Environmental pollution impact on radiation properties of atmosphere, snow and ice cover: Study from Barentsburg (Spitsbergen Archipelago)

2014 ◽  
Vol 4 (2) ◽  
pp. 178-184
Author(s):  
Pavel N. Sviashchennikov ◽  
Boris V. Ivanov ◽  
Irina A. Govorina

The value of the albedo of snow and ice surface is associated with the texture and structure of the surface layer of snow or ice (sea ice, glaciers), the peculiarities of the vertical redistribution of contaminations in this layer (mineral or organic particles of various concentrations, the size and shape), temperature regime of the surface layer of the atmosphere. Identifying links with the albedo characteristics of natural and artificial contamination is very important. For example, the results of mathematic modeling the evolution of ice sheets, sea ice and snow cover demonstrate the high sensitivity of the model to this parameter. Original results in the framework of this problem were obtained by researches from AARI and St. Petersburg State University during the 2010-2012 years on Svalbard in the vicinity of the Russian mining settlement Barentsburg. We present original results showing the relationship of "albedo-contaminations" and the influence of anthropogenic factors. The estimation of solar radiation that penetrates deep into the snow, and the impact of contamination on its redistribution in the snow thickness were obtained.

2021 ◽  
Author(s):  
Ruzica Dadic ◽  
Martin Schneebeli ◽  
Henna-Reeta Hannula ◽  
Amy Macfarlane ◽  
Roberta Pirazzini

<p>Snow cover dominates the thermal and optical properties of sea ice and the energy fluxes between the ocean and the atmosphere, yet data on the physical properties of snow and its effects on sea ice are limited. This lack of data leads to two significant problems: 1) significant biases in model representations of the sea ice cover and the processes that drive it, and 2) large uncertainties in how sea ice influences the global energy budget and the coupling of climate feedback. The  MOSAiC research initiative enabled the most extensive data collection of snow and surface scattering layer (SSL) properties over sea ice to date. During leg 5 of the MOSAiC expedition, we collected multi-scale (microscale to 100-m scale) measurements of the surface layer (snow/SSL) over first year ice (FYI) and MYI on a daily basis. The ultimate goal of our measurements is to determine the spatial distribution of physical properties of the surface layer. During leg 5 of the MOSAiC expedition, that surface layer changed from the  surface scattering layer (SSL),   characteristic for the melt season, to an early autumn snow pack. Here,  we will present data showing both a) the physical properties and the spatial distribution of the SSL during the late melt season and b) the transition of the sea ice surface from the SSL to the fresh autumn snowpack. The structural properties of this transition period are poorly documented, and this season is critical  for the initialization of sea ice and snow models. Furthermore, these data are crucial to interpret simultaneous observations of surface energy fluxes, surface optical and remote sensing data (microwave signals in particular), near-surface biochemical activity, and to understand the sea ice  processes that occur as the sea ice transitions from melting to freezing.</p>


1993 ◽  
Vol 17 ◽  
pp. 1-16 ◽  
Author(s):  
K. Steffen ◽  
R. Bindschadler ◽  
G. Casassa ◽  
J. Comiso ◽  
D. Eppler ◽  
...  

The third symposium on Remote Sensing of Snow and Ice, organized by the International Glaciological Society, took place in Boulder, Colorado, 17–22 May 1992. As part of this meeting a total of 21 papers was presented on snow and ice applications of Advanced Very High Resolution Radiometer (AVHRR) satellite data in polar regions. Also during this meeting a NASA sponsored Workshop was held to review the status of polar surface measurements from AVHRR. In the following we have summarized the ideas and recommendations from the workshop, and the conclusions of relevant papers given during the regular symposium sessions. The seven topics discussed include cloud masking, ice surface temperature, narrow-band albedo, ice concentration, lead statistics, sea-ice motion and ice-sheet studies with specifics on applications, algorithms and accuracy, following recommendations for future improvements. In general, we can affirm the strong potential of AVHRR for studying sea ice and snow covered surfaces, and we highly recommend this satellite data set for long-term monitoring of polar process studies. However, progress is needed to reduce the uncertainty of the retrieved parameters for all of the above mentioned topics to make this data set useful for direct climate applications such as heat balance studies and others. Further, the acquisition and processing of polar AVHRR data must become better coordinated between receiving stations, data centers and funding agencies to guarantee a long-term commitment to the collection and distribution of high quality data.


