Tianjin Meteorological Bureau

Abstract. In order to study the temporal and spatial variations of PM2.5 and its chemical compositions in the region of Beijing, Tianjin, and Hebei (BTH), PM2.5 samples were collected at four urban sites in Beijing (BJ), Tianjin (TJ), Shijiazhuang (SJZ), and Chengde (CD), and also one site at Shangdianzi (SDZ) regional background station over four seasons from 2009 to 2010. The samples were weighted for mass concentrations and analyzed in the laboratory for chemical profiles of 19 elements (Al, As, Ba, Ca, Cd, Co, Cr, Cu, Fe, K, Mg, Mn, Ni, P, Pb, Sr, Ti, V, and Zn), eight water-soluble inorganic ions (Na+, NH4+, K+, Mg2+, Ca2+, Cl−, NO3−, and SO42−, and carbon fractions (OC and EC). The concentrations of PM2.5 and its major chemical species were season dependent and showed spatially similar characteristics in the plain area of BTH. The average annual concentrations of PM2.5 were 71.8–191.2 μg m−3 at the five sites, with more than 90% of sampling days exceeding 50 μg m−3 at BJ, TJ, and SJZ. PM2.5 pollution was most serious at SJZ, and the annual concentrations of PM2.5, secondary inorganic ions, OC, EC, and most crustal elements were all highest. Due to stronger photochemical oxidation, the sum of concentrations of secondary inorganic ions (NH4+, NO3−, and SO42− was highest in the summer at SDZ, BJ, TJ, and CD. Analysis of electric charges of water-soluble inorganic ions indicated the existence of nitric acid or hydrochloric acid in PM2.5. For all five sites, the concentrations of OC, EC and also secondary organic carbon (SOC) in the spring and summer were lower than those in the autumn and winter. SOC had more percentages of increase than primary organic carbon (POC) during the winter. The sums of crustal elements (Al, Ca, Fe, Mg, Ti, Ba, and Sr) were higher in the spring and autumn owing to more days with blowing or floating dust. The concentrations of heavy metals were at higher levels in the BTH area by comparison with other studies. In Shijiazhuang and Chengde, the PM2.5 pollution was dominated by coal combustion. Motor vehicle exhausts and coal combustion emissions both played important roles in Tianjin PM2.5 pollution. However, motor vehicle exhausts had played a more important role in Beijing owing to the reduction of coal consumption and sharp increase of cars in recent years. At SDZ, regional transportation of air pollutants from southern urban areas was significant.

Abstract A dataset of 282 meteorological stations including all of the ordinary and national basic/reference surface stations of north China is used to analyze the urbanization effect on surface air temperature trends. These stations are classified into rural, small city, medium city, large city, and metropolis based on the updated information of total population and specific station locations. The significance of urban warming effects on regional average temperature trends is estimated using monthly mean temperature series of the station group datasets, which undergo inhomogeneity adjustment. The authors found that the largest effect of urbanization on annual mean surface air temperature trends occurs for the large-city station group, with the urban warming being 0.16°C (10 yr)−1, and the effect is the smallest for the small-city station group with urban warming being only 0.07°C (10 yr)−1. A similar assessment is made for the dataset of national basic/reference stations, which has been widely used in regional climate change analyses in China. The results indicate that the regional average annual mean temperature series, as calculated using the data from the national basic/reference stations, is significantly impacted by urban warming, and the trend of urban warming is estimated to be 0.11°C (10 yr)−1. The contribution of urban warming to total annual mean surface air temperature change as estimated with the national basic/reference station dataset reaches 37.9%. It is therefore obvious that, in the current regional average surface air temperature series in north China, or probably in the country as a whole, there still remain large effects from urban warming. The urban warming bias for the regional average temperature anomaly series is corrected. After that, the increasing rate of the regional annual mean temperature is brought down from 0.29°C (10 yr)−1 to 0.18°C (10 yr)−1, and the total change in temperature approaches 0.72°C for the period analyzed.

