scholarly journals Non–stationarity in annual maxima rainfall across Australia – implications for Intensity–Frequency–Duration (IFD) relationships

2015 ◽  
Vol 12 (3) ◽  
pp. 3449-3475 ◽  
Author(s):  
D. C. Verdon-Kidd ◽  
A. S. Kiem
Keyword(s):  
Climate Variability ◽  
Daily Rainfall ◽  
Data Sets ◽  
Time Period ◽  
The World ◽  
Multidecadal Climate Variability ◽  
Guidance Needs ◽  
Hydroclimatic Variability ◽  
Climate Statistics

Abstract. Rainfall Intensity–Frequency–Duration (IFD) relationships are commonly required for the design and planning of water supply and management systems around the world. Currently IFD information is based on the "stationary climate assumption" – that weather at any point in time will vary randomly and that the underlying climate statistics (including both averages and extremes) will remain constant irrespective of the period of record. However, the validity of this assumption has been questioned over the last 15 years, particularly in Australia, following an improved understanding of the significant impact of climate variability and change occurring on interannual to multidecadal timescales. This paper provides evidence of non-stationarity in annual maxima rainfall timeseries using 96 daily rainfall stations and 66 sub-daily rainfall stations across Australia. Further, the effect of non-stationarity on the resulting IFD estimates are explored for three long-term sub-daily rainfall records (Brisbane, Sydney and Melbourne) utilising insights into multidecadal climate variability. It is demonstrated that IFD relationships may under- or over-estimate the design rainfall depending on the length and time period spanned by the rainfall data used to develop the IFD information. It is recommended that non-stationarity in annual maxima rainfall be explicitly considered and appropriately treated in the ongoing revisions of Engineers Australia's guide to estimating and utilising IFD information, "Australian Rainfall and Runoff", and that clear guidance needs to be provided on how to deal with the issue of non-stationarity of extreme events (irrespective of whether that non-stationarity is due to natural or anthropogenic climate change). The findings of our study also have important implications for other regions of the world that exhibit considerable hydroclimatic variability and where IFD information is based on relatively short data sets.

scholarly journals Regime shifts in annual maximum rainfall across Australia – implications for intensity–frequency–duration (IFD) relationships

2015 ◽  
Vol 19 (12) ◽  
pp. 4735-4746 ◽  
Author(s):  
D. C. Verdon-Kidd ◽  
A. S. Kiem
Keyword(s):  
Climate Variability ◽  
Daily Rainfall ◽  
Regime Shifts ◽  
Rainfall Time Series ◽  
Annual Maximum ◽  
Maximum Rainfall ◽  
The World ◽  
Guidance Needs ◽  
Annual Maximum Rainfall ◽  
Hydroclimatic Variability

Abstract. Rainfall intensity–frequency–duration (IFD) relationships are commonly required for the design and planning of water supply and management systems around the world. Currently, IFD information is based on the "stationary climate assumption" that weather at any point in time will vary randomly and that the underlying climate statistics (including both averages and extremes) will remain constant irrespective of the period of record. However, the validity of this assumption has been questioned over the last 15 years, particularly in Australia, following an improved understanding of the significant impact of climate variability and change occurring on interannual to multidecadal timescales. This paper provides evidence of regime shifts in annual maximum rainfall time series (between 1913–2010) using 96 daily rainfall stations and 66 sub-daily rainfall stations across Australia. Furthermore, the effect of these regime shifts on the resulting IFD estimates are explored for three long-term (1913–2010) sub-daily rainfall records (Brisbane, Sydney, and Melbourne) utilizing insights into multidecadal climate variability. It is demonstrated that IFD relationships may under- or over-estimate the design rainfall depending on the length and time period spanned by the rainfall data used to develop the IFD information. It is recommended that regime shifts in annual maximum rainfall be explicitly considered and appropriately treated in the ongoing revisions of the Engineers Australia guide to estimating and utilizing IFD information, Australian Rainfall and Runoff (ARR), and that clear guidance needs to be provided on how to deal with the issue of regime shifts in extreme events (irrespective of whether this is due to natural or anthropogenic climate change). The findings of our study also have important implications for other regions of the world that exhibit considerable hydroclimatic variability and where IFD information is based on relatively short data sets.

