Last modified on May 20, 2024 12:08

Contributors: S. B. Simonsen (Technical University of Denmark)

Issued by: Technical University of Denmark / S. B. Simonsen

Date: 18/04/2024

Ref: C3S2_312a_Lot4.WP2-FDDP-IS-v2_202312_SEC_PQAR-v5_i1.2

Official reference number service contract: 2021/C3S_312a_Lot4_EODC/SC1

History of modifications

List of datasets covered by this document

Related documents

Acronyms

General definitions

Backscatter: The portion of the outgoing radar signal that the target redirects directly back toward the radar antenna.

Baseline: A combination of processor versions, auxiliary data, and other needed enablers that allows the generation of a coherent set of Earth observation products. 

Bias: The tendency of an instrument to preferentially make measurements over a certain type of surface.

Climate Data Record (CDR): A time series of measurements of sufficient length, consistency, and continuity to determine climate variability and change.

Crossover analysis: A method for deriving elevation change at locations where the orbits of a single or multiple satellites cross.

Cross-calibration: A method that merges datasets from multiple satellites into one consistent dataset. 

Key performance indicator: A quantifiable measure used to evaluate the success of a product in meeting its performance objectives.

Laser altimeter: An instrument mounted on an aircraft or spacecraft that measures altitude from the ground surface below by timing how long it takes a pulse of laser light to travel to ground, reflect, and return to the craft.

Outlier-resistant: In mathematical model fitting, outlier-resistant (or 'robust') methods exclude spurious measurements from the dataset during the modelling process.

Radar altimeter: An instrument mounted on an aircraft or spacecraft that measures altitude from the ground surface below by timing how long it takes a pulse of radio waves to travel to ground, reflect, and return to the craft.

Stability: An estimate of the consistency of the measurements over time.

Surface Elevation Change (SEC): The surface elevation of a point on an ice sheet is the height of the ice sheet surface above a reference geoid (a hypothetical solid figure whose surface corresponds to mean sea level and its imagined extension under land areas). An increase in surface elevation over time at a given location indicates a gain of ice or snow at that location, and conversely decrease indicates a loss. The surface elevation change product provides the rate of change given at monthly intervals at each location on a grid covering the ice sheet. The definition of the grid projection includes the geoid used. Given the rates of change, absolute change can be calculated for any period of time. 

Tracking: Retrieving the radar echo from a given radar pulse.

Uncertainty: An estimate of the error in a measurement, due to limitations in the measuring instrument or statistical fluctuations in the quantity being measured.

Validation: Comparison between two independent datasets to test their agreement.

Scope of the document

This document is the Product Quality Assessment Report (PQAR) for the Copernicus Ice Sheets and Ice Shelves Service Surface Elevation Change (SEC) essential climate variable (ECV). The latest version, Version 5.0, includes updates solely for the Greenland data product, while the production of Antarctic data has been temporarily halted. We refer the reader to PQAR version 4.0 [D4] for a description of the Antarctic SEC, also hosted at the Copernicus Climate Data Store. This document presents the results of the quality assessment for the provided Antarctic and Greenland datasets and a discussion of how well the Global Climate Observing System (GCOS) and user requirements have been met.

The products are hosted on the Copernicus Climate Data Store at https://cds.climate.copernicus.eu/cdsapp#!/dataset/satellite-ice-sheet-elevation-change?tab=overview¹

Executive summary

In this document, we provide the validation results from the Climate Data Record (CDR) v5.0 for the surface elevation change datasets produced by the Copernicus Ice Sheets and Ice Shelves service. For v4.0, we validated only against data from National Aeronautics and Space Administration (NASA)'s Operation IceBridge and ICESat-2 mission, and we repeat that validation here and compare the results from the two versions. 

In section 1 we briefly describe the external datasets used in the validation, list the target requirements we aim to fulfill, and describe the CDR parameters that relate to those targets.

In section 2 we give the validation results and discuss differences seen between the v5.0 and v4.0 products. 

In section 3 we describe the application-specific requirements for the Greenland SEC product.

In section 4 we summarise how well the product achieves the target requirements. 

1. Product validation methodology

1.1. Validation data

Before turning to the methodology of model validation, the two external validation datasets are presented.