The continuous measurement of nitric oxide (NO), nitrogen dioxide (NO2), nitrogen oxides (NOx) and ozone (O3) was conducted in Tianjin from September 8 to October 15, 2006. The data were used to investigate the relationship between the O3 distribution and its association with ambient concentrations of NO, NO2 and NOx (NO and NO2). The measured concentrations of the pollutants in the study area varied as a function of time, while peaks in NO, NO2 and O3 all occurred in succession in the daytime. The diurnal cycle of ground-level ozone concentration showed a mid-day peak and lower nighttime concentrations. Furthermore, an inverse relationship was found between O3 NO, NO2 and NOx. In addition, a linear relationship between NO2 and NOx, as well as NO and NOx, and a polynomial relationship between O3 and NO2/NO was found. The variation in the level of oxidant (O3 and NO2) with NO2 was also obtained. It can be seen that OX concentration at a given location is made up of two parts: one independent and the other dependent on NO2 concentration. The independent part can be considered as a regional contribution and is about 20 ppb in Tianjin. An obvious difference in NO, NOx and O3 concentrations between weekdays and weekends was also found, but this difference did not appear in NO2. Lastly, the diurnal variation of O3 concentration under different meteorological conditions was demonstrated and analyzed.

Abstract. North China Plain (NCP) is one of the most densely populated regions in China and has experienced enormous economic growth in the past decades. Its regional trace gas pollution has also become one of the top environmental concerns in China. Measurements of surface trace gases, including O3, NOx, SO2 and CO were carried out within the HaChi (Haze in China) project at Wuqing Meteorology Station, located between 2 mega-cities (Beijing and Tianjin) in the NCP, from 9 July 2009 to 21 January 2010. Detailed statistical analyses were made in order to provide information on the levels of the measured air pollutants and their characteristics. Gaseous air pollutant concentrations were also studied together with meteorological data and satellite data to help us better understand the causes of the observed variations in the trace gases during the field campaign. In comparison to measurements from other rural and background stations in the NCP, relatively high concentrations were detected in Wuqing, presumably due to regional mixing and transport of pollutants. Local meteorology had deterministic impacts on air pollution levels, which have to be accounted for when evaluating other effects on pollutant concentrations. Trace gas concentrations showed strong dependence on wind, providing information on regional pollution characteristics. O3 mixing ratio also showed clear dependencies on temperature and relative humidity.

Various methods are available to estimate reference evapotranspiration (ET 0 ) from standard meteorological observations. The Penman-Monteith method is considered to be the most physical and reliable method and is often used as a standard to verify other empirical methods. This study estimates and compares the monthly ET 0 calculated by 3 methods at 580 Chinese stations over the last 50 yr. The Penman-Monteith method is used here as a reference, and its spatial and temporal differences with the Thornthwaite method and pan measurement are evaluated. The results show that:

