Abstract

This study investigates the causes of severe ice conditions over the Bohai Sea, China, and mild ice cover over the North American Great Lakes under the same hemispheric climate patterns during the 2009/10 winter with a strong negative Arctic Oscillation (AO) and an El Niño event. The main cause of severe ice cover over the Bohai Sea was the strong negative AO. Six of seven winters with severe ice were associated with a strong negative AO during the period 1954–2010. The Siberian high (SH) in the 2009/10 winter was close to normal. The influence of El Niño on the Bohai Sea was not significant. In contrast, the mild ice conditions in the Great Lakes were mainly caused by the strong El Niño event. Although the negative AO generally produces significant colder surface air temperature (SAT) and heavy ice cover over the Great Lakes, when it coincided with a strong El Niño event during the 2009/10 winter the El Niño–induced Pacific–North America (PNA)-like pattern dominated the midlatitudes and was responsible for the flattening of the ridge–trough system over North America, leading to warmer-than-normal temperatures and mild ice conditions over the Great Lakes. This comparative study revealed that interannual variability of SAT in North America, including the Great Lakes, is effectively influenced by El Niño events through a PNA or PNA-like pattern whereas the interannual variability of SAT in northeastern China, including the Bohai Sea area, was mainly controlled by AO and SH.

1. Introduction

The Arctic Oscillation (AO) was defined by Thompson and Wallace (1998) as the leading empirical orthogonal function (EOF) mode of wintertime sea level pressure (SLP) anomalies over the extratropical Northern Hemisphere. The AO has an out-of-phase pattern in atmospheric pressure between the Arctic Basin and middle latitudes. It is shown to exert a strong influence on wintertime climate at virtually all longitudes (Thompson and Wallace 2001), including far eastern Asia (Gong and Ho 2003; Yu and Zhou 2004; Li et al. 2008). In association with AO, a surface atmosphere temperature (SAT) anomaly typically swings between Eurasia–Arctic Ocean and the Labrador Sea–eastern Canada (van Loon and Rogers 1978; Wang et al. 1994; Mysak et al. 1996; Wang and Ikeda 2000).

During a negative phase of AO, higher-than-normal atmospheric pressure over the Arctic induces weaker westerly winds in the upper atmosphere, which allows cold Arctic air to reach more southerly latitudes, resulting in a colder winter in the United States but warmer weather in northeastern Canada (Hodges 2000). The North American Great Lakes usually experience a colder winter. For the Eurasian continent, a negative AO is generally associated with warmer subtropical but colder mid–high latitudes (Yu and Zhou 2004; Li et al. 2008). Thus, during the negative phase of AO, the Bohai Sea in China (located off northeastern China, 37°–41°N, 117°–123°E) (Fig. 1a) and the Great Lakes in North America (41°–49°N, 75°–92°W) (Fig. 1b) are usually both expected to have higher-than-normal ice cover (Bai et al. 2010). In the 2009/10 winter with a very strong negative AO (winter mean index = −3.5), however, the Bohai Sea experienced severe ice cover (the greatest in 30 years) while the Great Lakes underwent a very mild ice season.

Fig. 1.

Locations of (a) the Bohai Sea, China, and (b) the Great Lakes in North America.

Fig. 1.

Locations of (a) the Bohai Sea, China, and (b) the Great Lakes in North America.

The 2009/10 winter was also a strong El Niño winter, with the December–February (DJF) mean Niño-3 index being 1.1°C. The event developed in the autumn of 2009 and persisted through winter. North America is significantly influenced by El Niño via the Pacific–North America (PNA) pattern (Wallace and Gutzler 1981). The well-known pattern, associated with El Niño, features above-normal SAT along the west coast of North America and western and central Canada and below-normal SAT in the southern United States and the Gulf of Mexico. The Great Lakes also experience warm winters during El Niño events.

During the 2009/10 winter, a strong negative AO and a strong El Niño event occurred simultaneously. The Bohai Sea and the Great Lakes experienced dramatically different ice conditions that did not follow usual conditions in strong negative AO years. This paper discusses this observation from the perspective of joint AO and El Niño–Southern Oscillation (ENSO) forcing. The causes of severe ice conditions over the Bohai Sea and mild ice on the Great Lakes in response to the same climate patterns were investigated.

2. Data

The data used here include monthly-mean temperatures from 160 stations in China for the period from 1951 to 2010 from the China Meteorological Administration (CMA), and monthly-mean SLP, SAT, surface-level and 700-hPa-level winds, and 500-hPa geopotential height for the period 1948–2010 from the National Centers for Environmental Prediction reanalysis dataset (Kalnay et al. 1996). The climatological monthly means of the period from 1949 to 2010 were calculated and then subtracted from the individual months to obtain the monthly anomalies.

