Inter-comparison and evaluation of Arctic sea ice type products

oai:publications.copernicus.org:tc102910Arctic sea ice type (SITY) variation is a sensitive indicator of climate change. However, systematic inter-comparison and analysis for SITY products are lacking. This study analysed eight daily SITY products from five retrieval approaches covering the winters of 1999–2019, including purely radiometer-based (C3S-SITY), scatterometer-based (KNMI-SITY and IFREMER-SITY) and combined ones (OSISAF-SITY and Zhang-SITY). These SITY products were inter-compared against a weekly sea ice age product (i.e. NSIDC-SIA – National Snow and Ice Data Center sea ice age) and evaluated with five synthetic aperture radar (SAR) images. The average Arctic multiyear ice (MYI) extent difference between the SITY products and NSIDC-SIA varies from -1.32×106 to 0.49×106 km2. Among them, KNMI-SITY and Zhang-SITY in the QuikSCAT (QSCAT) period (2002–2009) agree best with NSIDC-SIA and perform the best, with the smallest bias of -0.001×106 km2 in first-year ice (FYI) extent and -0.02×106 km2 in MYI extent. In the Advanced Scatterometer (ASCAT) period (2007–2019), KNMI-SITY tends to overestimate MYI (especially in early winter), whereas Zhang-SITY and IFREMER-SITY tend to underestimate MYI. C3S-SITY performs well in some early winter cases but exhibits large temporal variabilities like OSISAF-SITY. Factors that could impact performances of the SITY products are analysed and summarized. (1) The Ku-band scatterometer generally performs better than the C-band scatterometer for SITY discrimination, while the latter sometimes identifies FYI more accurately, especially when surface scattering dominates the backscatter signature. (2) A simple combination of scatterometer and radiometer data is not always beneficial without further rules of priority. (3) The representativeness of training data and efficiency of classification are crucial for SITY classification. Spatial and temporal variation in characteristic training datasets should be well accounted for in the SITY method. (4) Post-processing corrections play important roles and should be considered with caution.</p

A new tracking algorithm for sea ice age distribution estimation

A new algorithm for estimating sea ice age (SIA) distribution based on the Eulerian advection scheme is presented. The advection scheme accounts for the observed divergence or convergence and freezing or melting of sea ice and predicts consequent generation or loss of new ice. The algorithm uses daily gridded sea ice drift and sea ice concentration products from the Ocean and Sea Ice Satellite Application Facility. The major advantage of the new algorithm is the ability to generate individual ice age fractions in each pixel of the output product or, in other words, to provide a frequency distribution of the ice age allowing to apply mean, median, weighted average or other statistical measures. Comparison with the National Snow and Ice Data Center SIA product revealed several improvements of the new SIA maps and time series. First, the application of the Eulerian scheme provides smooth distribution of the ice age parameters and prevents product undersampling which may occur when a Lagrangian tracking approach is used. Second, utilization of the new sea ice drift product void of artifacts from EUMETSAT OSI SAF resulted in more accurate and reliable spatial distribution of ice age fractions. Third, constraining SIA computations by the observed sea ice concentration expectedly led to considerable reduction of multi-year ice (MYI) fractions. MYI concentration is computed as a sum of all MYI fractions and compares well to the MYI products based on passive and active microwave and SAR products

Thin ice and storms: Sea ice deformation from buoy arrays deployed during N-ICE2015

Arctic sea ice has displayed significant thinning as well as an increase in drift speed in recent years. Taken together this suggests an associated rise in sea ice deformation rate. A winter and spring expedition to the sea ice covered region north of Svalbard – the Norwegian young sea ICE 2015 expedition (N-ICE2015) - gave an opportunity to deploy extensive buoy arrays and to monitor the deformation of the first- and second-year ice now common in the majority of the Arctic Basin. During the 5-month long expedition, the ice cover underwent several strong deformation events, including a powerful storm in early February that damaged the ice cover irreversibly. The values of total deformation measured during N-ICE2015 exceed previously measured values in the Arctic Basin at similar scales: At 100 km scale, N-ICE2015 values averaged above 0.1, day−1, compared to rates of 0.08 day −1 or less for previous buoy arrays. The exponent of the power law between the deformation length scale and total deformation developed over the season from 0.37 to 0.54 with an abrupt increase immediately after the early February storm, indicating a weakened ice cover with more free drift of the sea ice floes. Our results point to a general increase in deformation associated with the younger and thinner Arctic sea ice and to a potentially destructive role of winter storms

