Surface Air Temperature Trends Research Articles

Effects of autumn-winter Arctic sea ice on winter Siberian High

The intensity of the winter Siberian High has significantly negative correlations with Arctic sea ice concentration anomalies from the previous autumn to winter seasons in the Eastern Arctic Ocean and Siberian marginal seas. Our results indicate that autumn-winter Arctic sea ice concentration and concurrent sea surface temperature anomalies are responsible for the winter Siberian High and surface air temperature anomalies over the mid-high latitudes of Eurasia and East Asia. Numerical experiments also support this conclusion, and consistently show that the low sea ice concentration causes negative surface air temperature anomalies over the mid-high latitudes of Eurasia. A mechanism is proposed to explain the association between autumn-winter sea ice concentration and winter Siberian High. Our results also show that September sea ice concentration provides a potential precursor for winter Siberian High that cannot be predicted using only tropical sea surface temperatures. In the last two decades (1990–2009), a strengthening trend of winter Siberian High along with a decline trend in surface air temperature in the mid-high latitudes of the Asian Continent have favored the recent frequent cold winters over East Asia. The reason for these short-term trends in winter Siberian High and surface air temperature are discussed.

Observed surface warming induced by urbanization in east China

[1] Monthly mean surface air temperature data from 463 meteorological stations, including those from the 1981–2007 ordinary and national basic reference surface stations in east China and from the National Centers for Environmental Prediction and National Center for Atmospheric Research (NCEP/NCAR) Reanalysis, are used to investigate the effect of rapid urbanization on temperature change. These stations are dynamically classified into six categories, namely, metropolis, large city, medium-sized city, small city, suburban, and rural, using satellite-measured nighttime light imagery and population census data. Both observation minus reanalysis (OMR) and urban minus rural (UMR) methods are utilized to detect surface air temperature change induced by urbanization. With objective and dynamic station classification, the observed and reanalyzed temperature changes over rural areas show good agreement, indicating that the reanalysis can effectively capture regional rural temperature trends. The trends of urban heat island (UHI) effects, determined using OMR and UMR approaches, are generally consistent and indicate that rapid urbanization has a significant influence on surface warming over east China. Overall, UHI effects contribute 24.2% to regional average warming trends. The strongest effect of urbanization on annual mean surface air temperature trends occurs over the metropolis and large city stations, with corresponding contributions of about 44% and 35% to total warming, respectively. The UHI trends are 0.398°C and 0.26°C decade−1. The most substantial UHI effect occurred after the early 2000s, implying a significant effect of rapid urbanization on surface air temperature change during this period.

Sea ice trends in the Antarctic and their relationship to surface air temperature during 1979–2009

Surface air temperature (SAT) from four reanalysis/analysis datasets are analyzed and compared with the observed SAT from 11 stations in the Antarctic. It is found that the SAT variation from Goddard Institute for Space Studies (GISS) is the best to represent the observed SAT. Then we use the sea ice concentration (SIC) data from satellite measurements, the SAT data from the GISS dataset and station observations to examine the trends and variations of sea ice and SAT in the Antarctic during 1979–2009. The Antarctic sea ice extent (SIE) shows an increased trend during 1979–2009, with a trend rate of 1.36 ± 0.43% per decade. Ensemble empirical mode decomposition analysis shows that the rate of the increased trend has been accelerating in the past decade. Antarctic SIE trend depends on the season, with the maximum increase occurring in autumn. If the relationship between SIC and GISS SAT trends is examined regionally, Antarctic SIC trends agree well with the local SAT trends in the most Antarctic regions. That is, Antarctic SIC and SAT show an inverse relationship: a cooling (warming) SAT trend is associated with an upward (downward) SIC trend. It is also concluded that the relationship between sea ice and SAT trends in the Antarctic should be examined regionally rather than integrally.

