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.

Links between large-scale circulation patterns and streamflow in Central Europe: A review

NASA Astrophysics Data System (ADS)

Steirou, Eva; Gerlitz, Lars; Apel, Heiko; Merz, Bruno

2017-06-01

We disentangle the relationships between streamflow and large-scale atmospheric circulation in Central Europe (CE), an area affected by climatic influences from different origins (Atlantic, Mediterranean and Continental) and characterized by diverse topography and flow regimes. Our literature review examines in detail the links between mean, high and low flows in CE and large-scale circulation patterns, with focus on two closely related phenomena, the North Atlantic Oscillation (NAO) and the Western-zonal circulation (WC). For both patterns, significant relations, consistent between different studies, are found for large parts of CE. The strongest links are found for the winter season, forming a dipole-like pattern with positive relationships with streamflow north of the Alps and the Carpathians for both indices and negative relationships for the NAO in the south. An influence of winter NAO is also detected in the amplitude and timing of snowmelt flows later in the year. Discharge in CE has further been linked to other large-scale climatic modes such as the Scandinavia pattern (SCA), the East Atlantic/West Russian pattern (EA/WR), the El Niño-Southern Oscillation (ENSO) and synoptic weather patterns such as the Vb weather regime. Different mechanisms suggested in the literature to modulate links between streamflow and the NAO are combined with topographical characteristics of the target area in order to explain the divergent NAO/WC influence on streamflow in different parts of CE. In particular, a precipitation mechanism seems to regulate winter flows in North-Western Germany, an area with short duration of snow cover and with rainfall-generated floods. The precipitation mechanism is also likely in Southern CE, where correlations between the NAO and temperature are low. Finally, in the rest of the study area (Northern CE, Alpine region), a joint precipitation-snow mechanism influences floods not only in winter, but also in the spring/snowmelt period, providing some possibilities for flood forecasting.

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.

Spatial patterns and broad-scale weather cues of beech mast seeding in Europe.

PubMed

Vacchiano, Giorgio; Hacket-Pain, Andrew; Turco, Marco; Motta, Renzo; Maringer, Janet; Conedera, Marco; Drobyshev, Igor; Ascoli, Davide

2017-07-01

Mast seeding is a crucial population process in many tree species, but its spatio-temporal patterns and drivers at the continental scale remain unknown . Using a large dataset (8000 masting observations across Europe for years 1950-2014) we analysed the spatial pattern of masting across the entire geographical range of European beech, how it is influenced by precipitation, temperature and drought, and the temporal and spatial stability of masting-weather correlations. Beech masting exhibited a general distance-dependent synchronicity and a pattern structured in three broad geographical groups consistent with continental climate regimes. Spearman's correlations and logistic regression revealed a general pattern of beech masting correlating negatively with temperature in the summer 2 yr before masting, and positively with summer temperature 1 yr before masting (i.e. 2T model). The temperature difference between the two previous summers (DeltaT model) was also a good predictor. Moving correlation analysis applied to the longest eight chronologies (74-114 yr) revealed stable correlations between temperature and masting, confirming consistency in weather cues across space and time. These results confirm widespread dependency of masting on temperature and lend robustness to the attempts to reconstruct and predict mast years using temperature data. © 2017 The Authors. New Phytologist © 2017 New Phytologist Trust.

Monitoring water use and crop condition in California vineyards at multiple scales using multi-sensor satellite data fusion

USDA-ARS?s Scientific Manuscript database

Recent weather patterns have left California’s agricultural areas in severe drought. Given the reduced water availability in much of California it is critical to be able to measure water use and crop condition over large areas, but also in fine detail at scales of individual fields to support water...

The Contribution of Mesoscale Convective Weather Systems to the Warm-Season Precipitation in the United States.

NASA Astrophysics Data System (ADS)

Fritsch, J. M.; Kane, R. J.; Chelius, C. R.

1986-10-01

The contribution of precipitation from mesoscale convective weather systems to the warm-season (April-September) rainfall in the United States is evaluated. Both Mesoscale Convective Complexes (MCC's) and other large, long-lived mesoscale convective systems that do not quite meet Maddox's criteria for being termed an MCC are included in the evaluation. The distribution and geographical limits of the precipitation from the convective weather systems are constructed for the warm seasons of 1982, a `normal' year, and 1983, a drought year. Precipitation characteristics of the systems are compared for the 2 years to determine how large-scale drought patterns affect their precipitation production.The frequency, precipitation characteristics and hydrologic ramifications of multiple occurrences, or series, of convective weather systems are presented and discussed. The temporal and spatial characteristics of the accumulated precipitation from a series of convective complexes is investigated and compared to that of Hurricane Alicia.It is found that mesoscale convective weather systems account for approximately 30% to 70% of the warm-season (April-September) precipitation over much of the region between the Rocky Mountains and the Mississippi River. During the June through August period, their contribution is even larger. Moreover, series of convective weather systems are very likely the most prolific precipitation producer in the United States, rivaling and even exceeding that of hurricanes.Changes in the large-scale circulation patterns affected the seasonal precipitation from mesoscale convective weather systems by altering the precipitation characteristics of individual systems. In particular, for the drought period of 1983, the frequency of the convective systems remained nearly the same as in the `normal' year (1982); however, the average precipitation area and the average volumetric production significantly decreased. Nevertheless, the rainfall that was produced by mesoscale convective weather systems in the drought year accounted for most of the precipitation received during the critical crop growth period.It is concluded that mesoscale convective weather systems may be a crucial precipitation-producing deterrent to drought and an important mechanism for enhancing midsummer crop growth throughout the midwestern United States. Furthermore, because mesoscale convective weather systems account for such a large fraction of the warm-season precipitation, significant improvements in prediction of such systems would likely translate into significant improvements in quantitative precipitation forecast skill and corresponding improvements in hydrologic forecasts of runoff.

Linking Low-Frequency Large-Scale Circulation Patterns to Cold Air Outbreak Formation in the Northeastern North Atlantic

NASA Astrophysics Data System (ADS)

Papritz, L.; Grams, C. M.

2018-03-01

The regional variability of wintertime marine cold air outbreaks (CAOs) in the northeastern North Atlantic is studied focusing on the role of weather regimes in modulating the large-scale circulation. Each regime is characterized by a typical CAO frequency anomaly pattern and a corresponding imprint in air-sea heat fluxes. Cyclonically dominated regimes, Greenland blocking and the Atlantic ridge regime are found to provide favorable conditions for CAO formation in at least one major sea of the study region; CAO occurrence is suppressed, however, by blocked regimes whose associated anticyclones are centered over northern Europe (European / Scandinavian blocking). Kinematic trajectories reveal that strength and location of the storm tracks are closely linked to the pathways of CAO air masses and, thus, CAO occurrence. Finally, CAO frequencies are also linked to the strength of the stratospheric polar vortex, which is understood in terms of associated variations in the frequency of weather regimes.

Developing New Strategies for Coping with Weather: Work in Alaskan and Canadian Coastal Communities

NASA Astrophysics Data System (ADS)

Atkinson, D. E.

2014-12-01

A changing climate is manifested at ground level through the day to day weather. For all Northern residents - community, industrial, operational and response - the need to think about the weather is ever present. Northern residents, and in particular, indigenous community residents, fully understand implications of the weather, however, a comment that has been heard more often is that old ways of knowing are not as reliable as they once were. Weather patterns seem less consistent and subject to more rapid fluctuations. Compromised traditional ways of knowing puts those who need to travel or hunt at greater risk. One response to adapt to this emerging reality is to make greater use of western sources of information, such as weather data and charts provided by NOAA's National Weather Service or Environment Canada. The federal weather agencies have very large and complex forecasting regions to cover, and so one problem is that it can be difficult to provide perfectly tailored forecasts, that cover all possible problems, right down to the very local scale in the communities. Only those affected have a complete feel for their own concerns. Thus, key to a strategy to improve the utility of available weather information is a linking of local-scale manifestations of problematic weather to the larger-scale weather patterns. This is done in two ways: by direct consultation with Northern residents, and by installation of equipment to measure parameters of interest to residents, which are not already being measured. This talk will overview projects in coastal Alaska and Canada targeting this objective. The challenge of designing and conducting interviews, and then of harvesting relevant information, will be visited using examples from the three major contexts: coastal community, industrial, and operational. Examples of how local comments can be married to weather products will be presented.

Spatio-temporal atmospheric circulation variability around the Antarctic Peninsula based on hemispheric circulation modes and weather types

NASA Astrophysics Data System (ADS)

Wachter, Paul; Beck, Christoph; Philipp, Andreas; Jacobeit, Jucundus; Höppner, Kathrin

2017-04-01

Large parts of the Polar Regions are affected by a warming trend associated with substantial changes in the cryosphere. In Antarctica this positive trend pattern is most dominant in the western part of the continent and on the Antarctic Peninsula (AP). An important driving mechanism of temperature variability and trends in this region is the atmospheric circulation. Changes in atmospheric circulation modes and frequencies of circulation types have major impacts on temperature characteristics at a certain station or region. We present results of a statistical downscaling study focused on AP temperature variability showing both results of large-scale atmospheric circulation modes and regional weather type classifications derived from monthly and daily gridded reanalysis data sets. In order to investigate spatial trends and variabilities of the Southern Annular Mode (SAM), we analyze spatio-temporally resolved SAM-pattern maps from 1979 to 2015. First results show dominant multi-annual to decadal pattern variabilities which can be directly linked to temperature variabilities at the Antarctic Peninsula. A sub-continental to regional view on the influence of atmospheric circulation on AP temperature variability is given by the analysis of weather type classifications (WTC). With this analysis we identify significant changes in the frequency of occurrence of highly temperature-relevant circulation patterns. The investigated characteristics of weather type frequencies can also be related to the identified changes of the SAM.

A case study of the Santa Ana winds in the San Gabriel mountains

Treesearch

Michael A. Fosberg

1965-01-01

Santa Ana wind structure varies between the high main ridges, the foothills, and the canyon bottoms. In each of these regions, a typical pattern characterizes the Santa Ana. Strong steady wind, at the high levels are determined almost completely by the large scale weather patterns. lntermediate canyons and ridges are affected by Santa Ana winds only when the foehn is...

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.

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.

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.

Ability of an ensemble of regional climate models to reproduce weather regimes over Europe-Atlantic during the period 1961-2000

NASA Astrophysics Data System (ADS)

Sanchez-Gomez, Emilia; Somot, S.; Déqué, M.

2009-10-01

One of the main concerns in regional climate modeling is to which extent limited-area regional climate models (RCM) reproduce the large-scale atmospheric conditions of their driving general circulation model (GCM). In this work we investigate the ability of a multi-model ensemble of regional climate simulations to reproduce the large-scale weather regimes of the driving conditions. The ensemble consists of a set of 13 RCMs on a European domain, driven at their lateral boundaries by the ERA40 reanalysis for the time period 1961-2000. Two sets of experiments have been completed with horizontal resolutions of 50 and 25 km, respectively. The spectral nudging technique has been applied to one of the models within the ensemble. The RCMs reproduce the weather regimes behavior in terms of composite pattern, mean frequency of occurrence and persistence reasonably well. The models also simulate well the long-term trends and the inter-annual variability of the frequency of occurrence. However, there is a non-negligible spread among the models which is stronger in summer than in winter. This spread is due to two reasons: (1) we are dealing with different models and (2) each RCM produces an internal variability. As far as the day-to-day weather regime history is concerned, the ensemble shows large discrepancies. At daily time scale, the model spread has also a seasonal dependence, being stronger in summer than in winter. Results also show that the spectral nudging technique improves the model performance in reproducing the large-scale of the driving field. In addition, the impact of increasing the number of grid points has been addressed by comparing the 25 and 50 km experiments. We show that the horizontal resolution does not affect significantly the model performance for large-scale circulation.

Field Studies Delve Into the Intricacies of Mountain Weather

NASA Astrophysics Data System (ADS)

Fernando, Harindra J. S.; Pardyjak, Eric R.

2013-09-01

Mountain meteorology, in particular weather prediction in complex (rugged) terrain, is emerging as an important topic for science and society. Large urban settlements such as Los Angeles, Hong Kong, and Rio de Janeiro have grown within or in the shadow of complex terrain, and managing the air quality of such cities requires a good understanding of the air flow patterns that spill off of mountains. On a daily time scale, the interconnected engineered and natural systems that sustain urban metabolism and quality of life are affected by weather [Fernando, 2010]. Further, recent military engagements in remote mountainous areas have heightened the need for better weather predictions—alpine warfare is considered to be one of the most dangerous types of combat.

ENSO Weather and Coral Bleaching on the Great Barrier Reef, Australia

NASA Astrophysics Data System (ADS)

McGowan, Hamish; Theobald, Alison

2017-10-01

The most devastating mass coral bleaching has occurred during El Niño events, with bleaching reported to be a direct result of increased sea surface temperatures (SSTs). However, El Niño itself does not cause SSTs to rise in all regions that experience bleaching. Nor is the upper ocean warming trend of 0.11°C per decade since 1971, attributed to global warming, sufficient alone to exceed the thermal tolerance of corals. Here we show that weather patterns during El Niño that result in reduced cloud cover, higher than average air temperatures and higher than average atmospheric pressures, play a crucial role in determining the extent and location of coral bleaching on the world's largest coral reef system, the World Heritage Great Barrier Reef (GBR), Australia. Accordingly, synoptic-scale weather patterns and local atmosphere-ocean feedbacks related to El Niño-Southern Oscillation (ENSO) and not large-scale SST warming due to El Niño alone and/or global warming are often the cause of coral bleaching on the GBR.

Extratropical Weather Systems on Mars: Radiatively-Active Water Ice Effects

NASA Technical Reports Server (NTRS)

Hollingsworth, J. L.; Kahre, M. A.; Haberle, R. M.; Urata, R. A.; Montmessin, F.

2017-01-01

Extratropical, large-scale weather disturbances, namely transient, synoptic-period,baroclinic barotropic eddies - or - low- (high-) pressure cyclones (anticyclones), are components fundamental to global circulation patterns for rapidly rotating, differentially heated, shallow atmospheres such as Earth and Mars. Such "wave-like" disturbances that arise via (geophysical) fluid shear instability develop, mature and decay, and travel west-to-east in the middle and high latitudes within terrestrial-like planetary atmospheres. These disturbances serve as critical agents in the transport of heat and momentum between low and high latitudes of the planet. Moreover, they transport trace species within the atmosphere (e.g., water vapor/ice, other aerosols (dust), chemical species, etc). Between early autumn through early spring, middle and high latitudes on Mars exhibit strong equator-to-pole mean temperature contrasts (i.e., "baroclinicity"). Data collected during the Viking era and observations from both the Mars Global Surveyor (MGS) and Mars Reconnaissance Orbiter (MRO) indicate that such strong baroclinicity supports vigorous, large-scale eastward traveling weather systems [Banfield et al., 2004; Barnes et al., 1993]. A good example of traveling weather systems, frontal wave activity and sequestered dust activity from MGS/MOC image analyses is provided in Figure 1 (cf. Wang et al. [2005]). Utilizing an upgraded and evolving version of the NASA Ames Research Center (ARC) Mars global climate model, investigated here are key dynamical and physical aspects of simulated northern hemisphere (NH) large-scale extratropica lweather systems,with and without radiatively-active water ice clouds. Mars Climate Model:

Observation and modelling of urban dew

NASA Astrophysics Data System (ADS)

Richards, Katrina

Despite its relevance to many aspects of urban climate and to several practical questions, urban dew has largely been ignored. Here, simple observations an out-of-doors scale model, and numerical simulation are used to investigate patterns of dewfall and surface moisture (dew + guttation) in urban environments. Observations and modelling were undertaken in Vancouver, B.C., primarily during the summers of 1993 and 1996. Surveys at several scales (0.02-25 km) show that the main controls on dew are weather, location and site configuration (geometry and surface materials). Weather effects are discussed using an empirical factor, FW . Maximum dew accumulation (up to ~ 0.2 mm per night) is seen on nights with moist air and high FW , i.e., cloudless conditions with light winds. Favoured sites are those with high Ysky and surfaces which cool rapidly after sunset, e.g., grass and well insulated roofs. A 1/8-scale model is designed, constructed, and run at an out-of-doors site to study dew patterns in an urban residential landscape which consists of house lots, a street and an open grassed park. The Internal Thermal Mass (ITM) approach is used to scale the thermal inertia of buildings. The model is validated using data from full-scale sites in Vancouver. Patterns in the model agree with those seen at the full-scale, i.e., dew distribution is governed by weather, site geometry and substrate conditions. Correlation is shown between Ysky and surface moisture accumulation. The feasibility of using a numerical model to simulate urban dew is investigated using a modified version of a rural dew model. Results for simple isolated surfaces-a deciduous tree leaf and an asphalt shingle roof-show promise, especially for built surfaces.

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.

Assessment of the Suitability of High Resolution Numerical Weather Model Outputs for Hydrological Modelling in Mountainous Cold Regions

NASA Astrophysics Data System (ADS)

Rasouli, K.; Pomeroy, J. W.; Hayashi, M.; Fang, X.; Gutmann, E. D.; Li, Y.

2017-12-01

The hydrology of mountainous cold regions has a large spatial variability that is driven both by climate variability and near-surface process variability associated with complex terrain and patterns of vegetation, soils, and hydrogeology. There is a need to downscale large-scale atmospheric circulations towards the fine scales that cold regions hydrological processes operate at to assess their spatial variability in complex terrain and quantify uncertainties by comparison to field observations. In this research, three high resolution numerical weather prediction models, namely, the Intermediate Complexity Atmosphere Research (ICAR), Weather Research and Forecasting (WRF), and Global Environmental Multiscale (GEM) models are used to represent spatial and temporal patterns of atmospheric conditions appropriate for hydrological modelling. An area covering high mountains and foothills of the Canadian Rockies was selected to assess and compare high resolution ICAR (1 km × 1 km), WRF (4 km × 4 km), and GEM (2.5 km × 2.5 km) model outputs with station-based meteorological measurements. ICAR with very low computational cost was run with different initial and boundary conditions and with finer spatial resolution, which allowed an assessment of modelling uncertainty and scaling that was difficult with WRF. Results show that ICAR, when compared with WRF and GEM, performs very well in precipitation and air temperature modelling in the Canadian Rockies, while all three models show a fair performance in simulating wind and humidity fields. Representation of local-scale atmospheric dynamics leading to realistic fields of temperature and precipitation by ICAR, WRF, and GEM makes these models suitable for high resolution cold regions hydrological predictions in complex terrain, which is a key factor in estimating water security in western Canada.

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.

Assessing Weather-Yield Relationships in Rice at Local Scale Using Data Mining Approaches

PubMed Central

Delerce, Sylvain; Dorado, Hugo; Grillon, Alexandre; Rebolledo, Maria Camila; Prager, Steven D.; Patiño, Victor Hugo; Garcés Varón, Gabriel; Jiménez, Daniel

2016-01-01

Seasonal and inter-annual climate variability have become important issues for farmers, and climate change has been shown to increase them. Simultaneously farmers and agricultural organizations are increasingly collecting observational data about in situ crop performance. Agriculture thus needs new tools to cope with changing environmental conditions and to take advantage of these data. Data mining techniques make it possible to extract embedded knowledge associated with farmer experiences from these large observational datasets in order to identify best practices for adapting to climate variability. We introduce new approaches through a case study on irrigated and rainfed rice in Colombia. Preexisting observational datasets of commercial harvest records were combined with in situ daily weather series. Using Conditional Inference Forest and clustering techniques, we assessed the relationships between climatic factors and crop yield variability at the local scale for specific cultivars and growth stages. The analysis showed clear relationships in the various location-cultivar combinations, with climatic factors explaining 6 to 46% of spatiotemporal variability in yield, and with crop responses to weather being non-linear and cultivar-specific. Climatic factors affected cultivars differently during each stage of development. For instance, one cultivar was affected by high nighttime temperatures in the reproductive stage but responded positively to accumulated solar radiation during the ripening stage. Another was affected by high nighttime temperatures during both the vegetative and reproductive stages. Clustering of the weather patterns corresponding to individual cropping events revealed different groups of weather patterns for irrigated and rainfed systems with contrasting yield levels. Best-suited cultivars were identified for some weather patterns, making weather-site-specific recommendations possible. This study illustrates the potential of data mining for adding value to existing observational data in agriculture by allowing embedded knowledge to be quickly leveraged. It generates site-specific information on cultivar response to climatic factors and supports on-farm management decisions for adaptation to climate variability. PMID:27560980

Assessing Weather-Yield Relationships in Rice at Local Scale Using Data Mining Approaches.

PubMed

Delerce, Sylvain; Dorado, Hugo; Grillon, Alexandre; Rebolledo, Maria Camila; Prager, Steven D; Patiño, Victor Hugo; Garcés Varón, Gabriel; Jiménez, Daniel

2016-01-01

Seasonal and inter-annual climate variability have become important issues for farmers, and climate change has been shown to increase them. Simultaneously farmers and agricultural organizations are increasingly collecting observational data about in situ crop performance. Agriculture thus needs new tools to cope with changing environmental conditions and to take advantage of these data. Data mining techniques make it possible to extract embedded knowledge associated with farmer experiences from these large observational datasets in order to identify best practices for adapting to climate variability. We introduce new approaches through a case study on irrigated and rainfed rice in Colombia. Preexisting observational datasets of commercial harvest records were combined with in situ daily weather series. Using Conditional Inference Forest and clustering techniques, we assessed the relationships between climatic factors and crop yield variability at the local scale for specific cultivars and growth stages. The analysis showed clear relationships in the various location-cultivar combinations, with climatic factors explaining 6 to 46% of spatiotemporal variability in yield, and with crop responses to weather being non-linear and cultivar-specific. Climatic factors affected cultivars differently during each stage of development. For instance, one cultivar was affected by high nighttime temperatures in the reproductive stage but responded positively to accumulated solar radiation during the ripening stage. Another was affected by high nighttime temperatures during both the vegetative and reproductive stages. Clustering of the weather patterns corresponding to individual cropping events revealed different groups of weather patterns for irrigated and rainfed systems with contrasting yield levels. Best-suited cultivars were identified for some weather patterns, making weather-site-specific recommendations possible. This study illustrates the potential of data mining for adding value to existing observational data in agriculture by allowing embedded knowledge to be quickly leveraged. It generates site-specific information on cultivar response to climatic factors and supports on-farm management decisions for adaptation to climate variability.

It's the Physics: Organized Complexity in the Arctic/Midlatitude Weather Controversy

NASA Astrophysics Data System (ADS)

Overland, J. E.; Francis, J. A.; Wang, M.

2017-12-01

There is intense scientific and public interest in whether major Arctic changes can and will impact mid-latitude weather. Despite numerous workshops and a growing literature, convergence of understanding is lacking, with major objections about possible large impacts within the scientific community. Yet research on the Arctic as a new potential driver in improving subseasonal forecasting at midlatitudes remains a priority. A recent review laid part of the controversy on shortcomings in experimental design and ill-suited metrics, such as examining the influence of only sea-ice loss rather than overall Arctic temperature amplification, and/or calculating averages over large regions, long time periods, or many ensemble members that would tend to obscure event-like Arctic connections. The present analysis lays the difficulty at a deeper level owing to the inherently complex physics. Jet-stream dynamics and weather linkages on the scale of a week to months has characteristics of an organized complex system, with large-scale processes that operate in patterned, quasi-geostrophic ways but whose component feedbacks are continually changing. Arctic linkages may be state dependent, i.e., relationships may be more robust in one atmospheric wave pattern than another, generating intermittency. The observational network is insufficient to fully initialize such a system and the inherent noise obscures linkage signals, leading to an underdetermined problem; often more than one explanation can fit the data. Further, the problem may be computationally irreducible; the only way to know the result of these interactions is to trace out their path over time. Modeling is a suggested approach, but at present it is unclear whether previous model studies fully resolve anticipated complexity. The jet stream from autumn to early winter is characterized by non-linear interactions among enhanced atmospheric planetary waves, irregular transitions between the zonal and meridional flows, and the maintenance of atmospheric blocks (near stationary large amplitude atmospheric waves). For weather forecast improvement, but not necessarily to elucidate mechanism of linkages, a Numerical Weather Prediction (NWP) approach is appropriate; such is the plan for the upcoming Year of Polar Prediction (YOPP).

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.

The contribution of changes in P release and CO2 consumption by chemical weathering to the historical trend in land carbon uptake

NASA Astrophysics Data System (ADS)

Goodale, C. L.; Fredriksen, G.; McCalley, C. K.; Sparks, J. P.; Thomas, S. A.

2011-12-01

The atmospheric carbon dioxide (CO2) concentration has increased to a level unprecedented in the last 2 million years, and the concentration is projected to increase further with a rate unseen in geological past. The increase in CO2 cause a rise in surface temperatures and changes in the hydrological cycle through the redistribution of rainfall patterns. All of these changes will impact the weathering of rocks, which in turn affect atmospheric CO2 concentrations via two different pathways. On the one hand, CO2 is consumed by the dissolution reaction of the exposed minerals. And on the other hand, biological CO2 fixation is affected due to changes in phosphorus release from minerals, as biological activity is constrained by phosphorus availability at large scales. The traditional view is that both effects are negligible on a centennial time scale, but recent work on catchment scale challenge this view in favor of a potential high sensitivity of weathering to ongoing climate and land use changes. To globally quantify the contribution of CO2 fixation associated with weathering on the historical trend in terrestrial CO2 uptake, we applied a model of chemical weathering and phosphorus release under climate reconstructions from four Earth System Models. The simulations indicate that changes in weathering could have contributed considerably to the trend in terrestrial CO2 uptake since the pre-industrial revolution, with warming being the main driver of change. The increase in biological CO2 fixation is of comparable magnitude as the increase in CO2 consumption by chemical weathering. Our simulations support the previous findings on catchment scale that weathering can change significantly on a centennial time scale. This finding has implications for 21st century climate projections, which ignore changes in weathering, as well as for long-term airborne fraction of CO2 emissions, whose calculation usually neglects changes in phosphorus availability.