BACKGROUND: The advantages of angiotensin-converting enzyme inhibitors (ACEIs) or angiotensin II receptor blockers (ARBs) in reducing risk of cardiovascular events (CVEs) and delaying end-stage kidney disease (ESKD) in patients with chronic kidney disease (CKD) is well-known. However, the efficacy and safety of these agents in non-dialysis CKD stages 3-5 patients are still a controversial issue. METHODS: Two investigators (Yaru Zhang and Dandan He) independently searched and identified relevant studies from MEDLINE (from 1950 to October 2018), EMBASE (from 1970 to October 2018), and the Cochrane Library database. Randomised clinical trials in non-dialysis CKD3-5 patients treated with renin-angiotensin system (RAS) inhibitors were included. We used standard criteria (Cochrane risk of bias tool) to assess the inherent risk of bias of trials. We calculated the odds ratio (OR) and 95% confidence interval (CI) for each outcome by random-effects model. A 2-sided p value < 0.05 was considered statistically significant, and all statistical analyses were performed using STATA, version 15.0. This network meta-analysis was undertaken by the frequency model. RESULTS: Forty-four randomised clinical trials with 42,319 patients were included in our network meta-analysis. ACEIs monotherapy significantly decreased the odds of kidney events (OR 0.54, 95% CI 0.41-0.73), cardiovascular events (OR 0.73, 95% CI 0.64-0.84), cardiovascular death (OR 0.73, 95% CI 0.63-0.86) and all-cause death (OR 0.77, 95% CI 0.66-0.91) when compared to placebo. According to the cumulative ranking area (SUCRA), ACEI monotherapy had the highest probabilities of their protective effects on outcomes of kidney events (SUCRA 93.3%), cardiovascular events (SUCRA 77.2%), cardiovascular death (SUCRA 86%), and all-cause death (SUCRA 94.1%), even if there were no significant differences between ACEIs and other antihypertensive drugs, including calcium channel blockers (CCBs), β-blockers and diuretics on above outcomes except for kidney events. ARB monotherapy and combination therapy of an ACEI plus an ARB showed no more advantage than CCBs, β-blockers and diuretics in all primary outcomes. In the subgroup of non-dialysis diabetic kidney disease patients, no drugs, including ACEIs or ARBs, significantly lowered the odds of cardiovascular events and all-cause death. However, ACEIs were still better than other antihypertensive drugs including ARBs in all-cause death but not ARBs in cardiovascular events according to the SUCRA. Only ARBs had significant differences in preventing the occurrence of kidney events compared with placebo (OR 0.82, 95% CI 0.72-0.95). Both ACEI/ARB monotherapy and combination therapy had higher odds of hyperkalaemia. ACEIs had 3.81 times higher odds than CCBs (95% CI 1.58-9.20), ARBs had 2.08-5.10 times higher odds than placebo and CCBs and combination therapy of an ACEI and an ARB had 4.80-24.5 times higher odds than all other treatments. Compared with placebo, CCBs and β blockers, ACEI therapy significantly increased the odds of cough (OR 2.90, 95% CI 1.76-4.77; OR 8.21, 95% CI 3.13-21.54 and OR 1.80, 95% CI 1.08-3.00). There were no statistical differences in hypotension among all comparisons except ACEIs versus placebo. CONCLUSIONS: Although ACEIs increased the odds of hyperkalaemia, cough and hypotension, they were still superior to ARBs and other antihypertensive drugs and had the highest benefits for the prevention of kidney events, cardiovascular outcomes, cardiovascular death and all-cause mortality in non-dialysis CKD3-5 patients. In patients with advanced diabetic kidney disease, ACEIs were superior to ARBs in lowering risk of all-cause death but not in kidney events and cardiovascular events.

Abstract. The largest uncertainty in the estimation of climate forcing stems from atmospheric aerosols. In early spring and summer of 2009, two periods of in-situ measurements on aerosol physical and chemical properties were conducted within the HaChi (Haze in China) project at Wuqing, a town between Beijing and Tianjin in the North China Plain (NCP). Aerosol optical properties, including the scattering coefficient (σsp), the hemispheric back scattering coefficient (σbsp), the absorption coefficient (σap), as well as the single scattering albedo (ω), are presented. The diurnal and seasonal variations are analyzed together with meteorology and satellite data. The mean values of σsp, 550 nm of the dry aerosol in spring and summer are 280±253 and 379±251 Mm−1, respectively. The average σap for the two periods is respectively 47±38 and 43±27 Mm−1. The mean values of ω at the wavelength of 637 nm are 0.82±0.05 and 0.86±0.05 for spring and summer, respectively. The relative high levels of σsp and σbsp are representative of the regional aerosol pollution in the NCP. Pronounced diurnal cycle of $σsp, σap and ω are found, mainly influenced by the evolution of boundary layer and the accumulation of local emissions during nighttime. The pollutants transported from the southwest of the NCP are more significant than that from the two megacities, Beijing and Tianjin, in both spring and summer. An optical closure experiment is conducted to better understand the uncertainties of the measurements. Good correlations (R&gt;0.98) are found between the values measured by the nephelometer and the values calculated with a modified Mie model. The Monte Carlo simulation shows an uncertainty of about 30 % for the calculations. Considering all possible uncertainties of measurements, calculated σsp and σbsp agree well with the measured values, indicating a stable performance of instruments and thus reliable aerosol optical data.

