DETECTION OF DAYTIME FOG IN SOUTH CHINA SEA USING MODIS DATA

Based on a current fog detection theory, a multiband threshold method for MODIS data was put forward to detect daytime fog in the South China Sea. It used Bands 1, 2, 18, 20 and 31 of MODIS data to separate fog from the cloud and the sea surface. The digital detection indexes were as follows. If RB1<20%, RB2<20% and RB1>RB2, the pixel was identified to be the sea surface. If RB1>55%, RB2>55% and TB31<273 K, the pixel was identified to be a middle- and high-level cloud. If IFC>20, the pixel was classified to be sea fog. The method was verified with sea fog data observed from the coastal region of Guangdong during January-April 2011. Out of the 13 samples of satellite detection, nine were consistent with the surface observations, three were identified to be low-level the cloud according to the satellite detection but fog according to the surface observations, and only one sample was identified to be the ocean surface by the satellite detection but fog by the surface observations. Because the MODIS data cannot penetrate the cloud or fog, the model was designed for a single field of view which had only one layer of cloud or fog. It can accurately distinguish fog which is not covered by the cloud, but it identifies fog as cloud if the former is covered by a cloud. Generally speaking, the model is effective and feasible.     

A Comparative Analysis of Chemical Properties and Factors Impacting Spring Sea Fog over the Northwestern South China Sea

In the present study, we analyzed the chemical properties and factors impacting the sea fog water during two sea fog events over the northwestern South China Sea in March 2017, and compared our results with those of other regions. The sea fog water during these two events were highly acidic and their average pH was below 3, which was related to the high initial acidifying potential and large amounts of NO3- and SO42- not involved in the neutralization reaction. The dominant cations in the sea fog water were Na+ and NH4+. The primary anions in the sea fog water over the South China Sea were Cl- and NO3-, while that over the North Pacific Ocean was mainly SO42-, and ratios of the three fog water ions near the Donghai Island were similar. Ions in the sea fog water during the two events were mainly derived from marine aerosols, while the difference was that the first low-level sea fog airflow trajectory passed over Hainan Island. Therefore, the proportion of K+ in the first sea fog was much higher than that in sea water and the second. Sulfate was the key to fog water nucleation, which made ion concentration in the sea fog water during the second event higher than that during the first. A decrease in average diameter during the first sea fog formation led to an ion concentration increase, while the average diameter of sea fog water during the second event was lower than that during the first, which corresponded with a moderate ion concentration increase.     

Evaluation of the Global and Regional Assimilation and Prediction System for Predicting Sea Fog over the South China Sea

In the South China Sea, sea fog brings severe disasters every year, but forecasters have yet to implement an effective seafog forecast. To address this issue, we test a liquid-water-content-only(LWC-only) operational sea-fog prediction method based on a regional mesoscale numerical model with a horizontal resolution of about 3 km, the Global and Regional Assimilation and Prediction System(GRAPES), hereafter GRAPES-3 km. GRAPES-3 km models the LWC over the sea, from which we infer the visibility that is then used to identify fog. We test the GRAPES-3 km here against measurements in 2016 and 2017 from coastal-station observations, as well as from buoy data, data from the Integrated Observation Platform for Marine Meteorology, and retrieved fog and cloud patterns from Himawari-8 satellite data. For two cases that we examine in detail, the forecast region of sea fog overlaps well with the multi-observational data within 72 h. Considering forecasting for0–24 h, GRAPES-3 km has a 2-year-average equitable threat score(ETS) of 0.20 and a Heidke skill score(HSS) of 0.335,which is about 5.6%(ETS) and 6.4%(HSS) better than our previous method(GRAPES-MOS). Moreover, the stations near the particularly foggy region around the Leizhou Peninsula have relatively high forecast scores compared to other sea areas.Overall, the results show that GRAPES-3 km can roughly predict the formation, evolution, and dissipation of sea fog on the southern China coast.     