The contribution of changes in P release and CO2 consumption by chemical weathering to the historical trend in land carbon uptake

NASA Astrophysics Data System (ADS)

Goll, D. S.; Moosdorf, N.; Brovkin, V.; Hartmann, J.

2013-12-01

The atmospheric carbon dioxide (CO2) concentration has increased to a level unprecedented in the last 2 million years, and the concentration is projected to increase further with a rate unseen in geological past. The increase in CO2 cause a rise in surface temperatures and changes in the hydrological cycle through the redistribution of rainfall patterns. All of these changes will impact the weathering of rocks, which in turn affect atmospheric CO2 concentrations via two different pathways. On the one hand, CO2 is consumed by the dissolution reaction of the exposed minerals. And on the other hand, biological CO2 fixation is affected due to changes in phosphorus release from minerals, as biological activity is constrained by phosphorus availability at large scales. The traditional view is that both effects are negligible on a centennial time scale, but recent work on catchment scale challenge this view in favor of a potential high sensitivity of weathering to ongoing climate and land use changes. To globally quantify the contribution of CO2 fixation associated with weathering on the historical trend in terrestrial CO2 uptake, we applied a model of chemical weathering and phosphorus release under climate reconstructions from four Earth System Models. The simulations indicate that changes in weathering could have contributed considerably to the trend in terrestrial CO2 uptake since the pre-industrial revolution, with warming being the main driver of change. The increase in biological CO2 fixation is of comparable magnitude as the increase in CO2 consumption by chemical weathering. Our simulations support the previous findings on catchment scale that weathering can change significantly on a centennial time scale. This finding has implications for 21st century climate projections, which ignore changes in weathering, as well as for long-term airborne fraction of CO2 emissions, whose calculation usually neglects changes in phosphorus availability.

Atlantic multi-decadal oscillation influence on weather regimes over Europe and the Mediterranean in spring and summer

NASA Astrophysics Data System (ADS)

Zampieri, M.; Toreti, A.; Schindler, A.; Scoccimarro, E.; Gualdi, S.

2017-04-01

We analyze the influence of the Atlantic sea surface temperature multi-decadal variability on the day-by-day sequence of large-scale atmospheric circulation patterns (i.e. the ;weather regimes;) over the Euro-Atlantic region. In particular, we examine of occurrence of weather regimes from 1871 to present. This analysis is conducted by applying a clustering technique on the daily mean sea level pressure field provided by the 20th Century Reanalysis project, which was successfully applied in other studies focused on the Atlantic Multi-decadal Oscillation (AMO). In spring and summer, results show significant changes in the frequencies of certain weather regimes associated with the phase shifts of the AMO. These changes are consistent with the seasonal surface pressure, precipitation, and temperature anomalies associated with the AMO shifts in Europe.

Analysis of the ability of large-scale reanalysis data to define Siberian fire danger in preparation for future fire prediction

NASA Astrophysics Data System (ADS)

Soja, Amber; Westberg, David; Stackhouse, Paul, Jr.; McRae, Douglas; Jin, Ji-Zhong; Sukhinin, Anatoly

2010-05-01

Fire is the dominant disturbance that precipitates ecosystem change in boreal regions, and fire is largely under the control of weather and climate. Fire frequency, fire severity, area burned and fire season length are predicted to increase in boreal regions under current climate change scenarios. Therefore, changes in fire regimes have the potential to compel ecological change, moving ecosystems more quickly towards equilibrium with a new climate. The ultimate goal of this research is to assess the viability of large-scale (1°) data to be used to define fire weather danger and fire regimes, so that large-scale data can be confidently used to predict future fire regimes using large-scale fire weather data, like that available from current Intergovernmental Panel on Climate Change (IPCC) climate change scenarios. In this talk, we intent to: (1) evaluate Fire Weather Indices (FWI) derived using reanalysis and interpolated station data; (2) discuss the advantages and disadvantages of using these distinct data sources; and (3) highlight established relationships between large-scale fire weather data, area burned, active fires and ecosystems burned. Specifically, the Canadian Forestry Service (CFS) Fire Weather Index (FWI) will be derived using: (1) NASA Goddard Earth Observing System version 4 (GEOS-4) large-scale reanalysis and NASA Global Precipitation Climatology Project (GPCP) data; and National Climatic Data Center (NCDC) surface station-interpolated data. Requirements of the FWI are local noon surface-level air temperature, relative humidity, wind speed, and daily (noon-noon) rainfall. GEOS-4 reanalysis and NCDC station-interpolated fire weather indices are generally consistent spatially, temporally and quantitatively. Additionally, increased fire activity coincides with increased FWI ratings in both data products. Relationships have been established between large-scale FWI to area burned, fire frequency, ecosystem types, and these can be use to estimate historic and future fire regimes.

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 %.

Cloud Properties under Different Synoptic Circulations: Comparison of Radiosonde and Ground-Based Active Remote Sensing Measurements

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

Zhang, Jinqiang; Li, Jun; Xia, Xiangao

In this study, long-term (10 years) radiosonde-based cloud data are compared with the ground-based active remote sensing product under six prevailing large-scale synoptic patterns, i.e., cyclonic center (CC), weak pressure pattern (WP), the southeast bottom of cyclonic center (CB), cold front (CF), anticyclone edge (AE) and anticyclone center (AC) over the Southern Great Plains (SGP) site. The synoptic patterns are generated by applying the self-organizing map weather classification method to the daily National Centers for Environmental Protection mean sea level pressure records from the North American Regional Reanalysis. It reveals that the large-scale synoptic circulations can strongly influence the regionalmore » cloud formation, and thereby have impact on the consistency of cloud retrievals from the radiosonde and ground-based cloud product. The total cloud cover at the SGP site is characterized by the least in AC and the most in CF. The minimum and maximum differences between the two cloud methods are 10.3% for CC and 13.3% for WP. Compared to the synoptic patterns characterized by scattered cloudy and clear skies (AE and AC), the agreement of collocated cloud boundaries between the two cloud approaches tends to be better under the synoptic patterns dominated by overcast and cloudy skies (CC, WP and CB). The rainy and windy weather conditions in CF synoptic pattern influence the consistency of the two cloud retrieval methods associated with the limited capabilities inherent to the instruments. As a result, the cloud thickness distribution from the two cloud datasets compares favorably with each other in all synoptic patterns, with relative discrepancy of ≤0.3 km.« less

Cloud Properties under Different Synoptic Circulations: Comparison of Radiosonde and Ground-Based Active Remote Sensing Measurements

DOE PAGES

Zhang, Jinqiang; Li, Jun; Xia, Xiangao; ...

2016-11-28

In this study, long-term (10 years) radiosonde-based cloud data are compared with the ground-based active remote sensing product under six prevailing large-scale synoptic patterns, i.e., cyclonic center (CC), weak pressure pattern (WP), the southeast bottom of cyclonic center (CB), cold front (CF), anticyclone edge (AE) and anticyclone center (AC) over the Southern Great Plains (SGP) site. The synoptic patterns are generated by applying the self-organizing map weather classification method to the daily National Centers for Environmental Protection mean sea level pressure records from the North American Regional Reanalysis. It reveals that the large-scale synoptic circulations can strongly influence the regionalmore » cloud formation, and thereby have impact on the consistency of cloud retrievals from the radiosonde and ground-based cloud product. The total cloud cover at the SGP site is characterized by the least in AC and the most in CF. The minimum and maximum differences between the two cloud methods are 10.3% for CC and 13.3% for WP. Compared to the synoptic patterns characterized by scattered cloudy and clear skies (AE and AC), the agreement of collocated cloud boundaries between the two cloud approaches tends to be better under the synoptic patterns dominated by overcast and cloudy skies (CC, WP and CB). The rainy and windy weather conditions in CF synoptic pattern influence the consistency of the two cloud retrieval methods associated with the limited capabilities inherent to the instruments. As a result, the cloud thickness distribution from the two cloud datasets compares favorably with each other in all synoptic patterns, with relative discrepancy of ≤0.3 km.« less

Evaluation of the synoptic and mesoscale predictive capabilities of a mesoscale atmospheric simulation system

NASA Technical Reports Server (NTRS)

Koch, S. E.; Skillman, W. C.; Kocin, P. J.; Wetzel, P. J.; Brill, K.; Keyser, D. A.; Mccumber, M. C.

1983-01-01

The overall performance characteristics of a limited area, hydrostatic, fine (52 km) mesh, primitive equation, numerical weather prediction model are determined in anticipation of satellite data assimilations with the model. The synoptic and mesoscale predictive capabilities of version 2.0 of this model, the Mesoscale Atmospheric Simulation System (MASS 2.0), were evaluated. The two part study is based on a sample of approximately thirty 12h and 24h forecasts of atmospheric flow patterns during spring and early summer. The synoptic scale evaluation results benchmark the performance of MASS 2.0 against that of an operational, synoptic scale weather prediction model, the Limited area Fine Mesh (LFM). The large sample allows for the calculation of statistically significant measures of forecast accuracy and the determination of systematic model errors. The synoptic scale benchmark is required before unsmoothed mesoscale forecast fields can be seriously considered.

Objective Use of Climate Indices to Inform Ensemble Streamflow Forecasts in the Columbia River Basin - An Initial Review

NASA Astrophysics Data System (ADS)

Pytlak, E.; McManamon, A.; Hughes, S. P.; Van Der Zweep, R. A.; Butcher, P.; Karafotias, C.; Beckers, J.; Welles, E.

2016-12-01

Numerous studies have documented the impacts that large scale weather patterns and climate phenomenon like the El Niño Southern Oscillation (ENSO), Pacific-North American (PNA) Pattern, and others can have on seasonal temperature and precipitation in the Columbia River Basin (CRB). While far from perfect in terms of seasonal predictability in specific locations, these intra-annual weather and climate signal do tilt the odds toward different temperature and precipitation outcomes, which in turn can have impacts on seasonal snowpacks, streamflows and water supply in large river basins like the CRB. We hypothesize that intraseasonal climate signals and long wave jet stream patterns can be objectively incorporated into what it is otherwise a climatology-based set of Ensemble Streamflow Forecasts, and can increase the predictive skill and utility of these forecasts used for mid-range hydropower planning. The Bonneville Power Administration (BPA) and Deltares have developed a subsampling-resampling method to incorporate climate mode information into the Ensemble Streamflow Prediction (ESP) forecasts (Beckers, et al., 2016). Since 2015, BPA and Deltares USA have experimented with this method in pre-operational use, using five objective multivariate climate indices that appear to have the greatest predictive value for seasonal temperature and precipitation in the CRB. The indices are used to objectively select historical weather from about twenty analog years in the 66-year (1949-2015) historical ESP set. These twenty scenarios then serve as the starting point to generate monthly synthetic weather and streamflow time series to return to a set of 66 streamflow traces. Our poster will share initial results from the 2015 and 2016 water years, which included large swings in the Quasi-Biennial Oscillation, persistent blocking jet stream patterns, and the development of a strong El Niño event. While the results are very preliminary and for only two seasons, there may be some value in incorporating objectively-identified climate signals into ESP-based streamflow forecasts.Beckers, J. V. L., Weerts, A. H., Tijdeman, E., and Welles, E.: ENSO-Conditioned Weather Resampling Method for Seasonal Ensemble Streamflow Prediction, Hydrol. Earth Syst. Sci. Discuss., doi:10.5194/hess-2016-72, in review, 2016.

Simulation and thermal imaging of the 2006 Esperanza Wildfire in southern California: application of a coupled weather-wildland fire model

Treesearch

Janice L. Coen; Philip J Riggan

2014-01-01

The 2006 Esperanza Fire in Riverside County, California, was simulated with the Coupled Atmosphere-Wildland Fire Environment (CAWFE) model to examine how dynamic interactions of the atmosphere with large-scale fire spread and energy release may affect observed patterns of fire behavior as mapped using the FireMapper thermal imaging radiometer. CAWFE simulated the...

Rocks and Rain: orographic precipitation and the form of mountain ranges

NASA Astrophysics Data System (ADS)

Roe, G. H.; Anders, A. M.; Durran, D. R.; Montgomery, D. R.; Hallet, B.

2005-12-01

In mountainous landscapes patterns of erosion reflect patterns of precipitation that are, in turn, controlled by the orography. Ultimately therefore, the feedbacks between orography and the climate it creates are responsible for the sculpting of mountain ranges. Key questions concerning these interactions are: 1) how robust are patterns of precipitation on geologic time scales? and 2) how do those patterns affect landscape form? Since climate is by definition the statistics of weather, there is tremendous information to be gleaned from how patterns of precipitation vary between different weather events. However up to now sparse measurements and computational limitations have hampered our knowledge of such variations. For the Olympics in Washington State, a characteristic midlatitude mountain range, we report results from a high-resolution, state-of-the-art numerical weather prediction model and a dense network of precipitation gauges. Down to scales around 10 km, the patterns of precipitation are remarkably robust both storm-by-storm and year-to-year, lending confidence that they are indeed persistent on the relevant time scales. Secondly, the consequences of the coupled interactions are presented using a landscape evolution model coupled with a simple model of orographic precipitation that is able to substantially reproduce the observed precipitation patterns.

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.

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.

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.

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.

A comparative analysis of rawinsonde and NIMBUS 6 and TIROS N satellite profile data

NASA Technical Reports Server (NTRS)

Scoggins, J. R.; Carle, W. E.; Knight, K.; Moyer, V.; Cheng, N. M.

1981-01-01

Comparisons are made between rawinsonde and satellite profiles in seven areas for a wide range of surface and weather conditions. Variables considered include temperature, dewpoint temperature, thickness, precipitable water, lapse rate of temperature, stability, geopotential height, mixing ratio, wind direction, wind speed, and kinematic parameters, including vorticity and the advection of vorticity and temperature. In addition, comparisons are made in the form of cross sections and synoptic fields for selected variables. Sounding data from the NIMBUS 6 and TIROS N satellites were used. Geostrophic wind computed from smoothed geopotential heights provided large scale flow patterns that agreed well with the rawinsonde wind fields. Surface wind patterns as well as magnitudes computed by use of the log law to extrapolate wind to a height of 10 m agreed with observations. Results of this study demonstrate rather conclusively that satellite profile data can be used to determine characteristics of large scale systems but that small scale features, such as frontal zones, cannot yet be resolved.

Frequency analyses for recent regional floods in the United States

USGS Publications Warehouse

Melcher, Nick B.; Martinez, Patsy G.; ,

1996-01-01

During 1993-95, significant floods that resulted in record-high river stages, loss of life, and significant property damage occurred in the United States. The floods were caused by unique global weather patterns that produced large amounts of rain over large areas. Standard methods for flood-frequency analyses may not adequately consider the probability of recurrence of these global weather patterns.

Pattern recognition of satellite cloud imagery for improved weather prediction

NASA Technical Reports Server (NTRS)

Gautier, Catherine; Somerville, Richard C. J.; Volfson, Leonid B.

1986-01-01

The major accomplishment was the successful development of a method for extracting time derivative information from geostationary meteorological satellite imagery. This research is a proof-of-concept study which demonstrates the feasibility of using pattern recognition techniques and a statistical cloud classification method to estimate time rate of change of large-scale meteorological fields from remote sensing data. The cloud classification methodology is based on typical shape function analysis of parameter sets characterizing the cloud fields. The three specific technical objectives, all of which were successfully achieved, are as follows: develop and test a cloud classification technique based on pattern recognition methods, suitable for the analysis of visible and infrared geostationary satellite VISSR imagery; develop and test a methodology for intercomparing successive images using the cloud classification technique, so as to obtain estimates of the time rate of change of meteorological fields; and implement this technique in a testbed system incorporating an interactive graphics terminal to determine the feasibility of extracting time derivative information suitable for comparison with numerical weather prediction products.

A Study into the Impact of Physical Structures on the Runway Velocity Field at the Atlantic City International Airport

NASA Astrophysics Data System (ADS)

King, David, Jr.; Manson, Russell; Trout, Joseph; Decicco, Nicholas; Rios, Manny

2015-04-01

Wake vortices are generated by airplanes in flight. These vortices decay slowly and may persist for several minutes after their creation. These vortices and associated smaller scale turbulent structures present a hazard to incoming flights. It is for this reason that incoming flights are timed to arrive after these vortices have dissipated. Local weather conditions, mainly prevailing winds, can affect the transport and evolution of these vortices; therefore, there is a need to fully understand localized wind patterns at the airport-sized mircoscale. Here we have undertaken a computational investigation into the impacts of localized wind flows and physical structures on the velocity field at Atlantic City International Airport. The simulations are undertaken in OpenFOAM, an open source computational fluid dynamics software package, using an optimized geometric mesh of the airport. Initial conditions for the simulations are based on historical data with the option to run simulations based on projected weather conditions imported from the Weather Research & Forcasting (WRF) Model. Sub-grid scale turbulence is modeled using a Large Eddy Simulation (LES) approach. The initial results gathered from the WRF Model simulations and historical weather data analysis are presented elsewhere.

Surface temperature patterns in complex terrain: Daily variations and long-term change in the central Sierra Nevada, California

USGS Publications Warehouse

Lundquist, J.D.; Cayan, D.R.

2007-01-01

A realistic description of how temperatures vary with elevation is crucial for ecosystem studies and for models of basin-scale snowmelt and spring streamflow. This paper explores surface temperature variability using temperature data from an array of 37 sensors, called the Yosemite network, which traverses both slopes of the Sierra Nevada in the vicinity of Yosemite National Park, California. These data indicate that a simple lapse rate is often a poor description of the spatial temperature structure. Rather, the spatial pattern of temperature over the Yosemite network varies considerably with synoptic conditions. Empirical orthogonal functions (EOFs) were used to identify the dominant spatial temperature patterns and how they vary in time. Temporal variations of these surface temperature patterns were correlated with large-scale weather conditions, as described by National Centers for Environmental Prediction-National Center for Atmospheric Research Reanalysis data. Regression equations were used to downscale larger-scale weather parameters, such as Reanalysis winds and pressure, to the surface temperature structure over the Yosemite network. These relationships demonstrate that strong westerly winds are associated with relatively warmer temperatures on the east slope and cooler temperatures on the west slope of the Sierra, and weaker westerly winds are associated with the opposite pattern. Reanalysis data from 1948 to 2005 indicate weakening westerlies over this time period, a trend leading to relatively cooler temperatures on the east slope over decadal timescale's. This trend also appears in long-term observations and demonstrates the need to consider topographic effects when examining long-term changes in mountain regions. Copyright 2007 by the American Geophysical Union.

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...

From the clouds to the ground - snow precipitation patterns vs. snow accumulation patterns

NASA Astrophysics Data System (ADS)

Gerber, Franziska; Besic, Nikola; Mott, Rebecca; Gabella, Marco; Germann, Urs; Bühler, Yves; Marty, Mauro; Berne, Alexis; Lehning, Michael

2017-04-01

Knowledge about snow distribution and snow accumulation patterns is important and valuable for different applications such as the prediction of seasonal water resources or avalanche forecasting. Furthermore, accumulated snow on the ground is an important ground truth for validating meteorological and climatological model predictions of precipitation in high mountains and polar regions. Snow accumulation patterns are determined by many different processes from ice crystal nucleation in clouds to snow redistribution by wind and avalanches. In between, snow precipitation undergoes different dynamical and microphysical processes, such as ice crystal growth, aggregation and riming, which determine the growth of individual particles and thereby influence the intensity and structure of the snowfall event. In alpine terrain the interaction of different processes and the topography (e.g. lifting condensation and low level cloud formation, which may result in a seeder-feeder effect) may lead to orographic enhancement of precipitation. Furthermore, the redistribution of snow particles in the air by wind results in preferential deposition of precipitation. Even though orographic enhancement is addressed in numerous studies, the relative importance of micro-physical and dynamically induced mechanisms on local snowfall amounts and especially snow accumulation patterns is hardly known. To better understand the relative importance of different processes on snow precipitation and accumulation we analyze snowfall and snow accumulation between January and March 2016 in Davos (Switzerland). We compare MeteoSwiss operational weather radar measurements on Weissfluhgipfel to a spatially continuous snow accumulation map derived from airborne digital sensing (ADS) snow height for the area of Dischma valley in the vicinity of the weather radar. Additionally, we include snow height measurements from automatic snow stations close to the weather radar. Large-scale radar snow accumulation patterns show a snowfall gradient consistent with the prevailing wind direction. Deriving snow accumulation based on radar data is challenging as the close-ground precipitation patters cannot be resolved by the radar due to shielding and ground clutter in highly complex terrain. Nonetheless, radar measurements show distinct patterns of snowfall and accumulation, which may be the result of orographic enhancement. Station-based snow accumulation measurements are in reasonable agreement with the estimated large-scale radar snow accumulation. The ADS-based snow accumulation maps feature much smaller scale snow accumulation patterns likely due to close-ground wind effects and snow redistribution on top of an altitudinal gradient. To evaluate microphysical processes and patterns influenced by the topography we run a hydrometeor classification on the radar data. The relative importance of topographically induced effects on snow accumulation patterns is investigated based on vertical cross sections of hydrometeor data and corresponding snow accumulation.

Importance of the Gulf of Mexico as a climate driver for U.S. severe thunderstorm activity

NASA Astrophysics Data System (ADS)

Molina, M. J.; Timmer, R. P.; Allen, J. T.

2016-12-01

Different features of the Gulf of Mexico (GOM), such as the Loop Current and warm-core rings, are found to influence monthly-to-seasonal severe weather occurrence in different regions of the United States (U.S.). The warmer (cooler) the GOM sea surface temperatures, the more (less) hail and tornadoes occur during March-May over the southern U.S. This pattern is reflected physically in boundary layer specific humidity and mixed-layer convective available potential energy, two large-scale atmospheric conditions favorable for severe weather occurrence. This relationship is complicated by interactions between the GOM and El Niño-Southern Oscillation (ENSO) but persists when analyzing ENSO neutral conditions. This suggests that the GOM can influence hail and tornado occurrence and provides another source of regional predictability for seasonal severe weather.

Links between teleconnection patterns and mean temperature in Spain

NASA Astrophysics Data System (ADS)

Ríos-Cornejo, David; Penas, Ángel; Álvarez-Esteban, Ramón; del Río, Sara

2015-10-01

This work describes the relationships between Spanish temperature and four teleconnection patterns with influence on the Iberian Peninsula on monthly, seasonal and annual time scales, using data from 144 meteorological stations. Partial correlation analyses were carried out using Spearman test, and spatial distribution maps of the correlation coefficients were produced with geostatistical interpolation techniques. We regionalize the study area based on homogeneous areas containing weather stations with a similar response of temperatures to the same patterns. The links between the temperature and the patterns are mainly positive; only the correlations with Western Mediterranean Oscillation (WeMO) in the north and west are negative, indicating that WeMO plays an opposed role in temperature behaviour in Spain. In general terms, the four modes exert considerable influence on temperature in February, May and September. The East Atlantic (EA) is the pattern with the strongest influence on temperature in Spain—mainly in the north—except in June. Generally, on the seasonal and annual scales, large significant areas were only observed for the EA. EA and WeMO best account for the mean temperature on the Mediterranean fringe and in northern Spain, while EA and North Atlantic Oscillation largely explain the temperature in the rest of Spain.

Synoptic-scale circulation patterns during summer derived from tree rings in mid-latitude Asia

NASA Astrophysics Data System (ADS)

Seim, Andrea; Schultz, Johannes A.; Leland, Caroline; Davi, Nicole; Byambasuren, Oyunsanaa; Liang, Eryuan; Wang, Xiaochun; Beck, Christoph; Linderholm, Hans W.; Pederson, Neil

2017-09-01

Understanding past and recent climate and atmospheric circulation variability is vital for regions that are affected by climate extremes. In mid-latitude Asia, however, the synoptic climatology is complex and not yet fully understood. The aim of this study was to investigate dominant synoptic-scale circulation patterns during the summer season using a multi-species tree-ring width (TRW) network comprising 78 sites from mid-latitude Asia. For each TRW chronology, we calculated an atmospheric circulation tree-ring index (ACTI), based on 1000 hPa geopotential height data, to directly link tree growth to 13 summertime weather types and their associated local climate conditions for the period 1871-1993. Using the ACTI, three groups of similarly responding tree-ring sites can be associated with distinct large-scale atmospheric circulation patterns: 1. growth of drought sensitive trees is positively affected by a cyclone over northern Russia; 2. temperature sensitive trees show positive associations to a cyclone over northwestern Russia and an anticyclone over Mongolia; 3. trees at two high elevation sites show positive relations to a zonal cyclone extending from mid-latitude Eurasia to the West Pacific. The identified synoptic-scale circulation patterns showed spatiotemporal variability in their intensity and position, causing temporally varying climate conditions in mid-latitude Asia. Our results highlight that for regions with less pronounced atmospheric action centers during summer such as the occurrence of large-scale cyclones and anticyclones, synoptic-scale circulation patterns can be extracted and linked to the Northern Hemisphere circulation system. Thus, we provide a new and solid envelope for climate studies covering the past to the future.

