scholarly journals Spatiotemporal analysis of some extreme rainfall indices over Iraq (1981–2017)

2021 ◽  
Vol 30 (2) ◽  
pp. 221-235
Author(s):  
Alaa Al-Lami ◽  
Hasanain Al-Shamarti ◽  
Yaseen Al-Timimi
Keyword(s):  
Time Series ◽  
Extreme Rainfall ◽  
Spatiotemporal Analysis ◽  
Rate Of Change ◽  
Mean Annual Precipitation ◽  
Spatiotemporal Pattern ◽  
Northwestern Part ◽  
Positive Trend ◽  
Human Environment ◽  
The Impact

Extreme rainfall is one of the environmental hazards with disastrous effects on the human environment. Water resources management is very vulnerable to any changes in rainfall intensities. A spatiotemporal analysis is essential for study the impact of climate change and variability on extreme rainfall. In this study, daily rainfall data for 36 meteorological stations in Iraq during 1981–2017 were used to investigate the spatiotemporal pattern of 10 extreme rainfall indices using RClimDex package. These indices were classified into two categories: rainfall total (PRCPTOT, SDII, R95p, R99p, RX1day, and RX5day) and rainfall days (CDD, CWD, R10, and R20). Depending on the mean annual precipitation data, the study area was divided into three climatic zones to examine the time series features of those 10 indices. Results showed a tendency to increase in precipitation toward the northwestern part of Iraq, and more than 70% of stations achieved a positive trend for most indices. The most frequent negative trend appeared in eight stations distributed in the western and southern parts of Iraq, namely (Heet, Haditha, Anah, Rutba, Qaim, Nukheb, Najaf, and Fao). A significant positive trend appeared obviously in PRCPTOT and R95p with a rate of 0.1–4.6 and 0.5–2.7 mm per year, respectively. Additionally, the least trend increasing appeared in all precipitation days indices specifically in R10 and R20. Time series analyses revealed a positive trend in all regions under study, except SDII in the southern region. The most significant rate of change was noticed in regions one and two (northern and middle parts of Iraq), particularly for PRCPTOT and R95p 3.26 and 2.45 mm per day, respectively. Only the northern and eastern regions of Iraq experienced a high probability of significant extreme rainfall.

scholarly journals Selecting Time Series Length to Moderate the Impact of Nonstationarity in Extreme Rainfall Analyses

2018 ◽  
Vol 57 (10) ◽  
pp. 2285-2296 ◽  
Author(s):  
Arthur T. DeGaetano ◽  
Christopher Castellano
Keyword(s):  
Time Series ◽  
Location Parameter ◽  
Extreme Rainfall ◽  
Extreme Value ◽  
Series Length ◽  
Limited Length ◽  
Long Term Trends ◽  
Recurrence Intervals ◽  
Stationary Location ◽  
The Impact

AbstractObserved and projected increases in the frequency of extreme rainfall complicate the extreme value analyses of precipitation that are used to guide engineering design specifications, because conventional methods assume stationarity. Uncertainty in the magnitude of the trend in future years precludes directly accounting for the trend in these analyses. While previous extreme value analyses have sought to use as long a record as possible, it is shown using stochastically generated time series that this practice exacerbates the potential error introduced by long-term trends. For extreme precipitation series characterized by a trend in the location parameter exceeding approximately 0.005% yr−1, limiting the record length to fewer than 70 years is recommended. The use of longer time periods results in partial-duration series that are significantly different from their stationary counterparts and a greater percentage of rainfall extremes that exceed the 90% confidence interval corresponding to a stationary distribution. The effect is most pronounced on the shortest (i.e., 2 yr) recurrence intervals and generally becomes undetectable for recurrence intervals of more than 25 years. The analyses also indicate that the practice of including stations with records of limited length that end several decades prior to the present should be avoided. Distributions having a stationary location parameter but trended scale parameter do not exhibit this behavior.

scholarly journals Influence of Government Price Regulation on the Price, Volume and Spending of Antibiotics in China: A Controlled Interrupted Time Series Study

2020 ◽  
Author(s):  
Haishaerjiang Wushouer ◽  
Zhenhuan Luo ◽  
Xiaodong Guan ◽  
Luwen Shi
Keyword(s):  
Time Series ◽  
Interrupted Time Series ◽  
Price Regulation ◽  
Chinese Government ◽  
Positive Trend ◽  
Daily Cost ◽  
Average Hospital ◽  
Intervention Point ◽  
The Impact ◽  
Average Daily Cost

