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As the climate evolves over the next century, the interaction of accelerating sea level rise (SLR) and storms, combined with confining development and infrastructure, will place greater stresses on physical, ecological, and human systems along the ocean-land margin. Many of these valued coastal systems could reach tipping points, at which hazard exposure substantially increases and threatens the present-day form, function, and viability of communities, infrastructure, and ecosystems. Determining the timing and nature of these tipping points is essential for effective climate adaptation planning. Here we present a multidisciplinary case study from Santa Barbara, California (USA), to identify potential climate change-related tipping points for various coastal systems. This study integrates numerical and statistical models of the climate, ocean water levels, beach and cliff evolution, and two soft sediment ecosystems, sandy beaches and tidal wetlands. We find that tipping points for beaches and wetlands could be reached with just 0.25 m or less of SLR (~ 2050), with > 50% subsequent habitat loss that would degrade overall biodiversity and ecosystem function. In contrast, the largest projected changes in socioeconomic exposure to flooding for five communities in this region are not anticipated until SLR exceeds 0.75 m for daily flooding and 1.5 m for storm-driven flooding (~ 2100 or later). These changes are less acute relative to community totals and do not qualify as tipping points given the adaptive capacity of communities. Nonetheless, the natural and human built systems are interconnected such that the loss of natural system function could negatively impact the quality of life of residents and disrupt the local economy, resulting in indirect socioeconomic impacts long before built infrastructure is directly impacted by flooding.

Abstract: The presence of low-lying stratocumulus clouds and fog has been known to modify biophysical and ecological properties in coastal California where forests are frequently shaded by low-lying clouds or immersed in fog during otherwise warm and dry summer months. Summer fog and stratus can ameliorate summer drought stress and enhance soil water budgets and often have different spatial and temporal patterns. Here, this study uses remote sensing datasets to characterize the spatial and temporal patterns of cloud cover over California’s northern Channel Islands. The authors found marine stratus to be persistent from May to September across the years 2001–12. Stratus clouds were both most frequent and had the greatest spatial extent in July. Clouds typically formed in the evening and dissipated by the following early afternoon. This study presents a novel method to downscale satellite imagery using atmospheric observations and discriminate patterns of fog from those of stratus and help explain patterns of fog deposition previously studied on the islands. The outcomes of this study contribute significantly to the ability to quantify the occurrence of coastal fog at biologically meaningful spatial and temporal scales that can improve the understanding of cloud–ecosystem interactions, species distributions, and coastal ecohydrology.

Climate model simulations were used to investigate possible changes in regional climate over California. To accomplish this, the model simulations were downscaled from the coarse global climate model resolution (usually 150 kilometers [km] or greater horizontal grid spacing) to about 12 km horizontal grid spacing over the California region, using statistical techniques. The global model output was used in a statistical modeling scheme to produce sea-level projections for selected California coastal sites. Six global climate models and two greenhouse emissions scenarios, the medium-high emissions Special Report on Emissions Scenarios (SRES) A2 and the lower emissions SRES B1 were considered. By the end of the twenty-first century, the envelope of warming in the models projections, as an annual average, ranges from about 2°C to 6°C (about 3.5 °F to 11°F). On average, mean annual temperature of the A2 scenarios is about 1.5°C (about 3°F) greater than that of the B1 scenario. There is greater warming in summer than in winter. All simulations indicate that hot daytime and nighttime temperatures (heat waves) increase in frequency, magnitude, and duration from the historical period and during the projected period through the first half of the twenty-first century. Projected precipitation is marked by considerable variability between years and decades. In the southern half of California, the models show a decline in annual precipitation. Sea level, at hourly intervals for the historical through the projected twenty-first century, is estimated for selected tide gage sites along the California coast, with rises in the sample of simulations considered here ranging from 27 to 48 centimeters (cm) (11 to 19 in) over historical levels by 2050, and ranging from 77 cm to 140 cm (30 to 55 in) over historical levels by 2100. The rise of mean sea level would provoke an increase in extreme events, as gaged by exceedances above a relatively high or rare historical threshold. Such events become much more frequent and have longer durations than has been seen historically.

