Meltwater sources and sinks for multiyear Arctic sea ice in summer

On Arctic sea ice, the melt of snow and sea ice generate a summertime flux of fresh water to the upper ocean. The partitioning of this meltwater to storage in melt ponds and deposition in the ocean has consequences for the surface heat budget, the sea ice mass balance, and primary productivity. Synthesizing results from the 1997-1998 SHEBA field experiment, we calculate the sources and sinks of meltwater produced on a multiyear floe during summer melt. The total meltwater input to the system from snowmelt, ice melt, and precipitation from 1 June to 9 August was equivalent to a layer of water 80ĝ€¯cm thick over the ice-covered and open ocean. A total of 85ĝ€¯% of this meltwater was deposited in the ocean, and only 15ĝ€¯% of this meltwater was stored in ponds. The cumulative contributions of meltwater input to the ocean from drainage from the ice surface and bottom melting were roughly equal

Contrasting Sea-Ice Algae Blooms in a Changing Arctic Documented by Autonomous Drifting Buoys

Novel observations of the seasonal evolution of an ice algal bloom on the Chukchi shelf were collected by two autonomous buoys deployed 180 km apart in first-year drifting sea ice. High attenuation of blue light in the bottom of the ice indicated considerable accumulation of ice algae biomass with derived Chlorophyll-a concentrations (Chl a) up to 184 mg m−2. Differences in the magnitude and persistence of ice algae biomass under each buoy appear to have been driven by differences in snow thickness, as ice thickness was similar between the sites. Minimal snow cover (0.02 m) around one buoy was associated with algae growth beginning in mid-May and lasting 70 days. The second buoy had notably more snow (0.4 m), causing ice algae production to lag behind the first site by approximately 4 weeks. The delay in growth diminished the peak of ice algae Chl a and duration compared to the first site. Light attenuation through the ice was intense enough at both buoys to have a potentially inhibiting impact on water column phytoplankton Chl a. Modeling ice algae growth with observed light intensities determined that nutrients were the limiting resource at the low snow site. In contrast, the algae at the high snow site were light-limited and never nutrient-limited. These data point toward changes in ice algae phenology with an earlier and longer window for growth; and nutrients rather than light determining the longevity and magnitude of production

Light Availability and Phytoplankton Growth Beneath Arctic Sea Ice: Integrating Observations and Modeling

Observations of the seasonal light field in the upper Arctic Ocean are critical to understanding the impacts of changing Arctic ice conditions on phytoplankton growth in the water column. Here we discuss data from a new sensor system, deployed in seasonal ice cover north‐east of Utqiaġvik, Alaska in March 2014. The system was designed to provide observations of light and phytoplankton biomass in the water column during the formation of surface melt ponds and the transition from ice to open water. Hourly observations of downwelling irradiance beneath the ice (at 2.9, 6.9, and 17.9 m depths) and phytoplankton biomass (at 2.9 m depth) were transmitted via Iridium satellite from 9 March to 10 November 2014. Evidence of an under‐ice phytoplankton bloom (Chl a ∼8 mg m−3) was seen in June and July. Increases in light intensity observed by the buoy likely resulted from the loss of snow cover and development of surface melt ponds. A bio‐optical model of phytoplankton production supported this probable trigger for the rapid onset of under‐ice phytoplankton growth. Once under‐ice light was no longer a limiting factor for photosynthesis, open water exposure almost marginally increased daily phytoplankton production compared to populations that remained under the adjacent ice. As strong effects of climate change continue to be documented in the Arctic, the insight derived from autonomous buoys will play an increasing role in understanding the dynamics of primary productivity where ice and cloud cover limit the utility of ocean color satellite observations

Arctic sea-ice melt in 2008 and the role of solar heating

There has been a marked decline in the summer extent of Arctic sea ice over the past few decades. Data from autonomous ice mass-balance buoys can enhance our understanding of this decline. These buoys monitor changes in snow deposition and ablation, ice growth, and ice surface and bottom melt. Results from the summer of 2008 showed considerable large-scale spatial variability in the amount of surface and bottom melt. Small amounts of melting were observed north of Greenland, while melting in the southern Beaufort Sea was quite large. Comparison of net solar heat input to the ice and heat required for surface ablation showed only modest correlation. However, there was a strong correlation between solar heat input to the ocean and bottom melting. As the ice concentration in the Beaufort Sea region decreased, there was an increase in solar heat to the ocean and an increase in bottom melting

