Historical Records

1996 ◽  
Author(s):  
Ilya Polyak
Keyword(s):  
Time Series ◽  
Normal Distribution ◽  
Air Temperature ◽  
Surface Air Temperature ◽  
Historical Records ◽  
Long Period ◽  
Climate Forecasting ◽  
Straight Line ◽  
Instrumental Observations ◽  
Climatic Time Series

In this chapter, the historical records of annual surface air temperature, pressure, and precipitation with the longest observational time series will be studied. The analysis of the statistically significant systematic variations, as well as random fluctuations of such records, provides important empirical information for climate change studies or for statistical modeling and long-range climate forecasting. Of course, compared with the possible temporal scales of climatic variations, the interval of instrumental observations of meteorological elements proves to be very small. For this reason, in spite of the great value of such records, they basically characterize the climatic features of a particular interval of instrumental observations, and only some statistics, obtained with their aid, can have more general meaning. Because each annual or monthly value of such records is obtained by averaging a large number of daily observations, the corresponding central limit theorem of the probability theory can guarantee their approximate normality. In spite of this, we computed the sample distribution functions for each time series analyzed below and evaluated their closeness to the normal distribution by the Kolmogorov- Smirnov criterion. As expected, the probability of the hypothesis that each of the climatic time series (annual or monthly) has a normal distribution is equal to one with three or four zeros after the decimal point. As seen in this section, the straight line least squares approximation of the climatic time series enables us to obtain very simple and easy-to-interpret information about the power of the long period climate variability. Carrying out such an approximation, we assume that the fluctuation with a period several times greater than the observational interval will become apparent as a gradual increase or decrease of the observed values. Using only a small sample, it is impossible to determine accurately the amplitude and frequency of such long-period climate fluctuation. Consequently, the straight-line model is the simplest approach in this case. Let us begin with an analysis of the annual surface air temperature time series, the observations of which are published in Bider et al., (1959), Bider and Schiiepp, (1961), Lebrijn (1954), Manlcy (1974), and in the World Weather Records (1975).

Assessment of urbanization effects in time series of surface air temperature over land

Nature ◽  
1990 ◽  
Vol 347 (6289) ◽  
pp. 169-172 ◽  
Author(s):  
P. D. Jones ◽  
P. Ya. Groisman ◽  
M. Coughlan ◽  
N. Plummer ◽  
W-C. Wang ◽  
...  
Keyword(s):  
Time Series ◽  
Air Temperature ◽  
Surface Air Temperature

scholarly journals A Technique to Detect Microclimatic Inhomogeneities in Historical Records of Screen-Level Air Temperature

2006 ◽  
Vol 19 (6) ◽  
pp. 959-978 ◽  
Author(s):  
K. E. Runnalls ◽  
T. R. Oke
Keyword(s):  
Time Series ◽  
Air Temperature ◽  
Weather Conditions ◽  
Historical Records ◽  
Vegetation Development ◽  
Environment Effects ◽  
Thermal Changes ◽  
Screen Level ◽  
Temperature Records

Abstract A new method to detect errors or biases in screen-level air temperature records at standard climate stations is developed and applied. It differs from other methods by being able to detect microclimatic inhomogeneities in time series. Such effects, often quite subtle, are due to alterations in the immediate environment of the station such as changes of vegetation, development (buildings, paving), irrigation, cropping, and even in the maintenance of the site and its instruments. In essence, the technique recognizes two facts: differences of thermal microclimate are enhanced at night, and taking the ratio of the nocturnal cooling at a pair of neighboring stations nullifies thermal changes that occur at larger-than-microclimatic scales. Such ratios are shown to be relatively insensitive to weather conditions. After transforming the time series using Hurst rescaling, which identifies long-term persistence in geophysical phenomena, cooling ratio records show distinct discontinuities, which, when compared against detailed station metadata records, are found to correspond to even minor changes in the station environment. Effects detected by this method are shown to escape detection by current generally accepted techniques. The existence of these microclimatic effects are a source of uncertainty in long-term temperature records, which is in addition to those presently recognized such as local and mesoscale urban development, deforestation, and irrigation.

scholarly journals Spatial and Temporal Distribution of Air Temperature in the Northern Hemisphere

2013 ◽  
Vol 6 (3) ◽  
pp. 177-182
Keyword(s):  
Time Series ◽  
20Th Century ◽  
Northern Hemisphere ◽  
Air Temperature ◽  
Temporal Distribution ◽  
Surface Air Temperature ◽  
Temperature Time Series ◽  
Mean Values ◽  
The Mean ◽  
Temperature Time

In the present study, the spatial and temporal surface air temperature variability for the Northern Hemisphere has been examined, for the period 1900-1996. Factor Analysis has been applied to 5o Latitude x 10o Longitude grid box data covering the area from almost the equator to 70o N. These data are anomalies of the mean annual air temperature from the respective mean values of the period 1961- 1990. The analysis showed that, mainly 20 regions were determined in the Northern Hemisphere with significantly covariant air temperature time series. The comparison of the trends of the mean annual surface air temperature time series of these regions, revealed such common characteristics as the minimum of the first decade of the 20th century and the recent years warming. The results of this study are also compared to the respective results of a former study in which data for the last half of the century (1948-1996) have been analyzed. The findings extracted indicate the stability of climate distribution in Northern Hemisphere during the 20th century.

