Dominance of grain size impacts on seasonal snow albedo at deforested sites in New Hampshire

Snow cover serves as a major control on the surface energy budget in temperate regions due to its high reflectivity compared to underlying surfaces. Winter in the northeastern United States has changed over the last several decades, resulting in shallower snowpacks, fewer days of snow cover, and increasing precipitation falling as rain in the winter. As these climatic changes occur, it is imperative that we understand current controls on the evolution of seasonal snow albedo in the region. Over three winter seasons between 2013 and 2015, snow characterization measurements were made at three open sites across New Hampshire. These near-daily measurements include spectral albedo, snow optical grain size determined through contact spectroscopy, snow depth, snow density, black carbon content, local meteorological parameters, and analysis of storm trajectories using the Hybrid Single-Particle Lagrangian Integrated Trajectory model. Using analysis of variance, we determine that land-based winter storms result in marginally higher albedo than coastal storms or storms from the Atlantic Ocean. Through multiple regression analysis, we determine that snow grain size is significantly more important in albedo reduction than black carbon content or snow density. And finally, we present a parameterization of albedo based on days since snowfall and temperature that accounts for 52% of variance in albedo over all three sites and years. Our improved understanding of current controls on snow albedo in the region will allow for better assessment of potential response of seasonal snow albedo and snow cover to changing climate

A longer vernal window: The role of winter coldness and snowpack in driving spring thresholds and lags

Climate change is altering the timing and duration of the vernal window, a period that marks the end of winter and the start of the growing season when rapid transitions in ecosystem energy, water, nutrient, and carbon dynamics take place. Research on this period typically captures only a portion of the ecosystem in transition and focuses largely on the dates by which the system wakes up. Previous work has not addressed lags between transitions that represent delays in energy, water, nutrient, and carbon flows. The objectives of this study were to establish the sequence of physical and biogeochemical transitions and lags during the vernal window period and to understand how climate change may alter them. We synthesized observations from a statewide sensor network in New Hampshire, USA, that concurrently monitored climate, snow, soils, and streams over a three-year period and supplemented these observations with climate reanalysis data, snow data assimilation model output, and satellite spectral data. We found that some of the transitions that occurred within the vernal window were sequential, with air temperatures warming prior to snow melt, which preceded forest canopy closure. Other transitions were simultaneous with one another and had zero-length lags, such as snowpack disappearance, rapid soil warming, and peak stream discharge. We modeled lags as a function of both winter coldness and snow depth, both of which are expected to decline with climate change. Warmer winters with less snow resulted in longer lags and a more protracted vernal window. This lengthening of individual lags and of the entire vernal window carries important consequences for the thermodynamics and biogeochemistry of ecosystems, both during the winter-to-spring transition and throughout the rest of the year

Analyzing Near Surface Temperature Inversions Across the Greenland Ice Sheet Using In-situ, Remote Sensing, and Reanalysis Data

&amp;lt;p&amp;gt;As Arctic temperatures have increased, the Greenland Ice Sheet has exhibited a negative mass balance, with a substantial and increasing fraction of mass loss due to surface melt. Understanding surface energy exchange processes in Greenland is critical for our ability to predict changes in mass balance. In-situ and remotely sensed surface temperatures are useful for monitoring trends, melt events, and surface energy balance processes, but these observations are complicated by the fact that surface temperatures and near surface air temperatures can significantly differ due to the presence of inversions that exist across the Arctic. Our previous work shows that even in the summer, very near surface inversions are present between the 2m air and surface temperatures a majority of the time at Summit, Greenland. In this study, we expand upon these results and combine a variety of data sources to quantify differences between surface snow/ice temperatures and 2m air temperatures across the Greenland Ice Sheet and investigate controls on the magnitude of these near surface temperature inversions. In-situ temperatures, wind speed, specific humidity, and albedo data are provided from automatic weather stations operated by the Programme for Monitoring of the Greenland Ice Sheet (PROMICE). We use the Clouds and the Earth's Radiant Energy System (CERES) cloud area fraction data to analyze effects of cloud presence on near surface temperature gradients. The in-situ temperatures are compared to Modern-Era Retrospective analysis for Research and Applications Version 2 (MERRA-2) and Moderate Resolution Imaging Spectrometer (MODIS) ice surface temperature data to extend findings across the ice sheet. Using PROMICE in-situ data from 2015, we find that these 2m temperature inversions are present 77% of the time, with a median strength of 1.7&amp;amp;#176;C. The data confirm that the presence of clouds weakens inversions. Initial results indicate a RMSE of 3.9&amp;amp;#176;C between MERRA-2 and PROMICE 2m air temperature, and a RMSE of 5.6&amp;amp;#176;C between the two datasets for surface temperature. Improved understanding of controls on near surface inversions is important for use of remotely sensed snow surface temperatures and for modeling of surface mass and energy exchange processes.&amp;lt;/p&amp;gt; </jats:p

Monitoring of snow surface near-infrared bidirectional reflectance factors with added light-absorbing particles

