extreme weather patterns: Topics by Science.gov

Sample records for extreme weather patterns

78 FR 78486 - Notice of Funding Availability for Resilience Projects in Response to Hurricane Sandy

Federal Register 2010, 2011, 2012, 2013, 2014

2013-12-26

... changes in development patterns, demographics, or climate change and extreme weather patterns. For the... located; or projected changes in development patterns, demographics, or extreme weather or other climate... climate-related disasters are a continuing threat. According to the ``Hurricane Sandy Rebuilding Strategy...
A dynamical systems approach to studying midlatitude weather extremes

NASA Astrophysics Data System (ADS)

Messori, Gabriele; Caballero, Rodrigo; Faranda, Davide

2017-04-01

Extreme weather occurrences carry enormous social and economic costs and routinely garner widespread scientific and media coverage. The ability to predict these events is therefore a topic of crucial importance. Here we propose a novel predictability pathway for extreme events, by building upon recent advances in dynamical systems theory. We show that simple dynamical systems metrics can be used to identify sets of large-scale atmospheric flow patterns with similar spatial structure and temporal evolution on time scales of several days to a week. In regions where these patterns favor extreme weather, they afford a particularly good predictability of the extremes. We specifically test this technique on the atmospheric circulation in the North Atlantic region, where it provides predictability of large-scale wintertime surface temperature extremes in Europe up to 1 week in advance.
Deep Learning for Extreme Weather Detection

NASA Astrophysics Data System (ADS)

Prabhat, M.; Racah, E.; Biard, J.; Liu, Y.; Mudigonda, M.; Kashinath, K.; Beckham, C.; Maharaj, T.; Kahou, S.; Pal, C.; O'Brien, T. A.; Wehner, M. F.; Kunkel, K.; Collins, W. D.

2017-12-01

We will present our latest results from the application of Deep Learning methods for detecting, localizing and segmenting extreme weather patterns in climate data. We have successfully applied supervised convolutional architectures for the binary classification tasks of detecting tropical cyclones and atmospheric rivers in centered, cropped patches. We have subsequently extended our architecture to a semi-supervised formulation, which is capable of learning a unified representation of multiple weather patterns, predicting bounding boxes and object categories, and has the capability to detect novel patterns (w/ few, or no labels). We will briefly present our efforts in scaling the semi-supervised architecture to 9600 nodes of the Cori supercomputer, obtaining 15PF performance. Time permitting, we will highlight our efforts in pixel-level segmentation of weather patterns.
No evidence of the effect of extreme weather events on annual occurrence of four groups of ectothermic species.

PubMed

Malinowska, Agnieszka H; van Strien, Arco J; Verboom, Jana; WallisdeVries, Michiel F; Opdam, Paul

2014-01-01

Weather extremes may have strong effects on biodiversity, as known from theoretical and modelling studies. Predicted negative effects of increased weather variation are found only for a few species, mostly plants and birds in empirical studies. Therefore, we investigated correlations between weather variability and patterns in occupancy, local colonisations and local extinctions (metapopulation metrics) across four groups of ectotherms: Odonata, Orthoptera, Lepidoptera, and Reptilia. We analysed data of 134 species on a 1×1 km-grid base, collected in the last 20 years from the Netherlands, combining standardised data and opportunistic data. We applied dynamic site-occupancy models and used the results as input for analyses of (i) trends in distribution patterns, (ii) the effect of temperature on colonisation and persistence probability, and (iii) the effect of years with extreme weather on all the three metapopulation metrics. All groups, except butterflies, showed more positive than negative trends in metapopulation metrics. We did not find evidence that the probability of colonisation or persistence increases with temperature nor that extreme weather events are reflected in higher extinction risks. We could not prove that weather extremes have visible and consistent negative effects on ectothermic species in temperate northern hemisphere. These findings do not confirm the general prediction that increased weather variability imperils biodiversity. We conclude that weather extremes might not be ecologically relevant for the majority of species. Populations might be buffered against weather variation (e.g. by habitat heterogeneity), or other factors might be masking the effects (e.g. availability and quality of habitat). Consequently, we postulate that weather extremes have less, or different, impact in real world metapopulations than theory and models suggest.
No Evidence of the Effect of Extreme Weather Events on Annual Occurrence of Four Groups of Ectothermic Species

PubMed Central

Malinowska, Agnieszka H.; van Strien, Arco J.; Verboom, Jana; WallisdeVries, Michiel F.; Opdam, Paul

2014-01-01

Weather extremes may have strong effects on biodiversity, as known from theoretical and modelling studies. Predicted negative effects of increased weather variation are found only for a few species, mostly plants and birds in empirical studies. Therefore, we investigated correlations between weather variability and patterns in occupancy, local colonisations and local extinctions (metapopulation metrics) across four groups of ectotherms: Odonata, Orthoptera, Lepidoptera, and Reptilia. We analysed data of 134 species on a 1×1 km-grid base, collected in the last 20 years from the Netherlands, combining standardised data and opportunistic data. We applied dynamic site-occupancy models and used the results as input for analyses of (i) trends in distribution patterns, (ii) the effect of temperature on colonisation and persistence probability, and (iii) the effect of years with extreme weather on all the three metapopulation metrics. All groups, except butterflies, showed more positive than negative trends in metapopulation metrics. We did not find evidence that the probability of colonisation or persistence increases with temperature nor that extreme weather events are reflected in higher extinction risks. We could not prove that weather extremes have visible and consistent negative effects on ectothermic species in temperate northern hemisphere. These findings do not confirm the general prediction that increased weather variability imperils biodiversity. We conclude that weather extremes might not be ecologically relevant for the majority of species. Populations might be buffered against weather variation (e.g. by habitat heterogeneity), or other factors might be masking the effects (e.g. availability and quality of habitat). Consequently, we postulate that weather extremes have less, or different, impact in real world metapopulations than theory and models suggest. PMID:25330414
Wildfire risk in the wildland-urban interface: A simulation study in northwestern Wisconsin

USGS Publications Warehouse

Massada, Avi Bar; Radeloff, Volker C.; Stewart, Susan I.; Hawbaker, Todd J.

2009-01-01

The rapid growth of housing in and near the wildland–urban interface (WUI) increases wildfirerisk to lives and structures. To reduce fire risk, it is necessary to identify WUI housing areas that are more susceptible to wildfire. This is challenging, because wildfire patterns depend on fire behavior and spread, which in turn depend on ignition locations, weather conditions, the spatial arrangement of fuels, and topography. The goal of our study was to assess wildfirerisk to a 60,000 ha WUI area in northwesternWisconsin while accounting for all of these factors. We conducted 6000 simulations with two dynamic fire models: Fire Area Simulator (FARSITE) and Minimum Travel Time (MTT) in order to map the spatial pattern of burn probabilities. Simulations were run under normal and extreme weather conditions to assess the effect of weather on fire spread, burn probability, and risk to structures. The resulting burn probability maps were intersected with maps of structure locations and land cover types. The simulations revealed clear hotspots of wildfire activity and a large range of wildfirerisk to structures in the study area. As expected, the extreme weather conditions yielded higher burn probabilities over the entire landscape, as well as to different land cover classes and individual structures. Moreover, the spatial pattern of risk was significantly different between extreme and normal weather conditions. The results highlight the fact that extreme weather conditions not only produce higher fire risk than normal weather conditions, but also change the fine-scale locations of high risk areas in the landscape, which is of great importance for fire management in WUI areas. In addition, the choice of weather data may limit the potential for comparisons of risk maps for different areas and for extrapolating risk maps to future scenarios where weather conditions are unknown. Our approach to modeling wildfirerisk to structures can aid fire risk reduction management activities by identifying areas with elevated wildfirerisk and those most vulnerable under extreme weather conditions.
Dynamical systems proxies of atmospheric predictability and mid-latitude extremes

NASA Astrophysics Data System (ADS)

Messori, Gabriele; Faranda, Davide; Caballero, Rodrigo; Yiou, Pascal

2017-04-01

Extreme weather ocurrences carry enormous social and economic costs and routinely garner widespread scientific and media coverage. Many extremes (for e.g. storms, heatwaves, cold spells, heavy precipitation) are tied to specific patterns of midlatitude atmospheric circulation. The ability to identify these patterns and use them to enhance the predictability of the extremes is therefore a topic of crucial societal and economic value. We propose a novel predictability pathway for extreme events, by building upon recent advances in dynamical systems theory. We use two simple dynamical systems metrics - local dimension and persistence - to identify sets of similar large-scale atmospheric flow patterns which present a coherent temporal evolution. When these patterns correspond to weather extremes, they therefore afford a particularly good forward predictability. We specifically test this technique on European winter temperatures, whose variability largely depends on the atmospheric circulation in the North Atlantic region. We find that our dynamical systems approach provides predictability of large-scale temperature extremes up to one week in advance.
Extreme weather events and infectious disease outbreaks.

PubMed

McMichael, Anthony J

2015-01-01

Human-driven climatic changes will fundamentally influence patterns of human health, including infectious disease clusters and epidemics following extreme weather events. Extreme weather events are projected to increase further with the advance of human-driven climate change. Both recent and historical experiences indicate that infectious disease outbreaks very often follow extreme weather events, as microbes, vectors and reservoir animal hosts exploit the disrupted social and environmental conditions of extreme weather events. This review article examines infectious disease risks associated with extreme weather events; it draws on recent experiences including Hurricane Katrina in 2005 and the 2010 Pakistan mega-floods, and historical examples from previous centuries of epidemics and 'pestilence' associated with extreme weather disasters and climatic changes. A fuller understanding of climatic change, the precursors and triggers of extreme weather events and health consequences is needed in order to anticipate and respond to the infectious disease risks associated with human-driven climate change. Post-event risks to human health can be constrained, nonetheless, by reducing background rates of persistent infection, preparatory action such as coordinated disease surveillance and vaccination coverage, and strengthened disaster response. In the face of changing climate and weather conditions, it is critically important to think in ecological terms about the determinants of health, disease and death in human populations.
Identification of large-scale meteorological patterns associated with extreme precipitation in the US northeast

NASA Astrophysics Data System (ADS)

Agel, Laurie; Barlow, Mathew; Feldstein, Steven B.; Gutowski, William J.

2018-03-01

Patterns of daily large-scale circulation associated with Northeast US extreme precipitation are identified using both k-means clustering (KMC) and Self-Organizing Maps (SOM) applied to tropopause height. The tropopause height provides a compact representation of the upper-tropospheric potential vorticity, which is closely related to the overall evolution and intensity of weather systems. Extreme precipitation is defined as the top 1% of daily wet-day observations at 35 Northeast stations, 1979-2008. KMC is applied on extreme precipitation days only, while the SOM algorithm is applied to all days in order to place the extreme results into the overall context of patterns for all days. Six tropopause patterns are identified through KMC for extreme day precipitation: a summertime tropopause ridge, a summertime shallow trough/ridge, a summertime shallow eastern US trough, a deeper wintertime eastern US trough, and two versions of a deep cold-weather trough located across the east-central US. Thirty SOM patterns for all days are identified. Results for all days show that 6 SOM patterns account for almost half of the extreme days, although extreme precipitation occurs in all SOM patterns. The same SOM patterns associated with extreme precipitation also routinely produce non-extreme precipitation; however, on extreme precipitation days the troughs, on average, are deeper and the downstream ridges more pronounced. Analysis of other fields associated with the large-scale patterns show various degrees of anomalously strong moisture transport preceding, and upward motion during, extreme precipitation events.
Large Scale Meteorological Pattern of Extreme Rainfall in Indonesia

NASA Astrophysics Data System (ADS)

Kuswanto, Heri; Grotjahn, Richard; Rachmi, Arinda; Suhermi, Novri; Oktania, Erma; Wijaya, Yosep

2014-05-01

Extreme Weather Events (EWEs) cause negative impacts socially, economically, and environmentally. Considering these facts, forecasting EWEs is crucial work. Indonesia has been identified as being among the countries most vulnerable to the risk of natural disasters, such as floods, heat waves, and droughts. Current forecasting of extreme events in Indonesia is carried out by interpreting synoptic maps for several fields without taking into account the link between the observed events in the 'target' area with remote conditions. This situation may cause misidentification of the event leading to an inaccurate prediction. Grotjahn and Faure (2008) compute composite maps from extreme events (including heat waves and intense rainfall) to help forecasters identify such events in model output. The composite maps show large scale meteorological patterns (LSMP) that occurred during historical EWEs. Some vital information about the EWEs can be acquired from studying such maps, in addition to providing forecaster guidance. Such maps have robust mid-latitude meteorological patterns (for Sacramento and California Central Valley, USA EWEs). We study the performance of the composite approach for tropical weather condition such as Indonesia. Initially, the composite maps are developed to identify and forecast the extreme weather events in Indramayu district- West Java, the main producer of rice in Indonesia and contributes to about 60% of the national total rice production. Studying extreme weather events happening in Indramayu is important since EWEs there affect national agricultural and fisheries activities. During a recent EWE more than a thousand houses in Indramayu suffered from serious flooding with each home more than one meter underwater. The flood also destroyed a thousand hectares of rice plantings in 5 regencies. Identifying the dates of extreme events is one of the most important steps and has to be carried out carefully. An approach has been applied to identify the dates involving observations from multiple sites (rain gauges). The approach combines the POT (Peaks Over Threshold) with 'declustering' of the data to approximate independence based on the autocorrelation structure of each rainfall series. The cross correlation among sites is considered also to develop the event's criteria yielding a rational choice of the extreme dates given the 'spotty' nature of the intense convection. Based on the identified dates, we are developing a supporting tool for forecasting extreme rainfall based on the corresponding large-scale meteorological patterns (LSMPs). The LSMPs methodology focuses on the larger-scale patterns that the model are better able to forecast, as those larger-scale patterns create the conditions fostering the local EWE. Bootstrap resampling method is applied to highlight the key features that statistically significant with the extreme events. Grotjahn, R., and G. Faure. 2008: Composite Predictor Maps of Extraordinary Weather Events in the Sacramento California Region. Weather and Forecasting. 23: 313-335.
Climate Change, Extreme Weather Events, and Human Health Implications in the Asia Pacific Region.

PubMed

Hashim, Jamal Hisham; Hashim, Zailina

2016-03-01

The Asia Pacific region is regarded as the most disaster-prone area of the world. Since 2000, 1.2 billion people have been exposed to hydrometeorological hazards alone through 1215 disaster events. The impacts of climate change on meteorological phenomena and environmental consequences are well documented. However, the impacts on health are more elusive. Nevertheless, climate change is believed to alter weather patterns on the regional scale, giving rise to extreme weather events. The impacts from extreme weather events are definitely more acute and traumatic in nature, leading to deaths and injuries, as well as debilitating and fatal communicable diseases. Extreme weather events include heat waves, cold waves, floods, droughts, hurricanes, tropical cyclones, heavy rain, and snowfalls. Globally, within the 20-year period from 1993 to 2012, more than 530 000 people died as a direct result of almost 15 000 extreme weather events, with losses of more than US$2.5 trillion in purchasing power parity. © 2015 APJPH.
Wildfire risk in the wildland-urban interface: A simulation study in northwestern Wisconsin

USGS Publications Warehouse

Bar-Massada, A.; Radeloff, V.C.; Stewart, S.I.; Hawbaker, T.J.

2009-01-01

The rapid growth of housing in and near the wildland-urban interface (WUI) increases wildfire risk to lives and structures. To reduce fire risk, it is necessary to identify WUI housing areas that are more susceptible to wildfire. This is challenging, because wildfire patterns depend on fire behavior and spread, which in turn depend on ignition locations, weather conditions, the spatial arrangement of fuels, and topography. The goal of our study was to assess wildfire risk to a 60,000 ha WUI area in northwestern Wisconsin while accounting for all of these factors. We conducted 6000 simulations with two dynamic fire models: Fire Area Simulator (FARSITE) and Minimum Travel Time (MTT) in order to map the spatial pattern of burn probabilities. Simulations were run under normal and extreme weather conditions to assess the effect of weather on fire spread, burn probability, and risk to structures. The resulting burn probability maps were intersected with maps of structure locations and land cover types. The simulations revealed clear hotspots of wildfire activity and a large range of wildfire risk to structures in the study area. As expected, the extreme weather conditions yielded higher burn probabilities over the entire landscape, as well as to different land cover classes and individual structures. Moreover, the spatial pattern of risk was significantly different between extreme and normal weather conditions. The results highlight the fact that extreme weather conditions not only produce higher fire risk than normal weather conditions, but also change the fine-scale locations of high risk areas in the landscape, which is of great importance for fire management in WUI areas. In addition, the choice of weather data may limit the potential for comparisons of risk maps for different areas and for extrapolating risk maps to future scenarios where weather conditions are unknown. Our approach to modeling wildfire risk to structures can aid fire risk reduction management activities by identifying areas with elevated wildfire risk and those most vulnerable under extreme weather conditions. ?? 2009 Elsevier B.V.
Evidence linking rapid Arctic warming to mid-latitude weather patterns.

PubMed

Francis, Jennifer; Skific, Natasa

2015-07-13

The effects of rapid Arctic warming and ice loss on weather patterns in the Northern Hemisphere is a topic of active research, lively scientific debate and high societal impact. The emergence of Arctic amplification--the enhanced sensitivity of high-latitude temperature to global warming--in only the last 10-20 years presents a challenge to identifying statistically robust atmospheric responses using observations. Several recent studies have proposed and demonstrated new mechanisms by which the changing Arctic may be affecting weather patterns in mid-latitudes, and these linkages differ fundamentally from tropics/jet-stream interactions through the transfer of wave energy. In this study, new metrics and evidence are presented that suggest disproportionate Arctic warming-and resulting weakening of the poleward temperature gradient-is causing the Northern Hemisphere circulation to assume a more meridional character (i.e. wavier), although not uniformly in space or by season, and that highly amplified jet-stream patterns are occurring more frequently. Further analysis based on self-organizing maps supports this finding. These changes in circulation are expected to lead to persistent weather patterns that are known to cause extreme weather events. As emissions of greenhouse gases continue unabated, therefore, the continued amplification of Arctic warming should favour an increased occurrence of extreme events caused by prolonged weather conditions.
Evaluation of the HadGEM3-A simulations in view of detection and attribution of human influence on extreme events in Europe

NASA Astrophysics Data System (ADS)

Vautard, Robert; Christidis, Nikolaos; Ciavarella, Andrew; Alvarez-Castro, Carmen; Bellprat, Omar; Christiansen, Bo; Colfescu, Ioana; Cowan, Tim; Doblas-Reyes, Francisco; Eden, Jonathan; Hauser, Mathias; Hegerl, Gabriele; Hempelmann, Nils; Klehmet, Katharina; Lott, Fraser; Nangini, Cathy; Orth, René; Radanovics, Sabine; Seneviratne, Sonia I.; van Oldenborgh, Geert Jan; Stott, Peter; Tett, Simon; Wilcox, Laura; Yiou, Pascal

2018-04-01

A detailed analysis is carried out to assess the HadGEM3-A global atmospheric model skill in simulating extreme temperatures, precipitation and storm surges in Europe in the view of their attribution to human influence. The analysis is performed based on an ensemble of 15 atmospheric simulations forced with observed sea surface temperature of the 54 year period 1960-2013. These simulations, together with dual simulations without human influence in the forcing, are intended to be used in weather and climate event attribution. The analysis investigates the main processes leading to extreme events, including atmospheric circulation patterns, their links with temperature extremes, land-atmosphere and troposphere-stratosphere interactions. It also compares observed and simulated variability, trends and generalized extreme value theory parameters for temperature and precipitation. One of the most striking findings is the ability of the model to capture North-Atlantic atmospheric weather regimes as obtained from a cluster analysis of sea level pressure fields. The model also reproduces the main observed weather patterns responsible for temperature and precipitation extreme events. However, biases are found in many physical processes. Slightly excessive drying may be the cause of an overestimated summer interannual variability and too intense heat waves, especially in central/northern Europe. However, this does not seem to hinder proper simulation of summer temperature trends. Cold extremes appear well simulated, as well as the underlying blocking frequency and stratosphere-troposphere interactions. Extreme precipitation amounts are overestimated and too variable. The atmospheric conditions leading to storm surges were also examined in the Baltics region. There, simulated weather conditions appear not to be leading to strong enough storm surges, but winds were found in very good agreement with reanalyses. The performance in reproducing atmospheric weather patterns indicates that biases mainly originate from local and regional physical processes. This makes local bias adjustment meaningful for climate change attribution.
Recent Weather Extremes and Impacts on Agricultural Production and Vector-Borne Disease Outbreak Patterns

NASA Technical Reports Server (NTRS)

Anyamba, Assaf; Small, Jennifer L.; Britch, Seth C.; Tucker, Compton J.; Pak, Edwin W.; Reynolds, Curt A.; Crutchfield, James; Linthicum, Kenneth J.

2014-01-01

We document significant worldwide weather anomalies that affected agriculture and vector-borne disease outbreaks during the 2010-2012 period. We utilized 2000-2012 vegetation index and land surface temperature data from NASA's satellite-based Moderate Resolution Imaging Spectroradiometer (MODIS) to map the magnitude and extent of these anomalies for diverse regions including the continental United States, Russia, East Africa, Southern Africa, and Australia. We demonstrate that shifts in temperature and/or precipitation have significant impacts on vegetation patterns with attendant consequences for agriculture and public health. Weather extremes resulted in excessive rainfall and flooding as well as severe drought, which caused,10 to 80% variation in major agricultural commodity production (including wheat, corn, cotton, sorghum) and created exceptional conditions for extensive mosquito-borne disease outbreaks of dengue, Rift Valley fever, Murray Valley encephalitis, and West Nile virus disease. Analysis of MODIS data provided a standardized method for quantifying the extreme weather anomalies observed during this period. Assessments of land surface conditions from satellite-based systems such as MODIS can be a valuable tool in national, regional, and global weather impact determinations.
Recent weather extremes and impacts on agricultural production and vector-borne disease outbreak patterns.

PubMed

Anyamba, Assaf; Small, Jennifer L; Britch, Seth C; Tucker, Compton J; Pak, Edwin W; Reynolds, Curt A; Crutchfield, James; Linthicum, Kenneth J

2014-01-01

We document significant worldwide weather anomalies that affected agriculture and vector-borne disease outbreaks during the 2010-2012 period. We utilized 2000-2012 vegetation index and land surface temperature data from NASA's satellite-based Moderate Resolution Imaging Spectroradiometer (MODIS) to map the magnitude and extent of these anomalies for diverse regions including the continental United States, Russia, East Africa, Southern Africa, and Australia. We demonstrate that shifts in temperature and/or precipitation have significant impacts on vegetation patterns with attendant consequences for agriculture and public health. Weather extremes resulted in excessive rainfall and flooding as well as severe drought, which caused ∼10 to 80% variation in major agricultural commodity production (including wheat, corn, cotton, sorghum) and created exceptional conditions for extensive mosquito-borne disease outbreaks of dengue, Rift Valley fever, Murray Valley encephalitis, and West Nile virus disease. Analysis of MODIS data provided a standardized method for quantifying the extreme weather anomalies observed during this period. Assessments of land surface conditions from satellite-based systems such as MODIS can be a valuable tool in national, regional, and global weather impact determinations.
The relationship between extreme weather events and crop losses in central Taiwan

NASA Astrophysics Data System (ADS)

Lai, Li-Wei

2017-09-01

The frequency of extreme weather events, which cause severe crop losses, is increasing. This study investigates the relationship between crop losses and extreme weather events in central Taiwan from 2003 to 2015 and determines the main factors influencing crop losses. Data regarding the crop loss area and meteorological information were obtained from government agencies. The crops were categorised into the following five groups: `grains', `vegetables', `fruits', `flowers' and `other crops'. The extreme weather events and their synoptic weather patterns were categorised into six and five groups, respectively. The data were analysed using the z score, correlation coefficient and stepwise regression model. The results show that typhoons had the highest frequency of all extreme weather events (58.3%). The largest crop loss area (4.09%) was caused by two typhoons and foehn wind in succession. Extreme wind speed coupled with heavy rainfall is an important factor affecting the losses in the grain and vegetable groups. Extreme wind speed is a common variable that affects the loss of `grains', `vegetables', `fruits' and `flowers'. Consecutive extreme weather events caused greater crop losses than individual events. Crops with long production times suffered greater losses than those with short production times. This suggests that crops with physical structures that can be easily damaged and long production times would benefit from protected cultivation to maintain food security.
Spatial extreme value analysis to project extremes of large-scale indicators for severe weather

PubMed Central

Gilleland, Eric; Brown, Barbara G; Ammann, Caspar M

2013-01-01

Concurrently high values of the maximum potential wind speed of updrafts (Wmax) and 0–6 km wind shear (Shear) have been found to represent conducive environments for severe weather, which subsequently provides a way to study severe weather in future climates. Here, we employ a model for the product of these variables (WmSh) from the National Center for Atmospheric Research/United States National Center for Environmental Prediction reanalysis over North America conditioned on their having extreme energy in the spatial field in order to project the predominant spatial patterns of WmSh. The approach is based on the Heffernan and Tawn conditional extreme value model. Results suggest that this technique estimates the spatial behavior of WmSh well, which allows for exploring possible changes in the patterns over time. While the model enables a method for inferring the uncertainty in the patterns, such analysis is difficult with the currently available inference approach. A variation of the method is also explored to investigate how this type of model might be used to qualitatively understand how the spatial patterns of WmSh correspond to extreme river flow events. A case study for river flows from three rivers in northwestern Tennessee is studied, and it is found that advection of WmSh from the Gulf of Mexico prevails while elsewhere, WmSh is generally very low during such extreme events. © 2013 The Authors. Environmetrics published by JohnWiley & Sons, Ltd. PMID:24223482
El Niño and human health.

PubMed Central

Kovats, R. S.

2000-01-01

The El Niño-Southern Oscillation (ENSO) is the best known example of quasi-periodic natural climate variability on the interannual time scale. It comprises changes in sea temperature in the Pacific Ocean (El Niño) and changes in atmospheric pressure across the Pacific Basin (the Southern Oscillation), together with resultant effects on world weather. El Niño events occur at intervals of 2-7 years. In certain countries around the Pacific and beyond, El Niño is associated with extreme weather conditions that can cause floods and drought. Globally it is linked to an increased impact of natural disasters. There is evidence that ENSO is associated with a heightened risk of certain vector-borne diseases in specific geographical areas where weather patterns are linked with the ENSO cycle and disease control is limited. This is particularly true for malaria, but associations are also suggested in respect of epidemics of other mosquito-borne and rodent-borne diseases that can be triggered by extreme weather conditions. Seasonal climate forecasts, predicting the likelihood of weather patterns several months in advance, can be used to provide early indicators of epidemic risk, particularly for malaria. Interdisciplinary research and cooperation are required in order to reduce vulnerability to climate variability and weather extremes. PMID:11019461
Recent Weather Extremes and Impacts on Agricultural Production and Vector-Borne Disease Outbreak Patterns

PubMed Central

Anyamba, Assaf; Small, Jennifer L.; Britch, Seth C.; Tucker, Compton J.; Pak, Edwin W.; Reynolds, Curt A.; Crutchfield, James; Linthicum, Kenneth J.

2014-01-01

We document significant worldwide weather anomalies that affected agriculture and vector-borne disease outbreaks during the 2010–2012 period. We utilized 2000–2012 vegetation index and land surface temperature data from NASA's satellite-based Moderate Resolution Imaging Spectroradiometer (MODIS) to map the magnitude and extent of these anomalies for diverse regions including the continental United States, Russia, East Africa, Southern Africa, and Australia. We demonstrate that shifts in temperature and/or precipitation have significant impacts on vegetation patterns with attendant consequences for agriculture and public health. Weather extremes resulted in excessive rainfall and flooding as well as severe drought, which caused ∼10 to 80% variation in major agricultural commodity production (including wheat, corn, cotton, sorghum) and created exceptional conditions for extensive mosquito-borne disease outbreaks of dengue, Rift Valley fever, Murray Valley encephalitis, and West Nile virus disease. Analysis of MODIS data provided a standardized method for quantifying the extreme weather anomalies observed during this period. Assessments of land surface conditions from satellite-based systems such as MODIS can be a valuable tool in national, regional, and global weather impact determinations. PMID:24658301

Extreme weather events and environmental contamination are associated with case-clusters of melioidosis in the Northern Territory of Australia.

PubMed

Cheng, Allen C; Jacups, Susan P; Gal, Daniel; Mayo, Mark; Currie, Bart J

2006-04-01

Melioidosis, the infection due to the environmental organism Burkholderia pseudomallei, is endemic to northern Australia and South East Asia. It is associated with exposure to mud and pooled surface water, but environmental determinants of this disease are poorly understood. We defined case-clusters in northern Australia, determined their contribution to the observed rate of melioidosis, and explored clinical features and associated environmental factors. Using geographical information systems data, we examined clustering of melioidosis cases in time and geographical space in the Top End of the Northern Territory of Australia between 1990 and 2002 using a scan statistic. DNA macrorestriction analysis, resolved by pulsed field gel electrophoresis, was performed on isolates from patients. We defined five case-clusters involving 27 patients that occurred within 7-28 days and/or a radius of 100-300 km. Clustered cases were associated with extreme weather events or environmental contamination; no difference in the clinical pattern of disease was noted from other patients not involved in clusters. Isolates from patients linked to environmental contamination were caused by isolates with similar DNA macrorestriction patterns, but isolates from patients linked to severe weather events had more diverse DNA macrorestriction patterns. Case-clusters of melioidosis where isolates exhibit diverse DNA macrorestriction patterns in our region are linked to extreme weather events and outbreaks where isolates are predominantly of the same DNA macrorestriction pattern are linked with contamination of an environmental source.
Extreme weather-year sequences have nonadditive effects on environmental nitrogen losses.

PubMed

Iqbal, Javed; Necpalova, Magdalena; Archontoulis, Sotirios V; Anex, Robert P; Bourguignon, Marie; Herzmann, Daryl; Mitchell, David C; Sawyer, John E; Zhu, Qing; Castellano, Michael J

2018-01-01

The frequency and intensity of extreme weather years, characterized by abnormal precipitation and temperature, are increasing. In isolation, these years have disproportionately large effects on environmental N losses. However, the sequence of extreme weather years (e.g., wet-dry vs. dry-wet) may affect cumulative N losses. We calibrated and validated the DAYCENT ecosystem process model with a comprehensive set of biogeophysical measurements from a corn-soybean rotation managed at three N fertilizer inputs with and without a winter cover crop in Iowa, USA. Our objectives were to determine: (i) how 2-year sequences of extreme weather affect 2-year cumulative N losses across the crop rotation, and (ii) if N fertilizer management and the inclusion of a winter cover crop between corn and soybean mitigate the effect of extreme weather on N losses. Using historical weather (1951-2013), we created nine 2-year scenarios with all possible combinations of the driest ("dry"), wettest ("wet"), and average ("normal") weather years. We analyzed the effects of these scenarios following several consecutive years of relatively normal weather. Compared with the normal-normal 2-year weather scenario, 2-year extreme weather scenarios affected 2-year cumulative NO 3 - leaching (range: -93 to +290%) more than N 2 O emissions (range: -49 to +18%). The 2-year weather scenarios had nonadditive effects on N losses: compared with the normal-normal scenario, the dry-wet sequence decreased 2-year cumulative N 2 O emissions while the wet-dry sequence increased 2-year cumulative N 2 O emissions. Although dry weather decreased NO 3 - leaching and N 2 O emissions in isolation, 2-year cumulative N losses from the wet-dry scenario were greater than the dry-wet scenario. Cover crops reduced the effects of extreme weather on NO 3 - leaching but had a lesser effect on N 2 O emissions. As the frequency of extreme weather is expected to increase, these data suggest that the sequence of interannual weather patterns can be used to develop short-term mitigation strategies that manipulate N fertilizer and crop rotation to maximize crop N uptake while reducing environmental N losses. © 2017 John Wiley & Sons Ltd.
Translating weather extremes into the future - a case for Norway

NASA Astrophysics Data System (ADS)

Sillmann, Jana; Mueller, Malte; Gjertsen, Uta; Haarsma, Rein; Hazeleger, Wilco; Amundsen, Helene

2017-04-01

We introduce a new project "Translating weather extremes into the future - a case for Norway" (TWEX - http://www.cicero.uio.no/en/twex). In TWEX, we take a novel "Tales of future weather" approach in which we use future scenarios tailored to a specific region and stakeholder in order to gain a more realistic picture of what future weather extremes might look like in a particular context. We focus on hydroclimatic extremes associated with a particular circulation pattern (so-called "Atmospheric River") leading to heavy rainfall in fall and winter along the West Coast of Norway and causing high-impact floods in Norwegian communities. We translate selected past events into the future (e.g., 2090) by using an approach very similar to what is used today for weather prediction. The data generated in TWEX will be distributed by standard (weather prediction) communication channels of the Norwegian Meteorological Institute and thus, will be accessible by end-user in a well-known data format for analyzing the impact of the events in the future and support decision-making on hazard prevention and adaptation planning.
49 CFR 602.5 - Definitions.

Code of Federal Regulations, 2014 CFR

2014-10-01

... again in the geographic area in which the public transportation system is located; or projected changes in development patterns, demographics, or extreme weather or other climate patterns. Serious damage...
49 CFR 602.5 - Definitions.

Code of Federal Regulations, 2013 CFR

2013-10-01

... again in the geographic area in which the public transportation system is located; or projected changes in development patterns, demographics, or extreme weather or other climate patterns. Serious damage...
The influence of weather on health-related help-seeking behavior of senior citizens in Hong Kong.

PubMed

Wong, Ho Ting; Chiu, Marcus Yu Lung; Wu, Cynthia Sau Ting; Lee, Tsz Cheung

2015-03-01

It is believed that extreme hot and cold weather has a negative impact on general health conditions. Much research focuses on mortality, but there is relatively little community health research. This study is aimed at identifying high-risk groups who are sensitive to extreme weather conditions, in particular, very hot and cold days, through an analysis of the health-related help-seeking patterns of over 60,000 Personal Emergency Link (PE-link) users in Hong Kong relative to weather conditions. In the study, 1,659,716 PE-link calls to the help center were analyzed. Results showed that females, older elderly, people who did not live alone, non-subsidized (relatively high-income) users, and those without medical histories of heart disease, hypertension, stroke, and diabetes were more sensitive to extreme weather condition. The results suggest that using official government weather forecast reports to predict health-related help-seeking behavior is feasible. An evidence-based strategic plan could be formulated by using a method similar to that used in this study to identify high-risk groups. Preventive measures could be established for protecting the target groups when extreme weather conditions are forecasted.
The influence of weather on health-related help-seeking behavior of senior citizens in Hong Kong

NASA Astrophysics Data System (ADS)

Wong, Ho Ting; Chiu, Marcus Yu Lung; Wu, Cynthia Sau Ting; Lee, Tsz Cheung

2015-03-01

It is believed that extreme hot and cold weather has a negative impact on general health conditions. Much research focuses on mortality, but there is relatively little community health research. This study is aimed at identifying high-risk groups who are sensitive to extreme weather conditions, in particular, very hot and cold days, through an analysis of the health-related help-seeking patterns of over 60,000 Personal Emergency Link (PE-link) users in Hong Kong relative to weather conditions. In the study, 1,659,716 PE-link calls to the help center were analyzed. Results showed that females, older elderly, people who did not live alone, non-subsidized (relatively high-income) users, and those without medical histories of heart disease, hypertension, stroke, and diabetes were more sensitive to extreme weather condition. The results suggest that using official government weather forecast reports to predict health-related help-seeking behavior is feasible. An evidence-based strategic plan could be formulated by using a method similar to that used in this study to identify high-risk groups. Preventive measures could be established for protecting the target groups when extreme weather conditions are forecasted.
Impact of climate change on European weather extremes

NASA Astrophysics Data System (ADS)

Duchez, Aurelie; Forryan, Alex; Hirschi, Joel; Sinha, Bablu; New, Adrian; Freychet, Nicolas; Scaife, Adam; Graham, Tim

2015-04-01

An emerging science consensus is that global climate change will result in more extreme weather events with concomitant increasing financial losses. Key questions that arise are: Can an upward trend in natural extreme events be recognised and predicted at the European scale? What are the key drivers within the climate system that are changing and making extreme weather events more frequent, more intense, or both? Using state-of-the-art coupled climate simulations from the UK Met Office (HadGEM3-GC2, historical and future scenario runs) as well as reanalysis data, we highlight the potential of the currently most advanced forecasting systems to progress understanding of the causative drivers of European weather extremes, and assess future frequency and intensity of extreme weather under various climate change scenarios. We characterize European extremes in these simulations using a subset of the 27 core indices for temperature and precipitation from The Expert Team on Climate Change Detection and Indices (Tank et al., 2009). We focus on temperature and precipitation extremes (e.g. extremes in daily and monthly precipitation and temperatures) and relate them to the atmospheric modes of variability over Europe in order to establish the large-scale atmospheric circulation patterns that are conducive to the occurrence of extreme precipitation and temperature events. Klein Tank, Albert M.G., and Francis W. Zwiers. Guidelines on Analysis of Extremes in a Changing Climate in Support of Informed Decisions for Adaptation. WMO-TD No. 1500. Climate Data and Monitoring. World Meteorological Organization, 2009.
Seeing is Believing? An Examination of Perceptions of Local Weather Conditions and Climate Change Among Residents in the U.S. Gulf Coast.

PubMed

Shao, Wanyun; Goidel, Kirby

2016-11-01

What role do objective weather conditions play in coastal residents' perceptions of local climate shifts and how do these perceptions affect attitudes toward climate change? While scholars have increasingly investigated the role of weather and climate conditions on climate-related attitudes and behaviors, they typically assume that residents accurately perceive shifts in local climate patterns. We directly test this assumption using the largest and most comprehensive survey of Gulf Coast residents conducted to date supplemented with monthly temperature data from the U.S. Historical Climatology Network and extreme weather events data from National Climatic Data Center. We find objective conditions have limited explanatory power in determining perceptions of local climate patterns. Only the 15- and 19-year hurricane trends and decadal summer temperature trend have some effects on perceptions of these weather conditions, while the decadal trend of total number of extreme weather events and 15- and 19-year winter temperature trends are correlated with belief in climate change. Partisan affiliation, in contrast, plays a powerful role affecting individual perceptions of changing patterns of air temperatures, flooding, droughts, and hurricanes, as well as belief in the existence of climate change and concern for future consequences. At least when it comes to changing local conditions, "seeing is not believing." Political orientations rather than local conditions drive perceptions of local weather conditions and these perceptions-rather than objectively measured weather conditions-influence climate-related attitudes. © 2016 Society for Risk Analysis.
Evaluating the Large-Scale Environment of Extreme Events Using Reanalyses

NASA Astrophysics Data System (ADS)

Bosilovich, M. G.; Schubert, S. D.; Koster, R. D.; da Silva, A. M., Jr.; Eichmann, A.

2014-12-01

Extreme conditions and events have always been a long standing concern in weather forecasting and national security. While some evidence indicates extreme weather will increase in global change scenarios, extremes are often related to the large scale atmospheric circulation, but also occurring infrequently. Reanalyses assimilate substantial amounts of weather data and a primary strength of reanalysis data is the representation of the large-scale atmospheric environment. In this effort, we link the occurrences of extreme events or climate indicators to the underlying regional and global weather patterns. Now, with greater than 3o years of data, reanalyses can include multiple cases of extreme events, and thereby identify commonality among the weather to better characterize the large-scale to global environment linked to the indicator or extreme event. Since these features are certainly regionally dependent, and also, the indicators of climate are continually being developed, we outline various methods to analyze the reanalysis data and the development of tools to support regional evaluation of the data. Here, we provide some examples of both individual case studies and composite studies of similar events. For example, we will compare the large scale environment for Northeastern US extreme precipitation with that of highest mean precipitation seasons. Likewise, southerly winds can shown to be a major contributor to very warm days in the Northeast winter. While most of our development has involved NASA's MERRA reanalysis, we are also looking forward to MERRA-2 which includes several new features that greatly improve the representation of weather and climate, especially for the regions and sectors involved in the National Climate Assessment.
Atmospheric conditions and weather regimes associated with extreme winter dry spells over the Mediterranean basin

NASA Astrophysics Data System (ADS)

Raymond, Florian; Ullmann, Albin; Camberlin, Pierre; Oueslati, Boutheina; Drobinski, Philippe

2018-06-01

Very long dry spell events occurring during winter are natural hazards to which the Mediterranean region is extremely vulnerable, because they can lead numerous impacts for environment and society. Four dry spell patterns have been identified in a previous work. Identifying the main associated atmospheric conditions controlling the dry spell patterns is key to better understand their dynamics and their evolution in a changing climate. Except for the Levant region, the dry spells are generally associated with anticyclonic blocking conditions located about 1000 km to the Northwest of the affected area. These anticyclonic conditions are favourable to dry spell occurrence as they are associated with subsidence of cold and dry air coming from boreal latitudes which bring low amount of water vapour and non saturated air masses, leading to clear sky and absence of precipitation. These extreme dry spells are also partly related to the classical four Euro-Atlantic weather regimes are: the two phases of the North Atlantic Oscillation, the Scandinavian "blocking" or "East-Atlantic", and the "Atlantic ridge". Only the The "East-Atlantic", "Atlantic ridge" and the positive phase of the North Atlantic Oscillation are frequently associated with extremes dry spells over the Mediterranean basin but they do not impact the four dry spell patterns equally. Finally long sequences of those weather regimes are more favourable to extreme dry spells than short sequences. These long sequences are associated with the favourable prolonged and reinforced anticyclonic conditions
Recent weather extremes and impact agricultural production and vector-borne disease patterns

USDA-ARS?s Scientific Manuscript database

We document significant worldwide weather anomalies that affected agriculture and vector-borne disease outbreaks during the 2010-2012 period. We utilized 2000-2012 vegetation index and land surface temperature data from NASA’s satellite-based Moderate Resolution Imaging Spectroradiometer (MODIS) to ...
Assessing Climate Change Impacts for Military Installations in the Southwest United States During the Warm Season

NASA Astrophysics Data System (ADS)

Castro, C.

2013-05-01

Arid and semi-arid regions are experiencing some of the most adverse impacts of climate change with increased heat waves, droughts, and extreme weather. These events will likely exacerbate socioeconomic and political instabilities in regions where the United States has vital strategic interests and ongoing military operations. The Southwest U.S. is strategically important in that it houses some of the most spatially expansive and important military installations in the country. The majority of severe weather events in the Southwest occur in association with the North American monsoon system (NAMS), and current observational record has shown a 'wet gets wetter and dry gets drier' global monsoon precipitation trend. We seek to evaluate the warm season extreme weather projection in the Southwest U.S., and how the extremes can affect Department of Defense (DoD) military facilities in that region. A baseline methodology is being developed to select extreme warm season weather events based on historical sounding data and moisture surge observations from Gulf of California. Numerical Weather Prediction (NWP)-type high resolution simulations will be performed for the extreme events identified from Weather Research and Forecast (WRF) model simulations initiated from IPCC GCM and NCAR Reanalysis data in both climate control and climate change periods. The magnitude in extreme event changes will be analyzed, and the synoptic forcing patterns of the future severe thunderstorms will provide a guide line to assess if the military installations in the Southwest will become more or less susceptible to severe weather in the future.
Public Health System Response to Extreme Weather Events.

PubMed

Hunter, Mark D; Hunter, Jennifer C; Yang, Jane E; Crawley, Adam W; Aragón, Tomás J

2016-01-01

Extreme weather events, unpredictable and often far-reaching, constitute a persistent challenge for public health preparedness. The goal of this research is to inform public health systems improvement through examination of extreme weather events, comparing across cases to identify recurring patterns in event and response characteristics. Structured telephone-based interviews were conducted with representatives from health departments to assess characteristics of recent extreme weather events and agencies' responses. Response activities were assessed using the Centers for Disease Control and Prevention Public Health Emergency Preparedness Capabilities framework. Challenges that are typical of this response environment are reported. Forty-five local health departments in 20 US states. Respondents described public health system responses to 45 events involving tornadoes, flooding, wildfires, winter weather, hurricanes, and other storms. Events of similar scale were infrequent for a majority (62%) of the communities involved; disruption to critical infrastructure was universal. Public Health Emergency Preparedness Capabilities considered most essential involved environmental health investigations, mass care and sheltering, surveillance and epidemiology, information sharing, and public information and warning. Unanticipated response activities or operational constraints were common. We characterize extreme weather events as a "quadruple threat" because (1) direct threats to population health are accompanied by damage to public health protective and community infrastructure, (2) event characteristics often impose novel and pervasive burdens on communities, (3) responses rely on critical infrastructures whose failure both creates new burdens and diminishes response capacity, and (4) their infrequency and scale further compromise response capacity. Given the challenges associated with extreme weather events, we suggest opportunities for organizational learning and preparedness improvements.
TECA: Petascale pattern recognition for climate science

DOE Office of Scientific and Technical Information (OSTI.GOV)

Prabhat, .; Byna, Surendra; Vishwanath, Venkatram

Climate Change is one of the most pressing challenges facing humanity in the 21st century. Climate simulations provide us with a unique opportunity to examine effects of anthropogenic emissions. Highresolution climate simulations produce “Big Data”: contemporary climate archives are ≈ 5PB in size and we expect future archives to measure on the order of Exa-Bytes. In this work, we present the successful application of TECA (Toolkit for Extreme Climate Analysis) framework, for extracting extreme weather patterns such as Tropical Cyclones, Atmospheric Rivers and Extra-Tropical Cyclones from TB-sized simulation datasets. TECA has been run at full-scale on Cray XE6 and IBMmore » BG/Q systems, and has reduced the runtime for pattern detection tasks from years to hours. TECA has been utilized to evaluate the performance of various computational models in reproducing the statistics of extreme weather events, and for characterizing the change in frequency of storm systems in the future.« less
Potential climate change impacts on fire weather in the United States

Treesearch

Warren E. Heilman; Ying Tang; Lifeng Luo; Shiyuan Zhong; Julie Winkler; Xindi. Bian

2015-01-01

Researchers at Michigan State University and the Forest Service's Northern Research Station worked on a joint study to examine the possible effects of future global and regional climate change on the occurrence of fire-weather patterns often associated with extreme and erratic wildfire behavior in the United States.
Food Security and Extreme Events: Evidence from Smallholder Farmers in Central America

NASA Astrophysics Data System (ADS)

Saborio-Rodriguez, M.; Alpizar, F.; Harvey, C.; Martinez, R.; Vignola, R.; Viguera, B.; Capitan, T.

2016-12-01

Extreme weather events, which are expected to increase in magnitude and frequency due to climate change, are one of the main threats for smallholder farmers in Central America. Using a rich dataset from carefully selected subsistence farm households, we explore the determinants and severity of food insecurity resulting from extreme hydrometeorological hazards. In addition, we analyze farmerś coping strategies. Our analysis sheds light over food insecurity as an expression of vulnerability in a region that is expected to be increasingly exposed to extreme events and in a population already stressed by poverty and lack of opportunities. Regarding food insecurity, multivariate analyses indicate that education, having at least one migrant in the household, labor allocation, number of plots, and producing coffee are determinants of the probability of experiencing lack of food after an extreme weather event. Once the household is lacking food, the duration of the episode is related to access to credit, number of plots, producing coffee, ownership of land and gender of the head of the household. This results are in line with previous literature on the determinants of food insecurity in particular, and vulnerability, in general. Our dataset also allows us to analyze coping strategies. Households experiencing lack of food after an extreme weather event report mainly changes in their habits, as decreasing the amount of food consumed (54%) and modifying their diet (35%). A low proportion of household (between 10% and 15%, depending on the nature of the event) use their assets, by redirecting their savings, migrating, and selling items from the house. Asking money or food from family and friends or from an organization is reported for 4% of the households. This general results are connected to the specific coping strategies related to damages in crops, which are explored in detail. Our results indicate that there are patterns among the household experiencing lack of food after an extreme weather event. These patterns create opportunities for directing help, and preparing farmers in advance. The coping strategies used are precarious. Therefore, there is a need for rethinking policies that effectively help farmers to cope with extreme weather events with sustainable responses that reduce their vulnerability.
Effects of ignition location models on the burn patterns of simulated wildfires

USGS Publications Warehouse

Bar-Massada, A.; Syphard, A.D.; Hawbaker, T.J.; Stewart, S.I.; Radeloff, V.C.

2011-01-01

Fire simulation studies that use models such as FARSITE often assume that ignition locations are distributed randomly, because spatially explicit information about actual ignition locations are difficult to obtain. However, many studies show that the spatial distribution of ignition locations, whether human-caused or natural, is non-random. Thus, predictions from fire simulations based on random ignitions may be unrealistic. However, the extent to which the assumption of ignition location affects the predictions of fire simulation models has never been systematically explored. Our goal was to assess the difference in fire simulations that are based on random versus non-random ignition location patterns. We conducted four sets of 6000 FARSITE simulations for the Santa Monica Mountains in California to quantify the influence of random and non-random ignition locations and normal and extreme weather conditions on fire size distributions and spatial patterns of burn probability. Under extreme weather conditions, fires were significantly larger for non-random ignitions compared to random ignitions (mean area of 344.5 ha and 230.1 ha, respectively), but burn probability maps were highly correlated (r = 0.83). Under normal weather, random ignitions produced significantly larger fires than non-random ignitions (17.5 ha and 13.3 ha, respectively), and the spatial correlations between burn probability maps were not high (r = 0.54), though the difference in the average burn probability was small. The results of the study suggest that the location of ignitions used in fire simulation models may substantially influence the spatial predictions of fire spread patterns. However, the spatial bias introduced by using a random ignition location model may be minimized if the fire simulations are conducted under extreme weather conditions when fire spread is greatest. ?? 2010 Elsevier Ltd.
Large-Scale Meteorological Patterns Associated with Extreme Precipitation in the US Northeast

NASA Astrophysics Data System (ADS)

Agel, L. A.; Barlow, M. A.

2016-12-01

Patterns of daily large-scale circulation associated with Northeast US extreme precipitation are identified using both k-means clustering (KMC) and Self-Organizing Maps (SOM) applied to tropopause height. Tropopause height provides a compact representation of large-scale circulation patterns, as it is linked to mid-level circulation, low-level thermal contrasts and low-level diabatic heating. Extreme precipitation is defined as the top 1% of daily wet-day observations at 35 Northeast stations, 1979-2008. KMC is applied on extreme precipitation days only, while the SOM algorithm is applied to all days in order to place the extreme results into a larger context. Six tropopause patterns are identified on extreme days: a summertime tropopause ridge, a summertime shallow trough/ridge, a summertime shallow eastern US trough, a deeper wintertime eastern US trough, and two versions of a deep cold-weather trough located across the east-central US. Thirty SOM patterns for all days are identified. Results for all days show that 6 SOM patterns account for almost half of the extreme days, although extreme precipitation occurs in all SOM patterns. The same SOM patterns associated with extreme precipitation also routinely produce non-extreme precipitation; however, on extreme precipitation days the troughs, on average, are deeper and the downstream ridges more pronounced. Analysis of other fields associated with the large-scale patterns show various degrees of anomalously strong upward motion during, and moisture transport preceding, extreme precipitation events.
Will climate change affect weather types associated with flooding in the Elbe river basin?

NASA Astrophysics Data System (ADS)

Nissen, Katrin M.; Pardowitz, Tobias; Ulbrich, Uwe; Nied, Manuela

2013-04-01

This study investigates the effects of anthropogenic climate change on weather types associated with flooding in the Elbe river basin. The study is based on an ensemble of 3 simulations with the ECHAM5 MPIOM coupled model forced with historical and SRES A1B greenhouse gas concentrations. Relevant weather types, occuring in association with recent flood events, are identified in the ERA40 reanalysis data set. The weather types are classified with the SANDRA cluster algorithm. Distributions of tropospheric humidity content, 500 hPa geopotential height and 500 hPa temperature over Europe are taken as input parameters. 8 (out of 40) weather types are found to be associated with flooding events in the Elbe river basin. The majority of these (6) typically occur during winter, while 2 are warm season patterns. Downscaling reveals characteristic precipitation anomalies associated with the individual patterns. The 8 flood relevant weather types are then identified in the ECHAM5 simulations. The effect of climate change on these patterns is investigated by comparing the last 30 years of the previous century to the last 30 years of the 21st century. According to the model the frequency of most patterns will not change. 5 patterns may experience a statistically significant increase in the mean precipitation over the catchment area and 4 patterns an increase in extreme precipitation. Persistence may slightly decrease for 2 patterns and remain unchanged for the others. Overall, this indicates a moderate increase in the risk for Elbe river flooding, related to changes in the weather patterns, in the coming decades.

Can Concentration - Discharge Relationships Diagnose Material Source During Extreme Events?

NASA Astrophysics Data System (ADS)

Karwan, D. L.; Godsey, S.; Rose, L.

2017-12-01

Floods can carry >90% of the basin material exported in a given year as well as alter flow pathways and material sources. In turn, sediment and solute fluxes can increase flood damages and negatively impact water quality and integrate physical and chemical weathering of landscapes and channels. Concentration-discharge (C-Q) relationships are used to both describe export patterns as well as compute them. Metrics for describing C-Q patterns and inferring their controls are vulnerable to infrequent sampling that affects how C-Q relationships are interpolated and interpreted. C-Q relationships are typically evaluated from multiple samples, but because hydrological extremes are rare, data are often unavailable for extreme events. Because solute and sediment C-Q relationships likely respond to changes in hydrologic extremes in different ways, there is a pressing need to define their behavior under extreme conditions, including how to properly sample to capture these patterns. In the absence of such knowledge, improving load estimates in extreme floods will likely remain difficult. Here we explore the use of C-Q relationships to determine when an event alters a watershed system such that it enters a new material source/transport regime. We focus on watersheds with sediment and discharge time series include low-frequency and/or extreme events. For example, we compare solute and sediment patterns in White Clay Creek in southeastern Pennsylvania across a range of flows inclusive of multiple hurricanes for which we have ample ancillary hydrochemical data. TSS is consistently mobilized during high flow events, even during extreme floods associated with hurricanes, and sediment fingerprinting indicates different sediment sources, including in-channel remobilization and landscape erosion, are active at different times. In other words, TSS mobilization in C-Q space is not sensitive to the source of material being mobilized. Unlike sediments, weathering solutes in this watershed tend to exhibit a relatively chemostatic C-Q pattern, except during the runoff-dominated Hurricane Irene, when they exhibit a diluting C-Q pattern. Finally, we summarize the vulnerability of these observations to shifts in sampling effort to highlight the utility and limitations of C-Q-derived export patterns.
Risk from drought and extreme heat in Russian wheat production and its relation to atmospheric blocking and teleconnection patterns

NASA Astrophysics Data System (ADS)

Giannakaki, Paraskevi; Calanca, Pierluigi

2017-04-01

Russia has become one of the leading wheat exporters worldwide. Major breakdowns in Russian wheat production induced by extreme weather events are therefore of high significance not only for the domestic but also for the global market. Wheat production in south-western Russia, the main growing area, suffers in particular from the adverse effects of drought and heat waves. For this reason knowledge of the occurrence of this type of extreme events and of the processes that lead to adverse conditions is of paramount importance for risk management. The negative impacts of heat waves and drought are particularly severe when anomalous conditions persist in time. As an example, a blocking event in summer 2010 resulted in one of the warmest and worst drought conditions in Russia's recent history. The latter caused a decline in Russian wheat production by more than 30%, which in turn prompted the Russian government to issue an export ban that lasted until summer 2011. In view of this, the question of course arises of how much of the negative variations in Russian wheat production levels can be explained by blocking events and other features of the large-scale atmospheric circulation. Specific questions are: how often are blocking events over Russia associated with extreme high temperatures and dry conditions? Which of the teleconnection patterns are correlated with drought and heat stress conditions in the area? Answering these questions can contribute to a develop strategies for agricultural risk management. In this contribution we present results of a study that aims at characterizing the occurrence of adverse weather conditions in south-western Russia in relation to atmospheric blocking and teleconnection patterns such as East Atlantic/Western Russia pattern, the Polar/Eurasia pattern, the North Atlantic Oscillation and the Scandinavia pattern. The analysis relies on weather data for 1980-2014 from 130 stations distributed across the wheat production area. The account for similarities in the occurrence of extreme heat, stations are clustered according to 90th percentile of daily maximum temperature. The results indicate that adverse conditions in the area are significantly correlated with the occurrence of blocking events and with the phase of some teleconnection patterns.
Holistic view to integrated climate change assessment and extreme weather adaptation in the Lake Victoria Basin East Africa

NASA Astrophysics Data System (ADS)

Mutua, F.; Koike, T.

2013-12-01

Extreme weather events have been the leading cause of disasters and damage all over the world.The primary ingredient to these disasters especially floods is rainfall which over the years, despite advances in modeling, computing power and use of new data and technologies, has proven to be difficult to predict. Also, recent climate projections showed a pattern consistent with increase in the intensity and frequency of extreme events in the East African region.We propose a holistic integrated approach to climate change assessment and extreme event adaptation through coupling of analysis techniques, tools and data. The Lake Victoria Basin (LVB) in East Africa supports over three million livelihoods and is a valuable resource to five East African countries as a source of water and means of transport. However, with a Mesoscale weather regime driven by land and lake dynamics,extreme Mesoscale events have been prevalent and the region has been on the receiving end during anomalously wet years in the region. This has resulted in loss of lives, displacements, and food insecurity. In the LVB, the effects of climate change are increasingly being recognized as a significant contributor to poverty, by its linkage to agriculture, food security and water resources. Of particular importance are the likely impacts of climate change in frequency and intensity of extreme events. To tackle this aspect, this study adopted an integrated regional, mesoscale and basin scale approach to climate change assessment. We investigated the projected changes in mean climate over East Africa, diagnosed the signals of climate change in the atmosphere, and transferred this understanding to mesoscale and basin scale. Changes in rainfall were analyzed and similar to the IPCC AR4 report; the selected three General Circulation Models (GCMs) project a wetter East Africa with intermittent dry periods in June-August. Extreme events in the region are projected to increase; with the number of wet days exceeding the 90% percentile of 1981-2000 likely to increase by 20-40% in the whole region. We also focused on short-term weather forecasting as a step towards adapting to a changing climate. This involved dynamic downscaling of global weather forecasts to high resolution with a special focus on extreme events. By utilizing complex model dynamics, the system was able to reproduce the Mesoscale dynamics well, simulated the land/lake breeze and diurnal pattern but was inadequate in some aspects. The quantitative prediction of rainfall was inaccurate with overestimation and misplacement but with reasonable occurrence. To address these shortcomings we investigated the value added by assimilating Advanced Microwave Scanning Radiometer (AMSR-E) brightness temperature during the event. By assimilating 23GHz (sensitive to water) and 89GHz (sensitive to cloud) frequency brightness temperature; the predictability of an extreme rain weather event was investigated. The assimilation through a Cloud Microphysics Data Assimilation (CMDAS) into the weather prediction model considerably improved the spatial distribution of this event.
Predicting atmospheric states from local dynamical properties of the underlying attractor

NASA Astrophysics Data System (ADS)

Faranda, Davide; Rodrigues, David; Alvarez-Castro, M. Carmen; Messori, Gabriele; Yiou, Pascal

2017-04-01

Mid-latitude flows are characterized by a chaotic dynamics and recurring patterns hinting to the existence of an atmospheric attractor. In 1963 Lorenz described this object as: "the collection of all states that the system can assume or approach again and again, as opposed to those that it will ultimately avoid" and analyzed a low dimensional system describing a convective dynamics whose attractor has the shape of a butterfly. Since then, many studies try to find equivalent of the Lorenz butterfly in the complex atmospheric dynamics. Most of the studies where focused to determine the average dimension D of the attractor i.e. the number of degrees of freedom sufficient to describe the atmospheric circulation. However, obtaining reliable estimates of D has proved challenging. Moreover, D does not provide information on transient atmospheric motions, such as those leading to weather extremes. Using recent developments in dynamical systems theory, we show that such motions can be classified through instantaneous rather than average properties of the attractor. The instantaneous properties are uniquely determined by instantaneous dimension and stability. Their extreme values correspond to specific atmospheric patterns, and match extreme weather occurrences. We further show the existence of a significant correlation between the time series of instantaneous stability and dimension and the mean spread of sea-level pressure fields in an operational ensemble weather forecast at lead times of over two weeks. Instantaneous properties of the attractor therefore provide an efficient way of evaluating and informing operational weather forecasts.
Extreme precipitation events and related weather patterns over Iraq

NASA Astrophysics Data System (ADS)

raheem Al-nassar, Ali; Sangrà, Pablo; Alarcón, Marta

2016-04-01

This study aims to investigate the extreme precipitation events and the associated weather phenomena in the Middle East and particularly in Iraq. For this purpose we used Baghdad daily precipitation records from the Iraqi Meteorological and Seismology Organization combined with ECMWF (ERA-Interim) reanalysis data for the period from January 2002 to December 2013. Extreme events were found statistically at the 90% percentile of the recorded precipitation, and were highly correlated with hydrological flooding in some cities of Iraq. We identified fifteen extreme precipitation events. The analysis of the corresponding weather patterns (500 hPa and 250 hPa geopotential and velocity field distribution) indicated that 5 events were related with cut off low causing the highest precipitation (180 mm), 3 events related with rex block (158 mm), 3 events related with jet streak occurrence (130 mm) and 4 events related with troughs (107 mm). . Five of these events caused flash floods and in particular one of them related with a rex block was the most dramatic heavy rain event in Iraq in 30 years. We investigated for each case the convective instability and dynamical forcing together with humidity sources. For convective instability we explored the distribution of the K index and SWEAT index. For dynamical forcing we analyzed at several levels Q vector, divergence, potential and relative vorticity advection and omega vertical velocity. Source of humidity was investigated through humidity and convergence of specific humidity distribution. One triggering factor of all the events is the advection and convergence of humidity from the Red Sea and the Persian Gulf. Therefore a necessary condition for extreme precipitation in Iraq is the advection and convergence of humidity from the Red Sea and Persian Gulf. Our preliminary analysis also indicates that extreme precipitation events are primary dynamical forced playing convective instability a secondary role.
A New Integrated Threshold Selection Methodology for Spatial Forecast Verification of Extreme Events

NASA Astrophysics Data System (ADS)

Kholodovsky, V.

2017-12-01

Extreme weather and climate events such as heavy precipitation, heat waves and strong winds can cause extensive damage to the society in terms of human lives and financial losses. As climate changes, it is important to understand how extreme weather events may change as a result. Climate and statistical models are often independently used to model those phenomena. To better assess performance of the climate models, a variety of spatial forecast verification methods have been developed. However, spatial verification metrics that are widely used in comparing mean states, in most cases, do not have an adequate theoretical justification to benchmark extreme weather events. We proposed a new integrated threshold selection methodology for spatial forecast verification of extreme events that couples existing pattern recognition indices with high threshold choices. This integrated approach has three main steps: 1) dimension reduction; 2) geometric domain mapping; and 3) thresholds clustering. We apply this approach to an observed precipitation dataset over CONUS. The results are evaluated by displaying threshold distribution seasonally, monthly and annually. The method offers user the flexibility of selecting a high threshold that is linked to desired geometrical properties. The proposed high threshold methodology could either complement existing spatial verification methods, where threshold selection is arbitrary, or be directly applicable in extreme value theory.
Shifting patterns of mild weather in response to projected radiative forcing

NASA Astrophysics Data System (ADS)

van der Wiel, Karin; Kapnick, Sarah; Vecchi, Gabriel

2017-04-01

Traditionally, climate change research has focused on changes in mean climate (e.g. global mean temperature, sea level rise, glacier melt) or change in extreme events (e.g. hurricanes, extreme precipitation, droughts, heat waves, wild fires). Though extreme events have the potential to disrupt society, extreme conditions are rare by definition. In contrast, mild weather occurs frequently and many human activities are built around it. Examples of such activities include football games, dog walks, bike rides, and outdoor weddings, but also activities of direct economic impact, e.g. construction work, infrastructure projects, road or rail transportation, air travel, and landscaping projects. Absence of mild weather impacts society in various way, understanding current and future mild weather is therefore of high scientific interest. We present a global analysis of mild weather based on simple and relatable criteria and we explore changes in mild weather occurrence in response to radiative forcing. A high-resolution global climate model, GFDL HiFLOR, is used to allow for investigation of local features and changes. In response to RCP4.5, we find a slight global mean decrease in the annual number of mild days projected both in the near future (-4 d/yr, 2016-2035) and at the end of this century (-10 d/yr, 2081-2100). Projected regional and seasonal redistributions of mild days are substantially greater. Tropical regions are projected to see large decreases, in the mid-latitudes small increases in the number of mild days are projected. Mediterranean climates are projected to see a shift of mild weather away from the local summer to the shoulder seasons. These changes are larger than the interannual variability of mild weather caused by El Niño-Southern Oscillation. Finally, we use reanalysis data to show an observed global decrease in the recent past, and we verify that these observed regional changes in mild weather resemble the projections.
Redesigning healthcare systems to meet the health challenges associated with climate change in the twenty-first century.

PubMed

Phua, Kai-Lit

2015-01-01

In the twenty-first century, climate change is emerging as a significant threat to the health and well-being of the public through links to the following: extreme weather events, sea level rise, temperature-related illnesses, air pollution patterns, water security, food security, vector-borne infectious diseases, and mental health effects (as a result of extreme weather events and climate change-induced population displacement). This article discusses how national healthcare systems can be redesigned through changes in its components such as human resources, facilities and technology, health information system, and health policy to meet these challenges.
Department of Defense 2014 Climate Change Adaptation Roadmap

DTIC Science & Technology

2014-06-01

CREDIT: NANCY JONESBONBREST, PEO C3T HATCHLINGS FROM ENDANGERED SEA TURTLES ARE RELEASED INTO THE ATLANTIC OCEAN NEAR KENNEDY SPACE CENTER/CAPE...changing precipitation patterns, climbing sea levels, and more extreme weather events will intensify the challenges of global instability, hunger...disasters. Our coastal installations are vulnerable to rising sea levels and increased flooding, while droughts, wildfires, and more extreme temperatures
Climate Shocks and Migration: An Agent-Based Modeling Approach.

PubMed

Entwisle, Barbara; Williams, Nathalie E; Verdery, Ashton M; Rindfuss, Ronald R; Walsh, Stephen J; Malanson, George P; Mucha, Peter J; Frizzelle, Brian G; McDaniel, Philip M; Yao, Xiaozheng; Heumann, Benjamin W; Prasartkul, Pramote; Sawangdee, Yothin; Jampaklay, Aree

2016-09-01

This is a study of migration responses to climate shocks. We construct an agent-based model that incorporates dynamic linkages between demographic behaviors, such as migration, marriage, and births, and agriculture and land use, which depend on rainfall patterns. The rules and parameterization of our model are empirically derived from qualitative and quantitative analyses of a well-studied demographic field site, Nang Rong district, Northeast Thailand. With this model, we simulate patterns of migration under four weather regimes in a rice economy: 1) a reference, 'normal' scenario; 2) seven years of unusually wet weather; 3) seven years of unusually dry weather; and 4) seven years of extremely variable weather. Results show relatively small impacts on migration. Experiments with the model show that existing high migration rates and strong selection factors, which are unaffected by climate change, are likely responsible for the weak migration response.
Climate Shocks and Migration: An Agent-Based Modeling Approach

PubMed Central

Entwisle, Barbara; Williams, Nathalie E.; Verdery, Ashton M.; Rindfuss, Ronald R.; Walsh, Stephen J.; Malanson, George P.; Mucha, Peter J.; Frizzelle, Brian G.; McDaniel, Philip M.; Yao, Xiaozheng; Heumann, Benjamin W.; Prasartkul, Pramote; Sawangdee, Yothin; Jampaklay, Aree

2016-01-01

This is a study of migration responses to climate shocks. We construct an agent-based model that incorporates dynamic linkages between demographic behaviors, such as migration, marriage, and births, and agriculture and land use, which depend on rainfall patterns. The rules and parameterization of our model are empirically derived from qualitative and quantitative analyses of a well-studied demographic field site, Nang Rong district, Northeast Thailand. With this model, we simulate patterns of migration under four weather regimes in a rice economy: 1) a reference, ‘normal’ scenario; 2) seven years of unusually wet weather; 3) seven years of unusually dry weather; and 4) seven years of extremely variable weather. Results show relatively small impacts on migration. Experiments with the model show that existing high migration rates and strong selection factors, which are unaffected by climate change, are likely responsible for the weak migration response. PMID:27594725
Tales from the Paleoclimate Underground: Lessons Learned from Reconstructing Extreme Events

NASA Astrophysics Data System (ADS)

Frappier, A. E.

2017-12-01

Tracing patterns of paleoclimate extremes over the past two millennia is becoming ever more important in the effort to understand and predict costly weather hazards and their varied societal impacts. I present three paleoclimate vignettes from the past ten years of different paleotempestology projects I have worked on closely, illustrating our collective challenges and productive pathways in reconstructing rainfall extremes: temporal, spatial, and combining information from disparate proxies. Finally, I aim to share new results from modeling multiple extremes and hazards in Yucatan, a climate change hotspot.
Extreme weather events and related disasters in the Philippines, 2004-08: a sign of what climate change will mean?

PubMed

Yumul, Graciano P; Cruz, Nathaniel A; Servando, Nathaniel T; Dimalanta, Carla B

2011-04-01

Being an archipelagic nation, the Philippines is susceptible and vulnerable to the ill-effects of weather-related hazards. Extreme weather events, which include tropical cyclones, monsoon rains and dry spells, have triggered hazards (such as floods and landslides) that have turned into disasters. Financial resources that were meant for development and social services have had to be diverted in response, addressing the destruction caused by calamities that beset different regions of the country. Changing climatic patterns and weather-related occurrences over the past five years (2004-08) may serve as an indicator of what climate change will mean for the country. Early recognition of this possibility and the implementation of appropriate action and measures, through disaster risk management, are important if loss of life and property is to be minimised, if not totally eradicated. This is a matter of urgent concern given the geographical location and geological characteristics of the Philippines. © 2011 The Author(s). Disasters © Overseas Development Institute, 2011.
Patterns of Storm Injury and Tree Response

Treesearch

Kevin Smith; Walter Shortle; Kenneth Dudzik

2001-01-01

The ice storm of January 1998 in the northeastern United States and adjacent Canada was an extreme example of severe weather that injures trees every year. Broken branches, split branch forks, and snapped stems are all examples of storm injury.
Extreme climatic events drive mammal irruptions: regression analysis of 100-year trends in desert rainfall and temperature

PubMed Central

Greenville, Aaron C; Wardle, Glenda M; Dickman, Chris R

2012-01-01

Extreme climatic events, such as flooding rains, extended decadal droughts and heat waves have been identified increasingly as important regulators of natural populations. Climate models predict that global warming will drive changes in rainfall and increase the frequency and severity of extreme events. Consequently, to anticipate how organisms will respond we need to document how changes in extremes of temperature and rainfall compare to trends in the mean values of these variables and over what spatial scales the patterns are consistent. Using the longest historical weather records available for central Australia – 100 years – and quantile regression methods, we investigate if extreme climate events have changed at similar rates to median events, if annual rainfall has increased in variability, and if the frequency of large rainfall events has increased over this period. Specifically, we compared local (individual weather stations) and regional (Simpson Desert) spatial scales, and quantified trends in median (50th quantile) and extreme weather values (5th, 10th, 90th, and 95th quantiles). We found that median and extreme annual minimum and maximum temperatures have increased at both spatial scales over the past century. Rainfall changes have been inconsistent across the Simpson Desert; individual weather stations showed increases in annual rainfall, increased frequency of large rainfall events or more prolonged droughts, depending on the location. In contrast to our prediction, we found no evidence that intra-annual rainfall had become more variable over time. Using long-term live-trapping records (22 years) of desert small mammals as a case study, we demonstrate that irruptive events are driven by extreme rainfalls (>95th quantile) and that increases in the magnitude and frequency of extreme rainfall events are likely to drive changes in the populations of these species through direct and indirect changes in predation pressure and wildfires. PMID:23170202
Characteristics of atmospheric circulation patterns associated with extreme temperatures over North America in observations and climate models

NASA Astrophysics Data System (ADS)

Loikith, Paul C.

Motivated by a desire to understand the physical mechanisms involved in future anthropogenic changes in extreme temperature events, the key atmospheric circulation patterns associated with extreme daily temperatures over North America in the current climate are identified. Several novel metrics are used to systematically identify and describe these patterns for the entire continent. The orientation, physical characteristics, and spatial scale of these circulation patterns vary based on latitude, season, and proximity to important geographic features (i.e., mountains, coastlines). The anomaly patterns associated with extreme cold events tend to be similar to, but opposite in sign of, those associated with extreme warm events, especially within the westerlies, and tend to scale with temperature in the same locations. The influence of the Pacific North American (PNA) pattern, the Northern Annular Mode (NAM), and the El Niño-Southern Oscillation (ENSO) on extreme temperature days and months shows that associations between extreme temperatures and the PNA and NAM are stronger than associations with ENSO. In general, the association with extremes tends to be stronger on monthly than daily time scales. Extreme temperatures are associated with the PNA and NAM in locations typically influenced by these circulation patterns; however many extremes still occur on days when the amplitude and polarity of these patterns do not favor their occurrence. In winter, synoptic-scale, transient weather disturbances are important drivers of extreme temperature days; however these smaller-scale events are often concurrent with amplified PNA or NAM patterns. Associations are weaker in summer when other physical mechanisms affecting the surface energy balance, such as anomalous soil moisture content, are associated with extreme temperatures. Analysis of historical runs from seventeen climate models from the CMIP5 database suggests that most models simulate realistic circulation patterns associated with extreme temperature days in most places. Model-simulated patterns tend to resemble observed patterns better in the winter than the summer and at 500 hPa than at the surface. There is substantial variability among the suite of models analyzed and most models simulate circulation patterns more realistically away from influential features such as large bodies of water and complex topography.
Evidence of fuels management and fire weather influencing fire severity in an extreme fire event

Treesearch

Jamie M. Lydersen; Brandon M. Collins; Matthew L. Brooks; John R. Matchett; Kristen L. Shive; Nicholas A. Povak; Van R. Kane; Douglas F. Smith

2017-01-01

Following changes in vegetation structure and pattern, along with a changing climate, large wildfire incidence has increased in forests throughout the western U.S. Given this increase there is great interest in whether fuels treatments and previous wildfire can alter fire severity patterns in large wildfires. We assessed the relative influence of previous fuels...
Weather patterns, food security and humanitarian response in sub-Saharan Africa.

PubMed

Haile, Menghestab

2005-11-29

Although considerable achievements in the global reduction of hunger and poverty have been made, progress in Africa so far has been very limited. At present, a third of the African population faces widespread hunger and chronic malnutrition and is exposed to a constant threat of acute food crisis and famine. The most affected are rural households whose livelihood is heavily dependent on traditional rainfed agriculture. Rainfall plays a major role in determining agricultural production and hence the economic and social well being of rural communities. The rainfall pattern in sub-Saharan Africa is influenced by large-scale intra-seasonal and inter-annual climate variability including occasional El Niño events in the tropical Pacific resulting in frequent extreme weather event such as droughts and floods that reduce agricultural outputs resulting in severe food shortages. Households and communities facing acute food shortages are forced to adopt coping strategies to meet the immediate food requirements of their families. These extreme responses may have adverse long-term, impacts on households' ability to have sustainable access to food as well as the environment. The HIV/AIDS crisis has also had adverse impacts on food production activities on the continent. In the absence of safety nets and appropriate financial support mechanisms, humanitarian aid is required to enable households effectively cope with emergencies and manage their limited resources more efficiently. Timely and appropriate humanitarian aid will provide households with opportunities to engage in productive and sustainable livelihood strategies. Investments in poverty reduction efforts would have better impact if complemented with timely and predictable response mechanisms that would ensure the protection of livelihoods during crisis periods whether weather or conflict-related. With an improved understanding of climate variability including El Niño, the implications of weather patterns for the food security and vulnerability of rural communities have become more predictable and can be monitored effectively. The purpose of this paper is to investigate how current advances in the understanding of climate variability, weather patterns and food security could contribute to improved humanitarian decision-making. The paper will propose new approaches for triggering humanitarian responses to weather-induced food crises.
Weather patterns, food security and humanitarian response in sub-Saharan Africa

PubMed Central

Haile, Menghestab

2005-01-01

Although considerable achievements in the global reduction of hunger and poverty have been made, progress in Africa so far has been very limited. At present, a third of the African population faces widespread hunger and chronic malnutrition and is exposed to a constant threat of acute food crisis and famine. The most affected are rural households whose livelihood is heavily dependent on traditional rainfed agriculture. Rainfall plays a major role in determining agricultural production and hence the economic and social well being of rural communities. The rainfall pattern in sub-Saharan Africa is influenced by large-scale intra-seasonal and inter-annual climate variability including occasional El Niño events in the tropical Pacific resulting in frequent extreme weather event such as droughts and floods that reduce agricultural outputs resulting in severe food shortages. Households and communities facing acute food shortages are forced to adopt coping strategies to meet the immediate food requirements of their families. These extreme responses may have adverse long-term impacts on households' ability to have sustainable access to food as well as the environment. The HIV/AIDS crisis has also had adverse impacts on food production activities on the continent. In the absence of safety nets and appropriate financial support mechanisms, humanitarian aid is required to enable households effectively cope with emergencies and manage their limited resources more efficiently. Timely and appropriate humanitarian aid will provide households with opportunities to engage in productive and sustainable livelihood strategies. Investments in poverty reduction efforts would have better impact if complemented with timely and predictable response mechanisms that would ensure the protection of livelihoods during crisis periods whether weather or conflict-related. With an improved understanding of climate variability including El Niño, the implications of weather patterns for the food security and vulnerability of rural communities have become more predictable and can be monitored effectively. The purpose of this paper is to investigate how current advances in the understanding of climate variability, weather patterns and food security could contribute to improved humanitarian decision-making. The paper will propose new approaches for triggering humanitarian responses to weather-induced food crises. PMID:16433102
Comparison of animated jet stream visualizations

NASA Astrophysics Data System (ADS)

Nocke, Thomas; Hoffmann, Peter

2016-04-01

The visualization of 3D atmospheric phenomena in space and time is still a challenging problem. In particular, multiple solutions of animated jet stream visualizations have been produced in recent years, which were designed to visually analyze and communicate the jet and related impacts on weather circulation patterns and extreme weather events. This PICO integrates popular and new jet animation solutions and inter-compares them. The applied techniques (e.g. stream lines or line integral convolution) and parametrizations (color mapping, line lengths) are discussed with respect to visualization quality criteria and their suitability for certain visualization tasks (e.g. jet patterns and jet anomaly analysis, communicating its relevance for climate change).

Using a Six Sigma Fishbone Analysis Approach To Evaluate the Effect of Extreme Weather Events on Salmonella Positives in Young Chicken Slaughter Establishments.

PubMed

Linville, John W; Schumann, Douglas; Aston, Christopher; Defibaugh-Chavez, Stephanie; Seebohm, Scott; Touhey, Lucy

2016-12-01

A six sigma fishbone analysis approach was used to develop a machine learning model in SAS, Version 9.4, by using stepwise linear regression. The model evaluated the effect of a wide variety of variables, including slaughter establishment operational measures, normal (30-year average) weather, and extreme weather events on the rate of Salmonella -positive carcasses in young chicken slaughter establishments. Food Safety and Inspection Service (FSIS) verification carcass sampling data, as well as corresponding data from the National Oceanographic and Atmospheric Administration and the Federal Emergency Management Agency, from September 2011 through April 2015, were included in the model. The results of the modeling show that in addition to basic establishment operations, normal weather patterns, differences from normal and disaster events, including time lag weather and disaster variables, played a role in explaining the Salmonella percent positive that varied by slaughter volume quartile. Findings show that weather and disaster events should be considered as explanatory variables when assessing pathogen-related prevalence analysis or research and slaughter operational controls. The apparent significance of time lag weather variables suggested that at least some of the impact on Salmonella rates occurred after the weather events, which may offer opportunities for FSIS or the poultry industry to implement interventions to mitigate those effects.
Characterization of extreme precipitation within atmospheric river events over California

DOE Office of Scientific and Technical Information (OSTI.GOV)

Jeon, S.; Prabhat,; Byna, S.

Atmospheric rivers (ARs) are large, spatially coherent weather systems with high concentrations of elevated water vapor. These systems often cause severe downpours and flooding over the western coastal United States – and with the availability of more atmospheric moisture in the future under global warming we expect ARs to play an important role as potential causes of extreme precipitation changes. Therefore, we aim to investigate changes in extreme precipitation properties correlated with AR events in a warmer climate, which are large-scale meteorological patterns affecting the weather and climate of California. We have recently developed the TECA (Toolkit for Extreme Climatemore » Analysis) software for automatically identifying and tracking features in climate data sets. Specifically, we can now identify ARs that make landfall on the western coast of North America. Based on this detection procedure, we can investigate the impact of ARs by exploring the spatial extent of AR precipitation using climate model (CMIP5) simulations and characterize spatial patterns of dependence for future projections between AR precipitation extremes under climate change within the statistical framework. Our results show that AR events in the future RCP (Representative Concentration Pathway)8.5 scenario (2076–2100) tend to produce heavier rainfall with higher frequency and longer days than events from the historical run (1981–2005). We also find that the dependence between extreme precipitation events has a shorter spatial range, within localized areas in California, under the high future emissions scenario than under the historical run.« less
Characterization of extreme precipitation within atmospheric river events over California

DOE PAGES

Jeon, S.; Prabhat,; Byna, S.; ...

2015-11-17

Atmospheric rivers (ARs) are large, spatially coherent weather systems with high concentrations of elevated water vapor. These systems often cause severe downpours and flooding over the western coastal United States – and with the availability of more atmospheric moisture in the future under global warming we expect ARs to play an important role as potential causes of extreme precipitation changes. Therefore, we aim to investigate changes in extreme precipitation properties correlated with AR events in a warmer climate, which are large-scale meteorological patterns affecting the weather and climate of California. We have recently developed the TECA (Toolkit for Extreme Climatemore » Analysis) software for automatically identifying and tracking features in climate data sets. Specifically, we can now identify ARs that make landfall on the western coast of North America. Based on this detection procedure, we can investigate the impact of ARs by exploring the spatial extent of AR precipitation using climate model (CMIP5) simulations and characterize spatial patterns of dependence for future projections between AR precipitation extremes under climate change within the statistical framework. Our results show that AR events in the future RCP (Representative Concentration Pathway)8.5 scenario (2076–2100) tend to produce heavier rainfall with higher frequency and longer days than events from the historical run (1981–2005). We also find that the dependence between extreme precipitation events has a shorter spatial range, within localized areas in California, under the high future emissions scenario than under the historical run.« less
A conditional approach to determining the effect of anthropogenic climate change on very rare events.