A Heavy Sea Fog Event over the Yellow Sea in March 2005： Analysis and Numerical Modeling

In 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） axe 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 axe 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 axe that sea fog forms in response to relatively persistent southerly waxm/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.     

A New Algorithm for Sea Fog／Stratus Detection Using GMS-5 IR Data

A new algorithm for the detection of fog/stratus over the ocean from the GMS-5 infrared (IR) channel data is presented. The new algorithm uses a clear-sky radiance composite map (CSCM) to compare the hourly observations of the IR radiance. The feasibility of the simple comparison is justified by the theoretical simulations of the fog effect on the measured radiance using a radiative transfer model. The simulation results show that the presence of fog can be detected provided the visibility is worse than 1 km and the background clear-sky radiances are accurate enough with known uncertainties. For the current study, an accurate CSCM is constructed using a modified spatial and temporal coherence method, which takes advantage of the high temporal resolution of the GMS-5 observations. The new algorithm is applied for the period of 10-12 May 1999, when heavy sea fog formed near the southwest coast of the Korean Peninsula. Comparisons of the fog/stratus index, defined as the difference between the measured and clear-sky brightness temperature, from the new algorithm to the results from other methods, such as the dual channel difference of NOAA/AVHRR and the earth albedo method, show a good agreement. The fog/stratus index also compares favorably with the ground observations of visibility and relative humidity. The general characteristics of the fog/stratus index and visibility are relatively well matched, although the relationship among the absolute values, the fog/stratus index, visibility, and relative humidity, varies with time. This variation is thought to be due to the variation of the atmospheric conditions and the characteristics of fog/stratus, which affect the derived fog/stratus index.     

High Spatial Resolution and High Temporal Frequency(30-m/15-day) Fractional Vegetation Cover Estimation over China Using Multiple Remote Sensing Datasets:Method Development and Validation

High spatial resolution and high temporal frequency fractional vegetation cover(FVC) products have been increasingly in demand to monitor and research land surface processes. This paper develops an algorithm to estimate FVC at a 30-m/15-day resolution over China by taking advantage of the spatial and temporal information from different types of sensors: the 30-m resolution sensor on the Chinese environment satellite(HJ-1) and the 1-km Moderate Resolution Imaging Spectroradiometer(MODIS). The algorithm was implemented for each main vegetation class and each land cover type over China. First, the high spatial resolution and high temporal frequency normalized difference vegetation index(NDVI) was acquired by using the continuous correction(CC) data assimilation method. Then, FVC was generated with a nonlinear pixel unmixing model. Model coefficients were obtained by statistical analysis of the MODIS NDVI. The proposed method was evaluated based on in situ FVC measurements and a global FVC product(GEOV1 FVC). Direct validation using in situ measurements at 97 sampling plots per half month in 2010 showed that the annual mean errors(MEs) of forest, cropland, and grassland were-0.025, 0.133, and 0.160, respectively, indicating that the FVCs derived from the proposed algorithm were consistent with ground measurements [R2 = 0.809,root-mean-square deviation(RMSD) = 0.065]. An intercomparison between the proposed FVC and GEOV1 FVC demonstrated that the two products had good spatial–temporal consistency and similar magnitude(RMSD approximates 0.1). Overall, the approach provides a new operational way to estimate high spatial resolution and high temporal frequency FVC from multiple remote sensing datasets.     

A COMPARISON OF THE BLENDING AND CONSTRAINING METHODS TO INTRODUCE LARGE-SCALE INFORMATION INTO GRAPES MESOSCALE ANALYSIS

