Ocean Surface Temperature Changes Research Articles

Study of upper ocean parameters during passage of tropical cyclones over Indian seas

ABSTRACTThe primary energy supply for tropical cyclones is the upward latent heat fluxes that are directly related to Sea Surface Temperatures (SST). The strong winds induce a negative SST anomaly in the tropical cyclone wake. This is usually referred to as the ‘cold wake’. Many studies have suggested that the cold wake results in a significant reduction of upward latent heat fluxes that supply energy to the tropical cyclone, and hence provides a negative feedback on its intensity. The cold-wake feedback on the intensity of tropical cyclones is a strong motivation to understand the oceanic response to tropical cyclones. A recent study of re-examining the mechanisms controlling the cold wake has shown the importance of vertical Ekman pumping. Under the core of tropical cyclones (typically over a disk of 100 km radius), vertical pumping is responsible for a cooling of the entire water column, while surface heat fluxes and vertical mixing both contribute to the surface cooling during the cyclone passage. Farther away from the cyclone core, vertical mixing generally overwhelms the effect of vertical pumping, and also the effect of heat fluxes in the case of strong tropical cyclones. The study examines the Ekman pumping during the passage of few cyclonic storms in the Arabian Sea (AS) and Bay of Bengal (BOB) during last decade using different datasets such as Satellite (QuikScat) and reanalysis (ERA-Interim) data and calls up the value for satellite deliverables. Surface currents and subsurface temperature structure is examined further and for different Ekman pumping velocity (EPV), variable subsurface response is illustrated. The changes in ocean surface temperature, sea level and heat content obtained from the remote sensing data products, in the wake of cyclone are also reported and thus the usefulness of satellite products to study the coupled tropical system is demonstrated.

Distinct global warming rates tied to multiple ocean surface temperature changes

The planet is warming; however, this includes periods of accelerated and slowed warming. Although the tropical Pacific played a role in the recent slowdown, this study shows sea surface temperatures across multiple basins influence the rate of warming.

Wavelet nonparametric estimation from strong spatial correlated high-dimensional data

This paper addresses the problem of spatial prediction from strong spatial correlated high-dimensional data. Two approaches are considered: spatial wavelet kernel penalized nonparametric regression, and wavelet shrinkage. The best performance corresponds to spatial wavelet thresholding techniques applied to coarser scales, when slowly varying data displaying strong spatial correlations are analyzed. Our initial motivation relies on spatial estimation of annual mean ocean surface temperature maps to detect changes in ocean-surface temperatures, that could cause modifications in atmospheric circulation and precipitation. Specifically, we have analyzed daily ocean surface temperature curves from the Hawaii ocean stations, available at latitude–longitude interval [22.7,22.8]×[−158.1,−157.94] during the period 2000–2007, from The World-Wide Ocean Optics Database (WOOD). Additionally, wavelet-based non-linear estimation procedures are compared with wavelet-based Gaussian linear model estimation methods, based on spatial autoregressive Hilbertian processes, and heavy tail covariance processes, solution to fractional pseudodifferential equations.

Spring land temperature anomalies in northwestern US and the summer drought over Southern Plains and adjacent areas

Recurrent drought and associated heatwave episodes are important features of the US climate. Many studies have examined the connection between ocean surface temperature changes and conterminous US droughts. However, remote effects of large-scale land surface temperature variability, over shorter but still considerable distances, on US regional droughts have been largely ignored. The present study combines two types of evidence to address these effects: climate observations and model simulations. Our analysis of observational data shows that springtime land temperature in northwest US is significantly correlated with summer rainfall and surface temperature changes in the US Southern Plains and its adjacent areas. Our model simulations of the 2011 Southern Plains drought using a general circulation model and a regional climate model confirm the observed relationship between land temperature anomaly and drought, and suggest that the long-distance effect of land temperature changes in the northwest US on Southern Plains droughts is probably as large as the more familiar effects of ocean surface temperatures and atmospheric internal variability. We conclude that the cool 2011 springtime climate conditions in the northwest US increased the probability of summer drought and abnormal heat in the Southern Plains. The present study suggests a strong potential for more skillful intra-seasonal predictions of US Southern Plains droughts when such facts as ones presented here are considered.