2019 ◽  
Author(s):  
Mark A. Tschudi ◽  
Walter N. Meier ◽  
J. Scott Stewart

Abstract. A new version of the sea ice motion and age products distributed at the National Snow and Ice Data Center's NASA Snow and Ice Distributed Active Archive Center has been developed. The new version, 4.0, includes several significant upgrades in processing, corrects known issues with the previous version, and updates the time series through 2018, with regular updates planned for the future. Here, we provide a history of the product development, discuss the improvements to the algorithms that create these products, and compare the Version 4 products to the previous version. While Version 4 algorithm changes were significant, the impact on the products is relatively minor, particularly for more recent years. Trends in motion and age are not substantially different between the versions. Changes in sea ice motion and age derived from the product show a significant shift in the Arctic ice cover, from a pack with a high concentration of older ice, to a sea ice cover dominated by first-year ice, which is more susceptible to summer melt. We also observe an increase in the speed of the ice in recent years, which is anticipated with the annual decrease in sea ice extent.


1993 ◽  
Vol 17 ◽  
pp. 1-16 ◽  
Author(s):  
K. Steffen ◽  
R. Bindschadler ◽  
G. Casassa ◽  
J. Comiso ◽  
D. Eppler ◽  
...  

The third symposium on Remote Sensing of Snow and Ice, organized by the International Glaciological Society, took place in Boulder, Colorado, 17–22 May 1992. As part of this meeting a total of 21 papers was presented on snow and ice applications of Advanced Very High Resolution Radiometer (AVHRR) satellite data in polar regions. Also during this meeting a NASA sponsored Workshop was held to review the status of polar surface measurements from AVHRR. In the following we have summarized the ideas and recommendations from the workshop, and the conclusions of relevant papers given during the regular symposium sessions. The seven topics discussed include cloud masking, ice surface temperature, narrow-band albedo, ice concentration, lead statistics, sea-ice motion and ice-sheet studies with specifics on applications, algorithms and accuracy, following recommendations for future improvements. In general, we can affirm the strong potential of AVHRR for studying sea ice and snow covered surfaces, and we highly recommend this satellite data set for long-term monitoring of polar process studies. However, progress is needed to reduce the uncertainty of the retrieved parameters for all of the above mentioned topics to make this data set useful for direct climate applications such as heat balance studies and others. Further, the acquisition and processing of polar AVHRR data must become better coordinated between receiving stations, data centers and funding agencies to guarantee a long-term commitment to the collection and distribution of high quality data.


Elem Sci Anth ◽  
2019 ◽  
Vol 7 ◽  
Author(s):  
L. C. Matthes ◽  
J. K. Ehn ◽  
S. L.-Girard ◽  
N. M. Pogorzelec ◽  
M. Babin ◽  
...  

The Arctic spring phytoplankton bloom has been reported to commence under a melting sea ice cover as transmission of photosynthetically active radiation (PAR; 400–700 nm) suddenly increases with the formation of surface melt ponds. Spatial variability in ice surface characteristics, i.e., snow thickness or melt pond distributions, and subsequent impact on transmitted PAR makes estimating light-limited primary production difficult during this time of year. Added to this difficulty is the interpretation of data from various sensor types, including hyperspectral, multispectral, and PAR-band irradiance sensors, with either cosine-corrected (planar) or spherical (scalar) sensor heads. To quantify the impact of the heterogeneous radiation field under sea ice, spectral irradiance profiles were collected beneath landfast sea ice during the Green Edge ice-camp campaigns in May–June 2015 and June–July 2016. Differences between PAR measurements are described using the downwelling average cosine, μd, a measure of the degree of anisotropy of the downwelling underwater radiation field which, in practice, can be used to convert between downwelling scalar, E0d, and planar, Ed, irradiance. A significantly smallerμd(PAR) was measured prior to snow melt compared to after (0.6 vs. 0.7) when melt ponds covered the ice surface. The impact of the average cosine on primary production estimates, shown in the calculation of depth-integrated daily production, was 16% larger under light-limiting conditions when E0d was used instead of Ed. Under light-saturating conditions, daily production was only 3% larger. Conversion of underwater irradiance data also plays a role in the ratio of total quanta to total energy (EQ/EW, found to be 4.25), which reflects the spectral shape of the under-ice light field. We use these observations to provide factors for converting irradiance measurements between irradiance detector types and units as a function of surface type and depth under sea ice, towards improving primary production estimates.


