The Forecast Skills and Predictability Sources of Marine Heatwaves in the NUIST-CFS1.0 Hindcasts

Using monthly observations and ensemble hindcasts of the Nanjing University of Information Science and Technology Climate Forecast System(NUIST-CFS1.0) for the period 1983–2020, this study investigates the forecast skill of marine heatwaves(MHWs) over the globe and the predictability sources of the MHWs over the tropical oceans. The MHW forecasts are demonstrated to be skillful on seasonal-annual time scales, particularly in tropical oceans. The forecast skill of the MHWs over the tropical Pacific Ocean(TPO) remains high at lead times of 1–24 months, indicating a forecast better than random chance for up to two years. The forecast skill is subject to the spring predictability barrier of El Nino-Southern Oscillation(ENSO). The forecast skills for the MHWs over the tropical Indian Ocean(TIO), tropical Atlantic Ocean(TAO), and tropical Northwest Pacific(NWP) are lower than that in the TPO. A reliable forecast at lead times of up to two years is shown over the TIO, while a shorter reliable forecast window(less than 17 months) occurs for the TAO and NWP.Additionally, the forecast skills for the TIO, TAO, and NWP are seasonally dependent. Higher skills for the TIO and TAO appear in boreal spring, while a greater skill for the NWP emerges in late summer-early autumn. Further analyses suggest that ENSO serves as a critical source of predictability for MHWs over the TIO and TAO in spring and MHWs over the NWP in summer.

Evaluation and projection of marine heatwaves in the South China Sea: insights from CMIP6 multi-model ensemble

This study evaluates the performance of 16 models sourced from the coupled model intercomparison project phase 6(CMIP6)in simulating marine heatwaves(MHWs)in the South China Sea(SCS)during the historical period(1982−2014),and also investigates future changes in SCS MHWs based on simulations from three shared socioeconomic pathway(SSP)scenarios(SSP126,SSP245,and SSP585)using CMIP6 models.Results demonstrate that the CMIP6 models perform well in simulating the spatial-temporal distribution and intensity of SCS MHWs,with their multi-model ensemble(MME)results showing the best performance.The reasonable agreement between the observations and CMIP6 MME reveals that the increasing trends of SCS MHWs are attributed to the warming sea surface temperature trend.Under various SSP scenarios,the year 2040 emerges as pivotal juncture for future shifts in SCS MHWs,marked by distinct variations in changing rate and amplitudes.This is characterized by an accelerated decrease in MHWs frequency and a notably heightened increase in mean intensity,duration,and total days after 2040.Furthermore,the projection results for SCS MHWs suggest that the spatial pattern of MHWs remains consistent across future periods.However,the intensity shows higher consistency only during the near-term period(2021−2050),while notable inconsistencies are observed during the medium-term(2041−2070)and long-term(2071−2100)periods under the three SSP scenarios.During the nearterm period,the SCS MHWs are characterized by moderate and strong events with high frequencies and relatively shorter durations.In contrast,during the medium-term period,MHWs are also characterized by moderate and strong events,but with longer-lasting and more intense events under the SSP245 and SSP585 scenarios.However,in the long-term period,extreme MHWs become the dominant feature under the SSP585 scenario,indicating a substantial intensification of SCS MHWs,effectively establishing a near-permanent state.

Long-term ocean temperature trend and marine heatwaves

Marine heatwaves(MHWs)can cause irreversible damage to marine ecosystems and livelihoods.Appropriate MHW characterization remains difficult,because the choice of a sea surface temperature(SST)temporal baseline strongly influences MHW identification.Following a recent work suggesting that there should be a communicating baseline for long-term ocean temperature trends(LTT)and MHWs,we provided an effective and quantitative solution to calculate LTT and MHWs simultaneously by using the ensemble empirical mode decomposition(EEMD)method.The long-term nonlinear trend of SST obtained by EEMD shows superiority over the traditional linear trend in that the data extension does not alter prior results.The MHWs identified from the detrended SST data exhibited low sensitivity to the baseline choice,demonstrating the robustness of our method.We also derived the total heat exposure(THE)by combining LTT and MHWs.The THE was sensitive to the fixed-period baseline choice,with a response to increasing SST that depended on the onset time of a perpetual MHW state(identified MHW days equal to the year length).Subtropical areas,the Indian Ocean,and part of the Southern Ocean were most sensitive to the long-term global warming trend.