A Remote-Sensing Method of Selecting Reference Stations for Evaluating Urbanization Effect on Surface Air Temperature Trends

Abstract In the global lands, the bias of urbanization effects still exits in the surface air temperature series of many city weather stations to a certain extent. Reliable reference climate stations need to be selected for the detection and correction of the local manmade warming bias. The underlying image data of remote sensing retrieval is adopted in this study to obtain the spatial distribution of surface brightness temperature, and the surface air temperature reference stations are determined based on the locations of the weather stations in the remote sensing surface thermal fields. Among the 672 national reference climate stations and national basic weather stations of mainland China, for instance, 113 surface air temperature reference stations are selected for applying this method. Compared with the average surface air temperature series of the reference stations obtained by a more sophisticated method developed in China, this method is proven to be robust and applicable, and can be adopted for the evaluation and adjustment study on the urbanization bias of the currently used air temperature records of surface climate stations in the global lands.

Discriminating between climate observations in terms of their ability to improve an ensemble of climate predictions

In view of the cost and complexity of climate-observing systems, it is a matter of concern to know which measurements, by satellite or in situ, can best improve the accuracy and precision of long-term ensembles of climate projections. We follow a statistical procedure to evaluate the relative capabilities of a wide variety of observable data types for improving the accuracy and precision of an ensemble of Intergovernmental Panel on Climate Change (IPCC) models. Thirty-two data types are evaluated for their potential for improving a 50-y surface air temperature trend prediction with data from earlier periods, with an emphasis on 20y. Data types can be ordered in terms of their ability to increase the precision of a forecast. Results show that important conclusions can follow from this ordering. The small size of the IPCC model ensemble (20 members) creates uncertainties in these conclusions, which need to be substantiated with the larger ensembles expected in the future. But the larger issue of whether the methodology can provide useful answers is demonstrated.

Imposed and Neglected Uncertainty in the Global Average Surface Air Temperature Index

The statistical error model commonly applied to monthly surface station temperatures assumes a physically incomplete climatology that forces deterministic temperature trends to be interpreted as measurement errors. Large artefactual uncertainties are thereby imposed onto the global average surface air temperature record. To illustrate this problem, representative monthly and annual uncertainties were calculated using air temperature data sets from globally distributed surface climate stations, yielding ±2.7 C and ±6.3 C, respectively. Further, the magnitude uncertainty in the 1961–1990 global air temperature annual anomaly normal, entirely neglected until now, is found to be ±0.17 C. After combining magnitude uncertainty with the previously reported ±0.46 C lower limit of measurement error, the 1856–2004 global surface air temperature anomaly with its 95% confidence interval is 0.8±0.98 C, Thus, the global average surface air temperature trend is statistically indistinguishable from 0 C. Regulatory policies aimed at influencing global surface air temperature are not empirically justifiable.

The twentieth century contiguous US temperature changes indicated by daily data and higher statistical moments

The daily surface air temperature data are used to assess the climate changes of the contiguous United States during the period of 1901 to 2000. The assessment is made through the first four statistical moments of the daily maximum, minimum, and mean temperature anomalies, the linear trends of the moments, and the changes of the anomalies’ probability density functions. The results on the first moment, i.e., the mean, are compared with the existing ones in terms of intra-annual means and their linear trends. Our first moment results agree with known ones and demonstrate a decrease from the 1930s to the 1960s and an increase from the 1970s to 2000. The temperature fluctuation is the smallest in the 1960s among the decades from 1931 to 2000. The trends of the higher (second-, third- and fourth-order) moments of the mean, maximum, and minimum surface air temperatures are calculated for the periods 1901–2000, 1910–1945, 1946–1975, and 1976–2000. The results show a decreasing trend of the second- and third-order moments of all the temperatures. The fourth-order moments of the mean and maximum surface air temperatures have increasing trends, but that of the minimum surface air temperature has a decreasing trend. The seasonal histograms of the mean, maximum, and minimum surface air temperatures are calculated for the three periods 1910–1945, 1946–1975, and 1976–2000 for the stations which have the largest trend of maximum daily surface air temperature. An obvious change has been identified in the probability density functions. Among the changes of statistical parameters, the ones for the minimum temperature are larger than those for the maximum and mean temperatures.