2020 ◽  
Vol 14 (5) ◽  
pp. 1519-1536 ◽  
Author(s):  
Mark A. Tschudi ◽  
Walter N. Meier ◽  
J. Scott Stewart

Abstract. A new version of sea ice motion and age products includes several significant upgrades in processing, corrects known issues with the previous version, and updates the time series through 2018, with regular updates planned for the future. First, we provide a history of these NASA products distributed at the National Snow and Ice Data Center. Then we discuss the improvements to the algorithms, provide validation results for the new (Version 4) and older versions, and intercompare the two. While Version 4 algorithm changes were significant, the impact on the products is relatively minor, particularly for more recent years. The changes in Version 4 reduce motion biases by ∼ 0.01 to 0.02 cm s−1 and error standard deviations by ∼ 0.3 cm s−1. Overall, ice speed increased in Version 4 over Version 3 by 0.5 to 2.0 cm s−1 over most of the time series. Version 4 shows a higher positive trend for the Arctic of 0.21 cm s−1 per decade compared to 0.13 cm s−1 per decade for Version 3. The new version of ice age estimates indicates more older ice than Version 3, especially earlier in the record, but similar trends toward less multiyear ice. Changes in sea ice motion and age derived from the product show a significant shift in the Arctic ice cover, from a pack with a high concentration of older ice to a sea ice cover dominated by first-year ice, which is more susceptible to summer melt. We also observe an increase in the speed of the ice over the time series ≥ 30 years, which has been shown in other studies and is anticipated with the annual decrease in sea ice extent.


1994 ◽  
Vol 40 (134) ◽  
pp. 16-30 ◽  
Author(s):  
Mohammede.E Shokr ◽  
David G. Barber

AbstractThe first field experiment in the 5 year seasonal Sea Ice Monitoring Site (SIMS) program was conducted in Resolute Passage, Canadian Eastern Arctic, between 15 May and 8 June 1990. This period signals the early melt season of sea ice in that region. A standard array of ice and snow measurements was collected on a daily basis from first-year and multi-year ice to monitor temporal evolution. Measurements included ice salinity, ice temperature and ice-surface roughness, snow salinity, snow temperature, snow density and snow depth. The complex dielectric constant of sea ice was computed from these measurements. Rapid desalination of first-year ice was noticed in the surface layer. Towards the end of the experiment period, salinities of the snow-hoar layer were higher than those of the ice-surface layer. Variation in air temperature is replicated by ice-surface temperature but not by the salinity or dielectric properties. No temporal variation in permittivity and dielectric loss was observed for first-year ice, but a slight increase in both parameters was observed for multi-year ice. As a result, a slight decrease in the microwave-penetration depth was observed for multi-year ice. Physical properties of ice and snow were compared against results obtained from other experiments conducted in different ice-formation regions in the late winter and in the early melt season.


2016 ◽  
Vol 9 (6) ◽  
pp. 2239-2254 ◽  
Author(s):  
Yao Yao ◽  
Jianbin Huang ◽  
Yong Luo ◽  
Zongci Zhao

Abstract. Sea ice plays an important role in the air–ice–ocean interaction, but it is often represented simply in many regional atmospheric models. The Noah sea ice scheme, which is the only option in the current Weather Research and Forecasting (WRF) model (version 3.6.1), has a problem of energy imbalance due to its simplification in snow processes and lack of ablation and accretion processes in ice. Validated against the Surface Heat Budget of the Arctic Ocean (SHEBA) in situ observations, Noah underestimates the sea ice temperature which can reach −10 °C in winter. Sensitivity tests show that this bias is mainly attributed to the simulation within the ice when a time-dependent ice thickness is specified. Compared with the Noah sea ice model, the high-resolution thermodynamic snow and ice model (HIGHTSI) uses more realistic thermodynamics for snow and ice. Most importantly, HIGHTSI includes the ablation and accretion processes of sea ice and uses an interpolation method which can ensure the heat conservation during its integration. These allow the HIGHTSI to better resolve the energy balance in the sea ice, and the bias in sea ice temperature is reduced considerably. When HIGHTSI is coupled with the WRF model, the simulation of sea ice temperature by the original Polar WRF is greatly improved. Considering the bias with reference to SHEBA observations, WRF-HIGHTSI improves the simulation of surface temperature, 2 m air temperature and surface upward long-wave radiation flux in winter by 6, 5 °C and 20 W m−2, respectively. A discussion on the impact of specifying sea ice thickness in the WRF model is presented. Consistent with previous research, prescribing the sea ice thickness with observational information results in the best simulation among the available methods. If no observational information is available, we present a new method in which the sea ice thickness is initialized from empirical estimation and its further change is predicted by a complex thermodynamic sea ice model. The ice thickness simulated by this method depends much on the quality of the initial guess of the ice thickness and the role of the ice dynamic processes.


