AMSR2 Thin Ice Detection Algorithm for the Arctic Winter Conditions

2022 ◽  
pp. 1-1
Author(s):  
Marko Makynen ◽  
Markku Simila
Keyword(s):  
Detection Algorithm ◽  
The Arctic ◽  
Winter Conditions ◽  
Ice Detection

scholarly journals An improved sea ice detection algorithm using MODIS: application as a new European sea ice extent indicator

2021 ◽  
Vol 15 (6) ◽  
pp. 2803-2818
Author(s):  
Joan Antoni Parera-Portell ◽  
Raquel Ubach ◽  
Charles Gignac
Keyword(s):  
Sea Ice ◽  
Regional Scale ◽  
Ice Cover ◽  
Detection Algorithm ◽  
Temporal Variations ◽  
The Arctic ◽  
Sea Ice Extent ◽  
Monitoring Tools ◽  
Spatio Temporal ◽  
Ice Detection

Abstract. The continued loss of sea ice in the Northern Hemisphere due to global warming poses a threat to biota and human activities, evidencing the necessity of efficient sea ice monitoring tools. Aiming at the creation of an improved sea ice extent indicator covering the European regional seas, the new IceMap500 algorithm has been developed to classify sea ice and water at a resolution of 500 m at nadir. IceMap500 features a classification strategy built upon previous MODIS sea ice extent algorithms and a new method to reclassify areas affected by resolution-breaking features inherited from the MODIS cloud mask. This approach results in an enlargement of mapped area, a reduction of potential error sources and a better delineation of the sea ice edge, while still systematically achieving accuracies above 90 %, as obtained by manual validation. Swath maps have been aggregated at a monthly scale to obtain sea ice extent with a method that is sensitive to spatio-temporal variations in the sea ice cover and that can be used as an additional error filter. The resulting dataset, covering the months of maximum and minimum sea ice extent (i.e. March and September) over 2 decades (from 2000 to 2019), demonstrates the algorithm's applicability as a monitoring tool and as an indicator, illustrating the sea ice decline at a regional scale. The European sea regions located in the Arctic, NE Atlantic and Barents seas display clear negative trends in both March (−27.98 ± 6.01 × 103 km2yr−1) and September (−16.47 ± 5.66 × 103 km2yr−1). Such trends indicate that the sea ice cover is shrinking at a rate of ∼ 9 % and ∼ 13 % per decade, respectively, even though the sea ice extent loss is comparatively ∼ 70 % greater in March.

scholarly journals Wintertime Arctic Air Pollution over central Alaska: pre-ALPACA campaign

2021 ◽  
Author(s):  
Eleftherios Ioannidis ◽  
Kathy S. Law ◽  
Jean-Christophe Raut ◽  
Tatsuo Onishi ◽  
Louis Marelle ◽  
...  
Keyword(s):  
Air Pollution ◽  
The United States ◽  
Point Sources ◽  
The Arctic ◽  
Formation Mechanisms ◽  
Winter Conditions ◽  
Local Point ◽  
Temperature Inversions ◽  
Local Emissions ◽  
Pollution Episodes

<p>The wintertime Arctic is influenced by air pollution transported from mid-latitudes, leading to formation of Arctic Haze, as well as local emissions such as combustion for heating and power production in very cold winter conditions. This contributes to severe air pollution episodes, with enhanced aerosol concentrations, inter-dispersed with cleaner periods. However, the formation of secondary aerosol particles (sulphate, organics, nitrate) in cold/dark wintertime Arctic conditions, which could contribute to these pollution episodes, is poorly understood.</p><p>In this study, which contributes to the Air Pollution in the Arctic: Climate, Environment and Societies - Alaskan Layered Pollution and Arctic Chemical Analysis (PACES-ALPACA) initiative, the Weather Research Forecasting Model with chemistry (WRF-Chem) is used to investigate wintertime pollution over central Alaska focusing on the Fairbanks region, during the pre-ALPACA campaign in winter 2019-2020. Fairbanks is the most polluted city in the United States during wintertime, due to high local emissions and the occurrence of strong surface temperature inversions trapping pollutants near the surface.</p><p>Firstly, different WRF meteorological and surface schemes were tested over Alaska with a particular focus on improving simulations of the wintertime boundary layer structure including temperature inversions. An optimal WRF set-up, with increased vertical resolution below 2km, was selected based on evaluation against available data.</p><p>Secondly, a quasi-hemispheric WRF-Chem simulation, using the improved WRF setup, was used to assess large-scale synoptic conditions and to evaluate background aerosols originating from remote anthropogenic and natural sources affecting central Alaska during the campaign. The model was run with Evaluating the Climate and Air Quality Impacts of Short-Lived Pollutants (ECLIPSE) v6b anthropogenic emissions and improved sea-spray aerosol emissions. Discrepancies in modelled aerosols compared available data are being investigated (e.g. missing dark formation mechanisms, treatment of removal processes).</p><p>Thirdly, fine resolution simulations, using high resolution emissions (e.g. 2019 CAMS inventory), including local point sources, over the Fairbanks region, were used to investigate chemical and dynamical processes influencing aerosols under different meteorological conditions observed during the field campaign including a cold stable episode and a period with possible mixing of air masses from aloft. The model was evaluated against available aerosol, oxidant (ozone) and aerosol precursor data from surface monitoring sites and collected during the pre-campaign, including vertical profile data collected in the lowest 20m. The sensitivity of modelled aerosols to meteorological factors, such as relative humidity, temperature gradients and vertical mixing under winter conditions are investigated.</p>