Influence of winter NAO pattern on variable renewable energies potential in Europe over the 20th century

NASA Astrophysics Data System (ADS)

François, Baptiste; Raynaud, Damien; Hingray, Benoit; Creutin, Jean-Dominique

2017-04-01

Integration of Variable Renewable Energy (VRE) sources in the electricity system is a challenge because of temporal and spatial fluctuations of their power generation resulting from their driving weather variables (i.e. solar radiation wind speed, precipitation, and temperature). Very few attention was paid to low frequency variability (i.e. from annual to decades) even though it may have significant impact on energy system and energy market Following the current increase in electricity supplied by VRE generation, one could ask the question about the risk of ending up in a situation in which the level of production of one or more VRE is exceptionally low or exceptionally high for a long period of time and/or over a large area. What would be the risk for an investor if the return on investment has been calculated on a high energy production period? What would be the cost in term of carbon emission whether the system manager needs to turn on coal power plant to satisfy the demand? Such dramatic events would definitely impact future stakeholder decision to invest in a particular energy source or another. Weather low frequency variability is mainly governed by large-scale teleconnection patterns impacting the climate at global scale such as El Niño - Southern Oscillation (ENSO) in the tropics and in North America or the North Atlantic Oscillation (hereafter, NAO) in North America and Europe. Teleconnection pattern's influence on weather variability cascades to VRE variability and ends up by impacting electricity system. The aim of this study is to analysis the impact of the NAO on VRE generation in Europe during the winter season. The analysis is carried out over the twentieth century (i.e. from 1900 to 2010), in order to take into account climate low frequency variability, and for a set of 12 regions covering a large range of climates in Europe. Weather variable time series are obtained by using the ERA20C reanalysis and the SCAMP model (Sequential Constructive Atmospheric Analogues for Multivariate weather Predictions, Raynaud et al. 2016). The analysis is performed for solar, wind and run-of-the river energy sources taken individually. For NAO sensitive regions, results shown important deviations between power generation distributions obtained either for strongly positive or strongly negative NAO events. We also used the optimal VRE combination provided by the 100 % solution project (http://thesolutionsproject.org/). We then discuss over the 12 considered regions the vulnerability to NAO events for the energy mix suggested by the 100 % solution project. Reference: Raynaud, D., Hingray, B., Zin, I., Anquetin, S., Debionne, S., Vautard, R., 2016. Atmospheric analogues for physically consistent scenarios of surface weather in Europe and Maghreb. Int. J. Climatol. doi:10.1002/joc.4844

Characterizing Temperature Variability and Associated Large Scale Meteorological Patterns Across South America

NASA Astrophysics Data System (ADS)

Detzer, J.; Loikith, P. C.; Mechoso, C. R.; Barkhordarian, A.; Lee, H.

2017-12-01

South America's climate varies considerably owing to its large geographic range and diverse topographical features. Spanning the tropics to the mid-latitudes and from high peaks to tropical rainforest, the continent experiences an array of climate and weather patterns. Due to this considerable spatial extent, assessing temperature variability at the continent scale is particularly challenging. It is well documented in the literature that temperatures have been increasing across portions of South America in recent decades, and while there have been many studies that have focused on precipitation variability and change, temperature has received less scientific attention. Therefore, a more thorough understanding of the drivers of temperature variability is critical for interpreting future change. First, k-means cluster analysis is used to identify four primary modes of temperature variability across the continent, stratified by season. Next, composites of large scale meteorological patterns (LSMPs) are calculated for months assigned to each cluster. Initial results suggest that LSMPs, defined using meteorological variables such as sea level pressure (SLP), geopotential height, and wind, are able to identify synoptic scale mechanisms important for driving temperature variability at the monthly scale. Some LSMPs indicate a relationship with known recurrent modes of climate variability. For example, composites of geopotential height suggest that the Southern Annular Mode is an important, but not necessarily dominant, component of temperature variability over southern South America. This work will be extended to assess the drivers of temperature extremes across South America.

Regional severe particle pollution and its association with synoptic weather patterns in the Yangtze River Delta region, China

NASA Astrophysics Data System (ADS)

Shu, Lei; Xie, Min; Gao, Da; Wang, Tijian; Fang, Dexian; Liu, Qian; Huang, Anning; Peng, Liwen

2017-11-01

Regional air pollution is significantly associated with dominant weather systems. In this study, the relationship between the particle pollution over the Yangtze River Delta (YRD) region and weather patterns is investigated. First, the pollution characteristics of particles in the YRD are studied using in situ monitoring data (PM2.5 and PM10) in 16 cities and Terra/MODIS AOD (aerosol optical depth) products collected from December 2013 to November 2014. The results show that the regional mean value of AOD is high in the YRD, with an annual mean value of 0.71±0.57. The annual mean particle concentrations in the cities of Jiangsu Province all exceed the national air quality standard. The pollution level is higher in inland areas, and the highest concentrations of PM2.5 and PM10 are 79 and 130 µg m-3, respectively, in Nanjing. The PM2.5 : PM10 ratios are typically high, thus indicating that PM2.5 is the overwhelmingly dominant particle pollutant in the YRD. The wintertime peak of particle concentrations is tightly linked to the increased emissions during the heating season as well as adverse meteorological conditions. Second, based on NCEP (National Center for Environmental Prediction) reanalysis data, synoptic weather classification is conducted and five typical synoptic patterns are objectively identified. Finally, the synthetic analysis of meteorological fields and backward trajectories are applied to further clarify how these patterns impact particle concentrations. It is demonstrated that air pollution is more or less influenced by high-pressure systems. The relative position of the YRD to the anti-cyclonic circulation exerts significant effects on the air quality of the YRD. The YRD is largely influenced by polluted air masses from the northern and the southern inland areas when it is located at the rear of the East Asian major trough. The significant downward motion of air masses results in stable weather conditions, thereby hindering the diffusion of air pollutants. Thus, this pattern is quite favorable for the accumulation of pollutants in the YRD, resulting in higher regional mean PM10 (116.5 ± 66.9 µg m-3), PM2.5 (75.9 ± 49.9 µg m-3), and AOD (0.74) values. Moreover, this pattern is also responsible for the occurrence of most large-scale regional PM2.5 (70.4 %) and PM10 (78.3 %) pollution episodes. High wind speed and clean marine air masses may also play important roles in the mitigation of pollution in the YRD. Especially when the clean marine air masses account for a large proportion of all trajectories (i.e., when the YRD is affected by the cyclonic system or oceanic circulation), the air in the YRD has a lesser chance of being polluted. The observed correlation between weather patterns and particle pollution can provide valuable insight into making decisions about pollution control and mitigation strategies.

Timing of seasonal migration in mule deer: effects of climate, plant phenology, and life-history characteristics

USGS Publications Warehouse

Monteith, Kevin L.; Bleich, Vernon C.; Stephenson, Thomas R.; Pierce, Beck M.; Conner, Mary M.; Klaver, Robert W.; Bowyer, R. Terry

2011-01-01

Phenological events of plants and animals are sensitive to climatic processes. Migration is a life-history event exhibited by most large herbivores living in seasonal environments, and is thought to occur in response to dynamics of forage and weather. Decisions regarding when to migrate, however, may be affected by differences in life-history characteristics of individuals. Long-term and intensive study of a population of mule deer (Odocoileus hemionus) in the Sierra Nevada, California, USA, allowed us to document patterns of migration during 11 years that encompassed a wide array of environmental conditions. We used two new techniques to properly account for interval-censored data and disentangle effects of broad-scale climate, local weather patterns, and plant phenology on seasonal patterns of migration, while incorporating effects of individual life-history characteristics. Timing of autumn migration varied substantially among individual deer, but was associated with the severity of winter weather, and in particular, snow depth and cold temperatures. Migratory responses to winter weather, however, were affected by age, nutritional condition, and summer residency of individual females. Old females and those in good nutritional condition risked encountering severe weather by delaying autumn migration, and were thus risk-prone with respect to the potential loss of foraging opportunities in deep snow compared with young females and those in poor nutritional condition. Females that summered on the west side of the crest of the Sierra Nevada delayed autumn migration relative to east-side females, which supports the influence of the local environment on timing of migration. In contrast, timing of spring migration was unrelated to individual life-history characteristics, was nearly twice as synchronous as autumn migration, differed among years, was related to the southern oscillation index, and was influenced by absolute snow depth and advancing phenology of plants. Plasticity in timing of migration in response to climatic conditions and plant phenology may be an adaptive behavioral strategy, which should reduce the detrimental effects of trophic mismatches between resources and other life-history events of large herbivores. Failure to consider effects of nutrition and other life-history traits may cloud interpretation of phenological patterns of mammals and conceal relationships associated with climate change.

Weakening of Indian Summer Monsoon Rainfall due to Changes in Land Use Land Cover

PubMed Central

Paul, Supantha; Ghosh, Subimal; Oglesby, Robert; Pathak, Amey; Chandrasekharan, Anita; Ramsankaran, RAAJ

2016-01-01

Weakening of Indian summer monsoon rainfall (ISMR) is traditionally linked with large-scale perturbations and circulations. However, the impacts of local changes in land use and land cover (LULC) on ISMR have yet to be explored. Here, we analyzed this topic using the regional Weather Research and Forecasting model with European Center for Medium range Weather Forecast (ECMWF) reanalysis data for the years 2000–2010 as a boundary condition and with LULC data from 1987 and 2005. The differences in LULC between 1987 and 2005 showed deforestation with conversion of forest land to crop land, though the magnitude of such conversion is uncertain because of the coarse resolution of satellite images and use of differential sources and methods for data extraction. We performed a sensitivity analysis to understand the impacts of large-scale deforestation in India on monsoon precipitation and found such impacts are similar to the observed changes in terms of spatial patterns and magnitude. We found that deforestation results in weakening of the ISMR because of the decrease in evapotranspiration and subsequent decrease in the recycled component of precipitation. PMID:27553384

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.

Diagnosing Possible Anthropogenic Contributions to Heavy Colorado Rainfall in September 2013

NASA Astrophysics Data System (ADS)

Pall, Pardeep; Patricola, Christina; Wehner, Michael; Stone, Dáithí; Paciorek, Christopher; Collins, William

2015-04-01

Unusually heavy rainfall occurred over the Colorado Front Range during early September 2013, with record or near-record totals recorded in several locations. It was associated predominantly with a stationary large-scale weather pattern (akin to the North American Monsoon, which occurs earlier in the year) that drove a strong plume of deep moisture inland from the Gulf of Mexico against the Front Range foothills. The resulting floods across the South Platte River basin impacted several thousands of people and many homes, roads, and businesses. To diagnose possible anthropogenic contributions to the odds of such heavy rainfall, we adapt an existing event attribution paradigm of modelling an 'event that was' for September 2013 and comparing it to a modelled 'event that might have been' for that same time but for the absence of historical anthropogenic drivers of climate. Specifically, we first perform 'event that was' simulations with the regional Weather Research and Forecasting (WRF) model at 12 km resolution over North America, driven by NCEP2 re-analysis. We then re-simulate, having adjusted the re-analysis to 'event that might have been conditions' by modifying atmospheric greenhouse gas and other pollutant concentrations, temperature, humidity, and winds, as well as sea ice coverage, and sea-surface temperatures - all according to estimates from global climate model simulations. Thus our findings are highly conditional on the driving re-analysis and adjustments therein, but the setup allows us to elucidate possible mechanisms responsible for heavy Colorado rainfall in September 2013. Our model results suggests that, given an insignificant change in the pattern of large-scale driving weather, there is an increase in atmospheric water vapour under anthropogenic climate warming leading to a substantial increase in the probability of heavy rainfall occurring over the South Platte River basin in September 2013.

On the linkage between Arctic sea ice and Mid-latitude weather pattern: the situation in East Asia

NASA Astrophysics Data System (ADS)

Gu, S.; Zhang, Y.; Wu, Q.

2017-12-01

The influence of Arctic changes on the weather patterns in the highly populated mid-latitude is a complex and controversial topic with considerable uncertainties such as the low signal-to-noise, ill-suited metrics of circulation changes and the missing of dynamical understanding. In this study, the possible linkage between the Arctic sea ice concentration (SIC) and the wintertime weather patterns in East Asia is investigated by comparing groups of statistical and diagnostic analyses. Our study shows a robust relationship between the early autumn SIC in Barents, Kara, Laptev and East Siberia Sea and the energies of wintertime transient activities corresponding to the weather patterns over East Asia on inter-annual time scales. With the reduction of SIC in autumn, the wintertime synoptic (2-10 day) kinetic energy in the north of Eurasia decreases while the low-frequency (10-30 days) kinetic energy, which corresponds to persistent weather patterns, exhibits an evident and dominant increase over the north of Caspian Sea, Lake Baikal and the Ural Mountain. With the reduction of SIC, the intra-seasonal temperature fluctuations present coherent changes over a broader region as well, with significant increase of the low-frequency variability in the vast north of Tibet Plateau and East Asia. The changes of the low-frequency transient activities may be attributed to the slowly southward propagating wave energies from polar regions. However, no consistent stratosphere signals are found associated with such linkage on inter-annual time scales.

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.

Simulating spatial and temporally related fire weather

Treesearch

Isaac C. Grenfell; Mark Finney; Matt Jolly

2010-01-01

Use of fire behavior models has assumed an increasingly important role for managers of wildfire incidents to make strategic decisions. For fire risk assessments and danger rating at very large spatial scales, these models depend on fire weather variables or fire danger indices. Here, we describe a method to simulate fire weather at a national scale that captures the...

Modeling rock weathering in small watersheds

NASA Astrophysics Data System (ADS)

Pacheco, Fernando A. L.; Van der Weijden, Cornelis H.

2014-05-01

Many mountainous watersheds are conceived as aquifer media where multiple groundwater flow systems have developed (Tóth, 1963), and as bimodal landscapes where differential weathering of bare and soil-mantled rock has occurred (Wahrhaftig, 1965). The results of a weathering algorithm (Pacheco and Van der Weijden, 2012a, 2014), which integrates topographic, hydrologic, rock structure and chemical data to calculate weathering rates at the watershed scale, validated the conceptual models in the River Sordo basin, a small watershed located in the Marão cordillera (North of Portugal). The coupling of weathering, groundwater flow and landscape evolution analyses, as accomplished in this study, is innovative and represents a remarkable achievement towards regionalization of rock weathering at the watershed scale. The River Sordo basin occupies an area of approximately 51.2 km2 and was shaped on granite and metassediment terrains between the altitudes 185-1300 m. The groundwater flow system is composed of recharge areas located at elevations >700 m, identified on the basis of δ18O data. Discharge cells comprehend terminations of local, intermediate and regional flow systems, identified on the basis of spring density patterns, infiltration depth estimates based on 87Sr/86Sr data, and spatial distributions of groundwater pH and natural mineralization. Intermediate and regional flow systems, defined where infiltration depths >125 m, develop solely along the contact zone between granites and metassediments, because fractures in this region are profound and their density is very large. Weathering is accelerated where rocks are covered by thick soils, being five times faster relative to sectors of the basin where rocks are covered by thin soils. Differential weathering of bare and soil-mantled rock is also revealed by the spatial distribution of calculated aquifer hydraulic diffusivities and groundwater travel times.

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.

Temporal and geographic patterns in population trends of brown-headed cowbirds

USGS Publications Warehouse

Peterjohn, B.G.; Sauer, J.R.; Schwarz, S.

2000-01-01

The temporal and geographic patterns in the population trends of Brown-headed Cowbirds are summarized from the North American Breeding Bird Survey. During 1966-1992, the survey-wide population declined significantly, a result of declining populations in the Eastern BBS Region, southern Great Plains, and the Pacific coast states. Increasing populations were most evident in the northern Great Plains. Cowbird populations were generally stable or increasing during 1966-1976, but their trends became more negative after 1976. The trends in cowbird populations were generally directly correlated with the trends of both host and nonhost species, suggesting that large-scale factors such as changing weather patterns, land use practices, or habitat availability were responsible for the observed temporal and geographic patterns in the trends of cowbirds and their hosts.

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.

Diagnostics of Rainfall Anomalies in the Nordeste During the Global Weather Experiment

NASA Technical Reports Server (NTRS)

Sikdar, D. M.

1984-01-01

The relationship of the daily variability of large-scale pressure, cloudiness and upper level wind patterns over the Brazil-Atlantic sector during March/April 1979 to rainfall anomalies in northern Nordeste was investigated. The experiment divides the rainy season (March/April) of 1979 into wet and dry days, then composites bright cloudiness, sea level pressure, and upper level wind fields with respect to persistent rainfall episodes. Wet and dry anomalies are analyzed along with seasonal mean conditions.

The use of fair-weather cases from the ACT-America Summer 2016 field campaign to better constrain regional biogenic CO2 surface fluxes

NASA Astrophysics Data System (ADS)

Gaudet, B. J.; Davis, K. J.; DiGangi, J. P.; Feng, S.; Hoffman, K.; Jacobson, A. R.; Lauvaux, T.; McGill, M. J.; Miles, N.; Pal, S.; Pauly, R.; Richardson, S.

2017-12-01

The Atmospheric Carbon and Transport - America (ACT-America) study is a multi-year NASA-funded project designed to increase our understanding of regional-scale greenhouse gas (GHG) fluxes over North America through aircraft, satellite, and tower-based observations. This is being accomplished through a series of field campaigns that cover three focus regions (Mid-Atlantic, Gulf Coast, and Midwest), and all four seasons (summer, winter, fall, and spring), as well as a variety of meteorological conditions. While constraints on GHG fluxes can be derived on the global scale (through remote-site concentration measurements and global flux inversion models) and the local scale (through eddy-covariance flux tower measurements), observational constraints on the intermediate scales are not as readily available. Biogenic CO2 fluxes are particularly challenging because of their strong seasonal and diurnal cycles and large spatial variability. During the summer 2016 ACT field campaign, fair weather days were targeted for special flight patterns designed to estimate surface fluxes at scales on the order of 105 km2 using a modified mass-balance approach. For some onshore flow cases in the Gulf Coast, atmospheric boundary layer (ABL) flight transects were performed both inland and offshore when it could be reasonably inferred that the homogeneous Gulf air provided the background GHG field for the inland transect. On other days, two-day flight sequences were performed, where the second-day location of the flight patterns was designed to encompass the air mass that was sampled on the first day. With these flight patterns, the average regional flux can be estimated from the ABL CO2 concentration change. Direct measurements of ABL depth from both aircraft profiles and high-resolution airborne lidar will be used, while winds and free-tropospheric CO2 can be determined from model output and in situ aircraft observations. Here we will present examples of this flux estimation for both Gulf-inflow and two-day fair-weather pattern cases from the summer 2016 ACT-America field campaign. We will also examine processes that lead to uncertainty in these estimates, and quantify these uncertainties. Implications for the ability of this regional flux determination to constrain the existing suite of GHG flux estimates will be discussed.

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.

Soil chemistry in lithologically diverse datasets: the quartz dilution effect

USGS Publications Warehouse

Bern, Carleton R.

2009-01-01

National- and continental-scale soil geochemical datasets are likely to move our understanding of broad soil geochemistry patterns forward significantly. Patterns of chemistry and mineralogy delineated from these datasets are strongly influenced by the composition of the soil parent material, which itself is largely a function of lithology and particle size sorting. Such controls present a challenge by obscuring subtler patterns arising from subsequent pedogenic processes. Here the effect of quartz concentration is examined in moist-climate soils from a pilot dataset of the North American Soil Geochemical Landscapes Project. Due to variable and high quartz contents (6.2–81.7 wt.%), and its residual and inert nature in soil, quartz is demonstrated to influence broad patterns in soil chemistry. A dilution effect is observed whereby concentrations of various elements are significantly and strongly negatively correlated with quartz. Quartz content drives artificial positive correlations between concentrations of some elements and obscures negative correlations between others. Unadjusted soil data show the highly mobile base cations Ca, Mg, and Na to be often strongly positively correlated with intermediately mobile Al or Fe, and generally uncorrelated with the relatively immobile high-field-strength elements (HFS) Ti and Nb. Both patterns are contrary to broad expectations for soils being weathered and leached. After transforming bulk soil chemistry to a quartz-free basis, the base cations are generally uncorrelated with Al and Fe, and negative correlations generally emerge with the HFS elements. Quartz-free element data may be a useful tool for elucidating patterns of weathering or parent-material chemistry in large soil datasets.

Shallow to Deep Convection Transition over a Heterogeneous Land Surface Using the Land Model Coupled Large-Eddy Simulation

NASA Astrophysics Data System (ADS)

Lee, J.; Zhang, Y.; Klein, S. A.

2017-12-01

The triggering of the land breeze, and hence the development of deep convection over heterogeneous land should be understood as a consequence of the complex processes involving various factors from land surface and atmosphere simultaneously. That is a sub-grid scale process that many large-scale models have difficulty incorporating it into the parameterization scheme partly due to lack of our understanding. Thus, it is imperative that we approach the problem using a high-resolution modeling framework. In this study, we use SAM-SLM (Lee and Khairoutdinov, 2015), a large-eddy simulation model coupled to a land model, to explore the cloud effect such as cold pool, the cloud shading and the soil moisture memory on the land breeze structure and the further development of cloud and precipitation over a heterogeneous land surface. The atmospheric large scale forcing and the initial sounding are taken from the new composite case study of the fair-weather, non-precipitating shallow cumuli at ARM SGP (Zhang et al., 2017). We model the land surface as a chess board pattern with alternating leaf area index (LAI). The patch contrast of the LAI is adjusted to encompass the weak to strong heterogeneity amplitude. The surface sensible- and latent heat fluxes are computed according to the given LAI representing the differential surface heating over a heterogeneous land surface. Separate from the surface forcing imposed from the originally modeled surface, the cases that transition into the moist convection can induce another layer of the surface heterogeneity from the 1) radiation shading by clouds, 2) adjusted soil moisture pattern by the rain, 3) spreading cold pool. First, we assess and quantifies the individual cloud effect on the land breeze and the moist convection under the weak wind to simplify the feedback processes. And then, the same set of experiments is repeated under sheared background wind with low level jet, a typical summer time wind pattern at ARM SGP site, to account for more realistic situations. Our goal is to assist answering the question: "Do the sub-grid scale land surface heterogeneity matter for the weather and climate modeling?" This work performed under the auspices of the U.S. Department of Energy by Lawrence Livermore National Laboratory under Contract DE-AC52-07NA27344. LLNL-ABS- 736011.

A weather regime characterisation of Irish wind generation and electricity demand in winters 2009–11

NASA Astrophysics Data System (ADS)

Cradden, Lucy C.; McDermott, Frank

2018-05-01

Prolonged cold spells were experienced in Ireland in the winters of 2009–10 and 2010–11, and electricity demand was relatively high at these times, whilst wind generation capacity factors were low. Such situations can cause difficulties for an electricity system with a high dependence on wind energy. Studying the atmospheric conditions associated with these two winters offers insights into the large-scale drivers for cold, calm spells, and helps to evaluate if they are rare events over the long-term. The influence of particular atmospheric patterns on coincidental winter wind generation and weather-related electricity demand is investigated here, with a focus on blocking in the North Atlantic/European sector. The occurrences of such patterns in the 2009–10 and 2010–11 winters are examined, and 2010–11 in particular was found to be unusual in a long-term context. The results are discussed in terms of the relevance to long-term planning and investment in the electricity system.

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

Multiresolution comparison of precipitation datasets for large-scale models

NASA Astrophysics Data System (ADS)

Chun, K. P.; Sapriza Azuri, G.; Davison, B.; DeBeer, C. M.; Wheater, H. S.

2014-12-01

Gridded precipitation datasets are crucial for driving large-scale models which are related to weather forecast and climate research. However, the quality of precipitation products is usually validated individually. Comparisons between gridded precipitation products along with ground observations provide another avenue for investigating how the precipitation uncertainty would affect the performance of large-scale models. In this study, using data from a set of precipitation gauges over British Columbia and Alberta, we evaluate several widely used North America gridded products including the Canadian Gridded Precipitation Anomalies (CANGRD), the National Center for Environmental Prediction (NCEP) reanalysis, the Water and Global Change (WATCH) project, the thin plate spline smoothing algorithms (ANUSPLIN) and Canadian Precipitation Analysis (CaPA). Based on verification criteria for various temporal and spatial scales, results provide an assessment of possible applications for various precipitation datasets. For long-term climate variation studies (~100 years), CANGRD, NCEP, WATCH and ANUSPLIN have different comparative advantages in terms of their resolution and accuracy. For synoptic and mesoscale precipitation patterns, CaPA provides appealing performance of spatial coherence. In addition to the products comparison, various downscaling methods are also surveyed to explore new verification and bias-reduction methods for improving gridded precipitation outputs for large-scale models.

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.

Impacts of large-scale atmospheric circulation changes in winter on black carbon transport and deposition to the Arctic

NASA Astrophysics Data System (ADS)

Pozzoli, Luca; Dobricic, Srdan; Russo, Simone; Vignati, Elisabetta

2017-10-01

Winter warming and sea-ice retreat observed in the Arctic in the last decades may be related to changes of large-scale atmospheric circulation pattern, which may impact the transport of black carbon (BC) to the Arctic and its deposition on the sea ice, with possible feedbacks on the regional and global climate forcing. In this study we developed and applied a statistical algorithm, based on the maximum likelihood estimate approach, to determine how the changes of three large-scale weather patterns associated with increasing temperatures in winter and sea-ice retreat in the Arctic impact the transport of BC to the Arctic and its deposition. We found that two atmospheric patterns together determine a decreasing winter deposition trend of BC between 1980 and 2015 in the eastern Arctic while they increase BC deposition in the western Arctic. The increasing BC trend is mainly due to a pattern characterized by a high-pressure anomaly near Scandinavia favouring the transport in the lower troposphere of BC from Europe and North Atlantic directly into to the Arctic. Another pattern with a high-pressure anomaly over the Arctic and low-pressure anomaly over the North Atlantic Ocean has a smaller impact on BC deposition but determines an increasing BC atmospheric load over the entire Arctic Ocean with increasing BC concentrations in the upper troposphere. The results show that changes in atmospheric circulation due to polar atmospheric warming and reduced winter sea ice significantly impacted BC transport and deposition. The anthropogenic emission reductions applied in the last decades were, therefore, crucial to counterbalance the most likely trend of increasing BC pollution in the Arctic.

Fast and fuel efficient? Optimal use of wind by flying albatrosses.

