Cold Regions Research and Engineering Laboratory

A major challenge in predicting Earth's future climate state is to understand feedbacks that alter greenhouse-gas forcing. Here we synthesize field data from arctic Alaska, showing that terrestrial changes in summer albedo contribute substantially to recent high-latitude warming trends. Pronounced terrestrial summer warming in arctic Alaska correlates with a lengthening of the snow-free season that has increased atmospheric heating locally by about 3 watts per square meter per decade (similar in magnitude to the regional heating expected over multiple decades from a doubling of atmospheric CO2). The continuation of current trends in shrub and tree expansion could further amplify this atmospheric heating by two to seven times.

Abstract One expected response to climate warming in the Arctic is an increase in the abundance and extent of shrubs in tundra areas. Repeat photography shows that there has been an increase in shrub cover over the past 50 years in northern Alaska. Using 202 pairs of old and new oblique aerial photographs, we have found that across this region spanning 620 km east to west and 350 km north to south, alder, willow, and dwarf birch have been increasing, with the change most easily detected on hill slopes and valley bottoms. Plot and remote sensing studies from the same region using the normalized difference vegetation index are consistent with the photographic results and indicate that the smaller shrubs between valleys are also increasing. In Canada, Scandinavia, and parts of Russia, there is both plot and remote sensing evidence for shrub expansion. Combined with the Alaskan results, the evidence suggests that a pan‐Arctic vegetation transition is underway. If continued, this transition will alter the fundamental architecture and function of this ecosystem with important ramifications for the climate, the biota, and humans.

Abstract Since its initial release in 2000, the Weather Research and Forecasting (WRF) Model has become one of the world’s most widely used numerical weather prediction models. Designed to serve both research and operational needs, it has grown to offer a spectrum of options and capabilities for a wide range of applications. In addition, it underlies a number of tailored systems that address Earth system modeling beyond weather. While the WRF Model has a centralized support effort, it has become a truly community model, driven by the developments and contributions of an active worldwide user base. The WRF Model sees significant use for operational forecasting, and its research implementations are pushing the boundaries of finescale atmospheric simulation. Future model directions include developments in physics, exploiting emerging compute technologies, and ever-innovative applications. From its contributions to research, forecasting, educational, and commercial efforts worldwide, the WRF Model has made a significant mark on numerical weather prediction and atmospheric science.

The Stardust spacecraft collected thousands of particles from comet 81P/Wild 2 and returned them to Earth for laboratory study. The preliminary examination of these samples shows that the nonvolatile portion of the comet is an unequilibrated assortment of materials that have both presolar and solar system origin. The comet contains an abundance of silicate grains that are much larger than predictions of interstellar grain models, and many of these are high-temperature minerals that appear to have formed in the inner regions of the solar nebula. Their presence in a comet proves that the formation of the solar system included mixing on the grandest scales.

Glaciochemical time series developed from Summit, Greenland, indicate that the chemical composition of the atmosphere was dynamic during the Holocene epoch. Concentrations of sea salt and terrestrial dusts increased in Summit snow during the periods 0 to 600, 2400 to 3100, 5000 to 6100, 7800 to 8800, and more than 11,300 years ago. The most recent increase, and also the most abrupt, coincides with the Little Ice Age. These changes imply that either the north polar vortex expanded or the meridional air flow intensified during these periods, and that temperatures in the mid to high northern latitudes were potentially the coldest since the Younger Dryas event.

reference on thermal radiation heat transfer, this is the book of choice.The book contains too much material for a onesemester graduate course but the authors have been kind enough to place asterisks by those sections which they suggest

The present paper contains a critical study of a number of foundation models as well as a further development of some of the ideas involved. Among others it is shown that the Pasternak foundation is a mechanical model for the so-called “generalized” foundation. It is also demonstrated that the kernel for the Pasternak foundation in plane stress or plane strain is identical with Wieghardt’s exponential kernel, and that for the three-dimensional case the kernel is a modified Bessel function. It is also shown that the “non solvability” of the problem of a finite beam or plate resting on a continuous foundation as posed by Wieghardt and further elaborated by Pflanz is not correct, and that problems of this type are solvable for any load distribution permissible in classical plate theory. Throughout the paper, emphasis is placed on the proper mathematical formulation of the physical problems in question.

