Spatial and temporal multiyear sea ice distributions in the Arctic: A neural network analysis of SSM/I data, 1988-2001

被引:20
作者
Belchansky, GI
Douglas, DC
Alpatsky, IV
Platonov, NG
机构
[1] Russian Acad Sci, Inst Ecol, Space Monitoring & Ecoinformat Syst Sector, Moscow 119071, Russia
[2] US Geol Survey, Alaska Sci Ctr, Juneau Field Stn, Juneau, AK 99801 USA
关键词
SSM/I; ERS; Okean; passive microwave; multiyear; sea ice;
D O I
10.1029/2004JC002388
中图分类号
P7 [海洋学];
学科分类号
0707 ;
摘要
[1] Arctic multiyear sea ice concentration maps for January 1988 - 2001 were generated from SSM/I brightness temperatures (19H, 19V, and 37V) using modified multiple layer perceptron neural networks. Learning data for the neural networks were extracted from ice maps derived from Okean and ERS satellite imagery to capitalize on the stability of active radar multiyear ice signatures. Evaluations of three learning algorithms and several topologies indicated that networks constructed with error back propagation learning and 3-20-1 topology produced the most consistent and physically plausible results. Operational neural networks were developed specifically with January learning data, and then used to estimate daily multiyear ice concentrations from daily-averaged SSM/I brightness temperatures during January. Monthly mean maps were produced for analysis by averaging the respective daily estimates. The 14-year series of January multiyear ice distributions revealed dense and persistent cover in the central Arctic surrounded by expansive regions of highly fluctuating interannual cover. Estimates of total multiyear ice area by the neural network were intermediate to those of other passive microwave algorithms, but annual fluctuations and trends were similar among all algorithms. When compared to Radarsat estimates of multiyear ice concentration in the Beaufort and Chukchi Seas ( 1997 - 1999), average discrepancies were small (0.9 - 2.5%) and spatial coherency was reasonable, indicating the neural network's Okean and ERS learning data facilitated passive microwave inversion that emulated backscatter signatures. During 1988 - 2001, total January multiyear ice area declined at a significant linear rate of - 54.3 x 10(3) km(2) yr(-1) (- 1.4% yr(-1)). The most persistent and extensive decline in multiyear ice concentration (-3.3% yr(-1)) occurred in the southern Beaufort and Chukchi Seas. In autumn 1996, a large multiyear ice recruitment of over 10 6 km 2 ( mostly in the Siberian Arctic) fully replenished the previous 8-year decline in total area, but it was followed by an accelerated and compensatory decline during the subsequent 4 years. Seventy-five percent of the interannual variation in January multiyear sea ice area was explained by linear regression on two atmospheric parameters: the previous winter's (JFM) Arctic Oscillation index as a proxy to melt duration and the previous year's average sea level pressure gradient across the Fram Strait as a proxy to annual ice export. Consecutive year changes ( 1994 - 2001) in January multiyear ice volume were significantly correlated with duration of the intervening melt season (R-2 = 0.73, -80.0 km(3) d(-1)), emphasizing a large thermodynamic influence on the Arctic's mass sea ice balance during summers with anomalous melt durations.
引用
收藏
页码:C100171 / 17
页数:17
相关论文
共 130 条
[1]   Some thoughts on the freezing and melting of sea ice and their effects on the ocean [J].
Aagaard, K. ;
Woodgate, R. A. .
OCEAN MODELLING, 2001, 3 (1-2) :127-135
[2]   COMPARISON OF BRIGHTNESS TEMPERATURES FROM SSMI INSTRUMENTS ON THE DMSP F8 AND F11 SATELLITES FOR ANTARCTICA AND THE GREENLAND ICE-SHEET [J].
ABDALATI, W ;
STEFFEN, K ;
OTTO, C ;
JEZEK, KC .
INTERNATIONAL JOURNAL OF REMOTE SENSING, 1995, 16 (07) :1223-1229
[3]   SIMULTANEOUS WINTER SEA-ICE AND ATMOSPHERIC CIRCULATION ANOMALY PATTERNS [J].
AGNEW, T .
ATMOSPHERE-OCEAN, 1993, 31 (02) :259-280
[4]  
Alekseev GV, 2003, ARCTIC ENVIRONMENT VARIABILITY IN THE CONTEXT OF GLOBAL CHANGE, P107
[5]  
[Anonymous], 1 IEEE INT C NEUR NE
[6]   Simulation of the interannual variability of the wind-driven Arctic sea-ice cover during 1958-1998 [J].
Arfeuille, G ;
Mysak, LA ;
Tremblay, LB .
CLIMATE DYNAMICS, 2000, 16 (2-3) :107-121
[7]   A CLUSTERING TECHNIQUE FOR SUMMARIZING MULTIVARIATE DATA [J].
BALL, GH ;
HALL, DJ .
BEHAVIORAL SCIENCE, 1967, 12 (02) :153-&
[8]   The adverse neuro-developmental effects of postnatal steroids in the preterm infant: A systematic review of RCTs [J].
Barrington K.J. .
BMC Pediatrics, 1 (1)
[9]   THE ARCTIC SEA-ICE CLIMATE SYSTEM - OBSERVATIONS AND MODELING [J].
BARRY, RG ;
SERREZE, MC ;
MASLANIK, JA ;
PRELLER, RH .
REVIEWS OF GEOPHYSICS, 1993, 31 (04) :397-422
[10]   A Matrix Method for Optimizing a Neural Network [J].
Barton, Simon A. .
NEURAL COMPUTATION, 1991, 3 (03) :450-459