2020 ◽  
Vol 20 (16) ◽  
pp. 9895-9914 ◽  
Author(s):  
Johannes Stapf ◽  
André Ehrlich ◽  
Evelyn Jäkel ◽  
Christof Lüpkes ◽  
Manfred Wendisch

Abstract. The concept of cloud radiative forcing (CRF) is commonly applied to quantify the impact of clouds on the surface radiative energy budget (REB). In the Arctic, specific radiative interactions between microphysical and macrophysical properties of clouds and the surface strongly modify the warming or cooling effect of clouds, complicating the estimate of CRF obtained from observations or models. Clouds tend to increase the broadband surface albedo over snow or sea ice surfaces compared to cloud-free conditions. However, this effect is not adequately considered in the derivation of CRF in the Arctic so far. Therefore, we have quantified the effects caused by surface-albedo–cloud interactions over highly reflective snow or sea ice surfaces on the CRF using radiative transfer simulations and below-cloud airborne observations above the heterogeneous springtime marginal sea ice zone (MIZ) during the Arctic CLoud Observations Using airborne measurements during polar Day (ACLOUD) campaign. The impact of a modified surface albedo in the presence of clouds, as compared to cloud-free conditions, and its dependence on cloud optical thickness is found to be relevant for the estimation of the shortwave CRF. A method is proposed to consider this surface albedo effect on CRF estimates by continuously retrieving the cloud-free surface albedo from observations under cloudy conditions, using an available snow and ice albedo parameterization. Using ACLOUD data reveals that the estimated average shortwave cooling by clouds almost doubles over snow- and ice-covered surfaces (−62 W m−2 instead of −32 W m−2), if surface-albedo–cloud interactions are considered. As a result, the observed total (shortwave plus longwave) CRF shifted from a warming effect to an almost neutral one. Concerning the seasonal cycle of the surface albedo, it is demonstrated that this effect enhances shortwave cooling in periods when snow dominates the surface and potentially weakens the cooling by optically thin clouds during the summertime melting season. These findings suggest that the surface-albedo–cloud interaction should be considered in global climate models and in long-term studies to obtain a realistic estimate of the shortwave CRF to quantify the role of clouds in Arctic amplification.


2015 ◽  
Vol 8 (12) ◽  
pp. 10305-10337 ◽  
Author(s):  
Y. Yao ◽  
J. Huang ◽  
Y. Luo ◽  
Z. Zhao

Abstract. Sea ice plays an important role in the air–ice–ocean interaction, but it is often represented simply in many regional atmospheric models. The Noah sea ice model, which has been widely used in the Weather Research and Forecasting (WRF) model, exhibits cold bias in simulating the Arctic sea ice temperature when validated against the Surface Heat Budget of the Arctic Ocean (SHEBA) in situ observations. According to sensitivity tests, this bias is attributed not only to the simulation of snow depth and turbulent fluxes but also to the heat conduction within snow and ice. Compared with the Noah sea ice model, the high-resolution thermodynamic snow and ice model (HIGHTSI) has smaller bias in simulating the sea ice temperature. HIGHTSI is further coupled with the WRF model to evaluate the possible added value from better resolving the heat transport and solar penetration in sea ice from a complex thermodynamic sea ice model. The cold bias in simulating the surface temperature over sea ice in winter by the original Polar WRF is reduced when HIGHTSI rather than Noah is coupled with the WRF model, and this also leads to a better representation of surface upward longwave radiation and 2 m air temperature. A discussion on the impact of specifying sea ice thickness in the WRF model is presented. Consistent with previous research, prescribing the sea ice thickness with observational information would result in the best simulation among the available methods. If no observational information is available, using an empirical method based on the relationship between sea ice concentration and sea ice thickness could mimic the large-scale spatial feature of sea ice thickness. The potential application of a thermodynamic sea ice model in predicting the change in sea ice thickness in a RCM is limited by the lack of sea ice dynamic processes in the model and the coarse assumption on the initial value of sea ice thickness.


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