NASA Astrophysics Data System (ADS)

Wehner, Michael; Pall, Pardeep; Zarzycki, Colin; Stone, Daithi

2016-04-01

Probabilistic extreme event attribution is especially difficult for weather events that are caused by extremely rare large-scale meteorological patterns. Traditional modeling techniques have involved using ensembles of climate models, either fully coupled or with prescribed ocean and sea ice. Ensemble sizes for the latter case ranges from several 100 to tens of thousand. However, even if the simulations are constrained by the observed ocean state, the requisite large-scale meteorological pattern may not occur frequently enough or even at all in free running climate model simulations. We present a method to ensure that simulated events similar to the observed event are modeled with enough fidelity that robust statistics can be determined given the large scale meteorological conditions. By initializing suitably constrained short term ensemble hindcasts of both the actual weather system and a counterfactual weather system where the human interference in the climate system is removed, the human contribution to the magnitude of the event can be determined. However, the change (if any) in the probability of an event of the observed magnitude is conditional not only on the state of the ocean/sea ice system but also on the prescribed initial conditions determined by the causal large scale meteorological pattern. We will discuss the implications of this technique through two examples; the 2013 Colorado flood and the 2014 Typhoon Haiyan.
Intercontinental difference in extreme weather events for the Northern Hemisphere over the past half century

NASA Astrophysics Data System (ADS)

Chen, A.; Tan, J.; Piao, S.

2014-12-01

Weather events that are located in the tails of a weather distribution are called weather extremes. Weather extremes, including severe drought, flooding, heat and cold waves, usually can cause greatest damage to human lives and properties, and have profound implication on ecosystem productivity and carbon cycles. There is mounting evidence suggests that the frequency of temperature and hydrological weather extremes have steadily increased over the last decades, largely due to the ongoing climate change. On the other hand, the distribution and trend of weather extremes can be regionally heterogeneous, which have not been well understood. Here we investigate the spatial distribution and temporal trend of weather extremes in the Northern Hemisphere (NH) over the past half century (1961-2010), with emphasis on the intercontinental comparisons. Our results suggest that warming extremes have increased significantly in East Asia and West Europe; while coldness extremes have decreased globally. Heavy precipitation extremes significantly increased in eastern Northern America, boreal Eurasia, and some parts of China; while drought events showed an increasing trend in northern China-southern Mongolia and some parts of western United States. Our results highlight the regional difference in the trend of weather extremes, which need to be incorporated in the mitigation measures.
Quantification of temperature persistence over the Northern Hemisphere land-area

NASA Astrophysics Data System (ADS)

Pfleiderer, Peter; Coumou, Dim

2017-10-01

Extreme weather events such as heat waves and floods are damaging to society and their contribution to future climate impacts is expected to be large. Such extremes are often related to persistent local weather conditions. Weather persistence is linked to sea surface temperatures, soil-moisture (especially in summer) and large-scale circulation patterns and these factors can alter under past and future climate change. Though persistence is a key characteristic for extreme weather events, to date the climatology and potential changes in persistence have only been poorly documented. Here, we present a systematic analysis of temperature persistence for the northern hemisphere land area. We define persistence as the length of consecutive warm or cold days and use spatial clustering techniques to create regional persistence distributions. We find that persistence is longest in the Arctic and shortest in the mid-latitudes. Parameterizations of the regional persistence distributions show that they are characterized by an exponential decay with a drop in the decay rate for very persistent events, implying that feedback mechanisms are important in prolonging these events. For the mid-latitudes, we find that persistence in summer has increased over the past 60 years. The changes are particularly pronounced for prolonged events suggesting a lengthening in the duration of heat waves.
Attempting to physically explain space-time correlation of extremes

NASA Astrophysics Data System (ADS)

Bernardara, Pietro; Gailhard, Joel

2010-05-01

Spatial and temporal clustering of hydro-meteorological extreme events is scientific evidence. Moreover, the statistical parameters characterizing their local frequencies of occurrence show clear spatial patterns. Thus, in order to robustly assess the hydro-meteorological hazard, statistical models need to be able to take into account spatial and temporal dependencies. Statistical models considering long term correlation for quantifying and qualifying temporal and spatial dependencies are available, such as multifractal approach. Furthermore, the development of regional frequency analysis techniques allows estimating the frequency of occurrence of extreme events taking into account spatial patterns on the extreme quantiles behaviour. However, in order to understand the origin of spatio-temporal clustering, an attempt to find physical explanation should be done. Here, some statistical evidences of spatio-temporal correlation and spatial patterns of extreme behaviour are given on a large database of more than 400 rainfall and discharge series in France. In particular, the spatial distribution of multifractal and Generalized Pareto distribution parameters shows evident correlation patterns in the behaviour of frequency of occurrence of extremes. It is then shown that the identification of atmospheric circulation pattern (weather types) can physically explain the temporal clustering of extreme rainfall events (seasonality) and the spatial pattern of the frequency of occurrence. Moreover, coupling this information with the hydrological modelization of a watershed (as in the Schadex approach) an explanation of spatio-temporal distribution of extreme discharge can also be provided. We finally show that a hydro-meteorological approach (as the Schadex approach) can explain and take into account space and time dependencies of hydro-meteorological extreme events.
Ozone trends and their relationship to characteristic weather patterns.

PubMed

Austin, Elena; Zanobetti, Antonella; Coull, Brent; Schwartz, Joel; Gold, Diane R; Koutrakis, Petros

2015-01-01

Local trends in ozone concentration may differ by meteorological conditions. Furthermore, the trends occurring at the extremes of the Ozone distribution are often not reported even though these may be very different than the trend observed at the mean or median and they may be more relevant to health outcomes. Classify days of observation over a 16-year period into broad categories that capture salient daily local weather characteristics. Determine the rate of change in mean and median O3 concentrations within these different categories to assess how concentration trends are impacted by daily weather. Further examine if trends vary for observations in the extremes of the O3 distribution. We used k-means clustering to categorize days of observation based on the maximum daily temperature, standard deviation of daily temperature, mean daily ground level wind speed, mean daily water vapor pressure and mean daily sea-level barometric pressure. The five cluster solution was determined to be the appropriate one based on cluster diagnostics and cluster interpretability. Trends in cluster frequency and pollution trends within clusters were modeled using Poisson regression with penalized splines as well as quantile regression. There were five characteristic groupings identified. The frequency of days with large standard deviations in hourly temperature decreased over the observation period, whereas the frequency of warmer days with smaller deviations in temperature increased. O3 trends were significantly different within the different weather groupings. Furthermore, the rate of O3 change for the 95th percentile and 5th percentile was significantly different than the rate of change of the median for several of the weather categories.We found that O3 trends vary between different characteristic local weather patterns. O3 trends were significantly different between the different weather groupings suggesting an important interaction between changes in prevailing weather conditions and O3 concentration.
Spatial extremes modeling applied to extreme precipitation data in the state of Paraná

NASA Astrophysics Data System (ADS)

Olinda, R. A.; Blanchet, J.; dos Santos, C. A. C.; Ozaki, V. A.; Ribeiro, P. J., Jr.

2014-11-01

Most of the mathematical models developed for rare events are based on probabilistic models for extremes. Although the tools for statistical modeling of univariate and multivariate extremes are well developed, the extension of these tools to model spatial extremes includes an area of very active research nowadays. A natural approach to such a modeling is the theory of extreme spatial and the max-stable process, characterized by the extension of infinite dimensions of multivariate extreme value theory, and making it possible then to incorporate the existing correlation functions in geostatistics and therefore verify the extremal dependence by means of the extreme coefficient and the Madogram. This work describes the application of such processes in modeling the spatial maximum dependence of maximum monthly rainfall from the state of Paraná, based on historical series observed in weather stations. The proposed models consider the Euclidean space and a transformation referred to as space weather, which may explain the presence of directional effects resulting from synoptic weather patterns. This method is based on the theorem proposed for de Haan and on the models of Smith and Schlather. The isotropic and anisotropic behavior of these models is also verified via Monte Carlo simulation. Estimates are made through pairwise likelihood maximum and the models are compared using the Takeuchi Information Criterion. By modeling the dependence of spatial maxima, applied to maximum monthly rainfall data from the state of Paraná, it was possible to identify directional effects resulting from meteorological phenomena, which, in turn, are important for proper management of risks and environmental disasters in countries with its economy heavily dependent on agribusiness.
It Takes Two to Tango: Arctic Influence on Mid-Latitude Weather is State-Dependent

NASA Astrophysics Data System (ADS)

Francis, J. A.; Vavrus, S. J.; Cohen, J. L.

2016-12-01

Since the late 1990s the Arctic has been warming two to three times faster than mid-latitude regions, a phenomenon known as Arctic amplification (AA). During the first half of 2016, AA reached a new record high value. This disproportionate warming is expected to influence the large-scale atmospheric circulation of the northern hemisphere, but understanding exactly how, where, when, and under what conditions has been an active and controversial topic of research. Observational studies of the atmospheric response are challenged by the short record of AA in a noisy environment, while modeling efforts have produced mixed results owing in part to deficiencies in both capturing the full signal of AA and simulating highly amplified atmospheric features (such as blocks, cut-off lows, and sharp ridging). Despite these challenges, progress in understanding the effects of AA on mid-latitude weather has been steady. In this presentation, we will discuss a new hypothesis and supporting evidence suggesting that the influence of regional AA depends on the background state of the large-scale circulation. Long-lived sea-surface temperature patterns in mid-latitudes, such as the Pacific Decadal Oscillation, favor particular ridge/trough configurations that affect the magnitude of AA's influence on weather patterns. These relationships vary both regionally and seasonally. As AA continues to strengthen with unabated rising concentrations of greenhouse gases, the mechanisms by which AA affects mid-latitude weather, particularly extreme events, may become clearer. The record-breaking AA of 2016 and associated extreme mid-latitude weather events may be a preview of the "new normal" in a warmer world.
Extreme cyclone events in the Arctic: Wintertime variability and trends

NASA Astrophysics Data System (ADS)

Rinke, A.; Maturilli, M.; Graham, R. M.; Matthes, H.; Handorf, D.; Cohen, L.; Hudson, S. R.; Moore, J. C.

2017-09-01

Typically 20-40 extreme cyclone events (sometimes called ‘weather bombs’) occur in the Arctic North Atlantic per winter season, with an increasing trend of 6 events/decade over 1979-2015, according to 6 hourly station data from Ny-Ålesund. This increased frequency of extreme cyclones is consistent with observed significant winter warming, indicating that the meridional heat and moisture transport they bring is a factor in rising temperatures in the region. The winter trend in extreme cyclones is dominated by a positive monthly trend of about 3-4 events/decade in November-December, due mainly to an increasing persistence of extreme cyclone events. A negative trend in January opposes this, while there is no significant trend in February. We relate the regional patterns of the trend in extreme cyclones to anomalously low sea-ice conditions in recent years, together with associated large-scale atmospheric circulation changes such as ‘blockinglike’ circulation patterns (e.g. Scandinavian blocking in December and Ural blocking during January-February).
Nonlinear response of mid-latitude weather to the changing Arctic

NASA Astrophysics Data System (ADS)

Overland, James E.; Dethloff, Klaus; Francis, Jennifer A.; Hall, Richard J.; Hanna, Edward; Kim, Seong-Joong; Screen, James A.; Shepherd, Theodore G.; Vihma, Timo

2016-11-01

Are continuing changes in the Arctic influencing wind patterns and the occurrence of extreme weather events in northern mid-latitudes? The chaotic nature of atmospheric circulation precludes easy answers. The topic is a major science challenge, as continued Arctic temperature increases are an inevitable aspect of anthropogenic climate change. We propose a perspective that rejects simple cause-and-effect pathways and notes diagnostic challenges in interpreting atmospheric dynamics. We present a way forward based on understanding multiple processes that lead to uncertainties in Arctic and mid-latitude weather and climate linkages. We emphasize community coordination for both scientific progress and communication to a broader public.
Addressing the mischaracterization of extreme rainfall in regional climate model simulations - A synoptic pattern based bias correction approach

NASA Astrophysics Data System (ADS)

Li, Jingwan; Sharma, Ashish; Evans, Jason; Johnson, Fiona

2018-01-01

Addressing systematic biases in regional climate model simulations of extreme rainfall is a necessary first step before assessing changes in future rainfall extremes. Commonly used bias correction methods are designed to match statistics of the overall simulated rainfall with observations. This assumes that change in the mix of different types of extreme rainfall events (i.e. convective and non-convective) in a warmer climate is of little relevance in the estimation of overall change, an assumption that is not supported by empirical or physical evidence. This study proposes an alternative approach to account for the potential change of alternate rainfall types, characterized here by synoptic weather patterns (SPs) using self-organizing maps classification. The objective of this study is to evaluate the added influence of SPs on the bias correction, which is achieved by comparing the corrected distribution of future extreme rainfall with that using conventional quantile mapping. A comprehensive synthetic experiment is first defined to investigate the conditions under which the additional information of SPs makes a significant difference to the bias correction. Using over 600,000 synthetic cases, statistically significant differences are found to be present in 46% cases. This is followed by a case study over the Sydney region using a high-resolution run of the Weather Research and Forecasting (WRF) regional climate model, which indicates a small change in the proportions of the SPs and a statistically significant change in the extreme rainfall over the region, although the differences between the changes obtained from the two bias correction methods are not statistically significant.
Climate change & extreme weather vulnerability assessment framework.

DOT National Transportation Integrated Search

2012-12-01

The Federal Highway Administrations (FHWAs) Climate Change and Extreme Weather Vulnerability : Assessment Framework is a guide for transportation agencies interested in assessing their vulnerability : to climate change and extreme weather event...
Weather model performance on extreme rainfall events simulation's over Western Iberian Peninsula

NASA Astrophysics Data System (ADS)

Pereira, S. C.; Carvalho, A. C.; Ferreira, J.; Nunes, J. P.; Kaiser, J. J.; Rocha, A.

2012-08-01

This study evaluates the performance of the WRF-ARW numerical weather model in simulating the spatial and temporal patterns of an extreme rainfall period over a complex orographic region in north-central Portugal. The analysis was performed for the December month of 2009, during the Portugal Mainland rainy season. The heavy rainfall to extreme heavy rainfall periods were due to several low surface pressure's systems associated with frontal surfaces. The total amount of precipitation for December exceeded, in average, the climatological mean for the 1971-2000 time period in +89 mm, varying from 190 mm (south part of the country) to 1175 mm (north part of the country). Three model runs were conducted to assess possible improvements in model performance: (1) the WRF-ARW is forced with the initial fields from a global domain model (RunRef); (2) data assimilation for a specific location (RunObsN) is included; (3) nudging is used to adjust the analysis field (RunGridN). Model performance was evaluated against an observed hourly precipitation dataset of 15 rainfall stations using several statistical parameters. The WRF-ARW model reproduced well the temporal rainfall patterns but tended to overestimate precipitation amounts. The RunGridN simulation provided the best results but model performance of the other two runs was good too, so that the selected extreme rainfall episode was successfully reproduced.
Seasonal Forecasts of Extreme Conditions for Wildland Fire Management in Alaska using NMME

NASA Astrophysics Data System (ADS)

Bhatt, U. S.; Bieniek, P.; Thoman, R.; York, A.; Ziel, R.

2016-12-01

The summer of 2015 was the second largest Alaska fire season since 1950 where approximately the land area of Massachusetts burned. The record fire year of 2004 resulted in 6.5 million acres burned and was costly from property loss (> 35M) and emergency personnel (> 17M). In addition to requiring significant resources, wildfire smoke impacts air quality in Alaska and downstream into North America. Fires in Alaska result from lightning strikes coupled with persistent (extreme) dry warm conditions in remote areas with limited fire management and the seasonal climate/weather determine the extent of the fire season in Alaska. Fire managers rely on weather/climate outlooks for allocating staff and resources from days to a season in advance. Though currently few tested products are available at the seasonal scale. Probabilistic forecasts of the expected seasonal climate/weather would aid tremendously in the planning process. Advanced knowledge of both lightning and fuel conditions would assist managers in planning resource allocation for the upcoming season. For fuel conditions, the Canadian Forest Fire Weather Index System (CFFWIS) has been used since 1992 because it better suits the Alaska fire regime than the standard US National Fire Danger Rating System (NFDRS). This CFFWIS is based on early afternoon values of 2-m air temperature, relative humidity, and 10-m winds and daily total precipitation. Extremes of these indices and the variables are used to calculate these indices will be defined in reference to fire weather for the boreal forest. The CFFWIS will be applied and evaluated for the NMME hindcasts. This study will evaluate the quality of the forecasts comparing the hindcast NMME CFFWIS to acres burned in Alaska. Spatial synoptic patterns in the NMME related to fire weather extremes will be constructed using self-organized maps and probabilities of occurrence will be evaluated against acres burned.
Global Warming: Understanding and Teaching the Forecast.

ERIC Educational Resources Information Center

Andrews, Bill

1995-01-01

A resource for teaching about the consequences of global warming. Discusses feedback from the temperature increase, changes in the global precipitation pattern, effects on agriculture, weather extremes, effects on forests, effects on biodiversity, effects on sea levels, and actions which will help the global community cope with global warming. (LZ)
Rainfall extremes, weather and climatic characterization over complex terrain: A data-driven approach based on signal enhancement methods and extreme value modeling

NASA Astrophysics Data System (ADS)

Pineda, Luis E.; Willems, Patrick

2017-04-01

Weather and climatic characterization of rainfall extremes is both of scientific and societal value for hydrometeorogical risk management, yet discrimination of local and large-scale forcing remains challenging in data-scarce and complex terrain environments. Here, we present an analysis framework that separate weather (seasonal) regimes and climate (inter-annual) influences using data-driven process identification. The approach is based on signal-to-noise separation methods and extreme value (EV) modeling of multisite rainfall extremes. The EV models use a semi-automatic parameter learning [1] for model identification across temporal scales. At weather scale, the EV models are combined with a state-based hidden Markov model [2] to represent the spatio-temporal structure of rainfall as persistent weather states. At climatic scale, the EV models are used to decode the drivers leading to the shift of weather patterns. The decoding is performed into a climate-to-weather signal subspace, built via dimension reduction of climate model proxies (e.g. sea surface temperature and atmospheric circulation) We apply the framework to the Western Andean Ridge (WAR) in Ecuador and Peru (0-6°S) using ground data from the second half of the 20th century. We find that the meridional component of winds is what matters for the in-year and inter-annual variability of high rainfall intensities alongside the northern WAR (0-2.5°S). There, low-level southerly winds are found as advection drivers for oceanic moist of the normal-rainy season and weak/moderate the El Niño (EN) type; but, the strong EN type and its unique moisture surplus is locally advected at lowlands in the central WAR. Moreover, the coastal ridges, south of 3°S dampen meridional airflows, leaving local hygrothermal gradients to control the in-year distribution of rainfall extremes and their anomalies. Overall, we show that the framework, which does not make any prior assumption on the explanatory power of the weather and climate drivers, allows identification of well-known features of the regional climate in a purely data-driven fashion. Thus, this approach shows potential for characterization of precipitation extremes in data-scarce and orographically complex regions in which model reconstructions are the only climate proxies References [1] Mínguez, R., F.J. Méndez, C. Izaguirre, M. Menéndez, and I.J. Losada (2010), Pseudooptimal parameter selection of non-stationary generalized extreme value models for environmental variables, Environ. Modell. Softw. 25, 1592-1607. [2] Pineda, L., P. Willems (2016), Multisite Downscaling of Seasonal Predictions to Daily Rainfall Characteristics over Pacific-Andean River Basins in Ecuador and Peru using a non-homogenous hidden Markov model, J. Hydrometeor, 17(2), 481-498, doi:10.1175/JHM-D-15-0040.1, http://journals.ametsoc.org/doi/full/10.1175/JHM-D-15-0040.1
Enhanced seasonal predictability of the summer mean temperature in Central Europe favored by new dominant weather patterns

NASA Astrophysics Data System (ADS)

Hoffmann, P.

2018-04-01

In this study two complementary approaches have been combined to estimate the reliability of the data-driven seasonal predictability of the meteorological summer mean temperature (T_{JJA}) over Europe. The developed model is based on linear regressions and uses early season predictors to estimate the target value T_{JJA}. We found for the Potsdam (Germany) climate station that the monthly standard deviations (σ) from January to April and the temperature mean ( m) in April are good predictors to describe T_{JJA} after 1990. However, before 1990 the model failed. The core region where this model works is the north-eastern part of Central Europe. We also analyzed long-term trends of monthly Hess/Brezowsky weather types as possible causes of the dynamical changes. In spring, a significant increase of the occurrences for two opposite weather patterns was found: Zonal Ridge across Central Europe (BM) and Trough over Central Europe (TRM). Both currently make up about 30% of the total alternating weather systems over Europe. Other weather types are predominantly decreasing or their trends are not significant. Thus, the predictability may be attributed to these two weather types where the difference between the two Z500 composite patterns is large. This also applies to the north-eastern part of Central Europe. Finally, the detected enhanced seasonal predictability over Europe is alarming, because severe side effects may occur. One of these are more frequent climate extremes in summer half-year.
Studying Weather and Climate Extremes in a Non-stationary Framework

NASA Astrophysics Data System (ADS)

Wu, Z.

2010-12-01

The study of weather and climate extremes often uses the theory of extreme values. Such a detection method has a major problem: to obtain the probability distribution of extremes, one has to implicitly assume the Earth’s climate is stationary over a long period within which the climatology is defined. While such detection makes some sense in a purely statistical view of stationary processes, it can lead to misleading statistical properties of weather and climate extremes caused by long term climate variability and change, and may also cause enormous difficulty in attributing and predicting these extremes. To alleviate this problem, here we report a novel non-stationary framework for studying weather and climate extremes in a non-stationary framework. In this new framework, the weather and climate extremes will be defined as timescale-dependent quantities derived from the anomalies with respect to non-stationary climatologies of different timescales. With this non-stationary framework, the non-stationary and nonlinear nature of climate system will be taken into account; and the attribution and the prediction of weather and climate extremes can then be separated into 1) the change of the statistical properties of the weather and climate extremes themselves and 2) the background climate variability and change. The new non-stationary framework will use the ensemble empirical mode decomposition (EEMD) method, which is a recent major improvement of the Hilbert-Huang Transform for time-frequency analysis. Using this tool, we will adaptively decompose various weather and climate data from observation and climate models in terms of the components of the various natural timescales contained in the data. With such decompositions, the non-stationary statistical properties (both spatial and temporal) of weather and climate anomalies and of their corresponding climatologies will be analyzed and documented.

Extreme weather caused by concurrent cyclone, front and thunderstorm occurrences

PubMed Central

Dowdy, Andrew J.; Catto, Jennifer L.

2017-01-01

Phenomena such as cyclones, fronts and thunderstorms can cause extreme weather in various regions throughout the world. Although these phenomena have been examined in numerous studies, they have not all been systematically examined in combination with each other, including in relation to extreme precipitation and extreme winds throughout the world. Consequently, the combined influence of these phenomena represents a substantial gap in the current understanding of the causes of extreme weather events. Here we present a systematic analysis of cyclones, fronts and thunderstorms in combination with each other, as represented by seven different types of storm combinations. Our results highlight the storm combinations that most frequently cause extreme weather in various regions of the world. The highest risk of extreme precipitation and extreme wind speeds is found to be associated with a triple storm type characterized by concurrent cyclone, front and thunderstorm occurrences. Our findings reveal new insight on the relationships between cyclones, fronts and thunderstorms and clearly demonstrate the importance of concurrent phenomena in causing extreme weather. PMID:28074909
Climate change, extreme weather events, air pollution and respiratory health in Europe.

PubMed

De Sario, M; Katsouyanni, K; Michelozzi, P

2013-09-01

Due to climate change and other factors, air pollution patterns are changing in several urbanised areas of the world, with a significant effect on respiratory health both independently and synergistically with weather conditions; climate scenarios show Europe as one of the most vulnerable regions. European studies on heatwave episodes have consistently shown a synergistic effect of air pollution and high temperatures, while the potential weather-air pollution interaction during wildfires and dust storms is unknown. Allergen patterns are also changing in response to climate change, and air pollution can modify the allergenic potential of pollens, especially in the presence of specific weather conditions. The underlying mechanisms of all these interactions are not well known; the health consequences vary from decreases in lung function to allergic diseases, new onset of diseases, exacerbation of chronic respiratory diseases, and premature death. These multidimensional climate-pollution-allergen effects need to be taken into account in estimating both climate and air pollution-related respiratory effects, in order to set up adequate policy and public health actions to face both the current and future climate and pollution challenges.
Natural hazards and climate change in Dhaka: future trends, social adaptation and informal dynamics

NASA Astrophysics Data System (ADS)

Thiele-Eich, I.; Aßheuer, T.; Simmer, C.; Braun, B.

2009-04-01

Similar to many megacities in the world, Dhaka is regularly threatened by natural hazards. Risks associated with floods and cyclones in particular are expected to increase in the years to come because of global climate change and rapid urbanization. Greater Dhaka is expected to grow from 13.5 million inhabitants in 2007 to 22 million inhabitants by 2025. The vast majority of this growth will take place in informal settlements. Due to the setting of Greater Dhaka in a deltaic plain, the sprawl of slums is primarily taking place in wetlands, swamps and other flood-prone areas. Slum dwellers and informal businesses are vulnerable, but have somehow learned to cope with seasonal floods and developed specific adaptation strategies. An increase of precipitation extremes and tropical cyclones, however, would put considerable stress on the adaptability of the social and economic system. DhakaHazard, a joint research project of the Department of Meteorology at the University of Bonn and the Department of Geography at the University of Cologne, takes up these issues in an interdisciplinary approach. The project, which begun in November 2008, aims to achieve two main objectives: To link analyses of informal social and economic adaptation strategies to models on future climate change and weather extremes. To estimate more accurately the future frequency and magnitude of weather extremes and floods which are crucial for the future adaptability of informal systems. To fulfill these objectives, scientists at the Meteorological Institute are studying the evolution of natural hazards in Bangladesh, while researchers at the Department of Geography are undertaking the task of assessing these hazards from a social point of view. More specifically, the meteorologists are identifying global and regional weather conditions resulting in flooding of the Greater Dhaka region, while possible variations in flood-inducing weather patterns are analyzed by evaluating their frequency and magnitude. Findings are then applied to future global climate scenario runs to obtain a first estimate of trends for the frequency and magnitude of weather extremes and their impact on spatial and temporal characteristics of floods in the Greater Dhaka region. From this estimate, a prediction method for the spatial patterns of flooding within the Dhaka area will be developed. The social part of the project analyzes the vulnerability and resilience of economic and social systems within high-risk areas by utilizing methods such as e.g. quantitative household surveys in Dhaka and qualitative expert interviews. Geographers are hoping to identify adaptation and recovery strategies of slum dwellers and informal businesses (e.g. brickfields, tanneries), analyze the role of social capital as well as formal and informal institutions for building up resilience, and analyze possibilities and limits of adaptation strategies under conditions of further urban growth and climate change. By paying attention to the important behavioral patterns of the informal sector, a meteorological early warning system can then be developed to make better use of weather predictions to mitigate weather-related risks for Greater Dhaka. If successful, this project poses as an exemplary intersection of social science and natural hazards research.
Remote sensing, global warming, and vector-borne disease

DOE Office of Scientific and Technical Information (OSTI.GOV)

Wood, B.; Beck, L.; Dister, S.

1997-12-31

The relationship between climate change and the pattern of vector-borne disease can be viewed at a variety of spatial and temporal scales. At one extreme are changes such as global warming, which are continental in scale and occur over periods of years, decades, or longer. At the opposite extreme are changes associated with severe weather events, which can occur at local and regional scales over periods of days, weeks, or months. Key ecological factors affecting the distribution of vector-borne diseases include temperature, precipitation, and habitat availability, and their impact on vectors, pathogens, reservoirs, and hosts. Global warming can potentially altermore » these factors, thereby affecting the spatial and temporal patterns of disease.« less
Understanding the science of climate change: Talking points - Impacts to the Gulf Coast

Treesearch

Rachel Loehman; Greer Anderson

2010-01-01

Predicted climate changes in the Gulf Coast bioregion include increased air and sea surface temperatures, altered fire regimes and rainfall patterns, increased frequency of extreme weather events, rising sea levels, increased hurricane intensity, and potential destruction of coastal wetlands and the species that reside within them. Prolonged drought conditions, storm...
Integrating K-means Clustering with Kernel Density Estimation for the Development of a Conditional Weather Generation Downscaling Model

NASA Astrophysics Data System (ADS)

Chen, Y.; Ho, C.; Chang, L.

2011-12-01

In previous decades, the climate change caused by global warming increases the occurrence frequency of extreme hydrological events. Water supply shortages caused by extreme events create great challenges for water resource management. To evaluate future climate variations, general circulation models (GCMs) are the most wildly known tools which shows possible weather conditions under pre-defined CO2 emission scenarios announced by IPCC. Because the study area of GCMs is the entire earth, the grid sizes of GCMs are much larger than the basin scale. To overcome the gap, a statistic downscaling technique can transform the regional scale weather factors into basin scale precipitations. The statistic downscaling technique can be divided into three categories include transfer function, weather generator and weather type. The first two categories describe the relationships between the weather factors and precipitations respectively based on deterministic algorithms, such as linear or nonlinear regression and ANN, and stochastic approaches, such as Markov chain theory and statistical distributions. In the weather type, the method has ability to cluster weather factors, which are high dimensional and continuous variables, into weather types, which are limited number of discrete states. In this study, the proposed downscaling model integrates the weather type, using the K-means clustering algorithm, and the weather generator, using the kernel density estimation. The study area is Shihmen basin in northern of Taiwan. In this study, the research process contains two steps, a calibration step and a synthesis step. Three sub-steps were used in the calibration step. First, weather factors, such as pressures, humidities and wind speeds, obtained from NCEP and the precipitations observed from rainfall stations were collected for downscaling. Second, the K-means clustering grouped the weather factors into four weather types. Third, the Markov chain transition matrixes and the conditional probability density function (PDF) of precipitations approximated by the kernel density estimation are calculated respectively for each weather types. In the synthesis step, 100 patterns of synthesis data are generated. First, the weather type of the n-th day are determined by the results of K-means clustering. The associated transition matrix and PDF of the weather type were also determined for the usage of the next sub-step in the synthesis process. Second, the precipitation condition, dry or wet, can be synthesized basing on the transition matrix. If the synthesized condition is dry, the quantity of precipitation is zero; otherwise, the quantity should be further determined in the third sub-step. Third, the quantity of the synthesized precipitation is assigned as the random variable of the PDF defined above. The synthesis efficiency compares the gap of the monthly mean curves and monthly standard deviation curves between the historical precipitation data and the 100 patterns of synthesis data.
Fluoride pollution of atmospheric precipitation and its relationship with air circulation and weather patterns (Wielkopolski National Park, Poland).

PubMed

Walna, Barbara; Kurzyca, Iwona; Bednorz, Ewa; Kolendowicz, Leszek

2013-07-01

A 2-year study (2010-2011) of fluorides in atmospheric precipitation in the open area and in throughfall in Wielkopolski National Park (west-central Poland) showed their high concentrations, reaching a maximum value of 2 mg/l under the tree crowns. These high values indicate substantial deposition of up to 52 mg/m(2)/year. In 2011, over 51% of open area precipitation was characterized by fluoride concentration higher than 0.10 mg/l, and in throughfall such concentrations were found in more than 86% of events. In 2010, a strong connection was evident between fluoride and acid-forming ions, and in 2011, a correlation between phosphate and nitrite ions was seen. Analysis of available data on F(-) concentrations in the air did not show an unequivocal effect on F(-) concentrations in precipitation. To find reasons for and source areas of high fluoride pollution, the cases of extreme fluoride concentration in rainwater were related to atmospheric circulation and weather patterns. Weather conditions on days of extreme pollution were determined by movement of weather fronts over western Poland, or by small cyclonic centers with meteorological fronts. Macroscale air advection over the sampling site originated in the western quadrant (NW, W, and SW), particularly in the middle layers of the troposphere (2,500-5,000 m a.s.l.). Such directions indicate western Poland and Germany as possible sources of the pollution. At the same time in the lower troposphere, air inflow was frequently from the north, showing short distance transport from local emitters, and from the agglomeration of Poznań.
A Framework to Understand Extreme Space Weather Event Probability.

PubMed

Jonas, Seth; Fronczyk, Kassandra; Pratt, Lucas M

2018-03-12

An extreme space weather event has the potential to disrupt or damage infrastructure systems and technologies that many societies rely on for economic and social well-being. Space weather events occur regularly, but extreme events are less frequent, with a small number of historical examples over the last 160 years. During the past decade, published works have (1) examined the physical characteristics of the extreme historical events and (2) discussed the probability or return rate of select extreme geomagnetic disturbances, including the 1859 Carrington event. Here we present initial findings on a unified framework approach to visualize space weather event probability, using a Bayesian model average, in the context of historical extreme events. We present disturbance storm time (Dst) probability (a proxy for geomagnetic disturbance intensity) across multiple return periods and discuss parameters of interest to policymakers and planners in the context of past extreme space weather events. We discuss the current state of these analyses, their utility to policymakers and planners, the current limitations when compared to other hazards, and several gaps that need to be filled to enhance space weather risk assessments. © 2018 Society for Risk Analysis.
Climate projection of synoptic patterns forming extremely high wind speed over the Barents Sea

NASA Astrophysics Data System (ADS)

Surkova, Galina; Krylov, Aleksey

2017-04-01

Frequency of extreme weather events is not very high, but their consequences for the human well-being may be hazardous. These seldom events are not always well simulated by climate models directly. Sometimes it is more effective to analyze numerical projection of large-scale synoptic event generating extreme weather. For example, in mid-latitude surface wind speed depends mainly on the sea level pressure (SLP) field - its configuration and horizontal pressure gradient. This idea was implemented for analysis of extreme wind speed events over the Barents Sea. The calendar of high surface wind speed V (10 m above the surface) was prepared for events with V exceeding 99th percentile value in the central part of the Barents Sea. Analysis of probability distribution function of V was carried out on the base of ERA-Interim reanalysis data (6-hours, 0.75x0.75 degrees of latitude and longitude) for the period 1981-2010. Storm wind events number was found to be 240 days. Sea level pressure field over the sea and surrounding area was selected for each storm wind event. For the climate of the future (scenario RCP8.5), projections of SLP from CMIP5 numerical experiments were used. More than 20 climate models results of projected SLP (2006-2100) over the Barents Sea were correlated with modern storm wind SLP fields. Our calculations showed the positive tendency of annual frequency of storm SLP patterns over the Barents Sea by the end of 21st century.
High-resolution downscaling for hydrological management

NASA Astrophysics Data System (ADS)

Ulbrich, Uwe; Rust, Henning; Meredith, Edmund; Kpogo-Nuwoklo, Komlan; Vagenas, Christos

2017-04-01

Hydrological modellers and water managers require high-resolution climate data to model regional hydrologies and how these may respond to future changes in the large-scale climate. The ability to successfully model such changes and, by extension, critical infrastructure planning is often impeded by a lack of suitable climate data. This typically takes the form of too-coarse data from climate models, which are not sufficiently detailed in either space or time to be able to support water management decisions and hydrological research. BINGO (Bringing INnovation in onGOing water management; ) aims to bridge the gap between the needs of hydrological modellers and planners, and the currently available range of climate data, with the overarching aim of providing adaptation strategies for climate change-related challenges. Producing the kilometre- and sub-daily-scale climate data needed by hydrologists through continuous simulations is generally computationally infeasible. To circumvent this hurdle, we adopt a two-pronged approach involving (1) selective dynamical downscaling and (2) conditional stochastic weather generators, with the former presented here. We take an event-based approach to downscaling in order to achieve the kilometre-scale input needed by hydrological modellers. Computational expenses are minimized by identifying extremal weather patterns for each BINGO research site in lower-resolution simulations and then only downscaling to the kilometre-scale (convection permitting) those events during which such patterns occur. Here we (1) outline the methodology behind the selection of the events, and (2) compare the modelled precipitation distribution and variability (preconditioned on the extremal weather patterns) with that found in observations.
Using Weather Types to Understand and Communicate Weather and Climate Impacts

NASA Astrophysics Data System (ADS)

Prein, A. F.; Hale, B.; Holland, G. J.; Bruyere, C. L.; Done, J.; Mearns, L.

2017-12-01

A common challenge in atmospheric research is the translation of scientific advancements and breakthroughs to decision relevant and actionable information. This challenge is central to the mission of NCAR's Capacity Center for Climate and Weather Extremes (C3WE, www.c3we.ucar.edu). C3WE advances our understanding of weather and climate impacts and integrates these advances with distributed information technology to create tools that promote a global culture of resilience to weather and climate extremes. Here we will present an interactive web-based tool that connects historic U.S. losses and fatalities from extreme weather and climate events to 12 large-scale weather types. Weather types are dominant weather situations such as winter high-pressure systems over the U.S. leading to very cold temperatures or summertime moist humid air masses over the central U.S. leading to severe thunderstorms. Each weather type has a specific fingerprint of economic losses and fatalities in a region that is quantified. Therefore, weather types enable a direct connection of observed or forecasted weather situation to loss of life and property. The presented tool allows the user to explore these connections, raise awareness of existing vulnerabilities, and build resilience to weather and climate extremes.
Impact of extreme weather events and climate change for health and social care systems.

PubMed

Curtis, Sarah; Fair, Alistair; Wistow, Jonathan; Val, Dimitri V; Oven, Katie

2017-12-05

This review, commissioned by the Research Councils UK Living With Environmental Change (LWEC) programme, concerns research on the impacts on health and social care systems in the United Kingdom of extreme weather events, under conditions of climate change. Extreme weather events considered include heatwaves, coldwaves and flooding. Using a structured review method, we consider evidence regarding the currently observed and anticipated future impacts of extreme weather on health and social care systems and the potential of preparedness and adaptation measures that may enhance resilience. We highlight a number of general conclusions which are likely to be of international relevance, although the review focussed on the situation in the UK. Extreme weather events impact the operation of health services through the effects on built, social and institutional infrastructures which support health and health care, and also because of changes in service demand as extreme weather impacts on human health. Strategic planning for extreme weather and impacts on the care system should be sensitive to within country variations. Adaptation will require changes to built infrastructure systems (including transport and utilities as well as individual care facilities) and also to institutional and social infrastructure supporting the health care system. Care sector organisations, communities and individuals need to adapt their practices to improve resilience of health and health care to extreme weather. Preparedness and emergency response strategies call for action extending beyond the emergency response services, to include health and social care providers more generally.
How to introduce climate change into extreme precipitation predetermination? First attempts to tamper with the MEWP method.

NASA Astrophysics Data System (ADS)

Gérardin, Maxime; Brigode, Pierre; Bernardara, Pietro; Gailhard, Joël; Garçon, Rémy; Paquet, Emmanuel; Ribstein, Pierre

2013-04-01

The MEWP (Multi-Exponential Weather Pattern, Garavaglia et al. 2010) distribution is part of the operational method in use at EDF (Electricité de France) for computing dam spillways design floods, i.e. the magnitude of the flood that occurs at a given return period. The return periods of interest lie in the 100 - 10,000 years range. Relying on a purposely-designed classification of atmospheric circulations into weather patterns, and assigning a catchment-specific asymptotical coefficient to each of these patterns, the MEWP distribution provides the daily areal rainfall as a function of the return period. In its current state, the method relies on the implicit assumption of climate stationnarity. In this work we seek to introduce climate change into the MEWP framework. Since the MEWP distribution basically contains two sorts of parameters, namely frequencies of the weather patterns, and magnitudes of the events occurring within each of these patterns, we examine the plausible evolution of these two sets of parameters under climate change, and the sensitivity of the final result to these two sorts of changes. On the one hand, the future frequencies are assessed thanks to GCM outputs from CMIP5, and significant, albeit not greater than the internal variability, changes are observed. On the other hand, the future magnitudes can be suspected to follow the Clausius-Clapeyron relationship (e.g. Pall et al., 2007, and Lenderink et van Meijgaard, 2008). We assess the validity of this hypothesis on the observed daily areal precipitation series for more than a hundred catchments in France. The sensitivity analysis shows that, for the return periods at stake, the impact of frequency changes is small relative to that of magnitude changes, while this would not be true for smaller return periods. Therefore, we propose to incorporate climate change into the MEWP distribution in a simple but realistic way, by taking account of the magnitude change only. We conclude with some insights into the next steps that will allow a more sophisticated representation of climate change in the MEWP distribution. References: Garavaglia, F., J. Gailhard, E. Paquet, M. Lang, R. Garçon, and P. Bernardara. 2010. "Introducing a Rainfall Compound Distribution Model Based on Weather Patterns Sub-sampling." Hydrology and Earth System Sciences 14 (6): 951-964. doi:10.5194/hess-14-951-2010. Lenderink, Geert, and Erik van Meijgaard. 2008. "Increase in Hourly Precipitation Extremes Beyond Expectations from Temperature Changes." Nature Geoscience 1 (8) (July 20): 511-514. doi:10.1038/ngeo262. Pall, P., MR Allen, and DA Stone. 2007. "Testing the Clausius-Clapeyron Constraint on Changes in Extreme Precipitation Under CO 2 Warming." Climate Dynamics 28 (4): 351-363.
Intra-seasonal risk of agriculturally-relevant weather extremes in West African Sudan Savanna

NASA Astrophysics Data System (ADS)

Boansi, David; Tambo, Justice A.; Müller, Marc

2018-01-01

Using household survey data and historical daily climate data for 29 communities across Upper East Ghana and Southwest Burkina Faso, we document climatic conditions deemed major threat to farming in the West African Sudan Savanna and assess risks posed by such conditions over the period 1997-2014. Based on farmers' perception, it is found that drought, low rainfall, intense precipitation, flooding, erratic rainfall pattern, extremely high temperatures, delayed rains, and early cessation of rains are the major threats farmers face. Using first-order Markov chain model and relevant indices for monitoring weather extremes, it is discovered that climatic risk is a general inherent attribute of the rainy season in the study area. Due to recent changes in onset of rains and length of the rainy season, some farmers have either resorted to early planting of drought-hardy crops, late planting of drought-sensitive crops, or spreading of planting across the first 3 months of the season to moderate harm. Each of these planting decisions however has some risk implications. The months of May, June, and October are found to be more susceptible to relatively longer duration of dry and hot spells, while July, August, and September are found to be more susceptible to intense precipitation and flooding. To moderate harm from anticipated weather extremes, farmers need to adjust their cropping calendar, adopt appropriate crop varieties, and implement soil and water management practices. For policy makers and other stakeholders, we recommend the supply of timely and accurate weather forecasts to guide farmers in their seasonal cropping decisions and investment in/installation of low cost irrigation facilities to enhance the practice of supplemental irrigation.
Linking Teleconnections and Iowa's Climate

NASA Astrophysics Data System (ADS)

Rowe, S. T.; Villarini, G.; Lavers, D. A.; Scoccimarro, E.

2013-12-01

In recent years Iowa and the U.S. Midwest has experienced both extreme drought and flood periods. With a drought in 2012 bounded by major floods in 2011 and 2013, the rapid progression from one extreme to the next is on the forefront of the public mind. Given that Iowa is a major agricultural state, extreme weather conditions can have severe socioeconomic consequences. In this research we investigate the large-scale climate processes that occurred concurrently and before a range of dry/wet and cold/hot periods to improve process understanding of these events. It is essential to understand the large-scale climate processes, as these can then provide valuable insight toward the development of long-term climate forecasts for Iowa. In this study monthly and seasonal surface temperature and precipitation over 1950-2012 across Iowa are used. Precipitation and surface temperature data are retrieved from the Parameter-elevation Regressions on Independent Slopes Model (PRISM) Climate Group at Oregon State University. The large-scale atmospheric fields are obtained from the National Center for Environmental Prediction (NCEP) / National Center for Atmospheric Research (NCAR) Reanalysis 1 Project. Precipitation is stratified according to wet, normal, and dry conditions, while temperature according to hot, average, and cold periods. Different stratification criteria based on the precipitation and temperature distributions are examined. Mean sea-level pressure and sea-surface temperature composite maps for the northern hemisphere are then produced for the wet/dry conditions, and cold/hot conditions. Further analyses include correlation, anomalies, and assessment of large-scale planetary wave activity, shedding light on the differences and similarities among the opposite weather conditions. The results of this work will highlight regional weather patterns that are related to the climate over Iowa, providing valuable insight into the mechanisms controlling the occurrence of potentially extreme weather conditions over this area.
Dynamical ocean-atmospheric drivers of floods and droughts

NASA Astrophysics Data System (ADS)

Perdigão, Rui A. P.; Hall, Julia

2014-05-01

The present study contributes to a better depiction and understanding of the "facial expression" of the Earth in terms of dynamical ocean-atmospheric processes associated to both floods and droughts. For this purpose, the study focuses on nonlinear dynamical and statistical analysis of ocean-atmospheric mechanisms contributing to hydrological extremes, broadening the analytical hydro-meteorological perspective of floods and hydrological droughts to driving mechanisms and feedbacks at the global scale. In doing so, the analysis of the climate-related causality of hydrological extremes is not limited to the synoptic situation in the region where the events take place. Rather, it goes further in the train of causality, peering into dynamical interactions between planetary-scale ocean and atmospheric processes that drive weather regimes and influence the antecedent and event conditions associated to hydrological extremes. In order to illustrate the approach, dynamical ocean-atmospheric drivers are investigated for a selection of floods and droughts. Despite occurring in different regions with different timings, common underlying mechanisms are identified for both kinds of hydrological extremes. For instance, several analysed events are seen to have resulted from a large-scale atmospheric situation consisting on standing planetary waves encircling the northern hemisphere. These correspond to wider vortices locked in phase, resulting in wider and more persistent synoptic weather patterns, i.e. with larger spatial and temporal coherence. A standing train of anticyclones and depressions thus encircled the mid and upper latitudes of the northern hemisphere. The stationary regime of planetary waves occurs when the mean eastward zonal flow decreases up to a point in which it no longer exceeds the westward phase propagation of the Rossby waves produced by the latitude-varying Coriolis effect. The ocean-atmospheric causes for this behaviour and consequences on hydrological extremes are investigated and the findings supported with spatiotemporal geostatistical analysis and nonlinear geophysical models. Overall, the study provides a three-fold contribution to the research on hydrological extremes: Firstly, it improves their physical attribution by better understanding the dynamical reasons behind the meteorological drivers. Secondly, it brings out fundamental early warning signs for potential hydrological extremes, by bringing out global ocean-atmospheric features that manifest themselves much earlier than the regional weather patterns. Thirdly, it provides tools for addressing and understanding hydrological regime changes at wider spatiotemporal scales, by providing links to planetary-scale dynamical processes that play a crucial role in multi-decadal global climate variability.
Topological data analyses and machine learning for detection, classification and characterization of atmospheric rivers

NASA Astrophysics Data System (ADS)

Muszynski, G.; Kashinath, K.; Wehner, M. F.; Prabhat, M.; Kurlin, V.

2017-12-01

We investigate novel approaches to detecting, classifying and characterizing extreme weather events, such as atmospheric rivers (ARs), in large high-dimensional climate datasets. ARs are narrow filaments of concentrated water vapour in the atmosphere that bring much of the precipitation in many mid-latitude regions. The precipitation associated with ARs is also responsible for major flooding events in many coastal regions of the world, including the west coast of the United States and western Europe. In this study we combine ideas from Topological Data Analysis (TDA) with Machine Learning (ML) for detecting, classifying and characterizing extreme weather events, like ARs. TDA is a new field that sits at the interface between topology and computer science, that studies "shape" - hidden topological structure - in raw data. It has been applied successfully in many areas of applied sciences, including complex networks, signal processing and image recognition. Using TDA we provide ARs with a shape characteristic as a new feature descriptor for the task of AR classification. In particular, we track the change in topology in precipitable water (integrated water vapour) fields using the Union-Find algorithm. We use the generated feature descriptors with ML classifiers to establish reliability and classification performance of our approach. We utilize the parallel toolkit for extreme climate events analysis (TECA: Petascale Pattern Recognition for Climate Science, Prabhat et al., Computer Analysis of Images and Patterns, 2015) for comparison (it is assumed that events identified by TECA is ground truth). Preliminary results indicate that our approach brings new insight into the study of ARs and provides quantitative information about the relevance of topological feature descriptors in analyses of a large climate datasets. We illustrate this method on climate model output and NCEP reanalysis datasets. Further, our method outperforms existing methods on detection and classification of ARs. This work illustrates that TDA combined with ML may provide a uniquely powerful approach for detection, classification and characterization of extreme weather phenomena.
Decision analysis to address extreme weather : extreme weather effects on ridership and modeling the decision to invest in canopy coverage.

DOT National Transportation Integrated Search

2016-09-01

This project applies a decision analytic methodology that takes considerations of extreme weather events to quantify and assess canopy investment options. The project collected data for two cases studies in two different transit agencies: Chicago Tra...
Extreme water-related weather events and waterborne disease.

PubMed

Cann, K F; Thomas, D Rh; Salmon, R L; Wyn-Jones, A P; Kay, D

2013-04-01

Global climate change is expected to affect the frequency, intensity and duration of extreme water-related weather events such as excessive precipitation, floods, and drought. We conducted a systematic review to examine waterborne outbreaks following such events and explored their distribution between the different types of extreme water-related weather events. Four medical and meteorological databases (Medline, Embase, GeoRef, PubMed) and a global electronic reporting system (ProMED) were searched, from 1910 to 2010. Eighty-seven waterborne outbreaks involving extreme water-related weather events were identified and included, alongside 235 ProMED reports. Heavy rainfall and flooding were the most common events preceding outbreaks associated with extreme weather and were reported in 55·2% and 52·9% of accounts, respectively. The most common pathogens reported in these outbreaks were Vibrio spp. (21·6%) and Leptospira spp. (12·7%). Outbreaks following extreme water-related weather events were often the result of contamination of the drinking-water supply (53·7%). Differences in reporting of outbreaks were seen between the scientific literature and ProMED. Extreme water-related weather events represent a risk to public health in both developed and developing countries, but impact will be disproportionate and likely to compound existing health disparities.
Temperature can interact with landscape factors to affect songbird productivity

Treesearch

W. Andrew Cox; Frank R. III Thompson; Jennifer L. Reidy; John Faaborg

2013-01-01

Increased temperatures and more extreme weather patterns associated with global climate change can interact with other factors that regulate animal populations, but many climate change studies do not incorporate other threats to wildlife in their analyses. We used 20 years of nest-monitoring data from study sites across a gradient of habitat fragmentation in Missouri,...

The role of temperature variability in stabilizing the mountain pine beetle-fungus mutualism

Treesearch

A. L. Addison; J. A. Powell; D. L. Six; M. Moore; B. J. Bentz

2013-01-01

As global climate patterns continue to change and extreme weather events become increasingly common, it is likely that many ecological interactions will be affected. One such interaction is the multipartite symbiosis that exists between the mountain pine beetle and two species of fungi, Grosmannia clavigera and Ophiostoma montium. In this mutualism, the fungi provide...
Tamm Review: Shifting global fire regimes: Lessons from reburns and research needs

Treesearch

Susan J. Prichard; Camille S. Stevens-Rumann; Paul F. Hessburg

2017-01-01

Across the globe, rising temperatures and altered precipitation patterns have caused persistent regional droughts, lengthened fire seasons, and increased the number of weather-driven extreme fire events. Because wildfires currently impact an increasing proportion of the total area burned, land managers need to better understand reburns â in which previously burned...
Chesapeake Bay Program Scientific and Technical Advisory Committee Workshop: Monitoring and Assessing Impacts of Changes in Weather Patterns and Extreme Events. "U.S. EPA National Stormwater Calculator"

EPA Science Inventory

Stormwater discharges continue to cause impairment of our Nation’s waterbodies. In order to reduce impairment, EPA has developed the National Stormwater Calculator (SWC) to help support local, state, and national stormwater management objectives and regulatory efforts to re...
Using Space Weather for Enhanced, Extreme Terrestrial Weather Predictions.

NASA Astrophysics Data System (ADS)

McKenna, M. H.; Lee, T. A., III

2017-12-01

Considering the complexities of the Sun-Earth system, the impacts of space weather to weather here on Earth are not fully understood. This study attempts to analyze this interrelationship by providing a theoretical framework for studying the varied modalities of solar inclination and explores the extent to which they contribute, both in formation and intensity, to extreme terrestrial weather. Using basic topologic and ontology engineering concepts (TOEC), the transdisciplinary syntaxes of space physics, geophysics, and meteorology are analyzed as a seamless interrelated system. This paper reports this investigation's initial findings and examines the validity of the question "Does space weather contribute to extreme weather on Earth, and if so, to what degree?"
Public perceptions of climate change and extreme weather events

NASA Astrophysics Data System (ADS)

Bruine de Bruin, W.; Dessai, S.; Morgan, G.; Taylor, A.; Wong-Parodi, G.

2013-12-01

Climate experts face a serious communication challenge. Public debate about climate change continues, even though at the same time people seem to complain about extreme weather events becoming increasingly common. As compared to the abstract concept of ';climate change,' (changes in) extreme weather events are indeed easier to perceive, more vivid, and personally relevant. Public perception research in different countries has suggested that people commonly expect that climate change will lead to increases in temperature, and that unseasonably warm weather is likely to be interpreted as evidence of climate change. However, relatively little is known about whether public concerns about climate change may also be driven by changes in other types of extreme weather events, such as exceptional amounts of precipitation or flooding. We therefore examined how perceptions of and personal experiences with changes in these specific weather events are related to public concerns about climate change. In this presentation, we will discuss findings from two large public perception surveys conducted in flood-prone Pittsburgh, Pennsylvania (US) and with a national sample in the UK, where extreme flooding has recently occurred across the country. Participants completed questions about their perceptions of and experiences with specific extreme weather events, and their beliefs about climate change. We then conducted linear regressions to predict individual differences in climate-change beliefs, using perceptions of and experiences with specific extreme weather events as predictors, while controlling for demographic characteristics. The US study found that people (a) perceive flood chances to be increasing over the decades, (b) believe climate change to play a role in increases in future flood chances, and (c) would interpret future increases in flooding as evidence for climate change. The UK study found that (a) UK residents are more likely to perceive increases in ';wet' events such as flooding and heavy rainfall than in ';hot' events such as heatwaves, (b) perceptions of these ';wet' weather events are more strongly associated with climate-change beliefs than were extremely ';hot' weather events, and (c) personal experiences with the negative consequences of specific extreme weather events are associated with stronger climate-change beliefs. Hence, which specific weather events people interpret as evidence of climate change may depend on their personal perceptions and experiences - which may not involve the temperature increases that are commonly the focus of climate-change communications. Overall, these findings suggest that climate experts should consider focusing their public communications on extreme weather events that are relevant to their intended audience. We will discuss strategies for designing and evaluating communications about climate change and adaptation.
Modeling extreme (Carrington-type) space weather events using three-dimensional MHD code simulations

NASA Astrophysics Data System (ADS)

Ngwira, C. M.; Pulkkinen, A. A.; Kuznetsova, M. M.; Glocer, A.

2013-12-01

There is growing concern over possible severe societal consequences related to adverse space weather impacts on man-made technological infrastructure and systems. In the last two decades, significant progress has been made towards the modeling of space weather events. Three-dimensional (3-D) global magnetohydrodynamics (MHD) models have been at the forefront of this transition, and have played a critical role in advancing our understanding of space weather. However, the modeling of extreme space weather events is still a major challenge even for existing global MHD models. In this study, we introduce a specially adapted University of Michigan 3-D global MHD model for simulating extreme space weather events that have a ground footprint comparable (or larger) to the Carrington superstorm. Results are presented for an initial simulation run with ``very extreme'' constructed/idealized solar wind boundary conditions driving the magnetosphere. In particular, we describe the reaction of the magnetosphere-ionosphere system and the associated ground induced geoelectric field to such extreme driving conditions. We also discuss the results and what they might mean for the accuracy of the simulations. The model is further tested using input data for an observed space weather event to verify the MHD model consistence and to draw guidance for future work. This extreme space weather MHD model is designed specifically for practical application to the modeling of extreme geomagnetically induced electric fields, which can drive large currents in earth conductors such as power transmission grids.
Applying Customized Climate Advisory Information to Translate Extreme Rainfall Events into Farming Options in the Sudan-Sahel of West Africa

NASA Astrophysics Data System (ADS)

Salack, S.; Worou, N. O.; Sanfo, S.; Nikiema, M. P.; Boubacar, I.; Paturel, J. E.; Tondoh, E. J.

2017-12-01

In West Africa, the risk of food insecurity linked to the low productivity of small holder farming increases as a result of rainfall extremes. In its recent evolution, the rainy season in the Sudan-Sahel zone presents mixed patterns of extreme climatic events. In addition to intense rain events, the distribution of events is associated with pockets of intra-seasonal long dry spells. The negative consequences of these mixed patterns are obvious on the farm: soil water logging, erosion of arable land, dwartness and dessication of crops, and loss in production. The capacity of local farming communities to respond accordingly to rainfall extreme events is often constrained by lack of access to climate information and advisory on smart crop management practices that can help translate extreme rainfall events into farming options. The objective of this work is to expose the framework and the pre-liminary results of a scheme that customizes climate-advisory information package delivery to subsistence farmers in Bakel (Senegal), Ouahigouya & Dano (Burkina Faso) and Bolgatanga (Ghana) for sustainable family agriculture. The package is based on the provision of timely climate information (48-hours, dekadal & seasonal) embedded with smart crop management practices to explore and exploite the potential advantage of intense rainfall and extreme dry spells in millet, maize, sorghum and cowpea farming communities. It is sent via mobile phones and used on selected farms (i.e agro-climatic farm schools) on which some small on-farm infrastructure were built to alleviate negative impacts of weather. Results provide prominent insight on how co-production of weather/climate information, customized access and guidiance on its use can induce fast learning (capacity building of actors), motivation for adaptation, sustainability, potential changes in cropping system, yields and family income in the face of a rainfall extremes at local scales of Sudan-Sahel of West Africa. Keywords: Climate Information, Smart Practices, Farming Options, Agro-Climatic Farm Schools, Sudan-Sahel
Global Weirding? - Using Very Large Ensembles and Extreme Value Theory to assess Changes in Extreme Weather Events Today

NASA Astrophysics Data System (ADS)

Otto, F. E. L.; Mitchell, D.; Sippel, S.; Black, M. T.; Dittus, A. J.; Harrington, L. J.; Mohd Saleh, N. H.

2014-12-01

A shift in the distribution of socially-relevant climate variables such as daily minimum winter temperatures and daily precipitation extremes, has been attributed to anthropogenic climate change for various mid-latitude regions. However, while there are many process-based arguments suggesting also a change in the shape of these distributions, attribution studies demonstrating this have not currently been undertaken. Here we use a very large initial condition ensemble of ~40,000 members simulating the European winter 2013/2014 using the distributed computing infrastructure under the weather@home project. Two separate scenarios are used:1. current climate conditions, and 2. a counterfactual scenario of "world that might have been" without anthropogenic forcing. Specifically focusing on extreme events, we assess how the estimated parameters of the Generalized Extreme Value (GEV) distribution vary depending on variable-type, sampling frequency (daily, monthly, …) and geographical region. We find that the location parameter changes for most variables but, depending on the region and variables, we also find significant changes in scale and shape parameters. The very large ensemble allows, furthermore, to assess whether such findings in the fitted GEV distributions are consistent with an empirical analysis of the model data, and whether the most extreme data still follow a known underlying distribution that in a small sample size might otherwise be thought of as an out-lier. The ~40,000 member ensemble is simulated using 12 different SST patterns (1 'observed', and 11 best guesses of SSTs with no anthropogenic warming). The range in SSTs, along with the corresponding changings in the NAO and high-latitude blocking inform on the dynamics governing some of these extreme events. While strong tele-connection patterns are not found in this particular experiment, the high number of simulated extreme events allows for a more thorough analysis of the dynamics than has been performed before. Therefore, combining extreme value theory with very large ensemble simulations allows us to understand the dynamics of changes in extreme events which is not possible just using the former but also shows in which cases statistics combined with smaller ensembles give as valid results as very large initial conditions.
The waviness of the extratropical jet and daily weather extremes

NASA Astrophysics Data System (ADS)

Röthlisberger, Matthias; Martius, Olivia; Pfahl, Stephan

2016-04-01

In recent years the Northern Hemisphere mid-latitudes have experienced a large number of weather extremes with substantial socio-economic impact, such as the European and Russian heat waves in 2003 and 2010, severe winter floods in the United Kingdom in 2013/2014 and devastating winter storms such as Lothar (1999) and Xynthia (2010) in Central Europe. These have triggered an engaged debate within the scientific community on the role of human induced climate change in the occurrence of such extremes. A key element of this debate is the hypothesis that the waviness of the extratropical jet is linked to the occurrence of weather extremes, with a wavier jet stream favouring more extremes. Previous work on this topic is expanded in this study by analyzing the linkage between a regional measure of jet waviness and daily temperature, precipitation and wind gust extremes. We show that indeed such a linkage exists in many regions of the world, however this waviness-extremes linkage varies spatially in strength and sign. Locally, it is strong only where the relevant weather systems, in which the extremes occur, are affected by the jet waviness. Its sign depends on how the frequency of occurrence of the relevant weather systems is correlated with the occurrence of high and low jet waviness. These results go beyond previous studies by noting that also a decrease in waviness could be associated with an enhanced number of some weather extremes, especially wind gust and precipitation extremes over western Europe.
Quantifying Observed Temperature Extremes in the Southeastern United States

NASA Astrophysics Data System (ADS)

Sura, P.; Stefanova, L. B.; Griffin, M.; Worsnop, R.

2011-12-01

There is broad consensus that the most hazardous effects of climate change are related to a potential increase (in frequency and/or intensity) of extreme weather and climate events. In particular, the statistics of regional daily temperature extremes are of practical interest for the agricultural community and energy suppliers. This is notably true for the Southeastern United States where winter hard freezes are a relatively rare and potentially catastrophic event. Here we use a long record of quality-controlled observations collected from 272 National Weather Service (NWS) Cooperative Observing Network (COOP) stations throughout Florida, Georgia, Alabama, and South and North Carolina to provide a detailed climatology of temperature extremes in the Southeastern United States. We employ two complementary approaches. First, we analyze the effect of El Nino-Southern Oscillation (ENSO) and the Arctic Oscillation (AO) on the non-Gaussian (i.e. higher order) statistics of wintertime daily minimum and maximum temperatures. We find a significant and spatially varying impact of ENSO and AO on the non-Gaussian statistics of daily maximum and minimum temperatures throughout the domain. Second, the extremes of the temperature distributions are studied by calculating the 1st and 99th percentiles, and then analyzing the number of days with record low/high temperatures per season. This analysis of daily temperature extremes reveals oscillating, multi-decadal patterns with spatially varying centers of action.
A regressive storm model for extreme space weather

NASA Astrophysics Data System (ADS)

Terkildsen, Michael; Steward, Graham; Neudegg, Dave; Marshall, Richard

2012-07-01

Extreme space weather events, while rare, pose significant risk to society in the form of impacts on critical infrastructure such as power grids, and the disruption of high end technological systems such as satellites and precision navigation and timing systems. There has been an increased focus on modelling the effects of extreme space weather, as well as improving the ability of space weather forecast centres to identify, with sufficient lead time, solar activity with the potential to produce extreme events. This paper describes the development of a data-based model for predicting the occurrence of extreme space weather events from solar observation. The motivation for this work was to develop a tool to assist space weather forecasters in early identification of solar activity conditions with the potential to produce extreme space weather, and with sufficient lead time to notify relevant customer groups. Data-based modelling techniques were used to construct the model, and an extensive archive of solar observation data used to train, optimise and test the model. The optimisation of the base model aimed to eliminate false negatives (missed events) at the expense of a tolerable increase in false positives, under the assumption of an iterative improvement in forecast accuracy during progression of the solar disturbance, as subsequent data becomes available.
Sensitivity of extreme precipitation to temperature: the variability of scaling factors from a regional to local perspective

NASA Astrophysics Data System (ADS)

Schroeer, K.; Kirchengast, G.

2018-06-01

Potential increases in extreme rainfall induced hazards in a warming climate have motivated studies to link precipitation intensities to temperature. Increases exceeding the Clausius-Clapeyron (CC) rate of 6-7%/°C-1 are seen in short-duration, convective, high-percentile rainfall at mid latitudes, but the rates of change cease or revert at regionally variable threshold temperatures due to moisture limitations. It is unclear, however, what these findings mean in term of the actual risk of extreme precipitation on a regional to local scale. When conditioning precipitation intensities on local temperatures, key influences on the scaling relationship such as from the annual cycle and regional weather patterns need better understanding. Here we analyze these influences, using sub-hourly to daily precipitation data from a dense network of 189 stations in south-eastern Austria. We find that the temperature sensitivities in the mountainous western region are lower than in the eastern lowlands. This is due to the different weather patterns that cause extreme precipitation in these regions. Sub-hourly and hourly intensities intensify at super-CC and CC-rates, respectively, up to temperatures of about 17 °C. However, we also find that, because of the regional and seasonal variability of the precipitation intensities, a smaller scaling factor can imply a larger absolute change in intensity. Our insights underline that temperature precipitation scaling requires careful interpretation of the intent and setting of the study. When this is considered, conditional scaling factors can help to better understand which influences control the intensification of rainfall with temperature on a regional scale.
Climate Change in Nicaragua: a dynamical downscaling of precipitation and temperature.

NASA Astrophysics Data System (ADS)

Porras, Ignasi; Domingo-Dalmau, Anna; Sole, Josep Maria; Arasa, Raul; Picanyol, Miquel; Ángeles Gonzalez-Serrano, M.°; Masdeu, Marta

2016-04-01

Climate Change affects weather patterns and modifies meteorological extreme events like tropical cyclones, heavy rainfalls, dry events, extreme temperatures, etc. The aim of this study is to show the Climate Change projections over Nicaragua for the period 2010-2040 focused on precipitation and temperature. In order to obtain the climate change signal, the results obtained by modelling a past period (1980-2009) were compared with the ones obtained by modelling a future period (2010-2040). The modelling method was based on a dynamical downscaling, coupling global and regional models. The MPI-ESM-MR global climate model was selected due to the better performance over Nicaragua. Moreover, a detailed sensitivity analysis for different parameterizations and schemes of the Weather Research and Forecast (WRF-ARW) model was made to minimize the model uncertainty. To evaluate and validate the methodology, a comparison between model outputs and satellite measurements data was realized. The results show an expected increment of the temperature and an increment of the number of days per year with temperatures higher than 35°C. Monthly precipitation patterns will change although annual total precipitation will be similar. In addition, number of dry days are expected to increase.
Effects of weather on the abundance and distribution on populations of 103 breeding bird species across the United States

NASA Astrophysics Data System (ADS)

Allstadt, A. J.; Gorzo, J.; Bateman, B. L.; Heglund, P. J.; Pidgeon, A. M.; Thogmartin, W.; Vavrus, S. J.; Radeloff, V.

2016-12-01

Often, fewer birds are often observed in an area experiencing extreme weather, as local populations tend to leave an area (via out-migration or concentration in refugia) or experience a change in population size (via mortality or reduced fecundity). Further, weather patterns are often coherent over large areas so unsuitable weather may threaten large portions of an entire species range simultaneously. However, beyond a few iconic irruptive species, rarely have studies applied both the necessary scale and sensitivity required to assess avian population responses over entire species range. Here, we examined the effects of pre-breeding season weather on the distribution and abundances of 103 North American bird species from the late 1966-2010 using observed abundance records from the Breeding Bird Survey. We compared abundances with measures of drought and temperature over each species' range, and with three atmospheric teleconnections that describe large-scale circulation patterns influencing conditions on the ground. More than 90% of the species responded to at least one of our five weather variables. Grassland bird species tended to be most responsive to weather conditions and forest birds the least, though we found relations among all habitat types. For most species, the response was movement rather than large effects on the overall population size. Maps of these responses indicate that concentration and out-migration are both common strategies for coping with challenging weather conditions across a species range. The dynamic distribution of many bird species makes clear the need to account for temporal variability in conservation planning, as areas that are less important for a species' breeding success in most years may be very important in years with abnormal weather conditions.
Subsurface Salts in Antarctic Dry Valley Soils

NASA Technical Reports Server (NTRS)

Englert, P.; Bishop, J. L.; Gibson, E. K.; Koeberl, C.

2013-01-01

The distribution of water-soluble ions, major and minor elements, and other parameters were examined to determine the extent and effects of chemical weathering on cold desert soils. Patterns at the study sites support theories of multiple salt forming processes, including marine aerosols and chemical weathering of mafic minerals. Periodic solar-mediated ionization of atmospheric nitrogen might also produce high nitrate concentrations found in older sediments. Chemical weathering, however, was the major contributor of salts in Antarctic Dry Valleys. The Antarctic Dry Valleys represent a unique analog for Mars, as they are extremely cold and dry desert environments. Similarities in the climate, surface geology, and chemical properties of the Dry Valleys to that of Mars imply the possible presence of these soil formation mechanisms on Mars, other planets and icy satellites.
Influence of extreme weather disasters on global crop production.

PubMed

Lesk, Corey; Rowhani, Pedram; Ramankutty, Navin

2016-01-07

In recent years, several extreme weather disasters have partially or completely damaged regional crop production. While detailed regional accounts of the effects of extreme weather disasters exist, the global scale effects of droughts, floods and extreme temperature on crop production are yet to be quantified. Here we estimate for the first time, to our knowledge, national cereal production losses across the globe resulting from reported extreme weather disasters during 1964-2007. We show that droughts and extreme heat significantly reduced national cereal production by 9-10%, whereas our analysis could not identify an effect from floods and extreme cold in the national data. Analysing the underlying processes, we find that production losses due to droughts were associated with a reduction in both harvested area and yields, whereas extreme heat mainly decreased cereal yields. Furthermore, the results highlight ~7% greater production damage from more recent droughts and 8-11% more damage in developed countries than in developing ones. Our findings may help to guide agricultural priorities in international disaster risk reduction and adaptation efforts.
A Synoptic Weather Typing Approach and Its application to Assess Climate Change Impacts on Extreme Weather Events at Local Scale in South-Central Canada

NASA Astrophysics Data System (ADS)

Shouquan Cheng, Chad; Li, Qian; Li, Guilong

2010-05-01

The synoptic weather typing approach has become popular in evaluating the impacts of climate change on a variety of environmental problems. One of the reasons is its ability to categorize a complex set of meteorological variables as a coherent index, which can facilitate analyses of local climate change impacts. The weather typing method has been successfully applied in Environment Canada for several research projects to analyze climatic change impacts on a number of extreme weather events, such as freezing rain, heavy rainfall, high-/low-flow events, air pollution, and human health. These studies comprise of three major parts: (1) historical simulation modeling to verify the extreme weather events, (2) statistical downscaling to provide station-scale future hourly/daily climate data, and (3) projections of changes in frequency and intensity of future extreme weather events in this century. To achieve these goals, in addition to synoptic weather typing, the modeling conceptualizations in meteorology and hydrology and a number of linear/nonlinear regression techniques were applied. Furthermore, a formal model result verification process has been built into each of the three parts of the projects. The results of the verification, based on historical observations of the outcome variables predicted by the models, showed very good agreement. The modeled results from these projects found that the frequency and intensity of future extreme weather events are projected to significantly increase under a changing climate in this century. This talk will introduce these research projects and outline the modeling exercise and result verification process. The major findings on future projections from the studies will be summarized in the presentation as well. One of the major conclusions from the studies is that the procedures (including synoptic weather typing) used in the studies are useful for climate change impact analysis on future extreme weather events. The implication of the significant increases in frequency and intensity of future extreme weather events would be useful to be considered when revising engineering infrastructure design standards and developing adaptation strategies and policies.
Large scale meteorological patterns and moisture sources during precipitation extremes over South Asia

NASA Astrophysics Data System (ADS)

Mehmood, S.; Ashfaq, M.; Evans, K. J.; Black, R. X.; Hsu, H. H.

2017-12-01

Extreme precipitation during summer season has shown an increasing trend across South Asia in recent decades, causing an exponential increase in weather related losses. Here we combine a cluster analyses technique (Agglomerative Hierarchical Clustering) with a Lagrangian based moisture analyses technique to investigate potential commonalities in the characteristics of the large scale meteorological patterns (LSMP) and moisture anomalies associated with the observed extreme precipitation events, and their representation in the Department of Energy model ACME. Using precipitation observations from the Indian Meteorological Department (IMD) and Asian Precipitation Highly Resolved Observational Data Integration Towards Evaluation (APHRODITE), and atmospheric variables from Era-Interim Reanalysis, we first identify LSMP both in upper and lower troposphere that are responsible for wide spread precipitation extreme events during 1980-2015 period. For each of the selected extreme event, we perform moisture source analyses to identify major evaporative sources that sustain anomalous moisture supply during the course of the event, with a particular focus on local terrestrial moisture recycling. Further, we perform similar analyses on two sets of five-member ensemble of ACME model (1-degree and ¼ degree) to investigate the ability of ACME model in simulating precipitation extremes associated with each of the LSMP patterns and associated anomalous moisture sourcing from each of the terrestrial and oceanic evaporative region. Comparison of low and high-resolution model configurations provides insight about the influence of horizontal grid spacing in the simulation of extreme precipitation and the governing mechanisms.
Extreme Weather and Climate: Workshop Report

NASA Technical Reports Server (NTRS)

Sobel, Adam; Camargo, Suzana; Debucquoy, Wim; Deodatis, George; Gerrard, Michael; Hall, Timothy; Hallman, Robert; Keenan, Jesse; Lall, Upmanu; Levy, Marc;

2016-01-01

Extreme events are the aspects of climate to which human society is most sensitive. Due to both their severity and their rarity, extreme events can challenge the capacity of physical, social, economic and political infrastructures, turning natural events into human disasters. Yet, because they are low frequency events, the science of extreme events is very challenging. Among the challenges is the difficulty of connecting extreme events to longer-term, large-scale variability and trends in the climate system, including anthropogenic climate change. How can we best quantify the risks posed by extreme weather events, both in the current climate and in the warmer and different climates to come? How can we better predict them? What can we do to reduce the harm done by such events? In response to these questions, the Initiative on Extreme Weather and Climate has been created at Columbia University in New York City (extreme weather.columbia.edu). This Initiative is a University-wide activity focused on understanding the risks to human life, property, infrastructure, communities, institutions, ecosystems, and landscapes from extreme weather events, both in the present and future climates, and on developing solutions to mitigate those risks. In May 2015,the Initiative held its first science workshop, entitled Extreme Weather and Climate: Hazards, Impacts, Actions. The purpose of the workshop was to define the scope of the Initiative and tremendously broad intellectual footprint of the topic indicated by the titles of the presentations (see Table 1). The intent of the workshop was to stimulate thought across disciplinary lines by juxtaposing talks whose subjects differed dramatically. Each session concluded with question and answer panel sessions. Approximately, 150 people were in attendance throughout the day. Below is a brief synopsis of each presentation. The synopses collectively reflect the variety and richness of the emerging extreme event research agenda.

The Weather of the Future: Heat Waves, Extreme Storms, and Other Scenes from a Climate-Changed Planet

NASA Astrophysics Data System (ADS)

Cullen, H. M.

2010-12-01

In The Weather of the Future, Dr. Heidi Cullen puts a vivid face on climate change, offering a new way of seeing this phenomenon not just as an event set to happen in the distant future but as something happening right now in our own backyards. Arguing that we must connect the weather of today with the climate change of tomorrow, Cullen combines the latest research from scientists on the ground with state-of-the-art climate model projections to create climate-change scenarios for seven of the most at-risk locations around the world. From the Central Valley of California, where coming droughts will jeopardize the entire state’s water supply, to Greenland, where warmer temperatures will give access to mineral wealth buried beneath ice sheets for millennia, Cullen illustrates how, if left unabated, climate change will transform every corner of the world by midcentury. What emerges is a mosaic of changing weather patterns that collectively spell out the range of risks posed by global warming—whether it’s New York City, whose infrastructure is extremely vulnerable even to a relatively weak Category 3 hurricane or to Bangladesh, a country so low-lying that millions of people could become climate refugees thanks to rising sea levels. The Weather of the Future makes climate change local, showing how no two regions of the country or the world will be affected in quite the same way and demonstrating that melting ice is just the beginning.

Climate change and infectious diseases in North America: the road ahead.

PubMed

Greer, Amy; Ng, Victoria; Fisman, David

2008-03-11

Global climate change is inevitable--the combustion of fossil fuels has resulted in a buildup of greenhouse gases within the atmosphere, causing unprecedented changes to the earth's climate. The Fourth Assessment Report of the Intergovernmental Panel on Climate Change suggests that North America will experience marked changes in weather patterns in coming decades, including warmer temperatures and increased rainfall, summertime droughts and extreme weather events (e.g., tornadoes and hurricanes). Although these events may have direct consequences for health (e.g., injuries and displacement of populations due to thermal stress), they are also likely to cause important changes in the incidence and distribution of infectious diseases, including vector-borne and zoonotic diseases, water-and food-borne diseases and diseases with environmental reservoirs (e.g., endemic fungal diseases). Changes in weather patterns and ecosystems, and health consequences of climate change will probably be most severe in far northern regions (e.g., the Arctic). We provide an overview of the expected nature and direction of such changes, which pose current and future challenges to health care providers and public health agencies.
Climate change and infectious diseases in North America: the road ahead

PubMed Central

Greer, Amy; Ng, Victoria; Fisman, David

2008-01-01

Global climate change is inevitable — the combustion of fossil fuels has resulted in a buildup of greenhouse gases within the atmosphere, causing unprecedented changes to the earth's climate. The Fourth Assessment Report of the Intergovernmental Panel on Climate Change suggests that North America will experience marked changes in weather patterns in coming decades, including warmer temperatures and increased rainfall, summertime droughts and extreme weather events (e.g., tornadoes and hurricanes). Although these events may have direct consequences for health (e.g., injuries and displacement of populations due to thermal stress), they are also likely to cause important changes in the incidence and distribution of infectious diseases, including vector-borne and zoonotic diseases, water-and food-borne diseases and diseases with environmental reservoirs (e.g., endemic fungal diseases). Changes in weather patterns and ecosystems, and health consequences of climate change will probably be most severe in far northern regions (e.g., the Arctic). We provide an overview of the expected nature and direction of such changes, which pose current and future challenges to health care providers and public health agencies. PMID:18332386
Weathering a Perfect Storm from Space

USGS Publications Warehouse

Love, Jeffrey J.

2016-01-01

Extreme space-weather events — intense solar and geomagnetic storms — have occurred in the past: most recently in 1859, 1921 and 1989. So scientists expect that, sooner or later, another extremely intense spaceweather event will strike Earth again. Such storms have the potential to cause widespread interference with and damage to technological systems. A National Academy of Sciences study projects that an extreme space-weather event could end up costing the American economy more than $1 trillion. The question now is whether or not we will take the actions needed to avoid such expensive consequences. Let’s assume that we do. Below is an imagined scenario of how, sometime in the future, an extreme space-weather event might play out.
Examining Projected Changes in Weather & Air Quality Extremes Between 2000 & 2030 using Dynamical Downscaling

EPA Science Inventory

Climate change may alter regional weather extremes resulting in a range of environmental impacts including changes in air quality, water quality and availability, energy demands, agriculture, and ecology. Dynamical downscaling simulations were conducted with the Weather Research...
Extreme Weather Events and Impacts on Vector-borne Diseases and Agriculture

USDA-ARS?s Scientific Manuscript database

Extreme weather events during the period 2010-2012 impacted agriculture and vector-borne disease throughout the world. We evaluated specific weather events with satellite remotely sensed environmental data and evaluated crop production and diseases associated with these events. Significant droughts ...
Research progress of extreme climate and its vegetation response

NASA Astrophysics Data System (ADS)

Cui, Xiaolin; Wei, Xiaoqing; Wang, Tao

2017-08-01

The IPCC’s fifth assessment report indicates that climate warming is unquestionable, the frequency and intensity of extreme weather events may increase, and extreme weather events can destroy the growth conditions of vegetation that is otherwise in a stable condition. Therefore, it is essential to research the formation of extreme weather events and its ecological response, both in terms scientific development and the needs of societal development. This paper mainly examines these issues from the following aspects: (1) the definition of extreme climate events and the methods of studying the associated response of vegetation; (2) the research progress on extreme climate events and their vegetation response; and (3) the future direction of research on extreme climate and its vegetation response.
Climate Change and Your National Forest: Assessing the potential effects of climate change on the El Yunque National Forest

Treesearch

L.N. Jennings; E.A. Treasure; S.G. McNulty

2013-01-01

Forestlands across the world are experiencing increased threats from fire, insect and plant invasions, disease, extreme weather, and drought. Scientists project increases in temperature and changes in rainfall patterns that can make these threats occur more often, with more intensity, and/or for longer durations. Although many of the effects of future changes are...
ClimateNet: A Machine Learning dataset for Climate Science Research

NASA Astrophysics Data System (ADS)

Prabhat, M.; Biard, J.; Ganguly, S.; Ames, S.; Kashinath, K.; Kim, S. K.; Kahou, S.; Maharaj, T.; Beckham, C.; O'Brien, T. A.; Wehner, M. F.; Williams, D. N.; Kunkel, K.; Collins, W. D.

2017-12-01

Deep Learning techniques have revolutionized commercial applications in Computer vision, speech recognition and control systems. The key for all of these developments was the creation of a curated, labeled dataset ImageNet, for enabling multiple research groups around the world to develop methods, benchmark performance and compete with each other. The success of Deep Learning can be largely attributed to the broad availability of this dataset. Our empirical investigations have revealed that Deep Learning is similarly poised to benefit the task of pattern detection in climate science. Unfortunately, labeled datasets, a key pre-requisite for training, are hard to find. Individual research groups are typically interested in specialized weather patterns, making it hard to unify, and share datasets across groups and institutions. In this work, we are proposing ClimateNet: a labeled dataset that provides labeled instances of extreme weather patterns, as well as associated raw fields in model and observational output. We develop a schema in NetCDF to enumerate weather pattern classes/types, store bounding boxes, and pixel-masks. We are also working on a TensorFlow implementation to natively import such NetCDF datasets, and are providing a reference convolutional architecture for binary classification tasks. Our hope is that researchers in Climate Science, as well as ML/DL, will be able to use (and extend) ClimateNet to make rapid progress in the application of Deep Learning for Climate Science research.
The importance of range edges for an irruptive species during extreme weather events

USGS Publications Warehouse

Bateman, Brooke L.; Pidgeon, Anna M.; Radeloff, Volker C.; Allstadt, Andrew J.; Akçakaya, H. Resit; Thogmartin, Wayne E.; Vavrus, Stephen J.; Heglund, Patricia J.

