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Impact of the Pacific-Japan Teleconnection Pattern on July Sea Fog over the Northwestern Pacific: Interannual Variations and Global Warming Effect


doi: 10.1007/s00376-015-5097-4

  • The northwestern Pacific (NWP) is a fog-prone area, especially the ocean east of the Kuril Islands. The present study analyzes how the Pacific-Japan (PJ) teleconnection pattern influences July sea fog in the fog-prone area using independent datasets. The covariation between the PJ index and sea fog frequency (SFF) index in July indicates a close correlation, with a coefficient of 0.62 exceeding the 99% confidence level. Composite analysis based on the PJ index, a case study, and model analysis based on GFDL-ESM2M, show that in high PJ index years the convection over the east of the Philippines strengthens and then triggers a Rossby wave, which propagates northward to maintain an anticyclonic anomaly in the midlatitudes, indicating a northeastward shift of the NWP subtropical high. The anticyclonic anomaly facilitates the formation of relatively stable atmospheric stratification or even an inversion layer in the lower level of the troposphere, and strengthens the horizontal southerly moisture transportation from the tropical-subtropical oceans to the fog-prone area. On the other hand, a greater meridional SST gradient over the cold flank of the Kuroshio Extension, due to ocean downwelling, is produced by the anticyclonic wind stress anomaly. Both of these two aspects are favorable for the warm and humid air to cool, condense, and form fog droplets, when air masses cross the SST front. The opposite circumstances occur in low PJ index years, which are not conducive to the formation of sea fog. Finally, a multi-model ensemble mean projection reveals a prominent downward trend of the PJ index after the 2030s, implying a possible decline of the SFF in this period.
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  • Carton J. A., B. S. Giese, 2008: A reanalysis of ocean climate using Simple Ocean Data Assimilation (SODA). Mon. Wea. Rev., 136, 2999- 3017.10.1175/2007MWR1978.1454a78caf21a0c20ffebed73838f4b6ahttp%3A%2F%2Fadsabs.harvard.edu%2Fabs%2F2008MWRv..136.2999Chttp://adsabs.harvard.edu/abs/2008MWRv..136.2999CAbstract This paper describes the Simple Ocean Data Assimilation (SODA) reanalysis of ocean climate variability. In the assimilation, a model forecast produced by an ocean general circulation model with an average resolution of 0.25° × 0.4° × 40 levels is continuously corrected by contemporaneous observations with corrections estimated every 10 days. The basic reanalysis, SODA 1.4.2, spans the 44-yr period from 1958 to 2001, which complements the span of the 40-yr European Centre for Medium-Range Weather Forecasts (ECMWF) atmospheric reanalysis (ERA-40). The observation set for this experiment includes the historical archive of hydrographic profiles supplemented by ship intake measurements, moored hydrographic observations, and remotely sensed SST. A parallel run, SODA 1.4.0, is forced with identical surface boundary conditions, but without data assimilation. The new reanalysis represents a significant improvement over a previously published version of the SODA algorithm. In particular, eddy kinetic energy and sea level variability are much larger than in previous versions and are more similar to estimates from independent observations. One issue addressed in this paper is the relative importance of the model forecast versus the observations for the analysis. The results show that at near-annual frequencies the forecast model has a strong influence, whereas at decadal frequencies the observations become increasingly dominant in the analysis. As a consequence, interannual variability in SODA 1.4.2 closely resembles interannual variability in SODA 1.4.0. However, decadal anomalies of the 0–700-m heat content from SODA 1.4.2 more closely resemble heat content anomalies based on observations.
    Clement A. C., R. Burgman, and J. R. Norris, 2009: Observational and model evidence for positive low-level cloud feedback. Science, 325, 460- 464.10.1126/science.117125519628865126799b2cd05d3fcacf14682e1121129http%3A%2F%2Fmed.wanfangdata.com.cn%2FPaper%2FDetail%2FPeriodicalPaper_PM19628865http://med.wanfangdata.com.cn/Paper/Detail/PeriodicalPaper_PM19628865Feedbacks involving low-level clouds remain a primary cause of uncertainty in global climate model projections. This issue was addressed by examining changes in low-level clouds over the Northeast Pacific in observations and climate models. Decadal fluctuations were identified in multiple, independent cloud data sets, and changes in cloud cover appeared to be linked to changes in both local temperature structure and large-scale circulation. This observational analysis further indicated that clouds act as a positive feedback in this region on decadal time scales. The observed relationships between cloud cover and regional meteorological conditions provide a more complete way of testing the realism of the cloud simulation in current-generation climate models. The only model that passed this test simulated a reduction in cloud cover over much of the Pacific when greenhouse gases were increased, providing modeling evidence for a positive low-level cloud feedback.
    Dunne J.P., Coauthors , 2012: GFDL's ESM2 global coupled climate-carbon earth system models. Part I: physical formulation and baseline simulation characteristics. J. Climate, 25, 6646- 6665.10.1175/JCLI-D-11-00560.117ee3468-6d6e-4896-b5b5-decd23a1be10c30fd68884a88979d418e8c82289d0c8http%3A%2F%2Fadsabs.harvard.edu%2Fabs%2F2012JCli...25.6646Drefpaperuri:(51c0f4c6fe097b6e1c8be211b12d9a4f)http://adsabs.harvard.edu/abs/2012JCli...25.6646DAbstract The physical climate formulation and simulation characteristics of two new global coupled carbon–climate Earth System Models, ESM2M and ESM2G, are described. These models demonstrate similar climate fidelity as the Geophysical Fluid Dynamics Laboratory’s previous Climate Model version 2.1 (CM2.1) while incorporating explicit and consistent carbon dynamics. The two models differ exclusively in the physical ocean component; ESM2M uses Modular Ocean Model version 4p1 with vertical pressure layers while ESM2G uses Generalized Ocean Layer Dynamics with a bulk mixed layer and interior isopycnal layers. Differences in the ocean mean state include the thermocline depth being relatively deep in ESM2M and relatively shallow in ESM2G compared to observations. The crucial role of ocean dynamics on climate variability is highlighted in El Ni09o–Southern Oscillation being overly strong in ESM2M and overly weak in ESM2G relative to observations. Thus, while ESM2G might better represent climate changes relating to total heat content variability given its lack of long-term drift, gyre circulation, and ventilation in the North Pacific, tropical Atlantic, and Indian Oceans, and depth structure in the overturning and abyssal flows, ESM2M might better represent climate changes relating to surface circulation given its superior surface temperature, salinity, and height patterns, tropical Pacific circulation and variability, and Southern Ocean dynamics. The overall assessment is that neither model is fundamentally superior to the other, and that both models achieve sufficient fidelity to allow meaningful climate and earth system modeling applications. This affords the ability to assess the role of ocean configuration on earth system interactions in the context of two state-of-the-art coupled carbon–climate models.
    Fu G., Y. J. Song., 2014: Climatology characteristics of sea fog frequency over the Northern Pacific. Periodical of Ocean University of China, 44, 35- 41. (in Chinese)284f171bad856149864a3923baa4f9dbhttp%3A%2F%2Fen.cnki.com.cn%2FArticle_en%2FCJFDTotal-QDHY201410005.htmhttp://en.cnki.com.cn/Article_en/CJFDTotal-QDHY201410005.htmIn this paper,the International Comprehensive Ocean-Atmosphere Data Set(ICOADS)is utilized to investigate the temporal and spatial distribution of sea fog over the Northern Pacific and the East Asian Seas,as well as the characteristics of meteorological elements that are favorable for sea fog occurrence.The"occurrence frequency"of sea fog(hereafter"sea fog frequency ")derived from ICOADS covering 100-year from 1909 to 2008is examined to display the monthly distribution of sea fog frequency based upon two grid sizes(2(°)×2(°)over the Northern Pacific,but 1(°)×1(°)over the East Asian Seas).It is found that sea fog mainly occurs over the middle-and high-latitude regions of the Northern Pacific.The sea fog frequency from the Hokkaido to the Aleutian Islands is larger,and its maximum value is above 40%in June and July.However,the sea fog frequency over the low-latitude waters is almost zero.The period from April to August is a most frequent season for sea fog occurrence over the Northwestern Pacific.From April to July,sea fog mainly occurs over the Yellow Sea,the East China Sea and the Bohai Sea.In June,the maximum value of sea fog frequency over the southern waters of Shandong Peninsula may reach to 20%.After August,the sea fog frequency over the seas may suddenly reduce below to 5%.Corresponding to the synoptic observations,the relationship between sea fog occurrence and meteorological elements is also discussed in the vicinity of Kuril Islands.When the atmospheric horizontal visibility is less than 1 000 m,usually the southerly,southeasterly and southwesterly are dominated over the oceans,and the wind speed is from 4.4to 12.3ms-1.And the air temperature is usually close to dew-point temperature,and sometimes even lower than dew-point temperature.In the east region of the Kuril islands before the sea fog occurrence,the temperature difference between air and sea is around-1~3 ℃.
    Gao S. H., H. Lin, B. Shen, and G. Fu, 2007: A heavy sea fog event over the Yellow Sea in March 2005: Analysis and numerical modeling. Adv. Atmos. Sci.,24, 65-81, doi: 10.1007/s00376-007-0065-2.10.1007/s00376-007-0065-23662de97-be98-4e0e-b4cf-6151157d6820ef86d6d3a01d4c96c58f72c30a04a53ahttp%3A%2F%2Flink.springer.com%2F10.1007%2Fs00376-007-0065-2refpaperuri:(a0970f3c0d840e135bc10da545824437)http://d.wanfangdata.com.cn/Periodical_dqkxjz-e200701007.aspxIn this paper, a heavy sea fog episode that occurred over the Yellow Sea on 9 March 2005 is investigated.The sea fog patch, with a spatial scale of several hundred kilometers at its mature stage, reduced visibility along the Shandong Peninsula coast to 100 m or much less at some sites. Satellite images, surface observations and soundings at islands and coasts, and analyses from the Japan Meteorology Agency (JMA) are used to describe and analyze this event. The analysis indicates that this sea fog can be categorized as advection cooling fog. The main features of this sea fog including fog area and its movement are reasonably reproduced by the Fifth-generation Pennsylvania State University/National Center for Atmospheric Research Mesoscale Model (MM5). Model results suggest that the formation and evolution of this event can be outlined as:(1) southerly warm/moist advection of low-level air resulted in a strong sea-surface-based inversion with a thickness of about 600 m; (2) when the inversion moved from the warmer East Sea to the colder Yellow Sea, a thermal internal boundary layer (TIBL) gradually formed at the base of the inversion while the sea fog grew in response to cooling and moistening by turbulence mixing; (3) the sea fog developed as the TIBL moved northward and (4) strong northerly cold and dry wind destroyed the TIBL and dissipated the sea fog. The principal findings of this study are that sea fog forms in response to relatively persistent southerly warm/moist wind and a cold sea surface, and that turbulence mixing by wind shear is the primary mechanism for the cooling and moistening the marine layer. In addition, the study of sensitivity experiments indicates that deterministic numerical modeling offers a promising approach to the prediction of sea fog over the Yellow Sea but it may be more efficient to consider ensemble numerical modeling because of the extreme sensitivity to model input.
    Gao S. H., S. B. Zhang, Y. L. Qi, and G. Fu, 2010: Initial conditions improvement of sea fog numerical modeling over the Yellow Sea by using cycling 3DVAR-Part II: RAMS numerical experiments. Periodical of Ocean University of China, 40, 1- 10, 18. (in Chinese)
    Hu R. J., F. Zhou, 1997: A numerical study on the effects on air sea conditions on the process of sea fog. Journal of Ocean University of China, 27, 282- 290. (in Chinese)c1f8849a-a3da-4e75-b3ba-eb5e6e4311d7c2cd76a1038b92a2c9f8a0256721a097http%3A%2F%2Fen.cnki.com.cn%2FArticle_en%2FCJFDTOTAL-QDHY703.002.htmrefpaperuri:(a24760038feeb37586e8dbe2a44c74ef)http://en.cnki.com.cn/Article_en/CJFDTOTAL-QDHY703.002.htmUsing a two dimensional model, the effects of air sea condions such as air temperature, humidity, wind and sea surface temprature on the process of seafog are studied. It is shown that (1) sea temperature has a great influence on the initial formation of seafog and a decreasing control after seafog formation; (2) a great gradient of air temperature and a reverse lapse of temperature is not of benifit and not absolutely necessary for the formation of seafog, respectively; (3) the magnitude and the distribution of relative humidity play a critical impotrant role on fog formation and development; (4) wind with higher speeds impedes the formation of seafog but promotes the development of seafog once it has formed.
    Huang G., X. Qu, 2009: Meridional location of west pacific subtropical high in Summer in IPCC AR4 simulation. Transactions of Atmospheric Sciences, 32, 351- 359. (in Chinese)
    Huang R. H., 1990: Studies on the teleconnections of the general circulation anomalies of East Asia causing the summer drought and flood in China and their physical mechanism. Scientia Atmospheric Sinica, 14, 108- 117. (in Chinese)10.1007/BF030088747a469075ce9af592fbae660c35180d10http%3A%2F%2Fwww.cqvip.com%2Fqk%2F91836X%2F199001%2F224974.htmlhttp://www.cnki.com.cn/Article/CJFDTotal-DQXK199001013.htm本文综述了引起我国夏季旱涝的东亚大范围、持续性大气环流异常遥相关方面的国内外研究状况。本文特别强调了关于夏季东亚大气环流异常遥相关物理机制的研究,其中不少研究是作者多年努力的成果。本文还指出在这方面应进一步研究的问题。
