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.

Identification of droughts and heatwaves in the Western Mediterranean, variability and impacts on vegetation and wildfires using the coupled ORCHIDEE-WRF regional model

2020 ◽  
Author(s):  
Antoine Guion ◽  
Solène Turquety ◽  
Jan Polcher ◽  
Romain Pennel ◽  
Lluis Fita
Keyword(s):  
Extreme Events ◽  
Regional Model ◽  
Western Mediterranean ◽  
Plant Phenology ◽  
Extreme Weather Events ◽  
Area Index ◽  
Fire Weather Index ◽  
Mitigation And Adaptation ◽  
Extreme High Temperature ◽  
The Impact

<p>In line with what is expected in a context of global warming, droughts and heatwaves have increased both in frequency and intensity over the last century. Severe wildfires and vegetation depletion can result from those extreme weather events with considerable economic, social and environmental damages.</p><p>For the development of mitigation and adaptation strategies, there is a need for exhaustive vulnerability assessments, including the impacts of droughts and heatwaves on the Mediterranean environment.</p><p>If heatwave characteristics are well documented, similar studies about droughts are partial. Most of them are focused on meteorological droughts while agronomical ones are more complex to identify.</p><p> </p><p>Using a coupled land surface–atmosphere regional model (ORCHIDEE-WRF) with the integration of plant phenology, we present an analysis of droughts and heatwaves occurring in the Western Mediterranean over the last 40 years. These extreme events are identified using two complementary methods: the Percentile Limit Anomalies (PLA) and the Standardized Precipitation Evapotranspiration Index (SPEI).</p><p>Impact assessment analysis show significant and dominant effect of droughts on plant phenology during summer. Evaluated using the Leaf Area Index (LAI), plant depletion can reach more than 50%. Response to drought depends on the vegetation type (long vs short root system) and biome (temperate vs semi-arid).</p><p>The impact of these extreme events on fire risk will be presented based on calculations of the wildfire meteorological risk (Fire Weather Index) and an analysis of the fire activity observed by the MODIS satellite instrument. We show that, even if extreme high temperature is the dominant cause, drought contributes to an increase of risk. Simultaneous heatwaves and droughts are the worst environmental conditions. The observed burned area can be <span>±</span>4 times greater than during non-extreme conditions and the fire duration <span>±</span>0.25 times longer.</p>

scholarly journals Shift Detection in Hydrological Regimes and Pluriannual Low-Frequency Streamflow Forecasting Using the Hidden Markov Model

Water ◽  
2020 ◽  
Vol 12 (7) ◽  
pp. 2058 ◽  
Author(s):  
Larissa Rolim ◽  
Francisco de Souza Filho
Keyword(s):  
Time Series ◽  
Markov Model ◽  
Hidden Markov Model ◽  
Extreme Events ◽  
Hidden Markov ◽  
Low Frequency ◽  
Streamflow Forecasting ◽  
Hydrologic Time Series ◽  
Low Frequency Variability ◽  
The Impact

Improved water resource management relies on accurate analyses of the past dynamics of hydrological variables. The presence of low-frequency structures in hydrologic time series is an important feature. It can modify the probability of extreme events occurring in different time scales, which makes the risk associated with extreme events dynamic, changing from one decade to another. This article proposes a methodology capable of dynamically detecting and predicting low-frequency streamflow (16–32 years), which presented significance in the wavelet power spectrum. The Standardized Runoff Index (SRI), the Pruned Exact Linear Time (PELT) algorithm, the breaks for additive seasonal and trend (BFAST) method, and the hidden Markov model (HMM) were used to identify the shifts in low frequency. The HMM was also used to forecast the low frequency. As part of the results, the regime shifts detected by the BFAST approach are not entirely consistent with results from the other methods. A common shift occurs in the mid-1980s and can be attributed to the construction of the reservoir. Climate variability modulates the streamflow low-frequency variability, and anthropogenic activities and climate change can modify this modulation. The identification of shifts reveals the impact of low frequency in the streamflow time series, showing that the low-frequency variability conditions the flows of a given year.