Background: Chinese government established maximum retail prices for antibiotics listed in China’s National Reimbursement List in February 2013. This study aimed to analyze the impact of pharmaceutical price regulation on the price, volume and spending of antibiotics in China. Methods: An interrupted time series design with comparison series was used to examine impacts of the policy changes on average daily cost, monthly hospital purchase volume and spending of the 11 price-regulated antibiotics and 40 priceunregulated antibiotics in 699 hospitals. One intervention point was applied to assess the impact of policy. Results: After government price regulation, compared to price-unregulated antibiotics, the average daily cost of the price-regulated group declined rapidly (β=-5.68, P<.001). The average hospital monthly purchase spending of priceregulated antibiotics also decreased rapidly (β=-0.49, P<.010) and a positive trend change (β=0.04, P<.001) in average hospital spending of price-unregulated antibiotics was found. Conclusion: Government regulation can reduce the prices and spending of price-regulated antibiotics. To control increasing expenditure, besides price caps regulation, factors determining drug utilization also need to be considered in policy designing.

The impact of the quality of democracy on the economic growth of provinces in Indonesia

2021 ◽  
Vol 1 (2) ◽  
pp. 121-132
Author(s):  
Nairobi Nairobi ◽  
◽  
Nur Rita Santi ◽  
Fadeli Yusuf Afif ◽  
◽  
...  
Keyword(s):  
Economic Growth ◽  
Time Series ◽  
Foreign Investment ◽  
Good Condition ◽  
Series Data ◽  
Positive Trend ◽  
Analysis Tool ◽  
Quality Of Democracy ◽  
The Impact

Abstract Purpose: The impact of democracy on economic growth is an interesting study of economic institutions and there is still debate about the impact on economic growth. One side of the research finds that democracy has a significant and positive impact on economic growth, but the other side states that the improvement of the country's democracy causes economic growth to decline. This study aims to examine the impact of the quality of democracy on economic growth at the provincial level in Indonesia. Research methodology: The data used in this study use panel data using the Eviews 9.0 analysis tool, so that the best method named the Random Effect Model is obtained. Result: The results show that democracy in Indonesia has a significant impact on economic growth and there is a positive trend in the long run. Other variables used are labor and foreign investment, which statistically, if these variables occur, can increase economic growth in Indonesia and increase employment and data on foreign investment play a role in driving economic growth. Economic growth in Indonesia is already in good condition and the economic growth that occurs is convergence growth which shows that some provinces that are poor/underdeveloped can catch up with developed provinces. Limitations: This study uses fairly short time-series data, so that the addition of a longer time-series will of course give better results. Contribution: Improvements in democracy in Indonesia should also strengthen democratic norms that apply in society, such as reducing corrupt behaviors, especially political corruption and money politics to get public office because if this behavior cannot be corrected, then democracy will have little impact on the economy.

scholarly journals Impact of ICD-9-CM to ICD-10-CM coding transition on trauma hospitalization trends among young adults in 12 states

2021 ◽  
Vol 8 (1) ◽  
Author(s):  
Yuri V. Sebastião ◽  
Gregory A. Metzger ◽  
Deena J. Chisolm ◽  
Henry Xiang ◽  
Jennifer N. Cooper
Keyword(s):  
Time Series ◽  
Young Adults ◽  
Injury Severity ◽  
Traumatic Injury ◽  
Interrupted Time Series ◽  
Positive Trend ◽  
Level Of Evidence ◽  
Severity Of Injury ◽  
Icd 10 ◽  
The Impact