Monthly AO and Niño-3 indices for the years 1950–2010 were taken from the National Oceanic and Atmospheric Administration (NOAA) Climate Prediction Center. The AO index is defined by the first EOF mode of SLP north of 20°N in the Northern Hemisphere. The Niño-3 index is defined as the 3-month running mean of sea surface temperature anomalies in the Niño-3 region (5°N–5°S, 150°–90°W). The east Asian winter monsoon (EAWM) index is defined as the normalized SLP difference between 110° and 160°E within 20°–50°N (Shi et al. 1996). The Siberian high (SH) intensity index is defined as the regionally averaged SLP (40°–60°N, 80°–120°E), following the method of Wu and Wang (2002).

In 1973, the State Oceanic Administration (SOA) of China defined five categories (scales) of sea ice severity according to the ice thickness and extent in the Bohai Sea and northern Yellow Sea based on the observed data since 1963. The five categories range from 1.0 to 5.0. Category I represents the lightest ice severity, V is the most severe (most of the sea is covered by sea ice), III represents the normal severity, and II and IV denote the moderately light and moderately heavy severity, respectively. Figure 2 shows the ice edges corresponding to the ice categories. The ice category is evaluated by the weighted sum of ice scales of three bays. The weighted coefficients are 0.5, 0.3, and 0.2, respectively, for Liaodong Bay, Bohai Bay, and Laizhou Bay (Bai et al. 2001). In this study, the sea ice severity index was taken from Bai et al. (2001) and Gong et al. (2007). The updated data were from SOA’ s Annual Bulletin of Ocean Disasters. The sea ice severity time series covers winters for the period 1953/54–2009/10 (Fig. 3). The long-term mean sea ice severity index for the period 1953/54–2009/10 is 2.57. Thus, the climatological ice edge is between line II and line III (diagonally striped area in Fig. 2). Measurements from the Moderate Resolution Imaging Spectroradiometer (MODIS) on board the National Aeronautics and Space Administration (NASA) Terra satellite during the 2009/10 winter were also used to study the extreme sea ice event in the Bohai Sea.

Fig. 2.

Ice edges corresponding to the ice categories (I, II, III, etc.) in the Bohai Sea, China. The diagonally striped area denotes the climatological ice cover.

Fig. 2.

Ice edges corresponding to the ice categories (I, II, III, etc.) in the Bohai Sea, China. The diagonally striped area denotes the climatological ice cover.

Fig. 3.

Time series of the Bohai Sea ISI (bars) and WSI (black line with filled circles) for winters 1954–2010. The 0-lag correlation coefficient is also shown.

Fig. 3.

Time series of the Bohai Sea ISI (bars) and WSI (black line with filled circles) for winters 1954–2010. The 0-lag correlation coefficient is also shown.

An index of winter severity (WSI) over the Bohai Sea area was defined as the average of the monthly-mean temperatures from November through February at six stations around the Bohai Sea: Tianjin, Yingkou, Dalian, Weifang, Yantai, and Chaoyang (Table 1). Monthly-mean temperatures for the six stations obtained from CMA were used to calculate the winter severity index for winters from 1951/52 to 2009/10, as shown along with the Bohai Sea ice severity index in Fig. 3.

Table 1.

Meteorological stations (WMO = World Meteorological Organization).

Meteorological stations (WMO = World Meteorological Organization).
Meteorological stations (WMO = World Meteorological Organization).

Annual maximum ice coverage (AMIC) is defined as the greatest percentage of surface area of a lake covered by ice each winter for the Great Lakes. Figure 4 shows the spatial distribution of the 30-yr (1973–2002) mean annual maximum ice cover. The map was constructed by two steps: first, the date and magnitude of the AMIC were identified for the Great Lakes as a whole for each of these winters based on analysis of daily spatial average ice cover of the entire Great Lakes as given in Assel (2003); second, the mean ice cover concentration for the 30 AMIC dates was calculated at each grid cell. The AMIC for the Great Lakes as a whole for winters 1963–2010 was calculated using the dataset obtained from the National Snow and Ice Data Center (Fig. 5). The long-term mean (1963–2010) AMIC is 54.5%, and the standard deviation is 21%. In this analysis, winters with normalized AMIC of greater than or equal to 0.7 (≥69%) were identified as maximal-ice-cover winters, and winters with normalized AMIC of less than or equal to −0.7 (≤40%) were identified as minimal-ice-cover winters.

Fig. 4.

Long-term (1973–2002) mean AMIC in the Great Lakes.

Fig. 4.

Long-term (1973–2002) mean AMIC in the Great Lakes.