PubMed

Weimerskirch, H; Guionnet, T; Martin, J; Shaffer, S A; Costa, D P

2000-09-22

The influence of wind patterns on behaviour and effort of free-ranging male wandering albatrosses (Diomedea exulans) was studied with miniaturized external heart-rate recorders in conjunction with satellite transmitters and activity recorders. Heart rate was used as an instantaneous index of energy expenditure. When cruising with favourable tail or side winds, wandering albatrosses can achieve high flight speeds while expending little more energy than birds resting on land. In contrast, heart rate increases concomitantly with increasing head winds, and flight speeds decrease. Our results show that effort is greatest when albatrosses take off from or land on the water. On a larger scale, we show that in order for birds to have the highest probability of experiencing favourable winds, wandering albatrosses use predictable weather systems to engage in a stereotypical flight pattern of large looping tracks. When heading north, albatrosses fly in anticlockwise loops, and to the south, movements are in a clockwise direction. Thus, the capacity to integrate instantaneous eco-physiological measures with records of large-scale flight and wind patterns allows us to understand better the complex interplay between the evolution of morphological, physiological and behavioural adaptations of albatrosses in the windiest place on earth.

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

Divergence in Forest-Type Response to Climate and Weather: Evidence for Regional Links Between Forest-Type Evenness and Net Primary Productivity

USGS Publications Warehouse

Bradford, J.B.

2011-01-01

Climate change is altering long-term climatic conditions and increasing the magnitude of weather fluctuations. Assessing the consequences of these changes for terrestrial ecosystems requires understanding how different vegetation types respond to climate and weather. This study examined 20 years of regional-scale remotely sensed net primary productivity (NPP) in forests of the northern Lake States to identify how the relationship between NPP and climate or weather differ among forest types, and if NPP patterns are influenced by landscape-scale evenness of forest-type abundance. These results underscore the positive relationship between temperature and NPP. Importantly, these results indicate significant differences among broadly defined forest types in response to both climate and weather. Essentially all weather variables that were strongly related to annual NPP displayed significant differences among forest types, suggesting complementarity in response to environmental fluctuations. In addition, this study found that forest-type evenness (within 8 ?? 8 km2 areas) is positively related to long-term NPP mean and negatively related to NPP variability, suggesting that NPP in pixels with greater forest-type evenness is both higher and more stable through time. This is landscape- to subcontinental-scale evidence of a relationship between primary productivity and one measure of biological diversity. These results imply that anthropogenic or natural processes that influence the proportional abundance of forest types within landscapes may influence long-term productivity patterns. ?? 2011 Springer Science+Business Media, LLC (outside the USA).

Large-Scale Weather Disturbances in Mars’ Southern Extratropics

NASA Astrophysics Data System (ADS)

Hollingsworth, Jeffery L.; Kahre, Melinda A.

2015-11-01

Between late autumn and early spring, Mars’ middle and high latitudes within its atmosphere support strong mean thermal gradients between the tropics and poles. Observations from both the Mars Global Surveyor (MGS) and Mars Reconnaissance Orbiter (MRO) indicate that this strong baroclinicity supports intense, large-scale eastward traveling weather systems (i.e., transient synoptic-period waves). These extratropical weather disturbances are key components of the global circulation. Such wave-like disturbances act as agents in the transport of heat and momentum, and generalized scalar/tracer quantities (e.g., atmospheric dust, water-vapor and ice clouds). The character of large-scale, traveling extratropical synoptic-period disturbances in Mars' southern hemisphere during late winter through early spring is investigated using a moderately high-resolution Mars global climate model (Mars GCM). This Mars GCM imposes interactively lifted and radiatively active dust based on a threshold value of the surface stress. The model exhibits a reasonable "dust cycle" (i.e., globally averaged, a dustier atmosphere during southern spring and summer occurs). Compared to their northern-hemisphere counterparts, southern synoptic-period weather disturbances and accompanying frontal waves have smaller meridional and zonal scales, and are far less intense. Influences of the zonally asymmetric (i.e., east-west varying) topography on southern large-scale weather are examined. Simulations that adapt Mars’ full topography compared to simulations that utilize synthetic topographies emulating key large-scale features of the southern middle latitudes indicate that Mars’ transient barotropic/baroclinic eddies are highly influenced by the great impact basins of this hemisphere (e.g., Argyre and Hellas). The occurrence of a southern storm zone in late winter and early spring appears to be anchored to the western hemisphere via orographic influences from the Tharsis highlands, and the Argyre and Hellas impact basins. Geographically localized transient-wave activity diagnostics are constructed that illuminate dynamical differences amongst the simulations and these are presented.

Long-term variability of the thunderstorm and hail potential in Europe

NASA Astrophysics Data System (ADS)

Mohr, Susanna; Kunz, Michael; Speidel, Johannes; Piper, David

2016-04-01

Severe thunderstorms and associated hazardous weather events such as hail frequently cause considerable damage to buildings, crops, and automobiles, resulting in large monetary costs in many parts of Europe and the world. To relate single extreme hail events to the historic context and to estimate their return periods and possible trends related to climate change, long-term statistics of hail events are required. Due to the local-scale nature of hail and a lack of suitable observation systems, however, hailstorms are not captured reliably and comprehensively for a long period of time. In view of this fact, different proxies (indirect climate data) obtained from sounding stations and regional climate models can be used to infer the probability and intensity of thunderstorms or hailstorms. In contrast to direct observational data, such proxies are available homogeneously over a long time period. The aim of the study is to investigate the potential for severe thunderstorms and their changes over past decades. Statistical analyses of sounding data show that the convective potential over the past 20 - 30 years has significantly increased over large parts of Central Europe, making severe thunderstorms more likely. A similar picture results from analyses of weather types that are most likely associated with damaging hailstorms. These weather patterns have increased, even if only slightly but nevertheless statistically significantly, in the time period from 1971 to 2000. To improve the diagnostics of hail events in regional climate models, a logistic hail model has been developed by means of a multivariate analysis method. The model is based on a combination of appropriate hail-relevant meteorological parameters. The output of the model is a new index that estimates the potential of the atmosphere for hailstorm development, referred to as potential hail index (PHI). Applied to a high-resolved reanalysis run for Europe driven by NCEP/NCAR1, long-term changes of the PHI for 60 years (1951-2010) show large annual and multiannual variability. The trends are mostly positive in the western parts and negative to the east. However, due to the large temporal variability, the trends are not significant at most of the grid points. Furthermore, it becomes clear that the environmental conditions that favor the formation of hailstorms prevail in larger areas. This finding suggests that, despite the local-scale nature of convective storms, the ambient conditions favoring these events are mainly controlled by large-scale circulation patterns and mechanisms. This result is important to estimate the convective potential of the atmosphere in case of single events.

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

A kinetic energy study of the meso beta-scale storm environment during AVE-SESAME 5 (20-21 May 1979)

NASA Technical Reports Server (NTRS)

Printy, M. F.; Fuelberg, H. E.

1984-01-01

Kinetic energy of the near storm environment was analyzed by meso beta scale data. It was found that horizontal winds in the 400 to 150 mb layer strengthen rapidly north of the developing convection. Peak values then decrease such that the maximum disappears 6 h later. Southeast of the storms, wind speeds above 300 mb decrease nearly 50% during the 3 h period of most intense thunderstorm activity. When the convection dissipates, wind patterns return to prestorm conditions. The mesoscale storm environment of AVE-SESAME 5 is characterized by large values of cross contour generation of kinetic energy, transfers of energy to nonresolvable scales of motion, and horizontal flux divergence. These processes are maximized within the upper troposphere and are greatest during times of strongest convection. It is shown that patterns agree with observed weather features. The southeast area of the network is examined to determine causes for vertical wind variations.

Large-Scale Traveling Weather Systems in Mars’ Southern Extratropics

NASA Astrophysics Data System (ADS)

Hollingsworth, Jeffery L.; Kahre, Melinda A.

2017-10-01

Between late fall and early spring, Mars’ middle- and high-latitude atmosphere supports strong mean equator-to-pole temperature contrasts and an accompanying mean westerly polar vortex. Observations from both the MGS Thermal Emission Spectrometer (TES) and the MRO Mars Climate Sounder (MCS) indicate that a mean baroclinicity-barotropicity supports intense, large-scale eastward traveling weather systems (i.e., transient synoptic-period waves). Such extratropical weather disturbances are critical components of the global circulation as they serve as agents in the transport of heat and momentum, and generalized scalar/tracer quantities (e.g., atmospheric dust, water-vapor and ice clouds). The character of such traveling extratropical synoptic disturbances in Mars' southern hemisphere during late winter through early spring is investigated using a moderately high-resolution Mars global climate model (Mars GCM). This Mars GCM imposes interactively-lifted and radiatively-active dust based on a threshold value of the surface stress. The model exhibits a reasonable "dust cycle" (i.e., globally averaged, a dustier atmosphere during southern spring and summer occurs). Compared to the northern-hemisphere counterparts, the southern synoptic-period weather disturbances and accompanying frontal waves have smaller meridional and zonal scales, and are far less intense. Influences of the zonally asymmetric (i.e., east-west varying) topography on southern large-scale weather are investigated, in addition to large-scale up-slope/down-slope flows and the diurnal cycle. A southern storm zone in late winter and early spring presents in the western hemisphere via orographic influences from the Tharsis highlands, and the Argyre and Hellas impact basins. Geographically localized transient-wave activity diagnostics are constructed that illuminate dynamical differences amongst the simulations and these are presented.

Large-Scale Traveling Weather Systems in Mars Southern Extratropics

NASA Technical Reports Server (NTRS)

Hollingsworth, Jeffery L.; Kahre, Melinda A.

2017-01-01

Between late fall and early spring, Mars' middle- and high-latitude atmosphere supports strong mean equator-to-pole temperature contrasts and an accompanying mean westerly polar vortex. Observations from both the MGS Thermal Emission Spectrometer (TES) and the MRO Mars Climate Sounder (MCS) indicate that a mean baroclinicity-barotropicity supports intense, large-scale eastward traveling weather systems (i.e., transient synoptic-period waves). Such extratropical weather disturbances are critical components of the global circulation as they serve as agents in the transport of heat and momentum, and generalized scalar/tracer quantities (e.g., atmospheric dust, water-vapor and ice clouds). The character of such traveling extratropical synoptic disturbances in Mars' southern hemisphere during late winter through early spring is investigated using a moderately high-resolution Mars global climate model (Mars GCM). This Mars GCM imposes interactively-lifted and radiatively-active dust based on a threshold value of the surface stress. The model exhibits a reasonable "dust cycle" (i.e., globally averaged, a dustier atmosphere during southern spring and summer occurs). Compared to the northern-hemisphere counterparts, the southern synoptic-period weather disturbances and accompanying frontal waves have smaller meridional and zonal scales, and are far less intense. Influences of the zonally asymmetric (i.e., east-west varying) topography on southern large-scale weather are investigated, in addition to large-scale up-slope/down-slope flows and the diurnal cycle. A southern storm zone in late winter and early spring presents in the western hemisphere via orographic influences from the Tharsis highlands, and the Argyre and Hellas impact basins. Geographically localized transient-wave activity diagnostics are constructed that illuminate dynamical differences amongst the simulations and these are presented.

Climate, Santa Ana Winds and Autumn Wildfires in Southern California

NASA Astrophysics Data System (ADS)

Westerling, Anthony L.; Cayan, Daniel R.; Brown, Timothy J.; Hall, Beth L.; Riddle, Laurence G.

2004-08-01

Wildfires periodically burn large areas of chaparral and adjacent woodlands in autumn and winter in southern California. These fires often occur in conjunction with Santa Ana weather events, which combine high winds and low humidity, and tend to follow a wet winter rainy season. Because conditions fostering large fall and winter wildfires in California are the result of large-scale patterns in atmospheric circulation, the same dangerous conditions are likely to occur over a wide area at the same time. Furthermore, over a century of watershed reserve management and fire suppression have promoted fuel accumulations, helping to shape one of the most conflagration-prone environments in the world. Combined with a complex topography and a large human population, southern Californian ecology and climate pose a considerable physical and societal challenge to fire management.

The Aleutian Low and Winter Climatic Conditions in the Bering Sea. Part I: Classification

NASA Astrophysics Data System (ADS)

Rodionov, S. N.; Overland, J. E.; Bond, N. A.

2005-01-01

The Aleutian low is examined as a primary determinant of surface air temperature (SAT) variability in the Bering Sea during the winter (December-January-February-March (DJFM)) months. The Classification and Regression Tree (CART) method is used to classify five types of atmospheric circulation for anomalously warm months (W1-W5) and cold months (C1-C5). For the Bering Sea, changes in the position of the Aleutian low are shown to be more important than changes in its central pressure. The first two types, W1 and C1, account for 51% of the "warm" and 37% of the "cold" months. The W1-type pattern is characterized by the anomalously deep Aleutian low shifted west and north of its mean position. In this situation, an increased cyclonic activity occurs in the western Bering Sea. The C1-type pattern represents a split Aleutian low with one center in the northwestern Pacific and the other in the Gulf of Alaska. The relative frequency of the W1 to C1 types of atmospheric circulation varies on decadal time scales, which helps to explain the predominance of fluctuations on these time scales in the weather of the Bering Sea. Previous work has noted the prominence of multidecadal variability in the North Pacific. The present study finds multidecadal variations in frequencies of the W3 and C3 patterns, both of which are characterized by increased cyclonic activity south of 51°N. In general, the CART method is found to be a suitable means for characterizing the wintertime atmospheric circulation of the North Pacific in terms of its impact on the Bering Sea. The results show that similar pressure anomaly patterns for the North Pacific as a whole can actually result in different conditions for the Bering Sea, and that similar weather conditions in the Bering Sea can arise from decidedly different large-scale pressure patterns.

The impact of large-scale circulation patterns on summer crop yields in IP

NASA Astrophysics Data System (ADS)

Capa Morocho, Mirian; Rodríguez Fonseca, Belén; Ruiz Ramos, Margarita

2014-05-01

Large-scale circulations patterns (ENSO, NAO) have been shown to have a significant impact on seasonal weather, and therefore on crop yield over many parts of the world(Garnett and Khandekar, 1992; Aasa et al., 2004; Rozas and Garcia-Gonzalez, 2012). In this study, we analyze the influence of large-scale circulation patterns and regional climate on the principal components of maize yield variability in Iberian Peninsula (IP) using reanalysis datasets. Additionally, we investigate the modulation of these relationships by multidecadal patterns. This study is performed analyzing long time series of maize yield, only climate dependent, computed with the crop model CERES-maize (Jones and Kiniry, 1986) included in Decision Support System for Agrotechnology Transfer (DSSAT v.4.5). To simulate yields, reanalysis daily data of radiation, maximum and minimum temperature and precipitation were used. The reanalysis climate data were obtained from National Center for Environmental Prediction (20th Century and NCEP) and European Centre for Medium-Range Weather Forecasts (ECMWF) data server (ERA 40 and ERA Interim). Simulations were run at five locations: Lugo (northwestern), Lerida (NE), Madrid (central), Albacete (southeastern) and Córdoba (S IP) (Gabaldón et al., 2013). From these time series standardized anomalies were calculated. Afterwards, time series were time filtered to focus on the interannual-to-multiannual variability, splitting up in two components: low frequency (LF) and high frequency (HF) time scales. The principal components of HF yield anomalies in IP were compared with a set of documented patterns. These relationships were compared with multidecadal patterns, as Atlanctic Multidecadal Oscillations (AMO) and Interdecadal Pacific Oscillations (IPO). The results of this study have important implications in crop forecasting. In this way, it may have a positive impact on both public (agricultural planning) and private (decision support to farmers, insurance companies) sectors, to take advantage of favorable conditions or reduce the effect of adverse conditions. Acknowledgements Research by M. Capa-Morocho has been partly supported by a PICATA predoctoral fellowship of the Moncloa Campus of International Excellence (UCM-UPM) and MULCLIVAR project (CGL2012-38923-C02-02) References Aasa, A., Jaagus, J., Ahas, R. and Sepp, M. 2004. The influence of atmospheric circulation on plant phenological phases in central and eastern Europe. International Journal of Climatology 24, 1551-1564. Gabaldón, C. et al. 2013. Evaluation of local strategies to climate change of maize crop in Andalusia for the first half of 21st century. European Geosciences Union - General Assembly2013 Vol. 15 (Vienna - Austria, 2013). Garnett, E. R. and Khandekar, M. L. 1992. The impact of large-scale atmospheric circulations and anomalies on Indian monsoon droughts and floods and on world grain yields-a statistical analysis. Agricultural and Forest Meteorology 61, 113-128. Jones, C. and Kiniry, J. 1986. CERES-Maize: A Simulation Model of Maize Growth and Development. Texas A&M University Press, 194. Rozas, V. and Garcia-Gonzalez, I. 2012. Non-stationary influence of El Nino-Southern Oscillation and winter temperature on oak latewood growth in NW Iberian Peninsula. Int J Biometeorol 56, 787-800.

A Linkage of Recent Arctic Summer Sea Ice and Snowfall Variability of Japan

NASA Astrophysics Data System (ADS)

Iwamoto, K.; Honda, M.; Ukita, J.

2014-12-01

In spite of its mid-latitude location, Japan has a markedly high amount of snowfall, which owes much to the presence of cold air-break from Siberia and thus depends on the strength of the Siberian high and the Aleutian low. With this background this study examines the relationship between interannual variability and spatial patterns of snowfall in Japan with large-scale atmospheric and sea ice variations. The lag regression map of the winter snowfall in Japan on the time series of the Arctic SIE from the preceding summer shows a seesaw pattern in the snowfall, suggesting an Arctic teleconnection to regional weather. From the EOF analyses conducted on the snowfall distribution in Japan, we identify two modes with physical significance. The NH SIC and SLP regressed on PC1 show a sea ice reduction in the Barents and Kara Seas and anomalous strength of the Siberia high as discussed in Honda et al. (2009) and other studies, which support the above notion that the snowfall variability of Japan is influenced by Arctic sea ice conditions. Another mode is related to the AO/NAO and the hemispheric scale double sea-ice seesaw centered over the sub-Arctic region: one between the Labrador and Nordic Seas in the Atlantic and the other between the Okhotsk and Bering Seas from the Pacific as discussed in Ukita et al. (2007). Together, observations point to a significant role of the sea-ice in determining mid-latitude regional climate and weather patterns.

Assessing Landscape Scale Wildfire Exposure for Highly Valued Resources in a Mediterranean Area

NASA Astrophysics Data System (ADS)

Alcasena, Fermín J.; Salis, Michele; Ager, Alan A.; Arca, Bachisio; Molina, Domingo; Spano, Donatella

2015-05-01

We used a fire simulation modeling approach to assess landscape scale wildfire exposure for highly valued resources and assets (HVR) on a fire-prone area of 680 km2 located in central Sardinia, Italy. The study area was affected by several wildfires in the last half century: some large and intense fire events threatened wildland urban interfaces as well as other socioeconomic and cultural values. Historical wildfire and weather data were used to inform wildfire simulations, which were based on the minimum travel time algorithm as implemented in FlamMap. We simulated 90,000 fires that replicated recent large fire events in the area spreading under severe weather conditions to generate detailed maps of wildfire likelihood and intensity. Then, we linked fire modeling outputs to a geospatial risk assessment framework focusing on buffer areas around HVR. The results highlighted a large variation in burn probability and fire intensity in the vicinity of HVRs, and allowed us to identify the areas most exposed to wildfires and thus to a higher potential damage. Fire intensity in the HVR buffers was mainly related to fuel types, while wind direction, topographic features, and historically based ignition pattern were the key factors affecting fire likelihood. The methodology presented in this work can have numerous applications, in the study area and elsewhere, particularly to address and inform fire risk management, landscape planning and people safety on the vicinity of HVRs.

A Multiscale Analysis of Upstream Precursors associated with High Impact Severe Weather Events across the Upper Midwest

NASA Astrophysics Data System (ADS)

Metz, N. D.; Cordeira, J. M.

2014-12-01

Between 30 June and 1 July 2011, a heavy-rain-producing mesoscale convective system (MCS) occurred over Lake Michigan. A second MCS subsequently occurred over Minnesota, Iowa, and Wisconsin on 1 July 2011 resulting in more than 200 severe weather reports. The antecedent large-scale flow evolution was strongly influenced by early-season tropical cyclones (TCs) Haima and Meari in the western North Pacific. The recurvature and subsequent interaction of these TCs with the extratropical large-scale flow was associated with Rossby wave train (RWT) amplification on 22-26 June 2011 over the western North Pacific and dispersion across North America on 28-30 June 2011. The RWT dispersion was associated with trough (ridge) development over western (central) North America at the time of MCS development over the Midwestern United States. This evolution of the large-scale flow and attendant meso-synoptic scale forcing for ascent were particularly conducive to heavy rainfall and severe weather as a surface-based mixed layer over the Intermountain Western United States was advected eastward, transitioning to an elevated mixed layer (EML) over the Midwestern United States. These two MCSs serve as motivation for a climatology of EML days and their relationship to severe weather over the Midwestern United States. The climatology illustrates that severe weather reports near Minneapolis, MN during the summer are twice as numerous on EML days as compared to normal. The increase in severe weather reports are primarily driven by more large hail and severe wind, which account for 95% of all severe weather reports on EML days. A time-lagged composite analysis indicates that RWT amplification over the central North Pacific and RWT dispersion across the eastern North Pacific and North American, as occurred prior to the 30 June-1 July period, is a common upstream precursor to EML days over the Midwestern United States. These results suggest that investigations of far upstream precursors to RWT amplification and dispersion over the North Pacific may be particularly useful in better understanding warm-season severe weather outbreaks over North America.

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.

Extratropical Cyclogenesis and Frontal Waves on Mars: Influences on Dust, Weather and the Planet's climate

NASA Technical Reports Server (NTRS)

Hollingsworth, J. L.; Kahre, Melinda A.

2012-01-01

Between late autumn and early spring, middle and high latitudes on Mars exhibit strong equatortopole mean temperature contrasts (i.e., "baroclinicity"). Data collected during the Viking era and observations from both the Mars Global Surveyor (MGS) and Mars Reconnaissance Orbiter (MRO) indicate that this strong baroclinicity supports vigorous, large-scale eastward traveling weather systems (i.e., transient synoptic periodwaves) [1,2]. For a rapidly rotating, differentially heated, shallow atmosphere such as on Earth and Mars, these large-scale, extratropical weather disturbances are critical components of the global circulation. The wavelike disturbances act as agents in the transport of heat and momentum between low and high latitudes of the planet. Through cyclonic/anticyclonic winds, intense shear deformations, contractions-dilatations in temperature and density, and sharp perturbations amongst atmospheric tracers (i.e., dust, volatiles (e.g., water vapor) and condensates (e.g., water-ice cloud particles)), Mars extratropical weather systems have significant subsynoptic scale ramifications by supporting atmospheric frontal waves (Fig. 1).

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.

Satellite-derived mineral mapping and monitoring of weathering, deposition and erosion

PubMed Central

Cudahy, Thomas; Caccetta, Mike; Thomas, Matilda; Hewson, Robert; Abrams, Michael; Kato, Masatane; Kashimura, Osamu; Ninomiya, Yoshiki; Yamaguchi, Yasushi; Collings, Simon; Laukamp, Carsten; Ong, Cindy; Lau, Ian; Rodger, Andrew; Chia, Joanne; Warren, Peter; Woodcock, Robert; Fraser, Ryan; Rankine, Terry; Vote, Josh; de Caritat, Patrice; English, Pauline; Meyer, Dave; Doescher, Chris; Fu, Bihong; Shi, Pilong; Mitchell, Ross

2016-01-01

The Earth’s surface comprises minerals diagnostic of weathering, deposition and erosion. The first continental-scale mineral maps generated from an imaging satellite with spectral bands designed to measure clays, quartz and other minerals were released in 2012 for Australia. Here we show how these satellite mineral maps improve our understanding of weathering, erosional and depositional processes in the context of changing weather, climate and tectonics. The clay composition map shows how kaolinite has developed over tectonically stable continental crust in response to deep weathering during northwardly migrating tropical conditions from 45 to 10 Ma. The same clay composition map, in combination with one sensitive to water content, enables the discrimination of illite from montmorillonite clays that typically develop in large depositional environments over thin (sinking) continental crust such as the Lake Eyre Basin. Cutting across these clay patterns are sandy deserts that developed <10 Ma and are well mapped using another satellite product sensitive to the particle size of silicate minerals. This product can also be used to measure temporal gains/losses of surface clay caused by periodic wind erosion (dust) and rainfall inundation (flood) events. The accuracy and information content of these satellite mineral maps are validated using published data. PMID:27025192

Analysis of weather patterns associated with air quality degradation and potential health impacts

EPA Science Inventory

Emissions from anthropogenic and natural sources into the atmosphere are determined in large measure by prevailing weather conditions through complex physical, dynamical and chemical processes. Air pollution episodes are characterized by degradation in air quality as reflected by...

Measuring ignitability for in situ burning of oil spills weathered under Arctic conditions: from laboratory studies to large-scale field experiments.

PubMed

Fritt-Rasmussen, Janne; Brandvik, Per Johan

2011-08-01

This paper compares the ignitability of Troll B crude oil weathered under simulated Arctic conditions (0%, 50% and 90% ice cover). The experiments were performed in different scales at SINTEF's laboratories in Trondheim, field research station on Svalbard and in broken ice (70-90% ice cover) in the Barents Sea. Samples from the weathering experiments were tested for ignitability using the same laboratory burning cell. The measured ignitability from the experiments in these different scales showed a good agreement for samples with similar weathering. The ice conditions clearly affected the weathering process, and 70% ice or more reduces the weathering and allows a longer time window for in situ burning. The results from the Barents Sea revealed that weathering and ignitability can vary within an oil slick. This field use of the burning cell demonstrated that it can be used as an operational tool to monitor the ignitability of oil spills. Copyright © 2011 Elsevier Ltd. All rights reserved.

Spatial patterns of large natural fires in Sierra Nevada wilderness areas

USGS Publications Warehouse

Collins, B.M.; Kelly, M.; van Wagtendonk, J.W.; Stephens, S.L.