Concentrations of organic carbon (OC) and elemental carbon (EC) in atmospheric particles were measured in Tianjin during January, April, July and October in 2008. The 24-h PM2.5 (particles with aerodynamic diameters less than 2.5 micrometer [μm]) and PM10 (particles with aerodynamic diameters less than 10 micrometer [μm]) samples were simultaneously collected every day during sampling periods. These samples were analyzed for OC/EC by thermal/optical reflectance (TOR) following the Interagency Monitoring of Protected Visual Environments (IMPROVE) protocol. The annual average concentration was 109.8 ± 48.5 μg/m3 in PM2.5, and 196.2 ± 86.1 μg/m3 in PM10, respectively. The average ratio of PM2.5/PM10 was 57.9%, indicating the PM2.5 had been one of the main contaminations affecting urban atmospheric environmental quality in Tianjin. The concentrations of OC and EC in PM2.5 and PM10 were all relatively higher in winter and fall and lower in summer and spring. This seasonal variation could be attributed to the cooperative effects of changes in emission rates and seasonal meteorological conditions. The annual average concentration of the estimated secondary organic carbon (SOC) was 14.9 μg/m3 and occupied 61.7% of the total OC in PM2.5, while those in PM10 were 23.4 μg/m3 and 61.2%, respectively, indicating SOC had been an important contributor to organic aerosol in Tianjin. The distribution of eight carbon fractions (OC1, OC2, OC3, OC4, EC1, EC2, EC3 and OP) was also reported and found that the biomass burning, coal–combustion and motor-vehicle exhaust were all contributed to the carbonaceous particles in Tianjin.

Abstract. Measurements of ozone and its precursors conducted within the HaChi (Haze in China) project in summer 2009 were analyzed to characterize volatile organic compounds (VOCs) and their effects on ozone photochemical production at a suburban site in the North China Plain (NCP). Ozone episodes, during which running 8-h average ozone concentrations exceeding 80 ppbv lasted for more than 4 h, occurred on about two thirds of the observational days during the 5-week field campaign. This suggests continuous ozone exposure risks in this region in the summer. Average concentrations of nitrogen oxides (NOx) and VOCs are about 20 ppbv and 650 ppbC, respectively. On average, total VOC reactivity is dominated by anthropogenic VOCs. The contribution of biogenic VOCs to total ozone-forming potential, however, is also considerable in the daytime. Key species associated with ozone photochemical production are 2-butenes (18 %), isoprene (15 %), trimethylbenzenes (11 %), xylenes (8.5 %), 3-methylhexane (6 %), n-hexane (5 %) and toluene (4.5 %). Formation of ozone is found to be NOx-limited as indicated by measured VOCs/NOx ratios and further confirmed by a sensitivity study using a photochemical box model NCAR_MM. The Model simulation suggests that ozone production is also sensitive to changes in VOC reactivity under the NOx-limited regime, although this sensitivity depends strongly on how much NOx is present.

and 493 m, respectively. Our results imply that additional emission reduction measures should be implemented under unfavorable meteorological situations to attain ambient air quality standards in the future.

