Evaluation of simulated sea-ice concentrations from sea-ice/ocean models using satellite data and polynya classification methods

Figures & data

Fig. 1.  Moderate Resolution Imaging Spectroradiometer channel 1 image of the Laptev Sea for 22 April 2008, 1055 UTC. The area enclosed by a black solid line denotes the Laptev Sea polynya mask (LAP). The polynyas can be seen as a dark narrow band along the landfast-ice edge (see Fig. 2). The black-dashed rectangle borders the core model domain of the two Finite Element Sea-Ice Ocean Model versions, FESOM-HR and FESOM-FI.

Fig. 2.  Landfast-ice masks derived from Moderate Resolution Imaging Spectroradiometer surface temperatures for December 2007 to April 2008. Contour lines show 25- and 30-m isobaths. Black-bordered areas show the different Laptev Sea polynya subsets: the north-eastern Taimyr polynya (NET), the Taimyr polynya (T), the Anabar–Lena polynya (AL) and the western New Siberian polynya (WNS).

Table 1. Specifications of the data sets used in this study: two versions of the North Atlantic–Arctic Ocean–Sea-Ice Model (NAOSIM and NAOSIM-FI); three versions of the Finite Element Sea-Ice Ocean Model (FESOM, FESOM-CR and FESOM-FI); the Advanced Microwave Scanning Radiometer–Earth Observing System (AMSR-E) satellite data and the Polynya Signature Simulation Method (PSSM) data.

	NAOSIM		FESOM
	Without landfast ice (NAOSIM)	With landfast ice (NAOSIM-FI)	Without landfast ice, coarse resolution (FESOM-CR)	Without landfast ice, high resolution (FESOM-HR)	With landfast ice, high resolution (FESOM-FI)	AMSR-E	PSSM
Spatial resolution	1/12°	1/12°	1/4°	1/20°	1/20°	6.25×6.25 km^2	6.25×6.25 km^2
Temporal resolution	Daily mean	Daily mean	Daily mean	Daily mean	Daily mean	Daily mean	Daily mean
Period	1 Nov 2007–11 May 2008	1 Nov 2007–11 May 2008	1 Nov 2007–11 May 2008	1 April 2008–11 May 2008	1 April 2008–11 May 2008	1 Nov 2007–11 May 2008	1 Nov 2007–11 May 2008
Forcing data	Name	NCEP^a	NCEP	NCEP	GME^b	GME
	Spatial res.	1.875°	1.875°	1.875°	0.5°	0.5°
	Temp. res.	Daily	Daily	Daily	6 hourly	6 hourly

^aUS National Centers for Environmental Prediction.

^bGlobal Model Extended.

Fig. 3.  Time series of open-water areas (OWA) for the whole polynya system (LAP) and the individual Laptev Sea sub-polynyas (see Fig. 2). Open-water areas are calculated from ice concentrations of: (a) the North Atlantic–Arctic Ocean–Sea-Ice Model (OWA_NAOSIM) and another version of this model, the NAOSIM-FI (OWA_NAOSIM-FI) from 1 November 2007 to 11 May 2008 and (b) the coarse-resolution version of the Finite Element Sea-Ice Ocean Model (OWA_FESOM-CR) from 1 November 2007 to 11 May 2008 and two other versions of the FESOM model, FESOM-HR (OWA_FESOM-HR) and FESOM-FI (OWA_FESOM-FI) from 1 April to 11 May 2008. Open-water areas derived from Advanced Microwave Scanning Radiometer–Earth Observing System (AMSR-E) data (OWA_AMSR-E) are shown in (a) and (b). Vertical lines mark polynya events.

Table 2. Mean, standard deviation (SD) and correlation coefficients (r) of the different open-water area (OWA) time series for all polynya subsets for the period from 1 November 2007 to 11 May 2008 and 1 April to 11 May 2008. Mean and SD of open-water area of (a) the Advanced Microwave Scanning Radiometer-Earth Observing System (AMSR-E), (b) the two versions of the North Atlantic–Arctic Ocean–Sea-Ice Model (NAOSIM and NAOSIM-FI) and (c) the three versions of the Finite Element Sea-Ice Ocean Model (FESOM-CR, FESOM-HR and FESOM-FI). Correlation coefficients between results derived from AMSR-E and NAOSIM/NAOSIM-FI are presented in (b). AMSR-E and FESOM-CR/FESOM-HR/FESOM-FI correlations are presented in (c). Correlations significant at the 95% confidence level (t-test) are in boldface.

