A Comparison Study Between Spring and Summer Fogs in the Yellow Sea-Observations and Mechanisms

New observations from buoys and soundings reveal the discrepancies in air–sea interface and in vertical structures between spring (April to May) and summer (July) fogs in the Yellow Sea. Spring fogs are shallow with a robust temperature inversion, dry layer and cold phase (surface air temperature or SAT is lower than sea surface temperature or SST); summer fogs are deep with weaker stability, indistinct fog top and warm phase (SAT?>?SST). Along with numerical simulations, conceptual models for the mechanisms of temperature inversion are suggested. The land–sea contrast is responsible for the robust temperature inversion in spring, and the deep southerlies derived from the east Asian summer monsoon and the adiabatic sinking from the western Pacific subtropical high contributes to the weaker inversion in summer. The dry layer above the sea fog top intensifies the longwave radiative cooling effect to lead to the cold phase in spring fogs. The radiative cooling is weaker in summer fogs resulting in SAT?>?SST.     

Marine Layer Stratus Study

The intent of this study is to develop a better understanding of the behavior of late spring through early fall marine layer stratus and fog at Vandenberg Air Force Base, which accounts for a majority of aviation forecasting difficulties. The main objective was to use Leipper (1995) study as a starting point to evaluate synoptic and mesoscale processes involved, and identify specific meteorological parameters that affected the behavior of marine layer stratus and fog. After identifying those parameters, the study evaluates how well the various weather models forecast them. The main conclusion of this study is that weak upper-air dynamic features work with boundary layer motions to influence marine layer behavior. It highlights the importance of correctly forecasting the surface temperature by showing how it ties directly to the wind field. That wind field, modified by the local terrain, establishes the low-level convergence and divergence pattern and the resulting marine layer cloud thicknesses and visibilities.     

Air–sea interactions during strong winter extratropical storms

A high-resolution, regional coupled atmosphere–ocean model is used to investigate strong air–sea interactions during a rapidly developing extratropical cyclone (ETC) off the east coast of the USA. In this two-way coupled system, surface momentum and heat fluxes derived from the Weather Research and Forecasting model and sea surface temperature (SST) from the Regional Ocean Modeling System are exchanged via the Model Coupling Toolkit. Comparisons are made between the modeled and observed wind velocity, sea level pressure, 10 m air temperature, and sea surface temperature time series, as well as a comparison between the model and one glider transect. Vertical profiles of modeled air temperature and winds in the marine atmospheric boundary layer and temperature variations in the upper ocean during a 3-day storm period are examined at various cross-shelf transects along the eastern seaboard. It is found that the air–sea interactions near the Gulf Stream are important for generating and sustaining the ETC. In particular, locally enhanced winds over a warm sea (relative to the land temperature) induce large surface heat fluxes which cool the upper ocean by up to 2 °C, mainly during the cold air outbreak period after the storm passage. Detailed heat budget analyses show the ocean-to-atmosphere heat flux dominates the upper ocean heat content variations. Results clearly show that dynamic air–sea interactions affecting momentum and buoyancy flux exchanges in ETCs need to be resolved accurately in a coupled atmosphere–ocean modeling framework.     

Implications of Warm Rain in Shallow Cumulus and Congestus Clouds for Large-Scale Circulations

Space-borne observations reveal that 20–40% of marine convective clouds below the freezing level produce rain. In this paper we speculate what the prevalence of warm rain might imply for convection and large-scale circulations over tropical oceans. We present results using a two-column radiative–convective model of hydrostatic, nonlinear flow on a non-rotating sphere, with parameterized convection and radiation, and review ongoing efforts in high-resolution modeling and observations of warm rain. The model experiments investigate the response of convection and circulation to sea surface temperature (SST) gradients between the columns and to changes in a parameter that controls the conversion of cloud condensate to rain. Convection over the cold ocean collapses to a shallow mode with tops near 850 hPa, but a congestus mode with tops near 600 hPa can develop at small SST differences when warm rain formation is more efficient. Here, interactive radiation and the response of the circulation are crucial: along with congestus a deeper moist layer develops, which leads to less low-level radiative cooling, a smaller buoyancy gradient between the columns, and therefore a weaker circulation and less subsidence over the cold ocean. The congestus mode is accompanied with more surface precipitation in the subsiding column and less surface precipitation in the deep convecting column. For the shallow mode over colder oceans, circulations also weaken with more efficient warm rain formation, but only marginally. Here, more warm rain reduces convective tops and the boundary layer depth—similar to Large-Eddy Simulation (LES) studies—which reduces the integrated buoyancy gradient. Elucidating the impact of warm rain can benefit from large-domain high-resolution simulations and observations. Parameterizations of warm rain may be constrained through collocated cloud and rain profiling from ground, and concurrent changes in convection and rain in subsiding and convecting branches of circulations may be revealed from a collocation of space-borne sensors, including the Global Precipitation Measurement (GPM) and upcoming Aeolus missions.     