scholarly journals Intention, Principle, Outputs and Aims of the Experimental Pavilion Research of Building Envelopes Including Windows for Wooden Buildings

2017 ◽  
Vol 13 (1) ◽  
pp. 42-51 ◽  
Author(s):  
Daniela Štaffenová ◽  
Ján Rybárik ◽  
Miroslav Jakubčík
Keyword(s):  
Experimental Research ◽  
Climatic Conditions ◽  
Point Of View ◽  
Physical Parameters ◽  
Data Sets ◽  
Data Set ◽  
Building Envelopes ◽  
Climate Conditions ◽  
Time Period

AbstractThe aim of experimental research in the area of exterior walls and windows suitable for wooden buildings was to build special pavilion laboratories. These laboratories are ideally isolated from the surrounding environment, airtight and controlled by the constant internal climate. The principle of experimental research is measuring and recording of required physical parameters (e.g. temperature or relative humidity). This is done in layers of experimental fragment sections in the direction from exterior to interior, as well as in critical places by stable interior and real exterior climatic conditions. The outputs are evaluations of experimental structures behaviour during the specified time period, possibly during the whole year by stable interior and real exterior boundary conditions. The main aim of this experimental research is processing of long-term measurements of experimental structures and the subsequent analysis. The next part of the research consists of collecting measurements obtained with assistance of the experimental detached weather station, analysis, evaluation for later setting up of reference data set for the research locality, from the point of view of its comparison to the data sets from Slovak Hydrometeorological Institute (SHMU) and to localities with similar climate conditions. Later on, the data sets could lead to recommendations for design of wooden buildings.

scholarly journals Comparison of GPS tropospheric delays derived from two consecutive EPN reprocessing campaigns from the point of view of climate monitoring

2016 ◽  
Vol 9 (9) ◽  
pp. 4861-4877 ◽  
Author(s):  
Zofia Baldysz ◽  
Grzegorz Nykiel ◽  
Andrzej Araszkiewicz ◽  
Mariusz Figurski ◽  
Karolina Szafranek
Keyword(s):  
Time Series ◽  
Point Of View ◽  
Trend Test ◽  
Data Sets ◽  
Total Delay ◽  
University Of Technology ◽  
Time Period ◽  
Seasonal Signals ◽  
Linear Trends

Abstract. The main purpose of this research was to acquire information about consistency of ZTD (zenith total delay) linear trends and seasonal components between two consecutive GPS reprocessing campaigns. The analysis concerned two sets of the ZTD time series which were estimated during EUREF (Reference Frame Sub-Commission for Europe) EPN (Permanent Network) reprocessing campaigns according to 2008 and 2015 MUT AC (Military University of Technology Analysis Centre) scenarios. Firstly, Lomb–Scargle periodograms were generated for 57 EPN stations to obtain a characterisation of oscillations occurring in the ZTD time series. Then, the values of seasonal components and linear trends were estimated using the LSE (least squares estimation) approach. The Mann–Kendall trend test was also carried out to verify the presence of linear long-term ZTD changes. Finally, differences in seasonal signals and linear trends between these two data sets were investigated. All these analyses were conducted for the ZTD time series of two lengths: a shortened 16-year series and a full 18-year one. In the case of spectral analysis, amplitudes of the annual and semi-annual periods were almost exactly the same for both reprocessing campaigns. Exceptions were found for only a few stations and they did not exceed 1 mm. The estimated trends were also similar. However, for the reprocessing performed in 2008, the trends values were usually higher. In general, shortening of the analysed time period by 2 years resulted in a decrease of the linear trends values of about 0.07 mm yr−1. This was confirmed by analyses based on two data sets.

scholarly journals Internal consistency of the Regional Brewer Calibration Centre for Europe triad during the period 2005–2016

