A possible cause of decreasing summer rainfall in northeast Australia

Rainfall over northern Australia (NA) in austral summer is the largest water source of Australia. Previous studies have suggested a strong zonal-dipole trend pattern in austral summer rainfall since 1950, with rainfall increasing in northwest Australia (NWA) but decreasing in northeast Australia (NEA). The dynamics of rainfall increase in NWA was linked to sea surface temperature (SST) in the south Indian Ocean and the rainfall decrease in NEA was associated with SST in the northeast Indian Ocean.This study reports that, in contrast to a zonal-dipole trend pattern, a dominant wetting pattern over NA has recently been observed in the post-1979 satellite era. The recent NA rainfall increase also manifests as the first leading mode of summer rainfall variability over the Australian continent. Further investigation reveals that SST in the tropical western Pacific (TWP) has replaced the SST in the south and northeast Indian Ocean as the controlling factor responsible for the recent NA rainfall increase. Direct thermal forcing by increasing TWP SST gives rise to an anomalous Gill-type cyclone centered around NA, leading to anomalously high rainfall. As such, the increasing SST in the TWP induces over 50% of the observed rainfall wetting trend over NA. The increased rainfall in turn induces land surface cooling in NA. This mechanism can be confirmed with results obtained from sensitivity experiments of a numerical spectral atmospheric general circulation model. Thus, increasing SST in the TWP has contributed much of the recent summer rainfall increase and consequently the surface cooling over NA.

The relationships between the summer (June to September) rainfall variability in South and East Asia and the sea level pressure (SLP) field in the tropics are clarified both by principal component analysis (PCA) and by singular value decomposition analysis (SVDA). First, we applied PCA to summer rainfall for detecting temporal and spatial variations in this area. Then, components of common variations between summer rainfall and the SLP field in the tropics from the Indian Ocean to the Pacific were revealed by SVDA. We found that the first 2 components of summer rainfall variation derived from PCA and SVDA have the same spatial patterns and temporal variations. The first SVD mode (SVD 1) has large signals of rainfall variations in India and north China, and its time coefficients show the relation to the warm event of ENSO. The corresponding spatial pattern of the SLP field indicates variations in the east-west circulation pattern between the areas from the Indian Ocean to the western Pacific and the eastern Pacific in the tropics. Time series of the first principal component (PC I) for summer rainfall and SVD 1 have decadal scale variations with a remarkable change in the latter half of the 1970 s. The second SVD mode (SVD 2) shows a variation in summer rainfall in central China associated with variation in the SLP field and convective activities in the western tropical Pacific. We discuss the relationships between the variation in summer rainfall and the SLP field for the first two SVD modes in terms of sea surface wind anomalies accompanied by variation in the SLP field. The rainfall anomalies over India in SVD I are explained by wind anomalies of meridional components in the southwestern monsoon over the Arabian Sea. These wind anomalies are accompanied by large SLP anomalies over the Arabian Sea near the Eurasian continent. On the other hand, the variation in summer rainfall in north China appears to be closely connected to the formation of a relative pressure anomaly field over the western tropical Pacific in the Northern Hemisphere. Positive (negative) SLP anomalies both in south China and in the western equatorial Pacific develop relative cyclonic (anticyclonic) circulations. This cyclonic (anticyclonic) circulation weakens (strengthens) the southerly wind component in the middle latitudes over East Asia. As a result, the water vapor transport to north China seems to be inhibited (promoted). Concerning SVD 2, SLP variations in the northwestern tropical Pacific are accompanied by the convergence or divergence of surface wind and variation in convective activities in the corresponding region. The variation in summer rainfall in central China is considered to be related to the impact of convective activities in- the northwestern tropical Pacific. Variation in the sea surface temperature (SST) accompanied by these variations in the SLP field were investigated using correlation analysis. The variation in SLP for SVD 1 is correlated significantly with those in the SST in the eastern tropical Pacific and the tropical Indian Ocean. The variation in east-west circulation from the Indian Ocean to the Pacific is considered to be caused by the movement of tropical convective regions with the variation in SST over the eastern tropical Pacific.

