Publications by Author: AHall

2011
Lee, WL, KN Liou, and A Hall. 2011. “Parameterization of solar fluxes over mountain surfaces for application to climate models.” Journal of Geophysical Research: Atmospheres 116: D01101. Publisher's Version Abstract
On the basis of 3‐D Monte Carlo photon tracing simulations, we have developed a parameterization of solar fluxes over mountain surfaces by means of the multiple linear regression analysis associated with topographic information, including elevation, solar incident angle, sky view factor, and terrain configuration factor. For clear skies without aerosols and clouds, the regression equation for the direct flux can explain more than 98% of the variation in which the solar incident angle is the dominant factor, except when the Sun is very low or at zenith. About 60% of the variation in the diffuse flux is predicted by the regression equation in which the mean elevation, sky view factor, and solar incident angle are key factors. The terrain‐reflected fluxes, proportional to the surface albedo, are well correlated with the terrain configuration factor with more than 80% of the variation that can be explained. The coupled fluxes involve intricate interactions, and the regression analysis is less satisfactory in cases of low albedo values. However, over high‐albedo surfaces, the terrain configuration factor becomes most dominant, leading to a significant improvement in regression performance. In these analyses, a surface albedo invariant with wavelength has been used. Using a region over the Sierra Nevada as a testbed, the preceding regression parameterizations have been specifically developed so that the fluxes evaluated from the 3‐D Monte Carlo model over intense topography can be used as a perturbation term to correct those computed from the plane‐parallel counterpart, commonly used in regional climate models and GCMs.
Dong, C, JC McWilliams, A Hall, and M Hughes. 2011. “Numerical simulation of a synoptic event in the Southern California Bight.” Journal of Geophysical Research: Oceans 116: C05018. Publisher's Version Abstract
In the middle of March 2002 a synoptic upwelling event occurred in the Southern California Bight; it was marked by a precipitous cooling of at least 4°C within 10–20 km of the coast. By the end of the month the preevent temperatures had slowly recovered. The Regional Oceanic Model System (ROMS) is used to simulate the event with an atmospheric downscaling reanalysis for surface wind and buoyancy flux forcing. Lateral boundary conditions of temperature, salinity, velocity, and sea level are taken from a global oceanic product. Barotropic tidal fields from a global barotropic model are imposed along the open boundaries. The simulation reproduces well the upwelling process compared with observed data. The sensitivity of the simulation is examined to wind resolution, heat flux, and tidal forcing. The oceanic response to the different wind resolutions converges at the level of the 6 km resolution, which is the finest scale present in the terrain elevation data set used in the atmospheric downscaling. The combination of an analytical diurnal cycle in the solar radiation and the empirical coupling with the instantaneous ROMS sea surface temperature produces a similar oceanic response to the downscaled heat flux. Tidal effects are significant in the upwelling evolution due to the increase in wind energy input through a quasi‐resonant alignment of the wind and surface current, probably by chance.
Pavelsky, T, S Kapnick, and A Hall. 2011. “Accumulation and melt dynamics of snowpack from a multiresolution regional climate model in the central Sierra Nevada, California.” Journal of Geophysical Research: Atmospheres 116: D16115. Publisher's Version Abstract
The depth and timing of snowpack in the Sierra Nevada Mountains are of fundamental importance to California water resource availability, and recent studies indicate a shift toward earlier snowmelt consistent with projected impacts of anthropogenic climate change. In order for future studies to assess snowpack variability on seasonal to centennial time scales, physically based models of snowpack evolution at high spatial resolution must be improved. Here we evaluate modeled snowpack accuracy for the central Sierra Nevada in the Weather Research and Forecasting regional climate model coupled to the Noah land surface model. A simulation with nested domains at 27, 9, and 3 km grid spacings is presented for November 2001 to July 2002. Model outputs are compared with daily snowpack observations at 41 locations, air temperature at 31 locations, and precipitation at 10 locations. Comparison of snowpack at different resolutions suggests that 27 km simulations substantially underestimate snowpack, while 9 and 3 km simulations are closer to observations. Regional snowpack accumulation is accurately simulated at these high resolutions, but model snowmelt occurs an average of 22–25 days early. Some error can be traced to differences in elevation and observation scale between point‐based measurements and model grid cells, but these factors cannot explain the persistent bias toward early snowmelt. A high correlation between snowmelt and error in modeled surface air temperature is found, with melt coinciding systematically with excessively cold air temperatures. One possible source of bias is an imbalance in turbulent heat fluxes, erroneously warming the snowpack while cooling the surface atmosphere.
