Hadley Centre Sea Ice Research Articles

Interannual variations in atmospheric mass over liquid water oceans, continents, and sea‐ice‐covered arctic regions and their possible impacts on the boreal winter climate

AbstractUsing reanalysis data from National Centers for Environmental Prediction/National Center for Atmospheric Research, ERA‐interim, and Hadley Centre Sea Ice and Sea Surface Temperature for the period of 1979–2012, the variations in atmospheric mass (AM) over liquid water oceans, continents, and sea‐ice‐covered Arctic regions during boreal winter are investigated. It is found that AM may migrate in a compensatory manner among these three types of surfaces on interannual time scales. There are two pairs of strong antiphase relations. One lies in a zonal orientation between the Eurasian continent and the midlatitude Pacific (referred to as Eurasian continent/Pacific antiphase relation) and exhibits a teleconnection pattern characterized by two strong correlation centers, one over Eurasia and one over the North Pacific. The other antiphase AM relation, referred to as ocean/ice‐covered Arctic antiphase relation (OIAR), exhibits a meridional orientation between the ice‐covered Arctic and liquid water oceans, including the Atlantic and Pacific. In the context of the OIAR, two teleconnection patterns are observed. One features three strong correlation centers, one each over the Mediterranean, Arctic, and North Pacific, and corresponds to AM fluctuations over liquid water oceans. The other is characterized by three strong correlation centers over the Mediterranean, the Arctic, and East Asia, and corresponds to AM fluctuations over the ice‐covered Arctic. These teleconnections are the results of thermal contrasts among the three types of surfaces. Rossby waves and vertical circulations play important roles in the formation of these teleconnections. Interestingly, these teleconnections may have significant and widespread influences on the winter climate in the Northern Hemisphere, especially in regions near the Mediterranean, the northern Eurasia, parts of North America, and East Asia.

Trends and Variability of Sea Surface Temperature in the Northwest Atlantic from Three Historical Gridded Datasets

ABSTRACTHistorical variability in sea surface temperature (SST) in the North Atlantic (NA) is examined using trend and Empirical Orthogonal Function (EOF) analyses of annual and summer means from three interpolated monthly datasets: Hadley Centre Sea Ice and Sea Surface Temperature (HadISST1), Extended Reconstruction of SST (ERSST), and Centennial in situ Observation-Based Estimates (COBE). Comparisons with time series of upper-ocean temperature from four monitoring sites off Atlantic Canada reveal substantial similarity in the interannual to multi-decadal variability but notable differences in the longer-term trends. The magnitude of decadal-scale variability is comparable to, or greater than, the long-term changes in all of the datasets; together with the trend discrepancies, this needs to be considered in climate change applications. Averaged over the NA, the annual means have a long-term increasing trend and a pronounced multi-decadal variation, resembling those in global mean (land-ocean) surface temperature and the Atlantic Multi-decadal Oscillation (AMO). There is remarkable similarity in the spatial and temporal variability of the three leading EOF modes from the different gridded datasets, with the first highly correlated with the AMO, the second modestly correlated with the winter North Atlantic Oscillation, and the third apparently related to ocean circulation variability. Trends since 1981 are generally two to three times larger than those since 1900 and 1950, which is at least partly related to the phase of the AMO. Trends in the summer means are generally larger than in the annual means. Overall, the results provide support for both anthropogenic global warming and decadal-scale natural variations making important contributions to ocean climate variability in the Northwest Atlantic.

Factors contributing to uncertainty in Pacific Decadal Oscillation index

AbstractPacific Decadal Oscillation (PDO) index is an important indicator of climate variability. However, large discrepancies are found among real‐time PDO monitoring indices maintained by several operational centers, with larger uncertainty exhibiting prior to 1950s and after late 1990s on seasonal to decadal time scales. Two historical sea surface temperature (SST) data sets are used to investigate causes for the uncertainty: the Extended Reconstructed Sea Surface Temperature version 3b (ERSST 3b) and the Hadley Center Sea Ice and SST data set (HadISST) version 1. It is found that choices of spatial structure of Empirical Orthogonal Function (EOF) vector and SST data set are important sources of uncertainty on seasonal to decadal time scales, while choice of climatological base period only contributes to uncertainty on seasonal time scale. Decadal variation of differences in PDO indices from ERSST and HadISST is associated with systematic differences between the two data sets in the central and the north‐eastern Pacific.

