Seasonal influence of freshwater discharge on spatio-temporal variations in primary productivity, sea surface temperature, and euphotic zone depth in the northern Bay of Bengal

Ocean productivity is the foundation of marine food web,which continuously removes atmospheric carbon dioxide and supports life at sea and on land.Spatio-temporal variability of net primary productivity(NPP),sea surface temperature(SST),sea surface salinity(SSS),mixed layer depth(MLD),and euphotic zone depth(EZD) in the northern B ay of Bengal(BoB) during three monsoon seasons were examined in this study based on remote sensing data for the period 2005 to 2020.To compare the NPP distribution between the coastal zones and open BoB,the study area was divided into five zones(Z1-Z5).Results suggest that most productive zones Z2 and Zl are located at the head bay area and are directly influenced by freshwater discharge together with riverine sediment and nutrient loads.Across Z1-Z5,the NPP ranges from 5 315.38 mg/(m^(2)·d) to 346.7 mg/(m^(2)·d)(carbon,since then the same).The highest monthly average NPP of 5 315.38 mg/(m^(2)·d) in February and 5 039.36 mg/(m^(2)·d) in June were observed from Z2,while the lowest monthly average of 346.72 mg/(m^(2)·d) was observed in March from Z4,which is an oceanic zone.EZD values vary from 6-154 m for the study area,and it has an inverse correlation with NPP concentration.EZD is deeper during the summer season and shallower during the wintertime,with a corresponding increase in productivity.Throughout the year,monthly SST shows slight fluctuation for the entire study area,and statistical analysis shows a significant correlation among NPP,and EZD,overall positive between NPP and MLD,whereas no significant correlation among SSS,and SST for the northern BoB.Long-term trends in SST and productivity were significantly po sitive in head bay zones but negatively productive in the open ocean.The findings in this study on the distribution of NPP,SST,SSS,MLD,and EZD and their seasonal variability in five different zones of BoB can be used to further improve the management of marine resources and overall environmental condition in response to climate changes in BoB as they are of utmost relevance to the fisheries for the three bordering countries.

Contribution of Surface Waves to Sea Surface Temperatures in the Arctic Ocean

The aim of our study was to examine the contribution of surface waves from WAVEWATCH-III(WW3)to the variation in sea surface temperature(SST)in the Arctic Ocean.The simulated significant wave height(SWH)were validated against the products from Haiyang-2B(HY-2B)in 2021,obtaining a root mean squared error(RMSE)of 0.45 with a correlation of 0.96 and scatter index of 0.18.The wave-induced effects,i.e.,wave breaking and mixing induced by nonbearing waves resulting in changes in radiation stress and Stokes drift,were calculated from WW3,ERA-5 wind,SST,and salinity data from the National Centers for Environmental Prediction and were taken as forcing fields in the Stony Brook Parallel Ocean Model.The results showed that an RMSE of 0.81℃ with wave-induced effects was less than the RMSE of 1.11℃ achieved without the wave term compared with the simulated SST with the measurements from Argos.Considering the four wave effects and sea ice freezing,the SST in the Arctic Ocean decreased by up to 1℃ in winter.Regression analysis revealed that the SWH was linear in SST(values without subtraction of waves)in summer and autumn,but this behavior was not observed in spring or winter due to the presence of sea ice.The interannual variation also presented a negative relationship between the difference in SST and SWH.

Analysis of Sea Surface Temperature Cooling in Typhoon Events Passing the Kuroshio Current