2007-01-01

The effects of fire on vegetation vary based on the properties and amount of existing biomass (or fuel) in a forest stand, weather conditions, and topography. Identifying controls over the spatial patterning of fire-induced vegetation change, or fire severity, is critical in understanding fire as a landscape scale process. We use gridded estimates of fire severity, derived from Landsat ETM+ imagery, to identify the biotic and abiotic factors contributing to the observed spatial patterns of fire severity in two large natural fires. Regression tree analysis indicates the importance of weather, topography, and vegetation variables in explaining fire severity patterns between the two fires. Relative humidity explained the highest proportion of total sum of squares throughout the Hoover fire (Yosemite National Park, 2001). The lowest fire severity corresponded with increased relative humidity. For the Williams fire (Sequoia/Kings Canyon National Parks, 2003) dominant vegetation type explains the highest proportion of sum of squares. Dominant vegetation was also important in determining fire severity throughout the Hoover fire. In both fires, forest stands that were dominated by lodgepole pine (Pinus contorta) burned at highest severity, while red fir (Abies magnifica) stands corresponded with the lowest fire severities. There was evidence in both fires that lower wind speed corresponded with higher fire severity, although the highest fire severity in the Williams fire occurred during increased wind speed. Additionally, in the vegetation types that were associated with lower severity, burn severity was lowest when the time since last fire was fewer than 11 and 17 years for the Williams and Hoover fires, respectively. Based on the factors and patterns identified, managers can anticipate the effects of management ignited and naturally ignited fires at the forest stand and the landscape levels. ?? 2007 Springer Science+Business Media, Inc.

How does pedogenesis drive plant diversity?

USGS Publications Warehouse

Laliberté, Etienne; Grace, James B.; Huston, Michael A.; Lambers, Hans; Teste, François P.; Turner, Benjamin L.; Wardle, David A.

2013-01-01

Some of the most species-rich plant communities occur on ancient, strongly weathered soils, whereas those on recently developed soils tend to be less diverse. Mechanisms underlying this well-known pattern, however, remain unresolved. Here, we present a conceptual model describing alternative mechanisms by which pedogenesis (the process of soil formation) might drive plant diversity. We suggest that long-term soil chronosequences offer great, yet largely untapped, potential as 'natural experiments' to determine edaphic controls over plant diversity. Finally, we discuss how our conceptual model can be evaluated quantitatively using structural equation modeling to advance multivariate theories about the determinants of local plant diversity. This should help us to understand broader-scale diversity patterns, such as the latitudinal gradient of plant diversity.

Influence of synoptic weather patterns on solar irradiance variability in Europe

NASA Astrophysics Data System (ADS)

Parding, Kajsa; Hinkelman, Laura; Liepert, Beate; Ackerman, Thomas; Dagestad, Knut-Frode; Asle Olseth, Jan

2014-05-01

Solar radiation is important for many aspects of existence on Earth, including the biosphere, the hydrological cycle, and creatures living on the planet. Previous studies have reported decadal trends in observational records of surface shortwave (SW) irradiance around the world, too strong to be caused by varying solar output. These observed decadal trends have been dubbed "solar dimming and brightening" and are believed to be related to changes in atmospheric aerosols and cloud cover. Because the observed solar variability coincides with qualitative air pollution histories, the dimming and brightening have become almost synonymous with shortwave attenuation by anthropogenic aerosols. However, there are indications that atmospheric circulation patterns have influenced the dimming and brightening in some regions, e.g., Alaska and Scandinavia. In this work, we focus on the role of atmospheric circulation patterns in modifying shortwave irradiance. An examination of European SW irradiance data from the Global Energy Balance Archive (GEBA) shows that while there are periods of predominantly decreasing (~1970-1985) and increasing (~1985-2007) SW irradiance, the changes are not spatially uniform within Europe and in a majority of locations not statistically significant. To establish a connection between weather patterns and sunshine, regression models of SW irradiance are fitted using a daily classification of European weather called Grosswetterlagen (GWL). The GWL reconstructions of shortwave irradiance represent the part of the solar variability that is related to large scale weather patterns, which should be effectively separated from the influence of varying anthropogenic aerosol emissions. The correlation (R) between observed and reconstruced SW irradiance is between 0.31 and 0.75, depending on station and season, all statistically significant (p<0.05, estimated with a bootstrap test). In central and eastern parts of Europe, the observed decadal SW variability is poorly represented by the GWL models, but in northern Europe, the GWL model recreates observed decadal solar variability well. This finding suggests that natural and/or anthropogenic variations in circulation patterns have influenced solar dimming and brightening to a higher degree in the north than in the rest of Europe.

Interannual variations in fire weather, fire extent, and synoptic-scale circulation patterns in northern California and Oregon

Treesearch

Valerie Trouet; Alan H. Taylor; Andrew M. Carleton; Carl N. Skinner

2009-01-01

The Mediterranean climate region on the west coast of the United States is characterized by wet winters and dry summers, and by high fire activity. The importance of synoptic-scale circulation patterns (ENSO, PDO, PNA) on fire-climate interactions is evident in contemporary fire data sets and in pre-Euroamerican tree-ring-based fire records. We investigated how...

Climate-soil Interactions: Global Change, Local Properties, and Ecological Sites

USDA-ARS?s Scientific Manuscript database

Global climate change is predicted to alter historic patterns of precipitation and temperature in rangelands globally. Vegetation community response to altered weather patterns will be mediated at the site level by local-scale properties that govern ecological potential, including geology, topograph...

Global comparison reveals biogenic weathering as driven by nutrient limitation at ecosystem scale

NASA Astrophysics Data System (ADS)

Boy, Jens; Godoy, Roberto; Dechene, Annika; Shibistova, Olga; Amir, Hamid; Iskandar, Issi; Fogliano, Bruno; Boy, Diana; McCulloch, Robert; Andrino, Alberto; Gschwendtner, Silvia; Marin, Cesar; Sauheitl, Leopold; Dultz, Stefan; Mikutta, Robert; Guggenberger, Georg

2017-04-01

A substantial contribution of biogenic weathering in ecosystem nutrition, especially by symbiotic microorganisms, has often been proposed, but large-scale in vivo studies are still missing. Here we compare a set of ecosystems spanning from the Antarctic to tropical forests for their potential biogenic weathering and its drivers. To address biogenic weathering rates, we installed mineral mesocosms only accessible for bacteria and fungi for up to 4 years, which contained freshly broken and defined nutrient-baring minerals in soil A horizons of ecosystems along a gradient of soil development differing in climate and plant species communities. Alterations of the buried minerals were analyzed by grid-intersection, confocal lascer scanning microscopy, energy-dispersive X-ray spectroscopy, and X-ray photoelectron spectroscopy on the surface and on thin sections. On selected sites, carbon fluxes were tracked by 13C labeling, and microbial community was identified by DNA sequencing. In young ecosystems (protosoils) biogenic weathering is almost absent and starts after first carbon accumulation by aeolian (later litter) inputs and is mainly performed by bacteria. With ongoing soil development and appearance of symbiotic (mycorrhized) plants, nutrient availability in soil increasingly drove biogenic weathering, and fungi became the far more important players than bacteria. We found a close relation between fungal biogenic weathering and available potassium across all 16 forested sites in the study, regardless of the dominant mycorrhiza type (AM or EM), climate, and plant-species composition. We conclude that nutrient limitations at ecosystem scale are generally counteracted by adapted fungal biogenic weathering. The close relation between fungal weathering and plant-available nutrients over a large range of severely contrasting ecosystems points towards a direct energetic support of these weathering processes by the photoautotrophic community, making biogenic weathering a directional on-demand process common in all types of ecosystems.

Using long-term ARM observations to evaluate Arctic mixed-phased cloud representation in the GISS ModelE GCM

NASA Astrophysics Data System (ADS)

Lamer, K.; Fridlind, A. M.; Luke, E. P.; Tselioudis, G.; Ackerman, A. S.; Kollias, P.; Clothiaux, E. E.

2016-12-01

The presence of supercooled liquid in clouds affects surface radiative and hydrological budgets, especially at high latitudes. Capturing these effects is crucial to properly quantifying climate sensitivity. Currently, a number of CGMs disagree on the distribution of cloud phase. Adding to the challenge is a general lack of observations on the continuum of clouds, from high to low-level and from warm to cold. In the current study, continuous observations from 2011 to 2014 are used to evaluate all clouds produced by the GISS ModelE GCM over the ARM North Slope of Alaska site. The International Satellite Cloud Climatology Project (ISCCP) Global Weather State (GWS) approach reveals that fair-weather (GWS 7, 32% occurrence rate), as well as mid-level storm related (GWS 5, 28%) and polar (GWS 4, 14%) clouds, dominate the large-scale cloud patterns at this high latitude site. At higher spatial and temporal resolutions, ground-based cloud radar observations reveal a majority of single layer cloud vertical structures (CVS). While clear sky and low-level clouds dominate (each with 30% occurrence rate) a fair amount of shallow ( 10%) to deep ( 5%) convection are observed. Cloud radar Doppler spectra are used along with depolarization lidar observations in a neural network approach to detect the presence, layering and inhomogeneity of supercooled liquid layers. Preliminary analyses indicate that most of the low-level clouds sampled contain one or more supercooled liquid layers. Furthermore, the relationship between CVS and the presence of supercooled liquid is established, as is the relationship between the presence of supercool liquid and precipitation susceptibility. Two approaches are explored to bridge the gap between large footprint GCM simulations and high-resolution ground-based observations. The first approach consists of comparing model output and ground-based observations that exhibit the same column CVS type (i.e. same cloud depth, height and layering). Alternatively, the second approach consists of comparing model output and ground-based observations that exhibit the same large-scale GWS type (i.e. same cloud top pressure and optical depth patterns) where ground-based observations are associated to large-scale GWS every 3 hours using the closest satellite overpass.

Traveling Weather Disturbances in Mars Southern Extratropics: Sway of the Great Impact Basins

NASA Technical Reports Server (NTRS)

Hollingsworth, Jeffery L.

2016-01-01

As on Earth, between late autumn and early spring on Mars middle and high latitudes within its atmosphere support strong mean thermal contrasts between the equator and poles (i.e. "baroclinicity"). Data collected during the Viking era and observations from both the Mars Global Surveyor (MGS) and Mars Reconnaissance Orbiter (MRO) indicate that this strong baroclinicity supports vigorous, large-scale eastward traveling weather systems (i.e. transient synoptic-period waves). Within a rapidly rotating, differentially heated, shallow atmosphere such as on Earth and Mars, such large-scale, extratropical weather disturbances are critical components of the global circulation. These wave-like disturbances act as agents in the transport of heat and momentum, and moreover generalized tracer quantities (e.g., atmospheric dust, water vapor and water-ice clouds) between low and high latitudes of the planet. The character of large-scale, traveling extratropical synoptic-period disturbances in Mars' southern hemisphere during late winter through early spring is investigated using a high-resolution Mars global climate model (Mars GCM). This global circulation model imposes interactively lifted (and radiatively active) dust based on a threshold value of the instantaneous surface stress. Compared to observations, the model exhibits a reasonable "dust cycle" (i.e. globally averaged, a more dusty atmosphere during southern spring and summer occurs). In contrast to their northern-hemisphere counterparts, southern synoptic-period weather disturbances and accompanying frontal waves have smaller meridional and zonal scales, and are far less intense synoptically. Influences of the zonally asymmetric (i.e. east-west varying) topography on southern large-scale weather disturbances are examined. Simulations that adapt Mars' full topography compared to simulations that utilize synthetic topographies emulating essential large-scale features of the southern middle latitudes indicate that Mars' transient barotropic/baroclinic eddies are significantly influenced by the great impact basins of this hemisphere (e.g., Argyre and Hellas). In addition, the occurrence of a southern storm zone in late winter and early spring is keyed particularly to the western hemisphere via orographic influences arising from the Tharsis highlands, and the Argyre and Hellas impact basins. Geographically localized transient-wave activity diagnostics are constructed that illuminate fundamental differences amongst such simulations and these are described.

Traveling Weather Disturbances in Mars' Southern Extratropics: Sway of the Great Impact Basins

NASA Astrophysics Data System (ADS)

Hollingsworth, Jeffery L.

2016-04-01

As on Earth, between late autumn and early spring on Mars middle and high latitudes within its atmosphere support strong mean thermal contrasts between the equator and poles (i.e., "baroclinicity"). Data collected during the Viking era and observations from both the Mars Global Surveyor (MGS) and Mars Reconnaissance Orbiter (MRO) indicate that this strong baroclinicity supports vigorous, large-scale eastward traveling weather systems (i.e., transient synoptic-period waves). Within a rapidly rotating, differentially heated, shallow atmosphere such as on Earth and Mars, such large-scale, extratropical weather disturbances are critical components of the global circulation. These wave-like disturbances act as agents in the transport of heat and momentum, and moreover generalized tracer quantities (e.g., atmospheric dust, water vapor and water-ice clouds) between low and high latitudes of the planet. The character of large-scale, traveling extratropical synoptic-period disturbances in Mars' southern hemisphere during late winter through early spring is investigated using a high-resolution Mars global climate model (Mars GCM). This global circulation model imposes interactively lifted (and radiatively active) dust based on a threshold value of the instantaneous surface stress. Compared to observations, the model exhibits a reasonable "dust cycle" (i.e., globally averaged, a more dusty atmosphere during southern spring and summer occurs). In contrast to their northern-hemisphere counterparts, southern synoptic-period weather disturbances and accompanying frontal waves have smaller meridional and zonal scales, and are far less intense synoptically. Influences of the zonally asymmetric (i.e., east-west varying) topography on southern large-scale weather disturbances are examined. Simulations that adapt Mars' full topography compared to simulations that utilize synthetic topographies emulating essential large-scale features of the southern middle latitudes indicate that Mars' transient barotropic/baroclinic eddies are significantly influenced by the great impact basins of this hemisphere (e.g., Argyre and Hellas). In addition, the occurrence of a southern storm zone in late winter and early spring is keyed particularly to the western hemisphere via orographic influences arising from the Tharsis highlands, and the Argyre and Hellas impact basins. Geographically localized transient-wave activity diagnostics are constructed that illuminate fundamental differences amongst such simulations and these are described.

Seeing is believing I: The use of thermal sensing from satellite imagery to predict crop yield

NASA Astrophysics Data System (ADS)

B, Potgieter A.; D, Rodriguez; B, Power; J, Mclean; P, Davis

2014-02-01

Volatility in crop production has been part of the Australian environment since cropping began with the arrival of the first European settlers. Climate variability is the main factor affecting crop production at national, state and local scales. At field level spatial patterns on yield production are also determined by spatially changing soil properties in interaction with seasonal climate conditions and weather patterns at critical stages in the crop development. Here we used a combination of field level weather records, canopy characteristics, and satellite information to determine the spatial performance of a large field of wheat. The main objective of this research is to determine the ability of remote sensing technologies to capture yield losses due to water stress at the canopy level. The yield, canopy characteristics (i.e. canopy temperature and ground cover) and seasonal conditions of a field of wheat (~1400ha) (-29.402° South and 149.508°, New South Wales, Australia) were continuously monitored during the winter of 2011. Weather and crop variables were continuously monitored by installing three automatic weather stations in a transect covering different positions and soils in the landscape. Weather variables included rainfall, minimum and maximum temperatures and relative humidity, and crop characteristics included ground cover and canopy temperature. Satellite imagery Landsat TM 5 and 7 was collected at five different stages in the crop cycle. Weather variables and crop characteristics were used to calculate a crop stress index (CSI) at point and field scale (39 fields). Field data was used to validate a spatial satellite image derived index. Spatial yield data was downloaded from the harvester at the different locations in the field. We used the thermal band (land surface temperature, LST) and enhanced vegetation index (EVI) bands from the MODIS (250 m for visible bands and 1km for thermal band) and a derived EVI from Landsat TM 7 (25 m for visible and 90m for thermal) satellite platforms. Results showed that spatial variations in crop yield were related to a satellite derived canopy stress index (CSIsat) and a moisture stress index (MSIsat). A weather station level canopy stress index (CSIws) calculated at midday was correlated to the CSIsat at late morning. In addition, a strong linear relationship was observed between EVI and LST at point scale throughout the crop growth period. Differences were smallest at anthesis when the canopy closure was highest. This suggests that LST imagery data around flowering could be used to calculate crop stress over large areas of the crop. The harvested yield was related (R2 = 0.67) to CSIsat using a fix date across all fields. This relationship improved (R2 = 0.92) using both indices from all five dates across all fields during the crop growth period. Here we successfully showed that satellite derived crop attributes (CSIsat and MSIsat) can account for most of the variability in final crop yield and that they can be used to predict crop yield at field scales. Applications of these results could enhance the ability of producers to hedge their financial on -farm crop production losses due to in-season water stress by taking crop insurance. This is likely to further improve their adaptive capacity and thus strengthening the long-term viability of the industry domestically and elsewhere.

Influence of large-scale climate modes on dynamical complexity patterns of Indian Summer Monsoon rainfall

NASA Astrophysics Data System (ADS)

Papadimitriou, Constantinos; Donner, Reik V.; Stolbova, Veronika; Balasis, Georgios; Kurths, Jürgen

2015-04-01

Indian Summer monsoon is one of the most anticipated and important weather events with vast environmental, economical and social effects. Predictability of the Indian Summer Monsoon strength is crucial question for life and prosperity of the Indian population. In this study, we are attempting to uncover the relationship between the spatial complexity of Indian Summer Monsoon rainfall patterns, and the monsoon strength, in an effort to qualitatively determine how spatial organization of the rainfall patterns differs between strong and weak instances of the Indian Summer Monsoon. Here, we use observational satellite data from 1998 to 2012 from the Tropical Rainfall Measuring Mission (TRMM 3B42V7) and reanalysis gridded daily rainfall data for a time period of 57 years (1951-2007) (Asian Precipitation Highly Resolved Observational Data Integration Towards the Evaluation of Water Resources, APHRODITE). In order to capture different aspects of the system's dynamics, first, we convert rainfall time series to binary symbolic sequences, exploring various thresholding criteria. Second, we apply the Shannon entropy formulation (in a block-entropy sense) using different measures of normalization of the resulting entropy values. Finally, we examine the effect of various large-scale climate modes such as El-Niño-Southern Oscillation, North Atlantic Oscillation, and Indian Ocean Dipole, on the emerging complexity patterns, and discuss the possibility for the utilization of such pattern maps in the forecasting of the spatial variability and strength of the Indian Summer Monsoon.

Impact of the hydrological cycle on past climate changes: three illustrations at different time scales

NASA Astrophysics Data System (ADS)

Ramstein, Gilles; Khodri, Myriam; Donnadieu, Yannick; Fluteau, Frédéric; Goddéris, Yves

2005-02-01

We investigate in the paper the impact of the hydrologic cycle on climate at different periods. The aim is to illustrate how the changes in moisture transport, precipitation pattern, and weathering may alter, at regional or global scales, the CO 2 and climate equilibriums. We choose three climate periods to pinpoint intricate relationships between water cycle and climate. The illustrations are the following. ( i) The onset of ice-sheet build-up, 115 kyr BP. We show that the increased thermal meridian gradient of SST allows large moisture advection over the North American continent and provides appropriate conditions for perennial snow on the Canadian Archipelago. ( ii) The onset of Indian Monsoon at the end of the Tertiary. We demonstrate that superimposed to the Tibetan Plateau, the shrinkage of the Tethys, since Oligocene, plays a major role to explain changes in the geographical pattern of the southeastern Asian Monsoon. ( iii) The onset of Global Glaciation (750 Ma). We show that the break-up of Rodinia occurring at low latitudes is an important feature to explain how the important precipitation increase leads to weathering and carbon burial, which contribute to decrease atmospheric CO 2 enough to produce a snows ball Earth. All these periods have been simulated with a hierarchy of models appropriate to quantify the water cycle impact on climate. To cite this article: G. Ramstein et al., C. R. Geoscience 337 (2005).

Large-scale data analysis of power grid resilience across multiple US service regions

NASA Astrophysics Data System (ADS)

Ji, Chuanyi; Wei, Yun; Mei, Henry; Calzada, Jorge; Carey, Matthew; Church, Steve; Hayes, Timothy; Nugent, Brian; Stella, Gregory; Wallace, Matthew; White, Joe; Wilcox, Robert

2016-05-01

Severe weather events frequently result in large-scale power failures, affecting millions of people for extended durations. However, the lack of comprehensive, detailed failure and recovery data has impeded large-scale resilience studies. Here, we analyse data from four major service regions representing Upstate New York during Super Storm Sandy and daily operations. Using non-stationary spatiotemporal random processes that relate infrastructural failures to recoveries and cost, our data analysis shows that local power failures have a disproportionally large non-local impact on people (that is, the top 20% of failures interrupted 84% of services to customers). A large number (89%) of small failures, represented by the bottom 34% of customers and commonplace devices, resulted in 56% of the total cost of 28 million customer interruption hours. Our study shows that extreme weather does not cause, but rather exacerbates, existing vulnerabilities, which are obscured in daily operations.

An assessment of potential weather effects due to operation of the Space Orbiting Light Augmentation Reflector Energy System (SOLARES)

NASA Technical Reports Server (NTRS)

Allen, N. C.

1978-01-01

Implementation of SOLARES will input large quantities of heat continuously into a stationary location on the Earth's surface. The quantity of heat released by each of the SOlARES ground receivers, having a reflector orbit height of 6378 km, exceeds by 30 times that released by large power parks which were studied in detail. Using atmospheric models, estimates are presented for the local weather effects, the synoptic scale effects, and the global scale effects from such intense thermal radiation.

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.

Using NDVI to assess vegetative land cover change in central Puget Sound.

PubMed

Morawitz, Dana F; Blewett, Tina M; Cohen, Alex; Alberti, Marina

2006-03-01

We used the Normalized Difference Vegetation Index (NDVI) in the rapidly growing Puget Sound region over three 5-year time blocks between 1986-1999 at three spatial scales in 42 Watershed Administrative Units (WAUs) to assess changes in the amounts and patterns of green vegetation. On average, approximately 20% of the area in each WAU experienced significant NDVI change over each 5-year time block. Cumulative NDVI change over 15 years (summing change over each 5-year time block) was an average of approximately 60% of each WAU, but was as high as 100% in some. At the regional scale, seasonal weather patterns and green-up from logging were the primary drivers of observed increases in NDVI values. At the WAU scale, anthropogenic factors were important drivers of both positive and negative NDVI change. For example, population density was highly correlated with negative NDVI change over 15 years (r = 0.66, P < 0.01), as was road density (r = 0.71, P < 0.01). At the smallest scale (within 3 case study WAUs) land use differences such as preserving versus harvesting forest lands drove vegetation change. We conclude that large areas within most watersheds are continually and heavily impacted by the high levels of human use and development over short time periods. Our results indicate that varying patterns and processes can be detected at multiple scales using changes in NDVIa values.

Wildland fire probabilities estimated from weather model-deduced monthly mean fire danger indices

Treesearch

Haiganoush K. Preisler; Shyh-Chin Chen; Francis Fujioka; John W. Benoit; Anthony L. Westerling

2008-01-01

The National Fire Danger Rating System indices deduced from a regional simulation weather model were used to estimate probabilities and numbers of large fire events on monthly and 1-degree grid scales. The weather model simulations and forecasts are ongoing experimental products from the Experimental Climate Prediction Center at the Scripps Institution of Oceanography...

Environmental change pattern in central Japan as revealed by LANDSAT data

NASA Technical Reports Server (NTRS)

Maruyasu, T. (Principal Investigator); Tsuchiya, K.; Ochiai, H.

1977-01-01

The author has identified the following significant results. A patched cirrus reported by weather stations was hardly recognizable by the eye in LANDSAT MSS data of a three year time lapse. The cloud cover affected radiance values significantly in band 4, while its effect was minimal in bands 6 and 7 (near infrared spectra). The cross correlation coefficient analysis between the two images indicated that the highest value obtained in central Japan was 0.963 for the area where little change occurred in land use over the three period. An analysis of land use in Nagoya showed little change in the metropolitan area while a fairly large change occurred in the northern periphery of the city where large scale housing projects are located.

Abrupt response of chemical weathering to Late Quaternary hydroclimate changes in northeast Africa

PubMed Central

Bastian, Luc; Revel, Marie; Bayon, Germain; Dufour, Aurélie; Vigier, Nathalie

2017-01-01

Chemical weathering of silicate rocks on continents acts as a major sink for atmospheric carbon dioxide and has played an important role in the evolution of the Earth’s climate. However, the magnitude and the nature of the links between weathering and climate are still under debate. In particular, the timescale over which chemical weathering may respond to climate change is yet to be constrained at the continental scale. Here we reconstruct the relationships between rainfall and chemical weathering in northeast Africa for the last 32,000 years. Using lithium isotopes and other geochemical proxies in the clay-size fraction of a marine sediment core from the Eastern Mediterranean Sea, we show that chemical weathering in the Nile Basin fluctuated in parallel with the monsoon-related climatic evolution of northeast Africa. We also evidence strongly reduced mineral alteration during centennial-scale regional drought episodes. Our findings indicate that silicate weathering may respond as quickly as physical erosion to abrupt hydroclimate reorganization on continents. Consequently, we anticipate that the forthcoming hydrological disturbances predicted for northeast Africa may have a major impact on chemical weathering patterns and soil resources in this region. PMID:28290474

Abrupt response of chemical weathering to Late Quaternary hydroclimate changes in northeast Africa.

PubMed

Bastian, Luc; Revel, Marie; Bayon, Germain; Dufour, Aurélie; Vigier, Nathalie

2017-03-14

Chemical weathering of silicate rocks on continents acts as a major sink for atmospheric carbon dioxide and has played an important role in the evolution of the Earth's climate. However, the magnitude and the nature of the links between weathering and climate are still under debate. In particular, the timescale over which chemical weathering may respond to climate change is yet to be constrained at the continental scale. Here we reconstruct the relationships between rainfall and chemical weathering in northeast Africa for the last 32,000 years. Using lithium isotopes and other geochemical proxies in the clay-size fraction of a marine sediment core from the Eastern Mediterranean Sea, we show that chemical weathering in the Nile Basin fluctuated in parallel with the monsoon-related climatic evolution of northeast Africa. We also evidence strongly reduced mineral alteration during centennial-scale regional drought episodes. Our findings indicate that silicate weathering may respond as quickly as physical erosion to abrupt hydroclimate reorganization on continents. Consequently, we anticipate that the forthcoming hydrological disturbances predicted for northeast Africa may have a major impact on chemical weathering patterns and soil resources in this region.