Sun, F, A Hall, and X Qu. 2011. “On the relationship between low cloud variability and lower tropospheric stability in the Southeast Pacific.” Atmospheric Chemistry and Physics 11: 9053–9065. Publisher's Version Abstract
In this study, we examine marine low cloud cover variability in the Southeast Pacific and its association with lower-tropospheric stability (LTS) across a spectrum of timescales. On both daily and interannual timescales, LTS and low cloud amount are very well correlated in austral summer (DJF). Meanwhile in winter (JJA), when ambient LTS increases, the LTS–low cloud relationship substantially weakens. The DJF LTS–low cloud relationship also weakens in years with unusually large ambient LTS values. These are generally strong El Niño years, in which DJF LTS values are comparable to those typically found in JJA. Thus the LTS–low cloud relationship is strongly modulated by the seasonal cycle and the ENSO phenomenon. We also investigate the origin of LTS anomalies closely associated with low cloud variability during austral summer. We find that the ocean and atmosphere are independently involved in generating anomalies in LTS and hence variability in the Southeast Pacific low cloud deck. This highlights the importance of the physical (as opposed to chemical) component of the climate system in generating internal variability in low cloud cover. It also illustrates the coupled nature of the climate system in this region, and raises the possibility of cloud feedbacks related to LTS. We conclude by addressing the implications of the LTS–low cloud relationship in the Southeast Pacific for low cloud feedbacks in anthropogenic climate change.
Hughes, M, A Hall, and J Kim. 2011. “Human-induced changes in wind, temperature and relative humidity during Santa Ana events.” Climatic Change 109 (S1): 119–132. Publisher's Version Abstract
The frequency and character of Southern California’s Santa Ana wind events are investigated within a 12-km-resolution downscaling of late-20th and mid-21st century time periods of the National Center for Atmospheric Research Community Climate System Model global climate change scenario run. The number of Santa Ana days per winter season is approximately 20% fewer in the mid 21st century compared to the late 20th century. Since the only systematic and sustained difference between these two periods is the level of anthropogenic forcing, this effect is anthropogenic in origin. In both time periods, Santa Ana winds are partly katabatically-driven by a temperature difference between the cold wintertime air pooling in the desert against coastal mountains and the adjacent warm air over the ocean. However, this katabatic mechanism is significantly weaker during the mid 21st century time period. This occurs because of the well-documented differential warming associated with transient climate change, with more warming in the desert interior than over the ocean. Thus the mechanism responsible for the decrease in Santa Ana frequency originates from a well-known aspect of the climate response to increasing greenhouse gases, but cannot be understood or simulated without mesoscale atmospheric dynamics. In addition to the change in Santa Ana frequency, we investigate changes during Santa Anas in two other meteorological variables known to be relevant to fire weather conditions—relative humidity and temperature. We find a decrease in the relative humidity and an increase in temperature. Both these changes would favor fire. A fire behavior model accounting for changes in wind, temperature, and relative humidity simultaneously is necessary to draw firm conclusions about future fire risk and growth associated with Santa Ana events. While our results are somewhat limited by a relatively small sample size, they illustrate an observed and explainable regional change in climate due to plausible mesoscale processes.
