scholarly journals The emergence of heat and humidity too severe for human tolerance

2020 ◽  
Vol 6 (19) ◽  
pp. eaaw1838 ◽  
Author(s):  
Colin Raymond ◽  
Tom Matthews ◽  
Radley M. Horton

Humans’ ability to efficiently shed heat has enabled us to range over every continent, but a wet-bulb temperature (TW) of 35°C marks our upper physiological limit, and much lower values have serious health and productivity impacts. Climate models project the first 35°C TW occurrences by the mid-21st century. However, a comprehensive evaluation of weather station data shows that some coastal subtropical locations have already reported a TW of 35°C and that extreme humid heat overall has more than doubled in frequency since 1979. Recent exceedances of 35°C in global maximum sea surface temperature provide further support for the validity of these dangerously high TW values. We find the most extreme humid heat is highly localized in both space and time and is correspondingly substantially underestimated in reanalysis products. Our findings thus underscore the serious challenge posed by humid heat that is more intense than previously reported and increasingly severe.

2021 ◽  
Vol 8 (1) ◽  
Author(s):  
Weiying Peng ◽  
Quanliang Chen ◽  
Shijie Zhou ◽  
Ping Huang

AbstractSeasonal forecasts at lead times of 1–12 months for sea surface temperature (SST) anomalies (SSTAs) in the offshore area of China are a considerable challenge for climate prediction in China. Previous research suggests that a model-based analog forecasting (MAF) method based on the simulations of coupled global climate models provide skillful climate forecasts of tropical Indo-Pacific SSTAs. This MAF method selects the model-simulated cases close to the observed initial state as a model-analog ensemble, and then uses the subsequent evolution of the SSTA to generate the forecasts. In this study, the MAF method is applied to the offshore area of China (0°–45°N, 105°–135°E) based on the simulations of 23 models from phase 6 of the Coupled Model Intercomparison Project (CMIP6) for the period 1981–2010. By optimizing the key factors in the MAF method, we suggest that the optimal initial field for the analog criteria should be concentrated in the western North Pacific. The multi-model ensemble of the optimized MAF prediction using these 23 CMIP6 models shows anomaly correlation coefficients exceeding 0.6 at the 3-month lead time, which is much improved relative to previous SST-initialized hindcasts and appears practical for operational forecasting.


2020 ◽  
Vol 33 (14) ◽  
pp. 6025-6045
Author(s):  
Jing Sun ◽  
Mojib Latif ◽  
Wonsun Park ◽  
Taewook Park

AbstractThe North Atlantic (NA) basin-averaged sea surface temperature (NASST) is often used as an index to study climate variability in the NA sector. However, there is still some debate on what drives it. Based on observations and climate models, an analysis of the different influences on the NASST index and its low-pass filtered version, the Atlantic multidecadal oscillation (AMO) index, is provided. In particular, the relationships of the two indices with some of its mechanistic drivers including the Atlantic meridional overturning circulation (AMOC) are investigated. In observations, the NASST index accounts for significant SST variability over the tropical and subpolar NA. The NASST index is shown to lump together SST variability originating from different mechanisms operating on different time scales. The AMO index emphasizes the subpolar SST variability. In the climate models, the SST-anomaly pattern associated with the NASST index is similar. The AMO index, however, only represents pronounced SST variability over the extratropical NA, and this variability is significantly linked to the AMOC. There is a sensitivity of this linkage to the cold NA SST bias observed in many climate models. Models suffering from a large cold bias exhibit a relatively weak linkage between the AMOC and AMO and vice versa. Finally, the basin-averaged SST in its unfiltered form, which has been used to question a strong influence of ocean dynamics on NA SST variability, mixes together multiple types of variability occurring on different time scales and therefore underemphasizes the role of ocean dynamics in the multidecadal variability of NA SSTs.


2011 ◽  
Vol 24 (23) ◽  
pp. 6203-6209 ◽  
Author(s):  
Fabian Lienert ◽  
John C. Fyfe ◽  
William J. Merryfield

Abstract This study evaluates the ability of global climate models to reproduce observed tropical influences on North Pacific Ocean sea surface temperature variability. In an ensemble of climate models, the study finds that the simulated North Pacific response to El Niño–Southern Oscillation (ENSO) forcing is systematically delayed relative to the observed response because of winter and spring mixed layers in the North Pacific that are too deep and air–sea feedbacks that are too weak. Model biases in mixed layer depth and air–sea feedbacks are also associated with a model mean ENSO-related signal in the North Pacific whose amplitude is overestimated by about 30%. The study also shows that simulated North Pacific variability has more power at lower frequencies than is observed because of model errors originating in the tropics and extratropics. Implications of these results for predictions on seasonal, decadal, and longer time scales are discussed.


1994 ◽  
Vol 12 (9) ◽  
pp. 903-909
Author(s):  
S. G. Dobrovolski

Abstract. Data on the South Atlantic monthly sea surface temperature anomalies (SSTA) are analysed using the maximum-entropy method. It is shown that the Markov first-order process can describe, to a first approximation, SSTA series. The region of maximum SSTA values coincides with the zone of maximum residual white noise values (sub-Antarctic hydrological front). The theory of dynamic-stochastic climate models is applied to estimate the variability of South Atlantic SSTA and air-sea interactions. The Adem model is used as a deterministic block of the dynamic-stochastic model. Experiments show satisfactorily the SSTA intensification in the sub-Antarctic front zone, with appropriate standard deviations, and demonstrate the leading role of the abnormal drift currents in these processes.


