scholarly journals Is the Last Years Abrupt Warming in the National Observatory of Athens Records a Climate Change Manifestation?

2013 ◽  
Vol 9 (2) ◽  
pp. 107-116
Keyword(s):  
Time Series ◽  
Air Temperature ◽  
Eastern Mediterranean ◽  
National Observatory ◽  
Urban Effect ◽  
Long Term Trends ◽  
Temperature Records ◽  
The 19Th Century ◽  
Temperature Time

Instrumental data time series show an average global warming of approximately 0.90C over the last century. Eastern Mediterranean air temperature follows the northern hemisphere (NH) secular trend till 1970s, while the NH warming of the last 30 years is not noticeable in the eastern Mediterranean till 1990s. National Observatory of Athens (NOA) meteorological time series start from the last decades of the 19th Century, therefore are at first suitable for detection of long term trends in the region. In this study we investigate whether the abrupt increase of the NOA air temperature time series, which appears during the last few years, is the finger-print of the broader scale climatic change or it is a discontinuity in the record of urban effect or of station’s problems origin. It is shown that NOA air temperature records display a statistically significant discontinuity attributable to change of the station thermometers on 1995 and therefore NOA records must be treated with caution for long term air temperature trends detection.

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 Changepoint Detection in Climate Time Series with Long-Term Trends

2013 ◽  
Vol 26 (14) ◽  
pp. 4994-5006 ◽  
Author(s):  
Colin Gallagher ◽  
Robert Lund ◽  
Michael Robbins
Keyword(s):  
Time Series ◽  
Mean Shift ◽  
Asymptotic Properties ◽  
Erroneous Conclusion ◽  
Test Application ◽  
Long Term Trends ◽  
Temperature Records ◽  
Climate Time Series ◽  
Two Temperature

Abstract Climate time series often have artificial shifts induced by instrumentation changes, station relocations, observer changes, etc. Climate time series also often exhibit long-term trends. Much of the recent literature has focused on identifying the structural breakpoint time(s) of climate time series—the so-called changepoint problem. Unfortunately, application of rudimentary mean-shift changepoint tests to scenarios with trends often leads to the erroneous conclusion that a mean shift occurred near the series' center. This paper examines this problem in detail, constructing some simple homogeneity tests for series with trends. The asymptotic distribution of the proposed statistic is derived; en route, an attempt is made to unify the asymptotic properties of the changepoint methods used in today's climate literature. The tests presented here are linked to the ubiquitous t test. Application is made to two temperature records: 1) the continental United States record and 2) a local record from Jacksonville, Illinois.

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.

Statistical analysis of long-term trends in UK effective rainfall: implications for deep-seated landsliding

2020 ◽  
Vol 53 (4) ◽  
pp. 587-597
Author(s):  
E.M. Lee
Keyword(s):  
Time Series ◽  
Statistical Test ◽  
Positive Trend ◽  
Effective Rainfall ◽  
Significant Spatial Variation ◽  
Long Term Trends ◽  
Temperature Records ◽  
Parametric Statistical Test ◽  
The Uk

Rainfall and its impact on the water content of a slope are known to be important controls on landslide activity in the UK. This paper presents an analysis of long-term monthly rainfall and temperature records from selected stations throughout the UK, including the application of a non-parametric statistical test to evaluate the significance of any trends in these time series. The results indicate that there is significant spatial variation in the long-term trends. A positive trend of increasing effective rainfall (precipitation minus evapotranspiration) is present at some (but not all) Scottish stations (Eskdalemuir, Lerwick, Paisley, Stornoway and Tiree), but is not present across the rest of the UK.

scholarly journals Maps, trends, and temperature sensitivities—phenological information from and for decreasing numbers of volunteer observers

2021 ◽  
Author(s):  
Ye Yuan ◽  
Stefan Härer ◽  
Tobias Ottenheym ◽  
Gourav Misra ◽  
Alissa Lüpke ◽  
...  
Keyword(s):  
Climate Change ◽  
Time Series ◽  
Strong Decrease ◽  
Temperature Changes ◽  
Interpolation Accuracy ◽  
Observation Network ◽  
Shiny App ◽  
Long Term Trends ◽  
Autumn And Winter