Detection of thermal pollution from power plants on China’s eastern coast using remote sensing data

The acceleration of the industrialization process in China has increased the demand for electricity and triggered a power-plant building boom, especially along China’s eastern coast, where the economy gets off early and enjoys a fast development. The thermal plumes, residual chlorine, nuclides and other pollutions produced by the thermal and nuclear power plants have exerted an impact on the coastal eco-environment. To monitor the thermal pollution from the power plants at Yueqing Bay on the eastern coast, in this research, the distribution of sea surface temperature (SST) surrounding the power plants is obtained by using the SST retrieval methods developed for Landsat Enhanced Thematic Mapper Plus (ETM+), HJ-1B infrared sensor (IRS) and Terra moderate resolution imaging spectroradiometer (MODIS) data. The comparison of the SST retrieval results before and after the operation of power plants indicates that the total area of sea waters that is impacted by the thermal discharge from the two power plants at Yueqing Bay is approximately 17.95 km², with the highest SST rise of 4.5 °C appearing over the waters around the outlet of the Huaneng Yuhuan power plant on the eastern shore, whereas the highest SST rise around the Zheneng Yueqing power plant on the western shore reaches 3.8 °C. The intensity and scope of influence of the thermal discharge mainly depend on the installed capacity of power plants, coastal terrain, and tide. Although the area where the SST rise is more than 3 °C is not large, thermal discharge still has an impact on bay ecosystems due to the relatively closed nature of the bay environment. Due to the influence of rising water temperatures on the reproduction and individual evolution of fish, shrimp, crabs, shellfish and other aquatic creatures, in the long term, the thermal pollution from coastal power plants will affect the volume of natural fishery and biological resources throughout the waters. The quantitative retrieval results also suggest that relative to MODIS data, Landsat ETM+ and HJ-1B IRS data with a high spatial resolution are more applicable to the estimation of small-scale SST, and IRS data with a high temporal resolution are more helpful in the study of spatio-temporal variability of thermal plumes from coastal power plants.     

North Atlantic extratropical and subpolar gyre variability during the last 120 years: a gridded dataset of surface temperature,salinity, and density. Part 1: dataset validation and RMS variability

We present a binned annual product (BINS) of sea surface temperature (SST), sea surface salinity (SSS), and sea surface density (SSD) observations for 1896–2015 of the subpolar North Atlantic between 40° N and 70° N, mostly excluding the shelf areas. The product of bin averages over spatial scales on the order of 200 to 500 km, reproducing most of the interannual variability in different time series covering at least the last three decades or of the along-track ship monitoring. Comparisons with other SSS and SST gridded products available since 1950 suggest that BINS captures the large decadal to multidecadal variability. Comparison with the HadSST3 SST product since 1896 also indicates that the decadal and multidecadal variability is usually well-reproduced, with small differences in long-term trends or in areas with marginal data coverage in either of the two products. Outside of the Labrador Sea and Greenland margins, interannual variability is rather similar in different seasons. Variability at periods longer than 15 years is a large part of the total interannual variability, both for SST and SSS, except possibly in the south-western part of the domain. Variability in SST and SSS increases towards the west, with the contribution of salinity variability to density dominating that of temperature in the western Atlantic, except close to the Gulf Stream and North Atlantic Current in the southwest area. Weaker variability and larger relative temperature contributions to density changes are found in the eastern part of the gyre and south of Iceland.