To solve the problem of mesoscale analysis error accumulation after a period of continuous cycle data assimilation (CCDA), a blending method and a constraining method are compared to introduce global analysis information into the Global/Regional Assimilation and Prediction Enhanced System mesoscale three-dimensional variational data assimilation system (GRAPES-Meso 3Dvar). Based on a spatial filter used to obtain a blended analysis, the blending method is weighted toward the T639 global analysis for scales larger than the cutoff wavelength of 1,200 km and toward the GRAPES mesoscale analysis for wavelengths below that. The constraining method considers the T639 global analysis data as an extra source of information to be added in the 3DVar cost function. The cloud-resolving GRAPES-Meso system (3 km resolution) with a 3 h analysis cycle update is chosen, and forecast experiments on an extreme precipitation event over the eastern part of China are presented. The comparison shows that the inclusion of large-scale information with both methods has a positive impact on the regional model, in which the 3 h background forecasts are slightly closer to the radiosonde observations. The results also show that both methods are effective in improving large-scale analysis while reserving the well-featured mesoscale information, leading to an enhancement in the balance and accuracy of the analysis. Subjective verification reveals that the introduction of large-scale information has a visible beneficial impact on the forecast of precipitation location and intensity. The methodologies and experiences presented in this paper could serve as a reference for ongoing efforts toward the development of multi-scale analysis in GRAPES-Meso.     

Establishment of the South Asian High over the Indo-China Peninsula During Late Spring to Summer

The establishment of the upper-level South Asian high(SAH) over the Indo-China Peninsula(ICP) during late boreal spring and its possible causes are investigated using long-term NCEP–NCAR and ERA-40 reanalysis and satellite-observed OLR data. Results show that, from early March to mid-April, deep convection stays south of ～6?N over the northern Sumatran islands. As the maximum solar radiation moves over the latitudes of the ICP(10?–20?N) in late April, the air over the ICP becomes unstable. It ascends over the ICP and descends over the adjacent waters to the east and west. This triggers deep convection over the ICP that induces large latent heating and strong updrafts and upper-level divergence, leading to the formation of an upper-level anticyclonic circulation and the SAH over the ICP. During early to mid-May, deep convection over the ICP intensifies and extends northwards to the adjacent waters. Strong latent heating from deep convection enhances and maintains the strong updrafts and upper-level divergence, and the SAH is fully established by mid-May. Thus, the seasonal maximum solar heating and the land–sea contrast around the ICP provide the basic conditions for deep convection to occur preferentially over the ICP, which leads to the formation of the SAH over the ICP from late April to mid-May. Simulations using Reg CM4 also indicate that the diabatic heating over the ICP is conducive to the generation and development of upperlevel anticyclonic circulation, which leads to an earlier establishment of the SAH.     

The Application of Sea-Surface Wind Detection with Doppler Lidar in Olympic Sailing

The mobile incoherent Doppler lidar(MIDL),which was jointly developed by State Key Laboratory of Severe Weather(LaSW) of the Chinese Academy of Meteorological Sciences(CAMS) and Ocean University of China,provided meteorological services during the Olympic sailing events in Qingdao in 2008.In this study,two experiments were performed based on these measurements.First,the capabilities of MIDL detection of sea-surface winds were investigated by comparing its radial velocities with those from a sea buoy.MIDL radial velocity was almost consistent with sea-buoy data;both reflected the changes in wind with time.However,the MIDL data was 0.5 m s 1 lower on average than the sea-buoy data due to differences in detection principle,sample volume,sample interval,spatial and temporal resolution.Second,the wind fields during the Olympic sailing events were calculated using a four-dimensional variation data assimilation(4DVAR) algorithm and were evaluated by comparing them with data from a sea buoy.The results show that the calculations made with the 4DVAR wind retrieval method are able to simulate the fine retrieval of sea-surface wind data-the retrieved wind fields were consistent with those of sea-buoy data.Overall,the correlation coefficient of wind direction was 0.93,and the correlation coefficient of wind speed was 0.70.The distribution of retrieval wind fields was consistent with that of MIDL radial velocity;the root-mean-square error between them had an average of only 1.52 m s 1.     

