scholarly journals A History of Open Weather in New Zealand (HOWNZ): an open access 1-km resolution monthly 1910–2019 time-series of interpolated temperature and rainfall grids with associated uncertainty

2021 ◽  
Author(s):  
Thomas R. Etherington ◽  
George L. W. Perry ◽  
Janet M. Wilmshurst
Keyword(s):  
Time Series ◽  
New Zealand ◽  
Air Temperature ◽  
Temporal Trends ◽  
Spatial Uncertainty ◽  
Daily Maximum ◽  
Long Time ◽  
Ecological Patterns ◽  
History Of ◽  
Patterns And Processes

Abstract. Long time-series of weather grids are fundamental to understanding how weather affects environmental or ecological patterns and processes such as plant distributions, plant and animal phenology, wildfires, and hydrology. Ideally such weather grids should be openly available and be associated with uncertainties so that users can understand any data quality issues. We present a History of Open Weather in New Zealand (HOWNZ) that uses climatological aided natural neighbour interpolation to provide monthly 1-km resolution grids of total rainfall, mean air temperature, mean daily maximum air temperature, and mean daily minimum air temperature across New Zealand from 1910 to 2019. HOWNZ matches the best available temporal extent and spatial resolution of any open weather grids that include New Zealand, and is unique in providing associated spatial uncertainty in appropriate units of measurement. The HOWNZ weather and uncertainty grids capture the dynamic spatial and temporal nature of the monthly weather variables and the uncertainty associated with the interpolation. We also demonstrate how to quantify and visualise temporal trends across New Zealand that recognise the temporal and spatial variation of uncertainties in the HOWNZ data. The HOWNZ data is openly available at https://doi.org/10.7931/zmvz-xf30 (Etherington et al., 2021).

A Time-Varying Causality Formalism Based on the Liang–Kleeman Information Flow for Analyzing Directed Interactions in Nonstationary Climate Systems

2019 ◽  
Vol 32 (21) ◽  
pp. 7521-7537 ◽  
Author(s):  
Daniel Fiifi Tawia Hagan ◽  
Guojie Wang ◽  
X. San Liang ◽  
Han A. J. Dolman
Keyword(s):  
Time Series ◽  
Soil Moisture ◽  
Information Flow ◽  
Air Temperature ◽  
Land Surface ◽  
Full Range ◽  
Accurate Estimation ◽  
Time Varying ◽  
Long Time Series ◽  
Long Time

Abstract The interaction between the land surface and the atmosphere is of significant importance in the climate system because it is a key driver of the exchanges of energy and water. Several important relations to heat waves, floods, and droughts exist that are based on the interaction of soil moisture and, for instance, air temperature and humidity. Our ability to separate the elements of this coupling, identify the exact locations where they are strongest, and quantify their strengths is, therefore, of paramount importance to their predictability. A recent rigorous causality formalism based on the Liang–Kleeman (LK) information flow theory has been shown, both theoretically and in real-world applications, to have the necessary asymmetry to infer the directionality and magnitude within geophysical interactions. However, the formalism assumes stationarity in time, whereas the interactions within the land surface and atmosphere are generally nonstationary; furthermore, it requires a sufficiently long time series to ensure statistical sufficiency. In this study, we remedy this difficulty by using the square root Kalman filter to estimate the causality based on the LK formalism to derive a time-varying form. Results show that the new formalism has similar properties compared to its time-invariant form. It is shown that it is also able to capture the time-varying causality structure within soil moisture–air temperature coupling. An advantage is that it does not require very long time series to make an accurate estimation. Applying a wavelet transform to the results also reveals the full range of temporal scales of the interactions.

scholarly journals The five million bird eggs in the world’s museum collections are an invaluable and underused resource

The Auk ◽  
2020 ◽  
Vol 137 (4) ◽  
Author(s):  
Miguel Ângelo Marini ◽  
Linnea Hall ◽  
John Bates ◽  
Frank D Steinheimer ◽  
Robert McGowan ◽  
...  
Keyword(s):  
Time Series ◽  
Scientific Community ◽  
Recent Literature ◽  
Spatial Scales ◽  
Museum Collections ◽  
Scientific Disciplines ◽  
Bird Eggs ◽  
Long Time ◽  
History Of ◽  
Avian Biology

