Eight atmospheric general circulation models (AGCMs) are forced with observed historical (1871–2010) monthly sea surface temperature and sea ice variations using the Atmospheric Model Intercomparison ...Project II data set. The AGCMs therefore have a similar temperature pattern and trend to that of observed historical climate change. The AGCMs simulate a spread in climate feedback similar to that seen in coupled simulations of the response to CO2 quadrupling. However, the feedbacks are robustly more stabilizing and the effective climate sensitivity (EffCS) smaller. This is due to a pattern effect, whereby the pattern of observed historical sea surface temperature change gives rise to more negative cloud and longwave clear‐sky feedbacks. Assuming the patterns of long‐term temperature change simulated by models, and the radiative response to them, are credible; this implies that existing constraints on EffCS from historical energy budget variations give values that are too low and overly constrained, particularly at the upper end. For example, the pattern effect increases the long‐term Otto et al. (2013, https://doi.org/10.1038/ngeo1836) EffCS median and 5–95% confidence interval from 1.9 K (0.9–5.0 K) to 3.2 K (1.5–8.1 K).
Plain Language Summary
Recent decades have seen cooling over the eastern tropical Pacific and Southern Oceans while temperatures rise globally. Climate models indicate that these regional features, and others, are not expected to continue into the future under sustained forcing from atmospheric carbon dioxide increases. This matters because climate sensitivity depends on the pattern of warming, so if the past has warmed differently from what we expect in the future, then climate sensitivity estimated from the historical record may not apply to the future. We investigate this with a suite of climate models and show that climate sensitivity simulated for observed historical climate change is smaller than for long‐term carbon dioxide increases. The results imply that historical energy budget changes only weakly constrain climate sensitivity.
Key Points
Climate sensitivity simulated for observed surface temperature change is smaller than for long‐term carbon dioxide increases
Observed historical energy budget constraints give climate sensitivity values that are too low and overly constrained, particularly at the upper end
Historical energy budget changes only weakly constrain climate sensitivity
Understanding the long-term change of extreme temperature events is important to the detection and attribution of climate change. It is unclear, however, how much effect urbanization has had on ...trends of the extreme temperature indices series constructed based on the commonly used datasets on a subcontinental scale. Applying a homogenized daily temperature dataset of the national reference climate stations and basic meteorological stations, and a rural station network previously developed, urbanization effects on trends of extreme temperature indices in mainland China for the time period 1961–2008 are evaluated. It is found that 1) the country-averaged annual- and seasonal-mean extreme temperature indices series generally experience statistically significant trends; 2) annual-mean urbanization effects in the country as a whole are statistically significant for daily minimum temperature (Tmin), maximum temperature (Tmax), and mean temperature of Tmin and Tmax (Tavg), reaching 0.070°, 0.023°, and 0.047°C(10 yr)−1, respectively, with the largest values for annual-mean Tmin occurring in north China; 3) annual- and seasonal-mean urbanization effects for the declining diurnal temperature range (DTR) are highly significant, and the largest seasonal-mean DTR decline because of urbanization occurs in winter and spring; 4) annual-mean urbanization effects for the lowest Tmin, summer days, tropical nights, and frost days series are significant, but an insignificant urbanization effect is detected for icing days series; 5) urbanization has led to a highly significant decline of annual cold nights at a rate of −1.485 days (10 yr)−1and a highly significant increase of annual warm nights at a rate of 2.264 days (10 yr)−1. Although urbanization effects are also significant for cold days and warm days, they are relatively smaller, and 6) the smallest absolute values of annual-mean urbanization effects for most of the indices series are found to dominantly appear during 1966–76, a well-known deurbanization period resulting from the Cultural Revolution.
Water temperature microprofiles at the air‐water interface of a stratified lake were measured concurrently with moderate wind speeds of 0.8–8.2 ms−1 above the lake surface. The day‐time measurements ...revealed the cool skin effect of water surface temperatures that triggers the cooling of the lake surface and the occurrence of natural convection. Natural convection velocity scale mediates the thickness of the diffusive thermal sublayer and the corresponding net heat flux at the interface. The diffusive thermal sublayer thickness ranged from 0.7 to 3.6 mm. The temperature microprofiles and proposed parameterization of skin‐to‐bulk temperatures enable similarity scaling of temperature microprofiles over the diffusive thermal sublayer thickness. The proposed parameterizations allow for the estimation of diffusive thermal sublayer thickness and skin‐to‐bulk temperature difference in the presence of natural convection. Our results have the potential to facilitate the validation and integration of satellite‐derived lake surface temperatures.
Plain Language Summary
Inland water and ocean surface temperatures are a “global thermometer” of the planet. These water surface temperatures provide an important coupling channel between water and atmosphere environments and mediate the exchange of energy and chemicals between the two. We measured and analyzed temperature profiles in the proximity of air‐water interface in a small stratified lake. These measurements revealed a “cool skin” effect—colder water temperatures at the lake surface than those just below it. This cool skin effect triggers the convective cooling of the subsurface water. We propose a model to quantify the cool skin effect in the presence of natural convection. The proposed model can potentially facilitate verification and integration of large‐scale measurements of satellite‐derived surface water temperatures and may assist the estimation of greenhouse gas transport across lake and ocean surfaces.