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.

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 Extreme Weather Events and Its Impacts on Rice Production in Coastal Odisha Region of India

2021 ◽  
Author(s):  
S Vijayakumar ◽  
A.K. Nayak ◽  
N. Manikandan ◽  
Suchismita Pattanaik ◽  
Rahul Tripathi ◽  
...  
Keyword(s):  
Grain Yield ◽  
Extreme Events ◽  
Heavy Precipitation ◽  
Extreme Weather ◽  
Significant Trend ◽  
Extreme Weather Events ◽  
Positive Trend ◽  
Rice Grain ◽  
Weather Events ◽  
Precipitation And Temperature

Abstract The study investigates trend in extreme daily precipitation and temperature over coastal Odisha, India. 18 weather indices (8 related to temperature and 10 related to rainfall) were calculated using RClimDex software package for the period 1980–2010 . Trend analysis was carried out using linear regression and non-parametric Mann-Kendall test to find out the statistical significance of various indices. Results indicated, a strong and significant trend in temperature indices while the weak and non-significant trend in precipitation indices. The positive trend in Tmax mean, Tmin mean, TN90p (warm nights), TX90p (warm days), diurnal temperature range (DTR), warm spell duration indicator (WSDI), consecutive dry days (CDD) indicates increasing the frequency of warming events in coastal Odisha. Similarly, positive trend in highest maximum 1-day precipitation (RX1), highest maximum 2 consecutive day precipitation (RX2), highest maximum 3 consecutive day precipitation (RX3), highest maximum 5 consecutive day precipitation (RX5), number of heavy precipitation days (≥64.5mm), number of very heavy precipitation days (≥124.5mm) and negative trend in the number of rainy days (R2.5mm), consecutive wet days (CWD) indicate changes toward the more intense and poor distribution of precipitation in coastal Odisha. The combined effect of precipitation and temperature extreme events showed negative effects on rice grain yield. With the increasing number of extreme events there was sharp decline in rice grain yield was observed in the same year in all the coastal districts. This study emphasizes the need for new technology/management practice to minimize the impacts of extreme weather events on rice yield.

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 Advances in Modelling and Prediction on the Impact of Human Activities and Extreme Events on Environments

Water ◽  
2020 ◽  
Vol 12 (6) ◽  
pp. 1768
Author(s):  
Matteo Rubinato ◽  
Min Luo ◽  
Xing Zheng ◽  
Jaan H. Pu ◽  
Songdong Shao
Keyword(s):  
Climate Change ◽  
Extreme Events ◽  
Human Activities ◽  
Health And Safety ◽  
Coastal Environments ◽  
Complex Flow ◽  
Mitigation And Adaptation ◽  
Wide Range ◽  
The Impact ◽  
Mountainous River

Fast urbanization and industrialization have progressively caused severe impacts on mountainous, river, and coastal environments, and have increased the risks for people living in these areas. Human activities have changed ecosystems hence it is important to determine ways to predict these consequences to enable the preservation and restoration of these key areas. Furthermore, extreme events attributed to climate change are becoming more frequent, aggravating the entire scenario and introducing ulterior uncertainties on the accurate and efficient management of these areas to protect the environment as well as the health and safety of people. In actual fact, climate change is altering rain patterns and causing extreme heat, as well as inducing other weather mutations. All these lead to more frequent natural disasters such as flood events, erosions, and the contamination and spreading of pollutants. Therefore, efforts need to be devoted to investigate the underlying causes, and to identify feasible mitigation and adaptation strategies to reduce negative impacts on both the environment and citizens. To contribute towards this aim, the selected papers in this Special Issue covered a wide range of issues that are mainly relevant to: (i) the numerical and experimental characterization of complex flow conditions under specific circumstances induced by the natural hazards; (ii) the effect of climate change on the hydrological processes in mountainous, river, and coastal environments, (iii) the protection of ecosystems and the restoration of areas damaged by the effects of climate change and human activities.