The aim of this study is to investigate the sea surface temperature(SST) cooling as typhoons pass the Kuroshio Current.A numerical circulation model,denoted as the Stony Brook Parallel Ocean Model(sbPOM),was used to simulate the SST,which includes four wave-induced effect terms(i.e.,radiation stress,nonbreaking waves,Stokes drift,and breaking waves) simulated using the third-generation wave model,called WAVEWATCH-Ⅲ(WW3).The significant wave height(SWH) measurements from the Jason-2 altimeter were used to validate the WW3-simulated results,yielding a root mean square error(RMSE) of less than 0.50 m and a correlation coefficient(COR) of approximately 0.93.The water temperature measured from the Advanced Research and Global Observation Satellite was applied to validate the model simulation.Accordingly,the RMSE of the SST is 0.92℃ with a COR of approximately 0.99.As revealed in the sbPOM-simulated SST fields,a reduction in the SST at the Kuroshio Current region was observed as a typhoon passed,although the water temperature of the Kuroshio Current is relatively high.The variation of the SST is consistent with that of the current,whereas the maximum SST lagged behind the occurrence of the peak SWH.Moreover,the Stokes drift plays an important role in the SST cooling after analyzing four wave-induced terms in the background of the Kuroshio Current.The sensitivity experiment also showed that the accuracy of the water temperature was significantly reduced when including breaking waves,which play a negative role in the inside part of the ocean.The variation in the mean mixing layer depth(MLD) showed that a typhoon could enhance the mean MLD in the Kuroshio Current area in September and October,whereas a typhoon has little influence on the mean MLD in the Kuroshio Current area in May.Moreover,the mean MLD rapidly decreased with the weakening of the strong wind force and wave-induced effects when a typhoon crossed the Kuroshio Current.

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.

The long-term variability of sea surface temperature in the seas east of China in the past 40 a

The global surface temperature change since the mid-19th century has caused general concern and intensive study. However, long-term changes in the marginal seas, including the seas east of China, are not well understood because long-term observations are sparse and, even when they exist, they are over limited areas. Preliminary results on the long-term variability of sea surface temperature （SST） in summer and winter in the seas east of China during the period of 1957-2001 are reported using the Ocean Science Database of Institute of Oceanology, Chinese Academy of Sciences, the coastal hydrological station in situ and satellite data. The results show well-defined warming trends in the study area. However warming and cooling trends vary from decade to decade, with steady and rapid warming trends after the 1980s and complicated spatial patterns. The distribution of SST variation is intricate and more blurred in the areas far away from the Kuroshio system. Both historical and satellite data sets show significant warming trends after 1985. The warming trends are larger and spread to wider areas in winter than in summer, which means decrease in the seasonal cycle of SST probably linked with recently observed increase of the tropical zooplankton species in the region. Spatial structures of the SST trends are roughly consistent with the circulation pattern especially in winter when the meridional SST gradients are larger, suggesting that a horizontal advection may play an important role in the long-term SST variability in winter.

Analysis on Long-Term Change of Sea Surface Temperature in the China Seas

Long-term change of sea surface temperature （SST） in the China Seas from 1900 to 2006 is examined based on two different observation datasets （HadlSSTI and HadSST3）. Similar to the Atlantic, SST in the China Seas has been well observed during the past 107 years. A comparison between the reconstructed （HadISSTI） and un-interpolated （HadSST3） datasets shows that the SST wanning trends from both datasets are consistent with each other in most of the China Seas. The warming trends are stronger in winter than in summer, with a maximum rate of SST increase exceeding 2.7℃ （100year）-I in the East China Sea and the Taiwan Strait during winter based on HadISSTI. However, the SST from both datasets experienced a sudden decrease after 1999 in the China Seas. The estimated trend from HadlSSTI is stronger than that fi＇om HadSST3 in the East China Sea and the east of Taiwan Island, where the difference in the linear SST warming trends are as large as about 1℃ （100year）-I when using respectively HadISST1 and HadSST3 datasets. When compared to the linear winter warnling trend of the land surface air temperature （1.6℃ （100 year）-1）, HadSST3 shows a more reasonable trend of less than 2.1℃（ 100 year）-1 than HadISST 1 ＇s trend of larger than 2.7℃ （ 100 year）-1 at the mouth of the Yangtze River. The restllts also indicate large uncertainties in the estimate of SST warming patterns.