    Huang R. H., W. J. Li, 1987: Influence of the anomaly of heat source over the northwestern tropical Pacific for the subtropical high over East Asia. Proc. International Conf. on the General Circulation of East Asia, April 10-15, 1987,Chengdu, China, 40- 45.
    Klein S. A., D. L. Hartmann, 1993: The seasonal cycle of low stratiform clouds. J. Climate, 6, 1587- 1606.10.1175/1520-0442(1993)006<1587:TSCOLS>2.0.CO;28404e14e29af5b92da7ca738528124cehttp%3A%2F%2Fadsabs.harvard.edu%2Fabs%2F1993JCli....6.1587Khttp://adsabs.harvard.edu/abs/1993JCli....6.1587KAbstract The seasonal cycle of low stratiform clouds is studied using data from surface-based cloud climatologies. The impact of low clouds on the radiation budget is illustrated by comparison of data from the Earth Radiation Budget Experiment with the cloud climatologies. Ten regions of active stratocumulus convection are identified. These regions fall into four categories: subtropical marine, midlatitude marine, Arctic stratus, and Chinese stratus. With the exception of the Chinese region, all the regions with high amounts of stratus clouds are over the oceans. In all regions except the Arctic, the season of maximum stratus corresponds to the season of greatest lower-troposphere static stability. Interannual variations in stratus cloud amount also are related to changes in static stability. A linear analysis indicates that a 6% increase in stratus fractional area coverage is associated with each 1掳C increase in static stability. Over midlatitude oceans, sky-obscuring fog is a large component of the summertime stratus amount. The amount of fog appears to be related to warm advection across sharp gradients of SST.
    Kora\vcin, D., J. Lewis, W. T. Thompson, 2001: Transition of stratus into fog along the California coast: observations and modeling. J. Atmos. Sci., 58, 1714- 1731.10.1175/1520-0469(2001)058<1714:TOSIFA>2.0.CO;2f294d3414474b19103a9edb683dcd93ehttp%3A%2F%2Fadsabs.harvard.edu%2Fabs%2F2001JAtS...58.1714Khttp://adsabs.harvard.edu/abs/2001JAtS...58.1714KABSTRACT A case of fog formation along the California coast is examined with the aid of a one-dimensional, higher-order, turbulence-closure model in conjunction with a set of myriad observations. The event is characterized by persistent along-coast winds in the marine layer, and this pattern justifies a Lagrangian approach to the study. A slab of marine layer air is tracked from the waters near the California-Oregon border to the California bight over a 2-day period. Observations indicate that the marine layer is covered by stratus cloud and comes under the influence of large-scale subsidence and progressively increasing sea surface temperature along the southbound trajectory.It is hypothesized that cloud-top cooling and large-scale subsidence are paramount to the fog formation process. The one-dimensional model, evaluated with various observations along the Lagrangian path, is used to test the hypothesis. The principal findings of the study are 1) fog forms in response to relatively long preconditioning of the marine layer, 2) radiative cooling at the cloud top is the primary mechanism for cooling and mixing the cloud-topped marine layer, and 3) subsidence acts to strengthen the inversion above the cloud top and forces lowering of the cloud. Although the positive fluxes of sensible and latent heat at the air-sea interface are the factors that govern the onset of fog, sensitivity studies with the one-dimensional model indicate that these sensible and latent heat fluxes are of secondary importance as compared to subsidence and cloud-top cooling. Sensitivity tests also suggest that there is an optimal inversion strength favorable to fog formation and that the moisture conditions above the inversion influence fog evolution.
    Kosaka Y., H. Nakamura, 2006: Structure and dynamics of the summertime Pacific-Japan teleconnection pattern. Quart. J. Roy. Meteor. Soc., 132, 2009- 2030.
    Kosaka Y., H. Nakamura, 2008: A comparative study on the dynamics of the Pacific-Japan (PJ) teleconnection pattern based on reanalysis datasets. SOLA, 4, 9- 12.10.2151/sola.2008-003ab7e24b0b9a20453a968454a39a15eb5http%3A%2F%2Fci.nii.ac.jp%2Fnaid%2F130004940885%2Fhttp://ci.nii.ac.jp/naid/130004940885/ABSTRACT
    Kosaka Y., H. Nakamura, 2010: Mechanisms of meridional teleconnection observed between a summer monsoon system and a subtropical anticyclone. Part II: A global survey. J. Climate, 23, 5109- 5125.10.1175/2010JCLI3414.12b6d163f238d4db93dc2e3455e931e2fhttp%3A%2F%2Fwww.cabdirect.org%2Fabstracts%2F20103338197.htmlhttp://www.cabdirect.org/abstracts/20103338197.htmlSummertime atmospheric circulation over the midlatitude western North Pacific (WNP) is influenced by anomalous convective activity near the Philippines. This meridional teleconnection, observed in monthly anomalies and known as the Pacific-Japan (PJ) pattern, is characterized by zonally elongated cyclonic and anticyclonic anomalies around the enhanced convection center and to its northeast, res...
    Kosaka Y., H. Nakamura, 2011: Dominant mode of climate variability, intermodel diversity, and projected future changes over the summertime Western North Pacific simulated in the CMIP3 models. J. Climate, 24, 3935- 3955.10.1175/2011JCLI3907.191e55027-f126-4624-a372-5a5543da0356b65642fd1c0dca848555d4c51c8bfd41http%3A%2F%2Fadsabs.harvard.edu%2Fabs%2F2011JCli...24.3935Krefpaperuri:(bac28e4bdf86f87451b9715dbd92553d)http://adsabs.harvard.edu/abs/2011JCli...24.3935KAbstract A set of multimodel twentieth-century climate simulations for phase 3 of the Coupled Model Intercomparison Project (CMIP3) is analyzed to assess the model reproducibility of the Pacific apan (PJ) teleconnection pattern. It is the dominant low-frequency anomaly pattern over the summertime western North Pacific (WNP), characterized by a meridional dipole of zonally elongated vorticity anomalies in the lower troposphere and by anomalous precipitation over the tropical WNP. Most of the models can reproduce the PJ pattern reasonably well as one of the leading anomaly patterns or their combination. The model reproducibility of the pattern tends to be higher for those models in which the climatological-mean state over the WNP is better reproduced. Furthermore, intermodel diversity in the summertime climatological-mean fields over the WNP, especially in the lower troposphere, is found to be large and projected most strongly onto the observed PJ pattern. Nevertheless, the multimodel ensemble (MME) mean of these climatological-mean states is close to the observations. Projected future changes in the summertime climatological-mean state under the Intergovernmental Panel on Climate Change (IPCC) Special Report on Emission Scenarios (SRES) A1B also bear certain similarities with the PJ pattern, in a manner consistent with the aforementioned sensitivity of the model climate to that pattern. The MME projection indicates an overall increase in precipitation over the entire tropics, but it is overwhelmed locally by the effects of the enhanced tropospheric stratification over the tropical WNP. A resultant local reduction of the mean ascent is dynamically consistent with the anticyclonic projection around the Philippines and the cyclonic projection around Japan in MME, as in the observed anomalous dipole associated with the PJ pattern. However, the polarity and magnitude of the PJ-like projected change vary substantially from one model to another.
    Kosaka Y., H. Nakamura, M. Watanabe, and M. Kimoto, 2009: Analysis on the dynamics of a wave-like teleconnection pattern along the summertime Asian jet based on a reanalysis dataset and climate model simulations. J. Meteor. Soc.Japan, 87, 561- 580.10.2151/jmsj.87.56102fd34ff-90ce-47d5-b583-cace2e0d3839b7b9084a4d867d687cb468766d9a81e2http%3A%2F%2Fci.nii.ac.jp%2Fnaid%2F130004788706refpaperuri:(6f159afb8d4582b6c50df135b7b87040)http://ci.nii.ac.jp/naid/130004788706The Silk Road pattern, a wave-like anomaly pattern observed along the summertime Asian jet, is one of the major teleconnection patterns that can influence the East Asian summertime climate. Our analysis based on a reanalysis (JRA-25) dataset confirms the conventional notion that the pattern has a characteristic of a free stationary Rossby wave train, with its horizontal wavenumber close to the stationary Rossby wavenumber determined by the mean intensity of the jet. However, our analysis reveals its more essential characteristic as a dynamical mode whose extraction of available potential energy from the baroclinic Asian jet is highly efficient for its self-maintenance. Our analysis also reveals high sensitivity of its barotropic energy conversion to subtle zonal asymmetries of the Asian jet, which can be regarded as a critical factor to anchor the strongest vorticity anomaly around the western jet core and thereby determine the preferred longitudinal phase alignment of the wave train as observed. In fact, singular value decomposition of a global baroclinic model linearized about the observed mean state for boreal summer leads to identification of a perturbation similar to the Silk Road pattern with respect to its structure and energetics. It is thus indicated that the configuration of the mean flow determines the dominant phase, as well as the meridional location and the wavenumber, of the Silk Road pattern.The aforementioned dynamical characteristics of the Silk Road pattern are found useful for assessing and interpreting the reproducibility of the pattern in the present-day climate simulated in climate models that participated in the phase 3 of the Coupled Model Intercomparison Project (CMIP3). The pattern tends to be identified as the dominant mode of upper-tropospheric meridional wind variability as observed in such models that can reproduce the mean Asian jet realistically, including its zonal structure, which confirms the dynamics of the Silk Road pattern revealed in our observational analysis. On the basis of our analysis, a metric is proposed for assessing the models' reproducibility of the pattern.
    Li M., S. P. Zhang, 2013: Impact of sea surface temperature front on stratus-sea fog over the Yellow and East China Seas-case study with implications for climatology. Journal of Ocean University of China, 12, 301- 311.
    Lu R. Y., R. H. Huang, 1998: Influence of East Asia/Pacific teleconnection pattern on the interannual variations of the blocking highs over the Northeastern Asia in summer. Scientia Atmospheric Sinica, 22, 727- 734. (in Chinese)f404483c021ef579455f1b672c370b30http%3A%2F%2Fen.cnki.com.cn%2FArticle_en%2FCJFDTOTAL-DQXK805.006.htmhttp://en.cnki.com.cn/Article_en/CJFDTOTAL-DQXK805.006.htmBy the 1980锝1988 ECWMF data, the interannual variations of the blocking highs over the northeastern Asia in summer and their relation to the precipitations over the Yangtze River and Huaihe River basin in summer are analysed The results show that the blocking highs over the northeastern Asia in summer have obviously interannual variations The results also show that there is a close relation between blocking highs over the northeastern Asia and the precipitations over the Yangtze River and Huaihe River basin: when blocking highs occur frequently over the northeastern Asia in summer, the precipitations over the Yangtze River and Huaihe River basin are more than normal; when blocking highs occur seldom, the precipitations are less than normal To investigate the causes of the above noted results, we analysed the sea surface temperature (SST) anomalies, and simulated the influence of the SST anomalies in the tropical western Pacific on the blocking highs over the northeastern Asia, using the composite SST anomalies Results show that the East Asia/Pacific teleconnection pattern caused by the SST anomalies in the tropical western Pacific is one of the important causes of producing the interannual variations of the blocking highs over the northeastern Asia in summer and their relation to the summer precipitations over the Yangtze River and Huaihe River basin
    Lu J., C. Gang, and D. M. W. Frierson, 2008: Response of the zonal mean atmospheric circulation to El Niño versus global warming. J. Climate, 21, 5835- 5851.10.1175/2008JCLI2200.13ea20202-cb34-4c54-a84f-c51490a2147aa70dbe3a94d2d1d1df443803b9b90dfbhttp%3A%2F%2Fadsabs.harvard.edu%2Fabs%2F2008JCli...21.5835Lrefpaperuri:(5417908c47455f8c2033056a44445f26)http://adsabs.harvard.edu/abs/2008JCli...21.5835LABSTRACT
    Nitta T., 1987: Convective activities in the tropical Western Pacific and their impact on the northern Hemisphere summer circulation. J. Meteor. Soc.Japan, 65, 373- 390.10.1175/1520-0469(1987)044<1554:TAOPVT>2.0.CO;2af5b68de-3681-4ebe-ae76-3e53b273cf8e84fda2b986d0d4e7d94b9557e8a62161http%3A%2F%2Fci.nii.ac.jp%2Fnaid%2F10013126166%2Frefpaperuri:(9b2fb89014c1d66010d07550d41568c2)http://ci.nii.ac.jp/naid/10013126166/Investigation, à l'aide de la couverture nuageuse vue par satellite, de la TSM (SST) et du géopotentiel, toutes données sur 7 ans (1978-84), des variations interannuelle et intrasaisonnière de l'activité convective en été, dans le Pacifique tropical ouest, ainsi que de l'impact sur la circulation dans l'hémisphère nord. Résultats principaux: lorsque la TSM est plus chaude de 1,0°C que la normale, les régions de convection active (typhons, dépressions tropicales) se déplacent vers le NE à partir d'une position normale près des Philippines jusqu'à 20 N, la couverture nuageuse dans les zones tempérée et équatoriale est fortement atténuée; une anomalie de haute p prédomine dans la zone tempérée (de la Chine est jusqu'au Pacifique nord); l'activité convective est très modulée par la variation intrasaisonnière; il existe des trains d'ondes de hauteur géopotentielle qui émanent de la source de chaleur qui s'étend des Philippines à l'Amérique du Nord; ils sont générés lorsque l'activité convective dans la mer des Philippines devient intense; en conclusion les ondes de Rossby sont générées par la source de chaleur associée à la variation intrasaisonnière; des anomalies de p en Asie de l'Est peuvent être considérées comme une conséquence de la génération de ces ondes
