Periodicities in the time-series of the annual mean temperatures of Central England

ABSTRACT .Maximum Entropy spectral Analysis (MESA) of the 8IUlua1 mean temperature series for Central England for 1659-1991 indicated significant periodicilies at T = 7.8, 11.1, 12.5, 15, 18, 23, 32, 37, 68, 81, l09 and 203 years. These compare well with T = 22, 30, 80, 200 years obtained for China. Also, a good comparison is obtained with some periodicities in the sunspot number series.

SARIMA modeling of the monthly average maximum and minimum temperatures in the eastern plateau region of India

The SARIMA time series model is fitted to the monthly average maximum and minimum temperature data sets collected at Giridih, India for the years 1990-2011. From the time-series plots, we observe that the patterns of both the series are quite different; maximum temperature series contain sharp peaks in almost all the years while it is not true for the minimum temperature series and hence both the series are modeled separately (also for the sake of simplicity). SARIMA models are selected based on observing autocorrelation function (ACF) and partial autocorrelation function (PACF) of the monthly temperature series. The model parameters are obtained by using maximum likelihood method with the help of three tests [i.e., standard error, ACF and PACF of residuals and Akaike Information Criteria (AIC), Bayesian Information Criteria (BIC) and corrected Akaike Information Criteria (AICc)]. Adequacy of the selected models is determined using diagnostic checking with the standardized residuals, ACF of residuals, normal Q-Q plot of the standardized residuals and p-values of the Ljung-Box statistic. The models ARIMA (1; 0; 2) × (0; 1; 1)12 and ARIMA (0; 1; 1) × (1; 1; 1)12 are finally selected for forecasting of monthly average maximum and minimum temperature values respectively for the eastern plateau region of India.

Variability of The Minimum Temperature Over Two Centuries In The Overlap Region Between The Fringe of The Asian Westerly Region and The Temperate Continental-Monsoon Climate Transition Zone

The overlap region between the eastern fringe of the Asian westerly region and the temperate continental-monsoon climate transition zone is sensitive to climate changes and is characterized by fragile ecosystems. It is necessary to uncover the patterns of long-term historical climate variability there. A standardized tree-ring width chronology was constructed based on the tree-ring samples collected from four representative tree species in four typical areas in the overlap region, and the 203- to 343-year annual mean minimum temperature series in the overlap region were reconstructed. The reconstructed series overlapped well with extreme climate events and low-temperature periods recorded in historical data. Therefore, the reconstructed model is stable and reliable. As suggested by the reconstructed series, the variability of annual mean minimum temperature was increasingly drastic from east to west in the overlap region, with gradually shorter periodicities. In the 19th century, the high-latitude area was in the high-temperature period, and the entire overlap region experienced significant low-temperature periods lasting 20–45 years till the 1950s. The western part had an earlier start time of low-temperature periods, longer cooling duration, and slower cooling rate than the central part. The overlap region experienced a significant warming period in approximately the last half-century, with temperature increasing faster in the western and eastern parts than in the central part. The temperature variability in the overlap region was more intense in the last two centuries, with shorter periodicities and a larger proportion of cold periods. The central and western parts of the Asian westerly region, the mid- to high-latitude regions of the transition zone, and the overlap region saw significantly low-temperature periods or drastic cooling trends (the Little Ice Age) in the first half of the 19th century and significant warming trends under global warming afterwards. The influences of these changes might have been exacerbated by the westerly circulation. This study not only provides new insight into the use of dendroclimatology to extract temperature series in the Asian westerly region and the transition zone but also serves as a reference for research on global climate change.

Modelling long memory in maximum and minimum temperature series in India

Time series analysis of weather data can be a very valuable tool to investigate its variability pattern and, maybe, even to predict short- and long-term changes in the time series. In this study, the long memory behaviour of monthly minimum and maximum temperature of India for the period 1901 to 2007 by means of fractional integration techniques has been investigated. The results show that the time series can be specified in terms of autoregressive fractionally integrated moving average (ARFIMA) process. Both the series were found to be integrated with orders of integration smaller than 0.5 ensuring the long memory stationarity. Wavelet methodology in frequency domain with Haar wavelet filter was applied in order to see the oscillation at different scale and at different time epochs of the series. Multiresolution analysis (MRA) was carried out to explore the local as well as global variations in both the temperature series over the years. The variability in minimum temperature is found to be more than maximum temperature. Though there is no clear significance trend in the temperature series in the long run, but there are pockets of change in the temperature pattern. The predictive ability of ARFIMA model was investigated in terms of relative mean absolute percentage error.