The influence of snow on sea ice as assessed from simulations of CESM2

We assess the influence of snow on sea ice in experiments using the Community Earth System Model version 2 for a preindustrial and a 2xCO2 climate state. In the preindustrial climate, we find that increasing simulated snow accumulation on sea ice results in thicker sea ice and a cooler climate in both hemispheres. The sea ice mass budget response differs fundamentally between the two hemispheres. In the Arctic, increasing snow results in a decrease in both congelation sea ice growth and surface sea ice melt due to the snow\u27s impact on conductive heat transfer and albedo, respectively. These factors dominate in regions of perennial ice but have a smaller influence in seasonal ice areas. Overall, the mass budget changes lead to a reduced amplitude in the annual cycle of ice thickness. In the Antarctic, with increasing snow, ice growth increases due to snow-ice formation and is balanced by larger basal ice melt, which primarily occurs in regions of seasonal ice. In a warmer 2xCO2 climate, the Arctic sea ice sensitivity to snow depth is small and reduced relative to that of the preindustrial climate. In contrast, in the Antarctic, the sensitivity to snow on sea ice in the 2xCO2 climate is qualitatively similar to the sensitivity in the preindustrial climate. These results underscore the importance of accurately representing snow accumulation on sea ice in coupled Earth system models due to its impact on a number of competing processes and feedbacks that affect the melt and growth of sea ice

Melt pond conditions on declining arctic sea ice over 1979-2016: Model development, validation, and results

Author Posting. © American Geophysical Union, 2018. This article is posted here by permission of American Geophysical Union for personal use, not for redistribution. The definitive version was published in Journal of Geophysical Research-Oceans, 123(11), (2018): 7983-8003. doi:10.1029/2018JC014298.A melt pond (MP) distribution equation has been developed and incorporated into the Marginal Ice‐Zone Modeling and Assimilation System to simulate Arctic MPs and sea ice over 1979–2016. The equation differs from previous MP models and yet benefits from previous studies for MP parameterizations as well as a range of observations for model calibration. Model results show higher magnitude of MP volume per unit ice area and area fraction in most of the Canada Basin and the East Siberian Sea and lower magnitude in the central Arctic. This is consistent with Moderate Resolution Imaging Spectroradiometer observations, evaluated with Measurements of Earth Data for Environmental Analysis (MEDEA) data, and closely related to top ice melt per unit ice area. The model simulates a decrease in the total Arctic sea ice volume and area, owing to a strong increase in bottom and lateral ice melt. The sea ice decline leads to a strong decrease in the total MP volume and area. However, the Arctic‐averaged MP volume per unit ice area and area fraction show weak, statistically insignificant downward trends, which is linked to the fact that MP water drainage per unit ice area is increasing. It is also linked to the fact that MP volume and area decrease relatively faster than ice area. This suggests that overall the actual MP conditions on ice have changed little in the past decades as the ice cover is retreating in response to Arctic warming, thus consistent with the Moderate Resolution Imaging Spectroradiometer observations that show no clear trend in MP area fraction over 2000–2011.We gratefully acknowledge the support of the NASA Cryosphere Program (grants NNX15AG68G, NNX17AD27G, and NNX14AH61G), the Office of Naval Research (N00014‐12‐1‐0112), the NSF Office of Polar Programs (PLR‐1416920, PLR‐1603259, PLR‐1602521, and ARC‐1203425), and the Department of Homeland Security (DHS, 2014‐ST‐061‐ML‐0002). The DHS grant is coordinated through the Arctic Domain Awareness Center (ADAC), a DHS Center of Excellence, which conducts maritime research and development for the Arctic region. The views and conclusions in this document are those of the authors and should not be interpreted as representing the official policies, either expressed or implied, of the DHS. MODIS‐derived MP area data are available at https://icdc.cen.uni‐hamburg.de/1/daten/cryosphere/arctic‐meltponds.html. MP area fraction statistics derived from MEDEA images are available from http://psc.apl.uw.edu/melt‐pond‐data/. Sea ice thickness and snow observations are available at http://psc.apl.washington.edu/sea_ice_cdr. CFS forcing data used to drive MIZMAS are available at https://www.ncdc.noaa.gov/data‐access/model‐data/model‐datasets/climate‐forecast‐system‐version2‐cfsv2.2019-04-1