Fig. 5.

Great Lakes (GL) AMIC (solid line with open circles) and WSI (dashed line with plus signs) for winters 1963–2010. The 0-lag correlation coefficient is also shown.

Fig. 5.

Great Lakes (GL) AMIC (solid line with open circles) and WSI (dashed line with plus signs) for winters 1963–2010. The 0-lag correlation coefficient is also shown.

In an earlier study (Quinn et al. 1978), C. R. Snider developed an index of Great Lakes winter severity. It is defined as the average of the monthly-mean temperatures from November through February at Duluth, Minnesota; Sault Ste. Marie and Detroit, Michigan; and Buffalo, New York (see Table 1 for station information), which was found to correlate with the mass of ice formation on the Great Lakes. In this study, monthly-mean temperature for the four stations obtained from National Climatic Data Center was used to calculate winter severity index for the period from 1963 to 2010, which was shown along with AMIC in Fig. 5.

The Bohai Sea is a semienclosed and very shallow sea (average depth is about 20 m), and the local weather plays an essential role in sea ice conditions. Observations indicated that the dynamical factors such as wind stress and surface ocean currents are not so important in the distribution of sea ice (Zhang 1986). The correlation between the time series of Bohai sea ice severity index and winter severity index for the winters of 1954–2010 was −0.81 (Fig. 3), which is significant at the 99% confidence level. Great Lakes ice conditions are also mainly governed by surface air temperature. The correlation between the AMIC and Great Lakes winter severity was −0.79 for the winters of 1963–2010 (Fig. 5), which is also significant. In this study, we do not address the influence of wind-related ice dynamics; we only focus on the temperature influences.

3. Results

a. Synoptic description of the 2009/10 ice season

In contrast to the recent warm winters since the 1980s, the Bohai Sea experienced severe ice cover in the winter of 2010. The maximum ice coverage occurred on 23 January 2010 with 51% of the Bohai Sea being covered by ice (China Daily, 27 January 2010) (Fig. 6a). On 26 January, the maximum ice thickness was 40, 25, and 20 cm in Liaodong Bay, Bohai Bay, and Laizhou Bay, respectively (China Daily, 27 January 2010). On 13 February, Liaodong Bay was almost completely covered by ice (Fig. 6b). The ice conditions were some of the most severe in the last 30 years and were defined as category 4. Since 1954, there were seven winters (1956, 1957, 1968, 1969, 1977, 2001, and 2010) with an ice severity index of equal to or greater than category 4. The most recent two years were 2001 and 2010 (Fig. 3). Although both were defined as category 4, ice conditions during the winter of 2010 were a little more severe than those during the winter of 2001: Annual maximum ice coverage and its duration in winter 2010 were a little greater and longer than those in 2001.

Fig. 6.

(a) AMIC over the Bohai Sea on 23 Jan 2010 as measured by MODIS on board NASA’ s Terra satellite; (b) ice cover on 13 Feb 2010 as measured by MODIS; (c) AMIC over the Great Lakes on 9 Feb 2010 as measured by a blend of observations (ships, shore, aircraft, and satellite).

Fig. 6.

(a) AMIC over the Bohai Sea on 23 Jan 2010 as measured by MODIS on board NASA’ s Terra satellite; (b) ice cover on 13 Feb 2010 as measured by MODIS; (c) AMIC over the Great Lakes on 9 Feb 2010 as measured by a blend of observations (ships, shore, aircraft, and satellite).

In contrast, the Great Lakes of North America experienced a very mild winter. The AMIC in Lake Superior was only 27.1%. Lakes Michigan, Huron, and Ontario had 22.6%, 35.7%, and 14.2%, respectively, with Lake Erie being an exception with an AMIC of 89.5%. The average AMIC for all lakes was 26.6%, which occurred on 9 February 2010 (Fig. 6c). Ice cover in the 2009/10 winter was the fifth mildest since 1963 (Fig. 5). The long-term mean and standard deviation of AMIC of each lake for the period from 1973 to 2010 are listed in Table 2. The normalized AMICs in Lakes Superior, Michigan, Huron, Erie, and Ontario during the 2010 winter were −1.23, −0.75, −1.14, 0.24, and −0.64, respectively. Ice cover over Lakes Superior and Huron was greatly reduced.

Table 2.

Long-term mean and standard deviations (STD) of AMIC of each Great Lake for the period 1973–2010.

Long-term mean and standard deviations (STD) of AMIC of each Great Lake for the period 1973–2010.
Long-term mean and standard deviations (STD) of AMIC of each Great Lake for the period 1973–2010.

