This book covers topics ranging from a detailed error analysis of SSTs to new applications employed, for example, in the study of the El Niño–La Niña Southern Oscillation, lake temperatures, and ...coral bleaching. New techniques for interpolation and algorithm development are presented, including improvements for cloud detection. Analysis of the pixel-to-pixel uncertainties provides insight to applications for high spatial resolutions. New approaches for the estimation and evaluation of SSTs are presented. In addition, an overview of the Climate Change Initiative, with specific applications to SST, is presented. The book provides an excellent overview of the current technology, while also highlighting new technologies and their applications to new missions.
Sea surface temperature (SST) is one of the most important parameters in the global ocean-atmospheric system, changes of which can have profound effects on the global climate and may lead to extreme ...weather events such as droughts and floods. Therefore, predicting the dynamics of future SSTs is of vital importance which can help identify these extreme events and alleviate the losses they cause. In this paper, a machine learning method combining the long short-term memory (LSTM) deep recurrent neural network model and the AdaBoost ensemble learning model (LSTM-AdaBoost) is proposed to predict the short and mid-term daily SST considering that LSTM is good at modelling long-term dependencies but suffers from overfitting, while AdaBoost has strong prediction capability and is not easily overfitted. By combining these two strong and heterogeneous models, the prediction errors related to variance may cancel out each other and the final results can be improved. In this method, the historical time-series satellite data of SST anomaly (SSTA) is used instead of SST itself considering that the fluctuations of SSTs are very small compared to their absolute magnitudes. The seasonality of the SSTA time series is first modelled using polynomial regression and then removed. Then, the deseasonalized time series are used to train the developed LSTM model and AdaBoost model independently. Daily SSTA predictions are made using these two models, and eventually, their predictions are combined as final predictions using the averaging strategy. A case study in the East China Sea that predicts the daily SSTA 10 days ahead shows that the proposed LSTM-AdaBoost combination model outperforms the LSTM and AdaBoost separately, as well as the optimized support vector regression (SVR) model, the optimized feedforward backpropagation neural network model (BPNN), and the stacking LSTM-AdaBoost model (S_LSTM-AdaBoost), when judged using multiple error statistics and from different perspectives. The results suggest that the LSTM-AdaBoost combination model using the averaging strategy is highly promising for short and mid-term daily SST predictions.
•A LSTM-AdaBoost combination method is proposed to predict short and mid-term SST.•36-year satellite-derived time series daily SST data are used.•A case study has been demonstrated in the East China Sea.•The proposed method outperforms LSTM, AdaBoost, SVR, BPNN and S_LSTM-AdaBoost.
Tropical reef systems are transitioning to a new era in which the interval between recurrent bouts of coral bleaching is too short for a full recovery of mature assemblages. We analyzed bleaching ...records at 100 globally distributed reef locations from 1980 to 2016. The median return time between pairs of severe bleaching events has diminished steadily since 1980 and is now only 6 years. As global warming has progressed, tropical sea surface temperatures are warmer now during current La Niña conditions than they were during El Niño events three decades ago. Consequently, as we transition to the Anthropocene, coral bleaching is occurring more frequently in all El Niño-Southern Oscillation phases, increasing the likelihood of annual bleaching in the coming decades.
Marine heatwaves under global warming Frölicher, Thomas L; Fischer, Erich M; Gruber, Nicolas
Nature (London),
08/2018, Volume:
560, Issue:
7718
Journal Article
Peer reviewed
Marine heatwaves (MHWs) are periods of extreme warm sea surface temperature that persist for days to months
and can extend up to thousands of kilometres
. Some of the recently observed marine ...heatwaves revealed the high vulnerability of marine ecosystems
and fisheries
to such extreme climate events. Yet our knowledge about past occurrences
and the future progression of MHWs is very limited. Here we use satellite observations and a suite of Earth system model simulations to show that MHWs have already become longer-lasting and more frequent, extensive and intense in the past few decades, and that this trend will accelerate under further global warming. Between 1982 and 2016, we detect a doubling in the number of MHW days, and this number is projected to further increase on average by a factor of 16 for global warming of 1.5 degrees Celsius relative to preindustrial levels and by a factor of 23 for global warming of 2.0 degrees Celsius. However, current national policies for the reduction of global carbon emissions are predicted to result in global warming of about 3.5 degrees Celsius by the end of the twenty-first century
, for which models project an average increase in the probability of MHWs by a factor of 41. At this level of warming, MHWs have an average spatial extent that is 21 times bigger than in preindustrial times, last on average 112 days and reach maximum sea surface temperature anomaly intensities of 2.5 degrees Celsius. The largest changes are projected to occur in the western tropical Pacific and Arctic oceans. Today, 87 per cent of MHWs are attributable to human-induced warming, with this ratio increasing to nearly 100 per cent under any global warming scenario exceeding 2 degrees Celsius. Our results suggest that MHWs will become very frequent and extreme under global warming, probably pushing marine organisms and ecosystems to the limits of their resilience and even beyond, which could cause irreversible changes.