scholarly journals Generation of layering in the upper arctic troposphere away from the jet stream

2003 ◽  
Vol 21 (7) ◽  
pp. 1653-1665
Author(s):  
A. Karpetchko ◽  
E. Kyro ◽  
P. von der Gathen
Keyword(s):  
Detection Algorithm ◽  
Vertical Shear ◽  
Atmospheric Composition ◽  
The Arctic ◽  
Back Trajectory ◽  
Synoptic Situation ◽  
Jet Stream ◽  
Composition And Structure ◽  
Streamer Propagation ◽  
Frontal Zones

Abstract. Ozone sounding databases for two stations, So-dankylä (67° N, 27° E) and Ny-Ålesund (79° N, 12° E) were used in order to investigate the generation of layering in the upper and middle troposphere of the Arctic. We concentrated on dry, ozone-rich and stable layers observed below the thermal tropopause under light wind conditions. This condition ensures that the observed layer is not a tropopause fold, a well-known phenomenon that develops within frontal zones near the jet stream. Selection criteria for ozone, humidity and stability anomalies of the tropopause fold detection algorithm were used here to pick out for detailed studies the most pronounced examples of laminae. For all these cases the meteorological situations were investigated in order to establish the origin of the observed layers. We found that layers could be classified into two groups. Laminae of the first group were observed equatorward of the jet stream and those of a second group were observed poleward of the jet. The meteorological situation for the first group resembles that for equatorward stratospheric streamer propagation. It was found that this group accounts for only a small fraction of the layers observed at Sodankylä and for none of those observed at Ny-Ålesund during the period investigated. A large case-to-case variability in the synoptic situation was observed for the second group of laminae, which were detected northward of the jet stream. Nevertheless, in about half of the cases, streamers of tropospheric air were found in the vicinity of the stations on the isentropic surfaces just above the detected stratospheric layers. Back trajectory analyses showed that these layers originated in the vicinity of the polar jet stream. We suppose that laminae-like structures in the troposphere were caused, in both groups, by equatorward (poleward) advection of the stratospheric (tropospheric) air, together with differential vertical shear. Forward-trajectory calculations suggest that, subsequently, a part of the stratospheric layers can mix irreversibly into the troposphere.Key words. Atmospheric composition and structure (pressure, density, and temperature; troposphere-composition and chemistry)

scholarly journals Potential of Passive Microwave around 183 GHz for Snowfall Detection in the Arctic

2019 ◽  
Vol 11 (19) ◽  
pp. 2200 ◽  
Author(s):  
Léo Edel ◽  
Jean-François Rysman ◽  
Chantal Claud ◽  
Cyril Palerme ◽  
Christophe Genthon
Keyword(s):  
Detection Algorithm ◽  
The Arctic ◽  
Mountainous Areas ◽  
Phase Precipitation ◽  
Water Path ◽  
Brightness Temperatures ◽  
Microwave Humidity Sounder ◽  
Snow Water ◽  
Potential Use ◽  
Selection Of

This study evaluates the potential use of the Microwave Humidity Sounder (MHS) for snowfall detection in the Arctic. Using two years of colocated MHS and CloudSat observations, we develop an algorithm that is able to detect up to 90% of the most intense snowfall events (snow water path ≥400 g m−2 and 50% of the weak snowfall rate events (snow water path ≤50 g m−2. The brightness temperatures at 190.3 GHz and 183.3 ± 3 GHz, the integrated water vapor, and the temperature at 2 m are identified as the most important variables for snowfall detection. The algorithm tends to underestimate the snowfall occurrence over Greenland and mountainous areas (by as much as −30%), likely due to the dryness of these areas, and to overestimate the snowfall occurrence over the northern part of the Atlantic (by up to 30%), likely due to the occurrence of mixed phase precipitation. An interpretation of the selection of the variables and their importance provides a better understanding of the snowfall detection algorithm. This work lays the foundation for the development of a snowfall rate quantification algorithm.

