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.

Major weather-related risks to crop performance along the Australian wheat belt for recent past and longer-term historical weather records

2021 ◽  
Author(s):  
Gennady Bracho Mujica ◽  
Peter Hayman ◽  
Victor Sadras ◽  
Bertram Ostendorf ◽  
Nicole Ferreira C. R. ◽  
...  
Keyword(s):  
Grain Yield ◽  
Extreme Events ◽  
Extreme Weather Events ◽  
Yield Reduction ◽  
Recent Past ◽  
Weather Extremes ◽  
Crop Failure ◽  
Weather Events ◽  
Australian Wheat ◽  
Historical Past

<p>Extreme events, such as drought, heat and/or frost are among the major weather-related causes of yield reduction and crop failure worldwide. Changes in the frequency and intensity of such weather extremes affect the shape and scale of yield distributions. Wheat growers, in Australia, are particularly vulnerable to climate due to its high variability. Risks of both, extremely high or low temperatures and water stress occurring simultaneously or at different crop stages within the growing season (May-October, e.g. frost mid-season, drought during the season and heat towards the end) often lead to yield reductions, or sometimes even to crop failure. In this study, we focused on assessing the frequency and impact of these relevant extreme weather events (i.e. drought, heat and frost) affecting wheat production in Australia. Specifically, we used a widely used and calibrated crop model (APSIM) to simulate wheat grain yield, and determine probability density functions (PDFs) of grain yield and crop failure. Chances of crop failure due to these extreme events are explored for the recent past (1991-2020) and the longer-term historical past (1901-1990). Key adaption strategies to minimise the impacts of these extreme events, and reduce crop failure risk are assessed in this study, including early sowing and cultivar choice. Our findings are in line with recent studies, indicating that drought and heat are major risk factors contributing to reduced yields or crop failure. However, due to the timing, frequency and impacts of frost events on wheat productivity, frost also remains a relevant risk for the wheat industry in Australia.</p>

scholarly journals Impacts of compound extreme weather events on ozone in the present and future

2018 ◽  
Author(s):  
Junxi Zhang ◽  
Yang Gao ◽  
Kun Luo ◽  
L. Ruby Leung ◽  
Yang Zhang ◽  
...  
Keyword(s):  
Extreme Events ◽  
Heat Waves ◽  
Extreme Weather ◽  
Extreme Weather Events ◽  
Low Wind Speed ◽  
Weather Events ◽  
The Us ◽  
The Future ◽  
Compound Events ◽  
Ozone Episodes

Abstract. The Weather Research and Forecasting model with Chemistry (WRF/Chem) was used to study the effect of extreme weather events on ozone in US for historical (2001–2010) and future (2046–2055) periods under RCP8.5 scenario. During extreme weather events, including heat waves, atmospheric stagnation, and their compound events, ozone concentration is much higher compared to non-extreme events period. A striking enhancement of effect during compound events is revealed when heat wave and stagnation occur simultaneously and both high temperature and low wind speed promote the production of high ozone concentrations. In regions with high emissions, compound extreme events can shift the high-end tails of the probability density functions (PDFs) of ozone to even higher values to generate extreme ozone episodes. In regions with low emissions, extreme events can still increase high ozone frequency but the high-end tails of the PDFs are constrained by the low emissions. Despite large anthropogenic emission reduction projected for the future, compound events increase ozone more than the single events by 10 % to 13 %, comparable to the present, and high ozone episodes are not eliminated. Using the CMIP5 multi-model ensemble, the frequency of compound events is found to increase more dominantly compared to the increased frequency of single events in the future over the US, Europe, and China. High ozone episodes will likely continue in the future due to increases in both frequency and intensity of extreme events, despite reductions in anthropogenic emissions of its precursors. However, the latter could reduce or eliminate extreme ozone episodes, so improving projections of compound events and their impacts on extreme ozone may better constrain future projections of extreme ozone episodes that have detrimental effects on human health.