Abstract Background We aimed to estimate the impact of the International Classification of Diseases, Tenth Revision, Clinical Modification (ICD-10-CM) coding transition on traumatic injury-related hospitalization trends among young adults across a geographically and demographically diverse group of U.S. states. Methods Interrupted time series analyses were conducted using statewide inpatient databases from 12 states and including traumatic injury-related hospitalizations in adults aged 19–44 years in 2011–2017. Segmented regression models were used to estimate the impact of the October 2015 coding transition on external cause of injury (ECOI) completeness (percentage of hospitalizations with a documented ECOI code) and on population-level rates of injury-related hospitalizations by nature, intent, mechanism, and severity of injury. Results The transition to ICD-10-CM was associated with a drop in ECOI completion in the transition month (− 3.7%; P < .0001), but there was no significant change in the positive trend in ECOI completion from the pre- to post-transition periods. There were significant increases post-transition in the measured rates of hospitalization for traumatic brain injury (TBI), unintentional injury, mild injury (injury severity score (ISS) < 9), and injuries caused by drowning, firearms, machinery, other pedestrian, suffocation, and unspecified mechanism. Conversely, there were significant decreases in October 2015 in the rates of hospitalization for assault, injuries of undetermined intent, injuries of moderate severity (ISS 9–15), and injuries caused by fire/burn, other pedal cyclist, other transportation, natural/environmental, and other specified mechanism. A significant increase in the percentage of hospitalizations classified as resulting from severe injury (ISS > 15) was observed when the general equivalence mapping maximum severity method for converting ICD-10-CM codes to ICD-9-CM codes was used. State-specific results for the outcomes of ECOI completion and TBI-related hospitalization rates are provided in an online supplement. Conclusions The U.S. transition from ICD-9-CM to ICD-10-CM coding led to a significant decrease in ECOI completion and several significant changes in measured rates of injury-related hospitalizations by injury intent, mechanism, nature, and severity. The results of this study can inform the design and analysis of future traumatic injury-related health services research studies that use both ICD-9-CM and ICD-10-CM coded data. Level of evidence II (Interrupted Time Series)

scholarly journals A critical assessment of extreme events trends in times of global warming

2022 ◽  
Vol 137 (1) ◽  
Author(s):  
Gianluca Alimonti ◽  
Luigi Mariani ◽  
Franco Prodi ◽  
Renato Angelo Ricci
Keyword(s):  
Time Series ◽  
Extreme Events ◽  
Surface Wind ◽  
Extreme Weather Events ◽  
Global Changes ◽  
Positive Trend ◽  
Precipitation Frequency ◽  
Mitigation And Adaptation ◽  
The Impact ◽  
Response Indicators

AbstractThis article reviews recent bibliography on time series of some extreme weather events and related response indicators in order to understand whether an increase in intensity and/or frequency is detectable. The most robust global changes in climate extremes are found in yearly values of heatwaves (number of days, maximum duration and cumulated heat), while global trends in heatwave intensity are not significant. Daily precipitation intensity and extreme precipitation frequency are stationary in the main part of the weather stations. Trend analysis of the time series of tropical cyclones show a substantial temporal invariance and the same is true for tornadoes in the USA. At the same time, the impact of warming on surface wind speed remains unclear. The analysis is then extended to some global response indicators of extreme meteorological events, namely natural disasters, floods, droughts, ecosystem productivity and yields of the four main crops (maize, rice, soybean and wheat). None of these response indicators show a clear positive trend of extreme events. In conclusion on the basis of observational data, the climate crisis that, according to many sources, we are experiencing today, is not evident yet. It would be nevertheless extremely important to define mitigation and adaptation strategies that take into account current trends.

scholarly journals An enhancement to sea ice motion and age products at the National Snow and Ice Data Center (NSIDC)

2020 ◽  
Vol 14 (5) ◽  
pp. 1519-1536 ◽  
Author(s):  
Mark A. Tschudi ◽  
Walter N. Meier ◽  
J. Scott Stewart
Keyword(s):  
Time Series ◽  
Sea Ice ◽  
Data Center ◽  
Ice Cover ◽  
Ice Age ◽  
The Arctic ◽  
Significant Shift ◽  
Positive Trend ◽  
The Impact ◽  
Snow And Ice