A CLIMATOLOGY OF DEEP CONVECTION OVER SOUTH CHINA AND THE ADJACENT WATERS DURING SUMMER

Due to the higher temporal and spatial resolution and the better integrality of long-term satellite infrared(IR) Brightness Temperature(TBB) data,a climatology of deep convection during summer over South China and the adjacent waters is presented in this paper based on the 1-hourly infrared IR TBB data during June-August of 1996-2007(except 2004).The results show that the geographic distribution of deep convection denoted by TBB ≤-52℃ over South China and the adjacent waters are basically consistent with previous statistical results based on surface thunderstorm observations and low-orbit satellite lightning observations.The monthly,ten-day,five-day and diurnal variations of deep convection in this region are focused on in this paper.There are 5 active deep-convection areas in June-August.The monthly variations of the deep convection are closely associated with the large-scale atmospheric circulations.The deep convection over the land areas of South China is more active in June while that over the South China Sea is more active in July and August.The development of deep convection is prominently intermittent and its period is about 3 to 5 five-day periods.However,the deep convection over the coastal areas in South China remains more active during summer and has no apparent intermittence.The ten-day and five-day variations of deep convection show that there are different variations of deep convection over different areas in South China and the adjacent waters.The tendency of deep convection over the land areas of South China is negatively correlated with that over the South China Sea.The diurnal variations of deep convection show that the sea-land breeze,caused by the thermal differences between land and sea,and the mountain-valley breeze,caused by the thermal differences between mountains and plains or basins,cause deep convection to propagate from sea to land in the afternoon and from land to sea after midnight,and the convection over mountains propagates from mountains to plains after midnight.The different diurnal variations of deep convection over different underlying surfaces show that not only there are general mountainous,marine and multi-peak deep convection,but also there is longer-duration deep convection over coastal areas and other deep convection triggered and maintained by larger-scale weather systems in South China during summer.     

Comparison of Satellite and Ship Observations for Total Cloud Amount

The data series of monthly clouldiness over global ocean from COADS was compared with that of from satellite Nimbus-7 during April 1979 to March 1985. The correspondence between them is good. Both the two methods of observation can provide useful information of the distribution of cloudiness and the two data sets can be mutually complementary.     

MICROSTRUCTURES AND TEMPORAL VARIATION CHARACTERISTICS DURING A SEA FOG EVENT ALONG THE WEST COAST OF THE TAIWAN STRAIT

Synoptic systems and microphysical properties associated with a sea fog event are analyzed based on the measurements of visibility, meteorological elements and fog droplet spectrum from a comprehensive field campaign in Xiamen, Fujian province during spring 2013. The influences of meteorological elements on the microstructures of the sea fog are also discussed. The results showed that the wind speed and direction changed suddenly during the intermittent and disperse phases of the sea fog. Liquid water content, number concentration and average diameter varied obviously in the development, mature and disperse phases of the sea fog. The burst re-enforcement of sea fog was accompanied by explosive broadening of fog droplet spectrum; average diameter, number concentration and liquid water content increased sharply; and background meteorological conditions also changed significantly. The microstructures fluctuated intensely due to changes in turbulence, radiation and meteorological conditions at different stages, including nucleation, condensation, coagulation, and evaporation, as well as the discontinuity of spatial distribution of droplets.     

Aerosol Data Assimilation Using Data from Fengyun-3A and MODIS:Application to a Dust Storm over East Asia in 2011

Aerosol optical depth(AOD) is the most basic parameter that describes the optical properties of atmospheric aerosols,and it can be used to indicate aerosol content. In this study, we assimilated AOD data from the Fengyun-3 A(FY-3 A) and MODIS meteorological satellite using the Gridpoint Statistical Interpolation three-dimensional variational data assimilation system. Experiments were conducted for a dust storm over East Asia in April 2011. Each 0600 UTC analysis initialized a24-h Weather Research and Forecasting with Chemistry model forecast. The results generally showed that the assimilation of satellite AOD observational data can significantly improve model aerosol mass prediction skills. The AOD distribution of the analysis field was closer to the observations of the satellite after assimilation of satellite AOD data. In addition, the analysis resulting from the experiment assimilating both FY-3 A/MERSI(Medium-resolution Spectral Imager) AOD data and MODIS AOD data had closer agreement with the ground-based values than the individual assimilation of the two datasets for the dust storm over East Asia. These results suggest that the Chinese FY-3 A satellite aerosol products can be effectively applied to numerical models and dust weather analysis.     