scholarly journals Assessing the impacts of extreme weather events on potable water quality: the value to managers of a highly participatory, integrated modelling approach

2018 ◽  
Vol 2 (1) ◽  
pp. 9-24
Author(s):  
Edoardo Bertone ◽  
Oz Sahin ◽  
Russell Richards ◽  
Anne Roiko
Keyword(s):  
Water Quality ◽  
Decision Support ◽  
Extreme Events ◽  
Drinking Water Treatment ◽  
Extreme Weather ◽  
Integrated Modelling ◽  
Extreme Weather Events ◽  
Weather Events ◽  
Sd Model

Abstract A decision support tool was created to estimate the treatment efficiency of an Australian drinking water treatment system based on different combinations of extreme weather events and long-term changes. To deal with uncertainties, missing data, and nonlinear behaviours, a Bayesian network (BN) was coupled with a system dynamics (SD) model. The preliminary conceptual structures of these models were developed through stakeholders' consultation. The BN model could rank extreme events, and combinations of them, based on the severity of their impact on health-related water quality. The SD model, in turn, was used to run a long-term estimation of extreme events' impacts by including temporal factors such as increased water demand and customer feedback. The integration of the two models was performed through a combined Monte Carlo–fuzzy logic approach which allowed to take the BN's outputs as inputs for the SD model. The final product is a participatory, multidisciplinary decision support system allowing for robust, sustainable long-term water resources management under uncertain conditions for a specific location.

scholarly journals Awareness of climate change's impacts and motivation to adapt are not enough to drive action: A look of Puerto Rican farmers after Hurricane Maria

PLoS ONE ◽  
2021 ◽  
Vol 16 (1) ◽  
pp. e0244512
Author(s):  
Luis Alexis Rodríguez-Cruz ◽  
Meredith T. Niles
Keyword(s):  
Climate Change ◽  
Puerto Rican ◽  
Adaptive Capacity ◽  
Extreme Events ◽  
Structural Equation ◽  
Climate Adaptation ◽  
Psychological Distance ◽  
Extreme Weather ◽  
Extreme Weather Events ◽  
Weather Events

Understanding how perceptions around motivation, capacity, and climate change’s impacts relate to the adoption of adaptation practices in light of experiences with extreme weather events is important in assessing farmers’ adaptive capacity. However, very little of this work has occurred in islands, which may have different vulnerabilities and capacities for adaptation. Data of surveyed farmers throughout Puerto Rico after Hurricane Maria (n = 405, 87% response rate) were used in a structural equation model to explore the extent to which their adoption of agricultural practices and management strategies was driven by perceptions of motivation, vulnerability, and capacity as a function of their psychological distance of climate change. Our results show that half of farmers did not adopt any practice or strategy, even though the majority perceived themselves capable and motivated to adapt to climate change, and understood their farms to be vulnerable to future extreme events. Furthermore, adoption was neither linked to these adaptation perceptions, nor to their psychological distance of climate change, which we found to be both near and far. Puerto Rican farmers’ showed a broad awareness of climate change’s impacts both locally and globally in different dimensions (temporal, spatial, and social), and climate distance was not linked to reported damages from Hurricane Maria or to previous extreme weather events. These results suggest that we may be reaching a tipping point for extreme events as a driver for climate belief and action, especially in places where there is a high level of climate change awareness and continued experience of compounded impacts. Further, high perceived capacity and motivation are not linked to actual adaptation behaviors, suggesting that broadening adaptation analyses beyond individual perceptions and capacities as drivers of climate adaptation may give us a better understanding of the determinants to strengthen farmers’ adaptive capacity.

