Marco Tedesco

Intercomparison of Electromagnetic Models for Passive Microwave Remote Sensing of Snow

Electromagnetic models can be used for understanding the interaction between electromagnetic waves and matter, interpreting experimental data, and retrieving geophysical parameters. Comparing the results of different snow models, when driven with the same set of input parameters, can benefit remote sensing of snow. Microwave brightness temperatures of snow at 19 and 37 GHz for six different classes of snow (prairie, tundra, taiga, alpine, maritime, and ephemeral) are simulated by means of four different electromagnetic models: the Helsinki University of Technology snow emission model, the microwave emission model of layered snowpacks, a dense-medium radiative-transfer theory model, and a strong fluctuation theory model. The frequency behavior of the extinction coefficients obtained with the different models between 5 and 90 GHz is also studied. The four models are also driven with inputs derived from snow-pit data, and the outputs are compared with ground-based measurements of brightness temperatures at 18.7 and 36.5 GHz. Significant differences among the brightness temperatures and the extinction coefficients simulated with the four models in the cases of the six classes of snow are observed. Moreover, no particular model is found to be able to systematically reproduce all of the experimental data. The results highlight the need to more closely examine the relationships relating mean grain size and correlation length, introduce multiple layers in each model, and to perform controlled laboratory measurements on materials with well-known electromagnetic properties in order to improve the understanding of the causes of the observed differences and to improve model performance

Microwave emission from dry snow: a comparison of experimental and model results

Field measurements of microwave emission from snow-covered soil were carried out in 1996, 1997, and 1999 on the Italian Alps using a three-frequency dual polarized microwave system. At the same time, nivological time measurements were carried out using standard methods and an electromagnetic contact probe. Collected data confirmed the possibility of separating wet from dry snow and of estimating the water equivalent of dry snow. Simulations performed by means of a model based on the dense medium radiative theory (DMRT) were able to reproduce experimental data very well.

Brightness Temperatures of Snow Melting/Refreezing Cycles: Observations and Modeling Using a Multilayer Dense Medium Theory-Based Model

The ability of electromagnetic models to accurately predict microwave emission of a snowpack is complicated by the need to account for, among other things, nonindependent scattering by closely packed snow grains, stratigraphic variations, and the occurrence of wet snow. A multilayer dense medium model can account for the first two effects. While microwave remote sensing is well known to be capable of binary wet/dry discrimination, the ability to model brightness as a function of wetness opens up the possibility of ultimately retrieving a percentage wetness value during such hydrologically significant melting conditions. In this paper, the first application of a multilayer dense medium radiative transfer theory (DMRT) model is proposed to simulate emission from both wet and dry snow during melting and refreezing cycles. Wet snow is modeled as a mixture of ice particles surrounded by a thin film of water embedded in an air background. Melting/refreezing cycles are studied by means of brightness temperatures at 6.7, 19, and 37 GHz recorded by the University of Michigan Truck-Mounted Radiometer System at the Local Scale Observation Site during the Cold Land Processes Experiment-1 in March 2003. Input parameters to the DMRT model are obtained from snow pit measurements carried out in conjunction with the microwave observations. The comparisons between simulated and measured brightness temperatures show that the electromagnetic model is able to reproduce the brightness temperatures with an average percentage error of 3% (~8 K) and a maximum relative percentage error of around 8% (~20 K)

Analysis of multiscale radiometric data collected during the Cold Land Processes Experiment-1 (CLPX-1)

[1]xa0Histograms of brightness temperatures collected at 18.7 and 37 GHz over the Fraser and North Park Meso-Scale Areas during the Cold Land Processes Experiment by the NOAA Polarimetric Scanning Radiometer (PSR/A) airborne sensor are modelled by a log-normal distribution (Fraser, forested area) and by a bi-modal distribution (North Park, patchy-snow, non-forested area). The brightness temperatures are re-sampled over a range of resolutions to study the effects of sensor resolution on the shape of the distribution, on the values of the average brightness temperatures and standard deviations. The histograms become more uniform and the spatial information in the initial distribution is lost for a resolution larger than 5000 m, in both areas. The values of brightness temperatures obtained by re-sampling the PSR-A data at 25 km resolution are consistent with those recorded by the Advanced Microwave Scanning Radiometer (AMSR-E) and Special Sensor Microwave/Imager (SSM/I) satellite radiometers at similar resolutions.