Abstract. A new version of sea ice motion and age products includes several significant upgrades in processing, corrects known issues with the previous version, and updates the time series through 2018, with regular updates planned for the future. First, we provide a history of these NASA products distributed at the National Snow and Ice Data Center. Then we discuss the improvements to the algorithms, provide validation results for the new (Version 4) and older versions, and intercompare the two. While Version 4 algorithm changes were significant, the impact on the products is relatively minor, particularly for more recent years. The changes in Version 4 reduce motion biases by ∼ 0.01 to 0.02 cm s−1 and error standard deviations by ∼ 0.3 cm s−1. Overall, ice speed increased in Version 4 over Version 3 by 0.5 to 2.0 cm s−1 over most of the time series. Version 4 shows a higher positive trend for the Arctic of 0.21 cm s−1 per decade compared to 0.13 cm s−1 per decade for Version 3. The new version of ice age estimates indicates more older ice than Version 3, especially earlier in the record, but similar trends toward less multiyear ice. Changes in sea ice motion and age derived from the product show a significant shift in the Arctic ice cover, from a pack with a high concentration of older ice to a sea ice cover dominated by first-year ice, which is more susceptible to summer melt. We also observe an increase in the speed of the ice over the time series ≥ 30 years, which has been shown in other studies and is anticipated with the annual decrease in sea ice extent.

scholarly journals Spatiotemporal Analysis of Land Use and Land Cover (LULC) Changes and Precipitation Trends in Shanghai

2020 ◽  
Vol 10 (21) ◽  
pp. 7897
Author(s):  
Qin Jiang ◽  
Xiaogang He ◽  
Jun Wang ◽  
Jiahong Wen ◽  
Haizhen Mu ◽  
...  
Keyword(s):  
Land Use ◽  
Land Cover ◽  
Extreme Precipitation ◽  
Urban Climate ◽  
Central Area ◽  
Spatiotemporal Analysis ◽  
Rate Of Change ◽  
Lulc Changes ◽  
Increasing Trends ◽  
The Impact

The impacts of anthropogenic land use and land cover (LULC) changes on the spatiotemporal distribution of precipitation in megacities have been highlighted in studies on urban climate change. In this study, we conducted a quantitative analysis of urban growth on the impact on precipitation in Shanghai, China. We considered four periods of LULC data in 1979, 1990, 2000 and 2010, in addition to the long-term (1979–2010) trend of daily precipitation. The results indicate that the trend in precipitation exhibit different characteristics for urban (Ur), outskirt of urban (OUr) and outer suburb (OS) regions. Most Ur regions had an upward trend in annual and extreme precipitation during 1979–2010, while annual precipitation for the OUr and OS regions exhibited a decreasing trend. From 1979 to 2010, the areas of fastest expansion were located in the OUr region. The OS region, far away from the central area, had a relatively lower rate of change. In addition, OUr regions with rapid LULC changes exhibited higher increasing trends in annual and daily extreme precipitation, which is critical for the identification of frequent precipitation areas and the reliable projection of further changes.

scholarly journals Detecting regime shifts in communities using estimated rates of change

2020 ◽  
Vol 77 (4) ◽  
pp. 1546-1555 ◽  
Author(s):  
Eric J Pedersen ◽  
Mariano Koen-Alonso ◽  
Tyler D Tunney
Keyword(s):  
Time Series ◽  
Rapid Change ◽  
Single Species ◽  
Community Change ◽  
Regime Shifts ◽  
Rate Of Change ◽  
Spatiotemporal Pattern ◽  
Wide Range ◽  
Capita Rate ◽  
Per Capita

Abstract Regime shifts (periods of rapid change punctuating longer periods of lower variability) are observed in a wide range of ecosystems, and effective fisheries management requires the ability to detect these shifts. Detecting shifts is straightforward in single-species time series when transitions are detectable as periods of rapid change. However, shifts in complex and spatially structured communities may be harder to detect. We propose an approach to characterize community regime shifts, using nonparametric spatiotemporal regression models to estimate three indicators of community change (the among-species mean rate of change, mean per-capita rate of change, and standard deviation of per-capita rate of change). These indicators can detect shifts that result in either changes in abundance or composition. We applied our approach to a 37-year community biomass time series that spans the Newfoundland Shelf groundfish collapse. Our method detected a community shift earlier than alternative single-indicator breakpoint approaches and gave additional insight into the spatiotemporal pattern of the change, including detecting three separate periods of change and characterizing the first locations to show signs of recovery. The indicators applied in this study provide novel insights into Newfoundland groundfish dynamics and should be useful in the characterization of other abrupt ecological changes.