Extreme Weather and Climate

2017 ◽  
Author(s):  
Friederike Otto
Keyword(s):  
Extreme Events ◽  
The United States ◽  
Extreme Weather ◽  
Extreme Weather Events ◽  
Weather Event ◽  
Weather Forecasts ◽  
Global Mean Temperature ◽  
Mean Temperature ◽  
Weather Events ◽  
Global Mean

Natural disasters and extreme weather events have been of great societal importance throughout history and often brought everyday life to a catastrophic halt, in a way sometimes comparable to wars and epidemics, only without the lead time. Extreme weather events with large impacts serve as an anchor point of the collective memory of the population in the affected area. Every northern German of the right age remembers the storm surge of 1962 and where they were at the time and has friends or family effected by the event. The “dust bowl” of the 1930s with extensive droughts and heat waves shaped the life of a generation in the United States, and the Sahel droughts in the 1960s and 1970s led to famine and dislocation of population on a massive scale the region arguably never quite recovered from. Hurricane Hyian in 2013 is said to have directly influenced the outcome of the annual Conference of the Parties (COP) United Nation Framework Convention for Climate Change Negotiations in Warsaw, leading to the inclusion of a mechanism to deal with loss and damage from climate-related disasters. Though earthquakes are still fairly unpredictable on short timescales, this is not the case for weather events. Weather forecasts today are so good that we normally know the time and location of the landfall of a hurricane within a 100-mile radius days in advance. Improvements in the prediction of slow-onset events such as droughts (which depend on the rainfall over a large region and whole season) are less striking but have still improved dramatically in the late 20th and early 21st centuries. One of the major reasons for the large increase in the accuracy of weather forecasts is the exponential increase in computing power, which allows scientists to predict and study extreme weather events using complex computer models, simulating possible weather events under certain conditions to understand the statistics of and physical mechanisms behind extreme events. Extreme events are by definition rare and thus impossible to understand from historical records of weather observation alone. Despite the progress on our understanding of and ability to predict extreme weather events, substantial uncertainties remain. Two aspects are of particular importance. Firstly, we know that the climate is changing, having observed almost a one-degree increase in global mean temperature. However, global mean temperature doesn’t kill anyone, extreme weather events do. Their frequency and intensity is changing and will continue to change, but the extent of these changes depends on a host of both global and local factors. Secondly, whether or not a rare weather event leads to extreme impacts depends largely on the vulnerability and exposure of the affected societies. If these are high, even a perfectly forecasted weather event leads to disaster.

scholarly journals Environmental prediction, risk assessment and extreme events: adaptation strategies for the developing world

2011 ◽  
Vol 369 (1956) ◽  
pp. 4768-4797 ◽  
Author(s):  
Peter J. Webster ◽  
Jun Jian
Keyword(s):  
Climate Change ◽  
Fresh Water ◽  
Extreme Events ◽  
Water Resource Management ◽  
Developing World ◽  
Rural Poverty ◽  
Extreme Weather ◽  
Extreme Weather Events ◽  
Weather Events ◽  
Environmental Prediction

The uncertainty associated with predicting extreme weather events has serious implications for the developing world, owing to the greater societal vulnerability to such events. Continual exposure to unanticipated extreme events is a contributing factor for the descent into perpetual and structural rural poverty. We provide two examples of how probabilistic environmental prediction of extreme weather events can support dynamic adaptation. In the current climate era, we describe how short-term flood forecasts have been developed and implemented in Bangladesh. Forecasts of impending floods with horizons of 10 days are used to change agricultural practices and planning, store food and household items and evacuate those in peril. For the first time in Bangladesh, floods were anticipated in 2007 and 2008, with broad actions taking place in advance of the floods, grossing agricultural and household savings measured in units of annual income. We argue that probabilistic environmental forecasts disseminated to an informed user community can reduce poverty caused by exposure to unanticipated extreme events. Second, it is also realized that not all decisions in the future can be made at the village level and that grand plans for water resource management require extensive planning and funding. Based on imperfect models and scenarios of economic and population growth, we further suggest that flood frequency and intensity will increase in the Ganges, Brahmaputra and Yangtze catchments as greenhouse-gas concentrations increase. However, irrespective of the climate-change scenario chosen, the availability of fresh water in the latter half of the twenty-first century seems to be dominated by population increases that far outweigh climate-change effects. Paradoxically, fresh water availability may become more critical if there is no climate change.