Satellite Observations for Detecting and Forecasting Sea-Ice Conditions: A Summary of Advances Made in the SPICES Project by the EU’s Horizon 2020 Programme

The detection, monitoring, and forecasting of sea-ice conditions, including their extremes, is very important for ship navigation and offshore activities, and for monitoring of sea-ice processes and trends. We summarize here recent advances in the monitoring of sea-ice conditions and their extremes from satellite data as well as the development of sea-ice seasonal forecasting capabilities. Our results are the outcome of the three-year (2015–2018) SPICES (Space-borne Observations for Detecting and Forecasting Sea-Ice Cover Extremes) project funded by the EU’s Horizon 2020 programme. New SPICES sea-ice products include pancake ice thickness and degree of ice ridging based on synthetic aperture radar imagery, Arctic sea-ice volume and export derived from multisensor satellite data, and melt pond fraction and sea-ice concentration using Soil Moisture and Ocean Salinity (SMOS) radiometer data. Forecasts of July sea-ice conditions from initial conditions in May showed substantial improvement in some Arctic regions after adding sea-ice thickness (SIT) data to the model initialization. The SIT initialization also improved seasonal forecasts for years with extremely low summer sea-ice extent. New SPICES sea-ice products have a demonstrable level of maturity, and with a reasonable amount of further work they can be integrated into various operational sea-ice services.</jats:p

Utilisation d'un radar UHF RASS pour l'étude de la couche limite atmosphérique en vue d'une application à la pollution atmosphérique

TOULOUSE3-BU Sciences (315552104) / SudocTOULOUSE-Observ. Midi Pyréné (315552299) / SudocSudocFranceF

Iceberg detection in open water by altimeter waveform analysis.

International audienceSmall icebergs (edge lengths <1 km) are difficult to detect and track. In a recently published study, it was demonstrated that small targets (ships, islets,...) emerging from the sea can be detected by the analysis of high-rate altimeter waveforms. The analysis of Jason altimeter data revealed that small icebergs also have a detectable signature in the thermal noise part of the altimeter waveforms for open water. These signatures are very similar to that of transponders and are almost deterministic. An automated method based on the detection of parabolic shapes in the thermal part of the waveforms by analysis of the convolution product with a filter has been developed and applied to 1 year of Jason high-rate waveform data. In addition, the minimum height and backscatter of the iceberg can also be estimated by this method. More than 8000 icebergs were identified between December 2004 and November 2005 in the open water around Antarctica. The annual distribution of icebergs presents a well-defined tripole structure, with maxima near the Antarctic Peninsula, the West Ice Shelf, and the Ross Sea. This distribution is in good agreement with the main trends in Antarctic iceberg motion presented in the scientific literature. The high concentration of icebergs propagating from the Antarctic Peninsula seems to confirm the importance of this region in the discharge of Antarctic ice into the ocean. The results clearly show that altimeter data are a powerful tool in the study of the distribution of small icebergs largely inaccessible by other satellite means. The principle of detection of icebergs by altimeter is quite simple and could be easily applied to the existing archive of all the past and present altimeters (ERS, Topex/Poseidon, Jason, and Envisat) to create a database covering more than 13 years that could improve our knowledge of climate change in Antarctica

Floe Size Effect on Wave-Ice Interactions: Possible Effects, Implementation in Wave Model, and Evaluation

