A study of arctic sea ice and sea‐level pressure using POP and neural network methods

1994 ◽  
Vol 32 (3) ◽  
pp. 507-529 ◽  
Author(s):  
Benyang Tang ◽  
Gregory M. Flato ◽  
Greg Holloway
2020 ◽  
Vol 14 (2) ◽  
pp. 693-708
Author(s):  
Xiao-Yi Yang ◽  
Guihua Wang ◽  
Noel Keenlyside

Abstract. After an unprecedented retreat, the total Arctic sea ice cover for the post-2007 period is characterized by low extent and a remarkable increase in annual cycle amplitude. We have identified the leading role of spring Bering Sea ice in explaining the changes in the amplitude of the annual cycle of total Arctic sea ice. In particular, these changes are related to the recent occurrence of multiyear variability in spring Bering Sea ice extent. This is due to the phase-locking of the North Pacific Gyre Oscillation (NPGO) and the Pacific Decadal Oscillation (PDO) after about 2007, with a correlation coefficient reaching −0.6. Furthermore, there emerge notable changes in the sea level pressure and sea surface temperature patterns associated with the NPGO in the recent decade. After 2007, the NPGO is related to a quadrupole of sea level pressure (SLP) anomalies that is associated with the wind stress curl and Ekman pumping rate anomalies in the Bering deep basin; these account for the change in Bering Sea subsurface variability that contribute to the decadal oscillation of the spring Bering Sea ice extent.


2019 ◽  
Vol 13 (11) ◽  
pp. 3007-3021
Author(s):  
Nakbin Choi ◽  
Kyu-Myong Kim ◽  
Young-Kwon Lim ◽  
Myong-In Lee

Abstract. Besides its negative trend, the interannual and the interdecadal changes in the Arctic sea ice have also been pronounced in recent decades. The three leading modes in the sea level pressure (SLP) variability in the Arctic (70–90∘ N) – the Arctic Oscillation (AO), the Arctic Dipole (AD), and the third mode (A3) – are analyzed to understand the linkage between sea ice variability and large-scale atmospheric circulation in boreal summer (June–August). This study also compares the decadal changes of the modes between the early (1982–1997) and the recent (1998–2017) periods and their influences on the Arctic sea ice extent (SIE). Only the AD mode shows a significant correlation increase with SIE in summer (JJA) from −0.05 in the early period to 0.57 in the recent period. The AO and the A3 modes show a less significant relationship with SIE for the two periods. The AD is characterized by a dipole pattern of SLP, which modulates the strength of meridional surface winds and the Transpolar Drift Stream (TDS). The major circulation change in the late 1990s is that the direction of the wind has been changed more meridionally over the exit region of the Fram Strait, which causes sea ice drift and discharge through that region. In addition, the response of surface albedo and the net surface heat flux becomes larger and much clearer, suggesting a positive sea-ice–albedo feedback in the sea ice variability associated with the AD. The analysis also reveals that the zonal shift of the centers of SLP anomalies and associated circulation change affects a significant reduction in sea ice concentration over the Pacific sector of the Arctic Ocean. This study further suggests that the Pacific Decadal Oscillation (PDO) phase change could influence the spatial pattern change in the AD.


2019 ◽  
Author(s):  
Nakbin Choi ◽  
Kyu-Myong Kim ◽  
Young-Kwon Lim ◽  
Myong-In Lee

Abstract. Besides its negative trend, the interannual and the interdecadal changes in the Arctic sea ice are also pronounced in recent decades. The three leading modes in the sea level pressure (SLP) variability in the Arctic (70°–90 °N) – the Arctic Oscillation (AO), the Arctic Dipole (AD), and the third mode (A3) – are analyzed to understand the linkage between sea ice variability and large-scale atmospheric circulation in boreal summer (June–August). This study also compares the decadal changes of the modes between the early (1982–1997) and the recent (1998–2017) periods and their influences on the Arctic sea ice extent (SIE). Only the AD mode shows a significant correlation increase with SIE from −0.05 in the early period to 0.57 in the recent period. The AO and the A3 modes show a less significant relationship with SIE for the two periods. The AD is characterized by a dipole pattern of SLP, which modulates the strength of meridional surface winds and the transpolar drift stream (TDS). The major circulation change in the late 1990s is that the direction of the wind has been changed more meridionally over the exit region of the Fram Strait, which causes sea ice drift and discharge through that region. The analysis also reveals that the zonal shift of the centers of SLP anomalies and associated circulation change affects a significant reduction in sea ice concentration over the Pacific sector of the Arctic Ocean. This study further suggests that the Pacific Decadal Oscillation (PDO) phase change could influence the spatial pattern change in the AD.


Author(s):  
Isobel R. Lawrence ◽  
Thomas W.K. Armitage ◽  
Michel C. Tsamados ◽  
Julienne C. Stroeve ◽  
Salvatore Dinardo ◽  
...  