During December of 2009, a typical negative AO pattern dominated the Northern Hemisphere, with above-normal heights over the polar region and below-normal heights over the middle latitudes, with two centers over the North Pacific and the North Atlantic Oceans (Fig. 7a). Monthly-mean 500-hPa height shows an expanded circumpolar vortex with three low centers over the Canadian Maritimes and Hudson Bay, the western Siberian Plain, and the Sea of Okhotsk. The positions of these three lows were well south of their usual latitudes, which were favorable for advecting cold Arctic air to southern latitudes, leading to cold temperatures there. In particular, over North America, there was a deep trough from Hudson Bay all the way to the southwest and a strong ridge over the West Coast off Canada and Alaska (Fig. 7a). This amplified ridge–trough system led to an extremely cold December in southwestern Canada and almost the entire United States. The greatest negative anomaly was as much as −6°C (Fig. 8a). The warm advection downstream of the deep troughs led to above-normal temperatures in Alaska, much of Canada, and the northeast area in the United States, including the Great Lakes. The Great Lakes area was slightly warmer than normal, with SAT anomaly ranging from 0° to 2°C (Fig. 8a). Over Eurasia, cold advection associated with the polar low over the western Siberian Plain led to a large cooling in northern Asia with a center in western and central Siberia (Fig. 8a). The cooling covered much of China except for the southwestern area. Temperatures were 0.5°–1.5°C below normal in the Bohai Sea area. The Bohai Sea WSI was −3.5°C. This global SAT anomaly pattern is similar to the regression map of SAT upon negative AO index and will be discussed shortly.

Fig. 7.

The 500-hPa height (m × 10 MSL) and anomalies (in color) for (a) December 2009, (b) January 2010, and (c) February 2010. The anomalies are referenced to the climatological means of 1949–2010.

Fig. 7.

The 500-hPa height (m × 10 MSL) and anomalies (in color) for (a) December 2009, (b) January 2010, and (c) February 2010. The anomalies are referenced to the climatological means of 1949–2010.

Fig. 8.

Surface air temperature (color shaded; °C) and surface wind (vectors; m s−1) anomalies for (a) December 2009, (b) January 2010, and (c) February 2010.

Fig. 8.

Surface air temperature (color shaded; °C) and surface wind (vectors; m s−1) anomalies for (a) December 2009, (b) January 2010, and (c) February 2010.

The 500-hPa height anomaly in January of 2010 shows a positive PNA-like pattern dominating the midlatitudes, with negative anomalies over the Gulf of Alaska and over the southeastern United States and central Atlantic and positive anomalies over Hudson Bay and the Great Lakes (Fig. 7b). This pattern resembles a positive PNA pattern, but the locations of anomaly centers were well east of the classical PNA pattern. These anomalies reflected a stronger trough over the Gulf of Alaska and a much weaker Hudson Bay trough. The Aleutian low was somewhat southeast of its normal position (not shown). These conditions allowed warm and humid air from the Pacific Ocean to flow into high latitudes, resulting in above-normal temperatures in southern Alaska, Canada, and the northern United States, including the Great Lakes region. The SAT anomaly in the Great Lakes ranged from −1.5° to 3°C. The upper lakes were warmer than normal while Lake Erie and southern Lake Michigan were colder than normal (Fig. 8b). Thus, Lake Erie was heavily ice covered while the other lakes had mild ice cover (Fig. 6c). There was also a negative North Atlantic Oscillation (NAO) pattern with above-normal heights across the high latitudes of the North Atlantic and below-normal heights over the central North Atlantic, the eastern United States, and western Europe. The enhanced blocking over Greenland prevented the usual warmer, damper, westerly winds from reaching Europe across the Atlantic, pushing large amounts of cold Arctic air from the north, and resulting in significant cooling in northern Eurasia with a center of 8°C below normal in Siberia (Fig. 8b). In Asia, the polar low center over the western Siberian Plain in December 2009 disappeared. Above-normal heights occupied much of Asia except for below-normal heights over the Lake Baikal region. The northwest Pacific subtropical high was strong and was located north of its normal position (not shown). Monthly-mean temperature over much of China was 1°–4°C above normal, and air temperatures were 1°–2°C below normal in northern north China, eastern inner Mongolia, and southern northeast China (China Climate System Monitoring Bulletin, January 2010). The SAT anomaly in the Bohai Sea ranged from −1.0° to −1.5°C (Fig. 8b). The Bohai Sea WSI was −6.35°C in January.