Impacts of XBT, TAO, Altimetry and ARGO Observations on the Tropical Pacific Ocean Data Assimilation

This study aims at assessing the relative impacts of four major components of the tropical Pacific Ocean observing system on assimilation of temperature and salinity fields. Observations were collected over a period between January 2001 through June 2003 including temperature data from the expendable bathythermographs （XBT）, thermistor data from the Tropical Ocean Global Atmosphere Tropical Atmosphere-Ocean （TOGA-TAO） mooring array, sea level anomalies from the Topex/Poseidon and Jason-1 altimetry （T/P-J）, and temperature and salinity profiles from the Array for Real-time Geostrophic Oceanography （ARGO） floats. An efficient three-dimensional variational analysis-based method was introduced to assimilate the above data into the tropical-Pacific circulation model. To evaluate the impact of the individual component of the observing system, four observation system experiments were carried out. The experiment that assimilated all four components of the observing system was taken as the reference. The other three experiments were implemented by withholding one of the four components. Results show that the spatial distribution of the data influences its relative contribution. XBT observations produce the most distinguished effects on temperature analyses in the off-equatorial region due to the large amount of measurements and high quality. Similarly, the impact of TAO is dominant in the equatorial region due to the focus of the spatial distribution. The Topex/Poseidon-Jason-1 can be highly complementary where the XBT and TAO observations are sparse. The contribution of XBT or TAO on the assimilated salinity is made by the model dynamics because no salinity observations from them are assimilated. Therefore, T/P-J, as a main source for providing salinity data, has been shown to have greater impacts than either XBT or TAO on the salinity analysis. Although ARGO includes the subsurface observations, the relatively smaller number of observation makes it have the smallest contribution to the assimilation syst     

DECADAL VARIABILITY OF THE ANTARCTIC OSCILLATION

This paper summarizes the long term and decadal time scale fluctuations of atmosphericcirculation in the Southern(Hemisphere)middle and high latitudes.The long time series ofAntarctic Oscillation Indices(AOIs)were established for January.April.July and October basedon the historical sea level pressure maps and NCEP/NCAR reanalysis surface pressure data set.Itwas found that the AOI of January had upward trend at a rate of 1.17 hPa/100 a.and July haddownward trend at a rate of—1.49 hPa/100 a since 1871.The method of wavelet analysis wasapplied to detect the low frequency characteristics of AOIs,and it is clear that there are decadalvariations in the time scale of about 20—30 years in all 4 indices.Since the averaged value of 4months could explain most variance of annual AOI.thus it is reasonable using the mean AOI ofJanuary,April,July and October to represent the annual AOI.The value of annual AOI was muchlower in periods of about 1894—1901.1910—1935,and was much higher in periods of about 1880—1893,1936—1945.The positive anomalies were remarkable since 1980s.Power spectra ofmodeled AOIs from Hadley Center Control Integration(HCCI)were compared with theobservations,it is found that the interannual time scale frequencies were more significant thandecadal frequencies.But.there also had the possibility for generating weak deeadal fluctuations insome special months and years by Hasselmann mechanism.     

A CASE STUDY OF NUMERICAL SIMULATION OF SEA FOG ON THE SOUTHERN CHINA COAST

This study uses numerical simulations to examine a case of sea fog that was observed from 20 to 22 March2011 on the southern China coast. The observation dataset includes observatory data, cloud-top temperature from MODIS, GPS sonde, and data from the Integrated Observation Platform for Marine Meteorology(IOPMM). The simulations are based on the Weather Research and Forecasting(WRF) model with four distinct parameter settings.Both the observations and simulations focus on the characteristics of the fog extent, boundary layer structure, and meteorological elements near the air-sea interface. Our main results are as follows:(1) The extent of mesoscale sea fog can be well simulated when the sea surface temperature has at least 0.5 ×0.5 horizontal resolution.(2) To accurately model the vertical structure of the sea fog, particularly the surface-based inversion, vertical levels must be added in the boundary layer.(3) When these model conditions are met, the simulations faithfully reproduce the measured downward shortwave radiation, downward longwave radiation, and surface sensible heat flux during the sea fog period.     