Increased sensitivity of the Plio-Pleistocene northwest Pacific to obliquity forcing

Insolation-driven changes in poleward heat transport and changes in greenhouse gas concentrations can explain aspects of the rise of obliquity-paced climate variability during the Pliocene–Pleistocene transition. Based on an alkenone-based sea surface temperature (SST) reconstruction of the Kuroshio Current Extension (KCE), we propose here that emergence of this region as the primary locus of ocean–atmosphere heat transfer in the Pacific Ocean promoted Northern Hemisphere Glaciation (NHG). Our record shows that with intensification of NHG at 2.7 Ma, the KCE cooled 2–4 °C during glacial intervals, likely in NH winter/spring. These high-amplitude 41-kyr SST cycles slightly lead δO18 variations, ruling out global ice-volume changes as the primary cause. The lead of SST over δO18 cycles matches the phasing between these two proxies observed in the tropics, supporting changes in CO2 concentrations as a unifying mechanism of ocean surface temperature change. However, the amplitude of the KCE SST cycle is twice that of the tropical records, pointing to an additional, regional process. We infer that cooling of the North Pacific sea surface by the East Asian winter monsoon and associated westerlies intensified during glacial intervals. This transfer of heat and moisture from the ocean to the atmosphere potentially furthered glacial formation by accelerating snow fall in North America. Therefore, these results might also support a role for tropical–extratropical heat balance in enhancing glacial growth via the obliquity pacing.

Global imprint of climate change on marine life

Research that combines all available studies of biological responses to regional and global climate change shows that 81–83% of all observations were consistent with the expected impacts of climate change. These findings were replicated across taxa and oceanic basins. Past meta-analyses of the response of marine organisms to climate change have examined a limited range of locations1,2, taxonomic groups2,3,4 and/or biological responses5,6. This has precluded a robust overview of the effect of climate change in the global ocean. Here, we synthesized all available studies of the consistency of marine ecological observations with expectations under climate change. This yielded a meta-database of 1,735 marine biological responses for which either regional or global climate change was considered as a driver. Included were instances of marine taxa responding as expected, in a manner inconsistent with expectations, and taxa demonstrating no response. From this database, 81–83% of all observations for distribution, phenology, community composition, abundance, demography and calcification across taxa and ocean basins were consistent with the expected impacts of climate change. Of the species responding to climate change, rates of distribution shifts were, on average, consistent with those required to track ocean surface temperature changes. Conversely, we did not find a relationship between regional shifts in spring phenology and the seasonality of temperature. Rates of observed shifts in species’ distributions and phenology are comparable to, or greater, than those for terrestrial systems.

Response of the North American monsoon to regional changes in ocean surface temperature

The North American monsoon (NAM), an onshore wind shift occurring between July and September, has evolved in character during the Holocene largely due to changes in Northern Hemisphere insolation. Published paleoproxy and modeling studies suggest that prior to ∼8000 cal years BP, the NAM affected a broader region than today, extending westward into the Mojave Desert of California. Holocene proxy SST records from the Gulf of California (GoC) and the adjacent Pacific provide constraints for this changing NAM climatology. Prior to ∼8000 cal years BP, lower GoC SSTs would not have fueled northward surges of tropical moisture up the GoC, which presently contribute most of the monsoon precipitation to the western NAM region. During the early Holocene, the North Pacific High was further north and SSTs in the California Current off Baja California were warmer, allowing monsoonal moisture flow from the subtropical Pacific to take a more direct, northwesterly trajectory into an expanded area of the southwestern U.S. west of 114°W. A new upwelling record off southwest Baja California reveals that enhanced upwelling in the California Current beginning at ∼7500 cal year BP may have triggered a change in NAM climatology, focusing the geographic expression of NAM in the southwest USA into its modern core region east of ∼114°W, in Arizona and New Mexico. Holocene proxy precipitation records from the southwestern U.S. and northwestern Mexico, including lakes, vegetation/pollen, and caves are reviewed and found to be largely supportive of this hypothesis of changing Holocene NAM climatology.