Warmer-get-wetter or wet-get-wetter? A criterion to classify oceanic precipitation

In this study, the temporal and spatial variations of observed global oceanic precipitation during 1979–2010 are investigated. It is found that the global trend in precipitation during this period varies at a rate of 1.5%/K of surface warming while the rate is 6.6%/K during 2006–2010. The precipitation is highly correlated with Sea Surface Temperature (SST) in both the temporal and the spatial patterns since the strong 1997–98 El Nino event. Considering the distributions of precipitation and SST, seven oceanic regions are classified and presented using the observed Global Precipitation Climatology Project (GPCP) data and Extended Reconstructed Sea Surface Temperatures, version 3 (ERSST.v3) data. Further examining the mechanisms of the classified oceanic precipitation regions is conducted using the Tropical Rainfall Measuring Mission (TRMM) satellite, GFDL-ESM-2G model precipitation and SST data and Hadley Center sea ice and SST version 1 (HadISST1) data. More than 85% of global oceanic precipitations are controlled by either one or both of the warmer-get-wetter mechanism and wet-get-wetter mechanism. It is estimated that a 0.5 SST signal-to-noise ratio, representing the trend of SST time series to the standard deviation, is a criterion to distinguish the mechanism of a region. When the SST ratio is larger than 0.5, the precipitation of this region is controlled by the warmer-get-wetter mechanism. SST, rather than the humidity, is the pivotal factor. On the other hand, when the SST ratio is less than 0.5, the precipitation is controlled by the wet-get-wetter mechanism. The SST variability is a significant factor contributing to the precipitation variation.

The Met Office Hadley Centre sea ice and sea surface temperature data set, version 2: 1. Sea ice concentrations

We present a new version of the sea ice concentration component of the Met Office Hadley Centre sea ice and sea surface temperature data set, HadISST.2.1.0.0. Passive microwave data are combined with historical sources, such as sea ice charts, to create global analyses on a 1° grid from 1850 to 2007. Climatology was used when no information about the sea ice was available. Our main aim was to create a homogenous data set by calculating and applying bias adjustments using periods of overlaps between the different data sources used. National Ice Center charts from 1995 to 2007 have been used as a reference to achieve this. In particular, large bias adjustments have been applied to the passive microwave data in both the Antarctic and Arctic summers. Overall, HadISST.2.1.0.0 contains more ice than HadISST1.1, with higher concentrations, shorter marginal ice zones, and larger extents and areas in some regions and periods. A new method for estimating the concentrations within the ice pack using the distance from the ice edge has been developed and evaluated. This was used when only the extents were known or the original concentration fields were heterogeneous. A number of discontinuities in the HadISST1.1 record are no longer found in HadISST.2.1.0.0.

The simulation of water vapor transport in East Asia using a regional air–sea coupled model

A regional air–sea coupled model (RegCM3‐POM) is used, and the ability of the model to simulate June, July, and August (JJA) moisture transport is verified. The coupled model (RegCM3‐POM) has better performances than the uncoupled model (RegCM3) in the simulation of the JJA mean water vapor characteristics from 1979 to 2002 and its interannual variations. The differences of water vapor between RegCM3‐POM and RegCM3 are mainly caused by different winds in the middle and low troposphere. The simulated circulation pattern of RegCM3‐POM is more similar to the Climate Forecast System Reanalysis (CFSR) data than that of the uncoupled model. The simulated geopotential height and the gradient of geopotential height in the coupled model are more accurate than those in the uncoupled model. The real‐time and lead–lag relationship between geopotential height and sea surface temperature (SST) in RegCM3‐POM is consistent with that between the height of CFSR data and HadISST (Hadley Center Sea Ice and Sea Surface Temperature data). Thus, the simulated water vapor in the lower troposphere and the vertically integrated moisture transport are more accurate in the coupled model than in RegCM3. In addition, the correlation coefficients between moisture transport and SST in RegCM3 are positive in South China Sea, corresponding to SST forcing; the correlation coefficients in RegCM3‐POM are negative, which is consistent with that between the vapor transport in CFSR data and HadISST. Thus, the air–sea coupled model represents more accurately than the uncoupled model the relationship between SST and moisture transport.