Key Points
Natural convection velocity mediate the thickness of diffusive thermal sublayer and the corresponding net heat flux at the interface
Proposed parameterization of skin‐to‐bulk temperatures
Similarity scaling of temperature microprofiles over the diffusive thermal sublayer thickness
Satellite and in situ measurements of the sea surface and the atmosphere often have inadequate sampling frequencies and often lack consistent global coverage. Because of such limitations, reanalysis ...model output is frequently used in atmospheric and oceanographic research endeavors to complement satellite and in situ data. The National Aeronautics and Space Administration’s (NASA’s) Goddard Earth Sciences Modern-Era Retrospective Analysis for Research and Applications version 2 (MERRA-2) and the European Centre for Medium-Range Weather Forecasts (ECMWF) interim reanalysis (ERA-Interim) datasets provide accurate, complete fields through the assimilation of many atmospheric and surface observations. Still, the reanalysis output data must be rigorously and continuously evaluated to understand their strengths and weaknesses. To this end, this study evaluates sea surface skin temperature (SSTskin) and atmospheric temperature and humidity profiles in MERRA-2 and ERAInterim data through comparisons with independent Marine-Atmospheric Emitted Radiance Interferometer (M-AERI) and radiosonde data from theAerosols and Ocean Science Expeditions (AEROSE) cruises, focusing on the representation of spatial and temporal variability. SSTskin values are generally in good agreement with corresponding M-AERI measurements, with the average differences on the order of 0.1 K. Comparisons between MERRA-2 and ERA-Interim relative humidity and air temperature profiles with a total of 553 radiosondes that have been withheld from data assimilation schemes show good correspondence below 500 hPa: the average air temperature difference is, <2 K and the average relative humidity discrepancy is within 10%. These results support the use of these MERRA-2 and ERA-Interim reanalysis fields in a variety of research applications.
Palaeoclimate reconstructions of periods with warm climates and high atmospheric CO
concentrations are crucial for developing better projections of future climate change. Deep-ocean
and high-latitude
...palaeotemperature proxies demonstrate that the Eocene epoch (56 to 34 million years ago) encompasses the warmest interval of the past 66 million years, followed by cooling towards the eventual establishment of ice caps on Antarctica. Eocene polar warmth is well established, so the main obstacle in quantifying the evolution of key climate parameters, such as global average temperature change and its polar amplification, is the lack of continuous high-quality tropical temperature reconstructions. Here we present a continuous Eocene equatorial sea surface temperature record, based on biomarker palaeothermometry applied on Atlantic Ocean sediments. We combine this record with the sparse existing data
to construct a 26-million-year multi-proxy, multi-site stack of Eocene tropical climate evolution. We find that tropical and deep-ocean temperatures changed in parallel, under the influence of both long-term climate trends and short-lived events. This is consistent with the hypothesis that greenhouse gas forcing
, rather than changes in ocean circulation
, was the main driver of Eocene climate. Moreover, we observe a strong linear relationship between tropical and deep-ocean temperatures, which implies a constant polar amplification factor throughout the generally ice-free Eocene. Quantitative comparison with fully coupled climate model simulations indicates that global average temperatures were about 29, 26, 23 and 19 degrees Celsius in the early, early middle, late middle and late Eocene, respectively, compared to the preindustrial temperature of 14.4 degrees Celsius. Finally, combining proxy- and model-based temperature estimates with available CO
reconstructions
yields estimates of an Eocene Earth system sensitivity of 0.9 to 2.3 kelvin per watt per square metre at 68 per cent probability, consistent with the high end of previous estimates
.
The recent slowdown in global mean surface temperature (GMST) warming during boreal winter is examined from a regional perspective using 10‐member initial‐condition ensembles with two global coupled ...climate models in which observed tropical Pacific sea surface temperature anomalies (TPAC SSTAs) and radiative forcings are specified. Both models show considerable diversity in their surface air temperature (SAT) trend patterns across the members, attesting to the importance of internal variability beyond the tropical Pacific that is superimposed upon the response to TPAC SSTA and radiative forcing. Only one model shows a close relationship between the realism of its simulated GMST trends and SAT trend patterns. In this model, Eurasian cooling plays a dominant role in determining the GMST trend amplitude, just as in nature. In the most realistic member, intrinsic atmospheric dynamics and teleconnections forced by TPAC SSTA cause cooling over Eurasia (and North America), and contribute equally to its GMST trend.