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 The impact of climatic extreme events on the feasibility of fully renewable power systems: a case study for Sweden

2018 ◽  
Author(s):  
Stefan Höltinger ◽  
Johann Baumgartner ◽  
Christian Mikovits ◽  
Johannes Schmidt ◽  
Berit Arheimer ◽  
...  
Keyword(s):  
Time Series ◽  
Power Systems ◽  
Wind Power ◽  
Extreme Events ◽  
Power Plants ◽  
Thermal Power ◽  
Physical Models ◽  
Cold Weather ◽  
Pv Generation ◽  
The Impact

Future energy systems with high shares of intermittent renewables will be stressed by climatic extreme events. We assess the frequency, duration, and magnitude of such extreme residual load events with a share of VRE generation of about 50% for the case of Sweden. For our analysis, we use 29 years of river runoff and of wind power and PV generation simulated from physical models. Hourly load is simulated from temperature data with a time series model. The resulting time series are combined with historic capacity and ramping restrictions of hydro and thermal power plants in an optimization model to minimize extreme residual load events. Results indicate that under high VRE shares climatic extreme events affect even highly flexible power systems as the Swedish one. Replacing current nuclear power capacities by wind power results on average in three extreme residual load events per year. These events are partly linked to the observation that wind speeds are likely below seasonal average in very cold weather conditions. Deploying PV generation capacities instead of wind increases the number of extreme residual load events by about 6 %, as most events occur during the winter month when solar generation is close to zero.

scholarly journals Droughts and heatwaves in the Western Mediterranean: impact on vegetation and wildfires using the coupled WRF-ORCHIDEE regional model (RegIPSL)

2021 ◽  
Author(s):  
Antoine Guion ◽  
Solène Turquety ◽  
Jan Polcher ◽  
Romain Pennel ◽  
Sophie Bastin ◽  
...  
Keyword(s):  
Extreme Events ◽  
Land Surface ◽  
Synergistic Effects ◽  
Regional Model ◽  
Western Mediterranean ◽  
Extreme Weather Events ◽  
Fuel Load ◽  
Burned Area ◽  
Area Index ◽  
The Impact

AbstractDroughts and heatwaves in the Mediterranean can induce plant activity decline and severe wildfires leading to considerable economic, social and environmental damages. This study aims at statistically quantifying the isolated and combined impacts of these extreme events based on a combination of regional land surface-atmosphere modeling and satellite observations of surface properties (MODIS). A simulation by the RegIPSL coupled regional model (ORCHIDEE-WRF) over the 1979–2016 period in the Western Mediterranean is used to identify heatwaves and droughts. After an evaluation of the model performance against surface observations of temperature and precipitation, a spatio-temporal analysis is conducted using specific indicators of extreme events: Percentile Limit Anomalies (PLA) and the Standardized Precipitation Evapotranspiration Index (SPEI). The impact on vegetation and wildfires is assessed using the MODIS observations of Leaf Area Index (LAI), burned area (BA) and fire radiative power (FRP), clustered by simulated extreme weather events. Due to water stress, droughts lead to significant biomass decrease (− 10$$\%$$ % LAI on average and reaching − 23$$\%$$ % in some areas). The isolated effect of heatwaves is smaller ($$\sim$$ ∼  − 3$$\%$$ % LAI) so that the combined effect is dominated by the impact of droughts. Heatwaves and droughts significantly exacerbate wildfire regimes. Through synergistic effects, simultaneous droughts and heatwaves increase BA and FRP by 2.1 and 2.9 times, respectively, compared to normal conditions. By reducing biomass, droughts slightly decrease fuel availability. However, our results show that the inter-annual variation in fire activity is mainly driven by weather conditions rather than fuel load.

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