scholarly journals An Optimized System for the Classification of Meteorological Drought Intensity with Applications in Drought Frequency Analysis

2014 ◽  
Vol 53 (8) ◽  
pp. 1943-1960 ◽  
Author(s):  
Hugo Carrão ◽  
Andrew Singleton ◽  
Gustavo Naumann ◽  
Paulo Barbosa ◽  
Jürgen V. Vogt
Keyword(s):  
Classification System ◽  
Meteorological Drought ◽  
Classification Systems ◽  
Cumulative Distribution ◽  
Monthly Precipitation ◽  
Drought Frequency ◽  
Drought Intensity ◽  
Threshold Levels ◽  
Intensity Threshold ◽  
Drought Frequency Analysis

AbstractThe adequacy of meteorological drought intensity threshold levels based on deviations of monthly precipitation totals from normal climatological conditions is reconsidered. The motivation for this study is the observation that reference classification systems are fixed for all climatological regions, and threshold levels have been proposed without regard for the statistical distribution of accumulated precipitation in space and time. This misrepresentation of precipitation variability may lead to erroneous estimates of meteorological drought onset in specific areas where natural breaks in the cumulative distribution of monthly precipitation do not fit the generalized classification systems. In this study, a new optimized classification system based on the nonparametric “Fisher–Jenks” algorithm is proposed for the estimation of meteorological drought intensity threshold levels from monthly precipitation totals. The optimized classification system is compared using the tabular accuracy index (TAI) to three fixed classification systems that are proposed in the literature and widely applied in the operational setting. An assessment of drought intensity classifications with optimized and fixed threshold levels shows that 1) six optimized categories most accurately divide precipitation totals into the most appropriate drought intensities, 2) optimized thresholds always give considerably improved drought intensity category allocations over fixed thresholds with the same number of categories, and 3) fixed thresholds underestimate the drought onset. An analysis of monthly and long-term drought frequency for Latin America has been conducted for assessing the spatial link between meteorological drought intensity categories computed with the Fisher–Jenks algorithm and different climate classifications. The results show a systematic match between climate variability in the region and spatial patterns of meteorological drought intensity.

scholarly journals Analysis of Trends, Recurrences, Severity and Frequency of Droughts using SPI: Case of OR Tambo DM, Eastern Cape in South Africa

2021 ◽  
Author(s):  
M Nkamisa ◽  
Simbarashe Ndhleve ◽  
MDV Nakin ◽  
A Mngeni ◽  
H Kabiti
Keyword(s):  
South Africa ◽  
National Level ◽  
Standardized Precipitation Index ◽  
Hydrological Drought ◽  
Average Intensity ◽  
Monthly Precipitation ◽  
Drought Frequency ◽  
Drought Intensity ◽  
Local Municipalities

Abstract South Africa is susceptible to droughts. However, there is little documentation on drought occurrence in South Africa at national level and its various administrative boundaries. The study aimed to profile the hydrological drought in ORTDM from 1998–2018; computing their frequency, severity and intensity so as to show areas of high vulnerability. Data used on this study was obtained from South African Weather Services in Pretoria. Standardized Precipitation Index (SPI) was calculated using the Meteorological Drought Monitor (MDM) software computing drought frequency, severity and intensity using 3 and 6 months SPI. The results showed a wide variation in monthly precipitation throughout the year. Coastal areas receive high rainfall than inland municipalities. When recorded in descending order, the drought intensity Nyandeni shows the highest drought frequency with a percentage of 62%, Mhlontlo (58%), KSDM (57%), Ngquza Hill (55%) and Port St Johns showing the least at (52%). The hydrological drought severity frequency and duration varied between 7 days to 9 weeks. Drought intensity class exposed the annual average intensity for the 5 local municipalities represented as follows; KSDM (-0.71), PSJM (-0.99), Ngquza Hill (-0.81), Nyandeni (-0.71) and Mhlontlo (-0.62). Maximum drought intensity for the 5 local municipalities showed the following results KSDM (-2.4), PSJM (-1.8), Ngquza Hill M (-1.9), Nyandeni M (-2.8) and Mhlontlo M (-3.1). The longest drought duration across OR Tambo was experienced in 2014 and has the following durations: KSDM (3 weeks), PSJM (5 weeks), Ngquza Hill (7 weeks), Nyandeni (8 weeks) and Mhlontlo (11 weeks). ORTDM is susceptible to hydrological droughts and the extent vary across local municipalities. The results could be used as a guide to the allocation of resources for drought relief purpose in a way that seeks to prioritize drought prone areas and vulnerable municipality. The SPI could be a useful when forecasting and estimating the frequency, duration and intensity of droughts. However, emphasis should be placed on improving the quality of data as this is key in improving the quality of its outcome.

scholarly journals Toward the Development of a Comprehensive Clinically Oriented Patient Profile: A Systematic Review of the Purpose, Characteristic, and Methodological Quality of Classification Systems of Adult Spinal Deformity