During February 2010, the anomalous 500-hPa heights reflected a mixture of AO, NAO, and PNA-like patterns. The centers of the PNA-like pattern shifted westward (Fig. 7c) a little in comparison with that during January 2010 (Fig. 7b). Similar to December 2009, the monthly-mean 500-hPa heights show an expended circumpolar vortex with an Arctic cold air mass being pushed southward. Three low centers were over eastern Canada, Scandinavia, and eastern Siberia, respectively (Fig. 7c). Consistent with this anomalous circulation pattern, the main temperature signals in North America include above-normal temperatures across Canada and Alaska and below-normal temperatures in the central and eastern United States. The Great Lakes were between, with warming in the upper lakes and cooling in the lower lakes (Fig. 8c). In Asia, the amplified blocking over the Ural Mountains and the strong low center over eastern Siberia (Fig. 7c) pushed Arctic cold air southward, resulting in significant cooling in northern Asia with the center in western Siberia (Fig. 8c). The cooling was mainly north of 40°N. The temperatures in northeast China and Xinjiang (northwest tip in China) were 1°–4°C below normal while the temperatures in most of China were 1°–4°C above normal (China Climate System Monitoring Bulletin, February 2010). Temperature anomalies in the Bohai Sea area were from −0.5° to +0.5°C with warming in the south and cooling in the north (Fig. 8c). The Bohai Sea WSI was −2.67°C. As MODIS pictures during February show (Fig. 6b), the ice over Laizhou and Bohai Bays in the south was almost melted while the ice over Liaodong Bay in the north kept growing and covered almost the entire bay.

Average winter (November–February) surface temperature for six stations (Table 1) around the Bohai Sea in the 2009/10 winter was −2.8°C, which was the lowest since 1977 (Fig. 3). It is noted that the temperature in November 2009 (1.9°C) was one of the lowest since 1954, which was a significant cold preconditioning for the upcoming ice growth.

The overall climate patterns during DJF 2009/10 reflected the combination of El Niño and a negative AO/NAO. During December 2009, the pattern was a typical negative AO, and the signals of El Niño influences in midlatitude were not as obvious as in the coming months. During January and February 2010, in addition to the obvious negative AO/NAO signals, the PNA-like pattern, which was considered to be associated with the strong El Niño event, developed and dominated over North America. In Asia, the signals of El Niño impacts include above-normal 500-hPa heights in the subtropical Pacific Ocean and the enhanced northwestern Pacific subtropical high. The different ice conditions in the Bohai Sea in China and the Great Lakes are hypothesized to be caused by the different responses in Eurasia and North America to these two simultaneously occurring events.

b. Causes of severe sea ice in the Bohai Sea and mild ice cover in the Great Lakes

1) The Bohai Sea

Interannual variability of winter temperature in China as well as the EAWM is controlled by various factors: SH, AO, and ENSO (Wu and Wang 2002). Thus, it is reasonable to investigate these as possible causes of severe ice cover in the Bohai Sea.

Figure 9 shows the time series of these three indices along with the Bohai Sea WSI and the EAWM index for the 59-yr period from 1952 to 2010 and their 0-lag correlations. The SH has the largest positive correlation with the EAWM index (0.68) and the largest negative correlation with the Bohai Sea WSI (−0.482). That is, the stronger the SH is, the colder it is and the heavier is the ice cover in the Bohai Sea. The correlation between SH and Bohai Sea ice severity index (ISI) was 0.38, which is significant at the 95% level (Table 3). The correlation between the AO and the Bohai Sea WSI was 0.50, which implies that the positive (negative) phase of AO will lead to warming (cooling) in the Bohai Sea area. The AO has the largest negative correlation with Bohai Sea ISI (−0.55) (Table 3). The Niño-3 index has the smallest correlation (0.13) with Bohai Sea WSI and ISI (−0.12). The correlation analysis clearly shows that interannual variation of the Bohai Sea WSI is controlled significantly by both SH and AO and is slightly influenced by ENSO.

Fig. 9.

Time series of (a) winter-mean AO, SH, and Niño-3 indices; (b) Bohai winter severity (solid line with open circles) and EAWM (dashed line with open triangles) index for winters 1952–2010. The 0-lag correlation coefficients are also shown.

Fig. 9.

Time series of (a) winter-mean AO, SH, and Niño-3 indices; (b) Bohai winter severity (solid line with open circles) and EAWM (dashed line with open triangles) index for winters 1952–2010. The 0-lag correlation coefficients are also shown.

Table 3.

Correlation coefficients between Bohai Sea ISI (1954–2010) or GL AMIC (1963–2010) and climatic indices. Boldface indicates that the correlations are significant at the 95% level.

Correlation coefficients between Bohai Sea ISI (1954–2010) or GL AMIC (1963–2010) and climatic indices. Boldface indicates that the correlations are significant at the 95% level.
Correlation coefficients between Bohai Sea ISI (1954–2010) or GL AMIC (1963–2010) and climatic indices. Boldface indicates that the correlations are significant at the 95% level.

