scholarly journals Non-stationarity in daily and sub-daily intense rainfall – Part 1: Sydney, Australia

2011 ◽  
Vol 11 (8) ◽  
pp. 2263-2271 ◽  
Author(s):  
D. Jakob ◽  
D. J. Karoly ◽  
A. Seed
Keyword(s):  
Statistical Significance ◽  
Daily Rainfall ◽  
Data Sets ◽  
Intense Rainfall ◽  
Rainfall Extremes ◽  
Using Data ◽  
The One ◽  
Quantile Estimates ◽  
Frequency Magnitude

Abstract. This study was driven by a need to clarify how variations in climate might affect intense rainfall and the potential for flooding. Sub-daily durations are of particular interest for urban applications. Worldwide, few such observation-based studies exist, which is mainly due to limitations in data. While there are still large discrepancies between precipitation data sets from observations and models, both show that there is a tendency for moist regions to become wetter and for dry regions to become drier. However, changes in extreme conditions may show the opposite sign to those in average conditions. Where changes in observed intense precipitation have been studied, this has typically been for daily durations or longer. The purpose of this two-part study is to examine daily and sub-daily rainfall extremes for evidence of non-stationarity. Here the problem was addressed by supplementing one long record (Part 1) by a set of shorter records for a 30-yr concurrent period (Part 2). Variations in frequency and magnitude of rainfall extremes across durations from 6 min to 72 h were assessed using data from sites in the south-east of Australia. For the analyses presented in this paper, a peaks-over-threshold approach was chosen since it allows investigating changes in frequency as well as magnitude. Non-parametric approaches were used to assess changes in frequency, magnitude, and quantile estimates as well as the statistical significance of changes for one station (Sydney Observatory Hill) for the period 1921 to 2005. Deviations from the long-term average vary with season, duration, and threshold. The effects of climate variations are most readily detected for the highest thresholds. Deviations from the long-term average tend to be larger for frequencies than for magnitudes, and changes in frequency and magnitude may have opposite signs. Investigations presented in this paper show that variations in frequency and magnitude of events at daily durations are a poor indicator of changes at sub-daily durations. Studies like the one presented here should be undertaken for other regions to allow the identification of regions with significant increase/decrease in intense rainfall, whether there are common features with regards to duration and season exhibiting most significant changes (which in turn could lead to establishing a theoretical framework), and assist in validation of projections of rainfall extremes.

scholarly journals Non-stationarity in daily and sub-daily intense rainfall – Part 2: Regional assessment for sites in south-east Australia

2011 ◽  
Vol 11 (8) ◽  
pp. 2273-2284 ◽  
Author(s):  
D. Jakob ◽  
D. J. Karoly ◽  
A. Seed
Keyword(s):  
Radar Data ◽  
Intense Rainfall ◽  
Long Term Conditions ◽  
Rainfall Events ◽  
Practical Applications ◽  
The North ◽  
Alternative Approaches ◽  
Using Data ◽  
Quantile Estimates

Abstract. Using data for a common period (1976–2005) for a set of 31 sites located in south-east Australia, variations in frequency and magnitude of intense rainfall events across durations from 6 min to 72 h were assessed. This study was driven by a need to clarify how variations in climate might affect intense rainfall and the potential for flooding. Sub-daily durations are of particular interest for urban applications. Worldwide, few such observation-based studies exist, which is mainly due to limitations in data. Analysis of seasonality in frequency and magnitude of events revealed considerable variation across the set of sites, implying different dominating rainfall-producing mechanisms and/or interactions with local topography. Both these factors are relevant when assessing the potential effects of climate variations on intense rainfall events. The set of sites was therefore split into groups ("north cluster" and "south cluster") according to the characteristics of intense rainfall events. There is a strong polarisation in the nature of changes found for the north cluster and south cluster. While sites in the north cluster typically exhibit decrease in frequency of events, particularly in autumn and at durations of 1 h and longer; sites in the south cluster experience an increase in frequency of events, particularly for summer and sub-hourly durations. Non-stationarity found in historical records has the potential to significantly affect design rainfall estimates. An assessment of quantile estimates derived using a standard regionalisation technique and periods representative of record lengths available for practical applications show that such estimates may not be representative of long-term conditions, so alternative approaches need to be considered, particularly where short records are concerned. Additional rainfall information, in particular radar data, could be used for an in-depth spatial analysis of intense rainfall events.