Arctic cut-off high drives the poleward shift of a new Greenland melting record

Large-scale atmospheric circulation controls the mass and energy balance of the Greenland ice sheet through its impact on radiative budget, runoff and accumulation. Here, using reanalysis data and the outputs of a regional climate model, we show that the persistence of an exceptional atmospheric ridge, centred over the Arctic Ocean, was responsible for a poleward shift of runoff, albedo and surface temperature records over the Greenland during the summer of 2015. New records of monthly mean zonal winds at 500u2009hPa and of the maximum latitude of ridge peaks of the 5,700±50u2009m isohypse over the Arctic were associated with the formation and persistency of a cutoff high. The unprecedented (1948–2015) and sustained atmospheric conditions promoted enhanced runoff, increased the surface temperatures and decreased the albedo in northern Greenland, while inhibiting melting in the south, where new melting records were set over the past decade.

Greenland Ice Sheet Surface Mass Loss: Recent Developments in Observation and Modeling

Surface processes currently dominate Greenland ice sheet (GrIS) mass loss. We review recent developments in the observation and modeling of GrIS surface mass balance (SMB), published after the July 2012 deadline for the Fifth Assessment Report of the Intergovernmental Panel on Climate Change (IPCC AR5). Since IPCC AR5, our understanding of GrIS SMB has further improved, but new observational and model studies have also revealed that temporal and spatial variability of many processes are still poorly quantified and understood, e.g., bio-albedo, the formation of ice lenses and their impact on lateral meltwater transport, heterogeneous vertical meltwater transport (‘piping’), the impact of atmospheric-circulation changes and mixed-phase clouds on the surface energy balance, and the magnitude of turbulent heat exchange over rough ice surfaces. As a result, these processes are only schematically or not at all included in models that are currently used to assess and predict future GrIS surface mass loss.

Melting glaciers stimulate large summer phytoplankton blooms in southwest Greenland waters

Each summer, large quantities of freshwater and associated dissolved and particulate material are released from the Greenland Ice Sheet (GrIS) into local fjords where they promote local phytoplankton growth. Whether the influx of freshwater and associated micronutrients in glacial meltwater is able to stimulate phytoplankton growth beyond the fjords is disputed, however. Here we show that the arrival of freshwater discharge from outlet glaciers from both southeast and southwest GrIS coincides with large-scale blooms in the Labrador Sea that extend over 300xa0km from the coast during summer. This summer bloom develops about a week after the arrival of glacial meltwater in early July and persists until the input of glacial meltwater slows in August or September, accounting for ~40% of annual net primary production for the area. In view of the absence of a significant change in the depth of the mixed layer associated with the arrival of glacial meltwater to the Labrador Sea, we suggest that the increase in phytoplankton biomass and productivity in summer is likely driven by a greater nutrient supply (most likely iron). Our results highlight that the ecological impact of meltwater from the GrIS likely extends far beyond the boundaries of the local fjords, encompassing much of the eastern Labrador Sea. Such impacts may increase if melting of the GrIS accelerates as predicted.

Atmospheric drivers of Greenland surface melt revealed by self‐organizing maps

Recent acceleration in surface melt on the Greenland ice sheet (GrIS) has occurred concurrently with a rapidly warming Arctic and has been connected to persistent, anomalous atmospheric circulation patterns over Greenland. To identify synoptic setups favoring enhanced GrIS surface melt and their decadal changes, we develop a summer Arctic synoptic climatology by employing self-organizing maps. These are applied to daily 500u2009hPa geopotential height fields obtained from the Modern Era Retrospective Analysis for Research and Applications reanalysis, 1979–2014. Particular circulation regimes are related to meteorological conditions and GrIS surface melt estimated with outputs from the Modele Atmospherique Regional. Our results demonstrate that the largest positive melt anomalies occur in concert with positive height anomalies near Greenland associated with wind, temperature, and humidity patterns indicative of strong meridional transport of heat and moisture. We find an increased frequency in a 500u2009hPa ridge over Greenland coinciding with a 63% increase in GrIS melt between the 1979–1988 and 2005–2014 periods, with 75.0% of surface melt changes attributed to thermodynamics, 17% to dynamics, and 8.0% to a combination. We also confirm that the 2007–2012 time period has the largest dynamic forcing relative of any period but also demonstrate that increased surface energy fluxes, temperature, and moisture separate from dynamic changes contributed more to melt even during this period. This implies that GrIS surface melt is likely to continue to increase in response to an ever warmer future Arctic, regardless of future atmospheric circulation patterns.