    Norris J. R., C. B. Leovy, 1994: Interannual variability in stratiform cloudiness and sea surface temperature. J. Climate, 7, 1915- 1925.10.1175/1520-0442(1994)007<1915:IVISCA>2.0.CO;2a5a2948c327bc5e761bcd4d8b13f2c12http%3A%2F%2Fadsabs.harvard.edu%2Fabs%2F1994JCli....7.1915Nhttp://adsabs.harvard.edu/abs/1994JCli....7.1915NAbstract Marine stratiform cloudiness (MSC) (stratus, stratocumulus, and fog) is widespread over subtropical oceans west of the continents and over midlatitude oceans during summer, the season when MSC has maximum influence on surface downward radiation and is most influenced by boundary-layer processes. Long-term datasets of cloudiness and sea surface temperature (SST) from surface observations from 1952 to 1981 are used to examine interannual variations in MSC and SST. Linear correlations of anomalies in seasonal MSC amount with seasonal SST anomalies are negative and significant in midlatitude and eastern subtropical oceans, especially during summer. Significant negative correlations between SST and nimbostratus and nonprecipitating midlevel cloudiness are also observed at midlatitudes during summer, suggesting that summer storm tracks shift from year to year following year-to-year meridional shifts in the SST gradient. Over the 30-yr period, there are significant upward trends in MSC amount over the northern midlatitude oceans and a significant downward trend off the coast of California. The highest correlations and trends occur where gradients in MSC and SST are strongest. During summer, correlations between SST and MSC anomalies peak at zero lag in midlatitudes where warm advection prevails, but SST lags MSC in subtropical regions where cold advection predominates. This difference is attributed to a tendency for anomalies in latent heat flux to compensate anomalies in surface downward radiation in warm advection regions but not in cold advection regions.
    Saha S., Coauthors , 2010: The NCEP climate forecast system reanalysis. Bull. Amer. Meteor. Soc., 91, 1015- 1057.10.1175/2010BAMS3001.14c0ac0d59c0ed958eb2a699acc395abdhttp%3A%2F%2Fwww.cabdirect.org%2Fabstracts%2F20103296323.htmlhttp://www.cabdirect.org/abstracts/20103296323.htmlAbstract The NCEP Climate Forecast System Reanalysis (CFSR) was completed for the 31-yr period from 1979 to 2009, in January 2010. The CFSR was designed and executed as a global, high-resolution coupled atmosphere–ocean–land surface–sea ice system to provide the best estimate of the state of these coupled domains over this period. The current CFSR will be extended as an operational, real-time product into the future. New features of the CFSR include 1) coupling of the atmosphere and ocean during the generation of the 6-h guess field, 2) an interactive sea ice model, and 3) assimilation of satellite radiances by the Gridpoint Statistical Interpolation (GSI) scheme over the entire period. The CFSR global atmosphere resolution is ~38 km (T382) with 64 levels extending from the surface to 0.26 hPa. The global ocean's latitudinal spacing is 0.25° at the equator, extending to a global 0.5° beyond the tropics, with 40 levels to a depth of 4737 m. The global land surface model has four soil levels and the global sea ice model has three layers. The CFSR atmospheric model has observed variations in carbon dioxide (CO 2 ) over the 1979–2009 period, together with changes in aerosols and other trace gases and solar variations. Most available in situ and satellite observations were included in the CFSR. Satellite observations were used in radiance form, rather than retrieved values, and were bias corrected with “spin up” runs at full resolution, taking into account variable CO 2 concentrations. This procedure enabled the smooth transitions of the climate record resulting from evolutionary changes in the satellite observing system. CFSR atmospheric, oceanic, and land surface output products are available at an hourly time resolution and a horizontal resolution of 0.5° latitude × 0.5° longitude. The CFSR data will be distributed by the National Climatic Data Center (NCDC) and NCAR. This reanalysis will serve many purposes, including providing the basis for most of the NCEP Climate Prediction Center's operational climate products by defining the mean states of the atmosphere, ocean, land surface, and sea ice over the next 30-yr climate normal (1981–2010); providing initial conditions for historical forecasts that are required to calibrate operational NCEP climate forecasts (from week 2 to 9 months); and providing estimates and diagnoses of the Earth's climate state over the satellite data period for community climate research. Preliminary analysis of the CFSR output indicates a product that is far superior in most respects to the reanalysis of the mid-1990s. The previous NCEP–NCAR reanalyses have been among the most used NCEP products in history; there is every reason to believe the CFSR will supersede these older products both in scope and quality, because it is higher in time and space resolution, covers the atmosphere, ocean, sea ice, and land, and was executed in a coupled mode with a more modern data assimilation system and forecast model. A supplement to this article is available online: DOI: 10.1175/2010BAMS3001.2.S1
    Smith T. M., R. W. Reynolds, T. C. Peterson, and J. Lawrimore, 2008: Improvements to NOAAs historical merged land-ocean temp analysis (1880-2006). J. Climate, 21, 2283- 2296.
    Sugimoto S., T. Sato, and K. Nakamura, 2013: Effects of synoptic-scale control on long-term declining trends of summer fog frequency over the pacific side of Hokkaido Island. J. Appl. Meteor. and Climatol., 52, 2226- 2242.eb58189d1f4bc171e913e968f0d42adchttp%3A%2F%2Fadsabs.harvard.edu%2Fabs%2F2013JApMC..52.2226S/s?wd=paperuri%3A%28caa669f8cf027b7d4bb9b61b96629b3e%29&filter=sc_long_sign&tn=SE_xueshusource_2kduw22v&sc_vurl=http%3A%2F%2Fadsabs.harvard.edu%2Fabs%2F2013JApMC..52.2226S&ie=utf-8
    Takaya K., H. Nakamura, 2001: A formulation of a phase-independent wave-activity flux for stationary and migratory quasi geostrophic eddies on a zonally varying basic flow. J. Atmos. Sci., 58, 608- 627.10.1175/1520-0469(2001)058<0608:AFOAPI>2.0.CO;22eaffd83-f431-4eed-8090-96669e71b247cd8c40c8181e2ef17726a6d7ec840f85http%3A%2F%2Fwww.researchgate.net%2Fpublication%2F249610023_A_Formulation_of_a_Phase-Independent_Wave-Activity_Flux_for_Stationary_and_Migratory_Quasigeostrophic_Eddies_on_a_Zonally_Varying_Basic_Flowrefpaperuri:(48fdd5619a2cc4d95799548d32c1f6e7)http://www.researchgate.net/publication/249610023_A_Formulation_of_a_Phase-Independent_Wave-Activity_Flux_for_Stationary_and_Migratory_Quasigeostrophic_Eddies_on_a_Zonally_Varying_Basic_FlowPresents a study which derived a formulation of an approximate conservation relation of wave-activity pseudomomentum applicable for stationary or migratory quasigeostrophic (QG) eddies on a zonally varying basic flow. Description of the formulation of a phase-independent wave-activity flux for QG eddies; Physical interpretations of phase-independent wave-activity fluxes; Conclusions.
    TAMU Research Group, 2014: SODA 2.2. 4.
    [ Available online at http://sodaserver.tamu.edu/assim/SODA2.2.4/]
    Wang B. H., 1983: Sea Fog. China Ocean Press, Beijing, 352 pp. (in Chinese)d090138ec5d65a6b9bd1a15ba12258b6http%3A%2F%2Fci.nii.ac.jp%2Fncid%2FBA58254824http://ci.nii.ac.jp/ncid/BA58254824CiteSeerX - Scientific documents that cite the following paper: Sea Fog
    Wang X., F. Huang, and X. Zhou, 2006: Climatic characteristics of sea fog formation of the Huanghai Sea in summer. Acta Oceanologica Sinica, 28, 26- 34. (in Chinese)10.1016/S1001-8042(06)60021-33a43fe53445a574a0ddf0bf3c30052e4http%3A%2F%2Fen.cnki.com.cn%2FArticle_en%2FCJFDTotal-SEAC200601003.htmhttp://en.cnki.com.cn/Article_en/CJFDTotal-SEAC200601003.htmBy using composed and case analysis the climatic background of sea fog formation of the Huanghai Sea in summer(July) has been analyzed,which includes circulation,vapour transport condition,SST,and net long wave radiation.The results show that the summer monsoon determines the foggy days,and vapour formatted fog is not afforded by local atmosphere but by lower tropospheric jet from tropic atmosphere.Cooperated with the circulation,the SST is very important for the formation of fog.
    Weaver C. P., V. Ramanathan, 1997: Relationships between large-scale vertical velocity, static stability, and cloud radiative forcing over Northern Hemisphere Extratropical Oceans. J. Climate, 10, 2871- 2887.10.1175/1520-0442(1997)010<2871:RBLSVV>2.0.CO;2cfff58cf71c744ad5e4d5f6f6f207a20http%3A%2F%2Fadsabs.harvard.edu%2Fabs%2F1997JCli...10.2871Whttp://adsabs.harvard.edu/abs/1997JCli...10.2871WAbstract This paper identifies dynamical and thermodynamical factors that govern the seasonal and interocean differences in cloud cover and cloud radiative forcing (CRF) over the storm track regions of the northern extratropical Pacific and Atlantic Oceans. An outstanding problem of interest is the fact that cloud cover is larger in the summer than winter in the North Pacific, while the converse is true in the North Atlantic. This paper considers separately January and July in the North Pacific and North Atlantic and finds that, on daily timescales, rising motion associated with synoptic-scale events such as cyclones produces greater CRF. However, CRF does not vary much with vertical velocity in regions of subsidence. In addition, increased moist static stability is associated on daily and monthly mean timescales with increased cloud cover and shortwave CRF. These results imply that, on monthly mean timescales, if we hold moist static stability constant, CRF should increase with increasing vertical velocity variance. This effect, by itself, would tend to increase CRF during winter, since the variance of vertical velocity is much larger during winter than summer. This is consistent with what is observed in the North Atlantic. In the North Pacific, however, the mean moist static stability is much larger during summer, and this effect tends to counteract the summertime decrease in vertical velocity variance, resulting in greater summertime cloud cover. Extending the argument to explain interocean differences in cloudiness or CRF during the same season, this paper finds that the North Pacific and North Atlantic have approximately the same CRF (or cloud cover) during winter because the mean vertical velocity variance and moist static stability are approximately the same. The North Pacific is more cloudy than the North Atlantic during summer because, while the mean vertical velocity variance is approximately the same, mean moist static stability is much greater in the North Pacific. Finally, spatial variations in both parameters within a given ocean basin tend to either reinforce each other or compete in their effect on CRF.
    Woodruff, S. D., Coauthors , 2011: ICOADS Release 2.5: Extensions and enhancements to the surface marine meteorological archive. Int. J. Climatol., 31, 951- 967.10.1002/joc.2103ecac71db0999fcac5002bf67a0256968http%3A%2F%2Fonlinelibrary.wiley.com%2Fdoi%2F10.1002%2Fjoc.2103%2Ffullhttp://onlinelibrary.wiley.com/doi/10.1002/joc.2103/fullAbstract Top of page Abstract 1.Introduction 2.The national and international contributing community 3.Release 2.5 4.Data characteristics and unresolved issues 5.Data and product access 6.Community data products derived from ICOADS observations 7.Future plans 8.Conclusions Acknowledgements References Release 2.5 of the International Comprehensive Ocean-Atmosphere Data Set (ICOADS) is a major update (covering 1662–2007) of the world's most extensive surface marine meteorological data collection. Building on extensive national and international partnerships, many new and improved contributing datasets have been processed into a uniform format and combined with the previous Release 2.4. The new data range from early non-instrumental ship observations to measurements initiated in the twentieth century from buoys and other automated platform types. Improvements to existing data include replacing preliminary Global Telecommunication System (GTS) receipts with more reliable, delayed mode reports for post-1997 data, and in the processing and quality control (QC) of humidity observations. Over the entire period of record, spatial and temporal coverage has been enriched and data and metadata quality has been improved. Along with the observations, now updated monthly in near real time, Release 2.5 includes quality-controlled monthly summary products for 2° latitude × 2° longitude (since 1800) and 1° × 1° boxes (since 1960), together with multiple options for access to the data and products. The measured and estimated data in Release 2.5 are subject to many technical changes, multiple archive sources, and historical events throughout the more than three-century record. Some of these data characteristics are highlighted, including known unresolved errors and inhomogeneities, which may impact climate and other research applications. Anticipated future directions for ICOADS aim to continue adding scientific value to the observations, products, and metadata, as well as strengthen the cooperative enterprise through expanded linkages to international initiatives and organisations. Copyright 08 2010 Royal Meteorological Society
    Xie S. P., K. M. Hu, Jan Hafner, H. Tokinaga, Y. Du, G. Huang, and T. Sampe, 2009: Indian Ocean capacitor effect on indo-western Pacific climate during the summer following El Niño. J. Climate, 22, 730- 747.
