Seasonal prediction skills of FIO-ESM for North Pacific sea surface temperature and precipitation

The seasonal prediction of sea surface temperature(SST) and precipitation in the North Pacific based on the hindcast results of The First Institute of Oceanography Earth System Model(FIO-ESM) is assessed in this study.The Ensemble Adjusted Kalman Filter assimilation scheme is used to generate initial conditions, which are shown to be reliable by comparison with the observations. Based on this comparison, we analyze the FIO-ESM 6-month hindcast results starting from each month of 1993–2013. The model exhibits high SST prediction skills over most of the North Pacific for two seasons in advance. Furthermore, it remains skillful at long lead times for midlatitudes. The reliable prediction of SST can transfer fairly well to precipitation prediction via air-sea interactions.The average skill of the North Pacific variability(NPV) index from 1 to 6 months lead is as high as 0.72(0.55) when El Ni?o-Southern Oscillation and NPV are in phase(out of phase) at initial conditions. The prediction skill of the NPV index of FIO-ESM is improved by 11.6%(23.6%) over the Climate Forecast System, Version 2. For seasonal dependence, the skill of FIO-ESM is higher than the skill of persistence prediction in the later period of prediction.

THE CORRELATION BETWEEN THE PACIFIC SEA SURFACE TEMPERATURE(SST) and PRECIPITATION OVER NW CHINA

With the singular value decomposition (SVD), correlation analysis has been conducted between the Pacific Ocean sea surface temperature (SST) and northwestern China precipitation over March May (MAM). The result shows that there is good relationship between the North Pacific and spring precipitation in northwestern China. When the SST is of the peak El Ni駉 phase, precipitation is less over this part of the country except for the Qinghai-Tibetan Plateau; when the SST for the months DJF is of the mature El Ni駉 phase, precipitation is more over the region in the subsequent March May; when the North Pacific SST for DJF is of the La Ni馻 pattern, precipitation is less over the plateau in the subsequent March May. For the Pacific SST, the westerly drift, kuroshio current, Californian current and north equatorial current are all significantly correlating with the March May precipitation in northwestern China. Specifically, the SST in DJF over the kuroshio current region is out of phase with the precipitation in northern Xinjiang, i.e. when the former is low, the latter is more. In northwestern China, regions in which March May precipitation response to the variation of SST in the Pacific Ocean are northern Xinjiang, the Qinghai-Tibetan Plateau and areas off its northeastern part, the desert basin and western part of the Corridor of the Great Bend of Yellow River valley (Corridor).

Influence of Sea Surface Temperature on the Predictability of Idealized Tropical Cyclone Intensity

The role of sea surface temperature(SST)forcing in the development and predictability of tropical cyclone(TC)intensity is examined using a large set of idealized numerical experiments in the Weather Research and Forecasting(WRF)model.The results indicate that the onset time of rapid intensification of TC gradually decreases,and the peak intensity of TC gradually increases,with the increased magnitude of SST.The predictability limits of the maximum 10 m wind speed(MWS)and minimum sea level pressure(MSLP)are~72 and~84 hours,respectively.Comparisons of the analyses of variance for different simulation time confirm that the MWS and MSLP have strong signal-to-noise ratios(SNR)from 0-72 hours and a marked decrease beyond 72 hours.For the horizontal and vertical structures of wind speed,noticeable decreases in the magnitude of SNR can be seen as the simulation time increases,similar to that of the SLP or perturbation pressure.These results indicate that the SST as an external forcing signal plays an important role in TC intensity for up to 72 hours,and it is significantly weakened if the simulation time exceeds the predictability limits of TC intensity.

