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Su-Ping Zhang, Shang-Ping Xie, Qin-Yu Liu, Yu-Qiang Yang, Xin-Gong Wang, and Zhao-Peng Ren

Abstract

Sea fog is frequently observed over the Yellow Sea, with an average of 50 fog days on the Chinese coast during April–July. The Yellow Sea fog season is characterized by an abrupt onset in April in the southern coast of Shandong Peninsula and an abrupt, basin-wide termination in August. This study investigates the mechanisms for such steplike evolution that is inexplicable from the gradual change in solar radiation. From March to April over the northwestern Yellow Sea, a temperature inversion forms in a layer 100–350 m above the sea surface, and the prevailing surface winds switch from northwesterly to southerly, both changes that are favorable for advection fog. The land–sea contrast is the key to these changes. In April, the land warms up much faster than the ocean. The prevailing west-southwesterlies at 925 hPa advect warm continental air to form an inversion over the western Yellow Sea. The land–sea differential warming also leads to the formation of a shallow anticyclone over the cool Yellow and northern East China Seas in April. The southerlies on the west flank of this anticyclone advect warm and humid air from the south, causing the abrupt fog onset on the Chinese coast. The lack of such warm/moist advection on the east flank of the anticyclone leads to a gradual increase in fog occurrence on the Korean coast. The retreat of Yellow Sea fog is associated with a shift in the prevailing winds from southerly to easterly from July to August. The August wind shift over the Yellow Sea is part of a large-scale change in the East Asian–western Pacific monsoons, characterized by enhanced convection over the subtropical northwest Pacific and the resultant teleconnection into the midlatitudes, the latter known as the western Pacific–Japan pattern. Back trajectories for foggy and fog-free air masses support the results from the climatological analysis.

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Kyong-Hwan Seo, Wanqiu Wang, Jon Gottschalck, Qin Zhang, Jae-Kyung E. Schemm, Wayne R. Higgins, and Arun Kumar

Abstract

This work examines the performance of Madden–Julian oscillation (MJO) forecasts from NCEP’s coupled and uncoupled general circulation models (GCMs) and statistical models. The forecast skill from these methods is evaluated in near–real time. Using a projection of El Niño–Southern Oscillation (ENSO)-removed variables onto the principal patterns of MJO convection and upper- and lower-level circulations, MJO-related signals in the dynamical model forecasts are extracted. The operational NCEP atmosphere–ocean fully coupled Climate Forecast System (CFS) model has useful skill (>0.5 correlation) out to ∼15 days when the initial MJO convection is located over the Indian Ocean. The skill of the CFS hindcast dataset for the period from 1995 to 2004 is nearly comparable to that from a lagged multiple linear regression model, which uses information from the previous five pentads of the leading two principal components (PCs). In contrast, the real-time analysis for the MJO forecast skill for the period from January 2005 to February 2006 using the lagged multiple linear regression model is reduced to ∼10–12 days. However, the operational CFS forecast for this period is skillful out to ∼17 days for the winter season, implying that the coupled dynamical forecast has some usefulness in predicting the MJO compared to the statistical model.

It is shown that the coupled CFS model consistently, but only slightly, outperforms the uncoupled atmospheric model (by one to two days), indicating that only limited improvement is gained from the inclusion of the coupled air–sea interaction in the MJO forecast in this model. This slight improvement may be the result of the existence of a propagation barrier around the Maritime Continent and the far western Pacific in the NCEP Global Forecast System (GFS) and CFS models, as shown in several previous studies. This work also suggests that the higher horizontal resolution and finer initial data might contribute to improving the forecast skill, presumably as a result of an enhanced representation of the Maritime Continent region.

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Ian Baxter, Qinghua Ding, Axel Schweiger, Michelle L’Heureux, Stephen Baxter, Tao Wang, Qin Zhang, Kirstin Harnos, Bradley Markle, Daniel Topal, and Jian Lu

Abstract

Over the past 40 years, the Arctic sea ice minimum in September has declined. The period between 2007 and 2012 showed accelerated melt contributed to the record minima of 2007 and 2012. Here, observational and model evidence shows that the changes in summer sea ice since the 2000s reflect a continuous anthropogenically forced melting masked by interdecadal variability of Arctic atmospheric circulation. This variation is partially driven by teleconnections originating from sea surface temperature (SST) changes in the east-central tropical Pacific via a Rossby wave train propagating into the Arctic [herein referred to as the Pacific–Arctic teleconnection (PARC)], which represents the leading internal mode connecting the pole to lower latitudes. This mode has contributed to accelerated warming and Arctic sea ice loss from 2007 to 2012, followed by slower declines in recent years, resulting in the appearance of a slowdown over the past 11 years. A pacemaker model simulation, in which we specify observed SST in the tropical eastern Pacific, demonstrates a physically plausible mechanism for the PARC mode. However, the model-based PARC mechanism is considerably weaker and only partially accounts for the observed acceleration of sea ice loss from 2007 to 2012. We also explore features of large-scale circulation patterns associated with extreme melting periods in a long (1800 yr) CESM preindustrial simulation. These results further support that remote SST forcing originating from the tropical Pacific can excite significant warm episodes in the Arctic. However, further research is needed to identify the reasons for model limitations in reproducing the observed PARC mode featuring a cold Pacific–warm Arctic connection.

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Suranjana Saha, Shrinivas Moorthi, Xingren Wu, Jiande Wang, Sudhir Nadiga, Patrick Tripp, David Behringer, Yu-Tai Hou, Hui-ya Chuang, Mark Iredell, Michael Ek, Jesse Meng, Rongqian Yang, Malaquías Peña Mendez, Huug van den Dool, Qin Zhang, Wanqiu Wang, Mingyue Chen, and Emily Becker

Abstract

The second version of the NCEP Climate Forecast System (CFSv2) was made operational at NCEP in March 2011. This version has upgrades to nearly all aspects of the data assimilation and forecast model components of the system. A coupled reanalysis was made over a 32-yr period (1979–2010), which provided the initial conditions to carry out a comprehensive reforecast over 29 years (1982–2010). This was done to obtain consistent and stable calibrations, as well as skill estimates for the operational subseasonal and seasonal predictions at NCEP with CFSv2. The operational implementation of the full system ensures a continuity of the climate record and provides a valuable up-to-date dataset to study many aspects of predictability on the seasonal and subseasonal scales. Evaluation of the reforecasts show that the CFSv2 increases the length of skillful MJO forecasts from 6 to 17 days (dramatically improving subseasonal forecasts), nearly doubles the skill of seasonal forecasts of 2-m temperatures over the United States, and significantly improves global SST forecasts over its predecessor. The CFSv2 not only provides greatly improved guidance at these time scales but also creates many more products for subseasonal and seasonal forecasting with an extensive set of retrospective forecasts for users to calibrate their forecast products. These retrospective and real-time operational forecasts will be used by a wide community of users in their decision making processes in areas such as water management for rivers and agriculture, transportation, energy use by utilities, wind and other sustainable energy, and seasonal prediction of the hurricane season.

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