2018 ◽  
Vol 11 (7) ◽  
pp. 4059-4072 ◽  
Author(s):  
Sergio Fabián León-Luis ◽  
Alberto Redondas ◽  
Virgilio Carreño ◽  
Javier López-Solano ◽  
Alberto Berjón ◽  
...  
Keyword(s):  
Standard Deviation ◽  
Relative Standard Deviation ◽  
Data Sets ◽  
Individual Values ◽  
Relative Standard ◽  
The World ◽  
The Mean ◽  
The Individual ◽  
Ozone Column

Abstract. Total ozone column measurements can be made using Brewer spectrophotometers, which are calibrated periodically in intercomparison campaigns with respect to a reference instrument. In 2003, the Regional Brewer Calibration Centre for Europe (RBCC-E) was established at the Izaña Atmospheric Research Center (Canary Islands, Spain), and since 2011 the RBCC-E has transferred its calibration based on the Langley method using travelling standard(s) that are wholly and independently calibrated at Izaña. This work is focused on reporting the consistency of the measurements of the RBCC-E triad (Brewer instruments #157, #183 and #185) made at the Izaña Atmospheric Observatory during the period 2005–2016. In order to study the long-term precision of the RBCC-E triad, it must be taken into account that each Brewer takes a large number of measurements every day and, hence, it becomes necessary to calculate a representative value of all of them. This value was calculated from two different methods previously used to study the long-term behaviour of the world reference triad (Toronto triad) and Arosa triad. Applying their procedures to the data from the RBCC-E triad allows the comparison of the three instruments. In daily averages, applying the procedure used for the world reference triad, the RBCC-E triad presents a relative standard deviation equal to σ = 0.41 %, which is calculated as the mean of the individual values for each Brewer (σ157 = 0.362 %, σ183 = 0.453 % and σ185 = 0.428 %). Alternatively, using the procedure used to analyse the Arosa triad, the RBCC-E presents a relative standard deviation of about σ = 0.5 %. In monthly averages, the method used for the data from the world reference triad gives a relative standard deviation mean equal to σ = 0.3 % (σ157 = 0.33 %, σ183 = 0.34 % and σ185 = 0.23 %). However, the procedure of the Arosa triad gives monthly values of σ = 0.5 %. In this work, two ozone data sets are analysed: the first includes all the ozone measurements available, while the second only includes the simultaneous measurements of all three instruments. Furthermore, this paper also describes the Langley method used to determine the extraterrestrial constant (ETC) for the RBCC-E triad, the necessary first step toward accurate ozone calculation. Finally, the short-term or intraday consistency is also studied to identify the effect of the solar zenith angle on the precision of the RBCC-E triad.

An integrated deterministic–stochastic approach for forecasting the long-term trajectories of COVID-19

2021 ◽  
pp. 2141001
Author(s):  
Indrajit Ghosh ◽  
Tanujit Chakraborty
Keyword(s):  
Time Series ◽  
Stochastic Approach ◽  
World Population ◽  
Data Sets ◽  
Univariate Time Series ◽  
Reproduction Numbers ◽  
The World ◽  
Long Term Forecasting ◽  
Ar Models

The ongoing coronavirus disease 2019 (COVID-19) pandemic is one of the major health emergencies in decades that affected almost every country in the world. As of June 30, 2020, it has caused an outbreak with more than 10 million confirmed infections, and more than 500,000 reported deaths globally. Due to the unavailability of an effective treatment (or vaccine) and insufficient evidence regarding the transmission mechanism of the epidemic, the world population is currently in a vulnerable position. The daily cases data sets of COVID-19 for profoundly affected countries represent a stochastic process comprised of deterministic and stochastic components. This study proposes an integrated deterministic–stochastic approach to forecast the long-term trajectories of the COVID-19 cases for Italy and Spain. The deterministic component of the daily-cases univariate time series is assessed by an extended version of the SIR [Susceptible–Infected–Recovered–Protected–Isolated (SIRCX)] model, whereas its stochastic component is modeled using an autoregressive (AR) time series model. The proposed integrated SIRCX-AR (ISA) approach based on two operationally distinct modeling paradigms utilizes the superiority of both the deterministic SIRCX and stochastic AR models to find the long-term trajectories of the epidemic curves. Experimental analysis based on the proposed ISA model shows significant improvement in the long-term forecasting of COVID-19 cases for Italy and Spain in comparison to the ODE-based SIRCX model. The estimated Basic reproduction numbers for Italy and Spain based on SIRCX model are found to be [Formula: see text] and [Formula: see text], respectively. ISA model-based results reveal that the number of cases in Italy and Spain between 11 May, 2020–9 June, 2020 will be 10,982 (6383–15,582) and 13,731 (3395–29,013), respectively. Additionally, the expected number of daily cases on 9 July, 2020 for Italy and Spain is estimated to be 30 (0–183) and 92 (0–602), respectively.