Low‐level stratiform clouds modulate California's coastal climate during the warm season. Previous work describing the seasonal and daily variability of coastal low cloudiness (CLC) suggests that in July, August, and September southern California's CLC is under the influence of an additional driver, which has less impact in northern California. In this work, we introduce the link in which free‐tropospheric moisture dictated by North American Monsoon (NAM) processes can impact southern California CLC. We use in situ and remote sensing observations, as well as reanalysis and single column model simulations to identify and investigate this previously missing component. We find that monsoonal moisture advected by southeasterly flow from the core NAM region into southern California reduces CLC by diminishing cloud‐top longwave cooling. To add to an already complex brew of known factors influencing coastal cloudiness, another one is hereby introduced and should be accounted for in future work. Plain Language Summary: Low‐altitude marine layer clouds shade and cool coastal California in spring and summer. When these clouds are low enough that the base of the cloud intercepts terrain (which is known as fog), they additionally add moisture to the landscape during a typically dry time of year in California. Future trends in coastal low cloudiness (CLC) are uncertain. Although CLC impact the whole coast of California and beyond, previous studies have exposed differences in seasonal and daily CLC behavior in southern and northern California. The North American Monsoon (NAM), which becomes active in the US Southwest in summer, brings rain and thunderstorms to the desert southwest. Coastal southern California is on the northwest edge of the NAM influence and typically does not receive much rain from NAM. In this study, we show how low altitude coastal cloud cover in southern California and northern Baja California can be diminished by higher altitude moisture from the NAM. Dry and stable air above the top of low clouds helps to maintain the cloud layer, and higher altitude moisture interrupts this process. To better understand how CLC varies and may change, an accounting of all key drivers of CLC behavior, including the NAM, is needed. Key Points: An increase in free‐tropospheric moisture over coastal southern California in summer is attributed to the North American Monsoon (NAM)NAM moisture intrusions can diminish southern California coastal low cloudiness by decreasing longwave cloud‐top coolingThese results link two iconic regional climate phenomena of the U.S. Southwest [ABSTRACT FROM AUTHOR]

A single-column model (SCM) and observational data collected during TOGA COARE were used to investigate the sensitivity of model-produced cloud properties and radiative fluxes to the representation of cloud microphysics in the cloud-radiation parameterizations. Four 78-day SCM numerical experiments were conducted for the atmospheric column overlying the COARE Intensive Flux Array. Each SCM experiment used a different cloud-radiation parameterization with a different representation of cloud microphysics. All the SCM experiments successfully reproduced most of the observed temporal variability in precipitation, cloud fraction, shortwave and longwave cloud forcing, and downwelling surface shortwave flux. The magnitude and temporal variability of the downward surface longwave flux was overestimated by all the SCM experiments. This bias is probably due to clouds forming too low in the model atmosphere. Time-averaged model results were used to examine the sensitivity of model performance to the differences between the four cloud-radiation parameterization packages. The SCM versions that calculated cloud amount as a function of cloud liquid water, instead of using a relative humidity-based cloud scheme, produced smaller amounts of both low and deep convective clouds. Additionally, larger high (cirrus) cloud emissivities were obtained with interactive cloud liquid water schemes than with the relative humidity-based scheme. Surprisingly, calculating cloud optical properties as a function of cloud liquid water amount, instead of parameterizing them based on temperature, humidity, and pressure, resulted in relatively little change in radiative fluxes. However, model radiative fluxes were sensitive to the specification of the effective cloud droplet radius. Optically thicker low clouds and optically thinner high clouds were produced when an interactive effective cloud droplet radius scheme was used instead of specifying a constant value. Comparison of model results to both surface and satellite observations revealed that model experiments that calculated cloud properties as a function of cloud liquid water produced more realistic cloud amounts and radiative fluxes. The most realistic vertical distribution of clouds was obtained from the SCM experiment that included the most complete representation of cloud microphysics. Due to the limitations of SCMs, the above conclusions are model dependent and need to be tested in a general circulation model.