Severe Weather Forecast Decision Aid

NASA Technical Reports Server (NTRS)

Bauman, William H., III; Wheeler, Mark M.; Short, David A.

2005-01-01

This report presents a 15-year climatological study of severe weather events and related severe weather atmospheric parameters. Data sources included local forecast rules, archived sounding data, Cloud-to-Ground Lightning Surveillance System (CGLSS) data, surface and upper air maps, and two severe weather event databases covering east-central Florida. The local forecast rules were used to set threat assessment thresholds for stability parameters that were derived from the sounding data. The severe weather events databases were used to identify days with reported severe weather and the CGLSS data was used to differentiate between lightning and non-lightning days. These data sets provided the foundation for analyzing the stability parameters and synoptic patterns that were used to develop an objective tool to aid in forecasting severe weather events. The period of record for the analysis was May - September, 1989 - 2003. The results indicate that there are certain synoptic patterns more prevalent on days with severe weather and some of the stability parameters are better predictors of severe weather days based on locally tuned threat values. The results also revealed the stability parameters that did not display any skill related to severe weather days. An interactive web-based Severe Weather Decision Aid was developed to assist the duty forecaster by providing a level of objective guidance based on the analysis of the stability parameters, CGLSS data, and synoptic-scale dynamics. The tool will be tested and evaluated during the 2005 warm season.

Assessing landscape scale wildfire exposure for highly valued resources in a Mediterranean area.

PubMed

Alcasena, Fermín J; Salis, Michele; Ager, Alan A; Arca, Bachisio; Molina, Domingo; Spano, Donatella

2015-05-01

We used a fire simulation modeling approach to assess landscape scale wildfire exposure for highly valued resources and assets (HVR) on a fire-prone area of 680 km(2) located in central Sardinia, Italy. The study area was affected by several wildfires in the last half century: some large and intense fire events threatened wildland urban interfaces as well as other socioeconomic and cultural values. Historical wildfire and weather data were used to inform wildfire simulations, which were based on the minimum travel time algorithm as implemented in FlamMap. We simulated 90,000 fires that replicated recent large fire events in the area spreading under severe weather conditions to generate detailed maps of wildfire likelihood and intensity. Then, we linked fire modeling outputs to a geospatial risk assessment framework focusing on buffer areas around HVR. The results highlighted a large variation in burn probability and fire intensity in the vicinity of HVRs, and allowed us to identify the areas most exposed to wildfires and thus to a higher potential damage. Fire intensity in the HVR buffers was mainly related to fuel types, while wind direction, topographic features, and historically based ignition pattern were the key factors affecting fire likelihood. The methodology presented in this work can have numerous applications, in the study area and elsewhere, particularly to address and inform fire risk management, landscape planning and people safety on the vicinity of HVRs.

Seasonality and weather conditions jointly drive flight activity patterns of aquatic and terrestrial chironomids.

PubMed

Vebrová, Lucie; van Nieuwenhuijzen, Andre; Kolář, Vojtěch; Boukal, David S

2018-06-19

Chironomids, a major invertebrate taxon in many standing freshwaters, rely on adult flight to reach new suitable sites, yet the impact of weather conditions on their flight activity is little understood. We investigated diel and seasonal flight activity patterns of aquatic and terrestrial chironomids in a reclaimed sandpit area and analysed how weather conditions and seasonality influenced their total abundance and species composition. Air temperature, relative humidity, wind speed, and air pressure significantly affected total flight activity of both groups, but not in the same way. We identified an intermediate temperature and humidity optimum for the flight activity of terrestrial chironomids, which contrasted with weaker, timescale-dependent relationships in aquatic species. Flight activity of both groups further declined with wind speed and increased with air pressure. Observed flight patterns also varied in time on both daily and seasonal scale. Flight activity of both groups peaked in the evenings after accounting for weather conditions but, surprisingly, aquatic and terrestrial chironomids used partly alternating time windows for dispersal during the season. This may be driven by different seasonal trends of key environmental variables in larval habitats and hence implies that species phenologies and conditions experienced by chironomid larvae (and probably other aquatic insects with short-lived adults) influence adult flight patterns more than weather conditions. Our results provide detailed insights into the drivers of chironomid flight activity and highlight the methodological challenges arising from the inherent collinearity of weather characteristics and their diurnal and seasonal cycles.

How does pedogenesis drive plant diversity?

PubMed

Laliberté, Etienne; Grace, James B; Huston, Michael A; Lambers, Hans; Teste, François P; Turner, Benjamin L; Wardle, David A

2013-06-01

Some of the most species-rich plant communities occur on ancient, strongly weathered soils, whereas those on recently developed soils tend to be less diverse. Mechanisms underlying this well-known pattern, however, remain unresolved. Here, we present a conceptual model describing alternative mechanisms by which pedogenesis (the process of soil formation) might drive plant diversity. We suggest that long-term soil chronosequences offer great, yet largely untapped, potential as 'natural experiments' to determine edaphic controls over plant diversity. Finally, we discuss how our conceptual model can be evaluated quantitatively using structural equation modeling to advance multivariate theories about the determinants of local plant diversity. This should help us to understand broader-scale diversity patterns, such as the latitudinal gradient of plant diversity. Copyright © 2013 Elsevier Ltd. All rights reserved.

Mountain ranges, climate and weathering. Do orogens strengthen or weaken the silicate weathering carbon sink?

NASA Astrophysics Data System (ADS)

Maffre, Pierre; Ladant, Jean-Baptiste; Moquet, Jean-Sébastien; Carretier, Sébastien; Labat, David; Goddéris, Yves

2018-07-01

The role of mountains in the geological evolution of the carbon cycle has been intensively debated for the last decades. Mountains are thought to increase the local physical erosion, which in turns promotes silicate weathering, organic carbon transport and burial, and release of sulfuric acid by dissolution of sulfides. In this contribution, we explore the impact of mountain ranges on silicate weathering. Mountains modify the global pattern of atmospheric circulation as well as the local erosion conditions. Using an IPCC-class climate model, we first estimate the climatic impact of mountains by comparing the present day climate with the climate when all the continents are assumed to be flat. We then use these climate output to calculate weathering changes when mountains are present or absent, using standard expression for physical erosion and a 1D vertical model for rock weathering. We found that large-scale climate changes and enhanced rock supply by erosion due to mountain uplift have opposite effect, with similar orders of magnitude. A thorough testing of the weathering model parameters by data-model comparison shows that best-fit parameterizations lead to a decrease of weathering rate in the absence of mountain by about 20%. However, we demonstrate that solutions predicting an increase in weathering in the absence of mountain cannot be excluded. A clear discrimination between the solutions predicting an increase or a decrease in global weathering is pending on the improvement of the existing global databases for silicate weathering. Nevertheless, imposing a constant and homogeneous erosion rate for models without relief, we found that weathering decrease becomes unequivocal for very low erosion rates (below 10 t/km2/yr). We conclude that further monitoring of continental silicate weathering should be performed with a spatial distribution allowing to discriminate between the various continental landscapes (mountains, plains …).

Coring the deep critical zone in the Jemez River Basin Critical Zone Observatory, Valles Caldera National Preserve, Northern New Mexico

NASA Astrophysics Data System (ADS)

Moravec, B. G.; White, A. M.; Paras, B.; Sanchez, A.; McGuffy, C.; Fairbanks, D.; McIntosh, J. C.; Pelletier, J. D.; Gallery, R. E.; Rasmussen, C.; Carr, B.; Holbrook, W. S.; Chorover, J.

2016-12-01

The Critical Zone (CZ) is the focus of current interdisciplinary Earth surface science research that aims to describe the interactions between geological and biological processes that influence ecosystem function, soil formation, nutrient and carbon cycling, hydrologic partitioning, biological activity and diversity, and mineral weathering. Prior research at the Catalina-Jemez (C-J) CZO has focused on the CZ near-surface, including remote sensing, and sampling/analysis of vegetation and soil microbiota, soils and saprolite, and surface water. However, the extent to which weathering, water/rock interaction, and solute mobility along flowpaths in the deep CZ respond to near surface CZ processes (i.e. water, energy, and mass fluxes) is not well understood. The goal of the present research is to understand depth-dependent trends in weathering dynamics from the mobile soil to unweathered bedrock in relation to landscape position (hillslope aspect and downgradient hollow). We used diamond core drilling techniques to excavate three boreholes to depths of 18.9, 41.8, and 46.3 meters in an instrumented forested sub-catchment of the C-J CZO in northern New Mexico. Here we present field methodology and preliminary data collected during the field campaign conducted during summer 2016. Element concentrations were measured during core extractions using portable X-ray fluorescence (XRF), which was subsequently validated against bench-scale XRF. Depth-dependent trends in both regolith depth and chemical depletion patterns show significant variation with landscape position. All three boreholes show complex weathering profiles with differences potentially due to textural controls on weathering, development of preferential flowpaths, and differing hydrologic base levels. Preliminary data indicate that chemical depletion patterns are not monotonic, but rather comprise large excursions that are being investigated for their relation to variation in local mineralogical composition and incongruent weathering reactions.

Diagnosing Possible Anthropogenic Contributions to Colorado Floods in September 2013.

NASA Astrophysics Data System (ADS)

Pall, P.; Patricola, C. M.; Wehner, M. F.; Stone, D. A.

2015-12-01

Unusually heavy rainfall occurred over the Colorado Front Range during the second week of September 2013, with record or near-record totals recorded in several locations. It was associated predominantly with a stationary large-scale weather pattern (akin to the North American Monsoon, which occurs earlier in the year) that drove a strong plume of deep moisture inland from the Gulf of Mexico and eastern tropical Pacific towards the Front Range foothills. The resulting floods across the South Platte River basin impacted several thousands of people and many homes, roads, and businesses. A recent study using observational-based re-analysis to drive the regional WRF model finds that, given very little change in the large-scale weather pattern, there is an increase in atmospheric water vapour over northeast Colorado under anthropogenic climate warming, with a positive dynamical feedback drawing in moisture from further afield. This leads to a substantial increase in the magnitude and odds of heavy rainfall occurring over northeast Colorado during the rainy week of September 2013. Here we develop this work by including a hydrological modelling component in order to investigate any anthropogenic influence on the actual flood magnitude and occurrence across the South Platte basin during that time. We use WRF precipitation output from the aforementioned study - in both anthropogenic and non-anthropogenic configurations for September 2013 - to drive the recently developed high-resolution WRF-Hydro model over the basin and generate river runoff. Thus by comparing changes in runoff under the anthropogenic / non-anthropogenic driving conditions we assess any influence on the magnitude and odds of flood occurrence. Integral to this, we test the sensitivity of our results to hydrological parameters, such as infiltration, base flow, and land use/cover.

Diagnosing Possible Anthropogenic Contributions to Heavy Colorado Rainfall in September 2013

NASA Astrophysics Data System (ADS)

Pall, P.; Patricola, C. M.; Wehner, M. F.; Stone, D. A.; Paciorek, C. J.; Collins, W.

2014-12-01

Unusually heavy rainfall occurred over the Colorado Front Range during early September 2013, with record or near-record totals recorded in several locations. It was associated predominantly with a stationary large-scale weather pattern (akin to the North American Monsoon, which occurs earlier in the year) that drove a strong plume of deep moisture inland from the Gulf of Mexico against the Front Range foothills. The resulting floods impacted several thousands of people and many homes, roads, and businesses. To diagnose possible anthropogenic contributions to the odds of such heavy rainfall, we adapt an existing event attribution paradigm of modelling a 'world that was' for September 2013 and comparing it to a modelled 'world that might have been' for that same time but for the absence of historical anthropogenic drivers of climate. Specifically, we first perform 'world that was' simulations with the regional WRF model at 12 km resolution over North America, driven by NCEP2 re-analysis. We then re-simulate, having adjusted the re-analysis to 'world that might have been conditions' by modifying atmospheric greenhouse gas and other pollutant concentrations, temperature, humidity, and winds, as well as sea ice coverage, and sea-surface temperatures - all according to estimates from global climate model simulations. Thus our findings are highly conditional on the driving re-analysis and adjustments therein, but the setup allows us to elucidate possible mechanisms responsible for heavy Colorado rainfall in September 2013. For example, preliminary analysis suggests that, given no change in the pattern of large-scale driving weather, there is an increase in atmospheric water vapour under anthropogenic climate warming leading to a substantial increase in the odds of heavy rainfall over the Front Range.

Do GCM's Predict the Climate.... Or the Low Frequency Weather?

NASA Astrophysics Data System (ADS)

Lovejoy, S.; Varon, D.; Schertzer, D. J.

2011-12-01

Over twenty-five years ago, a three-regime scaling model was proposed describing the statistical variability of the atmosphere over time scales ranging from weather scales out to ≈ 100 kyrs. Using modern in situ data reanalyses, monthly surface series (at 5ox5o), 8 "multiproxy" (yearly) series of the Northern hemisphere from 1500- 1980, and GRIP and Vostok paleotemperatures at 5.2 and ≈ 100 year resolutions (over the past 91-420 kyrs), we refine the model and show how it can be understood with the help of new developments in nonlinear dynamics, especially multifractals and cascades. In a scaling range, mean fluctuations in state variables such as temperature ΔT ≈ ΔtH the where Δt is the duration. At small (weather) scales the fluctuation exponents are generally H>0; they grow with scale. At longer scales Δt >τw (≈ 10 days) they change sign, the fluctuations decrease with scale; this is the low variability, "low frequency weather" regime the spectrum is a relatively flat "plateau", it's variability is that of the usual idea of "long term weather statistics". Finally for longer times, Δt>τc ≈ 10 - 100 years, again H>0, the variability again increases with scale. This is the true climate regime. These scaling regimes allow us to objectively define the weather as fluctuations over periods <τw, "climate states", as fluctuations at scale τc and "climate change" as the fluctuations at longer periods >τc). We show that the intermediate regime is the result of the weather regime undergoing a "dimensional transition": at temporal scales longer than the typical lifetime of planetary structures (τw), the spatial degrees of freedom are rapidly quenched, only the temporal degrees of freedom are important. This low frequency weather regime has statistical properties well reproduced not only by weather cascade models, but also by control runs (i.e. without climate forcing) of GCM's (including IPSL and ECHAM GCM's). In order for GCM's to go beyond simply predicting this low frequency weather so as to predict the climate, they need appropriate climate forcings and/ or new internal mechanisms of variability. We examine this using wavelet analyses of forced and unforced GCM outputs, including the ECHO-G simulation used in the Millenium project. For example, we find that climate scenarios with large CO2 increases do give rise to a climate regime but that Hc>1 i.e. much larger than that of natural variability which for temperatures has Hc≈0.4. In comparison, the (largely volcanic) forcing of the ECHO-G Millenium simulation is fairly realistic (Hc≈0.4), although it is not clear that this mechanism can explain the even lower frequency variability found in the paleotemperature series, nor is it clear that this is compatible with low frequency solar or orbital forcings.

Downscaling large-scale circulation to local winter climate using neural network techniques

NASA Astrophysics Data System (ADS)

Cavazos Perez, Maria Tereza

1998-12-01

The severe impacts of climate variability on society reveal the increasing need for improving regional-scale climate diagnosis. A new downscaling approach for climate diagnosis is developed here. It is based on neural network techniques that derive transfer functions from the large-scale atmospheric controls to the local winter climate in northeastern Mexico and southeastern Texas during the 1985-93 period. A first neural network (NN) model employs time-lagged component scores from a rotated principal component analysis of SLP, 500-hPa heights, and 1000-500 hPa thickness as predictors of daily precipitation. The model is able to reproduce the phase and, to some decree, the amplitude of large rainfall events, reflecting the influence of the large-scale circulation. Large errors are found over the Sierra Madre, over the Gulf of Mexico, and during El Nino events, suggesting an increase in the importance of meso-scale rainfall processes. However, errors are also due to the lack of randomization of the input data and the absence of local atmospheric predictors such as moisture. Thus, a second NN model uses time-lagged specific humidity at the Earth's surface and at the 700 hPa level, SLP tendency, and 700-500 hPa thickness as input to a self-organizing map (SOM) that pre-classifies the atmospheric fields into different patterns. The results from the SOM classification document that negative (positive) anomalies of winter precipitation over the region are associated with: (1) weaker (stronger) Aleutian low; (2) stronger (weaker) North Pacific high; (3) negative (positive) phase of the Pacific North American pattern; and (4) La Nina (El Nino) events. The SOM atmospheric patterns are then used as input to a feed-forward NN that captures over 60% of the daily rainfall variance and 94% of the daily minimum temperature variance over the region. This demonstrates the ability of artificial neural network models to simulate realistic relationships on daily time scales. The results of this research also reveal that the SOM pre-classification of days with similar atmospheric conditions succeeded in emphasizing the differences of the atmospheric variance conducive to extreme events. This resulted in a downscaling NN model that is highly sensitive to local-scale weather anomalies associated with El Nino and extreme cold events.

Using Unplanned Fires to Help Suppressing Future Large Fires in Mediterranean Forests

PubMed Central

Regos, Adrián; Aquilué, Núria; Retana, Javier; De Cáceres, Miquel; Brotons, Lluís

2014-01-01

Despite the huge resources invested in fire suppression, the impact of wildfires has considerably increased across the Mediterranean region since the second half of the 20th century. Modulating fire suppression efforts in mild weather conditions is an appealing but hotly-debated strategy to use unplanned fires and associated fuel reduction to create opportunities for suppression of large fires in future adverse weather conditions. Using a spatially-explicit fire–succession model developed for Catalonia (Spain), we assessed this opportunistic policy by using two fire suppression strategies that reproduce how firefighters in extreme weather conditions exploit previous fire scars as firefighting opportunities. We designed scenarios by combining different levels of fire suppression efficiency and climatic severity for a 50-year period (2000–2050). An opportunistic fire suppression policy induced large-scale changes in fire regimes and decreased the area burnt under extreme climate conditions, but only accounted for up to 18–22% of the area to be burnt in reference scenarios. The area suppressed in adverse years tended to increase in scenarios with increasing amounts of area burnt during years dominated by mild weather. Climate change had counterintuitive effects on opportunistic fire suppression strategies. Climate warming increased the incidence of large fires under uncontrolled conditions but also indirectly increased opportunities for enhanced fire suppression. Therefore, to shift fire suppression opportunities from adverse to mild years, we would require a disproportionately large amount of area burnt in mild years. We conclude that the strategic planning of fire suppression resources has the potential to become an important cost-effective fuel-reduction strategy at large spatial scale. We do however suggest that this strategy should probably be accompanied by other fuel-reduction treatments applied at broad scales if large-scale changes in fire regimes are to be achieved, especially in the wider context of climate change. PMID:24727853

Using unplanned fires to help suppressing future large fires in Mediterranean forests.

PubMed

Regos, Adrián; Aquilué, Núria; Retana, Javier; De Cáceres, Miquel; Brotons, Lluís

2014-01-01

Despite the huge resources invested in fire suppression, the impact of wildfires has considerably increased across the Mediterranean region since the second half of the 20th century. Modulating fire suppression efforts in mild weather conditions is an appealing but hotly-debated strategy to use unplanned fires and associated fuel reduction to create opportunities for suppression of large fires in future adverse weather conditions. Using a spatially-explicit fire-succession model developed for Catalonia (Spain), we assessed this opportunistic policy by using two fire suppression strategies that reproduce how firefighters in extreme weather conditions exploit previous fire scars as firefighting opportunities. We designed scenarios by combining different levels of fire suppression efficiency and climatic severity for a 50-year period (2000-2050). An opportunistic fire suppression policy induced large-scale changes in fire regimes and decreased the area burnt under extreme climate conditions, but only accounted for up to 18-22% of the area to be burnt in reference scenarios. The area suppressed in adverse years tended to increase in scenarios with increasing amounts of area burnt during years dominated by mild weather. Climate change had counterintuitive effects on opportunistic fire suppression strategies. Climate warming increased the incidence of large fires under uncontrolled conditions but also indirectly increased opportunities for enhanced fire suppression. Therefore, to shift fire suppression opportunities from adverse to mild years, we would require a disproportionately large amount of area burnt in mild years. We conclude that the strategic planning of fire suppression resources has the potential to become an important cost-effective fuel-reduction strategy at large spatial scale. We do however suggest that this strategy should probably be accompanied by other fuel-reduction treatments applied at broad scales if large-scale changes in fire regimes are to be achieved, especially in the wider context of climate change.

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.

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.

Moisture source classification of heavy precipitation events in Switzerland in the last 130 years (1871-2011)

NASA Astrophysics Data System (ADS)

Aemisegger, Franziska; Piaget, Nicolas

2017-04-01

A new weather-system oriented classification framework of extreme precipitation events leading to large-scale floods in Switzerland is presented on this poster. Thirty-six high impact floods in the last 130 years are assigned to three representative categories of atmospheric moisture origin and transport patterns. The methodology underlying this moisture source classification combines information of the airmass history in the twenty days preceding the precipitation event with humidity variations along the large-scale atmospheric transport systems in a Lagrangian approach. The classification scheme is defined using the 33-year ERA-Interim reanalysis dataset (1979-2011) and is then applied to the Twentieth Century Reanalysis (1871-2011) extreme precipitation events as well as the 36 selected floods. The three defined categories are characterised by different dominant moisture uptake regions including the North Atlantic, the Mediterranean and continental Europe. Furthermore, distinct anomalies in the large-scale atmospheric flow are associated with the different categories. The temporal variations in the relative importance of the three categories over the last 130 years provides new insights into the impact of changing climate conditions on the dynamical mechanisms leading to heavy precipitation in Switzerland.

Large-scale derived flood frequency analysis based on continuous simulation

NASA Astrophysics Data System (ADS)

Dung Nguyen, Viet; Hundecha, Yeshewatesfa; Guse, Björn; Vorogushyn, Sergiy; Merz, Bruno

2016-04-01

There is an increasing need for spatially consistent flood risk assessments at the regional scale (several 100.000 km2), in particular in the insurance industry and for national risk reduction strategies. However, most large-scale flood risk assessments are composed of smaller-scale assessments and show spatial inconsistencies. To overcome this deficit, a large-scale flood model composed of a weather generator and catchments models was developed reflecting the spatially inherent heterogeneity. The weather generator is a multisite and multivariate stochastic model capable of generating synthetic meteorological fields (precipitation, temperature, etc.) at daily resolution for the regional scale. These fields respect the observed autocorrelation, spatial correlation and co-variance between the variables. They are used as input into catchment models. A long-term simulation of this combined system enables to derive very long discharge series at many catchment locations serving as a basic for spatially consistent flood risk estimates at the regional scale. This combined model was set up and validated for major river catchments in Germany. The weather generator was trained by 53-year observation data at 528 stations covering not only the complete Germany but also parts of France, Switzerland, Czech Republic and Australia with the aggregated spatial scale of 443,931 km2. 10.000 years of daily meteorological fields for the study area were generated. Likewise, rainfall-runoff simulations with SWIM were performed for the entire Elbe, Rhine, Weser, Donau and Ems catchments. The validation results illustrate a good performance of the combined system, as the simulated flood magnitudes and frequencies agree well with the observed flood data. Based on continuous simulation this model chain is then used to estimate flood quantiles for the whole Germany including upstream headwater catchments in neighbouring countries. This continuous large scale approach overcomes the several drawbacks reported in traditional approaches for the derived flood frequency analysis and therefore is recommended for large scale flood risk case studies.

Linking Satellite-Derived Fire Counts to Satellite-Derived Weather Data in Fire Prediction Models to Forecast Extreme Fires in Siberia

NASA Astrophysics Data System (ADS)

Westberg, David; Soja, Amber; Stackhouse, Paul, Jr.

2010-05-01

Fire is the dominant disturbance that precipitates ecosystem change in boreal regions, and fire is largely under the control of weather and climate. Boreal systems contain the largest pool of terrestrial carbon, and Russia holds 2/3 of the global boreal forests. Fire frequency, fire severity, area burned and fire season length are predicted to increase in boreal regions under climate change scenarios. Meteorological parameters influence fire danger and fire is a catalyst for ecosystem change. Therefore to predict fire weather and ecosystem change, we must understand the factors that influence fire regimes and at what scale these are viable. Our data consists of NASA Langley Research Center (LaRC)-derived fire weather indices (FWI) and National Climatic Data Center (NCDC) surface station-derived FWI on a domain from 50°N-80°N latitude and 70°E-170°W longitude and the fire season from April through October for the years of 1999, 2002, and 2004. Both of these are calculated using the Canadian Forest Service (CFS) FWI, which is based on local noon surface-level air temperature, relative humidity, wind speed, and daily (noon-noon) rainfall. The large-scale (1°) LaRC product uses NASA Goddard Earth Observing System version 4 (GEOS-4) reanalysis and NASA Global Precipitation Climatology Project (GEOS-4/GPCP) data to calculate FWI. CFS Natural Resources Canada uses Geographic Information Systems (GIS) to interpolate NCDC station data and calculate FWI. We compare the LaRC GEOS- 4/GPCP FWI and CFS NCDC FWI based on their fraction of 1° grid boxes that contain satellite-derived fire counts and area burned to the domain total number of 1° grid boxes with a common FWI category (very low to extreme). These are separated by International Geosphere-Biosphere Programme (IGBP) 1°x1° resolution vegetation types to determine and compare fire regimes in each FWI/ecosystem class and to estimate the fraction of each of the 18 IGBP ecosystems burned, which are dependent on the FWI. On days with fire counts, the domain total of 1°x1° grid boxes with and without daily fire counts and area burned are totaled. The fraction of 1° grid boxes with fire counts and area burned to the total number of 1° grid boxes having common FWI category and vegetation type are accumulated, and a daily mean for the burning season is calculated. The mean fire counts and mean area burned plots appear to be well related. The ultimate goal of this research is to assess the viability of large-scale (1°) data to be used to assess fire weather danger and fire regimes, so these data can be confidently used to predict future fire regimes using large-scale fire weather data. Specifically, we related large-scale fire weather, area burned, and the amount of fire-induced ecosystem change. Both the LaRC and CFS FWI showed gradual linear increase in fraction of grid boxes with fire counts and area burned with increasing FWI category, with an exponential increase in the higher FWI categories in some cases, for the majority of the vegetation types. Our analysis shows a direct correlation between increased fire activity and increased FWI, independent of time or the severity of the fire season. During normal and extreme fire seasons, we noticed the fraction of fire counts and area burned per 1° grid box increased with increasing FWI rating. Given this analysis, we are confident large-scale weather and climate data, in this case from the GEOS-4 reanalysis and the GPCP data sets, can be used to accurately assess future fire potential. This increases confidence in the ability of large-scale IPCC weather and climate scenarios to predict future fire regimes in boreal regions.