The Relationship between Land–Ocean Surface Temperature Contrast and Radiative Forcing

Abstract Previous work has demonstrated that observed and modeled climates show a near-time-invariant ratio of mean land to mean ocean surface temperature change under transient and equilibrium global warming. This study confirms this in a range of atmospheric models coupled to perturbed sea surface temperatures (SSTs), slab (thermodynamics only) oceans, and a fully coupled ocean. Away from equilibrium, it is found that the atmospheric processes that maintain the ratio cause a land-to-ocean heat transport anomaly that can be approximated using a two-box energy balance model. When climate is forced by increasing atmospheric CO2 concentration, the heat transport anomaly moves heat from land to ocean, constraining the land to warm in step with the ocean surface, despite the small heat capacity of the land. The heat transport anomaly is strongly related to the top-of-atmosphere radiative flux imbalance, and hence it tends to a small value as equilibrium is approached. In contrast, when climate is forced by prescribing changes in SSTs, the heat transport anomaly replaces “missing” radiative forcing over land by moving heat from ocean to land, warming the land surface. The heat transport anomaly remains substantial in steady state. These results are consistent with earlier studies that found that both land and ocean surface temperature changes may be approximated as local responses to global mean radiative forcing. The modeled heat transport anomaly has large impacts on surface heat fluxes but small impacts on precipitation, circulation, and cloud radiative forcing compared with the impacts of surface temperature change. No substantial nonlinearities are found in these atmospheric variables when the effects of forcing and surface temperature change are added.

Control of land‐ocean temperature contrast by ocean heat uptake

We show that the ratio of observed annual‐mean land temperature change to ocean surface temperature change, ϕ, has remained almost constant during 1955–2003. This is the case, despite most of the heat capacity of the climate system lying in the oceans, and rapid variations in climate forcing. Examining seven General Circulation Models (GCMs), we find land and ocean temperature behavior comparable to observations in six cases. For three models that reproduce observed ϕ and for which we have data, we find no significant changes in future ϕ under the SRES A1B scenario. We suggest that variations in land‐ocean heat flux primarily balanced by ocean heat uptake are sufficient to maintain constant ϕ. This flux is present in the six GCMs that resemble observations, suggesting that observed ϕ may remain constant into the future, even if radiative forcing is markedly different than in the past.

Global and Regional Sea Surface Temperature Trends

Individual sea surface temperature (SST) anomalies are calculated using a satellite-based climatology and observations from the World Ocean Atlas 1994(WOA94) and the Comprehensive Ocean‐Atmosphere Data Set (COADS) to characterize global and regional changes in ocean surface temperature since 1942. For each of these datasets, anomaly trends are computed using a new method that groups individual anomalies into climatological temperature classes. These temperature class anomaly trends are compared with trends estimated using a technique representative of previous studies based on 58 latitude‐longitude bins. Global linear trends in the data-rich period between 1960 and 1990 calculated from the WOA94 data are found to be 0.14 86 0.048C decade21 for the temperature class approach and 0.13 86 0.048C decade21 for the 58 bin approach. The corresponding results for the COADS data are 0.10 86 0.038C and 0.09 86 0.038C decade21. These trends are not statistically different at the 95% confidence level. Additionally, they agree closely with both SST and land‐air temperature trends estimated from results reported by the Intergovernmental Panel on Climate Change. The similarity between the COADS trends and the trends calculated from the WOA94 dataset provides confirmation of previous SST trend studies, which are based almost exclusively on volunteer observing ship datasets like COADS. Regional linear trends reveal a nonuniformity in the SST rates between 1945‐70 and 1970‐95. Intensified warming during the later period is observed in the eastern equatorial Pacific, the North Atlantic subtropical convergence, and in the vicinity of the Kuroshio extension. Also, despite close agreement globally, localized differences between COADS and WOA94 trends are observed.