The effects of different sea surface temperature distributions over the western Pacific on the summer monsoon properties

A modified and improved primitive equation numerical model with p-sigma incorporated vertical coordinates is used to simulate the effects of different sea surface temperature distributions over the western Pacific on the summer monsoon properties. The different sea surface temperature (SST) distributions are automatically generated in the time integrations by using two different SST models, one of which is called the deep ocean model (DOM) and the other the shallow ocean model (SOM). The SST generated by the DOM has the distribution pattern of the initial SST which is similar to the pattern in the cold water years over the western Pacific, while the SST generated by the SOM has the pattern similar to that in the warm water years. The differences between the experimental results by using DOM and SOM are analyzed in detail. The analyses indicate that the most basic and important characteristics of the summer monsoon climate can be simulated successfully in both experiments, that means the climatic properties in the monsoonal climate regions are mainly determined by the seasonal heating, the contrast between the land and the sea, the topography, and the physical properties of the underlying surfaces. However, the differences between the two experiments tell us that the climatic properties in the summer monsoon regions in the cold water year and the warm water year do differ from each other in details. In the warm water year, the thermal contrast between the land and the sea becomes weaker. Over the warm water area, the upward motions are induced and the dynamical conditions favorable for the convective activities are formed, the Somali low-level cross equatorial current is somewhat weakened, while the cross equatorial currents, east of 90°E, are strongly strengthened, the precipitation amount in the tropical regions largely increases, and the precipitation over the coastal regions increases, too. However the precipitation over the southeast China and its coastal area decreases. The precipitation amount mainly depends on the strength of the convective activity.

Relation between sea surface temperature anomaly in the Atlantic and summer precipitation over the Northeast China

Based on global monthly average data set of sea surface temperature (SST) during 1950 - 1992 and global monthly average 500 hPa height during 1930- 1997 offered by NCARINCEP, the feature of SST anomaly in the Atlantic and its relation with summer precipitation over the Northeast China are analyzed. The results show that, the second eigenvector of the SST’s empirical orthogonal expanssion in winter season over the North Atlantic suggests that dist-ibution of SST anomaly has unusual meridional difference; The location of its center is basically identical to center of significant correlation region be- tween summer precipitation over the Northeast China and winter SST in the Atlantic. When winter SST in the North Atlantic is hot in south and cold in north, the blocking situation is stronger in the middle- high latitude. Correspondingly, the blocking high pressure in the northern North Pacific is also getting stronger, the westerlies circulation index in East Asia in next summer would be lower,as a result,more precipitation in the summer would be experienced over Northeast China and vice versa.

Influence of Sea Surface Temperature on Outbreak of Ulva prolifera in the Southern Yellow Sea,China

In this study,using Moderate Resolution Imaging Spectroradiometer(MODIS)satellite images and environmental satellite CCD images,the spatio-temporal distribution of Ulva prolifera in the southern Yellow Sea during the period of 2011–2018 was extracted and combined with MODIS Level3 Photosynthetically Active Radiation(PAR)product data and Earth System Research Laboratory(ESRL)Sea Surface Temperature(SST)data to analyze their influences on the growth and outbreak of Ulva prolifera.The following conclusions were drawn:1)comprehensive analysis of Ulva prolifera distribution during the eight-year period revealed that the coverage area of Ulva prolifera typically exhibited a gradually increasing trend.The coverage area of Ulva prolifera reached a maximum of approximately 1714.21 km^2 during the eight-year period in late June 2015.The area affected by Ulva prolifera fluctuated.In mid-July 2014,the area affected by Ulva prolifera reached a maximum of approximately 39020.63 km^2.2)The average growth rate of Ulva prolifera was positive in May and June but negative in July.During the outbreak of Ulva prolifera,the SST in the southern Yellow Sea tended to increase each month.The SST anomaly and average growth rate of Ulva prolifera were positively correlated in May(R^2=0.62),but not significantly correlated in June or July.3)The variation trends of PAR and SST were approximately the same,and the PAR during this time period maintained a range of 40–50 mol/(m^2·d),providing sufficient illumination for the growth and outbreak of Ulva prolifera.In addition,the abundant nutrients and suitable temperature in the sea area near northern Jiangsu shoal resulted in a high growth rate of Ulva prolifera in May.In summary,the outbreak of Ulva prolifera was closely related to the environmental factors including SST,nutrients,and PAR.Sufficient nutrients and suitable temperatures resulted in a fast growth rate of Ulva prolifera.However,under poor nutrient conditions,even more suitable temperatures were not sufficient to trigger an outbreak of Ulva prolifera.