AbstractPhenology serves as a major indicator of ongoing climate change. Long-term phenological observations are critically important for tracking and communicating these changes. The phenological observation network across Germany is operated by the National Meteorological Service with a major contribution from volunteering activities. However, the number of observers has strongly decreased for the last decades, possibly resulting in increasing uncertainties when extracting reliable phenological information from map interpolation. We studied uncertainties in interpolated maps from decreasing phenological records, by comparing long-term trends based on grid-based interpolated and station-wise observed time series, as well as their correlations with temperature. Interpolated maps in spring were characterized by the largest spatial variabilities across Bavaria, Germany, with respective lowest interpolated uncertainties. Long-term phenological trends for both interpolations and observations exhibited mean advances of −0.2 to −0.3 days year−1 for spring and summer, while late autumn and winter showed a delay of around 0.1 days year−1. Throughout the year, temperature sensitivities were consistently stronger for interpolated time series than observations. Such a better representation of regional phenology by interpolation was equally supported by satellite-derived phenological indices. Nevertheless, simulation of observer numbers indicated that a decline to less than 40% leads to a strong decrease in interpolation accuracy. To better understand the risk of declining phenological observations and to motivate volunteer observers, a Shiny app is proposed to visualize spatial and temporal phenological patterns across Bavaria and their links to climate change–induced temperature changes.

Mercury trends and cycling in northern Wisconsin related to atmospheric and hydrologic processes

2019 ◽  
Vol 76 (5) ◽  
pp. 831-846 ◽  
Author(s):  
C.J. Watras ◽  
D. Grande ◽  
A.W. Latzka ◽  
L.S. Tate
Keyword(s):  
Time Series ◽  
Water Cycle ◽  
Water Levels ◽  
Hydrologic Processes ◽  
Littoral Sediments ◽  
Long Term Trends ◽  
Acid Base Status ◽  
Explanatory Mechanism ◽  
Regional Water

Atmospheric deposition is the principal source of mercury (Hg) to remote northern landscapes, but its fate depends on multiple factors and internal feedbacks. Here we document long-term trends and cycles of Hg in the air, precipitation, surface water, and fish of northern Wisconsin that span the past three decades, and we investigate relationships to atmospheric processes and other variables, especially the regional water cycle. Consistent with declining emission inventories, there was evidence of declining trends in these time series, but the time series for Hg in some lakes and most fish were dominated by a near-decadal oscillation that tracked the regional oscillation of water levels. Concentrations of important solutes (SO4, dissolved organic carbon) and the acid–base status of lake water also tracked water levels in ways that cannot be attributed to simple dilution or concentration. The explanatory mechanism is analogous to the “reservoir effect” wherein littoral sediments are periodically exposed and reflooded, altering the internal cycles of sulfur, carbon, and mercury. These climatically driven, near-decadal oscillations confound short or sparse time series and complicate relationships among Hg emissions, deposition, and bioaccumulation.

Warming is Driving Decreases in Snow Fractions While Runoff Efficiency Remains Mostly Unchanged in Snow-Covered Areas of the Western United States

2018 ◽  
Vol 19 (5) ◽  
pp. 803-814 ◽  
Author(s):  
Gregory J. McCabe ◽  
David M. Wolock ◽  
Melissa Valentin
Keyword(s):  
United States ◽  
Time Series ◽  
Winter Precipitation ◽  
Western United States ◽  
Balance Model ◽  
Winter Temperatures ◽  
Long Term Trends ◽  
Monthly Water Balance ◽  
Surface Water Supply

Abstract Winter snowfall and accumulation is an important component of the surface water supply in the western United States. In these areas, increasing winter temperatures T associated with global warming can influence the amount of winter precipitation P that falls as snow S. In this study we examine long-term trends in the fraction of winter P that falls as S (Sfrac) for 175 hydrologic units (HUs) in snow-covered areas of the western United States for the period 1951–2014. Because S is a substantial contributor to runoff R across most of the western United States, we also examine long-term trends in water-year runoff efficiency [computed as water-year R/water-year P (Reff)] for the same 175 HUs. In that most S records are short in length, we use model-simulated S and R from a monthly water balance model. Results for Sfrac indicate long-term negative trends for most of the 175 HUs, with negative trends for 139 (~79%) of the HUs being statistically significant at a 95% confidence level (p = 0.05). Additionally, results indicate that the long-term negative trends in Sfrac have been largely driven by increases in T. In contrast, time series of Reff for the 175 HUs indicate a mix of positive and negative long-term trends, with few trends being statistically significant (at p = 0.05). Although there has been a notable shift in the timing of R to earlier in the year for most HUs, there have not been substantial decreases in water-year R for the 175 HUs.

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