     

An objective algorithm for reconstructing the three-dimensional ocean temperature field based on Argo profiles and SST data

While global oceanic surface information with large-scale, real-time, high-resolution data is collected by satellite remote sensing instrumentation, three-dimensional (3D) observations are usually obtained from in situ measurements, but with minimal coverage and spatial resolution. To meet the needs of 3D ocean investigations, we have developed a new algorithm to reconstruct the 3D ocean temperature field based on the Array for Real-time Geostrophic Oceanography (Argo) profiles and sea surface temperature (SST) data. The Argo temperature profiles are first optimally fitted to generate a series of temperature functions of depth, with the vertical temperature structure represented continuously. By calculating the derivatives of the fitted functions, the calculation of the vertical temperature gradient of the Argo profiles at an arbitrary depth is accomplished. A gridded 3D temperature gradient field is then found by applying inverse distance weighting interpolation in the horizontal direction. Combined with the processed SST, the 3D temperature field reconstruction is realized below the surface using the gridded temperature gradient. Finally, to confirm the effectiveness of the algorithm, an experiment in the Pacific Ocean south of Japan is conducted, for which a 3D temperature field is generated. Compared with other similar gridded products, the reconstructed 3D temperature field derived by the proposed algorithm achieves satisfactory accuracy, with correlation coefficients of 0.99 obtained, including a higher spatial resolution (0.25° × 0.25°), resulting in the capture of smaller-scale characteristics. Finally, both the accuracy and the superiority of the algorithm are validated.     

Can Sea Fog be Inferred from Operational GEM Forecast Fields?

Three cases of widespread sea fog in Lunenburg Bay, Nova Scotia were used to evaluate the suitability of operational regional GEM forecast fields for inferring advection fog occurrences. Verification scores suggest that the objective analyses contain significant departures from observations that will affect model accuracy, given the sensitivity of fog condensation microphysics. Dew point depression (ES) scores show larger differences compared to temperature, with both influenced by surface characteristics. For objective analyses and GEM forecasts ES < 2 C seems to match fog satellite images better than the physical threshold ES ≤ 0 C. In addition the GEM forecasts show a general tendency towards drier conditions near the surface, therefore reconfiguring GEM to better represent condensation in the boundary layer is proposed.     

Processes of India’s offshore summer intraseasonal sea surface temperature variability

Active and break phases of the Indian summer monsoon are associated with sea surface temperature (SST) fluctuations at 30–90 days timescale in the Arabian Sea and Bay of Bengal. Mechanisms responsible for basin-scale intraseasonal SST variations have previously been discussed, but the maxima of SST variability are actually located in three specific offshore regions: the South-Eastern Arabian Sea (SEAS), the Southern Tip of India (STI) and the North-Western Bay of Bengal (NWBoB). In the present study, we use an eddy-permitting 0.25° regional ocean model to investigate mechanisms of this offshore intraseasonal SST variability. Modelled climatological mixed layer and upper thermocline depth are in very good agreement with estimates from three repeated expendable bathythermograph transects perpendicular to the Indian Coast. The model intraseasonal forcing and SST variability agree well with observed estimates, although modelled intraseasonal offshore SST amplitude is undere-stimated by 20–30 %. Our analysis reveals that surface heat flux variations drive a large part of the intraseasonal SST variations along the Indian coastline while oceanic processes have contrasted contributions depending of the region considered. In the SEAS, this contribution is very small because intraseasonal wind variations are essentially cross-shore, and thus not associated with significant upwelling intraseasonal fluctuations. In the STI, vertical advection associated with Ekman pumping contributes to ～30 % of the SST fluctuations. In the NWBoB, vertical mixing diminishes the SST variations driven by the atmospheric heat flux perturbations by 40 %. Simple slab ocean model integrations show that the amplitude of these intraseasonal SST signals is not very sensitive to the heat flux dataset used, but more sensitive to mixed layer depth.     

