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  • Author or Editor: Justin R. Minder x
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Justin R. Minder

Abstract

Controls on the sensitivity of mountain snowpack accumulation to climate warming (λS ) are investigated. This is accomplished using two idealized, physically based models of mountain snowfall to simulate snowpack accumulation for the Cascade Mountains under current and warmed climates. Both models are forced from sounding observations. The first model uses the linear theory (LT) model of orographic precipitation to predict precipitation as a function of the incoming flow characteristics and uses the sounding temperatures to estimate the elevation of the rain–snow boundary, called the melting level (ML). The second “ML model” uses only the ML from the sounding and assumptions of uniform and constant precipitation. Both models simulate increases in precipitation intensity and elevated storm MLs under climate warming. The LT model predicts a 14.8%–18.1% loss of Cascade snowfall per degree of warming, depending on the vertical structure of the warming. The loss of snowfall is significantly greater, 19.4%–22.6%, if precipitation increases are neglected. Comparing the two models shows that the predominant control on λS is the relationship between the distribution of storm MLs and the distribution of topographic area with elevation. Although increases in precipitation due to warming may act to moderate λS , the loss of snow accumulation area profoundly limits the ability of precipitation increases to maintain the snowpack under substantial climate warming (beyond 1°–2°C). Circulation changes may act to moderate or exacerbate the loss of mountain snowpack under climate change via impacts on orographic precipitation enhancement.

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Theodore W. Letcher
and
Justin R. Minder

Abstract

Midlatitude mountain regions are particularly sensitive to climate change because of an active snow albedo feedback (SAF). Here, the SAF is characterized and quantified over the complex terrain of the Colorado Headwaters region using high-resolution regional climate model simulations. A pair of 7-yr control and pseudo-global warming simulations is used to study the regional climate response to a large-scale thermodynamic climate perturbation. Warming is strongly enhanced in regions of snow loss by as much as 5°C. Linear feedback analysis is used to quantify the strength of the SAF within the Headwaters region. The strength of the SAF reaches a maximum value of 4 W m−2 K−1 during April when snow loss coincides with strong incoming solar radiation. Simulations using 4- and 12-km horizontal grid spacing show good agreement in the strength and timing of the SAF, whereas a 36-km simulation shows discrepancies that are tied to differences in snow accumulation and ablation caused by smoother terrain. Energy budget analysis shows that transport by atmospheric circulations acts as a negative feedback to regional warming, damping the effects of the SAF. On the mesoscale, the SAF nonlocally enhances warming in locations with no snow, and enhances snowmelt in locations that do not experience snow cover change. The methods presented here can be used generally to quantify the role of the SAF in simulated regional climate change, illuminating the causes of differences in climate warming between models and regions.

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Oscar Chimborazo
,
Justin R. Minder
, and
Mathias Vuille

Abstract

Many mountain regions around the world are exposed to enhanced warming when compared to their surroundings, threatening key environmental services provided by mountains. Here we investigate this effect, known as elevation-dependent warming (EDW), in the Andes of Ecuador, using observations and simulations with the Weather Research and Forecasting (WRF) Model. EDW is discernible in observations of mean and maximum temperature in the Andes of Ecuador, but large uncertainties remain due to considerable data gaps in both space and time. WRF simulations of present-day (1986–2005) and future climate (RCP4.5 and RCP8.5 for 2041–60) reveal a very distinct EDW signal, with different rates of warming on the eastern and western slopes. This EDW effect is the combined result of multiple feedback mechanisms that operate on different spatial scales. Enhanced upper-tropospheric warming projects onto surface temperature on both sides of the Andes. In addition, changes in the zonal mean midtropospheric circulation lead to enhanced subsidence and warming over the western slopes at high elevation. The increased subsidence also induces drying, reduces cloudiness, and results in enhanced net surface radiation receipts, further contributing to stronger warming. Finally, the highest elevations are also affected by the snow-albedo feedback, due to significant reductions in snow cover by the middle of the twenty-first century. While these feedbacks are more pronounced in the high-emission scenario RCP8.5, our results indicate that high elevations in Ecuador will continue to warm at enhanced rates in the twenty-first century, regardless of emission scenario.

Significance Statement

Mountains are often projected to experience stronger warming than their surrounding lowlands going forward, a phenomenon known as elevation-dependent warming (EDW), which can threaten high-altitude ecosystems and lead to accelerated glacier retreat. We investigate the mechanisms associated with EDW in the Andes of Ecuador using both observations and model simulations for the present and the future. A combination of factors amplify warming at mountain tops, including a stronger warming high in the atmosphere, reduced cloudiness, and a reduction of snow and ice at high elevations. The latter two factors also favor enhanced absorption of sunlight, which promotes warming. The degree to which this warming is enhanced at high elevations in the future depends on the greenhouse gas emission pathway.

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Justin R. Minder
,
Theodore W. Letcher
, and
Changhai Liu

Abstract

The character and causes of elevation-dependent warming (EDW) of surface temperatures are examined in a suite of high-resolution ( km) regional climate model (RCM) simulations of climate change over the Rocky Mountains using the Weather Research and Forecasting Model. A clear EDW signal is found over the region, with warming enhanced in certain elevation bands by as much as 2°C. During some months warming maximizes at middle elevations, whereas during others it increases monotonically with elevation or is nearly independent of elevation. Simulated EDW is primarily caused by the snow albedo feedback (SAF). Warming maximizes in regions of maximum snow loss and albedo reduction. The role of the SAF is confirmed by sensitivity experiments wherein the SAF is artificially suppressed. The elevation dependence of free-tropospheric warming appears to play a secondary role in shaping EDW. No evidence is found for a contribution from elevation-dependent water vapor feedbacks. Sensitivity experiments show that EDW depends strongly on certain aspects of RCM configuration. Simulations using 4- and 12-km horizontal grid spacings show similar EDW signals, but substantial differences are found when using a grid spacing of 36 km due to the influence of terrain resolution on snow cover and the SAF. Simulations using the Noah and Noah-MP land surface models (LSMs) exhibit large differences in EDW. These are caused by differences between LSMs in their representations of midelevation snow extent and in their parameterization of subpixel fractional snow cover. These lead to albedo differences that act to modulate the simulated SAF and its effect on EDW.

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