Statistical Uncertainty in Long-Term Distributions of Significant Wave Height

1996 ◽  
Vol 118 (4) ◽  
pp. 284-291 ◽  
Author(s):  
C. Guedes Soares ◽  
A. C. Henriques
Keyword(s):  
Probability Distribution ◽  
Wave Height ◽  
Significant Wave Height ◽  
Data Sets ◽  
Monthly Basis ◽  
Significant Wave ◽  
Fitting Procedure ◽  
The One ◽  
Homogeneous Data

This work examines some aspects involved in the estimation of the parameters of the probability distribution of significant wave height, in particular the homogeneity of the data sets and the statistical methods of fitting a distribution to data. More homogeneous data sets are organized by collecting the data on a monthly basis and by separating the simple sea states from the combined ones. A three-parameter Weibull distribution is fitted to the data. The parameters of the fitted distribution are estimated by the methods of maximum likelihood, of regression, and of the moments. The uncertainty involved in estimating the probability distribution with the three methods is compared with the one that results from using more homogeneous data sets, and it is concluded that the uncertainty involved in the fitting procedure can be more significant unless the method of moments is not considered.

Relationship Between Environmental Temperature and Yields of Subarctic and Temperate Zone Fish Species

1983 ◽  
Vol 40 (10) ◽  
pp. 1829-1837 ◽  
Author(s):  
David A. Schlesinger ◽  
Henry A. Regier
Keyword(s):  
Optimal Growth ◽  
Temperate Zone ◽  
Data Sets ◽  
Coregonus Clupeaformis ◽  
Influence Of Temperature On ◽  
Northern United States ◽  
Using Data ◽  
Curvilinear Relationships ◽  
Fish Yields

Fishes inhabiting subarctic and temperate zone lakes exhibit distinct optimal growth temperatures and temperature preferenda. However, within regional data sets, attempts to correlate fish yields with temperature variables have generally been unsuccessful. In our study, curvilinear relationships between "long-term mean annual air temperature" (TEMP) and sustained yields of three species were fitted using data from 23 intensively fished lakes in Canada and the northern United States. Optimum TEMP values for sustained yield were approximately −1.0, 1.5, and 2 °C, respectively, for lake whitefish (Coregonus clupeaformis), northern pike (Esox lucius), and walleye (Stizostedion vitreum vitreum). These differences suggest that the influence of temperature on sustained fish yields from subarctic and temperate zone lakes may, in the past, have been underestimated.

scholarly journals Smithsonian Astrophysical Observatory Ozone Mapping and Profiler Suite (SAO OMPS) formaldehyde retrieval

2015 ◽  
Vol 8 (9) ◽  
pp. 9209-9240 ◽  
Author(s):  
G. González Abad ◽  
A. Vasilkov ◽  
C. Seftor ◽  
X. Liu ◽  
K. Chance
Keyword(s):  
Detection Limit ◽  
Spectral Resolution ◽  
Signal To Noise Ratio ◽  
Data Sets ◽  
Ozone Monitoring Instrument ◽  
Vertical Column ◽  
High Concentrations ◽  
One Year ◽  
The One