2015-01-01

In a changing climate where more frequent extreme weather may be more common, conservation strategies for weather-sensitive species may require consideration of habitat in the edges of species’ ranges, even though non-core areas may be unoccupied in ‘normal’ years. Our results highlight the conservation importance of range edges in providing refuge from extreme events, such as drought, and climate change.
Extreme weather events: Should drinking water quality management systems adapt to changing risk profiles?

PubMed

Khan, Stuart J; Deere, Daniel; Leusch, Frederic D L; Humpage, Andrew; Jenkins, Madeleine; Cunliffe, David

2015-11-15

Among the most widely predicted and accepted consequences of global climate change are increases in both the frequency and severity of a variety of extreme weather events. Such weather events include heavy rainfall and floods, cyclones, droughts, heatwaves, extreme cold, and wildfires, each of which can potentially impact drinking water quality by affecting water catchments, storage reservoirs, the performance of water treatment processes or the integrity of distribution systems. Drinking water guidelines, such as the Australian Drinking Water Guidelines and the World Health Organization Guidelines for Drinking-water Quality, provide guidance for the safe management of drinking water. These documents present principles and strategies for managing risks that may be posed to drinking water quality. While these principles and strategies are applicable to all types of water quality risks, very little specific attention has been paid to the management of extreme weather events. We present a review of recent literature on water quality impacts of extreme weather events and consider practical opportunities for improved guidance for water managers. We conclude that there is a case for an enhanced focus on the management of water quality impacts from extreme weather events in future revisions of water quality guidance documents. Copyright © 2015 Elsevier Ltd. All rights reserved.
Operational early warning platform for extreme meteorological events

NASA Astrophysics Data System (ADS)

Mühr, Bernhard; Kunz, Michael

2015-04-01

Operational early warning platform for extreme meteorological events Most natural disasters are related to extreme weather events (e.g. typhoons); weather conditions, however, are also highly relevant for humanitarian and disaster relief operations during and after other natural disaster like earthquakes. The internet service "Wettergefahren-Frühwarnung" (WF) provides various information on extreme weather events, especially when these events are associated with a high potential for large damage. The main focus of the platform is on Central Europe, but major events are also monitored worldwide on a daily routine. WF provides high-resolution forecast maps for many weather parameters which allow detailed and reliable predictions about weather conditions during the next days in the affected areas. The WF service became operational in February 2004 and is part of the Center for Disaster Management and Risk Reduction Technology (CEDIM) since 2007. At the end of 2011, CEDIM embarked a new type of interdisciplinary disaster research termed as forensic disaster analysis (FDA) in near real time. In case of an imminent extreme weather event WF plays an important role in CEDIM's FDA group. It provides early and precise information which are always available and updated several times during a day and gives advice and assists with articles and reports on extreme events.
Spatiotemporal influence of temperature, air quality, and urban environment on cause-specific mortality during hazy days.

PubMed

Ho, Hung Chak; Wong, Man Sing; Yang, Lin; Shi, Wenzhong; Yang, Jinxin; Bilal, Muhammad; Chan, Ta-Chien

2018-03-01

Haze is an extreme weather event that can severely increase air pollution exposure, resulting in higher burdens on human health. Few studies have explored the health effects of haze, and none have investigated the spatiotemporal interaction between temperature, air quality and urban environment that may exacerbate the adverse health effects of haze. We investigated the spatiotemporal pattern of haze effects and explored the additional effects of temperature, air pollution and urban environment on the short-term mortality risk during hazy days. We applied a Poisson regression model to daily mortality data from 2007 through 2014, to analyze the short-term mortality risk during haze events in Hong Kong. We evaluated the adverse effect on five types of cause-specific mortality after four types of haze event. We also analyzed the additional effect contributed by the spatial variability of urban environment on each type of cause-specific mortality during a specific haze event. A regular hazy day (lag 0) has higher all-cause mortality risk than a day without haze (odds ratio: 1.029 [1.009, 1.049]). We have also observed high mortality risks associated with mental disorders and diseases of the nervous system during hazy days. In addition, extreme weather and air quality contributed to haze-related mortality, while cold weather and higher ground-level ozone had stronger influences on mortality risk. Areas with a high-density environment, lower vegetation, higher anthropogenic heat, and higher PM 2.5 featured stronger effects of haze on mortality than the others. A combined influence of haze, extreme weather/air quality, and urban environment can result in extremely high mortality due to mental/behavioral disorders or diseases of the nervous system. In conclusion, we developed a data-driven technique to analyze the effects of haze on mortality. Our results target the specific dates and areas with higher mortality during haze events, which can be used for development of health warning protocols/systems. Copyright © 2017 Elsevier Ltd. All rights reserved.
Extreme Weather Events and Interconnected Infrastructures: Toward More Comprehensive Climate Change Planning [Meeting challenges in understanding impacts of extreme weather events on connected infrastructures

DOE Office of Scientific and Technical Information (OSTI.GOV)

Wilbanks, Thomas J.; Fernandez, Steven J.; Allen, Melissa R.

The President s Climate Change Action Plan calls for the development of better science, data, and tools for climate preparedness. Many of the current questions about preparedness for extreme weather events in coming decades are, however, difficult to answer with assets that have been developed by climate science to answer longer-term questions about climate change. Capacities for projecting exposures to climate-related extreme events, along with their implications for interconnected infrastructures, are now emerging.
Extreme Weather Events and Interconnected Infrastructures: Toward More Comprehensive Climate Change Planning [Meeting challenges in understanding impacts of extreme weather events on connected infrastructures

DOE PAGES

Wilbanks, Thomas J.; Fernandez, Steven J.; Allen, Melissa R.

2015-06-23

The President s Climate Change Action Plan calls for the development of better science, data, and tools for climate preparedness. Many of the current questions about preparedness for extreme weather events in coming decades are, however, difficult to answer with assets that have been developed by climate science to answer longer-term questions about climate change. Capacities for projecting exposures to climate-related extreme events, along with their implications for interconnected infrastructures, are now emerging.
An Overview of Science Challenges Pertaining to our Understanding of Extreme Geomagnetically Induced Currents. Chapter 8

NASA Technical Reports Server (NTRS)

Ngwira, Chigomezyo M.; Pulkkinen, Antti A.

2018-01-01

Vulnerability of man-made infrastructure to Earth-directed space weather events is a serious concern for today's technology-dependent society. Space weather-driven geomagnetically induced currents (GICs) can disrupt operation of extended electrically conducting technological systems. The threat of adverse impacts on critical technological infrastructure, like power grids, oil and gas pipelines, and communication networks, has sparked renewed interest in extreme space weather. Because extreme space weather events have low occurrence rate but potentially high impact, this presents a major challenge for our understanding of extreme GIC activity. In this chapter, we discuss some of the key science challenges pertaining to our understanding of extreme events. In addition, we present an overview of GICs including highlights of severe impacts over the last 80 years and recent U.S. Federal actions relevant to this community.
Ionospheric Response to Extremes in the Space Environment: Establishing Benchmarks for the Space Weather Action Plan.

NASA Astrophysics Data System (ADS)

Viereck, R. A.; Azeem, S. I.

2017-12-01

One of the goals of the National Space Weather Action Plan is to establish extreme event benchmarks. These benchmarks are estimates of environmental parameters that impact technologies and systems during extreme space weather events. Quantitative assessment of anticipated conditions during these extreme space weather event will enable operators and users of affected technologies to develop plans for mitigating space weather risks and improve preparedness. The ionosphere is one of the most important regions of space because so many applications either depend on ionospheric space weather for their operation (HF communication, over-the-horizon radars), or can be deleteriously affected by ionospheric conditions (e.g. GNSS navigation and timing, UHF satellite communications, synthetic aperture radar, HF communications). Since the processes that influence the ionosphere vary over time scales from seconds to years, it continues to be a challenge to adequately predict its behavior in many circumstances. Estimates with large uncertainties, in excess of 100%, may result in operators of impacted technologies over or under preparing for such events. The goal of the next phase of the benchmarking activity is to reduce these uncertainties. In this presentation, we will focus on the sources of uncertainty in the ionospheric response to extreme geomagnetic storms. We will then discuss various research efforts required to better understand the underlying processes of ionospheric variability and how the uncertainties in ionospheric response to extreme space weather could be reduced and the estimates improved.
Climate change, extreme weather events, and us health impacts: what can we say?

PubMed

Mills, David M

2009-01-01

Address how climate change impacts on a group of extreme weather events could affect US public health. A literature review summarizes arguments for, and evidence of, a climate change signal in select extreme weather event categories, projections for future events, and potential trends in adaptive capacity and vulnerability in the United States. Western US wildfires already exhibit a climate change signal. The variability within hurricane and extreme precipitation/flood data complicates identifying a similar climate change signal. Health impacts of extreme events are not equally distributed and are very sensitive to a subset of exceptional extreme events. Cumulative uncertainty in forecasting climate change driven characteristics of extreme events and adaptation prevents confidently projecting the future health impacts from hurricanes, wildfires, and extreme precipitation/floods in the United States attributable to climate change.
Tying Variability in Summertime North American Extreme Weather Regimes to the Boreal Summer Intraseasonal Oscillation

NASA Astrophysics Data System (ADS)

Jenney, A. M.; Randall, D. A.

2017-12-01

Tropical intraseasonal oscillations are known to be a source of extratropical variability. We show that subseasonal variability in observed North American epidemiologically significant regional extreme weather regimes is teleconnected to the boreal summer intraseasonal oscillation (BSISO)—a complex tropical weather system that is active during the northern summer and has a 30-50 day timescale. The dynamics of the teleconnection are examined. We also find that interannual variability of the tropical mean-state can modulate the teleconnection. Our results suggest that the BSISO may enable subseasonal to seasonal predictions of North American summertime weather extremes.
A basis set for exploration of sensitivity to prescribed ocean conditions for estimating human contributions to extreme weather in CAM5.1-1degree

DOE Office of Scientific and Technical Information (OSTI.GOV)

Stone, Dáithí A.; Risser, Mark D.; Angélil, Oliver M.

This paper presents two contributions for research into better understanding the role of anthropogenic warming in extreme weather. The first contribution is the generation of a large number of multi-decadal simulations using a medium-resolution atmospheric climate model, CAM5.1-1degree, under two scenarios of historical climate following the protocols of the C20C+ Detection and Attribution project: the one we have experienced (All-Hist), and one that might have been experienced in the absence of human interference with the climate system (Nat-Hist). These simulations are also specifically designed for understanding extreme weather and atmospheric variability in the context of anthropogenic climate change.The second contributionmore » takes advantage of the duration and size of these simulations in order to identify features of variability in the prescribed ocean conditions that may strongly influence calculated estimates of the role of anthropogenic emissions on extreme weather frequency (event attribution). There is a large amount of uncertainty in how much anthropogenic emissions should warm regional ocean surface temperatures, yet contributions to the C20C+ Detection and Attribution project and similar efforts so far use only one or a limited number of possible estimates of the ocean warming attributable to anthropogenic emissions when generating their Nat-Hist simulations. Thus, the importance of the uncertainty in regional attributable warming estimates to the results of event attribution studies is poorly understood. The identification of features of the anomalous ocean state that seem to strongly influence event attribution estimates should therefore be able to serve as a basis set for effective sampling of other plausible attributable warming patterns. The identification performed in this paper examines monthly temperature and precipitation output from the CAM5.1-1degree simulations averaged over 237 land regions, and compares interannual anomalous variations in the ratio between the frequencies of extremes in the All-Hist and Nat-Hist simulations against variations in ocean temperatures.« less
A basis set for exploration of sensitivity to prescribed ocean conditions for estimating human contributions to extreme weather in CAM5.1-1degree

DOE PAGES

Stone, Dáithí A.; Risser, Mark D.; Angélil, Oliver M.; ...

2018-03-01

This paper presents two contributions for research into better understanding the role of anthropogenic warming in extreme weather. The first contribution is the generation of a large number of multi-decadal simulations using a medium-resolution atmospheric climate model, CAM5.1-1degree, under two scenarios of historical climate following the protocols of the C20C+ Detection and Attribution project: the one we have experienced (All-Hist), and one that might have been experienced in the absence of human interference with the climate system (Nat-Hist). These simulations are also specifically designed for understanding extreme weather and atmospheric variability in the context of anthropogenic climate change.The second contributionmore » takes advantage of the duration and size of these simulations in order to identify features of variability in the prescribed ocean conditions that may strongly influence calculated estimates of the role of anthropogenic emissions on extreme weather frequency (event attribution). There is a large amount of uncertainty in how much anthropogenic emissions should warm regional ocean surface temperatures, yet contributions to the C20C+ Detection and Attribution project and similar efforts so far use only one or a limited number of possible estimates of the ocean warming attributable to anthropogenic emissions when generating their Nat-Hist simulations. Thus, the importance of the uncertainty in regional attributable warming estimates to the results of event attribution studies is poorly understood. The identification of features of the anomalous ocean state that seem to strongly influence event attribution estimates should therefore be able to serve as a basis set for effective sampling of other plausible attributable warming patterns. The identification performed in this paper examines monthly temperature and precipitation output from the CAM5.1-1degree simulations averaged over 237 land regions, and compares interannual anomalous variations in the ratio between the frequencies of extremes in the All-Hist and Nat-Hist simulations against variations in ocean temperatures.« less

Future frequencies of extreme weather events in the National Wildlife Refuges of the conterminous U.S.

USGS Publications Warehouse

Martinuzzi, Sebastian; Allstadt, Andrew J.; Bateman, Brooke L.; Heglund, Patricia J.; Pidgeon, Anna M.; Thogmartin, Wayne E.; Vavrus, Stephen J.; Radeloff, Volker C.

2016-01-01

Climate change is a major challenge for managers of protected areas world-wide, and managers need information about future climate conditions within protected areas. Prior studies of climate change effects in protected areas have largely focused on average climatic conditions. However, extreme weather may have stronger effects on wildlife populations and habitats than changes in averages. Our goal was to quantify future changes in the frequency of extreme heat, drought, and false springs, during the avian breeding season, in 415 National Wildlife Refuges in the conterminous United States. We analyzed spatially detailed data on extreme weather frequencies during the historical period (1950–2005) and under different scenarios of future climate change by mid- and late-21st century. We found that all wildlife refuges will likely experience substantial changes in the frequencies of extreme weather, but the types of projected changes differed among refuges. Extreme heat is projected to increase dramatically in all wildlife refuges, whereas changes in droughts and false springs are projected to increase or decrease on a regional basis. Half of all wildlife refuges are projected to see increases in frequency (> 20% higher than the current rate) in at least two types of weather extremes by mid-century. Wildlife refuges in the Southwest and Pacific Southwest are projected to exhibit the fastest rates of change, and may deserve extra attention. Climate change adaptation strategies in protected areas, such as the U.S. wildlife refuges, may need to seriously consider future changes in extreme weather, including the considerable spatial variation of these changes.
Climate change and health in Israel: adaptation policies for extreme weather events.

PubMed

Green, Manfred S; Pri-Or, Noemie Groag; Capeluto, Guedi; Epstein, Yoram; Paz, Shlomit

2013-06-27

Climatic changes have increased the world-wide frequency of extreme weather events such as heat waves, cold spells, floods, storms and droughts. These extreme events potentially affect the health status of millions of people, increasing disease and death. Since mitigation of climate change is a long and complex process, emphasis has recently been placed on the measures required for adaptation. Although the principles underlying these measures are universal, preparedness plans and policies need to be tailored to local conditions. In this paper, we conducted a review of the literature on the possible health consequences of extreme weather events in Israel, where the conditions are characteristic of the Mediterranean region. Strong evidence indicates that the frequency and duration of several types of extreme weather events are increasing in the Mediterranean Basin, including Israel. We examined the public health policy implications for adaptation to climate change in the region, and proposed public health adaptation policy options. Preparedness for the public health impact of increased extreme weather events is still relatively limited and clear public health policies are urgently needed. These include improved early warning and monitoring systems, preparedness of the health system, educational programs and the living environment. Regional collaboration should be a priority.
Basement Fracturing and Weathering On- and Offshore Norway - Genesis, Age, and Landscape Development

NASA Astrophysics Data System (ADS)

Knies, J.; van der Lelij, R.; Faust, J.; Scheiber, T.; Broenner, M.; Fredin, O.; Mueller, A.; Viola, G.

2014-12-01

Saprolite remnants onshore Scandinavia have been investigated only sporadically. The nature and age of the deeply weathered material thus remains only loosely constrained. The type and degree of weathering of in situ weathered soils are indicative of the environmental conditions during their formation. When external forcing changes, properties related to previous weathering conditions are usually preserved, for example in clay mineral assemblages. By constraining the age and rate of weathering onshore and by isotopically dating selected faults determined to be intimately linked to weathered basement blocks, the influence of climate development, brittle deformation and landscape processes on weathering can be quantified. The "BASE" project aims to establish a temporal and conceptual framework for brittle tectonics, weathering patterns and landscape evolution affecting the basement onshore and offshore Norway. We will study the formation of saprolite in pre-Quaternary times, the influence of deep weathering on landscape development and establish a conceptual structural template of the evolution of the brittle deformational features that are exposed on onshore (weathered) basement blocks. Moreover, saprolitic material may have been eroded and preserved along the Norwegian continental margin during Cenozoic times. By studying both the onshore remnants and offshore erosional products deposited during periods of extreme changes of climate and tectonic boundary conditions (e..g Miocene-Pliocene), new inferences on the timing and controlling mechanisms of denudation, and on the relevance of deep weathering on Late Cenozoic global cooling can be drawn.
Observations of an extreme storm in interplanetary space caused by successive coronal mass ejections.

PubMed

Liu, Ying D; Luhmann, Janet G; Kajdič, Primož; Kilpua, Emilia K J; Lugaz, Noé; Nitta, Nariaki V; Möstl, Christian; Lavraud, Benoit; Bale, Stuart D; Farrugia, Charles J; Galvin, Antoinette B

2014-03-18

Space weather refers to dynamic conditions on the Sun and in the space environment of the Earth, which are often driven by solar eruptions and their subsequent interplanetary disturbances. It has been unclear how an extreme space weather storm forms and how severe it can be. Here we report and investigate an extreme event with multi-point remote-sensing and in situ observations. The formation of the extreme storm showed striking novel features. We suggest that the in-transit interaction between two closely launched coronal mass ejections resulted in the extreme enhancement of the ejecta magnetic field observed near 1 AU at STEREO A. The fast transit to STEREO A (in only 18.6 h), or the unusually weak deceleration of the event, was caused by the preconditioning of the upstream solar wind by an earlier solar eruption. These results provide a new view crucial to solar physics and space weather as to how an extreme space weather event can arise from a combination of solar eruptions.
Nonstationarity RC Workshop Report: Nonstationary Weather Patterns and Extreme Events Informing Design and Planning for Long-Lived Infrastructure

DTIC Science & Technology

2017-11-01

magnitude, intensity, and seasonality of climate. For infrastructure projects, relevant design life often exceeds 30 years—a period of time of...uncertainty about future statistical properties of climate at time and spatial scales required for planning and design purposes. Information...about future statistical properties of climate at time and spatial scales required for planning and design , and for assessing future operational
Changing climates, changing forests: A western North American perspective

Treesearch

Christopher J. Fettig; Mary L. Reid; Barbara J. Bentz; Sanna Sevanto; David L. Spittlehouse; T. Wang

2013-01-01

The Earthâs mean surface air temperature has warmed by ~1C over the last 100 years and is projected to increase at a faster rate in the future, accompanied by changes in precipitation patterns and increases in the occurrence of extreme weather events. In western North America, projected increases in mean annual temperatures range from ~1−3.5C by the 2050s,...
Recent Weather Extremes and Impacts on Agricultural Production and Vector-Borne Disease Outbreak Patterns

DTIC Science & Technology

2014-03-21

funding from USDA Foreign Agricultural Service towards the Global Agricultural Monitoring project, DoD Armed Forces Health Surveillance Center’s...Global Emerging Infections Surveillance and Response System (AFHSC/GEIS) under the Human Febrile and Vector -Borne Illnesses (FVBI) Program and USDA ...outbreaks during the 2010?2012 period. We utilized 2000?2012 vegetation index and land surface temperature data from NASA ?s satellitebased Moderate
Observed variability of summer precipitation pattern and extreme events in East China associated with variations of the East Asian summer monsoon: VARIABILITY OF SUMMER PRECIPITATION AND EXTREME EVENT IN EAST CHINA

DOE Office of Scientific and Technical Information (OSTI.GOV)

Wang, Lei; Qian, Yun; Zhang, Yaocun

This paper presents a comprehensive analysis of interannual and interdecadal variations of summer precipitation and precipitation-related extreme events in China associated with variations of the East Asian summer monsoon (EASM) from 1979-2012. A high-quality daily precipitation dataset covering 2287 weather stations in China is analyzed. Based on the precipitation pattern analysis using empirical orthogonal functions, three sub-periods of 1979-1992 (period I), 1993-1999 (period II) and 2000-2012 (period III) are identified to be representative of the precipitation variability. Similar significant variability of the extreme precipitation indices is found across four sub-regions in eastern China. The spatial patterns of summer mean precipitation,more » the number of days with daily rainfall exceeding 95th percentile precipitation (R95p) and the maximum number of consecutive wet days (CWD) anomalies are consistent, but opposite to that of maximum consecutive dry days (CDD) anomalies during the three sub-periods. However, the spatial patterns of hydroclimatic intensity (HY-INT) are notably different from that of the other three extreme indices, but highly correlated to the dry events. The changes of precipitation anomaly patterns are accompanied by the change of the EASM regime and the abrupt shift of the position of the west Pacific subtropical high around 1992/1993 and 1999/2000, respectively, which influence the moisture transport that contributes most to the precipitation anomalies. Lastly, the EASM intensity is linked to sea surface temperature anomaly over the tropical Indian and Pacific Ocean that influences deep convection over the oceans.« less
Detection and attribution of extreme weather disasters

NASA Astrophysics Data System (ADS)

Huggel, Christian; Stone, Dáithí; Hansen, Gerrit

2014-05-01

Single disasters related to extreme weather events have caused loss and damage on the order of up to tens of billions US dollars over the past years. Recent disasters fueled the debate about whether and to what extent these events are related to climate change. In international climate negotiations disaster loss and damage is now high on the agenda, and related policy mechanisms have been discussed or are being implemented. In view of funding allocation and effective risk reduction strategies detection and attribution to climate change of extreme weather events and disasters is a key issue. Different avenues have so far been taken to address detection and attribution in this context. Physical climate sciences have developed approaches, among others, where variables that are reasonably sampled over climatically relevant time periods and related to the meteorological characteristics of the extreme event are examined. Trends in these variables (e.g. air or sea surface temperatures) are compared between observations and climate simulations with and without anthropogenic forcing. Generally, progress has been made in recent years in attribution of changes in the chance of some single extreme weather events to anthropogenic climate change but there remain important challenges. A different line of research is primarily concerned with losses related to the extreme weather events over time, using disaster databases. A growing consensus is that the increase in asset values and in exposure are main drivers of the strong increase of economic losses over the past several decades, and only a limited number of studies have found trends consistent with expectations from climate change. Here we propose a better integration of existing lines of research in detection and attribution of extreme weather events and disasters by applying a risk framework. Risk is thereby defined as a function of the probability of occurrence of an extreme weather event, and the associated consequences, with consequences being a function of the intensity of the physical weather event, the exposure and value of assets, and vulnerabilities. We have examined selected major extreme events and disasters, including superstorm Sandy in 2012, the Pakistan floods and the heat wave in Russia in 2010, the 2010 floods in Colombia and the 2011 floods in Australia. We systematically analyzed to what extent (anthropogenic) climate change may have contributed to intensity and frequency of the event, along with changes in the other risk variables, to eventually reach a more comprehensive understanding of the relative role of climate change in recent loss and damage of extreme weather events.
Evaluation of dynamically downscaled extreme temperature using a spatially-aggregated generalized extreme value (GEV) model

DOE Office of Scientific and Technical Information (OSTI.GOV)

Wang, Jiali; Han, Yuefeng; Stein, Michael L.

2016-02-10

The Weather Research and Forecast (WRF) model downscaling skill in extreme maximum daily temperature is evaluated by using the generalized extreme value (GEV) distribution. While the GEV distribution has been used extensively in climatology and meteorology for estimating probabilities of extreme events, accurately estimating GEV parameters based on data from a single pixel can be difficult, even with fairly long data records. This work proposes a simple method assuming that the shape parameter, the most difficult of the three parameters to estimate, does not vary over a relatively large region. This approach is applied to evaluate 31-year WRF-downscaled extreme maximummore » temperature through comparison with North American Regional Reanalysis (NARR) data. Uncertainty in GEV parameter estimates and the statistical significance in the differences of estimates between WRF and NARR are accounted for by conducting bootstrap resampling. Despite certain biases over parts of the United States, overall, WRF shows good agreement with NARR in the spatial pattern and magnitudes of GEV parameter estimates. Both WRF and NARR show a significant increase in extreme maximum temperature over the southern Great Plains and southeastern United States in January and over the western United States in July. The GEV model shows clear benefits from the regionally constant shape parameter assumption, for example, leading to estimates of the location and scale parameters of the model that show coherent spatial patterns.« less
Probabilistic forecasting of extreme weather events based on extreme value theory

NASA Astrophysics Data System (ADS)

Van De Vyver, Hans; Van Schaeybroeck, Bert

2016-04-01

Extreme events in weather and climate such as high wind gusts, heavy precipitation or extreme temperatures are commonly associated with high impacts on both environment and society. Forecasting extreme weather events is difficult, and very high-resolution models are needed to describe explicitly extreme weather phenomena. A prediction system for such events should therefore preferably be probabilistic in nature. Probabilistic forecasts and state estimations are nowadays common in the numerical weather prediction community. In this work, we develop a new probabilistic framework based on extreme value theory that aims to provide early warnings up to several days in advance. We consider the combined events when an observation variable Y (for instance wind speed) exceeds a high threshold y and its corresponding deterministic forecasts X also exceeds a high forecast threshold y. More specifically two problems are addressed:} We consider pairs (X,Y) of extreme events where X represents a deterministic forecast, and Y the observation variable (for instance wind speed). More specifically two problems are addressed: Given a high forecast X=x_0, what is the probability that Y>y? In other words: provide inference on the conditional probability: [ Pr{Y>y|X=x_0}. ] Given a probabilistic model for Problem 1, what is the impact on the verification analysis of extreme events. These problems can be solved with bivariate extremes (Coles, 2001), and the verification analysis in (Ferro, 2007). We apply the Ramos and Ledford (2009) parametric model for bivariate tail estimation of the pair (X,Y). The model accommodates different types of extremal dependence and asymmetry within a parsimonious representation. Results are presented using the ensemble reforecast system of the European Centre of Weather Forecasts (Hagedorn, 2008). Coles, S. (2001) An Introduction to Statistical modelling of Extreme Values. Springer-Verlag.Ferro, C.A.T. (2007) A probability model for verifying deterministic forecasts of extreme events. Wea. Forecasting {22}, 1089-1100.Hagedorn, R. (2008) Using the ECMWF reforecast dataset to calibrate EPS forecasts. ECMWF Newsletter, {117}, 8-13.Ramos, A., Ledford, A. (2009) A new class of models for bivariate joint tails. J.R. Statist. Soc. B {71}, 219-241.
An Urban Resilience to Extreme Weather Events Framework for Development of Post Event Learning and Transformative Adaptation in Cities

NASA Astrophysics Data System (ADS)

Solecki, W. D.; Friedman, E. S.; Breitzer, R.

2016-12-01

Increasingly frequent extreme weather events are becoming an immediate priority for urban coastal practitioners and stakeholders, adding complexity to decisions concerning risk management for short-term action and long-term needs of city climate stakeholders. The conflict between the prioritization of short versus long-term events by decision-makers creates disconnect between climate science and its applications. The Consortium for Climate Risk in the Urban Northeast (CCRUN), a NOAA RISA team, is developing a set of mechanisms to help bridge this gap. The mechanisms are designed to promote the application of climate science on extreme weather events and their aftermath. It is in the post event policy window where significant opportunities for science-policy linkages exist. In particular, CCRUN is interested in producing actionable and useful information for city managers to use in decision-making processes surrounding extreme weather events and climate change. These processes include a sector specific needs assessment survey instrument and two tools for urban coastal practitioners and stakeholders. The tools focus on post event learning and connections between resilience and transformative adaptation. Elements of the two tools are presented. Post extreme event learning supports urban coastal practitioners and decision-makers concerned about maximizing opportunities for knowledge transfer and assimilation, and policy initiation and development following an extreme weather event. For the urban U.S. Northeast, post event learning helps coastal stakeholders build the capacity to adapt to extreme weather events, and inform and develop their planning capacity through analysis of past actions and steps taken in response to Hurricane Sandy. Connecting resilience with transformative adaptation is intended to promote resilience in urban Northeast coastal settings to the long-term negative consequences of extreme weather events. This is done through a knowledge co-production engagement process that links innovative and flexible adaptation pathways that can address requirements for short-term action and long-term needs.
Re-emerging ocean temperature anomalies in late-2010 associated with a repeat negative NAO

NASA Astrophysics Data System (ADS)

Taws, Sarah L.; Marsh, Robert; Wells, Neil C.; Hirschi, Joël

2011-10-01

Northern Europe was influenced by consecutive episodes of extreme winter weather at the start and end of the 2010 calendar year. A tripole pattern in North Atlantic sea surface temperature anomalies (SSTAs), associated with an exceptionally negative phase of the North Atlantic Oscillation (NAO), characterized both winter periods. This pattern was largely absent at the surface during the 2010 summer season; however equivalent sub-surface temperature anomalies were preserved within the seasonal thermocline throughout the year. Here, we present evidence for the re-emergence of late-winter 2009/10 SSTAs during the following early winter season of 2010/11. The observed re-emergence contributes toward the winter-to-winter persistence of the anomalous tripole pattern. Considering the active influence of the oceans upon leading modes of atmospheric circulation over seasonal timescales, associated with the memory of large-scale sea surface temperature anomaly patterns, the re-emergence of remnant temperature anomalies may have also contributed toward the persistence of a negative winter NAO, and the recurrence of extreme wintry conditions over the initial 2010/11 winter season.
Global meteorological influences on the record UK rainfall of winter 2013-14

NASA Astrophysics Data System (ADS)

Knight, Jeff R.; Maidens, Anna; Watson, Peter A. G.; Andrews, Martin; Belcher, Stephen; Brunet, Gilbert; Fereday, David; Folland, Chris K.; Scaife, Adam A.; Slingo, Julia

2017-07-01

The UK experienced record average rainfall in winter 2013-14, leading to widespread and prolonged flooding. The immediate cause of this exceptional rainfall was a very strong and persistent cyclonic atmospheric circulation over the North East Atlantic Ocean. This was related to a very strong North Atlantic jet stream which resulted in numerous damaging wind storms. These exceptional meteorological conditions have led to renewed questions about whether anthropogenic climate change is noticeably influencing extreme weather. The regional weather pattern responsible for the extreme UK winter coincided with highly anomalous conditions across the globe. We assess the contributions from various possible remote forcing regions using sets of ocean-atmosphere model relaxation experiments, where winds and temperatures are constrained to be similar to those observed in winter 2013-14 within specified atmospheric domains. We find that influences from the tropics were likely to have played a significant role in the development of the unusual extra-tropical circulation, including a role for the tropical Atlantic sector. Additionally, a stronger and more stable stratospheric polar vortex, likely associated with a strong westerly phase of the stratospheric Quasi-Biennial Oscillation (QBO), appears to have contributed to the extreme conditions. While intrinsic climatic variability clearly has the largest effect on the generation of extremes, results from an analysis which segregates circulation-related and residual rainfall variability suggest that emerging climate change signals made a secondary contribution to extreme rainfall in winter 2013-14.
Evaluating sub-seasonal skill in probabilistic forecasts of Atmospheric Rivers and associated extreme events

NASA Astrophysics Data System (ADS)

Subramanian, A. C.; Lavers, D.; Matsueda, M.; Shukla, S.; Cayan, D. R.; Ralph, M.

2017-12-01

Atmospheric rivers (ARs) - elongated plumes of intense moisture transport - are a primary source of hydrological extremes, water resources and impactful weather along the West Coast of North America and Europe. There is strong demand in the water management, societal infrastructure and humanitarian sectors for reliable sub-seasonal forecasts, particularly of extreme events, such as floods and droughts so that actions to mitigate disastrous impacts can be taken with sufficient lead-time. Many recent studies have shown that ARs in the Pacific and the Atlantic are modulated by large-scale modes of climate variability. Leveraging the improved understanding of how these large-scale climate modes modulate the ARs in these two basins, we use the state-of-the-art multi-model forecast systems such as the North American Multi-Model Ensemble (NMME) and the Subseasonal-to-Seasonal (S2S) database to help inform and assess the probabilistic prediction of ARs and related extreme weather events over the North American and European West Coasts. We will present results from evaluating probabilistic forecasts of extreme precipitation and AR activity at the sub-seasonal scale. In particular, results from the comparison of two winters (2015-16 and 2016-17) will be shown, winters which defied canonical El Niño teleconnection patterns over North America and Europe. We further extend this study to analyze probabilistic forecast skill of AR events in these two basins and the variability in forecast skill during certain regimes of large-scale climate modes.
Extreme cyclone events in the Arctic during wintertime: Variability and Trends

NASA Astrophysics Data System (ADS)

Rinke, Annette; Maturilli, Marion; Graham, Robert; Matthes, Heidrun; Handorf, Doerthe; Cohen, Lana; Hudson, Stephen; Moore, John

2017-04-01

Extreme cyclone events are of significant interest as they can transport much heat, moisture, and momentum poleward. Associated impacts are warming and sea-ice breakup. Recently, several examples of such extreme weather events occurred in winter (e.g. during the N-ICE2015 campaign north of Svalbard and the Frank North Atlantic storm during the end of December 2015). With Arctic amplification and associated reduced sea-ice cover and warmer sea surface temperatures, the occurrence of extreme cyclones events could be a plausible scenario. We calculate the spatial patterns, and changes and trends of the number of extreme cyclone events in the Arctic based on ERA-Interim six-hourly sea level pressure (SLP) data for winter (November-February) 1979-2015. Further, we analyze the SLP data from the Ny Alesund station for the same 37 year period. We define an extreme cyclone event by a extreme low central pressure (SLP below 985 hPa, which is the 5th percentile of the Ny Alesund/N-ICE2015 SLP data) and a deepening of at least 6 hPa/6 hours. Areas of highest frequency of occurrence of extreme cyclones are south/southeast of Greenland (corresponding to the Islandic low), between Norway and Svalbard and in the Barents/Kara Seas. The time series of the number of occurrence of extreme cyclone events for Ny Alesund/N-ICE show considerable interannual variability. The trend is not consistent through the winter, but we detect an increase in early winter and a slight decrease in late winter. The former is due to the increased occurrence of longer events at the expense of short events. Furthermore, the difference patterns of the frequency of events for months following the September with high and low Arctic sea-ice extent ("Low minus high sea ice") conforms with the change patterns of extreme cyclones numbers (frequency of events "2000-2015 minus 1979-1994") and with the trend patterns. This indicates that the changes in extreme cyclone occurrence in early winter are associated with sea-ice changes (regional feedback). In contrast, different mechanisms via large-scale circulation changes/teleconnections seem to play a role in late winter.
Meteorological effects on the daily activity patterns of tabanid biting flies in northern Queensland, Australia.

PubMed

Van Hennekeler, K; Jones, R E; Skerratt, L F; Muzari, M O; Fitzpatrick, L A

2011-03-01

Information on the daily activity patterns of tabanid flies is important in the development of strategies that decrease the risk of pathogens transmitted by them. In addition, this information is useful to maximize numbers of tabanids trapped during short-term studies and to target feeding behavior studies of certain tabanid species to their times of peak activity. The current study examined the effects of various meteorological factors on the daily activity patterns of common tropical species of tabanids in north Queensland. Each species studied responded differently to weather factors. Tabanus townsvilli Ricardo (Diptera: Tabanidae) was most active during late morning and early afternoon, whereas Pseudotabanus silvester (Bergroth) and Tabanus pallipennis Macquart were most active in the late afternoon. Tabanus dorsobimaculatus Macquart was most active in the morning and early afternoon. Data on daily activity patterns of tabanid flies indicates that in an area such as Townsville, North Queensland, where several species of tabanid are present concurrently in high numbers, the overlapping periods of high activity for these species indicate a high risk of pathogen transmission for most of the day (10.00-19.00 hours). Similarly, because each species responds differently to weather variables, only extreme weather conditions are likely to inhibit activity of all species. These data also indicate that for maximal results, trapping and feeding behavior studies should be tailored to the preferred activity period of the species under investigation. © 2010 The Authors. Medical and Veterinary Entomology © 2010 The Royal Entomological Society.
Computational data sciences for assessment and prediction of climate extremes

NASA Astrophysics Data System (ADS)

Ganguly, A. R.

2011-12-01

Climate extremes may be defined inclusively as severe weather events or large shifts in global or regional weather patterns which may be caused or exacerbated by natural climate variability or climate change. This area of research arguably represents one of the largest knowledge-gaps in climate science which is relevant for informing resource managers and policy makers. While physics-based climate models are essential in view of non-stationary and nonlinear dynamical processes, their current pace of uncertainty reduction may not be adequate for urgent stakeholder needs. The structure of the models may in some cases preclude reduction of uncertainty for critical processes at scales or for the extremes of interest. On the other hand, methods based on complex networks, extreme value statistics, machine learning, and space-time data mining, have demonstrated significant promise to improve scientific understanding and generate enhanced predictions. When combined with conceptual process understanding at multiple spatiotemporal scales and designed to handle massive data, interdisciplinary data science methods and algorithms may complement or supplement physics-based models. Specific examples from the prior literature and our ongoing work suggests how data-guided improvements may be possible, for example, in the context of ocean meteorology, climate oscillators, teleconnections, and atmospheric process understanding, which in turn can improve projections of regional climate, precipitation extremes and tropical cyclones in an useful and interpretable fashion. A community-wide effort is motivated to develop and adapt computational data science tools for translating climate model simulations to information relevant for adaptation and policy, as well as for improving our scientific understanding of climate extremes from both observed and model-simulated data.
Climate change, extreme events and increased risk of salmonellosis in Maryland, USA: Evidence for coastal vulnerability.

PubMed

Jiang, Chengsheng; Shaw, Kristi S; Upperman, Crystal R; Blythe, David; Mitchell, Clifford; Murtugudde, Raghu; Sapkota, Amy R; Sapkota, Amir

2015-10-01

Salmonella is a leading cause of acute gastroenteritis worldwide. Patterns of salmonellosis have been linked to weather events. However, there is a dearth of data regarding the association between extreme events and risk of salmonellosis, and how this risk may disproportionately impact coastal communities. We obtained Salmonella case data from the Maryland Foodborne Diseases Active Surveillance Network (2002-2012), and weather data from the National Climatic Data Center (1960-2012). We developed exposure metrics related to extreme temperature and precipitation events using a 30 year baseline (1960-1989) and linked them with county-level salmonellosis data. Data were analyzed using negative binomial Generalized Estimating Equations. We observed a 4.1% increase in salmonellosis risk associated with a 1 unit increase in extreme temperature events (incidence rate ratio (IRR):1.041; 95% confidence interval (CI):1.013-1.069). This increase in risk was more pronounced in coastal versus non-coastal areas (5.1% vs 1.5%). Likewise, we observed a 5.6% increase in salmonellosis risk (IRR:1.056; CI:1.035-1.078) associated with a 1 unit increase in extreme precipitation events, with the impact disproportionately felt in coastal areas (7.1% vs 3.6%). To our knowledge, this is the first empirical evidence showing that extreme temperature/precipitation events-that are expected to be more frequent and intense in coming decades-are disproportionately impacting coastal communities with regard to salmonellosis. Adaptation strategies need to account for this differential burden, particularly in light of ever increasing coastal populations. Copyright © 2015. Published by Elsevier Ltd.
Assessing changes in extreme convective precipitation from a damage perspective

NASA Astrophysics Data System (ADS)

Schroeer, K.; Tye, M. R.

2016-12-01

Projected increases in high-intensity short-duration convective precipitation are expected even in regions that are likely to become more arid. Such high intensity precipitation events can trigger hazardous flash floods, debris flows and landslides that put people and local assets at risk. However, the assessment of local scale precipitation extremes is hampered by its high spatial and temporal variability. In addition to which, not only are extreme events rare, but such small scale events are likely to be underreported where they don't coincide with the observation network. Rather than focus solely on the convective precipitation, understanding the characteristics of these extremes which drive damage may be more effective to assess future risks. Two sources of data are used in this study. First, sub-daily precipitation observations over the Southern Alps enable an examination of seasonal and regional patterns in high-intensity convective precipitation and their relationship with weather types. Secondly, reports of private loss and damage on a household scale are used to identify which events are most damaging, or what conditions potentially enhance the vulnerability to these extremes.This study explores the potential added value from including recorded loss and damage data to understand the risks from summertime convective precipitation events. By relating precipitation generating weather types to the severity of damage we hope to develop a mechanism to assess future risks. A further benefit would be to identify from damage reports the likely occurrence of precipitation extremes where no direct observations are available and use this information to validate remotely sensed observations.

Climate change and health in Israel: adaptation policies for extreme weather events

PubMed Central

2013-01-01

Climatic changes have increased the world-wide frequency of extreme weather events such as heat waves, cold spells, floods, storms and droughts. These extreme events potentially affect the health status of millions of people, increasing disease and death. Since mitigation of climate change is a long and complex process, emphasis has recently been placed on the measures required for adaptation. Although the principles underlying these measures are universal, preparedness plans and policies need to be tailored to local conditions. In this paper, we conducted a review of the literature on the possible health consequences of extreme weather events in Israel, where the conditions are characteristic of the Mediterranean region. Strong evidence indicates that the frequency and duration of several types of extreme weather events are increasing in the Mediterranean Basin, including Israel. We examined the public health policy implications for adaptation to climate change in the region, and proposed public health adaptation policy options. Preparedness for the public health impact of increased extreme weather events is still relatively limited and clear public health policies are urgently needed. These include improved early warning and monitoring systems, preparedness of the health system, educational programs and the living environment. Regional collaboration should be a priority. PMID:23805950
Public Perception of Extreme Cold Weather-Related Health Risk in a Cold Area of Northeast China.

PubMed

Ban, Jie; Lan, Li; Yang, Chao; Wang, Jian; Chen, Chen; Huang, Ganlin; Li, Tiantian

2017-08-01

A need exists for public health strategies regarding extreme weather disasters, which in recent years have become more frequent. This study aimed to understand the public's perception of extreme cold and its related health risks, which may provide detailed information for public health preparedness during an extreme cold weather event. To evaluate public perceptions of cold-related health risk and to identify vulnerable groups, we collected responses from 891 participants in a face-to-face survey in Harbin, China. Public perception was measured by calculating the score for each perception question. Locals perceived that extreme cold weather and related health risks were serious, but thought they could not avoid these risks. The significant difference in perceived acceptance level between age groups suggested that the elderly are a "high health risk, low risk perception" group, meaning that they are relatively more vulnerable owing to their high susceptibility and low awareness of the health risks associated with extreme cold weather. The elderly should be a priority in risk communication and health protective interventions. This study demonstrated that introducing risk perception into the public health field can identify vulnerable groups with greater needs, which may improve the decision-making of public health intervention strategies. (Disaster Med Public Health Preparedness. 2017;11:417-421).
Spatial Analysis of Post-Hurricane Katrina Thermal Pattern and Intensity in Greater New Orleans: Implications for Urban Heat Island Phenomenon

NASA Astrophysics Data System (ADS)

Lief, Aram Parrish

In 2005, Hurricane Katrina's diverse impacts on the Greater New Orleans area included damaged and destroyed trees, and other despoiled vegetation, which also increased the exposure of artificial and bare surfaces, known factors that contribute to the climatic phenomenon known as the urban heat island (UHI). This is an investigation of UHI in the aftermath of Hurricane Katrina, which entails the analysis of pre and post-hurricane Katrina thermal imagery of the study area, including changes to surface heat patterns and vegetative cover. Imagery from Landsat TM was used to show changes to the pattern and intensity of the UHI effect, caused by an extreme weather event. Using remote sensing visualization methods, in situ data, and local knowledge, the author found there was a measurable change in the pattern and intensity of the New Orleans UHI effect, as well as concomitant changes to vegetative land cover. This finding may be relevant for urban planners and citizens, especially in the context of recovery from a large-scale disaster of a coastal city, regarding future weather events, and other natural and human impacts.
Extreme flood estimation by the SCHADEX method in a snow-driven catchment: application to Atnasjø (Norway)

NASA Astrophysics Data System (ADS)

Paquet, Emmanuel; Lawrence, Deborah

2013-04-01

The SCHADEX method for extreme flood estimation was developed by Paquet et al. (2006, 2013), and since 2008, it is the reference method used by Electricité de France (EDF) for dam spillway design. SCHADEX is a so-called "semi-continuous" stochastic simulation method in that flood events are simulated on an event basis and are superimposed on a continuous simulation of the catchment saturation hazard usingrainfall-runoff modelling. The MORDOR hydrological model (Garçon, 1999) has thus far been used for the rainfall-runoff modelling. MORDOR is a conceptual, lumped, reservoir model with daily areal rainfall and air temperature as the driving input data. The principal hydrological processes represented are evapotranspiration, direct and indirect runoff, ground water, snow accumulation and melt, and routing. The model has been intensively used at EDF for more than 15 years, in particular for inflow forecasts for French mountainous catchments. SCHADEX has now also been applied to the Atnasjø catchment (463 km²), a well-documented inland catchment in south-central Norway, dominated by snowmelt flooding during spring/early summer. To support this application, a weather pattern classification based on extreme rainfall was first established for Norway (Fleig, 2012). This classification scheme was then used to build a Multi-Exponential Weather Pattern distribution (MEWP), as introduced by Garavaglia et al. (2010) for extreme rainfall estimation. The MORDOR model was then calibrated relative to daily discharge data for Atnasjø. Finally, a SCHADEX simulation was run to build a daily discharge distribution with a sufficient number of simulations for assessing the extreme quantiles. Detailed results are used to illustrate how SCHADEX handles the complex and interacting hydrological processes driving flood generation in this snow driven catchment. Seasonal and monthly distributions, as well as statistics for several thousand simulated events reaching a 1000 years return level value and assessment of snowmelt role in extreme floods are presented. This study illustrates the complexity of the extreme flood estimation in snow driven catchments, and the need for a good representation of snow accumulation and melting processes in simulations for design flood estimations. In particular, the SCHADEX method is able to represent a range of possible catchment conditions (representing both soil moisture and snowmelt) in which extreme flood events can occur. This study is part of a collaboration between NVE and EDF, initiated within the FloodFreq COST Action (http://www.cost-floodfreq.eu/). References: Fleig, A., Scientific Report of the Short Term Scientific Mission Anne Fleig visiting Électricité de France, FloodFreq COST action - STSM report, 2012 Garavaglia, F., Gailhard, J., Paquet, E., Lang, M., Garçon, R., and Bernardara, P., Introducing a rainfall compound distribution model based on weather patterns sub-sampling, Hydrol. Earth Syst. Sci., 14, 951-964, doi:10.5194/hess-14-951-2010, 2010 Garçon, R. Modèle global pluie-débit pour la prévision et la prédétermination des crues, La Houille Blanche, 7-8, 88-95. doi: 10.1051/lhb/1999088 Paquet, E., Gailhard, J. and Garçon, R. (2006), Evolution of the GRADEX method: improvement by atmospheric circulation classification and hydrological modeling, La Houille Blanche, 5, 80-90. doi: 10.1051/lhb/2006091 Paquet, E., Garavaglia, F., Garçon, R. and Gailhard, J. (2012), The SCHADEX method: a semi-continuous rainfall-runoff simulation for extreme food estimation, Journal of Hydrology, under revision
Extreme cyclone events in the Arctic: Wintertime variability and trends

NASA Astrophysics Data System (ADS)

Rinke, A.; Maturilli, M.; Graham, R. M.; Matthes, H.; Handorf, D.; Cohen, L.; Hudson, S. R.; Moore, J. C.

2017-12-01

Extreme cyclone events often occur during Arctic winters, and are of concern as they transport heat and moisture into the Arctic, which is associated with mixed-phase clouds and increased longwave downward radiation, and can cause temperatures to rise above freezing resulting in wintertime sea-ice melting or retarded sea-ice growth. With Arctic amplification and associated reduced sea-ice cover and warmer sea surface temperatures, the occurrence of extreme cyclones events could be a plausible scenario. We calculate the spatial patterns, and changes and trends of the number of extreme cyclone events in the Arctic based on ERA-Interim six-hourly sea level pressure (SLP) data for winter (November-February) 1979-2015. Further, we analyze the SLP data from the Ny-Ålesund station for the same 37 year period. We define an extreme cyclone event by an extreme low central pressure (SLP below 985 hPa, which is the 5th percentile of the Ny-Ålesund/N-ICE2015 SLP data). Typically 20-40 extreme cyclone events (sometimes called `weather bombs') occur in the Arctic North Atlantic per winter season, with an increasing trend of 6 events/decade, according to the Ny-Ålesund data. This increased frequency of extreme cyclones drive considerable warming in that region, consistent with the observed significant winter warming of 3 K/decade. The positive winter trend in extreme cyclones is dominated by a positive monthly trend of about 3-4 events/decade in November-December, due mainly to an increasing persistence of extreme cyclone events. A negative trend in January opposes this, while there is no significant trend in February. We relate the regional patterns of the trend in extreme cyclones to anomalously low sea-ice conditions in recent years, together with associated large-scale atmospheric circulation changes such as "blocking-like" circulation patterns (e.g. Scandinavian blocking in December and Ural blocking during January-February).
Exceptional sequence of severe thunderstorms and related flash floods in May and June 2016 in Germany - Part 1: Meteorological background

NASA Astrophysics Data System (ADS)

Piper, David; Kunz, Michael; Ehmele, Florian; Mohr, Susanna; Mühr, Bernhard; Kron, Andreas; Daniell, James

2016-12-01

During a 15-day episode from 26 May to 9 June 2016, Germany was affected by an exceptionally large number of severe thunderstorms. Heavy rainfall, related flash floods and creek flooding, hail, and tornadoes caused substantial losses running into billions of euros (EUR). This paper analyzes the key features of the severe thunderstorm episode using extreme value statistics, an aggregated precipitation severity index, and two different objective weather-type classification schemes. It is shown that the thunderstorm episode was caused by the interaction of high moisture content, low thermal stability, weak wind speed, and large-scale lifting by surface lows, persisting over almost 2 weeks due to atmospheric blocking.For the long-term assessment of the recent thunderstorm episode, we draw comparisons to a 55-year period (1960-2014) regarding clusters of convective days with variable length (2-15 days) based on precipitation severity, convection-favoring weather patterns, and compound events with low stability and weak flow. It is found that clusters with more than 8 consecutive convective days are very rare. For example, a 10-day cluster with convective weather patterns prevailing during the recent thunderstorm episode has a probability of less than 1 %.
Impact of the 1997-1998 El-Nino of Regional Hydrology

NASA Technical Reports Server (NTRS)

Lakshmi, Venkataraman; Susskind, Joel

1998-01-01

The 1997-1998 El-Nino brought with it a range of severe local-regional hydrological phenomena. Record high temperatures and extremely dry soil conditions in Texas is an example of this regional effect. The El-Nino and La-Nina change the continental weather patterns considerably. However, connections between continental weather anomalies and regional or local anomalies have not been established to a high degree of confidence. There are several unique features of the recent El-Nino and La-Nina. Due to the recognition of the present El-Nino well in advance, there have been several coupled model studies on global and regional scales. Secondly, there is a near real-time monitoring of the situation using data from satellite sensors, namely, SeaWIFS, TOVS, AVHRR and GOES. Both observations and modeling characterize the large scale features of this El-Nino fairly well. However the connection to the local and regional hydrological phenomenon still needs to be made. This paper will use satellite observations and analysis data to establish a relation between local hydrology and large scale weather patterns. This will be the first step in using satellite data to perform regional hydrological simulations of surface temperature and soil moisture.
Physiological Evaluation of A1 (Extreme-Cold-Weather) and A2 (Buoyant, Intermediate-Cold-Weather) Jackets.

DTIC Science & Technology

1983-08-01

the resting metabolic heat will be dissipated through the clothing with the remaining 25% lost through the respiratory tract and insensible sweating...AD-A258 410 PHYSIOLOGICAL EVALUATION OF Al (EXTREME-COLD-WEATHER) AND A2 (BUOYANT, INTERMEDIATE-COLD-WEATHER) JACKETS NAVY CLOTHING AND TEXTILE...Navy Clothing and Textile Research Facility 523-003-30-06 21 Strathmore Road 523-003-30-08 Natick, MA 01760 11. CONTROLLING OFFICE NAME AND ADDRESS
NOAA Environmental Satellite Measurements of Extreme Space Weather Events

NASA Astrophysics Data System (ADS)

Denig, W. F.; Wilkinson, D. C.; Redmon, R. J.

2015-12-01

For over 40 years the National Oceanic and Atmospheric Administration (NOAA) has continuously monitored the near-earth space environment in support of space weather operations. Data from this period have covered a wide range of geophysical conditions including periods of extreme space weather such as the great geomagnetic March 1989, the 2003 Halloween storm and the more recent St Patrick's Day storm of 2015. While not specifically addressed here, these storms have stressed our technology infrastructure in unexpected and surprising ways. Space weather data from NOAA geostationary (GOES) and polar (POES) satellites along with supporting data from the Air Force are presented to compare and contrast the space environmental conditions measured during extreme events.
Fast-track extreme event attribution: How fast can we disentangle thermodynamic (forced) and dynamic (internal) contributions?

NASA Astrophysics Data System (ADS)

Haustein, Karsten; Otto, Friederike; Uhe, Peter; Allen, Myles; Cullen, Heidi

2016-04-01

Within the last decade, extreme weather event attribution has emerged as a new field of science and garnered increasing attention from the wider scientific community and the public. Numerous methods have been put forward to determine the contribution of anthropogenic climate change to individual extreme weather events. So far nearly all such analyses were done months after an event has happened. First, we present our newly established method which can assess the fraction of attributable risk (FAR) of a severe weather event due to an external driver in real-time. The method builds on a large ensemble of atmosphere-only GCM/RCM simulations forced by seasonal forecast sea surface temperatures (SSTs). Taking the UK 2013/14 winter floods as an example, we demonstrate that the change in risk for heavy rainfall during the England floods due to anthropogenic climate change is of similar magnitude using either observed or seasonal forecast SSTs. While FAR is assumed to be independent from event-specific dynamic contributions due to anomalous circulation patterns as a first approximation, the risk of an event to occur under current conditions is clearly a function of the state of the atmosphere. The shorter the event, the more it is a result of chaotic internal weather variability. Hence we are interested to (1) attribute the event to thermodynamic and dynamic causes and to (2) establish a sensible time-scale for which we can make a useful and potentially robust attribution statement with regard to event-specific dynamics. Having tested the dynamic response of our model to SST conditions in January 2014, we find that observed SSTs are required to establish a discernible link between anomalous ocean temperatures and the atmospheric circulation over the North Atlantic in general and the UK in particular. However, for extreme events occurring under strongly anomalous SST patterns, associated with known low-frequency climate modes such as El Nino or La Nina, forecast SSTs can provide sufficient guidance to determine the dynamic contribution to the event on the basis of monthly mean values. No such link can be made (North Atlantic/Western Europe region) for shorter time-scales, unless the observed state of the circulation is taken as reference for the model analysis (e.g. Christidis et al. 2014). We present results from our most recent attribution analysis for the December 2015 UK floods (Storm Desmond and Eva), during which we find a robust teleconnection link between Pacific SSTs and North Atlantic Jetstream anomalies. This is true for both experiments, with forecast and observed SSTs. We propose a fast and simple analysis method based on the comparison of current climatological circulation patterns with actual and natural conditions. Alternative methods are discussed and analysed regarding their potential for fast-track attribution of the role of dynamics. Also, we briefly revisit the issue of internal vs forced dynamic contributions.
Extreme Space Weather Events: From Cradle to Grave

NASA Astrophysics Data System (ADS)

Riley, Pete; Baker, Dan; Liu, Ying D.; Verronen, Pekka; Singer, Howard; Güdel, Manuel

2018-02-01

Extreme space weather events, while rare, can have a substantial impact on our technologically-dependent society. And, although such events have only occasionally been observed, through careful analysis of a wealth of space-based and ground-based observations, historical records, and extrapolations from more moderate events, we have developed a basic picture of the components required to produce them. Several key issues, however, remain unresolved. For example, what limits are imposed on the maximum size of such events? What are the likely societal consequences of a so-called "100-year" solar storm? In this review, we summarize our current scientific understanding about extreme space weather events as we follow several examples from the Sun, through the solar corona and inner heliosphere, across the magnetospheric boundary, into the ionosphere and atmosphere, into the Earth's lithosphere, and, finally, its impact on man-made structures and activities, such as spacecraft, GPS signals, radio communication, and the electric power grid. We describe preliminary attempts to provide probabilistic forecasts of extreme space weather phenomena, and we conclude by identifying several key areas that must be addressed if we are better able to understand, and, ultimately, predict extreme space weather events.
Spatial variation in extreme winds predicts large wildfire locations in chaparral ecosystems

NASA Astrophysics Data System (ADS)

Moritz, Max A.; Moody, Tadashi J.; Krawchuk, Meg A.; Hughes, Mimi; Hall, Alex

2010-02-01

Fire plays a crucial role in many ecosystems, and a better understanding of different controls on fire activity is needed. Here we analyze spatial variation in fire danger during episodic wind events in coastal southern California, a densely populated Mediterranean-climate region. By reconstructing almost a decade of fire weather patterns through detailed simulations of Santa Ana winds, we produced the first high-resolution map of where these hot, dry winds are consistently most severe and which areas are relatively sheltered. We also analyzed over half a century of mapped fire history in chaparral ecosystems of the region, finding that our models successfully predict where the largest wildfires are most likely to occur. There is a surprising lack of information about extreme wind patterns worldwide, and more quantitative analyses of their spatial variation will be important for effective fire management and sustainable long-term urban development on fire-prone landscapes.
The use of ERTS-1 satellite data in Great Lakes mesometeorological studies

NASA Technical Reports Server (NTRS)

Lyons, W. A. (Principal Investigator)

1972-01-01

The author has identified the following significant results. In the original proposal, it was hoped that ERTS could, with its extremely high resolution and multispectral capability, detect many meteorological phenomena occurring at the low end of the mesoscale motion spectrum (1 - 100 km). This included convective cloud phenomena, internal wave patterns, air pollution, snow squalls, etc. For meteorologists, ERTS-1 has more than lived up to initial hopes. First-look inspection of images has produced a large number of truly remarkable finds. Some of the most significant are: (1) Images of Lake Ontario during late summer have revealed several extremely good examples of lake breeze frontal cloud patterns. (2) Detection of suspended particulates from Chicago-Gary industrial complex in the 50,000 to 150,000 tons/year category. (3) Inadvertant weather modification due to anthropogenic condensation and ice nuclei from urban areas.
A new precipitation and drought climatology based on weather patterns.

PubMed

Richardson, Douglas; Fowler, Hayley J; Kilsby, Christopher G; Neal, Robert

2018-02-01

Weather-pattern, or weather-type, classifications are a valuable tool in many applications as they characterize the broad-scale atmospheric circulation over a given region. This study analyses the aspects of regional UK precipitation and meteorological drought climatology with respect to a new set of objectively defined weather patterns. These new patterns are currently being used by the Met Office in several probabilistic forecasting applications driven by ensemble forecasting systems. Weather pattern definitions and daily occurrences are mapped to Lamb weather types (LWTs), and parallels between the two classifications are drawn. Daily precipitation distributions are associated with each weather pattern and LWT. Standardized precipitation index (SPI) and drought severity index (DSI) series are calculated for a range of aggregation periods and seasons. Monthly weather-pattern frequency anomalies are calculated for SPI wet and dry periods and for the 5% most intense DSI-based drought months. The new weather-pattern definitions and daily occurrences largely agree with their respective LWTs, allowing comparison between the two classifications. There is also broad agreement between weather pattern and LWT changes in frequencies. The new data set is shown to be adequate for precipitation-based analyses in the UK, although a smaller set of clustered weather patterns is not. Furthermore, intra-pattern precipitation variability is lower in the new classification compared to the LWTs, which is an advantage in this context. Six of the new weather patterns are associated with drought over the entire UK, with several other patterns linked to regional drought. It is demonstrated that the new data set of weather patterns offers a new opportunity for classification-based analyses in the UK.
When Siberia came to the Netherlands: The response of continental black-tailed godwits to a rare spring weather event

USGS Publications Warehouse

Senner, Nathan R.; Verhoeven, Mo A.; Abad-Gómez, José M.; Gutiérrez, Jorge S.; Hooijmeijer, Jos C. E. W.; Kentie, Rosemarie; Masero, José A.; Tibbitts, T. Lee; Piersma, Theunis

2015-01-01

This suggests that populations with continued access to food, behavioural flexibility and time to dissipate the costs of the event can likely withstand the consequences of an extreme weather event. For populations constrained in one of these respects, though, extreme events may entail extreme ecological consequences.
Transportation system resilience, extreme weather and climate change : a thought leadership series

DOT National Transportation Integrated Search

2014-09-01

This report summarizes key findings from the Transportation System Resilience, Extreme Weather and Climate Change thought leadership series held at Volpe, the National Transportation Systems Center from fall 2013 to spring 2014.
75 FR 8044 - Summer Undergraduate Research Program Extension of Due Date for Proposals

Federal Register 2010, 2011, 2012, 2013, 2014

2010-02-23

...: Due to extreme weather conditions in the Mid-Atlantic United States, NIST is extending the deadline.... Eastern Time, Tuesday, February 16, 2010. Due to extreme weather conditions and associated power outages...
Local finite-amplitude wave activity as an objective diagnostic of midlatitude extreme weather

DOE Office of Scientific and Technical Information (OSTI.GOV)

Chen, Gang; Lu, Jian; Burrows, Alex D.

Midlatitude extreme weather events are responsible for a large part of climate related damage, yet our understanding of these extreme events is limited, partly due to the lack of a theoretical basis for midlatitude extreme weather. In this letter, the local finite-amplitude wave activity (LWA) of Huang and Nakamura [2015] is introduced as a diagnostic of the 500-hPa geopotential height (Z500) to characterizing midlatitude weather events. It is found that the LWA climatology and its variability associated with the Arctic Oscillation (AO) agree broadly with the previously reported blocking frequency in literature. There is a strong seasonal and spatial dependencemore » in the trend13 s of LWA in recent decades. While there is no observational evidence for a hemispheric-scale increase in wave amplitude, robust trends in wave activity can be identified at the regional scales, with important implications for regional climate change.« less
A new precipitation and meteorological drought climatology based on weather patterns

NASA Astrophysics Data System (ADS)

Richardson, D.; Fowler, H. J.; Kilsby, C. G.; Neal, R.

2017-12-01

Weather-pattern, or weather-type, classifications are a valuable tool in many applications as they characterise the broad-scale atmospheric circulation over a given region. An analysis of regional UK precipitation and meteorological drought climatology with respect to a set of objectively defined weather patterns is presented. This classification system, introduced last year, is currently being used by the Met Office in several probabilistic forecasting applications driven by ensemble forecasting systems. The classification consists of 30 daily patterns derived from North Atlantic Ocean and European mean sea level pressure data. Clustering these 30 patterns yields another set of eight patterns that are intended for use in longer-range applications. Weather pattern definitions and daily occurrences are mapped to the commonly-used Lamb Weather Types (LWTs), and parallels between the two classifications are drawn. Daily precipitation distributions are associated with each weather pattern and LWT. Drought index series are calculated for a range of aggregation periods and seasons. Monthly weather-pattern frequency anomalies are calculated for different drought index thresholds, representing dry, wet and drought conditions. The set of 30 weather patterns is shown to be adequate for precipitation-based analyses in the UK, although the smaller set of clustered patterns is not. Furthermore, intra-pattern precipitation variability is lower in the new classification compared to the LWTs, which is an advantage in the context of precipitation studies. Weather patterns associated with drought over the different UK regions are identified. This has potential forecasting application - if a model (e.g. a global seasonal forecast model) can predict weather pattern occurrences then regional drought outlooks may be derived from the forecasted weather patterns.
Non-stationarity of extreme weather events in a changing climate - an application to long-term droughts in the US Southwest

NASA Astrophysics Data System (ADS)

Grossmann, I.

2013-12-01

Return periods of many extreme weather events are not stationary over time, given increasing risks due to global warming and multidecadal variability resulting from large scale climate patterns. This is problematic as extreme weather events and long-term climate risks such as droughts are typically conceptualized via measures such as return periods that implicitly assume non-stationarity. I briefly review these problems and present an application to the non-stationarity of droughts in the US Southwest. The US Southwest relies on annual precipitation maxima during winter and the North American Monsoon (NAM), both of which vary with large-scale climate patterns, in particular ENSO, the Pacific Decadal Oscillation (PDO) and the Atlantic Multidecadal Oscillation (AMO). The latter two exhibit variability on longer (multi-decadal) time scales in addition to short-term variations. The region is also part of the subtropical belt projected to become more arid in a warming climate. The possible multidecadal impacts of the PDO on precipitation in the study region are analyzed with a focus on Arizona and New Mexico, using GPCC and CRU data since 1900. The projected impacts of the PDO on annual precipitation during the next three decades with GPCC data are similar in scale to the impacts of global warming on precipitation according to the A1B scenario and the CMIP2 multi-model means, while the combined impact of the PDO and AMO is about 19% larger. The effects according to the CRU dataset are about half as large as the projected global warming impacts. Given the magnitude of the projected impacts from both multidecadal variability and global warming, water management needs to explicitly incorporate both of these trends into long-term planning. Multi-decadal variability could be incorporated into the concept of return periods by presenting return periods as time-varying or as conditional on the respective 'phase' of relevant multidecadal patterns and on global warming. Problems in detecting the PDO signal and potential solutions are also discussed. We find that the long-term effect of the PDO can be more clearly separated from short-term variability by considering return periods of multi-year drought measures rather than return periods of simple drought measures that are more affected by short-term variations.

Observations and simulations of the interactions between clouds, radiation, and precipitation

NASA Astrophysics Data System (ADS)

Naegele, Alexandra Claire

Increasing precipitation and warming temperatures associated with climate change have been documented across the globe, including in the Northeast US. These climate changes threaten human health in many ways. Research is necessary to understand and explain the relationship between climate change and human health. Extreme weather events such as extreme temperatures, convective storms, floods, lightning events, wintry precipitation, and low visibility, are frequently associated with adverse effects on human health. While more media attention is typically given to events that cause the most structural or economic damage (e.g., tornadoes, hurricanes, earthquakes, etc.), extreme temperatures ultimately account for the greatest loss of life in the US. Extreme weather events can be unpredictable; however, improved knowledge and technology allow meteorologists to accurately forecast many of these events, specifically extreme temperature and precipitation events. Advancing our knowledge of climate variability and trends in extreme weather can inform: public education programs to alert the community of the dangers of extreme heat or cold, emergency response plans to hazardous weather conditions, and current thresholds for emergency alerts. This study evaluates trends in extreme weather events across New Hampshire and links these extreme events to adverse health outcomes. Using data from NCEI Global Historical Climatological Network (GHCN) - Daily dataset (1981 - 2015), five daily xiii Extreme Weather Metrics (EWMs) were defined: Daily Maximum Temperature ≤32°F, Daily Maximum Temperature ≥90°F, Daily Maximum Temperature ≥95°F, Daily Precipitation ≥1", and Daily Precipitation ≥2". Relevant human health outcomes were extracted from the New Hampshire Hospital Discharge Dataset for the years 2001-2009. Health cases were defined based on the International Classification of Disease 9th Revision (ICD-9). Outcomes in this analysis include: All-Cause Injury, Vehicle Accidents, Accidental Falls, Accidents Due to Natural and Environmental (including excessive heat, excessive cold, exposure due to weather conditions, lightning, and storms and floods), Accidental Drowning, and Carbon Monoxide Poisoning. Temporal and spatial trends were assessed, and the associations between all health outcomes and EWMs, daily maximum temperature, and daily precipitation were evaluated via Spearman correlations. Once the four strongest correlations were determined, a quasi-Poisson regression model was used to evaluate the relationship between each exposureoutcome pair. These pairs were modeled to show the relation between maximum temperature and all-cause hospital visits, hospital visits related to vehicle accidents, hospital visits related to accidental falls, and hospital visits related to heat. Future work will incorporate these findings into public health planning and programming. This project is a collaboration with New Hampshire Department of Health and Human Services (NH DHHS) who have a shared interest in understanding the impact of extreme weather events on the citizens of New Hampshire. Furthermore, this work supports an ongoing effort to implement the Centers for Disease Control (CDC) Building Resilience Against Climate Effects (BRACE) Framework, which focuses on identifying climate and weather-related hazards and estimating the associated disease burden.
The C20C+ Detection and Attribution Project

NASA Astrophysics Data System (ADS)

Stone, D. A.; Angélil, O. M.; Cholia, S.; Christidis, N.; Dittus, A. J.; Folland, C. K.; King, A.; Kinter, J. L.; Krishnan, H.; Min, S. K.; Shiogama, H.; Wehner, M. F.; Wolski, P.

2015-12-01

Over the past decade there has been a remarkable growth in interest concerning the effects of anthropogenic emissions on extreme weather. However, research has been constrained by the lack of a public climate-model-based data product optimised for investigation of extreme weather in the context of climate change, relying instead on products designed for other purposes or on bespoke simulations designed for the particular study and not generally applicable to other extremes. The international Climate of the 20th Century Plus (C20C+) Detection and Attribution Project is filling this gap by producing the first large ensemble, multi-model, multi-year, and multi-scenario historical climate data product, specifically designed for resolving variations in the occurrence and characteristics of extreme weather from year to year and their differences from what might have been in the absence of anthropogenic emissions. Updates on project status and tens of terabytes of simulation output are available at http://portal.nersc.gov/c20c.Here we describe the experimental design of the first phase of the project, conducted with six atmospheric climate models, and discuss its various strengths and weaknesses with respect to various types of extreme weather. We also present analyses of the relative importance of climate model, estimate of anthropogenic ocean warming, spatial and temporal scale, and aspects of experimental design on estimates of how much emissions have affected extreme weather.
Estimating the effects of extreme weather on transportation infrastructure.

DOT National Transportation Integrated Search

2016-12-01

Climate change, already taking place, is expected to become more pronounced in the future. Current damage assessment models for extreme weather events, such as FEMAs Hazus, do not take the full impact to transportation systems into consideration. ...
Trends in Cold Extremes and Winter Weather for the SPTC Region

DOT National Transportation Integrated Search

2017-05-31

Extreme weather poses multifaceted hazards to transportation. There is now increased awareness of the threats of climate variability and change on transportation safety and state of good repair. In particular, a non-stationary climate will potentiall...
Increasing weather-related impacts on European population under climate and demographic change

NASA Astrophysics Data System (ADS)

Forzieri, Giovanni; Cescatti, Alessandro; Batista e Silva, Filipe; Kovats, Sari R.; Feyen, Luc

2017-04-01

Over the last three decades the overwhelming majority of disasters have been caused by weather-related events. The observed rise in weather-related disaster losses has been largely attributed to increased exposure and to a lesser degree to global warming. Recent studies suggest an intensification in the climatology of multiple weather extremes in Europe over the coming decades in view of climate change, while urbanization continues. In view of these pressures, understanding and quantifying the potential impacts of extreme weather events on future societies is imperative in order to identify where and to what extent their livelihoods will be at risk in the future, and develop timely and effective adaptation and disaster risk reduction strategies. Here we show a comprehensive assessment of single- and multi-hazard impacts on the European population until the year 2100. For this purpose, we developed a novel methodology that quantifies the human impacts as a multiplicative function of hazard, exposure and population vulnerability. We focus on seven of the most impacting weather-related hazards - including heat and cold waves, wildfires, droughts, river and coastal floods and windstorms - and evaluated their spatial and temporal variations in intensity and frequency under a business-as-usual climate scenario. Long-term demographic dynamics were modelled to assess exposure developments under a corresponding middle-of-the-road scenario. Vulnerability of humans to weather extremes was appraised based on more than 2300 records of weather-related disasters. The integration of these elements provides a range of plausible estimates of extreme weather-related risks for future European generations. Expected impacts on population are quantified in terms of fatalities and number of people exposed. We find a staggering rise in fatalities from extreme weather events, with the projected death toll by the end of the century amounting to more than 50 times the present number of people killed. Approximately two-thirds of European citizens could then be exposed to a weather-related disaster each year, which will bring about huge rises in health costs to society. Future impacts show a prominent spatial gradient towards southern regions, where weather extremes could become the greatest environmental risk factor for people. The projected changes are dominated by global warming, mainly through a rise in heatwaves, but ongoing urbanization, development in hazard-prone areas and ageing population will likely further increase human risk. The results call for immediate action to achieve the Paris goals on climate mitigation and adaptation in order to protect future European generations.
P2 Guide for Making a Visible Difference in Communities During Extreme Weather Events

EPA Pesticide Factsheets

Developing procedures for minimizing hazardous materials releases during extreme weather events can reduce or even eliminate risks to human life and property and should be an integral part of a community’s emergency management planning.
National survey of US public transit agency experience with and response to extreme weather events.

DOT National Transportation Integrated Search

2016-09-01

Extreme weather events pose serious challenges public transit systems. They disrupt transit operations, impair service quality, increase threats to public safety, and damage infrastructure. This report presents findings from a June 2016 national surv...
How vulnerable is Texas’ freight infrastructure to extreme weather events? Final report.

DOT National Transportation Integrated Search

2017-03-01

The Texas Freight Mobility Plan forecasts significant increases in freight volumes across all transportation modes over the next three decades. An increased frequency of extreme weather events such as prolonged droughts and flash flooding is also exp...
How do blockings relate to heavy precipitation events in Europe?

NASA Astrophysics Data System (ADS)

Lenggenhager, Sina; Romppainen, Olivia; Brönnimann, Stefan; Croci-Maspoli, Mischa

2017-04-01

Atmospheric blockings are quasi-stationary high pressure systems that persist for several days. Due to their longevity, blockings can be key features for extreme weather events. While several studies have shown their relevant role for temperatures extremes, the link between blockings and extreme precipitation and floods is still poorly understood. A case study of a Swiss lake flood event in the year 2000 reveals how different processes connected to blockings can favour the development of a flood. First upstream blocks helped to form strongly elongated troughs that are known to be associated with heavy precipitation events south of the Alps. Second recurrent precipitation events upstream of a block led to a moistening of the catchment and an increase of the lake level. Third the progression of the upstream weather systems was slowed and thereby the precipitation period over a catchment prolonged. Additionally, cloud diabatic processes in the flood region contributed to the establishment and maintenance of blocking anticyclones. Based on this case study we extend our analysis to all of Europe. Focusing on flood relevant precipitation events, i.e. extreme precipitation events that last for several days and affect larger areas, we show that different regions in Europe have very distinct seasonal precipitation patterns. Hence there is a strong seasonality in the occurrence of extreme events, depending on the geographical region. We further suggest that for different precipitation regimes, the preferred location of blockings varies strongly. Heavy precipitation events in southern France, for example, are often observed during Scandinavian blockings, while heavy precipitation events in south-eastern Europe coincide more often with eastern North-Atlantic blockings.
AgroClimate: Simulating and Monitoring the Risk of Extreme Weather Events from a Crop Phenology Perspective

NASA Astrophysics Data System (ADS)

Fraisse, C.; Pequeno, D.; Staub, C. G.; Perry, C.

2016-12-01

Climate variability, particularly the occurrence of extreme weather conditions such as dry spells and heat stress during sensitive crop developmental phases can substantially increase the prospect of reduced crop yields. Yield losses or crop failure risk due to stressful weather conditions vary mainly due to stress severity and exposure time and duration. The magnitude of stress effects is also crop specific, differing in terms of thresholds and adaptation to environmental conditions. To help producers in the Southeast USA mitigate and monitor the risk of crop losses due to extreme weather events we developed a web-based tool that evaluates the risk of extreme weather events during the season taking into account the crop development stages. Producers can enter their plans for the upcoming season in a given field (e.g. crop, variety, planting date, acreage etc.), select or not a specific El Nino Southern Oscillation (ENSO) phase, and will be presented with the probabilities (ranging from 0 -100%) of extreme weather events occurring during sensitive phases of the growing season for the selected conditions. The DSSAT models CERES-Maize, CROPGRO-Soybean, CROPGRO-Cotton, and N-Wheat phenology models have been translated from FORTRAN to a standalone versions in R language. These models have been tested in collaboration with Extension faculty and producers during the 2016 season and their usefulness for risk mitigation and monitoring evaluated. A companion AgroClimate app was also developed to help producers track and monitor phenology development during the cropping season.
Overview of Hydrometeorologic Forecasting Procedures at BC Hydro

NASA Astrophysics Data System (ADS)

McCollor, D.

2004-12-01

Energy utility companies must balance production from limited sources with increasing demand from industrial, business, and residential consumers. The utility planning process requires a balanced, efficient, and effective distribution of energy from source to consumer. Therefore utility planners must consider the impact of weather on energy production and consumption. Hydro-electric companies should be particularly tuned to weather because their source of energy is water, and water supply depends on precipitation. BC Hydro operates as the largest hydro-electric company in western Canada, managing over 30 reservoirs within the province of British Columbia, and generating electricity for 1.6 million people. BC Hydro relies on weather forecasts of watershed precipitation and temperature to drive hydrologic reservoir inflow models and of urban temperatures to meet energy demand requirements. Operations and planning specialists in the company rely on current, value-added weather forecasts for extreme high-inflow events, daily reservoir operations planning, and long-term water resource management. Weather plays a dominant role for BC Hydro financial planners in terms of sensitive economic responses. For example, a two percent change in hydropower generation, due in large part to annual precipitation patterns, results in an annual net change of \\50 million in earnings. A five percent change in temperature produces a \\5 million change in yearly earnings. On a daily basis, significant precipitation events or temperature extremes involve potential profit/loss decisions in the tens of thousands of dollars worth of power generation. These factors are in addition to environmental and societal costs that must be considered equally as part of a triple bottom line reporting structure. BC Hydro water resource managers require improved meteorological information from recent advancements in numerical weather prediction. At BC Hydro, methods of providing meteorological forecast data are changing as new downscaling and ensemble techniques evolve to improve environmental information supplied to water managers.
Contribution of large-scale midlatitude disturbances to hourly precipitation extremes in the United States

NASA Astrophysics Data System (ADS)

Barbero, Renaud; Abatzoglou, John T.; Fowler, Hayley J.