    Xie S. P., C. Deser, G. A. Vecchi, J. Ma, H. Y. Teng, and A. T. Wittenberg, 2010: Global warming pattern formation: Sea surface temperature and rainfall. J. Climate, 23, 966- 986.10.1175/2009JCLI3329.13eff0181-4d63-488f-92b9-71a15a93bf303eefc59c87e4f4ca7ffcbe050a36a436http%3A%2F%2Fwww.cabdirect.org%2Fabstracts%2F20103118162.htmlrefpaperuri:(b0ebeb07b4f54809d624dfe9936fb36c)http://www.cabdirect.org/abstracts/20103118162.htmlAbstract Spatial variations in sea surface temperature (SST) and rainfall changes over the tropics are investigated based on ensemble simulations for the first half of the twenty-first century under the greenhouse gas (GHG) emission scenario A1B with coupled ocean tmosphere general circulation models of the Geophysical Fluid Dynamics Laboratory (GFDL) and National Center for Atmospheric Research (NCAR). Despite a GHG increase that is nearly uniform in space, pronounced patterns emerge in both SST and precipitation. Regional differences in SST warming can be as large as the tropical-mean warming. Specifically, the tropical Pacific warming features a conspicuous maximum along the equator and a minimum in the southeast subtropics. The former is associated with westerly wind anomalies whereas the latter is linked to intensified southeast trade winds, suggestive of wind vaporation ST feedback. There is a tendency for a greater warming in the northern subtropics than in the southern subtropics in accordance with asymmetries in trade wind changes. Over the equatorial Indian Ocean, surface wind anomalies are easterly, the thermocline shoals, and the warming is reduced in the east, indicative of Bjerknes feedback. In the midlatitudes, ocean circulation changes generate narrow banded structures in SST warming. The warming is negatively correlated with wind speed change over the tropics and positively correlated with ocean heat transport change in the northern extratropics. A diagnostic method based on the ocean mixed layer heat budget is developed to investigate mechanisms for SST pattern formation. Tropical precipitation changes are positively correlated with spatial deviations of SST warming from the tropical mean. In particular, the equatorial maximum in SST warming over the Pacific anchors a band of pronounced rainfall increase. The gross moist instability follows closely relative SST change as equatorial wave adjustments flatten upper-tropospheric warming. The comparison with atmospheric simulations in response to a spatially uniform SST warming illustrates the importance of SST patterns for rainfall change, an effect overlooked in current discussion of precipitation response to global warming. Implications for the global and regional response of tropical cyclones are discussed.
    Xue Y., T. M. Smith, and R. W. Reynolds, 2003: Interdecadal changes of 30-Yr SST normals during 1871-2000. J. Climate, 16, 1601- 1612.10.1175/1520-0442-16.10.1601bbebd145-8ce2-4c96-bfa4-fa8c749a4accc20a4f063700df8ee19ef55b90dc7641http%3A%2F%2Fadsabs.harvard.edu%2Fabs%2F2003JCli...16.1601Xrefpaperuri:(43f25f76e87bb02031dcc4e2d05e08d4)http://adsabs.harvard.edu/abs/2003JCli...16.1601XAbstract SST predictions are usually issued in terms of anomalies and standardized anomalies relative to a 30-yr normal: climatological mean (CM) and standard deviation (SD). The World Meteorological Organization (WMO) suggests updating the 30-yr normal every 10 yr. In complying with the WMO's suggestion, a new 30-yr normal for the 1971–2000 base period is constructed. To put the new 30-yr normal in historical perspective, all the 30-yr normals since 1871 are investigated, starting from the beginning of each decade (1871–1900, 1881–1910, …65, 1971–2000). Using the extended reconstructed sea surface temperature (ERSST) on a 2° grid for 1854–2000 and the Hadley Centre Sea Ice and SST dataset (HadISST) on a 1° grid for 1870–1999, eleven 30-yr normals are calculated, and the interdecadal changes of seasonal CM, seasonal SD, and seasonal persistence ( P ) are discussed. The interdecadal changes of seasonal CM are prominent (0.3°–0.6°) in the tropical Indian Ocean, the midlatitude North Pacific, the midlatitude North Atlantic, most of the South Atlantic, and the sub-Antarctic front. Four SST indices are used to represent the key regions of the interdecadal changes: the Indian Ocean (“INDIAN”; 10°S–25°N, 45°–100°E), the Pacific decadal oscillation (PDO; 35°–45°N, 160°E–160°W), the North Atlantic Oscillation (NAO; 40°–60°N, 20°–60°W), and the South Atlantic (SATL; 22°S–2°N, 35°W–10°E). Both INDIAN and SATL show a warming trend that is consistent between ERSST and HadISST. Both PDO and NAO show a multidecadal oscillation that is consistent between ERSST and HadISST except that HadISST is biased toward warm in summer and cold in winter relative to ERSST. The interdecadal changes in Ni09o-3 (5°S–5°N, 90°–150°W) are small (0.2°) and are inconsistent between ERSST and HadISST. The seasonal SD is prominent in the eastern equatorial Pacific, the North Pacific, and North Atlantic. The seasonal SD in Ni09o-3 varies interdecadally: intermediate during 1885–1910, small during 1910–65, and large during 1965–2000. These interdecadal changes of ENSO variance are further verified by the Darwin sea level pressure. The seasonality of ENSO variance (smallest in spring and largest in winter) also varies interdecadally: moderate during 1885–1910, weak during 1910–65, and strong during 1965–2000. The interdecadal changes of the seasonal SD of other indices are weak and cannot be determined well by the datasets. The seasonal P, measured by the autocorrelation of seasonal anomalies at a two-season lag, is largest in the eastern equatorial Pacific, the tropical Indian, and the tropical North and South Atlantic Oceans. It is also seasonally dependent. The “spring barrier” of P in Ni09o-3 (largest in summer and smallest in winter) varies interdecadally: relatively weak during 1885–1910, moderate during 1910–55, strong during 1955–75, and moderate during 1975–2000. The interdecadal changes of SD and P not only have important implications for SST forecasts but also have significant scientific values to be explored.
    Zhang S. P., X. W. Bao, 2008: The main advances in sea fog research in China. Periodical of Ocean University of China, 38, 359- 366. (in Chinese)10.1007/s11442-008-0201-709a42fc7ad287ad4bf8b647fa59f5b0bhttp%3A%2F%2Fen.cnki.com.cn%2FArticle_en%2FCJFDTOTAL-QDHY200803004.htmhttp://en.cnki.com.cn/Article_en/CJFDTOTAL-QDHY200803004.htmThe Chinese east coast area and the Chinese adjacent marginal seas are foggy regions.Sea fog occurrence is one of the most important events that can lead to low visibility and thus cause casualties and the loss of properties.An effective development of forecasting methods rests upon a comprehensive knowledge of the phenomena.This review covers the main achievements in sea fog research during the past decade in China,including sea fog synoptic and climatic studies,numerical study,fog monitoring and detection by satellite remote sensing and the micro physics of sea fog,and work by the authors.Besides,some outlook is given on future sea fog research.This review provides a helpful summary about sea fog research.
    Zhang H. Y., F. X. Zhou, and X. H. Zhang, 2005: Interannual change of sea fog over the Yellow Sea in spring. Oceanologia et Limnologia Sinica, 36, 36- 42. (in Chinese)518c43c3-626c-45f2-90de-fa32fd35e795273792005361663b2780f98340eed0b766510b76b4ff4http%3A%2F%2Fen.cnki.com.cn%2FArticle_en%2FCJFDTOTAL-HYFZ200501005.htmrefpaperuri:(5ab45b8a410b5511954fd681605fcbee)http://en.cnki.com.cn/Article_en/CJFDTOTAL-HYFZ200501005.htmSea fog is sometimes dangerous condition for aviation and ocean shipping. It occurs mostly between April and July every year, with evident interannual change. It can provide reliable basis for shor-t range climatic forecast, in our case, to understand the climatic condition of sea fog occurrence over the Yellow Sea. Because of the data insufficiency in the area, representative conventional observations along the Yellow Sea coast including Chaoliandao, Qingdao, Haiyangdao were used with NCEP/NCAR data to analyze the interannual change of sea fog over the Yellow Sea in spring. Good correlation was revealed in Chaoliandao, Qingdao and Haiyangdao by statistical analysis, which shows that the interannual change of the Yellow Sea fog is consistent in space, and the climatic background that sea fog occurs across the Yellow Sea is coherent. Therefore, Chaoliandao was taken as the representative station and the data there was used to analyze the interannual change. Because spring time is a transitional stage of atmospheric circulation from winter to summer, and data in May are coherent to the data of whole spring, so May was taken as the representative of spring to analyze the interannual change of sea fog. Abnormity can be evaluated in different scales by the relation between anomaly and standard deviation based on abnormal standard presented by WMO (Word Meteorological Organization). Based on the standardized value, if it is greater than or equal to 1.2, more foggy days year is defined, if less than or equal to -1.2, less foggy days year is considered. The authors found that the climatic conditions favoring the fog formation are weak winter circulation, northward transportation of ample lower level vapors and stable stratification. When sea fog occurs, wind direction is range from S to ESE and the temperature difference between air and sea is range from 0.5°C to 2.2°C. Several conclusions are listed as follows:1. The interannual change of spring sea fog over the Yellow Sea is related to the variability of atmospheric circulation. Abnomal circulation is accompanied by abnormal foggy year. Weak winter circulation is favorable for the northward transport of warm and wet air current from lower latitude producing more foggy days, and vise versa.2. The vapor needed by the sea fog formation and maintenance comes mostly from lower latitude of the Pacific instead of locally provided. Favorable stream field in the lower level provides richer vapor to the Yellow Sea and generate more foggy days, and vise versa.3. In the years of more foggy days, air stratification is stable, and the middle and low levels are moister. The pattern of the east high and west low SLP (surface level pressure) is favorable for moist air transportation from lower latitude and coagulation of the fog in the Yellow Sea.4. Spring sea fog in the Yellow Sea occurs mostly when wind direction is between S and ESE and wind speed ranges from 2m/s to 10m/s, which is obviously different from the radiation fog.5. Case study in the paper showed that sea fog is easy to occur when the temperature difference between air and sea is between 0.5°C and 2.2°C.
    Zhang S. P., S. P. Xie, Q. Y. Liu, Y. Q. Yang, X. G. Wang, and Z. P. Ren, 2009: Seasonal variations of yellow sea fog: Observations and mechanisms. J. Climate, 22, 6758- 6772.10.1175/2009JCLI2806.19e9fae803d132a063d73dd5ab3daf038http%3A%2F%2Fwww.cabdirect.org%2Fabstracts%2F20103053269.htmlhttp://www.cabdirect.org/abstracts/20103053269.htmlSea fog is frequently observed over the Yellow Sea, with an average of 50 fog days on the Chinese coast during April09 uly. 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 10009恪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 ea 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 landea 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 Asian09恪皐estern 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 apan pattern. Back trajectories for foggy and fog-free air masses support the results from the climatological analysis.
    Zhang S. P., Y. Chen, J. C. Long, and G. Han, 2014a: Interannual variability of sea fog frequency in the Northwestern Pacific in July. Atmos. Res., 151, 189- 199.10.1016/j.atmosres.2014.04.004a5903f3e-e5da-40f9-b280-058fea05fe447b56ee8535d6c5b3410d35f97b195624http%3A%2F%2Fwww.sciencedirect.com%2Fscience%2Farticle%2Fpii%2FS0169809514001604http://www.sciencedirect.com/science/article/pii/S0169809514001604The interannual variability in the sea fog frequency (SFF) in July in the midlatitude Northwestern Pacific (40°N–50°N, 140°E–170°W) from 1979 to 2009 is investigated with observations and reanalysis datasets. Composite analysis shows that in high-SSF years the center of the Northwestern Pacific subtropical high (SH) shifts eastward and a strengthened ridge exists in the midlatitude Northwestern Pacific. Under such conditions, large amount of moisture from the subtropics are transported northwardly by the southerlies over the west flank of the SH. The ridge is helpful for stable stratification and conductive to fog formation. In contrast, in low-SFF years the center of the SH expands westward and drifts further south; thus moisture can hardly reach the midlatitudes. Meanwhile an anomalous trough in the midlatitudes and the associated anomalous northerlies both weaken the southerlies and reduce the stability, unfavorable for fog occurrence. The case studies confirmed that the air parcels moving from the subtropical zone to the midlatitudes controlled by the SH, kept the higher temperature and humidity when flowing across the Kuroshio Extension, and then cooled down over the cold oceanic surface in fog case. The SFF in the Northwestern Pacific would decline under the conditions of global warming.
    Zhang S. P., J. C. Long, Y. J. Yin, W. Y. Yang, and W. B. Yang, 2014b: Analysis of the process of a local sea fog lifted into low cloud in eastern China. Periodical of Ocean University of China, 44, 1- 10. (in Chinese)17c72d7c074826214d9335760377cdb4http%3A%2F%2Fen.cnki.com.cn%2FArticle_en%2FCJFDTotal-QDHY201402001.htmhttp://en.cnki.com.cn/Article_en/CJFDTotal-QDHY201402001.htmIn this paper,the Hongjia single-station L-band radar sounding data,high-resolution coupled ocean-atmosphere model reanalysis data,geostationary meteorological satellite imageries and ground observations are used to analyze a local sea fog dissipated process due to the sea fog uplift into the low clouds in the East China Sea.The analysis found that near sea surface wind speed increased suddenly,the mechanical shear strengthening in the marine atmospheric boundary layer(MABL)and upward development of the turbulent mixing layer,resulting in the uplift of sea fog conversion for low clouds.The sudden increase in near sea surface wind speed is related to the high-altitude jet stream northward,trough and ridge amplitude in average layer intensify,the input of positive vorticity advection in front of trough induce the ground low-pressure system development,surface pressure gradient force increases.Near sea surface temperature rise also contributed to the dissipation of sea fog.Rising temperature caused by the combined effect of the warm advection,adiabatic sinking and the air-sea interface heat flux.The downdraft in the cold water side of oceanic front may have a significant influence in warming of adiabatic sinking in MABL and the formation of the height of low cloud.The study provides a new approach to sea fog dissipation forecast.
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Manuscript received: 16 April 2015
Manuscript revised: 02 October 2015
Manuscript accepted: 20 October 2015
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Impact of the Pacific-Japan Teleconnection Pattern on July Sea Fog over the Northwestern Pacific: Interannual Variations and Global Warming Effect