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.

Atmospheric forcing of sea ice leads in the Beaufort Sea

NASA Astrophysics Data System (ADS)

Lewis, B. J.; Hutchings, J.; Mahoney, A. R.; Shapiro, L. H.

2016-12-01

Leads in sea ice play an important role in the polar marine environment where they allow heat and moisture transfer between the oceans and atmosphere and act as travel pathways for both marine mammals and ships. Examining AVHRR thermal imagery of the Beaufort Sea, collected between 1994 and 2010, sea ice leads appear in repeating patterns and locations (Eicken et al 2005). The leads, resolved by AVHRR, are at least 250m wide (Mahoney et al 2012), thus the patterns described are for lead systems that extend up to hundreds of kilometers across the Beaufort Sea. We describe how these patterns are associated with the location of weather systems relative to the coastline. Mean sea level pressure and 10m wind fields from ECMWF ERA-Interim reanalysis are used to identify if particular lead patterns can be uniquely forecast based on the location of weather systems. Ice drift data from the NSIDC's Polar Pathfinder Daily 25km EASE-Grid Sea Ice Motion Vectors indicates the role shear along leads has on the motion of ice in the Beaufort Gyre. Lead formation is driven by 4 main factors: (i) coastal features such as promontories and islands influence the origin of leads by concentrating stresses within the ice pack; (ii) direction of the wind forcing on the ice pack determines the type of fracture, (iii) the location of the anticyclone (or cyclone) center determines the length of the fracture for certain patterns; and (iv) duration of weather conditions affects the width of the ice fracture zones. Movement of the ice pack on the leeward side of leads originating at promontories and islands increases, creating shear zones that control ice transport along the Alaska coast in winter. . Understanding how atmospheric conditions influence the large-scale motion of the ice pack is needed to design models that predict variability of the gyre and export of multi-year ice to lower latitudes.

Atmospheric turbulence triggers pronounced diel pattern in karst carbonate geochemistry

NASA Astrophysics Data System (ADS)

Roland, M.; Serrano-Ortiz, P.; Kowalski, A. S.; Goddéris, Y.; Sánchez-Cañete, E. P.; Ciais, P.; Domingo, F.; Cuezva, S.; Sanchez-Moral, S.; Longdoz, B.; Yakir, D.; Van Grieken, R.; Schott, J.; Cardell, C.; Janssens, I. A.

2013-07-01

CO2 exchange between terrestrial ecosystems and the atmosphere is key to understanding the feedbacks between climate change and the land surface. In regions with carbonaceous parent material, CO2 exchange patterns occur that cannot be explained by biological processes, such as disproportionate outgassing during the daytime or nighttime CO2 uptake during periods when all vegetation is senescent. Neither of these phenomena can be attributed to carbonate weathering reactions, since their CO2 exchange rates are too small. Soil ventilation induced by high atmospheric turbulence is found to explain atypical CO2 exchange between carbonaceous systems and the atmosphere. However, by strongly altering subsurface CO2 concentrations, ventilation can be expected to influence carbonate weathering rates. By imposing ventilation-driven CO2 outgassing in a carbonate weathering model, we show here that carbonate geochemistry is accelerated and does play a surprisingly large role in the observed CO2 exchange pattern of a semi-arid ecosystem. We found that by rapidly depleting soil CO2 during the daytime, ventilation disturbs soil carbonate equilibria and therefore strongly magnifies daytime carbonate precipitation and associated CO2 production. At night, ventilation ceases and the depleted CO2 concentrations increase steadily. Dissolution of carbonate is now enhanced, which consumes CO2 and largely compensates for the enhanced daytime carbonate precipitation. This is why only a relatively small effect on global carbonate weathering rates is to be expected. On the short term, however, ventilation has a drastic effect on synoptic carbonate weathering rates, resulting in a pronounced diel pattern that exacerbates the non-biological behavior of soil-atmosphere CO2 exchanges in dry regions with carbonate soils.

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...

Quantifying nonstationary radioactivity concentration fluctuations near Chernobyl: A complete statistical description

NASA Astrophysics Data System (ADS)

Viswanathan, G. M.; Buldyrev, S. V.; Garger, E. K.; Kashpur, V. A.; Lucena, L. S.; Shlyakhter, A.; Stanley, H. E.; Tschiersch, J.

2000-09-01

We analyze nonstationary 137Cs atmospheric activity concentration fluctuations measured near Chernobyl after the 1986 disaster and find three new results: (i) the histogram of fluctuations is well described by a log-normal distribution; (ii) there is a pronounced spectral component with period T=1yr, and (iii) the fluctuations are long-range correlated. These findings allow us to quantify two fundamental statistical properties of the data: the probability distribution and the correlation properties of the time series. We interpret our findings as evidence that the atmospheric radionuclide resuspension processes are tightly coupled to the surrounding ecosystems and to large time scale weather patterns.

Modeling Mars Cyclogenesis and Frontal Waves: Seasonal Variations and Implications on Dust Activity

NASA Technical Reports Server (NTRS)

Hollingsworth, J. L.; Kahre, M. A.

2014-01-01

Between late autumn through early spring,middle and high latitudes onMars exhibit strong equator-to-polemean temperature contrasts (i.e., "baroclinicity"). Data collected during the Viking era and observations from both the Mars Global Surveyor (MGS) and Mars Reconnaissance Orbiter (MRO) indicate that such strong baroclinicity supports vigorous, large-scale eastward traveling weather systems (i.e., transient synoptic period waves) [1, 2]. For a rapidly rotating, differentially heated, shallow atmosphere such as on Earth and Mars, these large-scale, extratropical weather disturbances are critical components of the global circulation. The wave-like disturbances serve as agents in the transport of heat and momentum between low and high latitudes of the planet. Through cyclonic/anticyclonic winds, intense shear deformations, contractions-dilatations in temperature and density, and sharp perturbations amongst atmospheric tracers (i.e., dust, volatiles (e.g., water vapor) and condensates (e.g., water-ice cloud particles)), Mars' extratropical weather systems have significant sub-synoptic scale ramifications by supporting atmospheric frontal waves (Fig. 1).

Influence of Kuroshio Oceanic Eddies on North Pacific Weather Patterns

NASA Astrophysics Data System (ADS)

Ma, X.; Chang, P.; Saravanan, R.; Montuoro, R.; Hsieh, J. S.; Wu, D.; Lin, X.; Wu, L.; Jing, Z.

2016-02-01

High-resolution satellite observations reveal energetic meso-scale ocean eddy activity and positive correlation between meso-scale sea surface temperature (SST) and surface wind along oceanic frontal zones, such as the Kuroshio and Gulf Stream, suggesting a potential role of meso-scale oceanic eddies in forcing the atmosphere. Using a 27 km horizontal resolution Weather Research Forecasting (WRF) model forced with observed daily SST at 0.09° spatial resolution during boreal winter season, two ensembles of 10 WRF simulations, in one of which meso-scale SST variability induced by ocean eddies was suppressed, were conducted in the North Pacific to study the local and remote influence of meso-scale oceanic eddies in the Kuroshio Extention Region (KER) on the atmosphere. Suppression of meso-scale oceanic eddies results in a deep tropospheric response along and downstream of the KER, including a significant decrease (increase) in winter season mean rainfall along the KER (west coast of US), a reduction of storm genesis in the KER, and a southward shift of the jet stream and North Pacific storm track in the eastern North Pacific. The simulated local and remote rainfall response to meso-scale oceanic eddies in the KER is also supported by observational analysis. A mechanism invoking moist baroclinic instability is proposed as a plausible explanation for the linkage between meso-scale oceanic eddies in the KER and large-scale atmospheric response in the North Pacific. It is argued that meso-scale oceanic eddies can have a rectified effect on planetary boundary layer moisture, the stability of the lower atmosphere and latent heat release, which in turn affect cyclogenesis. The accumulated effect of the altered storm development downstream further contributes to the equivalent barotropic mean flow change in the eastern North Pacific basin.

The role of soil weathering and hydrology in regulating chemical fluxes from catchments (Invited)

NASA Astrophysics Data System (ADS)

Maher, K.; Chamberlain, C. P.

2010-12-01

Catchment-scale chemical fluxes have been linked to a number of different parameters that describe the conditions at the Earth’s surface, including runoff, temperature, rock type, vegetation, and the rate of tectonic uplift. However, many of the relationships relating chemical denudation to surface processes and conditions, while based on established theoretical principles, are largely empirical and derived solely from modern observations. Thus, an enhanced mechanistic basis for linking global solute fluxes to both surface processes and climate may improve our confidence in extrapolating modern solute fluxes to past and future conditions. One approach is to link observations from detailed soil-based studies with catchment-scale properties. For example, a number of recent studies of chemical weathering at the soil-profile scale have reinforced the importance of hydrologic processes in controlling chemical weathering rates. An analysis of data from granitic soils shows that weathering rates decrease with increasing fluid residence times and decreasing flow rates—over moderate fluid residence times, from 5 days to 10 years, transport-controlled weathering explains the orders of magnitude variation in weathering rates to a better extent than soil age. However, the importance of transport-controlled weathering is difficult to discern at the catchment scale because of the range of flow rates and fluid residence times captured by a single discharge or solute flux measurement. To assess the importance of transport-controlled weathering on catchment scale chemical fluxes, we present a model that links the chemical flux to the extent of reaction between the soil waters and the solids, or the fluid residence time. Different approaches for describing the distribution of fluid residence times within a catchment are then compared with the observed Si fluxes for a limited number of catchments. This model predicts high solute fluxes in regions with high run-off, relief, and long flow paths suggesting that the particular hydrologic setting of a landscape will be the underlying control on the chemical fluxes. As such, we reinterpret the large chemical fluxes that are observed in active mountain belts, like the Himalaya, to be primarily controlled by the long reactive flow paths created by the steep terrain coupled with high amounts of precipitation.

Simulating the impact of the large-scale circulation on the 2-m temperature and precipitation climatology

EPA Science Inventory

The impact of the simulated large-scale atmospheric circulation on the regional climate is examined using the Weather Research and Forecasting (WRF) model as a regional climate model. The purpose is to understand the potential need for interior grid nudging for dynamical downscal...

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.

Residual delay maps unveil global patterns of atmospheric nonlinearity and produce improved local forecasts

PubMed Central

Sugihara, George; Casdagli, Martin; Habjan, Edward; Hess, Dale; Dixon, Paul; Holland, Greg

1999-01-01

We use residual-delay maps of observational field data for barometric pressure to demonstrate the structure of latitudinal gradients in nonlinearity in the atmosphere. Nonlinearity is weak and largely lacking in tropical and subtropical sites and increases rapidly into the temperate regions where the time series also appear to be much noisier. The degree of nonlinearity closely follows the meridional variation of midlatitude storm track frequency. We extract the specific functional form of this nonlinearity, a V shape in the lagged residuals that appears to be a basic feature of midlatitude synoptic weather systems associated with frontal passages. We present evidence that this form arises from the relative time scales of high-pressure versus low-pressure events. Finally, we show that this nonlinear feature is weaker in a well regarded numerical forecast model (European Centre for Medium-Range Forecasts) because small-scale temporal and spatial variation is smoothed out in the grided inputs. This is significant, in that it allows us to demonstrate how application of statistical corrections based on the residual-delay map may provide marked increases in local forecast accuracy, especially for severe weather systems. PMID:10588685

Imaging and Analytical Approaches for Characterization of Soil Mineral Weathering

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

Dohnalkova, Alice; Arey, Bruce; Varga, Tamas

Soil minerals weathering is the primary natural source of nutrients necessary to sustain productivity in terrestrial ecosystems. Soil microbial communities increase soil mineral weathering and mineral-derived nutrient availability through physical and chemical processes. Rhizosphere, the zone immediately surrounding plant roots, is a biogeochemical hotspot with microbial activity, soil organic matter production, mineral weathering, and secondary phase formation all happening in a small temporally ephemeral zone of steep geochemical gradients. The detailed exploration of the micro-scale rhizosphere is essential to our better understanding of large-scale processes in soils, such as nutrient cycling, transport and fate of soil components, microbial-mineral interactions, soilmore » erosion, soil organic matter turnover and its molecular-level characterization, and predictive modeling.« less

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

Modelling hurricane exposure and wind speed on a mesoclimate scale: a case study from Cusuco NP, Honduras.

PubMed

Batke, Sven P; Jocque, Merlijn; Kelly, Daniel L

2014-01-01

High energy weather events are often expected to play a substantial role in biotic community dynamics and large scale diversity patterns but their contribution is hard to prove. Currently, observations are limited to the documentation of accidental records after the passing of such events. A more comprehensive approach is synthesising weather events in a location over a long time period, ideally at a high spatial resolution and on a large geographic scale. We provide a detailed overview on how to generate hurricane exposure data at a meso-climate level for a specific region. As a case study we modelled landscape hurricane exposure in Cusuco National Park (CNP), Honduras with a resolution of 50 m×50 m patches. We calculated actual hurricane exposure vulnerability site scores (EVVS) through the combination of a wind pressure model, an exposure model that can incorporate simple wind dynamics within a 3-dimensional landscape and the integration of historical hurricanes data. The EVSS was calculated as a weighted function of sites exposure, hurricane frequency and maximum wind velocity. Eleven hurricanes were found to have affected CNP between 1995 and 2010. The highest EVSS's were predicted to be on South and South-East facing sites of the park. Ground validation demonstrated that the South-solution (i.e. the South wind inflow direction) explained most of the observed tree damage (90% of the observed tree damage in the field). Incorporating historical data to the model to calculate actual hurricane exposure values, instead of potential exposure values, increased the model fit by 50%.

Modelling Hurricane Exposure and Wind Speed on a Mesoclimate Scale: A Case Study from Cusuco NP, Honduras

PubMed Central

Batke, Sven P.; Jocque, Merlijn; Kelly, Daniel L.

2014-01-01

High energy weather events are often expected to play a substantial role in biotic community dynamics and large scale diversity patterns but their contribution is hard to prove. Currently, observations are limited to the documentation of accidental records after the passing of such events. A more comprehensive approach is synthesising weather events in a location over a long time period, ideally at a high spatial resolution and on a large geographic scale. We provide a detailed overview on how to generate hurricane exposure data at a meso-climate level for a specific region. As a case study we modelled landscape hurricane exposure in Cusuco National Park (CNP), Honduras with a resolution of 50 m×50 m patches. We calculated actual hurricane exposure vulnerability site scores (EVVS) through the combination of a wind pressure model, an exposure model that can incorporate simple wind dynamics within a 3-dimensional landscape and the integration of historical hurricanes data. The EVSS was calculated as a weighted function of sites exposure, hurricane frequency and maximum wind velocity. Eleven hurricanes were found to have affected CNP between 1995 and 2010. The highest EVSS’s were predicted to be on South and South-East facing sites of the park. Ground validation demonstrated that the South-solution (i.e. the South wind inflow direction) explained most of the observed tree damage (90% of the observed tree damage in the field). Incorporating historical data to the model to calculate actual hurricane exposure values, instead of potential exposure values, increased the model fit by 50%. PMID:24614168

Dynamical Networks Characterization of Space Weather Events

NASA Astrophysics Data System (ADS)

Orr, L.; Chapman, S. C.; Dods, J.; Gjerloev, J. W.

2017-12-01

Space weather can cause disturbances to satellite systems, impacting navigation technology and telecommunications; it can cause power loss and aviation disruption. A central aspect of the earth's magnetospheric response to space weather events are large scale and rapid changes in ionospheric current patterns. Space weather is highly dynamic and there are still many controversies about how the current system evolves in time. The recent SuperMAG initiative, collates ground-based vector magnetic field time series from over 200 magnetometers with 1-minute temporal resolution. In principle this combined dataset is an ideal candidate for quantification using dynamical networks. Network properties and parameters allow us to characterize the time dynamics of the full spatiotemporal pattern of the ionospheric current system. However, applying network methodologies to physical data presents new challenges. We establish whether a given pair of magnetometers are connected in the network by calculating their canonical cross correlation. The magnetometers are connected if their cross correlation exceeds a threshold. In our physical time series this threshold needs to be both station specific, as it varies with (non-linear) individual station sensitivity and location, and able to vary with season, which affects ground conductivity. Additionally, the earth rotates and therefore the ground stations move significantly on the timescales of geomagnetic disturbances. The magnetometers are non-uniformly spatially distributed. We will present new methodology which addresses these problems and in particular achieves dynamic normalization of the physical time series in order to form the network. Correlated disturbances across the magnetometers capture transient currents. Once the dynamical network has been obtained [1][2] from the full magnetometer data set it can be used to directly identify detailed inferred transient ionospheric current patterns and track their dynamics. We will show our first results that use network properties such as cliques and clustering coefficients to map these highly dynamic changes in ionospheric current patterns.[l] Dods et al, J. Geophys. Res 120, doi:10.1002/2015JA02 (2015). [2] Dods et al, J. Geophys. Res. 122, doi:10.1002/2016JA02 (2017).

Sixty-One Martian Days of Weather Monitoring

NASA Technical Reports Server (NTRS)

2008-01-01

The Canadian Meteorological Station on NASA's Phoenix Mars Lander tracked some changes in daily weather patterns over the first 61 Martian days of the mission (May 26 to July 22, 2008), a period covering late spring to early summer on northern Mars.

This summary weather report notes that daily temperature ranges have changed only about 4 Celsius degrees (7 Fahrenheit degrees) since the start of the mission. The average daily high has been minus 30 degrees C (minus 22 degrees F), and the average daily low has been minus 79 degrees C (minus 110 degrees F).

The mission has been accumulating enough wind data to recognize daily patterns, such as a change in direction between day and night, and to begin analyzing whether the patterns are driven by local factors or larger-scale movement of the atmosphere.

The air pressure has steadily decreased. Scientists attribute this to a phenomenon on Mars that is not shared by Earth. The south polar cap of carbon dioxide ice grows during the southern winter on Mars, pulling enough carbon dioxide out of the thin atmosphere to cause a seasonal decrease in the amount of atmosphere Mars has. Most of the Martian atmosphere is carbon dioxide. This measurable dip in atmospheric pressure, even near the opposite pole, is a sign of large amounts of carbon dioxide being pulled out of the atmosphere as carbon-dioxide ice accumulates at the south pole.

The Phoenix Mission is led by the University of Arizona, Tucson, on behalf of NASA. Project management of the mission is by NASA's Jet Propulsion Laboratory, Pasadena, Calif. Spacecraft development is by Lockheed Martin Space Systems, Denver.

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.

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.

Elevation-dependent temperature trends in the Rocky Mountain Front Range: changes over a 56- and 20-year record.

PubMed

McGuire, Chris R; Nufio, César R; Bowers, M Deane; Guralnick, Robert P

2012-01-01

Determining the magnitude of climate change patterns across elevational gradients is essential for an improved understanding of broader climate change patterns and for predicting hydrologic and ecosystem changes. We present temperature trends from five long-term weather stations along a 2077-meter elevational transect in the Rocky Mountain Front Range of Colorado, USA. These trends were measured over two time periods: a full 56-year record (1953-2008) and a shorter 20-year (1989-2008) record representing a period of widely reported accelerating change. The rate of change of biological indicators, season length and accumulated growing-degree days, were also measured over the 56 and 20-year records. Finally, we compared how well interpolated Parameter-elevation Regression on Independent Slopes Model (PRISM) datasets match the quality controlled and weather data from each station. Our results show that warming signals were strongest at mid-elevations over both temporal scales. Over the 56-year record, most sites show warming occurring largely through increases in maximum temperatures, while the 20-year record documents warming associated with increases in maximum temperatures at lower elevations and increases in minimum temperatures at higher elevations. Recent decades have also shown a shift from warming during springtime to warming in July and November. Warming along the gradient has contributed to increases in growing-degree days, although to differing degrees, over both temporal scales. However, the length of the growing season has remained unchanged. Finally, the actual and the PRISM interpolated yearly rates rarely showed strong correlations and suggest different warming and cooling trends at most sites. Interpretation of climate trends and their seasonal biases in the Rocky Mountain Front Range are dependent on both elevation and the temporal scale of analysis. Given mismatches between interpolated data and the directly measured station data, we caution against an over-reliance on interpolation methods for documenting local patterns of climatic change.

Elevation-Dependent Temperature Trends in the Rocky Mountain Front Range: Changes over a 56- and 20-Year Record

PubMed Central

McGuire, Chris R.; Nufio, César R.; Bowers, M. Deane; Guralnick, Robert P.

2012-01-01

Determining the magnitude of climate change patterns across elevational gradients is essential for an improved understanding of broader climate change patterns and for predicting hydrologic and ecosystem changes. We present temperature trends from five long-term weather stations along a 2077-meter elevational transect in the Rocky Mountain Front Range of Colorado, USA. These trends were measured over two time periods: a full 56-year record (1953–2008) and a shorter 20-year (1989–2008) record representing a period of widely reported accelerating change. The rate of change of biological indicators, season length and accumulated growing-degree days, were also measured over the 56 and 20-year records. Finally, we compared how well interpolated Parameter-elevation Regression on Independent Slopes Model (PRISM) datasets match the quality controlled and weather data from each station. Our results show that warming signals were strongest at mid-elevations over both temporal scales. Over the 56-year record, most sites show warming occurring largely through increases in maximum temperatures, while the 20-year record documents warming associated with increases in maximum temperatures at lower elevations and increases in minimum temperatures at higher elevations. Recent decades have also shown a shift from warming during springtime to warming in July and November. Warming along the gradient has contributed to increases in growing-degree days, although to differing degrees, over both temporal scales. However, the length of the growing season has remained unchanged. Finally, the actual and the PRISM interpolated yearly rates rarely showed strong correlations and suggest different warming and cooling trends at most sites. Interpretation of climate trends and their seasonal biases in the Rocky Mountain Front Range are dependent on both elevation and the temporal scale of analysis. Given mismatches between interpolated data and the directly measured station data, we caution against an over-reliance on interpolation methods for documenting local patterns of climatic change. PMID:22970205

The Amazon and climate

NASA Technical Reports Server (NTRS)

Nobre, C. A.

1984-01-01

The climatologies of cloudiness and precipitation for the Amazon, are reviewed and the physical causes of some of the observed features and those which are not well known are explained. The atmospheric circulation over the Amazon is discussed on the large scale tropical circulations forced by deep diabatic heating sources. Weather deforestation which leads to a reduction in evapotranspiration into the atmosphere, and a reduction in precipitation and its implicated for the gobal climate is discussed. It is indicated that a large scale clearing of tropical rainforests there would be a reduction in rainfall which would have global effects on climate and weather both in the tropical and extratropical regions.

Optimized circulation and weather type classifications relating large-scale atmospheric conditions to local PM10 concentrations in Bavaria

NASA Astrophysics Data System (ADS)

Weitnauer, C.; Beck, C.; Jacobeit, J.

2013-12-01

In the last decades the critical increase of the emission of air pollutants like nitrogen dioxide, sulfur oxides and particulate matter especially in urban areas has become a problem for the environment as well as human health. Several studies confirm a risk of high concentration episodes of particulate matter with an aerodynamic diameter < 10 μm (PM10) for the respiratory tract or cardiovascular diseases. Furthermore it is known that local meteorological and large scale atmospheric conditions are important influencing factors on local PM10 concentrations. With climate changing rapidly, these connections need to be better understood in order to provide estimates of climate change related consequences for air quality management purposes. For quantifying the link between large-scale atmospheric conditions and local PM10 concentrations circulation- and weather type classifications are used in a number of studies by using different statistical approaches. Thus far only few systematic attempts have been made to modify consisting or to develop new weather- and circulation type classifications in order to improve their ability to resolve local PM10 concentrations. In this contribution existing weather- and circulation type classifications, performed on daily 2.5 x 2.5 gridded parameters of the NCEP/NCAR reanalysis data set, are optimized with regard to their discriminative power for local PM10 concentrations at 49 Bavarian measurement sites for the period 1980 to 2011. Most of the PM10 stations are situated in urban areas covering urban background, traffic and industry related pollution regimes. The range of regimes is extended by a few rural background stations. To characterize the correspondence between the PM10 measurements of the different stations by spatial patterns, a regionalization by an s-mode principal component analysis is realized on the high-pass filtered data. The optimization of the circulation- and weather types is implemented using two representative classification approaches, a k-means cluster analysis and an objective version of the Grosswetter types. They have been run with varying spatial and temporal settings as well as modified numbers of classes. As an evaluation metric for their performance several skill scores are used. Taking into account the outcome further attempts towards the optimization of circulation type classifications are made. These are varying meteorological input parameters (e.g. geopotential height, zonal and meridional wind, specific humidity, temperature) on several pressure levels (1000, 850 and 500 hPa) and combinations of these variables. All classification variants are again evaluated. Based on these analyses it is further intended to develop robust downscaling models for estimating possible future - climate change induced - variations of local PM10 concentrations in Bavaria from scenario runs of global CMIP5 climate models.