Abstract. Broadband snow albedo can range from 0.3 to 0.9 depending on microphysical properties and light-absorbing particle (LAP) concentrations. Beyond the widely observed direct and visibly apparent effect of darkening snow, it is still unclear how LAPs influence snow albedo feedbacks. To investigate LAPs' indirect effect on snow albedo feedbacks, we developed and calibrated the Near-Infrared Emitting and Reflectance-Monitoring Dome (NERD) and monitored bidirectional reflectance factors (BRFs) hourly after depositing dust and black carbon (BC) particles onto experimental snow surfaces. After comparing snow infrared BRFs to snow specific surface areas (SSAs), we found that both measured and modeled snow infrared BRFs are correlated with snow SSA. These results, however, demonstrate a considerable uncertainty of ±10 m2 kg−1 in the determination of snow SSA from our BRF measurements. The nondestructive technique for snow SSA retrieval that we present here can be further developed for science applications that require rapid in situ snow SSA measurements. After adding large amounts of dust and BC to snow, we found more rapid decreasing of snow BRFs and SSAs in snow with added LAPs compared to natural (clean) snow but only during clear-sky conditions. These results suggest that deposition of LAPs onto snow can accelerate snow metamorphism via a net positive snow grain-size feedback. </jats:p

Near-surface thermal stratification during summer at Summit, Greenland, and its relation to MODIS-derived surface temperatures

Abstract. As rapid warming of the Arctic occurs, it is imperative that climate indicators such as temperature be monitored over large areas to understand and predict the effects of climate changes. Temperatures are traditionally tracked using in situ 2 m air temperatures, but in remote locations where few ground-based measurements exist, such as on the Greenland Ice Sheet, temperatures over large areas are assessed using remote sensing techniques. Because of the presence of surface-based temperature inversions in ice-covered areas, differences between 2 m air temperature and the temperature of the actual snow surface (referred to as skin temperature) can be significant and are particularly relevant when considering validation and application of remote sensing temperature data. We present results from a field campaign extending from 8 June through 18 July 2015, near Summit Station in Greenland to study surface temperature using the following measurements: skin temperature measured by an infrared (IR) sensor, thermochrons, and thermocouples; 2 m air temperature measured by a NOAA meteorological station; and a MODerate-resolution Imaging Spectroradiometer (MODIS) surface temperature product. Our data indicate that 2 m air temperature is often significantly higher than snow skin temperature measured in-situ, and this finding may account for apparent biases in previous surface temperature studies of MODIS products that used 2 m air temperature for validation. This inversion is present during summer months when incoming solar radiation and wind speed are both low. As compared to our in-situ IR skin temperature measurements, after additional cloud masking, the MOD/MYD11 Collection 6 surface-temperature standard product has an RMSE of 1.0 °C, spanning a range of temperatures from −35 °C to −5 °C. For our study area and time series, MODIS surface temperature products agree with skin surface temperatures better than previous studies indicated, especially at temperatures below −20 °C where other studies found a significant cold bias. The apparent cold bias present in others’ comparison of 2 m air temperature and MODIS surface temperature is perhaps a result of the near-surface temperature inversion that our data demonstrate. Further investigation of how in-situ IR skin temperatures compare to MODIS surface temperature at lower temperatures (below −35 °C) is warranted to determine if this cold bias does indeed exist. </jats:p

Principles and test methods of non-contact body thermometry

AbstractSignificanceFar infrared (IR) has a long history in thermometry and febrile screening. Concerns have been raised recently over the accuracy of non-contact body thermometry. Clinical testing with febrile individuals constitutes the standard performance assessment. This is challenging to replicate, which may have inadvertently allowed approval of IR systems that are unable to detect fevers. The ability to test performance without relying on febrile participants would have ramifications for public health, especially if this discovered undisclosed differences in accuracy in widely used devices.AimTo identify foundational issues in, demonstrate principles of, and develop test methods for non-contact body thermometry.ApproachWe review foundational literature and identify confounds impeding performance of IR thermography (IRT) and non-contact IR thermometry (NCIT) for febrile screening and demonstrate corrections for their effects, which would otherwise be unacceptable. Almost none of the devices we are aware of compensate for these confounds. We reverse-engineer surface-to-body temperature relations for several FDA-cleared NCITs. We note their similarity to recently reported bias-to-normal behavior in other devices and determine range of body temperatures for which the device would produce a "normal" (non-febrile) output. Finally, we generate predictable elevated face temperatures in healthy subjects and demonstrate this in several devices.ResultsThe surface-to-body relationships for two IRT and one NCIT were linear, while all others exhibited nonlinear bias-to-normal behavior that produce normal temperatures when presented with surface temperatures ranging from hypothermia to moderate-to-severe fever. The test method was used in healthy, non-febrile subjects to generate elevated temperatures corresponding to body temperatures from 97.35F to 102.45F. Three out of five systems had negligible sensitivity.ConclusionsThis demonstrates an alternative evaluation method without the limitations and risks of febrile patients. These results indicate many devices may be unusable for body thermometry and may be providing a false sense of security for public health surveillance.</jats:sec