2018-02-01

Midlatitude synoptic weather regimes account for a substantial portion of annual precipitation accumulation as well as multi-day precipitation extremes across parts of the United States (US). However, little attention has been devoted to understanding how synoptic-scale patterns contribute to hourly precipitation extremes. A majority of 1-h annual maximum precipitation (AMP) across the western US were found to be linked to two coherent midlatitude synoptic patterns: disturbances propagating along the jet stream, and cutoff upper-level lows. The influence of these two patterns on 1-h AMP varies geographically. Over 95% of 1-h AMP along the western coastal US were coincident with progressive midlatitude waves embedded within the jet stream, while over 30% of 1-h AMP across the interior western US were coincident with cutoff lows. Between 30-60% of 1-h AMP were coincident with the jet stream across the Ohio River Valley and southeastern US, whereas a a majority of 1-h AMP over the rest of central and eastern US were not found to be associated with either midlatitude synoptic features. Composite analyses for 1-h AMP days coincident to cutoff lows and jet stream show that an anomalous moisture flux and upper-level dynamics are responsible for initiating instability and setting up an environment conducive to 1-h AMP events. While hourly precipitation extremes are generally thought to be purely convective in nature, this study shows that large-scale dynamics and baroclinic disturbances may also contribute to precipitation extremes on sub-daily timescales.
The late Little Ice Age landslide calamity in North Bohemia: Triggers, impacts and post-landslide development reconstructed from documentary data (case study of the Kozí vrch Hill landslide)

NASA Astrophysics Data System (ADS)

Raška, Pavel; Zábranský, Vilém; Brázdil, Rudolf; Lamková, Jana

2016-02-01

The beginning of the 1770s in the Czech Lands is well documented for its meteorological extremes and their social impacts. However, the effects of these extremes on geomorphic systems and on landslide occurrence and activity in particular have been minimally studied. In this paper, we use a complex set of written and iconographic documentary data to reconstruct the landslide calamity in North Bohemia, with a detailed case study of the Kozí vrch Hill landslide. The landslide calamity of 1770 is the oldest known landslide calamity in this region, including 14 documented events; and its reconstruction may therefore provide important data on landslide frequency, triggers, and impacts during the adverse weather patterns in the last part of the Little Ice Age (LIA). We focus on a case study of the Kozí vrch Hill landslide, and we use the documentary evidence and field techniques to reconstruct its location, extent, topography, kinematics, and triggers. Based on precipitation indices and weather descriptions, the extremely wet and rainy preceding year and the 1769/1770 winter were the major triggering factors that resulted in water saturation of Neogene volcaniclastics underlying the basalt lava flows and their subsequent collapse. Furthermore, we analyse the post-landslide terrain transformation and land use patterns during the 240 years following the landslide to illustrate the persistence of particular landslide features. We conclude that the major transformations, which obscured most of the landslide features, occurred in only the last 50-60 years. Finally, we discuss the role of documentary data and the current methodological advances in their use for the reconstruction of landslide frequency and impacts during the LIA.
Understanding Extreme Precipitation Behaviour in British Columbia's Lower Mainland Using Historical and Proxy Records

NASA Astrophysics Data System (ADS)

Spry, Christina

In British Columbia, Pineapple Express storms can lead to flooding, slope failures and negative impacts to water quality. Mitigating the impacts of extreme weather events in a changing climate requires an understanding of how local climate responds to regional-toglobal climate forcing patterns. In this study, I use historical and proxy data to identify the distinguishing characteristics of Pineapple Express storms and to develop a tree ring oxygen isotope record (1960--1995) of local climate conditions in the Lower Mainland of British Columbia. I found that high magnitude Pineapple Express storms have significantly higher precipitation and streamflow than other storms types, which result in relatively high contributions of Pineapple Express storms to the annual water budget. As well, Pineapple Express precipitation is characterized by an enriched delta18O isotopic signature when compared to precipitation originating from the North Pacific Ocean. However, differences in source water do not appear to be driving the variability in tree ring delta18O ratios. Instead, tree ring isotopic values exhibit a regional climate pattern that is strongly driven by latitudinal temperature gradients and the Rayleigh distillation effect. Therefore, future warmer conditions may decrease the temperature gradient between the equator and the poles, which can be recorded in the tree ring isotope record. The results also suggest that warmer temperatures due to climate change could result in more active Pineapple Express storm seasons, with multiple PE storms happening over a short period of time. Concurrent storms significantly increase the risk to society because the resulting antecedent saturated soil conditions can trigger precipitationinduced natural hazards. Keywords: extreme weather; stable isotopes; Pineapple Express; British Columbia; climate change; tree rings.
A comparative study of European insurance schemes for extreme weather risks and incentives for risk reduction

NASA Astrophysics Data System (ADS)

de Ruiter, Marleen; Hudson, Paul; de Ruig, Lars; Kuik, Onno; Botzen, Wouter

2017-04-01

This paper provides an analysis of the insurance schemes that cover extreme weather events in twelve different EU countries and the risk reduction incentives offered by these schemes. Economic impacts of extreme weather events in many regions in Europe and elsewhere are on the rise due to climate change and increasing exposure as driven by urban development. In an attempt to manage impacts from extreme weather events, natural disaster insurance schemes can provide incentives for taking measures that limit weather-related risks. Insurance companies can influence public risk management policies and risk-reducing behaviour of policyholders by "rewarding behaviour that reduces risks and potential damages" (Botzen and Van den Bergh, 2008, p. 417). Examples of insurance market systems that directly or indirectly aim to incentivize risk reduction with varying degrees of success are: the U.S. National Flood Insurance Programme; the French Catastrophes Naturelles system; and the U.K. Flood Re program which requires certain levels of protection standards for properties to be insurable. In our analysis, we distinguish between four different disaster types (i.e. coastal and fluvial floods, droughts and storms) and three different sectors (i.e. residential, commercial and agriculture). The selected case studies also provide a wide coverage of different insurance market structures, including public, private and public-private insurance provision, and different methods of coping with extreme loss events, such as re-insurance, governmental aid and catastrophe bonds. The analysis of existing mechanisms for risk reduction incentives provides recommendations about incentivizing adaptive behaviour, in order to assist policy makers and other stakeholders in designing more effective insurance schemes for extreme weather risks.
Extreme Weather Risk Assessment: The Case of Jiquilisco, El Salvador

NASA Astrophysics Data System (ADS)

Melendez, Karla; Ceppi, Claudia; Molero, Juanjo; Rios Insua, David

2014-05-01

All major climate models predict increases in both global and regional mean temperatures throughout this century, under different scenarios concerning future trends in population growth or economic and technological development. This consistency of results across models has strengthened the evidence about global warming. Despite the convincing facts and findings of climate researchers, there is still a great deal of skepticism around climate change. There is somewhat less consensus about some of the consequences of climate change, for example in reference to extreme weather changes, in particular as regards more local scales. However, such changes seem to have already considerable impact in many regions across the world in terms of lives, economic losses, and required changes in lifestyles. This may demand appropriate policy responses both at national and local levels. Our work provides a framework for extreme weather multithreat risk management, based on probabilistic risk assessment (PRA). This may be useful in comparing the effectiveness of different actions to manage risks and inform judgment concerning the appropriate resource allocation to mitigate the risks. The methodology has been applied to the case study of the "El Marillo II" community, located in the municipality of Jiquilisco in El Salvador. There, the main problem related with extreme weather conditions are the frequent floods caused by rainfall, hurricanes , and water increases in the Lempa river nearby located. However, droughts are also very relevant. Based on several sources like SNET, newspapers, field visits to the region and interviews, we have built a detailed database that comprises extreme weather daily data from January 1971 until December 2011. Forecasting models for floods and droughts were built suggesting the need to properly manage the risks. We subsequently obtained the optimal portfolio of countermeasures, given the budget constraints. KEYWORDS: CLIMATE CHANGE, EXTREME WEATHER, RISK ANALYSIS, DECISION ANALYSIS, EL SALVADOR.
Water-Borne Diseases and Extreme Weather Events in Cambodia: Review of Impacts and Implications of Climate Change

PubMed Central

Davies, Grace I.; McIver, Lachlan; Kim, Yoonhee; Hashizume, Masahiro; Iddings, Steven; Chan, Vibol

2014-01-01

Cambodia is prone to extreme weather events, especially floods, droughts and typhoons. Climate change is predicted to increase the frequency and intensity of such events. The Cambodian population is highly vulnerable to the impacts of these events due to poverty; malnutrition; agricultural dependence; settlements in flood-prone areas, and public health, governance and technological limitations. Yet little is known about the health impacts of extreme weather events in Cambodia. Given the extremely low adaptive capacity of the population, this is a crucial knowledge gap. A literature review of the health impacts of floods, droughts and typhoons in Cambodia was conducted, with regional and global information reviewed where Cambodia-specific literature was lacking. Water-borne diseases are of particular concern in Cambodia, in the face of extreme weather events and climate change, due to, inter alia, a high pre-existing burden of diseases such as diarrhoeal illness and a lack of improved sanitation infrastructure in rural areas. A time-series analysis under quasi-Poisson distribution was used to evaluate the association between floods and diarrhoeal disease incidence in Cambodian children between 2001 and 2012 in 16 Cambodian provinces. Floods were significantly associated with increased diarrhoeal disease in two provinces, while the analysis conducted suggested a possible protective effect from toilets and piped water. Addressing the specific, local pre-existing vulnerabilities is vital to promoting population health resilience and strengthening adaptive capacity to extreme weather events and climate change in Cambodia. PMID:25546280
Water-borne diseases and extreme weather events in Cambodia: review of impacts and implications of climate change.

PubMed

Davies, Grace I; McIver, Lachlan; Kim, Yoonhee; Hashizume, Masahiro; Iddings, Steven; Chan, Vibol

2014-12-23

Cambodia is prone to extreme weather events, especially floods, droughts and typhoons. Climate change is predicted to increase the frequency and intensity of such events. The Cambodian population is highly vulnerable to the impacts of these events due to poverty; malnutrition; agricultural dependence; settlements in flood-prone areas, and public health, governance and technological limitations. Yet little is known about the health impacts of extreme weather events in Cambodia. Given the extremely low adaptive capacity of the population, this is a crucial knowledge gap. A literature review of the health impacts of floods, droughts and typhoons in Cambodia was conducted, with regional and global information reviewed where Cambodia-specific literature was lacking. Water-borne diseases are of particular concern in Cambodia, in the face of extreme weather events and climate change, due to, inter alia, a high pre-existing burden of diseases such as diarrhoeal illness and a lack of improved sanitation infrastructure in rural areas. A time-series analysis under quasi-Poisson distribution was used to evaluate the association between floods and diarrhoeal disease incidence in Cambodian children between 2001 and 2012 in 16 Cambodian provinces. Floods were significantly associated with increased diarrhoeal disease in two provinces, while the analysis conducted suggested a possible protective effect from toilets and piped water. Addressing the specific, local pre-existing vulnerabilities is vital to promoting population health resilience and strengthening adaptive capacity to extreme weather events and climate change in Cambodia.
How sensitive extreme precipitation events on the west coast of Norway are to changes in the Sea Surface Temperature?

NASA Astrophysics Data System (ADS)

Sandvik, M. I.; Sorteberg, A.

2013-12-01

Studies (RegClim, 2005; Caroletti & Barstad, 2010; Bengtsson et al., 2009; Trenberth, 1999; Pall et al., 2007) indicate an increased risk of more frequent precipitation extremes in a warming world, which may result in more frequent flooding, avalanches and landslides. Thus, the ability to understand how processes influence extreme precipitation events could result in a better representation in models used in both research and weather forecasting. The Weather Research and Forecasting (WRF) model was used on 26 extreme precipitation events located on the west coast of Norway between 1980-2011. The goal of the study was to see how sensitive the intensity and distribution of the precipitation for these case studies were to a warmer/colder Atlantic Ocean, with a uniform change of ×2°C. To secure that the large-scale system remained the same when the Sea Surface Temperature (SST) was changed, spectral nudging was introduced. To avoid the need of a convective scheme, and the uncertainties it brings, a nested domain with a 2km grid resolution was used over Southern Norway. WRF generally underestimated the daily precipitation. The case studies were divided into 2 clusters, depending on the wind direction towards the coast, to search for patterns within each of the clusters. By the use of ensemble mean, the percentage change between the control run and the 2 sensitivity runs were different for the 2 clusters.
Climate, not conflict, explains extreme Middle East dust storm

DOE PAGES

Parolari, Anthony J.; Li, Dan; Bou-Zeid, Elie; ...

2016-11-08

The recent dust storm in the Middle East (Sepember 2015) was publicized in the media as a sign of an impending 'Dust Bowl.' Its severity, demonstrated by extreme aerosol optical depth in the atmosphere in the 99th percentile compared to historical data, was attributed to the ongoing regional conflict. However, surface meteorological and remote sensing data, as well as regional climate model simulations, support an alternative hypothesis: the historically unprecedented aridity played a more prominent role, as evidenced by unusual climatic and meteorological conditions prior to and during the storm. Remotely sensed normalized difference vegetation index demonstrates that vegetation covermore » was high in 2015 relative to the prior drought and conflict periods, suggesting that agricultural activity was not diminished during that year, thus negating the media narrative. Instead, meteorological simulations using the Weather Research and Forecasting (WRF) model show that the storm was associated with a cyclone and 'Shamal' winds, typical for dust storm generation in this region, that were immediately followed by an unusual wind reversal at low levels that spread dust west to the Mediterranean Coast. These unusual meteorological conditions were aided by a significant reduction in the critical shear stress due to extreme dry and hot conditions, thereby enhancing dust availability for erosion during this storm. Concluding, unusual aridity, combined with unique synoptic weather patterns, enhanced dust emission and westward long-range transport across the region, thus generating the extreme storm.« less

Climate, not conflict, explains extreme Middle East dust storm

DOE Office of Scientific and Technical Information (OSTI.GOV)

Parolari, Anthony J.; Li, Dan; Bou-Zeid, Elie

The recent dust storm in the Middle East (Sepember 2015) was publicized in the media as a sign of an impending 'Dust Bowl.' Its severity, demonstrated by extreme aerosol optical depth in the atmosphere in the 99th percentile compared to historical data, was attributed to the ongoing regional conflict. However, surface meteorological and remote sensing data, as well as regional climate model simulations, support an alternative hypothesis: the historically unprecedented aridity played a more prominent role, as evidenced by unusual climatic and meteorological conditions prior to and during the storm. Remotely sensed normalized difference vegetation index demonstrates that vegetation covermore » was high in 2015 relative to the prior drought and conflict periods, suggesting that agricultural activity was not diminished during that year, thus negating the media narrative. Instead, meteorological simulations using the Weather Research and Forecasting (WRF) model show that the storm was associated with a cyclone and 'Shamal' winds, typical for dust storm generation in this region, that were immediately followed by an unusual wind reversal at low levels that spread dust west to the Mediterranean Coast. These unusual meteorological conditions were aided by a significant reduction in the critical shear stress due to extreme dry and hot conditions, thereby enhancing dust availability for erosion during this storm. Concluding, unusual aridity, combined with unique synoptic weather patterns, enhanced dust emission and westward long-range transport across the region, thus generating the extreme storm.« less
European temperature responses to blocking and ridge regional patterns

NASA Astrophysics Data System (ADS)

Sousa, Pedro M.; Trigo, Ricardo M.; Barriopedro, David; Soares, Pedro M. M.; Santos, João A.

2018-01-01

Blocking occurrence and its impacts on European temperature have been studied in the last decade. However, most previous studies on blocking impacts have focused on winter only, disregarding its fingerprint in summer and differences with other synoptic patterns that also trigger temperature extremes. In this work, we provide a clear distinction between high-latitude blocking and sub-tropical ridges occurring in three sectors of the Euro-Atlantic region, describing their climatology and consequent impacts on European temperature during both winter and summer. Winter blocks (ridges) are generally associated to colder (warmer) than average conditions over large regions of Europe, in some areas with anomalies larger than 5 °C, particularly for the patterns occurring in the Atlantic and Central European sectors. During summer, there is a more regional response characterized by above average temperature for both blocking and ridge patterns, especially those occurring in continental areas, although negative temperature anomalies persist in southernmost areas during blocking. An objective analysis of the different forcing mechanisms associated to each considered weather regime has been performed, quantifying the importance of the following processes in causing the temperature anomalies: horizontal advection, vertical advection and diabatic heating. While during winter advection processes tend to be more relevant to explain temperature responses, in summer radiative heating under enhanced insolation plays a crucial role for both blocking and ridges. Finally, the changes in the distributions of seasonal temperature and in the frequencies of extreme temperature indices were also examined for specific areas of Europe. Winter blocking and ridge patterns are key drivers in the occurrence of regional cold and warm extreme temperatures, respectively. In summer, they are associated with substantial changes in the frequency of extremely warm days, but with different signatures in southern Europe. We conclude that there has been some misusage of the traditional blocking definition in the attribution of extreme events.
An end-to-end assessment of extreme weather impacts on food security

NASA Astrophysics Data System (ADS)

Chavez, Erik; Conway, Gordon; Ghil, Michael; Sadler, Marc

2015-11-01

Both governments and the private sector urgently require better estimates of the likely incidence of extreme weather events, their impacts on food crop production and the potential consequent social and economic losses. Current assessments of climate change impacts on agriculture mostly focus on average crop yield vulnerability to climate and adaptation scenarios. Also, although new-generation climate models have improved and there has been an exponential increase in available data, the uncertainties in their projections over years and decades, and at regional and local scale, have not decreased. We need to understand and quantify the non-stationary, annual and decadal climate impacts using simple and communicable risk metrics that will help public and private stakeholders manage the hazards to food security. Here we present an `end-to-end’ methodological construct based on weather indices and machine learning that integrates current understanding of the various interacting systems of climate, crops and the economy to determine short- to long-term risk estimates of crop production loss, in different climate and adaptation scenarios. For provinces north and south of the Yangtze River in China, we have found that risk profiles for crop yields that translate climate into economic variability follow marked regional patterns, shaped by drivers of continental-scale climate. We conclude that to be cost-effective, region-specific policies have to be tailored to optimally combine different categories of risk management instruments.
The development of a non-linear autoregressive model with exogenous input (NARX) to model climate-water clarity relationships: reconstructing a historical water clarity index for the coastal waters of the southeastern USA

NASA Astrophysics Data System (ADS)

Lee, Cameron C.; Sheridan, Scott C.; Barnes, Brian B.; Hu, Chuanmin; Pirhalla, Douglas E.; Ransibrahmanakul, Varis; Shein, Karsten

2017-10-01

The coastal waters of the southeastern USA contain important protected habitats and natural resources that are vulnerable to climate variability and singular weather events. Water clarity, strongly affected by atmospheric events, is linked to substantial environmental impacts throughout the region. To assess this relationship over the long-term, this study uses an artificial neural network-based time series modeling technique known as non-linear autoregressive models with exogenous input (NARX models) to explore the relationship between climate and a water clarity index (KDI) in this area and to reconstruct this index over a 66-year period. Results show that synoptic-scale circulation patterns, weather types, and precipitation all play roles in impacting water clarity to varying degrees in each region of the larger domain. In particular, turbid water is associated with transitional weather and cyclonic circulation in much of the study region. Overall, NARX model performance also varies—regionally, seasonally and interannually—with wintertime estimates of KDI along the West Florida Shelf correlating to the actual KDI at r > 0.70. Periods of extreme (high) KDI in this area coincide with notable El Niño events. An upward trend in extreme KDI events from 1948 to 2013 is also present across much of the Florida Gulf coast.
Extreme wildfire events are linked to global-change-type droughts in the northern Mediterranean

NASA Astrophysics Data System (ADS)

Ruffault, Julien; Curt, Thomas; Martin-StPaul, Nicolas K.; Moron, Vincent; Trigo, Ricardo M.

2018-03-01

Increasing drought conditions under global warming are expected to alter the frequency and distribution of large and high-intensity wildfires. However, our understanding of the impact of increasing drought on extreme wildfires events remains incomplete. Here, we analyzed the weather conditions associated with the extreme wildfires events that occurred in Mediterranean France during the exceptionally dry summers of 2003 and 2016. We identified that these fires were related to two distinct shifts in the fire weather space towards fire weather conditions that had not been explored before and resulting from specific interactions between different types of drought and different fire weather types. In 2016, a long-lasting press drought intensified wind-driven fires. In 2003, a hot drought combining a heat wave with a press drought intensified heat-induced fires. Our findings highlight that increasing drought conditions projected by climate change scenarios might affect the dryness of fuel compartments and lead to a higher frequency of extremes wildfires events.
Compilation of 1986 Annual Reports of the Navy ELF (Extremely Low Frequency) Communications System Ecological Monitoring Program. Volume 1. TABS A-C.

DTIC Science & Technology

1987-07-01

temperature increase ccrnpared to the antenna plantation while the control pole-size stand type had a -.3’ decrease. These relationships emphasize ...study of the timing of life cycle events relative to environmental cues (Barbour et al. 1980), has been used to quantitatively describe the herbaceous...successful, emphasizing the importance of ainual weather patterns on the buildup of microbial populations and their activities. These analyses indicate
Weather based risks and insurances for crop production in Belgium

NASA Astrophysics Data System (ADS)

Gobin, Anne

2014-05-01

Extreme weather events such as late frosts, droughts, heat waves and rain storms can have devastating effects on cropping systems. Damages due to extreme events are strongly dependent on crop type, crop stage, soil type and soil conditions. The perspective of rising risk-exposure is exacerbated further by limited aid received for agricultural damage, an overall reduction of direct income support to farmers and projected intensification of weather extremes with climate change. According to both the agriculture and finance sectors, a risk assessment of extreme weather events and their impact on cropping systems is needed. The impact of extreme weather events particularly during the sensitive periods of the farming calendar requires a modelling approach to capture the mixture of non-linear interactions between the crop, its environment and the occurrence of the meteorological event. The risk of soil moisture deficit increases towards harvesting, such that drought stress occurs in spring and summer. Conversely, waterlogging occurs mostly during early spring and autumn. Risks of temperature stress appear during winter and spring for chilling and during summer for heat. Since crop development is driven by thermal time and photoperiod, the regional crop model REGCROP (Gobin, 2010) enabled to examine the likely frequency, magnitude and impacts of frost, drought, heat stress and waterlogging in relation to the cropping season and crop sensitive stages. The risk profiles were subsequently confronted with yields, yield losses and insurance claims for different crops. Physically based crop models such as REGCROP assist in understanding the links between different factors causing crop damage as demonstrated for cropping systems in Belgium. Extreme weather events have already precipitated contraction of insurance coverage in some markets (e.g. hail insurance), and the process can be expected to continue if the losses or damages from such events increase in the future. Climate change will stress this further and impacts on crop growth are expected to be twofold, owing to the sensitive stages occurring earlier during the growing season and to the changes in return period of extreme weather events. Though average yields have risen continuously due to technological advances, there is no evidence that relative tolerance to adverse weather events has improved. The research is funded by the Belgian Science Policy Organisation (Belspo) under contract nr SD/RI/03A.
How to assess extreme weather impacts - case European transport network

NASA Astrophysics Data System (ADS)

Leviäkangas, P.

2010-09-01

To assess the impacts of climate change and preparing for impacts is a process. This process we must understand and learn to apply. EWENT (Extreme Weather impacts on European Networks of Transport) will be a test bench for one prospective approach. It has the following main components: 1) identifying what is "extreme", 2) assessing the change in the probabilities, 3) constructing the causal impact models, 4) finding appropriate methods of pricing and costing, 5) finding alternative strategy option, 6) assessing the efficiency of strategy option. This process follows actually the steps of standardized risk management process. Each step is challenging, but if EWENT project succeeds to assess the extreme weather impacts on European transport networks, it is one possible benchmark how to carry out similar analyses in other regions and on country level. EWENT approach could particularly useful for weather and climate information service providers, offering tools for transport authorities and financiers to assess weather risks, and then rationally managing the risks. EWENT project is financed by the European Commission and participated by met-service organisations and transport research institutes from different parts of Europe. The presentation will explain EWENT approach in detail and bring forth the findings of the first work packages.
Developing Effective Communications about Extreme Weather Risks.

NASA Astrophysics Data System (ADS)

Bruine de Bruin, W.

2014-12-01

Members of the general public often face complex decisions about the risks that they face, including those associated with extreme weather and climate change adaptation. Scientific experts may be asked to develop communications with the goal of improving people's understanding of weather and climate risks, and informing people's decisions about how to protect against these risks. Unfortunately, scientific experts' communication efforts may fail if they lack information about what people need or want to know to make more informed decisions or what wording people prefer use to describe relevant concepts. This presentation provides general principles for developing effective risk communication materials that aim for widespread dissemination, such as brochures and websites. After a brief review of the social science evidence on how to design effective risk communication materials, examples will focus on communications about extreme weather events and climate change. Specifically, data will be presented from ongoing projects on flood risk perception, public preparedness for heat waves, and public perceptions of climate change. The presentation will end with specific recommendations about how to improve recipients' understanding about risks and inform decisions. These recommendations should be useful to scientific experts who aim to communicate about extreme weather, climate change, or other risks.
Past and future weather-induced risk in crop production

NASA Astrophysics Data System (ADS)

Elliott, J. W.; Glotter, M.; Russo, T. A.; Sahoo, S.; Foster, I.; Benton, T.; Mueller, C.

2016-12-01

Drought-induced agricultural loss is one of the most costly impacts of extreme weather and may harm more people than any other consequence of climate change. Improvements in farming practices have dramatically increased crop productivity, but yields today are still tightly linked to climate variation. We report here on a number of recent studies evaluating extreme event risk and impacts under historical and near future conditions, including studies conducted as part of the Agricultural Modeling Intercomparison and Improvement Project (AgMIP), the Inter-Sectoral Impacts Model Intercomparison Project (ISI-MIP) and the UK-US Taskforce on Extreme Weather and Global Food System Resilience.
The potential impacts of climate variability and change on health impacts of extreme weather events in the United States.

PubMed

Greenough, G; McGeehin, M; Bernard, S M; Trtanj, J; Riad, J; Engelberg, D

2001-05-01

Extreme weather events such as precipitation extremes and severe storms cause hundreds of deaths and injuries annually in the United States. Climate change may alter the frequency, timing, intensity, and duration of these events. Increases in heavy precipitation have occurred over the past century. Future climate scenarios show likely increases in the frequency of extreme precipitation events, including precipitation during hurricanes, raising the risk of floods. Frequencies of tornadoes and hurricanes cannot reliably be projected. Injury and death are the direct health impacts most often associated with natural disasters. Secondary effects, mediated by changes in ecologic systems and public health infrastructure, also occur. The health impacts of extreme weather events hinge on the vulnerabilities and recovery capacities of the natural environment and the local population. Relevant variables include building codes, warning systems, disaster policies, evacuation plans, and relief efforts. There are many federal, state, and local government agencies and nongovernmental organizations involved in planning for and responding to natural disasters in the United States. Future research on health impacts of extreme weather events should focus on improving climate models to project any trends in regional extreme events and as a result improve public health preparedness and mitigation. Epidemiologic studies of health effects beyond the direct impacts of disaster will provide a more accurate measure of the full health impacts and will assist in planning and resource allocation.
An Independent Assessment of Anthropogenic Attribution Statements for Recent Extreme Temperature and Rainfall Events

DOE Office of Scientific and Technical Information (OSTI.GOV)

Angélil, Oliver; Stone, Dáithí; Wehner, Michael

The annual "State of the Climate" report, published in the Bulletin of the American Meteorological Society (BAMS), has included a supplement since 2011 composed of brief analyses of the human influence on recent major extreme weather events. There are now several dozen extreme weather events examined in these supplements, but these studies have all differed in their data sources as well as their approaches to defining the events, analyzing the events, and the consideration of the role of anthropogenic emissions. This study reexamines most of these events using a single analytical approach and a single set of climate model andmore » observational data sources. In response to recent studies recommending the importance of using multiple methods for extreme weather event attribution, results are compared from these analyses to those reported in the BAMS supplements collectively, with the aim of characterizing the degree to which the lack of a common methodological framework may or may not influence overall conclusions. Results are broadly similar to those reported earlier for extreme temperature events but disagree for a number of extreme precipitation events. Based on this, it is advised that the lack of comprehensive uncertainty analysis in recent extreme weather attribution studies is important and should be considered when interpreting results, but as yet it has not introduced a systematic bias across these studies.« less
An Independent Assessment of Anthropogenic Attribution Statements for Recent Extreme Temperature and Rainfall Events

DOE PAGES

Angélil, Oliver; Stone, Dáithí; Wehner, Michael; ...

2016-12-16

The annual "State of the Climate" report, published in the Bulletin of the American Meteorological Society (BAMS), has included a supplement since 2011 composed of brief analyses of the human influence on recent major extreme weather events. There are now several dozen extreme weather events examined in these supplements, but these studies have all differed in their data sources as well as their approaches to defining the events, analyzing the events, and the consideration of the role of anthropogenic emissions. This study reexamines most of these events using a single analytical approach and a single set of climate model andmore » observational data sources. In response to recent studies recommending the importance of using multiple methods for extreme weather event attribution, results are compared from these analyses to those reported in the BAMS supplements collectively, with the aim of characterizing the degree to which the lack of a common methodological framework may or may not influence overall conclusions. Results are broadly similar to those reported earlier for extreme temperature events but disagree for a number of extreme precipitation events. Based on this, it is advised that the lack of comprehensive uncertainty analysis in recent extreme weather attribution studies is important and should be considered when interpreting results, but as yet it has not introduced a systematic bias across these studies.« less
Weather conditions: a neglected factor in human salivary cortisol research?

NASA Astrophysics Data System (ADS)

Milas, Goran; Šupe-Domić, Daniela; Drmić-Hofman, Irena; Rumora, Lada; Klarić, Irena Martinović

2018-02-01

There is ample evidence that environmental stressors such as extreme weather conditions affect animal behavior and that this process is in part mediated through the elevated activity of the hypothalamic pituitary adrenal axis which results in an increase in cortisol secretion. This relationship has not been extensively researched in humans, and weather conditions have not been analyzed as a potential confounder in human studies of stress. Consequently, the goal of this paper was to assess the relationship between salivary cortisol and weather conditions in the course of everyday life and to test a possible moderating effect of two weather-related variables, the climate region and timing of exposure to outdoors conditions. The sample consisted of 903 secondary school students aged 18 to 21 years from Mediterranean and Continental regions. Cortisol from saliva was sampled in naturalistic settings at three time points over the course of a single day. We found that weather conditions are related to salivary cortisol concentration and that this relationship may be moderated by both the specific climate and the anticipation of immediate exposure to outdoors conditions. Unpleasant weather conditions are predictive for the level of salivary cortisol, but only among individuals who anticipate being exposed to it in the immediate future (e.g., in students attending school in the morning shift). We also demonstrated that isolated weather conditions or their patterns may be relevant in one climate area (e.g., Continental) while less relevant in the other (e.g., Mediterranean). Results of this study draw attention to the importance of controlling weather conditions in human salivary cortisol research.
European summer heatwaves and North Atlantic weather regimes in the last Millennium

NASA Astrophysics Data System (ADS)

Alvarez Castro, Maria del Carmen; Trasancos, Romain; Yiou, Pascal

2015-04-01

The European summer heatwaves have been increasing in frequency and magnitude in the past decades. A higher confidence in future changes in such extremes necessitates to have a better knowledge about extremes behavior in the past climate. The last millennium is well documented in terms of climate forcings. Modelling efforts have provided a wealth of climate simulations covering the last millennium. We want to exploit such data in order to assess how models simulate extreme summer heatwaves. The surface temperature and precipitation are closely related to atmospheric patterns. It has been shown that rainy winter/spring seasons reduce the frequency of hot summer days whereas dry seasons can be followed by summers with high or low frequency of hot days. In this poster, we show the relation between winter/spring precipitation with the frequency of hot days in the 10 hottest summers in Europe and Southern Europe during the Medieval Warm Period (MWP 1150-1250), the Little Ice Age (LIA 1650-1750), and the historical-present period (1850-2005). We first focus on a millennium simulations with the IPSL model (IPSL-CM5). We use daily temperature, precipitation, and SLP data from CMIP5 (Coupled Model Intercomparison Project phase 5) and a couple of IPSL simulations with diferents forcings. Summer weather regimes has been computed as well for NCEP sea level pressure data in order to compare observations with the same period (1948-2005) in CMIP5 and IPSL simulations outputs. We discuss and present the results comparing the effects of hydrological deficits in the preceding season, and the occurrence of specific weather regimes, during the hottest summers over Europe and SouthWestern Europe. This analysis compares differents climate forcings simulations.
Extreme Weather Events and Climate Change Attribution

DOE Office of Scientific and Technical Information (OSTI.GOV)

Thomas, Katherine

A report from the National Academies of Sciences, Engineering, and Medicine concludes it is now possible to estimate the influence of climate change on some types of extreme events. The science of extreme event attribution has advanced rapidly in recent years, giving new insight to the ways that human-caused climate change can influence the magnitude or frequency of some extreme weather events. This report examines the current state of science of extreme weather attribution, and identifies ways to move the science forward to improve attribution capabilities. Confidence is strongest in attributing types of extreme events that are influenced by climatemore » change through a well-understood physical mechanism, such as, the more frequent heat waves that are closely connected to human-caused global temperature increases, the report finds. Confidence is lower for other types of events, such as hurricanes, whose relationship to climate change is more complex and less understood at present. For any extreme event, the results of attribution studies hinge on how questions about the event's causes are posed, and on the data, modeling approaches, and statistical tools chosen for the analysis.« less
Rossby waves, extreme fronts, and wildfires in southeastern Australia

NASA Astrophysics Data System (ADS)

Reeder, Michael J.; Spengler, Thomas; Musgrave, Ruth

2015-03-01

The most catastrophic fires in recent history in southern Australia have been associated with extreme cold fronts. Here an extreme cold front is defined as one for which the maximum temperature at 2 m is at least 17°C lower on the day following the front. An anticyclone, which precedes the cold front, directs very dry northerlies or northwesterlies from the interior of the continent across the region. The passage of the cold front is followed by strong southerlies or southwesterlies. European Centre for Medium-Range Weather Forecasts ERA-Interim Reanalyses show that this regional synoptic pattern common to all strong cold fronts, and hence severe fire conditions, is a consequence of propagating Rossby waves, which grow to large amplitude and eventually irreversibly overturn. The process of overturning produces the low-level anticyclone and dry conditions over southern Australia, while simultaneously producing an upper level trough and often precipitation in northeastern Australia.
Transportation System Vulnerability and Resilience to Extreme Weather Events and Other Natural Hazards : Final Results of Vulnerability Assessment of National Highway System for All KYTC Districts

DOT National Transportation Integrated Search

2018-05-01

Recent federal legislation and the Federal Highway Administration (FHWA) have directed state transportation agencies to identify potential vulnerabilities associated with extreme weather events and climate change, develop a risk-based asset managemen...
Cross-timescale Interference and Rainfall Extreme Events in South Eastern South America

NASA Astrophysics Data System (ADS)

Munoz, Angel G.

The physical mechanisms and predictability associated with extreme daily rainfall in South East South America (SESA) are investigated for the December-February season. Through a k-mean analysis, a robust set of daily circulation regimes is identified and then it is used to link the frequency of rainfall extreme events with large-scale potential predictors at subseasonal-to-seasonal scales. This basic set of daily circulation regimes is related to the continental and oceanic phases of the South Atlantic Convergence Zone (SACZ) and wave train patterns superimposed on the Southern Hemisphere Polar Jet. Some of these recurrent synoptic circulation types are conducive to extreme rainfall events in the region through synoptic control of different meso-scale physical features and, at the same time, are influenced by climate phenomena that could be used as sources of potential predictability. Extremely high rainfall (as measured by the 95th- and 99th-percentiles) is preferentially associated with two of these weather types, which are characterized by moisture advection intrusions from lower latitudes and the Pacific; another three weather types, characterized by above-normal moisture advection toward lower latitudes or the Andes, are preferentially associated with dry days (days with no rain). The analysis permits the identification of several subseasonal-to-seasonal scale potential predictors that modulate the occurrence of circulation regimes conducive to extreme rainfall events in SESA. It is conjectured that a cross-timescale interference between the different climate drivers improves the predictive skill of extreme precipitation in the region. The potential and real predictive skill of the frequency of extreme rainfall is then evaluated, finding evidence indicating that mechanisms of climate variability at one timescale contribute to the predictability at another scale, i.e., taking into account the interference of different potential sources of predictability at different timescales increases the predictive skill. This fact is in agreement with the Cross-timescale Interference Conjecture proposed in the first part of the thesis. At seasonal scale, a combination of those weather types tends to outperform all the other potential predictors explored, i.e., sea surface temperature patterns, phases of the Madden-Julian Oscillation, and combinations of both. Spatially averaged Kendall’s τ improvements of 43% for the potential predictability and 23% for realtime predictions are attained with respect to standard models considering sea-surface temperature fields alone. A new subseasonal-to-seasonal predictive methodology for extreme rainfall events is proposed, based on probability forecasts of seasonal sequences of these weather types. The cross-validated realtime skill of the new probabilistic approach, as measured by the Hit Score and the Heidke Skill Score, is on the order of twice that associated with climatological values. The approach is designed to offer useful subseasonal-to-seasonal climate information to decision-makers interested not only in how many extreme events will happen in the season, but also in how, when and where those events will probably occur. In order to gain further understanding about how the cross-timescale interference occurs, an externally-forced Lorenz model is used to explore the impact of different kind of forcings, at inter-annual and decadal scales, in the establishment of constructive interactions associated with the simulated “extreme events”. Using a wavelet analysis, it is shown that this simple model is capable of reproducing the same kind of cross-timescale structures observed in the wavelet power spectrum of the Nino3.4 index only when it is externally forced by both inter-annual and decadal signals: the annual cycle and a decadal forcing associated with the natural solar variability. The nature of this interaction is non-linear, and it impacts both mean and extreme values in the time series. No predictive power was found when using metrics like standard deviation and auto-correlation. Nonetheless, it was proposed that an early warning signal for occurrence of extreme rainfall in SESA may be possible via a continuous monitoring of relative phases between the cross-timescale leading components.
Future projections of synoptic weather types over the Arabian Peninsula during the twenty-first century using an ensemble of CMIP5 models

NASA Astrophysics Data System (ADS)

El Kenawy, Ahmed M.; McCabe, Matthew F.

2017-10-01

An assessment of future change in synoptic conditions over the Arabian Peninsula throughout the twenty-first century was performed using 20 climate models from the Coupled Model Intercomparison Project Phase 5 (CMIP5) database. We employed the mean sea level pressure (SLP) data from model output together with NCEP/NCAR reanalysis data and compared the relevant circulation types produced by the Lamb classification scheme for the base period 1975-2000. Overall, model results illustrated good agreement with the reanalysis, albeit with a tendency to underestimate cyclonic (C) and southeasterly (SE) patterns and to overestimate anticyclones and directional flows. We also investigated future projections for each circulation-type during the rainy season (December-May) using three Representative Concentration Pathways (RCPs), comprising RCP2.6, RCP4.5, and RCP8.5. Overall, two scenarios (RCP4.5 and RCP 8.5) revealed a statistically significant increase in weather types favoring above normal rainfall in the region (e.g., C and E-types). In contrast, weather types associated with lower amounts of rainfall (e.g., anticyclones) are projected to decrease in winter but increase in spring. For all scenarios, there was consistent agreement on the sign of change (i.e., positive/negative) for the most frequent patterns (e.g., C, SE, E and A-types), whereas the sign was uncertain for less recurrent types (e.g., N, NW, SE, and W). The projected changes in weather type frequencies in the region can be viewed not only as indicators of change in rainfall response but may also be used to inform impact studies pertinent to water resource planning and management, extreme weather analysis, and agricultural production.

21st Century Changes in Precipitation Extremes Based on Resolved Atmospheric Patterns

NASA Astrophysics Data System (ADS)

Gao, X.; Schlosser, C. A.; O'Gorman, P. A.; Monier, E.

2014-12-01

Global warming is expected to alter the frequency and/or magnitude of extreme precipitation events. Such changes could have substantial ecological, economic, and sociological consequences. However, climate models in general do not correctly reproduce the frequency distribution of precipitation, especially at the regional scale. In this study, a validated analogue method is employed to diagnose the potential future shifts in the probability of extreme precipitation over the United States under global warming. The method is based on the use of the resolved large-scale meteorological conditions (i.e. flow features, moisture supply) to detect the occurrence of extreme precipitation. The CMIP5 multi-model projections have been compiled for two radiative forcing scenarios (Representative Concentration Pathways 4.5 and 8.5). We further analyze the accompanying circulation features and their changes that may be responsible for shifts in extreme precipitation in response to changed climate. The application of such analogue method to detect other types of hazard events, i.e. landslides is also explored. The results from this study may guide hazardous weather watches and help society develop adaptive strategies for preventing catastrophic losses.
Patterns of change in high frequency precipitation variability over North America.

PubMed

Roque-Malo, Susana; Kumar, Praveen

2017-09-18

Precipitation variability encompasses attributes associated with the sequencing and duration of events of the full range of magnitudes. However, climate change studies have largely focused on extreme events. Using analyses of long-term weather station data, we show that high frequency events, such as fraction of wet days in a year and average duration of wet and dry periods, are undergoing significant changes across North America. Further, these changes are more prevalent and larger than those associated with extremes. Such trends also exist for events of a range of magnitudes. Existence of localized clusters with opposing trend to that of broader geographic variation illustrates the role of microclimate and other drivers of trends. Such hitherto unknown patterns over the entire North American continent have the potential to significantly inform our characterization of the resilience and vulnerability of a broad range of ecosystems and agricultural and socio-economic systems. They can also set new benchmarks for climate model assessments.
Frostbite

MedlinePlus

... Preventing Frostbite To help prevent frostbite in cold weather: Stay updated on weather forecasts. If it's extremely cold, even brief exposure ... Medical History Cold, Ice, and Snow Safety Cold-Weather Sports and Your Family First-Aid Kit What ...
A new precipitation and drought climatology based on weather patterns

PubMed Central

Fowler, Hayley J.; Kilsby, Christopher G.; Neal, Robert

2017-01-01

ABSTRACT Weather‐pattern, or weather‐type, classifications are a valuable tool in many applications as they characterize the broad‐scale atmospheric circulation over a given region. This study analyses the aspects of regional UK precipitation and meteorological drought climatology with respect to a new set of objectively defined weather patterns. These new patterns are currently being used by the Met Office in several probabilistic forecasting applications driven by ensemble forecasting systems. Weather pattern definitions and daily occurrences are mapped to Lamb weather types (LWTs), and parallels between the two classifications are drawn. Daily precipitation distributions are associated with each weather pattern and LWT. Standardized precipitation index (SPI) and drought severity index (DSI) series are calculated for a range of aggregation periods and seasons. Monthly weather‐pattern frequency anomalies are calculated for SPI wet and dry periods and for the 5% most intense DSI‐based drought months. The new weather‐pattern definitions and daily occurrences largely agree with their respective LWTs, allowing comparison between the two classifications. There is also broad agreement between weather pattern and LWT changes in frequencies. The new data set is shown to be adequate for precipitation‐based analyses in the UK, although a smaller set of clustered weather patterns is not. Furthermore, intra‐pattern precipitation variability is lower in the new classification compared to the LWTs, which is an advantage in this context. Six of the new weather patterns are associated with drought over the entire UK, with several other patterns linked to regional drought. It is demonstrated that the new data set of weather patterns offers a new opportunity for classification‐based analyses in the UK. PMID:29456290
The Engineering for Climate Extremes Partnership

NASA Astrophysics Data System (ADS)

Holland, G. J.; Tye, M. R.

2014-12-01

Hurricane Sandy and the recent floods in Thailand have demonstrated not only how sensitive the urban environment is to the impact of severe weather, but also the associated global reach of the ramifications. These, together with other growing extreme weather impacts and the increasing interdependence of global commercial activities point towards a growing vulnerability to weather and climate extremes. The Engineering for Climate Extremes Partnership brings academia, industry and government together with the goals encouraging joint activities aimed at developing new, robust, and well-communicated responses to this increasing vulnerability. Integral to the approach is the concept of 'graceful failure' in which flexible designs are adopted that protect against failure by combining engineering or network strengths with a plan for efficient and rapid recovery if and when they fail. Such an approach enables optimal planning for both known future scenarios and their assessed uncertainty.
The Heat Exposure Integrated Deprivation Index (HEIDI): A data-driven approach to quantifying neighborhood risk during extreme hot weather.

PubMed

Krstic, Nikolas; Yuchi, Weiran; Ho, Hung Chak; Walker, Blake B; Knudby, Anders J; Henderson, Sarah B

2017-12-01

Mortality attributable to extreme hot weather is a growing concern in many urban environments, and spatial heat vulnerability indexes are often used to identify areas at relatively higher and lower risk. Three indexes were developed for greater Vancouver, Canada using a pool of 20 potentially predictive variables categorized to reflect social vulnerability, population density, temperature exposure, and urban form. One variable was chosen from each category: an existing deprivation index, senior population density, apparent temperature, and road density, respectively. The three indexes were constructed from these variables using (1) unweighted, (2) weighted, and (3) data-driven Heat Exposure Integrated Deprivation Index (HEIDI) approaches. The performance of each index was assessed using mortality data from 1998-2014, and the maps were compared with respect to spatial patterns identified. The population-weighted spatial correlation between the three indexes ranged from 0.68-0.89. The HEIDI approach produced a graduated map of vulnerability, whereas the other approaches primarily identified areas of highest risk. All indexes performed best under extreme temperatures, but HEIDI was more useful at lower thresholds. Each of the indexes in isolation provides valuable information for public health protection, but combining the HEIDI approach with unweighted and weighted methods provides richer information about areas most vulnerable to heat. Copyright © 2017 The Authors. Published by Elsevier Ltd.. All rights reserved.
Employing Numerical Weather Models to Enhance Fire Weather and Fire Behavior Predictions

Treesearch

Joseph J. Charney; Lesley A. Fusina

2006-01-01

This paper presents an assessment of fire weather and fire behavior predictions produced by a numerical weather prediction model similar to those used by operational weather forecasters when preparing their forecasts. The PSU/NCAR MM5 model is used to simulate the weather conditions associated with three fire episodes in June 2005. Extreme fire behavior was reported...
Municipalities' Preparedness for Weather Hazards and Response to Weather Warnings

PubMed Central

Mehiriz, Kaddour; Gosselin, Pierre

2016-01-01

The study of the management of weather-related disaster risks by municipalities has attracted little attention even though these organizations play a key role in protecting the population from extreme meteorological conditions. This article contributes to filling this gap with new evidence on the level and determinants of Quebec municipalities’ preparedness for weather hazards and response to related weather warnings. Using survey data from municipal emergency management coordinators and secondary data on the financial and demographic characteristics of municipalities, the study shows that most Quebec municipalities are sufficiently prepared for weather hazards and undertake measures to protect the population when informed of imminent extreme weather events. Significant differences between municipalities were noted though. Specifically, the level of preparedness was positively correlated with the municipalities’ capacity and population support for weather-related disaster management policies. In addition, the risk of weather-related disasters increases the preparedness level through its effect on population support. We also found that the response to weather warnings depended on the risk of weather-related disasters, the preparedness level and the quality of weather warnings. These results highlight areas for improvement in the context of increasing frequency and/or severity of such events with current climate change. PMID:27649547
Municipalities' Preparedness for Weather Hazards and Response to Weather Warnings.

PubMed

Mehiriz, Kaddour; Gosselin, Pierre

2016-01-01

The study of the management of weather-related disaster risks by municipalities has attracted little attention even though these organizations play a key role in protecting the population from extreme meteorological conditions. This article contributes to filling this gap with new evidence on the level and determinants of Quebec municipalities' preparedness for weather hazards and response to related weather warnings. Using survey data from municipal emergency management coordinators and secondary data on the financial and demographic characteristics of municipalities, the study shows that most Quebec municipalities are sufficiently prepared for weather hazards and undertake measures to protect the population when informed of imminent extreme weather events. Significant differences between municipalities were noted though. Specifically, the level of preparedness was positively correlated with the municipalities' capacity and population support for weather-related disaster management policies. In addition, the risk of weather-related disasters increases the preparedness level through its effect on population support. We also found that the response to weather warnings depended on the risk of weather-related disasters, the preparedness level and the quality of weather warnings. These results highlight areas for improvement in the context of increasing frequency and/or severity of such events with current climate change.
Spatio-temporal dynamics and synoptic characteristics of wet and drought extremes in Northern Eurasia

NASA Astrophysics Data System (ADS)

Utkuzova, Dilyara; Khan, Valentina

2015-04-01

Synoptical-statistical analysis has been conducted using SPI index calculated for 478 stations with records from 1966 through 2013. Different parameters of SPI frequency distribution and long-term tendencies were calculated as well as spatial characteristics indicating drought and wetness propagation. Results of analysis demonstrate that during last years there is a tendency of increasing of the intensity of draught and wetness extremes over Russia. There are fewer droughts in the northern regions. The drought propagation for the European territory of Russia is decreasing in June and August, and increasing in July. The situation is opposite for the wetness tendencies. For the Asian territory of Russia, the drought propagation is significantly increasing in July along with decreasing wetness trend. Synoptic conditions favorable for the formation of wet and drought extremes were identified by comparing synoptic charts with the spatial patterns of SPI. For synoptic analysis, episodes of extremely wet (6 episodes for the APR and 7 episodes for the EPR) and drought (6 episodes for the APR and 6 for the EPR) events were classified using A. Katz' typology of weather regimes. For European part of Russia, extreme DROUGHT events are linked to the weather type named "MIXED", for Asian part of Russia - the type "CENTRAL". For European part of Russia, extreme WET events associated with "CENTRAL" type. There is a displacement of the planetary frontal zone into southward direction approximately for 5-25 degrees relatively to normal climatological position during WET extreme events linked to «EASTERN» classification type. Intercomparison of SPI calculated on the base of NOAA NCEP CPC CAMS for the same period and with the resolution 0,5 degree, month precipitation data, Era-Interim Daily fields archive for the period 1979-2014 with the resolution 0,5 degree reanalysis and observational precipitation data was done. The results of comparative analysis has been discussed.
Hurlburt Field, Florida. Revised Uniform Summary of Surface Weather Observations (RUSSWO). Parts A-F.

DTIC Science & Technology

1982-09-20

SURFACE WEATHER OBSERVATIONS 2 2 SEP W ISJRLSURT FLD FL MSC #747770 E 30 26 w o86 41 FLU ELEV 38 FT FRT PARTS A-F POR FROM HOURLY OBS: JAN 67 - DEC 70...amounts and extreme valuesl; C) Surface winds; (D) Ceiling versus Visibility; Sky Cover; ( E )-Psychrometric Summaries (daily maximum and minimum...for this station: PART A WEATHER CONDITIONS PART E DAILY MAX, MIN, & MEAN TEMP ATMOSPHERIC PHENOMENA EXTREME MAX & MIN TEMP PART I PRECIPITATION
The potential impacts of climate variability and change on health impacts of extreme weather events in the United States.

PubMed Central

Greenough, G; McGeehin, M; Bernard, S M; Trtanj, J; Riad, J; Engelberg, D

2001-01-01

Extreme weather events such as precipitation extremes and severe storms cause hundreds of deaths and injuries annually in the United States. Climate change may alter the frequency, timing, intensity, and duration of these events. Increases in heavy precipitation have occurred over the past century. Future climate scenarios show likely increases in the frequency of extreme precipitation events, including precipitation during hurricanes, raising the risk of floods. Frequencies of tornadoes and hurricanes cannot reliably be projected. Injury and death are the direct health impacts most often associated with natural disasters. Secondary effects, mediated by changes in ecologic systems and public health infrastructure, also occur. The health impacts of extreme weather events hinge on the vulnerabilities and recovery capacities of the natural environment and the local population. Relevant variables include building codes, warning systems, disaster policies, evacuation plans, and relief efforts. There are many federal, state, and local government agencies and nongovernmental organizations involved in planning for and responding to natural disasters in the United States. Future research on health impacts of extreme weather events should focus on improving climate models to project any trends in regional extreme events and as a result improve public health preparedness and mitigation. Epidemiologic studies of health effects beyond the direct impacts of disaster will provide a more accurate measure of the full health impacts and will assist in planning and resource allocation. PMID:11359686
Extreme Events in China under Climate Change: Uncertainty and related impacts (CSSP-FOREX)

NASA Astrophysics Data System (ADS)

Leckebusch, Gregor C.; Befort, Daniel J.; Hodges, Kevin I.

2016-04-01

Suitable adaptation strategies or the timely initiation of related mitigation efforts in East Asia will strongly depend on robust and comprehensive information about future near-term as well as long-term potential changes in the climate system. Therefore, understanding the driving mechanisms associated with the East Asian climate is of major importance. The FOREX project (Fostering Regional Decision Making by the Assessment of Uncertainties of Future Regional Extremes and their Linkage to Global Climate System Variability for China and East Asia) focuses on the investigation of extreme wind and rainfall related events over Eastern Asia and their possible future changes. Here, analyses focus on the link between local extreme events and their driving weather systems. This includes the coupling between local rainfall extremes and tropical cyclones, the Meiyu frontal system, extra-tropical teleconnections and monsoonal activity. Furthermore, the relation between these driving weather systems and large-scale variability modes, e.g. NAO, PDO, ENSO is analysed. Thus, beside analysing future changes of local extreme events, the temporal variability of their driving weather systems and related large-scale variability modes will be assessed in current CMIP5 global model simulations to obtain more robust results. Beyond an overview of FOREX itself, first results regarding the link between local extremes and their steering weather systems based on observational and reanalysis data are shown. Special focus is laid on the contribution of monsoonal activity, tropical cyclones and the Meiyu frontal system on the inter-annual variability of the East Asian summer rainfall.
Weather based risks and insurances for agricultural production

NASA Astrophysics Data System (ADS)

Gobin, Anne

2015-04-01

Extreme weather events such as frost, drought, heat waves and rain storms can have devastating effects on cropping systems. According to both the agriculture and finance sectors, a risk assessment of extreme weather events and their impact on cropping systems is needed. The principle of return periods or frequencies of natural hazards is adopted in many countries as the basis of eligibility for the compensation of associated losses. For adequate risk management and eligibility, hazard maps for events with a 20-year return period are often used. Damages due to extreme events are strongly dependent on crop type, crop stage, soil type and soil conditions. The impact of extreme weather events particularly during the sensitive periods of the farming calendar therefore requires a modelling approach to capture the mixture of non-linear interactions between the crop, its environment and the occurrence of the meteorological event in the farming calendar. Physically based crop models such as REGCROP (Gobin, 2010) assist in understanding the links between different factors causing crop damage. Subsequent examination of the frequency, magnitude and impacts of frost, drought, heat stress and soil moisture stress in relation to the cropping season and crop sensitive stages allows for risk profiles to be confronted with yields, yield losses and insurance claims. The methodology is demonstrated for arable food crops, bio-energy crops and fruit. The perspective of rising risk-exposure is exacerbated further by limited aid received for agricultural damage, an overall reduction of direct income support to farmers and projected intensification of weather extremes with climate change. Though average yields have risen continuously due to technological advances, there is no evidence that relative tolerance to adverse weather events has improved. The research is funded by the Belgian Science Policy Organisation (Belspo) under contract nr SD/RI/03A.
Aircraft Weather Mitigation for the Next Generation Air Transportation System

NASA Technical Reports Server (NTRS)

Stough, H. Paul, III

2007-01-01

Atmospheric effects on aviation are described by Mahapatra (1999) as including (1) atmospheric phenomena involving air motion - wind shear and turbulence; (2) hydrometeorological phenomena - rain, snow and hail; (3) aircraft icing; (4) low visibility; and (5) atmospheric electrical phenomena. Aircraft Weather Mitigation includes aircraft systems (e.g. airframe, propulsion, avionics, controls) that can be enacted (by a pilot, automation or hybrid systems) to suppress and/or prepare for the effects of encountered or unavoidable weather or to facilitate a crew operational decision-making process relative to weather. Aircraft weather mitigation can be thought of as a continuum (Figure 1) with the need to avoid all adverse weather at one extreme and the ability to safely operate in all weather conditions at the other extreme. Realistic aircraft capabilities fall somewhere between these two extremes. The capabilities of small general aviation aircraft would be expected to fall closer to the "Avoid All Adverse Weather" point, and the capabilities of large commercial jet transports would fall closer to the "Operate in All Weather Conditions" point. The ability to safely operate in adverse weather conditions is dependent upon the pilot s capabilities (training, total experience and recent experience), the airspace in which the operation is taking place (terrain, navigational aids, traffic separation), the capabilities of the airport (approach guidance, runway and taxiway lighting, availability of air traffic control), as well as the capabilities of the airplane. The level of mitigation may vary depending upon the type of adverse weather. For example, a small general aviation airplane may be equipped to operate "in the clouds" without outside visual references, but not be equipped to prevent airframe ice that could be accreted in those clouds.
Severe Weather in a Changing Climate: Getting to Adaptation

NASA Astrophysics Data System (ADS)

Wuebbles, D. J.; Janssen, E.; Kunkel, K.

2011-12-01

Analyses of observation records from U.S. weather stations indicate there is an increasing trend over recent decades in certain types of severe weather, especially large precipitation events. Widespread changes in temperature extremes have been observed over the last 50 years. In particular, the number of heat waves globally (and some parts of the U.S.) has increased, and there have been widespread increases in the numbers of warm nights. Also, analyses show that we are now breaking twice as many heat records as cold records in the U.S. Since 1957, there has been an increase in the number of historically top 1% of heavy precipitation events across the U.S. Our new analyses of the repeat or reoccurrence frequencies of large precipitation storms are showing that such events are occurring more often than in the past. The pattern of precipitation change is one of increases generally at higher northern latitudes and drying in the tropics and subtropics over land. It needs to be recognized that every weather event that happens nowadays takes place in the context of the changes in the background climate system. So nothing is entirely "natural" anymore. It's a fallacy to think that individual events are caused entirely by any one thing, either natural variation or human-induced climate change. Every event is influenced by many factors. Human-induced climate change is now a factor in weather events. The changes occurring in precipitation are consistent with the analyses of our changing climate. For extreme precipitation, we know that more precipitation is falling in very heavy events. And we know key reasons why; warmer air holds more water vapor, and so when any given weather system moves through, the extra water dumps can lead to a heavy downpour. As the climate system continues to warm, models of the Earth's climate system indicate severe precipitation events will likely become more commonplace. Water vapor will continue to increase in the atmosphere along with the warming, and large precipitation events will likely increase in intensity and frequency. In the presentation, we will not only discuss the recent trends in severe weather and the projections of the impacts of climate change on severe weather in the future, but also specific examples of how this information is being used in developing and applying adaptation policies.
Identifying Heat Waves in Florida: Considerations of Missing Weather Data

PubMed Central

Leary, Emily; Young, Linda J.; DuClos, Chris; Jordan, Melissa M.

2015-01-01

Background Using current climate models, regional-scale changes for Florida over the next 100 years are predicted to include warming over terrestrial areas and very likely increases in the number of high temperature extremes. No uniform definition of a heat wave exists. Most past research on heat waves has focused on evaluating the aftermath of known heat waves, with minimal consideration of missing exposure information. Objectives To identify and discuss methods of handling and imputing missing weather data and how those methods can affect identified periods of extreme heat in Florida. Methods In addition to ignoring missing data, temporal, spatial, and spatio-temporal models are described and utilized to impute missing historical weather data from 1973 to 2012 from 43 Florida weather monitors. Calculated thresholds are used to define periods of extreme heat across Florida. Results Modeling of missing data and imputing missing values can affect the identified periods of extreme heat, through the missing data itself or through the computed thresholds. The differences observed are related to the amount of missingness during June, July, and August, the warmest months of the warm season (April through September). Conclusions Missing data considerations are important when defining periods of extreme heat. Spatio-temporal methods are recommended for data imputation. A heat wave definition that incorporates information from all monitors is advised. PMID:26619198
Identifying Heat Waves in Florida: Considerations of Missing Weather Data.

PubMed

Leary, Emily; Young, Linda J; DuClos, Chris; Jordan, Melissa M

2015-01-01

Using current climate models, regional-scale changes for Florida over the next 100 years are predicted to include warming over terrestrial areas and very likely increases in the number of high temperature extremes. No uniform definition of a heat wave exists. Most past research on heat waves has focused on evaluating the aftermath of known heat waves, with minimal consideration of missing exposure information. To identify and discuss methods of handling and imputing missing weather data and how those methods can affect identified periods of extreme heat in Florida. In addition to ignoring missing data, temporal, spatial, and spatio-temporal models are described and utilized to impute missing historical weather data from 1973 to 2012 from 43 Florida weather monitors. Calculated thresholds are used to define periods of extreme heat across Florida. Modeling of missing data and imputing missing values can affect the identified periods of extreme heat, through the missing data itself or through the computed thresholds. The differences observed are related to the amount of missingness during June, July, and August, the warmest months of the warm season (April through September). Missing data considerations are important when defining periods of extreme heat. Spatio-temporal methods are recommended for data imputation. A heat wave definition that incorporates information from all monitors is advised.
Hypothetical scenario exercises to improve planning and readiness for drinking water quality management during extreme weather events.

PubMed

Deere, Daniel; Leusch, Frederic D L; Humpage, Andrew; Cunliffe, David; Khan, Stuart J

2017-03-15

Two hypothetical scenario exercises were designed and conducted to reflect the increasingly extreme weather-related challenges faced by water utilities as the global climate changes. The first event was based on an extreme flood scenario. The second scenario involved a combination of weather events, including a wild forest fire ('bushfire') followed by runoff due to significant rainfall. For each scenario, a panel of diverse personnel from water utilities and relevant agencies (e.g. health departments) formed a hypothetical water utility and associated regulatory body to manage water quality following the simulated extreme weather event. A larger audience participated by asking questions and contributing key insights. Participants were confronted with unanticipated developments as the simulated scenarios unfolded, introduced by a facilitator. Participants were presented with information that may have challenged their conventional experiences regarding operational procedures in order to identify limitations in current procedures, assumptions, and readily available information. The process worked toward the identification of a list of specific key lessons for each event. At the conclusion of each simulation a facilitated discussion was used to establish key lessons of value to water utilities in preparing them for similar future extreme events. Copyright © 2016 Elsevier Ltd. All rights reserved.
Assessing the Implications of Changing Extreme Value Distributions of Weather on Carbon and Water Cycling in Grasslands

NASA Astrophysics Data System (ADS)

Brunsell, N. A.; Nippert, J. B.

2011-12-01

As the climate warms, it is generally acknowledged that the number and magnitude of extreme weather events will increase. We examined an ecophysiological model's responses to precipitation and temperature anomalies in relation to the mean and variance of annual precipitation along a pronounced precipitation gradient from eastern to western Kansas. This natural gradient creates a template of potential responses for both the mean and variance of annual precipitation to compare the timescales of carbon and water fluxes. Using data from several Ameriflux sites (KZU and KFS) and a third eddy covariance tower (K4B) along the gradient, BIOME-BGC was used to characterize water and carbon cycle responses to extreme weather events. Changes in the extreme value distributions were based on SRES A1B and A2 scenarios using an ensemble mean of 21 GCMs for the region, downscaled using a stochastic weather generator. We focused on changing the timing and magnitude of precipitation and altering the diurnal and seasonal temperature ranges. Biome-BGC was then forced with daily output from the stochastic weather generator, and we examined how potential changes in these extreme value distributions impact carbon and water cycling at the sites across the Kansas precipitation gradient at time scales ranging from daily to interannual. To decompose the time scales of response, we applied a wavelet based information theory analysis approach. Results indicate impacts in soil moisture memory and carbon allocation processes, which vary in response to both the mean and variance of precipitation along the precipitation gradient. These results suggest a more pronounced focus ecosystem responses to extreme events across a range of temporal scales in order to fully characterize the water and carbon cycle responses to global climate change.

Machine learning methods for the classification of extreme rainfall and hail events

NASA Astrophysics Data System (ADS)

Teschl, Reinhard; Süsser-Rechberger, Barbara; Paulitsch, Helmut

2015-04-01

In this study, an analysis of a meteorological data set with machine learning tools is presented. The aim was to identify characteristic patterns in different sources of remote sensing data that are associated with hazards like extreme rainfall and hail. The data set originates from a project that was started in 2007 with the goal to document and mitigate hail events in the province of Styria, Austria. It consists of three dimensional weather radar data from a C-band Doppler radar, cloud top temperature information from infrared channels of a weather satellite, as well as the height of the 0° C isotherm from the forecast of the national weather service. The 3D radar dataset has a spatial resolution of 1 km x 1 km x 1 km, up to a height of 16 km above mean sea level, and a temporal resolution of 5 minutes. The infrared satellite image resolution is about 3 km x 3 km, the images are updated every 30 minutes. The study area has approx. 16,000 square kilometers. So far, different criteria for the occurrence of hail (and its discrimination from heavy rain) have been found and are documented in the literature. When applying these criteria to our data and contrasting them with damage reports from an insurance company, a need for adaption was identified. Here we are using supervised learning paradigms to find tailored relationships for the study area, validated by a sub-dataset that was not involved in the training process.
77 FR 74788 - Long-Term Cooling and Unattended Water Makeup of Spent Fuel Pools

Federal Register 2010, 2011, 2012, 2013, 2014

2012-12-18

... frequency estimate of 1 in 100 years (1E-2/yr) for extreme space weather/ geomagnetic disturbance to perform... Accidents B. Geomagnetic Storms and Effects on the Earth C. Frequency of Geomagnetic Storms With Potential... commercial electric power grids are vulnerable to prolonged outage caused by extreme space weather, such as...
Numerical tools to predict the environmental loads for offshore structures under extreme weather conditions

NASA Astrophysics Data System (ADS)

Wu, Yanling

2018-05-01

In this paper, the extreme waves were generated using the open source computational fluid dynamic (CFD) tools — OpenFOAM and Waves2FOAM — using linear and nonlinear NewWave input. They were used to conduct the numerical simulation of the wave impact process. Numerical tools based on first-order (with and without stretching) and second-order NewWave are investigated. The simulation to predict force loading for the offshore platform under the extreme weather condition is implemented and compared.
Regional Climate Change and Development of Public Health Decision Aids

NASA Astrophysics Data System (ADS)

Hegedus, A. M.; Darmenova, K.; Grant, F.; Kiley, H.; Higgins, G. J.; Apling, D.

2011-12-01

According to the World Heath Organization (WHO) climate change is a significant and emerging threat to public health, and changes the way we must look at protecting vulnerable populations. Worldwide, the occurrence of some diseases and other threats to human health depend predominantly on local climate patterns. Rising average temperatures, in combination with changing rainfall patterns and humidity levels, alter the lifecycle and regional distribution of certain disease-carrying vectors, such as mosquitoes, ticks and rodents. In addition, higher surface temperatures will bring heat waves and heat stress to urban regions worldwide and will likely increase heat-related health risks. A growing body of scientific evidence also suggests an increase in extreme weather events such as floods, droughts and hurricanes that can be destructive to human health and well-being. Therefore, climate adaptation and health decision aids are urgently needed by city planners and health officials to determine high risk areas, evaluate vulnerable populations and develop public health infrastructure and surveillance systems. To address current deficiencies in local planning and decision making with respect to regional climate change and its effect on human health, our research is focused on performing a dynamical downscaling with the Weather Research and Forecasting (WRF) model to develop decision aids that translate the regional climate data into actionable information for users. WRF model is initialized with the Max Planck Institute European Center/Hamburg Model version 5 (ECHAM5) General Circulation Model simulations forced with the Special Report on Emissions (SRES) A1B emissions scenario. Our methodology involves development of climatological indices of extreme weather, quantifying the risk of occurrence of water/rodent/vector-borne diseases as well as developing various heat stress related decision aids. Our results indicate that the downscale simulations provide the necessary detailed output required by state and local governments and the private sector to develop climate adaptation plans with respect to human health.
360 deg Camera Head for Unmanned Sea Surface Vehicles

NASA Technical Reports Server (NTRS)

Townsend, Julie A.; Kulczycki, Eric A.; Willson, Reginald G.; Huntsberger, Terrance L.; Garrett, Michael S.; Trebi-Ollennu, Ashitey; Bergh, Charles F.

2012-01-01

The 360 camera head consists of a set of six color cameras arranged in a circular pattern such that their overlapping fields of view give a full 360 view of the immediate surroundings. The cameras are enclosed in a watertight container along with support electronics and a power distribution system. Each camera views the world through a watertight porthole. To prevent overheating or condensation in extreme weather conditions, the watertight container is also equipped with an electrical cooling unit and a pair of internal fans for circulation.
Assessing the vulnerability of the transportation industry of Ukraine to future climate change

NASA Astrophysics Data System (ADS)

Khomenko, Inna

2017-04-01

Climate change will affect transportation primarily through increases in several types of weather and climate extremes. The impacts will vary by mode of transportation and region of the country, but they will be widespread and costly in both human and economic terms and will require significant changes in the planning, design, construction, operation, and maintenance of transportation systems. In the study impact of climate change on operation of road transport are analysed on the basis of RCP 4.5 and RCP 8.5 scenarios. Data contains series of daily mean, maximum and minimum temperature, daily liquid (or mixed) and solid precipitation, daily mean relative humidity and daily mean and maximum wind speed, obtained for the period of 2011 to 2050 for 28 cities distributed evenly across Ukraine. Spatial and temporal distributions of meteorological variables are obtained. The statistic characteristics obtained were compared with the correspondent climate normals and highway-related temporal changeability is determined. Frequency of freezing rain, wet snow, very hot days, droughts, fogs, ice-covered ground, slippery wet ground, ice and snow slippery coat are investigated. Climate and economic risks to the road transport network are assessed. Maps of spatial distribution of risk assessment are obtained. The results obtained show typical weather pattern is changed and climate and weather extreme influencing on operation of road transport are more frequent for the both scenarios, but for the RCP 8.5 scenario hazard weather occurs more often. During the period of 2011-2050 significant climate warming (by 2-3°C) is registered. Extreme temperatures are observed more frequently. High temperatures bring on growth in frequency of wildfires and heat waves. Annual precipitation amount decreases, except the western mountain and northern regions, where precipitation amount increase on 35%. Increase in temperature and decrease in precipitation can produce droughts in southern, eastern and central regions. But growth in precipitation in mountain region can cause flooding and landslides. Strong increase in mixed precipitation and significant reduction in ice and liquid precipitation take place for all territory of Ukraine. In the southern region ice precipitation is virtually vanished and observed only 2-3 days per year. Growth of mixed precipitation causes increase in severe weather events such as freezing precipitation, ice-covered ground and snow slippery coat.
Historical Time Series of Extreme Convective Weather in Finland

NASA Astrophysics Data System (ADS)

Laurila, T. K.; Mäkelä, A.; Rauhala, J.; Olsson, T.; Jylhä, K.

2016-12-01

Thunderstorms, lightning, tornadoes, downbursts, large hail and heavy precipitation are well-known for their impacts to human life. In the high latitudes as in Finland, these hazardous warm season convective weather events are focused in the summer season, roughly from May to September with peak in the midsummer. The position of Finland between the maritime Atlantic and the continental Asian climate zones makes possible large variability in weather in general which reflects also to the occurrence of severe weather; the hot, moist and extremely unstable air masses sometimes reach Finland and makes possible for the occurrence of extreme and devastating weather events. Compared to lower latitudes, the Finnish climate of severe convection is "moderate" and contains a large year-to-year variation; however, behind the modest annual average is hidden the climate of severe weather events that practically every year cause large economical losses and sometimes even losses of life. Because of the increased vulnerability of our modern society, these episodes have gained recently plenty of interest. During the decades, the Finnish Meteorological Institute (FMI) has collected observations and damage descriptions of severe weather episodes in Finland; thunderstorm days (1887-present), annual number of lightning flashes (1960-present), tornados (1796-present), large hail (1930-present), heavy rainfall (1922-present). The research findings show e.g. that a severe weather event may occur practically anywhere in the country, although in general the probability of occurrence is smaller in the Northern Finland. This study, funded by the Finnish Research Programme on Nuclear Power Plant Safety (SAFIR), combines the individual Finnish severe weather time series' and examines their trends, cross-correlation and correlations with other atmospheric parameters. Furthermore, a numerical weather model (HARMONIE) simulation is performed for a historical severe weather case for analyzing how well the present state-of-the-art models grasp these small-scale weather phenomena. Our results give important background for estimating the Finnish severe weather climate in the future.
The hydrometeorological implications of zoning laws: Can land use regulations of urban density and sprawl improve a city's resilience?

NASA Astrophysics Data System (ADS)

Bou-Zeid, E.; Ryu, Y. H.; Smith, J. A.; Newburn, D. A.

2015-12-01

The intensification of heat waves and of the hydrological cycle due to global climate change pose particularly high risks to urban residents. Cities are already hotter than their surroundings due to the urban heat island effect and are known to result in local intensification of rainfall and flooding due to their coupled impacts on the surface and the lower atmosphere. These interacting local and global changes can adversely affect the health and well being of urban residents, and city administrators are increasing efforts to mitigate and adapt to the potential disruptions though various infrastructure and preparedness programs. However, as cities worldwide continue to expand, a key decision is how to manage that urban sprawl and regulate its spatial features to aid in the mitigation and adaptation effort. This study assesses whether alternative zoning regulations that modify the density and extent of a metropolitan region, but have a minimal impact on total population and demographic growth, have an appreciable impact on its response to extreme weather events, and as such, whether they can be used to increase urban resilience. We consider Baltimore (the city and its surrounding suburbs), which in 1967 adopted one of the first urban growth boundaries (UGBs) in the United States, as our test case. Departing from the urban extent circa 1900, we create alternative land use patterns that, compared to the actual current land use baseline, would have resulted from drastically different policy scenarios and approaches to zoning that the city would have undertaken. We consider various alternatives where the city is smaller and denser, due to stricter regulation, versus larger and less dense than the actual baseline, while maintaining the same total population. Our findings indicate that lower densities have significant benefits: compared to the current landscape and to denser patterns, they reduce both extreme temperatures during heat waves and spatio-temporal rainfall peaks. While the particular findings hold for Baltimore and many cities with comparable climates, the conclusion that zoning laws and the resulting spatial patterns for urban density have important implications on a city's response to changing climate and extreme weather are more broadly applicable.
A methodology to leverage cross-sectional accelerometry to capture weather's influence in active living research.

PubMed

Katapally, Tarun R; Rainham, Daniel; Muhajarine, Nazeem

2016-06-27

While active living interventions focus on modifying urban design and built environment, weather variation, a phenomenon that perennially interacts with these environmental factors, is consistently underexplored. This study's objective is to develop a methodology to link weather data with existing cross-sectional accelerometry data in capturing weather variation. Saskatoon's neighbourhoods were classified into grid-pattern, fractured grid-pattern and curvilinear neighbourhoods. Thereafter, 137 Actical accelerometers were used to derive moderate to vigorous physical activity (MVPA) and sedentary behaviour (SB) data from 455 children in 25 sequential one-week cycles between April and June, 2010. This sequential deployment was necessary to overcome the difference in the ratio between the sample size and the number of accelerometers. A data linkage methodology was developed, where each accelerometry cycle was matched with localized (Saskatoon-specific) weather patterns derived from Environment Canada. Statistical analyses were conducted to depict the influence of urban design on MVPA and SB after factoring in localized weather patterns. Integration of cross-sectional accelerometry with localized weather patterns allowed the capture of weather variation during a single seasonal transition. Overall, during the transition from spring to summer in Saskatoon, MVPA increased and SB decreased during warmer days. After factoring in localized weather, a recurring observation was that children residing in fractured grid-pattern neighbourhoods accumulated significantly lower MVPA and higher SB. The proposed methodology could be utilized to link globally available cross-sectional accelerometry data with place-specific weather data to understand how built and social environmental factors interact with varying weather patterns in influencing active living.
Revisiting the 1993 historical extreme precipitation and damaging flood event in Central Nepal

NASA Astrophysics Data System (ADS)

Marahatta, S.; Adhikari, L.; Pokharel, B.

2017-12-01

Nepal is ranked the fourth most climate-vulnerable country in the world and it is prone to different weather-related hazards including droughts, floods, and landslides [Wang et al., 2013; Gillies et al., 2013]. Although extremely vulnerable to extreme weather events, there are no extreme weather warning system established to inform public in Nepal. Nepal has witnessed frequent drought and flood events, however, the extreme precipitation that occurred on 19-20 July 1993 created a devastating flood and landslide making it the worst weather disaster in the history of Nepal. During the second week of July, Nepal and northern India experienced abnormal dry condition due to the shifting of the monsoon trough to central India. The dry weather changed to wet when monsoon trough moved northward towards foothills of the Himalayas. Around the same period, a low pressure center was located over the south-central Nepal. The surface low was supported by the mid-, upper-level shortwave and cyclonic vorticity. A meso-scale convective system created record breaking one day rainfall (540 mm) in the region. The torrential rain impacted the major hydropower reservoir, Bagmati barrage in Karmaiya and triggered many landslides and flash floods. The region had the largest hydropower (Kulekhani hydropower, 92 MW) of the country at that time and the storm event deposited extremely large amount of sediments that reduced one-fourth (4.8 million m3) of reservoir dead storage (12 million m3). The 1-in-1000 years flood damaged the newly constructed barrage and took more than 700 lives. Major highways were damaged cutting off supply of daily needed goods, including food and gas, in the capital city, Kathmandu, for more than a month. In this presentation, the meteorological conditions of the extreme event will be diagnosed and the impact of the sedimentation due to the flood on Kulekhani reservoir and hydropower generation will be discussed.
Adverse weather impacts on arable cropping systems

NASA Astrophysics Data System (ADS)

Gobin, Anne

2016-04-01

Damages due to extreme or adverse weather strongly depend on crop type, crop stage, soil conditions and management. The impact is largest during the sensitive periods of the farming calendar, and requires a modelling approach to capture the interactions between the crop, its environment and the occurrence of the meteorological event. The hypothesis is that extreme and adverse weather events can be quantified and subsequently incorporated in current crop models. Since crop development is driven by thermal time and photoperiod, a regional crop model was used to examine the likely frequency, magnitude and impacts of frost, drought, heat stress and waterlogging in relation to the cropping season and crop sensitive stages. Risk profiles and associated return levels were obtained by fitting generalized extreme value distributions to block maxima for air humidity, water balance and temperature variables. The risk profiles were subsequently confronted with yields and yield losses for the major arable crops in Belgium, notably winter wheat, winter barley, winter oilseed rape, sugar beet, potato and maize at the field (farm records) to regional scale (statistics). The average daily vapour pressure deficit (VPD) and reference evapotranspiration (ET0) during the growing season is significantly lower (p < 0.001) and has a higher variability before 1988 than after 1988. Distribution patterns of VPD and ET0 have relevant impacts on crop yields. The response to rising temperatures depends on the crop's capability to condition its microenvironment. Crops short of water close their stomata, lose their evaporative cooling potential and ultimately become susceptible to heat stress. Effects of heat stress therefore have to be combined with moisture availability such as the precipitation deficit or the soil water balance. Risks of combined heat and moisture deficit stress appear during the summer. These risks are subsequently related to crop damage. The methodology of defining meteorological risks and subsequently relating the risk to the cropping calendar will be demonstrated for major arable crops in Belgium. Physically based crop models assist in understanding the links between adverse weather events, sensitive crop stages and crop damage. Financial support was obtained from Belspo under research contract SD/RI/03A.
NASA GSFC's Role in the US Space Program

NASA Technical Reports Server (NTRS)

Simpson, James E.

2004-01-01

The paper discussss the GSFC research interests and how GSFC contributes to solve some of most basic questions Humans having been asking for thousands of years. How big is universe? How old is the universe? Will Humans and industrialization of the Earth change the climate significantly? Can Humans live in space? How does the Sun affect life on Earth? Goddard s role in Earth Science is very unique. We buy and build instruments that collect data about weather around the world. By flying those instruments on spacecraft, we have a unique vantage point to observe the weather patterns on a global scale. The best example is a satellite network called GOES (Geostationary Operational Environmental Satellite) which produces the weather pictures and videos you see on the nightly news and weather channel. Earth Science is another area of great interest to Goddard scientists and spacecraft designers. This photo of an oil fire in Iraq taken on March 2Ist of this year shows the down range effect pollution will have on entire region. Space Weather has become extremely important in the Space business. Satellites not only can become inoperable due to the occasional high level of radiation but astronauts can be exposed to dangerous levels of radiation. Space Weather is actually an issue when planning Extra Vehicular Activities (EVA). At Goddard, our operation of the Hubble Space Telescope has meant we have worked closely with several Shuttle crews over the years.
The Major Solar Eruptive Event in July 2012: Defining Extreme Space Weather Scenarios (Invited)

NASA Astrophysics Data System (ADS)

Baker, D. N.

2013-12-01

A key goal for the space weather community is to define extreme conditions that might plausibly afflict human technology. On 23 July 2012 solar active region 1520 (~133°W heliographic longitude) gave rise to a powerful coronal mass ejection (CME) with an initial speed that was determined to be >3000 km/s. The eruption was directed away from Earth toward 144°W longitude. STEREO-A sensors detected the CME arrival only about 18 hours later and made in situ measurements of the solar wind and interplanetary magnetic field. We have posed the question of what would have happened if this huge interplanetary event had been Earthward directed. Using a well-proven geomagnetic storm forecast model, we find that the 23-24 July event would certainly have produced a geomagnetic storm that was comparable to the largest events of the 20th Century (Dst ~ -500nT). Using plausible assumptions about seasonal and time-of-day orientation of the Earth's magnetic dipole, the most extreme modeled value of storm-time disturbance would have been Dst=-1182nT. This is probably considerably larger than the famous Carrington storm of 1859. This finding has far reaching implications because it demonstrates that extreme space weather conditions such as those during March of 1989 or September of 1859 can happen even during a modest solar activity cycle such as the one presently underway. We argue that this extreme event should immediately be employed by the space weather community to model severe space weather effects on technological systems such as the electric power grid.
MESSENGER Observations of Extreme Space Weather in Mercury's Magnetosphere

NASA Astrophysics Data System (ADS)

Slavin, J. A.

2013-09-01

Increasing activity on the Sun is allowing MESSENGER to make its first observations of Mercury's magnetosphere under extreme solar wind conditions. At Earth interplanetary shock waves and coronal mass ejections produce severe "space weather" in the form of large geomagnetic storms that affect telecommunications, space systems, and ground-based power grids. In the case of Mercury the primary effect of extreme space weather in on the degree to which this it's weak global magnetic field can shield the planet from the solar wind. Direct impact of the solar wind on the surface of airless bodies like Mercury results in space weathering of the regolith and the sputtering of atomic species like sodium and calcium to high altitudes where they contribute to a tenuous, but highly dynamic exosphere. MESSENGER observations indicate that during extreme interplanetary conditions the solar wind plasma gains access to the surface of Mercury through three main regions: 1. The magnetospheric cusps, which fill with energized solar wind and planetary ions; 2. The subsolar magnetopause, which is compressed and eroded by reconnection to very low altitudes where the natural gyro-motion of solar wind protons may result in their impact on the surface; 3. The magnetotail where hot plasma sheet ions rapidly convect sunward to impact the surface on the nightside of Mercury. The possible implications of these new MESSENGER observations for our ability to predict space weather at Earth and other planets will be described.
Modeling Future Fire danger over North America in a Changing Climate

NASA Astrophysics Data System (ADS)

Jain, P.; Paimazumder, D.; Done, J.; Flannigan, M.

2016-12-01

Fire danger ratings are used to determine wildfire potential due to weather and climate factors. The Fire Weather Index (FWI), part of the Canadian Forest Fire Danger Rating System (CFFDRS), incorporates temperature, relative humidity, windspeed and precipitation to give a daily fire danger rating that is used by wildfire management agencies in an operational context. Studies using GCM output have shown that future wildfire danger will increase in a warming climate. However, these studies are somewhat limited by the coarse spatial resolution (typically 100-400km) and temporal resolution (typically 6-hourly to monthly) of the model output. Future wildfire potential over North America based on FWI is calculated using output from the Weather, Research and Forecasting (WRF) model, which is used to downscale future climate scenarios from the bias-corrected Community Climate System Model (CCSM) under RCP8.5 scenarios at a spatial resolution of 36km. We consider five eleven year time slices: 1990-2000, 2020-2030, 2030-2040, 2050-2060 and 2080-2090. The dynamically downscaled simulation improves determination of future extreme weather by improving both spatial and temporal resolution over most GCM models. To characterize extreme fire weather we calculate annual numbers of spread days (days for which FWI > 19) and annual 99th percentile of FWI. Additionally, an extreme value analysis based on the peaks-over-threshold method allows us to calculate the return values for extreme FWI values.
Restoring surface fire stabilizes forest carbon under extreme fire weather in the Sierra Nevada

Treesearch

Daniel J. Krofcheck; Matthew D. Hurteau; Robert M. Scheller; E. Louise Loudermilk

2017-01-01

Climate change in the western United States has increased the frequency of extreme fire weather events and is projected to increase the area burned by wildfire in the coming decades. This changing fire regime, coupled with increased high-severity fire risk from a legacy of fire exclusion, could destabilize forest carbon (C), decrease net ecosystem exchange (...
Quantifying the daily economic impact of extreme space weather due to failure in electricity transmission infrastructure

NASA Astrophysics Data System (ADS)

Oughton, Edward J.; Skelton, Andrew; Horne, Richard B.; Thomson, Alan W. P.; Gaunt, Charles T.

2017-01-01

Extreme space weather due to coronal mass ejections has the potential to cause considerable disruption to the global economy by damaging the transformers required to operate electricity transmission infrastructure. However, expert opinion is split between the potential outcome being one of a temporary regional blackout and of a more prolonged event. The temporary blackout scenario proposed by some is expected to last the length of the disturbance, with normal operations resuming after a couple of days. On the other hand, others have predicted widespread equipment damage with blackout scenarios lasting months. In this paper we explore the potential costs associated with failure in the electricity transmission infrastructure in the U.S. due to extreme space weather, focusing on daily economic loss. This provides insight into the direct and indirect economic consequences of how an extreme space weather event may affect domestic production, as well as other nations, via supply chain linkages. By exploring the sensitivity of the blackout zone, we show that on average the direct economic cost incurred from disruption to electricity represents only 49% of the total potential macroeconomic cost. Therefore, if indirect supply chain costs are not considered when undertaking cost-benefit analysis of space weather forecasting and mitigation investment, the total potential macroeconomic cost is not correctly represented. The paper contributes to our understanding of the economic impact of space weather, as well as making a number of key methodological contributions relevant for future work. Further economic impact assessment of this threat must consider multiday, multiregional events.
Framing Extreme Event Attribution from the Bottom up - an Enquiry into the Social Representations of key stakeholders, of the Press and of Climate Scientists.

NASA Astrophysics Data System (ADS)

Vanderlinden, J. P.; Fellmer, M.; Capellini, N.; Meinke, I.; Remvikos, Y.; Bray, D.; Pacteau, C.; Von Storch, H.

