Jon Holmgren

Bio: Jon Holmgren is an academic researcher from Cold Regions Research and Engineering Laboratory. The author has contributed to research in topics: Snow & Sea ice. The author has an hindex of 15, co-authored 18 publications receiving 2578 citations. Previous affiliations of Jon Holmgren include United States Department of the Army.

A Seasonal Snow Cover Classification System for Local to Global Applications

Abstract: 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...

Snow-Shrub Interactions in Arctic Tundra: A Hypothesis with Climatic Implications

Abstract: 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 CO 2 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.

The thermal conductivity of seasonal snow

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 equations 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, k eff = 0.138 - 1.01ρ + 3.233ρ 2 {0.156 ≤ ρ ≤ 0.6} k eff = 0.023 + 0.234ρ {ρ < 0.156}, 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, k eff = 10 (2.650ρ-1.652) {ρ ≤ 0.6}, 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.

Thermal conductivity and heat transfer through the snow on the ice of the Beaufort Sea

Abstract: [1] Eighty-nine point measurements of the thermal conductivity (ks) of the snow on the sea ice of the Beaufort Sea were made using a heated needle probe. Average values ranged from 0.078 W m−1 K−1 for new snow to 0.290 W m−1 K−1 for an ubiquitous wind slab. ks increased with increasing density, consistent with published equations, but could also be reliably estimated from the metamorphic state of the snow. Using measured values of ks and snow stratigraphy, the average bulk value for the full snowpack was 0.14 W m−1 K−1. In contrast, ks inferred from ice growth and temperature gradients in the snow was 0.33 W m−1 K−1. The mismatch arises in part because the second estimate is based on measurements from an aggregate scale that includes enhanced heat flow due to two- and three-dimensional snow and ice geometry. A finite element model suggests that the complex geometry produces areas of concentrated heat loss at the snow surface. These “hot spots,” however, increase the apparent conductivity only by a factor of 1.4, not enough to fully explain the mismatch. Nonconductive heat transfer mechanisms, like natural and forced air convection, may also be operating in the snowpack, though the ubiquitous presence of low permeability wind slabs potentially limits their effectiveness. The relative contributions of effects due to snow and ice geometric and nonconductive processes within the snowpack remain uncertain.

Winter snow cover on the sea ice of the Arctic Ocean at the Surface Heat Budget of the Arctic Ocean (SHEBA): Temporal evolution and spatial variability

Abstract: [1] The evolution and spatial distribution of the snow cover on the sea ice of the Arctic Ocean was observed during the Surface Heat Budget of the Arctic Ocean (SHEBA) project. The snow cover built up in October and November, reached near maximum depth by mid-December, then remained relatively unchanged until snowmelt. Ten layers were deposited, the result of a similar number of weather events. Two basic types of snow were present: depth hoar and wind slab. The depth hoar, 37% of the pack, was produced by the extreme temperature gradients imposed on the snow. The wind slabs, 42% of the snowpack, were the result of two storms in which there was simultaneous snow and high winds (>10 m s−1). The slabs impacted virtually all bulk snow properties emphasizing the importance of episodic events in snowpack development. The mean snow depth (n = 21,169) was 33.7 cm with a bulk density of 0.34 g cm−3 (n = 357, r2 of 0.987), giving an average snow water equivalent of 11.6 cm, 25% higher than the amount record by precipitation gauge. Both depth and stratigraphy varied significantly with ice type, the greatest depth, and the greatest variability in depth occurring on deformed ice (ridges and rubble fields). Across all ice types a persistent structural length in depth variations of ∼20 m was found. This appears to be the result of drift features at the snow surface interacting with small-scale ice surface structures. A number of simple ways of representing the complex temporal and spatial variations of the snow cover in ice-ocean-atmosphere models are suggested.

Climate change. Increasing shrub abundance in the Arctic.

Abstract: The warming of the Alaskan Arctic during the past 150 years has accelerated over the last three decades and is expected to increase vegetation productivity in tundra if shrubs become more abundant; indeed, this transition may already be under way according to local plot studies and remote sensing. Here we present evidence for a widespread increase in shrub abundance over more than 320 km of Arctic landscape during the past 50 years, based on a comparison of historic and modern aerial photographs. This expansion will alter the partitioning of energy in summer and the trapping and distribution of snow in winter, as well as increasing the amount of carbon stored in a region that is believed to be a net source of carbon dioxide.

Evidence and implications of recent climate change in northern Alaska and other arctic regions.

Abstract: The Arctic climate is changing. Permafrost is warming, hydrological processes are chang- ing and biological and social systems are also evolving in response to these changing conditions. Knowing how the structure and function of arctic terrestrial ecosystems are responding to recent and persistent climate change is paramount to understanding the future state of the Earth system and how humans will need to adapt. Our holistic review presents a broad array of evidence that illustrates con- vincingly; the Arctic is undergoing a system-wide response to an altered climatic state. New extreme and seasonal surface climatic conditions are being experienced, a range of biophysical states and pro- cesses influenced by the threshold and phase change of freezing point are being altered, hydrological and biogeochemical cycles are shifting, and more regularly human sub-systems are being affected. Importantly, the patterns, magnitude and mechanisms of change have sometimes been unpredictable or difficult to isolate due to compounding factors. In almost every discipline represented, we show

Role of Land-Surface Changes in Arctic Summer Warming

Abstract: 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.

Plant community responses to experimental warming across the tundra biome

Abstract: Recent observations of changes in some tundra ecosystems appear to be responses to a warming climate. Several experimental studies have shown that tundra plants and ecosystems can respond strongly to environmental change, including warming; however, most studies were limited to a single location and were of short duration and based on a variety of experimental designs. In addition, comparisons among studies are difficult because a variety of techniques have been used to achieve experimental warming and different measurements have been used to assess responses. We used metaanalysis on plant community measurements from standardized warming experiments at 11 locations across the tundra biome involved in the International Tundra Experiment. The passive warming treatment increased plant-level air temperature by 1-3°C, which is in the range of predicted and observed warming for tundra regions. Responses were rapid and detected in whole plant communities after only two growing seasons. Overall, warming increased height and cover of deciduous shrubs and graminoids, decreased cover of mosses and lichens, and decreased species diversity and evenness. These results predict that warming will cause a decline in biodiversity across a wide variety of tundra, at least in the short term. They also provide rigorous experimental evidence that recently observed increases in shrub cover in many tundra regions are in response to climate warming. These changes have important implications for processes and interactions within tundra ecosystems and between tundra and the atmosphere.