APPLICATION OF NONLINEAR MULTI-CHANNEL ALGORITHMS FOR ESTIMATING SEA SURFACE TEMPERATURE WITH NOAA 14 AVHRR DATA

NOAA global operational NOAA/AVHRR Nonlinear Sea Surface Temperature (NLSST) retrieval algorithms were used to generate Global Area Coverage (GAC) sea surface temperature (SST) measurements in the global ocean in 1998. The accuracy of SST retrieved from daytime split window NLSST algorithm and nighttime triple window NLSST algorithm for NOAA 14 AVHRR data was investigated in this study. A matchup dataset of drifting buoys and NOAA 14 satellite measurements in the global ocean was generated to validate these operational split window and triple window algorithms. For NOAA 14 in 1998, we had 14095 and 22643 satellite and buoy matchups that matched within 25 km and 4 hours for daytime and nighttime, respectively. The satellite derived SST had a bias of less than 0.1℃ and standard deviation of about 0.5℃. This study also showed that the NLSST algorithm provided the same order of SST accuracy in different time of the year and under a wide range of satellite zenith angle and water vapor represented by the channel 4 and 5 brightness temperature difference. Therefore, NLSST algorithms are usually independent of season, geographic location, or atmospheric moisture content. Comparison between the low resolution AVHRR GAC data accuracy and high resolution Local Area Coverage (LAC) data accuracy is also discussed.

Sea surface temperature and salinity reconstruction based on stable isotopes and Mg/Ca of planktonic foraminifera in the western Pacific Warm Pool during the last 155 ka

Changes in sea surface temperature(SST), seawater oxygen isotope(δ 18 O sw), and local salinity proxy(δ 18 O sw-ss) in the past 155 ka were studied using a sediment core(MD06-3052) from the northern edge of the western Pacifi c Warm Pool(WPWP), within the fl ow path of the bifurcation of the North Equatorial Current. Our records reveal a lead-lag relationship between paired Mg/Ca-SST and δ 18 O during Termination II and the last interglacial period. Similarity in SST between our site and the Antarctic temperature proxy and in CO 2 profi le showed a close connection between the WPWP and the Antarctic. Values of δ 18 O sw exhibited very similar variations to those of mean ocean δ 18 O sw, owing to the past sea-level changes on glacial-interglacial timescale. Calculated values of δ 18 O sw-ss refl ect a more saline condition during high local summer insolation(SI) periods. Such correspondence between δ 18 O sw-ss and local SI in the WPWP may refl ect complex interaction between ENSO and monsoon, which was stimulated by changes in solar irradiance and their infl uence on the local hydrologic cycle. This then caused a striking reorganization of atmospheric circulation over the WPWP.

A Gaussian process regression-based sea surface temperature interpolation algorithm

The resolution of ocean reanalysis datasets is generally low because of the limited resolution of their associated numerical models.Low-resolution ocean reanalysis datasets are therefore usually interpolated to provide an initial or boundary field for higher-resolution regional ocean models.However,traditional interpolation methods(nearest neighbor interpolation,bilinear interpolation,and bicubic interpolation)lack physical constraints and can generate significant errors at land-sea boundaries and around islands.In this paper,a machine learning method is used to design an interpolation algorithm based on Gaussian process regression.The method uses a multiscale kernel function to process two-dimensional space meteorological ocean processes and introduces multiscale physical feature information(sea surface wind stress,sea surface heat flux,and ocean current velocity).This greatly improves the spatial resolution of ocean features and the interpolation accuracy.The eff ectiveness of the algorithm was validated through interpolation experiments relating to sea surface temperature(SST).The root mean square error(RMSE)of the interpolation algorithm was 38.9%,43.7%,and 62.4%lower than that of bilinear interpolation,bicubic interpolation,and nearest neighbor interpolation,respectively.The interpolation accuracy was also significantly better in off shore area and around islands.The algorithm has an acceptable runtime cost and good temporal and spatial generalizability.

Sea surface temperature anomalies in the South China Sea during mature phase of ENSO

Based on the 18-year(1993–2010) National Centers for Environmental Prediction optimum interpolation sea surface temperature(SST) and simple ocean data assimilation datasets,this study investigated the patterns of the SST anomalies(SSTAs) that occurred in the South China Sea(SCS) during the mature phase of the El Ni?o/Southern Oscillation.The most dominant characteristic was that of the outof-phase variation between southwestern and northeastern parts of the SCS,which was influenced primarily by the net surface heat flux and by horizontal thermal advection.The negative SSTA in the northeastern SCS was caused mainly by the loss of heat to the atmosphere and because of the cold-water advection from the western Pacific through the Luzon Strait during El Ni?o episodes.Conversely,it was found that the anomalous large-scale atmospheric circulation and weakened western boundary current during El Ni?o episodes led to the development of the positive SSTA in the southwestern SCS.