2014-12-01

Attribution of extreme weather events has recently generated a lot of interest simultaneously within the general public, the scientific community, and stakeholders affected by meteorological extremes. This interest calls for the need to explore the potential convergence of the current atttribution science with the desire and needs of stakeholders. Such an euiry contributes to the development of climate services aiming at quantifying the human responsibility for particular events. Through interviews with climate scientists, through the analysis of the press coverage of extreme meteorological events, and through stakeholder (private sector, covernment services and local and regional government) focus groups, we analyze how social representations of the concepts associated with extreme event attribution are theorized. From the corpuses generated in the course of this enquiry, we build up a grounded, bottom-up, theorization of extreme weather event attribution. This bottom-up theorization allows for a framing of the potential climate services in a way that is attuned to the needs and expectations of the stakeholders. From apparently simple formulations: "what is an extreme event?", "what makes it extreme?", "what is meant by attribution of extreme weather events?", "what do we want to attribute?", "what is a climate service?", we demonstrate the polysemy of these terms and propose ways to address the challenges associated with the juxtaposition of four highly loaded concepts: extreme - event - attribution - climate services.
Investigation of the 2006 Drought and 2007 Flood Extremes at the Southern Great Plains Through an Integrative Analysis of Observations

NASA Technical Reports Server (NTRS)

Dong, Xiquan; Xi, Baike; Kennedy, Aaron; Feng, Zhe; Entin, Jared K.; Houser, Paul R.; Schiffer, Robert A.; LEucyer, Tristan; Olson, William S.; Hsu, Kuo-lin;

2010-01-01

Hydrological years 2006 (HY06, 10/2005-09/2006) and 2007 (HY07, 10/2006-09/2007) provide a unique opportunity to examine hydrological extremes in the central US because there are no other examples of two such highly contrasting precipitation extremes occurring in consecutive years at the Southern Great Plains (SGP) in recorded history. The HY06 annual precipitation in the state of Oklahoma, as observed by the Oklahoma Mesonet, is around 61% of the normal (92.84 cm, based on the 1921-2008 climatology), which results in HY06 the second-driest year in the record. In particular, the total precipitation during the winter of 2005-06 is only 27% of the normal, and this winter ranks as the driest season. On the other hand, the HY07 annual precipitation amount is 121% of the normal and HY07 ranks as the seventh-wettest year for the entire state and the wettest year for the central region of the state. Summer 2007 is the second-wettest season for the state. Large-scale dynamics play a key role in these extreme events. During the extreme dry period (10/2005-02/2006), a dipole pattern in the 500-hPa GH anomaly existed where an anomalous high was over the southwestern U.S. region and an anomalous low was over the Great Lakes. This pattern is associated with inhibited moisture transport from the Gulf of Mexico and strong sinking motion over the SGP, both contributing to the extreme dryness. The precipitation deficit over the SGP during the extreme dry period is clearly linked to significantly suppressed cyclonic activity over the southwestern U.S., which shows robust relationship with the Western Pacific (WP) teleconnection pattern. The precipitation events during the extreme wet period (May-July 2007) were initially generated by active synoptic weather patterns, linked with moisture transport from the Gulf of Mexico by the northward low level jet, and enhanced by the mesoscale convective systems. Although the drought and pluvial conditions are dominated by large-scale dynamic patterns, we have demonstrated that the two positive feedback processes during the extreme dry and wet periods found in this study play a key role to maintain and reinforce the length and severity of existing drought and flood events. For example, during the extreme dry period, with less clouds, LWP, PWV, precipitation, and thinner Cu cloud thickness, more net radiation was absorbed and used to evaporate water from the ground. The evaporated moisture, however, was removed by low-level divergence. Thus, with less precipitation and removed atmospheric moisture, more absorbed incoming solar radiation was used to increase surface temperature and to make the ground drier.

Managing the risks of extreme events and disasters to advance climate change adaptation. Special report of the Intergovernmental Panel on Climate Change (IPCC)

DOE Office of Scientific and Technical Information (OSTI.GOV)

Field, C.B.; Barros, V.; Stocker, T.F.

2012-07-01

This Special Report on Managing the Risks of Extreme Events and Disasters to Advance Climate Change Adaptation (SREX) has been jointly coordinated by Working Groups I (WGI) and II (WGII) of the Intergovernmental Panel on Climate Change (IPCC). The report focuses on the relationship between climate change and extreme weather and climate events, the impacts of such events, and the strategies to manage the associated risks. This Special Report, in particular, contributes to frame the challenge of dealing with extreme weather and climate events as an issue in decision making under uncertainty, analyzing response in the context of risk management.more » The report consists of nine chapters, covering risk management; observed and projected changes in extreme weather and climate events; exposure and vulnerability to as well as losses resulting from such events; adaptation options from the local to the international scale; the role of sustainable development in modulating risks; and insights from specific case studies. (LN)« less

Butterflies, Black swans and Dragon kings: How to use the Dynamical Systems Theory to build a "zoology" of mid-latitude circulation atmospheric extremes?

NASA Astrophysics Data System (ADS)

Faranda, D.; Yiou, P.; Alvarez-Castro, M. C. M.

2015-12-01

A combination of dynamical systems and statistical techniques allows for a robust assessment of the dynamical properties of the mid-latitude atmospheric circulation. Extremes at different spatial and time scales are not only associated to exceptionally intense weather structures (e.g. extra-tropical cyclones) but also to rapid changes of circulation regimes (thunderstorms, supercells) or the extreme persistence of weather structure (heat waves, cold spells). We will show how the dynamical systems theory of recurrence combined to the extreme value theory can take into account the spatial and temporal dependence structure of the mid-latitude circulation structures and provide information on the statistics of extreme events.
Climate Change in the Pacific Islands

NASA Astrophysics Data System (ADS)

Hamnett, Michael P.

Climate change have been a major concern among Pacific Islanders since the late 1990s. During that period, Time Magazine featured a cover story that read: Say Goodbye to the Marshall Islands, Kiribati, and Tuvalu from sea level rise. Since that time, the South Pacific Regional Environment Programme, UN and government agencies and academic researchers have been assessing the impacts of long-term climate change and seasonal to inter-annual climate variability on the Pacific Islands. The consensus is that long-term climate change will result in more extreme weather and tidal events including droughts, floods, tropical cyclones, coastal erosion, and salt water inundation. Extreme weather events already occur in the Pacific Islands and they are patterned. El Niño Southern Oscillation (ENSO) events impact rainfall, tropical cyclone and tidal patterns. In 2000, the first National Assessment of the Consequences of Climate Variability and Change concluded that long-term climate change will result in more El Niño events or a more El Niño like climate every year. The bad news is that will mean more natural disasters. The good news is that El Niño events can be predicted and people can prepare for them. The reallly bad news is that some Pacific Islands are already becoming uninhabitable because of erosion of land or the loss of fresh water from droughts and salt water intrusion. Many of the most vulnerable countries already overseas populations in New Zealand, the US, or larger Pacific Island countries. For some Pacific Islander abandoning their home countries will be their only option.
Patterns in Patient Access and Utilization of Online Medical Records: Analysis of MyChart

PubMed Central

2018-01-01

Background Electronic patient portals provide a new method for sharing personal medical information with individual patients. Objective Our aim was to review utilization patterns of the largest online patient portal in Canada's largest city. Methods We conducted a 4-year time-trend analysis of aggregated anonymous utilization data of the MyChart patient portal at Sunnybrook Health Sciences Centre in Ontario, Canada, from January 1, 2012, through December 31, 2015. Prespecified analyses examined trends related to day (weekend vs weekday), season (July vs January), year (2012 vs 2015), and an extreme adverse weather event (ice storm of December 20-26, 2013). Primary endpoints included three measures of patient portal activity: registrations, logins, and pageviews. Results We identified 32,325 patients who registered for a MyChart account during the study interval. Time-trend analysis showed no sign of attenuating registrations over time. Logins were frequent, averaged 734 total per day, and showed an increasing trend over time. Pageviews mirrored logins, averaged about 3029 total per day, and equated to about 5 pageviews during the average login. The most popular pageviews were clinical notes, followed by laboratory results and medical imaging reports. All measures of patient activity were lower on weekends compared to weekdays (P<.001) yet showed no significant changes related to seasons or extreme weather. No major security breach, malware attack, or software failure occurred during the study. Conclusions Online patient portals can provide a popular and reliable system for distributing personal medical information to active patients and may merit consideration for hospitals. PMID:29410386
Climate, Waterborne Disease, and Public Health in Eastern Russia

NASA Astrophysics Data System (ADS)

Tirrell, Andrew

2013-04-01

As global temperatures rise, waterborne diseases have expanded their ranges northward. Exposure to new diseases is especially threatening to isolated communities, whose remote locations and lack of health resources and infrastructure leave them particularly vulnerable. For this project, a time series analysis of existing data will be used to assess temporal and spatial associations between long-term, seasonal and short-term weather variability, and waterborne infectious diseases in several Siberian communities. Building on these associations, we will generate estimates of future changes in infectious disease patterns based upon existing forecasts of climate change and likely increases in extreme weather events in eastern Russia. Finally, we will contemplate the public health implications of these findings and offer appropriate policy recommendations. One of our policy aims will be to identify easily measured water quality indicators that may serve as useful proxies for environmental health in rural, especially indigenous, communities.
Flow Down! Can managing forests help maintain water supplies in the face of climate change?

Treesearch

Stephanie Laseter; Chelcy Miniat; James Vose

2014-01-01

Climate change can have a direct and indirect impacts on water resources. Direct impacts of climate change can be seen by the presence of more extreme weather events. Extreme weather events include things like heat waves and droughts. Droughts have a direct impact on water and water supply. The indirect impacts of climate change on water resources relate to temperature...
Fingerprint and weathering characteristics of stranded oils after the Hebei Spirit oil spill.

PubMed

Yim, Un Hyuk; Ha, Sung Yong; An, Joon Geon; Won, Jong Ho; Han, Gi Myung; Hong, Sang Hee; Kim, Moonkoo; Jung, Jee-Hyun; Shim, Won Joon

2011-12-15

After the Hebei Spirit oil spill in December 2007, mixtures of three types of Middle East crude oil were stranded along 375 km of coastline in Western Korea. Stranded oils were monitored for their identity and weathering status in 19 stations in three provinces. The results obtained using a weathering model indicated that evaporation would be a dominant weathering process immediately after the spill and the sequential changes of chemical composition in the field verified this prediction positively. In the early stages of weathering, the half-life of spilled oil was calculated to be 2.6 months. Tiered fingerprinting approaches identified background contamination and confirmed the identity of the stranded oils with the spill source. Double ratios using alkylated phenanthrenes and dibenzothiophenes in samples after the spill clearly reveal the impact of weathering on oil. However, to derive defensible fingerprinting for source identification and allocation, recalcitrant biomarkers are extremely useful. Weathering status of the stranded oils was evaluated using composition profiles of saturated hydrocarbons, polycyclic aromatic hydrocarbons and various weathering indices. Most samples collected 8 months after the spill were categorized in either the advanced or extreme weathering states. Gradual increase in toxic components in the residual oil through weathering emphasizes the need for adaptive ecotoxicological approaches. Copyright © 2011 Elsevier B.V. All rights reserved.
Forest bat population dynamics over 14 years at a climate refuge: Effects of timber harvesting and weather extremes.

PubMed

Law, Bradley S; Chidel, Mark; Law, Peter R

2018-01-01

Long-term data are needed to explore the interaction of weather extremes with habitat alteration; in particular, can 'refugia' buffer population dynamics against climate change and are they robust to disturbances such as timber harvesting. Because forest bats are good indicators of ecosystem health, we used 14 years (1999-2012) of mark-recapture data from a suite of small tree-hollow roosting bats to estimate survival, abundance and body condition in harvested and unharvested forest and over extreme El Niño and La Niña weather events in southeastern Australia. Trapping was replicated within an experimental forest, located in a climate refuge, with different timber harvesting treatments. We trapped foraging bats and banded 3043 with a 32% retrap rate. Mark-recapture analyses allowed for dependence of survival on time, species, sex, logging treatment and for transients. A large portion of the population remained resident, with a maximum time to recapture of nine years. The effect of logging history (unlogged vs 16-30 years post-logging regrowth) on apparent survival was minor and species specific, with no detectable effect for two species, a positive effect for one and negative for the other. There was no effect of logging history on abundance or body condition for any of these species. Apparent survival of residents was not strongly influenced by weather variation (except for the smallest species), unlike previous studies outside of refugia. Despite annual variation in abundance and body condition across the 14 years of the study, no relationship with extreme weather was evident. The location of our study area in a climate refuge potentially buffered bat population dynamics from extreme weather. These results support the value of climate refugia in mitigating climate change impacts, though the lack of an external control highlights the need for further studies on the functioning of climate refugia. Relatively stable population dynamics were not compromised by timber harvesting, suggesting ecologically sustainable harvesting may be compatible with climate refugia.
Fifty Years of Space Weather Forecasting from Boulder

NASA Astrophysics Data System (ADS)

Berger, T. E.

2015-12-01

The first official space weather forecast was issued by the Space Disturbances Laboratory in Boulder, Colorado, in 1965, ushering in an era of operational prediction that continues to this day. Today, the National Oceanic and Atmospheric Administration (NOAA) charters the Space Weather Prediction Center (SWPC) as one of the nine National Centers for Environmental Prediction (NCEP) to provide the nation's official watches, warnings, and alerts of space weather phenomena. SWPC is now integral to national and international efforts to predict space weather events, from the common and mild, to the rare and extreme, that can impact critical technological infrastructure. In 2012, the Strategic National Risk Assessment included extreme space weather events as low-to-medium probability phenomena that could, unlike any other meteorogical phenomena, have an impact on the government's ability to function. Recognizing this, the White House chartered the Office of Science and Technology Policy (OSTP) to produce the first comprehensive national strategy for the prediction, mitigation, and response to an extreme space weather event. The implementation of the National Strategy is ongoing with NOAA, its partners, and stakeholders concentrating on the goal of improving our ability to observe, model, and predict the onset and severity of space weather events. In addition, work continues with the research community to improve our understanding of the physical mechanisms - on the Sun, in the heliosphere, and in the Earth's magnetic field and upper atmosphere - of space weather as well as the effects on critical infrastructure such as electrical power transmission systems. In fifty years, people will hopefully look back at the history of operational space weather prediction and credit our efforts today with solidifying the necessary developments in observational systems, full-physics models of the entire Sun-Earth system, and tools for predicting the impacts to infrastructure to protect against any and all forms of space weather.
Weather extremes in very large, high-resolution ensembles: the weatherathome experiment

NASA Astrophysics Data System (ADS)

Allen, M. R.; Rosier, S.; Massey, N.; Rye, C.; Bowery, A.; Miller, J.; Otto, F.; Jones, R.; Wilson, S.; Mote, P.; Stone, D. A.; Yamazaki, Y. H.; Carrington, D.

2011-12-01

Resolution and ensemble size are often seen as alternatives in climate modelling. Models with sufficient resolution to simulate many classes of extreme weather cannot normally be run often enough to assess the statistics of rare events, still less how these statistics may be changing. As a result, assessments of the impact of external forcing on regional climate extremes must be based either on statistical downscaling from relatively coarse-resolution models, or statistical extrapolation from 10-year to 100-year events. Under the weatherathome experiment, part of the climateprediction.net initiative, we have compiled the Met Office Regional Climate Model HadRM3P to run on personal computer volunteered by the general public at 25 and 50km resolution, embedded within the HadAM3P global atmosphere model. With a global network of about 50,000 volunteers, this allows us to run time-slice ensembles of essentially unlimited size, exploring the statistics of extreme weather under a range of scenarios for surface forcing and atmospheric composition, allowing for uncertainty in both boundary conditions and model parameters. Current experiments, developed with the support of Microsoft Research, focus on three regions, the Western USA, Europe and Southern Africa. We initially simulate the period 1959-2010 to establish which variables are realistically simulated by the model and on what scales. Our next experiments are focussing on the Event Attribution problem, exploring how the probability of various types of extreme weather would have been different over the recent past in a world unaffected by human influence, following the design of Pall et al (2011), but extended to a longer period and higher spatial resolution. We will present the first results of the unique, global, participatory experiment and discuss the implications for the attribution of recent weather events to anthropogenic influence on climate.
How to Visualize and Communicate Challenges in Climate and Environmental Sciences?

NASA Astrophysics Data System (ADS)

Vicari, R.; Schertzer, D. J. M.; Deutsch, J. C.

2014-12-01

The challenges of climate and environmental sciences need a renewed dialogue with a large spectrum of stakeholders, ranging from the general publics to specialists. This requires a better use of sophisticated visualization techniques to both forward the information and to follow the corresponding flow of information. A particular case of interest is the question of resilience to extreme weather events that also relies on increasing awareness of urban communities. This research looks at the development of exploration techniques of unstructured Big Data. Indeed access to information on environmental and climate sciences has hugely increased in terms of variety and quantity, as a consequence of different factors, among others the development of public relations by research institutes and the pervasive role of digital media (Bucchi 2013; Trench 2008). We are left with unthinkable amounts of information from blogs, social networks postings, public speeches, press releases, articles, etc. It is possible now to explore and visualize patterns followed by digital information with the support of automated analysis tools. On the other hand these techniques can provide important insights on how different techniques of visual communication can impact on urban resilience to extreme weather. The selected case studies correspond to several research projects under the umbrella of the Chair "Hydrology for resilient cities" aimed to develop and test new solutions in urban hydrology that will contribute to the resilience of our cities to extreme weather. These research projects - ranging from regional projects (e.g. RadX@IdF), European projects (e.g. Blue Green Dream and RainGain), to worldwide collaborations (e.g. TOMACS) - include awareness raising and capacity building activities aimed to foster cooperation between scientists, professionals, and beneficiaries. This presentation will explore how visualization techniques can be used in the above mentioned projects in order to support outreach activities as well as to illustrate the impact of digital communication on urban resilience.
Providing the Larger Climate Context During Extreme Weather - Lessons from Local Television News

NASA Astrophysics Data System (ADS)

Woods, M.; Cullen, H. M.

2015-12-01

Local television weathercasters, in their role as Station Scientists, are often called upon to educate viewers about the science and impacts of climate change. Climate Central supports these efforts through its Climate Matters program. Launched in 2010 with support from the National Science Foundation, the program has grown into a network that includes more than 245 weathercasters from across the country and provides localized information on climate and ready-to-use, broadcast quality graphics and analyses in both English and Spanish. This presentation will focus on discussing best practices for integrating climate science into the local weather forecast as well as advances in the science of extreme event attribution. The Chief Meteorologist at News10 (Sacramento, CA) will discuss local news coverage of the ongoing California drought, extreme weather and climate literacy.
Improving Predictions and Management of Hydrological Extremes

NASA Astrophysics Data System (ADS)

Wijngaard, Janet; Liggins, Felicity; Hurk, Bart vd; Lavers, David; Magnusson, Linus; Bouwer, Laurens; Weerts, Albrecht; Kjellström, Erik; Mañez, Maria; Ramos, Maria-Helena; Hananel, Cedric; Ercin, Ertug; Hunink, Johannes; Klein, Bastian; Pouget, Laurent; de Moel, Hans

2017-04-01

The EU Roadmap on Climate Services can be seen as a result of convergence between society's call for "actionable research" and the climate research community's provision of tailored data, information and knowledge. Although weather and climate have distinct definitions, a strong link between weather and climate services does exist but, to date, this link has not been explored extensively. Stakeholders being interviewed in the context of the Roadmap consider changes in our climate as distant, long-term impacts that are difficult to consider in present-day decision making, a process usually dominated by their daily experience with handling adverse weather and extreme events. However, it could be argued that this experience is a rich source of inspiration to increase society's resilience to an unknown future. The European research project, IMPREX, is built on the notion that "experience in managing present day weather extremes can help us anticipate the consequences of future climate variability and change". This presentation illustrates how IMPREX is building the link between the providers and users of information and services addressing both the weather and climate timescales. For different stakeholders in key economic sectors the needs and vulnerabilities in their daily practice are discussed, followed by an analysis of how weather and climate (W&C) services could contribute to the demands that arise from this. Examples of case studies showing the relevance of the tailored W&C information in users' operations will be included.
Extreme weather events in southern Germany - Climatological risk and development of a large-scale identification procedure

NASA Astrophysics Data System (ADS)

Matthies, A.; Leckebusch, G. C.; Rohlfing, G.; Ulbrich, U.

2009-04-01

Extreme weather events such as thunderstorms, hail and heavy rain or snowfall can pose a threat to human life and to considerable tangible assets. Yet there is a lack of knowledge about present day climatological risk and its economic effects, and its changes due to rising greenhouse gas concentrations. Therefore, parts of economy particularly sensitve to extreme weather events such as insurance companies and airports require regional risk-analyses, early warning and prediction systems to cope with such events. Such an attempt is made for southern Germany, in close cooperation with stakeholders. Comparing ERA40 and station data with impact records of Munich Re and Munich Airport, the 90th percentile was found to be a suitable threshold for extreme impact relevant precipitation events. Different methods for the classification of causing synoptic situations have been tested on ERA40 reanalyses. An objective scheme for the classification of Lamb's circulation weather types (CWT's) has proved to be most suitable for correct classification of the large-scale flow conditions. Certain CWT's have been turned out to be prone to heavy precipitation or on the other side to have a very low risk of such events. Other large-scale parameters are tested in connection with CWT's to find out a combination that has the highest skill to identify extreme precipitation events in climate model data (ECHAM5 and CLM). For example vorticity advection in 700 hPa shows good results, but assumes knowledge of regional orographic particularities. Therefore ongoing work is focused on additional testing of parameters that indicate deviations of a basic state of the atmosphere like the Eady Growth Rate or the newly developed Dynamic State Index. Evaluation results will be used to estimate the skill of the regional climate model CLM concerning the simulation of frequency and intensity of the extreme weather events. Data of the A1B scenario (2000-2050) will be examined for a possible climate change signal.
Evaluation of a variable speed limit system for wet and extreme weather conditions : phase 1 report.

DOT National Transportation Integrated Search

2012-06-01

Weather presents considerable challenges to the highway system, both in terms of safety and operations. From a safety standpoint, weather (i.e. precipitation in the form of rain, snow or ice) reduces pavement friction, thus increasing the potential f...
weather@home 2: validation of an improved global-regional climate modelling system

NASA Astrophysics Data System (ADS)

Guillod, Benoit P.; Jones, Richard G.; Bowery, Andy; Haustein, Karsten; Massey, Neil R.; Mitchell, Daniel M.; Otto, Friederike E. L.; Sparrow, Sarah N.; Uhe, Peter; Wallom, David C. H.; Wilson, Simon; Allen, Myles R.

2017-05-01

Extreme weather events can have large impacts on society and, in many regions, are expected to change in frequency and intensity with climate change. Owing to the relatively short observational record, climate models are useful tools as they allow for generation of a larger sample of extreme events, to attribute recent events to anthropogenic climate change, and to project changes in such events into the future. The modelling system known as weather@home, consisting of a global climate model (GCM) with a nested regional climate model (RCM) and driven by sea surface temperatures, allows one to generate a very large ensemble with the help of volunteer distributed computing. This is a key tool to understanding many aspects of extreme events. Here, a new version of the weather@home system (weather@home 2) with a higher-resolution RCM over Europe is documented and a broad validation of the climate is performed. The new model includes a more recent land-surface scheme in both GCM and RCM, where subgrid-scale land-surface heterogeneity is newly represented using tiles, and an increase in RCM resolution from 50 to 25 km. The GCM performs similarly to the previous version, with some improvements in the representation of mean climate. The European RCM temperature biases are overall reduced, in particular the warm bias over eastern Europe, but large biases remain. Precipitation is improved over the Alps in summer, with mixed changes in other regions and seasons. The model is shown to represent the main classes of regional extreme events reasonably well and shows a good sensitivity to its drivers. In particular, given the improvements in this version of the weather@home system, it is likely that more reliable statements can be made with regards to impact statements, especially at more localized scales.
Climate Central World Weather Attribution (WWA) project: Real-time extreme weather event attribution analysis

NASA Astrophysics Data System (ADS)

Haustein, Karsten; Otto, Friederike; Uhe, Peter; Allen, Myles; Cullen, Heidi

2015-04-01

Extreme weather detection and attribution analysis has emerged as a core theme in climate science over the last decade or so. By using a combination of observational data and climate models it is possible to identify the role of climate change in certain types of extreme weather events such as sea level rise and its contribution to storm surges, extreme heat events and droughts or heavy rainfall and flood events. These analyses are usually carried out after an extreme event has occurred when reanalysis and observational data become available. The Climate Central WWA project will exploit the increasing forecast skill of seasonal forecast prediction systems such as the UK MetOffice GloSea5 (Global seasonal forecasting system) ensemble forecasting method. This way, the current weather can be fed into climate models to simulate large ensembles of possible weather scenarios before an event has fully emerged yet. This effort runs along parallel and intersecting tracks of science and communications that involve research, message development and testing, staged socialization of attribution science with key audiences, and dissemination. The method we employ uses a very large ensemble of simulations of regional climate models to run two different analyses: one to represent the current climate as it was observed, and one to represent the same events in the world that might have been without human-induced climate change. For the weather "as observed" experiment, the atmospheric model uses observed sea surface temperature (SST) data from GloSea5 (currently) and present-day atmospheric gas concentrations to simulate weather events that are possible given the observed climate conditions. The weather in the "world that might have been" experiments is obtained by removing the anthropogenic forcing from the observed SSTs, thereby simulating a counterfactual world without human activity. The anthropogenic forcing is obtained by comparing the CMIP5 historical and natural simulations from a variety of CMIP5 model ensembles. Here, we present results for the UK 2013/14 winter floods as proof of concept and we show validation and testing results that demonstrate the robustness of our method. We also revisit the record temperatures over Europe in 2014 and present a detailed analysis of this attribution exercise as it is one of the events to demonstrate that we can make a sensible statement of how the odds for such a year to occur have changed while it still unfolds.
North Europe power transmission system vulnerability during extreme space weather

NASA Astrophysics Data System (ADS)

Piccinelli, Roberta; Krausmann, Elisabeth

2018-01-01

Space weather driven by solar activity can induce geomagnetic disturbances at the Earth's surface that can affect power transmission systems. Variations in the geomagnetic field result in geomagnetically induced currents that can enter the system through its grounding connections, saturate transformers and lead to system instability and possibly collapse. This study analyzes the impact of extreme space weather on the northern part of the European power transmission grid for different transformer designs to understand its vulnerability in case of an extreme event. The behavior of the system was analyzed in its operational mode during a severe geomagnetic storm, and mitigation measures, like line compensation, were also considered. These measures change the topology of the system, thus varying the path of geomagnetically induced currents and inducing a local imbalance in the voltage stability superimposed on the grid operational flow. Our analysis shows that the North European power transmission system is fairly robust against extreme space weather events. When considering transformers more vulnerable to geomagnetic storms, only few episodes of instability were found in correspondence with an existing voltage instability due to the underlying system load. The presence of mitigation measures limited the areas of the network in which bus voltage instabilities arise with respect to the system in which mitigation measures are absent.
Changes in Extreme Events and the Potential Impacts on National Security

NASA Astrophysics Data System (ADS)

Bell, J.

2017-12-01

Extreme weather and climate events affect human health by causing death, injury, and illness, as well as having large socio-economic impacts. Climate change has caused changes in extreme event frequency, intensity and geographic distribution, and will continue to be a driver for changes in the future. Some of the extreme events that have already changed are heat waves, droughts, wildfires, flooding rains, coastal flooding, storm surge, and hurricanes. The pathways connecting extreme events to health outcomes and economic losses can be diverse and complex. The difficulty in predicting these relationships comes from the local intricacies of societal and environmental factors that influences the level of exposure. The goal of this presentation is to discuss the national security implications of changes in extreme weather events and demonstrate how changes in extremes can lead to a host cascading issues. To illustrate this point, this presentation will provide examples of the various pathways that extreme events can increase disease burden and cause economic stress.
Home Fires

MedlinePlus

... to the touch and lights that flicker. Portable Space Heaters Keep combustible objects at least three feet ... Radiological Dispersion Device Severe Weather Snowstorms & Extreme Cold Space Weather Thunderstorms & Lightning Tornadoes Tsunamis Volcanoes Wildfires Ready. ...
Blood pressure response to patterns of weather fluctuations and effect on mortality.

PubMed

Aubinière-Robb, Louise; Jeemon, Panniyammakal; Hastie, Claire E; Patel, Rajan K; McCallum, Linsay; Morrison, David; Walters, Matthew; Dawson, Jesse; Sloan, William; Muir, Scott; Dominiczak, Anna F; McInnes, Gordon T; Padmanabhan, Sandosh

2013-07-01

Very few studies have looked at longitudinal intraindividual blood pressure responses to weather conditions. There are no data to suggest that specific response to changes in weather will have an impact on survival. We analyzed >169 000 clinic visits of 16 010 Glasgow Blood Pressure Clinic patients with hypertension. Each clinic visit was mapped to the mean West of Scotland monthly weather (temperature, sunshine, rainfall) data. Percentage change in blood pressure was calculated between pairs of consecutive clinic visits, where the weather alternated between 2 extreme quartiles (Q(1)-Q(4) or Q(4)-Q(1)) or remained in the same quartile (Q(n)-Q(n)) of each weather parameter. Subjects were also categorized into 2 groups depending on whether their blood pressure response in Q(1)-Q(4) or Q(4)-Q(1) were concordant or discordant to Q(n)-Q(n). Generalized estimating equations and Cox proportional hazards model were used to model the effect on longitudinal blood pressure and mortality, respectively. Q(n)-Q(n) showed a mean 2% drop in blood pressure consistently, whereas Q(4)-Q(1) showed a mean 2.1% and 1.6% rise in systolic and diastolic blood pressure, respectively. However, Q(1)-Q(4) did not show significant changes in blood pressure. Temperature-sensitive subjects had significantly higher mortality (1.35 [95% confidence interval, 1.06-1.71]; P=0.01) and higher follow-up systolic blood pressure (1.85 [95% confidence interval, 0.24-3.46]; P=0.02) compared with temperature-nonsensitive subjects. Blood pressure response to temperature may be one of the underlying mechanisms that determine long-term blood pressure variability. Knowing a patient's blood pressure response to weather can help reduce unnecessary antihypertensive treatment modification, which may in turn increase blood pressure variability and, thus, risk.

A predictive model for spotted wilt epidemics in peanut based on local weather conditions and the tomato spotted wilt virus risk index.

PubMed

Olatinwo, R O; Paz, J O; Brown, S L; Kemerait, R C; Culbreath, A K; Beasley, J P; Hoogenboom, G

2008-10-01

Tomato spotted wilt virus (TSWV), a member of the genus Tospovirus (family Bunyaviridae), is an important plant virus that causes severe damage to peanut (Arachis hypogaea) in the southeastern United States. Disease severity has been extremely variable in individual fields in Georgia, due to several factors including variability in weather patterns. A TSWV risk index has been developed by the University of Georgia to aid peanut growers with the assessment and avoidance of high risk situations. This study was conducted to examine the relationship between weather parameters and spotted wilt severity in peanut, and to develop a predictive model that integrates localized weather information into the risk index. On-farm survey data collected during 1999, 2002, 2004, and 2005 growing seasons, and derived weather variables during the same years were analyzed using nonlinear and multiple regression analyses. Meteorological data were obtained from the Georgia Automated Environmental Monitoring Network. The best model explained 61% of the variation in spotted wilt severity (square root transformed) as a function of the interactions between the TSWV risk index, the average daily temperature in April (TavA), the average daily minimum temperature between March and April (TminMA), the accumulated rainfall in March (RainfallM), the accumulated rainfall in April (RainfallA), the number of rain days in April (RainDayA), evapotranspiration in April (EVTA), and the number of days from 1 January to the planting date (JulianDay). Integrating this weather-based model with the TSWV risk index may help peanut growers more effectively manage tomato spotted wilt disease.
The cross wavelet and wavelet coherence analysis of spatio-temporal rainfall-groundwater system in Pingtung plain, Taiwan

NASA Astrophysics Data System (ADS)

Lin, Yuan-Chien; Yu, Hwa-Lung

2013-04-01

The increasing frequency and intensity of extreme rainfall events has been observed recently in Taiwan. Particularly, Typhoon Morakot, Typhoon Fanapi, and Typhoon Megi consecutively brought record-breaking intensity and magnitude of rainfalls to different locations of Taiwan in these two years. However, records show the extreme rainfall events did not elevate the amount of annual rainfall accordingly. Conversely, the increasing frequency of droughts has also been occurring in Taiwan. The challenges have been confronted by governmental agencies and scientific communities to come up with effective adaptation strategies for natural disaster reduction and sustainable environment establishment. Groundwater has long been a reliable water source for a variety of domestic, agricultural, and industrial uses because of its stable quantity and quality. In Taiwan, groundwater accounts for the largest proportion of all water resources for about 40%. This study plans to identify and quantify the nonlinear relationship between precipitation and groundwater recharge, find the non-stationary time-frequency relations between the variations of rainfall and groundwater levels to understand the phase difference of time series. Groundwater level data and over-50-years hourly rainfall records obtained from 20 weather stations in Pingtung Plain, Taiwan has been collected. Extract the space-time pattern by EOF method, which is a decomposition of a signal or data set in terms of orthogonal basis functions determined from the data for both time series and spatial patterns, to identify the important spatial pattern of groundwater recharge and using cross wavelet and wavelet coherence method to identify the relationship between rainfall and groundwater levels. Results show that EOF method can specify the spatial-temporal patterns which represents certain geological characteristics and other mechanisms of groundwater, and the wavelet coherence method can identify general correlation between rainfall and groundwater signal at low frequency and high frequency relationship at some certain extreme rainfall events. Keywords: extreme rainfall, groundwater, EOF, wavelet coherence
Improving Predictions and Management of Hydrological Extremes through Climate Services

NASA Astrophysics Data System (ADS)

van den Hurk, Bart; Wijngaard, Janet; Pappenberger, Florian; Bouwer, Laurens; Weerts, Albrecht; Buontempo, Carlo; Doescher, Ralf; Manez, Maria; Ramos, Maria-Helena; Hananel, Cedric; Ercin, Ertug; Hunink, Johannes; Klein, Bastian; Pouget, Laurent; Ward, Philip

2016-04-01

The EU Roadmap on Climate Services can be seen as a result of convergence between the society's call for "actionable research", and the climate research community providing tailored data, information and knowledge. However, although weather and climate have clearly distinct definitions, a strong link between weather and climate services exists that is not explored extensively. Stakeholders being interviewed in the context of the Roadmap consider climate as a far distant long term feature that is difficult to consider in present-day decision taking, which is dominated by daily experience with handling extreme events. It is argued that this experience is a rich source of inspiration to increase society's resilience to an unknown future. A newly started European research project, IMPREX, is built on the notion that "experience in managing current day weather extremes is the best learning school to anticipate consequences of future climate". This paper illustrates possible ways to increase the link between information and services addressing weather and climate time scales by discussing the underlying concepts of IMPREX and its expected outcome.
A Modeling Study of the Spring 2011 Extreme US Weather Activity

NASA Technical Reports Server (NTRS)

Schubert, S.; Suarez, M.; Chang, Y.

2012-01-01

The spring of 2011 was characterized by record-breaking tornadic activity with substantial loss of life and destruction of property. While a waning La Nina and other atmospheric teleconnections have been implicated in the development of these extreme weather events, a quantitative assessment of their causes is still lacking. This study uses high resolution (1/4 lat/lon) GEOS-5 AGCM experiments to quantify the role of SSTs and soil moisture in the development of the extreme weather activity with a focus on April - the month of peak tornadic activity. The simulations, consisting of 22-member ensembles of three-month long simulations (initialized March 1st) reproduce the main features of the observed large-scale changes including the below-normal temperature and above-normal precipitation in the Central US, and the hot and dry conditions to the south. Various sensitivity experiments are conducted to separate the roles of the SST, soil moisture and the initial atmospheric conditions in the development and predictability of the atmospheric conditions (wind shear, moisture, etc.) favoring the severe weather activity and flooding.
Assessing Individual Weather Risk-Taking and Its Role in Modeling Likelihood of Hurricane Evacuation

NASA Astrophysics Data System (ADS)

Stewart, A. E.

2017-12-01

This research focuses upon measuring an individual's level of perceived risk of different severe and extreme weather conditions using a new self-report measure, the Weather Risk-Taking Scale (WRTS). For 32 severe and extreme situations in which people could perform an unsafe behavior (e. g., remaining outside with lightning striking close by, driving over roadways covered with water, not evacuating ahead of an approaching hurricane, etc.), people rated: 1.their likelihood of performing the behavior, 2. The perceived risk of performing the behavior, 3. the expected benefits of performing the behavior, and 4. whether the behavior has actually been performed in the past. Initial development research with the measure using 246 undergraduate students examined its psychometric properties and found that it was internally consistent (Cronbach's a ranged from .87 to .93 for the four scales) and that the scales possessed good temporal (test-retest) reliability (r's ranged from .84 to .91). A second regression study involving 86 undergraduate students found that taking weather risks was associated with having taken similar risks in one's past and with the personality trait of sensation-seeking. Being more attentive to the weather and perceiving its risks when it became extreme was associated with lower likelihoods of taking weather risks (overall regression model, R2adj = 0.60). A third study involving 334 people examined the contributions of weather risk perceptions and risk-taking in modeling the self-reported likelihood of complying with a recommended evacuation ahead of a hurricane. Here, higher perceptions of hurricane risks and lower perceived benefits of risk-taking along with fear of severe weather and hurricane personal self-efficacy ratings were all statistically significant contributors to the likelihood of evacuating ahead of a hurricane. Psychological rootedness and attachment to one's home also tend to predict lack of evacuation. This research highlights the contributions that a psychological approach can offer in understanding preparations for severe weather. This approach also suggests that a great deal of individual variation exists in weather-protective behaviors, which may explain in part why some people take weather-related risks despite receiving warnings for severe weather.
Mortality gradients within and among dominant plant populations as barometers of ecosystem change during extreme drought.

PubMed

Gitlin, Alicyn R; Sthultz, Christopher M; Bowker, Matthew A; Stumpf, Stacy; Paxton, Kristina L; Kennedy, Karla; Muñoz, Axhel; Bailey, Joseph K; Whitham, Thomas G

2006-10-01

Understanding patterns of plant population mortality during extreme weather events is important to conservation planners because the frequency of such events is expected to increase, creating the need to integrate climatic uncertainty into management. Dominant plants provide habitat and ecosystem structure, so changes in their distribution can be expected to have cascading effects on entire communities. Observing areas that respond quickly to climate fluctuations provides foresight into future ecological changes and will help prioritize conservation efforts. We investigated patterns of mortality in six dominant plant species during a drought in the southwestern United States. We quantified population mortality for each species across its regional distribution and tested hypotheses to identify ecological stress gradients for each species. Our results revealed three major patterns: (1) dominant species from diverse habitat types (i.e., riparian, chaparral, and low- to high-elevation forests) exhibited significant mortality, indicating that the effects of drought were widespread; (2) average mortality differed among dominant species (one-seed juniper[Juniperus monosperma (Engelm.) Sarg.] 3.3%; manzanita[Arctostaphylos pungens Kunth], 14.6%; quaking aspen[Populus tremuloides Michx.], 15.4%; ponderosa pine[Pinus ponderosa P. & C. Lawson], 15.9%; Fremont cottonwood[Populus fremontii S. Wats.], 20.7%; and pinyon pine[Pinus edulis Engelm.], 41.4%); (3) all dominant species showed localized patterns of very high mortality (24-100%) consistent with water stress gradients. Land managers should plan for climatic uncertainty by promoting tree recruitment in rare habitat types, alleviating unnatural levels of competition on dominant plants, and conserving sites across water stress gradients. High-stress sites, such as those we examined, have conservation value as barometers of change and because they may harbor genotypes that are adapted to climatic extremes.
Role of quasiresonant planetary wave dynamics in recent boreal spring-to-autumn extreme events

PubMed Central

Petoukhov, Vladimir; Petri, Stefan; Rahmstorf, Stefan; Coumou, Dim; Kornhuber, Kai; Schellnhuber, Hans Joachim

2016-01-01

In boreal spring-to-autumn (May-to-September) 2012 and 2013, the Northern Hemisphere (NH) has experienced a large number of severe midlatitude regional weather extremes. Here we show that a considerable part of these extremes were accompanied by highly magnified quasistationary midlatitude planetary waves with zonal wave numbers m = 6, 7, and 8. We further show that resonance conditions for these planetary waves were, in many cases, present before the onset of high-amplitude wave events, with a lead time up to 2 wk, suggesting that quasiresonant amplification (QRA) of these waves had occurred. Our results support earlier findings of an important role of the QRA mechanism in amplifying planetary waves, favoring recent NH weather extremes. PMID:27274064
Semi-supervised tracking of extreme weather events in global spatio-temporal climate datasets

NASA Astrophysics Data System (ADS)

Kim, S. K.; Prabhat, M.; Williams, D. N.

2017-12-01

Deep neural networks have been successfully applied to solve problem to detect extreme weather events in large scale climate datasets and attend superior performance that overshadows all previous hand-crafted methods. Recent work has shown that multichannel spatiotemporal encoder-decoder CNN architecture is able to localize events in semi-supervised bounding box. Motivated by this work, we propose new learning metric based on Variational Auto-Encoders (VAE) and Long-Short-Term-Memory (LSTM) to track extreme weather events in spatio-temporal dataset. We consider spatio-temporal object tracking problems as learning probabilistic distribution of continuous latent features of auto-encoder using stochastic variational inference. For this, we assume that our datasets are i.i.d and latent features is able to be modeled by Gaussian distribution. In proposed metric, we first train VAE to generate approximate posterior given multichannel climate input with an extreme climate event at fixed time. Then, we predict bounding box, location and class of extreme climate events using convolutional layers given input concatenating three features including embedding, sampled mean and standard deviation. Lastly, we train LSTM with concatenated input to learn timely information of dataset by recurrently feeding output back to next time-step's input of VAE. Our contribution is two-fold. First, we show the first semi-supervised end-to-end architecture based on VAE to track extreme weather events which can apply to massive scaled unlabeled climate datasets. Second, the information of timely movement of events is considered for bounding box prediction using LSTM which can improve accuracy of localization. To our knowledge, this technique has not been explored neither in climate community or in Machine Learning community.
The effect of extreme spring weather on body condition and stress physiology in Lapland longspurs and white-crowned sparrows breeding in the Arctic.

PubMed

Krause, Jesse S; Pérez, Jonathan H; Chmura, Helen E; Sweet, Shannan K; Meddle, Simone L; Hunt, Kathleen E; Gough, Laura; Boelman, Natalie; Wingfield, John C

2016-10-01

Climate change is causing rapid shifts in temperature while also increasing the frequency, duration, and intensity of extreme weather. In the northern hemisphere, the spring of 2013 was characterized as extreme due to record high snow cover and low temperatures. Studies that describe the effects of extreme weather on phenology across taxa are limited while morphological and physiological responses remain poorly understood. Stress physiology, as measured through baseline and stress-induced concentrations of cortisol or corticosterone, has often been studied to understand how organisms respond to environmental stressors. We compared body condition and stress physiology of two long-distance migrants breeding in low arctic Alaska - the white-crowned sparrow (Zonotrichia leucophrys) and Lapland longspur (Calcarius lapponicus) - in 2013, an extreme weather year, with three more typical years (2011, 2012, and 2014). The extended snow cover in spring 2013 caused measureable changes in phenology, body condition and physiology. Arrival timing for both species was delayed 4-5days compared to the other three years. Lapland longspurs had reduced fat stores, pectoralis muscle profiles, body mass, and hematocrit levels, while stress-induced concentrations of corticosterone were increased. Similarly, white-crowned sparrows had reduced pectoralis muscle profiles and hematocrit levels, but in contrast to Lapland longspurs, had elevated fat stores and no difference in mass or stress physiology relative to other study years. An understanding of physiological mechanisms that regulate coping strategies is of critical importance for predicting how species will respond to the occurrence of extreme events in the future due to global climate change. Copyright © 2016 The Authors. Published by Elsevier Inc. All rights reserved.
Monitoring a local extreme weather event with the scope of hyperspectral sounding

NASA Astrophysics Data System (ADS)

Satapathy, Jyotirmayee; Jangid, Buddhi Prakash

2018-06-01

Operational space-based hyperspectral Infrared sounders retrieve atmospheric temperature and humidity profiles from the measured radiances. These sounders like Atmospheric InfraRed Sounder, Infrared Atmospheric Sounding Interferometer as well as INSAT-3D sounders on geostationary orbit have proved to be very successful in providing these retrievals on global and regional scales, respectively, with good enough spatio-temporal resolutions and are well competent with that of traditional profiles from radiosondes and models fields. The aim of this work is to show how these new generation hyperspectral Infrared sounders can benefit in real-time weather monitoring. We have considered a regional extreme weather event to demonstrate how the profiles retrieved from these operational sounders are consistent with the environmental conditions which have led to this severe weather event. This work has also made use of data products of Moderate Resolution Imaging Spectroradiometer as well as by radiative transfer simulation of clear and cloudy atmospheric conditions using Numerical Weather Prediction profiles in conjunction with INSAT-3D sounder. Our results indicate the potential use of high-quality hyperspectral atmospheric profiles to aid in delineation of real-time weather prediction.
Local Climate Experts: The Influence of Local TV Weather Information on Climate Change Perceptions

PubMed Central

Bloodhart, Brittany; Maibach, Edward; Myers, Teresa; Zhao, Xiaoquan

2015-01-01

Individuals who identify changes in their local climate are also more likely to report that they have personally experienced global climate change. One way that people may come to recognize that their local climate is changing is through information provided by local TV weather forecasters. Using random digit dialing, 2,000 adult local TV news viewers in Virginia were surveyed to determine whether routine exposure to local TV weather forecasts influences their perceptions of extreme weather in Virginia, and their perceptions about climate change more generally. Results indicate that paying attention to TV weather forecasts is associated with beliefs that extreme weather is becoming more frequent in Virginia, which in turn is associated with stronger beliefs and concerns about climate change. These associations were strongest for individuals who trust their local TV weathercaster as a source of information about climate change, and for those who identify as politically conservative or moderate. The findings add support to the literature suggesting that TV weathercasters can play an important role in educating the public about climate change. PMID:26551357
Local Climate Experts: The Influence of Local TV Weather Information on Climate Change Perceptions.

PubMed

Bloodhart, Brittany; Maibach, Edward; Myers, Teresa; Zhao, Xiaoquan

2015-01-01

Individuals who identify changes in their local climate are also more likely to report that they have personally experienced global climate change. One way that people may come to recognize that their local climate is changing is through information provided by local TV weather forecasters. Using random digit dialing, 2,000 adult local TV news viewers in Virginia were surveyed to determine whether routine exposure to local TV weather forecasts influences their perceptions of extreme weather in Virginia, and their perceptions about climate change more generally. Results indicate that paying attention to TV weather forecasts is associated with beliefs that extreme weather is becoming more frequent in Virginia, which in turn is associated with stronger beliefs and concerns about climate change. These associations were strongest for individuals who trust their local TV weathercaster as a source of information about climate change, and for those who identify as politically conservative or moderate. The findings add support to the literature suggesting that TV weathercasters can play an important role in educating the public about climate change.
Integration of Weather Avoidance and Traffic Separation

NASA Technical Reports Server (NTRS)

Consiglio, Maria C.; Chamberlain, James P.; Wilson, Sara R.

2011-01-01

This paper describes a dynamic convective weather avoidance concept that compensates for weather motion uncertainties; the integration of this weather avoidance concept into a prototype 4-D trajectory-based Airborne Separation Assurance System (ASAS) application; and test results from a batch (non-piloted) simulation of the integrated application with high traffic densities and a dynamic convective weather model. The weather model can simulate a number of pseudo-random hazardous weather patterns, such as slow- or fast-moving cells and opening or closing weather gaps, and also allows for modeling of onboard weather radar limitations in range and azimuth. The weather avoidance concept employs nested "core" and "avoid" polygons around convective weather cells, and the simulations assess the effectiveness of various avoid polygon sizes in the presence of different weather patterns, using traffic scenarios representing approximately two times the current traffic density in en-route airspace. Results from the simulation experiment show that the weather avoidance concept is effective over a wide range of weather patterns and cell speeds. Avoid polygons that are only 2-3 miles larger than their core polygons are sufficient to account for weather uncertainties in almost all cases, and traffic separation performance does not appear to degrade with the addition of weather polygon avoidance. Additional "lessons learned" from the batch simulation study are discussed in the paper, along with insights for improving the weather avoidance concept. Introduction
Weather chains during the 2013/2014 winter and their significance for seasonal prediction

NASA Astrophysics Data System (ADS)

Davies, Huw C.

2015-11-01

Day-to-day weather forecasting has improved substantially over the past few decades. In contrast, progress in seasonal prediction outside the tropics has been meagre and mixed. On seasonal timescales, the constraining influence of the initial atmospheric state is weak, and the internal variability associated with transient weather systems tends to be large compared with the nuanced influence of anomalies in external forcing. Current research and operational activities focus on exploring and exploiting potential links between external anomalies and seasonal-mean climate patterns. Here I examine reanalysed meteorological data sets for the unusual winter 2013/2014, with drought and freezing conditions juxtaposed over North America and severe wet and stormy weather over parts of Europe, to study the role of weather systems and their transient upper-tropospheric flow patterns. I find that the amplitude, recurrence and location of these transient patterns account directly for the corresponding anomalous seasonal-mean patterns. They occurred episodically and sequentially, were linked dynamically, and exhibited some circumpolar connectivity. I conclude that the upper-tropospheric components of transient weather systems are significant for understanding and predicting seasonal weather patterns, whereas the role of external factors is more subtle.
Preparing for Extremes.

ERIC Educational Resources Information Center

Herman, Dan

1998-01-01

Describes some basic maintenance and proper preparations for changing weather that can help keep school bus operations moving. Provides advice on diesel engine usage that can lengthen engine life and maintain all weather performance is provided. (GR)
Winter Weather Frequently Asked Questions

MedlinePlus

... Hot Weather Tips Warning Signs and Symptoms FAQs Social Media How to Stay Cool Missouri Cooling Centers Extreme ... PSAs for Disasters Resources for Emergency Health Professionals Social Media Health and Safety Concerns for All Disasters Animals ...
Winter Weather: Outdoor Safety

MedlinePlus

... Hot Weather Tips Warning Signs and Symptoms FAQs Social Media How to Stay Cool Missouri Cooling Centers Extreme ... PSAs for Disasters Resources for Emergency Health Professionals Social Media Health and Safety Concerns for All Disasters Animals ...
Efficient Simulation of Tropical Cyclone Pathways with Stochastic Perturbations

NASA Astrophysics Data System (ADS)

Webber, R.; Plotkin, D. A.; Abbot, D. S.; Weare, J.

2017-12-01

Global Climate Models (GCMs) are known to statistically underpredict intense tropical cyclones (TCs) because they fail to capture the rapid intensification and high wind speeds characteristic of the most destructive TCs. Stochastic parametrization schemes have the potential to improve the accuracy of GCMs. However, current analysis of these schemes through direct sampling is limited by the computational expense of simulating a rare weather event at fine spatial gridding. The present work introduces a stochastically perturbed parametrization tendency (SPPT) scheme to increase simulated intensity of TCs. We adapt the Weighted Ensemble algorithm to simulate the distribution of TCs at a fraction of the computational effort required in direct sampling. We illustrate the efficiency of the SPPT scheme by comparing simulations at different spatial resolutions and stochastic parameter regimes. Stochastic parametrization and rare event sampling strategies have great potential to improve TC prediction and aid understanding of tropical cyclogenesis. Since rising sea surface temperatures are postulated to increase the intensity of TCs, these strategies can also improve predictions about climate change-related weather patterns. The rare event sampling strategies used in the current work are not only a novel tool for studying TCs, but they may also be applied to sampling any range of extreme weather events.
Intensifying postfire weather and biological invasion drive species loss in a Mediterranean-type biodiversity hotspot.

PubMed

Slingsby, Jasper A; Merow, Cory; Aiello-Lammens, Matthew; Allsopp, Nicky; Hall, Stuart; Kilroy Mollmann, Hayley; Turner, Ross; Wilson, Adam M; Silander, John A

2017-05-02

Prolonged periods of extreme heat or drought in the first year after fire affect the resilience and diversity of fire-dependent ecosystems by inhibiting seed germination or increasing mortality of seedlings and resprouting individuals. This interaction between weather and fire is of growing concern as climate changes, particularly in systems subject to stand-replacing crown fires, such as most Mediterranean-type ecosystems. We examined the longest running set of permanent vegetation plots in the Fynbos of South Africa (44 y), finding a significant decline in the diversity of plots driven by increasingly severe postfire summer weather events (number of consecutive days with high temperatures and no rain) and legacy effects of historical woody alien plant densities 30 y after clearing. Species that resprout after fire and/or have graminoid or herb growth forms were particularly affected by postfire weather, whereas all species were sensitive to invasive plants. Observed differences in the response of functional types to extreme postfire weather could drive major shifts in ecosystem structure and function such as altered fire behavior, hydrology, and carbon storage. An estimated 0.5 °C increase in maximum temperature tolerance of the species sets unique to each survey further suggests selection for species adapted to hotter conditions. Taken together, our results show climate change impacts on biodiversity in the hyperdiverse Cape Floristic Region and demonstrate an important interaction between extreme weather and disturbance by fire that may make flammable ecosystems particularly sensitive to climate change.
Improved forecasts of winter weather extremes over midlatitudes with extra Arctic observations

NASA Astrophysics Data System (ADS)

Sato, Kazutoshi; Inoue, Jun; Yamazaki, Akira; Kim, Joo-Hong; Maturilli, Marion; Dethloff, Klaus; Hudson, Stephen R.; Granskog, Mats A.

2017-02-01

Recent cold winter extremes over Eurasia and North America have been considered to be a consequence of a warming Arctic. More accurate weather forecasts are required to reduce human and socioeconomic damages associated with severe winters. However, the sparse observing network over the Arctic brings errors in initializing a weather prediction model, which might impact accuracy of prediction results at midlatitudes. Here we show that additional Arctic radiosonde observations from the Norwegian young sea ICE expedition (N-ICE2015) drifting ice camps and existing land stations during winter improved forecast skill and reduced uncertainties of weather extremes at midlatitudes of the Northern Hemisphere. For two winter storms over East Asia and North America in February 2015, ensemble forecast experiments were performed with initial conditions taken from an ensemble atmospheric reanalysis in which the observation data were assimilated. The observations reduced errors in initial conditions in the upper troposphere over the Arctic region, yielding more precise prediction of the locations and strengths of upper troughs and surface synoptic disturbances. Errors and uncertainties of predicted upper troughs at midlatitudes would be brought with upper level high potential vorticity (PV) intruding southward from the observed Arctic region. This is because the PV contained a "signal" of the additional Arctic observations as it moved along an isentropic surface. This suggests that a coordinated sustainable Arctic observing network would be effective not only for regional weather services but also for reducing weather risks in locations distant from the Arctic.

A Paleo Perspective on Arctic and Mid-latitude Linkages from a Southeast Alaska Ice Core

NASA Astrophysics Data System (ADS)

Porter, S. E.; Mosley-Thompson, E.; Thompson, L. G.; Bolzan, J. F.

2017-12-01

Recent extreme weather events in the Northern Hemisphere have been linked to anomalously amplified jet stream patterns, North Pacific marine heatwaves, retreating Arctic sea ice extent, and/or the combination thereof. The role of the Arctic in influencing mid-latitude weather and extreme events is a burgeoning topic of climate research that is limited primarily to the recent decades in which Arctic amplification and shrinking Arctic sea ice extent are occurring. Paleo-proxy data afford an opportunity to place the changing Arctic and its far-reaching climatic consequences in the longer context of Earth's climate history and allow identification of time periods with conditions analogous to the present. Ice core-derived annual net accumulation from the Bona-Churchill (BC) ice core, retrieved in 2002 from the Wrangell-St. Elias mountain range in southeast Alaska, is used to explore the historical characteristics of the regional North Pacific climate and the further afield teleconnections. Variability of accumulation on BC is driven primarily by shifts in the position of the Aleutian Low which influences the available moisture sources for the drill site. The accumulation record is also related to sea surface temperatures in the Gulf of Alaska, defined here by the North Pacific Mode and somewhat colloquially as the North Pacific "blob". Thus due to its connection with the Aleutian Low and North Pacific sea surface temperatures, this uniquely situated ice core record indirectly captures the phasing of troughs and ridges in the polar jet stream over North America, and thereby facilitates examination of the atmospheric wave structure prior to the instrumental record. The relationships among the ice core accumulation record and various North Pacific climate features are presented along with evidence identifying specific time periods possibly characterized by persistently amplified wave patterns.
Patterns in Patient Access and Utilization of Online Medical Records: Analysis of MyChart.

PubMed

Redelmeier, Donald A; Kraus, Nicole C

2018-02-06

Electronic patient portals provide a new method for sharing personal medical information with individual patients. Our aim was to review utilization patterns of the largest online patient portal in Canada's largest city. We conducted a 4-year time-trend analysis of aggregated anonymous utilization data of the MyChart patient portal at Sunnybrook Health Sciences Centre in Ontario, Canada, from January 1, 2012, through December 31, 2015. Prespecified analyses examined trends related to day (weekend vs weekday), season (July vs January), year (2012 vs 2015), and an extreme adverse weather event (ice storm of December 20-26, 2013). Primary endpoints included three measures of patient portal activity: registrations, logins, and pageviews. We identified 32,325 patients who registered for a MyChart account during the study interval. Time-trend analysis showed no sign of attenuating registrations over time. Logins were frequent, averaged 734 total per day, and showed an increasing trend over time. Pageviews mirrored logins, averaged about 3029 total per day, and equated to about 5 pageviews during the average login. The most popular pageviews were clinical notes, followed by laboratory results and medical imaging reports. All measures of patient activity were lower on weekends compared to weekdays (P<.001) yet showed no significant changes related to seasons or extreme weather. No major security breach, malware attack, or software failure occurred during the study. Online patient portals can provide a popular and reliable system for distributing personal medical information to active patients and may merit consideration for hospitals. ©Donald A Redelmeier, Nicole C Kraus. Originally published in the Journal of Medical Internet Research (http://www.jmir.org), 06.02.2018.
Large Scale Drivers for the Extreme Storm Season over the North Atlantic and the UK in Winter 2013-14

NASA Astrophysics Data System (ADS)

Wild, Simon; Befort, Daniel J.; Leckebusch, Gregor C.

2016-04-01

The British Isles experienced exceptional stormy and rainy weather conditions in winter 2013-2014 while large parts of central North America recorded near record minimum surface temperatures values. Potential drivers for these cold conditions include increasingly warm surface waters of the tropical west Pacific. It has been suggested these increasing sea surface temperatures could also be the cause for extreme weather over the Europe, particularly the UK. Testing this hypothesis, we investigate mechanisms linking the tropical west Pacific and European wind storm activity. We will firstly analyse anomaly patterns along such a potential link in winter 2013-14. Secondly, we will investigate whether these identified anomaly patterns show a strong interannual relationship in the recent past. Our results, using primarily ERA-Interim Reanalysis from 1979 to 2014, show an absolute maximum of wind storm frequency over the northeast Atlantic and the British Isles in winter 2013-14. We also find absolute minimum surface temperatures in central North America and increased convective activity over the tropical west Pacific in the same season. The winter 2013-14 was additionally characterized by anomalous warm sea surface temperatures over the subtropical northwest Atlantic. Although the interannual variability of wind storms in the northeast Atlantic and surface temperatures in North America are significantly anti-correlated, we cannot directly relate wind storm frequency with tropical west Pacific anomalies. We thus conclude that the conditions over the Pacific in winter 2013-14 were favourable but not sufficient to explain the record number of wind storms in this season. Instead, we suggest that warm north Atlantic sea surface temperature anomalies in combination with cold surface temperatures over North America played a more important role for generating higher wind storm counts over the northeast Atlantic and the UK.
Weathering, erosion and fluvial transfers of particulate and dissolved materials from the Taiwan orogen

NASA Astrophysics Data System (ADS)

Hovius, Niels; Galy, Albert; Hilton, Robert; West, Joshua; Chen, Hongey; Horng, Ming-Jame; Chen, Meng-Chiang

2010-05-01

Systematic monitoring of river loads helps refine and extend the map of internal dynamics and external feedbacks in Earth's surface and near-surface system. Our focus is on Taiwan where hillslope mass wasting and fluvial sediment transport are driven by earthquakes and cyclonic storms. The biggest trigger events cause instantaneous erosion and seed a weakness in the landscape that is removed over time in predictable fashion. This gives rise to patterns of erosion that can not be understood in terms of bulk characteristics of climate, such as average annual precipitation. Instead, these patterns reflect the distribution and history of seismicity and extreme precipitation. For example, the 1999 Mw 7.6 Chi-Chi earthquake has resulted in elevated rates of sediment transport that decayed to normal values over seven years since the earthquake. Very large typhoons, with enhanced precipitation due to a monsoonal feed, have caused a similar, temporary deviation from normal catchment dynamics. Crucially, these events do not only mobilize large quantities of clastic sediment, but they also harvest particulate organic carbon (POC) from rock mass, soils and the biosphere. In Taiwan, most non-fossil POC is carried in hyperpycnal storm floods. This may promote rapid burial and preservation of POC in turbidites, representing a draw down of CO2 from the atmosphere that is potentially larger than that by silicate weathering in the same domain. Oxidation of fossil POC during exhumation and surface transport could offset this effect, but in Taiwan the rate of preservation of fossil POC is extremely high, due to rapid erosion and short fluvial transfer paths. Meanwhile, coarse woody debris flushed from the Taiwan mountains is probably not buried efficiently in geological deposits, representing a concentrated flux of nutrients to coastal and marine environments instead.
Total lightning characteristics of recent hazardous weather events in Japan

NASA Astrophysics Data System (ADS)

Hobara, Y.; Kono, S.; Ogawa, T.; Heckman, S.; Stock, M.; Liu, C.

2017-12-01

In recent years, the total lightning (IC + CG) activity have attracted a lot of attention to improve the quality of prediction of hazardous weather phenomena (hail, wind gusts, tornadoes, heavy precipitation). Sudden increases of the total lightning flash rate so-called lightning jump (LJ) preceding the hazardous weather, reported in several studies, are one of the promising precursors. Although, increases in the frequency and intensity of these extreme weather events were reported in Japan, relationship with these events with total lightning have not studied intensively yet. In this paper, we will demonstrate the recent results from Japanese total lightning detection network (JTLN) in relation with hazardous weather events occurred in Japan in the period of 2014-2016. Automatic thunderstorm cell tracking was carried out based on the very high spatial and temporal resolution X-band MP radar echo data (1 min and 250 m) to correlate with total lightning activity. Results obtained reveal promising because the flash rate of total lightning tends to increase about 10 40 minutes before the onset of the extreme weather events. We also present the differences in lightning characteristics of thunderstorm cells between hazardous weather events and non-hazardous weather events, which is a vital information to improve the prediction efficiency.
How Satellites Have Contributed to Building a Weather Ready Nation

NASA Astrophysics Data System (ADS)

Lapenta, W.

2017-12-01

NOAA's primary mission since its inception has been to reduce the loss of life and property, as well as disruptions from, high impact weather and water-related events. In recent years, significant societal losses resulting even from well forecast extreme events have shifted attention from the forecast alone toward ensuring societal response is equal to the risks that exist for communities, businesses and the public. The responses relate to decisions ranging from coastal communities planning years in advance to mitigate impacts from rising sea level, to immediate lifesaving decisions such as a family seeking adequate shelter during a tornado warning. NOAA is committed to building a "Weather-Ready Nation" where communities are prepared for and respond appropriately to these events. The Weather-Ready Nation (WRN) strategic priority is building community resilience in the face of increasing vulnerability to extreme weather, water, climate and environmental threats. To build a Weather-Ready Nation, NOAA is enhancing Impact-Based Decision Support Services (IDSS), transitioning science and technology advances into forecast operations, applying social science research to improve the communication and usefulness of information, and expanding its dissemination efforts to achieve far-reaching readiness, responsiveness and resilience. These four components of Weather-Ready Nation are helping ensure NOAA data, products and services are fully utilized to minimize societal impacts from extreme events. Satellite data and satellite products have been important elements of the national Weather Service (NWS) operations for more than 40 years. When one examines the uses of satellite data specific to the internal forecast and warning operations of NWS, two main applications are evident. The first is the use of satellite data in numerical weather prediction models; the second is the use of satellite imagery and derived products for mesoscale and short-range weather warning and prediction. The purpose of this paper is to highlight the value of the satellite component of the global observing system to NWS operational weather forecasting and emphasize how these data form a critical component of the NWS ability to protect life and property and ensure economic well-being.
Resilient Grid Operational Strategies

DOE Office of Scientific and Technical Information (OSTI.GOV)

Pasqualini, Donatella

Extreme weather-related disturbances, such as hurricanes, are a leading cause of grid outages historically. Although physical asset hardening is perhaps the most common way to mitigate the impacts of severe weather, operational strategies may be deployed to limit the extent of societal and economic losses associated with weather-related physical damage.1 The purpose of this study is to examine bulk power-system operational strategies that can be deployed to mitigate the impact of severe weather disruptions caused by hurricanes, thereby increasing grid resilience to maintain continuity of critical infrastructure during extreme weather. To estimate the impacts of resilient grid operational strategies, Losmore » Alamos National Laboratory (LANL) developed a framework for hurricane probabilistic risk analysis (PRA). The probabilistic nature of this framework allows us to estimate the probability distribution of likely impacts, as opposed to the worst-case impacts. The project scope does not include strategies that are not operations related, such as transmission system hardening (e.g., undergrounding, transmission tower reinforcement and substation flood protection) and solutions in the distribution network.« less
Extremely cold events and sudden air temperature drops during winter season in the Czech Republic

NASA Astrophysics Data System (ADS)

Crhová, Lenka; Valeriánová, Anna; Holtanová, Eva; Müller, Miloslav; Kašpar, Marek; Stříž, Martin

2014-05-01

Today a great attention is turned to analysis of extreme weather events and frequency of their occurrence under changing climate. In most cases, these studies are focused on extremely warm events in summer season. However, extremely low values of air temperature during winter can have serious impacts on many sectors as well (e.g. power engineering, transportation, industry, agriculture, human health). Therefore, in present contribution we focus on extremely and abnormally cold air temperature events in winter season in the Czech Republic. Besides the seasonal extremes of minimum air temperature determined from station data, the standardized data with removed annual cycle are used as well. Distribution of extremely cold events over the season and the temporal evolution of frequency of occurrence during the period 1961-2010 are analyzed. Furthermore, the connection of cold events with extreme sudden temperature drops is studied. The extreme air temperature events and events of extreme sudden temperature drop are assessed using the Weather Extremity Index, which evaluates the extremity (based on return periods) and spatial extent of the meteorological extreme event of interest. The generalized extreme value distribution parameters are used to estimate return periods of daily temperature values. The work has been supported by the grant P209/11/1990 funded by the Czech Science Foundation.
Microwave Atmospheric Sounder on CubeSat

NASA Astrophysics Data System (ADS)

Padmanabhan, S.; Brown, S. E.; Kangaslahti, P.; Cofield, R.; Russell, D.; Stachnik, R. A.; Su, H.; Wu, L.; Tanelli, S.; Niamsuwan, N.

2014-12-01

To accurately predict how the distribution of extreme events may change in the future we need to understand the mechanisms that influence such events in our current climate. Our current observing system is not well-suited for observing extreme events globally due to the sparse sampling and in-homogeneity of ground-based in-situ observations and the infrequent revisit time of satellite observations. Observations of weather extremes, such as extreme precipitation events, temperature extremes, tropical and extra-tropical cyclones among others, with temporal resolution on the order of minutes and spatial resolution on the order of few kms (<10 kms), are required for improved forecasting of extreme weather events. We envision a suite of low-cost passive microwave sounding and imaging sensors on CubeSats that would work in concert with traditional flagship observational systems, such as those manifested on large environmental satellites (i.e. JPSS,WSF,GCOM-W), to monitor weather extremes. A 118/183 GHz sensor would enable observations of temperature and precipitation extremes over land and ocean as well as tropical and extra-tropical cyclones. This proposed project would enable low cost, compact radiometer instrumentation at 118 and 183 GHz that would fit in a 6U Cubesat with the objective of mass-producing this design to enable a suite of small satellites to image the key geophysical parameters needed to improve prediction of extreme weather events. We take advantage of past and current technology developments at JPL viz. HAMSR (High Altitude Microwave Scanning Radiometer), Advanced Component Technology (ACT'08) to enable low-mass, low-power high frequency airborne radiometers. In this paper, we will describe the design and implementation of the 118 GHz temperature sounder and 183 GHz humidity sounder on the 6U CubeSat. In addition, a summary of radiometer calibration and retrieval techniques of temperature and humidity will be discussed. The successful demonstration of this instrument on the 6U CubeSat would pave the way for the development of a constellation which could sample tropospheric temperature and humidity with fine temporal and spatial resolution.
Airborne Deployment and Calibration of Microwave Atmospheric Sounder on 6U CubeSat

NASA Astrophysics Data System (ADS)

Padmanabhan, S.; Brown, S. T.; Lim, B.; Kangaslahti, P.; Russell, D.; Stachnik, R. A.

2015-12-01

To accurately predict how the distribution of extreme events may change in the future we need to understand the mechanisms that influence such events in our current climate. Our current observing system is not well-suited for observing extreme events globally due to the sparse sampling and in-homogeneity of ground-based in-situ observations and the infrequent revisit time of satellite observations. Observations of weather extremes, such as extreme precipitation events, temperature extremes, tropical and extra-tropical cyclones among others, with temporal resolution on the order of minutes and spatial resolution on the order of few kms (<10 kms), are required for improved forecasting of extreme weather events. We envision a suite of low-cost passive microwave sounding and imaging sensors on CubeSats that would work in concert with traditional flagship observational systems, such as those manifested on large environmental satellites (i.e. JPSS,WSF,GCOM-W), to monitor weather extremes. A 118/183 GHz sensor would enable observations of temperature and precipitation extremes over land and ocean as well as tropical and extra-tropical cyclones. This proposed project would enable low cost, compact radiometer instrumentation at 118 and 183 GHz that would fit in a 6U Cubesat with the objective of mass-producing this design to enable a suite of small satellites to image the key geophysical parameters needed to improve prediction of extreme weather events. We take advantage of past and current technology developments at JPL viz. HAMSR (High Altitude Microwave Scanning Radiometer), Advanced Component Technology (ACT'08) to enable low-mass, low-power high frequency airborne radiometers. In this paper, we will describe the design and implementation of the 118 GHz temperature sounder and 183 GHz humidity sounder on the 6U CubeSat. In addition, we will discuss the maiden airborne deployment of the instrument during the Plain Elevated Convection at Night (PECAN) experiment. The successful demonstration of this instrument on the 6U CubeSat would pave the way for the development of a constellation which could sample tropospheric temperature and humidity with fine temporal and spatial resolution.
Forest bat population dynamics over 14 years at a climate refuge: Effects of timber harvesting and weather extremes

PubMed Central

Chidel, Mark; Law, Peter R.

2018-01-01

Long-term data are needed to explore the interaction of weather extremes with habitat alteration; in particular, can ‘refugia’ buffer population dynamics against climate change and are they robust to disturbances such as timber harvesting. Because forest bats are good indicators of ecosystem health, we used 14 years (1999–2012) of mark-recapture data from a suite of small tree-hollow roosting bats to estimate survival, abundance and body condition in harvested and unharvested forest and over extreme El Niño and La Niña weather events in southeastern Australia. Trapping was replicated within an experimental forest, located in a climate refuge, with different timber harvesting treatments. We trapped foraging bats and banded 3043 with a 32% retrap rate. Mark-recapture analyses allowed for dependence of survival on time, species, sex, logging treatment and for transients. A large portion of the population remained resident, with a maximum time to recapture of nine years. The effect of logging history (unlogged vs 16–30 years post-logging regrowth) on apparent survival was minor and species specific, with no detectable effect for two species, a positive effect for one and negative for the other. There was no effect of logging history on abundance or body condition for any of these species. Apparent survival of residents was not strongly influenced by weather variation (except for the smallest species), unlike previous studies outside of refugia. Despite annual variation in abundance and body condition across the 14 years of the study, no relationship with extreme weather was evident. The location of our study area in a climate refuge potentially buffered bat population dynamics from extreme weather. These results support the value of climate refugia in mitigating climate change impacts, though the lack of an external control highlights the need for further studies on the functioning of climate refugia. Relatively stable population dynamics were not compromised by timber harvesting, suggesting ecologically sustainable harvesting may be compatible with climate refugia. PMID:29444115
Space Weathering Perspectives on Europa Amidst the Tempest of the Jupiter Magnetospheric System

NASA Technical Reports Server (NTRS)

Cooper, J. F.; Hartle, R. E.; Lipatov, A. S.; Sittler, E. C.; Cassidy, T. A.; Ip. W.-H.

2010-01-01

Europa resides within a "perfect storm" tempest of extreme external field, plasma, and energetic particle interactions with the magnetospheric system of Jupiter. Missions to Europa must survive, functionally operate, make useful measurements, and return critical science data, while also providing full context on this ocean moon's response to the extreme environment. Related general perspectives on space weathering in the solar system are applied to mission and instrument science requirements for Europa.
Episode of intense chemical weathering during the termination of the 635 Ma Marinoan glaciation.

PubMed

Huang, Kang-Jun; Teng, Fang-Zhen; Shen, Bing; Xiao, Shuhai; Lang, Xianguo; Ma, Hao-Ran; Fu, Yong; Peng, Yongbo

2016-12-27

Cryogenian (∼720-635 Ma) global glaciations (the snowball Earth) represent the most extreme ice ages in Earth's history. The termination of these snowball Earth glaciations is marked by the global precipitation of cap carbonates, which are interpreted to have been driven by intense chemical weathering on continents. However, direct geochemical evidence for the intense chemical weathering in the aftermath of snowball glaciations is lacking. Here, we report Mg isotopic data from the terminal Cryogenian or Marinoan-age Nantuo Formation and the overlying cap carbonate of the basal Doushantuo Formation in South China. A positive excursion of extremely high δ 26 Mg values (+0.56 to +0.95)-indicative of an episode of intense chemical weathering-occurs in the top Nantuo Formation, whereas the siliciclastic component of the overlying Doushantuo cap carbonate has significantly lower δ 26 Mg values (<+0.40), suggesting moderate to low intensity of chemical weathering during cap carbonate deposition. These observations suggest that cap carbonate deposition postdates the climax of chemical weathering, probably because of the suppression of carbonate precipitation in an acidified ocean when atmospheric CO 2 concentration was high. Cap carbonate deposition did not occur until chemical weathering had consumed substantial amounts of atmospheric CO 2 and accumulated high levels of oceanic alkalinity. Our finding confirms intense chemical weathering at the onset of deglaciation but indicates that the maximum weathering predated cap carbonate deposition.
Fast-track extreme event attribution: General methods and techniques to determine the dynamic contribution to an event.

NASA Astrophysics Data System (ADS)

Otto, F. E. L.; Haustein, K.; Uhe, P.; Massey, N.; Rimi, R.; Allen, M. R.; Cullen, H. M.

2016-12-01

Extreme weather event attribution has become an accepted part of the atmospheric sciences with numerous methods having been put forward over the last decade. We have recently established a new framework which allows for event attribution in quasi-real-time. Here we present the methodology with which we can assess the fraction of attributable risk (FAR) of a severe weather event due to an external driver (Haustein et al. 2016). The method builds on a large ensemble of atmosphere-only GCM simulations forced by seasonal forecast SSTs (actual conditions) that are contrasted with ensembles forced by counterfactual SSTs (natural conditions). Having an associated 30 year actual and natural climatology in place, we are able to put the current event into a climatological context and determine the dynamic contribution that lead to the event as opposed to the thermodynamic contribution which would have made such an event more likely regardless of the synoptic situation. As a second independent method (also applicable in near-real-time), we apply pattern correlation to separate thermodynamic and dynamic contributions. Finally, using reanalysis data, we test whether our attributed dynamic contribution is also detectable in the observations. Despite the high monthly variability, ENSO related teleconnection patterns can be detected fairly robustly as we will demonstrate with a recent example during El Nino. The more consistent the 3 methods are, the more robust our results will be. We note that the choice of time scale matters a lot when determining the dynamic contribution as well as estimating the FAR (Uhe et al. 2016). The weather@home ensemble prediction approach is accompanied by two more methods based on observational data and the CMIP5 ensemble. If the FAR across 3 methods is consistent, we have reason to trust our central attribution statement. Two recent examples will be shown in order to demonstrate the feasibility (van Oldenborgh et al. 2016a/2016b), complemented by new results from South Asia where we also investigate the effects of anthropogenic aerosols.
Climate change and viticulture in Mediterranean climates: the complex response of socio-ecosystems. A comparative case study from France and Australia (1955-2040)

NASA Astrophysics Data System (ADS)

Lereboullet, A.-L.; Beltrando, G.; Bardsley, D. K.

2012-04-01

The wine industry is very sensitive to extreme weather events, especially to temperatures above 35°C and drought. In a context of global climate change, Mediterranean climate regions are predicted to experience higher variability in rainfall and temperatures and an increased occurrence of extreme weather events. Some viticultural systems could be particularly at risk in those regions, considering their marginal position in the growth climatic range of Vitis vinifera, the long commercial lifespan of a vineyard, the high added-value of wine and the volatile nature of global markets. The wine industry, like other agricultural systems, is inserted in complex networks of climatic and non-climatic (other physical, economical, social and legislative) components, with constant feedbacks. We use a socio-ecosystem approach to analyse the adaptation of two Mediterranean viticultural systems to recent and future increase of extreme weather events. The present analysis focuses on two wine regions with a hot-summer Mediterranean climate (CSb type in the Köppen classification): Côtes-du-Roussillon in southern France and McLaren Vale in southern Australia. Using climate data from two synoptic weather stations, Perpignan (France) and Adelaide (Australia), with time series running from 1955 to 2010, we highlight changes in rainfall patterns and an increase in the number of days with Tx >35°c since the last three decades in both regions. Climate models (DRIAS project data for France and CSIRO Mk3.5 for Australia) project similar trends in the future. To date, very few projects have focused on an international comparison of the adaptive capacity of viticultural systems to climate change with a holistic approach. Here, the analysis of climate data was complemented by twenty in-depth semi-structured interviews with key actors of the two regional wine industries, in order to analyse adaptation strategies put in place regarding recent climate evolution. This mixed-methods approach allows for a comprehensive assessment of adaptation capacity of the two viticultural systems to future climate change. The strategies of grape growers and wine producers focus on maintaining optimal yields and a constant wine style adapted to markets in a variable and uncertain climate. Their implementation and efficiency depend strongly on non-climatic factors. Thus, adaptation capacity to recent and future climate change depends strongly on adaptation to other non-climatic changes.
Dynamics of 2013 Sudden Stratospheric Warming event and its impact on cold weather over Eurasia: Role of planetary wave reflection

PubMed Central

Nath, Debashis; Chen, Wen; Zelin, Cai; Pogoreltsev, Alexander Ivanovich; Wei, Ke

2016-01-01

In the present study, we investigate the impact of stratospheric planetary wave reflection on tropospheric weather over Central Eurasia during the 2013 Sudden Stratospheric Warming (SSW) event. We analyze EP fluxes and Plumb wave activity fluxes to study the two and three dimensional aspects of wave propagation, respectively. The 2013 SSW event is excited by the combined influence of wavenumber 1 (WN1) and wavenumber 2 (WN2) planetary waves, which makes the event an unusual one and seems to have significant impact on tropospheric weather regime. We observe an extraordinary development of a ridge over the Siberian Tundra and the North Pacific during first development stage (last week of December 2012) and later from the North Atlantic in the second development stage (first week of January 2013), and these waves appear to be responsible for the excitation of the WN2 pattern during the SSW. The wave packets propagated upward and were then reflected back down to central Eurasia due to strong negative wind shear in the upper stratospheric polar jet, caused by the SSW event. Waves that propagated downward led to the formation of a deep trough over Eurasia and brought extreme cold weather over Kazakhstan, the Southern part of Russia and the Northwestern part of China during mid-January 2013. PMID:27051997
Dynamics of 2013 Sudden Stratospheric Warming event and its impact on cold weather over Eurasia: Role of planetary wave reflection.

PubMed

Nath, Debashis; Chen, Wen; Zelin, Cai; Pogoreltsev, Alexander Ivanovich; Wei, Ke

2016-04-07

In the present study, we investigate the impact of stratospheric planetary wave reflection on tropospheric weather over Central Eurasia during the 2013 Sudden Stratospheric Warming (SSW) event. We analyze EP fluxes and Plumb wave activity fluxes to study the two and three dimensional aspects of wave propagation, respectively. The 2013 SSW event is excited by the combined influence of wavenumber 1 (WN1) and wavenumber 2 (WN2) planetary waves, which makes the event an unusual one and seems to have significant impact on tropospheric weather regime. We observe an extraordinary development of a ridge over the Siberian Tundra and the North Pacific during first development stage (last week of December 2012) and later from the North Atlantic in the second development stage (first week of January 2013), and these waves appear to be responsible for the excitation of the WN2 pattern during the SSW. The wave packets propagated upward and were then reflected back down to central Eurasia due to strong negative wind shear in the upper stratospheric polar jet, caused by the SSW event. Waves that propagated downward led to the formation of a deep trough over Eurasia and brought extreme cold weather over Kazakhstan, the Southern part of Russia and the Northwestern part of China during mid-January 2013.
Extremely productive microbial communities in shallow saline pools respond immediately to changing meteorological conditions.

PubMed

Kirschner, A K T; Eiler, A; Zechmeister, T C; Velimirov, B; Herzig, A; Mach, R; Farnleitner, A H

2002-09-01

Diel changes in bacterial and cyanobacterial numbers, as well as heterotrophic bacterial production, were examined in two shallow alkaline pools, harbouring dense populations of cyanobacteria (up to 1100 x 109 cells l-1) and bacteria (up to 500 x 109 cells l-1). Together with the recorded bacterial production rates (925 micro gC l-1x h-1), these values are the highest reported for natural aquatic ecosystems. The investigations were performed during a fair-weather situation, and during a rapid change after a long-term fair-weather situation to thunderstorms and heavy rainfall. During fair weather, bacterial growth was significantly correlated to the diurnal light and temperature cycle. Prokaryotic abundances were fairly constant, and loss by grazing and viral lysis must have been of significant importance. During the invasion of rainy weather, the prokaryotic community showed a strong and immediate response. A significant enhancement of bacterial growth followed after rainfall, suggesting that the high salt concentrations had inhibited bacterial activity. Changes in bacterial and cyanobacterial numbers were consistent with this pattern. From comparison with the available literature, we conclude that diel changes of bacterioplankton are regulated by a complex combination of environmental factors specific for each investigated ecosystem. In the soda pools investigated, external abiotic factors were dominant on a diel scale. In larger ecosystems, such factors are much more buffered and internal biotic interactions may prevail.
DOE Office of Scientific and Technical Information (OSTI.GOV)

Woodroffe, Jesse; Jordanova, Vania; Toth, Gabor

Extreme weather happens worldwide and it takes place in the magnetosphere. The magnetosphere is the place where the majority of earth’s satellites reside. These satellites provide weather forecasting and serve as national defense. When solar storms take place, they can damage satellites.
Early Detection of Lightning Caused Wildfires and Prediction of Wildfire Behavior through Energy Distribution, Atmospherics, Geophysics, the Sun's Azimuth, and Topology

NASA Astrophysics Data System (ADS)

Giesige, C.; Nava, E.