Direct measurements of meltwater runoff on the Greenland ice sheet surface

Significance Meltwater runoff is an important hydrological process operating on the Greenland ice sheet surface that is rarely studied directly. By combining satellite and drone remote sensing with continuous field measurements of discharge in a large supraglacial river, we obtained 72 h of runoff observations suitable for comparison with climate model predictions. The field observations quantify how a large, fluvial supraglacial catchment attenuates the magnitude and timing of runoff delivered to its terminal moulin and hence the bed. The data are used to calibrate classical fluvial hydrology equations to improve meltwater runoff models and to demonstrate that broad-scale surface water drainage patterns that form on the ice surface powerfully alter the timing, magnitude, and locations of meltwater penetrating into the ice sheet. Meltwater runoff from the Greenland ice sheet surface influences surface mass balance (SMB), ice dynamics, and global sea level rise, but is estimated with climate models and thus difficult to validate. We present a way to measure ice surface runoff directly, from hourly in situ supraglacial river discharge measurements and simultaneous high-resolution satellite/drone remote sensing of upstream fluvial catchment area. A first 72-h trial for a 63.1-km2 moulin-terminating internally drained catchment (IDC) on Greenland’s midelevation (1,207–1,381 m above sea level) ablation zone is compared with melt and runoff simulations from HIRHAM5, MAR3.6, RACMO2.3, MERRA-2, and SEB climate/SMB models. Current models cannot reproduce peak discharges or timing of runoff entering moulins but are improved using synthetic unit hydrograph (SUH) theory. Retroactive SUH applications to two older field studies reproduce their findings, signifying that remotely sensed IDC area, shape, and supraglacial river length are useful for predicting delays in peak runoff delivery to moulins. Applying SUH to HIRHAM5, MAR3.6, and RACMO2.3 gridded melt products for 799 surrounding IDCs suggests their terminal moulins receive lower peak discharges, less diurnal variability, and asynchronous runoff timing relative to climate/SMB model output alone. Conversely, large IDCs produce high moulin discharges, even at high elevations where melt rates are low. During this particular field experiment, models overestimated runoff by +21 to +58%, linked to overestimated surface ablation and possible meltwater retention in bare, porous, low-density ice. Direct measurements of ice surface runoff will improve climate/SMB models, and incorporating remotely sensed IDCs will aid coupling of SMB with ice dynamics and subglacial systems.

Northern Hemisphere Snow-Covered Area Mapping: Optical Versus Active and Passive Microwave Data

Spaceborne passive microwave data have been available for the past 27 years, and have supported the development of several algorithms for the retrieval of snow water equivalent and snow depth that, in turn, can be used for mapping snow-covered areas. In contrast, only recently has the application of spaceborne active microwave instruments been investigated for remote sensing of snow on a global scale. This raises the question of whether a technique combining active and passive microwave data can improve the mapping of snow parameters with respect to techniques based solely on passive data. In this letter, we report results concerning the mapping of snow-covered area (SCA) in the Northern Hemisphere between the years 2000 and 2004 derived from the combination of the brightness temperatures at 19.35 and 37 GHz measured by the Special Sensor Microwave Imager Radiometer with backscatter coefficients at 13.4 GHz measured by the NASAs QuickSCAT. SCA derived from the Moderate Resolution Imaging Spectroradiometer (MODIS) is used as a reference to evaluate the performance of the microwave-based techniques and their combination. Results show that, generally, the technique using passive data provides better agreement with MODIS SCA than the technique using only scatterometer data. However, the results when both datasets are used show considerable improvement, demonstrating the potential benefits of a multisensor approach