  • 1. Physical Oceanography Laboratory, Ocean-Atmosphere Interaction and Climate Laboratory, Ocean University of China, Qingdao 266100
  • 2. Meteorological bureau of Quanzhou, Quanzhou 362000

Abstract: The northwestern Pacific (NWP) is a fog-prone area, especially the ocean east of the Kuril Islands. The present study analyzes how the Pacific-Japan (PJ) teleconnection pattern influences July sea fog in the fog-prone area using independent datasets. The covariation between the PJ index and sea fog frequency (SFF) index in July indicates a close correlation, with a coefficient of 0.62 exceeding the 99% confidence level. Composite analysis based on the PJ index, a case study, and model analysis based on GFDL-ESM2M, show that in high PJ index years the convection over the east of the Philippines strengthens and then triggers a Rossby wave, which propagates northward to maintain an anticyclonic anomaly in the midlatitudes, indicating a northeastward shift of the NWP subtropical high. The anticyclonic anomaly facilitates the formation of relatively stable atmospheric stratification or even an inversion layer in the lower level of the troposphere, and strengthens the horizontal southerly moisture transportation from the tropical-subtropical oceans to the fog-prone area. On the other hand, a greater meridional SST gradient over the cold flank of the Kuroshio Extension, due to ocean downwelling, is produced by the anticyclonic wind stress anomaly. Both of these two aspects are favorable for the warm and humid air to cool, condense, and form fog droplets, when air masses cross the SST front. The opposite circumstances occur in low PJ index years, which are not conducive to the formation of sea fog. Finally, a multi-model ensemble mean projection reveals a prominent downward trend of the PJ index after the 2030s, implying a possible decline of the SFF in this period.