Northern Hemisphere Ice-Sheet Influences on Global Climate Change

Large ice sheets actively interact with the rest of the climate system by amplifying, pacing, and potentially driving global climate change over several time scales. Direct and indirect influences of ice sheets on climate cause changes in ocean surface temperatures, ocean circulation, continental water balance, vegetation, and land-surface albedo, which in turn cause additional feedbacks in the climate system and help to synchronize global climate change. The effect of the underlying geological substrate on ice-sheet dynamics may be the missing link in understanding the ice sheet–climate interactions that are integral to the middle Pleistocene transition; the 100,000-year climate cycle; high-amplitude, millennial-scale climate variability; and low–aspect ratio ice sheets of the Last Glacial Maximum.

Uncertainty propagation within an integrated model of climate change

This paper demonstrates a methodology whereby stochastic dynamical systems are used to investigate a climate model's inherent capacity to propagate uncertainty over time. The usefulness of the methodology stems from its ability to identify the variables that account for most of the model's uncertainty. We accomplish this by reformulating a deterministic dynamical system capturing the structure of an integrated climate model into a stochastic dynamical system. Then, via the use of computational techniques of stochastic differential equations accurate uncertainty estimates of the model's variables are determined. The uncertainty is measured in terms of properties of probability distributions of the state variables. The starting characteristics of the uncertainty of the initial state and the random fluctuations are derived from estimates given in the literature. Two aspects of uncertainty are investigated: (1) the dependence on environmental scenario — which is determined by technological development and actions towards environmental protection; and (2) the dependence on the magnitude of the initial state measurement error determined by the progress of climate change and the total magnitude of the system's random fluctuations as well as by our understanding of the climate system. Uncertainty of most of the system's variables is found to be nearly independent of the environmental scenario for the time period under consideration (1990–2100). Even conservative uncertainty estimates result in scenario overlap of several decades during which the consequences of any actions affecting the environment could be very difficult to identify with a sufficient degree of confidence. This fact may have fundamental consequences on the level of social acceptance of any restrictive measures against accelerating global warming. In general, the stochastic fluctuations contribute more to the uncertainty than the initial state measurements. The variables coupling all major climate elements, such as CO 2 concentration of ocean surface temperature change are among the most sensitive variables to any kind of uncertainties.

A statistical method for testing a general circulation model with spectrally resolved satellite data

The motivation for this paper is to understand better the means available for testing climate models. Statistics of observed, outgoing, thermal spectra are compared with those predicted from a climate model, on the basis of data collected over a period of approximately 1 year. This is a powerful approach to testing a model with respect to processes internal to the atmosphere. These processes, which have characteristic timescales of less than a year, define the atmosphere's response to external forcing. Second‐moment statistics are particularly important for testing model variability, which is key to predicting the results of forcing the atmosphere, for example, by ocean surface temperature changes, increase of greenhouse gases, etc. Comparisons are presented between statistical data from the infrared interferometer spectrometer (IRIS), an orbiting fourier transform spectrometer, and spectra calculated using the medium‐resolution spectral code, MODTRAN, applied to the temperature and humidity profiles from a well‐known climate model. Ten months of IRIS data are available, and we have compared means, standard deviations, skew, and kurtosis of its spectrally resolved brightness temperature in three tropical regions for individual months and for a range of timescales. Also presented are comparisons of covariances using Empirical Orthogonal Functions (EOFs) calculated in frequency space. All data that are presented are based on radiance differences from two like spectra, which eliminates many of the errors generated by the use of MODTRAN and most of the errors due to calibration uncertainties in IRIS. Important differences (i.e., residuals) between the IRIS and the GCM statistics are found in comparisons, demonstrating that the spectral data can provide a severe test of many aspects of the variability of a general circulation model. We discuss some of the residuals and how they may be used to improve model performance in the context of an adjoint formalism. In the long run the only way to have confidence in the performance of a model is to subject it to as many discriminating comparisons with data as are practicable, and we present a good candidate.

