Publications

2014
Jin, Y, JT Randerson, N Faivre, SB Capps, A Hall, and ML Goulden. 2014. “Contrasting controls on wildland fires in Southern California during periods with and without Santa Ana winds.” Journal of Geophysical Research—Biogeosciences 119 (3): 432–450. Publisher's Version Abstract
Wildland fires in Southern California can be divided into two categories: fall fires, which are typically driven by strong offshore Santa Ana winds, and summer fires, which occur with comparatively weak onshore winds and hot and dry weather. Both types of fire contribute significantly to annual burned area and economic loss. An improved understanding of the relationship between Southern California's meteorology and fire is needed to improve predictions of how fire will change in the future and to anticipate management needs. We used output from a regional climate model constrained by reanalysis observations to identify Santa Ana events and partition fires into those occurring during periods with and without Santa Ana conditions during 1959–2009. We then developed separate empirical regression models for Santa Ana and non‐Santa Ana fires to quantify the effects of meteorology on fire number and size. These models explained approximately 58% of the seasonal and interannual variation in the number of Santa Ana fires and 36% of the variation in non‐Santa Ana fires. The number of Santa Ana fires increased during years when relative humidity during Santa Ana events and fall precipitation were below average, indicating that fuel moisture is a key controller of ignition. Relative humidity strongly affected Santa Ana fire size. Cumulative precipitation during the previous three winters was significantly correlated with the number of non‐Santa Ana fires, presumably through increased fine fuel density and connectivity between infrastructure and nearby vegetation. Both relative humidity and the preceding wet season precipitation influenced non‐Santa Ana fire size. Regression models driven by meteorology explained 57% of the temporal variation in Santa Ana burned area and 22% of the variation in non‐Santa Ana burned area. The area burned by non‐Santa Ana fires has increased steadily by 1.7% year−1 since 1959 (p < 0.006); the occurrence of extremely large Santa Ana fires has increased abruptly since 2003. Our results underscore the need to separately consider the fuel and meteorological controls on Santa Ana and non‐Santa Ana fires when projecting climate change impacts on regional fire.
Hall, A. 2014. “Projecting regional change.” Science 346 (6216): 1461–1462. Publisher's Version Abstract
Techniques to downscale global climate model (GCM) output and produce high-resolution climate change projections have emerged over the past two decades. GCM projections of future climate change, with typical resolutions of about 100 km, are now routinely downscaled to resolutions as high as hundreds of meters. Pressure to use these techniques to produce policy-relevant information is enormous. To prevent bad decisions, the climate science community must identify downscaling's strengths and limitations and develop best practices. A starting point for this discussion is to acknowledge that downscaled climate signals arising from warming are more credible than those arising from circulation changes.
2013
Flato, G, J Marotzke, B Abiodun, P Braconnot, SC Chou, W Collins, P Cox, et al. 2013. “Evaluation of climate models.” Climate Change 2013: The Physical Science Basis. Contribution of Working Group I to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change. New York: Cambridge University Press. Publisher's Version Abstract
Climate models have continued to be developed and improved since the AR4, and many models have been extended into Earth System models by including the representation of biogeochemical cycles important to climate change. These models allow for policy-relevant calculations such as the carbon dioxide (CO2) emissions compatible with a specified climate stabilization target. In addition, the range of climate variables and processes that have been evaluated has greatly expanded, and differences between models and observations are increasingly quantified using ‘performance metrics’. In this chapter, model evaluation covers simulation of the mean climate, of historical climate change, of variability on multiple time scales and of regional modes of variability. This evaluation is based on recent internationally coordinated model experiments, including simulations of historic and paleo climate, specialized experiments designed to provide insight into key climate processes and feedbacks and regional climate downscaling. Figure 9.44 provides an overview of model capabilities as assessed in this chapter, including improvements, or lack thereof, relative to models assessed in the AR4. The chapter concludes with an assessment of recent work connecting model performance to the detection and attribution of climate change as well as to future projections.