1. Introduction
  • Sea fog is a weather phenomenon that occurs over oceans and coastal regions wherein tiny water droplets sustain in the atmospheric boundary layer and cause atmospheric horizontal visibility of less than 1 km. Sea fogs influence offshore activities, maritime routes, and port operations. Besides, the coverage of low-level cloud, including sea fog, plays a significant role in the energy balance of the global climate system (Norris and Leovy, 1994; Clement et al., 2009).

    Previous researches indicate that sea fogs may occur over the cold Yellow Sea surface under the conditions of plentiful moisture supply and stable atmospheric stratification (Wang, 1983; Hu and Zhou, 1997; Gao et al., 2007, 2010; Zhang and Bao, 2008; Zhang et al., 2009). Besides, the transition of marine stratus cloud into fog, forced by subsidence from the Pacific high near the Californian coast, was proven by (Koravcin et al., 2001). Climatologically, the sea fog frequency (SFF) over China's adjacent seas is characterized by prominent seasonal variation, which (Zhang et al., 2009) comprehensively analyzed. On the interannual timescale, the variation in foggy days is controlled by the monsoon circulation anomaly in spring and summer in the Yellow Sea (Zhang et al., 2005; Wang et al., 2006).

    The midlatitude region of the northwestern Pacific (NWP) is highly foggy. The maximum annual mean SFF is 23% (Fu and Song, 2014), reaching its peak in July (Zhang et al., 2014a). (Sugimoto et al., 2013) indicated that an intensified Okhotsk high and southward shrinking of the northern Pacific subtropical high (NPSH) are responsible for low SFF at Kushiro, Hokkaido, in July. (Zhang et al., 2014a) suggested the primary controller of SFF in the NWP is the position and orientation of the NPSH. Yet, the mechanisms involved in the interannual variations of the atmospheric circulations associated with SFF are not well understood.

    The Pacific-Japan (PJ), or East Asia-Pacific (EAP), teleconnection pattern is an important atmospheric bridge connecting the tropical and midlatitude atmosphere. It is triggered by an SST anomaly in the western Pacific warm pool and maintained by the dispersive energy of a quasi-stationary Rossby wave (Nitta, 1987; Huang and Li, 1987; Huang, 1990; Lu and Huang, 1998; Kosaka and Nakamura, 2006, 2008, 2010, 2011). The PJ pattern can influence the atmospheric circulation, large-scale vertical motion, and moist static stability (Weaver and Ramanathan, 1997), which may affect the SFF in the NWP. (Zhang et al., 2009) found that the phase of the PJ plays an important role in the ending of the fog season in August in the Yellow Sea.

    In this study, we investigate the impact of the PJ pattern on SFF, with a focus on the atmospheric circulation over the NWP. The paper is organized as follows: A brief description of the datasets used and some definitions is provided in section 2. Section 3 introduces the seasonal and interannual variations of the SFF. Section 4 presents composite analyses, case study and model analysis based on GFED-ESM2M. In section 5, we provide a projection of the PJ index and SFF under global warming conditions. The paper concludes with a summary and discussion in the final section.

2. Data and method
  • The surface-based observations of visibility from ICOADS during 1981 to 2005 were used to obtain the SFF (Woodruff et al., 2011). The sounding data at Kushiro were obtained from the University of Wyoming (http://weather.uwyo.edu/upperair/sounding.html), and unified to 30-m vertical-interval boxes for calculation and drawing. Ocean temperature and velocity (1981-2005) were obtained from SODA (TAMU Research Group, 2014) (Carton and Giese, 2008) at a horizontal resolution of 0.5°× 0.5° and 40 vertical levels with 10-m spacing near the surface (1981-2005). Climate Forecast System Reanalysis data (CFSR) for the period 1981-2005, with a horizontal resolution of 0.5°× 0.5°, were applied in the analyses of cloud liquid water mixing ratio (CLWMR), geopotential height, air temperature, and winds (http://nomads.ncdc.noaa.gov/modeldata/cmd_pgbh/; Saha et al., 2010). These data include 12 vertical levels below 700 hPa and are capable of characterizing the marine atmospheric boundary layer (MABL) under different circulation conditions. The SST data (1981-2005), on a 2° grid, were from ERSST.v3b(http://www.esrl.noaa.gov/psd/)(Xue 2003 Smith et al., 2008). Data from CMIP5 were also used, including the following: the historical simulation data [precipitation, 3D wind, geopotential height, air temperature, cloud liquid water (CLW), and SST] for the period 1951-2005 from GFDL-ESM2M (Dunne et al., 2012), for analyzing the relationship between precipitation over the east of the Philippines, the PJ pattern, and sea fog in the fog-prone area [horizontal resolution of 2.5° lat × 2° lon, global grids (144× 90), and 17 levels in the vertical direction]; data from MIROC-ESM, CanESM2, GFDL-ESM2G, GFDL-ESM2M, CCSM4, CNRM-CM5, MIROC5, and MRI-CGCM3, including their historical and RCP4.5 experiments——used to project the possible trend of the PJ index under global warming. We interpolated the model data to a 2.5°× 2.5° horizontal resolution, following NCEP-NCAR data. The PJ pattern is reproduced well by these CMIP5 models (figure not shown), comparative to the findings of (Kosaka and Nakamura, 2011) using CMIP3.

    In this study, a foga(aWhen the visibility in an observational report in a certain grid is less than 1 km (the code of VV is 90–94 in ICOADS) and there is neither rainfall nor snow at the same time, we defined this as a sea fog event in this grid. ICOADS data are not routinely collected, since the number of ships, buoys, and other platforms available change with time. To avoid this uncertainty, we defined the relative frequency of sea fog occurrence (SFF). The NWP was meshed into a 1°× 1° grid to calculate the SFF.) event was defined as when the visibility was less than 1000 m (excluding precipitation and dust), according to ICOADS. The relative SFF in the grid of over the NWP was calculated by \begin{equation} \label{eq1} {\rm SFF}=\dfrac{N_{\rm fog}}{N_{\rm obs}}\times 100\%~, (1)\end{equation} where N fog is the number of fog events and N obs is the total number of observations (Zhang et al., 2014a). We defined the ocean east of the Kuril Islands (40°-50°N, 145°-165°E) as the climatological fog-prone area (hereinafter, fog-prone area), where the SFF is basically greater than 15% (Fig. 1). The time series of the SFF in each July from 1981 to 2005 in the fog-prone area is defined as the SFF index.