scholarly journals Impact of the economic crisis and contractions within the European long-term care systems

2021 ◽  
pp. 1-17
Author(s):  
Esther Albesa Jové
Keyword(s):  
Economic Crisis ◽  
Financial Crises ◽  
Long Term Care ◽  
Term Care ◽  
Development Level ◽  
Time Period ◽  
The World ◽  
Care Systems ◽  
The Impact

Abstract In 2008, the world underwent one of its worst economic and financial crises, whose consequences are still visible in some countries. This paper aims to analyse the impact of the crisis within the long-term care systems of Germany, England, Sweden and Spain from a comparative perspective. The time period analysed spans from the outset of the crisis in 2008, up to 2017. This article starts off from the thesis of the divergent impact of the economic crisis in these countries and the convergence between the impact of the crisis and long-term care contractions in the most afflicted countries. The outcome highlights the power of economic and financial pressures in order to explain the contractions within the care policies. Equally, it emphasizes the contradictions between the formal development level of the care systems and their practical institutional implementation in the field.

scholarly journals Spatiotemporal Variations in Hydroclimate across the Mediterranean Andes (30°–37°S) since the Early Twentieth Century

2017 ◽  
Vol 18 (7) ◽  
pp. 1929-1942 ◽  
Author(s):  
Álvaro González-Reyes ◽  
James McPhee ◽  
Duncan A. Christie ◽  
Carlos Le Quesne ◽  
Paul Szejner ◽  
...  
Keyword(s):  
Southern Oscillation ◽  
Kernel Estimation ◽  
Spatial And Temporal Patterns ◽  
The Andes ◽  
The Pacific ◽  
The Mediterranean ◽  
Multidecadal Climate Variability ◽  
Hydroclimatic Variability ◽  
North And South

Abstract In the Mediterranean Andes region (MA; 30°–37°S), the main rivers are largely fed by melting snowpack and provide freshwater to around 10 million people on both sides of the Andes Mountains. Water resources in the MA are under pressure because of the extensive development of industrial agriculture and mining activities. This pressure is increasing as the region faces one of its worst recorded droughts. Previous studies have pointed to El Niño–Southern Oscillation (ENSO) as the main climatic force impacting the MA. However, the role of decadal and multidecadal climate variability, their spatial patterns, and the recurrence of long-term droughts remains poorly studied. In an attempt to better understand these factors, spatial and temporal patterns of hydroclimatic variability are analyzed using an extensive database of streamflow, precipitation, and snowpack covering the period between 1910 and 2011. These analyses are based on the combination of correlation, principal components, and kernel estimation techniques. Despite a general common pattern across the MA, the results presented here identify two hydroclimatic subregions, located north and south of 34°S. While the interannual variability associated with ENSO is slightly stronger north of 34°S, the variability associated with the Pacific decadal oscillation (PDO) and/or the interdecadal Pacific oscillation (IPO) index shows similar patterns in both regions. However, variations produced by the IPO forcing seem to be greater in the southern subregion since 1975. The estimations presented here on drought recurrence reveal a generalized increase in dry extremes since the 1950s. These findings suggest that the northern MA is more vulnerable to changes in hydrology and climate than the southern MA.

scholarly journals Fishing, fast growth and climate variability increase the risk of collapse

2015 ◽  
Vol 282 (1813) ◽  
pp. 20151053 ◽  
Author(s):  
Malin L. Pinsky ◽  
David Byler
Keyword(s):  
Climate Variability ◽  
Species Traits ◽  
Fast Growth ◽  
Boosted Regression Trees ◽  
Fast Growing ◽  
Variable Environments ◽  
The World ◽  
Slow Growing ◽  
Fast Growing Species

