An ensemble-based SST nudging method proposed for correcting the subsurface temperature field in climate model

An ensemble-based assimilation method is proposed for correcting the subsurface temperature field when nudging the sea surface temperature(SST) observations into the Max Planck Institute(MPI) climate model,ECHAM5/MPI-OM. This method can project SST directly to subsurface according to model ensemble-based correlations between SST and subsurface temperature. Results from a 50 year(1960–2009) assimilation experiment show the method can improve the subsurface temperature field up to 300 m compared to the qualitycontrolled subsurface ocean temperature objective analyses(EN4), through reducing the biases of the thermal states, improving the thermocline structure, and reducing the root mean square(RMS) errors. Moreover, as most of the improvements concentrate over the upper 100 m, the ocean heat content in the upper 100 m(OHT100 m)is further adopted as a property to validate the performance of the ensemble-based correction method. The results show that RMS errors of the global OHT100 m convergent to one value after several times iteration,indicating this method can represent the relationship between SST and subsurface temperature fields well, and then improve the accuracy of the simulation in the subsurface temperature of the climate model.

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.

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).

The Relationship between Extreme Precipitation Events in East Africa during the Short Rainy Season and Indian Ocean Sea Surface Temperature

The East African short rainy season (October-November-December) is one of the major flood seasons in the East African region. The amount of rainfall during the short rainy season is closely related to the lives of the people and the socio-economic development of the area. By using precipitation data and sea surface temperature data, this study reveals the spatial and temporal variation patterns of extreme precipitation during the East African short rainy season. Key findings include significant rainfall variability, with Tanzania experiencing the highest amounts in December due to the southward shift of the Intertropical Convergence Zone (ITCZ), while other regions receive less than 100 mm. Extreme rainfall events (90th percentiles) are evenly distributed, averaging 2 to 10 days annually. Historical data shows maximum seasonal rainfall often peaks at 15 mm, with frequent occurrences of daily rainfall exceeding 10 mm during OND. Additionally, a positive correlation (0.48) between OND precipitation extremes and Indian Ocean Dipole (IOD) anomalies is statistically significant. These findings highlight the climatic variability and potential trends in extreme rainfall events in East Africa, providing valuable insights for regional climate adaptation strategies.

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.

The Singular Value Decomposition Analysis between Summer Precipitation in the Dongting Lake Region and the Global Sea Surface Temperature

By dint of the summer precipitation data from 21 stations in the Dongting Lake region during 1960-2008 and the sea surface temperature(SST) data from NOAA,the spatial and temporal distributions of summer precipitation and their correlations with SST are analyzed.The coupling relationship between the anomalous distribution in summer precipitation and the variation of SST has between studied with the Singular Value Decomposition(SVD) analysis.The increase or decrease of summer precipitation in the Dongting Lake region is closely associated with the SST anomalies in three key regions.The variation of SST in the three key regions has been proved to be a significant previous signal to anomaly of summer rainfall in Dongting region.

Sea Surface Temperature Simulation of Tropical and North Pacific Basins Using a Hybrid Coordinate Ocean Model (HYCOM)

A Hybrid Coordinate Ocean Model （HYCOM） is used to simulate the sea surface temperature of the Tropical and North Pacific. Based on the different combinations of two air-Sea flux data sets （COADS and ECMWF） and two bulk parameter formulas （non-constant and constant）, four numerical experiments are carried out. The following conclusions can be deduced from the numerical results. （1） The numerical results using non-constant bulk parameter formula are much better than those using constant one. In the Pacific area from 40°N to 20°S, the annual average SST obtained from the experiment using non-constant bulk parameter formula is 0.21 ℃ higher than that from the satellite-based SST climatology （the pathfinder data）. However, the difference is 0.63 ℃ for the experiment when the using constant one. （2） HYCOM successfully simulates the monthly variation of climatological SST in tropical and north Pacific basins and monthly spatial variation of Western Pacific Warm Pool. Especially in the Pacific area from 40°N to 20°S, the difference of the seasonal averaged SST between pathfinder data and the result of experiment 2 （using COADS data set and non-constant bulk parameter formula） is only about 0.02 ℃. （3）The simulation results using different Air-Sea flux data are different and the difference is very large in some regions. In the northwest of the model region, the annual average SST obtained from experiment 2 （using COADS data set） is 1℃ higher than that obtained from experiment 4 （using ECMWF data set）. Contrarily, the result of experiment 4 is 1 ℃ larger than that of experiment 2 in the southeast of the model region. The largest difference is about 4 ℃ occurred near the area of 58°N, 140°E and the Bohai sea.