Abstract. This paper presents our new formaldehyde (H2CO) retrievals, obtained from spectra recorded by the nadir instrument of the Ozone Mapping and Profiler Suite (OMPS) flown on-board NASA's Suomi National Polar-orbiting Partnership (SUOMI-NPP) satellite. Our algorithm is similar to the one currently in place for the production of NASA's Ozone Monitoring Instrument (OMI) operational H2CO product. We are now able to produce a consistent set of long term data from two different instruments that share a similar concept. The ongoing overlap period between OMI and OMPS offers a perfect opportunity to study the consistency between both data sets. The different spatial and spectral resolution of the instruments is a source of discrepancy in the retrievals despite the similarity of the physic assumptions of the algorithm. We have concluded that the reduced spectral resolution of OMPS in comparison with OMI is not a significant obstacle in obtaining good quality retrievals. Indeed, the improved signal to noise ratio (SNR) of OMPS with respect to OMI helps to reduce the noise of the retrievals performed using OMPS spectra. However, the size of OMPS spatial pixels imposes a limitation in the capability to distinguish particular features of H2CO that are discernible with OMI. With root mean square (RMS) residuals ~ 5 × 10−4 for individual pixels we estimate the detection limit to be about 7.5 × 1015 molecules cm−2. Total vertical column densities (VCD) errors for individual pixels range between 40 % for pixels with high concentrations to 100 % or more for pixels with concentrations at or below the detection limit. We compare different OMI products with our OMPS product using one year of data, between September 2012 and September 2013. The seasonality of the retrieved slant columns is captured similarly by all products but there are discrepancies in the values of the VCDs. The mean biases among the two OMI products and our OMPS product are 21 % between OMI SAO and OMPS SAO and 38 % between OMI BIRA and OMPS SAO for eight selected regions.

Inconsistency-Induced Learning for Perpetual Learners

2013 ◽  
pp. 70-87 ◽  
Author(s):  
Du Zhang ◽  
Meiliu Lu
Keyword(s):  
Machine Learning ◽  
Learning Algorithm ◽  
Target Function ◽  
Data Sets ◽  
Revision Process ◽  
Learning Agents ◽  
Learning Agent ◽  
The One ◽  
Over Time

One of the long-term research goals in machine learning is how to build never-ending learners. The state-of-the-practice in the field of machine learning thus far is still dominated by the one-time learner paradigm: some learning algorithm is utilized on data sets to produce certain model or target function, and then the learner is put away and the model or function is put to work. Such a learn-once-apply-next (or LOAN) approach may not be adequate in dealing with many real world problems and is in sharp contrast with the human’s lifelong learning process. On the other hand, learning can often be brought on through overcoming some inconsistent circumstances. This paper proposes a framework for perpetual learning agents that are capable of continuously refining or augmenting their knowledge through overcoming inconsistencies encountered during their problem-solving episodes. The never-ending nature of a perpetual learning agent is embodied in the framework as the agent’s continuous inconsistency-induced belief revision process. The framework hinges on the agents recognizing inconsistency in data, information, knowledge, or meta-knowledge, identifying the cause of inconsistency, revising or augmenting beliefs to explain, resolve, or accommodate inconsistency. The authors believe that inconsistency can serve as one of the important learning stimuli toward building perpetual learning agents that incrementally improve their performance over time.

scholarly journals Recent trends in daily rainfall extremes over Montenegro (1951–2010)

2015 ◽  
Vol 15 (9) ◽  
pp. 2069-2077 ◽  
Author(s):  
D. Burić ◽  
J. Luković ◽  
B. Bajat ◽  
M. Kilibarda ◽  
N. Živković
Keyword(s):  
North Atlantic Oscillation ◽  
North Atlantic ◽  
Large Scale ◽  
Winter Season ◽  
Daily Rainfall ◽  
Extreme Rainfall ◽  
Intense Rainfall ◽  
The North ◽  
Rainfall Extremes ◽  
The North Atlantic Oscillation

Abstract. More intense rainfall may cause a range of negative impacts upon society and the environment. In this study we analysed trends in extreme ETCCDI (Expert Team on Climate Change Detection and Indices) rainfall indices in Montenegro for the period between 1951 and 2010. Montenegro has been poorly studied in terms of rainfall extremes, yet it contains the wettest Mediterranean region known as Krivošije. Several indices of precipitation extremes were assessed including the number of dry days and rainfall totals in order to identify trends and possible changes. A spatial pattern relationship between extreme rainfall indices and the North Atlantic Oscillation has also been examined. The results generally suggest that the number of days with precipitation decreased while rainfall intensity increased, particularly in south-western parts of the country. A slight tendency towards intense rainfall events is suggested. The examined rainfall indices and North Atlantic Oscillation over Montenegro seemed to be directly linked to changes in one of the major large-scale circulation modes such as the NAO pattern that is particularly evident during the winter season.

