Sea Ice Remote Sensing—Recent Developments in Methods and Climate Data Sets

Abstract

Sea ice monitoring by polar orbiting satellites has been developed over more than four decades and is today one of the most well-established applications of space observations. This article gives an overview of data product development from the first sensors to the state-of-the-art regarding retrieval methods, new products and operational data sets serving climate monitoring as well as daily operational services including ice charting and forecasting. Passive microwave data has the longest history and represents the backbone of global ice monitoring with already more than four decades of consistent observations of ice concentration and extent. Time series of passive microwave data is the primary climate data set to document the sea ice decline in the Arctic. Scatterometer data is a valuable supplement to the passive microwave data, in particular to retrieve ice displacement and distinguish between firstyear and multiyear ice. Radar and laser altimeter data has become the main method to estimate sea ice thickness and thereby fill a gap in the observation of sea ice as an essential climate variable. Data on ice thickness allows estimation of ice volume and masses as well as improvement of the ice forecasts. The use of different altimetric frequencies also makes it possible to measure the depth of the snow covering the ice. Synthetic Aperture Radar (SAR) has become the work horse in operational ice observation on regional scale because high-resolution radar images are delivered year-round in nearly all regions where national ice services produce ice charts. Synthetic Aperture Radar data are also important for sea ice research because the data can be used to observe a number of sea ice processes and phenomena, like ice type development and sea ice dynamics, and thereby contribute to new knowledge about sea ice. The use of sea ice data products in modelling and forecasting services as well as in ice navigation is discussed. Finally, the article describes future plans for new satellites and sensors to be used in sea ice observation.

Multisensor data fusion of operational sea ice observations

“…The main focus here has been on the data fusion of operational sea ice observations (SIC, SIT, SIV, and their uncertainties), which are the most important for operational sea ice monitoring and predictions. It is straightforward to extend the present data sets to include more variables for climate studies, such as sea ice age, sea ice drift, melt pond fraction, and snow depth (Lavergne et al, 2022;Sandven et al, 2023). The MODF is also applicable for other environmental observations in order to form a consistent, multifaceted, and more robust and accurate description.…”

“…A comprehensive set of sea ice variables, such as SIC, SIT, SIV, sea ice drift, sea ice age, melt pond fraction, and sea ice surface albedo, would be valuable for climate analysis, simulation, evaluation, and prediction. There are emerging discussions on such needs (e.g., Lavergne et al, 2022;Sandven et al, 2023). The present framework can be naturally expanded with more variables, longer time scale, and larger spatial coverage, thus generating united, consistent, and multifaceted climate data sets.…”

“…Our main purpose here is to generate a united, consistent, and multifaceted daily sea ice observations for monitoring and prediction applications. Such a framework shall also be useful for the construction of consistent sea ice Essential Climate Variables (Lavergne et al, 2022;Sandven et al, 2023), which include more sea ice parameters.…”

Sea Ice Extent Retrieval Using CSCAT 12.5 km Sampling Data

“…These two sensors offer much higher resolution data than other radiometers due to their larger antenna reflector diameters. For AMSR2, the average resolution for each frequency channel is 49 km (6.93/7.3 GHz), 33 km (10.65 GHz), 18 km (18.7 GHz), 15 km (23 GHz), 10 km (36.5 GHz), and 4 km (89.0 GHz) [2]. As the frequency increases, the resolution also improves.…”

“…The objective of this study is twofold: (1) to investigate the sea ice extent retrieval on a 6.25 km grid using CSCAT 12.5 km sampling data; (2) to evaluate the different capabilities of two types of fan beam scatterometers (Ku-band rotating fan beam CSCAT and C-band fixed fan beam ASCAT) in sea ice detection. A comparison between the sea ice edge and extent on a grid size of 6.25 km of CSCAT and AMSR2 is therefore performed during their overlapping mission period (2020-2022).…”