Waliser, D, J Kim, Y Xue, Y Chao, A Eldering, R Fovell, A Hall, et al. 2011. “Simulating cold season snowpack: Impacts of snow albedo and multi-layer snow physics.” Climatic Change 109 (S1): 95–117. Publisher's Version Abstract
This study used numerical experiments to investigate two important concerns in simulating the cold season snowpack: the impact of the alterations of snow albedo due to anthropogenic aerosol deposition on snowpack and the treatment of snow physics using a multi-layer snow model. The snow albedo component considered qualitatively future changes in anthropogenic emissions and the subsequent increase or decrease of black carbon deposition on the Sierra Nevada snowpack by altering the prescribed snow albedo values. The alterations in the snow albedo primarily affect the snowpack via surface energy budget with little impact on precipitation. It was found that a decrease in snow albedo (by as little as 5–10% of the reference values) due to an increase in local emissions enhances snowmelt and runoff (by as much as 30–50%) in the early part of a cold season, resulting in reduced snowmelt-driven runoff (by as much as 30–50%) in the later part of the cold season, with the greatest impacts at higher elevations. An increase in snow albedo associated with reduced anthropogenic emissions results in the opposite effects. Thus, the most notable impact of the decrease in snow albedo is to enhance early-season snowmelt and to reduce late-season snowmelt, resulting in an adverse impact on warm season water resources in California. The timing of the sensitivity of snow water equivalent (SWE), snowmelt, and runoff vary systematically according to terrain elevation; as terrain elevation increases, the peak response of these fields occurs later in the cold season. The response of SWE and surface energy budget to the alterations in snow albedo found in this study shows that the effects of snow albedo on snowpack are further enhanced via local snow-albedo feedback. Results from this experiment suggest that a reduction in local emissions, which would increase snow albedo, could alleviate the early snowmelt and reduced runoff in late winter and early spring caused by global climate change, at least partially. The most serious uncertainties associated with this part of the study are a quantification of the relationship between the amount of black carbon deposition and snow albedo—a subject of future study. The comparison of the spring snowpack simulated with a single- and multi-layer snow model during the spring of 1998 shows that a more realistic treatment of snow physics in a multi-layer snow model could improve snowpack simulations, especially during spring when snow ablation is significant, or in conjunction with climate change projections.
2010
Hughes, M, and A Hall. 2010. “Local and synoptic mechanisms causing Southern California's Santa Ana winds.” Climate Dynamics 34 (6): 847–857. Publisher's Version Abstract
The atmospheric conditions that lead to strong offshore surface winds in Southern California, commonly referred to as Santa Ana winds, are investigated using the North American Regional Reanalysis and a 12-year, 6-km resolution regional climate simulation of Southern California. We first construct an index to characterize Santa Ana events based on offshore wind strength. This index is then used to identify the average synoptic conditions associated with Santa Ana events—a high pressure anomaly over the Great Basin. This pressure anomaly causes offshore geostrophic winds roughly perpendicular to the region’s mountain ranges, which in turn cause surface flow as the offshore momentum is transferred to the surface. We find, however, that there are large variations in the synoptic conditions during Santa Ana conditions, and that there are many days with strong offshore flow and weak synoptic forcing. This is due to local thermodynamic forcing that also causes strong offshore surface flow: a large temperature gradient between the cold desert surface and the warm ocean air at the same altitude creates an offshore pressure gradient at that altitude, in turn causing katabatic-like offshore flow in a thin layer near the surface. We quantify the contribution of “synoptic” and “local thermodynamic” mechanisms using a bivariate linear regression model, and find that, unless synoptic conditions force strongly onshore winds, the local thermodynamic forcing is the primary control on Santa Ana variability.
Moritz, M, T Moody, M Krawchuk, M Hughes, and A Hall. 2010. “Spatial variation in extreme winds predicts large wildfire locations in chaparral ecosystems.” Geophysical Research Letters 37: L04801. Publisher's Version Abstract
Fire plays a crucial role in many ecosystems, and a better understanding of different controls on fire activity is needed. Here we analyze spatial variation in fire danger during episodic wind events in coastal southern California, a densely populated Mediterranean‐climate region. By reconstructing almost a decade of fire weather patterns through detailed simulations of Santa Ana winds, we produced the first high‐resolution map of where these hot, dry winds are consistently most severe and which areas are relatively sheltered. We also analyzed over half a century of mapped fire history in chaparral ecosystems of the region, finding that our models successfully predict where the largest wildfires are most likely to occur. There is a surprising lack of information about extreme wind patterns worldwide, and more quantitative analyses of their spatial variation will be important for effective fire management and sustainable long‐term urban development on fire‐prone landscapes.
A study of the California Sierra Nevada snowpack has been conducted using snow station observations and reanalysis surface temperature data. Monthly snow water equivalent (SWE) measurements were combined from two datasets to provide sufficient data from 1930 to 2008. The monthly snapshots are used to calculate peak snow mass timing for each snow season. Since 1930, there has been an overall trend toward earlier snow mass peak timing by 0.6 days per decade. The trend toward earlier timing also occurs at nearly all individual stations. Even stations showing an increase in 1 April SWE exhibit the trend toward earlier timing, indicating that enhanced melting is occurring at nearly all stations. Analysis of individual years and stations reveals that warm daily maximum temperatures averaged over March and April are associated with earlier snow mass peak timing for all spatial and temporal scales included in the dataset. The influence is particularly pronounced for low accumulation years indicating the potential importance of albedo feedback for the melting of shallow snow. The robustness of the early spring temperature influence on peak timing suggests the trend toward earlier peak timing is attributable to the simultaneous warming trend (0.1°C decade−1 since 1930, with an acceleration in warming in later time periods). Given future scenarios of warming in California, one can expect acceleration in the trend toward earlier peak timing; this will reduce the warm season storage capacity of the California snowpack.