Abstract Climate change is expected to result in more frequent and intense heat waves (HWs) in South Asia (SA). The simultaneous increases in temperature and population will exacerbate the population exposure to future HWs. Here we estimate the future population exposure to daytime and nighttime HWs in SA using the Coupled Model Intercomparison Project 6 (CMIP6) models under four Shared Socioeconomic Pathways (SSPs) during 2061–2100, relative to 1975–2014. The results show that the projected frequency and spatial extent of the daytime (nighttime) HWs will be higher under scenario SSP5‐8.5, followed by SSP2‐4.5, SSP3‐7.0, and SSP1‐2.6 (SSP5‐8.5, followed by SSP3‐7.0, SSP2‐4.5, and SSP1‐2.6), relative to the historical period. The approach presented here allows decomposing the effects of climate change and future population on the overall exposure. The results reveal that the compounding effects of projected trends in population and HWs will significantly escalate the population exposure to HWs. Under the selected SSPs, the total population exposure to daytime and nighttime HWs ranges from 185 to 492 and 204–555 million people‐event, respectively, with the maximum exposure occurring in the Indo‐Gigantic Plain. The wide range of exposed populations highlights the sensitivity of the overall exposure to our future socioeconomic pathway decisions, emphasizing the importance of curbing anthropogenic greenhouse gas emissions and adopting sustainable urban planning solutions to minimize the potential socioeconomic and health impacts of HWs.

Abstract. Rapid increases in pollutant emissions in conjunction with stagnant meteorological conditions result in haze pollution in China. Recent frequent haze in China has attracted worldwide attention. Here we show a relationship between the haze events and Tibetan Plateau (TP)'s environment and climate changes. Based on observational data taken over recent decades, we identify central-eastern China (CEC) as a climatological large-scale “susceptible region” of frequent haze, which is harbored by the TP with its impact on midlatitude westerly winds. The observational and modeling studies demonstrate that the interannual variations in the thermal forcing of TP are positively correlated with the incidences of wintertime haze over CEC. Further analysis indicates that the climate warming of the TP induced changes in atmospheric circulation, driving frequent haze events in CEC. The frequent haze occurrences in CEC are consistent with decreasing winter monsoon winds, intensifying downward air flows and increasing atmospheric stability in the lower troposphere over the CEC in association with upstream plateau's thermal anomalies. Therefore, variations of haze in China are related to mechanical and thermal forcing by the TP. Our results also suggest that implications of the large TP topography for environment and climate changes should be taken into account for air pollution mitigation policies in China.

A severe dust storm (SDS) event occurred during March-20 to March-22, 2010 in China. A regional dynamical model coupled with a dust model (WRF-Dust) is used for analyzing this SDS event. The distribution of API (air pollution index) values in China and satellite (moderate-resolution imaging spectroradiometer—MODIS) AOD (aerosol optical depth) data are used to trace the dust storm and to compare with the model result. Several model sensitive studies are performed to analyze the roles of physical processes (such as dust source, transport, and deposition) in controlling the SDS event. The result suggests that the Gobi Desert is a major dust source of the SDS event. By contrast, the Taklamakan Desert plays minor roles for affecting the high dust concentrations in eastern/southern China during the SDS event. This study also suggests that a large amount of dust particles was deposited at the surface during the transport pathway between the Gobi Desert and eastern/southern China, and the high surface concentrations of dust particles can be considered as a new dust source region, which produced dust air pollution when surface winds were strong. In this study, we define this process as a propagate dust source (PDS). The calculation shows that the calculated dust concentrations were considerably lower than the measured values in the downwind regions of deserts when the PDS process was not included in the model. By including the PDS process, the calculated dust pollution in eastern and southern China is considerably improved. The further detailed analysis shows that the PDS played important roles in controlling the long-range transport of dust particles during the SDS event. This study suggests that this regional dust model (WRF-Dust) is a useful tool to analyze the important processes of dust storms that are often occurred in China.