2016-12-01

In the midst of a changing climate we have seen extremes in weather events: lightning, wildfires, hurricanes, tornadoes, and earthquakes. All of these ride on an imbalance of magnetic and electrical distribution about the earth including what goes on from the atmospheric and geophysic levels. There is relevance to the important role the sun plays in developing and feeding of the extreme weather events along with the sun's role helping to create a separation of charges on earth furthering climactic extremes. Focusing attention in North America and on how the sun, atmospheric and geophysic winds come together producing lightning events, there are connections between energy distribution in the environment, lightning caused wildfires, and extreme wildfire behavior. Lightning caused wildfires and extreme fire behavior have become enhanced with the changing climate conditions. Even with strong developments in wildfire science, there remains a lack in full understanding of connections that create a lightning caused wildfire event and lack of monitoring advancements in predicting extreme fire behavior. Several connections have been made in our research allowing us to connect multiple facets of the environment in regards to electric and magnetic influences on wildfires. Among them include: irradiance, winds, pressure systems, humidity, and topology. The connections can be made to develop better detection systems of wildfires, establish with more accuracy areas of highest risk for wildfire and extreme wildfire behavior, and prediction of wildfire behavior. A platform found within the environment can also lead to further understanding and monitoring of other extreme weather events in the future.

Climate teleconnections, weather extremes, and vector-borne disease outbreaks

USDA-ARS?s Scientific Manuscript database

Fluctuations in climate lead to extremes in temperature, rainfall, flooding, and droughts. These climate extremes create ideal ecological conditions that promote mosquito-borne disease transmission that impact global human and animal health. One well known driver of such global scale climate fluctua...
Continued increase of extreme El Niño frequency long after 1.5 °C warming stabilization

NASA Astrophysics Data System (ADS)

Wang, Guojian; Cai, Wenju; Gan, Bolan; Wu, Lixin; Santoso, Agus; Lin, Xiaopei; Chen, Zhaohui; McPhaden, Michael J.

2017-08-01

The Paris Agreement aims to constrain global mean temperature (GMT) increases to 2 °C above pre-industrial levels, with an aspirational target of 1.5 °C. However, the pathway to these targets and the impacts of a 1.5 °C and 2 °C warming on extreme El Niño and La Niña events--which severely influence weather patterns, agriculture, ecosystems, public health and economies--is little known. Here, by analysing climate models participating in the Climate Model Intercomparison Project's Phase 5 (CMIP5; ref. ) under a most likely emission scenario, we demonstrate that extreme El Niño frequency increases linearly with the GMT towards a doubling at 1.5 °C warming. This increasing frequency of extreme El Niño events continues for up to a century after GMT has stabilized, underpinned by an oceanic thermocline deepening that sustains faster warming in the eastern equatorial Pacific than the off-equatorial region. Ultimately, this implies a higher risk of extreme El Niño to future generations after GMT rise has halted. On the other hand, whereas previous research suggests extreme La Niña events may double in frequency under the 4.5 °C warming scenario, the results presented here indicate little to no change under 1.5 °C or 2 °C warming.
The USDA Southern Plains Climate Hub: Regional agricultural management in the context of weather and climate variability and change

USDA-ARS?s Scientific Manuscript database

In the Southern Great Plains of the United States, extremes of weather and climate are the norm. Farmers, ranchers, and foresters rely upon timely and authoritative data and information when making management decisions that are weather- and climate-dependent. In response to the needs of these agricu...
Learning and Risk Exposure in a Changing Climate

NASA Astrophysics Data System (ADS)

Moore, F.

2015-12-01

Climate change is a gradual process most apparent over long time-scales and large spatial scales, but it is experienced by those affected as changes in local weather. Climate change will gradually push the weather people experience outside the bounds of historic norms, resulting in unprecedented and extreme weather events. However, people do have the ability to learn about and respond to a changing climate. Therefore, connecting the weather people experience with their perceptions of climate change requires understanding how people infer the current state of the climate given their observations of weather. This learning process constitutes a first-order constraint on the rate of adaptation and is an important determinant of the dynamic adjustment costs associated with climate change. In this paper I explore two learning models that describe how local weather observations are translated into perceptions of climate change: an efficient Bayesian learning model and a simpler rolling-mean heuristic. Both have a period during which the learner's beliefs about the state of the climate are different from its true state, meaning the learner is exposed to a different range of extreme weather outcomes then they are prepared for. Using the example of surface temperature trends, I quantify this additional exposure to extreme heat events under both learning models and both RCP 8.5 and 2.6. Risk exposure increases for both learning models, but by substantially more for the rolling-mean learner. Moreover, there is an interaction between the learning model and the rate of climate change: the inefficient rolling-mean learner benefits much more from the slower rates of change under RCP 2.6 then the Bayesian. Finally, I present results from an experiment that suggests people are able to learn about a trending climate in a manner consistent with the Bayesian model.
Modernizing Distribution System Restoration to Achieve Grid Resiliency Against Extreme Weather Events: An Integrated Solution

DOE Office of Scientific and Technical Information (OSTI.GOV)

Chen, Chen; Wang, Jianhui; Ton, Dan

Recent severe power outages caused by extreme weather hazards have highlighted the importance and urgency of improving the resilience of the electric power grid. As the distribution grids still remain vulnerable to natural disasters, the power industry has focused on methods of restoring distribution systems after disasters in an effective and quick manner. The current distribution system restoration practice for utilities is mainly based on predetermined priorities and tends to be inefficient and suboptimal, and the lack of situational awareness after the hazard significantly delays the restoration process. As a result, customers may experience an extended blackout, which causes largemore » economic loss. On the other hand, the emerging advanced devices and technologies enabled through grid modernization efforts have the potential to improve the distribution system restoration strategy. However, utilizing these resources to aid the utilities in better distribution system restoration decision-making in response to extreme weather events is a challenging task. Therefore, this paper proposes an integrated solution: a distribution system restoration decision support tool designed by leveraging resources developed for grid modernization. We first review the current distribution restoration practice and discuss why it is inadequate in response to extreme weather events. Then we describe how the grid modernization efforts could benefit distribution system restoration, and we propose an integrated solution in the form of a decision support tool to achieve the goal. The advantages of the solution include improving situational awareness of the system damage status and facilitating survivability for customers. The paper provides a comprehensive review of how the existing methodologies in the literature could be leveraged to achieve the key advantages. The benefits of the developed system restoration decision support tool include the optimal and efficient allocation of repair crews and resources, the expediting of the restoration process, and the reduction of outage durations for customers, in response to severe blackouts due to extreme weather hazards.« less
Changes in heat waves indices in Romania over the period 1961-2015

NASA Astrophysics Data System (ADS)

Croitoru, Adina-Eliza; Piticar, Adrian; Ciupertea, Antoniu-Flavius; Roşca, Cristina Florina

2016-11-01

In the last two decades many climate change studies have focused on extreme temperatures as they have a significant impact on environment and society. Among the weather events generated by extreme temperatures, heat waves are some of the most harmful. The main objective of this study was to detect and analyze changes in heat waves in Romania based on daily observation data (maximum and minimum temperature) over the extended summer period (May-Sept) using a set of 10 indices and to explore the spatial patterns of changes. Heat wave data series were derived from daily maximum and minimum temperature data sets recorded in 29 weather stations across Romania over a 55-year period (1961-2015). In this study, the threshold chosen was the 90th percentile calculated based on a 15-day window centered on each calendar day, and for three baseline periods (1961-1990, 1971-2000, and 1981-2010). Two heat wave definitions were considered: at least three consecutive days when maximum temperature exceeds 90th percentile, and at least three consecutive days when minimum temperature exceeds 90th percentile. For each of them, five variables were calculated: amplitude, magnitude, number of events, duration, and frequency. Finally, 10 indices resulted for further analysis. The main results are: most of the indices have statistically significant increasing trends; only one index for one weather station indicated statistically significant decreasing trend; the changes are more intense in case of heat waves detected based on maximum temperature compared to those obtained for heat waves identified based on minimum temperature; western and central regions of Romania are the most exposed to increasing heat waves.
A Modeling Study of the Causes and Predictability of the Spring 2011 Extreme U.S. Weather Activity

NASA Technical Reports Server (NTRS)

Schubert, Siegfried D.; Chang, Yehui; Wang, Hailan; Koster, Randal; Suarez, Max

2016-01-01

This study examines the causes and predictability of the spring 2011 U.S. extreme weather using the Modern-Era Retrospective Analysis for Research and Applications (MERRA) and Goddard Earth Observing System Model, version 5, (GEOS-5) atmospheric general circulation model simulations. The focus is on assessing the impact on precipitation of sea surface temperature (SST) anomalies, land conditions, and large-scale atmospheric modes of variability. A key result is that the April record-breaking precipitation in the Ohio River valley was primarily the result of the unforced development of a positive North Atlantic Oscillation (NAO)-like mode of variability with unusually large amplitude, limiting the predictability of the precipitation in that region at 1-month leads. SST forcing (La Nia conditions) contributed to the broader continental-scale pattern of precipitation anomalies, producing drying in the southern plains and weak wet anomalies in the northeast, while the impact of realistic initial North American land conditions was to enhance precipitation in the upper Midwest and produce deficits in the Southeast. It was further found that 1) the 1 March atmospheric initial condition was the primary source of the ensemble mean precipitation response over the eastern United States in April (well beyond the limit of weather predictability), suggesting an influence on the initial state of the previous SST forcing and/or tropospheric/stratospheric coupling linked to an unusually persistent and cold polar vortex; and 2) stationary wave model experiments suggest that the SST-forced base state for April enhanced the amplitude of the NAO response compared to that of the climatological state, though the impact is modest and can be of either sign.
Wildland fire as a self-regulating mechanism: the role of previous burns and weather in limiting fire progression.

PubMed

Parks, Sean A; Holsinger, Lisa M; Miller, Carol; Nelson, Cara R

2015-09-01

Theory suggests that natural fire regimes can result in landscapes that are both self-regulating and resilient to fire. For example, because fires consume fuel, they may create barriers to the spread of future fires, thereby regulating fire size. Top-down controls such as weather, however, can weaken this effect. While empirical examples demonstrating this pattern-process feedback between vegetation and fire exist, they have been geographically limited or did not consider the influence of time between fires and weather. The availability of remotely sensed data identifying fire activity over the last four decades provides an opportunity to explicitly quantify-the ability of wildland fire to limit the progression of subsequent fire. Furthermore, advances in fire progression mapping now allow an evaluation of how daily weather as a top-down control modifies this effect. In this study, we evaluated the ability of wildland fire to create barriers that limit the spread of subsequent fire along a gradient representing time between fires in four large study areas in the western United States. Using fire progression maps in conjunction with weather station data, we also evaluated the influence of daily weather. Results indicate that wildland fire does limit subsequent fire spread in all four study areas, but this effect decays over time; wildland fire no longer limits subsequent fire spread 6-18 years after fire, depending on the study area. We also found that the ability of fire to regulate, subsequent fire progression was substantially reduced under extreme conditions compared to moderate weather conditions in all four study areas. This study increases understanding of the spatial feedbacks that can lead to self-regulating landscapes as well as the effects of top-down controls, such as weather, on these feedbacks. Our results will be useful to managers who seek to restore natural fire regimes or to exploit recent burns when managing fire.
Tools in Support of Planning for Weather and Climate Extremes

NASA Astrophysics Data System (ADS)

Done, J.; Bruyere, C. L.; Hauser, R.; Holland, G. J.; Tye, M. R.

2016-12-01

A major limitation to planning for weather and climate extremes is the lack of maintained and readily available tools that can provide robust and well-communicated predictions and advice on their impacts. The National Center for Atmospheric Research is facilitating a collaborative international program to develop and support such tools within its Capacity Center for Climate and Weather Extremes aimed at improving community resilience planning and reducing weather and climate impacts. A Global Risk, Resilience and Impacts Toolbox is in development and will provide: A portable web-based interface to process work requests from a variety of users and locations; A sophisticated framework that enables specialized community tools to access a comprehensive database (public and private) of geo-located hazard, vulnerability, exposure, and loss data; A community development toolkit that enables and encourages community tool developments geared towards specific user management and planning needs, and A comprehensive community support facilitated by NCAR utilizing tutorials and a help desk. A number of applications are in development, built off the latest climate science, and in collaboration with private industry and local and state governments. Example applications will be described, including a hurricane damage tool in collaboration with the reinsurance sector, and a weather management tool for the construction industry. These examples will serve as starting points to discuss the broader potential of the toolbox.
Urban Form and Extreme Heat Events: Are Sprawling Cities More Vulnerable to Climate Change Than Compact Cities?

PubMed Central

Stone, Brian; Hess, Jeremy J.; Frumkin, Howard

2010-01-01

Background Extreme heat events (EHEs) are increasing in frequency in large U.S. cities and are responsible for a greater annual number of climate-related fatalities, on average, than any other form of extreme weather. In addition, low-density, sprawling patterns of urban development have been associated with enhanced surface temperatures in urbanized areas. Objectives In this study. we examined the association between urban form at the level of the metropolitan region and the frequency of EHEs over a five-decade period. Methods We employed a widely published sprawl index to measure the association between urban form in 2000 and the mean annual rate of change in EHEs between 1956 and 2005. Results We found that the rate of increase in the annual number of EHEs between 1956 and 2005 in the most sprawling metropolitan regions was more than double the rate of increase observed in the most compact metropolitan regions. Conclusions The design and management of land use in metropolitan regions may offer an important tool for adapting to the heat-related health effects associated with ongoing climate change. PMID:21114000
Hydrological Responses of Weather Conditions and Crop Change of Agricultural Area in the Rincon Valley, New Mexico

NASA Astrophysics Data System (ADS)

Ahn, S.; Sheng, Z.; Abudu, S.

2017-12-01

Hydrologic cycle of agricultural area has been changing due to the impacts of climate and land use changes (crop coverage changes) in an arid region of Rincon Valley, New Mexico. This study is to evaluate the impacts of weather condition and crop coverage change on hydrologic behavior of agricultural area in Rincon Valley (2,466km2) for agricultural watershed management using a watershed-scale hydrologic model, SWAT (Soil and Water Assessment Tool). The SWAT model was developed to incorporate irrigation of different crops using auto irrigation function. For the weather condition and crop coverage change evaluation, three spatial crop coverages including a normal (2008), wet (2009), and dry (2011) years were prepared using USDA crop data layer (CDL) for fourteen different crops. The SWAT model was calibrated for the period of 2001-2003 and validated for the period of 2004-2006 using daily-observed streamflow data. Scenario analysis was performed for wet and dry years based on the unique combinations of crop coverages and releases from Caballo Reservoir. The SWAT model simulated the present vertical water budget and horizontal water transfer considering irrigation practices in the Rincon Valley. Simulation results indicated the temporal and spatial variability for irrigation and non-irrigation seasons of hydrologic cycle in agricultural area in terms of surface runoff, evapotranspiration, infiltration, percolation, baseflow, soil moisture, and groundwater recharge. The water supply of the dry year could not fully cover whole irrigation period due to dry weather conditions, resulting in reduction of crop acreage. For extreme weather conditions, the temporal variation of water budget became robust, which requires careful irrigation management of the agricultural area. The results could provide guidelines for farmers to decide crop patterns in response to different weather conditions and water availability.
Summary of Natural Hazard Statistics for 2017 in the United States

MedlinePlus

... Damage Costs Weather Event Convection Lightning Tornado Thunderstorm Wind Hail Extreme Temperatures Cold Heat Flood Flash Flood ... Drought Dust Storm Dust Devil Rain Fog High Wind Waterspout Fire Weather Mud Slide Volcanic Ash Miscellaneous ...
78 FR 51267 - Hours of Service of Drivers: National Ready Mixed Concrete Association; Application for Exemption

Federal Register 2010, 2011, 2012, 2013, 2014

2013-08-20

... rule is extremely difficult due to the numerous variables associated with delivery (e.g., weather... 2 hours resulting from weather or unforeseen construction delays. NRMCA claims that these frequent...
Summary of Natural Hazard Statistics for 2015 in the United States

MedlinePlus

... Damage Costs Weather Event Convection Lightning Tornado Thunderstorm Wind Hail Extreme Temperatures Cold Heat Flood Flash Flood ... Drought Dust Storm Dust Devil Rain Fog High Wind Waterspout Fire Weather Mud Slide Volcanic Ash Miscellaneous ...
Predictability of the atmospheric conditions leading to extreme weather events in the Western Mediterranean Region in comparison with the seasonal mean conditions

NASA Astrophysics Data System (ADS)

Khodayar, Samiro; Kalthoff, Norbert

2013-04-01

Among all severe convective weather situations, fall season heavy rainfall represents the most threatening phenomenon in the western Mediterranean region. Devastating flash floods occur every year somewhere in eastern Spain, southern France, Italy, or North Africa, being responsible for a great proportion of the fatalities, property losses, and destruction of infrastructure caused by natural hazards. Investigations in the area have shown that most of the heavy rainfall events in this region can be attributed to mesoscale convective systems. The main goal of this investigation is to understand and identify the atmospheric conditions that favor the initiation and development of such systems. Insight of the involved processes and conditions will improve their predictability and help preventing some of the fatal consequences related with the occurrence of these weather phenomena. The HyMeX (Hydrological cycle in the Mediterranean eXperiment) provides a unique framework to investigate this issue. Making use of high-resolution seasonal simulations with the COSMO-CLM model the mean atmospheric conditions of the fall season, September, October and November, are investigated in different western Mediterranean regions such as eastern Spain, Southern France, northern Africa and Italy. The precipitation distribution, its daily cycle, and probability distribution function are evaluated to ascertain the similarities and differences between the regions of interest, as well as the spatial distribution of extreme events. Additionally, the regional differences of the boundary layer and mid-tropospheric conditions, atmospheric stability and inhibition, and low-level triggering are presented. Selected high impact weather HyMeX episodes' are analyzed with special focus on the atmospheric pre-conditions leading to the extreme weather situations. These pre-conditions are then compared to the mean seasonal conditions to identify and point out possible anomalies in the atmospheric conditions which could favor the initiation and intensification of extreme precipitation weather events.
Changes in field workability and drought risk from projected climate change drive spatially variable risks in Illinois cropping systems.

PubMed

Tomasek, Bradley J; Williams, Martin M; Davis, Adam S

2017-01-01

As weather patterns become more volatile and extreme, risks introduced by weather variability will become more critical to agricultural production. The availability of days suitable for field work is driven by soil temperature and moisture, both of which may be altered by climate change. We projected changes in Illinois season length, spring field workability, and summer drought risk under three different emissions scenarios (B1, A1B, and A2) down to the crop district scale. Across all scenarios, thermal time units increased in parallel with a longer frost-free season. An increase in late March and Early April field workability was consistent across scenarios, but a decline in overall April through May workable days was observed for many cases. In addition, summer drought metrics were projected to increase for most scenarios. These results highlight how the spatial and temporal variability in climate change may present unique challenges to mitigation and adaptation efforts.
Tsunamis

MedlinePlus

... Extreme Heat Older Adults (Aged 65+) Infants and Children Chronic Medical Conditions Low Income Athletes Outdoor Workers Pets Hot Weather Tips Warning Signs and Symptoms FAQs Social Media How to Stay Cool Missouri Cooling Centers Extreme ...
Volcanoes

MedlinePlus

... Extreme Heat Older Adults (Aged 65+) Infants and Children Chronic Medical Conditions Low Income Athletes Outdoor Workers Pets Hot Weather Tips Warning Signs and Symptoms FAQs Social Media How to Stay Cool Missouri Cooling Centers Extreme ...
Low-frequency climate anomalies, changes in synoptic scale circulation patterns and statistics of extreme events over south-east Poland during the Last Millennium

NASA Astrophysics Data System (ADS)

Slawinska, J. M.; Bartoszek, K.; Gabriel, C. J.

2016-12-01

Long-term predictions of changes in extreme event frequency are of utmost importance due to their high societal and economic impact. Yet, current projections are of limited skills as they rely on satellite records that are relatively short compared to the timescale of interest, and also due to the presence of a significant anthropogenic trend superimposed onto other low-frequency variabilities. Novel simulations of past climates provide unique opportunity to separate external perturbations from internal climate anomalies and to attribute the latter to systematic changes in different types of synoptic scale circulation and distributions of high-frequency events. Here we study such changes by employing the Last Millennium Ensemble of climate simulations carried out with the Community Earth System Model (CESM) at the U.S. National Center for Atmospheric Research, focusing in particular on decadal changes in frequency of extreme precipitation events over south-east Poland. We analyze low-frequency modulations of dominant patterns of synoptic scale circulations over Europe and their dependence on the Atlantic Meridional Overturning Circulation, along with their coupling with the North Atlantic Oscillation. Moreover, we examine whether some decades of persistently anomalous statistics of extreme events can be attributed to externally forced (e.g., via volcanic eruptions) perturbations of the North Atlantic climate. In the end, we discuss the possible linkages and physical mechanisms connecting volcanic eruptions, low-frequency variabilities of North Atlantic climate and changes in statistics of high impact weather, and compare briefly our results with some historical and paleontological records.
Impacts of future changes in weather condition on U.S. transportation

NASA Astrophysics Data System (ADS)

Ashfaq, M.; Pagan, B. R.; Bonds, B. W.; Rastogi, D.

2016-12-01

High-resolution near-term climate projections suggest an intensification of the regional hydrological cycle over the U.S., leading to stronger and more frequent precipitation events. Increase in precipitation extremes is driven by both warm season convection driven rainstorms and frontal based cold season snowstorms. Results also indicate that future warming is driven more by hot extremes, as decrease in cold extremes is three times less than increase in hot extremes. While projected changes may likely impact the transportation system across the U.S., accurate estimation of such impacts requires knowledge of changes in precipitation types (rain, snow, ice, freezing rain). Here we apply four commonly used precipitation typing algorithms to determine different types of precipitation in an 11-memebr high-resolution (18 km) climate projections dataset that covers 40 years (1966-2005) in the baseline and 40 years (2011-2050) in the future period under Representative Concentration Pathway 8.5. The results are compared with the NARR-based precipitation classification in the historical period at the county level. Documented weather related county level fatal crash data for the CONUS and non-fatal crash data for selected states in the eastern half of the U.S. is compiled to develop the historical baseline for the impact of weather conditions on transportation. Further analysis is carried out to understand the ability of an ensemble of high-resolution simulations to produce different precipitation types in the baseline period, potential changes in the occurrence of each type of weather condition in the future period and that how such changes may impact road conditions, vehicle crashes and human fatalities. Additional analysis will also be explored to understand the impact of changes in winter weather conditions on the cost associated with road maintenance.

Quantitative methods for stochastic high frequency spatio-temporal and non-linear analysis: Assessing health effects of exposure to extreme ambient temperature

NASA Astrophysics Data System (ADS)

Liss, Alexander

Extreme weather events, such as heat waves and cold spells, cause substantial excess mortality and morbidity in the vulnerable elderly population, and cost billions of dollars. The accurate and reliable assessment of adverse effects of extreme weather events on human health is crucial for environmental scientists, economists, and public health officials to ensure proper protection of vulnerable populations and efficient allocation of scarce resources. However, the methodology for the analysis of large national databases is yet to be developed. The overarching objective of this dissertation is to examine the effect of extreme weather on the elderly population of the Conterminous US (ConUS) with respect to seasonality in temperature in different climatic regions by utilizing heterogeneous high frequency and spatio-temporal resolution data. To achieve these goals the author: 1) incorporated dissimilar stochastic high frequency big data streams and distinct data types into the integrated data base for use in analytical and decision support frameworks; 2) created an automated climate regionalization system based on remote sensing and machine learning to define climate regions for the Conterminous US; 3) systematically surveyed the current state of the art and identified existing gaps in the scientific knowledge; 4) assessed the dose-response relationship of exposure to temperature extremes on human health in relatively homogeneous climate regions using different statistical models, such as parametric and non-parametric, contemporaneous and asynchronous, applied to the same data; 5) assessed seasonal peak timing and synchronization delay of the exposure and the disease within the framework of contemporaneous high frequency harmonic time series analysis and modification of the effect by the regional climate; 6) modeled using hyperbolic functional form non-linear properties of the effect of exposure to extreme temperature on human health. The proposed climate regionalization method algorithmically forms eight climatically homogeneous regions for Conterminous US from satellite Remote Sensing inputs. The relative risk of hospitalizations due to extreme ambient temperature varied across climatic regions. Difference in regional hospitalization rates suggests presence of an adaptation effect to a prevailing climate. In various climatic regions the hospitalizations peaked earlier than the peak of exposure. This suggests disproportionally high impact of extreme weather events, such as cold spells or heat waves when they occur early in the season. These findings provide an insight into the use of high frequency disjoint data sets for the assessment of the magnitude, timing, synchronization and non-linear properties of adverse health consequences due to exposure to extreme weather events to the elderly in defined climatic regions. These findings assist in the creation of decision support frameworks targeting preventions and adaptation strategies such as improving infrastructure, providing energy assistance, education and early warning notifications for the vulnerable population. This dissertation offers a number of methodological innovations for the assessment of the high frequency spatio-temporal and non-linear impacts of extreme weather events on human health. These innovations help to ensure an improved protection of the elderly population, aid policy makers in the development of efficient disaster prevention strategies, and facilitate more efficient allocation of scarce resources.
Environmental Composites for Bomb Cyclones of the Western North Atlantic in Reanalysis, 1948-2016.

NASA Astrophysics Data System (ADS)

Adams, R.; Sheridan, S. C.

2017-12-01

"Bomb" cyclones represent a small subset of mid-latitude cyclones characterized by rapid intensification and frequently are associated with extreme weather conditions along the eastern coast of North America. Like other extreme phenomena, bomb cyclone predictions are prone to error leading to inadequate or untimely hazard warnings. The rare nature of bomb cyclones and the uniqueness of their evolutions has made it difficult for researchers to make meaningful generalizations on bomb cyclone events. This paper describes bomb cyclone climatology for the western North Atlantic, using data from the NCEP-NCAR Reanalysis for 1948-2016, and uses a synoptic climatological analysis to relate these bombs to their associated atmospheric environments. A self-organizing map (SOM) of 300-hPa geopotential height tendency is created to partition the regional atmospheric environment. Thermodynamic fields are contrasted by each 300-hPa geopotential height tendency pattern for both bomb and non-bomb events in composite difference maps. The SOM patterns most significantly associated with western North Atlantic bomb cyclogenesis are characterized by both strongly and weakly negative height tendencies along the eastern United States. In both cases, these patterns exhibit strong meridional flow, a distinction marked by the weakening and breaking down of the polar vortex in the boreal Winter. The composite maps for each pattern show the mean differences in low-mid level ascent and near surface thermodynamics for bomb environments contrasted with non-bomb environments, resulting in diverse spatiotemporal distributions of bombs in the western North Atlantic.
Bomb Cyclones Of The Western North Atlantic

NASA Astrophysics Data System (ADS)

Adams, Ryan E.

"Bomb" cyclones represent a small subset of mid-latitude cyclones characterized by rapid intensification and frequently are associated with extreme weather conditions along the eastern coast of North America. Like other extreme phenomena, bomb cyclone predictions are prone to error leading to inadequate or untimely hazard warnings. The rare nature of bomb cyclones and the uniqueness of their evolutions has made it difficult for researchers to make meaningful generalizations on bomb cyclone events. This paper describes bomb cyclone climatology for the western North Atlantic, using data from the NCEP-NCAR Reanalysis for 1948-2016, and uses a synoptic climatological analysis to relate these bombs to their associated atmospheric environments. A self-organizing map (SOM) of 300-hPa geopotential height tendency is created to partition the regional atmospheric environment. Thermodynamic fields are contrasted by each 300-hPa geopotential height tendency pattern for both bomb and non-bomb events in composite difference maps. The SOM patterns most significantly associated with western North Atlantic bomb cyclogenesis are characterized by both strongly and weakly negative height tendencies along the eastern United States. In both cases, these patterns exhibit strong meridional flow, a distinction marked by the weakening and breaking down of the polar vortex in the boreal Winter. The composite maps for each pattern show the mean differences in low-mid level ascent and near surface thermodynamics for bomb environments contrasted with non-bomb environments, resulting in diverse spatiotemporal distributions of bombs in the western North Atlantic.
Robust Engineering Designs for Infrastructure Adaptation to a Changing Climate

NASA Astrophysics Data System (ADS)

Samaras, C.; Cook, L.

2015-12-01

Infrastructure systems are expected to be functional, durable and safe over long service lives - 50 to over 100 years. Observations and models of climate science show that greenhouse gas emissions resulting from human activities have changed climate, weather and extreme events. Projections of future changes (albeit with uncertainties caused by inadequacies of current climate/weather models) can be made based on scenarios for future emissions, but actual future emissions are themselves uncertain. Most current engineering standards and practices for infrastructure assume that the probabilities of future extreme climate and weather events will match those of the past. Climate science shows that this assumption is invalid, but is unable, at present, to define these probabilities over the service lives of existing and new infrastructure systems. Engineering designs, plans, and institutions and regulations will need to be adaptable for a range of future conditions (conditions of climate, weather and extreme events, as well as changing societal demands for infrastructure services). For their current and future projects, engineers should: Involve all stakeholders (owners, financers, insurance, regulators, affected public, climate/weather scientists, etc.) in key decisions; Use low regret, adaptive strategies, such as robust decision making and the observational method, comply with relevant standards and regulations, and exceed their requirements where appropriate; Publish design studies and performance/failure investigations to extend the body of knowledge for advancement of practice. The engineering community should conduct observational and modeling research with climate/weather/social scientists and the concerned communities and account rationally for climate change in revised engineering standards and codes. This presentation presents initial research on decisionmaking under uncertainty for climate resilient infrastructure design.
Sustainable Arctic observing network for predicting weather extremes in mid-latitudes

NASA Astrophysics Data System (ADS)

Inoue, J.; Sato, K.; Yamazaki, A.

2016-12-01

Routine atmospheric observations within and over the Arctic Ocean are very expensive and difficult to conduct because of factors such as logistics and the harsh environment. Nevertheless, the great benefit of such observations is their contribution to an improvement of skills of weather predictions over the Arctic and mid-latitudes. The Year of Polar Prediction (YOPP) from mid-2017 to mid-2019 proposed by the World Weather Research Programme - Polar Prediction Project (WWRP-PPP) would be the best opportunity to address the issues. The combination of observations and data assimilation is an effective way to understand the predictability of weather extremes in mid-latitudes. This talk presents the current activities related to PPP based on international special radiosonde observing network in the Arctic, and challenges toward YOPP. Comparing with summer and winter cases, the additional observations over the Arctic during winter were more effective for improving the predicting skills of weather extremes because the impact of the observations would be carried toward the mid-latitudes by the stronger jet stream and its frequent meanderings. During summer, on the other hand, the impact of extra observations was localized over the Arctic region but still important for precise weather forecasts over the Arctic Ocean, contributing to safe navigation along the Northern Sea Route. To consolidate the sustainable Arctic radiosonde observing network, increasing the frequency of observations at Arctic coastal stations, instead of commissioning special observations from ships and ice camps, would be a feasible way. In fact, several existing stations facing the Arctic Ocean have already increased the frequency of observations during winter and/or summer.
Extreme Weather Years Drive Episodic Acidification and Brownification in Lakes in the Northeast US: Implications for Long-term Shifts in Dissolved Organic Carbon, Water Clarity, and Thermal Structure

NASA Astrophysics Data System (ADS)

Strock, K.; Saros, J. E.

2017-12-01

Interannual climate variability is expected to increase over the next century, but the extent to which hydroclimatic variability influences biogeochemical processes is unclear. To determine the effects of extreme weather on surface water chemistry, a 30-year record of surface water geochemistry for 84 lakes in the northeastern U.S. was combined with landscape data and watershed-specific weather data. With these data, responses in sulfate and dissolved organic carbon (DOC) concentrations were characterized during extreme wet and extreme dry conditions. Episodic acidification during drought and episodic brownification (increased DOC) during wet years were detected broadly across the northeastern U.S. Episodic chemical response was linearly related to wetland coverage in lake watersheds only during extreme wet years. The results of a redundancy analysis suggest that topographic features also need to be considered and that the interplay between wetlands and their degree of connectivity to surface waters could be driving episodic acidification in this region. A subset of lakes located in Acadia National Park, Maine U.S.A. were studied to better understand the implications of regional increases of DOC in lakes. Water transparency declined across six study sites since 1995 as DOC increased. As clarity declined, some lakes experienced reduced epilimnion thickness. The degree to which transparency changed across the lakes was dependent on DOC concentration, with a larger decline in transparency occurring in clear water lakes than brown water lakes. The results presented here help to clarify the variability observed in long-term recovery from acidification and regional increases in DOC. Specifically, an increased frequency of extreme wet years may be contributing to a recent acceleration in the recovery of lake ecosystems from acidification; however, increased frequency of wet years may also lead to reduced water clarity and altered physical lake habitat. Clarifying the response of DOC, a pivotal regulator of aquatic ecosystems, to extreme weather events across gradients of landscape position and atmospheric deposition, is increasingly important for policy and management decisions as the frequency of extreme events continues to increase in this region.
Extreme Magnetic Storms: Their Characteristics and Possible Consequences for Humanity

NASA Astrophysics Data System (ADS)

Falkowski, B. J.; Tsurutani, B.; Lakhina, G. S.; Deng, Y.; Mannucci, A. J.

2015-12-01

The solar and interplanetary conditions necessary to create an extreme magnetic storm will be discussed. The Carrington 1859 event was not the largest possible. It will be shown that different facets of fast ICMEs/extreme magnetic storms will have different limitations. Some possible adverse effects of such extreme space weather events on society will be addressed.
Reactions of Air Transport Flight Crews to Displays of Weather During Simulated Flight

NASA Technical Reports Server (NTRS)

Bliss, James P.; Fallon, Corey; Bustamante, Ernesto; Bailey, William R., III; Anderson, Brittany

2005-01-01

Display of information in the cockpit has long been a challenge for aircraft designers. Given the limited space in which to present information, designers have had to be extremely selective about the types and amount of flight related information to present to pilots. The general goal of cockpit display design and implementation is to ensure that displays present information that is timely, useful, and helpful. This suggests that displays should facilitate the management of perceived workload, and should allow maximal situation awareness. The formatting of current and projected weather displays represents a unique challenge. As technologies have been developed to increase the variety and capabilities of weather information available to flight crews, factors such as conflicting weather representations and increased decision importance have increased the likelihood for errors. However, if formatted optimally, it is possible that next generation weather displays could allow for clearer indications of weather trends such as developing or decaying weather patterns. Important issues to address include the integration of weather information sources, flight crew trust of displayed weather information, and the teamed reactivity of flight crews to displays of weather. Past studies of weather display reactivity and formatting have not adequately addressed these issues; in part because experimental stimuli have not approximated the complexity of modern weather displays, and in part because they have not used realistic experimental tasks or participants. The goal of the research reported here was to investigate the influence of onboard and NEXRAD agreement, range to the simulated potential weather event, and the pilot flying on flight crew deviation decisions, perceived workload, and perceived situation awareness. Fifteen pilot-copilot teams were required to fly a simulated route while reacting to weather events presented in two graphical formats on a separate visual display. Measures of flight crew reactions included performance-based measures such as deviation decision accuracy, and judgment-based measures such as perceived decision confidence, workload, situation awareness, and display trust. Results demonstrated that pilots adopted a conservative reaction strategy, often choosing to deviate from weather rather than ride through it. When onboard and NEXRAD displays did not agree, flight crews reacted in a complex manner, trusting the onboard system more but using the NEXRAD system to augment their situation awareness. Distance to weather reduced situation awareness and heightened workload levels. Overall, flight crews tended to adopt a participative leadership style marked by open communication. These results suggest that future weather displays should exploit the existing benefits of NEXRAD presentation for situation awareness while retaining the display structure and logic inherent in the onboard system.
Motivating and Facilitating Advancements in Space Weather Real-Time Data Availability: Factors, Data, and Access Methods

NASA Astrophysics Data System (ADS)

Pankratz, C. K.; Baker, D. N.; Jaynes, A. N.; Elkington, S. R.; Baltzer, T.; Sanchez, F.

2017-12-01

Society's growing reliance on complex and highly interconnected technological systems makes us increasingly vulnerable to the effects of space weather events - maybe more than for any other natural hazard. An extreme solar storm today could conceivably impact hundreds of the more than 1400 operating Earth satellites. Such an extreme storm could cause collapse of the electrical grid on continental scales. The effects on navigation, communication, and remote sensing of our home planet could be devastating to our social functioning. Thus, it is imperative that the scientific community address the question of just how severe events might become. At least as importantly, it is crucial that policy makers and public safety officials be informed by the facts on what might happen during extreme conditions. This requires essentially real-time alerts, warnings, and also forecasts of severe space weather events, which in turn demands measurements, models, and associated data products to be available via the most effective data discovery and access methods possible. Similarly, advancement in the fundamental scientific understanding of space weather processes is also vital, requiring that researchers have convenient and effective access to a wide variety of data sets and models from multiple sources. The space weather research community, as with many scientific communities, must access data from dispersed and often uncoordinated data repositories to acquire the data necessary for the analysis and modeling efforts that advance our understanding of solar influences and space physics on the Earth's environment. The Laboratory for Atmospheric and Space Physics (LASP), as a leading institution in both producing data products and advancing the state of scientific understanding of space weather processes, is well positioned to address many of these issues. In this presentation, we will outline the motivating factors for effective space weather data access, summarize the various data and models that are available, and present methods for meeting the data management and access needs of the disparate communities who require low-latency space weather data and information.
Predictability of extreme weather events for NE U.S.: improvement of the numerical prediction using a Bayesian regression approach

NASA Astrophysics Data System (ADS)

Yang, J.; Astitha, M.; Anagnostou, E. N.; Hartman, B.; Kallos, G. B.

2015-12-01

Weather prediction accuracy has become very important for the Northeast U.S. given the devastating effects of extreme weather events in the recent years. Weather forecasting systems are used towards building strategies to prevent catastrophic losses for human lives and the environment. Concurrently, weather forecast tools and techniques have evolved with improved forecast skill as numerical prediction techniques are strengthened by increased super-computing resources. In this study, we examine the combination of two state-of-the-science atmospheric models (WRF and RAMS/ICLAMS) by utilizing a Bayesian regression approach to improve the prediction of extreme weather events for NE U.S. The basic concept behind the Bayesian regression approach is to take advantage of the strengths of two atmospheric modeling systems and, similar to the multi-model ensemble approach, limit their weaknesses which are related to systematic and random errors in the numerical prediction of physical processes. The first part of this study is focused on retrospective simulations of seventeen storms that affected the region in the period 2004-2013. Optimal variances are estimated by minimizing the root mean square error and are applied to out-of-sample weather events. The applicability and usefulness of this approach are demonstrated by conducting an error analysis based on in-situ observations from meteorological stations of the National Weather Service (NWS) for wind speed and wind direction, and NCEP Stage IV radar data, mosaicked from the regional multi-sensor for precipitation. The preliminary results indicate a significant improvement in the statistical metrics of the modeled-observed pairs for meteorological variables using various combinations of the sixteen events as predictors of the seventeenth. This presentation will illustrate the implemented methodology and the obtained results for wind speed, wind direction and precipitation, as well as set the research steps that will be followed in the future.
Relationship between fine particulate matter, weather condition and daily non-accidental mortality in Shanghai, China: A Bayesian approach.

PubMed

Fang, Xin; Fang, Bo; Wang, Chunfang; Xia, Tian; Bottai, Matteo; Fang, Fang; Cao, Yang

2017-01-01

There are concerns that the reported association of ambient fine particulate matter (PM2.5) with mortality might be a mixture of PM2.5 and weather conditions. We evaluated the effects of extreme weather conditions and weather types on mortality as well as their interactions with PM2.5 concentrations in a time series study. Daily non-accidental deaths, individual demographic information, daily average PM2.5 concentrations and meteorological data between 2012 and 2014 were obtained from Shanghai, China. Days with extreme weather conditions were identified. Six synoptic weather types (SWTs) were generated. The generalized additive model was set up to link the mortality with PM2.5 and weather conditions. Parameter estimation was based on Bayesian methods using both the Jeffreys' prior and an informative normal prior in a sensitivity analysis. We estimate the percent increase in non-accidental mortality per 10 μg/m3 increase in PM2.5 concentration and constructed corresponding 95% credible interval (CrI). In total, 336,379 non-accidental deaths occurred during the study period. Average daily deaths were 307. The results indicated that per 10 μg/m3 increase in daily average PM2.5 concentration alone corresponded to 0.26-0.35% increase in daily non-accidental mortality in Shanghai. Statistically significant positive associations between PM2.5 and mortality were found for favorable SWTs when considering the interaction between PM2.5 and SWTs. The greatest effect was found in hot dry SWT (percent increase = 1.28, 95% CrI: 0.72, 1.83), followed by warm humid SWT (percent increase = 0.64, 95% CrI: 0.15, 1.13). The effect of PM2.5 on non-accidental mortality differed under specific extreme weather conditions and SWTs. Environmental policies and actions should take into account the interrelationship between the two hazardous exposures.
Relationship between fine particulate matter, weather condition and daily non-accidental mortality in Shanghai, China: A Bayesian approach

PubMed Central

Wang, Chunfang; Xia, Tian; Bottai, Matteo; Fang, Fang; Cao, Yang

2017-01-01

There are concerns that the reported association of ambient fine particulate matter (PM2.5) with mortality might be a mixture of PM2.5 and weather conditions. We evaluated the effects of extreme weather conditions and weather types on mortality as well as their interactions with PM2.5 concentrations in a time series study. Daily non-accidental deaths, individual demographic information, daily average PM2.5 concentrations and meteorological data between 2012 and 2014 were obtained from Shanghai, China. Days with extreme weather conditions were identified. Six synoptic weather types (SWTs) were generated. The generalized additive model was set up to link the mortality with PM2.5 and weather conditions. Parameter estimation was based on Bayesian methods using both the Jeffreys’ prior and an informative normal prior in a sensitivity analysis. We estimate the percent increase in non-accidental mortality per 10 μg/m3 increase in PM2.5 concentration and constructed corresponding 95% credible interval (CrI). In total, 336,379 non-accidental deaths occurred during the study period. Average daily deaths were 307. The results indicated that per 10 μg/m3 increase in daily average PM2.5 concentration alone corresponded to 0.26–0.35% increase in daily non-accidental mortality in Shanghai. Statistically significant positive associations between PM2.5 and mortality were found for favorable SWTs when considering the interaction between PM2.5 and SWTs. The greatest effect was found in hot dry SWT (percent increase = 1.28, 95% CrI: 0.72, 1.83), followed by warm humid SWT (percent increase = 0.64, 95% CrI: 0.15, 1.13). The effect of PM2.5 on non-accidental mortality differed under specific extreme weather conditions and SWTs. Environmental policies and actions should take into account the interrelationship between the two hazardous exposures. PMID:29121092
Relative impact of weather vs. fuels on fire regimes in coastal California

Treesearch

Jon E. Keeley

2008-01-01

Extreme fire weather is of over riding importance in determining fire behavior in coastal chaparral and on these landscapes fire suppression policy has not resulted in fire exclusion. There is regional variation in foehn winds, which are most important in southern California. Under these severe fire weather conditions fuel age does not constrain fire behavior. As a...
Observations and Impact Assessments of Extreme Space Weather Events

NASA Astrophysics Data System (ADS)

Baker, D. N.

2007-05-01

"Space weather" refers to conditions on the Sun, in the solar wind, and in Earth`s magnetosphere, ionosphere, and thermosphere. Activity on the Sun such as solar flares and coronal mass ejections can lead to high levels of radiation in space and can cause major magnetic storms at the Earth. Space radiation can come as energetic particles or as electromagnetic emissions. Adverse conditions in the near-Earth space environment can cause disruption of satellite operations, communications, navigation, and electric power distribution grids. This can lead to a variety of socioeconomic losses. Astronauts and airline passengers exposed to high levels of radiation are also at risk. Society`s vulnerability to space weather effects is an issue of increasing concern. We are dependent on technological systems that are becoming more susceptible to space weather disturbances. We also have a permanent human presence in space with the International Space Station and the President and NASA have expressed a desire to expand our human space activities with missions to the moon and Mars. This will make space weather of even greater concern in the future. In this talk I will describe many space weather effects and will describe some of the societal and economic impacts that extreme events have had.
Influence of Anthropogenic Climate Change on Planetary Wave Resonance and Extreme Weather Events.

PubMed

Mann, Michael E; Rahmstorf, Stefan; Kornhuber, Kai; Steinman, Byron A; Miller, Sonya K; Coumou, Dim

2017-03-27

Persistent episodes of extreme weather in the Northern Hemisphere summer have been shown to be associated with the presence of high-amplitude quasi-stationary atmospheric Rossby waves within a particular wavelength range (zonal wavenumber 6-8). The underlying mechanistic relationship involves the phenomenon of quasi-resonant amplification (QRA) of synoptic-scale waves with that wavenumber range becoming trapped within an effective mid-latitude atmospheric waveguide. Recent work suggests an increase in recent decades in the occurrence of QRA-favorable conditions and associated extreme weather, possibly linked to amplified Arctic warming and thus a climate change influence. Here, we isolate a specific fingerprint in the zonal mean surface temperature profile that is associated with QRA-favorable conditions. State-of-the-art ("CMIP5") historical climate model simulations subject to anthropogenic forcing display an increase in the projection of this fingerprint that is mirrored in multiple observational surface temperature datasets. Both the models and observations suggest this signal has only recently emerged from the background noise of natural variability.
Extreme weather and air pollution effects on cardiovascular and respiratory hospital admissions in Cyprus.

PubMed

Tsangari, H; Paschalidou, A K; Kassomenos, A P; Vardoulakis, S; Heaviside, C; Georgiou, K E; Yamasaki, E N

2016-01-15

In many regions of the world, climatic change is associated with increased extreme temperatures, which can have severe effects on mortality and morbidity. In this study, we examine the effect of extreme weather on hospital admissions in Cyprus, for inland and coastal areas, through the use of synoptic weather classifications (air mass types). In addition, the effect of particulate air pollution (PM10) on morbidity is examined. Our results show that two air mass types, namely (a) warm, rainy days with increased levels of water vapour in the atmosphere and (b) cold, cloudy days with increased levels of precipitation, were associated with increased morbidity in the form of hospital admissions. This was true both for cardiovascular and respiratory conditions, for all age groups, but particularly for the elderly, aged over 65. Particulate air pollution was also associated with increased morbidity in Cyprus, where the effect was more pronounced for cardiovascular diseases. Copyright © 2015 Elsevier B.V. All rights reserved.
Weather elements, chemical air pollutants and airborne pollen influencing asthma emergency room visits in Szeged, Hungary: performance of two objective weather classifications

NASA Astrophysics Data System (ADS)

Makra, László; Puskás, János; Matyasovszky, István; Csépe, Zoltán; Lelovics, Enikő; Bálint, Beatrix; Tusnády, Gábor

2015-09-01

Weather classification approaches may be useful tools in modelling the occurrence of respiratory diseases. The aim of the study is to compare the performance of an objectively defined weather classification and the Spatial Synoptic Classification (SSC) in classifying emergency department (ED) visits for acute asthma depending from weather, air pollutants, and airborne pollen variables for Szeged, Hungary, for the 9-year period 1999-2007. The research is performed for three different pollen-related periods of the year and the annual data set. According to age and gender, nine patient categories, eight meteorological variables, seven chemical air pollutants, and two pollen categories were used. In general, partly dry and cold air and partly warm and humid air aggravate substantially the symptoms of asthmatics. Our major findings are consistent with this establishment. Namely, for the objectively defined weather types favourable conditions for asthma ER visits occur when an anticyclonic ridge weather situation happens with near extreme temperature and humidity parameters. Accordingly, the SSC weather types facilitate aggravating asthmatic conditions if warm or cool weather occur with high humidity in both cases. Favourable conditions for asthma attacks are confirmed in the extreme seasons when atmospheric stability contributes to enrichment of air pollutants. The total efficiency of the two classification approaches is similar in spite of the fact that the methodology for derivation of the individual types within the two classification approaches is completely different.
Weather elements, chemical air pollutants and airborne pollen influencing asthma emergency room visits in Szeged, Hungary: performance of two objective weather classifications.

PubMed

Makra, László; Puskás, János; Matyasovszky, István; Csépe, Zoltán; Lelovics, Enikő; Bálint, Beatrix; Tusnády, Gábor

2015-09-01

Weather classification approaches may be useful tools in modelling the occurrence of respiratory diseases. The aim of the study is to compare the performance of an objectively defined weather classification and the Spatial Synoptic Classification (SSC) in classifying emergency department (ED) visits for acute asthma depending from weather, air pollutants, and airborne pollen variables for Szeged, Hungary, for the 9-year period 1999-2007. The research is performed for three different pollen-related periods of the year and the annual data set. According to age and gender, nine patient categories, eight meteorological variables, seven chemical air pollutants, and two pollen categories were used. In general, partly dry and cold air and partly warm and humid air aggravate substantially the symptoms of asthmatics. Our major findings are consistent with this establishment. Namely, for the objectively defined weather types favourable conditions for asthma ER visits occur when an anticyclonic ridge weather situation happens with near extreme temperature and humidity parameters. Accordingly, the SSC weather types facilitate aggravating asthmatic conditions if warm or cool weather occur with high humidity in both cases. Favourable conditions for asthma attacks are confirmed in the extreme seasons when atmospheric stability contributes to enrichment of air pollutants. The total efficiency of the two classification approaches is similar in spite of the fact that the methodology for derivation of the individual types within the two classification approaches is completely different.
Extremely Severe Space Weather and Geomagnetically Induced Currents in Regions with Locally Heterogeneous Ground Resistivity

NASA Technical Reports Server (NTRS)

Fujita, Shigeru; Kataoka, Ryuho; Pulkkinen, Antti; Watari, Shinichi

2016-01-01

Large geomagnetically induced currents (GICs) triggered by extreme space weather events are now regarded as one of the serious natural threats to the modern electrified society. The risk is described in detail in High-Impact, Low-Frequency Event Risk, A Jointly-Commissioned Summary Report of the North American Electric Reliability Corporation and the US Department of Energy's November 2009 Workshop, June 2010. For example, the March 13-14,1989 storm caused a large-scale blackout affecting about 6 million people in Quebec, Canada, and resulting in substantial economic losses in Canada and the USA (Bolduc 2002). Therefore, European and North American nations have invested in GIC research such as the Solar Shield project in the USA (Pulkkinen et al. 2009, 2015a). In 2015, the Japanese government (Ministry of Economy, Trade and Industry, METI) acknowledged the importance of GIC research in Japan. After reviewing the serious damages caused by the 2011 Tohoku-Oki earthquake, METI recognized the potential risk to the electric power grid posed by extreme space weather. During extreme events, GICs can be concerning even in mid- and low-latitude countries and have become a global issue.
Demographic effects of extreme weather events: snow storms, breeding success, and population growth rate in a long-lived Antarctic seabird

PubMed Central

Descamps, Sébastien; Tarroux, Arnaud; Varpe, Øystein; Yoccoz, Nigel G; Tveraa, Torkild; Lorentsen, Svein-Håkon

2015-01-01

Weather extremes are one important element of ongoing climate change, but their impacts are poorly understood because they are, by definition, rare events. If the frequency and severity of extreme weather events increase, there is an urgent need to understand and predict the ecological consequences of such events. In this study, we aimed to quantify the effects of snow storms on nest survival in Antarctic petrels and assess whether snow storms are an important driver of annual breeding success and population growth rate. We used detailed data on daily individual nest survival in a year with frequent and heavy snow storms, and long term data on petrel productivity (i.e., number of chicks produced) at the colony level. Our results indicated that snow storms are an important determinant of nest survival and overall productivity. Snow storm events explained 30% of the daily nest survival within the 2011/2012 season and nearly 30% of the interannual variation in colony productivity in period 1985–2014. Snow storms are a key driver of Antarctic petrel breeding success, and potentially population dynamics. We also found state-dependent effects of snow storms and chicks in poor condition were more likely to die during a snow storm than chicks in good condition. This stresses the importance of considering interactions between individual heterogeneity and extreme weather events to understand both individual and population responses to climate change. PMID:25691959

Demographic effects of extreme weather events: snow storms, breeding success, and population growth rate in a long-lived Antarctic seabird.

PubMed

Descamps, Sébastien; Tarroux, Arnaud; Varpe, Øystein; Yoccoz, Nigel G; Tveraa, Torkild; Lorentsen, Svein-Håkon

2015-01-01

Weather extremes are one important element of ongoing climate change, but their impacts are poorly understood because they are, by definition, rare events. If the frequency and severity of extreme weather events increase, there is an urgent need to understand and predict the ecological consequences of such events. In this study, we aimed to quantify the effects of snow storms on nest survival in Antarctic petrels and assess whether snow storms are an important driver of annual breeding success and population growth rate. We used detailed data on daily individual nest survival in a year with frequent and heavy snow storms, and long term data on petrel productivity (i.e., number of chicks produced) at the colony level. Our results indicated that snow storms are an important determinant of nest survival and overall productivity. Snow storm events explained 30% of the daily nest survival within the 2011/2012 season and nearly 30% of the interannual variation in colony productivity in period 1985-2014. Snow storms are a key driver of Antarctic petrel breeding success, and potentially population dynamics. We also found state-dependent effects of snow storms and chicks in poor condition were more likely to die during a snow storm than chicks in good condition. This stresses the importance of considering interactions between individual heterogeneity and extreme weather events to understand both individual and population responses to climate change.
Assigning historic responsibility for extreme weather events

NASA Astrophysics Data System (ADS)

Otto, Friederike E. L.; Skeie, Ragnhild B.; Fuglestvedt, Jan S.; Berntsen, Terje; Allen, Myles R.

2017-11-01

Recent scientific advances make it possible to assign extreme events to human-induced climate change and historical emissions. These developments allow losses and damage associated with such events to be assigned country-level responsibility.
Health Effects of Tsunamis

MedlinePlus

... Extreme Heat Older Adults (Aged 65+) Infants and Children Chronic Medical Conditions Low Income Athletes Outdoor Workers Pets Hot Weather Tips Warning Signs and Symptoms FAQs Social Media How to Stay Cool Missouri Cooling Centers Extreme ...
Trench Foot or Immersion Foot

MedlinePlus

... Extreme Heat Older Adults (Aged 65+) Infants and Children Chronic Medical Conditions Low Income Athletes Outdoor Workers Pets Hot Weather Tips Warning Signs and Symptoms FAQs Social Media How to Stay Cool Missouri Cooling Centers Extreme ...
Evaluation of downscaled, gridded climate data for the conterminous United States

USGS Publications Warehouse

Robert J. Behnke,; Stephen J. Vavrus,; Andrew Allstadt,; Thomas P. Albright,; Thogmartin, Wayne E.; Volker C. Radeloff,

2016-01-01

Weather and climate affect many ecological processes, making spatially continuous yet fine-resolution weather data desirable for ecological research and predictions. Numerous downscaled weather data sets exist, but little attempt has been made to evaluate them systematically. Here we address this shortcoming by focusing on four major questions: (1) How accurate are downscaled, gridded climate data sets in terms of temperature and precipitation estimates?, (2) Are there significant regional differences in accuracy among data sets?, (3) How accurate are their mean values compared with extremes?, and (4) Does their accuracy depend on spatial resolution? We compared eight widely used downscaled data sets that provide gridded daily weather data for recent decades across the United States. We found considerable differences among data sets and between downscaled and weather station data. Temperature is represented more accurately than precipitation, and climate averages are more accurate than weather extremes. The data set exhibiting the best agreement with station data varies among ecoregions. Surprisingly, the accuracy of the data sets does not depend on spatial resolution. Although some inherent differences among data sets and weather station data are to be expected, our findings highlight how much different interpolation methods affect downscaled weather data, even for local comparisons with nearby weather stations located inside a grid cell. More broadly, our results highlight the need for careful consideration among different available data sets in terms of which variables they describe best, where they perform best, and their resolution, when selecting a downscaled weather data set for a given ecological application.
Fire weather and behavior of the Little Sioux fire.

Treesearch

Rodney W. Sando; Donald A. Haines

1972-01-01

In mid-May 1971, a northern Minnesota fire burned almost 15,000 acres of forest land. The extreme fire behavior it exhibited was the product of a number of described features. This paper documents the attendant fuel and weather conditions.
Weather and extremes in the last Millennium - a challenge for climate modelling

NASA Astrophysics Data System (ADS)

Raible, Christoph C.; Blumer, Sandro R.; Gomez-Navarro, Juan J.; Lehner, Flavio

2015-04-01

Changes in the climate mean state are expected to influence society, but the socio-economic sensitivity to extreme events might be even more severe. Whether or not the current frequency and severity of extreme events is a unique characteristic of anthropogenic-driven climate change can be assessed by putting the observed changes in a long-term perspective. In doing so, early instrumental series and proxy archives are a rich source to investigate also extreme events, in particular during the last millennium, yet they suffer from spatial and temporal scarcity. Therefore, simulations with coupled general circulation models (GCMs) could fill such gaps and help in deepening our process understanding. In this study, an overview of past and current efforts as well as challenges in modelling paleo weather and extreme events is presented. Using simulations of the last millennium we investigate extreme midlatitude cyclone characteristics, precipitation, and their connection to large-scale atmospheric patterns in the North Atlantic European region. In cold climate states such as the Maunder Minimum, the North Atlantic Oscillation (NAO) is found to be predominantly in its negative phase. In this sense, simulations of different models agree with proxy findings for this period. However, some proxy data available for this period suggests an increase in storminess during this period, which could be interpreted as a positive phase of the NAO - a superficial contradiction. The simulated cyclones are partly reduced over Europe, which is consistent with the aforementioned negative phase of the NAO. However, as the meridional temperature gradient is increased during this period - which constitutes a source of low-level baroclincity - they also intensify. This example illustrates how model simulations could be used to improve our proxy interpretation and to gain additional process understanding. Nevertheless, there are also limitations associated with climate modeling efforts to simulate the last millennium. In particular, these models still struggle to properly simulate atmospheric blocking events, an important dynamical feature for dry conditions during summer times. Finally, new and promising ways in improving past climate modelling are briefly introduced. In particular, the use of dynamical downscaling is a powerful tool to bridge the gap between the coarsely resolved GCMs and characteristics of the regional climate, which is potentially recorded in proxy archives. In particular, the representation of extreme events could be improved by dynamical downscaling as processes are better resolved than GCMs.
Northern hemisphere jet stream positions indices as diagnostic tools for climate and ecosystem dynamics

USGS Publications Warehouse

Belmecheri, Soumaya; Babst, Flurin; Hudson, Amy R.; Betancourt, Julio L.; Trouet, Valerie

2017-01-01

The latitudinal position of the Northern Hemisphere jet stream (NHJ) modulates the occurrence and frequency of extreme weather events. Precipitation anomalies in particular are associated with NHJ variability; the resulting floods and droughts can have considerable societal and economic impacts. This study develops a new climatology of the 300-hPa NHJ using a bottom-up approach based on seasonally explicit latitudinal NHJ positions. Four seasons with coherent NHJ patterns were identified (January–February, April–May, July–August, and October–November), along with 32 longitudinal sectors where the seasonal NHJ shows strong spatial coherence. These 32 longitudinal sectors were then used as NHJ position indices to examine the influence of seasonal NHJ position on the geographical distribution of NH precipitation and temperature variability and their link to atmospheric circulation pattern. The analyses show that the NHJ indices are related to broad-scale patterns in temperature and precipitation variability, in terrestrial vegetation productivity and spring phenology, and can be used as diagnostic/prognostic tools to link ecosystem and socioeconomic dynamics to upper-level atmospheric patterns.
Effects of extreme spring temperatures on phenology: a case study from Munich and Ingolstadt

NASA Astrophysics Data System (ADS)

Jochner, Susanne; Menzel, Annette

2010-05-01

Extreme events - e.g. warm spells or heavy precipitation events - are likely to increase in the future both in frequency and intensity. Therefore, research on extreme events gains new importance; also in terms of plant development which is mostly triggered by temperatures. An arising question is how plants respond to an extreme warm spell when following an extreme cold winter season. This situation could be studied in spring 2009 in the greater area of Munich and Ingolstadt by phenological observations of flowering and leaf unfolding of birch (Betula pendula L.) and flowering of horse chestnut (Aesculus hippocastanum L.). The long chilling period of winter 2008 and spring 2009 was followed by an immediate strong forcing of flowering and leaf unfolding, especially for birch. This extreme weather situation diminished the difference between urban and rural dates of onset. Another important fact that could be observed in the proceeding period of December 2008 to April 2009 was the reduced temperature difference among urban and rural sites (urban heat island effect). Long-term observations (1951-2008) of the phenological network of the German Meteorological Service (DWD) were used to identify years with reduced urban-rural differences between onset times in the greater area of Munich in the past. Statistical analyses were conducted in order to answer the question whether the sequence of extreme warm and cold events leads to a decreased difference in phenological onset times or if this behaviour can be attributed to extreme warm springs themselves or to the decreased urban heat island effect which is mostly affected by general atmospheric circulation patterns.
Application of data on climate extremes for the southwestern United States

NASA Astrophysics Data System (ADS)

Redmond, K. T.; Fleishman, E.; Cayan, D. R.; Daudert, B.; Gershunov, A.

2015-12-01

We are improving the scientific capacity to evaluate responses of natural resources to climate extremes. We also are enhancing a platform for derivation of and access to customized climate information for the full extent or any subset of the southwestern United States. Extreme climate can have substantial effects on species, ecological and evolutionary processes, and the health of visitors to public lands. We are working with federal and state managers and with researchers who collaborate with decision-makers to use data on climate extremes to inform resource management. Current applications include sudden oak death, estuarine management, and fine-resolution manipulation of montane vegetation. To facilitate practical use of data on climate extremes, we are screening global climate models on the basis of their realism in representing natural regional patterns and extremes of temperature and precipitation, including those driven by El Niño and La Niña. We are assessing how well each model represents different climate elements. We also are delivering point and gridded observations and downscaled model projections, all at daily and 6 km resolution, on past and future climate extremes. Additionally, we are using the downscaled outputs to drive a hydrologic model and derive multiple probabilistic measures of water availability, flood, and drought. Moreover, we are extending the capacity of the Southwest Climate and Environmental Information Collaborative (SCENIC; wrcc.dri.edu/csc/scenic), a product developed by the Western Regional Climate Center, to provide access to diverse observed and simulated data on regional weather and climate, particularly on extremes.
STAMMEX high resolution gridded daily precipitation dataset over Germany: a new potential for regional precipitation climate research

NASA Astrophysics Data System (ADS)

Zolina, Olga; Simmer, Clemens; Kapala, Alice; Mächel, Hermann; Gulev, Sergey; Groisman, Pavel

2014-05-01

We present new high resolution precipitation daily grids developed at Meteorological Institute, University of Bonn and German Weather Service (DWD) under the STAMMEX project (Spatial and Temporal Scales and Mechanisms of Extreme Precipitation Events over Central Europe). Daily precipitation grids have been developed from the daily-observing precipitation network of DWD, which runs one of the World's densest rain gauge networks comprising more than 7500 stations. Several quality-controlled daily gridded products with homogenized sampling were developed covering the periods 1931-onwards (with 0.5 degree resolution), 1951-onwards (0.25 degree and 0.5 degree), and 1971-2000 (0.1 degree). Different methods were tested to select the best gridding methodology that minimizes errors of integral grid estimates over hilly terrain. Besides daily precipitation values with uncertainty estimates (which include standard estimates of the kriging uncertainty as well as error estimates derived by a bootstrapping algorithm), the STAMMEX data sets include a variety of statistics that characterize temporal and spatial dynamics of the precipitation distribution (quantiles, extremes, wet/dry spells, etc.). Comparisons with existing continental-scale daily precipitation grids (e.g., CRU, ECA E-OBS, GCOS) which include considerably less observations compared to those used in STAMMEX, demonstrate the added value of high-resolution grids for extreme rainfall analyses. These data exhibit spatial variability pattern and trends in precipitation extremes, which are missed or incorrectly reproduced over Central Europe from coarser resolution grids based on sparser networks. The STAMMEX dataset can be used for high-quality climate diagnostics of precipitation variability, as a reference for reanalyses and remotely-sensed precipitation products (including the upcoming Global Precipitation Mission products), and for input into regional climate and operational weather forecast models. We will present numerous application of the STAMMEX grids spanning from case studies of the major Central European floods to long-term changes in different precipitation statistics, including those accounting for the alternation of dry and wet periods and precipitation intensities associated with prolonged rainy episodes.
The Sinuosity of Atmospheric Circulation over North America and its Relationship to Arctic Climate Change and Extreme Events

NASA Astrophysics Data System (ADS)

Vavrus, S. J.; Wang, F.; Martin, J. E.; Francis, J. A.

2015-12-01

Recent research has suggested a relationship between mid-latitude weather and Arctic amplification (AA) of global climate change via a slower and wavier extratropical circulation inducing more extreme events. To test this hypothesis and to quantify the waviness of the extratropical flow, we apply a novel application of the geomorphological concept of sinuosity (SIN) over greater North America. SIN is defined as the ratio of the curvilinear length of a geopotential height contour to the perimeter of its equivalent latitude, where the contour and the equivalent latitude enclose the same area. We use 500 hPa daily heights from reanalysis and model simulations to calculate past and future SIN. The circulation exhibits a distinct annual cycle of maximum SIN (waviness) in summer and a minimum in winter, inversely related to the annual cycle of zonal wind speed. Positive trends in SIN have emerged in recent decades during winter and summer at several latitude bands, generally collocated with negative trends in zonal wind speeds. High values of SIN coincide with many prominent extreme-weather events, including Superstorm Sandy. RCP8.5 simulations (2006-2100) project a dipole pattern of zonal wind changes that varies seasonally. In winter, AA causes inflated heights over the Arctic relative to mid-latitudes and an associated weakening (strengthening) of the westerlies north (south) of 40N. The AA signal in summer is strongest over upper-latitude land, promoting localized atmospheric ridging aloft with lighter westerlies to the south and stronger zonal winds to the north. The changes in wind speeds in both seasons are inversely correlated with SIN, indicating a wavier circulation where the flow weakens. In summer the lighter winds over much of the U. S. resemble circulation anomalies observed during extreme summer heat and drought. Such changes may be linked to enhanced heating of upper-latitude land surfaces caused by earlier snow melt during spring-summer.
Effect of weather patterns on preweaning growth of beef calves in the Northern Great Plains

USDA-ARS?s Scientific Manuscript database

Beef production records collected over a 76-year investigation into effects of linebreeding and selection of Hereford cattle, and concurrent weather records were used to assess effects of weather patterns on the growth of calves from birth to weaning. Data were simultaneously adjusted for trends in ...
Recent Increase in North Atlantic Jet Variability Emerges from Three-Century Long Context

NASA Astrophysics Data System (ADS)

Trouet, V.; Babst, F.; Meko, M. D.

2017-12-01

The position and strength of the Northern Hemisphere polar jet stream are important modulators of mid-latitude weather extremes and their societal, ecosystem, and economic impacts. A recent increase in mid-latitude extreme events highlights the need for long-term records of jet stream variability to put recent trends in a historical perspective and to investigate non-linear relationships between jet stream variability, mid-latitude extreme weather events, and anthropogenic climate change. In Europe, anomalies of the North Atlantic Jet (NAJ) create a summer temperature seesaw between the British Isles (BRIT) and the northeastern Mediterranean (NEMED). We combined summer temperature-sensitive tree-ring records from BRIT and NEMED to reconstruct inter-annual variability in the latitudinal position of the August NAJ back to 1725 CE. The two temperature proxies BRIT and NEMED counter-correlate significantly over their period of overlap, thus illustrate the temperature dipole generated by anomalous NAJ positions, and combined explain close to 40% of the variance in the August NAJ target (Fig. 1). The NAJ reconstruction is dominated by sub-decadal variability and no significant long-term poleward or equatorward trends were detected. However, the NAJ time series shows a steep and unprecedented increase in variance starting in the late 1960s. Enhanced late 20th century variance has also been detected in climate and ecosystem dynamics in the Central and Northeast Pacific, which are associated with the latitudinal position of the North Pacific Jet. Our combined results suggest a late 20th century increase in jet stream latitudinal variance in the North Atlantic and the North Pacific Basin that can be indicative of enhanced jet stream waviness and that coincides with a recent increase in quasi-resonant amplification (QRA). Our results show a late 20th century amplification of meridional flow in both the North Pacific and the North Atlantic Basin and support more sinuous jet stream patterns and QRA as potential dynamic pathways for Arctic warming to influence midlatitude weather. Moreover, the synchronization of variance increases between the North Atlantic and North Pacific basins in the late 20th century is unprecedented over the last 290 years and strongly suggests an impact of anthropogenic warming.
Changes in climate extremes, fresh water availability and vulnerability to food insecurity projected at 1.5°C and 2°C global warming with a higher-resolution global climate model

PubMed Central

Alfieri, Lorenzo; Bradshaw, Catherine; Caesar, John; Feyen, Luc; Friedlingstein, Pierre; Gohar, Laila; Koutroulis, Aristeidis; Lewis, Kirsty; Morfopoulos, Catherine; Papadimitriou, Lamprini; Richardson, Katy J.; Tsanis, Ioannis; Wyser, Klaus

2018-01-01

We projected changes in weather extremes, hydrological impacts and vulnerability to food insecurity at global warming of 1.5°C and 2°C relative to pre-industrial, using a new global atmospheric general circulation model HadGEM3A-GA3.0 driven by patterns of sea-surface temperatures and sea ice from selected members of the 5th Coupled Model Intercomparison Project (CMIP5) ensemble, forced with the RCP8.5 concentration scenario. To provide more detailed representations of climate processes and impacts, the spatial resolution was N216 (approx. 60 km grid length in mid-latitudes), a higher resolution than the CMIP5 models. We used a set of impacts-relevant indices and a global land surface model to examine the projected changes in weather extremes and their implications for freshwater availability and vulnerability to food insecurity. Uncertainties in regional climate responses are assessed, examining ranges of outcomes in impacts to inform risk assessments. Despite some degree of inconsistency between components of the study due to the need to correct for systematic biases in some aspects, the outcomes from different ensemble members could be compared for several different indicators. The projections for weather extremes indices and biophysical impacts quantities support expectations that the magnitude of change is generally larger for 2°C global warming than 1.5°C. Hot extremes become even hotter, with increases being more intense than seen in CMIP5 projections. Precipitation-related extremes show more geographical variation with some increases and some decreases in both heavy precipitation and drought. There are substantial regional uncertainties in hydrological impacts at local scales due to different climate models producing different outcomes. Nevertheless, hydrological impacts generally point towards wetter conditions on average, with increased mean river flows, longer heavy rainfall events, particularly in South and East Asia with the most extreme projections suggesting more than a doubling of flows in the Ganges at 2°C global warming. Some areas are projected to experience shorter meteorological drought events and less severe low flows, although longer droughts and/or decreases in low flows are projected in many other areas, particularly southern Africa and South America. Flows in the Amazon are projected to decline by up to 25%. Increases in either heavy rainfall or drought events imply increased vulnerability to food insecurity, but if global warming is limited to 1.5°C, this vulnerability is projected to remain smaller than at 2°C global warming in approximately 76% of developing countries. At 2°C, four countries are projected to reach unprecedented levels of vulnerability to food insecurity. This article is part of the theme issue ‘The Paris Agreement: understanding the physical and social challenges for a warming world of 1.5°C above pre-industrial levels’. PMID:29610383
Changes in climate extremes, fresh water availability and vulnerability to food insecurity projected at 1.5°C and 2°C global warming with a higher-resolution global climate model

NASA Astrophysics Data System (ADS)

Betts, Richard A.; Alfieri, Lorenzo; Bradshaw, Catherine; Caesar, John; Feyen, Luc; Friedlingstein, Pierre; Gohar, Laila; Koutroulis, Aristeidis; Lewis, Kirsty; Morfopoulos, Catherine; Papadimitriou, Lamprini; Richardson, Katy J.; Tsanis, Ioannis; Wyser, Klaus

2018-05-01

We projected changes in weather extremes, hydrological impacts and vulnerability to food insecurity at global warming of 1.5°C and 2°C relative to pre-industrial, using a new global atmospheric general circulation model HadGEM3A-GA3.0 driven by patterns of sea-surface temperatures and sea ice from selected members of the 5th Coupled Model Intercomparison Project (CMIP5) ensemble, forced with the RCP8.5 concentration scenario. To provide more detailed representations of climate processes and impacts, the spatial resolution was N216 (approx. 60 km grid length in mid-latitudes), a higher resolution than the CMIP5 models. We used a set of impacts-relevant indices and a global land surface model to examine the projected changes in weather extremes and their implications for freshwater availability and vulnerability to food insecurity. Uncertainties in regional climate responses are assessed, examining ranges of outcomes in impacts to inform risk assessments. Despite some degree of inconsistency between components of the study due to the need to correct for systematic biases in some aspects, the outcomes from different ensemble members could be compared for several different indicators. The projections for weather extremes indices and biophysical impacts quantities support expectations that the magnitude of change is generally larger for 2°C global warming than 1.5°C. Hot extremes become even hotter, with increases being more intense than seen in CMIP5 projections. Precipitation-related extremes show more geographical variation with some increases and some decreases in both heavy precipitation and drought. There are substantial regional uncertainties in hydrological impacts at local scales due to different climate models producing different outcomes. Nevertheless, hydrological impacts generally point towards wetter conditions on average, with increased mean river flows, longer heavy rainfall events, particularly in South and East Asia with the most extreme projections suggesting more than a doubling of flows in the Ganges at 2°C global warming. Some areas are projected to experience shorter meteorological drought events and less severe low flows, although longer droughts and/or decreases in low flows are projected in many other areas, particularly southern Africa and South America. Flows in the Amazon are projected to decline by up to 25%. Increases in either heavy rainfall or drought events imply increased vulnerability to food insecurity, but if global warming is limited to 1.5°C, this vulnerability is projected to remain smaller than at 2°C global warming in approximately 76% of developing countries. At 2°C, four countries are projected to reach unprecedented levels of vulnerability to food insecurity. This article is part of the theme issue `The Paris Agreement: understanding the physical and social challenges for a warming world of 1.5°C above pre-industrial levels'.
Changes in climate extremes, fresh water availability and vulnerability to food insecurity projected at 1.5°C and 2°C global warming with a higher-resolution global climate model.

PubMed

Betts, Richard A; Alfieri, Lorenzo; Bradshaw, Catherine; Caesar, John; Feyen, Luc; Friedlingstein, Pierre; Gohar, Laila; Koutroulis, Aristeidis; Lewis, Kirsty; Morfopoulos, Catherine; Papadimitriou, Lamprini; Richardson, Katy J; Tsanis, Ioannis; Wyser, Klaus

2018-05-13

We projected changes in weather extremes, hydrological impacts and vulnerability to food insecurity at global warming of 1.5°C and 2°C relative to pre-industrial, using a new global atmospheric general circulation model HadGEM3A-GA3.0 driven by patterns of sea-surface temperatures and sea ice from selected members of the 5th Coupled Model Intercomparison Project (CMIP5) ensemble, forced with the RCP8.5 concentration scenario. To provide more detailed representations of climate processes and impacts, the spatial resolution was N216 (approx. 60 km grid length in mid-latitudes), a higher resolution than the CMIP5 models. We used a set of impacts-relevant indices and a global land surface model to examine the projected changes in weather extremes and their implications for freshwater availability and vulnerability to food insecurity. Uncertainties in regional climate responses are assessed, examining ranges of outcomes in impacts to inform risk assessments. Despite some degree of inconsistency between components of the study due to the need to correct for systematic biases in some aspects, the outcomes from different ensemble members could be compared for several different indicators. The projections for weather extremes indices and biophysical impacts quantities support expectations that the magnitude of change is generally larger for 2°C global warming than 1.5°C. Hot extremes become even hotter, with increases being more intense than seen in CMIP5 projections. Precipitation-related extremes show more geographical variation with some increases and some decreases in both heavy precipitation and drought. There are substantial regional uncertainties in hydrological impacts at local scales due to different climate models producing different outcomes. Nevertheless, hydrological impacts generally point towards wetter conditions on average, with increased mean river flows, longer heavy rainfall events, particularly in South and East Asia with the most extreme projections suggesting more than a doubling of flows in the Ganges at 2°C global warming. Some areas are projected to experience shorter meteorological drought events and less severe low flows, although longer droughts and/or decreases in low flows are projected in many other areas, particularly southern Africa and South America. Flows in the Amazon are projected to decline by up to 25%. Increases in either heavy rainfall or drought events imply increased vulnerability to food insecurity, but if global warming is limited to 1.5°C, this vulnerability is projected to remain smaller than at 2°C global warming in approximately 76% of developing countries. At 2°C, four countries are projected to reach unprecedented levels of vulnerability to food insecurity.This article is part of the theme issue 'The Paris Agreement: understanding the physical and social challenges for a warming world of 1.5°C above pre-industrial levels'. © 2018 The Authors.
The Influence of Weather Variation, Urban Design and Built Environment on Objectively Measured Sedentary Behaviour in Children.

PubMed

Katapally, Tarun Reddy; Rainham, Daniel; Muhajarine, Nazeem

2016-01-01

With emerging evidence indicating that independent of physical activity, sedentary behaviour (SB) can be detrimental to health, researchers are increasingly aiming to understand the influence of multiple contexts such as urban design and built environment on SB. However, weather variation, a factor that continuously interacts with all other environmental variables, has been consistently underexplored. This study investigated the influence of diverse environmental exposures (including weather variation, urban design and built environment) on SB in children. This cross-sectional observational study is part of an active living research initiative set in the Canadian prairie city of Saskatoon. Saskatoon's neighbourhoods were classified based on urban street design into grid-pattern, fractured grid-pattern and curvilinear types of neighbourhoods. Diverse environmental exposures were measured including, neighbourhood built environment, and neighbourhood and household socioeconomic environment. Actical accelerometers were deployed between April and June 2010 (spring-summer) to derive SB of 331 10-14 year old children in 25 one week cycles. Each cycle of accelerometry was conducted on a different cohort of children within the total sample. Accelerometer data were matched with localized weather patterns derived from Environment Canada weather data. Multilevel modeling using Hierarchical Linear and Non-linear Modeling software was conducted by factoring in weather variation to depict the influence of diverse environmental exposures on SB. Both weather variation and urban design played a significant role in SB. After factoring in weather variation, it was observed that children living in grid-pattern neighbourhoods closer to the city centre (with higher diversity of destinations) were less likely to be sedentary. This study demonstrates a methodology that could be replicated to integrate geography-specific weather patterns with existing cross-sectional accelerometry data to understand the influence of urban design and built environment on SB in children.
Extreme Spacecraft Charging in Polar Low Earth Orbit

NASA Technical Reports Server (NTRS)

Colson, Andrew D.; Minow, Joseph I.; NeergaardParker, Linda

2012-01-01

Spacecraft in low altitude, high inclination (including sun-synchronous) orbits are widely used for remote sensing of the Earth's land surface and oceans, monitoring weather and climate, communications, scientific studies of the upper atmosphere and ionosphere, and a variety of other scientific, commercial, and military applications. These systems episodically charge to frame potentials in the kilovolt range when exposed to space weather environments characterized by a high flux of energetic (10 s kilovolt) electrons in regions of low background plasma density which is similar in some ways to the space weather conditions in geostationary orbit responsible for spacecraft charging to kilovolt levels. We first review the physics of space environment interactions with spacecraft materials that control auroral charging rates and the anticipated maximum potentials that should be observed on spacecraft surfaces during disturbed space weather conditions. We then describe how the theoretical values compare to the observational history of extreme charging in auroral environments. Finally, a set of extreme DMSP charging events are described varying in maximum negative frame potential from 0.6 kV to 2 kV, focusing on the characteristics of the charging events that are of importance both to the space system designer and to spacecraft operators. The goal of the presentation is to bridge the gap between scientific studies of auroral charging and the need for engineering teams to understand how space weather impacts both spacecraft design and operations for vehicles on orbital trajectories that traverse auroral charging environments.
Extreme Spacecraft Charging in Polar Low Earth Orbit

NASA Technical Reports Server (NTRS)

Colson, Andrew D.; Minow, Joseph I.; Parker, L. Neergaard

2012-01-01

Spacecraft in low altitude, high inclination (including sun -synchronous) orbits are widely used for remote sensing of the Earth fs land surface and oceans, monitoring weather and climate, communications, scientific studies of the upper atmosphere and ionosphere, and a variety of other scientific, commercial, and military applications. These systems episodically charge to frame potentials in the kilovolt range when exposed to space weather environments characterized by a high flux of energetic (approx.10 fs kilovolt) electrons in regions of low background plasma density. Auroral charging conditions are similar in some ways to the space weather conditions in geostationary orbit responsible for spacecraft charging to kilovolt levels. We first review the physics of space environment interactions with spacecraft materials that control auroral charging rates and the anticipated maximum potentials that should be observed on spacecraft surfaces during disturbed space weather conditions. We then describe how the theoretical values compare to the observational history of extreme charging in auroral environments. Finally, a set of extreme DMSP charging events are described varying in maximum negative frame potential from approx.0.6 kV to approx.2 kV, focusing on the characteristics of the charging events that are of importance both to the space system designer and to spacecraft operators. The goal of the presentation is to bridge the gap between scientific studies of auroral charging and the need for engineering teams to understand how space weather impacts both spacecraft design and operations for vehicles on orbital trajectories that traverse auroral charging environments.

The role of synoptic weather variability in Greenland ice sheet dynamics

NASA Astrophysics Data System (ADS)

Walker, J. M.; Radic, V.