ABSTRACT
We highlight improvements to the International Comprehensive Ocean‐Atmosphere Data Set (ICOADS) in the latest Release 3.0 (R3.0; covering 1662–2014). ICOADS is the most widely used freely ...available collection of surface marine observations, providing data for the construction of gridded analyses of sea surface temperature, estimates of air–sea interaction and other meteorological variables. ICOADS observations are assimilated into all major atmospheric, oceanic and coupled reanalyses, further widening its impact. R3.0 therefore includes changes designed to enable effective exchange of information describing data quality between ICOADS, reanalysis centres, data set developers, scientists and the public. These user‐driven innovations include the assignment of a unique identifier (UID) to each marine report – to enable tracing of observations, linking with reports and improved data sharing. Other revisions and extensions of the ICOADS' International Maritime Meteorological Archive common data format incorporate new near‐surface oceanographic data elements and cloud parameters. Many new input data sources have been assembled, and updates and improvements to existing data sources, or removal of erroneous data, made. Coupled with enhanced ‘preliminary’ monthly data and product extensions past 2014, R3.0 provides improved support of climate assessment and monitoring, reanalyses and near‐real‐time applications.
With CO2 concentrations similar to today (410 ppm), the Pliocene Epoch offers insights into climate changes under a moderately warmer world. Previous work suggested a low zonal sea surface ...temperature (SST) gradient in the tropical Pacific during the Pliocene, the so‐called “permanent El Niño.” Here, we recalculate SSTs using the alkenone proxy and find moderate reductions in both the zonal and meridional SST gradients during the mid‐Piacenzian warm period. These reductions are captured by coupled climate model simulations of the Pliocene, especially those that simulate weaker Walker circulation. We also produce a spatial reconstruction of mid‐Piacenzian warm period Pacific SSTs that closely resembles both Pliocene and future, low‐emissions simulations, a pattern that is, to a first order, diagnostic of weaker Walker circulation. Therefore, Pliocene warmth does not require drastic changes in the climate system—rather, it supports the expectation that the Walker circulation will weaken in the future under higher CO2.
Plain Language Summary
The Pliocene Epoch is the most recent time in Earth history when CO2 levels exceeded 400 ppm. The climate was warmer than preindustrial times, with smaller ice sheets. Previous studies suggested that the Pacific ocean was stuck in a “permanent El Niño” during the Pliocene. However, climate model simulations do not predict that this would happen at CO2 levels near 400 ppm—unusual changes in climate, such as large changes in cloud cover or hurricane frequency, would be needed to explain it. In this work we reanalyze Pliocene sea surface temperature data and do not find evidence of a permanent El Niño. Our results suggest that difference in temperatures across the tropical Pacific was smaller than it is today, but only by about 1 °C. Climate model simulations agree with our new analysis, suggesting that higher CO2, along with small changes in ice, vegetation, and mountains, is enough to explain Pliocene climate. We also show that the sea surface temperature patterns in the Pliocene Pacific Ocean look similar to those that climate models predict under a low‐emissions climate change scenario. The similarity suggests that the Pliocene can help us understand how the tropics respond to an ongoing increase in CO2.
Key Points
Pliocene SSTs calculated from the alkenone proxy do not support a “permanent El Niño”
Pliocene model simulations can reproduce proxy‐inferred SST patterns and gradients
The pattern of Pliocene warmth supports a weakening of Walker circulation under higher CO2
The monthly Extended Reconstructed Sea Surface Temperature (ERSST) dataset, available on global 2° × 2° grids, has been revised herein to version 4 (v4) from v3b. Major revisions include updated and ...substantially more complete input data from the International Comprehensive Ocean–Atmosphere Data Set (ICOADS) release 2.5; revised empirical orthogonal teleconnections (EOTs) and EOT acceptance criterion; updated sea surface temperature (SST) quality control procedures; revised SST anomaly (SSTA) evaluation methods; updated bias adjustments of ship SSTs using the Hadley Centre Nighttime Marine Air Temperature dataset version 2 (HadNMAT2); and buoy SST bias adjustment not previously made in v3b.