2011 ◽  
Vol 24 (7) ◽  
pp. 1869-1877 ◽  
Author(s):  
Shahadat Chowdhury ◽  
Ashish Sharma

Abstract This paper dynamically combined three multivariate forecasts where spatially and temporally variant combination weights are estimated using a nearest-neighbor approach. The case study presented combines forecasts from three climate models for the period 1958–2001. The variables of interest here are the monthly global sea surface temperature anomalies (SSTA) at a 5° × 5° latitude–longitude grid, predicted 3 months in advance. The forecast from the static weight combination is used as the base case for comparison. The forecasted sea surface temperature using the dynamic combination algorithm offers consistent improvements over the static combination approach for all seasons. This improved skill is achieved over at least 93% of the global grid cells, in four 10-yr independent validation segments. Dynamically combined forecasts reduce the mean-square error of the SSTA by at least 25% for 72% of the global grid cells when compared against the best-performing single forecast among the three climate models considered.


2014 ◽  
Vol 27 (22) ◽  
pp. 8510-8526 ◽  
Author(s):  
Baoqiang Xiang ◽  
Bin Wang ◽  
Juan Li ◽  
Ming Zhao ◽  
June-Yi Lee

Abstract Understanding the change of equatorial Pacific trade winds is pivotal for understanding the global mean temperature change and the El Niño–Southern Oscillation (ENSO) property change. The weakening of the Walker circulation due to anthropogenic greenhouse gas (GHG) forcing was suggested as one of the most robust phenomena in current climate models by examining zonal sea level pressure gradient over the tropical Pacific. This study explores another component of the Walker circulation change focusing on equatorial Pacific trade wind change. Model sensitivity experiments demonstrate that the direct/fast response due to GHG forcing is to increase the trade winds, especially over the equatorial central-western Pacific (ECWP) (5°S–5°N, 140°E–150°W), while the indirect/slow response associated with sea surface temperature (SST) warming weakens the trade winds. Further, analysis of the results from 19 models in phase 5 of the Coupled Model Intercomparison Project (CMIP5) and the Parallel Ocean Program (POP)–Ocean Atmosphere Sea Ice Soil (OASIS)–ECHAM model (POEM) shows that the projected weakening of the trades is robust only in the equatorial eastern Pacific (EEP) ( 5°S–5°N, 150°–80°W), but highly uncertain over the ECWP with 9 out of 19 CMIP5 models producing intensified trades. The prominent and robust weakening of EEP trades is suggested to be mainly driven by a top-down mechanism: the mean vertical advection of more upper-tropospheric warming downward to generate a cyclonic circulation anomaly in the southeast tropical Pacific. In the ECWP, the large intermodel spread is primarily linked to model diversity in simulating the relative warming of the equatorial Pacific versus the tropical mean sea surface temperature. The possible root causes of the uncertainty for the trade wind change are also discussed.


2021 ◽  
Author(s):  
Armineh Barkhordarian ◽  
Johanna Baehr

<p>We evaluate whether anthropogenic influence has affected the observed extreme sea surface temperature (SST), defined as discrete events of anomalously warm or cold ocean temperatures, over the last decades. To this end we utilize three large ensembles of coupled climate models and use two methods. The first method analyzes the observed long-term spatiotemporal changes of extreme SST to detect the presence of a signal beyond changes solely due to natural (internal) variability and to attribute the detected changes to external climate drivers. The second method is based on single event attribution, which determines how an external forcing have changed the likelihood of high-impact extreme SST events, such as the north Atlantic cold blob, the northeast Pacific warm blob, Tasman Sea marine heatwave, etc. In this study we further combine observations and model simulations under present and future forcing to assess how internal variability and anthropogenic climate change modulate extreme SST events.</p>


2005 ◽  
Vol 18 (10) ◽  
pp. 1449-1468 ◽  
Author(s):  
Wenju Cai ◽  
Harry H. Hendon ◽  
Gary Meyers

Abstract Coupled ocean–atmosphere variability in the tropical Indian Ocean is explored with a multicentury integration of the Commonwealth Scientific and Industrial Research Organisation (CSIRO) Mark 3 climate model, which runs without flux adjustment. Despite the presence of some common deficiencies in this type of coupled model, zonal dipolelike variability is produced. During July through November, the dominant mode of variability of sea surface temperature resembles the observed zonal dipole and has out-of-phase rainfall variations across the Indian Ocean basin, which are as large as those associated with the model El Niño–Southern Oscillation (ENSO). In the positive dipole phase, cold SST anomaly and suppressed rainfall south of the equator on the Sumatra–Java coast drives an anticyclonic circulation anomaly that is consistent with the steady response (Gill model) to a heat sink displaced south of the equator. The northwest–southeast tilting Sumatra–Java coast results in cold sea surface temperature (SST) centered south of the equator, which forces anticylonic winds that are southeasterly along the coast, which thus produces local upwelling, cool SSTs, and promotes more anticylonic winds; on the equator, the easterlies raise the thermocline to the east via upwelling Kelvin waves and deepen the off-equatorial thermocline to the west via off-equatorial downwelling Rossby waves. The model dipole mode exhibits little contemporaneous relationship with the model ENSO; however, this does not imply that it is independent of ENSO. The model dipole often (but not always) develops in the year following El Niño. It is triggered by an unrealistic transmission of the model’s ENSO discharge phase through the Indonesian passages. In the model, the ENSO discharge Rossby waves arrive at the Sumatra–Java coast some 6 to 9 months after an El Niño peaks, causing the majority of model dipole events to peak in the year after an ENSO warm event. In the observed ENSO discharge, Rossby waves arrive at the Australian northwest coast. Thus the model Indian Ocean dipolelike variability is triggered by an unrealistic mechanism. The result highlights the importance of properly representing the transmission of Pacific Rossby waves and Indonesian throughflow in the complex topography of the Indonesian region in coupled climate models.


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