2017-12-01

Much of the large uncertainty in predictions of future global sea level rise is due to our limited understanding of Greenland ice sheet (GrIS) motion and its interactions with climate. Over the next century, climate models predict that the GrIS will experience not only gradual warming, but also changes in atmospheric circulation, hydrology, and weather, including a northward shift of the North Atlantic storm track, with greater frequency and intensity of rain storms over the GrIS. Recent studies of GrIS dynamics have focused on the effects of increased seasonal mean meltwater on ice velocities, finding only a modest impact due to compensation by subglacial drainage systems, but subglacial hydraulic theory indicates that variability on shorter timescales is also relevant: short-term surges in meltwater or rainfall can overload drainage systems at rates faster than they can adjust, leading to water pressure spikes and ice acceleration. If the magnitude or frequency of these transient ice accelerations increase substantially as synoptic weather patterns change over the next century, there could be a significant cumulative impact on seasonal mean ice velocities. However, this issue has not been addressed in the literature and represents a major source of uncertainty. In this study, we investigate the role of synoptic weather variability in GrIS dynamics, with the ultimate goal of evaluating the relationships between extreme weather events and ice sheet flow in different seasons and regions of the GrIS. As a first step, we apply the machine learning technique of self-organizing maps to atmospheric reanalysis data to categorize the predominant synoptic weather systems over the GrIS domain, evaluating atmospheric moisture transport and rainfall to assess the impacts of each weather system on GrIS surface hydrology. The preliminary results presented here will be used in conjunction with ice velocity satellite measurements in future work, to identify any correlations between seasonal mean GrIS velocities and the frequency or intensity of storms during the season.
Linking animals aloft with the terrestrial landscape

USGS Publications Warehouse

Buler, Jeffrey J.; Barrow, Wylie; Boone, Matthew; Dawson, Deanna K.; Diehl, Robert H.; Moore, Frank R.; Randall, Lori A.; Schreckengost, Timothy; Smolinsky, Jaclyn A.

2018-01-01

Despite using the aerosphere for many facets of their life, most flying animals (i.e., birds, bats, some insects) are still bound to terrestrial habitats for resting, feeding, and reproduction. Comprehensive broad-scale observations by weather surveillance radars of animals as they leave terrestrial habitats for migration or feeding flights can be used to map their terrestrial distributions either as point locations (e.g., communal roosts) or as continuous surface layers (e.g., animal densities in habitats across a landscape). We discuss some of the technical challenges to reducing measurement biases related to how radars sample the aerosphere and the flight behavior of animals. We highlight a recently developed methodological approach that precisely and quantitatively links the horizontal spatial structure of birds aloft to their terrestrial distributions and provides novel insights into avian ecology and conservation across broad landscapes. Specifically, we present case studies that (1) elucidate how migrating birds contend with crossing ecological barriers and extreme weather events, (2) identify important stopover areas and habitat use patterns of birds along their migration routes, and (3) assess waterfowl response to wetland habitat management and restoration. These studies aid our understanding of how anthropogenic modification of the terrestrial landscape (e.g., urbanization, habitat management), natural geographic features, and weather (e.g., hurricanes) can affect the terrestrial distributions of flying animals.
Daily Weather and Children's Physical Activity Patterns.

PubMed

Remmers, Teun; Thijs, Carel; Timperio, Anna; Salmon, J O; Veitch, Jenny; Kremers, Stef P J; Ridgers, Nicola D

2017-05-01

Understanding how the weather affects physical activity (PA) may help in the design, analysis, and interpretation of future studies, especially when investigating PA across diverse meteorological settings and with long follow-up periods. The present longitudinal study first aims to examine the influence of daily weather elements on intraindividual PA patterns among primary school children across four seasons, reflecting day-to-day variation within each season. Second, we investigate whether the influence of weather elements differs by day of the week (weekdays vs weekends), gender, age, and body mass index. PA data were collected by ActiGraph accelerometers for 1 wk in each of four school terms that reflect each season in southeast Australia. PA data from 307 children (age range 8.7-12.8 yr) were matched to daily meteorological variables obtained from the Australian Government's Bureau of Meteorology (maximum temperature, relative humidity, solar radiation, day length, and rainfall). Daily PA patterns and their association with weather elements were analyzed using multilevel linear mixed models. Temperature was the strongest predictor of moderate and vigorous PA, followed by solar radiation and humidity. The relation with temperature was curvilinear, showing optimum PA levels at temperatures between 20°C and 22°C. Associations between weather elements on PA did not differ by gender, child's age, or body mass index. This novel study focused on the influence of weather elements on intraindividual PA patterns in children. As weather influences cannot be controlled, knowledge of its effect on individual PA patterns may help in the design of future studies, interpretation of their results, and translation into PA promotion.
Episode of intense chemical weathering during the termination of the 635 Ma Marinoan glaciation

PubMed Central

Huang, Kang-Jun; Teng, Fang-Zhen; Shen, Bing; Xiao, Shuhai; Lang, Xianguo; Ma, Hao-Ran; Fu, Yong; Peng, Yongbo

2016-01-01

Cryogenian (∼720–635 Ma) global glaciations (the snowball Earth) represent the most extreme ice ages in Earth’s history. The termination of these snowball Earth glaciations is marked by the global precipitation of cap carbonates, which are interpreted to have been driven by intense chemical weathering on continents. However, direct geochemical evidence for the intense chemical weathering in the aftermath of snowball glaciations is lacking. Here, we report Mg isotopic data from the terminal Cryogenian or Marinoan-age Nantuo Formation and the overlying cap carbonate of the basal Doushantuo Formation in South China. A positive excursion of extremely high δ26Mg values (+0.56 to +0.95)—indicative of an episode of intense chemical weathering—occurs in the top Nantuo Formation, whereas the siliciclastic component of the overlying Doushantuo cap carbonate has significantly lower δ26Mg values (<+0.40), suggesting moderate to low intensity of chemical weathering during cap carbonate deposition. These observations suggest that cap carbonate deposition postdates the climax of chemical weathering, probably because of the suppression of carbonate precipitation in an acidified ocean when atmospheric CO2 concentration was high. Cap carbonate deposition did not occur until chemical weathering had consumed substantial amounts of atmospheric CO2 and accumulated high levels of oceanic alkalinity. Our finding confirms intense chemical weathering at the onset of deglaciation but indicates that the maximum weathering predated cap carbonate deposition. PMID:27956606
The partitioning of litter carbon during litter decomposition under different rainfall patterns: a laboratory study

NASA Astrophysics Data System (ADS)

Yang, X.; Szlavecz, K. A.; Langley, J. A.; Pitz, S.; Chang, C. H.

2017-12-01

Quantifying litter C into different C fluxes during litter decomposition is necessary to understand carbon cycling under changing climatic conditions. Rainfall patterns are predicted to change in the future, and their effects on the fate of litter carbon are poorly understood. Soils from deciduous forests in Smithsonian Environmental Research Center (SERC) in Maryland, USA were collected to reconstruct soil columns in the lab. 13C labeled tulip poplar leaf litter was used to trace carbon during litter decomposition. Top 1% and the mean of 15-minute historical precipitation data from nearby weather stations were considered as extreme and control rainfall intensity, respectively. Both intensity and frequency of rainfall were manipulated, while the total amount was kept constant. A pulse of CO2 efflux was detected right after each rainfall event in the soil columns with leaf litter. After the first event, CO2 efflux of the control rainfall treatment soils increased to threefold of the CO2 efflux before rain event and that of the extreme treatment soils increased to fivefold. However, in soils without leaf litter, CO2 efflux was suppressed right after rainfall events. After each rainfall event, the leaf litter contribution to CO2 efflux first showed an increase, decreased sharply in the following two days, and then stayed relatively constant. In soil columns with leaf litter, the order of cumulative CO2 efflux was control > extreme > intermediate. The order of cumulative CO2 efflux in the bare soil treatment was extreme > intermediate > control. The order of volume of leachate from different treatments was extreme > intermediate > control. Our initial results suggest that more intense rainfall events result in larger pulses of CO2, which is rarely measured in the field. Additionally, soils with and without leaf litter respond differently to precipitation events. This is important to consider in temperate regions where leaf litter cover changes throughout the year. Including the rainfall pattern as a parameter to the partitioning of litter carbon could help better project soil carbon cycling in the Mid-Atlantic region.
Economic Value of Weather and Climate Forecasts

NASA Astrophysics Data System (ADS)

Katz, Richard W.; Murphy, Allan H.

1997-06-01

Weather and climate extremes can significantly impact the economics of a region. This book examines how weather and climate forecasts can be used to mitigate the impact of the weather on the economy. Interdisciplinary in scope, it explores the meteorological, economic, psychological, and statistical aspects of weather prediction. Chapters by area specialists provide a comprehensive view of this timely topic. They encompass forecasts over a wide range of temporal scales, from weather over the next few hours to the climate months or seasons ahead, and address the impact of these forecasts on human behavior. Economic Value of Weather and Climate Forecasts seeks to determine the economic benefits of existing weather forecasting systems and the incremental benefits of improving these systems, and will be an interesting and essential text for economists, statisticians, and meteorologists.
Isolating weather effects from seasonal activity patterns of a temperate North American Colubrid

Treesearch

Andrew D. George; Frank R. III Thompson; John Faaborg

2015-01-01

Forecasting the effects of climate change on threatened ecosystems and species will require an understanding of how weather influences processes that drive population dynamics. We have evaluated weather effects on activity patterns of western ratsnakes, a widespread predator of birds and small mammals in eastern North America. From 2010-2013 we radio-tracked 53...
A Generalized Framework for Non-Stationary Extreme Value Analysis

NASA Astrophysics Data System (ADS)

Ragno, E.; Cheng, L.; Sadegh, M.; AghaKouchak, A.

2017-12-01

Empirical trends in climate variables including precipitation, temperature, snow-water equivalent at regional to continental scales are evidence of changes in climate over time. The evolving climate conditions and human activity-related factors such as urbanization and population growth can exert further changes in weather and climate extremes. As a result, the scientific community faces an increasing demand for updated appraisal of the time-varying climate extremes. The purpose of this study is to offer a robust and flexible statistical tool for non-stationary extreme value analysis which can better characterize the severity and likelihood of extreme climatic variables. This is critical to ensure a more resilient environment in a changing climate. Following the positive feedback on the first version of Non-Stationary Extreme Value Analysis (NEVA) Toolbox by Cheng at al. 2014, we present an improved version, i.e. NEVA2.0. The upgraded version herein builds upon a newly-developed hybrid evolution Markov Chain Monte Carlo (MCMC) approach for numerical parameters estimation and uncertainty assessment. This addition leads to a more robust uncertainty estimates of return levels, return periods, and risks of climatic extremes under both stationary and non-stationary assumptions. Moreover, NEVA2.0 is flexible in incorporating any user-specified covariate other than the default time-covariate (e.g., CO2 emissions, large scale climatic oscillation patterns). The new feature will allow users to examine non-stationarity of extremes induced by physical conditions that underlie the extreme events (e.g. antecedent soil moisture deficit, large-scale climatic teleconnections, urbanization). In addition, the new version offers an option to generate stationary and/or non-stationary rainfall Intensity - Duration - Frequency (IDF) curves that are widely used for risk assessment and infrastructure design. Finally, a Graphical User Interface (GUI) of the package is provided, making NEVA accessible to a broader audience.
Weather Augmented Risk Determination (WARD) System

NASA Astrophysics Data System (ADS)

Niknejad, M.; Mazdiyasni, O.; Momtaz, F.; AghaKouchak, A.

2017-12-01

Extreme climatic events have direct and indirect impacts on society, economy and the environment. Based on the United States Bureau of Economic Analysis (BEA) data, over one third of the U.S. GDP can be considered as weather-sensitive involving some degree of weather risk. This expands from a local scale concrete foundation construction to large scale transportation systems. Extreme and unexpected weather conditions have always been considered as one of the probable risks to human health, productivity and activities. The construction industry is a large sector of the economy, and is also greatly influenced by weather-related risks including work stoppage and low labor productivity. Identification and quantification of these risks, and providing mitigation of their effects are always the concerns of construction project managers. In addition to severe weather conditions' destructive effects, seasonal changes in weather conditions can also have negative impacts on human health. Work stoppage and reduced labor productivity can be caused by precipitation, wind, temperature, relative humidity and other weather conditions. Historical and project-specific weather information can improve better project management and mitigation planning, and ultimately reduce the risk of weather-related conditions. This paper proposes new software for project-specific user-defined data analysis that offers (a) probability of work stoppage and the estimated project length considering weather conditions; (b) information on reduced labor productivity and its impacts on project duration; and (c) probabilistic information on the project timeline based on both weather-related work stoppage and labor productivity. The software (WARD System) is designed such that it can be integrated into the already available project management tools. While the system and presented application focuses on the construction industry, the developed software is general and can be used for any application that involves labor productivity (e.g., farming) and work stoppage due to weather conditions (e.g., transportation, agriculture industry).
Living with extreme weather events - perspectives from climatology, geomorphological analysis, chronicles and opinion polls

NASA Astrophysics Data System (ADS)

Auer, I.; Kirchengast, A.; Proske, H.

2009-09-01

The ongoing climate change debate focuses more and more on changing extreme events. Information on past events can be derived from a number of sources, such as instrumental data, residual impacts in the landscape, but also chronicles and people's memories. A project called "A Tale of Two Valleys” within the framework of the research program "proVision” allowed to study past extreme events in two inner-alpine valleys from the sources mentioned before. Instrumental climate time series provided information for the past 200 years, however great attention had to be given to the homogeneity of the series. To derive homogenized time series of selected climate change indices methods like HOCLIS and Vincent have been applied. Trend analyses of climate change indices inform about increase or decrease of extreme events. Traces of major geomorphodynamic processes of the past (e.g. rockfalls, landslides, debris flows) which were triggered or affected by extreme weather events are still apparent in the landscape and could be evaluated by geomorphological analysis using remote sensing and field data. Regional chronicles provided additional knowledge and covered longer periods back in time, however compared to meteorological time series they enclose a high degree of subjectivity and intermittent recordings cannot be obviated. Finally, questionnaires and oral history complemented our picture of past extreme weather events. People were differently affected and have different memories of it. The joint analyses of these four data sources showed agreement to some extent, however also showed some reasonable differences: meteorological data are point measurements only with a sometimes too coarse temporal resolution. Due to land-use changes and improved constructional measures the impact of an extreme meteorological event may be different today compared to earlier times.
A Tree-Ring Based Reconstruction (1725-present) of the Position of the Summer North Atlantic Jet Shows a 20th Century Northward Shift

NASA Astrophysics Data System (ADS)

Trouet, V.; Babst, F.

2014-12-01

The position and strength of the Northern Hemisphere polar jet are important modulators of mid-latitude weather extremes and the societal, ecosystem, and economic damage related to them. The position of the North Atlantic jet (NAJ) controls the location of the Atlantic storm track and anomalies in the NAJ position have been related to temperature and precipitation extremes over Europe. In summer, a southern NAJ regime can result in floods in the British Isles (BRIT) and increasing odds of heat waves in the northeastern Mediterranean (NEMED). Variability in the amplitude and speed of the Northern Hemisphere jet stream is hotly debated as a potential mechanism linking recent mid-latitude weather extremes to anthropogenic warming. However, the hypothesis of jet stream variability as a possible mechanism linking Arctic amplification to mid-latitude weather extremes is largely based on data sets with limited temporal extent that do not warrant robust results from a statistical significance perspective. Here, we combined two summer temperature-sensitive tree-ring records from BRIT and NEMED to reconstruct interannual variability in the latitudinal position of the summer NAJ back to 1725. The two well-replicated temperature proxies counter-correlate significantly over the full period and thus illustrate the temperature dipole generated by anomalous NAJ positions. Positive extremes in the NAJ reconstruction correspond to heatwaves recorded in the historical Central England temperature record and negative extremes correspond to reconstructed fire years in Greece. The reconstruction shows a northward shift in the latitudinal NAJ position since the 1930s that is most pronounced in the northern NAJ extremes, suggesting a more frequent occurrence of BRIT hot summers in the 20th century compared to previous centuries.
Analysis of extreme summers and prior late winter/spring conditions in central Europe

NASA Astrophysics Data System (ADS)

Träger-Chatterjee, C.; Müller, R. W.; Bendix, J.

2013-05-01

Drought and heat waves during summer in mid-latitudes are a serious threat to human health and agriculture and have negative impacts on the infrastructure, such as problems in energy supply. The appearance of such extreme events is expected to increase with the progress of global warming. A better understanding of the development of extremely hot and dry summers and the identification of possible precursors could help improve existing seasonal forecasts in this regard, and could possibly lead to the development of early warning methods. The development of extremely hot and dry summer seasons in central Europe is attributed to a combined effect of the dominance of anticyclonic weather regimes and soil moisture-atmosphere interactions. The atmospheric circulation largely determines the amount of solar irradiation and the amount of precipitation in an area. These two variables are themselves major factors controlling the soil moisture. Thus, solar irradiation and precipitation are used as proxies to analyse extreme sunny and dry late winter/spring and summer seasons for the period 1958-2011 in Germany and adjacent areas. For this purpose, solar irradiation data from the European Center for Medium Range Weather Forecast 40-yr and interim re-analysis dataset, as well as remote sensing data are used. Precipitation data are taken from the Global Precipitation Climatology Project. To analyse the atmospheric circulation geopotential data at 850 hPa are also taken from the European Center for Medium Range Weather Forecast 40-yr and interim re-analysis datasets. For the years in which extreme summers in terms of high solar irradiation and low precipitation are identified, the previous late winter/spring conditions of solar irradiation and precipitation in Germany and adjacent areas are analysed. Results show that if the El Niño-Southern Oscillation (ENSO) is not very intensely developed, extremely high solar irradiation amounts, together with extremely low precipitation amounts during late winter/spring, might serve as precursor of extremely sunny and dry summer months to be expected.
Weather patterns as a downscaling tool - evaluating their skill in stratifying local climate variables

NASA Astrophysics Data System (ADS)

Murawski, Aline; Bürger, Gerd; Vorogushyn, Sergiy; Merz, Bruno

2016-04-01

The use of a weather pattern based approach for downscaling of coarse, gridded atmospheric data, as usually obtained from the output of general circulation models (GCM), allows for investigating the impact of anthropogenic greenhouse gas emissions on fluxes and state variables of the hydrological cycle such as e.g. on runoff in large river catchments. Here we aim at attributing changes in high flows in the Rhine catchment to anthropogenic climate change. Therefore we run an objective classification scheme (simulated annealing and diversified randomisation - SANDRA, available from the cost733 classification software) on ERA20C reanalyses data and apply the established classification to GCMs from the CMIP5 project. After deriving weather pattern time series from GCM runs using forcing from all greenhouse gases (All-Hist) and using natural greenhouse gas forcing only (Nat-Hist), a weather generator will be employed to obtain climate data time series for the hydrological model. The parameters of the weather pattern classification (i.e. spatial extent, number of patterns, classification variables) need to be selected in a way that allows for good stratification of the meteorological variables that are of interest for the hydrological modelling. We evaluate the skill of the classification in stratifying meteorological data using a multi-variable approach. This allows for estimating the stratification skill for all meteorological variables together, not separately as usually done in existing similar work. The advantage of the multi-variable approach is to properly account for situations where e.g. two patterns are associated with similar mean daily temperature, but one pattern is dry while the other one is related to considerable amounts of precipitation. Thus, the separation of these two patterns would not be justified when considering temperature only, but is perfectly reasonable when accounting for precipitation as well. Besides that, the weather patterns derived from reanalyses data should be well represented in the All-Hist GCM runs in terms of e.g. frequency, seasonality, and persistence. In this contribution we show how to select the most appropriate weather pattern classification and how the classes derived from it are reflected in the GCMs.
The influence of mid-latitude storm tracks on hot, cold, dry and wet extremes

PubMed Central

Lehmann, Jascha; Coumou, Dim

2015-01-01

Changes in mid-latitude circulation can strongly affect the number and intensity of extreme weather events. In particular, high-amplitude quasi-stationary planetary waves have been linked to prolonged weather extremes at the surface. In contrast, analyses of fast-traveling synoptic-scale waves and their direct influence on heat and cold extremes are scarce though changes in such waves have been detected and are projected for the 21st century. Here we apply regression analyses of synoptic activity with surface temperature and precipitation in monthly gridded observational data. We show that over large parts of mid-latitude continental regions, summer heat extremes are associated with low storm track activity. In winter, the occurrence of cold spells is related to low storm track activity over parts of eastern North America, Europe, and central- to eastern Asia. Storm tracks thus have a moderating effect on continental temperatures. Pronounced storm track activity favors monthly rainfall extremes throughout the year, whereas dry spells are associated with a lack thereof. Trend analyses reveal significant regional changes in recent decades favoring the occurrence of cold spells in the eastern US, droughts in California and heat extremes over Eurasia. PMID:26657163
Influences of extreme weather, climate and pesticide use on invertebrates in cereal fields over 42 years.

PubMed

Ewald, Julie A; Wheatley, Christopher J; Aebischer, Nicholas J; Moreby, Stephen J; Duffield, Simon J; Crick, Humphrey Q P; Morecroft, Michael B

2015-11-01

Cereal fields are central to balancing food production and environmental health in the face of climate change. Within them, invertebrates provide key ecosystem services. Using 42 years of monitoring data collected in southern England, we investigated the sensitivity and resilience of invertebrates in cereal fields to extreme weather events and examined the effect of long-term changes in temperature, rainfall and pesticide use on invertebrate abundance. Of the 26 invertebrate groups examined, eleven proved sensitive to extreme weather events. Average abundance increased in hot/dry years and decreased in cold/wet years for Araneae, Cicadellidae, adult Heteroptera, Thysanoptera, Braconidae, Enicmus and Lathridiidae. The average abundance of Delphacidae, Cryptophagidae and Mycetophilidae increased in both hot/dry and cold/wet years relative to other years. The abundance of all 10 groups usually returned to their long-term trend within a year after the extreme event. For five of them, sensitivity to cold/wet events was lowest (translating into higher abundances) at locations with a westerly aspect. Some long-term trends in invertebrate abundance correlated with temperature and rainfall, indicating that climate change may affect them. However, pesticide use was more important in explaining the trends, suggesting that reduced pesticide use would mitigate the effects of climate change. © 2015 John Wiley & Sons Ltd.
Simulation of the 23 July 2012 Extreme Space Weather Event: What if This Extremely Rare CME Was Earth Directed?

NASA Technical Reports Server (NTRS)

Ngwira, Chigomezyo M.; Pulkkinen, Antti; Mays, M. Leila; Kuznetsova, Maria M.; Galvin, A. B.; Simunac, Kristin; Baker, Daniel N.; Li, Xinlin; Zheng, Yihua; Glocer, Alex

2013-01-01

Extreme space weather events are known to cause adverse impacts on critical modern day technological infrastructure such as high-voltage electric power transmission grids. On 23 July 2012, NASA's Solar Terrestrial Relations Observatory-Ahead (STEREO-A) spacecraft observed in situ an extremely fast coronal mass ejection (CME) that traveled 0.96 astronomical units (approx. 1 AU) in about 19 h. Here we use the SpaceWeather Modeling Framework (SWMF) to perform a simulation of this rare CME.We consider STEREO-A in situ observations to represent the upstream L1 solar wind boundary conditions. The goal of this study is to examine what would have happened if this Rare-type CME was Earth-bound. Global SWMF-generated ground geomagnetic field perturbations are used to compute the simulated induced geoelectric field at specific ground-based active INTERMAGNET magnetometer sites. Simulation results show that while modeled global SYM-H index, a high-resolution equivalent of the Dst index, was comparable to previously observed severe geomagnetic storms such as the Halloween 2003 storm, the 23 July CME would have produced some of the largest geomagnetically induced electric fields, making it very geoeffective. These results have important practical applications for risk management of electrical power grids.
Evidence of fuels management and fire weather influencing fire severity in an extreme fire event

USGS Publications Warehouse

Lydersen, Jamie M; Collins, Brandon M.; Brooks, Matthew L.; Matchett, John R.; Shive, Kristen L.; Povak, Nicholas A.; Kane, Van R.; Smith, Douglas F.

2017-01-01

Following changes in vegetation structure and pattern, along with a changing climate, large wildfire incidence has increased in forests throughout the western U.S. Given this increase there is great interest in whether fuels treatments and previous wildfire can alter fire severity patterns in large wildfires. We assessed the relative influence of previous fuels treatments (including wildfire), fire weather, vegetation and water balance on fire severity in the Rim Fire of 2013. We did this at three different spatial scales to investigate whether the influences on fire severity changed across scales. Both fuels treatments and previous low to moderate severity wildfire reduced the prevalence of high severity fire. In general, areas without recent fuels treatments and areas that previously burned at high severity tended to have a greater proportion of high severity fire in the Rim Fire. Areas treated with prescribed fire, especially when combined with thinning, had the lowest proportions of high severity. Proportion of the landscape burned at high severity was most strongly influenced by fire weather and proportional area previously treated for fuels or burned by low to moderate severity wildfire. The proportion treated needed to effectively reduce the amount of high fire severity fire varied by spatial scale of analysis, with smaller spatial scales requiring a greater proportion treated to see an effect on fire severity. When moderate and high severity fire encountered a previously treated area, fire severity was significantly reduced in the treated area relative to the adjacent untreated area. Our results show that fuels treatments and low to moderate severity wildfire can reduce fire severity in a subsequent wildfire, even when burning under fire growth conditions. These results serve as further evidence that both fuels treatments and lower severity wildfire can increase forest resilience.
CLIMATE CHANGE EFFECTS ON ECOSYSTEM SERVICES AND HUMAN HEALTH

EPA Science Inventory

Human health and well-being are and will be affected by climate change, both directly through changes in extreme weather events and indirectly through weather induced changes in societal systems and their supporting ecosystems. The goal of this study was to develop and apply a b...
Climate Risk Management in the Anthropocene: From Basic Science to Decisionmaking and Back.

NASA Astrophysics Data System (ADS)

King, A.; Karoly, D. J.

2014-12-01

In this talk I will discuss studies our group has conducted to investigate the role of anthropogenic climate change in the heavy rains of 2010-2012 and the heat and drought of 2013. Using a range of methodologies based on coupled climate models from the CMIP5 archive and very large atmosphere-only ensembles from the Weather@Home Australia-New Zealand ensemble we have found increases in the likelihood of hot extremes, such as the summer of 2012/13 and individual record-breaking hot days within that summer. In contrast, studies of the precipitation extremes that occurred in the summer of 2011/12 found limited evidence for a substantial anthropogenic role in these events. I will also present briefly on avenues of research we are currently pursuing in the Australian community. These include investigating whether anthropogenic climate change has altered the likelihood of weather associated with bushfires and the implementation of perturbed physics in the Weather@Home ensemble to allow us to study the potential role of human-induced climate change on extreme rainfall events.
Influence of Anthropogenic Climate Change on Planetary Wave Resonance and Extreme Weather Events

PubMed Central

Mann, Michael E.; Rahmstorf, Stefan; Kornhuber, Kai; Steinman, Byron A.; Miller, Sonya K.; Coumou, Dim

2017-01-01

Persistent episodes of extreme weather in the Northern Hemisphere summer have been shown to be associated with the presence of high-amplitude quasi-stationary atmospheric Rossby waves within a particular wavelength range (zonal wavenumber 6–8). The underlying mechanistic relationship involves the phenomenon of quasi-resonant amplification (QRA) of synoptic-scale waves with that wavenumber range becoming trapped within an effective mid-latitude atmospheric waveguide. Recent work suggests an increase in recent decades in the occurrence of QRA-favorable conditions and associated extreme weather, possibly linked to amplified Arctic warming and thus a climate change influence. Here, we isolate a specific fingerprint in the zonal mean surface temperature profile that is associated with QRA-favorable conditions. State-of-the-art (“CMIP5”) historical climate model simulations subject to anthropogenic forcing display an increase in the projection of this fingerprint that is mirrored in multiple observational surface temperature datasets. Both the models and observations suggest this signal has only recently emerged from the background noise of natural variability. PMID:28345645

Early prediction of extreme stratospheric polar vortex states based on causal precursors

NASA Astrophysics Data System (ADS)

Kretschmer, Marlene; Runge, Jakob; Coumou, Dim

2017-08-01

Variability in the stratospheric polar vortex (SPV) can influence the tropospheric circulation and thereby winter weather. Early predictions of extreme SPV states are thus important to improve forecasts of winter weather including cold spells. However, dynamical models are usually restricted in lead time because they poorly capture low-frequency processes. Empirical models often suffer from overfitting problems as the relevant physical processes and time lags are often not well understood. Here we introduce a novel empirical prediction method by uniting a response-guided community detection scheme with a causal discovery algorithm. This way, we objectively identify causal precursors of the SPV at subseasonal lead times and find them to be in good agreement with known physical drivers. A linear regression prediction model based on the causal precursors can explain most SPV variability (r2 = 0.58), and our scheme correctly predicts 58% (46%) of extremely weak SPV states for lead times of 1-15 (16-30) days with false-alarm rates of only approximately 5%. Our method can be applied to any variable relevant for (sub)seasonal weather forecasts and could thus help improving long-lead predictions.
Development of Radar-Satellite Blended QPF (Quantitative Precipitation Forecast) Technique for heavy rainfall

NASA Astrophysics Data System (ADS)

Jang, Sangmin; Yoon, Sunkwon; Rhee, Jinyoung; Park, Kyungwon

2016-04-01

Due to the recent extreme weather and climate change, a frequency and size of localized heavy rainfall increases and it may bring various hazards including sediment-related disasters, flooding and inundation. To prevent and mitigate damage from such disasters, very short range forecasting and nowcasting of precipitation amounts are very important. Weather radar data very useful in monitoring and forecasting because weather radar has high resolution in spatial and temporal. Generally, extrapolation based on the motion vector is the best method of precipitation forecasting using radar rainfall data for a time frame within a few hours from the present. However, there is a need for improvement due to the radar rainfall being less accurate than rain-gauge on surface. To improve the radar rainfall and to take advantage of the COMS (Communication, Ocean and Meteorological Satellite) data, a technique to blend the different data types for very short range forecasting purposes was developed in the present study. The motion vector of precipitation systems are estimated using 1.5km CAPPI (Constant Altitude Plan Position Indicator) reflectivity by pattern matching method, which indicates the systems' direction and speed of movement and blended radar-COMS rain field is used for initial data. Since the original horizontal resolution of COMS is 4 km while that of radar is about 1 km, spatial downscaling technique is used to downscale the COMS data from 4 to 1 km pixels in order to match with the radar data. The accuracies of rainfall forecasting data were verified utilizing AWS (Automatic Weather System) observed data for an extreme rainfall occurred in the southern part of Korean Peninsula on 25 August 2014. The results of this study will be used as input data for an urban stream real-time flood early warning system and a prediction model of landslide. Acknowledgement This research was supported by a grant (13SCIPS04) from Smart Civil Infrastructure Research Program funded by Ministry of Land, Infrastructure and Transport (MOLIT) of Korea government and Korea Agency for Infrastructure Technology Advancement (KAIA).
An approach for assessing the sensitivity of floods to regional climate change

NASA Astrophysics Data System (ADS)

Hughes, James P.; Lettenmaier, Dennis P.; Wood, Eric F.

1992-06-01

A high visibility afforded climate change issues is recent years has led to conflicts between and among decision makers and scientists. Decision makers inevitably feel pressure to assess the effect of climate change on the public welfare, while most climate modelers are, to a greater or lesser degree, concerned about the extent to which known inaccuracies in their models limit or preclude the use of modeling results for policy making. The water resources sector affords a good example of the limitations of the use of alternative climate scenarios derived from GCMs for decision making. GCM simulations of precipitation agree poorly between GCMs, and GCM predictions of runoff and evapotranspiration are even more uncertain. Further, water resources managers must be concerned about hydrologic extremes (floods and droughts) which are much more difficult to predict than ``average'' conditions. Most studies of the sensitivity of water resource systems and operating policies to climate change to data have been based on simple perturbations of historic hydroclimatological time series to reflect the difference between large area GCM simulations for an altered climate (e.g., CO2 doubling) and a GCM simulation of present climate. Such approaches are especially limited for assessment of the sensitivity of water resources systems under extreme conditions, conditions, since the distribution of storm inter-arrival times, for instance, is kept identical to that observed in the historic past. Further, such approaches have generally been based on the difference between the GCM altered and present climates for a single grid cell, primarily because the GCM spatial scale is often much larger than the scale at which climate interpretations are desired. The use of single grid cell GCM results is considered inadvisable by many GCM modelers, who feel the spatial scale for which interpretation of GCM results is most reasonable is on the order of several grid cells. In this paper, we demonstrate an alternative approach to assessing the implications of altered climates as predicted by GCMs for extreme (flooding) conditions. The approach is based on the characterization of regional atmospheric circulation patterns through a weather typing procedure, from which a stochastic model of the weather class occurrences is formulated. Weather types are identified through a CART (Classification and Regression Tree) approach. Precipitation occurence/non-occurence at multiple precipitation station is then predicted through a second stage stochastic model. Precipitation amounts are predicted conditional on the weather class identified from the large area circulation information.
Using the North American Breeding Bird Survey to assess broad-scale response of the continent's most imperiled avian community, grassland birds, to weather variability

USGS Publications Warehouse

Gorzo, Jessica; Pidgeon, Anna M.; Thogmartin, Wayne E.; Allstadt, Andrew J.; Radeloff, Volker C.; Heglund, Patricia J.; Vavrus, Stephen J.

2016-01-01

Avian populations can respond dramatically to extreme weather such as droughts and heat waves, yet patterns of response to weather at broad scales remain largely unknown. Our goal was to evaluate annual variation in abundance of 14 grassland bird species breeding in the northern mixed-grass prairie in relation to annual variation in precipitation and temperature. We modeled avian abundance during the breeding season using North American Breeding Bird Survey (BBS) data for the U.S. Badlands and Prairies Bird Conservation Region (BCR 17) from 1980 to 2012. We used hierarchical Bayesian methods to fit models and estimate the candidate weather parameters standardized precipitation index (SPI) and standardized temperature index (STI) for the same year and the previous year. Upland Sandpiper (Bartramia longicauda) responded positively to within-year STI (β = 0.101), and Baird's Sparrow (Ammodramus bairdii) responded negatively to within-year STI (β = −0.161) and positively to within-year SPI (β = 0.195). The parameter estimates were superficially similar (STI β = −0.075, SPI β = 0.11) for Grasshopper Sparrow (Ammodramus savannarum), but the best-selected model included an interaction between SPI and STI. The best model for both Eastern Kingbird (Tyrannus tyrannus) and Vesper Sparrow (Pooecetes gramineus) included the additive effects of within-year SPI (β = −0.032 and β = −0.054, respectively) and the previous-year's SPI (β = −0.057 and −0.02, respectively), although for Vesper Sparrow the lag effect was insignificant. With projected warmer, drier weather during summer in the Badlands and Prairies BCR, Baird's and Grasshopper sparrows may be especially threatened by future climate change.
Contributions of ignitions, fuels, and weather to the spatial patterns of burn probability of a boreal landscape

Treesearch

Marc-Andre Parisien; Sean A. Parks; Carol Miller; Meg A. Krawchuck; Mark Heathcott; Max A. Moritz

2011-01-01

The spatial pattern of fire observed across boreal landscapes is the outcome of complex interactions among components of the fire environment. We investigated how the naturally occurring patterns of ignitions, fuels, and weather generate spatial pattern of burn probability (BP) in a large and highly fireprone boreal landscape of western Canada, Wood Buffalo National...
Fatal pneumonia epizootic in musk ox (Ovibos moschatus) in a period of extraordinary weather conditions.

PubMed

Ytrehus, Bjørnar; Bretten, Tord; Bergsjø, Bjarne; Isaksen, Ketil

2008-06-01

The musk ox is adapted to extreme cold and regarded as vulnerable to the impacts of climate change. Population decline is proposed to occur due to changes in forage availability, insect harassment, parasite load, and habitat availability, while the possible role of infectious diseases has not been emphasized. The goal of the present article is to describe an outbreak of fatal pasteurellosis that occurred in the introduced musk ox population of Dovrefjell, Norway in 2006, causing the death of a large proportion of the animals. The epizootic coincided with extraordinary warm and humid weather, conditions that often are associated with outbreaks of pasteurellosis. The description is based on long series of data from the surveillance of the musk ox population, weather data from a closely located meteorological station, and pathoanatomical investigation of the diseased animals. It is concluded that the weather conditions likely were the decisive factors for the outbreak. It is suggested that such epizootics may occur increasingly among cold-adapted animals if global warming results in increased occurrence of heat waves and associated extreme weather events, thereby causing population declines and possibly extinctions.
Parametric vs. non-parametric daily weather generator: validation and comparison

NASA Astrophysics Data System (ADS)

Dubrovsky, Martin

2016-04-01

As the climate models (GCMs and RCMs) fail to satisfactorily reproduce the real-world surface weather regime, various statistical methods are applied to downscale GCM/RCM outputs into site-specific weather series. The stochastic weather generators are among the most favourite downscaling methods capable to produce realistic (observed like) meteorological inputs for agrological, hydrological and other impact models used in assessing sensitivity of various ecosystems to climate change/variability. To name their advantages, the generators may (i) produce arbitrarily long multi-variate synthetic weather series representing both present and changed climates (in the latter case, the generators are commonly modified by GCM/RCM-based climate change scenarios), (ii) be run in various time steps and for multiple weather variables (the generators reproduce the correlations among variables), (iii) be interpolated (and run also for sites where no weather data are available to calibrate the generator). This contribution will compare two stochastic daily weather generators in terms of their ability to reproduce various features of the daily weather series. M&Rfi is a parametric generator: Markov chain model is used to model precipitation occurrence, precipitation amount is modelled by the Gamma distribution, and the 1st order autoregressive model is used to generate non-precipitation surface weather variables. The non-parametric GoMeZ generator is based on the nearest neighbours resampling technique making no assumption on the distribution of the variables being generated. Various settings of both weather generators will be assumed in the present validation tests. The generators will be validated in terms of (a) extreme temperature and precipitation characteristics (annual and 30 years extremes and maxima of duration of hot/cold/dry/wet spells); (b) selected validation statistics developed within the frame of VALUE project. The tests will be based on observational weather series from several European stations available from the ECA&D database.
Surface atmospheric extremes (Launch and transportation areas)

NASA Technical Reports Server (NTRS)

1972-01-01

The effects of extreme values of surface and low altitude atmospheric parameters on space vehicle design, tests, and operations are discussed. Atmospheric extremes from the surface to 150 meters for geographic locations of interest to NASA are given. Thermal parameters (temperature and solar radiation), humidity, pressure, and atmospheric electricity (lighting and static) are presented. Weather charts and tables are included.
Arctic Sea Ice, Eurasia Snow, and Extreme Winter Haze in China

NASA Astrophysics Data System (ADS)

Zou, Y.; Wang, Y.; Xie, Z.; Zhang, Y.; Koo, J. H.

2017-12-01

Eastern China is experiencing more severe haze pollution in winter during recent years. Though the environmental deterioration in this region is usually attributed to the high intensity of anthropogenic emissions and large contributions from secondary aerosol formation, the impact of climate variability is also indispensable given its significant influence on regional weather systems and pollution ventilation. Here we analyzed the air quality related winter meteorological conditions over Eastern China in the last four decades and showed a worsening trend in poor regional air pollutant ventilation. Such variations increased the probability of extreme air pollution events, which is in good agreement with aerosol observations of recent years. We further identified the key circulation pattern that is conducive to the weakening ventilation and investigated the relationship between synoptic circulation changes and multiple climate forcing variables. Both statistical analysis and numerical sensitivity experiments suggested that the poor ventilation condition is linked to boreal cryosphere changes including Arctic sea ice in preceding autumn and Eurasia snowfall in earlier winter. We conducted comprehensive dynamic diagnosis and proposed a physical mechanism to explain the observed and simulated circulation changes. At last, we examined future projections of winter extreme stagnation events based on the CMIP5 projection data.
Coastal-storm Inundation and Sea-level Rise in New Zealand Scott A. Stephens and Rob Bell

NASA Astrophysics Data System (ADS)

Stephens, S. A.; Bell, R.

2016-12-01

Coastal-storm inundation is a growing problem in New Zealand. It happens occasionally, when the combined forces of weather and sea line up, causing inundation of low-elevation land, coastal erosion, and rivers and stormwater systems to back up causing inland flooding. This becomes a risk where we have placed buildings and infrastructure too close to the coast. Coastal-storm inundation is not a new problem, it has happened historically, but it is becoming more frequent as the sea level continues to rise. From analyses of historic extreme sea-level events, we show how the different sea-level components, such as tide and storm surge, contribute to extreme sea-level and how these components vary around New Zealand. Recent sea-level analyses reveal some large storm surges, bigger than previously reported, and we show the type of weather patterns that drive them, and how this leads to differences in storm surge potential between the east and west coasts. Although large and damaging storm-tides have occurred historically, we show that there is potential for considerably larger elevations to be reached in the "perfect storm", and we estimate the likelihood of such extreme events occurring. Sea-level rise (SLR) will greatly increase the frequency, depth and consequences of coastal-storm inundation in the future. We show an application of a new method to determine the increasing frequency of extreme sea-levels with SLR, one which integrates the extreme tail with regularly-occurring high tides. We present spatial maps of several extreme sea-level threshold exceedance statistics for a case study at Mission Bay, Auckland, New Zealand. The maps show how the local community is likely to face decision points at various SLR thresholds, and we conclude that coastal hazard assessments should ideally use several SLR scenarios and time windows within the next 100 years or more to support the decision-making process for future coastal adaptation and when response options will be needed. In tandem, coastal hazard assessments should also provide information on SLR values linked to expected inundation frequency or depth. This can be linked to plausible timeframes for SLR thresholds to determine when critical decision points for adaptation might be reached, and we show how this might be achieved.
Relating farmer's perceptions of climate change risk to adaptation behaviour in Hungary.

PubMed

Li, Sen; Juhász-Horváth, Linda; Harrison, Paula A; Pintér, László; Rounsevell, Mark D A

2017-01-01

Understanding how farmers perceive climate change risks and how this affects their willingness to adopt adaptation practices is critical for developing effective climate change response strategies for the agricultural sector. This study examines (i) the perceptual relationships between farmers' awareness of climate change phenomena, beliefs in climate change risks and actual adaptation behaviour, and (ii) how these relationships may be modified by farm-level antecedents related to human, social, financial capitals and farm characteristics. An extensive household survey was designed to investigate the current pattern of adaptation strategies and collect data on these perceptual variables and their potential antecedents from private landowners in Veszprém and Tolna counties, Hungary. Path analysis was used to explore the causal connections between variables. We found that belief in the risk of climate change was heightened by an increased awareness of directly observable climate change phenomena (i.e. water shortages and extreme weather events). The awareness of extreme weather events was a significant driver of adaptation behaviour. Farmers' actual adaptation behaviour was primarily driven by financial motives and managerial considerations (i.e. the aim of improving profit and product sales; gaining farm ownership and the amount of land managed; and, the existence of a successor), and stimulated by an innovative personality and the availability of information from socio-agricultural networks. These results enrich the empirical evidence in support of improving understanding of farmer decision-making processes, which is critical in developing well-targeted adaptation policies. Copyright © 2016 Elsevier Ltd. All rights reserved.
Torrejon AB, Madrid, Spain. revised uniform summary of surface weather observations (RUSSWO). parts a-f. Final report

DOE Office of Scientific and Technical Information (OSTI.GOV)

Not Available

1978-10-03

This report is a six-part statistical summary of surface weather observations for Torrejon AB, Madrid Spain. It contains the following parts: (A) Weather Conditions; Atmospheric Phenomena; (B) Precipitation, Snowfall and Snow Depth (daily amounts and extreme values); (C) Surface winds; (D) Ceiling Versus Visibility; Sky Cover; (E) Psychrometric Summaries (daily maximum and minimum temperatures, extreme maximum and minimum temperatures, psychrometric summary of wet-bulb temperature depression versus dry-bulb temperature, means and standard deviations of dry-bulb, wet-bulb and dew-point temperatures and relative humidity); and (F) Pressure Summary (means, standard, deviations, and observation counts of station pressure and sea-level pressure). Data in thismore » report are presented in tabular form, in most cases in percentage frequency of occurrence or cumulative percentage frequency of occurrence tables.« less
Climate change and natural disasters: integrating science and practice to protect health.

PubMed

Sauerborn, Rainer; Ebi, Kristie

2012-12-17

Hydro-meteorological disasters are the focus of this paper. The authors examine, to which extent climate change increases their frequency and intensity. Review of IPCC-projections of climate-change related extreme weather events and related literature on health effects. Projections show that climate change is likely to increase the frequency, intensity, duration, and spatial distribution of a range of extreme weather events over coming decades. There is a need for strengthened collaboration between climate scientists, the health researchers and policy-makers as well as the disaster community to jointly develop adaptation strategies to protect human.
Heat Waves, Droughts, and Preferences for Environmental Policy

ERIC Educational Resources Information Center

Owen, Ann L.; Conover, Emily; Videras, Julio; Wu, Stephen

2012-01-01

Using data from a new household survey on environmental attitudes, behaviors, and policy preferences, we find that current weather conditions affect preferences for environmental regulation. Individuals who have recently experienced extreme weather (heat waves or droughts) are more likely to support laws to protect the environment. We find…
Hurricane Proof This!

ERIC Educational Resources Information Center

Sterling, Donna R.

2010-01-01

While learning about the types of weather events that occur in the local area, students in grades 4-6 were asked to consider how structures can be built to withstand extreme weather conditions. Teams of students designed, constructed, and tested buildings to withstand hurricanes and designed the tests they would use to evaluate their structures.…
The Nature of Mercury's Hollows, and Space Weathering Close to the Sun

NASA Astrophysics Data System (ADS)

Blewett, D. T.; Chabot, N. L.; Denevi, B. W.; Ernst, C. M.

2018-05-01

Hollows are a landform that appear to form by loss of a volatile-bearing phase from silicate rock. Hollows are very young and are likely to be forming in the present day. Hollows may be an analog for extreme weathering on near-Sun asteroids.
Rare earth elements in weathering profiles and sediments of Minnesota: Implications for provenance studies

USGS Publications Warehouse

Morey, G.B.; Setterholm, D.R.

1997-01-01

The relative abundance of rare earth elements in sediments has been suggested as a tool for determining their source rocks. This correlation requires that weathering, erosion, and sedimentation do not alter the REE abundances, or do so in a predictable manner. We find that the rare earth elements are mobilized and fractionated by weathering, and that sediments derived from the weathered materials can display modifications of the original pattern of rare earth elements of some due to grain-size sorting of the weathered material. However, the REE distribution pattern of the provenance terrane can be recognized in the sediments.
Linking crop yield anomalies to large-scale atmospheric circulation in Europe.

PubMed

Ceglar, Andrej; Turco, Marco; Toreti, Andrea; Doblas-Reyes, Francisco J

2017-06-15

Understanding the effects of climate variability and extremes on crop growth and development represents a necessary step to assess the resilience of agricultural systems to changing climate conditions. This study investigates the links between the large-scale atmospheric circulation and crop yields in Europe, providing the basis to develop seasonal crop yield forecasting and thus enabling a more effective and dynamic adaptation to climate variability and change. Four dominant modes of large-scale atmospheric variability have been used: North Atlantic Oscillation, Eastern Atlantic, Scandinavian and Eastern Atlantic-Western Russia patterns. Large-scale atmospheric circulation explains on average 43% of inter-annual winter wheat yield variability, ranging between 20% and 70% across countries. As for grain maize, the average explained variability is 38%, ranging between 20% and 58%. Spatially, the skill of the developed statistical models strongly depends on the large-scale atmospheric variability impact on weather at the regional level, especially during the most sensitive growth stages of flowering and grain filling. Our results also suggest that preceding atmospheric conditions might provide an important source of predictability especially for maize yields in south-eastern Europe. Since the seasonal predictability of large-scale atmospheric patterns is generally higher than the one of surface weather variables (e.g. precipitation) in Europe, seasonal crop yield prediction could benefit from the integration of derived statistical models exploiting the dynamical seasonal forecast of large-scale atmospheric circulation.
Attribution of precipitation changes in African rainforest

NASA Astrophysics Data System (ADS)

Otto, F. E. L.; Allen, M. R.; Bowery, A.; Imbers, J.; Jones, R.; Massey, N.; Miller, J.; Rosier, S.; Rye, C.; Thurston, M.; Wilson, S.; Yamazaki, H.

2012-04-01

Global climate change is almost certainly affecting the magnitude and frequency of extreme weather and hydrological events. However, whether and to what extend the occurrence of such an event can be attributed to climate change remains a challenge that relies on good observations as well as climate modelling. A number of recent studies have attempted to quantify the role of human influence on climate in observed weather events as e.g. the 2010 Russian heat wave (Dole et al, 2011; Rahmstorf and Coumou, 2011; Otto et al, 2012). The overall approach is to simulate, with as realistic a model as possible and accounting as far as possible for modelling uncertainties, both the statistics of observed weather and the statistics of the weather that would have obtained had specific external drivers of climate change been absent. This approach requires a large ensemble size to provide results from which the statistical significance and the shape of the distribution of key variables can be assessed. Also, a sufficiently long period of time must be simulated to evaluate model bias and whether the model captures the observed distribution. The weatherathome.net within the climateprediction.net projects provides such an ensemble with many hundred ensemble members per year via volunteer distributed computing. Most previous attribution studies have been about European extreme weather events but the most vulnerable regions to climate change are in Asia and Africa. One of the most complex hydrological systems is the tropical rainforest, which is expected to react highly sensible to a changing climate. Analysing the weatherathome.net results we find that conditions which are too dry for rainforests to sustain without damages occurred more frequently and more severe in recent years. Furthermore the changes in precipitation in that region can be linked to El Nino/ La Nina events. Linking extreme weather events to large-scale teleconnections helps to understand the occurrence of this events and provides insights for developing forecast methods, also in a region with sparse observational data. We present an important step towards quantifying the link between climate change and extreme weather which is central both to the formulation of evidence-based adaptation policies and to a realistic assessment of the true cost of greenhouse gas emissions, other forms of pollution and land-use change. Dole, R., M. Hoerling, J. Perlwitz, J. Eischeid, P. Pegion, T. Zhang, Xiao-Wei Quan, Taiyi Xu, and D. Murray (2011): Was there a basis for anticipating the 2010 Russian Heat Wave?, GRL 38:L06702. Otto, F.E.L., N. Massey, R. Jones,G.J. van Oldenborgh, and M. R. Allen (2012): Reconciling two approaches to attribution of the 2010 Russian heat wave, GRL under revision. Rahmstorf,S., and D. Coumou (2011), Increase of extreme events in a warming world, PNAS early edition.
Climate Products and Services to Meet the Challenges of Extreme Events

NASA Astrophysics Data System (ADS)

McCalla, M. R.

2008-12-01

The 2002 Office of the Federal Coordinator for Meteorological Services and Supporting Research (OFCM1)-sponsored report, Weather Information for Surface Transportation: National Needs Assessment Report, addressed meteorological needs for six core modes of surface transportation: roadway, railway, transit, marine transportation/operations, pipeline, and airport ground operations. The report's goal was to articulate the weather information needs and attendant surface transportation weather products and services for those entities that use, operate, and manage America's surface transportation infrastructure. The report documented weather thresholds and associated impacts which are critical for decision-making in surface transportation. More recently, the 2008 Climate Change Science Program's (CCSP) Synthesis and Assessment Product (SAP) 4.7 entitled, Impacts of Climate Change and Variability on Transportation Systems and Infrastructure: Gulf Coast Study, Phase I, included many of the impacts from the OFCM- sponsored report in Table 1.1 of this SAP.2 The Intergovernmental Panel on Climate Change (IPCC) reported that since 1950, there has been an increase in the number of heat waves, heavy precipitation events, and areas of drought. Moreover, the IPCC indicated that greater wind speeds could accompany more severe tropical cyclones.3 Taken together, the OFCM, CCSP, and IPCC reports indicate not only the significance of extreme events, but also the potential increasing significance of many of the weather thresholds and associated impacts which are critical for decision-making in surface transportation. Accordingly, there is a real and urgent need to understand what climate products and services are available now to address the weather thresholds within the surface transportation arena. It is equally urgent to understand what new climate products and services are needed to address these weather thresholds, and articulate what can be done to fill the gap between the existing federal climate products and services and the needed federal climate products and services which will address these weather thresholds. Just as important, as we work to meet the needs, a robust education and outreach program is essential to take full advantage of new products, services and capabilities. To ascertain what climate products and services currently exist to address weather thresholds relative to surface transportation, what climate products and services are needed to address these weather thresholds, and how to bridge the gap between what is available and what is needed, the OFCM surveyed the federal meteorological community. Consistent with the extreme events highlighted in the IPCC report, the OFCM survey categorized the weather thresholds associated with surface transportation into the following extreme event areas: (a) excessive heat, (b) winter precipitation, (c) summer precipitation, (d) high winds, and (e) flooding and coastal inundation. The survey results, the gap analysis, as well as OFCM's planned, follow-on activities with additional categories (i.e., in addition to surface transportation) and weather thresholds will be shared with meeting participants. 1 The OFCM is an interdepartmental office established in response to Public Law 87-843 with the mission to ensure the effective use of federal meteorological resources by leading the systematic coordination of operational weather and climate requirements, products, services, and supporting research among the federal agencies. 2 http://www.climatescience.gov/Library/sap/sap4-7/final-report/sap4-7-final-ch1.pdf 3 http://www.gcrio.org/ipcc/ar4/wg1/faq/ar4wg1faq-3-3.pdf

Lessons from Hurricane Sandy: a community response in Brooklyn, New York.

PubMed

Schmeltz, Michael T; González, Sonia K; Fuentes, Liza; Kwan, Amy; Ortega-Williams, Anna; Cowan, Lisa Pilar

2013-10-01

The frequency and intensity of extreme weather events have increased in recent decades; one example is Hurricane Sandy. If the frequency and severity continue or increase, adaptation and mitigation efforts are needed to protect vulnerable populations and improve daily life under changed weather conditions. This field report examines the devastation due to Hurricane Sandy experienced in Red Hook, Brooklyn, New York, a neighborhood consisting of geographically isolated low-lying commercial and residential units, with a concentration of low-income housing, and disproportionate rates of poverty and poor health outcomes largely experienced by Black and Latino residents. Multiple sources of data were reviewed, including street canvasses, governmental reports, community flyers, and meeting transcripts, as well as firsthand observations by a local nonprofit Red Hook Initiative (RHI) and community members, and social media accounts of the effects of Sandy and the response to daily needs. These data are considered within existing theory, evidence, and practice on protecting public health during extreme weather events. Firsthand observations show that a community-based organization in Red Hook, RHI, was at the center of the response to disaster relief, despite the lack of staff training in response to events such as Hurricane Sandy. Review of these data underscores that adaptation and response to climate change and likely resultant extreme weather is a dynamic process requiring an official coordinated governmental response along with on-the-ground volunteer community responders.
The Influence of Weather Variation, Urban Design and Built Environment on Objectively Measured Sedentary Behaviour in Children

PubMed Central

Katapally, Tarun Reddy; Rainham, Daniel; Muhajarine, Nazeem

2016-01-01

With emerging evidence indicating that independent of physical activity, sedentary behaviour (SB) can be detrimental to health, researchers are increasingly aiming to understand the influence of multiple contexts such as urban design and built environment on SB. However, weather variation, a factor that continuously interacts with all other environmental variables, has been consistently underexplored. This study investigated the influence of diverse environmental exposures (including weather variation, urban design and built environment) on SB in children. This cross-sectional observational study is part of an active living research initiative set in the Canadian prairie city of Saskatoon. Saskatoon's neighbourhoods were classified based on urban street design into grid-pattern, fractured grid-pattern and curvilinear types of neighbourhoods. Diverse environmental exposures were measured including, neighbourhood built environment, and neighbourhood and household socioeconomic environment. Actical accelerometers were deployed between April and June 2010 (spring-summer) to derive SB of 331 10–14 year old children in 25 one week cycles. Each cycle of accelerometry was conducted on a different cohort of children within the total sample. Accelerometer data were matched with localized weather patterns derived from Environment Canada weather data. Multilevel modeling using Hierarchical Linear and Non-linear Modeling software was conducted by factoring in weather variation to depict the influence of diverse environmental exposures on SB. Both weather variation and urban design played a significant role in SB. After factoring in weather variation, it was observed that children living in grid-pattern neighbourhoods closer to the city centre (with higher diversity of destinations) were less likely to be sedentary. This study demonstrates a methodology that could be replicated to integrate geography-specific weather patterns with existing cross-sectional accelerometry data to understand the influence of urban design and built environment on SB in children. PMID:29546188
A proposed case-control framework to probabilistically classify individual deaths as expected or excess during extreme hot weather events.

PubMed

Henderson, Sarah B; Gauld, Jillian S; Rauch, Stephen A; McLean, Kathleen E; Krstic, Nikolas; Hondula, David M; Kosatsky, Tom

2016-11-15

Most excess deaths that occur during extreme hot weather events do not have natural heat recorded as an underlying or contributing cause. This study aims to identify the specific individuals who died because of hot weather using only secondary data. A novel approach was developed in which the expected number of deaths was repeatedly sampled from all deaths that occurred during a hot weather event, and compared with deaths during a control period. The deaths were compared with respect to five factors known to be associated with hot weather mortality. Individuals were ranked by their presence in significant models over 100 trials of 10,000 repetitions. Those with the highest rankings were identified as probable excess deaths. Sensitivity analyses were performed on a range of model combinations. These methods were applied to a 2009 hot weather event in greater Vancouver, Canada. The excess deaths identified were sensitive to differences in model combinations, particularly between univariate and multivariate approaches. One multivariate and one univariate combination were chosen as the best models for further analyses. The individuals identified by multiple combinations suggest that marginalized populations in greater Vancouver are at higher risk of death during hot weather. This study proposes novel methods for classifying specific deaths as expected or excess during a hot weather event. Further work is needed to evaluate performance of the methods in simulation studies and against clinically identified cases. If confirmed, these methods could be applied to a wide range of populations and events of interest.
Snow Tweets: Emergency Information Dissemination in a US County During 2014 Winter Storms

PubMed Central

Bonnan-White, Jess; Shulman, Jason; Bielecke, Abigail

2014-01-01

Introduction: This paper describes how American federal, state, and local organizations created, sourced, and disseminated emergency information via social media in preparation for several winter storms in one county in the state of New Jersey (USA). Methods: Postings submitted to Twitter for three winter storm periods were collected from selected organizations, along with a purposeful sample of select private local users. Storm-related posts were analyzed for stylistic features (hashtags, retweet mentions, embedded URLs). Sharing and re-tweeting patterns were also mapped using NodeXL. Results: Results indicate emergency management entities were active in providing preparedness and response information during the selected winter weather events. A large number of posts, however, did not include unique Twitter features that maximize dissemination and discovery by users. Visual representations of interactions illustrate opportunities for developing stronger relationships among agencies. Discussion: Whereas previous research predominantly focuses on large-scale national or international disaster contexts, the current study instead provides needed analysis in a small-scale context. With practice during localized events like extreme weather, effective information dissemination in large events can be enhanced. PMID:25685629
Snow Tweets: Emergency Information Dissemination in a US County During 2014 Winter Storms.

PubMed

Bonnan-White, Jess; Shulman, Jason; Bielecke, Abigail

2014-12-22

This paper describes how American federal, state, and local organizations created, sourced, and disseminated emergency information via social media in preparation for several winter storms in one county in the state of New Jersey (USA). Postings submitted to Twitter for three winter storm periods were collected from selected organizations, along with a purposeful sample of select private local users. Storm-related posts were analyzed for stylistic features (hashtags, retweet mentions, embedded URLs). Sharing and re-tweeting patterns were also mapped using NodeXL. RESULTS indicate emergency management entities were active in providing preparedness and response information during the selected winter weather events. A large number of posts, however, did not include unique Twitter features that maximize dissemination and discovery by users. Visual representations of interactions illustrate opportunities for developing stronger relationships among agencies. Whereas previous research predominantly focuses on large-scale national or international disaster contexts, the current study instead provides needed analysis in a small-scale context. With practice during localized events like extreme weather, effective information dissemination in large events can be enhanced.
Animal health aspects of adaptation to climate change: beating the heat and parasites in a warming Europe.

PubMed

Skuce, P J; Morgan, E R; van Dijk, J; Mitchell, M

2013-06-01

Weather patterns in northern European regions have changed noticeably over the past several decades, featuring warmer, wetter weather with more extreme events. The climate is projected to continue on this trajectory for the foreseeable future, even under the most modest warming scenarios. Such changes will have a significant impact on livestock farming, both directly through effects on the animals themselves, and indirectly through changing exposure to pests and pathogens. Adaptation options aimed at taking advantage of new opportunities and/or minimising the risks of negative impacts will, in themselves, have implications for animal health and welfare. In this review, we consider the potential consequences of future intensification of animal production, challenges associated with indoor and outdoor rearing of animals and aspects of animal transportation as key examples. We investigate the direct and indirect effects of climate change on the epidemiology of important livestock pathogens, with a particular focus on parasitic infections, and the likely animal health consequences associated with selected adaptation options. Finally, we attempt to identify key gaps in our knowledge and suggest future research priorities.
Depth-Related Changes in Community Structure of Culturable Mineral Weathering Bacteria and in Weathering Patterns Caused by Them along Two Contrasting Soil Profiles

PubMed Central

Huang, Jing; Xi, Jun; Huang, Zhi; Wang, Qi; Zhang, Zhen-Dong

2014-01-01

Bacteria play important roles in mineral weathering and soil formation. However, few reports of mineral weathering bacteria inhabiting subsurfaces of soil profiles have been published, raising the question of whether the subsurface weathering bacteria are fundamentally distinct from those in surface communities. To address this question, we isolated and characterized mineral weathering bacteria from two contrasting soil profiles with respect to their role in the weathering pattern evolution, their place in the community structure, and their depth-related changes in these two soil profiles. The effectiveness and pattern of bacterial mineral weathering were different in the two profiles and among the horizons within the respective profiles. The abundance of highly effective mineral weathering bacteria in the Changshu profile was significantly greater in the deepest horizon than in the upper horizons, whereas in the Yanting profile it was significantly greater in the upper horizons than in the deeper horizons. Most of the mineral weathering bacteria from the upper horizons of the Changshu profile and from the deeper horizons of the Yanting profile significantly acidified the culture media in the mineral weathering process. The proportion of siderophore-producing bacteria in the Changshu profile was similar in all horizons except in the Bg2 horizon, whereas the proportion of siderophore-producing bacteria in the Yanting profile was higher in the upper horizons than in the deeper horizons. Both profiles existed in different highly depth-specific culturable mineral weathering community structures. The depth-related changes in culturable weathering communities were primarily attributable to minor bacterial groups rather than to a change in the major population structure. PMID:24077700
Multiscaling properties of tropical rainfall: Analysis of rain gauge datasets in Lesser Antilles island environment

NASA Astrophysics Data System (ADS)

Bernard, Didier C.; Pasquier, Raphaël; Cécé, Raphaël; Dorville, Jean-François

2014-05-01

Changes in rainfall seem to be the main impact of climate change in the Caribbean area. The last conclusions of IPCC (2013), indicate that the end of this century will be marked by a rise of extreme rainfalls in tropical areas, linked with increase of the mean surface temperature. Moreover, most of the Lesser Antilles islands are characterized by a complex topography which tends to enhance the rainfall from synoptic disturbances by orographic effects. In the past five years, out of hurricanes passage, several extreme rainy events (approx. 16 mm in 6 minutes), including fatal cases, occurred in the Lesser Antilles Arc: in Guadeloupe (January 2011, May 2012 and 2013), in Martinique (May 2009, April 2011 and 2013), in Saint-Lucia (December 2013). These phenomena inducing floods, loss of life and material damages (agriculture sector and public infrastructures), inhibit the development of the islands. At this time, numerical weather prediction models as WRF, which are based on the equations of the atmospheric physics, do not show great results in the focused area (Bernard et al., 2013). Statistical methods may be used to examine explicitly local rainy updrafts, thermally and orographically induced at micro-scale. The main goal of the present insular tropical study is to characterize the multifractal symmetries occurring in the 6-min rainfall time series, registered since 2006 by the French Met. Office network weather stations. The universal multifractal model (Schertzer and Lovejoy, 1991) is used to define the statistical properties of measured rainfalls at meso-scale and micro-scale. This model is parametrized by a fundamental exponents set (H,a,C1,q) which are determined and compared with values found in the literature. The first three parameters characterize the mean pattern and the last parameter q, the extreme pattern. The occurrence ranges of multifractal regime are examined. The suggested links between the internal variability of the tropical rainy events and the multifractal properties found, are preliminary discussed. References Bernard, D., R. Cécé and J.-F. Dorville (2013). High resolution numerical simulation (WRF V3) of an extrem rainy event over the Guadeloupe archipelago: Case of 3-5 January 2011. EGU General Assembly 2013, Geophysical Research Abstracts, Vol. 15, EGU2013-9988, Vienna, April 2013. Schertzer, D., S. Lovejoy (1991). Nonlinear geodynamical variability: Multiple singularities, universality and observables. Scaling, fractals and non-linear variability in geophysics, D. Schertzer, S. Lovejoy eds.,41-82, Kluwer.
An Evaluation of Teleconnections Over the United States in an Ensemble of AMIP Simulations with the MERRA-2 Configuration of the GEOS Atmospheric Model

NASA Technical Reports Server (NTRS)

Collow, Allison B. Marquardt; Mahanama, Sarith P.; Bosilovich, Michael G.; Koster, Randal D.; Schubert, Siegfried D.

2017-01-01

The atmospheric general circulation model that is used in NASA's Modern Era Retrospective Analysis for Research and Applications Version 2 (MERRA-2) is evaluated with respect to the relationship between large-scale teleconnection patterns and daily temperature and precipitation over the United States (US) using a ten-member ensemble of simulations, referred to as M2AMIP. A focus is placed on four teleconnection patterns that are known to influence weather and climate in the US: El Nino Southern Oscillation, the Pacific Decadal Oscillation, the North Atlantic Oscillation, and the Pacific-North American Pattern. The monthly and seasonal indices associated with the patterns are correlated with daily temperature and precipitation statistics including: (i) monthly mean 2 m temperature and precipitation, (ii) the frequency of extreme temperature events at the 90th, 95th, and 99th percentiles, and (iii) the frequency and intensity of extreme precipitation events classified at the 90th, 95th, and 99th percentiles.Correlations obtained with M2AMIP data and thus the strength of teleconnections in the free-running model are evaluated through comparison against corresponding correlations computed from observations and from MERRA-2. Overall, the strongest teleconnections in all datasets occur during the winter and coincide with the largest agreement between the observations, MERRA-2, and M2AMIP. When M2AMIP does capture the correlation seen in observations, there is a tendency for the spatial extent to be exaggerated. The weakest agreement between the data sources, for all teleconnection patterns, is in the correlation with extreme precipitation; however there are discrepancies between the datasets in the number of days with at least 1 mm of precipitation: M2AMIP has too few days with precipitation in the Northwest and the Northern Great Plains and too many days in the Northeast. In JJA, M2AMIP has too few days with precipitation in the western two-thirds of the country and too many days with precipitation along the east coast.
Future projections of extreme precipitation using Advanced Weather Generator (AWE-GEN) over Peninsular Malaysia

NASA Astrophysics Data System (ADS)

Syafrina, A. H.; Zalina, M. D.; Juneng, L.

2014-09-01

A stochastic downscaling methodology known as the Advanced Weather Generator, AWE-GEN, has been tested at four stations in Peninsular Malaysia using observations available from 1975 to 2005. The methodology involves a stochastic downscaling procedure based on a Bayesian approach. Climate statistics from a multi-model ensemble of General Circulation Model (GCM) outputs were calculated and factors of change were derived to produce the probability distribution functions (PDF). New parameters were obtained to project future climate time series. A multi-model ensemble was used in this study. The projections of extreme precipitation were based on the RCP 6.0 scenario (2081-2100). The model was able to simulate both hourly and 24-h extreme precipitation, as well as wet spell durations quite well for almost all regions. However, the performance of GCM models varies significantly in all regions showing high variability of monthly precipitation for both observed and future periods. The extreme precipitation for both hourly and 24-h seems to increase in future, while extreme of wet spells remain unchanged, up to the return periods of 10-40 years.
Extreme rainfall, vulnerability and risk: a continental-scale assessment for South America.

PubMed

Vörösmarty, Charles J; Bravo de Guenni, Lelys; Wollheim, Wilfred M; Pellerin, Brian; Bjerklie, David; Cardoso, Manoel; D'Almeida, Cassiano; Green, Pamela; Colon, Lilybeth

2013-11-13

Extreme weather continues to preoccupy society as a formidable public safety concern bearing huge economic costs. While attention has focused on global climate change and how it could intensify key elements of the water cycle such as precipitation and river discharge, it is the conjunction of geophysical and socioeconomic forces that shapes human sensitivity and risks to weather extremes. We demonstrate here the use of high-resolution geophysical and population datasets together with documentary reports of rainfall-induced damage across South America over a multi-decadal, retrospective time domain (1960-2000). We define and map extreme precipitation hazard, exposure, affectedpopulations, vulnerability and risk, and use these variables to analyse the impact of floods as a water security issue. Geospatial experiments uncover major sources of risk from natural climate variability and population growth, with change in climate extremes bearing a minor role. While rural populations display greatest relative sensitivity to extreme rainfall, urban settings show the highest rates of increasing risk. In the coming decades, rapid urbanization will make South American cities the focal point of future climate threats but also an opportunity for reducing vulnerability, protecting lives and sustaining economic development through both traditional and ecosystem-based disaster risk management systems.
Weathering Patterns of Forensic Biomarker Compounds and PAHs in Coastal Marsh Sediment Samples since the 2010 Deepwater Horizon Oil Spill

NASA Astrophysics Data System (ADS)

Overton, E. B.; Meyer, B.; Miles, S.; Olson, G.; Adhikari, P. L.

2016-02-01

It has been well established that the composition of oil, when spilled into the marine environment, undergoes substantial changes caused by weathering. The general sequence of this compositional change begins with straight chain alkanes (the fastest to degrade), followed by low molecular weight branched and cyclic alkanes and, finally the aromatics. Most resistant to weathering are the higher molecular weight cyclic and branched alkanes (i.e., the "forensic biomarker compounds" such as the hopanes and steranes) and tri-aromatic ringed steroids. The composition of these biomarker compounds is particularly resistant to change because they are not affected by evaporative weathering, are not water soluble, and are not readily degraded by microbial and/or photo-oxidation. However, after extensive time in the environment, being subjected to numerous weathering factors, biomarker compositional patterns are beginning to exhibit significant changes. This presentation will describe the general weathering patterns of petroleum residues in sediment samples collected from marsh areas of coastal Louisiana over a five year period. Particular attention will focus on compositional changes that have been observed in the steranes and diasteranes compounds that traditionally have been considered the most resistant to compositional changes due to weathering.
New York Urban Hydro-Meteorological Testbed (NY-uHMT)

NASA Astrophysics Data System (ADS)

Norouzi, H.; Bah, A.

2017-12-01

It is well known that heat waves kill more persons, on average, than any other extreme weather event in the United States. New York City experiences much adversity due to inclement weather. Exploring climate variation in New Yorker City will help scientists and local government to detect and forecast extreme weather hazards and gather more localized temperature data within the five boroughs. Ground based weather stations are widely used to provide real time data to the public to prevent disasters. The New York urban Hydro-meteorological Testbed (NY-uHMT) is a hydro meteorological network that is used to investigate climate change in the New York City area. It is composed of twenty autonomous weather stations that will gather information on air temperature, relative humidity, rainfall and soil moisture properties around the densely populated NYC area. For each station, the data is stored on a Campbell Scientific CR200x data logger and can be accessed remotely using the LoggerNet software, or by direct connection using an RS-232 cable. Real-time weather data is acquired every fifteen minutes. The data is then periodically sampled and graphed through MATLAB code to be broadcasted on the uHMT website and is available at no charge to the public. We anticipate the results will show that the temperature, humidity, precipitation and soil moisture will vary from location to location depending on the magnitude of urbanization to the area.
A framework for standardized calculation of weather indices in Germany

NASA Astrophysics Data System (ADS)

Möller, Markus; Doms, Juliane; Gerstmann, Henning; Feike, Til

2018-05-01

Climate change has been recognized as a main driver in the increasing occurrence of extreme weather. Weather indices (WIs) are used to assess extreme weather conditions regarding its impact on crop yields. Designing WIs is challenging, since complex and dynamic crop-climate relationships have to be considered. As a consequence, geodata for WI calculations have to represent both the spatio-temporal dynamic of crop development and corresponding weather conditions. In this study, we introduce a WI design framework for Germany, which is based on public and open raster data of long-term spatio-temporal availability. The operational process chain enables the dynamic and automatic definition of relevant phenological phases for the main cultivated crops in Germany. Within the temporal bounds, WIs can be calculated for any year and test site in Germany in a reproducible and transparent manner. The workflow is demonstrated on the example of a simple cumulative rainfall index for the phenological phase shooting of winter wheat using 16 test sites and the period between 1994 and 2014. Compared to station-based approaches, the major advantage of our approach is the possibility to design spatial WIs based on raster data characterized by accuracy metrics. Raster data and WIs, which fulfill data quality standards, can contribute to an increased acceptance and farmers' trust in WI products for crop yield modeling or weather index-based insurances (WIIs).
A synoptic climatology for forest fires in the NE US and future implications for GCM simulations

Treesearch

Yan Qing; Ronald Sabo; Yiqiang Wu; J.Y. Zhu

1994-01-01

We studied surface-pressure patterns corresponding to reduced precipitation, high evaporation potential, and enhanced forest-fire danger for West Virginia, which experienced extensive forest-fire damage in November 1987. From five years of daily weather maps we identified eight weather patterns that describe distinctive flow situations throughout the year. Map patterns...
Global predictability of temperature extremes

NASA Astrophysics Data System (ADS)

Coughlan de Perez, Erin; van Aalst, Maarten; Bischiniotis, Konstantinos; Mason, Simon; Nissan, Hannah; Pappenberger, Florian; Stephens, Elisabeth; Zsoter, Ervin; van den Hurk, Bart

2018-05-01

Extreme temperatures are one of the leading causes of death and disease in both developed and developing countries, and heat extremes are projected to rise in many regions. To reduce risk, heatwave plans and cold weather plans have been effectively implemented around the world. However, much of the world’s population is not yet protected by such systems, including many data-scarce but also highly vulnerable regions. In this study, we assess at a global level where such systems have the potential to be effective at reducing risk from temperature extremes, characterizing (1) long-term average occurrence of heatwaves and coldwaves, (2) seasonality of these extremes, and (3) short-term predictability of these extreme events three to ten days in advance. Using both the NOAA and ECMWF weather forecast models, we develop global maps indicating a first approximation of the locations that are likely to benefit from the development of seasonal preparedness plans and/or short-term early warning systems for extreme temperature. The extratropics generally show both short-term skill as well as strong seasonality; in the tropics, most locations do also demonstrate one or both. In fact, almost 5 billion people live in regions that have seasonality and predictability of heatwaves and/or coldwaves. Climate adaptation investments in these regions can take advantage of seasonality and predictability to reduce risks to vulnerable populations.
Fat, weather, and date affect migratory songbirds' departure decisions, routes, and time it takes to cross the Gulf of Mexico.

PubMed

Deppe, Jill L; Ward, Michael P; Bolus, Rachel T; Diehl, Robert H; Celis-Murillo, Antonio; Zenzal, Theodore J; Moore, Frank R; Benson, Thomas J; Smolinsky, Jaclyn A; Schofield, Lynn N; Enstrom, David A; Paxton, Eben H; Bohrer, Gil; Beveroth, Tara A; Raim, Arlo; Obringer, Renee L; Delaney, David; Cochran, William W

2015-11-17

Approximately two thirds of migratory songbirds in eastern North America negotiate the Gulf of Mexico (GOM), where inclement weather coupled with no refueling or resting opportunities can be lethal. However, decisions made when navigating such features and their consequences remain largely unknown due to technological limitations of tracking small animals over large areas. We used automated radio telemetry to track three songbird species (Red-eyed Vireo, Swainson's Thrush, Wood Thrush) from coastal Alabama to the northern Yucatan Peninsula (YP) during fall migration. Detecting songbirds after crossing ∼1,000 km of open water allowed us to examine intrinsic (age, wing length, fat) and extrinsic (weather, date) variables shaping departure decisions, arrival at the YP, and crossing times. Large fat reserves and low humidity, indicative of beneficial synoptic weather patterns, favored southward departure across the Gulf. Individuals detected in the YP departed with large fat reserves and later in the fall with profitable winds, and flight durations (mean = 22.4 h) were positively related to wind profit. Age was not related to departure behavior, arrival, or travel time. However, vireos negotiated the GOM differently than thrushes, including different departure decisions, lower probability of detection in the YP, and longer crossing times. Defense of winter territories by thrushes but not vireos and species-specific foraging habits may explain the divergent migratory behaviors. Fat reserves appear extremely important to departure decisions and arrival in the YP. As habitat along the GOM is degraded, birds may be limited in their ability to acquire fat to cross the Gulf.
Fat, weather, and date affect migratory songbirds’ departure decisions, routes, and time it takes to cross the Gulf of Mexico

USGS Publications Warehouse

Deppe, Jill L.; Ward, Michael P.; Bolus, Rachel T.; Diehl, Robert H.; Celis-Murillo, A.; Zenzal, Theodore J.; Moore, Frank R.; Benson, Thomas J.; Smolinsky, Jaclyn A.; Schofield, Lynn N.; Enstrom, David A.; Paxton, Eben H.; Bohrer, Gil; Beveroth, Tara A.; Raim, Arlo; Obringer, Renee L.; Delaney, David; Cochran, William W.

2015-01-01

Approximately two thirds of migratory songbirds in eastern North America negotiate the Gulf of Mexico (GOM), where inclement weather coupled with no refueling or resting opportunities can be lethal. However, decisions made when navigating such features and their consequences remain largely unknown due to technological limitations of tracking small animals over large areas. We used automated radio telemetry to track three songbird species (Red-eyed Vireo, Swainson’s Thrush, Wood Thrush) from coastal Alabama to the northern Yucatan Peninsula (YP) during fall migration. Detecting songbirds after crossing ∼1,000 km of open water allowed us to examine intrinsic (age, wing length, fat) and extrinsic (weather, date) variables shaping departure decisions, arrival at the YP, and crossing times. Large fat reserves and low humidity, indicative of beneficial synoptic weather patterns, favored southward departure across the Gulf. Individuals detected in the YP departed with large fat reserves and later in the fall with profitable winds, and flight durations (mean = 22.4 h) were positively related to wind profit. Age was not related to departure behavior, arrival, or travel time. However, vireos negotiated the GOM differently than thrushes, including different departure decisions, lower probability of detection in the YP, and longer crossing times. Defense of winter territories by thrushes but not vireos and species-specific foraging habits may explain the divergent migratory behaviors. Fat reserves appear extremely important to departure decisions and arrival in the YP. As habitat along the GOM is degraded, birds may be limited in their ability to acquire fat to cross the Gulf.
Post-fire vegetation and fuel development influences fire severity patterns in reburns.

PubMed

Coppoletta, Michelle; Merriam, Kyle E; Collins, Brandon M

2016-04-01

In areas where fire regimes and forest structure have been dramatically altered, there is increasing concern that contemporary fires have the potential to set forests on a positive feedback trajectory with successive reburns, one in which extensive stand-replacing fire could promote more stand-replacing fire. Our study utilized an extensive set of field plots established following four fires that occurred between 2000 and 2010 in the northern Sierra Nevada, California, USA that were subsequently reburned in 2012. The information obtained from these field plots allowed for a unique set of analyses investigating the effect of vegetation, fuels, topography, fire weather, and forest management on reburn severity. We also examined the influence of initial fire severity and time since initial fire on influential predictors of reburn severity. Our results suggest that high- to moderate-severity fire in the initial fires led to an increase in standing snags and shrub vegetation, which in combination with severe fire weather promoted high-severity fire effects in the subsequent reburn. Although fire behavior is largely driven by weather, our study demonstrates that post-fire vegetation composition and structure are also important drivers of reburn severity. In the face of changing climatic regimes and increases in extreme fire weather, these results may provide managers with options to create more fire-resilient ecosystems. In areas where frequent high-severity fire is undesirable, management activities such as thinning, prescribed fire, or managed wildland fire can be used to moderate fire behavior not only prior to initial fires, but also before subsequent reburns.
Fat, weather, and date affect migratory songbirds’ departure decisions, routes, and time it takes to cross the Gulf of Mexico

PubMed Central

Deppe, Jill L.; Ward, Michael P.; Bolus, Rachel T.; Diehl, Robert H.; Celis-Murillo, Antonio; Zenzal, Theodore J.; Moore, Frank R.; Benson, Thomas J.; Smolinsky, Jaclyn A.; Schofield, Lynn N.; Enstrom, David A.; Paxton, Eben H.; Bohrer, Gil; Beveroth, Tara A.; Raim, Arlo; Obringer, Renee L.; Delaney, David; Cochran, William W.

2015-01-01

Approximately two thirds of migratory songbirds in eastern North America negotiate the Gulf of Mexico (GOM), where inclement weather coupled with no refueling or resting opportunities can be lethal. However, decisions made when navigating such features and their consequences remain largely unknown due to technological limitations of tracking small animals over large areas. We used automated radio telemetry to track three songbird species (Red-eyed Vireo, Swainson’s Thrush, Wood Thrush) from coastal Alabama to the northern Yucatan Peninsula (YP) during fall migration. Detecting songbirds after crossing ∼1,000 km of open water allowed us to examine intrinsic (age, wing length, fat) and extrinsic (weather, date) variables shaping departure decisions, arrival at the YP, and crossing times. Large fat reserves and low humidity, indicative of beneficial synoptic weather patterns, favored southward departure across the Gulf. Individuals detected in the YP departed with large fat reserves and later in the fall with profitable winds, and flight durations (mean = 22.4 h) were positively related to wind profit. Age was not related to departure behavior, arrival, or travel time. However, vireos negotiated the GOM differently than thrushes, including different departure decisions, lower probability of detection in the YP, and longer crossing times. Defense of winter territories by thrushes but not vireos and species-specific foraging habits may explain the divergent migratory behaviors. Fat reserves appear extremely important to departure decisions and arrival in the YP. As habitat along the GOM is degraded, birds may be limited in their ability to acquire fat to cross the Gulf. PMID:26578793

Influence of climate change on productivity of American White Pelicans, Pelecanus erythrorhynchos

USGS Publications Warehouse

Sovada, Marsha A.; Igl, Lawrence D.; Pietz, Pamela J.; Bartos, Alisa J.