Meteorological and aerosol data were measured at the atmospheric boundary layer observation station in Tianjin, China, and were analyzed to study the effects of aerosol mass, composition, and size distributions on visibility and short-wave radiation flux. The results show that fine particles played important roles in controlling visibility in Tianjin. The major contributors to light extinction coefficients included sulfate (28.7%), particulate organic matter (27.6%), elemental carbon (19.2%), and nitrate (6.1%). In addition to the measurement of aerosol composition, the size distribution of aerosol number concentrations were also measured and classified between haze days and non-haze days during spring. The extinction characteristics of ambient aerosol in haze days and non-haze days were calculated using Mie theory model. The average extinction coefficient and scattering coefficient of atmospheric aerosols were 0.253 1/km and 0.213 1/km in non-haze days, while 0.767 1/km and 0.665 1/km in haze days. A radiation transmission model LOWTRAN7 is also applied in this study. The model calculated radiant flux densities in haze days and non-haze days, which showed a fairly agreement with the observation results, showing that the heavy aerosol loadings in Tianjin had significantly impact on atmospheric visibility and radiation fluxes.

Abstract. Heavy particulate pollution events have frequently occurred in the North China Plain over the past decades. Due to high emissions and poor dispersion conditions, issues are becoming increasingly serious during cold seasons. Although early studies have explored some potential reasons for air pollution, there are few works focusing on the effects of intermittent turbulence. This paper draws upon two typical PM2.5 (particulate matter with diameter less than 2.5 mm) pollution cases from the winter of 2016–2017. After several days of gradual accumulation, the concentration of PM2.5 near the surface reached the maximum as a combined result of strong inversion layer, stagnant wind, and high ambient humidity and then sharply decreased to a very low level within a few hours. In order to identify the strength of turbulent intermittency, an effective index, called the intermittency factor (IF), was proposed by this work. The results show that the turbulence is very weak during the cumulative stage due to the suppression by strongly stratified layers, while for the stage of dispersion, the turbulence is highly intermittent and not locally generated. The vertical structure of turbulence and wind profiles confirms the generation and downward transport of intermittent turbulence associated with low-level jets. The intermittent turbulent fluxes contribute positively to the vertical transport of particulate matter and improve the air quality near the surface. This work has demonstrated a possible mechanism of how intermittent turbulence affects the dispersion of particulate matter.

Abstract. In this paper, an automated algorithm is developed, which is used to identify the spectral gap during the heavy haze pollution process, reconstruct acquired data, and obtain pure turbulence data. Comparisons of the reconstructed turbulent flux and eddy covariance (EC) flux show that there are overestimations regarding the exchange between the surface and the atmosphere during heavy haze pollution episodes. After reconstruction via the automated algorithm, pure turbulence data can be obtained. We introduce a definition to characterize the local intermittent strength of turbulence (LIST). The trend in the LIST during pollution episodes shows that when pollution is more intense, the LIST is smaller, and intermittency is stronger; when pollution is weaker, the LIST is larger, and intermittency is weaker. At the same time, the LIST at the city site is greater than at the suburban site, which means that intermittency over the complex city area is weaker than over the flat terrain area. Urbanization seems to reduce intermittency during heavy haze pollution episodes, which means that urbanization reduces the degree of weakening in turbulent exchange during pollution episodes. This result is confirmed by comparing the average diurnal variations in turbulent fluxes at urban and suburban sites during polluted and clean periods. The sensible heat flux, latent heat flux, momentum flux, and turbulent kinetic energy (TKE) in urban and suburban areas are all affected when pollution occurs. Material and energy exchanges between the surface and the atmosphere are inhibited. Moreover, the impact of the pollution process on suburban areas is much greater than on urban areas. The turbulent effects caused by urbanization seem to help reduce the consequences of pollution under the same weather and pollution source condition, because the turbulence intermittency is weaker, and the reduction in turbulence exchange is smaller over the urban underlying surface.