Impact of Sea Surface Temperature Front on Stratus-Sea Fog over the Yellow and East China Seas-A Case Study with Implications for Climatology

A stratus-sea fog event that occurred over the Yellow and East China Seas on 3 June 2011 is investigated using observations and a numerical model, with a focus on the effects of background circulation and Sea Surface Temperature Front （SSTF） on the transition of stratus into sea fog. Southerly winds of a synoptic high-pressure circulation transport water vapor to the Yellow Sea, creating conditions favorable for sea fog/stratus formation. The subsidence from the high-pressure contributes to the temperature inversion at the top of the stratus. The SSTF forces a secondary circulation within the ABL （Atmospheric Boundary Layer）, the sinking branch of which on the cold flank of SSTF helps lower the stratus layer fiLrther to reach the sea surface. The cooling effect over the cold sea surface counteracts the adiabatic warming induced by subsidence. The secondary circulation becomes weak and the fog patches are shrtmk heavily with the smoothed SSTE A conceptual model is proposed for the transition of stratus into sea fog over the Yellow and East China Seas. Finally, the analyses suggest that sea fog frequency will probably decrease due to the weakened SSTF and the reduced subsidence of secondary circulation under global wanning.

Assessment of the initial sea surface temperature product of the scanning microwave radiometer aboard on HY-2 satellite

HY-2 satellite is the first satellite for dynamic environmental parameters measurement of China,which was launched on 16th August 2011.A scanning microwave radiometer（RM） is carried for sea surface temperature（SST）,sea surface wind speed,columnar water vapor and columnar cloud liquid water detection.In this paper,the initial SST product of RM was validated with in-situ data of National Data of Buoy Center（NDBC） mooring and Argo buoy.The validation results indicate the accuracy of RM SST is better than 1.7 C.The comparison of RM SST and WindSat SST shows the former is warmer than the latter at high sea surface wind speed and the difference between these SSTs is depend on the sea surface wind speed.Then,the relationship between the errors of RM SST and sea surface wind speed was analyzed using NDBC mooring measurements.Based on the results of assessment and errors analysis,the suggestions of taking account of the affection of sea surface wind speed and using sea surface wind speed and direction derived from the microwave scatteromter aboard on HY-2 for SST product calibration were given for retrieval algorithm improvement.

Contribution of the Sea Surface Temperature over the Mediterranean-Black Sea to the Decadal Shift of the Summer North Atlantic Oscillation

Recent observational study has shown that the southern center of the summer North Atlantic Oscillation （SNAO） was located farther eastward after the late 1970s compared to before. In this study, the cause for this phenomenon is explored. The result shows that the eastward shift of the SNAO southern center after the late 1970s is related to the variability of the Mediterranean-Black Sea （MBS） SST. A warm MBS SST can heat and moisten its overlying atmosphere, consequently producing a negative sea level pressure （SLP） departure over the MBS region. Because the MBS SST is negatively correlated with the SNAO, the negative SLP departure can enhance the eastern part of the negative-phase of the SNAO southern center, consequently producing an eastward SNAO southern center shift. Similarly, a cold MBS SST produces an eastward positive-phase SNAO southern center shift. The reason for why the MBS SST has an impact on the SNAO after the late 1970s but why it is not the case beforehand is also discussed. It is found that this instable relationship is likely to be attributed to the change of the variability of the MBS SST on the decadal time-scale. In 1951 1975, the variability of the MBS SST is quite weak, but in 1978 2002, it becomes more active. The active SST can enhance the interaction between the sea and its overlying atmosphere, thus strengthening the connection between the MBS SST and the SNAO after the late 1970s. The above observational analysis results are further confirmed by sensitivity experiments.

Impacts of Sea Surface Temperature in the Tropical Pacific on Interannual Variability of Madden-Julian Oscillation in Precipitation