Long-term trends and regime shifts in sea surface temperature on the continental shelf of the northeast United States

Differences in coastal and oceanic SST warming rates along the Canary upwelling ecosystem from 1982 to 2010

Several atmospheric variables are directly influenced by oceanic conditions, mainly the sea surface temperature (SST). SST trends and variability over the southwestern Atlantic (SWA) have affected the South American climate, principally the monsoonal period (austral summer). This study analysed the SST trends over the SWA for all seasons. In addition, possible large‐scale triggers of the austral summer's warmest SST over the SWA and the straight impacts of these warmest SSTs on the South American climate were investigated. The results showed a significant positive SST trend of approximately 0.02°C·year−1 over the SWA for all seasons. Since 2000, positive SST anomalies have increased in frequency in all seasons, with the seven warmest summers occurring during the 2010s. The highest SST summers over the SWA have been related to four leading causes: (i) planetary waves triggered by warm anomalies over the subtropical South Pacific; (ii) an omega‐type blocking configuration over the South Atlantic; (iii) a Southern Annular Mode positive phase; and (iv) a strengthening of the Hadley Cell, responding to warm SST over tropical North Atlantic. They all reflected on intensification of the South Atlantic Subtropical High and the western boundary current, heating the SWA. The summer's warmest SST led to positive air temperature anomalies extending in almost all of eastern South America, with significantly highest temperatures over southeastern Brazil, northern Argentina and western Paraguay. Clouds decrease strengthen the incident shortwave in southeastern Brazil, warming the region. Significant reduction of cloudiness and precipitation indicate a low performance of the South Atlantic Convergence Zone. The comparison of the warmest summers in 1980s–1990s in the SWA ratified the role of SST intensification. In conclusion, the positive SST trends over the SWA are related to the summer's warmest SST after 2000s, causing heating and dryness in eastern South America, mainly over southeastern Brazil.

Different proxies for sea surface temperature (SST) often exhibit divergent trends for deglacial warming in tropical regions, hampering our understanding of the phase relationship between tropical SSTs and continental ice volume at glacial terminations. To reconcile divergent SST trends, we report reconstructions of two commonly used paleothermometers (the foraminifera G. ruber Mg/Ca and the alkenone unsaturation index) from a marine sediment core collected in the southwestern tropical Indian Ocean encompassing the last 37,000 years. Our results show that SSTs derived from the alkenone unsaturation index (UK′37) are consistently warmer than those derived from Mg/Ca by ~2–3°C except for the Heinrich Event 1. In addition, the initial timing for the deglacial warming of alkenone SST started at ~15.6 ka, which lags behind that of Mg/Ca temperatures by 2.5 kyr. We argue that the discrepancy between the two SST proxies reflects seasonal differences between summer and winter rather than postdepositional processes or sedimentary biases. The UK′37 SST record clearly mimics the deglacial SST trend recorded in the North Atlantic region for the earlier part of the termination, indicating that the early deglacial warming trend attributed to local summer temperatures was likely mediated by changes in the Atlantic Meridional Overturning Circulation at the onset of the deglaciation. In contrast, the glacial to interglacial SST pattern recorded by G. ruber Mg/Ca probably reflects cold season SSTs. This indicates that the cold season SSTs was likely mediated by climate changes in the southern hemisphere, as it closely tracks the Antarctic timing of deglaciation. Therefore, our study reveals that the tropical southwestern Indian Ocean seasonal SST was closely linked to climate changes occurring in both hemispheres. The austral summer and winter recorded by each proxy is further supported with seasonal SST trends modeled by Atmosphere–ocean General Circulation Models for our core site. Our interpretation that the alkenone and Mg/Ca SSTs are seasonally biased may also explain similar proxy mismatches observed in other tropical regions at the onset of the last termination.