To understand how the AO affects surface air temperature around the Bohai Sea area, we constructed the composite map of 500-hPa heights and anomalies and 700-hPa-level wind anomalies for 16 negative AO events (Table 4), which are shown in Figs. 10a and 10b, respectively. During the negative phase of AO, there are significant negative 500-hPa height anomalies over eastern Asia and positive anomalies over the Ural Mountains. Thus, the east-Asian trough is deeper than normal and the blocking over the Ural Mountains is enhanced. The buildup of the SLP high in Siberia is mainly due to strong surface radiation cooling and is partially due to the downward motion of air because of the midtroposphere convergence (Ding and Krishnamurti 1987; Ding 1990). In association with a negative AO, the stronger-than-normal midtroposphere convergence upstream of the deepened east-Asian trough and a mid–lower-troposphere cold advection (Fig. 10b) would help to strengthen the surface pressure and consequently lead to a stronger Siberian high (Gong et al. 2001, 2007). A deeper east-Asian trough, stronger blocking over the Urals, and an intensified Siberian high would tend to bring a cold air mass over eastern China and cause a notable decrease in temperature in the Bohai Sea area.

Table 4.

List of selected winters with standard deviations greater than 1 unit.

List of selected winters with standard deviations greater than 1 unit.
List of selected winters with standard deviations greater than 1 unit.
Fig. 10.

(a) Composite map of mean winter 500-hPa geopotential heights (solid lines) and anomalies (color shaded) for 16 winters of negative AO during the period from 1952 to 2010. The red contours indicate the 90% and 95% significant levels. (b) As in (a) but for 700-hPa-level wind anomalies. The contours indicate that the zonal or meridional wind is significant at the 95% level.

Fig. 10.

(a) Composite map of mean winter 500-hPa geopotential heights (solid lines) and anomalies (color shaded) for 16 winters of negative AO during the period from 1952 to 2010. The red contours indicate the 90% and 95% significant levels. (b) As in (a) but for 700-hPa-level wind anomalies. The contours indicate that the zonal or meridional wind is significant at the 95% level.

Figures 11a–c show wintertime mean SAT anomalies regressed upon SH, negative AO, and Niño-3 indices, respectively. Using 1 standard deviation of the SH index, significant negative anomalies from −0.2° to −1.0°C appear in eastern Asia (20°–50°N, 80°–150°E), with the center located at 42°N, 115°E (Fig. 11b). Using 1 standard deviation of negative AO, significant negative SAT anomalies from −0.5° to −2.0°C appear in Eurasia north of 40°N, with a center located in central Siberia (Fig. 11a). In the Bohai Sea area there are SAT anomalies from −0.5° to −1.0°C, and over the Great Lakes the SAT anomalies range from −0.2° to −0.8°C, both being statistically significant (Fig. 11a). SAT anomalies over the Bohai Sea area are from −0.4° to −0.8°C, associated with 1 standard deviation of SH, and the Great Lakes area is located around the zero line (Fig. 11b), since the SH phenomenon is only related to eastern Asia. The SAT anomalies associated with 1 standard deviation of the Niño-3 index show that there is an insignificant warming of 0.2°C over Eurasia, including the Bohai Sea area, and a significant warming of 0.4°–0.8°C over North America, including the Great Lakes. A comparison of the impacts of these three climate patterns indicates that the AO and SH have almost the same order of magnitude of contribution to the wintertime SAT anomalies over the Bohai Sea area, whereas the impact of ENSO is negligible over the Bohai Sea area but is significant over the Great Lakes. The AO also has the same significant impacts on the Great Lakes SAT anomaly as on the Bohai area; that is, positive AO (negative AO) leads to the same positive (negative) SAT anomalies over both the Bohai area and the Great Lakes.

Fig. 11.

Changes of surface air temperature in DJF in association with 1-standard-deviation stronger (a) negative AO, (b) SH, and (c) Niño-3 indices. Shaded areas are at the 95% significance level.

Fig. 11.

Changes of surface air temperature in DJF in association with 1-standard-deviation stronger (a) negative AO, (b) SH, and (c) Niño-3 indices. Shaded areas are at the 95% significance level.