scholarly journals Arctic Fog Detection Using Infrared Spectral Measurements

2019 ◽  
Vol 36 (8) ◽  
pp. 1643-1656
Author(s):  
Li Yi ◽  
King-Fai Li ◽  
Xianyao Chen ◽  
Ka-Kit Tung
Keyword(s):  
Sea Ice ◽  
Chukchi Sea ◽  
Open Water ◽  
Detection Algorithm ◽  
Probability Of Detection ◽  
Satellite Observations ◽  
The Arctic ◽  
Water Surface Area ◽  
Infrared Spectral ◽  
Fog Detection

AbstractThe rapid increase in open-water surface area in the Arctic, resulting from sea ice melting during the summer likely as a result of global warming, may lead to an increase in fog [defined as a cloud with a base height below 1000 ft (~304 m)], which may imperil ships and small aircraft transportation in the region. There is a need for monitoring fog formation over the Arctic. Given that ground-based observations of fog over Arctic open water are very sparse, satellite observations may become the most effective way for Arctic fog monitoring. We developed a fog detection algorithm using the temperature difference between the cloud top and the surface, called ∂T in this work. A fog event is said to be detected if ∂T is greater than a threshold, which is typically between −6 and −12 K, depending on the time of the day (day or night) and the surface types (open water or sea ice). We applied this method to the coastal regions of Chukchi Sea and Beaufort Sea near Barrow, Alaska (now known as Utqiaġvik), during the months of March–October. Training with satellite observations between 2007 and 2014 over this region, the ∂T method can detect Arctic fog with an optimal probability of detection (POD) between 74% and 90% and false alarm rate (FAR) between 5% and 17%. These statistics are validated with data between 2015 and 2016 and are shown to be robust from one subperiod to another.

scholarly journals Partitioning between the inorganic chlorine reservoirs HCl and ClONO<sub>2</sub> during the Arctic winter 2005 from the ACE-FTS

2006 ◽  
Vol 6 (8) ◽  
pp. 2355-2366 ◽  
Author(s):  
G. Dufour ◽  
R. Nassar ◽  
C. D. Boone ◽  
R. Skelton ◽  
K. A. Walker ◽  
...  
Keyword(s):  
Fourier Transform ◽  
High Resolution ◽  
Atmospheric Chemistry ◽  
Lower Stratosphere ◽  
The Arctic ◽  
Fourier Transform Spectrometer ◽  
Cold Winter ◽  
Winter Conditions ◽  
Reservoir Species ◽  
Chemistry Experiment

Abstract. From January to March 2005, the Atmospheric Chemistry Experiment high resolution Fourier transform spectrometer (ACE-FTS) on SCISAT-1 measured many of the changes occurring in the Arctic (50–80° N) lower stratosphere under very cold winter conditions. Here we focus on the partitioning between the inorganic chlorine reservoirs HCl and ClONO2 and their activation into ClO. The simultaneous measurement of these species by the ACE-FTS provides the data needed to follow chlorine activation during the Arctic winter and the recovery of the Cl-reservoir species ClONO2 and HCl. The time evolution of HCl, ClONO2 and ClO as well as the partitioning between the two reservoir molecules agrees well with previous observations and with our current understanding of chlorine activation during Arctic winter. The results of a chemical box model are also compared with the ACE-FTS measurements and are generally consistent with the measurements.

Development of a water clear of sea ice detection algorithm from enhanced SeaWinds/QuikSCAT and AMSR-E measurements

2010 ◽  
Vol 114 (11) ◽  
pp. 2594-2609 ◽  
Author(s):  
Stephen E.L. Howell ◽  
Chris Derksen ◽  
Adrienne Tivy
Keyword(s):  
Sea Ice ◽  
Detection Algorithm ◽  
Ice Detection

scholarly journals An improved sea ice detection algorithm using MODIS: application as a new European sea ice extent indicator

2021 ◽  
Author(s):  
Joan A. Parera-Portell ◽  
Raquel Ubach ◽  
Charles Gignac
Keyword(s):  
Sea Ice ◽  
Synthesis Method ◽  
Ice Cover ◽  
Detection Algorithm ◽  
Arctic Seas ◽  
Sea Ice Extent ◽  
Monitoring Tools ◽  
Ice Detection ◽  
The Baltic ◽  
Cloud Mask