We show that intermodel variations in the anthropogenically-forced evolution of September sea ice extent (SSIE) in the Arctic stem mainly from two factors: the baseline climatological sea ice thickness (SIT) distribution, and the local climate feedback parameter. The roles of these two factors evolve over the course of the twenty-first century. The SIT distribution is the most important factor in current trends and those of coming decades, accounting for roughly half the intermodel variations in SSIE trends. Then, its role progressively decreases, so that around the middle of the twenty-first century the local climate feedback parameter becomes the dominant factor. Through this analysis, we identify the investments in improved simulation of Arctic climate necessary to reduce uncertainties both in projections of sea ice loss over the coming decades and in the ultimate fate of the ice pack.
Boé, J, A Hall, F Colas, JC McWilliams, X Qu, J Kurian, and S Kapnick. 2010. “What shapes mesoscale wind anomalies in coastal upwelling zones?” Climate Dynamics 36: 2037–2049. Publisher's Version Abstract
Observational studies have shown that mesoscale variations in sea surface temperature may induce mesoscale variations in wind. In eastern subtropical upwelling regions such as the California coast, this mechanism could be of great importance for the mean state and variability of the climate system. In coastal regions orography also creates mesoscale variations in wind, and the orographic effect may extend more than 100 km offshore. The respective roles of SST/wind links and coastal orography in shaping mesoscale wind variations in nearshore regions is not clear. We address this question in the context of the California Upwelling System, using a high-resolution regional numerical modeling system coupling the WRF atmospheric model to the ROMS oceanic model, as well as additional uncoupled experiments to quantify and separate the effects of SST/wind links and coastal orography on mesoscale wind variations. After taking into account potential biases in the representation of the strength of SST/wind links by the model, our results suggest that the magnitude of mesoscale wind variations arising from the orographic effects is roughly twice that of wind variations associated with mesoscale SST anomalies. This indicates that even in this region where coastal orography is complex and leaves a strong imprint on coastal winds, the role of SST/winds links in shaping coastal circulation and climate cannot be neglected.
Qu, X, A Hall, and J Boé. 2010. “Why does the Antarctic Peninsula warm in climate simulations?” Climate Dynamics 38 (5–6): 913–927. Publisher's Version Abstract
The Antarctic Peninsula has warmed significantly since the 1950s. This pronounced and isolated warming trend is collectively captured by 29 twentieth-century climate hindcasts participating in the version 3 Coupled Model Intercomparison Project. To understand the factors driving warming trends in the hindcasts, we examine trends in Peninsula region’s atmospheric heat budget in every simulation. We find that atmospheric latent heat release increases in nearly all hindcasts. These increases are generally anthropogenic in origin, and account for about 60% of the ensemble-mean warming trend in the Peninsula. They are driven primarily by well-understood features of the anthropogenic intensification of global hydrological cycle. As sea surface temperature increases, moisture contained in atmospheric flows increases. When such flows are forced to ascend the Peninsula’s topography, enhanced local latent heat release results. The mechanism driving the warming of the Antarctic Peninsula is therefore clear in the models. Evidence for a similar mechanism operating in the real world is seen in the increasing snow accumulation rates inferred from ice cores drilled in the Peninsula. However, the relative importance of this mechanism and other processes previously identified as potentially causing the observed warming, such as the recent sea ice retreat in the Bellingshausen Sea, is difficult to assess. Thus the relevance of the simulated warming mechanism to the observed warming is unclear, in spite of its robustness in the models.
2009
Hughes, M, A Hall, and RG Fovell. 2009. “Blocking in areas of complex topography, and its influence on rainfall distribution.” Journal of the Atmospheric Sciences 66: 508–518. Publisher's Version Abstract

Using a 6-km-resolution regional climate simulation of Southern California, the effect of orographic blocking on the precipitation climatology is examined. To diagnose whether blocking occurs, precipitating hours are categorized by a bulk Froude number. The precipitation distribution becomes much more spatially homogeneous as the Froude number decreases, and an inspection of winds confirms that this results from the increasing prevalence of orographic blocking. Low Froude (Froude approximately less than 1), blocked cases account for a large fraction of climatological precipitation, particularly at the coastline where more than half is attributable to blocked cases. Thus, the climatological precipitation–slope relationship seen in observations and in the simulation is a hybrid of blocked and unblocked cases.