In winter of 2009/10, the SH, AO, Niño-3, and EAWM indices were −0.2, −3.5, 1.1°C, and −1.0, respectively. It was a strong negative AO and a strong El Niño winter. The monthly-mean AO index from December through February was −3.41, −2.59, and −4.27. The Niño-3 index with above 0.5°C persisted from June 2009 through April 2010 with a maximum of 1.58°C in December 2010. The Siberian high in 2010 winter was close to normal (Fig. 9a). From the above analysis, the negative phase of AO led to significant cooling in the Bohai Sea area. The high index of −3.5 produced significant cooling from approximately −1.75° to −3.5°C over the Bohai Sea area. Niño-3 of 1.1°C had around 0.2°C warming in the Bohai Sea area, which could not compete with the significant cooling response to the strong negative AO. In general, SH is the largest contributor to the Bohai Sea WSI (Wu and Wang 2002). However, SH was close to normal in winter 2010; thus its contribution to SAT anomalies in the Bohai Sea area during winter 2010 was negligible. Therefore, the severe ice conditions in the Bohai Sea during winter 2009/10 were caused by the strong negative AO event.

The extreme severe (ISI ≥ 4) ice conditions in the Bohai Sea occurred in 1956, 1957, 1968, 1969, 1977, 2001, and 2010. Except for 1957, all severe ice winters were in the negative phase of AO. The winter of 1957 had a strong SH (see Fig. 9a). In the winter of 1969, the Bohai Sea was completely covered by ice; it was also a strong negative AO and El Niño year while SH was weaker than normal (Fig. 9a).

In general, an El Niño year is often associated with a weaker-than-normal northeasterly winter monsoon along the east Asian coast (Wang et al. 2000). Wang et al. (2000) suggested that warming of the equatorial eastern Pacific surface tends to induce a weak EAWM through an anomalous anticyclonic circulation over the western North Pacific. The above-normal 500-hPa heights over eastern Asia and the northwestern Pacific in January and February 2010 were thought to be caused by the El Niño event. The correlation coefficient between winter Niño-3 index and EAWM index for the period from 1952 to 2010 is −0.35, which is significant at the 95% level. The 2010 EAWM was weaker than normal (index = −1.0), consistent with previous studies. The significant anomalous wind fields (not shown) and SAT associated with strong El Niño events were confined to the east coast of China, however, including the South China Sea, East China Sea, Yellow Sea, Korea, Japan, and Kuroshio and its extension area (Fig. 11c). SAT in most of China, including the Bohai Sea, was not significantly influenced by the 2010 winter El Niño event, which is consistent with the results of Zhou et al. (2009).

2) Great Lakes

It is well known that the Great Lakes region can be significantly influenced by the ENSO in the Pacific Ocean, the AO, or the NAO (Assel and Rodionov 1998; Rodionov and Assel 2001, 2003; Wang et al. 2010; Bai et al. 2010). The negative phase of AO usually produces a cold winter in the Great Lakes region. As shown in Fig. 11a, using 1 standard deviation of negative AO index, temperatures from −0.2° to −0.8°C below normal appear in the Great Lakes region. The upper lakes are colder than the lower lakes. In fact, from 1963 through 2010, 9 of 13 negative AO winters (AO index < −1.0; see Table 4) had above-normal ice cover, and seven of them had severe ice (AMIC ≥ 70%), which explained 54% of the 13 severe ice events in the Great Lakes. On the other hand, 4 of 13 negative AO winters were associated with mild winter in the Great Lakes. For example, the winter of 2009/10 was in a very strong negative phase of AO but had mild ice cover, with AMIC being only 26.6%. The other three winters are 1966, 1969, 2001, which all had minimal ice cover (≤40%).

The winters of 1966, 1969, and 2010 were also typical El Niño winters. During El Niño events, the northern states in the United States, including the Great Lakes region, usually experience a mild winter. As shown in Fig. 11c, using 1 standard deviation of Niño-3 index, the Great Lakes region has 0.2°–0.8°C warmer-than-normal SAT. The upper lakes are warmer than the lower lakes. The El Niño event has the same magnitude of impact as the AO, but with opposite sign. Historical ice cover data from 1963 to 2010 show that 7 of 10 strong El Niño winters had the minimal ice cover (≤40%), which explained 50% of the total 14 minimal ice cover winters (Bai et al. 2010). AMIC during the two strongest El Niño events, 1983 and 1998, was only 22.1% and 13%, respectively.