Climate‐driven population dynamics of a North American freshwater fish, Ictalurus furcatus: inference from the mitochondrial control region sequence data

Abstract – Using the Bayesian coalescent methodology and mitochondrial control region sequence data, the present study reconstructs the dynamics of effective population size of a temperature‐driven seasonal migratory North American freshwater fish, Ictalurus furcatus, during the last glacial cycle. The trend in effective population size is directly associated with the trend in surface air temperature; it is inversely associated with the accumulation of ice sheets in North America during the contemporary period. The long‐term decrease in effective population size during the cold period followed by rebound during the warmer period could be explained by this species’ preference for relatively warmer temperatures for its optimal growth and survival.

Air temperature trends related to changes in atmospheric circulation in the wider area of Greece

Surface air temperature trends in the wider region of Greece during the period 1951–2007, related to atmospheric circulation, are examined in this work. A network of 31 meteorological stations in the Hellenic area and the Asia Minor coasts and National Centers for Environmental Prediction/National Center for Atmospheric Research (NCEP/NCAR) reanalysis datasets were used for this purpose. The NCEP/NCAR reanalysis datasets were created by assimilating climate observations from different sources including ships, satellites, ground stations, radiosonde observations and radar. The general purpose of conducting the reanalyses was to produce multiyear global state-of-the-art gridded representations of atmospheric states, generated by a constant model and a constant data assimilation system. The findings of the analysis show that the mean annual surface air temperature in the wider region of Greece exhibits a pronounced cooling trend from the beginning of the 1950s up to the mid-1970s. It then remained at low levels until the beginning of the 1990s, and then increased up to 2000, when a turning-point is clear although the temperature remained at high levels. The well-known atmospheric circulation indices of the wider region of Europe, namely the North Atlantic Oscillation Index (NAOI), the Mediterranean Oscillation Index (MOI) and the North Sea Caspian Pattern Index (NCPI), were used to investigate the relationship between surface air temperature and atmospheric circulation in this region of the Eastern Mediterranean. The surface air temperature is not correlated to the NAOI, while it is statistically significantly (95% confidence level (CL)) correlated to the MOI, but only during wintertime. On the contrary, good correlations, which are statistically significant (95% CL), appear between the NCPI and the surface air temperature during all seasons, but particularly in winter.

Propagation of linear surface air temperature trends into the terrestrial subsurface

Previous studies have tested the long‐term coupling between air and terrestrial subsurface temperatures working under the assumption that linear trends in surface air temperature should be equal to those measured at depth within the subsurface. A one‐dimensional model of heat conduction is used to show that surface trends are attenuated as a function of depth within conductive media on time scales of decades to centuries, therefore invalidating the above assumption given practical observational constraints. The model is forced with synthetic linear temperature trends as the time‐varying upper boundary condition; synthetic trends are either noise free or include additions of Gaussian noise at the annual time scale. It is shown that over a 1000 year period, propagating surface trends are progressively damped with depth in both noise‐free and noise‐added scenarios. Over shorter intervals, the relationship between surface and subsurface trends is more variable and is strongly impacted by annual variability (i.e., noise). Using output from the FOR1 millennial simulation of the GKSS ECHO‐G General Circulation Model as a more realistic surface forcing function for the conductive model, it is again demonstrated that surface trends are damped as a function of depth within the subsurface. Observational air and subsurface temperature data collected over 100 years in Armagh, Ireland, and 29 years in Fargo, North Dakota, are also analyzed and shown to have subsurface temperature trends that are not equal to the surface trend. While these conductive effects are correctly accounted for in inversions of borehole temperature profiles in paleoclimatic studies, they have not been considered in studies seeking to evaluate the long‐term coupling between air and subsurface temperatures by comparing trends in their measured time series. The presented results suggest that these effects must be considered and that a demonstrated trend equivalency in air and subsurface temperatures is inconclusive regarding their long‐term tracking.

