Data access via download: https://doi.org/10.25592/uhhfdm.8559
Data access via file system: /data/icdc/ice_and_snow/uhh_seaiceareatimeseries/
The UHH sea-ice area product offered here contains time series of the monthly mean sea-ice area for both Polar regions. These time series are computed from the following publicly available gridded sea-ice concentration products: Walsh (v2), OSI-450 / OSI-430b, NASA-Team, Comiso-Bootstrap, HadISST (v2).
The sea-ice area in one hemisphere is the sum of the sea-ice areas of all grid cells of the respective hemisphere. The sea-ice area of each grid cell is the product of the grid cell area and the sea-ice concentration in that grid cell. The steps to compute the sea-ice area for the different products are specifically tailored to their content. These are based on Climate Data Operators (CDOs) and python/numpy and are described in the following.
Walsh: This data set contains monthly mean sea-ice concentration data used directly to compute the sea-ice area (SIA). We do not need to fill temporal or spatial data gaps. However, for the time period prior to the era of routine satellite observations of the polar regions (winter 1978/79) the sources (ship-, ground- and air-borne observations and reports) used to generate this data set contain many temporal and spatial gaps which were filled (see https://nsidc.org/sites/nsidc.org/files/G10010_V002.0_1.pdf).
OSI-450/OSI-430-b: First we compute the daily SIA from the daily sea-ice concentration data. We do not need to fill spatial data gaps. We fill temporal data gaps in the daily SIA time series of up to seven days duration by linear interpolation prior to the computation of the monthly mean SIA. For months containing temporal data gaps longer than seven days we do not compute the monthly mean SIA.
NASA-Team / Comiso-Bootstrap: Before computing the daily SIA from the daily sea-ice concentration data, we need to fill two types of spatial data gaps. One is the observation gap centered at the North Pole. This gap is filled with the mean daily sea-ice concentration computed from a ring around this gap. Other spatial gaps in the daily sea-ice concentration are filled by linear interpolation over time using values of the previous and the next day - provided that these data gaps cover less than 1000 non-contiguous grid cells. In case more grid cells are affected no daily SIA value is computed for the respective day. Subsquently, we compute the daily SIA from the gap-filled daily sea-ice concentration data. Gaps in the resulting daily SIA time series are treated similar to OSI-450/OSI-430-b before we compute the monthly SIA values. For months containing temporal data gaps longer than seven days we do not compute the monthly mean SIA.
HadISST: This data set contains monthly mean sea-ice concentration data used directly to compute the SIA. We do not need to fill temporal or spatial data gaps. Like the Walsh data set, the HadISST data set includes a substantial amount of data based on gap-filling methods and climatologies for the time period prior to the era of routine satellite observations. The HadISST data set utilizes a very conservative land-sea mask. In order to make HadISST SIA values more comparable to the other products, we interpolate the monthly HadISST sea-ice concentration data onto the NSIDC grid (used e.g. by NASA-Team / Comiso-Bootstrap) and provide an additional HadISST SIA time series for which we employ the NSIDC land-sea mask.
This data set was included into the data holding at ICDC on January 21 2021.
|Sea-ice area Walsh||10e6 km²||x|
|Sea-ice area HadISST original||10e6 km²||x||x|
|Sea-ice area HadISST NSIDC||10e6 km²||x||x|
|Sea-ice area NASA-Team||10e6 km²||x||x|
|Sea-ice area Comiso-Bootstrap||10e6 km²||x||x|
|Sea-ice area OSI-450/OSI-430-b||10e6 km²||x||x|
Period and temporal resolution:
- 1850-01 to 2019-12
Coverage and spatial resolution:
- Northern and Southern Hemisphere
- Spatial resolution: Northern and Southern Hemisphere
- Geographic longitude: 0°E to 360°E
- Geographic latitude: about 30°N and 30°S to 90°N and 90°S, respectively
- Dimensions: 2040 rows
- Altitude: 0.0 m
The data set does not contain an estimate of the uncertainty.
Jakob Doerr*, Dirk Notz**, Stefan Kern***
* Geophysical Institute / University of Bergen
** Institute of Oceanography / CEN / University of Hamburg
*** Integrated Climate Data Center / CEN / University of Hamburg
email: uhhsia.ifm (at) uni-hamburg.de
- Walsh, J. E., et al., 2017, A database for depicting Arctic sea ice variations back to 1850. Geographical Review, 107(1), 89-107.
- Titchner, H. A., and N. A. Rayner, 2014, The Met Office Hadley Centre sea ice and sea surface temperature data set, version 2: 1. Sea ice concentrations, J. Geophys. Res.-Atmospheres, 119, 2864-2889, https://doi.org/10.1002/2013JD020316.
- Lavergne, T., et al., 2019, Version 2 of the EUMETSAT OSI SAF and ESA CCI Sea Ice Concentration Climate Data Records, The Cryosphere, 13(1), 49-78, https://doi.org/10.5194/tc-2018-127
- Kern, S., et al., 2019, Satellite Passive Microwave Sea-Ice concentration data set inter-comparison: Closed ice and ship-based observations, The Cryosphere, 13(12), 3261-3307, https://doi.org/10.5194/tc-13-3261-2019.
- Kern, S., et al., 2020, Satellite passive microwave sea-ice concentration data set intercomparison for Arctic summer conditions, The Cryosphere, 14(7), 2469-2493, https://doi.org/10.5194/tc-14-2469-2020.