Statistical evaluation of temporary changes in annual precipitation in the plain territory of Ukraine

2020 ◽  
Vol 101-102 (3-4) ◽  
pp. 7-18
Author(s):  
Liudmyla Palamarchuk ◽  
Iryna Shedemenko
Keyword(s):  
Time Series ◽  
Linear Trend ◽  
Statistical Characteristics ◽  
Annual Precipitation ◽  
Mean Annual Precipitation ◽  
Positive Trend ◽  
The South ◽  
Positive Skewness ◽  
Weather Stations ◽  
Skewness And Kurtosis

The field of precipitation of the plain territory of Ukraine is investigated according to the data of evenly spaced 18 weather stations. The annual precipitation is analyzed for periods of different duration (from the beginning of observations at the station until 2015) and for the period 1961-2015. The main statistical characteristics are calculated, the patterns of their changes in the study area are shown. Gradient of decrease in multi-year annual precipitation for 1961-2015 (650 to 400 mm) directed from the northwest to the south and southeast of the country. The value of positive skewness and kurtosis, the coefficient of variation (0.16-0.26), on the contrary, increases in this direction. The standard deviation (91-137 mm) is maximum in the southwest and in the center of the plain part of Ukraine. It was determined that the distribution of annual precipitation can be considered normal, mainly with positive skewness and kurtosis. Multi-year fluctuations in annual precipitation are approximated by linear trend equations and a polynomial of the 6th degree. Regions with a negative and positive linear trend of annual precipitation in 1961-2015 were identified. A downward trend in precipitation was noted at stations located in a “strip” from the southwest (Chernivtsi) to the northeast (Sumy) through the center of Ukraine. In the south-west of this region (Vinnytsia), the decrease in precipitation is the greatest: the negative linear trend is statistically significant, the slope of the trend is -2.35, the coefficient of determination is 0.14; mean annual precipitation for 1991-2015 compared to 1961-1990 less by 10.5%, 53.4 mm. In the rest of the plain territory of the country, there was a tendency towards an increase in precipitation, but the positive trend for all stations is statistically insignificant. The absence of statistically significant linear trends (except for Vinnytsia) can be explained by the relative stability of the multi-year precipitation regime during this period. The use of a more complex approximation and a long time series of observations increased the trend approximation confidence, but the influence of these factors is not unambiguous for all weather stations. On the graphs of polynomial trends, the cycle manifestation in the time series of annual precipitation depends on the length of the observation series and decreases from west to east of Ukraine. The duration of the cycles is 25-30 and 35-40 years when determined according to the data of 1961-2015, and from 70 to 90 and 120 years according to the series of observations more than 100 years. In 2016-2025, as shown by estimates by the equations of polynomials of the 6th degree, a decrease in annual precipitation will prevail on the plain territory of Ukraine compared to 1961-2015. The largest decrease (by 10-13%) is likely in the central regions (Poltava, Dnipro). an increase (by 5%) - in the southwest (Vinnitsa, Chernivtsi).

scholarly journals Defining the climatic signal in stream salinity trends using the Interdecadal Pacific Oscillation and its rate of change

2006 ◽  
Vol 3 (5) ◽  
pp. 2963-2990 ◽  
Author(s):  
V. H. McNeil ◽  
M. E. Cox
Keyword(s):  
Time Series ◽  
Climatic Variability ◽  
Geographical Area ◽  
Shallow Groundwater ◽  
Rate Of Change ◽  
Interdecadal Pacific Oscillation ◽  
New Approach ◽  
Decadal Scale ◽  
Hydrological Cycles ◽  
The Impact

Abstract. The impact of landuse on stream salinity is difficult to separate from decadal climatic variability, as the decadal scale climatic cycles in ground water and stream hydrology have similar wavelengths to the landuse pattern. These hydrological cycles determine the stream salinity through accumulation or release of salt in the landscape. The Interdecadal Pacific Oscillation (IPO) has been investigated before as an indicator of hydrological and related time series in the southern hemisphere. This study presents a new approach, which uses the rate of change in the IPO, rather than just its absolute value, to define an indicator for the climate component of ambient shallow groundwater tables and corresponding stream salinity. Representative time series of water table and stream salinity indicators are compiled, using an extensive but irregular database covering a very wide geographical area. These are modelled with respect to the IPO and its rate of change to derive climatic indicators. The effect of removing the decadal climatic influence from stream salinity trends is demonstrated.

Sign in / Sign up

Export Citation Format

Share Document