Abstract The ~1.97 million egg sets (~5 million eggs) housed in museums have not been used in proportion to their availability. We highlight the wide variety of scientific disciplines that have used egg collections and the geographic locations and sizes of these collections, to increase awareness of the importance of egg collections, improve their visibility to the scientific community, and suggest that they offer a wealth of data covering large spatial scales and long time series for broad investigations into avian biology. We provide a brief history of egg collections and an updated list of museums/institutions with egg collections worldwide. We also review the limitations, challenges, and management of egg collections, and summarize recent literature based on historical and recent museum egg materials.

scholarly journals Analyses of the Zagreb Grič observatory air temperatures indices for the period 1881 to 2017

2018 ◽  
pp. 67-85 ◽  
Author(s):  
Ognjen Bonacci ◽  
Tanja Roje Bonacci
Keyword(s):  
Time Series ◽  
Air Temperature ◽  
Partial Sums ◽  
Daily Maximum ◽  
Absolute Maximum ◽  
Absolute Minimum ◽  
Air Temperatures ◽  
Temperature Regimes ◽  
Urban Heat ◽  
Maximum Temperatures

The paper studies time series of characteristic (minimum, mean, and maximum) daily, monthly, and yearly air temperatures measured at the Zagreb Grič Observatory in the period from 1 Jan. 1881 to 31 Dec. 2017. The following five air temperatures indices (ATI) are analysed: (1) absolute minimum yearly, monthly, and daily; (2) mean yearly, monthly, and daily minimum; (3) average mean yearly, monthly, and daily; (4) mean yearly, monthly, and daily maximum; (5) absolute maximum yearly, monthly, and daily. Methods of Rescaled Adjusted Partial Sums (RAPS), regression and correlation analyses, F-tests, and t-tests are used in order to describe changes in air temperature regimes over 137 years. Using the RAPS method the five analysed yearly ATI time series durations of 137 years were divided into two sub-periods. The analyses made in this paper showed that warming of minimum air temperatures started in 1970, mean air temperatures in 1988, and maximum air temperatures in 1998. Results of t-tests show an extreme statistically significant jump in the average air-temperature values in the second (recent time) sub-periods. Results of the t-tests of monthly temperatures show statistically significant differences between practically all five pairs (except in two cases) of analysed monthly ATI subseries for the period from January to August. From September to December the differences for most of pairs (except in six cases) of the analysed monthly ATI subseries are not statistically significant. It can be concluded that the urban heat island influenced the increase in recent temperatures more strongly than global warming. It seems that urbanisation firstly and chiefly influenced the minimum temperatures, as well as that Zagreb’s urbanisation had a bigger impact on minimum temperatures than on maximums. Increasing trend in time series of maximum temperatures started 20 years later.

Distribution of Self-Reported Alcohol Consumption in New Zealand, 1978–1979

1980 ◽  
Vol 47 (1) ◽  
pp. 159-170 ◽  
Author(s):  
Robert A. M. Gregson ◽  
Barrie G. Stacey
Keyword(s):  
Time Series ◽  
New Zealand ◽  
Alcohol Consumption ◽  
Frequency Distribution ◽  
National Survey ◽  
Recent History ◽  
Normal Frequency ◽  
Total Alcohol ◽  
History Of ◽  
Log Normal

The problem of estimating how much alcohol individuals actually drink is discussed with particular reference to the log-normal frequency distribution of alcohol consumption. It is then presented as being a problem of inference from the recent history of a time series. Following directly from this presentation, data obtained in a national survey of 10,000 New Zealand residents are analyzed (a) to yield the frequency distribution of estimated drinking rates; (b) to test whether this distribution is log-normal in form; and (c) to provide further information about the distribution of alcohol consumption. This analysis enabled us to account for almost the whole of the actual total alcohol consumption in New Zealand. The results are different from those expected on the basis of the uncorrected log-normal description of consumption.

scholarly journals Stratospheric NO2variations from a long time series at Lauder, New Zealand

2000 ◽  
Vol 105 (D9) ◽  
pp. 11633-11640 ◽  
Author(s):  
J. B. Liley ◽  
P. V. Johnston ◽  
R. L. McKenzie ◽  
A. J. Thomas ◽  
I. S. Boyd
Keyword(s):  
Time Series ◽  
New Zealand ◽  
Long Time Series ◽  
Long Time

scholarly journals Construction of homogenized daily surface air temperature for the city of Tianjin during 1887–2019

