Surface Air Temperature Series Research Articles

Identifying natural contributions to late Holocene climate change

Analytic climate models have provided the means to predict potential impacts on future climate by anthropogenic changes in atmospheric composition. However, future climate development will not only be influenced by anthropogenic changes, but also by natural variations. The knowledge on such natural variations and their detailed character, however, still remains incomplete. Here we present a new technique to identify the character of natural climate variations, and from this, to produce testable forecast of future climate. By means of Fourier and wavelet analyses climate series are decomposed into time–frequency space, to extract information on periodic signals embedded in the data series and their amplitude and variation over time. We chose to exemplify the potential of this technique by analysing two climate series, the Svalbard (78°N) surface air temperature series 1912–2010, and the last 4000 years of the reconstructed GISP2 surface temperature series from central Greenland. By this we are able to identify several cyclic climate variations which appear persistent on the time scales investigated. Finally, we demonstrate how such persistent natural variations can be used for hindcasting and forecasting climate. Our main focus is on identifying the character (timing, period, amplitude) of such recurrent natural climate variations, but we also comment on the likely physical explanations for some of the identified cyclic climate variations. The causes of millennial climate changes remain poorly understood, and this issue remains important for understanding causes for natural climate variability over decadal- and decennial time scales. We argue that Fourier and wavelet approaches like ours may contribute towards improved understanding of the role of such recurrent natural climate variations in the future climate development.

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.

The role of changes in the annual cycle in earlier onset of climatic spring in northern China

Climatic changes in the onset of spring in northern China associated with changes in the annual cycle and with a recent warming trend were quantified using a recently developed adaptive data analysis tool, the Ensemble Empirical Mode Decomposition. The study was based on a homogenized daily surface air temperature (SAT) dataset for the period 1955–2003. The annual cycle here is referred to as a refined modulated annual cycle (MAC). The results show that spring at Beijing has arrived significantly earlier by about 2.98 d (10 yr)−1, of which about 1.85 d (10 yr)−1 is due to changes in the annual cycle and 1.13 d (10 yr)−1 due to the long-term warming trend. Variations in the MAC component explain about 92.5% of the total variance in the Beijing daily SAT series and could cause as much as a 20-day shift in the onset of spring from one year to another. The onset of spring has been advancing all over northern China, but more significant in the east than in the west part of the region. These differences are somehow unexplainable by the zonal pattern of the warming trend over the whole region, but can be explained by opposite changes in the spring phase of the MAC, i.e. advancing in the east while delaying in the west. In the east of northern China, the change in the spring phase of MAC explains 40%–60% of the spring onset trend and is attributable to a weakening Asian winter monsoon. The average sea level pressure in Siberia (55°–80°N, 50°–110°E), an index of the strength of the winter monsoon, could serve as a potential short-term predictor for the onset of spring in the east of northern China.

Comparative Analysis of China Surface Air Temperature Series for the Past 100 Years

Temperature change plays a crucial role in global change sciences. In the past several decades, comprehensive findings have been achieved on temperature change in China for the past 100 years. Several time series have been created to illustrate the averaged surface air temperature for the country. The correlations of these series range from 0.73 to 0.97. It is also achieved in better data quality, wider spatial data coverage, improved homogeneity of time series, and enhanced reliability of findings. The results show an annual mean temperature increase by 0.78±0.27°C per 100 years in China for the period 1906–2005. After prolonging the period till 2007, it is found that 2007 is rated as the warmest year in the past 100 years. Although all the series, except one, reflect temperature changes in the eastern part of China before the 1930s, they represent the general temperature change in most parts of the country after the 1930s. CitationTang, G., Y. Ding, S. Wang, et al., 2010: Comparative analysis of China surface air temperature series for the past 100 years. Adv. Clim. Change Res., 1, doi: 10.3724/SP.J.1248.2010.00011.