Impacts of Two Types of El Niño and La Niña Events on Typhoon Activity

The HadISST (Hadley Centre Sea Ice and Sea Surface Temperature) dataset is used to define the years of El Niño, El Niño Modoki, and La Niña events and to find out the impacts of these events on typhoon activity. The results show that the formation positions of typhoon are farther eastward moving in El Niño years than in La Niña years and much further eastward in El Niño Modoki years. The lifetime and the distance of movement are longer, and the intensity of typhoons is stronger in El Niño and in El Niño Modoki years than in La Niña years. The Accumulated Cyclone Energy of typhoon is highly correlated with the Oceanic Niño Index with a correlation coefficient of 0.79. We also find that the typhoons anomalously decrease during El Niño years but increase during El Niño Modoki years. Besides, there are two types of El Niño Modoki, I and II. The intensity of typhoon in El Niño Modoki I years is stronger than in El Niño Modoki II years. Furthermore, the centroid position of the Western Pacific Warm Pool is strongly related to the area of typhoon formation with a correlation coefficient of 0.95.

Impact of sea ice cover changes on the Northern Hemisphere atmospheric winter circulation

ABSTRACTThe response of the Arctic atmosphere to low and high sea ice concentration phases based on European Center for Medium-Range Weather Forecast (ECMWF) Re-Analysis Interim (ERA-Interim) atmospheric data and Hadley Centre's sea ice dataset (HadISST1) from 1989 until 2010 has been studied. Time slices of winter atmospheric circulation with high (1990–2000) and low (2001–2010) sea ice concentration in the preceding August/September have been analysed with respect to tropospheric interactions between planetary and baroclinic waves. It is shown that a changed sea ice concentration over the Arctic Ocean impacts differently the development of synoptic and planetary atmospheric circulation systems. During the low ice phase, stronger heat release to the atmosphere over the Arctic Ocean reduces the atmospheric vertical static stability. This leads to an earlier onset of baroclinic instability that further modulates the non-linear interactions between baroclinic wave energy fluxes on time scales of 2.5–6 d and planetary scales of 10–90 d. Our analysis suggests that Arctic sea ice concentration changes exert a remote impact on the large-scale atmospheric circulation during winter, exhibiting a barotropic structure with similar patterns of pressure anomalies at the surface and in the mid-troposphere. These are connected to pronounced planetary wave train changes notably over the North Pacific.

North Australian Sea Surface Temperatures and the El Niño–Southern Oscillation in Observations and Models

Abstract Interannual variations in the sea surface temperature (SST) to the north of Australia are strongly linked to variations in Australian climate, including winter rainfall and tropical cyclone numbers. The north Australian SSTs are also closely linked to ENSO and tropical Pacific SSTs, with the relationship exhibiting a strong seasonal cycle. Credible predictions of Australian climate change therefore depend on climate models being able to represent ENSO and its connection to north Australian SSTs, the topic of this study. First, the observational datasets of the Met Office Hadley Centre Sea Ice and Sea Surface Temperature (HadISST) and the NOAA Extended Reconstructed Sea Surface Temperature (ERSST) are used to document the links between the Niño-3.4 index and a north Australian SST index, and the temporal evolution of north Australian SSTs during ENSO events. During austral autumn, the correlation between Niño-3.4 SST and north Australian SST is positive, while in austral spring it is strongly negative. During El Niño events, the north Australian SST anomalies become negative in the austral spring preceding the development of the positive Niño-3.4 SST anomalies. The coupled models participating in the Coupled Model Intercomparison Project phase 3 (CMIP3) are evaluated in terms of this temporal evolution of Niño-3.4 SST and the relationship to north Australian SST for the twentieth-century simulations. Some of the models perform very well, while some do not capture the seasonal cycle of correlations at all. The way in which these relationships may change in the future is examined using the A2 emissions scenario in those models that do a reasonable job of capturing the present-day observed relationship, and very little change is found.