(a) Remote sensing data set		(b) NAOSIM		(c) FESOM
Nov–May		Nov–May		Nov–May	Apr–May
	OWAAMSR-E	OWANAOSIM	OWANAOSIM-FI	OWAFESOM-CR	OWAAMSR-E	OWAFESOM-CR	OWAFESOM-HR	OWAFESOM-FI
Sum of all polynya regions (LAP)
Mean (km^2)	3105	6940	7054	7205	6651	5471	5058	7552
SD (km^2)	3578	4168	4272	7670	5244	3550	1779	3276
r		0.14	0.02	0.17		0.70	0.46	0.63
Western New Siberian polynya (WNS)
Mean (km^2)	1431	2365	2954	2107	3619	1719	3280	4631
SD (km^2)	2298	1746	2343	3479	3978	1319	862	2580
r		0.13	0.06	0.12		0.87	0.62	0.69
Anabar–Lena polynya (AL)
Mean (km^2)	941	2256	1473	1584	1979	1085	706	1270
SD (km^2)	1248	2004	1916	2345	1727	810	561	1084
r		0.08	−0.06	0.14		0.49	0.63	0.68
Taimyr polynya (T)
Mean (km^2)	157	691	806	1603	207	978	322	384
SD (km^2)	243	558	828	1391	298	1008	482	478
r		0.29	0.22	0.33		0.32	0.63	0.74
North-eastern Taimyr polynya (NET)
Mean (km^2)	576	1628	1821	1911	848	1688	749	1268
SD (km^2)	896	1090	1298	1457	1267	1683	1026	1670
R		0.22	0.13	0.55		0.86	0.81	0.71

Fig. 4.  Time series of polynya areas (POLA) for winter season 2007/08 in the WNS (eastern Laptev Sea) and NET (western Laptev Sea) polynyas (see Fig. 2). Polynya areas are calculated from ice concentrations of (a) the North Atlantic–Arctic Ocean–Sea-Ice Model (POLA_NAOSIM) and another version of this model, the NAOSIM-FI (POLA_NAOSIM-FI) from 1 November 2007 to 11 May 2008 and (b) the coarse-resolution Finite Element Sea-Ice Ocean Model (POLA_FESOM-CR) from 1 November 2007 to 11 May 2008 and two other versions of the FESOM model, FESOM-HR (POLA_FESOM-HR) and FESOM-FI (POLA_FESOM-FI) from 1 April to 11 May 2008. Polynya areas derived from Advanced Microwave Scanning Radiometer–Earth Observing System (AMSR-E) data (POLA_AMSR-E) and the Polynya Signature Simulation Method (POLA_PSSM) are shown in (a) and (b). After day 319 (vertical line) FESOM-CR shows no polynya area. The vertical line at day 99 marks an overestimation of FESOM-FI open-water area. Vertical line at day 121 in WNS marks a polynya event.

Table 3. Mean, standard deviation (SD) and correlation coefficients (r) of the different polynya area (POLA) time series for the western New Siberian polynya (WNS) and north-eastern Taimyr polynya (NET) for the period from 1 November 2007 to 11 May 2008 and 1 April to 11 May 2008. Mean and SD of polynya area of (a) the Advanced Microwave Scanning Radiometer-Earth Observing System (AMSR-E) and the Polynya Signature Simulation Method (PSSM), (b) the two versions of the North Atlantic–Arctic Ocean–Sea-Ice Model (NAOSIM and NAOSIM-FI) and (c) the three versions of the Finite Element Sea-Ice Ocean Model (FESOM-CR, FESOM-HR and FESOM-FI). Correlation coefficients between results derived from AMSR-E and PSSM are presented in (a). AMSR-E and NAOSIM/NAOSIM-FI correlation are presented in (b). AMSR-E and FESOM-CR/FESOM-HR/FESOM-FI correlation are presented in (c). Correlations significant at the 95% confidence level (t-test) are in boldface.