Tests show that the impacts of the revisions to ship SST bias adjustment in ERSST.v4 are dominant among all revisions and updates. The effect is to make SST 0.1°–0.2°C cooler north of 30°S but 0.1°–0.2°C warmer south of 30°S in ERSST.v4 than in ERSST.v3b before 1940. In comparison with the Met Office SST product the Hadley Centre Sea Surface Temperature dataset, version 3 (HadSST3), the ship SST bias adjustment in ERSST.v4 is 0.1°–0.2°C cooler in the tropics but 0.1°–0.2°C warmer in the midlatitude oceans both before 1940 and from 1945 to 1970. Comparisons highlight differences in long-term SST trends and SSTA variations at decadal time scales among ERSST.v4, ERSST.v3b, HadSST3, and Centennial Observation-Based Estimates of SST version 2 (COBE-SST2), which is largely associated with the difference of bias adjustments in these SST products. The tests also show that, when compared with v3b, SSTAs in ERSST.v4 can substantially better represent the El Niño/La Niña behavior when observations are sparse before 1940. Comparisons indicate that SSTs in ERSST.v4 are as close to satellite-based observations as other similar SST analyses.
Over the past decades, Beijing, the capital city of China, has encountered
increasingly frequent persistent haze events (PHE). While the increased
pollutant emissions are considered as the most ...important reason, changes in
regional atmospheric circulations associated with large-scale climate warming
also play a role. In this study, we find a significant positive trend of PHE
in Beijing for the winters from 1980 to 2016 based on updated daily
observations. This trend is closely related to an increasing frequency of
extreme anomalous southerly episodes in North China, a weakened East Asian
trough in the mid-troposphere and a northward shift of the East Asian jet
stream in the upper troposphere. These conditions together depict a weakened
East Asian winter monsoon (EAWM) system, which is then found to be associated with an anomalous
warm, high-pressure system in the middle–lower troposphere over the northwestern
Pacific. A practical EAWM index is defined as the seasonal meridional wind
anomaly at 850 hPa in winter over North China. Over the period 1900–2016,
this EAWM index is positively correlated with the sea surface temperature
anomalies over the northwestern Pacific, which indicates a wavy positive
trend, with an enhanced positive phase since the mid-1980s. Our results
suggest an observation-based mechanism linking the increase in PHE in Beijing
with large-scale climatic warming through changes in the typical regional
atmospheric circulation.
The Pacific decadal oscillation (PDO), the dominant year-round pattern of monthly North Pacific sea surface temperature (SST) variability, is an important target of ongoing research within ...themeteorological and climate dynamics communities and is central to the work of many geologists, ecologists, natural resource managers, and social scientists. Research over the last 15 years has led to an emerging consensus: the PDO is not a single phenomenon, but is instead the result of a combination of different physical processes, including both remote tropical forcing and local North Pacific atmosphere–ocean interactions, which operate on different time scales to drive similar PDO-like SST anomaly patterns. How these processes combine to generate the observed PDO evolution, including apparent regime shifts, is shown using simple autoregressive models of increasing spatial complexity. Simulations of recent climate in coupled GCMs are able to capture many aspects of the PDO, but do so based on a balance of processes often more independent of the tropics than is observed. Finally, it is suggested that the assessment of PDO-related regional climate impacts, reconstruction of PDO-related variability into the past with proxy records, and diagnosis of Pacific variability within coupled GCMs should all account for the effects of these different processes, which only partly represent the direct forcing of the atmosphere by North Pacific Ocean SSTs.
In early summer 2020, the Meiyu‐Baiu rainfall was markedly enhanced, triggering devastating floods in Japan and central China. We examined the underlying processes using a climate model and analysis. ...The enhanced Meiyu‐Baiu rainfall was reasonably predicted by the climate model initialized at the end of April. The sensitivity experiment indicated that Indian Ocean (IO) warming enhanced the Meiyu‐Baiu rainfall. Moreover, we found that the warm IO condition can be traced back to the super Indian Ocean Dipole (IOD) in 2019. The IO warmth was influenced by successive processes: record strong downwelling Rossby waves excited by the IOD and tripole sea surface temperature anomalies in the tropical IO‐western Pacific, their arrival to the southwestern IO in spring, and associated modulation of monsoon flow. The results suggest that the seasonal predictability of the Meiyu‐Baiu rainfall in 2020 originated from the super IOD.
Plain Language Summary
In early summer 2020, Japan and central China suffered from serious floods due to torrential rainfall associated with the intensified Meiyu‐Baiu front, which extends from central China to southern Japan. The results of climate model simulations indicated that a warm condition of the Indian Ocean (IO) was an underlying condition for the enhanced rainfall. We found that the warm IO condition can be traced back to the strong Indian Ocean Dipole (IOD) episode in 2019, which featured a pair of colder‐than‐normal and warmer‐than‐normal ocean temperatures west of the Sumatra coast and in the western IO, respectively. This IOD contributed to the IO warming in the following seasons through oceanic dynamics and monsoon modulation.
Key Points
The markedly enhanced rainfall in the Meiyu‐Baiu frontal zone in early summer 2020 was associated with the warm IO condition
The warm IO condition can be traced back to the super IOD event in 2019
Ocean dynamics and associated modulation of monsoon flow in the IO sector facilitated IO warming
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