Simulated precipitation distributions are compared to those predicted by a simple linear model that includes only rainfall arising from direct forced topographic ascent. The agreement is nearly perfect for high Froude (Froude substantially larger than 1) cases but degrades dramatically as the index decreases; as blocking becomes more prevalent, the precipitation–slope relationship becomes continuously weaker than that predicted by the linear model. Because of its high fidelity during unblocked cases, it is surmised that blocking effects are the primary limitation preventing the linear model from accurately representing precipitation climatology and that the representation would be significantly improved during low Froude hours by the addition of a term to reduce the effective slope of the topography. These results suggest orographic blocking may substantially affect climatological precipitation distributions in similarly configured coastal areas.

Boé, J, A Hall, and X Qu. 2009. “Current GCMs' unrealistic negative feedback in the Arctic.” . Journal of Climate 22: 4682–4695. Publisher's Version Abstract
The large spread of the response to anthropogenic forcing simulated by state-of-the-art climate models in the Arctic is investigated. A feedback analysis framework specific to the Arctic is developed to address this issue. The feedback analysis shows that a large part of the spread of Arctic climate change is explained by the longwave feedback parameter. The large spread of the negative longwave feedback parameter is in turn mainly due to variations in temperature feedback. The vertical temperature structure of the atmosphere in the Arctic, characterized by a surface inversion during wintertime, exerts a strong control on the temperature feedback and consequently on simulated Arctic climate change. Most current climate models likely overestimate the climatological strength of the inversion, leading to excessive negative longwave feedback. The authors conclude that the models’ near-equilibrium response to anthropogenic forcing is generally too small.
Fletcher, C, P Kushner, A Hall, and X Qu. 2009. “Circulation responses to snow albedo feedback in climate change.” Geophysical Research Letters 36: L09702. Publisher's Version Abstract
Climate change is expected to cause a reduction in the spatial extent of snow cover on land. Recent work suggests that this will exert a local influence on the atmosphere and the hydrology of snow‐margin areas through the snow‐albedo feedback (SAF) mechanism. A significant fraction of variability among IPCC AR4 general circulation model (GCM) predictions for future summertime climate change over these areas is related to the models' representation of springtime SAF. In this study, we demonstrate a nonlocal influence of SAF on the summertime circulation in the extratropical Northern Hemisphere. Increased land surface warming in models with stronger SAF is associated with large‐scale sea‐level pressure anomalies over the northern oceans and a poleward intensified subtropical jet. We find that up to 25–30% and, on average, 5–10% of the inter‐model spread in projections of the circulation response to climate change is linearly related to SAF strength.
Derevianko, G, C Deutsch, and A Hall. 2009. “On the relationship between DMS and solar radiation.” Geophysical Research Letters 36: L17606. Publisher's Version Abstract
Biologically produced dimethylsulfide (DMS) is an important source of sulfur to the marine atmosphere that may affect cloud formation and properties. DMS is involved in a complex set of biochemical transformations and ecological exchanges so its global distribution is influenced by numerous factors, including oxidative stress from UV radiation. We re‐examine correlations between global surface DMS concentrations and mixed layer solar radiation dose (SRD), and find that SRD accounts for only a very small fraction (14%) of total variance in DMS measurements when using minimal aggregation methods. Moreover this relationship arises in part from the fact that when mixed layers deepen, both SRD and DMS decrease. When we control for this confounding effect, the correlation between DMS and SRD is reduced even further. These results indicate that factors other than solar irradiance play a leading role in determining global DMS emissions.