Trois phénomènes météorologiques exceptionnels durant l'automne 2020

2021 ◽  
pp. 115
Author(s):  
Michaël Kreitz
Keyword(s):  
Heavy Precipitation ◽  
Extreme Weather ◽  
Extreme Weather Events ◽  
Precipitation Event ◽  
Heavy Precipitation Event ◽  
Weather Events

Durant cet automne 2020, la France est concernée par trois phénomènes météorologiques exceptionnels. Tout d'abord, le 19 septembre, un épisode cévenol intense apporte 700 mm en 12 heures sur la région de Valleraugue. Puis, le 1er octobre, la tempête Alex traverse le nord-ouest de la France, où les rafales atteignent 186 km/h à Belle-Île-en-Mer en raison de la présence d'un sting jet. Le lendemain, un nouvel épisode fortement précipitant déverse localement 500 mm de pluie sur les Alpes-Maritimes. Ces trois phénomènes ont tous relevé d'une vigilance rouge. During fall 2020, France is concerned by three extreme weather events. First, on september 19th , an intense cévenol event brings 700 mm in 12 hours over Valleraugue area. Then, on October the 1 st , Alex windstorm crosses northwestern France where gusts reach 186 km/h over Belle-Île-en-Mer because of the occurrence of a sting jet. The day after, a new heavy precipitation event spills a 500 mm rainfall locally over Alpes-Maritimes. All those three events received a red warning.

Climate Research and Reinsurance*

2004 ◽  
Vol 85 (5) ◽  
pp. 697-708 ◽  
Author(s):  
Richard J. Murnane
Keyword(s):  
Extreme Events ◽  
Extreme Weather ◽  
The Arctic ◽  
Extreme Weather Events ◽  
Quasi Biennial Oscillation ◽  
Research Areas ◽  
Weather Events ◽  
Mutual Interest ◽  
Insured Losses ◽  
Catastrophe Reinsurance

Extreme weather events produce some of the most deadly and costly natural disasters and are a major concern of the catastrophe reinsurance industry. For example, in 1992 Hurricane Andrew caused over $20 billion (in 2002 U.S. dollars) in insured losses, the largest loss on record due to a natural disaster. In addition, 26 of the top 30 insured losses were produced by extreme weather events, mainly landfalling hurricanes and typhoons and European windstorms. A better understanding of how extreme events vary with climate would benefit the reinsurance industry and society. The Risk Prediction Initiative hosted a workshop on Weather Extremes and Atmospheric Oscillations that examined how extreme meteorological events of interest to the reinsurance industry are influenced by the quasi-biennial oscillation (QBO), the Arctic Oscillation (AO), and the Madden–Julian oscillation (MJO). Workshop participants concluded that the stratosphere is much more relevant to predictions that aid the reinsurance industry than is generally recognized and that there is mutual interest in fostering research on the relationship between the stratospheric circulation and extreme weather events. A preliminary science–business research agenda, based on presentations and discussions during and after the workshop, highlights four areas of mutual interest to scientists and insurers. The research areas focus mainly on understanding how the QBO, AO, and MJO influence the frequency and intensity of extreme events, with particular emphasis on tropical cyclones and European windstorms. An awareness of how the catastrophe reinsurance industry operates provides insights into why specific research areas were chosen. For example, the reinsurance industry operates on the basis of annual contracts, most of which are renewed on 1 January. Thus, although skillful forecasts at any lead are of interest, skillful forecasts of extreme events are of greatest value when made in the final quarter of a calendar year.

scholarly journals Deoxynivalenol Occurrence in Triticale Crops in Romania during the 2012–2014 Period with Extreme Weather Events