    Figure 1.  Climatological distribution of annual SFF (%) over the NWP (color scale), climatological SST (contours; $^\circ$C), and the SFF seasonal variation (bottom right) in the fog-prone area (blue rectangle in the figure), based on ICOADS. Schematic flow patterns of the Kuroshio and its extension are shown by the meandering red vector.

    Figure 2.  (a) Regressions of geopotential height anomalies (contours; gpm) and wind anomalies (vectors; m s$^-1$) at 850 hPa in July onto the PJ index from 1981 to 2005 (gray shading denotes the 90% confidence level for the geopotential height anomaly). (b) Interannual variation of PJ index and SFF index in the fog-prone area in July (the blue rectangle is the same as in Fig. 1).

    According to Kosaka (2013, personal communication), the PJ pattern can be obtained by regressing vorticity or geopotential height anomalies onto the PJ index, which is extracted from the first principal component (PC1) of the EOF for the monthly meridional pressure gradient force at 850 hPa over the NWP (0°-60°N, 100°-160°E), \begin{equation} \label{eq2} fu=-\dfrac{\partial\phi}{\partial y} , (2)\end{equation} in which φ and u represent geopotential height and zonal wind velocity at 850 hPa, respectively; f is the geostrophic parameter and y denote meridional direction.

3. Relationship between SFF and the PJ pattern over the NWP
  • The climatological annual mean SFF in the NWP is characterized by a zonally elongated band with a maximum up to 21% in the fog-prone area located over the cold flank of the Kuroshio Extension (KE) (Fig. 1). The seasonal variations of the SFF are remarkable, with more fog in summer than in winter and a peak in July (Fig. 1).

    The regressions of geopotential height and the wind anomaly at 850 hPa in July onto the PJ index show that there are three anomalous centers——in the ocean east of the Philippines, southeast of Japan, and in the Okhotsk Sea (Fig. 2a)——in agreement with the pattern proposed by (Nitta, 1987) and (Huang and Li, 1987). The fog-prone area is situated just between the two anomalous centers of the PJ pattern (the rectangle in Fig. 2a). In Fig. 2b, both the PJ index and the SFF index in July exhibit a prominent interannual variability, with a correlation coefficient of 0.62 exceeding the 99% significant level. When the PJ index keeps in its positive phase, the convection over the tropical ocean east of the Philippines is stronger, which is conducive to the formation of a positive phase of the PJ pattern. Controlled by such a PJ pattern, the pressure pattern and associated southerly wind anomaly are favorable for fog formation; this is discussed in detail in the following sections.

4. Comparison between high and low PJ index years
  • To further investigate the impacts of the PJ pattern on atmospheric circulation and hence the SFF, a composite analysis was performed. As shown in Fig. 2b, 1981, 1984, 1989, 1994, 1997, 1999, 2000 and 2002 can be classified as high PJ index years (normalized PJ index of greater than 0.6) (hereinafter, HI years); and 1983, 1986, 1987, 1988, 1991, 1993, 1998 and 2003 as low PJ index years (normalized PJ index of less than 0.6) (hereinafter, LI years).

  • In HI years, the NPSH shifts northeastward, strengthening the southerly moisture flux over the fog-prone area (Fig. 3a). However, the NPSH is narrow and extends southwestward in LI years; the easterly wind weakens the moisture flux (Fig. 3b). Most of the moisture converges along the north flank of the NPSH over the south of the fog-prone area. The static stability at the low level (θ 975hPa-θ 1000hPa) is stronger in HI years than in LI years. The difference between HI years and LI years exhibits a PJ-like pattern in the geopotential height field with three anomalous centers (-,+,-, from south to north; Fig. 3c). The characteristics of the quasi-stationary Rossby wave are revealed by the wave-activity flux, defined by (Takaya and Nakamura, 2001). The southerly wind anomalies over the fog-prone area may lead to stronger warm advection, creating a more stable stratification in the low-level atmosphere.

    Figure 3.  Composite map of (a) HI years, (b) LI years, and (c) the difference between HI years and LI years at 1000 hPa: geopotential height (contours; gpm), low level static stability ($\theta_975hPa$-$\theta_1000hPa$; shading; K), moisture flux (black vectors; kg m$^-1$ s$^-1$), and wave-activity flux at 850 hPa (blue vectors; m$^2$ s$^-2$), with scaling in the bottom right of (c). The area circled by the purple contours represents statistical significance at the 90% confidence level, based on the Student's $t$-test. The blue rectangle is the same as in Fig. 1.

    Figure 4.  Difference between HI years and LI years: (a) SST (color scale; $^\circ$C), SAT (green contours; $^\circ$C) and wind (vectors; m s$^-1$) at 1000 hPa, with scaling in the bottom right; (b) air temperature at 2 m minus SST (color scale) and meridional SST gradient (black contours at 0.8 K km$^-1$ intervals, $\pm$0.8, $\pm$1.6, $\pm$2.4); (c) ocean vertical motion averaged from the sea surface to 50 m (color scale; m s$^-1$) and wind stress (vectors; N m$^-2$); (d) longitude-depth section of sea temperature (color scale; K), zonal (m s$^-1$) and vertical velocity (10$^-4$ m s$^-1$), averaged from 35$^\circ$ to 45$^\circ$N. The difference fields above show statistical significance at the 90% confidence level, based on the Student's $t$-test. The rectangle is the same as in Fig. 1.

    Figure 5.  Latitude-height composite maps in (a) HI years, (b) LI years and (c) the difference between HI and LI years: CLWMR (color scale; 10$^-4$ kg kg$^-1$), virtual potential temperature (contours; K), meridional wind (m s$^-1$) and vertical velocity ($-10^-2$ hPa s$^-1$) vectors, with scaling in the bottom left of (c). The red and black vectors in the top panels denote upward and downward motion, respectively. The units for the SST (blue line) and SAT-SST (red line) in the bottom panel are $^\circ$C, averaged from 150$^\circ$E to 155$^\circ$E. The synthetic fields above show statistical significance at the 90% confidence level, based on the Student's $t$-test. The fog-prone area lies between the two blue squares in (a-c). The July mean vertical profiles of Equivalent Potential Temperature (EPT, solid line; K), temperature (dashed line; $^\circ$C) and horizontal wind (arrows; m s$^-1$) at Kushiro shown in (d) and (e) represent typical years of high (2010) and low (2013) PJ index, respectively.

    The SST (SAT; surface air temperature) in HI years is about 0.8°C (1.5°C) higher than in LI years over the north flank of the KE, with southerly wind anomalies (Fig. 4a). The difference between SAT and SST, i.e., SAT-SST, is adopted to denote the stability of the air-sea interface. The spatial pattern of the difference in SAT-SST between HI years and LI years (Fig. 4b) resembles that of the low-level static stability in Fig. 3c. The greater values of SAT-SST imply greater stability at the air-sea interface. This configuration, along with the low-level stability, facilitates a damping of the development of turbulence farther upward, which is favorable for the maintenance of fog in the fog-prone area.

    Figure 6.  Fog case: (a) Synoptic map. Geopotential height (thick black contours represent 1016 hPa; contours with intervals of 2 hPa) and wind (arrows) at 1000 hPa. The trajectories are represented by red, blue and green lines at 10 m, 300 m and 1000 m, respectively. An overview of atmospheric circulation over the NWP is shown in the top left, and the red rectangle denotes the detail shown in the main part of the panel. (b) Multifunctional Transport Satellites (MTSAT) MTSAT visible cloud image at 0000 UTC 30 July. (c) Backward trajectories. Asterisks represent the starting point of the backward tracking. Meters MSL: height, THETA: potential temperature, RELHUMID: relative humidity. (d) Sounding at Kushiro at 0000 UTC 30 July, virtual potential temperature (solid line with black dots; K), temperature (solid line; $^\circ$C), dewpoint (dashed line, $^\circ$C), RH (dotted line; %), and horizontal wind (arrows; m s$^-1$).

    Figure 7.  As in Fig. 6 but for the non-fog case. The thick black contour in (a) represents 1004 hPa; contours with intervals of 2 hPa.

    Figure 8.  Composited anomalies of (a) stream function and wave activity flux at 200 hPa, (c) stream function, wave activity flux at 850 hPa (blue arrows with blue scaling in the bottom right) and precipitation (green contours), (e) latitude-height section of potential temperature (contours; interval of 0.2 K), CLW (color scale), meridional wind (m s$^-1$) and vertical velocity ($-10^-2$ hPa s$^-1$) vectors, with black scaling in the bottom right in (d) and SST, averaged from 150$^\circ$E to 155$^\circ$E, in enhanced convection (high PJ index) years. The composited anomalies in weakened convection (low PJ index) years are shown in (b, d and f). The gray shading, precipitation contours and synthetic fields above show statistical significance at the 95% confidence level, based on the Student's $t$-test.

    The fog-prone area lies at the north flank of the KE, with sharp changes in SST (Fig. 1). The difference in the meridional SST gradient between HI years and LI years shows that the SST front, which develops between the KE and Oyashio current with a sharp SST gradient, is stronger in HI years than in LI years (Fig. 4b). Since sea fogs over this area in July are advection cooling fogs that form when a warmer air mass flows over a colder sea surface and the air temperature decreases to the dew point (Wang, 1983), a sharp SST gradient will be favorable for air-mass cooling and hence fog formation (Klein and Hartmann, 1993; Li and Zhang, 2013). The reinforcement of the meridional SST gradient over the cold flank of the KE is likely to result from the increase in SST over the KE, which may be caused by the ocean downwelling associated with the anticyclonic wind stress anomaly (shown in Fig. 4c). A longitude-depth section of sea temperature and ocean vertical motion confirms that the stronger downwelling will lead to a warmer sea temperature under an anticyclonic wind stress anomaly in HI years (Figs. 4c and d).

  • Figures 5a and b show that the depth of the MABL is shallow at the cold flank of the SST front, and the strengthened vertical gradient of the virtual potential temperature implies the frequent occurrence of temperature inversions capping the MABL. Over the SST front and its warm flank, virtual potential temperature is relatively uniform under 950 hPa, indicating a well-mixed MABL. The CLWMR is used to represent the fog or cloud.