Statistical assessments of anthropogenic and natural global climate forcing. An update

In actualization of earlier papers we present a statistical analysis of anthropogenic and natural variance or signals, respectively, which can be detected in the observed global mean surface air temperature series 1860-2008 using multiple linear regression (MLR) and non-linear neural networks (NN). The forcing factors considered are greenhouse gases (GHG), tropospheric sulphate aerosols (SUL), solar activity, volcanism and ENSO (El Nino /southern oscillation). Thereby, a maximum total of explained variance of 88 % is reached by NN compared to 80 % by MLR. The related anthropogenic NN signals are 0.9-1.5 K warming due to GHG, 0.2-0.5 K cooling due to SUL and a combined (GHG+SUL) anthropogenic effect of 0.7-0.9 K warming. The natural signals have a magnitude of roughly 0.2 K. Moving MLR analysis shows that within recent decades the solar signal systematically decreased whereas the GHG signal increased to become a dominant factor of climate variability. Some test procedures address the confidence of the results and the sensitivity of the signals.

Forecasting estimates of surface air temperature changes by the wavelet transformation method

Analysis of a series of average annual surface air temperature (SAT) shows that they consist of three major components: a long-term trend, a set of harmonic components, and anomalies whose characters are close to a random process. We propose to use wavelet transformation of the source series to set aside quasi-periodic fluctuations. In this case, the distribution of the transformation coefficients enables one to set aside fluctuations of various scales, both the ones that are almost harmonic and those characterized as nonstationary fluctuation process. Then, forward extrapolation is performed by wavelet transformation coefficients for the set-aside scales in view of their temporal dynamics. The series’ fluctuation component is restored by inverse wavelet transformation. The proposed approach is demonstrated by the example of average annual SAT series registered by stations in the towns of Syktyvkar and Tomsk with an instrumental observation period of more than 100 years.

ARIMA representation for daily solar irradiance and surface air temperature time series

Autoregressive integrated moving average (ARIMA) models are used to compare long-range temporal variability of the total solar irradiance (TSI) at the top of the atmosphere (TOA) and surface air temperature series. The comparison shows that one and the same type of the model is applicable to represent the TSI and air temperature series. In terms of the model type surface air temperature imitates closely that for the TSI. This may mean that currently no other forcing to the climate system is capable to change the random walk type variability established by the varying activity of the rotating Sun. The result should inspire more detailed examination of the dependence of various climate series on short-range fluctuations of TSI.

Urbanization Effects on Observed Surface Air Temperature Trends in North China

Abstract A dataset of 282 meteorological stations including all of the ordinary and national basic/reference surface stations of north China is used to analyze the urbanization effect on surface air temperature trends. These stations are classified into rural, small city, medium city, large city, and metropolis based on the updated information of total population and specific station locations. The significance of urban warming effects on regional average temperature trends is estimated using monthly mean temperature series of the station group datasets, which undergo inhomogeneity adjustment. The authors found that the largest effect of urbanization on annual mean surface air temperature trends occurs for the large-city station group, with the urban warming being 0.16°C (10 yr)−1, and the effect is the smallest for the small-city station group with urban warming being only 0.07°C (10 yr)−1. A similar assessment is made for the dataset of national basic/reference stations, which has been widely used in regional climate change analyses in China. The results indicate that the regional average annual mean temperature series, as calculated using the data from the national basic/reference stations, is significantly impacted by urban warming, and the trend of urban warming is estimated to be 0.11°C (10 yr)−1. The contribution of urban warming to total annual mean surface air temperature change as estimated with the national basic/reference station dataset reaches 37.9%. It is therefore obvious that, in the current regional average surface air temperature series in north China, or probably in the country as a whole, there still remain large effects from urban warming. The urban warming bias for the regional average temperature anomaly series is corrected. After that, the increasing rate of the regional annual mean temperature is brought down from 0.29°C (10 yr)−1 to 0.18°C (10 yr)−1, and the total change in temperature approaches 0.72°C for the period analyzed.

Temporal Variability in Local Air Temperature Series Shows Negative Feedback

Long daily surface air temperature series from 24 European and Asian stations are analyzed, among them the Central England temperature dataset (1772 – 2005). The mean seasonal cycle in each series is removed and correlations between the consecutive increments of various increment intervals for the anomaly series are calculated. The sample correlations appear to behave similarly for all series. A positive coefficient between the short-term (daily etc) increments rapidly changes to the negative side while the increment interval increases. The value of the coefficient saturates at the level −0.5 and stays at that level for long range of intervals from 20 to 2000 days. The feature is a testimony to the regulating role of (cumulative) negative feedback in the climate system during the last two centuries.