Toxins ◽  
2021 ◽  
Vol 13 (7) ◽  
pp. 456
Author(s):  
Valeria Gagiu ◽  
Elena Mateescu ◽  
Alina Alexandra Dobre ◽  
Irina Smeu ◽  
Mirela Elena Cucu ◽  
...  
Keyword(s):  
Heavy Precipitation ◽  
Extreme Weather ◽  
Extreme Weather Events ◽  
P Value ◽  
Heavy Snowfall ◽  
Factors Influencing ◽  
Weather Events ◽  
Aridity Indices ◽  
Very High ◽  
Continental Climate

This article aims to evaluate deoxynivalenol occurrence in triticale crops in Romania in years with extreme weather events (2012: Siberian anticyclone with cold waves and heavy snowfall; 2013 and 2014: “Vb” cyclones with heavy precipitation and floods in spring). The deoxynivalenol level in triticale samples (N = 236) was quantified by ELISA. In Romania, the extreme weather events favoured deoxynivalenol occurrence in triticale in Transylvania and the southern hilly area (44–47°N, 22–25°E) with a humid/balanced-humid temperate continental climate, luvisols and high/very high risk of floods. Maximum deoxynivalenol contamination was lower in the other regions, although heavy precipitation in May–July 2014 was higher, with chernozems having higher aridity. Multivariate analysis of the factors influencing deoxynivalenol occurrence in triticale showed at least a significant correlation for all components of variation source (agricultural year, agricultural region, average of deoxynivalenol, average air temperature, cumulative precipitation, soil moisture reserve, aridity indices) (p-value < 0.05). The spatial and geographic distribution of deoxynivalenol in cereals in the countries affected by the 2012–2014 extreme weather events revealed a higher contamination in Central Europe compared to southeastern and eastern Europe. Deoxynivalenol occurrence in cereals was favoured by local and regional agroclimatic factors and was amplified by extreme weather events.

scholarly journals Impacts of extreme weather events on transport infrastructure in Norway

2017 ◽  
Author(s):  
Regula Frauenfelder ◽  
Anders Solheim ◽  
Ketil Isaksen ◽  
Bård Romstad ◽  
Anita V. Dyrrdal ◽  
...  
Keyword(s):  
Debris Flows ◽  
Climate Models ◽  
Heavy Precipitation ◽  
Extreme Weather ◽  
Transport Infrastructure ◽  
Extreme Weather Events ◽  
Local Climate ◽  
Weather Events ◽  
Interdisciplinary Research Project ◽  
Heavy Rainfall Events

Abstract. This paper presents selected results of the interdisciplinary research project Impacts of extreme weather events on infrastructure in Norway (InfraRisk) carried out between 2010 to 2013, as part of the program NORKLIMA (2004 2013) of the Research Council of Norway (RCN). The project has systematized large amounts of existing data and generated new results that are important for our handling of risks associated with future extreme weather and natural hazards threatening the transport infrastructure in Norway. The results of the InfaRisk project range widely, from the establishment of trends in key weather elements to studies of human response to threats from extreme weather. The analyses of weather elements have provided a clearer understanding of the trends in the development of extreme weather. The studies are based on both historical data and available future scenarios (projections) from climate models. Compared to previous studies, we calculated changes in climate variables that are particularly important in relation to nature hazards. Overall, the analyses document an increase in frequency as well as intensity of both precipitation and wind. Results of projections show that the observed changes will continue throughout this century. We could also identify large regional differences, with some areas experiencing, e.g., a reduction in the intensity of heavy rainfall events. However, most of the country will experience the opposite, i.e., both increased intensity and increased frequency of heavy precipitation. Our analyses show that at least 27 per cent of Norwegian roads and 31 per cent of railroads are exposed to rock fall and snow avalanches hazards. The project has also assessed relationships between different parameters that can affect the likelihood of debris flows. Variables such as terrain slope and size of watercourses are important, while local climate, which varies widely in Norway, determines threshold values for rainfall that can trigger debris flows.

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