A Review of some Recent Radiation Fog Prediction Studies and the Results of Integrating a Simple Numerical Model to Predict Radiation Fog over Brunei

— Several radiation fog studies with emphasis on numerical simulation and prediction are reviewed. One of the earliest attempts started with a given surface diurnal variation of temperature and water vapor, and concluded by forecasting the onset of saturation at various levels; thus fog, by examining the spread of temperature and moisture in the vertical. The one-dimensional (1-D) models are still popular. Some of the recent numerical simulations use more than 100 levels in the vertical and treat various kinds of vegetation, aerosols, and soils with moisture contents. Some also employ a mesoscale model in conjunction with a 1-D model to consider the advective effects. In the following a simple 1-D numerical model was used to predict the onset of fog at Brunei, based on a desktop computer and routine surface observations of dry bulb temperature (T), dewpoint temperature (T _d ), and wind speed at 1800 Local Time (LT). Optimism exists in improved predictions of fog and stratus as 1-D models incorporate many physical processes, and mesoscale models continue to improve in predicting advection and cloud cover.     

Regional characteristics of the effects of the El Niño-Southern Oscillation on the sea level in the China Sea

Based on coastal tide level, satellite altimetry, and sea surface temperature (SST) data of offshore areas of China’s coast and the equatorial Pacific Ocean, the regional characteristics of the effects of the El Niño-Southern Oscillation (ENSO) on the sea level in the China Sea were investigated. Singular value decomposition results show a significant teleconnection between the sea level in the China Sea and the SST of the tropical Pacific Ocean; the correlation coefficient decreases from south to north. Data from tide gauges along China’s coast show that the seasonal sea-level variations are significantly correlated with the ENSO. In addition, China’s coast was divided into three regions based on distinctive regional characteristics. Results obtained show that the annual amplitude of sea level was low during El Niño developing years, and especially so during the El Niño year. The ENSO intensity determined the response intensity of the annual amplitude of the sea level. The response region (amplitude) was relatively large for strong ENSO intensities. Significant oscillation periods at a timescale of 4–7 years existed in the sea level of the three regions. The largest amplitude of oscillation was 1.5 cm, which was the fluctuation with the 7-year period in the South China Sea. The largest amplitude of oscillation in the East China Sea was about 1.3 cm. The amplitude of oscillation with the 6-year period in the Bohai Sea and Yellow Sea was the smallest (less than 1 cm).     

Multivariate Prediction of Total Water Storage Changes Over West Africa from Multi-Satellite Data

West African countries have been exposed to changes in rainfall patterns over the last decades, including a significant negative trend. This causes adverse effects on water resources of the region, for instance, reduced freshwater availability. Assessing and predicting large-scale total water storage (TWS) variations are necessary for West Africa, due to its environmental, social, and economical impacts. Hydrological models, however, may perform poorly over West Africa due to data scarcity. This study describes a new statistical, data-driven approach for predicting West African TWS changes from (past) gravity data obtained from the gravity recovery and climate experiment (GRACE), and (concurrent) rainfall data from the tropical rainfall measuring mission (TRMM) and sea surface temperature (SST) data over the Atlantic, Pacific, and Indian Oceans. The proposed method, therefore, capitalizes on the availability of remotely sensed observations for predicting monthly TWS, a quantity which is hard to observe in the field but important for measuring regional energy balance, as well as for agricultural, and water resource management. Major teleconnections within these data sets were identified using independent component analysis and linked via low-degree autoregressive models to build a predictive framework. After a learning phase of 72 months, our approach predicted TWS from rainfall and SST data alone that fitted to the observed GRACE-TWS better than that from a global hydrological model. Our results indicated a fit of 79 % and 67 % for the first-year prediction of the two dominant annual and inter-annual modes of TWS variations. This fit reduces to 62 % and 57 % for the second year of projection. The proposed approach, therefore, represents strong potential to predict the TWS over West Africa up to 2 years. It also has the potential to bridge the present GRACE data gaps of 1 month about each 162 days as well as a—hopefully—limited gap between GRACE and the GRACE follow-on mission over West Africa. The method presented could also be used to generate a near-real-time GRACE forecast over the regions that exhibit strong teleconnections.     