Abrupt Summer Warming and Changes in Temperature Extremes over Northeast Asia Since the Mid-1990s: Drivers and Physical Processes

This study investigated the drivers and physical processes for the abrupt decadal summer surface warming and increases in hot temperature extremes that occurred over Northeast Asia in the mid-1990s. Observations indicate an abrupt increase in summer mean surface air temperature （SAT） over Northeast Asia since the mid-1990s. Accompanying this abrupt surface wanning, significant changes in some temperature extremes, characterized by increases in summer mean daily maximum temperature （Tmax）, daily minimum temperature （Train）, annual hottest day temperature （TXx）, and annual warmest night temperature （TNx） were observed. There were also increases in the frequency of summer days （SU） and tropical nights （TR）. Atmospheric general circulation model experiments forced by changes in sea surface temperature （SST）/sea ice extent （SIE）, anthropogenic greenhouse gas （GHG） concentrations, and anthropogenic aerosol （AA） forcing, relative to the period 1964- 93, reproduced the general patterns of observed summer mean SAT changes and associated changes in temperature extremes, although the abrupt decrease in precipitation since the mid-1990s was not simulated. Additional model experiments with different forcings indicated that changes in SST/SIE explained 76% of the area-averaged summer mean surface warming signal over Northeast Asia, while the direct impact of changes in GHG and AA explained the remaining 24% of the surface warming signal. Analysis of physical processes indicated that the direct impact of the changes in AA （through aerosol- radiation and aerosol-cloud interactions）, mainly related to the reduction of AA precursor emissions over Europe, played a dominant role in the increase in TXx and a similarly important role as SST/SIE changes in the increase in the frequency of SU over Northeast Asia via AA-induced coupled atmosphere-land surface and cloud feedbacks, rather than through a direct impact of AA changes on cloud condensation nuclei. The modelling results also imply that the abrupt summer surface warming and increases in hot temperature extremes over Northeast Asia since the mid-1990s will probably sustain in the next few decades as GHG concentrations continue to increase and AA precursor emissions over both North America and Europe continue to decrease.

The Reliability of Global and Hemispheric Surface Temperature Records

The purpose of this review article is to discuss the development and associated estimation of uncertainties in the global and hemispheric surface temperature records. The review begins by detailing the groups that produce surface temperature datasets. After discussing the reasons for similarities and differences between the various products, the main issues that must be addressed when deriving accurate estimates, particularly for hemispheric and global averages, are then considered. These issues are discussed in the order of their importance for temperature records at these spatial scales： biases in SST data, particularly before the 1940s; the exposure of land-based thermometers before the development of louvred screens in the late 19th century; and urbanization effects in some regions in recent decades. The homogeneity of land-based records is also discussed; however, at these large scales it is relatively unimportant. The article concludes by illustrating hemispheric and global temperature records from the four groups that produce series in near-real time.

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.

The effect of the wave-induced mixing on the upper ocean temperature in a climate model

The significant underestimation of sea surface temperature （SST） and the temperature in the upper ocean is one of common problems in present climate models. The influence of the wave-induced mixing on SST and the temperature in the upper ocean was examined based on a global climate model. The results from the model coupled with wave-induced mixing showed a significant improvement in the simulation of SST and the temperature in the upper ocean compared with those of the original model without wave effects. Although there has still a cold bias, the new simulation is much closer to the climatology, especially in the northern ocean and tropical ocean. This study indicates that some important physical processes in the accurate simulation of the ocean may be ignored in present climate models, and the wave-induced mixing is one of those factors. Thus, the wave-induced mixing （ or the effect of surface waves） should be incorporated properly into climate models in order to simulate or forecast the ocean, then climate system, more accurately.

VARIABILITY IN THE WESTERN PACIFIC SUBTROPICAL HIGH AND ITS RELATIONSHIP WITH SEA TEMPERATURE VARIATION CONSIDERING THE BACKGROUND OF CLIMATE WARMING OVER THE PAST 60 YEARS