2021 ◽  
Vol 13 (5) ◽  
pp. 2211-2226
Author(s):  
Peng Si ◽  
Qingxiang Li ◽  
Phil Jones
Keyword(s):  
Time Series ◽  
Air Temperature ◽  
Minimum Temperature ◽  
Surface Air Temperature ◽  
Warming Trend ◽  
Research Unit ◽  
Climatic Research Unit ◽  
Daily Maximum ◽  
Tianjin City ◽  
Monthly Journal

Abstract. Century-long continuous daily observations from some stations are important for the study of long-term trends and extreme climate events in the past. In this paper, three daily data sources – (1) the Department of Industry Agency of the British Concession in Tianjin covering 1 September 1890–31 December 1931, (2) the Water Conservancy Commission of North China covering 1 January 1932–31 December 1950 and (3) monthly journal sheets for Tianjin surface meteorological observation records covering 1 January 1951–31 December 2019 – have been collected from the Tianjin Meteorological Archive. The completed daily maximum and minimum temperature series for Tianjin from 1 January 1887 (1 September 1890 for minimum) to 31 December 2019 has been constructed and assessed for quality control with an early extension from 1890 back to 1887. Several significant breakpoints are detected by the penalized maximal T test (PMT) for the daily maximum and minimum time series using multiple reference series around Tianjin from monthly Berkeley Earth (BE), Climatic Research Unit Time-Series version 4.03 (CRU TS4.03) and Global Historical Climatology Network (GHCN) v3 data. Using neighboring daily series the record has been homogenized with quantile matching (QM) adjustments. Based on the homogenized dataset, the warming trend in annual mean temperature in Tianjin averaged from the newly constructed daily maximum and minimum temperature is evaluated as 0.154 ± 0.013 ∘C per decade during the last 130 years. Trends of temperature extremes in Tianjin are all significant at the 5 % level and have much more coincident change than those from the raw data, with amplitudes of −1.454, 1.196, −0.140 and 0.975 d per decade for cold nights (TN10p), warm nights (TN90p), cold days (TX10p) and warm days (TX90p) at the annual scale. The adjusted daily maximum, minimum and mean surface air temperature dataset for Tianjin city presented here is publicly available at https://doi.org/10.1594/PANGAEA.924561 (Si and Li, 2020).

scholarly journals Excess deaths associated with covid-19 pandemic in 2020: age and sex disaggregated time series analysis in 29 high income countries

BMJ ◽  
2021 ◽  
pp. n1137 ◽  
Author(s):  
Nazrul Islam ◽  
Vladimir M Shkolnikov ◽  
Rolando J Acosta ◽  
Ilya Klimkin ◽  
Ichiro Kawachi ◽  
...  
Keyword(s):  
Time Series ◽  
New Zealand ◽  
Temporal Trends ◽  
High Income ◽  
Mortality Data ◽  
Death Rates ◽  
Excess Death ◽  
England And Wales ◽  
Age And Sex ◽  
Excess Deaths