Neurosurgery ◽  
2021 ◽  
Author(s):  
Kenny Yat Hong Kwan ◽  
J Naresh-Babu ◽  
Wilco Jacobs ◽  
Marinus de Kleuver ◽  
David W Polly ◽  
...  
Keyword(s):  
Systematic Review ◽  
Decision Making ◽  
Classification System ◽  
Methodological Quality ◽  
Literature Search ◽  
Adult Spinal Deformity ◽  
Classification Systems ◽  
Systematic Literature Search ◽  
Patient Profile

Abstract BACKGROUND Existing adult spinal deformity (ASD) classification systems are based on radiological parameters but management of ASD patients requires a holistic approach. A comprehensive clinically oriented patient profile and classification of ASD that can guide decision-making and correlate with patient outcomes is lacking. OBJECTIVE To perform a systematic review to determine the purpose, characteristic, and methodological quality of classification systems currently used in ASD. METHODS A systematic literature search was conducted in MEDLINE, EMBASE, CINAHL, and Web of Science for literature published between January 2000 and October 2018. From the included studies, list of classification systems, their methodological measurement properties, and correlation with treatment outcomes were analyzed. RESULTS Out of 4470 screened references, 163 were included, and 54 different classification systems for ASD were identified. The most commonly used was the Scoliosis Research Society-Schwab classification system. A total of 35 classifications were based on radiological parameters, and no correlation was found between any classification system levels with patient-related outcomes. Limited evidence of limited quality was available on methodological quality of the classification systems. For studies that reported the data, intraobserver and interobserver reliability were good (kappa = 0.8). CONCLUSION This systematic literature search revealed that current classification systems in clinical use neither include a comprehensive set of dimensions relevant to decision-making nor did they correlate with outcomes. A classification system comprising a core set of patient-related, radiological, and etiological characteristics relevant to the management of ASD is needed.

scholarly journals Seasonal drought prediction for semiarid northeastern Brazil: verification of six hydro-meteorological forecast products

2018 ◽  
Vol 22 (9) ◽  
pp. 5041-5056 ◽  
Author(s):  
José Miguel Delgado ◽  
Sebastian Voss ◽  
Gerd Bürger ◽  
Klaus Vormoor ◽  
Aline Murawski ◽  
...  
Keyword(s):  
Rainy Season ◽  
Meteorological Drought ◽  
Skill Score ◽  
Hydrological Drought ◽  
Northeastern Brazil ◽  
Drought Indices ◽  
Monthly Precipitation ◽  
Seasonal Forecasts ◽  
Seasonal Drought ◽  
Drought Prediction

Abstract. A set of seasonal drought forecast models was assessed and verified for the Jaguaribe River in semiarid northeastern Brazil. Meteorological seasonal forecasts were provided by the operational forecasting system used at FUNCEME (Ceará's research foundation for meteorology) and by the European Centre for Medium-Range Weather Forecasts (ECMWF). Three downscaling approaches (empirical quantile mapping, extended downscaling and weather pattern classification) were tested and combined with the models in hindcast mode for the period 1981 to 2014. The forecast issue time was January and the forecast period was January to June. Hydrological drought indices were obtained by fitting a multivariate linear regression to observations. In short, it was possible to obtain forecasts for (a) monthly precipitation, (b) meteorological drought indices, and (c) hydrological drought indices. The skill of the forecasting systems was evaluated with regard to root mean square error (RMSE), the Brier skill score (BSS) and the relative operating characteristic skill score (ROCSS). The tested forecasting products showed similar performance in the analyzed metrics. Forecasts of monthly precipitation had little or no skill considering RMSE and mostly no skill with BSS. A similar picture was seen when forecasting meteorological drought indices: low skill regarding RMSE and BSS and significant skill when discriminating hit rate and false alarm rate given by the ROCSS (forecasting drought events of, e.g., SPEI1 showed a ROCSS of around 0.5). Regarding the temporal variation of the forecast skill of the meteorological indices, it was greatest for April, when compared to the remaining months of the rainy season, while the skill of reservoir volume forecasts decreased with lead time. This work showed that a multi-model ensemble can forecast drought events of timescales relevant to water managers in northeastern Brazil with skill. But no or little skill could be found in the forecasts of monthly precipitation or drought indices of lower scales, like SPI1. Both this work and those here revisited showed that major steps forward are needed in forecasting the rainy season in northeastern Brazil.

Computerized Cone Penetration Test for Soil Classification

2008 ◽  
Vol 2053 (1) ◽  
pp. 47-64 ◽  
Author(s):  
Murad Y. Abu-Farsakh ◽  
Zhongjie Zhang ◽  
Mehmet Tumay ◽  
Mark Morvant
Keyword(s):  
Classification System ◽  
Soil Classification ◽  
Cone Penetration Test ◽  
Classification Systems ◽  
Fuzzy Classification ◽  
Classification Methods ◽  
Penetration Test ◽  
Cone Penetration ◽  
Cone Tip Resistance ◽  
Tip Resistance