Trends in rainfall intensity for stormwater designs in Ontario

2012 ◽  
Vol 3 (1) ◽  
pp. 1-10 ◽  
Author(s):  
B. Vasiljevic ◽  
E. McBean ◽  
B. Gharabaghi
Keyword(s):  
Rainfall Intensity ◽  
Statistical Significance ◽  
Sewer Pipes ◽  
Rainfall Events ◽  
Rain Gauges ◽  
Long Term Trends ◽  
Using Data ◽  
Storm Sewer

The intensities of short-duration rainfall events are fundamental inputs to the design of stormwater management infrastructure. However, since stormwater infrastructure must function as designed for many decades, if there are long-term trends in rainfall intensities, design storms need to be modified. Evidence demonstrates, using data from 13 rain gauges in Ontario, that storm intensities relevant to urban stormwater (5 year) appear to have changed over the last 30 years. The results show, for example, statistical significance at 80% confidence that the 5-year storm has increased, and 85% that the 2-year storm has increased, for the 1 h storm in Waterloo, using partial duration series (PDS) data. The PDS data indicate intensities are increasing at a rate of 1–3% per year. Results show, for example, that a 5-year recurrence storm for PDS for the period 1970–1984 is now very close in magnitude to a 2-year recurrence storm for the period 1985–2003 for Waterloo, Ontario. The implications for a case study demonstrate that 5 out of 12 storm sewer pipes in a subdivision would need to be increased in diameter to obtain the same level of stormwater performance.

scholarly journals Long-term changes in UT/LS ozone between the late 1970s and the 1990s deduced from the GASP and MOZAIC aircraft programs and from ozonesondes

2009 ◽  
Vol 9 (1) ◽  
pp. 2435-2499 ◽  
Author(s):  
C. Schnadt Poberaj ◽  
J. Staehelin ◽  
D. Brunner ◽  
V. Thouret ◽  
H. De Backer ◽  
...  
Keyword(s):  
Statistical Significance ◽  
Data Sets ◽  
Air Masses ◽  
Long Term Changes ◽  
Eastern Usa ◽  
Research Aircraft ◽  
Atmospheric Sampling ◽  
Unites States ◽  
Aircraft Data

Abstract. We present ozone measurements of the Global Atmospheric Sampling Program (GASP) performed from four commercial and one research aircraft in the late 1970s to compare them with respective measurements of the ongoing MOZAIC project. Climatologies of UT/LS ozone were built using the aircraft data sets (1975–1979 and 1994–2001), and long-term changes between the 1970s and 1990s were derived by comparison. The data were binned relative to the dynamical tropopause to separate between UT and LS air masses. LS data were analysed using equivalent latitudes. In the UT, pronounced increases are found over the Middle East and South Asia in the spring and summer seasons. Increases are also found over Japan, Europe, and the eastern parts of the Unites States depending on season. LS ozone over northern mid- and high latitudes was found to be lower in the 1990s compared to the 1970s in all seasons of the year. In addition, a comparison with long-term changes deduced from ozonesondes is presented. An altitude offset was applied to the sonde data to account for the slow response time of the ozone sensors. The early 1970s European Brewer-Mast (BM) sonde data agree with GASP within the range of uncertainty (UT) or measured slightly less ozone (LS). In contrast, the 1990s BM sensors show consistently and significantly higher UT/LS ozone values than MOZAIC. This unequal behaviour of aircraft/sonde comparisons in the 1970s and 1990s leads to differences in the estimated long-term changes over Europe: while the comparison between GASP and MOZAIC indicates ozone changes of −5% to 10% over Europe, the sondes suggest a much larger increase of 10%–35% depending on station and season, although statistical significance is not conclusive due to data sample limitations. In contrast to the BM sondes, the Electrochemical Cell (ECC) sonde at Wallops Island, USA, measured higher UT ozone than both GASP and MOZAIC. Hence, long-term changes from GASP/MOZAIC agree within the range of uncertainty with the changes deduced from Wallops Island. The comparison of GASP with BM and ECC ozonesonde data over Europe and the eastern USA, respectively, corroborates earlier studies stating that early BM instruments measured less ozone than ECC sensor by 10–25%.