Correction to “Modeling the ENSO impact of orbitally induced mean state climate changes”

[1] In the paper “Modeling the ENSO impact of orbitally induced mean state climate changes” (Journal of Geophysical Research, 117, C05043, doi:10.1029/2011JC007742, 2012) an incorrect version of section 3.1 was published. The correct section 3.1 appears here. [2] To assess the baseline model configuration for the present study, the SSTs from the preindustrial control simulation (0K) are compared with observed SSTs from the Hadley Centre Sea Ice data, HadISST [Rayner et al., 2003] over the period of 1950–1999 (Figures 2a and 2b). The simulated annual mean Equatorial Pacific SSTs (averaged over 120°E–80°W, 5°N–5°S) are about 2°C colder compared to the data (Figures 2a and 2b and Table 2). This is a common bias of non-flux corrected climate models, and possibly due to overly strong trade winds [Guilyardi, 2006] and/or too strong vertical mixing in the ocean. The transient climate response (TCR), the temperature change at the time of CO2 doubling, is 2.9°C in the KCM, which is stronger than in other CMIP3 models (1.2°C–2.6°C) [Park et al., 2009]. [3] The annual cycle in the eastern Tropical Pacific, including the westward propagation of the SST signal, and the semi-annual cycle in the western Tropical Pacific are clearly reproduced by the model (Figures 2c and 2d). However, the amplitude of the annual cycle in the eastern Tropical Pacific is underestimated and it has its peak delayed by 1–2 months. Despite the equatorial cold bias, the zonal SST gradient is comparable to the observations (Table 2) [see also Liu, 1998]. The model overestimates the interannual SST variability in the Western Pacific Warm Pool (WPWP), as indicated by the spatial pattern of the long-term standard deviation. This could be expected given the equatorial cold tongue extends too far to the west. The interannual SST variability is in better agreement with the observations in the eastern Tropical Pacific in terms of both the strength and location of maximum variability (Figures 2e and 2f). [4] The ENSO amplitude in the KCM, defined as the standard deviation of the SST anomalies (SSTA) in the Niño3 region, amounts to 0.91°C, which agrees well with the data (Table 2). However, the small kurtosis and skewness indicate that the Niño3 SSTA distribution is too broad and too symmetric. In particular, the model underestimates the observed tendency toward very strong warm SST anomalies, as indicated by the much larger positive skewness in the Hadley Centre's SST data (Table 2). The spectrum of the Niño3 SST anomalies peaks between 3 and 4 years, which is slightly shorter than that in the observations (Figure 3). In spite of these differences, which in part may result from the different record length (500 years versus 50 years), the preindustrial control simulation represents the important aspects of the mean Tropical Pacific climate and of ENSO reasonably well.

Long Time-Scale Teleconnection Patterns in the Northern Atlantic and Pacific

AbstractLong time-scale teleconnection patterns, with common features in both the northern Atlantic and Pacific regions, are identified. The teleconnection patterns arise in an investigation of the internally generated variability in a multimodel ensemble of coupled climate model control simulations. The large amount of data involved offers statistical robustness and the benefits of combining results across models. Maxima of decadal potential predictability identify regions where long time-scale variability is an appreciable fraction of the total variability and serve as index regions for the teleconnection analysis. Annual, 5-yr, and decadal mean temperatures over these Atlantic and Pacific index regions are correlated with corresponding temperatures and precipitation rates over the globe. The resulting teleconnection patterns are reasonably similar despite the different long time-scale variability mechanisms thought to exist in the two ocean basins. Although lacking statistical robustness, some aspects of the temperature teleconnection patterns are obtained based on the Hadley Centre Sea Ice and Sea Surface Temperature (HadISST) dataset. The similarity of the teleconnection patterns in the two northern ocean regions suggests that common variability mechanisms may be involved.

Assessing the Quality of Regional Ocean Reanalysis Data from ENSO Signals

AbstractThe quality of regional ocean reanalysis data for “the joining area of Asia and the Indian-Pacific Ocean (AIPO)” has been assessed from the perspective of ENSO-related ocean signals. The results derived from the AIPO reanalysis, including SST, sea surface height (SSH), and subsurface ocean temperature and currents, are compared with those of Hadley Center Sea Ice and Sea Surface Temperature (HadISST) data set and Simple Ocean Data Assimilation (SODA) reanalysis data. Both the spatial pattern and the characteristics of evolution of the ENSO-related ocean temperature anomalies are well reproduced by the AIPO reanalysis data. The physical processes proposed to explain the life cycle of ENSO, including the delayed oscillator mechanism, rechargedischarge mechanism, and the zonal advection feedback, are reasonably represented in this dataset. However, the westward Rossby wave signal in 1992 is not obvious in the AIPO data, and the magnitude of the heat content anomalies is different from that of the SOD...