Key Points
Realistic simulation of the hiatus in global mean surface temperature is no guarantee that the pattern of temperature trends is reproduced
Dynamically induced cooling over Eurasia and North America is driven by internal atmospheric dynamics and tropical Pacific teleconnections
Hiatus in global mean surface temperature is due equally to cooling from internal atmospheric dynamics and tropical Pacific teleconnections
This paper presents a comprehensive analysis of the effect of urbanization on the surface air temperature (SAT) from 1951 to 2018 in the Philippines. The daily minimum temperature (Tmin) and daily ...maximum temperature (Tmax) records from 34 meteorological stations were used to derive extreme temperature indices. These stations were then classified as urban or rural based on satellite night‐lights. The results showed a significant difference in the SAT trends between urban and rural stations, indicative of the effect of urbanization in the country. Larger and more significant warming trends were observed in indices related to Tmin than those related to Tmax. In particular, the effects of urbanization were significant in the annual index series of Tmin, diurnal temperature range, minimum Tmin, percentage of days when Tmin was less than the 10th percentile (TN10p), percentage of days when Tmin was greater than 90th percentile (TN90p), and the number of coldest nights. The effects of urbanization were not as clear on the index series of maximum Tmax (TXx), minimum Tmax (TXn), percentage of days when Tmax was less than 10th percentile (TX10p), and the number of hottest days. The effects of urbanization on the annual series of extreme temperature indices were statistically significant at the 95% confidence level, with the exception of Tmax, TXn, TXx, TX10p, and the number of hottest days. Further analysis revealed that the effect of urbanization was the greatest during the DJF (December–January–February) season. These findings serve as a baseline study that focuses on the countrywide effect of urbanization on SAT trends in the Philippines.
The 34 synoptic stations in the Philippines were classified into urban and rural stations based on the satellite nightlights to estimate the effect of urbanization on the trends of extreme temperature indices (e.g., (a) Tmin and (b) Tmax) in the country for the first time. The results show that larger and significant effects of urbanization were found in the annual indices related to Tmin as compared to those indices related to Tmax. Further analysis reveals that the maximum urbanization effect occurred during the winter season.
Marine heatwaves have been shown to be increasing in frequency, duration and intensity over the past several decades. Are these changes related to rising mean temperatures, changes to temperature ...variability, or a combination of the two? Here we investigate this question using satellite observations of sea surface temperature (SST) covering 36 years (1982–2017). A statistical climate model is used to simulate SST time series, including realistic variability based on an autoregressive model fit to observations, with specified trends in mean and variance. These simulated SST time series are then used to test whether observed trends in marine heatwave properties can be explained by changes in either mean or variability in SST, or both. We find changes in mean SST to be the dominant driver of the increasing frequency of marine heatwave days over approximately 2/3 of the ocean; while it is the dominant driver of changes in marine heatwave intensity (temperature anomaly) over approximately 1/3 of the ocean. We also find that changes in mean SST explain changes in both MHW properties over a significantly larger proportion of the world’s ocean than changes in SST variance. The implication is that given the high confidence of continued mean warming throughout the twenty-first century due to anthropogenic climate change we can expect the historical trends in marine heatwave properties to continue over the coming decades.
Efforts to estimate past global mean temperature and latitudinal gradients must contend with spatial heterogeneity in sea surface temperatures (SSTs). Here, we use modern SSTs to show that the ...environments from which most paleoclimatic data are drawn, shallow epeiric seas and continental margins, are systematically offset from zonal mean temperatures. Epeiric seas are warmer and more seasonal than open‐ocean values from the same latitudes, while continental margins exhibit consistent and predictable deviations related to gyre circulation. Warm temperatures inferred from Paleozoic proxy data may largely reflect that these data derive almost entirely from epeiric seas. Moreover, pseudoproxy analysis using Paleogene sampling localities demonstrates how undersampling of the full range of dynamical environments associated with gyre circulation can generate spurious estimates of latitudinal temperature gradients. Recognition of these global patterns permits a predictive framework within which to more robustly interpret proxy data, improve Earth system models, and reconstruct ancient dynamic regimes.
Plain Language Summary
Geochemical analyses provide estimates of past sea surface temperature. These data are integral to calculating global climate metrics, such as the latitudinal temperature gradient. For myriad reasons, the sites of these data are not evenly distributed across the global oceans but, instead, are biased toward two environments—continental margins and shallow continental seas. It is therefore important to determine the extent to which theses environments reflect broader climatic conditions. We use global ocean data to demonstrate that modern shallow, restricted seas are consistently warmer and more seasonal than anticipated for their given latitude. Because all sea surface temperature data older than ~200 Ma come from these environments, this observation could help explain why many Paleozoic temperatures appear unrealistically hot. Similarly, nearshore environments exhibit consistent offsets from the open ocean, both in terms of annual temperature and seasonal range, depending on their position within a gyre. This observation helps explain some of the longitudinal heterogeneity in paleoclimate data and should be used to inform locations to target for future data collection. Ignoring environment‐specific patterns can lead to spurious estimates of global climate metrics. However, cognizance of and correction for sampling location biases can improve interpretations of ancient climates.
Key Points
Proxy‐derived estimates of past sea surface temperatures are biased toward epeiric seas in the Paleozoic and coasts in the Cenozoic
In the modern ocean, sea surface temperatures from these environments systematically deviate from open ocean values at the same latitude
These deviations, related to ocean dynamics, must be considered when reconstructing latitudinal gradients and assessing model fidelity
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