Reconstruction of the 500-year ground surface temperature history of northern Awaji Island, southwest Japan, using a layered thermal property model

Changes in the ground surface temperature (GST), propagating underground, can be recorded as thermal perturbations to the background thermal field. This paper presents a forward model of conductive propagation of GST in a layered material model with uniform thermal properties in each layer and a series of step functions as GST history. This model, which is expressed using the same mathematical form of that for a uniform thermal property model with a series of step functions as GST history, calculates subsurface temperature perturbations that originate from the GST change by superimposing numerically solved solutions of the model with surface boundary condition of a unit function. Using this model, we reconstruct the recent 500-year GST history from borehole temperature data in northern Awaji Island, southwest Japan, by Bayesian inversion. The reconstructed GST history shows the onset of warming in the mid-18th century to the early 19th century and an increase of 1.1–1.3 K up to the mid-20th century. From the middle to late 20th century, the GST decreased by about 0.2 K. The GST change in the 20th century fits the trend of mean annual surface air temperature records in Kobe, opposite the coast of northern Awaji Island. The GST history in northern Awaji Island differs from that in Ulsan, in the southeastern Republic of Korea, which is located at the same latitude as northern Awaji Island. Differences of the GST histories of these regions most likely reflect differences in sea surface temperatures in these regions.

Increasing fall‐winter energy loss from the Arctic Ocean and its role in Arctic temperature amplification

Arctic surface temperatures have risen faster than the global average in recent decades, in part due to positive feedbacks associated with the rapidly diminishing sea ice cover. Counter‐intuitively, the Arctic warming has been strongest in late fall and early winter whilst sea ice reductions and the direct ice‐albedo feedback have been greatest in summer and early fall. To reconcile this, previous studies have hypothesized that fall/winter Arctic warming has been enhanced by increased oceanic heat loss but have not presented quantitative evidence. Here we show increases in heat transfer from the Arctic Ocean to the overlying atmosphere during October–January, 1989–2009. The trends in surface air temperature, sea ice concentration and the surface heat fluxes display remarkable spatial correspondence. The increased oceanic heat loss is likely a combination of the direct response to fall/winter sea ice loss, and the indirect response to summer sea ice loss and increased summer ocean heating.

Surface air temperature variability over India during 1901–2007, and its association with ENSO

Seasonal and annual trends in surface air temperature over India and 7 homogeneous regions (western Himalaya, northwest, north-central, northeast, east coast, west coast and interior peninsula) were assessed during 3 periods: 1901–2007, 1971–2007 and 1998–2007. Indian annual mean (average of maximum and minimum), maximum and minimum temperatures showed significant warming trends of 0.51, 0.72 and 0.27°C 100 yr–1, respectively, during the period 1901–2007. However, accelerated warming was observed in the recent period 1971–2007, mainly due to intense warming in the recent decade 1998–2007. Temperatures (mean, maximum and minimum) increased by about 0.2°C per decade for the period 1971–2007, with a much steeper increase in minimum temperature than maximum temperature. In the most recent decade, maximum temperature was significantly higher compared to the long-term (1901–2007) mean, with a stagnated trend during this period, whereas minimum temperature showed an increasing trend, almost equal to that observed during 1971–2007. On a seasonal scale, pronounced warming trends in mean temperature were observed in winter and monsoon seasons, and a significant influence of El Nino Southern Oscillation events on temperature anomalies during certain seasons across India was observed. The composites of maximum and minimum temperatures of El Nino years showed positive anomalies during monsoon, post-monsoon and subsequent year winter and pre-monsoon seasons. However, statistically significant positive anomalies were observed only during monsoon and post-monsoon seasons over large areas of the country. The composite temperature anomalies of La Nina years were almost opposite to El Nino composites: the negative temperature anomalies associated with La Nina events persisted from the current monsoon season to the subsequent year pre-monsoon season.

Spatio-temporal changes in surface air temperature in the region of the northern Antarctic Peninsula and south Shetland islands during 1950–2003

Time series of surface air temperature recorded at eight stations upon the northern Antarctic Peninsula and South Shetland Islands were analyzed for the period 1971–2000 (longer time series were analyzed for some of the stations). Erroneous values and inhomogeneities were searched for. After homogenization, missing data were replaced by interpolated values. Monthly, seasonal, and annual trends in surface air temperature were analyzed, and their statistical significance calculated. Spatial variability in surface air-temperature trends was determined and three distinct regions identified: a southern region (Vernadsky, Rothera), eastern region (Esperanza, Marambio), and northern region (Bellingshausen, Prat, Frei, O'Higgins).Different trends in temperature were obtained for the eastern and western coasts of the Antarctic Peninsula, despite the close vicinity of the stations. The surface air temperature on the northern coast (O'Higgins) and in the northern region shows the smallest changes in temperature. The lowest surface air temperature and greatest warming trends during 1971–2000 were recorded on the eastern coast (Marambio and Esperanza) in autumn. The analyses confirm a warming trend (except for spring) at some stations. The most pronounced increasing seasonal trend was found in winter (five stations), followed by autumn (three stations). This warming is probably related to changes in atmospheric circulation, the extent of sea ice, and ocean processes.