Computerized MS-Windows Visual Basic software of a cone penetration test (CPT) for soil classification was developed as part of an extensive effort to facilitate the implementation of CPT technology in many geotechnical engineering applications. Five CPT soil engineering classification systems were implemented as a handy, user-friendly, software tool for geotechnical engineers. In the probabilistic region estimation and fuzzy classification methods, a conformal transformation is first applied to determine the profile of soil classification index (U) with depth from cone tip resistance (qc) and friction ratio (Rf). A statistical correlation was established in the probabilistic region estimation method between the U index and the compositional soil type given by the Unified Soil Classification System. Conversely, the CPT fuzzy classification emphasizes the certainty of soil behavior. The Schmertmann and Douglas and Olsen methods provide soil classification charts based on cone tip resistance and friction ratio. However, Robertson et al. proposed a three-dimensional classification system that is presented in two charts: one chart uses corrected tip resistance (qt) and friction ratio (Rf); the other chart uses qt and pore pressure parameter (Bq) as input data. Five sites in Louisiana were selected for this study. For each site, CPT tests and the corresponding soil boring results were correlated. The soil classification results obtained using the five different CPT soil classification methods were compared.

Yoruba Disease Classifications for Planning in Health Care

1983 ◽  
Vol 4 (2) ◽  
pp. 117-122 ◽  
Author(s):  
William R. Brieger ◽  
Jayashree Ramakrishna ◽  
Joshua D. Adeniyi
Keyword(s):  
Health Care ◽  
Primary Health Care ◽  
Classification System ◽  
Training Programs ◽  
Classification Systems ◽  
Disease Classification ◽  
General Point ◽  
Primary Health ◽  
Illness And Disease ◽  
Point Of Departure

An understanding of local concepts of illness and disease that underlie disease classification systems is essential for designing culturally relevant training programs in primary health care. Prior to training personnel in primary health care in Idere, Nigeria, residents were interviewed revealing that two main groups of disease exist. Generally, arun is serious, chronic and contagious, while aisan represents temporary indispositions. When given seventeen conditions to classify, respondents clearly demarked five as arun and five as aisan while the remainder fell in a grey area in between. Ironically, malaria which is a dangerous disease to young children, was classified as aisan. The disease classification system is being used as a general point of departure for discussion during training. Concerning training on the specific diseases, appropriate ideas are reinforced while others are modified all within the context of the local classification system.

scholarly journals Do audiological classification systems cause more confusion than clarity?

2020 ◽  
Keyword(s):  
Classification System ◽  
Intervention Studies ◽  
Classification Systems ◽  
Patient Access ◽  
Access To Services

The lack of a single classification system is clearly problematic, not least because it renders intervention studies difficult to interpret and has implications for patient access to services.

scholarly journals Robust Future Changes in Meteorological Drought in CMIP6 Projections Despite Uncertainty in Precipitation

2021 ◽  
Author(s):  
Anna Ukkola ◽  
Martin De Kauwe ◽  
Michael Roderick ◽  
Gab Abramowitz ◽  
Andy Pitman
Keyword(s):  
Climate Models ◽  
Water Security ◽  
Meteorological Drought ◽  
Resource Planning ◽  
Climate Projections ◽  
Land Area ◽  
Natural Ecosystems ◽  
Drought Duration ◽  
Drought Intensity ◽  
Projected Changes

<p>Understanding how climate change affects droughts guides adaptation planning in agriculture, water security, and ecosystem management. Earlier climate projections have highlighted high uncertainty in future drought projections, hindering effective planning. We use the latest CMIP6 projections and find more robust projections of meteorological drought compared to mean precipitation. We find coherent projected changes in seasonal drought duration and frequency (robust over >45% of the global land area), despite a lack of agreement across models in projected changes in mean precipitation (24% of the land area). Future drought changes are larger and more consistent in CMIP6 compared to CMIP5. We find regionalised increases and decreases in drought duration and frequency that are driven by changes in both precipitation mean and variability. Conversely, drought intensity increases over most regions but is not simulated well historically by the climate models. These more robust projections of meteorological drought in CMIP6 provide clearer direction for water resource planning and the identification of agricultural and natural ecosystems at risk.</p>

Evolution of Hotel Classification System in Russian Federation

2021 ◽  
Vol 12 (1) ◽  
pp. 277
Author(s):  
Dmitry Aleksandrovich KOZLOV
Keyword(s):  
Russian Federation ◽  
Classification System ◽  
State Standards ◽  
Classification Systems ◽  
International Standards ◽  
Economic Activities ◽  
World Tourism Organization ◽  
The Russian Federation ◽  
Tourism Organization

The main aim of this paper is to analyze the approaches to the system of classification of accommodation facilities in the Russian Federation. The United Nations World Tourism Organization pays great attention to the unification of classification systems for accommodation facilities in all countries of the world, issuing appropriate recommendations on tourism statistics systems, classification of economic activities, as well as criteria for interregional harmonization. In the Russian Federation, there are a number of laws, regulations, state standards, building and sanitary norms and rules concerning the classification of accommodation facilities. They are so imperfect that they have to be revised almost annually or even several times a year. The general statistics of accommodation facilities currently do not correspond to world recommendations. The classification system needs to be revised and brought into line with international standards as much as possible.

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