The SST Multidecadal Variability in the Atlantic–Mediterranean Region and Its Relation to AMO

Abstract Two sea surface temperature (SST) time series, the Extended Reconstructed SST version 3 (ERSST.v3) and the Hadley Centre Sea Ice and Sea Surface Temperature dataset (HadISST), are used to investigate SST multidecadal variability in the Mediterranean Sea and to explore possible connections with other regions of the global ocean. The consistency between these two time series and the original International Comprehensive Ocean–Atmosphere Dataset version 2.5 (ICOADS 2.5) over the Mediterranean Sea is investigated, evaluating differences from monthly to multidecadal scales. From annual to longer time scales, the two time series consistently describe the same trends and multidecadal oscillations and agree with Mediterranean ICOADS SSTs. At monthly time scales the two time series are less consistent with each other because of the evident annual cycle that characterizes their difference. The subsequent analysis of the Mediterranean annual SST time series, based on lagged-correlation analysis, multitaper method (MTM), and singular spectral analysis (SSA), revealed the presence of a significant oscillation with a period of about 70 yr, very close to that of the Atlantic multidecadal oscillation (AMO). An extension of the analysis to other World Ocean regions confirmed that the predominance of this multidecadal signal with respect to longer period trends is a unique feature of the Mediterranean and North Atlantic Ocean, where it reaches its maximum at subpolar latitudes. Signatures of multidecadal oscillations are also found in the global SST time series after removing centennial and longer-term components. The analysis also reveals that Mediterranean SST and North Atlantic indices are significantly correlated and coherent for periods longer than about 40 yr. For time scales in the range 40–55 yr the coherence between the Mediterranean and subpolar gyre temperatures is higher than the coherence between the Mediterranean SST and North Atlantic Oscillation (NAO) or AMO. Finally, the results of the analysis are discussed in the light of possible climate mechanisms that can couple the Mediterranean Sea with the North Atlantic and the Global Ocean.

Climatologic comparison of HadISST1 and TMI sea surface temperature datasets

Two monthly datasets of sea surface temperature (SST), TMI SST retrieved from satellite observations by Remote Sensing System and HadISST1 (Hadley Centre Sea-ice and Sea-surface Temperature Data Set Version 1) derived from in situ measurements by Hadley Centre, were compared on climatologic multiple time scales over tropical and subtropical areas from 1998 to 2006. Results indicate that there is a good consistency in the horizontal global distribution, with 1.0° resolution on multi-year and multi-season mean scales between the two datasets, and also in the time series of global mean SST anomalies. However, there are still some significant differences between the datasets. Generally, TMI SST is relatively higher than Had-ISST1. In addition, the differences between the two datasets show not only remarkable regionality, but also distinct seasonal variations. Moreover, the maximum departure occurs in summer, while the minimum takes place in autumn. For all seasons, over 30% of the regions in the Tropical and Subtropical areas have a difference of more than 0.3°C. EOF analysis of the SST anomaly field also shows that there are differences between the two datasets, where HadISST1 has more significant statistical characteristics than TMI SST. On the other hand, results show that the difference between the two datasets is related to the vertical structure of ocean temperatures, as well as other simultaneously retrieved parameters in TMI products, such as wind speed, water vapor, liquid cloud water and rain rates. In addition, large biases between HadISST1 and TMI SST are found in coastal regions, where TMI SST cannot be accurately retrieved because of polluted microwave signals.

