the most exposed communities to wildfire hazards in Southern California. Downslope, dry, and gusty windstorms are frequently observed on the south-facing slopes of the Santa Ynez Mountains that separate the Pacific Ocean from the Santa Ynez valley. These winds, known as “Sundowners,” peak after sunset and are strong throughout the night and early morning. The Sundowner Winds Experiment (SWEX) was a field campaign funded by the National Science Foundation that took place in Santa Barbara, California, between 1 April and 15 May 2022. It was a collaborative effort of 10 institutions to advance understanding and predictability of Sundowners, while providing rich datasets for developing new theories of downslope windstorms in coastal environments with similar geographic and climatic characteristics. Sundowner spatiotemporal characteristics are controlled by complex interactions among atmospheric processes occurring upstream (Santa Ynez valley), and downstream due to the influence of a cool and stable marine boundary layer. SWEX was designed to enhance spatial measurements to resolve local circulations and vertical structure from the surface to the midtroposphere and from the Santa Barbara Channel to the Santa Ynez valley. This article discusses how SWEX brought cutting-edge science and the strengths of multiple ground-based and mobile instrument platforms to bear on this important problem. Among them are flux towers, mobile and stationary lidars, wind profilers, ceilometers, radiosondes, and an aircraft equipped with three lidars and a dropsonde system. The unique features observed during SWEX using this network of sophisticated instruments are discussed here. 

With the increase in commercially available small unmanned aircraft systems (UAS), new observations in extreme environments are becoming more obtainable. One such application is the fire environment, wherein measuring both fire and atmospheric properties are challenging. The Fire and Smoke Model Evaluation Experiment offered the unique opportunity of a large controlled wildfire, which allowed measurements that cannot generally be taken during an active wildfire. Fire–atmosphere interactions have typically been measured from stationary instrumented towers and by remote sensing systems such as lidar. Advances in UAS and compact meteorological instrumentation have allowed for small moving weather stations that can move with the fire front while sampling. This study highlights the use of DJI Matrice 200, which was equipped with a TriSonica Mini Wind and Weather station sonic anemometer weather station in order to sample the fire environment in an experimental and controlled setting. The weather station was mounted on to a carbon fiber pole extending off the side of the platform. The system was tested against an RM-Young 81,000 sonic anemometer, mounted at 6 and 2 m above ground levelto assess any bias in the UAS platform. Preliminary data show that this system can be useful for taking vertical profiles of atmospheric variables, in addition to being used in place of meteorological tower measurements when suitable. 

The November 2018 Camp Fire quickly became the deadliest and most destructive wildfire in California history. In this case study, we investigate the contribution of meteorological conditions and, in particular, a downslope windstorm that occurred during the 2018 Camp Fire. Dry seasonal conditions prior to ignition led to 100-h fuel moisture contents in the region to reach record low levels. Meteorological observations were primarily made from a number of remote automatic weather stations and a mobile scanning Doppler lidar deployed to the fire on 8 November 2018. Additionally, gridded operational forecast models and high-resolution meteorological simulations were synthesized in the analysis to provide context for the meteorological observations and structure of the downslope windstorm. Results show that this event was associated with mid-level anti-cyclonic Rossby wave breaking likely caused by cold air advection aloft. An inverted surface trough over central California created a pressure gradient which likely enhanced the downslope winds. Sustained surface winds between 3–6 m s−1 were observed with gusts of over 25 m s−1 while winds above the surface were associated with an intermittent low-level jet. The meteorological conditions of the event were well forecasted, and the severity of the fire was not surprising given the fire danger potential for that day. However, use of surface networks alone do not provide adequate observations for understanding downslope windstorm events and their impact on fire spread. Fire management operations may benefit from the use of operational wind profilers to better understand the evolution of downslope windstorms and other fire weather phenomena that are poorly understood and observed.