The International Tundra Experiment (ITEX) is a collaborative, multisite experiment using a common temperature manipulation to examine variability in species response across climatic and geographic gradients of tundra ecosystems. ITEX was designed specifically to examine variability in arctic and alpine species response to increased temperature. We compiled from one to four years of experimental data from 13 different ITEX sites and used meta-analysis to analyze responses of plant phenology, growth, and reproduction to experimental warming. Results indicate that key phenological events such as leaf bud burst and flowering occurred earlier in warmed plots throughout the study period; however, there was little impact on growth cessation at the end of the season. Quantitative measures of vegetative growth were greatest in warmed plots in the early years of the experiment, whereas reproductive effort and success increased in later years. A shift away from vegetative growth and toward reproductive effort and success in the fourth treatment year suggests a shift from the initial response to a secondary response. The change in vegetative response may be due to depletion of stored plant reserves, whereas the lag in reproductive response may be due to the formation of flower buds one to several seasons prior to flowering. Both vegetative and reproductive responses varied among life-forms; herbaceous forms had stronger and more consistent vegetative growth responses than did woody forms. The greater responsiveness of the herbaceous forms may be attributed to their more flexible morphology and to their relatively greater proportion of stored plant reserves. Finally, warmer, low arctic sites produced the strongest growth responses, but colder sites produced a greater reproductive response. Greater resource investment in vegetative growth may be a conservative strategy in the Low Arctic, where there is more competition for light, nutrients, or water, and there may be little opportunity for successful germination or seedling development. In contrast, in the High Arctic, heavy investment in producing seed under a higher temperature scenario may provide an opportunity for species to colonize patches of unvegetated ground. The observed differential response to warming suggests that the primary forces driving the response vary across climatic zones, functional groups, and through time.

Phytoplankton blooms over Arctic Ocean continental shelves are thought to be restricted to waters free of sea ice. Here, we document a massive phytoplankton bloom beneath fully consolidated pack ice far from the ice edge in the Chukchi Sea, where light transmission has increased in recent decades because of thinning ice cover and proliferation of melt ponds. The bloom was characterized by high diatom biomass and rates of growth and primary production. Evidence suggests that under-ice phytoplankton blooms may be more widespread over nutrient-rich Arctic continental shelves and that satellite-based estimates of annual primary production in these waters may be underestimated by up to 10-fold.

Passive open‐top devices have been proposed as a method to experimentally increase temperature in high‐latitude ecosystems. There is, however, little documentation on the efficacy of these devices. This paper examines the performance of four open‐top chambers for altering temperature at six sites in the Arctic and Antarctica. Most of the heating effect was due to daytime warming above ambient; occasional night‐time cooling below ambient, especially of air temperatures, depressed mean daily temperature. The mean daily temperatures at four arctic sites were generally increased by 1.2–1.8 °C; but occasionally, temperature depressions also occurred. Under optimal conditions at the antarctic site (dry soils, no vegetation, high radiation) mean daily soil temperatures were increased by +2.2 °C (–10 cm) to +5.2 °C (0 cm). Protection from wind may play a more important role than temperature per se in providing a favourable environment for plant growth within open‐top devices. Wind speed had a generally negative impact on mean daily temperature. Daily global radiation was both positively and negatively related to chamber temperature response. The effect of chambers on snow accumulation was variable with the Alexandra Fjord site showing an increased accumulation in chambers but no difference in the date of snowmelt, while at Latnjajaure in a deep snowfall site, snowmelt occurred 1–2 weeks earlier in chambers, potentially increasing the growing season. Selection of a passive temperature‐enhancing system requires balancing the temperature enhancement desired against potential unwanted ecological effects such as chamber overheating and altered light, moisture, and wind. In general, the more closed the temperature‐enhancing system, the higher is the temperature enhancement, but the larger are the unwanted ecological effects. Open‐top chambers alter temperature significantly and minimize most unwanted ecological effects; as a consequence, these chambers are a useful tool for studying the response of high‐latitude ecosystems to warming.