2009 ◽  
Vol 22 (9) ◽  
pp. 2438-2457 ◽  
Author(s):  
R. Kwok

Abstract Twenty-nine years of Arctic sea ice outflow into the Greenland and Barents Seas are summarized. Outflow is computed at three passages: Fram Strait, between Svalbard and Franz Josef Land (S–FJL), and between Franz Josef Land and Severnaya Zemlya (FJL–SZ). Ice drift at the flux gates has been reprocessed using a consistent and updated time series of passive microwave brightness temperature and ice concentration (IC) fields. Over the record, the mean annual area outflow at the Fram Strait is 706(113) × 103 km2; it was highest in 1994/95 (1002 × 103 km2) when the North Atlantic Oscillation (NAO) index was near its 29-yr peak. The strength of the “Transpolar Drift Stream” (TDS) was high during the late 1980s through the mid-1990s. There is no statistically significant trend in the Fram Strait area flux. Even though there is a positive trend in the gradient of cross-strait sea level pressure, the outflow has not increased because of a negative trend in IC. Seasonally, the area outflow during recent summers (in 2005 and 2007) has been higher (> 2σ from the mean) than average, contributing to the decline of summer ice coverage. Without updated ice thickness estimates, the best estimate of mean annual volume flux (between 1991 and 1999) stands at ∼2200 km3 yr−1 (∼0.07 Sv: Sv ≡ 106 m3 s−1). Net annual outflow at the S–FJL passage is 37(39) × 103 km2; the large outflow of multiyear ice in 2002–03, marked by an area and volume outflow of 141 × 103 km2 and ∼300 km3, was unusual over the record. At the FJL–SZ passage, there is a mean annual inflow of 103(93) × 103 km2 of seasonal ice into the Arctic. While the recent pattern of winter Arctic circulation and sea level pressure (SLP) has nearly reverted to its conditions typical of the 1980s, the summer has not. Compared to the 1980s, the recent summer SLP distributions show much lower SLPs (2–3 hPa) over much of the Arctic. Overall, there is a strengthening of the summer TDS. Examination of the exchanges between the Pacific and Atlantic sectors shows a long-term trend that favors the summer advection of sea ice toward the Atlantic associated with a shift in the mean summer circulation patterns.


2019 ◽  
Vol 11 (23) ◽  
pp. 2864 ◽  
Author(s):  
Jiping Liu ◽  
Yuanyuan Zhang ◽  
Xiao Cheng ◽  
Yongyun Hu

The accurate knowledge of spatial and temporal variations of snow depth over sea ice in the Arctic basin is important for understanding the Arctic energy budget and retrieving sea ice thickness from satellite altimetry. In this study, we develop and validate a new method for retrieving snow depth over Arctic sea ice from brightness temperatures at different frequencies measured by passive microwave radiometers. We construct an ensemble-based deep neural network and use snow depth measured by sea ice mass balance buoys to train the network. First, the accuracy of the retrieved snow depth is validated with observations. The results show the derived snow depth is in good agreement with the observations, in terms of correlation, bias, root mean square error, and probability distribution. Our ensemble-based deep neural network can be used to extend the snow depth retrieval from first-year sea ice (FYI) to multi-year sea ice (MYI), as well as during the melting period. Second, the consistency and discrepancy of snow depth in the Arctic basin between our retrieval using the ensemble-based deep neural network and two other available retrievals using the empirical regression are examined. The results suggest that our snow depth retrieval outperforms these data sets.


2021 ◽  
Vol 9 (7) ◽  
pp. 755
Author(s):  
Kangkang Jin ◽  
Jian Xu ◽  
Zichen Wang ◽  
Can Lu ◽  
Long Fan ◽  
...  

Warm current has a strong impact on the melting of sea ice, so clarifying the current features plays a very important role in the Arctic sea ice coverage forecasting study field. Currently, Arctic acoustic tomography is the only feasible method for the large-range current measurement under the Arctic sea ice. Furthermore, affected by the high latitudes Coriolis force, small-scale variability greatly affects the accuracy of Arctic acoustic tomography. However, small-scale variability could not be measured by empirical parameters and resolved by Regularized Least Squares (RLS) in the inverse problem of Arctic acoustic tomography. In this paper, the convolutional neural network (CNN) is proposed to enhance the prediction accuracy in the Arctic, and especially, Gaussian noise is added to reflect the disturbance of the Arctic environment. First, we use the finite element method to build the background ocean model. Then, the deep learning CNN method constructs the non-linear mapping relationship between the acoustic data and the corresponding flow velocity. Finally, the simulation result shows that the deep learning convolutional neural network method being applied to Arctic acoustic tomography could achieve 45.87% accurate improvement than the common RLS method in the current inversion.


2017 ◽  
Author(s):  
Jamie G. L. Rae ◽  
Alexander D. Todd ◽  
Edward W. Blockley ◽  
Jeff K. Ridley

Abstract. This paper presents an analysis of Arctic summer cyclones in a climate model and in a reanalysis dataset. A cyclone identification and tracking algorithm is run for output from model simulations at two resolutions, and for the reanalysis, using two different tracking variables (mean sea-level pressure and 850 hPa vorticity) for identification of the cyclones. Correlations between characteristics of the cyclones and September Arctic sea ice extent are investigated, and the influence of the tracking variable, the spatial resolution of the model, and spatial and temporal sampling, on the correlations is explored. We conclude that the correlations obtained depend on all of these factors, and that care should be taken when interpreting the results of such analyses, especially when the focus is on one reanalysis, or output from one model, analysed with a single tracking variable for a short time period.


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