Boé, J, A Hall, and X Qu. 2009. “September sea-ice cover in the Arctic Ocean projected to vanish by 2100.” Nature Geoscience 2: 341–343. Publisher's Version Abstract
The Arctic climate is changing rapidly1. From 1979 to 2006, September sea-ice extent decreased by almost 25% or about 100,000 km2 per year (ref. 2). In September 2007, Arctic sea-ice extent reached its lowest level since satellite observations began3and in September 2008, sea-ice cover was still low. This development has raised concerns that the Arctic Ocean could be ice-free in late summer in only a few decades, with important economic and geopolitical implications. Unfortunately, most current climate models underestimate significantly the observed trend in Arctic sea-ice decline4, leading to doubts regarding their projections for the timing of ice-free conditions. Here we analyse the simulated trends in past sea-ice cover in 18 state-of-art-climate models and find a direct relationship between the simulated evolution of September sea-ice cover over the twenty-first century and the magnitude of past trends in sea-ice cover. Using this relationship together with observed trends, we project the evolution of September sea-ice cover over the twenty-first century. We find that under a scenario with medium future greenhouse-gas emissions, the Arctic Ocean will probably be ice-free in September before the end of the twenty-first century.
Boé, J, A Hall, and X Qu. 2009. “Deep ocean heat uptake as a major source of spread in transient climate change simulations.” Geophysical Research Letters 36: L22701. Publisher's Version Abstract

Two main mechanisms can potentially explain the spread in the magnitude of global warming simulated by climate models: deep ocean heat uptake and climate feedbacks. Here, we show that deep oceanic heat uptake is a major source of spread in simulations of 21st century climate change. Models with deeper baseline polar mixed layers are associated with larger deep ocean warming and smaller global surface warming. Based on this result, we set forth an observational constraint on polar vertical oceanic mixing. This constraint suggests that many models may overestimate the efficiency of polar oceanic mixing and therefore may underestimate future surface warming. Thus to reduce climate change uncertainties at time‐scales relevant for policy‐making, improved understanding and modelling of oceanic mixing at high latitudes is crucial.

Fernandes, R, H Zhao, X Wang, J Key, X Qu, and A Hall. 2009. “Controls on northern hemisphere snow albedo feedback quantified using satelllite Earth observations.” Geophysical Research Letters 36: L21702. Publisher's Version Abstract
Observation based estimates of controls on snow albedo feedback (SAF) are needed to constrain the snow and albedo parameterizations in general circulation model (GCM) projections of air temperature over the Northern Hemisphere (NH) landmass. The total April‐May NH SAF, corresponding to the sum of the effect of temperature on surface albedo over snow covered surfaces (‘metamorphism’) and over surfaces transitioning from snow covered to snow free conditions (‘snow cover’), is derived with daily NH snow cover and surface albedo products using Advanced Very High Resolution Radiometer Polar Pathfinder satellite data and surface air temperature from ERA40 reanalysis data between 1982–1999. Without using snow cover information, the estimated total SAF, for land surfaces north of 30°N, of −0.93 ± 0.06%K−1 was not significantly different (95% confidence) from estimates based on International Satellite Cloud Climatology Project surface albedo data. The SAF, constrained to only snow covered areas, grew to −1.06 ± 0.08%K−1 with similar magnitudes for the ‘snow cover’ and ‘metamorphosis’ components. The SAF pattern was significantly correlated with the ‘snow cover’ component pattern over both North America and Eurasia but only over Eurasia for the ‘metamorphosis’ component. However, in contrast to GCM model based diagnoses of SAF, the control on the ‘snow cover’ component related to the albedo contrast of snow covered and snow free surfaces was not strongly correlated to the total SAF.
2008
Hall, A, X Qu, and JD Neelin. 2008. “Improving predictions of summer climate change in the United States.” Geophysical Research Letters 35: L01702. Publisher's Version Abstract
Across vast, agriculturally intensive regions of the United States, the spread in predictions of summer temperature and soil moisture under global warming is curiously elevated in current climate models. Some models show modest warming of 2–3C° and little drying or slight moistening by the 22nd century, while at the other extreme are simulations with warming as large as 7–8C° and 20–40% reductions in soil moisture. We show this region of large spread arises from differences in simulations of snow albedo feedback. During winter and early spring, models with strong snow albedo feedback exhibit large reductions in snowpack and hence water storage. This water deficit persists in summer soil moisture, with reduced evapotranspiration yielding warmer temperatures. Comparison of simulated feedback strength to observations of the feedback from the current climate's seasonal cycle suggests the inter‐model differences are excessive. At the same time, the multi‐model mean feedback strength agrees reasonably well with the observed value. We estimate that if the next generation of models were brought into line with observations of snow albedo feedback, the unusually wide divergence in simulations of summer warming and drying over the US would shrink by roughly one third to one half.

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