A new classification system for seasonal snow covers is proposed. It has six classes (tundra, taiga, alpine, maritime, prairie, and ephemeral, each class defined by a unique ensemble of textural and stratigraphic characteristics including the sequence of snow layers, their thickness, density, and the crystal morphology and grain characteristics within each layer. The classes can also be derived using a binary system of three climate variables: wind, precipitation, and air temperature. Using this classification system, the Northern Hemisphere distribution of the snow cover classes is mapped on a 0.5° lat × 0.5° long grid. These maps are compared to maps prepared from snow cover data collected in the former Soviet Union and Alaska. For these areas where both climatologically based and texturally based snow cover maps are available, there is 62% and 90% agreement, respectively. Five of the six snow classes are found in Alaska. From 1989 through 1992, hourly measurements, consisting of 40 thermal and physical parameters, including snow depth, the temperature distribution in the snow, and basal heat flow, were made on four of these classes. In addition, snow stratigraphy and texture were measured every six weeks. Factor analysis indicates that the snow classes can be readily discriminated using four or more winter average thermal or physical parameters. Further, analysis of hourly time series indicates that 84% of the time, spot measurements of the parameters are sufficient to correctly differentiate the snow cover class. Using the new snow classification system, 1) classes can readily be distinguished using observations of simple thermal parameters, 2) physical and thermal attributes of the snow can be inferred, and 3) classes can be mapped from climate data for use in regional and global climate modeling.

Abstract : This monograph describes the thermal properties of soils, unfrozen or frozen. The effects on these properties of water and its phase changes are detailed. An explanation is given of the interaction between moisture and heat transfer. Other influences on soil thermal properties are described, including such factors as soil composition, structure, additives, salts, organics, hysteresis and temperature. Techniques for testing soil thermal conductivity are outlined and the methods for calculating this property are described. The monograph gives the results of an evaluation of these methods whereby their predictions were compared with measured values, thus showing their applicability to various soil types and conditions.

An analysis is made of the steady-state size of a two-dimensional ice sheet whose base is below sea-level and which terminates in floating ice shelves. Under the assumption of perfect plasticity it is found that an ice sheet placed on a bed whose surface was initially flat cannot exist if the depth of the bed below sea-level exceeds a critical depth. If this depth is less than the critical level, the ice sheet extends out to the edge of the continental shelf. Similar results are found with more realistic assumptions about the laws governing the flow of ice. If the bed slopes away from the centre, the ice sheet can have a stable width that increases in value as the accumulation rate increases or as sea-level is lowered. It is not possible to decide whether or not the West Antarctic ice sheet is in stable equilibrium. It is entirely possible that this ice sheet is disintegrating at present, as suggested by Hughes.

Sea ice in the Arctic is one of the most rapidly changing components of the global climate system. Over the past few decades, summer areal extent has declined over 30%, and all months show statistically significant declining trends. New satellite missions and techniques have greatly expanded information on sea ice thickness, but many uncertainties remain in the satellite data and long-term records are sparse. However, thickness observations and other satellite-derived data indicate a 40% decline in thickness, due in large part to the loss of thicker, older ice cover. The changes in sea ice are happening faster than models have projected. With continued increasing temperatures, summer ice-free conditions are likely sometime in the coming decades, though there are substantial uncertainties in the exact timing and high interannual variability will remain as sea ice decreases. The changes in Arctic sea ice are already having an impact on flora and fauna in the Arctic. Some species will face increasing challenges in the future, while new habitat will open up for other species. The changes are also affecting people living and working in the Arctic. Native communities are facing challenges to their traditional ways of life, while new opportunities open for shipping, fishing, and natural resource extraction. Significant progress has been made in recent years in understanding of Arctic sea ice and its role in climate, the ecosystem, and human activities. However, significant challenges remain in furthering the knowledge of the processes, impacts, and future evolution of the system.

In the Arctic, where wind transport of snow is common, the depth and insulative properties of the snow cover can be determined as much by the wind as by spatial variations in precipitation. Where shrubs are more abundant and larger, greater amounts of drifting snow are trapped and suffer less loss due to sublimation. The snow in shrub patches is both thicker and a better thermal insulator per unit thickness than the snow outside of shrub patches. As a consequence, winter soil surface temperatures are substantially higher, a condition that can promote greater winter decomposition and nutrient release, thereby providing a positive feedback that could enhance shrub growth. If the abundance, size, and coverage of arctic shrubs increases in response to climate warming, as is expected, snow–shrub interactions could cause a widespread increase (estimated 10%–25%) in the winter snow depth. This would increase spring runoff, winter soil temperatures, and probably winter CO2 emissions. The balance between these winter effects and changes in the summer energy balance associated with the increase in shrubs probably depends on shrub density, with the threshold for winter snow trapping occurring at lower densities than the threshold for summer effects such as shading. It is suggested that snow–shrub interactions warrant further investigation as a possible factor contributing to the transition of the arctic land surface from moist graminoid tundra to shrub tundra in response to climatic warming.