    In HI years, the stable atmospheric stratification and low MABL over the northern edge of the NPSH produces more horizontal motion; the southerly winds march to 50°N, taking more humid and warmer air to the fog-prone area below 920 hPa. The CLWMR is horizontally distributed with its peak around 960 hPa over the SST front and to its north (Fig. 5a). Whereas, the southerly wind in LI years, with an obvious ascending motion, results in the higher MABL and the rise of the maximum center of CLWMR to 940 hPa, which is probably related to low-level clouds (Fig. 5b). The averaged vertical profiles at Kushiro (the location is shown in Fig. 6b) in July 2010 (typical HI; Fig. 5d) and in July 2013 (typical LI; Fig. 5e) further clarify the difference. In July 2010, the temperature and virtual potential temperature (VPT) profiles show an inversion layer below 300 m. The VPT increases with height, indicating stable stratification in the low-level atmosphere, which results from the configuration of southerly wind below 800 m and westerly wind in the upper layer. The southerly wind in the low-level atmosphere is conducive to the transport of more moisture northward, consistent with Fig. 5a. However, the atmospheric stratification is unstable in the low-level atmosphere in July 2013, which is possibly associated with counterclockwise changes in wind direction, from southeasterly at around 400 m to easterly at around 800 m.

    In HI years, the positive SAT-SST corresponds to a low and stable MABL, with the CLWMR base close to the sea surface, indicating more fog (Fig. 5a). The positive SAT-SST results from the even larger increase in SAT associated with warm advection (Fig. 5a), in spite of the warmer SST in HI years (Fig. 5c). In LI years, the weaker warm advection leads to SAT-SST below or near 0°C, which brings about an unstable air-sea interface that facilitates the lift of the MABL and the level of the maximum CLWMR (Fig. 5b). The difference between HI years and LI years shows that a positive CLWMR near the sea surface is capped by a warmer potential temperature anomaly (Fig. 5c). The peak of the SAT-SST is not collocated with the maximum of the potential temperature, but is shifted to the north by about 2°, probably as a result of advection by the southerly wind in HI years (Fig. 5c).

    The northeasterly migration of the NPSH in HI years enhances the southerly advection, which is conducive to more moisture transportation and a more stable and lower MABL. On the other hand, the NPSH anomaly favors heating of the SST over the warm flank of the SST front, via downwelling forcing, producing a stronger SST gradient. All of these factors facilitate the generation of sea fog.

  • To confirm the results from the climatological analysis, we investigated a fog event (30-31 July 2014) and a non-fog event (23 July 2013) in the fog-prone area, based on ICOADS. HYSPLIT (version 4) was used to operate the backward tracing of the air parcels. For the fog event, Fig. 6b shows sea fog covered the ocean to the southeast of Hokkaido. The large-scale circulation pattern was positive-PJ-like (inserted in Fig. 6a), and the fog-prone area was controlled by an anticyclonic circulation with southerly wind and stable stratification (Figs. 6a and d). The backward tracing of the air parcels shows that the parcels at 10 m, 300 m and 1000 m came from south of the start location [(43°N, 147°E); asterisks in Fig. 6a], indicating the influence a deep Pacific high. The potential temperature (PT) maintained at 295 K and the RH at 10 m increased from 70% to 85% when the air parcel was over the KE, implying a possible contribution of the KE to maintaining the high temperature and humidity (Zhang et al., 2014a). Meanwhile, the PT decreased rapidly to 288 K once it had flowed across to the north flank of the KE, and the RH reached 91%, suggesting the possibility of fog occurrence.

    For the non-fog case, Fig. 7a shows that the fog-prone area was controlled by a cyclone with northeasterly wind and unstable stratification (Figs. 7a and d), favorable for cloud (Fig. 7b). The large-scale circulation pattern in this case was negative-PJ-like (inserted in Fig. 7a). The trajectory analyses show that the PT at 10 m was almost equal to, or even higher than, that at 300 m, suggestive of weakened stratification in the MABL over the cyclone. The PT dropped remarkably owing to the sharp front, while the RH almost reached saturation from near the sea surface to 1000 m, indicating a deep cloud layer.

    The above results imply that the atmospheric circulation and KE front play different roles in the formation of sea fog. The former determines the favorable wind direction and stable atmospheric stratification, while the latter is conducive to maintaining high temperature and humidity and, hence, condensation to fog droplets, after moving across the SST front, which is basically in agreement with the climatological results.

  • GFDL-ESM2M was used to analyze the atmospheric response to changes in the PJ pattern. Since the PJ pattern is maintained by the dispersive energy of the quasi-stationary Rossby wave triggered by the enhanced anomalous convection over the east of the Philippines (Nitta, 1987; Huang and Li, 1987; Kosaka and Nakamura, 2006), the normalized regional mean (15°-25°N, 145°-160°E) precipitation was used to define enhanced (weakened) convection years, with a value greater than 1.4 (less than -1.4), from which the composite analysis was made. In enhanced convection years, the intensified precipitation over the ocean east of the Philippines results in a negative stream function anomaly at 850 hPa, and triggers prominent wave activity flux propagating from the convective zone to the anticyclonic anomaly in the midlatitudes (Fig. 8c). At 200 hPa, the anticyclonic anomaly in the midlatitudes is also remarkable, but shifts to the north slightly, indicating a barotropic anticyclone (Figs. 8a and c), i.e., a PJ pattern consistent with (Huang and Li, 1987) and (Kosaka and Nakamura, 2006). The CLW anomaly near the sea surface, capped with a positive PT anomaly, denotes greater sea fog occurrence, when the convection strengthens over the east of the Philippines (Fig. 8e). In weakened convection years, anomalous atmospheric circulation is opposite compared with enhanced convection years (Figs. 8b and d). A northerly wind anomaly and unstable atmospheric stratification are dominant in the MABL (Fig. 8f), which are unfavorable for the formation of sea fog. All of these features are in agreement with the results from the reanalysis data and indicate that the model can simulate the PJ pattern and reflect its physical relations with sea fog in the fog-prone area.

5. Possible trend of the PJ index and SFF under global warming conditions
  • Based on the relations between the SFF and PJ index discussed above, we projected the possible trend of the PJ index and SFF under global warming conditions using eight models under the RCP4.5 scenario.

    The multi-model ensemble (MME) mean projection of the PJ index in the eight models reveals an obvious declining trend, statistically significant at the 99% confidence level, from the 2030s to the end of the 21st century (Fig. 9). During the 2030s and 2050s, the frequency of the positive phase of the PJ index is higher than that of the negative phase. After 2060, the negative phase increases, implying weakened convection over the ocean east of the Philippines and thus lower SFF in the fog-prone area. The Student's t-test shows the difference in the PJ index between 2030-2050 and 2060-2100 exceeds the 99% confidence level. The shift is similar to the projection of the EAP index in the SRES A1B experiment in IPCC AR4 models (Huang and Qu, 2009). Such a change in phase of the PJ pattern may decrease the SFF over the fog-prone area by the end of the 21st century, which is in agreement with our results.

    Figure 9.  Normalized PJ index in eight models under the RCP4.5 scenario from 2006 to 2099. The black bold line and red trend line denote the MME mean and linear trend in the period 2037-99, respectively.

    Figure 10.  Regressions of the SST (color scale; $^\circ$C) and wind anomalies at 1000 hPa [vectors, with scaling in the top left in (c)] onto the SFF index from 1981 to 2005: (a) preceding winter (December-February); (b) spring (March-May); (c) summer (June-August). The dotted areas denote statistical significance at the greater than 90% confidence level. The green circles represent the cyclonic and anticyclonic surface circulation anomalies, and the rectangle is the same as in Fig. 1.

6. Summary and discussion
  • The midlatitudes of the NWP is a highly foggy area, especially the ocean east of the Kuril Islands in July. In this study, we investigated the influences of the PJ pattern on sea fog over the fog-prone area in July and discussed the possible trend of the PJ pattern and the associated SFF under the conditions of global warming using eight models.

    Composite analysis, a case study, and analysis based on GFDL-ESM2M showed that, in HI years, the convective activity over the east of the Philippines strengthens, which triggers a Rossby wave to propagate northward and the maintenance of an anticyclone anomaly in the midlatitudes. In the geopotential height field, the NPSH shifts northeastward, strengthening the southerly wind and moisture flux over the fog-prone area. Under the influence of the northern edge of the NPSH, the atmospheric stratification in the lower troposphere is relatively stable. The reinforced horizontal southerly winds enhance the warm advection in the lower atmosphere, resulting in a stronger inversion layer over the cold flank of the SST front and a stable air-sea interface, providing favorable atmospheric conditions for fog formation. The greater meridional SST gradient over the cold flank of the KE, which results from the warming in the KE due to ocean downwelling forced by the anticyclonic wind stress anomaly, is conducive to a cooling and condensing of the warm and humid air to form fog droplets, when air masses cross the SST front. In low PJ index years, the opposite set of circumstances exists, which is unfavorable for the formation of sea fog.

    Previous research suggests that the PJ wave train is associated with remote anomalous SST forcing (Xie et al., 2009; Kosaka and Nakamura, 2010). The regressions of the SST and wind anomalies in the preceding winter onto the SFF index show that high SFF is more likely to occur in the subsequent summer of La Niña-like events (Fig. 10). The SST cooling in the tropical mid-eastern Pacific in La Niña-like winters can result in the decreases in SST in the following spring-summer in the northern Indian Ocean through the "capacitor effect", which triggers the positive phase of the PJ pattern, according to previous studies. Thus, the SFF might be projected by the phase of the PJ pattern as well as the changes in SST in the tropical mid-eastern Pacific. So, the projection of SST rising notably over the tropical eastern Pacific in the 21st century (Lu et al., 2008; Zhang et al., 2014a) also supports the possibility of a high frequency in the negative phase of the PJ index. It is worth noting that rainfall, associated with the cyclonic anomaly, may increase over the ocean east of the Kuril Islands, and there may be a decrease in atmospheric stability (corresponding to a negative PJ pattern) under global warming conditions, based on the "warmer-get-wetter" theory (Xie et al., 2010), which is highly compatible with our results.

    The present work focused mainly on the impact of the PJ pattern, with the signal coming from the tropical SST anomaly. A number of other influences were not considered in this study, such as the "Silk Road" pattern (Kosaka et al., 2009; Kosaka and Nakamura, 2011), forcing by local SST, and intraseasonal variation in the PJ pattern, all of which may also play a role in the formation of sea fog. These aspects constitute the next step in our research.

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