Intercomparison of historical sea surface temperature datasets

AbstractSeven historical sea surface temperature (SST) datasets are compared with each other: the Hadley Center sea ice and SST dataset (HadISST), version 1; the centennial in situ observation‐based estimate of SSTs (COBE); the extended reconstruction of global SST (ERSST), version 3; the optimal smoothing analysis by the Lamont‐Doherty Earth Observatory (LDEO); the monthly summaries of the International Comprehensive Ocean‐Atmosphere Data Set Release 2.1 (ICOADS); the second Hadley Center SST (HadSST); and SSTs by the authors at Tohoku University (TOHOKU). Differences in 30‐year climatologies and standard deviations of anomalies from the climatologies exist, especially in observation‐sparse areas and periods. Correlation among the datasets mainly depends on the number of observational data. Global means from all datasets are consistent with each other except for those from ICOADS. Signals of the El Niño/Southern Oscillation (ENSO) correlate highly with each other after 1880, although the durations and intensities of each event are different. Temporal variations of the Pacific Decadal Oscillation (PDO) correspond well after 1950, become gradually worse backward in time and are scattered before 1880. These differences are ascribed to the use of different interpolation methods for missing grids, treatments of satellite‐derived data, instrumental bias correction methods and other factors. Copyright © 2011 Royal Meteorological Society

The Pacific’s Response to Surface Heating in 130 Yr of SST: La Niña–like or El Niño–like?

Abstract Using a modified method of multiple linear regression on instrumented sea surface temperature (SST) in the two longest historical datasets [the Extended Reconstructed SST dataset (ERSST) and the Met Office Hadley Centre Sea Ice and SST dataset (HadISST)], it is found that the response to increased greenhouse forcing is a warm SST in the mid- to eastern Pacific Ocean in the equatorial region in the annual or seasonal mean. The warming is robustly statistically significant at the 95% confidence level. Consistent with this, the smaller radiative heating from solar forcing produces a weak warming also in this region, and the spatial pattern of the response is neither La Niña–like nor El Niño–like. It is noted that previous reports of a cold-tongue (La Niña–like) response to increased greenhouse or to solar-cycle heating were likely caused by contaminations due to the dominant mode of natural response in the equatorial Pacific. The present result has implications on whether the Walker circulation is weakened or strengthened in a warmer climate and on coupled atmosphere–ocean climate model validation.

Removing ENSO-Related Variations from the Climate Record

Abstract An important question in assessing twentieth-century climate change is to what extent have ENSO-related variations contributed to the observed trends. Isolating such contributions is challenging for several reasons, including ambiguities arising from how ENSO itself is defined. In particular, defining ENSO in terms of a single index and ENSO-related variations in terms of regressions on that index, as done in many previous studies, can lead to wrong conclusions. This paper argues that ENSO is best viewed not as a number but as an evolving dynamical process for this purpose. Specifically, ENSO is identified with the four dynamical eigenvectors of tropical SST evolution that are most important in the observed evolution of ENSO events. This definition is used to isolate the ENSO-related component of global SST variations on a month-by-month basis in the 136-yr (1871–2006) Hadley Centre Sea Ice and Sea Surface Temperature dataset (HadISST). The analysis shows that previously identified multidecadal variations in the Pacific, Indian, and Atlantic Oceans all have substantial ENSO components. The long-term warming trends over these oceans are also found to have appreciable ENSO components, in some instances up to 40% of the total trend. The ENSO-unrelated component of 5-yr average SST variations, obtained by removing the ENSO-related component, is interpreted as a combination of anthropogenic, naturally forced, and internally generated coherent multidecadal variations. The following two surprising aspects of these ENSO-unrelated variations are emphasized: 1) a strong cooling trend in the eastern equatorial Pacific Ocean and 2) a nearly zonally symmetric multidecadal tropical–extratropical seesaw that has amplified in recent decades. The latter has played a major role in modulating SSTs over the Indian Ocean.

A New Sea Surface Temperature and Sea Ice Boundary Dataset for the Community Atmosphere Model

Abstract A new surface boundary forcing dataset for uncoupled simulations with the Community Atmosphere Model is described. It is a merged product based on the monthly mean Hadley Centre sea ice and SST dataset version 1 (HadISST1) and version 2 of the National Oceanic and Atmospheric Administration (NOAA) weekly optimum interpolation (OI) SST analysis. These two source datasets were also used to supply ocean surface information to the 40-yr European Centre for Medium-Range Weather Forecasts Re-Analysis (ERA-40). The merged product provides monthly mean sea surface temperature and sea ice concentration data from 1870 to the present: it is updated monthly, and it is freely available for community use. The merging procedure was designed to take full advantage of the higher-resolution SST information inherent in the NOAA OI.v2 analysis.