Abstract. The continued loss of sea ice in the Northern Hemisphere due to global warming poses a threat on biota and human activities, evidencing the necessity of efficient sea ice monitoring tools. Aiming at the creation of an improved European sea ice extent indicator, the IceMap250 algorithm has been reworked to generate improved sea ice extent maps at 500 m resolution at nadir. Changes in the classification approach and a new method to correct artefacts arising from the MODIS cloud mask allow the enlargement of the mapped area, the reduction of potential error sources and a qualitative improvement of the resulting maps, while systematically achieving accuracies above 90 %. Monthly sea ice extent maps have been derived using a new synthesis method which acts as an additional error filter. Our results, covering the months of maximum (March) and minimum (September) sea ice extent during two decades (from 2000 to 2019), are a proof of the algorithm's applicability as an indicator, illustrating the sea ice decline in the European regional seas. We observed no significant trends in the Baltic (−2.75 ± 2.05 × 103 km2 yr−1) although, on the contrary, the European Arctic seas display clear negative trends both in March (−27.98 ± 6.01 × 103 km2 yr−1) and September (−16.47 ± 5.66 × 103 km2 yr−1). Such trends indicate that the sea ice cover in March and September is shrinking at a rate of ∼9 % and ∼13 % per decade, respectively, even though the sea ice extent loss is comparatively ∼70 % greater in March. Therefore, according to the trends and without taking into account the variability of the sea ice cover, the loss of sea ice extent over two decades in the study area would be comparable to the area of continental France in the case of the March maximum, and to that of Finland in the case of the September minimum.

scholarly journals Is Radar Phase Information Useful for Sea Ice Detection in the Marginal Ice Zone?

2020 ◽  
Vol 12 (11) ◽  
pp. 1847
Author(s):  
Fuhong Ding ◽  
Hui Shen ◽  
William Perrie ◽  
Yijun He
Keyword(s):  
High Resolution ◽  
Sea Ice ◽  
Phase Difference ◽  
Incidence Angle ◽  
The Arctic ◽  
Sar Images ◽  
Ecological Processes ◽  
Additional Tool ◽  
Marginal Ice Zone ◽  
Ice Detection

With continuing sea ice reductions in the Arctic, dynamic physical and ecological processes have more active roles compared to the ice-locked, isolated Arctic Ocean of previous decades. To better understand these changes, observations of high-resolution sea ice conditions are needed. Remote sensing is a useful tool for observations in the harsh Arctic environment. For unsupervised ice detection, we demonstrate the promising value of radar phase difference from polarimetric radar measurements in this study, based on full polarimetric complex RADARSAT-2 SAR images in the marginal ice zone. It is demonstrated that the phase difference from co-polarized and cross-polarized synthetic aperture radar (SAR) images show promising capability for high resolution sea ice discrimination from open water. In particular, the phase difference shows superior potential for the detection of frazil ice compared to the traditional methodology based on the radar intensity ratio. The relationship between phase difference and radar incidence angle is also analyzed, as well as the potential influence of high sea state. The new methodology provides an additional tool for ice detection. In order to make the best use of this tool, directions for further studies are discussed for operational ice detection and possible ice classification.

Strong changes in the relationship between storage and discharge during a period of thawing soils and climate warming in Northern Sweden

2020 ◽  
Author(s):  
Alexa Hinzman ◽  
Ylva Sjöberg ◽  
Steve Lyon ◽  
Stefan Ploum ◽  
Ype van der Velde
Keyword(s):  
Water Cycle ◽  
Landscape Configuration ◽  
The Arctic ◽  
Northern Sweden ◽  
Deep Soil ◽  
Frozen Soils ◽  
Soil Frost ◽  
Winter Conditions ◽  
Non Linear ◽  
Seasonally Frozen Soils

&lt;p&gt;The Arctic is warming at an unprecedented rate. This warming affects not just ecosystems, but also permafrost, landscape configuration, and water availability in watersheds. One relatively under researched process is how seasonally frozen soils and changes thereof affect the water cycle. As frozen soils thaw, flow pathways within a catchment open, allowing for enhanced hydrologic connectivity between groundwater and rivers. As the connectivity of flow paths increase, the storage-discharge relationship of a watershed changes, which can be perceived within a hydrograph. More specifically, previous studies hypothesized that storage-discharge relationships are relatively linear when soils are frozen and become increasingly non-linear as the landscape thaws.&lt;/p&gt;&lt;p&gt;The objective of our research is to expand on the assumption that soil thaw leads to increasingly non-linear storage-discharge relationships by quantifying trends and spatio-temporal differences of this relationship. We will present our analysis of sixteen watersheds within Northern Sweden throughout the years of 1951 and 2018. We focus on spring and summer storage-discharge relationships and show how they are affected by preceding winter conditions.&lt;/p&gt;&lt;p&gt;We found a clear increase in non-linearity of the storage-discharge relationship over time for all catchments with twelve out of sixteen watersheds (75%) having a statistically significant increase in non-linearity. For twelve watersheds, spring relationships were significantly more linear compared to summer, which supports the hypothesis that seasonally frozen soils have less hydrological connectivity leading to more linear storage-discharge relationships. Winter conditions that allow deep soil frost lead to more linear storage-discharge relationships for ten watersheds. Overall, we show that thawing soil leads to a more non-linear storage-discharge relationship which implies river runoff in the Arctic becomes more unpredictable.&lt;/p&gt;

Sign in / Sign up

Export Citation Format

Share Document