Observed Frequent Occurrences of Marine Heatwaves in Most Ocean Regions during the Last Two Decades

Marine heatwaves(MHWs)are prolonged high-temperature extreme events in the ocean that can be devastating to marine life and seriously impact climate systems and economies.This paper describes the accessibility,content,characteristics,and potential applications of an MHW dataset to facilitate its use in scientific research.Daily intensities of global MHWs from 1982 to 2020 were analyzed using gridded SST data sourced from the National Oceanic and Atmospheric Administration(NOAA)Optimum Interpolation(OI)SST V2 high-resolution(0.25°)dataset.The analysis shows a linear increase in the frequency of MHWs in most ocean regions of the world as well as significant interdecadal changes.This data product can be used as a basic dataset to study the seasonal to decadal changes in extreme ocean events and explore the effects of global warming on the surface layers of oceans during the last 40 years.

Summer marine heatwaves in the South China Sea:Trend,variability and possible causes

Marine heatwaves(MHWs)have been frequently observed worldwide,causing devastating impacts on marine organisms and ecosystems,but the trend of MHWs is still unclear in the South China Sea(SCS).Here,the long-term trend and inter-annual variability of the summer SCS MHW events are investigated based on the high-resolution daily satellite data.The results revealed remarkable increases in the duration,intensity,coverage,and severity during 1982-2019,indicating that the SCS MHW events have become more frequent,intense,extensive,and serious.The probability ratio of SCS MHW events is four times during the 2010s of that during the 1980s.The increasing trend can be largely attributed to the long-term increase in the mean SCS temperature.The inter-annual variability of the SCS MHWs is linked closely to the El Niño and Southern Oscillation,with more/less MHW events occurring during the following summer after the El Niño/La Niña events.A diagnosis of synoptic-scale heat budget suggests that the extreme SCS warming can be explained by the combined effects of positive surface heat flux largely due to the enhanced shortwave radiation and convergence of oceanic advection in association with an anomalous upper-ocean anticyclone.The effect of surface heat flux seems to be predominant over the large spatial coverage,whereas oceanic heat transport is also important in some specific regions.The large-scale anticyclonic circulation anomalies over the northwestern Pacific accompanying the westward-extending western Pacific subtropical high during the El Niño decay summers play an essential role in the building-up and persistence of the extreme warming,which has important implications for the prediction of the SCS MHWs.

Causes of 2022 summer marine heatwave in the East China Seas

Recent occurrences of marine heatwaves(MHWs)in coastal China seas have caused serious impacts on marine ecosystem services and socio-economics.Nevertheless,the underlying physical process,including local drivers and remote associations,remains poorly understood,thereby hindering accurate predictability.In this study,we reported an extreme MHW event in the East China Seas(ECSs,including the Bohai,Yellow,and East China Sea),lasting for 75 d with a maximum intensity of 1.96℃relative to 1982-2011 during the summer 2022.This ECSs MHW event was triggered by a combination of anomalous atmospheric and oceanic conditions,including enhanced insolation,weakened surface wind speed,suppressed latent heat loss from ocean,a shallower mixed layer,and upper ocean current anomaly.Mixed-layer temperature budget diagnosis suggested that changes in the ECSs temperature were dominated by the surface net heat flux,largely due to strong shortwave radiation flux,during the development and decay of the MHW event.Oceanic advection also created favorable conditions for the maintenance of the MHW.These physical drivers were further regulated by the westward expanded and intensified western Pacific subtropical high(WPSH),potentially linked to the negative phase of Indian Ocean Dipole(IOD).Despite the three years(2020-2022)consecutive La Niña events,the ECSs summer MHWs appeared to be more closely linked to negative IOD events,with a lagging period of 1-3 mon.The seasonal precursor signals of the negative IOD have the potential to affect local physical drivers of ECSs MHWs through regulating the strength and position of WPSH,thus serving as a promising predictor for the ECSs MHWs.The future likelihood and intensity of the ECSs MHWs are projected to increase substantially in the coming decades,largely due to broad-scale warming attributed to anthropogenic climate change.Consequently,there is an urgent need to develop MHW forecasting and early warning systems,and robust approaches to address climate change.