The Madden-Julian Oscillation (MJO) is investigated in two sets of 11-year records of observed precipitation, the daily mean Microwave Sounding Units (MSU) oceanic rainfall (Spencer, 1993) data and the pentad Climate Prediction Center Merged Analysis of Precipitation (CMAP) data (Xie and Arkin, 1997). Obvious interannual variability is found in the MJO in the tropical Pacific. MJO is limited to the west of dateline in normal years while extends more east during the year of warm sea surface temperature (SST) appeared in the eastern Pacific (i.e., El Ni?o years of 1982–1983, 1986–1988, 1991–1992) and manifested in the central-eastern Pacific for several months. The most significant correlation between interannual variability of MJO in the central-eastern Pacific and SST was found in the vicinity of the Ni?o3 region. Forced by observed SST, CCM3 presents a realistic trend of interannual variability to MJO in the 11 years, with a smaller magnitude than that from the observation. Comparison between the two realizations of the CCM3 simulation, which are forced by weekly and monthly mean SST respectively, showed that the MJO activities resemble each other in central-eastern Pacific while there is discrepancy in the western Pacific. It is suggested that the interannual variability of MJO is controlled, to certain extent bythe powerful interannual variability of SST in the central-eastern Pacific. In the western Pacific, however, there were remarkable impacts of the intraseasonal oscillation of SST on the MJO, where there was active MJO around the year. The notable disagreement between simulated and observed MJO in the western Pacific may come from the lack of high frequency variation of SST force, or from the shortage of air sea interaction for the intraseasonal time scale. It might be of importance to the MJO which is unable to be represented in the atmospheric model. Key words Madden-Julian Oscillation - Precipitation - Sea surface temperature - Interannual variability This study was sponsored by Chinese Academy of Sciences under grant “Hundred Talents” for “Validation of Coupled Climate Models”, the National Natural Science Foundation of China (Grant No. 49823002), and Project G1999043808.

The 30–60-day Intraseasonal Variability of Sea Surface Temperature in the South China Sea during May–September

This study investigates the structure and propagation of intraseasonal sea surface temperature（SST） variability in the South China Sea（SCS） on the 30-60-day timescale during boreal summer（May-September）. TRMM-based SST, GODAS oceanic reanalysis and ERA-Interim atmospheric reanalysis datasets from 1998 to 2013 are used to examine quantitatively the atmospheric thermodynamic and oceanic dynamic mechanisms responsible for its formation. Power spectra show that the 30-60-day SST variability is predominant, accounting for 60% of the variance of the 10-90-day variability over most of the SCS. Composite analyses demonstrate that the 30-60-day SST variability is characterized by the alternate occurrence of basin-wide positive and negative SST anomalies in the SCS, with positive（negative） SST anomalies accompanied by anomalous northeasterlies（southwesterlies）. The transition and expansion of SST anomalies are driven by the monsoonal trough-ridge seesaw pattern that migrates northward from the equator to the northern SCS. Quantitative diagnosis of the composite mixed-layer heat budgets shows that, within a strong 30-60-day cycle, the atmospheric thermal forcing is indeed a dominant factor, with the mixed-layer net heat flux（MNHF） contributing around 60% of the total SST tendency, while vertical entrainment contributes more than 30%. However, the entrainment-induced SST tendency is sometimes as large as the MNHF-induced component, implying that ocean processes are sometimes as important as surface fluxes in generating the30-60-day SST variability in the SCS.

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.

Major Mid-Late Holocene Cooling in the East China Sea Revealed by an Alkenone Sea Surface Temperature Record

Although the mid-late Holocene cold and dry event about 4000years ago （the 4ka event） has been observed almost globally, it was most prominent in terrestrial climate proxies from the lower latitudes. Here we evaluate the oceanic response to this event in terms of a Holocene sea surface temperature （SST） record reconstructed using the U^7 index for Core B3 on the continen- tal shelf of the East China Sea. The record reveals a large temperature drop of about 5~C from the mid-Holocene （24.7~C at 5.6ka） to the 4ka event （19.2~C at 3.8ka）. This mid-late Holocene cooling period in Core B3 correlated with （i） decreases in the East Asia summer monsoon intensity and （ii） the transition period with increased E1 Nifio/Southern Oscillation activities in the Equatorial Pa- cific. Our SST record provides oceanic evidence for a more global nature of the mid-late Holocene climate change, which was most likely caused by a southward migration of the Intertropical Converge Zone in response to the decreasing summer solar insolation in the Northern Hemisphere. However, the large SST drop around Core B3 indicates that the mid-late Holocene cooling was regionally amplified by the initiation/strengthening of eddy circulation/cold front which caused upwelling and resulted in additional SST de- crease. Upwelling during the mid-late Holocene also enhanced with surface productivity in the East China Sea as reflected by higher alkenone content around Core B3.