The interannual variability of northern Australian (NA) rainfall is caused by local processes as well as remote teleconnections, many of them being interrelated. Their influence evolves throughout the wet season, from October through April. Using a stepwise linear regression and examining individual months, we identify the key drivers for rainfall variability over northwest and northeast Australia. Our research shows that the El Niño‐Southern Oscillation (ENSO), followed by local sea surface temperatures (SSTs), are the key sources of rainfall variability in October and November. More specifically, the Arafura and Coral Sea SSTs contribute to rainfall variability over northwest Australia, while the Coral Sea SSTs strongly impact on northeast Australian rainfall during these months. The combined ENSO and local SST indices explain up to 50% of variance in observed NA spring monthly mean rainfall. However, the SST influence from both seas breaks down with the onset of the Australian summer monsoon in late December, and by January, SST indices explain zero variance in rainfall. Instead, December to March rainfall variability is associated with a wind‐evaporation feedback, which is particularly strong over northwest Australia. The evaporation index is the only predictor that we investigated that can explain any variance in northwest Australian rainfall in January. While the more purely monsoonal northwest of Australia is dominated by variability internal to the monsoon system, rainfall variability in the northeast retains some influence from remote climate drivers throughout the monsoon season. Further research is needed to clarify the processes and timescale involved in the wind‐evaporation feedback.

It has been reported that the sea surface temperature (SST) trend of the East China Sea during the twentieth century was a couple of times larger than the global mean SST trend. However, the detailed spatial structure of the SST trend in the East China Sea and its mechanism have not been understood. The present study examines the SST trend in the East China Sea from 1901 to 2010 using observational data and a Regional Ocean Modeling System (ROMS) with an eddy-resolving horizontal resolution. A comparison among two observational datasets and the model output reveals that enhanced SST warming occurred along the Kuroshio and along the coast of China over the continental shelf. In both regions, the SST trends were the largest in winter. The heat budget analysis using the model output indicates that the upper-layer temperature rises in both regions were induced by the trend of ocean advection, which was balanced in relation to the increase of surface net heat release. In addition, the rapid SST warming along the Kuroshio was induced by the acceleration of the Kuroshio. Sensitivity experiments revealed that this acceleration was likely caused by the negative wind stress curl anomalies over the North Pacific. In contrast, the enhanced SST warming along the China coast resulted from the ocean circulation change over the continental shelf by local atmospheric forcing.

Meteorological droughts in the Vietnam Mekong delta (VMD) are directly influenced by Sea surface temperature (SST) trends in Pacific Ocean (PO) and Indian Ocean (IO). This paper analyzes the characteristics of meteorological droughts based on the Standardized Precipitation Index (SPI); focus on the correlation between Sea surface temperature anomalies (SSTA) in PO and IO and SPI to analyze the relationship between SST in PO and IO with meteorological droughts trends The results show that: the occurrence of meteorological droughts is rather high, homogenous in regional scale, and mostly occur in rainy season. SST trends in PO and in IO are too factors causing meteorological droughts in VMD. Meteorological droughts in May, June, July and November influenced by SST in PO rather than SST in IO; while, in August, September, October, they are on the contrary. Considering in long term effect, however, the influence of SST in PO on meteorological droughts is larger. The results of the study can be used to build up the regression equation for forecasting meteorological drought in VMD.

Kassem, H.; Amos, C.L., and Thompson, C.E.L., 2023. Sea surface temperature trends in the coastal zone of southern England. Journal of Coastal Research, 39(1), 18–31. Charlotte (North Carolina), ISSN 0749-0208. Sea surface temperature (SST) trends along the south coast of England (northern English Channel) were examined based on data from systematic buoy measurements deployed by the National Network of Regional Coastal Monitoring Programmes of England (NNRCMP) since 2003. These data were supplemented with: (1) long-term, coastal SST measurements by the Centre for Environment, Fisheries and Aquaculture Science (CEFAS); (2) global data sets compiled by the Hadley Centre since 1900, and (3) satellite-derived observations from Moderate Resolution Imaging Spectroradiometer (MODIS) (Aqua) since 2002. These data sets were used to evaluate de-seasoned nearshore trends in SST along the south coast of England and examine links to regional ocean-atmosphere teleconnections. The analyses of long-term, CEFAS data support the proposal that prior to the mid-1980s there were no de-seasoned trends in SST and conditions from year to year were relatively stable. Subsequently, interannual fluctuations appear to have increased, associated with a period of warming between 1985 and 2003 (0.28 °C/decade). Post 2003, interannual fluctuations in SST monitored by the NNRCMP buoys continued, and the warming trend appears to be greater (0.42 °C/decade). This trend in SST is greatest in the nearshore and decreases with distance offshore. The warming in SST also varied greatly from month to month. The greatest warming took place from December to March, whilst the least heating (and sometimes cooling) occurred between September and November. Analysis of Hadley (HadSST1.1) and MODIS data sets substantiated these trends. The greatest warming (post 2003) was found west of Portland Bill (up to 0.76 °C/decade) and decreased towards the Strait of Dover. Despite this west-to-east trend, all 12 NNRCMP stations between Penzance and Folkestone showed remarkably similar results, suggesting regional and global sources of heat rather than local sources. This is corroborated through wavelet coherence analysis linking SST anomalies to regional/global ocean-atmosphere teleconnection indices at seasonal scales.