By adopting characteristic index data for the Western Pacific Subtropical High(WPSH) from the National Climate Center of China, U.S. National Centers for Environmental Prediction-National Center for Atmospheric Research(NCEP/NCAR) reanalysis data, and the National Oceanic and Atmospheric Administration(NOAA) sea surface temperature(SST) data, we studied the WPSH variability considering the background of climate warming by using a Gaussian filter, moving averages, correlation analysis, and synthetic analysis. Our results show that with climate warming over the past 60 years, significant changes in the WPSH include its enlarged area, strengthened intensity,westward extended ridge point and southward expanded southern boundary, as well as enhanced interannual fluctuations in all these indices. The western ridge point of the WPSH consistently varies with temperature changes in the Northern Hemisphere, but the location of the ridgeline varies independently. The intensity and area of the WPSH were both significantly increased in the late 1980 s. Specifically, the western ridge point started to significantly extend westward in the early 1990 s, and the associated interannual variability had a significant increase in the late 1990 s; in addition, the ridgeline was swaying along the north-south-north direction, and the corresponding variability was also greatly enhanced in the late 1990 s. With climate warming, the SST increase becomes more weakly correlated with the WPSH intensity enhancement but more strongly correlated with the westward extension of the ridge point in the equatorial central and eastern Pacific Ocean in winter, corresponding to an expanding WPSH in space. In the northern Pacific in winter, the SST decrease has a weaker correlation with the southerly location of the ridgeline but also a stronger correlation with the westward extension of the ridge point. In the tropical western Pacific in winter, the correlations of the SST decrease with the WPSH intensity enhancement, and the westward extension of the ridge point is strengthened. These observations can be explained by strengthened Hadley circulations, the dominant effects of the southward shift, and additional effects of the weakened ascending branch of the Walker circulation during warm climatological periods,which consequently lead to strengthened intensities, increased areas, and southward expansions of the WPSH in summer.

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.

Subseasonal Reversal of East Asian Surface Temperature Variability in Winter 2014/15

Although there has been a considerable amount of research conducted on the East Asian winter-mean climate, subseasonal surface air temperature（SAT） variability reversals in the early and late winter remain poorly understood. In this study,we focused on the recent winter of 2014/15, in which warmer anomalies dominated in January and February but colder conditions prevailed in December. Moreover, Arctic sea-ice cover（ASIC） in September–October 2014 was lower than normal,and warmer sea surface temperature（SST） anomalies occurred in the Ni ？no4 region in winter, together with a positive Pacific Decadal Oscillation（PDO｜＋） phase. Using observational data and CMIP5 historical simulations, we investigated the PDO｜＋ phase modulation upon the winter warm Ni ？no4 phase（autumn ASIC reduction） influence on the subseasonal SAT variability of East Asian winter. The results show that, under a PDO｜＋ phase modulation, warm Ni ？no4 SST anomalies are associated with a subseasonal delay of tropical surface heating and subsequent Hadley cell and Ferrel cell intensification in January–February, linking the tropical and midlatitude regions. Consistently, the East Asian jet stream（EAJS） is significantly decelerated in January–February and hence promotes the warm anomalies over East Asia. Under the PDO｜＋ phase,the decrease in ASIC is related to cold SST anomalies in the western North Pacific, which increase the meridional temperature gradient and generate an accelerated and westward-shifted EAJS in December. The westward extension of the EAJS is responsible for the eastward-propagating Rossby waves triggered by declining ASIC and thereby favors the connection between ASIC and cold conditions over East Asia.

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 （δ18Osw）, and local salinity proxy （δ18Osw-ss ） in the past 155 ka were studied using a sediment core （MD06-3052） from the northern edge of the western Pacific Warm Pool （WPWP）, within the flow path of the bifurcation of the North Equatorial Current. Our records reveal a lead-lag relationship between paired Mg/Ca-SST and δ18O during Termination II and the last interglacial period. Similarity in SST between our site and the Antarctic temperature proxy and in CO2 profile showed a close connection between the WPWP and the Antarctic. Values of 818Osw exhibited very similar variations to those of mean ocean δ18Osw, owing to the past sea-level changes on glacial-interglacial timescale. Calculated values of δ18O reflect a more saline condition during high local summer insolation （SI） periods. Such correspondence between δ18O and local SI in the WPWP may reflect complex interaction between ENSO and monsoon, which was stimulated by changes in solar irradiance and their influence on the local hydrologic cycle. This then caused a striking reorganization of atmospheric circulation over the WPWP.

Movements of the Western Pacific Warm Pool Centroid and Their Relationship to Sea Surface Temperature Changes in Nino Regions

By using monthly historical sea surface temperature (SST) data for the yearsfrom 1950 to 2000, the Western Pacific Warm Pool (WPWP) climatology and anomalies are studied inthis paper. The analysis of WPWP centroid (WPWPC) movement anomalies and the Nino-3 region SSTanomalies(SSTA) seems to reveal a close, linear relation between the zonal WPWPC and Nino-3 regionSSTA, which suggests that a 9° anomaly of the zonal displacement from the climatological positionof the WPWPC corresponds to about a 1℃ anomaly in the Nino-3 region area-mean SST. This studyconnects the WPWPC zonal displacement with the Nino-3 SSTA, and it may be helpful in betterunderstanding the fact that the WPWP eastward extension is conducive to the Nino-3 region SSTincrease during an El Nino-Southern Oscillation (ENSO) event.

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.

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 Nifio-Southem 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 Nifio3.4 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 ofEnteromorpha prolifera in the Yellow Sea are affected by global climatic changes, especially the PDO.

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.