Reduced Sensitivity of Tropical Cyclone Intensity and Size to Sea Surface Temperature in a Radiative-Convective Equilibrium Environment

It has been challenging to project the tropical cyclone （TC） intensity, structure and destructive potential changes in a warming climate. Here, we compare the sensitivities of TC intensity, size and destructive potential to sea surface warming with and without a pre-storm atmospheric adjustment to an idealized state of Radiative-Convective Equilibrium （RCE）. Without RCE, we find large responses of TC intensity, size and destructive potential to sea surface temperature （SST） changes, which is in line with some previous studies. However, in an environment under RCE, the TC size is almost insensitive to SST changes, and the sensitivity of intensity is also much reduced to 3% ~C-1-4% ~C-1. Without the pre-storm RCE adjustment, the mean destructive potential measured by the integrated power dissipation increases by about 25% ~C-1 during the mature stage. However, in an environment under RCE, the sensitivity of destructive potential to sea surface warming does not change significantly. Further analyses show that the reduced response of TC intensity and size to sea surface warming under RCE can be explained by the reduced thermodynamic disequilibrium between the air boundary layer and the sea surface due to the RCE adjustment. When conducting regional-scale sea surface warming experiments for TC case studies, without any RCE adjustment the TC response is likely to be unrealistically exaggerated. The TC intensity-temperature sensitivity under RCE is very similar to those found in coupled climate model simulations. This suggests global mean intensity projections under climate change can be understood in terms of a thermodynamic response to temperature with only a minor contribution from any changes in large-scale dynamics.

A COMPARISON AND EVALUATION OF TWO CENTENNIAL-SCALE SEA SURFACE TEMPERATURE DATASETS IN THE CHINA SEAS AND THEIR ADJACENT SEA AREAS

Two reconstructed sea surface temperature(SST) datasets(HadISST1 and COBE SST2) with centennial-scale are compared on the SST climate change over the China Seas and their adjacent sea areas. Two independent datasets show consistency in statistically significant trends, with a warming trend of 0.07—0.08 ℃ per decade from 1890 to2013. However, in shorter epochs(such as 1961—2013 and 1981—2013), HadISST1 exhibits stronger warming rates than those of COBE SST2. Both datasets experienced a sudden decrease in the global hiatus period(1998—2013), but the cooling rate of HadISST1 is lower than that of COBE SST2. These differences are possibly caused by the different observations sources which are incorporated to fill with data-sparse regions since 1982. Different data sources may lead to higher values in HadISST1 from 1981 to 2013 than that in COBE SST2. Meanwhile, the different data sources and bias adjustment before the World War II may also cause the large divergence between COBE SST2 and HadISST1,leading to lower SST from 1891 to 1930. These findings illustrate that the long-term linear trends are broadly similar in the centennial-scale in the China Seas using different datasets. However, there are large uncertainties in the estimate of warming or cooling tendency in the shorter epochs, because there are different data sources, different bias adjustment and interpolation method in different datasets.

Research on sea surface temperature retrieval by the one-dimensional synthetic aperture microwave radiometer, 1D-SAMR

Due to the low spatial resolution of sea surface temperature(T_S)retrieval by real aperture microwave radiometers,in this study,an iterative retrieval method that minimizes the differences between brightness temperature(T_B)measured and modeled was used to retrieve sea surface temperature with a one-dimensional synthetic aperture microwave radiometer,temporarily named 1 D-SAMR.Regarding the configuration of the radiometer,an angular resolution of 0.43°was reached by theoretical calculation.Experiments on sea surface temperature retrieval were carried out with ideal parameters;the results show that the main factors affecting the retrieval accuracy of sea surface temperature are the accuracy of radiometer calibration and the precision of auxiliary geophysical parameters.In the case of no auxiliary parameter errors,the greatest error in retrieved sea surface temperature is obtained at low T_S scene(i.e.,0.7106 K for the incidence angle of 35°under the radiometer calibration accuracy of0.5 K).While errors on auxiliary parameters are assumed to follow a Gaussian distribution,the greatest error on retrieved sea surface temperature was 1.3305 K at an incidence angle of 65°in poorly known sea surface wind speed(W)(the error on W of 1.0 m/s)over high W scene,for the radiometer calibration accuracy of 0.5 K.

