Flow Regimes and Föhn Types Characterize the Local Climate of Southern Patagonia

Abstract

The local climate in Southern Patagonia is strongly influenced by the interaction between the topography and persistent westerlies, which can generate föhn events, dry and warm downslope winds. The upstream flow regime influences different föhn types which dictate the lee-side atmospheric response regarding the strength, spatial extent and phenomenology. We use a combination of observations from four automatic weather stations (AWSs) and high-resolution numerical modeling with the Weather Research and Forecasting (WRF) model for a region in Southern Patagonia (48° S–52° S, 72° W–76.5° W) including the Southern Patagonian Icefield (SPI). The application of a föhn identification algorithm to a 10-month study period (June 2018–March 2019) reveals 81 föhn events in total. A simulation of three events of differing flow regimes (supercritical, subcritical, transition) suggests that a supercritical flow regime leads to a linear föhn event with a large spatial extent but moderate intensity. In contrast, a spatially limited but locally strong föhn response is induced by a subcritical regime with upstream blocking and by a transition regime with a hydraulic jump present. Our results imply that the hydraulic jump-type föhn event (transition case) is the most critical for glacier mass balances since it shows the strongest warming, drying, wind velocities and solar radiation over the SPI. The consideration of flow regimes over the last 40 years shows that subcritical flow occurs most frequently (78%), however transitional flow occurs 14% of the time, implying the potential impact on Patagonian glaciers.

A Detailed, Multi‐Scale Assessment of an Atmospheric River Event and Its Impact on Extreme Glacier Melt in the Southern Alps of New Zealand

“…There might thus be a different response of glaciers situated at the western and eastern sides of the Main Divide during the same large‐scale conditions, as recognized earlier by Purdie et al. (2011) for Franz Joseph and Tasman glaciers and found for other foehn‐affected glacier environments as well (e.g., Temme et al., 2020).…”

“…A partitioning of the total U error into u‐ and v‐components showed that the largest overestimations by WRF coincide with very high v‐winds, suggesting that localized, terrain‐induced flow features like flow reversal and/or downslope acceleration may have produced peaks that do not align with observations. Both wind speed overestimation and cold temperature biases in WRF are frequently reported phenomena, particularly with respect to locations situated in remote regions or within complex terrain (e.g., Gómez‐Navarro et al., 2015; Temme et al., 2020; Zhang et al., 2013).…”

“…It would be of interest for a future study to compare the modeling results to additional data such as observed wind products, which we presently do not have access to; however, overall, the properties (direction, magnitude, depth, extent, persistence) of the simulated barrier jet do compare notably well to those reported from other studies concerned with barrier jets along the south‐western New Zealand coast (McCauley & Sturman, 1999; McGowan & Sturman, 1996; Revell et al., 2002). The occurrence of orographic blocking and barrier jet development is a common phenomenon in New Zealand and has occurred in association with many mountain ranges worldwide including the Andes (Temme et al., 2020), the European Alps (Bousquet & Smull, 2003), Antarctica (Schwerdtfeger, 1975), the Sierra Nevada (Parish, 1982), and Taiwan (Yeh & Chen, 2003). Some of these events have been associated with the landfall of LLJs and ARs (Bozkurt et al., 2018; Neiman et al.…”

“…For the high‐resolution domain (D2), topographic effects on radiation, including both topographic shading and slope effects, were accounted for and a cumulus parameterization was neglected since model simulations using a grid spacing smaller than 4 km are considered to resolve most convective processes explicitly (Weisman et al., 1997). Cloud microphysics were represented by the Morrison 2‐moment scheme, which we consider the most robust parametrization scheme for clouds and precipitation in high‐mountain and/or glacierized environments based on our previous modeling studies in different climatic zones (e.g., Collier et al., 2018; Mölg et al., 2017; Temme et al., 2020; Turton et al., 2020). Specifically, in the Himalayas, the Morrison 2‐moment scheme has been proven to produce the most accurate output (compared to other microphysics schemes) when evaluated against observational data and radar/lidar cloud products (Orr et al., 2017).…”

“…A partitioning of the total U error into u-and v-components showed that the largest overestimations by WRF coincide with very high v-winds, suggesting that localized, terrain-induced flow features like flow reversal and/or downslope acceleration may have produced peaks that do not align with observations. Both wind speed overestimation and cold temperature biases in WRF are frequently reported phenomena, particularly with respect to locations situated in remote regions or within complex terrain (e.g., Gómez-Navarro et al, 2015;Temme et al, 2020;Zhang et al, 2013). Despite these deficiencies, the statistical performance metrics are in the typical range of reported values for model evaluations of WRF based on hourly data (e.g., Bannister & King, 2015;Collier et al, 2018;Temme et al, 2020) and are thus considered to be a reliable and appropriate basis for mesoscale investigations.…”