Species around the world have suffered collapses, and a key question is why some populations are more vulnerable than others. Traditional conservation biology and evidence from terrestrial species suggest that slow-growing populations are most at risk, but interactions between climate variability and harvest dynamics may alter or even reverse this pattern. Here, we test this hypothesis globally. We use boosted regression trees to analyse the influences of harvesting, species traits and climate variability on the risk of collapse (decline below a fixed threshold) across 154 marine fish populations around the world. The most important factor explaining collapses was the magnitude of overfishing, while the duration of overfishing best explained long-term depletion. However, fast growth was the next most important risk factor. Fast-growing populations and those in variable environments were especially sensitive to overfishing, and the risk of collapse was more than tripled for fast-growing when compared with slow-growing species that experienced overfishing. We found little evidence that, in the absence of overfishing, climate variability or fast growth rates alone drove population collapse over the last six decades. Expanding efforts to rapidly adjust harvest pressure to account for climate-driven lows in productivity could help to avoid future collapses, particularly among fast-growing species.

scholarly journals Price flexibility of world market for cocoa beans

2009 ◽  
Vol 57 (6) ◽  
pp. 267-274 ◽  
Author(s):  
Pavel Syrovátka
Keyword(s):  
World Market ◽  
Price Model ◽  
Cocoa Beans ◽  
Dynamic Price ◽  
Time Period ◽  
The World ◽  
Price Flexibility ◽  
Current Price ◽  
Log Linear

The article is focused on the quantitative analysis of the price flexibility of the world market for the cocoa beans. The ICCO databases from 1960/1961 to 2005/2006 crop years were used for this analysis. In the investigated time period, the analysis of the price flexibility was based on the autoregressive form of the price model with the log-linear construction: lnpt = 2.6824 − 0.4041 × lnstgt + 0.8301 × lnpt−1 + ut. The values of the parameters of the autoregressive price model were estimated using OLS. The developed model was statistically significant in all evaluated respects (F-test, T-tests and Durbin’s h-test). Within the analysis of the world market for the cocoa beans, the current, dynamic, long-term and long-equilibrium coefficients of price flexibility were evaluated. According to applied log-linear construction of the autoregressive price model, the level of the current price flexibility of the world market for the cocoa beans was −0.4041, the dynamic price flexibility of the first order achieved the value of −0.3354 and the long-equilibrium price flexibility of the world market for the cocoa beans takes the value of −2.3784.

scholarly journals An integrated deterministic-stochastic approach for predicting the long-term trajectories of COVID-19

2020 ◽  
Author(s):  
Indrajit Ghosh ◽  
Tanujit Chakraborty
Keyword(s):  
Time Series ◽  
Stochastic Approach ◽  
World Population ◽  
Data Sets ◽  
Major Health ◽  
Univariate Time Series ◽  
The World ◽  
Long Term Forecasting ◽  
Ar Models

The ongoing COVID-19 pandemic is one of the major health emergencies in decades that affected almost every country in the world. As of June 30, 2020, it has caused an outbreak with more than 10 million confirmed infections, and more than 500 thousand reported deaths globally. Due to the unavailability of an effective treatment (or vaccine) and insufficient evidence regarding the transmission mechanism of the epidemic, the world population is currently in a vulnerable position. The daily cases data sets of COVID-19 for profoundly affected countries represent a stochastic process comprised of deterministic and stochastic components. This study proposes an integrated deterministic-stochastic approach to forecast the long-term trajectories of the COVID-19 cases for Italy and Spain. The deterministic component of the daily-cases univariate time-series is assessed by an extended version of the SIR (SIRCX) model, whereas its stochastic component is modeled using an autoregressive (AR) time series model. The proposed integrated SIRCX-AR (ISA) approach based on two operationally distinct modeling paradigms utilizes the superiority of both the deterministic SIRCX and stochastic AR models to find the long-term trajectories of the epidemic curves. Experimental analysis based on the proposed ISA model shows significant improvement in the long-term forecasting of COVID-19 cases for Italy and Spain in comparison to the ODE-based SIRCX model.

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