Long-term changes in sea surface temperature(SST)within the southern Levantine Basin

Knowledge of sea surface temperature(SST)behaviour is vital for long-term climate scenarios.This study highlights essential outcomes about the distinguishable and unsurprising warming of the SST along the southern border of the Levantine Basin.The analysis is based on monthly SST data for the period 1948-2018.The southern Levantine Basin has undergone SST increase,during the last 71 years.In this study,a consistent warming trend has been found for the analysed SST data series,with a rate of 0.04℃/a,i.e.,0.4℃/(10 a).From 1975 to 1991 the mean annual SST was 17.1℃,and this increased to be 19.2℃,over the period 2002-2018.Results revealed two opposite trends of variability:a decreasing trend(−0.06℃/a)over the period 1975-1991,and an increasing trend(0.2℃/a)from 2002 to 2018.Over the period 1948-2018,positive mean annual SST anomalies had an average of 1.8℃,and negative anomalies had an average of−1.1℃.The lowest SST total increase was found from January to April,with values about 0.03℃,while the highest warming appeared from June to September.The driving mechanisms behind the SST changes need to be more investigated,to understand the future trends and impacts of climate change in the Levantine Basin.

Effects of sea surface temperature,cloud radiative and microphysical processes,and diurnal variations on rainfall in equilibrium cloud-resolving model simulations

The effects of sea surface temperature（SST）,cloud radiative and microphysical processes,and diurnal variations on rainfall statistics are documented with grid data from the two-dimensional equilibrium cloud-resolving model simulations.For a rain rate of higher than 3 mm.h 1,water vapor convergence prevails.The rainfall amount decreases with the decrease of SST from 29℃ to 27℃,the inclusion of diurnal variation of SST,or the exclusion of microphysical effects of ice clouds and radiative effects of water clouds,which are primarily associated with the decreases in water vapor convergence.However,the amount of rainfall increases with the increase of SST from 29℃ to 31℃,the exclusion of diurnal variation of solar zenith angle,and the exclusion of the radiative effects of ice clouds,which are primarily related to increases in water vapor convergence.For a rain rate of less than 3 mm.h 1,water vapor divergence prevails.Unlike rainfall statistics for rain rates of higher than 3 mm.h 1,the decrease of SST from 29℃ to 27℃ and the exclusion of radiative effects of water clouds in the presence of radiative effects of ice clouds increase the rainfall amount,which corresponds to the suppression in water vapor divergence.The exclusion of microphysical effects of ice clouds decreases the amount of rainfall,which corresponds to the enhancement in water vapor divergence.The amount of rainfall is less sensitive to the increase of SST from 29℃ to 31℃ and to the radiative effects of water clouds in the absence of the radiative effects of ice clouds.

Last Glacial Maximum Sea Surface Temperatures: A Model-Data Comparison

In this study,the authors investigated changes in Last Glacial Maximum （LGM） sea surface temperature （SST） simulated by the Paleoclimate Modelling Intercomparison Project （PMIP） multimodels and reconstructed by the Multiproxy Approach for the Reconstruction of the Glacial Ocean Surface （MARGO） project,focusing on model-data comparison.The results showed that the PMIP models produced greater ocean cooling in the North Pacific and Tropical Ocean than the MARGO,particularly in the northwestem Pacific,where the modeldata mismatch was larger.All the models failed to capture the anomalous east-west SST gradient in the North Atlantic.In addition,large discrepancies among the models were observed in the mid-latitude ocean,particularly with models in the second phase of the PMIP.Although these models showed better agreement with the MARGO,the latest models in the third phase of the PMIP did not show substantial progresses in simulating LGM ocean surface conditions.That is,improvements in the modeling community are still needed to describe SST for a better understanding of climate during the LGM.

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.