Correlation methods in fingerprint detection studies

This investigation addresses two general issues regarding the role of pattern similarity statistics in greenhouse warming detection studies: normalization, and the relative merits of centered versus uncentered statistics. A pattern correlation statistic is used to search for the greenhouse warming signals predicted by five different models in the observed records of land and ocean surface temperature changes. Two forms of this statistic were computed: R (t), which makes use of nonnormalized data, and $$\tilde R$$ (t), which employs point-wise normalized data in order to focus the search on regions where the signal-to-noise ratio is large. While there are no trends in the R (t) time series, the time series of $$\tilde R$$ (t) show large positive trends. However, it is not possible to infer from the $$\tilde R$$ (t) results that the observed pattern of temperature change is, in fact, becoming increasingly similar to the model-predicted signal. This is because point-wise normalization of the observed and simulated mean change fields by a single common field introduces a “common factor” effect, which means that the quantities being compared should show some similarity a priori. This does not necessarily make normalization inapplicable, because the detection test involves seeking a trend in the similarity statistic. We show, however, that trends in $$\tilde R$$ (t) must arise almost completely from the observed data, and cannot be an indicator of increasing observed data/signal similarity. We also compare the information provided by centered statistics such as R(t) and the uncentered C(t) statistic introduced by Barnett. We show that C(t) may be expressed as the weighted sum of two terms, one proportional to R(t) and the other proportional to the observed spatial mean. For near-surface temperatures, the spatial average term dominates over the R(t) term. In this case the use of C(t) is equivalent to the use of spatial-mean temperature. We conclude that at present, the most informative pattern correlation statistic for detection purposes is R(t), the standard product-moment correlation coefficient between the observed and model fields. Our failure to find meaningful trends in R(t) may be due to the fact that the signal is being obscured by the background noise of natural variability, and/or because of incorrect model signals or sensitivities.

Response time of an atmospheric general circulation model to changes in ocean surface temperature: Implications for interactive large-scale atmosphere and ocean models

To ensure efficient coupling strategies in asynchronous coupling experiments with atmospheric and oceanic general circulation models (GCMs), knowledge of the atmospheric model's response time to altered ocean surface temperature (OST) forcing is a necessary prerequisite. A general estimate of atmospheric response time of 30 days is obtained by analysis of the time evolution between different quasi-equilibrium states in response to altered OSTs in several atmospheric GCM experiments. It is recognized, however, that this estimate may be too conservative (longer than necessary) for lower atmospheric layers in the tropics. For a completely optimized asynchronous coupling strategy, an estimate of oceanic response time to altered atmospheric forcing is also necessary. DOI: 10.1111/j.2153-3490.1980.tb00939.x

Response of the NCAR General Circulation Model to Prescribed Changes in Ocean Surface Temperature. Part II: Midlatitude and Subtropical Changes

Abstract The sensitivity of a six-layer NCAR atmospheric general circulation model (GCM) to a variety of idealized, very large amplitude, midlatitude and subtropical North Pacific Ocean surface temperature (OST) anomalies is analyzed. In the Pacific sector, the model exhibits a differential sensitivity depending on the latitudinal position of the imposed anomaly. Typically, the model response is a combination of a relative direct thermal circulation, an alteration in the pattern of cyclonic activity, and a selective wave response dependent on the planetary waves present in the unmodified control case. The extent to which the background planetary waves affect the model response is dependent on several factors including latitude-dependent features of the control case and the relative position of the anomaly. Analogous experiments with a simple quasi-geostrophic model are useful in isolating important physical and dynamical processes, and thereby assist in the interpretation of the GCM results. An analysis o...