Twentieth Century Temperature Trends in Colorado’s San Juan Mountains

We examine trends in surface air temperature for the San Juan Mountain region in southwestern Colorado from 1895 to 2005. Observations from both National Weather Service (NWS) and Snow Telemetry (SNOTEL) sites are analyzed. Results show a net warming of 1 °C between 1895 and 2005. Most of this warming occurred between 1990 and 2005, when the region experienced rapid and secular increases in temperature. Between 1950 and 1985, there was a cooling trend in the region during which there were significant decreases in the maximum temperature (Tmax) and almost no trend in the minimum temperature (Tmin). This cooling trend appears to be, in part, associated with increases in atmospheric aerosols. Between 1990 and 2005, the large increases in temperature anomalies are strongly correlated at the NWS and SNOTEL sites. Annual increases in Tmax and Tmin are similar between 1990 and 2005; however, they generally show greater increases during summer and winter, respectively. Spatially, there are similar increases in Tmax and Tmin except in the central mountain region, where the increases in Tmin are larger and started earlier.

Pacific decadal oscillation hindcasts relevant to near-term climate prediction

Decadal-scale climate variations over the Pacific Ocean and its surroundings are strongly related to the so-called Pacific decadal oscillation (PDO) which is coherent with wintertime climate over North America and Asian monsoon, and have important impacts on marine ecosystems and fisheries. In a near-term climate prediction covering the period up to 2030, we require knowledge of the future state of internal variations in the climate system such as the PDO as well as the global warming signal. We perform sets of ensemble hindcast and forecast experiments using a coupled atmosphere-ocean climate model to examine the predictability of internal variations on decadal timescales, in addition to the response to external forcing due to changes in concentrations of greenhouse gases and aerosols, volcanic activity, and solar cycle variations. Our results highlight that an initialization of the upper-ocean state using historical observations is effective for successful hindcasts of the PDO and has a great impact on future predictions. Ensemble hindcasts for the 20th century demonstrate a predictive skill in the upper-ocean temperature over almost a decade, particularly around the Kuroshio-Oyashio extension (KOE) and subtropical oceanic frontal regions where the PDO signals are observed strongest. A negative tendency of the predicted PDO phase in the coming decade will enhance the rising trend in surface air-temperature (SAT) over east Asia and over the KOE region, and suppress it along the west coasts of North and South America and over the equatorial Pacific. This suppression will contribute to a slowing down of the global-mean SAT rise.

The Role of Long-Term Trends in Seasonal Predictions: Implication of Global Warming in the NCEP CFS

Abstract This paper analyzes long-term surface air temperature trends in a 25-yr (1982–2006) dataset of retrospective seasonal climate predictions made by the NCEP Climate Forecast System (CFS), a model that has its atmospheric greenhouse gases fixed at the 1988 concentration level. Although the CFS seasonal forecasts tend to follow the observed interannual variability very closely, there exists a noticeable time-dependent discrepancy between the CFS forecasts and observations, with a warm model bias before 1988 and a cold bias afterward except for a short-lived warm bias during 1992–94. The trend from warm to cold biases is likely caused by not including the observed increase in the anthropogenic greenhouse gases in the CFS, whereas the warm bias in 1992–94 reflects the absence of the anomalous aerosols released by the 1991 Mount Pinatubo eruption. Skill analysis of the CFS seasonal climate predictions with and without the warming trend suggests that the 1997–98 El Niño event contributes significantly to the record-breaking global warmth in 1998 whereas the record-breaking warm decade since 2000 is mainly due to the effects of the increased greenhouse gases. Implications for operational seasonal prediction will be discussed.