Icelandic Coastal Sea Surface Temperature Records Constructed: Putting the Pulse on Air–Sea–Climate Interactions in the Northern North Atlantic. Part I: Comparison with HadISST1 Open-Ocean Surface Temperatures and Preliminary Analysis of Long-Term Patterns and Anomalies of SSTs around Iceland

Abstract A new comprehensive record of long-term Icelandic sea surface temperature measurements, which have been updated and filled in with reference to air temperature records, is presented. The new SST series reveal important features of the variability of climate in Iceland and the northern North Atlantic. This study documents site histories and possible resulting inconsistencies and biases, for example, changes in observing sites and instruments. A new 119-yr continuous time series for north Iceland SST is presented, which should prove particularly useful for investigating air–sea ice interactions around northern Iceland. As this is the only part of the country to be regularly engulfed by winter and/or spring sea ice, it is therefore highly sensitive to climatic change. The coastal series correlate well overall with independent Hadley Centre Sea Ice and SST dataset version 1 (HadISST1) series from the adjacent open ocean (mean r = 0.59), although correlations are generally higher in summer than winter and for south and east Iceland compared with the west and north. The seasonal temperature range is generally twice as large at the coastal sites because of differential effects of radiation, melting, mixing, and advection of warmer or colder air or water masses, as well as spatial resolution differences and smoothing in HadISST1. The long-term climatological averages and graphs for the 10 SST stations and/or their composites reveal decadal variations and trends that are generally similar to Icelandic air temperature records: a cold late-nineteenth-century, rapid warming around the 1920s, an overall warm peak circa 1940, cooling until an “icy” period circa 1970, followed by warming. Regional differences between sites include relatively greater (lesser) long-term variations for the eastern and southern (western and northern) Icelandic coasts, suggesting greater variability and influence of ocean current advection in the southeast. Moreover, Vestmannaeyjar SST data reveal that the late-nineteenth-century cold period in the ocean was not confined to the cold currents off north and east Iceland but also affected the south coast markedly. The Stykkishólmur, Iceland, SST record is relatively noisy and shows very little decadal variation, which may largely be due to fjord ice in cold winters suppressing low temperatures. It is anticipated that researchers may find these Icelandic SST series of practical use as a historic measure of air–sea–climate interactions around Iceland.

Assessing bias corrections in historical sea surface temperature using a climate model

AbstractAnalyses of simulations of variations in global and large‐regional land surface air temperature (LSAT) for 1872–1998 using the HadAM3 atmospheric general circulation model are reported. The analyses are designed to test the accuracy of bias corrections to sea‐surface temperature (SST) used in the Hadley Centre's global sea ice and SST (GISST3.1) data set, the more recent Hadley Centre sea ice and SST (HadISST) data set, and in the underlying Met Office historical SST (MOHSST and HadSST1) data sets. The tests are important because SST corrections considerably affect estimates of the magnitude of global warming since the late 19th century. Two ensembles of simulations were created using GISST3.1 as the lower boundary condition. The first ensemble, of six integrations, was forced using GISST with bias‐corrections applied from 1871 until 1941, and was continued with no bias corrections to 1998. A second ensemble of four integrations, for 1871 to 1941, was forced with uncorrected GISST data. Simulations with uncorrected GISST show a substantial and often highly significant cold bias in simulated global and large‐regional annual mean LSAT changes before 1942 relative to a 1946–65 reference period. By contrast, corrected SST data led to simulations of LSAT changes that are generally insignificantly different from those of observed LSAT in most regions before 1942. Tests on extratropical hemispheric scales generally validate the seasonal variation of the bias corrections, though less clearly before 1890 in some seasons. Issues about the quality of the LSAT data are raised by the results in a couple of regions. Over Australia, the model may have reconstructed LSAT changes using bias‐corrected GISST with greater accuracy than the observations before about 1910. © Crown Copyright 2005. Reproduced with the permission of Her Majesty's Stationery Office. Published by John Wiley & Sons, Ltd.