scholarly journals ESTIMATE OF THE INTENSITY-DURATION-FREQUENCY PARAMETERS OF INTENSE RAINFALL FOR THE STATE OF ALAGOAS, BRAZIL

2020 ◽  
Vol 28 ◽  
pp. 314-325
Author(s):  
João Batista Lopes da Silva ◽  
Nicole Lopes Bento ◽  
Gabriel Soares Lopes Gomes ◽  
Alcinei Ribeiro Campos ◽  
Danilo Paulúcio da Silva
Keyword(s):  
Return Period ◽  
Probabilistic Models ◽  
Daily Rainfall ◽  
The State ◽  
Data Series ◽  
Intense Rainfall ◽  
Maximum Rainfall ◽  
Rain Gauges ◽  
Intensity Duration Frequency ◽  
Using Data

The study of the rainfall characteristics is of fundamental importance since the frequency of floods has increased in several parts of Brazil due to anthropic impacts of climatic changes. Thus, this study aimed to determine the parameters of the intense rainfall equation (K, a, b, c) for 52 municipalities in the State of Alagoas using data from 164 rain gauges ta available from the National Water Agency (ANA). The data series were subjected to consistency analysis and further desegregation of maximum daily rainfall to durations of the 5; 10; 15; 20; 25; 30; 60; 360; 480; 600; 720 and 1,440 minutes and return period of 5; 10; 25; 50 and 100 years according to different probabilistic models. The adjustment of the parameters was carried out by means of non-linear regression, with R² greater than 0.949 for all the stations, considering for this purpose one station per municipality, totaling 51 municipalities of study. It was obtained that the maximum rainfall intensity predicted increases with the increase in the return period and decreases with the increase of the duration of the rain. The greater intensities were detected in the mesoregion of Eastern Alagoano and the lowest intensities in the mesoregion of Sertão Alagoano.

Inconsistency-Induced Learning for Perpetual Learners

2011 ◽  
Vol 3 (4) ◽  
pp. 33-51 ◽  
Author(s):  
Du Zhang ◽  
Meiliu Lu
Keyword(s):  
Machine Learning ◽  
Learning Algorithm ◽  
Target Function ◽  
Data Sets ◽  
Revision Process ◽  
Learning Agents ◽  
Learning Agent ◽  
The One ◽  
Real World Problems

One of the long-term research goals in machine learning is how to build never-ending learners. The state-of-the-practice in the field of machine learning thus far is still dominated by the one-time learner paradigm: some learning algorithm is utilized on data sets to produce certain model or target function, and then the learner is put away and the model or function is put to work. Such a learn-once-apply-next (or LOAN) approach may not be adequate in dealing with many real world problems and is in sharp contrast with the human’s lifelong learning process. On the other hand, learning can often be brought on through overcoming some inconsistent circumstances. This paper proposes a framework for perpetual learning agents that are capable of continuously refining or augmenting their knowledge through overcoming inconsistencies encountered during their problem-solving episodes. The never-ending nature of a perpetual learning agent is embodied in the framework as the agent’s continuous inconsistency-induced belief revision process. The framework hinges on the agents recognizing inconsistency in data, information, knowledge, or meta-knowledge, identifying the cause of inconsistency, revising or augmenting beliefs to explain, resolve, or accommodate inconsistency. The authors believe that inconsistency can serve as one of the important learning stimuli toward building perpetual learning agents that incrementally improve their performance over time.

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