Interactions between the spatiotemporal distribution of pollutants and the structure of the atmospheric boundary layer were studied using data obtained by GPS (Global Positioning System) sounding balloons in an intensive observation period from December 2018 to January 2019 at the Dezhou experimental station in the North China Plain. Under haze weather conditions, negligible variation or a slight increase in temperature, higher relative humidity (RH) and lower wind speed with uncertain wind direction are common characteristics. The concentration distribution of particulate matter ≤2.5 μm (PM2.5) has a close relationship with the inversion layer, which contributes to the accumulation of PM2.5 in the lower atmosphere. The reduction of pollutants suspended in the upper layer during haze periods is closely related to low-level jets and intermittent turbulence. Higher RH values are also favourable for the formation of heavy haze, and the value of PM2.5 increases with an increase in humidity. During hazy days, the heat fluxes and turbulent kinetic energy (TKE) are much smaller than those during clear days. The values of the average maxima of net radiation, sensible heat flux, and latent heat flux are 154, 76, and 15 W/m2, respectively, and the value of TKE is approximately 0.67 m2/s2. The decrease in atmospheric boundary layer height (ABLH) is caused by weaker turbulent transfer during haze episodes. The ABLH is approximately 400 m during the daytime and 240 m at night. The power function relationship is shown by a negative correlation between the ABLH and surface PM2.5 concentration in the convective boundary layer.

Record rainfall and severe flooding struck eastern China in the summer of 2020. The extreme summer rainfall occurred during the COVID-19 pandemic, which started in China in early 2020 and spread rapidly across the globe. By disrupting human activities, substantial reductions in anthropogenic emissions of greenhouse gases and aerosols might have affected regional precipitation in many ways. Here, we investigate such connections and show that the abrupt emissions reductions during the pandemic strengthened the summer atmospheric convection over eastern China, resulting in a positive sea level pressure anomaly over northwestern Pacific Ocean. The latter enhanced moisture convergence to eastern China and further intensified rainfall in that region. Modeling experiments show that the reduction in aerosols had a stronger impact on precipitation than the decrease of greenhouse gases did. We conclude that through abrupt emissions reductions, the COVID-19 pandemic contributed importantly to the 2020 extreme summer rainfall in eastern China.

Abstract Based on the satellite-derived global daily sea surface temperature (SST) data set with high resolution (0.25° by 0.25°), we analyzed changes in annual mean SST and extreme SSTs over the China Seas since 1982. Results show that the annual mean SST in the China Seas has experienced a remarkable declining trend during the global warming hiatus (1998–2013), which was dominated by the striking cooling of SST in boreal winter. Despite annual mean SST experienced warming hiatus after 1998, the regional averaged SST for 1998–2013 was still 0.5 °C above that for 1982–1997. The statistical distributions show that there are not only significant warmer climate shift in annual mean SSTs but also in annual extreme hot SSTs and cold SSTs. These changes can increase the likelihood of extreme oceanic warming events, known as marine heatwaves (MHWs). Further analyses reveal that, from 1982 to present, the MHW frequency increases at a rate of 1.13 events per decade, 2.5 times the global mean rate. For the period 1998–2013, the MHWs in the China Sea has never decreased in both of the frequency and intensity but has already become more frequent, longer duration and more intense than those metrics of MHWs during 1982–1997.

Abstract The field of forecasting oceanic variables has traditionally relied on numerical models, which effectively consider the ocean's dynamic evolution and are of physical importance. However, to make the models more realistic, complicated processes need to be considered, which is difficult because their calculations are complex. In fact, information on the internal dynamic mechanisms and external driving forces of the ocean are already embedded in the time series of observations. Therefore, we can determine the patterns of ocean variations through data mining of these series to achieve forecasting. Furthermore, to predict variations in ocean processes more realistically, interactions between variables and spatial correlations should be effectively considered. Thus, inspired by available remote sensing data and advancements in deep learning technologies, we develop a hybrid model based on a statistical method and a deep learning model to predict multiple sea surface variables. A case study in the South China Sea shows that this model is highly promising for short‐term daily forecasts of the sea surface height anomaly (SSHA) and sea surface temperature (SST). When the forecast time is 10 days, the root mean square errors of this model forecasts for SSHA and SST are approximately 0.0276 m and 0.46°C, respectively, which are much smaller than those of persistence, climatology and linear regression predictions. The anomaly correlation coefficients for SSHA and SST are approximately 0.864 and 0.633, respectively. The model performs satisfactorily under both normal and typhoon weather conditions.