1.1.1. Operation IceBridge Airborne Topographic Mapper

The Airborne Topographic Mapper (ATM) is a scanning laser altimeter flown on board aircraft by NASA Operation IceBridge (OIB) (Studinger 2014). The ATM instrument has been flown in Greenland since 1993, and within the OIB data package are estimates of surface change from all repeat measurements of surface elevation done by OIB. At time of writing, SEC data is only available up to 2018, i.e. it is unchanged since the v3.0 validation. For further details see the related Product Quality Assurance Document [RD2] where both the IceBridge dataset and the validation methodology are described in detail.

1.1.2. ICESat-2 ATL15

The ICESat-2 ATL15² (Smith 2021a) data product is a gridded surface height change product over land ice. This dataset is derived from the Advanced Topographic Laser Altimeter System (ATLAS) aboard the NASA's ICESat-2 satellite. ATL15 is derived from the higher-order data product of collocated height measurements provided by ATL11 (Smith 2021b). In the following validations, the data subset "dhdt_lag8"³  is used, which provides biennial height-change-rate estimates in the period late-2019 to mid-2020.

1.2. Surface elevation change, Greenland

The Greenland surface elevation changes are validated against data provided by OIB ATM first. This higher-level product (level-4) has been downloaded from National Snow and Ice Data Center (NSIDC⁴) For the validation of the surface elevation change (SEC), we use the monthly dh estimates to derive the cumulative surface elevation change (dh/dt), thereby reproducing the temporal span in-between repeat observations by the OIB ATM. As the OIB data are usually obtained once a year (in spring), we summarize the mean and standard deviation of the difference in SEC between OIB and C3S SEC here. This mean and standard deviation of the estimated difference is ascribed to the year of the first ATM observation.

Secondly, a validation effort is conducted against ICESat-2 ATL15 data. The ATL15 product provided 2-year averaged surface elevation changes at 20 km grid posting. In line with the above presented ATM validation, we derive cumulative surface elevation change (DH/dt) from the C3S SEC at the same time span as the 2-year averaging in the ATL15 product. The ALT15 data is further regridded to the 25 km grid posting of the C3S CDR SEC product.  

As well as validation against external data, to comply with user requirements gathered by GCOS, the product should achieve two statistical targets. Moreover, the C3S project has identified two Key Performance Indicators (KPIs), as shown in Table 1.1. The Greenland surface elevation change uses the KPIs outlined in Table 1.1, except for the surface coverage which is obsolete due to the more optimal location of the Greenland ice sheet in relation to the satellite obits and differences in postprocessing interpolation. More details on the target requirements for the SEC product are discussed in the Target Requirements and Gap Analysis Document (TRGAD) [RD3]

Table 1.1: Greenland surface elevation change product targets. 

Here, the stability is taken as one standard deviation of the linear model fit to the surface elevation change time series used in deriving the surface elevation change rate whereas the accuracy is the total error budget for the surface elevation change rate. This, along with a more detailed discussion of the uncertainty processing is discussed in the Algorithm Theoretical Basis Document [RD1].

2.  Validation results

Figure 2.1 illustrates the results of the OIB ATM intercomparison, incorporating all available Greenland OIB elevation change data from the NSIDC as of November 2023. The right panel of the figure displays the geolocated differences between OIB and C3S observations, presenting a point-to-point intercomparison and the distribution of these differences.

Validation against ICESat-2 ATL15 was conducted for the specified time periods detailed in Table 2.2 and Figure 2.2. The analysis revealed an anticipated bias between the lidar observation (ATL15) and the radar, attributed to differences in scattering horizons, consistent with findings in existing literature (Simonsen and Sørensen 2017).

In the updated Version 5, a noticeable enhancement in standard deviation is observed compared to Version 4 in the validation against ICESat-2. Additionally, there is a slight improvement in the median difference between CDR_v5 and OIB, reducing it to 1.81 cm/yr when compared to CDR_v4 and OIB. This improvement signifies a reduction in the variability and uncertainty in the data, implying a more robust and reliable dataset for land ice.

Figure 2.1:  (Panel a) The point-to-point correlations between the C3S-surface elevation change and the OIB surface elevation estimate. (Panel b) The histogram of the point-to-point differences between C3S and OIB surface elevation change. The left panels also show the old version of the CDR (v4) for reference. (Panel c) The spatial distribution of the point-to-point inter-comparison with the OIB ATM surface elevation estimates.