Tropical Pacific–high latitude south Atlantic teleconnections as seen in δ18O variability in Antarctic coastal ice cores

We use a network of eight ice cores from coastal Dronning Maud Land (DML), Antarctica, to examine the role of the tropical ENSO (El Niño‐Southern Oscillation) in the temporal variability of δ18O in annual accumulation. The longest record from the S100 ice core covering the period 1737–1999 is used to analyze the teleconnections between the tropical Pacific and coastal DML on decadal scales and longer. A shorter stacked coastal DML δ18O series spanning 1955–1999 is constructed to assess the variability of ENSO teleconnection on interannual scales. Results suggest that, on typical ENSO timescales of 2–6 years, the strength of the teleconnection varies in time, being stronger for years with generally negative phase of the Southern Annular Mode (SAM). On the timescales of approximately two decades (bidecadal), positive isotope anomalies are associated with oceanic warming and a westward sea surface temperature (SST) gradient in the equatorial Pacific. Bidecadal variability in SAM, forced by the tropical Pacific, is proposed as a critical element in the teleconnection. Our analysis suggests that a multidecadal positive trend in the annual mean δ18O values from the analyzed cores can be indicative of the atmospheric warming that begun in this part of the DML already in the 1910s. The trend in δ18O, quantified in terms of long‐term surface air temperature (SAT) changes, is consistent with the instrumental data. Yet, we speculate that the accurate estimation of SAT trends requires an assessment of the potential role of secular SAM and sea ice extent changes in shaping the isotopic signal.

Elevation dependency of recent and future minimum surface air temperature trends in the Tibetan Plateau and its surroundings

Elevation dependency of climate change signals has been found over major mountain ranges such as the European Alps and the Rockies, as well as over the Tibetan Plateau. In this study we examined the temporal trends in monthly mean minimum temperatures from 116 weather stations in the eastern Tibetan Plateau and its vicinity during 1961–2006. We also analyzed projected climate changes in the entire Tibetan Plateau and its surroundings from two sets of modeling experiments under future global warming conditions. These analyses included the output of the NCAR Community Climate System Model (CCSM3) with approximately 150 km horizontal resolution for the scenario of annual 1% increase in atmospheric CO 2 for future 100 years and physically-based downscaling results from the NCAR CAM3/CLM3 model at 10' × 10' resolution during three 20-year mean periods (1980–1999, 2030–2049 and 2080–2099) for the IPCC mid-range emission (A1B) scenario. We divided the 116 weather stations and the regional model grids into elevation zones of 500 m interval to examine the relationship of climatic warming and elevation. With these corroborating datasets, we were able to confirm the elevation dependency in monthly mean minimum temperature in and around the Tibetan Plateau. The warming is more prominent at higher elevations than at lower elevations, especially during winter and spring seasons, and such a tendency may continue in future climate change scenarios. The elevation dependency is most likely caused by the combined effects of cloud-radiation and snow-albedo feedbacks among various influencing factors.

Observations of northern latitude ground‐surface and surface‐air temperatures

Note that the magnitude of temperature increases reconstructed from borehole records seems to contrast with some proxy based reconstructions of surface air temperature (SAT) that indicate lower amounts of warming over the same period. We present data suggesting that ground and snow cover may bias climate reconstructions based on BT in portions of the Canadian northwest. Eight sites west of the Canadian cordillera, were examined for long‐term SAT and GST changes. At seven of these sites precise borehole temperature profiles are used for the first time since the 1960s, thereby exploring the linkage between GST and SAT. New readings were made at four of these locations. All sites showed significant increasing SAT trends, in terms of annual mean minimum and maximum temperatures. Over a 54 year period, the minimum temperatures increased between 1.1°C and 1.5°C while the maximum increased between 0.8°C and 1.5°C, among those eight stations. Observations of GST at those sites, however, showed no obvious climate induced perturbations. Therefore, we believe that a trend in our area towards an increase in SAT temperatures only over the winter and spring is being masked by freeze thaw and latent energy effects. These results are important, particularly in northern locations where ground and snow cover may play an important role in creating a seasonal bias in GST reconstructions from borehole surveys.