Repeated temperature logs from Czech, Slovenian and Portuguese borehole climate observatories

Abstract. Two borehole climate observatories were established in Slovenia and Portugal within a joint Czech-Slovenian-Portuguese project in the years 2003-2005. Together with the older Czech observatory, which has been operating since the year 1994, they monitor air, soil and bedrock temperatures with the aim of studying air-ground coupling and the downward propagation of the surface temperature changes. We report here on repeated temperature logs carried out within 6 boreholes at the sites of the observatories and their surroundings within a time span of 8–20 years (1985–2005). The repeated logs revealed subsurface warming in all the boreholes amounting to 0.2–0.6°C below 20 m depth. The compatibility of the observed temporal changes of subsurface temperature with surface air temperature (SAT) series measured in Prague (since 1771), Ljubljana (since 1851) and Lisbon (since 1856) was checked by comparing repeated temperature logs with synthetic profiles that were calculated using SAT series as forcing functions. The depth of the Czech borehole (140 m) and the Portuguese borehole (180 m) was sufficient for a reconstruction of the ground surface temperature (GST) history of the last 150–200 years. Reconstructed GSTs were compared with the SAT series measured in Prague and Lisbon, respectively. The reconstructed histories reproduce reasonably well the amplitude of the recent warming inferred from the meteorological data, 1–1.5°C above the long-term mean. The depth (100 m) of the four repeatedly logged Slovenian boreholes was too shallow for inversion, but a climatic reconstruction was carried out for a deeper borehole, logged in 2006 and located within 5 km from the Slovenian observatory. The obtained GST history was compared with SAT series from Ljubljana.

Thermal log analysis for recognition of ground surface temperature change and water movements

Abstract. A joint analysis of surface air temperature series recorded at meteorological stations and temperature-depth profiles logged in nearby boreholes was performed to estimate conditions existing prior to the beginning of the instrumental record in central-northern Italy. The adopted method considers conductive and advective heat transport in a layered medium and provides simultaneous estimates of the pre-observational temperatures and the Darcy velocities. The reconstruction of the ground surface temperature history using a generalised least-squares inversion method was performed for boreholes where hydrological disturbances to measured temperature logs were proved negligible. Both methods revealed generally coherent climatic changes in the whole investigated area. Climatic conditions were generally warm and comparable with the reference period 1960–1990. The absence of the Little Ice Age seems to be a generic feature of the climate in central-northern Italy. Climate change of the 19th century was generally insignificant with well-balanced periods of cold and warmth. The investigated area became significantly colder only at the end of the 19th century. Cooling culminated around 1950 when it was replaced by rapid warming. Recent warming was not inferred only for one of the investigated holes.

Synchronization between the North Sea–Caspian pattern (NCP) and surface air temperatures in NCEP

AbstractIn this study, synchronous linkages of the North Sea–Caspian pattern (NCP), associated with large‐scale surface air temperature series selected from National Centers for Environmental Prediction–National Center of Atmospheric Research reanalysis (NCEP‐NCAR) for the region over 50°W–120°E and 0–80°N are investigated via teleconnection patterns based on phase synchronization. Phase synchronization is the process by which two or more cyclic systems (or subsystems) tend to oscillate with a repeating sequence of relative phase angles. Phase synchronization is usually applied to two waveforms of the same frequency with identical phase angles in each cycle. However, the notion of phase synchronization has been introduced as an extension of classical Huygens' synchronization in the case of interacting chaotic systems if there is an integer relationship of frequency, such that the cyclic systems share a repeating sequence of phase angles over consecutive cycles. The results of the phase synchronization method are compared with those of the classical cross‐correlation method in cases in which cross‐correlation method shows linear spatial cross‐dependency, but the phase synchronization yields nonlinear spatial phase dependency. In the analyses, teleconnection patterns derived from phase synchronization are first calculated for raw and de‐seasoned data (by removing periodic components in the surface air temperature series) in year‐month scale and then for the data in seasonal‐scale (namely, winter, spring, summer and autumn). Teleconnection patterns calculated by phase synchronization improve the experiential intra‐phase relationships between the NCP Index (NCPI) and large‐scale surface air temperature series, and ensures that the major modes of mid and high Northern Hemisphere variability in climate are characterized. Statistically significant phase synchronization patterns related to geopotential dipole heights of the NCPI extending over Greenland, the Balkans, Caspian Sea basin, eastern Mediterranean, Turkey and the Middle East, and further phase synchronization patterns over the circumpolar mode, which are utilized by phase interaction of Arctic oscillation (AO) with NCP, are obtained. In addition, significant phase synchronization patterns are also obtained over Tibetan plateau–Mongolia (Gobi Desert) interacting with the Siberian high, Asiatic monsoon and the intertropical convergence zone. Copyright © 2007 Royal Meteorological Society