Table 2.2: Results of ICESat-2 ATL15 validation

Figure 2.2: Validation against ICESat-2 ALT15 average elevation change from July 2019 to July 2021.

Additionally, Figure 2.3 shows the statistics from the internal-fitting accuracy.

Figure 2.3: The stability in the linear model fit to the surface elevation change time series used in deriving the surface elevation change rate. For reference, the C3S v4 estimate is also included. As seen, the new CDR (v5) fulfills the GCOS requirements (accuracy in the left panel) and the fitting stability (right panel)

3. Application(s) specific assessments

The user should note that the applied satellite data originate from a nadir-looking altimeter, hence no direct observations of SEC are available between satellite tracks. To compensate for this, we use ordinary kriging to interpolate data. However, the final solution may still exhibit some "stripiness due to slight differences in observational periods." Nevertheless, by employing ordinary kriging, we incorporate the distance to the nearest observational point into the error estimate, accounting for the stripiness in the final SEC estimate. This approach enhances users' ability to contextualize and utilize SEC data in their specific applications.

4. Compliance with user requirements

The uncertainty given in the product is derived from the combination of the epoch (derived from the supplied input data) and the model (derived from the plane-fitting) uncertainties. All the analysis and evaluation process is shown in the three figures presented in section 2.2 (Figure 2.1 to Figure 2.3).

The number of points with an accuracy within the GCOS requirements is 99.9%. This estimate is purely an internal stability indication and not a real error estimate, as multiple factors are not included in this estimate. Factors such as changes in the penetration depth of the radar, slope-induced relocation errors, and the fact that the radar only observes changes at the highest point within its footprint, may bias the elevation change estimate.

Therefore, the real error estimate and the number needed to fulfill the user-requirements needs are to be found by applying independent validation of the surface elevation change product. Here, the independent validation is provided by comparison to NASA's OIB airborne laser altimetry campaigns and ICESat-2 ATL15. Figure 2.6 shows the result of the inter-comparison between the OIB and C3S-Greenland SEC, with a mean bias of all observations of -1.81 cm per year. Therefore, the current processing version fulfills the GCOS requirement (given in Table 1.1). This is further confirmed with the new ICESat-2 data all showing similar biases.

References

ESA Mission Management, Copernicus S3 Product Notice – Altimetry, July 2022, available at https://sentinel.esa.int/documents/247904/2753172/Sentinel-3-Product-Notice-LAND-L1-L2-NRT-STC-NTC.pdf (URL resource last viewed 11^th December 2023)

Global Climate Observing System (2016). The Global Observing System for Climate: Implementation Needs, GCOS-200, available at https://gcos.wmo.int/index.php/en/publications/gcos-implementation-plan2016 (URL resource last viewed 11^th December 2023)

Simonsen, Sebastian B., and Louise Sandberg Sørensen. (2017). Implications of Changing Scattering Properties on Greenland Ice Sheet Volume Change from Cryosat-2 Altimetry. Remote Sensing of Environment. https://doi.org/10.1016/j.rse.2016.12.012 (URL resource last viewed 11^th December 2023)

Smith, B., B. P. Jelley, S. Dickinson, T. Sutterley, T. A. Neumann, K. Harbeck. (2021a). ATLAS/ICESat-2 L3B Gridded Antarctic and Arctic Land Ice Height Change, Version 1. Boulder, Colorado USA. NASA National Snow and Ice Data Center Distributed Active Archive Center. https://doi.org/10.5067/ATLAS/ATL15.001 (URL resource last viewed 11^th December 2023)

Smith, B. (2021b). ICESat-2 Algorithm Theoretical Basis Document for Land Ice DEM and Land Ice Height Change Release 001 Algorithm Theoretical Basis Document (ATBD) for Land-ice DEM (ATL14) and Land-ice height change (ATL15). https://icesat-2.gsfc.nasa.gov/sites/default/files/page_files/ICESat2_ATL14_ATL15_ATBD_r001.pdf (URL resource last viewed 11^th December 2023)

Studinger, M. (2014). IceBridge ATM L4 Surface Elevation Rate of Change, Version 299 1, Antarctica subset. N. S. a. I. D. C. D. A. A. Center. Boulder, Colorado, USA. DOI: 10.5067/BCW6CI3TXOCY

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