Christensen, JH, KK Kanikicharla, E Adlrian, SI An, IFA Cavalcanti, M de Castro, W Dong, et al. 2013. “Climate phenomena and their relevance for future regional climate change.” Climate Change 2013: The Physical Science Basis. Contribution of Working Group I to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change. New York: Cambridge University Press. Publisher's Version Abstract
This chapter assesses the scientific literature on projected changes in major climate phenomena and more specifically their relevance for future change in regional climates, contingent on global mean temperatures continue to rise.
Berg, N, A Hall, SB Capps, and M Hughes. 2013. “El Niño–Southern Oscillation impacts on winter winds over Southern California.” Climate Dynamics 40 (1–2): 109–121. Publisher's Version Abstract
Changes in wintertime 10 m winds due to the El Niño-Southern Oscillation are examined using a 6 km resolution climate simulation of Southern California covering the period from 1959 through 2001. Wind speed statistics based on regional averages reveal a general signal of increased mean wind speeds and wind speed variability during El Niño across the region. An opposite and nearly as strong signal of decreased wind speed variability during La Niña is also found. These signals are generally more significant than the better-known signals in precipitation. In spite of these regional-scale generalizations, there are significant sub-regional mesoscale structures in the wind speed impacts. In some cases, impacts on mean winds and wind variability at the sub-regional scale are opposite to those of the region as a whole. All of these signals can be interpreted in terms of shifts in occurrences of the region’s main wind regimes due to the El Niño phenomenon. The results of this study can be used to understand how interannual wind speed variations in regions of Southern California are influenced by the El Niño phenomenon.
Toniazzo, T, F Sun, CR Mechoso, and A Hall. 2013. “A regional modeling study of the diurnal cycle in the lower troposphere in the south-eastern tropical Pacific.” Climate Dynamics 41 (7–8): 1899–1922. Publisher's Version Abstract
We examine the influence of the South-American land-mass and its mountains on the significant cyclic diurnal and semidiurnal components of the average circulation in the adjacent area of the southeastern tropical Pacific (SEP). Our approach is based on a number of numerical simulations with the regional atmospheric model weather research and forecasting forced by the National Centers for Environmental Prediction’s final analysis operational analysis data. In the control simulation the model domain covers the SEP and a large part of South America. In several sensitivity experiments the domain is reduced to progressively exclude continental areas. We find that the mean diurnal cycle is sensitive to model domain in ways that reveal the existence of different contributions originating from the Chilean and Peruvian land-masses. The experiments suggest that diurnal variations in circulations and thermal structures over the SEP (mainly forced by local insolation) are influenced by convection over the Peruvian sector of the Andes cordillera, while the mostly dry mountain-breeze circulations force an additional component that results in semi-diurnal variations near the coast. A series of numerical tests, however, reveal sensitivity of the simulations to the choice of vertical grid, limiting the possibility of solid quantitative statements on the amplitudes and phases of the diurnal and semidiurnal components across the domain.
Boé, J, A Hall, and X Qu. 2013. “Reply to "Comments on 'Current GCMs' Unrealistic Negative Feedback in the Arctic.'".” Journal of Climate 26 (19): 7789–7792. Publisher's Version Abstract
Pithan and Mauritsen argue that the 2009 results of Boé et al. are not consistent with current understanding of the lapse-rate feedback in the Arctic. They also argue that these results arise to an important extent from self-correlation issues. In this response, the authors argue that their results are not inconsistent with current understanding of lapse-rate feedback and demonstrate that the conclusions remain unchanged when all possibilities of self-correlation are excluded.
Huang, HY, A Hall, and J Teixeira. 2013. “Evaluation of the WRF PBL parameterizations for marine boundary layer clouds: Cumulus and stratocumulus.” Monthly Weather Review 141: 2265–2271. Publisher's Version Abstract
The performance of five boundary layer parameterizations in the Weather Research and Forecasting Model is examined for marine boundary layer cloud regions running in single-column mode. Most parameterizations show a poor agreement of the vertical boundary layer structure when compared with large-eddy simulation models. These comparisons against large-eddy simulation show that a parameterization based on the eddy-diffusivity/mass-flux approach provides a better performance. The results also illustrate the key role of boundary layer parameterizations in model performance.