Large-Scale Environmental Influences on the Onset, Maintenance, and Dissipation of Six Sea Fog Cases over the Yellow Sea

Sea fog is typically formed and developed under a set of favorable environmental conditions, which are associated with the station pressure changes, sea level pressure, winds, temperature, water vapor supply, and sea surface temperature. Understanding of these environmental factors during the evolution of a sea fog episode is crucial for forecasting the occurrence and severity of sea fogs over the ocean and adjacent coastal areas. In this study, the large-scale environment variability of six fog events over the Yellow Sea was investigated. It was realized in the present study that the northwest Pacific Ocean high (NPH) is vital to fog formation over the Yellow Sea. In our study, six fog cases can be basically divided into two types: (1) pressure-weakening type, (2) pressure-strengthening type. The former type happened in spring and the latter type in summer. Prevailing southerly winds, accompanied with the well-positioned NPH, may supply a large amount of warm water vapor for the fog formation and maintenance. The intensity of the air temperature inversion is stronger in summer cases than that in spring ones. The wind direction change from south to north and the unstable lower atmosphere may lead to fog’s dissipation. This study may provide a comprehensive understanding of sea fog’s onset, maintenance, and dissipation over the Yellow Sea.     

Upper oceanic response to tropical cyclone Phailin in the Bay of Bengal using a coupled atmosphere-ocean model

A numerical simulation of very severe cyclonic storm ‘Phailin’, which originated in southeastern Bay of Bengal (BoB) and propagated northwestward during 10–15 October 2013, was carried out using a coupled atmosphere-ocean model. A Model Coupling Toolkit (MCT) was used to make exchanges of fluxes consistent between the atmospheric model ‘Weather Research and Forecasting’ (WRF) and ocean circulation model ‘Regional Ocean Modelling System’ (ROMS) components of the ‘Coupled Ocean-Atmosphere-Wave-Sediment Transport’ (COAWST) modelling system. The track and intensity of tropical cyclone (TC) Phailin simulated by the WRF component of the coupled model agrees well with the best-track estimates reported by the India Meteorological Department (IMD). Ocean model component (ROMS) was configured over the BoB domain; it utilized the wind stress and net surface heat fluxes from the WRF model to investigate upper oceanic response to the passage of TC Phailin. The coupled model shows pronounced sea surface cooling (2–2.5 °C) and an increase in sea surface salinity (SSS) (2–3 psu) after 06 GMT on 12 October 2013 over the northwestern BoB. Signature of this surface cooling was also observed in satellite data and buoy measurements. The oceanic mixed layer heat budget analysis reveals relative roles of different oceanic processes in controlling the mixed layer temperature over the region of observed cooling. The heat budget highlighted major contributions from horizontal advection and vertical entrainment processes in governing the mixed layer cooling (up to ?0.1 °C h^?1) and, thereby, reduction in sea surface temperature (SST) in the northwestern BoB during 11–12 October 2013. During the post-cyclone period, the net heat flux at surface regained its diurnal variations with a noontime peak that provided a warming tendency up to 0.05 °C h^?1 in the mixed layer. Clear signatures of TC-induced upwelling are seen in vertical velocity (about 2.5 × 10^?3 m s^?1), rise in isotherms and isohalines along 85–88° E longitudes in the northwestern BoB. The study demonstrates that a coupled atmosphere-ocean model (WRF + ROMS) serves as a useful tool to investigate oceanic response to the passage of cyclones.     

Seasonality and anomalies of sea surface temperature off the coast of Nayarit, Mexico

Sea surface temperature (SST) harmonic and empirical orthogonal function (EOF) analyses covering 18 years were performed for the area located from 114° to 105° W and from 18° to 25° N. The results indicate that the influence of the annual signal predominates over the semi-annual signal, and the closer to the coast, the stronger the annual harmonic. Several interannual anomalies arose that are connected with the main global indexes, especially the Oceanic Niño Index. Pearson correlations between the first temporal mode of the SST and regional rainfalls in Nayarit indicate that maximum correlations (r?>?0.7) are observed when there is a +1-month lag between the series. However, this result indicates that SST is delayed with 1 month after rainfall occurrence, which shows that the dominant influence in this relationship is not the SST forcing.     