The sea surface temperature (SST) variations play a veryimportant role in the genesis and maintenance of meteorological and oceanographic processessuch as monsoon depressions and subsequent floods, large-scale sea level fluctuationsand genesis of tropical cyclones. Many low lying coastal regions of South Asia are adjacentto river deltas and have large population. The dense population, poor economy and severalother socio-economic factors make these areas most vulnerable to the impact of climate change. Variability of sea surface temperature (SST) is importantas the duration and intensity of SST provide the basis for studies related to climatic changescenario. In this study an attempt has been made to estimate the recent SST trends in the coastalwaters of some cities, which lie on the Arabian Sea and Bay of Bengal. The annual andinterannual variability has also been studied. The SST variations have then been linkedwith the El Nino and La Nina events. The NOAA-NASA Pathfinder Advanced Very High Resolution Radiometer (AVHRR) SST fields from 1985-1998, created in the Jet Propulsion Laboratory(JPL), USA are used in this study. Here the quality of data is an important factor toobtain reliable estimates of Sea Surface Temperature (SST) trends and other related parameters.However, this is not possible with the conventional type data, due to low quality as wellas sparse data in the region. Though the satellite based SST climatologies have shorterobservation lengths, they can provide reliable estimates of recent SST variability overa large oceanic areas with sparse or no data. Increasing trend of SST is observed throughout all theseasons in the northern Arabian Sea extending from Oman to Karachi and Mumbai and furthersouth to Salalah and Colombo. However, in coastal islands stations further south ofIndia such as at Colombo the increment is not significant. Though the increasing trend in SSTduring winter is not significant, nevertheless it shows the increasing influence of coldspells on this Island. An interesting situation has been observed in the Bay of Bengal. On anaverage, increasing trends in the annual SST were observed in Visakhaputnam. But at thestations located in the northeastern part of Bay of Bengal, namely Hiron Point and Cox'sBazar reverse conditions are observed. In the Southern Bay of Bengal variations in SST isnot significant which reflects in the SST analysis of Chennai and Port Blair stations. Locationof these stations at lower latitudes (near by equator) probably is the reason for this insignificantchange. It has been found that the interannual mode of SST variations dominate the linear SSTtrends which is characterized by the El Nino Southern Oscillations (ENSO) scale cycle.

Maldives, a South Asian small island nation in the northern part of the Indian Ocean is extremely vulnerable to the impacts of Sea Level Rise (SLR) due to its low altitude from the mean sea level. This artricle attempts to estimate the recent rates of SLR in Maldives during different seasons of the year with the help of existing tidal data recorded in the Maldives coast. Corresponding Sea Surface Temperature (SST) trends, utilizing reliable satellite climatology, have also been obtained. The relationships between the SST and mean sea level have been comprehensively investigated. Results show that recent sea level trends in the Maldives coast are very high. At Male, the capital of the Republic of Maldives, the rising rates of Mean Tidal Level (MTL) are: 8.5, 7.6, and 5.8 mm/year during the postmonsoon (October-December), Premonsoon (March-May) and southwest monsoon (June-September) seasons respectively. At Gan, a station very close to the equator, the increasing rate of MTL is maximum during the period from June to September (which is 6.2 mm/year). These rising trends in MTL along the Maldives coast are certainly alarming for this small developing island nation, which is hardly one meter above the mean sea level. Thus there is a need for careful monitoring of future sea level changes in the Maldives coast. The trends presented are based on the available time-series of MTL for the Maldives coast, which are rather short. These trends need not necessarily reflect the long-term scenario. SST in the Maldives coast has also registered significant increasing trend during the period from June to September. There are large seasonal variations in the SST trends at Gan but SST and MTL trends at Male are consistently increasing during all the seasons and the rising rates are very high. The interannual mode of variation is prominent both in SST as well as MTL. Annual profile of MTL along the Maldives coast is bimodal, having two maxima during April and July. The April Mode is by far the dominant one. The SST appears to be the main factor governing the sea level variations along the Maldives coast. The influence of SST and sea level is more near the equatorial region (i.e., at Gan). There is lag of about two months for the maximum influence of SST on the sea level. The correlation coefficient between the smoothed SST and mean tidal level at Gan with lag of two months is as high as ~ +0.8, which is highly significant. The corresponding correlation coefficients at Male with the lags of one and two months are +0.5 and +0.3, respectively. Thus, the important finding of the present work for the Maldives coast is the dominance of SST factor in sea level variation, especially near the region close to the equator.

