In the past 2 decades, atmospheric rivers (ARs) have garnered continuous scientific interest and public attention due to their contributions to regional hydrological impacts including sources of freshwater supply,
Increasing severity of extreme heat is a hallmark of climate change. Its impacts depend on temperature but also on moisture and solar radiation, each with distinct spatial patterns and vertical profiles. Here, we consider these variables’ combined effect on extreme heat stress, as measured by the environmental stress index, using a suite of high-resolution climate simulations for historical (1980-2005) and future (2074-2099, RCP8.5) periods. We find that observed extreme heat stress drops off nearly linearly with elevation above a coastal zone, at a rate that is larger in more humid regions. Future projections indicate dramatic relative increases whereby the historical top-1% summer heat stress value may occur on about 25-50% of future summer days under the RCP8.5 scenario. Heat stress increases tend to be larger at higher latitudes and in areas of greater temperature increase, although in the southern and eastern US moisture increases are nearly as important. Imprinted on top of this dominant pattern we find secondary effects of smaller heat stress increases near ocean coastlines, notably along the Pacific coast, and larger increases in mountains, notably the Sierra Nevada and southern Appalachians. This differential warming is attributable to the greater warming of land relative to ocean, and to larger temperature increases at higher elevations outweighing larger water-vapor increases at lower elevations. All together, our results aid in furthering knowledge about drivers and characteristics that shape future extreme heat stress at scales difficult to capture in global assessments.
<p>Atmospheric rivers (ARs) are narrow, elongated structures, transporting large amounts of water vapor from the tropics towards polar regions. These synoptic scale features play an important role in the global hydrological cycle and for extreme precipitation events. To study how ARs will change in response to greenhouse warming we use a series of century-long fully coupled ultra-high-resolution simulations conducted with CESM 1.2.2 with an approximate horizontal resolution of ~25 km in the atmosphere and 10 km in the ocean. The simulations were carried out for present-day, 2xCO2 and 4xCO2 conditions. In this high atmospheric resolution, we obtain a much more realistic representation of complex orographic features (such as the Rocky Mountains), which can greatly influence the extreme precipitation often associated with ARs. Results from the present-day simulation are compared with ERA-Interim data to validate the model's fidelity in representing ARs. Our analysis focuses on future greenhouse-warming induced changes in AR frequency, geometry, landfalling latitude and strength. We find a global increase in the frequency of ARs amounting to ~0.5% for 2xCO2 and 0.9% for 4xCO2 respectively. In subtropical areas, such as the southwestern part of the United States AR frequencies increase by up to 7%. The presentation will further document the underlying processes for this increase.</p>
Abstract. Given the increasing use of climate projections and multi-model ensemble weighting for a diverse array of applications, this project assesses the sensitivities of climate model weighting, and their resulting ensemble means, to multiple components, such as the weighting schemes, climate variables, or spatial domains of interest. The analysis makes use of global climate models from the Coupled Model Intercomparison Project Phase 5 (CMIP5), and their statistically downscaled counterparts created with the Localized Canonical Analogs (LOCA) method. This work focuses on historical and projected future mean precipitation and daily high temperatures of the south-central United States. Results suggest that model weights and corresponding weighted projections are highly sensitive to the weighting method as well as to the selected variables and spatial domains. For instance, when estimating model weights based on Louisiana precipitation, the weighted projections show a wetter and cooler south-central domain in the future compared to other weighting schemes. Alternatively, for example, when estimating model weights based on New Mexico temperature, the weighted projections show a drier and warmer south-central domain in the future. However, when considering the entire south-central domain in estimating the model weights, the weighted future projections show a compromise in the precipitation and temperature estimates. If future impact assessments utilize weighting schemes, then our findings suggest that how the weighting scheme is derived and applied to the projections may depend on the needs of an impact assessment or adaptation plan. From the results of our analysis, we summarize our recommendations concerning multi-model ensemble weighting as follows: Weighted ensemble means should be used not only for national and international assessments but also for regional impacts assessments and planning. Multiple strategies for model weighting are employed when feasible, to assure that uncertainties from various sources (e.g., weighting strategy used, domain or variable of interest applied, etc.) are considered. That weighting is derived for individual sub-regions (such as the NCA regions) in addition to what is derived for the continental United States. That domain-specific weighting be derived using both common (e.g. precipitation) and stakeholder-specific (e.g. streamflow) variables to produce relevant analysis for impact assessments and planning.
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