Influence of climatic warming in the Southern and Northern Hemisphere on the tropical cyclone over the western North Pacific Ocean

Based on analyzing the surface air temperature series in the Southern and Northern Hemisphere and the tropical cyclone (TC) over the western North Pacific Ocean, the relationships between climatic warming and the frequency and intensity of tropical cyclone are investigated. The results showed that with the climatic warming in both hemispheres, the frequency of the tropical cyclone over the western North Pacific Ocean reduces and its intensity weakens simultaneously. A possible explanation might be that the cold air invasion from the Southern Hemisphere weakens due to global warming.

Borehole temperatures, climate change and the pre-observational surface air temperature mean: allowance for hydraulic conditions

Joint analysis of surface air temperature series recorded at weather stations together with the inversion of the temperature-depth profiles logged in the near-by boreholes enables an estimate of the conditions existing prior to the beginning of the meteorological observation, the so-called pre-observational mean (POM) temperature. Such analysis is based on the presumption of pure diffusive conditions in the underground. However, in real cases a certain subsurface fluid movement cannot be excluded and the measured temperature logs may contain an advective component. The paper addresses the correction for the hydraulic conditions, which may have perturbed the climate signal penetrating from the surface into the underground. The method accounts for vertical conductive and vertical advective heat transport in a 1-D horizontally layered stratum and provides a simultaneous evaluation of the POM-temperature together with the estimate of the Darcy fluid velocity. The correction strategy is illustrated on a synthetic example and its use is demonstrated on temperature logs measured in four closely spaced boreholes drilled near Tachlovice (located about 15 km SW of Prague, Czech Republic). The results revealed that in a case of moderately advectively affected subsurface conditions (fluid velocities about 10 −9 m/s), the difference between POM-values assessed for a pure conductive approach and for combined vertical conductive/advective approach may amount up to 0.3–0.5 K, the value comparable with the amount usually ascribed to the 20th century climate warming.

Detecting and adjusting temporal inhomogeneity in Chinese mean surface air temperature data

Adopting the Easterling-Peterson (EP) techniques and considering the reality of Chinese meteorological observations, this paper designed several tests and tested for inhomogeneities in all Chinese historical surface air temperature series from 1951 to 2001. The result shows that the time series have been widely impacted by inhomogeneities resulting from the relocation of stations and changes in local environment such as urbanization or some other factors. Among these factors, station relocations caused the largest magnitude of abrupt changes in the time series, and other factors also resulted in inhomogeneities to some extent. According to the amplitude of change of the difference series and the monthly distribution features of surface air temperatures, discontinuities identified by applying both the E-P technique and supported by China’s station history records, or by comparison with other approaches, have been adjusted. Based on the above processing, the most significant temporal inhomogeneities were eliminated, and China’s most homogeneous surface air temperature series has thus been created. Results show that the inhomogeneity testing captured well the most important change of the stations, and the adjusted dataset is more reliable than ever. This suggests that the adjusted temperature dataset has great value of decreasing the uncertaities in the study of observed climate change in China.

Daily dataset of 20th‐century surface air temperature and precipitation series for the European Climate Assessment