scholarly journals Global air temperature variability independent of sea-surface temperature influences

2012 ◽  
Vol 37 (1) ◽  
pp. 29-35
Author(s):  
Andrew C. Comrie ◽  
Gregory J. McCabe
Keyword(s):  
Time Series ◽  
Surface Temperature ◽  
Sea Surface Temperature ◽  
Air Temperature ◽  
Recent Literature ◽  
Surface Air Temperature ◽  
Warming Trend ◽  
Sea Surface ◽  
Sst Variability ◽  
Global Surface

Mean global surface air temperature (SAT) and sea surface temperature (SST) display substantial variability on timescales ranging from annual to multi-decadal. We review the key recent literature on connections between global SAT and SST variability. Although individual ocean influences on SAT have been recognized, the combined contributions of worldwide SST variability on the global SAT signal have not been clearly identified in observed data. We analyze these relations using principal components of detrended SST, and find that removing the underlying combined annual, decadal, and multi-decadal SST variability from the SAT time series reveals a nearly monotonic global warming trend in SAT since about 1900.

scholarly journals Análise de dados climáticos usando transformada em ondeletas cruzada e coerência

2020 ◽  
Vol 13 (2) ◽  
pp. 641
Author(s):  
Roseilson Souza Vale ◽  
Raoni Aquino Santana ◽  
Cléo Queresma Dias Júnior
Keyword(s):  
Time Series ◽  
Air Temperature ◽  
Wavelet Coherence ◽  
Climate Data ◽  
Mathematical Relationship ◽  
Cross Wavelet Transform ◽  
Climatic Time Series ◽  
Wavelet Coherence Analysis ◽  
Temperature Time ◽  
Cross Wavelet

Este estudo mostra uma análise em transformada em ondeleta cruzada e coerência em ondeleta aplicada a duas séries temporais, sendo uma delas precipitação e a outra temperatura do ar. O objetivo deste estudo é mostrar que esta técnica é uma ferramenta poderosa na análise de séries temporais climáticas, para isso à aplicamos a duas séries com relação física muito conhecida na climatologia. Além da aplicação realizada, recorreu-se também a uma descrição matemática dos métodos. A técnica da transformada em ondeletas cruzada e coerência mostrou-se eficiente em capturar a relação matemática entre as séries de precipitação e temperatura do ar. Com este estudo esperamos difundir o uso desta técnica para fins de ensino e pesquisa em diversos sistemas geofísicos. Analysis of Climate Data Using Transformed Crosswave and Coherence A B S T R A C TThis study presents a cross wavelet transform and wavelet coherence analysis applied to a precipitation and an air temperature time series. The objective of this study is to demonstrate that this technique is a powerful tool in the analysis of climatic time series, and can be applied to two time series with very well-known physical relationships in terms of climatology. In addition to this application, a mathematical description of the methods was done. The cross-curves and coherence technique proved to be efficient in capturing the mathematical relationship between precipitation series and air temperature. With this study we hope to disseminate the use of this technique for teaching and research purposes in various geophysical systems.Keywords: Phase Angle, Wavelet Coherence, Cross wavelet, Precipitation, Temperature. 

scholarly journals Construction of a surface air temperature series for Qingdao in China for the period 1899 to 2014

2018 ◽  
Vol 10 (1) ◽  
pp. 643-652
Author(s):  
Yan Li ◽  
Birger Tinz ◽  
Hans von Storch ◽  
Qingyuan Wang ◽  
Qingliang Zhou ◽  
...  
Keyword(s):  
Time Series ◽  
Air Temperature ◽  
Surface Air Temperature ◽  
Warming Trend ◽  
Observation Data ◽  
China Meteorological Administration ◽  
Ascii Format ◽  
Long Term Trends ◽  
The City

Abstract. We present a homogenized surface air temperature (SAT) time series at 2 m height for the city of Qingdao in China from 1899 to 2014. This series is derived from three data sources: newly digitized and homogenized observations of the German National Meteorological Service from 1899 to 1913, homogenized observation data of the China Meteorological Administration (CMA) from 1961 to 2014 and a gridded dataset of Willmott and Matsuura (2012) in Delaware to fill the gap from 1914 to 1960. Based on this new series, long-term trends are described. The SAT in Qingdao has a significant warming trend of 0.11 ± 0.03 ∘C decade−1 during 1899–2014. The coldest period occurred during 1909–1918 and the warmest period occurred during 1999–2008. For the seasonal mean SAT, the most significant warming can be found in spring, followed by winter. The homogenized time series of Qingdao is provided and archived by the Deutscher Wetterdienst (DWD) web page under overseas stations of the Deutsche Seewarte (http://www.dwd.de/EN/ourservices/overseas_stations/ueberseedoku/doi_qingdao.html) in ASCII format. Users can also freely obtain a short description of the data at https://doi.org/https://dx.doi.org/10.5676/DWD/Qing_v1. And the data can be downloaded at http://dwd.de/EN/ourservices/overseas_stations/ueberseedoku/data_qingdao.txt.

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