2014-01-01

In the past decade, severe weather and West Nile virus were major causes of chick mortality at American white pelican (Pelecanus erythrorhynchos) colonies in the northern plains of North America. At one of these colonies, Chase Lake National Wildlife Refuge in North Dakota, spring arrival by pelicans has advanced approximately 16 days over a period of 44 years (1965–2008). We examined phenology patterns of pelicans and timing of inclement weather through the 44-year period, and evaluated the consequence of earlier breeding relative to weather-related chick mortality. We found severe weather patterns to be random through time, rather than concurrently shifting with the advanced arrival of pelicans. In recent years, if nest initiations had followed the phenology patterns of 1965 (i.e., nesting initiated 16 days later), fewer chicks likely would have died from weather-related causes. That is, there would be fewer chicks exposed to severe weather during a vulnerable transition period that occurs between the stage when chicks are being brooded by adults and the stage when chicks from multiple nests become part of a thermally protective crèche.
Evaluation of the National Weather Service Extreme Cold Warning Experiment in North Dakota

PubMed Central

Chiu, Cindy H.; Vagi, Sara J.; Wolkin, Amy F.; Martin, John Paul; Noe, Rebecca S.

2016-01-01

Dangerously cold weather threatens life and property. During periods of extreme cold due to wind chill, the National Weather Service (NWS) issues wind chill warnings to prompt the public to take action to mitigate risks. Wind chill warnings are based on ambient temperatures and wind speeds. Since 2010, NWS has piloted a new extreme cold warning issued for cold temperatures in wind and nonwind conditions. The North Dakota Department of Health, NWS, and the Centers for Disease Control and Prevention collaborated in conducting household surveys in Burleigh County, North Dakota, to evaluate this new warning. The objectives of the evaluation were to assess whether residents heard the new warning and to determine if protective behaviors were prompted by the warning. This was a cross-sectional survey design using the Community Assessment for Public Health Emergency Response (CASPER) methodology to select a statistically representative sample of households from Burleigh County. From 10 to 11 April 2012, 188 door-to-door household interviews were completed. The CASPER methodology uses probability sampling with weighted analysis to estimate the number and percentage of households with a specific response within Burleigh County. The majority of households reported having heard both the extreme cold and wind chill warnings, and both warnings prompted protective behaviors. These results suggest this community heard the new warning and took protective actions after hearing the warning. PMID:27239260
Satellite-Enhanced Dynamical Downscaling of Extreme Events

NASA Astrophysics Data System (ADS)

Nunes, A.

2015-12-01

Severe weather events can be the triggers of environmental disasters in regions particularly susceptible to changes in hydrometeorological conditions. In that regard, the reconstruction of past extreme weather events can help in the assessment of vulnerability and risk mitigation actions. Using novel modeling approaches, dynamical downscaling of long-term integrations from global circulation models can be useful for risk analysis, providing more accurate climate information at regional scales. Originally developed at the National Centers for Environmental Prediction (NCEP), the Regional Spectral Model (RSM) is being used in the dynamical downscaling of global reanalysis, within the South American Hydroclimate Reconstruction Project. Here, RSM combines scale-selective bias correction with assimilation of satellite-based precipitation estimates to downscale extreme weather occurrences. Scale-selective bias correction is a method employed in the downscaling, similar to the spectral nudging technique, in which the downscaled solution develops in agreement with its coarse boundaries. Precipitation assimilation acts on modeled deep-convection, drives the land-surface variables, and therefore the hydrological cycle. During the downscaling of extreme events that took place in Brazil in recent years, RSM continuously assimilated NCEP Climate Prediction Center morphing technique precipitation rates. As a result, RSM performed better than its global (reanalysis) forcing, showing more consistent hydrometeorological fields compared with more sophisticated global reanalyses. Ultimately, RSM analyses might provide better-quality initial conditions for high-resolution numerical predictions in metropolitan areas, leading to more reliable short-term forecasting of severe local storms.
Communicating Climate Change in the Agricultural Sector: Insights from Surveys and Interviews with Agricultural Advisors in the Midwestern United States

NASA Astrophysics Data System (ADS)

Prokopy, L. S.; Carlton, S.; Dunn, M.

2014-12-01

Understanding U.S. agricultural stakeholder views about the existence of climate change and what influences these views is central to developing communication in support of adaptation and mitigation. It has been postulated in the literature that extreme weather events can shape people's climate change beliefs and adaptation attitudes. In this presentation, we use data from pre- and post-extreme event surveys and interviews to examine the effects of the 2012 Midwestern US drought on agricultural advisors' climate change beliefs, adaptation attitudes, and risk perceptions. We found that neither climate change beliefs nor attitudes toward adaptation changed significantly as a result of the drought. Risk perceptions did change, however, with advisors becoming more concerned about risks from drought and pests and less concerned about risks related to flooding and ponding. Qualitative interviews revealed that while advisors readily accept the occurrence of extreme weather as a risk, the irregularity and unpredictability of extreme events for specific localities limits day-to-day consideration in respect to prescribed management advice. Instead, advisors' attention is directed towards planning for short-term changes encompassing weather, pests, and the market, as well as planning for long-term trends related to water availability. These findings provide important insights for communicating climate change in this critical sector while illustrating the importance of social science research in planning and executing communication campaigns.
Characterization of genetic diversity of high temperature tolerance in sorghum

USDA-ARS?s Scientific Manuscript database

As global warming becomes inevitable, the sustainability of agricultural production in US and worldwide faces serious threat from extreme weather conditions, such as drought and elevated extreme temperatures (heat waves). Among cereal crops, sorghum is considered a versatile crop for semiarid area a...
Climate change impacts on extreme events in the United States: an uncertainty analysis

EPA Science Inventory

Extreme weather and climate events, such as heat waves, droughts and severe precipitation events, have substantial impacts on ecosystems and the economy. However, future climate simulations display large uncertainty in mean changes. As a result, the uncertainty in future changes ...
Integrated modeling for assessment of energy-water system resilience under changing climate

NASA Astrophysics Data System (ADS)

Yan, E.; Veselka, T.; Zhou, Z.; Koritarov, V.; Mahalik, M.; Qiu, F.; Mahat, V.; Betrie, G.; Clark, C.

2016-12-01

Energy and water systems are intrinsically interconnected. Due to an increase in climate variability and extreme weather events, interdependency between these two systems has been recently intensified resulting significant impacts on both systems and energy output. To address this challenge, an Integrated Water-Energy Systems Assessment Framework (IWESAF) is being developed to integrate multiple existing or developed models from various sectors. The IWESAF currently includes an extreme climate event generator to predict future extreme weather events, hydrologic and reservoir models, riverine temperature model, power plant water use simulator, and power grid operation and cost optimization model. The IWESAF can facilitate the interaction among the modeling systems and provide insights of the sustainability and resilience of the energy-water system under extreme climate events and economic consequence. The regional case demonstration in the Midwest region will be presented. The detailed information on some of individual modeling components will also be presented in several other abstracts submitted to AGU this year.
Validation of two (parametric vs non-parametric) daily weather generators

NASA Astrophysics Data System (ADS)

Dubrovsky, M.; Skalak, P.

2015-12-01

As the climate models (GCMs and RCMs) fail to satisfactorily reproduce the real-world surface weather regime, various statistical methods are applied to downscale GCM/RCM outputs into site-specific weather series. The stochastic weather generators are among the most favourite downscaling methods capable to produce realistic (observed-like) meteorological inputs for agrological, hydrological and other impact models used in assessing sensitivity of various ecosystems to climate change/variability. To name their advantages, the generators may (i) produce arbitrarily long multi-variate synthetic weather series representing both present and changed climates (in the latter case, the generators are commonly modified by GCM/RCM-based climate change scenarios), (ii) be run in various time steps and for multiple weather variables (the generators reproduce the correlations among variables), (iii) be interpolated (and run also for sites where no weather data are available to calibrate the generator). This contribution will compare two stochastic daily weather generators in terms of their ability to reproduce various features of the daily weather series. M&Rfi is a parametric generator: Markov chain model is used to model precipitation occurrence, precipitation amount is modelled by the Gamma distribution, and the 1st order autoregressive model is used to generate non-precipitation surface weather variables. The non-parametric GoMeZ generator is based on the nearest neighbours resampling technique making no assumption on the distribution of the variables being generated. Various settings of both weather generators will be assumed in the present validation tests. The generators will be validated in terms of (a) extreme temperature and precipitation characteristics (annual and 30-years extremes and maxima of duration of hot/cold/dry/wet spells); (b) selected validation statistics developed within the frame of VALUE project. The tests will be based on observational weather series from several European stations available from the ECA&D database. Acknowledgements: The weather generator is developed and validated within the frame of projects WG4VALUE (sponsored by the Ministry of Education, Youth and Sports of CR), and VALUE (COST ES 1102 action).
Power System Operations With Water Constraints

NASA Astrophysics Data System (ADS)

Qiu, F.; Wang, J.

2015-12-01

The interdependency between water and energy, although known for many decades, has not received enough attention until recent events under extreme weather conditions (especially droughts). On one hand, water and several types of energy supplies have become increasingly scarce; the demand on water and energy continues to grow. On the other hand, the climate change has become more and more disruptive (i.e., intensity and frequency of extreme events), causing severe challenges to both systems simultaneously. Water and energy systems have become deeply coupled and challenges from extreme weather events must be addressed in a coordinated way across the two systems.In this work, we will build quantitative models to capture the interactions between water and energy systems. We will incorporate water constraints in power system operations and study the impact of water scarcity on power system resilience.
On the relationship between atmospheric rivers, weather types and floods in Galicia (NW Spain)

NASA Astrophysics Data System (ADS)

Eiras-Barca, Jorge; Lorenzo, Nieves; Taboada, Juan; Robles, Alba; Miguez-Macho, Gonzalo

2018-06-01

Atmospheric rivers (ARs) - long and narrow structures of anomalously high water vapor flux located in the warm sector of extratropical cyclones - have been shown to be closely related to extreme precipitation and flooding. In this paper we analyze the connection between ARs and flooding in the northwestern Spanish region of Galicia under a variety of synoptic conditions represented by the so-called weather types, a classification of daily sea-level pressure patterns obtained by means of a simple scheme that adopts the subjective procedure of Lamb. Flood events are identified from official reports conducted by the Spanish emergency management agency (Protección Civil) from 1979 to 2010. Our results suggest that, although most flood events in Galicia do not coincide with the presence of an overhead AR, ARs are present in the majority of severe cases, particularly in coastal areas. Flood events associated with ARs are connected to cyclonic weather types with westerly and southwesterly flows, which occur mostly in winter months. The link between ARs and severe flooding is not very apparent in inland areas or during summer months, in which case heavy precipitation is usually not frontal in nature but rather convective. Nevertheless, our results show that, in general, the amount of precipitation in flood events in Galicia more than doubles when an AR is present.
A Model of the Temporal Variability of Optical Light from Extrasolar Terrestrial Planets

NASA Astrophysics Data System (ADS)

Ford, E. B.; Seager, S.; Turner, E. L.

2001-05-01

New observatories such as TPF (NASA) and Darwin (ESA) are being designed to detect light directly from terrestrial-mass planets. Such observations will provide new data to constrain theories of planet formation and may identify the possible presence of liquid water and even spectroscopic signatures suggestive of life. We model the light scattered by Earth-like planets focusing on temporal variability due to planetary rotation and weather. Since a majority of the scattered light comes from only a small fraction of the planet's surface, significant variations in brightness are possible. The variations can be as large as a factor of two for a cloud-free planet which has a range of albedos similar to those of the different surfaces found on Earth. If a significant fraction of the observed light is scattered by the planet's atmosphere, including clouds, then the amplitude of variations due to surface features will be diluted. Atmospheric variability (e.g. clouds) itself is extremely interesting because it provides evidence for weather. The planet's rotation period, fractional ice and cloud cover, gross distribution of land and water on the surface, large scale weather patterns, large regions of unusual reflectivity or color (such as major desserts or vegetation's "red edge") as well as the geometry of its spin, orbit, and illumination relative to the observer all have substantial effects on the planet's rotational light curve.
The spatial domain of wildfire risk and response in the wildland urban interface in Sydney, Australia

NASA Astrophysics Data System (ADS)

Price, O. F.; Bradstock, R. A.

2013-12-01

In order to quantify the risks from fire at the wildland urban interface (WUI), it is important to understand where fires occur and their likelihood of spreading to the WUI. For each of the 999 fires in the Sydney region we calculated the distance between the ignition and the WUI, the fire's weather and wind direction and whether it spread to the WUI. The likelihood of burning the WUI was analysed using binomial regression. Weather and distance interacted such that under mild weather conditions, the model predicted only a 5% chance that a fire starting >2.5 km from the interface would reach it, whereas when the conditions are extreme the predicted chance remained above 30% even at distances >10 km. Fires were more likely to spread to the WUI if the wind was from the west and in the western side of the region. We examined whether the management responses to wildfires are commensurate with risk by comparing the distribution of distance to the WUI of wildfires with roads and prescribed fires. Prescribed fires and roads were concentrated nearer to the WUI than wildfires as a whole, but further away than wildfires that burnt the WUI under extreme weather conditions (high risk fires). Overall, 79% of these high risk fires started within 2 km of the WUI, so there is some argument for concentrating more management effort near the WUI. By substituting climate change scenario weather into the statistical model, we predicted a small increase in the risk of fires spreading to the WUI, but the increase will be greater under extreme weather. This approach has a variety of uses, including mapping fire risk and improving the ability to match fire management responses to the threat from each fire. They also provide a baseline from which a cost-benefit analysis of complementary fire management strategies can be conducted.
The spatial domain of wildfire risk and response in the Wildland Urban Interface in Sydney, Australia

NASA Astrophysics Data System (ADS)

Price, O. F.; Bradstock, R. A.

2013-09-01

In order to quantify the risks from fire at the Wildland Urban Interface (WUI), it is important to understand where fires occur and their likelihood of spreading to the WUI. For each of 999 fires in the Sydney region we calculated the distance between the ignition and the WUI, the fire weather and wind direction and whether it spread to the WUI. The likelihood of burning the WUI was analysed using binomial regression. Weather and distance interacted such that under mild weather conditions, the model predicted only a 5% chance that a fire starting more than 2.5 km from the interface would reach it, whereas when the conditions are extreme the predicted chance remained above 30% even at distances further than 10 km. Fires were more likely to spread to the WUI if the wind was from the west and in the western side of the region. We examined whether the management responses to wildfires are commensurate with risk by comparing the distribution of distance to the WUI of wildfires with roads and prescribed fires. Prescribed fires and roads were concentrated nearer to the WUI than wildfires as a whole, but further away than wildfires that burnt the WUI under extreme weather conditions (high risk fires). 79% of these high risk fires started within 2 km of the WUI, so there is some argument for concentrating more management effort near the WUI. By substituting climate change scenario weather into the statistical model, we predicted a small increase in the risk of fires spreading to the WUI, but the increase will be greater under extreme weather. This approach has a variety of uses, including mapping fire risk and improving the ability to match fire management responses to the threat from each fire. They also provide a baseline from which a cost-benefit analysis of complementary fire management strategies can be conducted.
Coupled hydro-meteorological modelling on a HPC platform for high-resolution extreme weather impact study

NASA Astrophysics Data System (ADS)

Zhu, Dehua; Echendu, Shirley; Xuan, Yunqing; Webster, Mike; Cluckie, Ian

2016-11-01

Impact-focused studies of extreme weather require coupling of accurate simulations of weather and climate systems and impact-measuring hydrological models which themselves demand larger computer resources. In this paper, we present a preliminary analysis of a high-performance computing (HPC)-based hydrological modelling approach, which is aimed at utilizing and maximizing HPC power resources, to support the study on extreme weather impact due to climate change. Here, four case studies are presented through implementation on the HPC Wales platform of the UK mesoscale meteorological Unified Model (UM) with high-resolution simulation suite UKV, alongside a Linux-based hydrological model, Hydrological Predictions for the Environment (HYPE). The results of this study suggest that the coupled hydro-meteorological model was still able to capture the major flood peaks, compared with the conventional gauge- or radar-driving forecast, but with the added value of much extended forecast lead time. The high-resolution rainfall estimation produced by the UKV performs similarly to that of radar rainfall products in the first 2-3 days of tested flood events, but the uncertainties particularly increased as the forecast horizon goes beyond 3 days. This study takes a step forward to identify how the online mode approach can be used, where both numerical weather prediction and the hydrological model are executed, either simultaneously or on the same hardware infrastructures, so that more effective interaction and communication can be achieved and maintained between the models. But the concluding comments are that running the entire system on a reasonably powerful HPC platform does not yet allow for real-time simulations, even without the most complex and demanding data simulation part.
Investigating the impact of atmospheric blocking on temperature extremes across Europe using an objective index

NASA Astrophysics Data System (ADS)

Brunner, Lukas; Steiner, Andrea; Sillmann, Jana

2017-04-01

Atmospheric blocking is a key contributor to European temperature extremes. It leads to stable, long-lasting weather patterns, which favor the development of cold and warm spells. The link between blocking and such temperature extremes differs significantly across Europe. In northern Europe a majority of warm spells are connected to blocking, while cold spells are suppressed during blocked conditions. In southern Europe the opposite picture arises with most cold spells occurring during blocking and warm spells suppressed. Building on earlier work by Brunner et al. (2017) this study aims at a better understanding of the connection between blocking and temperature extremes in Europe. We investigate cold and warm spells with and without blocking in observations from the European daily high-resolution gridded dataset (E-OBS) from 1979 to 2015. We use an objective extreme index (Russo et al. 2015) to identify and compare cold and warm spells across Europe. Our work is lead by the main question: Are cold/warm spells coinciding with blocking different from cold/warm spells during unblocked conditions in regard to duration, extend, or amplitude? Here we present our research question and the study setup, and show first results of our analysis on European temperature extremes. Brunner, L., G. Hegerl, and A. Steiner (2017): Connecting Atmospheric Blocking to European Temperature Extremes in Spring. J. Climate, 30, 585-594, doi: 10.1175/JCLI-D-16-0518.1. Russo, S., J. Sillmann, and E. M. Fischer (2015): Top ten European heatwaves since 1950 and their occurrence in the coming decades. Environ. Res. Lett. 10.12, S. 124003. doi: 10.1088/1748-9326/10/12/124003.
Norway and Cuba Continue Collaborating to Build Capacity to Improve Weather Forecasting

NASA Astrophysics Data System (ADS)

Antuña, Juan Carlos; Kalnay, Eugenia; Mesquita, Michel D. S.

2014-06-01

The Future of Climate Extremes in the Caribbean Extreme Cuban Climate (XCUBE) project, which is funded by the Norwegian Directorate for Civil Protection as part of an assignment for the Norwegian Ministry of Foreign Affairs to support scientific cooperation between Norway and Cuba, carried out a training workshop on seasonal forecasting, reanalysis data, and weather research and forecasting (WRF). The workshop was a follow-up to the XCUBE workshop conducted in Havana in 2013 and provided Cuban scientists with access to expertise on seasonal forecasting, the WRF model developed by the National Center for Atmospheric Research (NCAR) and the community, data assimilation, and reanalysis.
Climate change and natural disasters – integrating science and practice to protect health

PubMed Central

Sauerborn, Rainer; Ebi, Kristie

2012-01-01

Background Hydro-meteorological disasters are the focus of this paper. The authors examine, to which extent climate change increases their frequency and intensity. Methods Review of IPCC-projections of climate-change related extreme weather events and related literature on health effects. Results Projections show that climate change is likely to increase the frequency, intensity, duration, and spatial distribution of a range of extreme weather events over coming decades. Conclusions There is a need for strengthened collaboration between climate scientists, the health researchers and policy-makers as well as the disaster community to jointly develop adaptation strategies to protect human. PMID:23273248
Mitigating Climate Change with Earth Orbital Sunshades

NASA Technical Reports Server (NTRS)

Coverstone, Victoria; Johnson, Les

2015-01-01

An array of rotating sunshades based on emerging solar sail technology will be deployed in a novel Earth orbit to provide near-continuous partial shading of the Earth, reducing the heat input to the atmosphere by blocking a small percentage of the incoming sunlight, and mitigating local weather effects of anticipated climate change over the next century. The technology will provide local cooling relief during extreme heat events (and heating relief during extreme cold events) thereby saving human lives, agriculture, livestock, water and energy needs. A synthesis of the solar sail design, the sails' operational modes, and the selected orbit combine to provide local weather modification.
Reduced CO2 fertilization effect in temperate C3 grasslands under more extreme weather conditions

NASA Astrophysics Data System (ADS)

Obermeier, W. A.; Lehnert, L. W.; Kammann, C. I.; Müller, C.; Grünhage, L.; Luterbacher, J.; Erbs, M.; Moser, G.; Seibert, R.; Yuan, N.; Bendix, J.

2017-02-01

The increase in atmospheric greenhouse gas concentrations from anthropogenic activities is the major driver of recent global climate change. The stimulation of plant photosynthesis due to rising atmospheric carbon dioxide concentrations ([CO2]) is widely assumed to increase the net primary productivity (NPP) of C3 plants--the CO2 fertilization effect (CFE). However, the magnitude and persistence of the CFE under future climates, including more frequent weather extremes, are controversial. Here we use data from 16 years of temperate grassland grown under `free-air carbon dioxide enrichment’ conditions to show that the CFE on above-ground biomass is strongest under local average environmental conditions. The observed CFE was reduced or disappeared under wetter, drier and/or hotter conditions when the forcing variable exceeded its intermediate regime. This is in contrast to predictions of an increased CO2 fertilization effect under drier and warmer conditions. Such extreme weather conditions are projected to occur more intensely and frequently under future climate scenarios. Consequently, current biogeochemical models might overestimate the future NPP sink capacity of temperate C3 grasslands and hence underestimate future atmospheric [CO2] increase.
Development of heat and drought related extreme weather events and their effect on winter wheat yields in Germany

NASA Astrophysics Data System (ADS)

Lüttger, Andrea B.; Feike, Til

2018-04-01

Climate change constitutes a major challenge for high productivity in wheat, the most widely grown crop in Germany. Extreme weather events including dry spells and heat waves, which negatively affect wheat yields, are expected to aggravate in the future. It is crucial to improve the understanding of the spatiotemporal development of such extreme weather events and the respective crop-climate relationships in Germany. Thus, the present study is a first attempt to evaluate the historic development of relevant drought and heat-related extreme weather events from 1901 to 2010 on county level (NUTS-3) in Germany. Three simple drought indices and two simple heat stress indices were used in the analysis. A continuous increase in dry spells over time was observed over the investigated periods from 1901-1930, 1931-1960, 1961-1990 to 2001-2010. Short and medium dry spells, i.e., precipitation-free periods longer than 5 and 8 days, respectively, increased more strongly compared to longer dry spells (longer than 11 days). The heat-related stress indices with maximum temperatures above 25 and 28 °C during critical wheat growth phases showed no significant increase over the first three periods but an especially sharp increase in the final 1991-2010 period with the increases being particularly pronounced in parts of Southwestern Germany. Trend analysis over the entire 110-year period using Mann-Kendall test revealed a significant positive trend for all investigated indices except for heat stress above 25 °C during flowering period. The analysis of county-level yield data from 1981 to 2010 revealed declining spatial yield variability and rather constant temporal yield variability over the three investigated (1981-1990, 1991-2000, and 2001-2010) decades. A clear spatial gradient manifested over time with variability in the West being much smaller than in the east of Germany. Correlating yield variability with the previously analyzed extreme weather indices revealed strong spatiotemporal fluctuations in explanatory power of the different indices over all German counties and the three time periods. Over the 30 years, yield deviations were increasingly well correlated with heat and drought-related indices, with the number of days with maximum temperature above 25 °C during anthesis showing a sharp increase in explanatory power over entire Germany in the final 2001-2010 period.

Classification and machine recognition of severe weather patterns

NASA Technical Reports Server (NTRS)

Wang, P. P.; Burns, R. C.

1976-01-01

Forecasting and warning of severe weather conditions are treated from the vantage point of pattern recognition by machine. Pictorial patterns and waveform patterns are distinguished. Time series data on sferics are dealt with by considering waveform patterns. A severe storm patterns recognition machine is described, along with schemes for detection via cross-correlation of time series (same channel or different channels). Syntactic and decision-theoretic approaches to feature extraction are discussed. Active and decayed tornados and thunderstorms, lightning discharges, and funnels and their related time series data are studied.
Climate change and temperature extremes: A review of heat- and cold-related morbidity and mortality concerns of municipalities.

PubMed

Gronlund, Carina J; Sullivan, Kyle P; Kefelegn, Yonathan; Cameron, Lorraine; O'Neill, Marie S

2018-08-01

Cold and hot weather are associated with mortality and morbidity. Although the burden of temperature-associated mortality may shift towards high temperatures in the future, cold temperatures may represent a greater current-day problem in temperate cities. Hot and cold temperature vulnerabilities may coincide across several personal and neighborhood characteristics, suggesting opportunities for increasing present and future resilience to extreme temperatures. We present a narrative literature review encompassing the epidemiology of cold- and heat-related mortality and morbidity, related physiologic and environmental mechanisms, and municipal responses to hot and cold weather, illustrated by Detroit, Michigan, USA, a financially burdened city in an economically diverse metropolitan area. The Detroit area experiences sharp increases in mortality and hospitalizations with extreme heat, while cold temperatures are associated with more gradual increases in mortality, with no clear threshold. Interventions such as heating and cooling centers may reduce but not eliminate temperature-associated health problems. Furthermore, direct hemodynamic responses to cold, sudden exertion, poor indoor air quality and respiratory epidemics likely contribute to cold-related mortality. Short- and long-term interventions to enhance energy and housing security and housing quality may reduce temperature-related health problems. Extreme temperatures can increase morbidity and mortality in municipalities like Detroit that experience both extreme heat and prolonged cold seasons amidst large socioeconomic disparities. The similarities in physiologic and built-environment vulnerabilities to both hot and cold weather suggest prioritization of strategies that address both present-day cold and near-future heat concerns. Copyright © 2018. Published by Elsevier B.V.
Tambora and the mackerel year: phenology and fisheries during an extreme climate event

USGS Publications Warehouse

Alexander, Karen E.; Leavenworth, William B.; Hall, Carolyn; Mattocks, Steven; Bittner, Steven M.; Klein, Emily; Staudinger, Michelle D.; Bryan, Alexander; Rosset, Julianne; Willis, Theodore V.; Carr, Benjamin H.; Jordaan, Adrian

2017-01-01

Global warming has increased the frequency of extreme climate events, yet responses of biological and human communities are poorly understood, particularly for aquatic ecosystems and fisheries. Retrospective analysis of known outcomes may provide insights into the nature of adaptations and trajectory of subsequent conditions. We consider the 1815 eruption of the Indonesian volcano Tambora and its impact on Gulf of Maine (GoM) coastal and riparian fisheries in 1816. Applying complex adaptive systems theory with historical methods, we analyzed fish export data and contemporary climate records to disclose human and piscine responses to Tambora’s extreme weather at different spatial and temporal scales while also considering sociopolitical influences. Results identified a tipping point in GoM fisheries induced by concatenating social and biological responses to extreme weather. Abnormal daily temperatures selectively affected targeted fish species—alewives, shad, herring, and mackerel—according to their migration and spawning phenologies and temperature tolerances. First to arrive, alewives suffered the worst. Crop failure and incipient famine intensified fishing pressure, especially in heavily settled regions where dams already compromised watersheds. Insufficient alewife runs led fishers to target mackerel, the next species appearing in abundance along the coast; thus, 1816 became the “mackerel year.” Critically, the shift from riparian to marine fisheries persisted and expanded after temperatures moderated and alewives recovered. We conclude that contingent human adaptations to extraordinary weather permanently altered this complex system. Understanding how adaptive responses to extreme events can trigger unintended consequences may advance long-term planning for resilience in an uncertain future.
Tambora and the mackerel year: Phenology and fisheries during an extreme climate event

PubMed Central

Alexander, Karen E.; Leavenworth, William B.; Willis, Theodore V.; Hall, Carolyn; Mattocks, Steven; Bittner, Steven M.; Klein, Emily; Staudinger, Michelle; Bryan, Alexander; Rosset, Julianne; Carr, Benjamin H.; Jordaan, Adrian

2017-01-01

Global warming has increased the frequency of extreme climate events, yet responses of biological and human communities are poorly understood, particularly for aquatic ecosystems and fisheries. Retrospective analysis of known outcomes may provide insights into the nature of adaptations and trajectory of subsequent conditions. We consider the 1815 eruption of the Indonesian volcano Tambora and its impact on Gulf of Maine (GoM) coastal and riparian fisheries in 1816. Applying complex adaptive systems theory with historical methods, we analyzed fish export data and contemporary climate records to disclose human and piscine responses to Tambora’s extreme weather at different spatial and temporal scales while also considering sociopolitical influences. Results identified a tipping point in GoM fisheries induced by concatenating social and biological responses to extreme weather. Abnormal daily temperatures selectively affected targeted fish species—alewives, shad, herring, and mackerel—according to their migration and spawning phenologies and temperature tolerances. First to arrive, alewives suffered the worst. Crop failure and incipient famine intensified fishing pressure, especially in heavily settled regions where dams already compromised watersheds. Insufficient alewife runs led fishers to target mackerel, the next species appearing in abundance along the coast; thus, 1816 became the “mackerel year.” Critically, the shift from riparian to marine fisheries persisted and expanded after temperatures moderated and alewives recovered. We conclude that contingent human adaptations to extraordinary weather permanently altered this complex system. Understanding how adaptive responses to extreme events can trigger unintended consequences may advance long-term planning for resilience in an uncertain future. PMID:28116356
Soil biotic legacy effects of extreme weather events influence plant invasiveness

PubMed Central

Meisner, Annelein; De Deyn, Gerlinde B.; de Boer, Wietse; van der Putten, Wim H.

2013-01-01

Climate change is expected to increase future abiotic stresses on ecosystems through extreme weather events leading to more extreme drought and rainfall incidences [Jentsch A, et al. (2007) Front Ecol Environ 5(7):365–374]. These fluctuations in precipitation may affect soil biota, soil processes [Evans ST, Wallenstein MD (2012) Biogeochemistry 109:101–116], and the proportion of exotics in invaded plant communities [Jiménez MA, et al. (2011) Ecol Lett 14:1277–1235]. However, little is known about legacy effects in soil on the performance of exotics and natives in invaded plant communities. Here we report that drought and rainfall effects on soil processes and biota affect the performance of exotics and natives in plant communities. We performed two mesocosm experiments. In the first experiment, soil without plants was exposed to drought and/or rainfall, which affected soil N availability. Then the initial soil moisture conditions were restored, and a mixed community of co-occurring natives and exotics was planted and exposed to drought during growth. A single stress before or during growth decreased the biomass of natives, but did not affect exotics. A second drought stress during plant growth resetted the exotic advantage, whereas native biomass was not further reduced. In the second experiment, soil inoculation revealed that drought and/or rainfall influenced soil biotic legacies, which promoted exotics but suppressed natives. Our results demonstrate that extreme weather events can cause legacy effects in soil biota, promoting exotics and suppressing natives in invaded plant communities, depending on the type, frequency, and timing of extreme events. PMID:23716656
Role of Winter Weather Conditions and Slipperiness on Tourists' Accidents in Finland.

PubMed

Lépy, Élise; Rantala, Sinikka; Huusko, Antti; Nieminen, Pentti; Hippi, Marjo; Rautio, Arja

2016-08-15

(1) BACKGROUND: In Finland, slippery snowy or icy ground surface conditions can be quite hazardous to human health during wintertime. We focused on the impacts of the variability in weather conditions on tourists' health via documented accidents during the winter season in the Sotkamo area. We attempted to estimate the slipping hazard in a specific context of space and time focusing on the weather and other possible parameters, responsible for fluctuations in the numbers of injuries/accidents; (2) METHODS: We used statistical distributions with graphical illustrations to examine the distribution of visits to Kainuu Hospital by non-local patients and their characteristics/causes; graphs to illustrate the distribution of the different characteristics of weather conditions; questionnaires and interviews conducted among health care and safety personnel in Sotkamo and Kuusamo; (3) RESULTS: There was a clear seasonal distribution in the numbers and types of extremity injuries of non-local patients. While the risk of slipping is emphasized, other factors leading to injuries are evaluated; and (4) CONCLUSIONS: The study highlighted the clear role of wintery weather conditions as a cause of extremity injuries even though other aspects must also be considered. Future scenarios, challenges and adaptive strategies are also discussed from the viewpoint of climate change.
Overview of Best Practices in Mitigating the Impact of Natural Disasters and Extreme Weather Phenomena on European Aviation - The MOWE-IT Project

NASA Astrophysics Data System (ADS)

Muehlhausen, Thorsten; Kreuz, Michael; Temme, Annette; Nokkala, Marko; Nurmi, Pertti; Perrels, Adriaan; Hyvarinen, Otto; Yuga, Ilkka; Pylkko, Pirkko; Kral, Stephan; Schaetter, Frank; Bartsch, Mariana; Wiens, Marcus; Michaelides, Silas; Tymvios, Filippos; Papadakis, Matheos; Athanasatos, Spyros

2014-05-01

The European transport system has shown various degrees of vulnerability to external shocks such as severe weather events, which have partially or, in some cases, totally shut down part of the transport system. Under climate change conditions, the identification of Best Practices within the European area and the proposal of short, medium and long term solutions in order to deal with induced disruptions are vital to upkeep the efficiency and integrity of the European transport network. The MOWE-IT (Management of weather events in the transport system) project is a continuation of the work performed in up-to-date European projects such as the EWENT, WEATHER and ECCONET projects. Its aim is to identify such existing best practices and to develop methodologies in order to assist transport operators, authorities and transport system users to mitigate the impact of natural disasters and extreme weather phenomena on transport system performance. While the MOWE-IT project covers a wide number of transportation modes such as road, rail, marine transport, aviation and inland waterways, in this current work, an overview of the project's work performed in the aviation sector in Europe is presented. The MOWE-IT project is funded by the European Union, under its 7th Framework Programme (TRANSPORT SUPPORT ACTIONS).
Role of Winter Weather Conditions and Slipperiness on Tourists’ Accidents in Finland

PubMed Central

Lépy, Élise; Rantala, Sinikka; Huusko, Antti; Nieminen, Pentti; Hippi, Marjo; Rautio, Arja

2016-01-01

(1) Background: In Finland, slippery snowy or icy ground surface conditions can be quite hazardous to human health during wintertime. We focused on the impacts of the variability in weather conditions on tourists’ health via documented accidents during the winter season in the Sotkamo area. We attempted to estimate the slipping hazard in a specific context of space and time focusing on the weather and other possible parameters, responsible for fluctuations in the numbers of injuries/accidents; (2) Methods: We used statistical distributions with graphical illustrations to examine the distribution of visits to Kainuu Hospital by non-local patients and their characteristics/causes; graphs to illustrate the distribution of the different characteristics of weather conditions; questionnaires and interviews conducted among health care and safety personnel in Sotkamo and Kuusamo; (3) Results: There was a clear seasonal distribution in the numbers and types of extremity injuries of non-local patients. While the risk of slipping is emphasized, other factors leading to injuries are evaluated; and (4) Conclusions: The study highlighted the clear role of wintery weather conditions as a cause of extremity injuries even though other aspects must also be considered. Future scenarios, challenges and adaptive strategies are also discussed from the viewpoint of climate change. PMID:27537899
A simplified rainfall-runoff stochastic simulation method for an application of the SCHADEX method to ungauged catchments.

NASA Astrophysics Data System (ADS)

Penot, David; Paquet, Emmanuel; Lang, Michel

2014-05-01

SCHADEX is a probabilistic method for extreme flood estimation, developed and applied since 2006 at Electricité de France (EDF) for dam spillway design [Paquet et al., 2013]. SCHADEX is based on a semi-continuous rainfall-runoff simulation process. The method has been built around two models: a Multi-Exponential Weather Pattern (MEWP) distribution for rainfall probability estimation [Garavaglia et al., 2010] and the MORDOR hydrological model. To use SCHADEX in ungauged context, rainfall distribution and hydrological model must be regionalized. The regionalization of the MEWP rainfall distribution can be managed with SPAZM, a daily rainfall interpolator [Gottardi et al., 2012] which provides reasonable estimates of point and areal rainfall up to hight quantiles. The main issue remains to regionalize MORDOR which is heavily parametrized. A much more simple model has been considered: the SCS model. It is a well known model for event simulation [USDA SCS, 1985; Beven, 2003] and it relies on only one parameter. Then, the idea is to use the SCS model instead of MORDOR within a simplified stochastic simulation scheme to produce a distribution of flood volume from an exhaustive crossing between rainy events and catchment saturation hazards. The presentation details this process and its capacity to generate a runoff distribution based on catchment areal rainfall distribution. The simulation method depends on a unique parameter Smax, the maximum initial loss of the catchment. Then an initial loss S (between zero and Smax) can be drawn to account for the variability of catchment state (between dry and saturated). The distribution of initial loss (or conversely, of catchment saturation, as modeled by MORDOR) seems closely linked to the catchment's regime, therefore easily to regionalize. The simulation takes into account a snow contribution for snow driven catchments, and an antecedent runoff. The presentation shows the results of this stochastic procedure applied on 80 French catchments and its capacity to represent the asymptotic behaviour of the runoff distribution. References: K. J. Beven. Rainfall-Runoff modelling The Primer, British Library, 2003. F. Garavaglia, J. Gailhard, E. Paquet, M. Lang, R. Garçon, and P. Bernardara. Introducing a rainfall compound distribution model based on weather patterns sub-sampling. Hydrology and Earth System Sciences, 14(6):951-964, 2010. F. Gottardi, C. Obled, J. Gailhard, and E. Paquet. Statistical reanalysis of precipitation fields based on ground network data and weather patterns : Application over french mountains. Journal of Hydrology, 432-433:154-167, 2012. ISSN 0022-1694. E. Paquet, F. Garavaglia, R Garçon, and J. Gailhard. The schadex method : a semi-continuous rainfall-runoff simulation for extreme flood estimation. Journal of Hydrology, 2013. USDA SCS, National Engineering Handbook, Supplement A, Section 4, Chapter 10. Whashington DC, 1985.
Association of weather and air pollution interactions on daily mortality in 12 Canadian cities.

PubMed

Vanos, J K; Cakmak, S; Kalkstein, L S; Yagouti, Abderrahmane

It has been well established that both meteorological attributes and air pollution concentrations affect human health outcomes. We examined all cause nonaccident mortality relationships for 28 years (1981-2008) in relation to air pollution and synoptic weather type (encompassing air mass) data in 12 Canadian cities. This study first determines the likelihood of summertime extreme air pollution events within weather types using spatial synoptic classification. Second, it examines the modifying effect of weather types on the relative risk of mortality (RR) due to daily concentrations of air pollution (nitrogen dioxide, ozone, sulfur dioxide, and particulate matter <2.5 μm). We assess both single- and two-pollutant interactions to determine dependent and independent pollutant effects using the relatively new time series technique of distributed lag nonlinear modeling (DLNM). Results display dry tropical (DT) and moist tropical plus (MT+) weathers to result in a fourfold and twofold increased likelihood, respectively, of an extreme pollution event (top 5 % of pollution concentrations throughout the 28 years) occurring. We also demonstrate statistically significant effects of single-pollutant exposure on mortality ( p < 0.05) to be dependent on summer weather type, where stronger results occur in dry moderate (fair weather) and DT or MT+ weather types. The overall average single-effect RR increases due to pollutant exposure within DT and MT+ weather types are 14.9 and 11.9 %, respectively. Adjusted exposures (two-way pollutant effect estimates) generally results in decreased RR estimates, indicating that the pollutants are not independent. Adjusting for ozone significantly lowers 67 % of the single-pollutant RR estimates and reduces model variability, which demonstrates that ozone significantly controls a portion of the mortality signal from the model. Our findings demonstrate the mortality risks of air pollution exposure to differ by weather type, with increased accuracy obtained when accounting for interactive effects through adjustment for dependent pollutants using a DLNM.
Impacts of extreme weather events on transport infrastructure in Norway

NASA Astrophysics Data System (ADS)

Frauenfelder, Regula; Solheim, Anders; Isaksen, Ketil; Romstad, Bård; Dyrrdal, Anita V.; Ekseth, Kristine H. H.; Gangstø Skaland, Reidun; Harbitz, Alf; Harbitz, Carl B.; Haugen, Jan E.; Hygen, Hans O.; Haakenstad, Hilde; Jaedicke, Christian; Jónsson, Árni; Klæboe, Ronny; Ludvigsen, Johanna; Meyer, Nele K.; Rauken, Trude; Sverdrup-Thygeson, Kjetil

2016-04-01

With the latest results on expected future increase in air temperature and precipitation changes reported by the Intergovernmental Panel on Climate Change (IPCC), the climate robustness of important infrastructure is of raising concern in Norway, as well as in the rest of Europe. Economic consequences of natural disasters have increased considerably since 1950. In addition to the effect of demographic changes such as population growth, urbanization and more and more concentration of valuable assets, this increase is also related to an augmenting frequency of extreme events, such as storms, flooding, drought, and landslides. This change is also observable in Norway, where the increased frequency of strong precipitation has led to frequent flooding and landslide events during the last 20 years. A number of studies show that climate change causes an increase in both frequency and intensity of several types of extreme weather, especially when it comes to precipitation. Such extreme weather events greatly affect the transport infrastructure, with numerous and long closures of roads and railroads, in addition to damage and repair costs. Frequent closures of railroad and roads lead to delay or failure in delivery of goods, which again may lead to a loss of customers and/or - eventually - markets. Much of the Norwegian transport infrastructure is more than 50 years old and therefore not adequately dimensioned, even for present climatic conditions. In order to assess these problems and challenges posed to the Norwegian transport infrastructure from present-day and future extreme weather events, the project "Impacts of extreme weather events on infrastructure in Norway (InfraRisk)" was performed under the research Council of Norway program 'NORKLIMA', between 2009 and 2013. The main results of the project are: - Moderate to strong precipitation events have become more frequent and more intense in Norway over the last 50 years, and this trend continues throughout the 21st century. The increase, both in total precipitation, and in the frequency and intensity of extreme events, is greatest in the west and southwest, and in parts of northern Norway, areas with the highest present precipitation. - Snowfall will increase due to increased precipitation in cold areas inland and at high elevations. In lower lying parts of the country, and along the coast, more precipitation as rain will replace snowfall. - The frequency of near-zero events, with freeze-thaw cycles, which can trigger rock falls, will decrease due to the generally increased temperatures. - The greatest uncertainties in the weather trends are linked to uncertainties in climate and emission scenarios, and to the downscaling. - More than 30% of the total length of road and railroads in Norway is exposed to snow avalanche and rock fall/slide hazard. As an example, one of the most exposed railroads, Raumabanen, has an annual probability of 1/3 to be hit by snow avalanches. - Total costs of geohazard impact on the road infrastructure (major roads only) were estimated to be roughly 100 mill. NOK per year, of which the costs of road closures comprise 70%. The numbers are unevenly distributed throughout the country, reflecting the topographic and climatic variability in Norway.
Mapping fire probability and severity in a Mediterranean area using different weather and fuel moisture scenarios

NASA Astrophysics Data System (ADS)

Arca, B.; Salis, M.; Bacciu, V.; Duce, P.; Pellizzaro, G.; Ventura, A.; Spano, D.

2009-04-01

Although in many countries lightning is the main cause of ignition, in the Mediterranean Basin the forest fires are predominantly ignited by arson, or by human negligence. The fire season peaks coincide with extreme weather conditions (mainly strong winds, hot temperatures, low atmospheric water vapour content) and high tourist presence. Many works reported that in the Mediterranean Basin the projected impacts of climate change will cause greater weather variability and extreme weather conditions, with drier and hotter summers and heat waves. At long-term scale, climate changes could affect the fuel load and the dead/live fuel ratio, and therefore could change the vegetation flammability. At short-time scale, the increase of extreme weather events could directly affect fuel water status, and it could increase large fire occurrence. In this context, detecting the areas characterized by both high probability of large fire occurrence and high fire severity could represent an important component of the fire management planning. In this work we compared several fire probability and severity maps (fire occurrence, rate of spread, fireline intensity, flame length) obtained for a study area located in North Sardinia, Italy, using FlamMap simulator (USDA Forest Service, Missoula). FlamMap computes the potential fire behaviour characteristics over a defined landscape for given weather, wind and fuel moisture data. Different weather and fuel moisture scenarios were tested to predict the potential impact of climate changes on fire parameters. The study area, characterized by a mosaic of urban areas, protected areas, and other areas subject to anthropogenic disturbances, is mainly composed by fire-prone Mediterranean maquis. The input themes needed to run FlamMap were input as grid of 10 meters; the wind data, obtained using a computational fluid-dynamic model, were inserted as gridded file, with a resolution of 50 m. The analysis revealed high fire probability and severity in most of the areas, and therefore a high potential danger. The FlamMap outputs and the derived fire probability maps can be used in decision support systems for fire spread and behaviour and for fire danger assessment with actual and future fire regimes.
Analysis of Synoptic Weather Types and Its Influence on Precipitation in the Marmara Region (NW Turkey)

NASA Astrophysics Data System (ADS)

Baltaci, H.; Kindap, T.; Unal, A.; Karaca, M.

2012-04-01

In this study, we investigated the relationship between synoptic weather types and rainfall patterns in the Marmara region, northwestern part of Turkey. For this purpose, the automated Lamb weather type classification method was applied to the NCEP/NCAR reanalysis daily mean sea level pressure data for the period between 2001 and 2010. Ten synoptic weather types were found that represent the 90% of the synoptic patterns that affect the Marmara region. Based on the annual frequency analysis, mainly six synoptic weather types, 24% (NorthEast), 21% (North), 11% (South), 9% (SouthWest), 7% (Anticyclonic), 5% (Cyclonic), were found dominant in the region. Multiple comparison tests suggest that (i.e., Bonferroni test) northerly patterns (i.e., North and NorthEast) have statistically significantly higher percentages as compared to the southerly (i.e., South and SouthWest) and the rest of the patterns (i.e., Anticylonic and Cylonic). During winter months, N- and NE-patterns observed less frequently than the annual frequencies of them, 18% and 13% of the period, respectively. On the other hand, due to the formation of the low pressure center located over the central Mediterranean Sea, S- and SW-patterns were observed more frequently than their annual mean frequencies, 16% and 17%, respectively. During summer months, N- and NE-patterns become dominant in the region, and they constitute about three quarters of the period, 25% and 44%, respectively. The low pressure center located over central Anatolia and Black Sea brings moist and cool air to the region, preventing excessive heating during the summer season. Cyclonic patterns observed less frequent during the winter and fall months, about 3%. They become more frequent during the summer season, 9% as a result of the shifting of the subtropical jet stream to the south, and the seasonal movement of the Basra low pressure toward the inner and northern parts of the Anatolian peninsula. On the other hand, Anticyclonic patterns are more common in the fall season 11% due to the expansion of spatial extent of the anticyclone center located over the Caspian Sea. Daily precipitation records for the period of between 2001 and 2010 belong to 14 meteorological stations in the region were investigated to understand the influence of synoptic weather types on precipitation. Based on daily precipitation records, about one-third of the NE-patterns result in precipitation which is slightly larger than patterns from other directions. The corresponding values for SW-, N- and S-patterns are 29%, 25% and 25%, respectively. Northerly patterns (N and NE) causes more frequent precipitation on the northern and eastern parts of the region. On the other hand, southerly patterns (S and SW) are more influential and cause more frequent precipitation on the south and northwestern parts of the region. Therefore, frequency of synoptic weather types and daily precipitation records suggest that precipitation regimes are of a different nature in northern and southern parts of the Marmara region. Keywords Synoptic weather types; Marmara Region; Lamb classification; Rainfall patterns
The Assessment of Climatological Impacts on Agricultural Production and Residential Energy Demand

NASA Astrophysics Data System (ADS)

Cooter, Ellen Jean

The assessment of climatological impacts on selected economic activities is presented as a multi-step, inter -disciplinary problem. The assessment process which is addressed explicitly in this report focuses on (1) user identification, (2) direct impact model selection, (3) methodological development, (4) product development and (5) product communication. Two user groups of major economic importance were selected for study; agriculture and gas utilities. The broad agricultural sector is further defined as U.S.A. corn production. The general category of utilities is narrowed to Oklahoma residential gas heating demand. The CERES physiological growth model was selected as the process model for corn production. The statistical analysis for corn production suggests that (1) although this is a statistically complex model, it can yield useful impact information, (2) as a result of output distributional biases, traditional statistical techniques are not adequate analytical tools, (3) the model yield distribution as a whole is probably non-Gausian, particularly in the tails and (4) there appears to be identifiable weekly patterns of forecasted yields throughout the growing season. Agricultural quantities developed include point yield impact estimates and distributional characteristics, geographic corn weather distributions, return period estimates, decision making criteria (confidence limits) and time series of indices. These products were communicated in economic terms through the use of a Bayesian decision example and an econometric model. The NBSLD energy load model was selected to represent residential gas heating consumption. A cursory statistical analysis suggests relationships among weather variables across the Oklahoma study sites. No linear trend in "technology -free" modeled energy demand or input weather variables which would correspond to that contained in observed state -level residential energy use was detected. It is suggested that this trend is largely the result of non-weather factors such as population and home usage patterns rather than regional climate change. Year-to-year changes in modeled residential heating demand on the order of 10('6) Btu's per household were determined and later related to state -level components of the Oklahoma economy. Products developed include the definition of regional forecast areas, likelihood estimates of extreme seasonal conditions and an energy/climate index. This information is communicated in economic terms through an input/output model which is used to estimate changes in Gross State Product and Household income attributable to weather variability.
Ecological Effects of Weather Modification: A Problem Analysis.

ERIC Educational Resources Information Center

Cooper, Charles F.; Jolly, William C.

This publication reviews the potential hazards to the environment of weather modification techniques as they eventually become capable of producing large scale weather pattern modifications. Such weather modifications could result in ecological changes which would generally require several years to be fully evident, including the alteration of…
The Characteristics of Cold Air Outbreaks in the Eastern United States and the Influence of Atmospheric Circulation Patterns

NASA Astrophysics Data System (ADS)

Smith, E. T.

2017-12-01

Periods of extreme cold impact the mid-latitudes every winter. Depending on the magnitude and duration of the occurrence, extremely cold periods may be deemed cold air outbreaks (CAOs). Atmospheric teleconnections impact the displacement of polar air, but the relationship between the primary teleconnections and the manifestation of CAOs is not fully understood. A systematic CAO index was developed from 20 surface weather stations based on a set of criteria concerning magnitude, duration, and spatial extent. Statistical analyses of the data were used to determine the overall trends in CAOs. Clusters of sea level pressure (SLP), 100mb, and 10mb geopotential height anomalies were mapped utilizing self-organizing maps (SOMs) to understand the surface, upper-tropospheric Polar Vortex (PV), and stratospheric PV patterns preceding CAOs. The Arctic Oscillation (AO), North Atlantic Oscillation (NAO), and Pacific-North American (PNA) teleconnections were used as variables to explain the magnitude and location of mid-latitude Arctic air displacement. Persistently negative SLP anomalies across the Arctic and North Atlantic were evident 1 - 2 weeks prior to the CAOs throughout the winter. The upper-tropospheric and stratospheric PV were found to be persistently weak/weakening prior to mid-winter CAOs and predominantly strong and off-centered prior to early and late season CAOs. Negative phases of the AO and NAO were favored prior to CAOs, while the PNA favored a near-neutral phase. This method of CAO and synoptic pattern characterization benefits from a continuous pattern representation and provides insight as to how specific teleconnections impact the atmospheric flow in a way that leads to CAOs in the eastern U.S.
The potential benefits of location-specific biometeorological indexes

NASA Astrophysics Data System (ADS)

Wong, Ho Ting; Wang, Jinfeng; Yin, Qian; Chen, Si; Lai, Poh Chin

2017-09-01

It is becoming popular to use biometeorological indexes to study the effects of weather on human health. Most of the biometeorological indexes were developed decades ago and only applicable to certain locations because of different climate types. Merely using standard biometeorological indexes to replace typical weather factors in biometeorological studies of different locations may not be an ideal research direction. This research is aimed at assessing the difference of statistical power between using standard biometeorological indexes and typical weather factors on describing the effects of extreme weather conditions on daily ambulance demands in Hong Kong. Results showed that net effective temperature and apparent temperature did not perform better than typical weather factors in describing daily ambulance demands in this study. The maximum adj- R 2 improvement was only 0.08, whereas the maximum adj- R 2 deterioration was 0.07. In this study, biometeorological indexes did not perform better than typical weather factors, possibly due to the differences of built environments and lifestyles in different locations and eras. Regarding built environments, the original parameters for calculating the index values may not be applicable to Hong Kong as buildings in Hong Kong are extremely dense and most are equipped with air conditioners. Regarding lifestyles, the parameters, which were set decades ago, may be outdated and not suitable to modern lifestyles as using hand-held electrical fans on the street to help reduce heat stress are popular. Hence, it is ideal to have tailor-made updated location-specific biometeorological indexes to study the effects of weather on human health.
The Extreme Climate Index: a novel and multi-hazard index for extreme weather events.

NASA Astrophysics Data System (ADS)

Cucchi, Marco; Petitta, Marcello; Calmanti, Sandro

2017-04-01

In this presentation we introduce the Extreme Climate Index (ECI): an objective, multi-hazard index capable of tracking changes in the frequency or magnitude of extreme weather events in African countries, thus indicating that a shift to a new climate regime is underway in a particular area. This index has been developed in the context of XCF (eXtreme Climate Facilities) project lead by ARC (African Risk Capacity, specialised agency of the African Union), and will be used in the payouts triggering mechanism of an insurance programme against risks related to the increase of frequency and magnitude of extreme weather events due to climate regimes' changes. The main hazards covered by ECI will be extreme dry, wet and heat events, with the possibility of adding region-specific risk events such as tropical cyclones for the most vulnerable areas. It will be based on data coming from consistent, sufficiently long, high quality historical records and will be standardized across broad geographical regions, so that extreme events occurring under different climatic regimes in Africa can be comparable. The first step to construct such an index is to define single hazard indicators. In this first study we focused on extreme dry/wet and heat events, using for their description respectively the well-known SPI (Standardized Precipitation Index) and an index developed by us, called SHI (Standardized Heat-waves Index). The second step consists in the development of a computational strategy to combine these, and possibly other indices, so that the ECI can describe, by means of a single indicator, different types of climatic extremes. According to the methodology proposed in this paper, the ECI is defined by two statistical components: the ECI intensity, which indicates whether an event is extreme or not; the angular component, which represent the contribution of each hazard to the overall intensity of the index. The ECI can thus be used to identify "extremes" after defining a suitable threshold above which the events can be held as extremes. In this presentation, after describing the methodology we used for the construction of the ECI, we present results obtained on different African regions, using NCEP Reanalysis dataset for air temperature at sig995 level and CHIRP dataset for precipitations. Particular attention will be devoted to 2015/2016 Malawi drought, which received some media attention due to the failure of the risk assessment model used to trigger due payouts: it will be shown how, on the contrary, combination of hydrological and temperature data used in ECI succeed in evaluating the extremeness of this event.
Arctic-midlatitude weather linkages in North America

NASA Astrophysics Data System (ADS)

Overland, James E.; Wang, Muyin

2018-06-01

There is intense public interest in whether major Arctic changes can and will impact midlatitude weather such as cold air outbreaks on the central and east side of continents. Although there is progress in linkage research for eastern Asia, a clear gap is conformation for North America. We show two stationary temperature/geopotential height patterns where warmer Arctic temperatures have reinforced existing tropospheric jet stream wave amplitudes over North America: a Greenland/Baffin Block pattern during December 2010 and an Alaska Ridge pattern during December 2017. Even with continuing Arctic warming over the past decade, other recent eastern US winter months were less susceptible for an Arctic linkage: the jet stream was represented by either zonal flow, progressive weather systems, or unfavorable phasing of the long wave pattern. The present analysis lays the scientific controversy over the validity of linkages to the inherent intermittency of jet stream dynamics, which provides only an occasional bridge between Arctic thermodynamic forcing and extended midlatitude weather events.
Weather effects on the patterns of people's everyday activities: a study using GPS traces of mobile phone users.

PubMed

Horanont, Teerayut; Phithakkitnukoon, Santi; Leong, Tuck W; Sekimoto, Yoshihide; Shibasaki, Ryosuke

2013-01-01

This study explores the effects that the weather has on people's everyday activity patterns. Temperature, rainfall, and wind speed were used as weather parameters. People's daily activity patterns were inferred, such as place visited, the time this took place, the duration of the visit, based on the GPS location traces of their mobile phones overlaid upon Yellow Pages information. Our analysis of 31,855 mobile phone users allowed us to infer that people were more likely to stay longer at eateries or food outlets, and (to a lesser degree) at retail or shopping areas when the weather is very cold or when conditions are calm (non-windy). When compared to people's regular activity patterns, certain weather conditions affected people's movements and activities noticeably at different times of the day. On cold days, people's activities were found to be more diverse especially after 10AM, showing greatest variations between 2PM and 6PM. A similar trend is observed between 10AM and midnight on rainy days, with people's activities found to be most diverse on days with heaviest rainfalls or on days when the wind speed was stronger than 4 km/h, especially between 10AM-1AM. Finally, we observed that different geographical areas of a large metropolis were impacted differently by the weather. Using data of urban infrastructure to characterize areas, we found strong correlations between weather conditions upon people's accessibility to trains. This study sheds new light on the influence of weather conditions on human behavior, in particular the choice of daily activities and how mobile phone data can be used to investigate the influence of environmental factors on urban dynamics.

Weather Effects on the Patterns of People's Everyday Activities: A Study Using GPS Traces of Mobile Phone Users

PubMed Central

Leong, Tuck W.; Sekimoto, Yoshihide; Shibasaki, Ryosuke

2013-01-01

This study explores the effects that the weather has on people's everyday activity patterns. Temperature, rainfall, and wind speed were used as weather parameters. People's daily activity patterns were inferred, such as place visited, the time this took place, the duration of the visit, based on the GPS location traces of their mobile phones overlaid upon Yellow Pages information. Our analysis of 31,855 mobile phone users allowed us to infer that people were more likely to stay longer at eateries or food outlets, and (to a lesser degree) at retail or shopping areas when the weather is very cold or when conditions are calm (non-windy). When compared to people's regular activity patterns, certain weather conditions affected people's movements and activities noticeably at different times of the day. On cold days, people's activities were found to be more diverse especially after 10AM, showing greatest variations between 2PM and 6PM. A similar trend is observed between 10AM and midnight on rainy days, with people's activities found to be most diverse on days with heaviest rainfalls or on days when the wind speed was stronger than 4 km/h, especially between 10AM–1AM. Finally, we observed that different geographical areas of a large metropolis were impacted differently by the weather. Using data of urban infrastructure to characterize areas, we found strong correlations between weather conditions upon people's accessibility to trains. This study sheds new light on the influence of weather conditions on human behavior, in particular the choice of daily activities and how mobile phone data can be used to investigate the influence of environmental factors on urban dynamics. PMID:24367481
The sensitivity of snowfall to weather states over Sweden

NASA Astrophysics Data System (ADS)

Norin, Lars; Devasthale, Abhay; L'Ecuyer, Tristan S.

2017-09-01

For a high-latitude country like Sweden snowfall is an important contributor to the regional water cycle. Furthermore, snowfall impacts surface properties, affects atmospheric thermodynamics, has implications for traffic and logistics management, disaster preparedness, and also impacts climate through changes in surface albedo and turbulent heat fluxes. For Sweden it has been shown that large-scale atmospheric circulation patterns, or weather states, are important for precipitation variability. Although the link between atmospheric circulation patterns and precipitation has been investigated for rainfall there are no studies focused on the sensitivity of snowfall to weather states over Sweden.In this work we investigate the response of snowfall to eight selected weather states. These weather states consist of four dominant wind directions together with cyclonic and anticyclonic circulation patterns and enhanced positive and negative phases of the North Atlantic Oscillation. The presented analysis is based on multiple data sources, such as ground-based radar measurements, satellite observations, spatially interpolated in situ observations, and reanalysis data. The data from these sources converge to underline the sensitivity of falling snow over Sweden to the different weather states.In this paper we examine both average snowfall intensities and snowfall accumulations associated with the different weather states. It is shown that, even though the heaviest snowfall intensities occur during conditions with winds from the south-west, the largest contribution to snowfall accumulation arrives with winds from the south-east. Large differences in snowfall due to variations in the North Atlantic Oscillation are shown as well as a strong effect of cyclonic and anticyclonic circulation patterns. Satellite observations are used to reveal the vertical structures of snowfall during the different weather states.
SUBMIT YOUR IMAGES TO NASA's "LET IT SNOW" PHOTO CONTEST!

NASA Image and Video Library

2017-12-08

NASA's Global Precipitation Measurement (GPM) mission wants to see your best photos of winter weather! You can submit your images to the contest here: www.flickr.com/groups/gpm-extreme-weather/ To read more about this image and or to see the high res file go to: earthobservatory.nasa.gov/IOTD/view.php?id=80082
Developing a model for effects of climate change on human health and health-environment interactions: Heat stress in Austin, Texas - Urban Climate

EPA Science Inventory

Human health and well-being are and will be affected by climate change, both directly through changes in extreme weather events and indirectly through weather-induced changes in human and natural systems. Populations are vulnerable to these changes in varying degrees, depending ...
Changing Pattern of Indian Monsoon Extremes: Global and Local Factors

NASA Astrophysics Data System (ADS)

Ghosh, Subimal; Shastri, Hiteshri; Pathak, Amey; Paul, Supantha

2017-04-01

Indian Summer Monsoon Rainfall (ISMR) extremes have remained a major topic of discussion in the field of global change and hydro-climatology over the last decade. This attributes to multiple conclusions on changing pattern of extremes along with poor understanding of multiple processes at global and local scales associated with monsoon extremes. At a spatially aggregate scale, when number of extremes in the grids are summed over, a statistically significant increasing trend is observed for both Central India (Goswami et al., 2006) and all India (Rajeevan et al., 2008). However, such a result over Central India does not satisfy flied significance test of increase and no decrease (Krishnamurthy et al., 2009). Statistically rigorous extreme value analysis that deals with the tail of the distribution reveals a spatially non-uniform trend of extremes over India (Ghosh et al., 2012). This results into statistically significant increasing trend of spatial variability. Such an increase of spatial variability points to the importance of local factors such as deforestation and urbanization. We hypothesize that increase of spatial average of extremes is associated with the increase of events occurring over large region, while increase in spatial variability attributes to local factors. A Lagrangian approach based dynamic recycling model reveals that the major contributor of moisture to wide spread extremes is Western Indian Ocean, while land surface also contributes around 25-30% of moisture during the extremes in Central India. We further test the impacts of local urbanization on extremes and find the impacts are more visible over West central, Southern and North East India. Regional atmospheric simulations coupled with Urban Canopy Model (UCM) shows that urbanization intensifies extremes in city areas, but not uniformly all over the city. The intensification occurs over specific pockets of the urban region, resulting an increase in spatial variability even within the city. This also points to the need of setting up multiple weather stations over the city at a finer resolution for better understanding of urban extremes. We conclude that the conventional method of considering large scale factors is not sufficient for analysing the monsoon extremes and characterization of the same needs a blending of both global and local factors. Ghosh, S., Das, D., Kao, S-C. & Ganguly, A. R. Lack of uniform trends but increasing spatial variability in observed Indian rainfall extremes. Nature Clim. Change 2, 86-91 (2012) Goswami, B. N., Venugopal, V., Sengupta, D., Madhusoodanan, M. S. & Xavier, P. K. Increasing trend of extreme rain events over India in a warming environment. Science 314, 1442-1445 (2006). Krishnamurthy, C. K. B., Lall, U. & Kwon, H-H. Changing frequency and intensity of rainfall extremes over India from 1951 to 2003. J. Clim. 22, 4737-4746 (2009). Rajeevan, M., Bhate, J. & Jaswal, A. K. Analysis of variability and trends of extreme rainfall events over India using 104 years of gridded daily rainfall data. Geophys. Res. Lett. 35, L18707 (2008).
Weather Fundamentals: Climate & Seasons. [Videotape].

ERIC Educational Resources Information Center

1998

The videos in this educational series for grades 4-7, help students understand the science behind weather phenomena through dramatic live-action footage, vivid animated graphics, detailed weather maps, and hands-on experiments. This episode (23 minutes), describes weather patterns and cycles around the globe. The various types of climates around…
Improving the health forecasting alert system for cold weather and heat-waves in England: a case-study approach using temperature-mortality relationships

NASA Astrophysics Data System (ADS)

Masato, Giacomo; Cavany, Sean; Charlton-Perez, Andrew; Dacre, Helen; Bone, Angie; Carmicheal, Katie; Murray, Virginia; Danker, Rutger; Neal, Rob; Sarran, Christophe

2015-04-01

The health forecasting alert system for cold weather and heatwaves currently in use in the Cold Weather and Heatwave plans for England is based on 5 alert levels, with levels 2 and 3 dependent on a forecast or actual single temperature action trigger. Epidemiological evidence indicates that for both heat and cold, the impact on human health is gradual, with worsening impact for more extreme temperatures. The 60% risk of heat and cold forecasts used by the alerts is a rather crude probabilistic measure, which could be substantially improved thanks to the state-of-the-art forecast techniques. In this study a prototype of a new health forecasting alert system is developed, which is aligned to the approach used in the Met Office's (MO) National Severe Weather Warning Service (NSWWS). This is in order to improve information available to responders in the health and social care system by linking temperatures more directly to risks of mortality, and developing a system more coherent with other weather alerts. The prototype is compared to the current system in the Cold Weather and Heatwave plans via a case-study approach to verify its potential advantages and shortcomings. The prototype health forecasting alert system introduces an "impact vs likelihood matrix" for the health impacts of hot and cold temperatures which is similar to those used operationally for other weather hazards as part of the NSWWS. The impact axis of this matrix is based on existing epidemiological evidence, which shows an increasing relative risk of death at extremes of outdoor temperature beyond a threshold which can be identified epidemiologically. The likelihood axis is based on a probability measure associated with the temperature forecast. The new method is tested for two case studies (one during summer 2013, one during winter 2013), and compared to the performance of the current alert system. The prototype shows some clear improvements over the current alert system. It allows for a much greater degree of flexibility, provides more detailed regional information about the health risks associated with periods of extreme temperatures, and is more coherent with other weather alerts which may make it easier for front line responders to use. It will require validation and engagement with stakeholders before it can be considered for use.
Climate Change and Extreme Weather Impacts on Salt Marsh Plants

EPA Science Inventory

Regional assessments of climate change impacts on New England demonstrate a clear rise in rainfall over the past century. The number of extreme precipitation events (i.e., two or more inches of rain falling during a 48-hour period) has also increased over the past few decades. ...
Enzyme Activity Dynamics in Response to Climate Change: 2011 Drought-Heat Wave

USDA-ARS?s Scientific Manuscript database

Extreme weather events such as severe droughts and heat waves may have permanent consequences on soil quality and functioning in agroecosystems. The Southern High Plains (SHP) region of Texas, U.S., a large cotton producing area, experienced a historically extreme drought and heat wave during 2011,...
Does Life Seem Better on a Sunny Day? Examining the Association between Daily Weather Conditions and Life Satisfaction Judgments

PubMed Central

Lucas, Richard E.; Lawless, Nicole M.

2013-01-01

Weather conditions have been shown to affect a broad range of thoughts, feelings, and behaviors. The current study examines whether these effects extend to life satisfaction judgments. We examine the association between daily weather conditions and life satisfaction in a representative sample of over 1 million Americans from all 50 states who were assessed (in a cross-sectional design) over a 5-year period. Most daily weather conditions were unrelated to life satisfaction judgments, and those effects that were significant reflect very small effects that were only detectable because of the extremely high power of these analyses. These results show that weather does not reliably affect judgments of life satisfaction. PMID:23607534
Predictability of Seasonal Precipitation Intensities Associated with Tropical Cyclones and Disturbances in Indo-China Region

NASA Astrophysics Data System (ADS)

Revel, M.; Utsumi, N.; Yoshikawa, S.; Kanae, S.

2016-12-01

Summer Monsoon precipitation provide support for the livelihood of the people of Southeast Asia where the population density is very high. Monsoon precipitation shows high variation in seasonal and yearly time scales affecting daily life of the people in the regions such Indo-China peninsula where most of the countries depend on agricultural economy. Predictability of seasonal extreme events such as flooding and droughts by different climatic conditions will enhance the ability to mitigate the risk of natural disasters in Indo-China peninsula. In addition lower tropospheric (850hPa) wind flow pattern is very useful in understanding the seasonal variability of Southeastern Asian Summer Monsoon. Furthermore summer monsoon in the Indo-China peninsula is strongly influenced by the local wind-terrain-precipitation interaction. Recently a set of Monsoon Indices has been developed by several researches, Indo China Monsoon Indices (ICMIs) as a representation of lower tropospheric wind flow patterns around Southeast Asian. On the other hand different precipitation providing weather systems vary according to the global position and local weather system. Responses of ICMIs to different precipitation providing weather systems may vary in temporal and spatial scales. Hence the seasonal responses of differentiated precipitation with ICMIs in Indo-China peninsula are being investigated. Objective detection methods are been adopted in order to identify the locations of tropical cyclones (TCs), and westward propagating disturbances (WDs) using a Japanese 25-year ReAnalysis data and the Global Precipitation Climatology Project One-Degree Daily data is differentiated into TCs, and WDs related precipitation. TCs contribute highly over the east coast of Indo China peninsula where WDs contributed all over land area of Indo-China peninsula but more towards Bay of Bengal. Correlations and regressions suggest that the indices which is calculated using the wind patterns, situated west of Indo-China peninsula tend to increase the moisture production to precipitation which is produced by seasonal winds and local convections. The increment of indices in the east of the peninsula tends withdraw the moisture of TCs and WDs related precipitation in Indo-China peninsula, as those originate from east of the peninsula.
The Interfaces Between Historical, Paleo-, and Modern Climatology

NASA Astrophysics Data System (ADS)

Mock, C. J.

2011-12-01

Historical climatology, commonly defined as the study of reconstructing past climates from documentary and early instrumental data, has routinely utilized data within the last several hundred years down to sub-daily temporal resolution prior to the advent of "modern" instrumental records beginning in the late 19th and 20th centuries. Historical climate reconstruction methods generally share similar aspects conducted in both paleoclimate reconstruction and modern climatology, given the need to quantify, calibrate, and conduct careful data quality assessments. Although some studies have integrated historical climatic studies with other high resolution paleoclimatic proxies, very few efforts have integrated historical data with modern "systematic" climate networks to further examine spatial and temporal patterns of climate variability. This presentation describes historical climate examples of how such data can be integrated within modern climate timescales, including examples of documentary data on tropical cyclones from the Western Pacific and Atlantic Basins, colonial records from Belize and Constantinople, ship logbooks in the Western Arctic, plantation diaries from the American Southeast, and newspaper data from the Fiji Islands and Bermuda. Some results include a unique wet period in Belize and active tropical cyclone periods in the Western and South Pacific in the early 20th century - both are not reflected in conventional modern climate datasets. Documentary data examples demonstrate high feasibility in further understanding extreme weather events at daily timeframes such as false spring/killing frost episodes and hydrological extremes in southeastern North America. Recent unique efforts also involve community participation, secondary education, and web- based volunteer efforts to digitize and archive historical weather and climate information.
Enhancing Extreme Heat Health-Related Intervention and Preparedness Activities Using Remote Sensing Analysis of Daily Surface Temperature, Surface Observation Networks and Ecmwf Reanalysis

NASA Astrophysics Data System (ADS)

Garcia, R. L.; Booth, J.; Hondula, D.; Ross, K. W.; Stuyvesant, A.; Alm, G.; Baghel, E.

2015-12-01

Extreme heat causes more human fatalities in the United States than any other natural disaster, elevating the concern of heat-related mortality. Maricopa County Arizona is known for its high heat index and its sprawling metropolitan complex which makes this region a perfect candidate for human health research. Individuals at higher risk are unequally spatially distributed, leaving the poor, homeless, non-native English speakers, elderly, and the socially isolated vulnerable to heat events. The Arizona Department of Health Services, Arizona State University and NASA DEVELOP LaRC are working to establish a more effective method of placing hydration and cooling centers in addition to enhancing the heat warning system to aid those with the highest exposure. Using NASA's Earth Observation Systems from Aqua and Terra satellites, the daily spatial variability within the UHI was quantified over the summer heat seasons from 2005 - 2014, effectively establishing a remotely sensed surface temperature climatology for the county. A series of One-way Analysis of Variance revealed significant differences between daily surface temperature averages of the top 30% of census tracts within the study period. Furthermore, synoptic upper tropospheric circulation patterns were classified to relate surface weather types and heat index. The surface weather observation networks were also reviewed for analyzing the veracity of the other methods. The results provide detailed information regarding nuances within the UHI effect and will allow pertinent recommendations regarding the health department's adaptive capacity. They also hold essential components for future policy decision-making regarding appropriate locations for cooling centers and efficient warning systems.
What Do Experienced Water Managers Think of Water Resources of Our Nation and Its Management Infrastructure?

PubMed

Hossain, Faisal; Arnold, Jeffrey; Beighley, Ed; Brown, Casey; Burian, Steve; Chen, Ji; Mitra, Anindita; Niyogi, Dev; Pielke, Roger; Tidwell, Vincent; Wegner, Dave

2015-01-01

This article represents the second report by an ASCE Task Committee "Infrastructure Impacts of Landscape-driven Weather Change" under the ASCE Watershed Management Technical Committee and the ASCE Hydroclimate Technical Committee. Herein, the 'infrastructure impacts" are referred to as infrastructure-sensitive changes in weather and climate patterns (extremes and non-extremes) that are modulated, among other factors, by changes in landscape, land use and land cover change. In this first report, the article argued for explicitly considering the well-established feedbacks triggered by infrastructure systems to the land-atmosphere system via landscape change. In this report by the ASCE Task Committee (TC), we present the results of this ASCE TC's survey of a cross section of experienced water managers using a set of carefully crafted questions. These questions covered water resources management, infrastructure resiliency and recommendations for inclusion in education and curriculum. We describe here the specifics of the survey and the results obtained in the form of statistical averages on the 'perception' of these managers. Finally, we discuss what these 'perception' averages may indicate to the ASCE TC and community as a whole for stewardship of the civil engineering profession. The survey and the responses gathered are not exhaustive nor do they represent the ASCE-endorsed viewpoint. However, the survey provides a critical first step to developing the framework of a research and education plan for ASCE. Given the Water Resources Reform and Development Act passed in 2014, we must now take into account the perceived concerns of the water management community.
What Do Experienced Water Managers Think of Water Resources of Our Nation and Its Management Infrastructure?

PubMed Central

Hossain, Faisal; Arnold, Jeffrey; Beighley, Ed; Brown, Casey; Burian, Steve; Chen, Ji; Mitra, Anindita; Niyogi, Dev; Pielke, Roger; Tidwell, Vincent; Wegner, Dave

2015-01-01

This article represents the second report by an ASCE Task Committee “Infrastructure Impacts of Landscape-driven Weather Change” under the ASCE Watershed Management Technical Committee and the ASCE Hydroclimate Technical Committee. Herein, the ‘infrastructure impacts” are referred to as infrastructure-sensitive changes in weather and climate patterns (extremes and non-extremes) that are modulated, among other factors, by changes in landscape, land use and land cover change. In this first report, the article argued for explicitly considering the well-established feedbacks triggered by infrastructure systems to the land-atmosphere system via landscape change. In this report by the ASCE Task Committee (TC), we present the results of this ASCE TC’s survey of a cross section of experienced water managers using a set of carefully crafted questions. These questions covered water resources management, infrastructure resiliency and recommendations for inclusion in education and curriculum. We describe here the specifics of the survey and the results obtained in the form of statistical averages on the ‘perception’ of these managers. Finally, we discuss what these ‘perception’ averages may indicate to the ASCE TC and community as a whole for stewardship of the civil engineering profession. The survey and the responses gathered are not exhaustive nor do they represent the ASCE-endorsed viewpoint. However, the survey provides a critical first step to developing the framework of a research and education plan for ASCE. Given the Water Resources Reform and Development Act passed in 2014, we must now take into account the perceived concerns of the water management community. PMID:26544045
Biogeochemistry and nitrogen cycling in an Arctic, volcanic ecosystem

NASA Astrophysics Data System (ADS)

Fogel, M. L.; Benning, L.; Conrad, P. G.; Eigenbrode, J.; Starke, V.

2007-12-01

As part of a study on Mars Analogue environments, the biogeochemistry of Sverrefjellet Volcano, Bocfjorden, Svalbard, was conducted and compared to surrounding glacial, thermal spring, and sedimentary environments. An understanding of how nitrogen might be distributed in a landscape that had extinct or very cold adapted, slow- growing extant organisms should be useful for detecting unknown life forms. From high elevations (900 m) to the base of the volcano (sea level), soil and rock ammonium concentrations were uniformly low, typically less than 1- 3 micrograms per gm of rock or soil. In weathered volcanic soils, reduced nitrogen concentrations were higher, and oxidized nitrogen concentrations lower. The opposite was found in a weathered Devonian sedimentary soil. Plants and lichens growing on volcanic soils have an unusually wide range in N isotopic compositions from -5 to +12‰, a range rarely measured in temperate ecosystems. Nitrogen contents and isotopic compositions of volcanic soils and rocks were strongly influenced by the presence or absence of terrestrial herbivores or marine avifauna with higher concentrations of N and elevated N isotopic compositions occurring as patches in areas immediately influenced by reindeer, Arctic fox ( Alopex lagopus), and marine birds. Because of the extreme conditions in this area, ephemeral deposition of herbivore feces results in a direct and immediate N pulses into the ecosystem. The lateral extent and distribution of marine- derived nitrogen was measured on a landscape scale surrounding an active fox den. Nitrogen was tracked from the bones of marine birds to soil to vegetation. Because of extreme cold, slow biological rates and nitrogen cycling, a mosaic of N patterns develops on the landscape scale.
Modelling Precipitation and Temperature Extremes: The Importance of Horizontal Resolution

NASA Astrophysics Data System (ADS)

Shields, C. A.; Kiehl, J. T.; Meehl, G. A.

2013-12-01

Understanding Earth's water cycle on a warming planet is of critical importance in society's ability to adapt to climate change. Extreme weather events, such as floods, heat waves, and drought will likely change with the water cycle as greenhouse gases continue to rise. Location, duration, and intensity of extreme events can be studied using complex earth system models. Here, we employ the fully coupled Community Earth System Model (CESM1.0) to evaluate extreme event impacts for different possible future forcing scenarios. Simulations applying the Representative Concentration Pathway (RCP) scenarios 2.6 and 8.5 were chosen to bracket the range of model responses. Because extreme weather events happen on a regional scale, there is a tendency to favor using higher resolution models, i.e. models that can represent regional features with greater accuracy. Within the CESM1.0 framework, we evaluate both the standard 1 degree resolution (1 degree atmosphere/land coupled to 1 degree ocean/sea ice), and the higher 0.5 degree resolution version (0.5 degree atmosphere/land coupled to 1 degree ocean/sea ice), focusing on extreme precipitation events, heat waves, and droughts. We analyze a variety of geographical regions, but generally find that benefits from increased horizontal resolution are most significant on the regional scale.
Extreme rainfall, vulnerability and risk: a continental-scale assessment for South America

USGS Publications Warehouse

Vorosmarty, Charles J.; de Guenni, Lelys Bravo; Wollheim, Wilfred M.; Pellerin, Brian A.; Bjerklie, David M.; Cardoso, Manoel; D'Almeida, Cassiano; Colon, Lilybeth

2013-01-01

Extreme weather continues to preoccupy society as a formidable public safety concern bearing huge economic costs. While attention has focused on global climate change and how it could intensify key elements of the water cycle such as precipitation and river discharge, it is the conjunction of geophysical and socioeconomic forces that shapes human sensitivity and risks to weather extremes. We demonstrate here the use of high-resolution geophysical and population datasets together with documentary reports of rainfall-induced damage across South America over a multi-decadal, retrospective time domain (1960–2000). We define and map extreme precipitation hazard, exposure, affectedpopulations, vulnerability and risk, and use these variables to analyse the impact of floods as a water security issue. Geospatial experiments uncover major sources of risk from natural climate variability and population growth, with change in climate extremes bearing a minor role. While rural populations display greatest relative sensitivity to extreme rainfall, urban settings show the highest rates of increasing risk. In the coming decades, rapid urbanization will make South American cities the focal point of future climate threats but also an opportunity for reducing vulnerability, protecting lives and sustaining economic development through both traditional and ecosystem-based disaster risk management systems.
Oceanic Extreme Model Atmospheres for Aerothermodynamic Calculations,

DTIC Science & Technology

Atmospheric temperature, Atmospheric sounding, Regression analysis, Aerothermodynamics, Marine meteorology, Radiosondes, Weather stations, Newfoundland(Province), Marshall Islands , Arabia, Iran, Coastal regions
Geodetic Space Weather Monitoring by means of Ionosphere Modelling

NASA Astrophysics Data System (ADS)

Schmidt, Michael

2017-04-01

The term space weather indicates physical processes and phenomena in space caused by radiation of energy mainly from the Sun. Manifestations of space weather are (1) variations of the Earth's magnetic field, (2) the polar lights in the northern and southern hemisphere, (3) variations within the ionosphere as part of the upper atmosphere characterized by the existence of free electrons and ions, (4) the solar wind, i.e. the permanent emission of electrons and photons, (5) the interplanetary magnetic field, and (6) electric currents, e.g. the van Allen radiation belt. It can be stated that ionosphere disturbances are often caused by so-called solar storms. A solar storm comprises solar events such as solar flares and coronal mass ejections (CMEs) which have different effects on the Earth. Solar flares may cause disturbances in positioning, navigation and communication. CMEs can effect severe disturbances and in extreme cases damages or even destructions of modern infrastructure. Examples are interruptions to satellite services including the global navigation satellite systems (GNSS), communication systems, Earth observation and imaging systems or a potential failure of power networks. Currently the measurements of solar satellite missions such as STEREO and SOHO are used to forecast solar events. Besides these measurements the Earth's ionosphere plays another key role in monitoring the space weather, because it responses to solar storms with an increase of the electron density. Space-geodetic observation techniques, such as terrestrial GNSS, satellite altimetry, space-borne GPS (radio occultation), DORIS and VLBI provide valuable global information about the state of the ionosphere. Additionally geodesy has a long history and large experience in developing and using sophisticated analysis and combination techniques as well as empirical and physical modelling approaches. Consequently, geodesy is predestinated for strongly supporting space weather monitoring via modelling the ionosphere and detecting and forecasting its disturbances. At present a couple of nations, such as the US, UK, Japan, Canada and China, are taken the threats from extreme space weather events seriously and support the development of observing strategies and fundamental research. However, (extreme) space weather events are in all their consequences on the modern highly technologized society, causative global problems which have to be treated globally and not regionally or even nationally. Consequently, space weather monitoring must include (1) all space-geodetic observation techniques and (2) geodetic evaluation methods such as data combination, real-time modelling and forecast. In other words, geodetic space weather monitoring comprises the basic ideas of GGOS and will provide products such as forecasts of severe solar events in order to initiate necessary activities to protect the infrastructure of modern society.

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