An Analysis of Thermally-Related Surface Rainfall Budgets Associated with Convective and Stratiform Rainfall

Both water vapor and heat processes play key roles in producing surface rainfall.While the water vapor effects of sea surface temperature and cloud radiative and microphysical processes on surface rainfall have been investigated in previous studies,the thermal effects on rainfall are analyzed in this study using a series of two-dimensional equilibrium cloud-resolving model experiments forced by zonally-uniform,constant,large-scale zonal wind and zero large-scale vertical velocity.The analysis of thermally-related surface rainfall budget reveals that the model domain mean surface rain rate is primarily associated with the mean infrared cooling rate.Convective rainfall and transport of hydrometeor concentration from convective regions to raining stratiform regions corresponds to the heat divergence over convective regions,whereas stratiform rainfall corresponds to the transport of hydrometeor concentration from convective regions and heat divergence over raining stratiform regions.The heat divergence over convective regions is mainly balanced by the heat convergence over rainfall-free regions,which is,in turn,offset by the radiative cooling over rainfall-free regions.The sensitivity experiments of rainfall to the effects of sea surface temperature and cloud radiative and microphysical processes show that the sea surface temperature and cloud processes affect convective rainfall through the changes in infrared cooling rate over rainfall-free regions and transport rate of heat from convective regions to rainfall-free regions.     

Regional estimates of evapotranspiration over Northern China using a remote-sensing-based triangle interpolation method

Regional estimates of evapotranspiration (ET) are critical for a wide range of applications. Satellite remote sensing is a promising tool for obtaining reasonable ET spatial distribution data. However, there are at least two major problems that exist in the regional estimation of ET from remote sensing data. One is the conflicting requirements of simple data over a wide region, and accuracy of those data. The second is the lack of regional ET products that cover the entire region of northern China. In this study, we first retrieved the evaporative fraction (EF) by interpolating from the difference of day/night land surface temperature ( T ) and the normalized difference vegetation index (NDVI) triangular-shaped scatter space. Then, ET was generated from EF and land surface meteorological data. The estimated eight-day EF and ET results were validated with 14 eddy covariance (EC) flux measurements in the growing season (July-September) for the year2008 over the study area. The estimated values agreed well with flux tower measurements, and this agreement was highly statistically significant for both EF and ET (p <0.01), with the correlation coefficient for EF (R2 =0.64) being relatively higher than for ET (R2 =0.57). Validation with EC-measured ET showed the mean RMSE and bias were 0.78 mm d-1 (22.03 W m-2 ) and 0.31 mm d-1 (8.86 W m-2 ), respectively. The ET over the study area increased along a clear longitudinal gradient, which was probably controlled by the gradient of precipitation, green vegetation fractions, and the intensity of human activities. The satellite-based estimates adequately captured the spatial and seasonal structure of ET. Overall, our results demonstrate the potential of this simple but practical method for monitoring ET over regions with heterogeneous surface areas.     

A Spatial Consistency Quality Control Method for Daily Surface Temperature Observations

A new spatial consistency quality control method (SRF) based on the spatial regression test (SRT) and random forest (RF) was adapted to identify potential outliers in daily surface temperature observations in this article. For the new method, the SRT method was used to filter the data and the RF method was used to conduct regression. To evaluate the performance of the quality control method, the SRF, SRT and RF methods were applied to a surface temperature dataset with seeded errors from different regions of China from 2005 to 2014. Compared to SRT and RF, the results indicate that the SRF method outperforms the other two methods for the most cases. And the results of the comparison led to the recommendation that the SRF method improves the regression accuracy of traditional spatial consistency quality control methods and reduces the runtime of random forest through data refinement.