Snow microstructure on sea ice: Importance for remote sensing applications

European Geosciences Union (EGU) General Assembly, 19-30 Apr 2021.-- 2 pagesSnow plays a key role in interpreting satellite remote sensing data from both active and passive sensors in the high Arctic and therefore impacts retrieved sea ice variables from these systems ( e.g., sea ice extent, thickness and age). Because there is high spatial and temporal variability in snow properties, this porous layer adds uncertainty to the interpretation of signals from spaceborne optical sensors, microwave radiometers, and radars (scatterometers, SAR, altimeters). We therefore need to improve our understanding of physical snow properties, including the snow specific surface area, snow wetness and the stratigraphy of the snowpack on different ages of sea ice in the high Arctic. The MOSAiC expedition provided a unique opportunity to deploy equivalent remote sensing sensors in-situ on the sea ice similar to those mounted on satellite platforms. To aid in the interpretation of the in situ remote sensing data collected, we used a micro computed tomography (micro-CT) device. This instrument was installed on board the Polarstern and was used to evaluate geometric and physical snow properties of in-situ snow samples. This allowed us to relate the snow samples directly to the data from the remote sensing instruments, with the goal of improving interpretation of satellite retrievals. Our data covers the full annual evolution of the snow cover properties on multiple ice types and ice topographies including level first-year (FYI), level multi-year ice (MYI) and ridges. First analysis of the data reveals possible uncertainties in the retrieved remote sensing data products related to previously unknown seasonal processes in the snowpack. For example, the refrozen porous summer ice surface, known as surface scattering layer, caused the formation of a hard layer at the multiyear ice/snow interface in the winter months, leading to significant differences in the snow stratigraphy and remote sensing signals from first-year ice, which has not experienced summer melt, and multiyear ice. Furthermore, liquid water dominates the extreme coarsening of snow grains in the summer months and in winter the temporally large temperature gradients caused strong metamorphism, leading to brine inclusions in the snowpack and large depth hoar structures, all this significantly influences the signal response of remote sensing instrumentsPeer reviewe

The magnitude of the snow-sourced reactive nitrogen flux to the boundary layer in the Uintah Basin

Reactive nitrogen (Nr = NO, NO2, HONO) and volatile organic carbon emissions from oil and gas extraction activities play a major role in wintertime ground-level ozone exceedance events of up to 140 ppb in the Uintah Basin in eastern Utah. Such events occur only when the ground is snow covered, due to the impacts of snow on the stability and depth of the boundary layer and ultraviolet actinic flux at the surface. Recycling of reactive nitrogen from the photolysis of snow nitrate has been observed in polar and midlatitude snow, but snow-sourced reactive nitrogen fluxes in mid-latitude regions have not yet been quantified in the field. Here we present vertical profiles of snow nitrate concentration and nitrogen isotopes (δ15N) collected during the Uintah Basin Winter Ozone Study 2014 (UBWOS 2014), along with observations of insoluble light-absorbing impurities, radiation equivalent mean ice grain radii, and snow density that determine snow optical properties. We use the snow optical properties and nitrate concentrations to calculate ultraviolet actinic flux in snow and the production of Nr from the photolysis of snow nitrate. The observed δ15N(NO−3) is used to constrain modeled fractional loss of snow nitrate in a snow chemistry column model, and thus the source of Nr to the overlying boundary layer. Snow-surface δ15N(NO−3) measurements range from −5 to 10 ‰ and suggest that the local nitrate burden in the Uintah Basin is dominated by primary emissions from anthropogenic sources, except during fresh snowfall events, where remote NOx sources from beyond the basin are dominant. Modeled daily averaged snow-sourced Nr fluxes range from 5.6 to 71 × 107 molec cm−2s−1 over the course of the field campaign, with a maximum noontime value of 3.1 × 109 molec cm−2s−1. The top-down emission estimate of primary, anthropogenic NOx in Uintah and Duchesne counties is at least 300 times higher than the estimated snow NOx emissions presented in this study. Our results suggest that snow-sourced reactive nitrogen fluxes are minor contributors to the Nr boundary layer budget in the highly polluted Uintah Basin boundary layer during winter 2014

Faculty roles and role preferences in ten fields of professional study

Teaching faculty in ten entry-level professional fields reported varying amounts of time devoted to teaching, research, consulting, and professional practice but did not differ in time devoted to administration. The faculty member's own role view was most closely related to time use, but for time spent in teaching and research, faculty age and institutional type (but not gender) were also significant predictors. Even after several general demographic characteristics and environmental variables that potentially differentiate professional from discipline-based faculty are taken into account, different professional fields may be characterized by group climates which influence or reinforce certain faculty roles.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/43598/1/11162_2004_Article_BF00991875.pd