AbstractWe present a dataset of daily resolution climatic time series that has been compiled for the European Climate Assessment (ECA). As of December 2001, this ECA dataset comprises 199 series of minimum, maximum and/or daily mean temperature and 195 series of daily precipitation amount observed at meteorological stations in Europe and the Middle East. Almost all series cover the standard normal period 1961–90, and about 50% extends back to at least 1925. Part of the dataset (90%) is made available for climate research on CDROM and through the Internet (at http://www.knmi.nl/samenw/eca).A comparison of the ECA dataset with existing gridded datasets, having monthly resolution, shows that correlation coefficients between ECA stations and nearest land grid boxes between 1946 and 1999 are higher than 0.8 for 93% of the temperature series and for 51% of the precipitation series. The overall trends in the ECA dataset are of comparable magnitude to those in the gridded datasets.The potential of the ECA dataset for climate studies is demonstrated in two examples. In the first example, it is shown that the winter (October–March) warming in Europe in the 1976–99 period is accompanied by a positive trend in the number of warm‐spell days at most stations, but not by a negative trend in the number of cold‐spell days. Instead, the number of cold‐spell days increases over Europe. In the second example, it is shown for winter precipitation between 1946 and 1999 that positive trends in the mean amount per wet day prevail in areas that are getting drier and wetter.Because of its daily resolution, the ECA dataset enables a variety of empirical climate studies, including detailed analyses of changes in the occurrence of extremes in relation to changes in mean temperature and total precipitation. Copyright © 2002 Royal Meteorological Society.

Fluctuations of surface air temperature in the Eastern Mediterranean

Changes in surface air temperature during the last century are widely discussed among researchers in the field of climatic change. Using various techniques, we investigate trends and periodicity of surface air temperature series from eight meteorological stations in the Eastern Mediterranean. For the analysis, we use the Mann-Kendall rank test, low-pass filtering, autocorrelation spectral analysis and maximum entropy spectral analysis. The latter two tests are compared. The study is based on series over one hundred years in length for four stations, and over fifty years in length for the other four. Increasing and decreasing surface temperature trends were found. These trends, however, are only significant for Malta, Jerusalem, and Tripoli at the 99% confidence level (positive trend) and for Amman at the 95% confidence level (negative trend). We also found inter-decadal variations in surface air temperature, including a fairly regular quasi 20-year oscillation, although its amplitude varied between different cycles. A period of warming began around 1910 at all stations. During the 1970s, the annual mean temperature series exhibit warming, but this warming was not uniform, continuous or of the same order at all the stations. The results of the Autocorrelation Spectral Analysis and the Maximum Entropy Spectral Analysis are similar, pointing to the reliability of the results. The quasi-biennial oscillation (QBO) exists at all stations during both increasing and decreasing trends. Similarly, a broad maximum from 3–8 years (related to El Nino) is found at Malta, Athens, Jerusalem, Beirut, and Latakia. An inverse relationship between El Nino and the North Atlantic Oscillation with surface air temperature over the Eastern Mediterranean is found at a highly significant confidence level.

Recent Climate Warming: Surface Air Temperature Series and Geothermal Evidence

Long-term (1961 – 1996) meteorological air temperature series together with the reconstructed ground surface temperature histories, obtained by inverting borehole temperature-depth profiles, were used to project regional patterns of the recent (climate) warming rate on the territory of the Czech Republic. The characteristic magnitude of the warming rate of 0.02 –0.03 K/yr was confirmed by the results of several years of monitoring the temperature in two experimental boreholes. The monitoring of shallow temperatures at depths of about 30 –40 m, i.e. below the reach of the seasonal surface temperature variations, can serve as an alternative tool of direct quantitative assessment of the present warming rate. The data also seem to sustain a potential man-made component contributing to the more pronounced recent warming rate observed in the areas of large agglomeration.

A provisional long mean air temperature series for Armagh observatory

Two long mean surface air temperature series are presented for Armagh Observatory; one based on twice daily ‘spot’ temperature readings, 1796–1882, and the other on daily maximum and minimum temperatures, 1844–1992. Our data confirm the correlation of temperature with solar cycle length, first suggested by Friis-Christensen and Lassen ( Science 254, 698, 1991) and, for this site, extend their result a further 65 years, back to the end of the 18th century.

A possible long-term solar impact on air temperature in relation to solar motion

Using the long-term relations between solar motion and solar activity, long-term relations between solar activity and air temperature variations on the Earth's surface have been studied. A long-term periodicity in the period range from 25 to 250 years, corresponding to the periodicity of solar motion and solar activity, has been found in four very long European surface air temperature series. The positions of the spectral peaks approximately obey the relation pi=178.7/i, i=1, 2, ... . Similar long-term patterns of solar and geomagnetic activity and of global surface air temperature have been found in the years 1861 to 1990. The results indicate that the solar activity impact on the climate could be significant, and that the prolonged minimum of solar activity, predicted from solar motion for the next 2 – 3 decades, could decreace global air temperatures.