Radiocarbon dating of shell middens and holocene sea-level fluctuations in Japan

From the distribution and radiocarbon dating of shell middens in the Japanese Islands, sea-level oscillations in the Holocene are inferred. Positive peaks occurred notably at 6700, 5300, 3100, and 2800 years B.P., and negative peaks at around 7500, around 6000, 4300, around 3500, and 3000 years B.P. The oscillations correlate with climatic and ocean surface-temperature changes in the vicinity of Japan.

Climatic impact of alternative energy sources

Detailed evaluations have suggested that the order of magnitude of energy demand 50 yr from the present will be 25–40 TW compared with about 8 TW at the present day. Three energy supply sources could be developed on a large enough scale to satisfy a demand of this magnitude: solar and nuclear energy and fossil fuels. The potential climate impact of the large-scale deployment of solar energy conversion systems has not been evaluated in detail. Solar thermal electric conversion systems could impact climate through large-scale changes in the energy balance at the earth's surface, in the surface roughness and in the surface wetness. Photovoltaic conversions could impact climate by acting as a local heat source. Ocean thermal electric conversion systems would have their main impact through changes in ocean surface temperature, but could also interfere with major ocean currents and have an impact through release of CO 2 into the atmosphere or albedo changes, for example. The cultivation of plants for biomass conversion systems could influence climate through causing large-scale changes in the surface characteristics. The biomass conversion could also impact climate through releases of gases and particulate matter into the atmosphere. Through the use of climate models and observational studies, these impacts should be studied in more detail. In the meantime, the climate constraint should be kept in mind during the development of energy policy and the policies should be kept flexible at the present time until some of the uncertainties about the climate system have been resolved.

Sensitivity of a General Circulation Model to Changes in Infrared Cooling due to Chlorofluoromethanes with and without Prescribed Zonal Ocean Surface Temperature Change

Abstract A detailed analysis is presented of the sensitivity of the 12-layer tropospheric/stratosphoric NCAR global circulation model (GCM) on a zonal, global and regional basis to changes in global radiative balance due to an atmospheric burden of 10 ppb of chlorofluoromethanes (CFM's). Large changes in both the amplitude and phase of Northern Hemisphere winter planetary waves are an apparent consequence of the prescribed change. Also, large and statistically significant changes in the regional distribution of mean surface temperature and precipitation patterns result. However, many of the regional details of the model's response appear to be sensitive to the change in ocean surface temperature, which was imposed in the model run with CFM added. Hence, any more definitive indication of the climatic impact of CFM's must await the development of physically reasonable, interactive, coupled ocean-atmosphere models.

Response of the NCAR General Circulation Model to Prescribed Changes in Ocean Surface Temperature Part I: Mid-Latitude Changes

Four numerical experiments are analyzed to determine the three-dimensional response of the NCAR general circulation model to large prescribed changes in mid-latitude North Pacific Ocean surface temperature. The ocean surface temperature (OST) boundary conditions are subjected to changes of opposite sign in the eastern and west-central portions of the North Pacific Ocean. The maximum amplitude of the temperature changes is either 12°C or 4°C. The model atmosphere response in the North Pacific sector includes changes in amplitude and vertical tilt of the long waves, an increased direct thermal circulation (i.e., warm air rises over the positive OST change and cold air sinks over the negative OST change), and locally enhanced westerlies to the north of the positive OST change. Cyclones form and/or intensify over the positive OST change and tend to be absent or weak over the negative OST change. The mid-tropospheric response extends downstream from the prescribed change region, and the response both over and downstream from the region depends strongly on the longitude of the prescribed changes. Many features of the response are statistically significant, although generally not over the continental United States. The amplitude and phase of the mid-tropospheric long waves (zonal wavenumbers 1–4) are also affected. The prescribed change response is largest and of greatest statistical significance when the prescribed change is very large (12°C maximum amplitude) but is also frequently detectable when the prescribed change is one-third as large (4°C maximum amplitude). A comparable experiment involving a prescribed North Atlantic OST change produces a similar mid-tropospheric response.