Marine heatwaves in the Gulf of Mexico 1983‒2021: Statistics, recent intensifications, and threats on coral reefs

There is the current lack of comprehensive understanding of the hotspots,frequency,duration,spatiotemporal trends,and physical drivers of marine heatwaves(MHWs)within the Gulf of Mexico(GoM).Here,a series of high-resolution satellite and reanalysis products are used to examine their spatiotemporal characteristics,trends,and possible geophysical triggers of MHWs.Possible impacts of the MHW on coral reefs are also discussed.Results reveal an increasing trend in their frequency,duration,and intensities from 1983–2021,particularly after 2016.It identifies MHWs hotspots within the GoM,notably the northern and western shelves and the Loop Current.The study further documents an intense MHW event from late 2020 to early 2021 near the Yucatan Channel,south of 24°N,attributing its development to oceanic processes such as wind anomalies,anticyclonic eddies,and current-driven heat transport anomalies.The occurrence of this MHW event potentially increased thermal stress on the Campeche and Tuxtlas Reef Systems.This research illuminates the increasing trends and impacts of MHWs in the GoM,providing valuable insights for understanding and predicting the effects of climate change on marine ecosystems.

Correcting Climate Model Sea Surface Temperature Simulations with Generative Adversarial Networks:Climatology,Interannual Variability,and Extremes

Climate models are vital for understanding and projecting global climate change and its associated impacts.However,these models suffer from biases that limit their accuracy in historical simulations and the trustworthiness of future projections.Addressing these challenges requires addressing internal variability,hindering the direct alignment between model simulations and observations,and thwarting conventional supervised learning methods.Here,we employ an unsupervised Cycle-consistent Generative Adversarial Network(CycleGAN),to correct daily Sea Surface Temperature(SST)simulations from the Community Earth System Model 2(CESM2).Our results reveal that the CycleGAN not only corrects climatological biases but also improves the simulation of major dynamic modes including the El Niño-Southern Oscillation(ENSO)and the Indian Ocean Dipole mode,as well as SST extremes.Notably,it substantially corrects climatological SST biases,decreasing the globally averaged Root-Mean-Square Error(RMSE)by 58%.Intriguingly,the CycleGAN effectively addresses the well-known excessive westward bias in ENSO SST anomalies,a common issue in climate models that traditional methods,like quantile mapping,struggle to rectify.Additionally,it substantially improves the simulation of SST extremes,raising the pattern correlation coefficient(PCC)from 0.56 to 0.88 and lowering the RMSE from 0.5 to 0.32.This enhancement is attributed to better representations of interannual,intraseasonal,and synoptic scales variabilities.Our study offers a novel approach to correct global SST simulations and underscores its effectiveness across different time scales and primary dynamical modes.

Mechanisms for Marine–Terrestrial Compound Heatwaves in Southern China and Adjacent Oceans

Extreme heat events over both lands and oceans have increased in frequency and intensity,and exerted profound impacts on human and natural systems.More impactful is their concurrence,leading to larger losses in health,food,economy,and ecosystem,but receiving far less attention.Understanding the mechanism for such marine–terrestrial compound heatwaves is a prerequisite to prediction and disaster prevention.Based on air particle trajectory analysis,we identified 87 compound heatwaves in China and adjacent oceans in summers of 1982–2021,with the connection between marine and terrestrial heatwaves particularly prominent between the oceans to Northeast Philippines and the lands in South/Southeast China.Through composite and case analysis,it is found that the connection is established by simultaneous governance of(i)the western Pacific subtropical high(WPSH),(ii)a dipole circulation pattern constituted by the WPSH and weak tropical cyclones(TCs),or(iii)strong and closer-to-coast TCs,each of which causes anomalously strong descending motion,increased incoming solar radiation,and strengthened adiabatic heating on lands.The marine heatwaves act to supply more moisture through enhanced evaporation,and/or intensify TCs that pass the region.The air particle tracking shows that these moister air masses are then advected by the WPSH and/or TCs to South/Southeast China,converting the adiabatic heating-caused dry heatwaves there into humid ones and thus adding to the heat stress.These diagnoses provide new insight into the mechanistic understanding and forecast precursors for terrestrial heatwaves,through the lens of compound events.