Abstract Objective To estimate the direct and indirect effects of the covid-19 pandemic on mortality in 2020 in 29 high income countries with reliable and complete age and sex disaggregated mortality data. Design Time series study of high income countries. Setting Austria, Belgium, Czech Republic, Denmark, England and Wales, Estonia, Finland, France, Germany, Greece, Hungary, Israel, Italy, Latvia, Lithuania, the Netherlands, New Zealand, Northern Ireland, Norway, Poland, Portugal, Scotland, Slovakia, Slovenia, South Korea, Spain, Sweden, Switzerland, and United States. Participants Mortality data from the Short-term Mortality Fluctuations data series of the Human Mortality Database for 2016-20, harmonised and disaggregated by age and sex. Interventions Covid-19 pandemic and associated policy measures. Main outcome measures Weekly excess deaths (observed deaths versus expected deaths predicted by model) in 2020, by sex and age (0-14, 15-64, 65-74, 75-84, and ≥85 years), estimated using an over-dispersed Poisson regression model that accounts for temporal trends and seasonal variability in mortality. Results An estimated 979 000 (95% confidence interval 954 000 to 1 001 000) excess deaths occurred in 2020 in the 29 high income countries analysed. All countries had excess deaths in 2020, except New Zealand, Norway, and Denmark. The five countries with the highest absolute number of excess deaths were the US (458 000, 454 000 to 461 000), Italy (89 100, 87 500 to 90 700), England and Wales (85 400, 83 900 to 86 800), Spain (84 100, 82 800 to 85 300), and Poland (60 100, 58 800 to 61 300). New Zealand had lower overall mortality than expected (−2500, −2900 to −2100). In many countries, the estimated number of excess deaths substantially exceeded the number of reported deaths from covid-19. The highest excess death rates (per 100 000) in men were in Lithuania (285, 259 to 311), Poland (191, 184 to 197), Spain (179, 174 to 184), Hungary (174, 161 to 188), and Italy (168, 163 to 173); the highest rates in women were in Lithuania (210, 185 to 234), Spain (180, 175 to 185), Hungary (169, 156 to 182), Slovenia (158, 132 to 184), and Belgium (151, 141 to 162). Little evidence was found of subsequent compensatory reductions following excess mortality. Conclusion Approximately one million excess deaths occurred in 2020 in these 29 high income countries. Age standardised excess death rates were higher in men than women in almost all countries. Excess deaths substantially exceeded reported deaths from covid-19 in many countries, indicating that determining the full impact of the pandemic on mortality requires assessment of excess deaths. Many countries had lower deaths than expected in children <15 years. Sex inequality in mortality widened further in most countries in 2020.

scholarly journals Flood history of the Bavarian Alpine Foreland since the late Middle Ages in the context of internal and external climate forcing factors

2014 ◽  
Vol 11 (7) ◽  
pp. 7409-7440 ◽  
Author(s):  
O. Böhm ◽  
J. Jacobeit ◽  
R. Glaser ◽  
K.-F. Wetzel
Keyword(s):  
Climate Change ◽  
Time Series ◽  
Climate Variability ◽  
Little Ice Age ◽  
Ice Age ◽  
Natural Climate Variability ◽  
Long Time ◽  
History Of ◽  
Alpine Foreland ◽  
Natural Climate

Abstract. This paper describes the flood history of the Bavarian part of the Alpine Foreland of Germany and addresses different questions concerning climate variability and flood frequencies from the 13th century until today. Will recent climatic change modify the flood frequencies within the Bavarian Alpine Foreland or are the flood frequencies varying due to altering climatic conditions since historical times? In the context of recent discussions whether man-made climate change will modify the present state of flood frequencies, a look back into the past is essential to understand the occurrence of floods in general and of recent floods in particular. In order to understand climatic variability and changes in a comprehensive way, it is necessary to review long time series. A perceived increase of summer floods in eastern Germany and Bavaria since 1997 requires examination of long time series to estimate changes in flood frequencies in a proper way. In view of the annual distribution of flood events within the Alpine Foreland of Germany, summer floods prove to be most important. Based on written historical sources, the flood history of the Alpine Foreland of Germany can be reconstructed back to the 14th century. One major result is the occurrence of "flood-rich" and "flood-poor" episodes in nearly cyclical sequences. Flood-rich periods were recorded in the periods 1300–1335, 1370–1450, 1470–1525, 1555–1590, 1615–1665, 1730–1780, 1820–1870, and 1910–1955 as well as in a 9th period beginning in 1980. The flood-rich periods are characterized by longer flood durations. Most of the flood-rich and flood-poor periods (in particular the beginning and the end of them) can be connected to changes in natural climate variability. These include changing sunspot numbers (as a measure of solar activity), so-called Little Ice Age Type Events (LIATEs) as well as changes in the North Atlantic Oscillation (NAO). Climate signals from external forcing factors, which could be used to explain the changing flood frequencies in the Bavarian Alpine Foreland, end in 1930. Relationships within the climate system such as the correlation of flood frequencies with the NAO have changed during the transition from the post Little Ice Age period to the Modern Climate Optimum around 1930. Natural climate variability might have been outperformed by anthropogenic climate change.

scholarly journals Mudança no Regime Temporal da Temperatura do Ar e Precipitação Pluviométrica na Região de Rio Largo, Alagoas (Change in the Temporal Regime of Air Temperature and Rainfall in the Region of Rio Largo, Alagoas, Brazil)