1901—2016年印太海域海表温度的偏差订正及数据集研制

海表温度系统性观测偏差的订正是开展长历史序列网格化海表温度气候数据产品研制的关键.本文在引入美国SR02海表温度偏差订正方法的基础上,结合国家气象信息中心自主研发的全球海表观测定时值数据集,进行了相关参数的优化改进,从而研制了1901-2016年印度洋-太平洋核心海域月平均2°×2°分辨率的海表温度偏差订正数据集.对海温偏差订正量的时空分布特征分析表明,基于自主研制的基础数据和优化改进的方法求解的偏差订正量能有效反映海表温度观测手段的历史变迁,以及海表温度系统性偏差随季节变化的规律.同时,与ERSST订正量的对比表明,由于优化改进后的方法其阈值计算随空间样本而变,因而其局地变化特征的表现能力更强,且其订正量在观测手段转型期的变化更为明显.相较订正前的海表温度距平(SSTA)场,订正后的SSTA资料与ERSSTv5SSTA间的偏差误差和均方根误差均有明显降低.其中,偏差误差的缩减比例在37.7%~87.9%之间,均方根误差可降低0.06℃.此外,与国际同类产品的对比表明,本文发展的SSTA订正数据集与国际同类SSTA产品序列的相关系数不低于0.97,且变化趋势类似.从差异对比上看,除中高纬东亚大陆近海区域外,本文的偏差订正数据集与国际上同类产品的SSTA差异基本在-0.2~0.2℃之间.     

Recent warming in the Yellow/East China Sea during winter and the associated atmospheric circulation

We examine characteristics in the variability of sea surface temperature (SST) in the Yellow/East China Sea during the boreal winter (December–January–February) for the period 1950–2008 in observations. It is found that the mean SST in the Yellow Sea/East China Sea gradually increases during recent decades. A warming trend of a basin scale SST is significant in most of the regions in the Yellow/East Sea, which is well explained by the variability of the first empirical orthogonal function SST mode. We suggest one candidate mechanism that the North Pacific oscillation (NPO)-like sea level pressure play an important role to warm the Yellow/East China Sea. Anomalous anticyclonic circulation, which is the southern lobe of NPO-like sea level pressure over the North Pacific, causes a weakening of northerly mean winds over the Yellow/East China Sea during winter. This contributes to increase in the SST in the Yellow/East China Sea through the changes in the latent heat and sensible heat fluxes.     

星载SAR遥感图像反演海洋大气边界层高度

本研究将边界层相似理论与对流理论应用到具有海洋大气边界层(Marine Atmospheric Boundary Layer, MABL)对流特征的星载合成孔径雷达(Synthetic Aperture Radar, SAR)遥感图像,探讨了星载SAR遥感图像描述海气应力作用下水平扰动尺度变化的潜在可能性.针对具有三维对流涡旋Cell和二维水平滚轴涡旋Roll特征的星载SAR遥感图像,反演了中国海海域MABL高度,并与同步实验获取的MABL高度结果进行对比.结果表明,利用具有对流特征的星载SAR遥感图像反演MABL高度是可行的,展示了以高分辨率、大面积观测为特点的星载SAR遥感图像探测MABL的广阔前景.     

The sea level at Port-aux-Français,Kerguelen Island,from 1949 to the present

Relative sea level rise at Kerguelen Island over the last 55 years has been investigated using a combination of historical and recent tide gauge data. The best estimate of relative sea level trend from data sets spanning 38 years is estimated to be 1.1±0.7 mm year^?1. We have tried to quantify the error budget due to some of the possible sources of uncertainty. As expected, the main source of uncertainty comes from oceanic interannual variability, preventing an accurate estimate of sea level trend over short record lengths. However, our values are reasonably consistent with other reported southern hemisphere sea level trends for similar time periods.     

The Twentieth-Century Sea Level Budget: Recent Progress and Challenges

For coastal areas, given the large and growing concentration of population and economic activity, as well as the importance of coastal ecosystems, sea level rise is one of the most damaging aspects of the warming climate. Huge progress in quantifying the cause of sea level rise and closure of sea level budget for the period since the 1990s has been made mainly due to the development of the global observing system for sea level components and total sea levels. We suggest that a large spread (1.2 ± 0.2–1.9 ± 0.3 mm year^?1) in estimates of sea level rise during the twentieth century from several reconstructions demonstrates the need for and importance of the rescue of historical observations from tide gauges, with a focus on the beginning of the twentieth century. Understanding the physical mechanisms contributing to sea level rise and controlling the variability of sea level over the past few 100 years are a challenging task. In this study, we provide an overview of the progress in understanding the cause of sea level rise during the twentieth century and highlight the main challenges facing the interdisciplinary sea level community in understanding the complex nature of sea level changes.