A comparison of Argo nominal surface and near-surface temperature for validation ofAMSR-E SST

Satellite SST(sea surface temperature) from the Advanced Microwave Scanning Radiometer for the Earth Observing System(AMSR-E) is compared with in situ temperature observations from Argo profiling floats over the global oceans to evaluate the advantages of Argo NST(near-surface temperature: water temperature less than 1 m from the surface). By comparing Argo nominal surface temperature(~5 m) with its NST, a diurnal cycle caused by daytime warming and nighttime cooling was found, along with a maximum warming of 0.08±0.36°C during 14:00–15:00 local time. Further comparisons between Argo 5-m temperature/Argo NST and AMSR-E SST retrievals related to wind speed, columnar water vapor, and columnar cloud water indicate warming biases at low wind speed(<5 m/s) and columnar water vapor >28 mm during daytime. The warming tendency is more remarkable for AMSR-E SST/Argo 5-m temperature compared with AMSR-E SST/Argo NST, owing to the effect of diurnal warming. This effect of diurnal warming events should be excluded before validation for microwave SST retrievals. Both AMSR-E nighttime SST/Argo 5-m temperature and nighttime SST/Argo NST show generally good agreement, independent of wind speed and columnar water vapor. From our analysis, Argo NST data demonstrated their advantages for validation of satellite-retrieved SST.

Impact of climatic change on sea surface temperature variation in Subei coastal waters,East China

Sea surface temperature(SST) variation in the Subei coastal waters,East China,which is important for the ecological environment of the Yellow Sea where Enteromorphaprolifera blooms frequently,is affected by the East Asian winter monsoon(EAWM),El Nino-Southern Oscillation(ENSO),and Pacific Decadal Oscillation(PDO).In this study,correlations between climatic events and SST anomalies(SSTA)around the Subei(North Jiangsu Province,East China) Coast from 1981-2012 are analyzed,using empirical orthogonal function(EOF) and correlation analyses.First,a key region was determined by EOF analysis to represent the Subei coastal waters.Then,coherency analyses were performed on this key region.According to the correlation analysis,the EAWM index has a positive correlation with the spring and summer SSTA of the key region.Furthermore,the Nino3.4 index is negatively correlated with the spring and summer SSTA of the key region 1 year ahead,and the PDO has significant negative coherency with spring SSTA and negative coherency with summer SSTA in the key region 1 year ahead.Overall,PDO exhibits the most significant impact on SSTA of the key region.In the key region,all these factors are correlated more significantly with SSTA in spring than in summer.This suggests that outbreaks of Enteromorpha prolifera in the Yellow Sea are affected by global climatic changes,especially the PDO.

Effective forecast of Northeast Pacific sea surface temperature based on a complementary ensemble empirical mode decomposition–support vector machine method

海洋表面温度(sea surface temperature,SST)对气候有着很大影响,但其所具有的非线性、无明显周期、强随机性等特点,给SST预测分析带来了很大的困难。本文将互补集合经验模态分解(complementary ensemble empirical mode decomposition,CEEMD)与支持向量机(support vector machine,SVM)相结合来研究对海洋表面温度异常(SSTA)的预报,并从预报准确性、可预报时长、不同起报时间对预报精度影响等方面设计了多组数值实验。实验结果显示CEEMDSVM方法预测12个月SSTA的效果较好,平均绝对误差在0.3°C左右,相关系数达到了0.85,而且试验中未出现春季预报障碍问题。

Co-variation of the surface wind speed and the sea surface temperature over mesoscale eddies in the Gulf Stream region:momentum vertical mixing aspect