The composite maps of winter 500-hPa heights and anomalies and 700-hPa-level wind anomalies for the 10 strong El Niño events were constructed to explore how El Niño events affect SAT in the Great Lakes region (Figs. 12a,b). The 500-hPa height anomalies (Fig. 12a) show a clear PNA-like signature with negative anomalies over the Gulf of Alaska and over the southeastern United States and positive anomalies over Hudson Bay and the Great Lakes region. The action centers are shifted eastward with respect to those of a typical PNA pattern. These anomalies reflect that strong El Niño events are usually associated with a deeper-than-normal trough over the Gulf of Alaska, a weaker-than-normal ridge over the West Coast, and a weaker-than-normal Hudson Bay trough over eastern Canada. At the 700-hPa level, significant anomalous easterlies prevail over the eastern United States and southeastern Canada, including the Great Lakes region, and anomalous southerlies and southeasterlies prevail over the western United States and western Canada (Fig. 12b). Thus, the climatological westerly or northwesterly pattern is weakened. These upper-circulation anomalies associated with El Niño events prevent a cold Arctic air mass from intruding from the north to the Great Lakes region, allowing the warm Pacific air to flow to the high latitudes, leading to a warmer winter in the northern United States, including the Great Lakes region.

Fig. 12.

(a) Composite map of mean winter 500-hPa geopotential height (solid lines) and anomaly (color shaded) for 10 strong El Niño winters during the period 1963–2010. The red contours indicate the 90% and 95% significant levels. (b) As in (a), but for 700-hPa-level wind anomaly. The contours indicate that the zonal or meridional wind is significant at the 95% level.

Fig. 12.

(a) Composite map of mean winter 500-hPa geopotential height (solid lines) and anomaly (color shaded) for 10 strong El Niño winters during the period 1963–2010. The red contours indicate the 90% and 95% significant levels. (b) As in (a), but for 700-hPa-level wind anomaly. The contours indicate that the zonal or meridional wind is significant at the 95% level.

The above analyses suggest that both negative AO and El Niño have significant impacts on the Great Lakes region. The anomalous circulation associated with a negative AO leads to a colder winter in the United States. When a negative AO coincides with a strong El Niño event like in the 2009/10 winter, however, a PNA-like pattern dominates the midlatitudes, with a deepened trough over the Gulf of Alaska and flattened ridge–trough system over North America, and prevents a cold Arctic air mass from intruding from the north, leading to a warmer winter in the northern United States.

In December 2009, the AO was negatively strong (index = −3.41) and the typical negative AO pattern dominated the Northern Hemisphere. At that time, the PNA or PNA-like pattern was not fully established (Fig. 7a). The ridge–trough system over North America was stronger than climatological values (Fig. 7a), leading to below-normal SAT (from −2° to −6°C) over almost the entire United States (Fig. 8a). The Great Lakes region was downstream of the trough, however, and the warm advection led to above-normal temperature there. In January and February 2010, the AO index was −2.45 and −4.27, respectively. In midlatitudes, the PNA-like pattern was fully developed (Figs. 7b,c), resulting in positive SAT anomalies over the Great Lakes (Figs. 8b,c).

4. Conclusions

During the 2009/10 winter with a strong negative AO and El Niño, the Bohai Sea in China experienced severe ice cover, the greatest in the past three decades, while the Great Lakes underwent a very mild ice season. The causes were investigated, and the following conclusions can be drawn:

  1. The severe ice in the Bohai Sea during the 2009/10 winter was caused by the strong negative AO. The impact of the AO on winter SAT in China is confined to the northeastern area, including the Bohai Sea. The EAWM was weaker than normal because of the El Niño event in the Pacific Ocean. The significant anomalous SAT associated with the strong El Niño event was confined to the eastern coast of China, however. SAT in most of China, including the Bohai Sea, was not significantly influenced by the 2010 winter El Niño event. The Siberian high in the 2009/10 winter was close to normal and did not produce a significant SAT anomaly. Historical data also show that most severe ice cover occurred during a negative AO.

  2. The mild ice conditions in the Great Lakes during the 2009/10 winter were mainly caused by the strong El Niño event. Although the strong negative AO dominated the high latitudes, when a strong El Niño occurred simultaneously, the PNA-like pattern dominated the midlatitudes in North America, which was responsible for the flattening of the ridge–trough system, leading to warmer-than-normal SAT and mild ice conditions in the Great Lakes. Seven of 10 strong El Niño events have been associated with minimal ice conditions in the Great Lakes since 1963.

  3. The comparative study of the dramatically different ice conditions between the Bohai Sea in Asia and the Great Lakes in North America under the same climate pattern during the 2009/10 winter revealed that North America was effectively influenced by the El Niño event via the PNA-like pattern with Rossby wave propagation while the impact of the El Niño on the winter SAT in northern Asia was not significant, which could not overwhelm the stronger influence of the negative AO when they coincided in the 2009/10 winter.

Acknowledgments

We acknowledge support from the National Research Council through NOAA GLERL for Xuezhi Bai and funding from the Great Lakes Restoration Initiative from the U.S. Environmental Protection Agency and NOAA.

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Footnotes

*

Great Lakes Environmental Research Laboratory Contribution Number 1585.