Neelin, JD, B Langenbrunner, JE Meyerson, A Hall, and N Berg. 2013. “California winter precipitation change under global warming in the Coupled Model Intercomparison Project 5 ensemble.” Journal of Climate 26: 6238–6256. Publisher's Version Abstract
Projections of possible precipitation change in California under global warming have been subject to considerable uncertainty because California lies between the region anticipated to undergo increases in precipitation at mid-to-high latitudes and regions of anticipated decrease in the subtropics. Evaluation of the large-scale model experiments for phase 5 of the Coupled Model Intercomparison Project (CMIP5) suggests a greater degree of agreement on the sign of the winter (December–February) precipitation change than in the previous such intercomparison, indicating a greater portion of California falling within the increased precipitation zone. While the resolution of global models should not be relied on for accurate depiction of topographic rainfall distribution within California, the precipitation changes depend substantially on large-scale shifts in the storm tracks arriving at the coast. Significant precipitation increases in the region arriving at the California coast are associated with an eastward extension of the region of strong Pacific jet stream, which appears to be a robust feature of the large-scale simulated changes. This suggests that effects of this jet extension in steering storm tracks toward the California coast constitute an important factor that should be assessed for impacts on incoming storm properties for high-resolution regional model assessments.
2012
Kapnick, S, and A Hall. 2012. “Causes of recent changes in western North American snowpack.” Climate Dynamics 40 (1–2): 109–121. Publisher's Version Abstract
Changes in wintertime 10 m winds due to the El Niño-Southern Oscillation are examined using a 6 km resolution climate simulation of Southern California covering the period from 1959 through 2001. Wind speed statistics based on regional averages reveal a general signal of increased mean wind speeds and wind speed variability during El Niño across the region. An opposite and nearly as strong signal of decreased wind speed variability during La Niña is also found. These signals are generally more significant than the better-known signals in precipitation. In spite of these regional-scale generalizations, there are significant sub-regional mesoscale structures in the wind speed impacts. In some cases, impacts on mean winds and wind variability at the sub-regional scale are opposite to those of the region as a whole. All of these signals can be interpreted in terms of shifts in occurrences of the region’s main wind regimes due to the El Niño phenomenon. The results of this study can be used to understand how interannual wind speed variations in regions of Southern California are influenced by the El Niño phenomenon.
2011
Pavelsky, T, J Boé, A Hall, and E Fetzer. 2011. “Atmospheric inversion strength over polar oceans in winter regulated by sea ice.” Climate Dynamics 36: 945–955. Publisher's Version Abstract
Low-level temperature inversions are a common feature of the wintertime troposphere in the Arctic and Antarctic. Inversion strength plays an important role in regulating atmospheric processes including air pollution, ozone destruction, cloud formation, and negative longwave feedback mechanisms that shape polar climate response to anthropogenic forcing. The Atmospheric Infrared Sounder (AIRS) instrument provides reliable measures of spatial patterns in mean wintertime inversion strength when compared with available radiosonde observations and reanalysis products. Here, we examine the influence of sea ice concentration on inversion strength in the Arctic and Antarctic. Correlation of inversion strength with mean annual sea ice concentration, likely a surrogate for the effective thermal conductivity of the wintertime ice pack, yields strong, linear relationships in the Arctic (r = 0.88) and Antarctic (r = 0.86). We find a substantially greater (stronger) linear relationship between sea ice concentration and surface air temperature than with temperature at 850 hPa, lending credence to the idea that sea ice controls inversion strength through modulation of surface heat fluxes. As such, declines in sea ice in either hemisphere may imply weaker mean inversions in the future. Comparison of mean inversion strength in AIRS and global climate models (GCMs) suggests that many GCMs poorly characterize mean inversion strength at high latitudes.
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.

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