The co-variation of surface wind speed and sea surface temperature (SST) over the Gulf Stream frontal region is investigated using high-resolution satellite measurements and atmospheric reanalysis data. Results show that the pattern of positive SST-surface wind speed correlations is anchored by strong SST gradient and marine atmospheric boundary layer (MABL) height front, with active warm and cold-ocean eddies around. The MABL has an obvious transitional structure along the strong SST front, with greater (lesser) heights over the north (south) side. The significant positive SST-surface wind-speed perturbation correlations are mostly found over both strong warm and cold eddies. The surface wind speed increases (decreases) about 0.32 (0.41) m/s and the MABL elevates (drops) approximate 55 (54) m per 1℃ of SST perturbation induced by warm (cold) eddies. The response of the surface wind speed to SST perturbations over the mesoscale eddies is mainly attributed to the momentum vertical mixing in the MABL, which is confirmed by the linear relationships between the downwind (crosswind) SST gradient and wind divergence (curl).

Interannual Fluctuations of Surface Air Temperature over North America and Its Relationship to the North Pacific SST Anomaly

The characteristics of interannual fluctuations of the surface air temperature over North America are investigated by using the surface air temperature data of 130 stations during 1941 through 1980. It is found that the surface air temperature bears about ten-year time scale oscillation over the southeastern and northwestern North America and along the west coast of the United States, and it has the characteristics of quasibiennial oscillation over the eastern North America. The ten-year scale oscillation of the surface air temperature is related to that of the sea surface temperature (SST) of North Pacific through the PNA pattern atmospheric circulation anomaly over North Pacific through North America. It is shown that the North Pacific SST has a closer association with the surface air temperature over North America than the central and eastern equatorial Pacific SST. The characteristics of the seasonal variations of the relationship between the North Pacific SST and the surface air temperature over North America are also analyzed.

SENSITIVITY OF PRECIPITATION TO SEA SURFACE TEMPERATURE AND ITS DIURNAL VARIATION:A PARTITIONING ANALYSIS BASED ON SURFACE RAINFALL BUDGET

The sensitivity of precipitation to sea surface temperature(SST) and its diurnal variation is investigated through a rainfall partitioning analysis of two-dimensional cloud-resolving model experiments based on surface rainfall budget.For all experiments,the model is set up using zero vertical velocity and a constant zonal wind and is integrated over 40 days to reach quasi-equilibrium states.The 10-day equilibrium grid-scale simulation data and a time-invariant SST of 29°C are used in the control experiment.In the sensitivity experiments,time-invariant SSTs are 27°C and 31°C with an average value of 29°C when the minimum and maximum values of diurnal SST differences are 1°C and 2°C,respectively.The results show that the largest contribution to total rainfall is from the rainfall with water vapor convergence and local atmospheric drying and hydrometeor gain/divergence(~30%) in all experiments.When SST increases from 27°C to 29°C,the contribution from water vapor convergence decreases.The increase of SST reduces the contribution of the rainfall with water vapor convergence primarily through the decreased contribution of the rainfall with local atmospheric drying and hydrometeor gain/divergence and the rainfall with local atmospheric moistening and hydrometeor loss/convergence.The inclusion of diurnal variation of SST with the diurnal difference of 1°C decreases the rainfall contribution from water vapor convergence primarily through the decreased contribution of the rainfall with local atmospheric moistening and hydrometeor loss/convergence.The contribution of the rainfall from water vapor convergence is barely changed as the diurnal difference of SST increases from 1°C to 2°C.

The PNA wavetrain and the sea surface temperature in the Northern Pacific

In this paper, the response of the atmospheric 3-5 year cycle to Northern Pacific SST is discussed, The results are as follows:1. From the simultaneous temporal correlations between the Equatorial Eastern Pacific SST, the westerly dirft area's SST and the Northern Pacific SST at all gridpoints, we find that there are three correlative regions in the Northern Pacific SST field, they are the westerly drift area, the Equatorial Eastern Pacific and the Alaska Bay , and their structures are very similar to the PNA pattern in the atmosphere The difference PTI between the Equatorial Eastern Pacific SST anomaly and the westerly drift area's SST anomaly can indicate the change of the PNA pattern of the Northern Pacific SST anomaly. It can represent SST change of 65 % areas over the Northern Pacific and can keep watch on El Nino and un-El Nino.2. Simultaneous temporal correlative field between PTI and filtered 500hPa (there is 3-5 year cycle only ) of the Northern Hemisphere presents clear PNA structure. The responses of the filtered 500hPa to El Nino and to un-EI Nino produce +PNA and -PNA wavetrains respectively.3. According to the different positions of the sea-surface temperature rise (drop) ,El Nino (un-EI Nino )can be divided into two classes: east-pattern and middle-pattern. The responses of the filtered 500hPa to the east-pattern and to the middle-pattern will produce PNA and EAA wavetrain respectively. This indicates that the responses of the atmosphere to the stationary heat sources in diffrent areas will produce wavetrains in diffrent track.