Models in the North American Multi-Model Ensemble (NMME) predict sea surface temperature (SST) trends in the central and eastern equatorial Pacific Ocean which are more positive than those observed over the period 1982–2020. These trend errors are accompanied by linear trends in the squared error of SST forecasts whose sign is determined by the mean model bias (cold equatorial bias is linked to negative trends in squared error and vice versa). The reason for this behavior is that the overly positive trend reduces the bias of models that are too cold and increases the bias of models that are too warm. The excessive positive SST trends in the models are also linked with overly positive trends in tropical precipitation anomalies. Larger (smaller) SST trend errors are associated with lower (higher) skill in predicting precipitation anomalies over the central Pacific Ocean. Errors in the linear SST trend do not explain a large percentage of variability in precipitation anomaly errors, but do account for large errors in amplitude. The predictions toward a too warm and wet tropical Pacific, especially since 2000, are strongly correlated with an increase in El Niño false alarms. These results may be relevant for interpreting the behavior of uninitialized CMIP5/6 models, which project SST trends that resemble the NMME trend errors.

Understanding the trends and periodicities in geophysical processes is imperative for assessing and forecasting their future change. However, it is possible to mistreat parts of cycles as linear trends with sudden breaks when analysing short-term data. We demonstrate this through the analysis of solar irradiance data as well as Northern Hemisphere (NH) and Southern Hemisphere (SH) sea surface temperature (SST) data sets, with emphasis on the (a) analyses of trends in total solar irradiance (TSI) and (b) association of trends in SST with solar activity during the period from 1900 to 2017. The trends estimated using singular spectrum analysis together with linear regression revealed statistically significant long periodic non-linear trends in both TSI and SST data. Our results suggest that the appraisal of linear trends to identify their breaks/sudden changes is a biased approach when analysing data sets of shorter periods, when the data are governed by long periodic dynamical processes. The non-linear trends identified in SST data may be physically associated with the TSI trend change and anthropogenic CO2. A plausible physical mechanism is also discussed with respect to the influence of solar activity on the trend in atmospheric CO2. Finally, our study concludes that (1) breaks in linear trends are pseudo-attribution of parts of cycles, and (2) the statistically significant trends in NH and SH SST are mainly associated with loadings from trend changes in solar irradiance.

The Adriatic Sea and its coastal region have experienced significant environmental changes in recent decades, aggravated by climate change. The most prominent effects of climate change (namely, an increase in sea surface and air temperature together with changes in the precipitation regime) could have an adverse effect on social and environmental processes. In this study, we analyzed the time series of sea surface temperature and air temperature measured at three meteorological stations in the Croatian part of the Adriatic Sea. To assess the trends and variations in the time series of sea surface and air temperature, different statistical methods were employed, i.e., linear and quadratic regressions, Mann–Kendall test, Rescaled Adjusted Partial Sums method, and autocorrelation. The results evidenced increasing trends in the mean annual sea surface temperature and air temperature; furthermore, sudden variations in values were observed in 1998 and 1992, respectively. Increasing trends in the mean monthly sea surface temperature and air temperature occurred in the warmer parts of the year (from March to August). The results of this study could provide a foundation for stakeholders, decision–makers, and other scientists for developing effective measures to mitigate the negative effects of climate change in the scattered environment of the Adriatic islands and coastal region.