2014 ◽  
Vol 7 (4) ◽  
pp. 662
Author(s):  
Henderson Silva Wanderley ◽  
André Luiz de Carvalho ◽  
Ronabson Cardoso Fernandes ◽  
José Leonaldo de Souza
Keyword(s):  
Time Series ◽  
Air Temperature ◽  
Change Point ◽  
Statistical Tests ◽  
Linear Regression Analysis ◽  
Homogeneity Test ◽  
Significance Level ◽  
Standard Normal Homogeneity Test ◽  
Standard Normal ◽  
History Of

Compreender como as alterações no clima têm modificado a temperatura do ar e a precipitação pluvial de uma região é essencial, sobretudo para regiões como o Nordeste brasileiro, que apresentam vasto histórico de secas e altas temperaturas. No entanto, estudos com esse fim são escassos ou até mesmo inexistentes para essa região. Deste modo, objetivou-se identificar mudanças ocorridas no regime temporal da temperatura diurna e noturna e na precipitação na região de Rio Largo, Alagoas. Para isto, utilizaram-se dados de temperatura diurna (máxima) e noturna (mínima) compreendidos entre 1973 e 2002, e de precipitação dispostos entre 1973 e 2008. As séries temporais foram submetidas ao teste estatístico SNHT (Standard Normal Homogeneity Test) para identificar possíveis pontos de mudança na média. A análise de regressão linear simples foi utilizada para identificar alterações nas séries temporais, testada por meio do teste t de Student, adotando-se nível de significância estatística de 0,05%, para ambos os testes estatísticos. A análise mostrou que as temperaturas demostraram pontos de mudanças significativos, no entanto, foi observada uma defasagem de quase dez anos entre os pontos. A tendência identificada entre as temperaturas foram opostas entre si, sendo de aumento para a temperatura diurna e de redução para a noturna. A precipitação demostrou tendência de redução, no entanto, não apresentou mudança estatística significativa.  ABSTRACTUnderstanding how changes in climate have changed air temperature and rainfall in a region is essential, especially for regions such as the Brazilian Northeast, which have long history of drought and high temperatures. However, studies for this purpose are scarce or even nonexistent for this region. Thus, this study aimed to identify changes in the temporal regime of daytime and nighttime temperature and rainfall in the region of Rio Largo, Alagoas, Brazil. For this, it was used data of daytime temperature (maximum) and night (minimum) ranging from 1973 to 2002, and rainfall arranged between 1973 and 2008. Time series were submitted to SNHT (Standard Normal Homogeneity Test) statistical test to identify possible change point in average. A simple linear regression analysis was used to identify changes in time series, tested using the Student t test, adopting a significance level of 0.05%, for both statistical tests. The analysis showed that temperatures demonstrated significant change points, however, there was a gap of almost ten years between the points. The trend identified among the temperatures was opposed to each other, with increasing daytime temperature and reduction of nighttime temperature. Rainfall demonstrated trend of reducing, however, showed no statistically significant change.Keywords: daytime and nighttime temperature, SNHT, trend, change point. 

scholarly journals Chaos in Three-Body Dynamics: Intermittency, Strange Attractor, Kolmogorov-Sinai Entropy

1999 ◽  
Vol 172 ◽  
pp. 465-466
Author(s):  
Arthur D. Chernin
Keyword(s):  
Time Series ◽  
Temporal Structure ◽  
High Amplitude ◽  
Close Binary ◽  
Body Dynamics ◽  
Long Time ◽  
History Of ◽  
Three Body ◽  
Similarity And Difference ◽  
Low Amplitude

The temporal structure of chaos in three-body dynamics is analyzed; the emphasis is made on a similarity and difference between three-body chaos and basic patterns of chaotic behaviour known in nonlinear physics.1. With the use of homology mapping (Agekian and Anosova 1967), we study a set of computer models of thee-body systems in a stationary spherically symmetric potential well (Valtonen et al. (1994); the well confines the bodies, and because of this the system can generate fairly long time series. Typical time series reveal sequences of seemingly periodic motion and short bursts of strong chaos that appear in an irregular manner (Heinämäki et al. 1998). The quasi-ordered states are associated with hierarchical homology, and the quasi-period of the low-amplitude oscillations is very near the period of the temporary close binary in the system. The high-amplitude irregular states are mostly due to active three-body interplay when each of the bodies interacts with the two others with almost equal intensity. In the evolutionary history of most systems, these two extreme kinds of states alternate in an apparently random way producing together a non-stationary pattern of unpredictable behaviour.

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