Abstract Laser altimetry (lidar) is a remote-sensing technology that holds tremendous promise for mapping snow depth in snow hydrology and avalanche applications. Recently lidar has seen a dramatic widening of applications in the natural sciences, resulting in technological improvements and an increase in the availability of both airborne and ground-based sensors. Modern sensors allow mapping of vegetation heights and snow or ground surface elevations below forest canopies. Typical vertical accuracies for airborne datasets are decimeter-scale with order 1 m point spacings. Ground-based systems typically provide millimeter-scale range accuracy and sub-meter point spacing over 1 m to several kilometers. Many system parameters, such as scan angle, pulse rate and shot geometry relative to terrain gradients, require specification to achieve specific point coverage densities in forested and/or complex terrain. Additionally, snow has a significant volumetric scattering component, requiring different considerations for error estimation than for other Earth surface materials. We use published estimates of light penetration depth by wavelength to estimate radiative transfer error contributions. This paper presents a review of lidar mapping procedures and error sources, potential errors unique to snow surface remote sensing in the near-infrared and visible wavelengths, and recommendations for projects using lidar for snow-depth mapping.

As part of ice albedo feedback studies during the Surface Heat Budget of the Arctic Ocean (SHEBA) field experiment, we measured spectral and wavelength‐integrated albedo on multiyear sea ice. Measurements were made every 2.5 m along a 200‐m survey line from April through October. Initially, this line was completely snow covered, but as the melt season progressed, it became a mixture of bare ice and melt ponds. Observed changes in albedo were a combination of a gradual evolution due to seasonal transitions and abrupt shifts resulting from synoptic weather events. There were five distinct phases in the evolution of albedo: dry snow, melting snow, pond formation, pond evolution, and fall freeze‐up. In April the surface albedo was high (0.8–0.9) and spatially uniform. By the end of July the average albedo along the line was 0.4, and there was significant spatial variability, with values ranging from 0.1 for deep, dark ponds to 0.65 for bare, white ice. There was good agreement between surface‐based albedos and measurements made from the University of Washington's Convair‐580 research aircraft. A comparison between net solar irradiance computed using observed albedos and a simplified model of seasonal evolution shows good agreement as long as the timing of the transitions is accurately determined.

Abstract In many practical applications snow depth is known, but snow water equivalent (SWE) is needed as well. Measuring SWE takes ∼20 times as long as measuring depth, which in part is why depth measurements outnumber SWE measurements worldwide. Here a method of estimating snow bulk density is presented and then used to convert snow depth to SWE. The method is grounded in the fact that depth varies over a range that is many times greater than that of bulk density. Consequently, estimates derived from measured depths and modeled densities generally fall close to measured values of SWE. Knowledge of snow climate classes is used to improve the accuracy of the estimation procedure. A statistical model based on a Bayesian analysis of a set of 25 688 depth–density–SWE data collected in the United States, Canada, and Switzerland takes snow depth, day of the year, and the climate class of snow at a selected location from which it produces a local bulk density estimate. When converted to SWE and tested against two continental-scale datasets, 90% of the computed SWE values fell within ±8 cm of the measured values, with most estimates falling much closer.

Abstract Equations are developed that can be used to determine the amount of gas present in sea ice from measurements of the bulk ice density, salinity, and temperature in the temperature range of −2 to −30 °C. Conversely these relationships can be used to give the density of sea ice as a function of its temperature and salinity, considering both the presence of gas and of solid salts in the ice. Equations are also given that allow the calculation of the gas and brine volumes in the ice at temperatures other than that at which the bulk density was determined.

Abstract Twenty-seven studies on the thermal conductivity of snow ( K eff ) have been published since 1886. Combined, they comprise 354 values of K eff , and have been used to derive over 13 regression equation and predicting K eff vs density. Due to large (and largely undocumented) differences in measurement methods and accuracy, sample temperature and snow type, it is not possible to know what part of the variability in this data set is the result of snow microstructure. We present a new data set containing 488 measurements for which the temperature, type and measurement accuracy are known. A quadratic equation, where ρ is in g cm −3 , and K eff is in W m −1 K −1 , can be fit to the new data ( R 2 = 0.79). A logarithmic expression, can also be used. The first regression is better when estimating values beyond the limits of the data; the second when estimating values for low-density snow. Within the data set, snow types resulting from kinetic growth show density-independent behavior. Rounded-grain and wind-blown snow show strong density dependence. The new data set has a higher mean value of density but a lower mean value of thermal conductivity than the old set. This shift is attributed to differences in snow types and sample temperatures in the sets. Using both data sets, we show that there are well-defined limits to the geometric configurations that natural seasonal snow can take.