Evaluation of NOAA/AVHRR Sea Surface Temperature at Full HRPT Resolution in the Northwest Pacific Ocean

The National Oceanic and Atmospheric Administration(NOAA)Polar Orbiting Environmental Satellites(POES)High Resolution Picture Transmission(HRPT)data in the Northwest Pacific Ocean has been acquired through the SeaSpace ground station located at the Ocean University of China since October 2000,and these data have been processed by the TeraScan system.The sea surface temperature(SST)products in the Northwest Pacific Ocean derived from Advanced Very High Resolution Radiometer(AVHRR)are evaluated.We compared the SST products with the buoy SSTs during the stable operational period of each satellite.There are a total of 33715 and 71819 matchups acquired for daytime and nighttime,respectively,between the NOAA/AVHRR SSTs and buoy SSTs.For each satellite,the biases and standard deviations at daytime are smaller than those at nighttime.The monthly biases at daytime generally oscillate around 0℃,except for NOAA-15.By contrast,the monthly biases at nighttime mostly oscillate around−0.5℃.Both daytime and nighttime biases exhibit seasonal oscillations for all satellites.The seasonal biases of the SST difference at daytime between each satellite and buoy are mostly within±0.25℃,except for the negative bias of−0.58℃in May for NOAA-18.The seasonal biases of the SST difference at nighttime are mostly around−0.5℃,and NOAA-16 has a lower bias,i.e.,−0.86℃,in April.These results indicate that the accuracy of the SST products is inconsistent for each satellite during different periods.It is suggested that the NOAA/AVHRR data should be reprocessed to provide highly accurate SST products.

Sea Surface Temperature Anomaly and Precipitation Distribution in the Alagoas State of the Brazilian Northeast

Precipitation data of 17 pluviometrical stations in the Alagoas State of the Brazilian Northeast and global spatial distribution of the Sea Surface Temperature Anomaly (SSTA) were analyzed for the period of 1981-2007. Techniques of constructing composite charts for SSTA fields are used to study the interrelation between the ocean thermal state with precipitation more than 50 mm/24 h, 20 mm/24 h or without precipitation for six ambient regions of the state. The student test is used for estimating statistical characteristics of the composites. Synoptic-scale pattern analyses of the composites reveal strikingly different spatial distribution of SSTA within each composite. The El Ni&#241;o Southern Oscillation cycle refers to the coherent, large-scale fluctuation of ocean temperatures. At the highest ambient regions during heavy precipitation days, more intensive SSTA was observed. The lowest anomalies were observed for all types of precipitation in the semi-arid region. Quantile analyses of NCEP/NCAR indexes of SSTA distribution, such as NATL, SATL, TROP and RNASA were used too. Positive SSTA values in tropical regions are associated with the highest possibility of precipitation formation. The SST interhemispheric north-south gradient in equatorial regions of the North and South Atlantic has direct influence on the precipitation formation in the Alagoas State.

SATELLITE REMOTE SENSING OF SEA-ICE AND SEA SURFACE TEMPERATURE

Sea-ice and Sea Surface Temperature in offshore seas are important terms for operational monitoring and forecasting marine environment in China. The software system of regional marine environmental application designed by author is used for realtime operational monitoring sea-ice, SST, oceanic current and colours and characters of land surface. This software system processes quantitative AVHRR data from NOAA satellite to calculate calibration coefficient, solar angle correction, earth location parameter and atmospheric attenuation correction, then SST field will be produced through calculation using special SST model, and top-quality of colour composite imagery of satellite with variable spacial resolution (1, 2 or 5km) will be produced via image processing. Inside front covor Figure 1 is colour enhanced imagery with 5km resolution of NOAA satellite in offshore