(a) Remote sensing data sets			(b) NAOSIM		(c) FESOM
Nov–May			Nov–May		Nov–May	Apr–May
	POLAAMSR-E	POLAPSSM	POLANAOSIM	POLANAOSIM-FI	POLAFESOM-CR	POLAAMSR-E	POLAFESOM-CR	POLAFESOM-HR	POLAFESOM-FI
Western New Siberian polynya (WNS)
Mean (km^2)	1065	806	632	1553	521	3529	0	837	3128
SD (km^2)	2592	2147	689	2135	3628	4722	0	852	3071
R		0.99	0.07	0.10	0.00		0.00	0.59	0.60
North-eastern Taimyr polynya (NET)
Mean (km^2)	471	364	870	1322	717	958	821	320	1092
SD (km^2)	1028	845	1291	1708	1630	1556	1939	689	2086
R		0.98	−0.02	0.10	0.43		0.79	0.68	0.56

Fig. 5.  Maps of sea-ice concentration (SIC) on 29 April 2008 derived from (a) Advanced Microwave Scanning Radiometer–Earth Observing System (AMSR-E) data, (b) the North Atlantic–Arctic Ocean–Sea-Ice Model (NAOSIM) and (c) another version of this model, NAOSIM-FI. In (a) and (b) yellow–green features denote the polynyas, light orange features indicate leads. Plots showing the difference that results when (d) NAOSIM and (e) NAOSIM-FI simulations are subtracted from the AMSR-E sea-ice concentration.

Fig. 6.  Maps of sea-ice concentration (SIC) on 29 April 2008 derived from (a) the coarse-resolution Finite Element Sea-Ice Ocean Model (FESOM-CR); and two other versions of this model, (b) FESOM-HR and (c) FESOM-FI. Plots showing the difference that results when (d) FESOM-CR, (e) FESOM-HR and (f) FESOM-FI simulations are subtracted from the AMSR-E sea-ice concentration (compare to Fig. 5a).

Fig. 7.  Sea-ice concentrations derived from the NAOSIM-FI version of the North Atlantic–Arctic Ocean–Sea-Ice Model are examined in terms of the occurrence of leads. The criterion is the 70% sea-ice concentration threshold that is also used for the classification of polynyas and includes open water and thin ice up to 0.2-m thickness (Willmes et al. 2010). Pixels with a sea-ice concentration below 70% are counted from 1 December 2007 to 11 May 2008. The map shows the frequency (%) of these pixels in the period in question. The darker grey areas along the fast-ice edge indicate polynyas. The lighter grey areas indicate simulated leads not attached to the fast-ice edge but located in the defined polynya regions. Black boxes indicate the polynya regions (see Fig. 2).

Table 4. Comparison of sea-ice concentrations (SIC) and polynya features simulated by the five different model runs: two versions of the North Atlantic–Arctic Ocean–Sea-Ice Model (NAOSIM) and three versions of the Finite Element Sea-Ice Ocean Model (FESOM).

Feature	NAOSIM	NAOSIM with landfast ice (NAOSIM-FI)	FESOM without landfast ice, coarse resolution (FESOM-CR)	FESOM without landfast ice, high resolution (FESOM-HR)	FESOM with landfast ice, high resolution (FESOM-FI)
SIC in general	Generally underestimated	Generally underestimated	Generally underestimated	Except for polynya regions: good agreement	Good agreement
Polynya location	Dislocation, located at the coastline	Realistic location at the landfast-ice edge	Dislocation, located at the coastline	Dislocation, located at the coastline	Realistic location at the landfast-ice edge
Polynya shape	Follows the coastline	In general good, small differences	Large areas with slightly reduced SIC, no well-formed polynya	Depends on coastline, no agreement with AMSR-E	Accurate
SIC in polynya	Uniformly distributed, lowest SIC are not reproduced	Uniformly distributed, lowest SIC are not reproduced	No well-formed polynya, slightly reduced SIC over a large area	Small-scale gradients, lowest SIC are reproduced	Small-scale gradients, lowest SIC are reproduced

Willmes S. Krumpen T. Adams S. Rabenstein L. Haas C. Hoelemann J. Hendricks S. Heinemann G. Cross-validation of polynya monitoring methods from multi-sensor satellite and airborne data: a case study. Canadian Journal of Remote Sensing. 2010; 36: 196–210.

 Web of Science ®Google Scholar