Wind waves may play an important role in the evolution of sea ice. That role is largely determined by how fast the ice layer dissipates the wave energy. The transition from a continuous layer of ice to a series of broken floes is expected to have a strong impact on the several attenuation processes. Here we explore the possible effects of basal friction, scattering, and dissipation within the ice layer. The ice is treated as a single layer that can be fractured in many floes. Dissipation associated with ice flexure is evaluated using an anelastic linear dissipation and a cubic inelastic viscous dissipation. Tests aiming to reproduce a Marginal Ice Zone are used to discuss the effects of each process separately. Attenuation is exponential for friction and scattering. Scattering produces an increase in the wave height near the ice edge and broadens the wave directional spectrum, especially for short-period waves. The nonlinear inelastic dissipation is larger for larger wave heights as long as the ice is not broken. These effects are combined in a realistic simulation of an ice break-up event observed south of Svalbard in 2010. The recorded rapid shift from a strong attenuation to little attenuation when the ice is broken is only reproduced when using a nonlinear dissipation that vanishes when the ice is broken. A preliminary pan-Arctic test of these different parameterizations suggests that inelastic dissipation alone is not enough and requires its combination with basal friction

Antarctic icebergs distributions 1992-2014

Basal melting of floating ice shelves and iceberg calving constitute the two almost equal paths of freshwater flux between the Antarctic ice cap and the Southern Ocean. The largest icebergs (>100 km2) transport most of the ice volume but their basal melting is small compared to their breaking into smaller icebergs that constitute thus the major vector of freshwater. The archives of nine altimeters have been processed to create a database of small icebergs (<8 km2) within open water containing the positions, sizes, and volumes spanning the 1992–2014 period. The intercalibrated monthly ice volumes from the different altimeters have been merged in a homogeneous 23 year climatology. The iceberg size distribution, covering the 0.1–10,000 km2 range, estimated by combining small and large icebergs size measurements follows well a power law of slope −1.52 ± 0.32 close to the −3/2 laws observed and modeled for brittle fragmentation. The global volume of ice and its distribution between the ocean basins present a very strong interannual variability only partially explained by the number of large icebergs. Indeed, vast zones of the Southern Ocean free of large icebergs are largely populated by small iceberg drifting over thousands of kilometers. The correlation between the global small and large icebergs volumes shows that small icebergs are mainly generated by large ones breaking. Drifting and trapping by sea ice can transport small icebergs for long period and distances. Small icebergs act as an ice diffuse process along large icebergs trajectories while sea ice trapping acts as a buffer delaying melting

Large icebergs characteristics from altimeter waveforms analysis

Large uncertainties exist on the volume of ice transported by the Southern Ocean large icebergs, a key parameter for climate studies, because of the paucity of information, especially on iceberg thickness. Using icebergs tracks from the National Ice Center (NIC) and Brigham Young University (BYU) databases to select altimeter data over icebergs and a method of analysis of altimeter waveforms, a database of 5366 icebergs freeboard elevation, length, and backscatter covering the 2002–2012 period has been created. The database is analyzed in terms of distributions of freeboard, length, and backscatter showing differences as a function of the iceberg's quadrant of origin. The database allows to analyze the temporal evolution of icebergs and to estimate a melt rate of 35–39 m·yr−1 (neglecting the firn compaction). The total daily volume of ice, estimated by combining the NIC and altimeter sizes and the altimeter freeboards, regularly decreases from 2.2 104km3 in 2002 to 0.9 104km3 in 2012. During this decade, the total loss of ice ( inline image km3·yr−1) is twice as large as than the input ( inline image km3·yr−1) showing that the system is out of equilibrium after a very large input of ice between 1997 and 2002. Breaking into small icebergs represents 80% ( inline image km3·yr−1) of the total ice loss while basal melting is only 18% ( inline image km3·yr−1). Small icebergs are thus the major vector of freshwater input in the Southern Ocean

Dérive à la surface de l'océan sous l'effet des vagues

We model the drift velocity near the ocean surface separating the motion induced by the local current, itself influenced by winds and waves, and the motion induced by the waves, which are generated by local and remote winds. Application to the drift of ‘tar balls', following the sinking of the oil tanker Prestige-Nassau in November 2002, shows that waves contribute at least one third of the drift for pollutants floating 1 m below the surface, with a mean direction about 30° to the right of the wind-sea direction. Although not new, this result was previously obtained with specific models, whereas the formalism used here combines classical wave and circulation forecasting models