Documentary-based climate reconstructions in the Czech Lands 1501–2020 CE and their European context

Annual and seasonal temperature, precipitation and drought index (SPI, SPEI, Z-index, PDSI) series covering the Czech Lands territory (now the Czech Republic) over 520 years (1501–2020 CE) reconstructed from documentary data combined with instrumental observations were analysed herein. The temperature series exhibits a statistically significant increasing trend, rising from ~1890 and particularly from the 1970s; 1991–2020 represents the warmest and driest 30-year period since 1501 CE. While the long-term precipitation total fluctuations (and derived SPI fluctuations) remain relatively stable with annual and decadal variabilities, past temperature increases are the key factor affecting recent increasing dryness in the SPEI, Z-index and PDSI series. The seasonal temperature series represent a broad European area, while the seasonal precipitation series show lower spatial correlations. A statistical attribution analysis conducted utilizing regression and wavelet techniques confirmed the influence of covariates related to volcanic activity (prompting temporary temperature decreases, especially during summer) and the North Atlantic Oscillation (influential in all seasons except summer) in the Czech climate reconstructions. Furthermore, components tied to multidecadal variabilities in the northern Atlantic and northern Pacific were identified in the temperature and precipitation series and in the drought indices, revealing notable shared oscillations, particularly at periods of approximately 70–100 years.

Development of a Quality-Controlled and Homogenised Long-Term Daily Maximum and Minimum Air Temperature Network Dataset for Ireland

Accurate long-term daily maximum and minimum air temperature series are needed to assess the frequency, intensity, distribution, and duration of extreme climatic events. However, quality control and homogenisation procedures are required to minimise errors and inhomogeneities in climate series before the commencement of climate data analysis. A semi-automatic quality control procedure consisting of climate consistency, internal consistency, day-to-day step-change, and persistency tests was applied for 12 long-term series registered in Ireland from 1831–1968, Armagh Observatory (Northern Ireland) from 1844–2018, and for 21 short-term series dating to the mid-19th century. There were 976,786 observations quality-controlled, and 27,854 (2.9%) values flagged. Of the flagged records, 98.5% (n = 27,446) were validated, 1.4% (n = 380) corrected and 0.1% (n = 28) deleted. The historical long-term quality-controlled series were merged with the modern series quality-controlled by Met Éireann and homogenised using the software MASHv3.03 in combination with station metadata for 1885–2018. The series presented better homogenisation outcomes when homogenised as part of smaller regional networks rather than as a national network. The homogenisation of daily, monthly, seasonal, and annual series improved for all stations, and the homogenised records showed stronger correlations with the Central England long-term temperature series.

Insights from 20 years of temperature parallel measurements in Mauritius around the turn of the 20^th Century

There is considerable import in creating more complete, better understood, holdings of early meteorological data. Such data permit an improved understanding of climate variability and long-term changes. Early records are particularly incomplete in the tropics, with implications for estimates of global and regional temperature. There is also a relatively low level of scientific understanding of how these measurements were made and, as a result, of their homogeneity and comparability to more modern techniques and measurements. Herein we describe and analyse a newly rescued set of long-term, up to six-way parallel measurements, undertaken over 1884–1903 in Mauritius, an island situated in the southern Indian Ocean. Data include: i) measurements from a well-ventilated room, ii) a shaded Thermograph; iii) instruments housed in a manner broadly equivalent to a modern Stevenson Screen; iv) a set of measurements by a Hygrometer mounted in a Stevenson Screen; and for a very much shorter period v) two additional Stevenson Screen configurations. All measurements were undertaken within roughly 80 metre radius. To our knowledge this is the first such multidecadal multi-instrument assessment of meteorological instrument transition impacts ever undertaken, providing potentially unique insights. The intercomparison also considers the impact of different ways of deriving daily and monthly averages. The long-term comparison is sufficient to robustly characterise systematic offsets between all the instruments and seasonally varying impacts. Differences between all techniques range from tenths of a degree Celsius to in excess of a degree Celsius and are considerably larger for maximum and minimum temperatures than for means or averages. Systematic differences of several tenths of a degree also exist for the different ways of deriving average / mean temperatures. All differences bar two average temperature series pairs are significant at the 0.01 level using a paired t-test. Given that all thermometers were regularly calibrated against a primary Kew standard thermometer this analysis highlights significant impacts of instrument exposure, housing, siting and measurement practices in early meteorological records. These results reaffirm the importance of thoroughly assessing the homogeneity of early meteorological records.