Robustness of serial clustering of extra-tropical cyclones to the choice of tracking method

NASA Astrophysics Data System (ADS)

Pinto, Joaquim G.; Ulbrich, Sven; Karremann, Melanie K.; Stephenson, David B.; Economou, Theodoros; Shaffrey, Len C.

2016-04-01

Cyclone families are a frequent synoptic weather feature in the Euro-Atlantic area in winter. Given appropriate large-scale conditions, the occurrence of such series (clusters) of storms may lead to large socio-economic impacts and cumulative losses. Recent studies analyzing Reanalysis data using single cyclone tracking methods have shown that serial clustering of cyclones occurs on both flanks and downstream regions of the North Atlantic storm track. This study explores the sensitivity of serial clustering to the choice of tracking method. With this aim, the IMILAST cyclone track database based on ERA-interim data is analysed. Clustering is estimated by the dispersion (ratio of variance to mean) of winter (DJF) cyclones passages near each grid point over the Euro-Atlantic area. Results indicate that while the general pattern of clustering is identified for all methods, there are considerable differences in detail. This can primarily be attributed to the differences in the variance of cyclone counts between the methods, which range up to one order of magnitude. Nevertheless, clustering over the Eastern North Atlantic and Western Europe can be identified for all methods and can thus be generally considered as a robust feature. The statistical links between large-scale patterns like the NAO and clustering are obtained for all methods, though with different magnitudes. We conclude that the occurrence of cyclone clustering over the Eastern North Atlantic and Western Europe is largely independent from the choice of tracking method and hence from the definition of a cyclone.

Identifying when weather influences life-history traits of grazing herbivores.

PubMed

Sims, Michelle; Elston, David A; Larkham, Ann; Nussey, Daniel H; Albon, Steve D

2007-07-01

1. There is increasing evidence that density-independent weather effects influence life-history traits and hence the dynamics of populations of animals. Here, we present a novel statistical approach to estimate when such influences are strongest. The method is demonstrated by analyses investigating the timing of the influence of weather on the birth weight of sheep and deer. 2. The statistical technique allowed for the pattern of temporal correlation in the weather data enabling the effects of weather in many fine-scale time intervals to be investigated simultaneously. Thus, while previous studies have typically considered weather averaged across a single broad time interval during pregnancy, our approach enabled examination simultaneously of the relationships with weekly and fortnightly averages throughout the whole of pregnancy. 3. We detected a positive effect of temperature on the birth weight of deer, which is strongest in late pregnancy (mid-March to mid-April), and a negative effect of rainfall on the birthweight of sheep, which is strongest during mid-pregnancy (late January to early February). The possible mechanisms underlying these weather-birth weight relationships are discussed. 4. This study enhances our insight into the pattern of the timing of influence of weather on early development. The method is of much more general application and could provide valuable insights in other areas of ecology in which sequences of intercorrelated explanatory variables have been collected in space or in time.

Weather assessment and forecasting

NASA Technical Reports Server (NTRS)

1977-01-01

Data management program activities centered around the analyses of selected far-term Office of Applications (OA) objectives, with the intent of determining if significant data-related problems would be encountered and if so what alternative solutions would be possible. Three far-term (1985 and beyond) OA objectives selected for analyses as having potential significant data problems were large-scale weather forecasting, local weather and severe storms forecasting, and global marine weather forecasting. An overview of general weather forecasting activities and their implications upon the ground based data system is provided. Selected topics were specifically oriented to the use of satellites.

Accelerating the carbon cycle: the ethics of enhanced weathering.

PubMed

Lawford-Smith, H; Currie, A

2017-04-01

Enhanced weathering, in comparison to other geoengineering measures, creates the possibility of a reduced cost, reduced impact way of decreasing atmospheric carbon, with positive knock-on effects such as decreased oceanic acidity. We argue that ethical concerns have a place alongside empirical, political and social factors as we consider how to best respond to the critical challenge that anthropogenic climate change poses. We review these concerns, considering the ethical issues that arise (or would arise) in the large-scale deployment of enhanced weathering. We discuss post-implementation scenarios, failures of collective action, the distribution of risk and externalities and redress for damage. We also discuss issues surrounding 'dirty hands' (taking conventionally immoral action to avoid having to take action that is even worse), whether enhanced weathering research might present a moral hazard, the importance of international governance and the notion that the implementation of large-scale enhanced weathering would reveal problematic hubris. Ethics and scientific research interrelate in complex ways: some ethical considerations caution against research and implementation, while others encourage them. Indeed, the ethical perspective encourages us to think more carefully about how, and what types of, geoengineering should be researched and implemented. © 2017 The Author(s).

Flying with the wind: Scale dependency of speed and direction measurements in modelling wind support in avian flight

USGS Publications Warehouse

Safi, Kamran; Kranstauber, Bart; Weinzierl, Rolf P.; Griffin, Larry; Reese, Eileen C.; Cabot, David; Cruz, Sebastian; Proaño, Carolina; Takekawa, John Y.; Newman, Scott H.; Waldenström, Jonas; Bengtsson, Daniel; Kays, Roland; Wikelski, Martin; Bohrer, Gil

2013-01-01

Background: Understanding how environmental conditions, especially wind, influence birds' flight speeds is a prerequisite for understanding many important aspects of bird flight, including optimal migration strategies, navigation, and compensation for wind drift. Recent developments in tracking technology and the increased availability of data on large-scale weather patterns have made it possible to use path annotation to link the location of animals to environmental conditions such as wind speed and direction. However, there are various measures available for describing not only wind conditions but also the bird's flight direction and ground speed, and it is unclear which is best for determining the amount of wind support (the length of the wind vector in a bird’s flight direction) and the influence of cross-winds (the length of the wind vector perpendicular to a bird’s direction) throughout a bird's journey.Results: We compared relationships between cross-wind, wind support and bird movements, using path annotation derived from two different global weather reanalysis datasets and three different measures of direction and speed calculation for 288 individuals of nine bird species. Wind was a strong predictor of bird ground speed, explaining 10-66% of the variance, depending on species. Models using data from different weather sources gave qualitatively similar results; however, determining flight direction and speed from successive locations, even at short (15 min intervals), was inferior to using instantaneous GPS-based measures of speed and direction. Use of successive location data significantly underestimated the birds' ground and airspeed, and also resulted in mistaken associations between cross-winds, wind support, and their interactive effects, in relation to the birds' onward flight.Conclusions: Wind has strong effects on bird flight, and combining GPS technology with path annotation of weather variables allows us to quantify these effects for understanding flight behaviour. The potentially strong influence of scaling effects must be considered and implemented in developing sampling regimes and data analysis.

Flying with the wind: scale dependency of speed and direction measurements in modelling wind support in avian flight.

PubMed

Safi, Kamran; Kranstauber, Bart; Weinzierl, Rolf; Griffin, Larry; Rees, Eileen C; Cabot, David; Cruz, Sebastian; Proaño, Carolina; Takekawa, John Y; Newman, Scott H; Waldenström, Jonas; Bengtsson, Daniel; Kays, Roland; Wikelski, Martin; Bohrer, Gil

2013-01-01

Understanding how environmental conditions, especially wind, influence birds' flight speeds is a prerequisite for understanding many important aspects of bird flight, including optimal migration strategies, navigation, and compensation for wind drift. Recent developments in tracking technology and the increased availability of data on large-scale weather patterns have made it possible to use path annotation to link the location of animals to environmental conditions such as wind speed and direction. However, there are various measures available for describing not only wind conditions but also the bird's flight direction and ground speed, and it is unclear which is best for determining the amount of wind support (the length of the wind vector in a bird's flight direction) and the influence of cross-winds (the length of the wind vector perpendicular to a bird's direction) throughout a bird's journey. We compared relationships between cross-wind, wind support and bird movements, using path annotation derived from two different global weather reanalysis datasets and three different measures of direction and speed calculation for 288 individuals of nine bird species. Wind was a strong predictor of bird ground speed, explaining 10-66% of the variance, depending on species. Models using data from different weather sources gave qualitatively similar results; however, determining flight direction and speed from successive locations, even at short (15 min intervals), was inferior to using instantaneous GPS-based measures of speed and direction. Use of successive location data significantly underestimated the birds' ground and airspeed, and also resulted in mistaken associations between cross-winds, wind support, and their interactive effects, in relation to the birds' onward flight. Wind has strong effects on bird flight, and combining GPS technology with path annotation of weather variables allows us to quantify these effects for understanding flight behaviour. The potentially strong influence of scaling effects must be considered and implemented in developing sampling regimes and data analysis.

Terrestrial photography as a complementary measurement in weather stations for snow monitoring

NASA Astrophysics Data System (ADS)

Pimentel, Rafael; José Pérez-Palazón, María; Herrero, Javier; José Polo, María

2015-04-01

Snow monitoring constitutes a basic key to know snow behaviour and evolution, which have particular features in semiarid regions (i.e. highly strong spatiotemporal variability, and the occurrence of several accumulation-melting cycles throughout the year). On one hand, traditional snow observation, such as snow surveys and snow pillows have the inconvenience of a limited accessibility during snow season and the impossibility to cover a vast extension. On the other hand, satellite remote sensing techniques, largely employed in medium to large scale regional studies, has the disadvantage of a fixed spatial and temporal resolutions which in some cases are not able to reproduce snow processes at small scale. An economic alternative is the use of terrestrial photography which scales are adapted to the study problem. At the microscale resolution permits the continuous monitoring of snow, adapting the resolution of the observation to the scales of the processes. Besides its use as raw observation datasets to calibrate and validate models' results, terrestrial photography constitutes valuable information to complement weather stations observations. It allows the discriminating possible mistakes in meteorological observations (i.e. overestimation on rain measurements) and a better understanding of snow behaviour against certain weather agents (i.e. blowing snow). Thus, terrestrial photography is a feasible and convenient technique to be included in weather monitoring stations in mountainous areas in semiarid regions.

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

Lightning jump as a nowcast predictor: Application to severe weather events in Catalonia

NASA Astrophysics Data System (ADS)

Farnell, C.; Rigo, T.; Pineda, N.

2017-01-01

Several studies reported sudden increases in the total lightning flash rate (intra-cloud+cloud-to-ground) preceding the occurrence of severe weather (large hail, wind gusts associated to thunderstorms and/or tornadoes). Named ;Lightning Jump;, this pattern has demonstrated to be of operational applicability in the forecasting of severe weather phenomena. The present study introduces the application of a lightning jump algorithm, with an identification of cells based solely on total lightning data, revealing that there is no need of radar data to trigger severe weather warnings. The algorithm was validated by means of a dataset severe weather events occurred in Catalonia in the period 2009-2014. Results obtained revealed very promising.

A Precipitation Climatology of the Snowy Mountains, Australia

NASA Astrophysics Data System (ADS)

Theobald, Alison; McGowan, Hamish; Speirs, Johanna

2014-05-01

The precipitation that falls in the Snowy Mountains region of southeastern Australia provides critical water resources for hydroelectric power generation. Water storages in this region are also a major source of agricultural irrigation, environmental flows, and offer a degree of flood protection for some of the major river systems in Australia. Despite this importance, there remains a knowledge gap regarding the long-term, historic variability of the synoptic weather systems that deliver precipitation to the region. This research aims to increase the understanding of long-term variations in precipitation-bearing weather systems resulting in runoff into the Snowy Mountains catchments and reservoirs, and the way in which these are influenced by large-scale climate drivers. Here we present initial results on the development of a climatology of precipitation-bearing synoptic weather systems (synoptic typology), spanning a period of over 100 years. The synoptic typology is developed from the numerical weather model re-analysis data from the European Centre for Medium-Range Weather Forecasts (ECMWF), in conjunction with regional precipitation and temperature data from a network of private gauges. Given the importance of surface, mid- and upper-air patterns on seasonal precipitation, the synoptic typing will be based on a range of meteorological variables throughout the depth of the troposphere, highlighting the importance of different atmospheric levels on the development and steering of synoptic precipitation bearing systems. The temporal and spatial variability of these synoptic systems, their response to teleconnection forcings and their contribution to inflow generation in the headwater catchments of the Snowy Mountains will be investigated. The resulting climatology will provide new understanding of the drivers of regional-scale precipitation variability at inter- and intra-annual timescales. It will enable greater understanding of how variability in synoptic scale atmospheric circulation affects the hydroclimate of alpine environments in southeast Australia - allowing recently observed precipitation declines to be placed in the context of a long-term record spanning at least 100 years. This information will provide further insight into the impacts of predicted anthropogenic climate change and will ultimately lead to more informed water resource management in the Snowy Mountains.

Weathering patterns of polycyclic aromatic hydrocarbons contained in submerged Deepwater Horizon oil spill residues when re-exposed to sunlight.

PubMed

John, Gerald F; Han, Yuling; Clement, T Prabhakar

2016-12-15

The Deepwater Horizon (DWH) oil spill event released a large amount of sweet crude oil into the Gulf of Mexico (GOM). An unknown portion of this oil that arrived along the Alabama shoreline interacted with nearshore sediments and sank forming submerged oil mats (SOMs). A considerable amount of hydrocarbons, including polycyclic aromatic hydrocarbons (PAHs), were trapped within these buried SOMs. Recent studies completed using the oil spill residues collected along the Alabama shoreline have shown that several PAHs, especially higher molecular weight PAHs (four or more aromatic rings), are slowly weathering compared to the weathering levels experienced by the oil when it was floating over the GOM. In this study we have hypothesized that the weathering rates of PAHs in SOMs have slowed down because the buried oil was isolated from direct exposure to sunlight, thus hindering the photodegradation pathway. We further hypothesized that re-exposing SOMs to sunlight can reactivate various weathering reactions. Also, SOMs contain 75-95% sand (by weight) and the entrapped sand could either block direct sunlight or form large oil agglomerates with very little exposed surface area; these processes could possibly interfere with weathering reactions. To test these hypotheses, we completed controlled experiments to study the weathering patterns of PAHs in a field recovered SOM sample after re-exposing it to sunlight. Our experimental results show that the weathering levels of several higher molecular weight PAHs have slowed down primarily due to the absence of sunlight-induced photodegradation reactions. The data also show that sand particles in SOM material could potentially interfere with photodegradation reactions. Copyright © 2016 Elsevier B.V. All rights reserved.

A Model Based Analysis of the Role of an Upper-Level Front and Stratospheric Intrusion in the Mack Lake Fire

Treesearch

Tarisa K. Zimet; Jonathan E. Martin

2003-01-01

Meteorological assessment of wildfire risk has traditionally involved identification of several synoptic types empirically determined to influence wildfire spread. Such weather types are characterized by identifiable synoptic-scale structures and processes. Schroeder et. al. (1964) identified four recognizable synoptic-scale patterns that contribute most frequently to...

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.

A coupled synoptic-hydrological model for climate change impact assessment

NASA Astrophysics Data System (ADS)

Wilby, Robert; Greenfield, Brian; Glenny, Cathy

1994-01-01

A coupled atmospheric-hydrological model is presented. Sequences of daily rainfall occurrence for the 20 year period 1971-1990 at sites in the British Isles are related to the Lamb's Weather Types (LWT) by using conditional probabilities. Time series of circulation patterns and hence rainfall were then generated using a Markov representation of matrices of transition probabilities between weather types. The resultant precipitation data were used as input to a semidistributed catchment model to simulate daily flows. The combined model successfully reproduced aspects of the daily weather, precipitation and flow regimes. A range of synoptic scenarios were further investigated with particular reference to low flows in the River Coln, UK. The modelling approach represents a means of translating general circulation model (GCM) climate change predictions at the macro-scale into hydrological concerns at the catchment scale.

Intense sub-kilometer-scale boundary layer rolls observed in hurricane fran

PubMed

Wurman; Winslow

1998-04-24

High-resolution observations obtained with the Doppler On Wheels (DOW) mobile weather radar near the point of landfall of hurricane Fran (1996) revealed the existence of intense, sub-kilometer-scale, boundary layer rolls that strongly modulated the near-surface wind speed. It is proposed that these structures are one cause of geographically varying surface damage patterns that have been observed after some landfalling hurricanes and that they cause much of the observed gustiness, bringing high-velocity air from aloft to the lowest observable levels. High-resolution DOW radar observations are contrasted with lower-resolution observations obtained with an operational weather radar, which underestimated peak low-level wind speeds.

Bridging the Gap Between the iLEAPS and GEWEX Land-Surface Modeling Communities

NASA Technical Reports Server (NTRS)

Bonan, Gordon; Santanello, Joseph A., Jr.

2013-01-01

Models of Earth's weather and climate require fluxes of momentum, energy, and moisture across the land-atmosphere interface to solve the equations of atmospheric physics and dynamics. Just as atmospheric models can, and do, differ between weather and climate applications, mostly related to issues of scale, resolved or parameterised physics,and computational requirements, so too can the land models that provide the required surface fluxes differ between weather and climate models. Here, however, the issue is less one of scale-dependent parameterisations.Computational demands can influence other minor land model differences, especially with respect to initialisation, data assimilation, and forecast skill. However, the distinction among land models (and their development and application) is largely driven by the different science and research needs of the weather and climate communities.

Spatial variability of polycyclic aromatic hydrocarbon load of urban wet weather pollution in combined sewers.

PubMed

Gasperi, J; Moilleron, R; Chebbo, G

2006-01-01

In Paris, the OPUR research programme created an experimental on-site observatory of urban pollutant loads in combined sewer systems in order to characterise the dry and wet weather flows at different spatial scales. This article presents the first results on the spatial variability of the polycyclic aromatic hydrocarbon (PAH) load during wet weather flow (WWF). At the scale of a rain event, investigations revealed that (i) PAH concentrations were relatively homogenous whatever the spatial scale and were greater than those of the dry weather flow (DWF), (ii) PAH distributions between dissolved and particulate phases were constant, and (iii) PAH fingerprints exhibited a similar pattern for all catchments. Moreover, an evaluation of the contribution of DWF, runoff and erosion of sewer deposits to WWF load was established. According to the hypothesis on the runoff concentration, the contributions were evaluated at 14, 8 and 78%, respectively, at the scale of the Marais catchment. For all the catchments, the runoff contribution was found quite constant and evaluated at approximately 10%. The DWF contribution seems to increase with the catchment area, contrary to the sewer erosion contribution, which seems to decrease. However, this latter still remains an important source of pollution. These first trends should be confirmed and completed by more investigations of rain events.

Mixed severity fire effects within the Rim fire: Relative importance of local climate, fire weather, topography, and forest structure

Treesearch

Van R. Kane; C. Alina Cansler; Nicholas A. Povak; Jonathan T. Kane; Robert J. McGaughey; James A. Lutz; Derek J. Churchill; Malcolm P. North

2015-01-01

Recent and projected increases in the frequency and severity of large wildfires in the western U.S. makes understanding the factors that strongly affect landscape fire patterns a management priority for optimizing treatment location. We compared the influence of variations in the local environment on burn severity patterns on the large 2013 Rim fire that burned under...

A new-old approach for shallow landslide analysis and susceptibility zoning in fine-grained weathered soils of southern Italy

NASA Astrophysics Data System (ADS)

Cascini, Leonardo; Ciurleo, Mariantonietta; Di Nocera, Silvio; Gullà, Giovanni

2015-07-01

Rainfall-induced shallow landslides involve several geo-environmental contexts and different types of soils. In clayey soils, they affect the most superficial layer, which is generally constituted by physically weathered soils characterised by a diffuse pattern of cracks. This type of landslide most commonly occurs in the form of multiple-occurrence landslide phenomena simultaneously involving large areas and thus has several consequences in terms of environmental and economic damage. Indeed, landslide susceptibility zoning is a relevant issue for land use planning and/or design purposes. This study proposes a multi-scale approach to reach this goal. The proposed approach is tested and validated over an area in southern Italy affected by widespread shallow landslides that can be classified as earth slides and earth slide-flows. Specifically, by moving from a small (1:100,000) to a medium scale (1:25,000), with the aid of heuristic and statistical methods, the approach identifies the main factors leading to landslide occurrence and effectively detects the areas potentially affected by these phenomena. Finally, at a larger scale (1:5000), deterministic methods, i.e., physically based models (TRIGRS and TRIGRS-unsaturated), allow quantitative landslide susceptibility assessment, starting from sample areas representative of those that can be affected by shallow landslides. Considering the reliability of the obtained results, the proposed approach seems useful for analysing other case studies in similar geological contexts.

A Bayesian hierarchical model with spatial variable selection: the effect of weather on insurance claims

PubMed Central

Scheel, Ida; Ferkingstad, Egil; Frigessi, Arnoldo; Haug, Ola; Hinnerichsen, Mikkel; Meze-Hausken, Elisabeth

2013-01-01

Climate change will affect the insurance industry. We develop a Bayesian hierarchical statistical approach to explain and predict insurance losses due to weather events at a local geographic scale. The number of weather-related insurance claims is modelled by combining generalized linear models with spatially smoothed variable selection. Using Gibbs sampling and reversible jump Markov chain Monte Carlo methods, this model is fitted on daily weather and insurance data from each of the 319 municipalities which constitute southern and central Norway for the period 1997–2006. Precise out-of-sample predictions validate the model. Our results show interesting regional patterns in the effect of different weather covariates. In addition to being useful for insurance pricing, our model can be used for short-term predictions based on weather forecasts and for long-term predictions based on downscaled climate models. PMID:23396890

Image-based optimization of coronal magnetic field models for improved space weather forecasting

NASA Astrophysics Data System (ADS)

Uritsky, V. M.; Davila, J. M.; Jones, S. I.; MacNeice, P. J.

2017-12-01

The existing space weather forecasting frameworks show a significant dependence on the accuracy of the photospheric magnetograms and the extrapolation models used to reconstruct the magnetic filed in the solar corona. Minor uncertainties in the magnetic field magnitude and direction near the Sun, when propagated through the heliosphere, can lead to unacceptible prediction errors at 1 AU. We argue that ground based and satellite coronagraph images can provide valid geometric constraints that could be used for improving coronal magnetic field extrapolation results, enabling more reliable forecasts of extreme space weather events such as major CMEs. In contrast to the previously developed loop segmentation codes designed for detecting compact closed-field structures above solar active regions, we focus on the large-scale geometry of the open-field coronal regions up to 1-2 solar radii above the photosphere. By applying the developed image processing techniques to high-resolution Mauna Loa Solar Observatory images, we perform an optimized 3D B-line tracing for a full Carrington rotation using the magnetic field extrapolation code developed S. Jones at al. (ApJ 2016, 2017). Our tracing results are shown to be in a good qualitative agreement with the large-scale configuration of the optical corona, and lead to a more consistent reconstruction of the large-scale coronal magnetic field geometry, and potentially more accurate global heliospheric simulation results. Several upcoming data products for the space weather forecasting community will be also discussed.

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).

Fire weather and likelihood: characterizing climate space for fire occurrence and extent in Puerto Rico

Treesearch

Ashley E. Van Beusekom; William A. Gould; A. Carolina Monmany; Azad Henareh Khalyani; Maya Quiñones; Stephen J. Fain; Maria José Andrade-Núñez; Grizelle González

2018-01-01

Abstract Assessing the relationships between weather patterns and the likelihood of fire occurrence in the Caribbean has not been as central to climate change research as in temperate regions, due in part to the smaller extent of individual fires. However, the cumulative effect of small frequent fires can shape large landscapes, and fire-prone ecosystems are abundant...

Effects of the Pacific Decadal Oscillation and global warming on drought in the US Southwest

NASA Astrophysics Data System (ADS)

Grossmann, I.

2012-12-01

Droughts are among the most expensive weather related disasters in the US. In the semi-arid regions of the US Southwest, where average annual rainfall is already very low, multiyear droughts can have large economic, societal and ecological impacts. The US Southwest relies on annual precipitation maxima during winter and the North American Monsoon (NAM), both of which undergo considerable interannual variability associated with large-scale climate patterns, in particular ENSO, the Pacific Decadal Oscillation (PDO) and the Atlantic Multidecadal Oscillation (AMO). The region is also part of the subtropical belt projected to become more arid in a warming climate. These impacts have not been combined and compared with projections of long-term variations due to natural climate patterns. This study addresses this need by deriving future projections of rainfall departures for Arizona and New Mexico with the PDO and AMO and combining these with projected global warming impacts. Depending on the precipitation dataset used, the impacts for the ongoing negative PDO phase are projected to be between 1-1.6 times as large as the multi-model means projection of precipitation minus evaporation during 2020-2040 in the IPCC A1B Scenario. The projected precipitation impacts of a combined negative PDO and positive AMO phase are between 1-2 times as large as the A1B Scenario projection. The study also advances earlier work by addressing problems in detecting the effect of the PDO on precipitation. Given the different mechanisms with which the PDO affects precipitation during winter and the NAM season, precipitation impacts are here investigated on a monthly scale. The impacts of the PDO also vary with other climate patterns. This can be partly addressed by investigating precipitation departures in dependence on other patterns. It is further found 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.

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

Synoptic weather typing applied to air pollution mortality among the elderly in 10 Canadian cities.

PubMed

Vanos, Jennifer K; Cakmak, Sabit; Bristow, Corben; Brion, Vladislav; Tremblay, Neil; Martin, Sara L; Sheridan, Scott S

2013-10-01

Synoptic circulation patterns (large-scale weather systems) affect ambient levels of air pollution, as well as the relationship between air pollution and human health. To investigate the air pollution-mortality relationship within weather types and seasons, and to determine which combination of atmospheric conditions may pose increased health threats in the elderly age categories. The relative risk of mortality (RR) due to air pollution was examined using Poisson generalized linear models (GLMs) within specific weather types. Analysis was completed by weather type and age group (all ages, ≤64, 65-74, 75-84, ≥85 years) in ten Canadian cities from 1981 to 1999. There was significant modification of RR by weather type and age. When examining the entire population, weather type was shown to have the greatest modifying effect on the risk of dying due to ozone (O3). This effect was highest on average for the dry tropical (DT) weather type, with the all-age RR of mortality at a population weighted mean (PWM) found to be 1.055 (95% CI 1.026-1.085). All-weather type risk estimates increased with age due to exposure to carbon monoxide (CO), nitrogen dioxide (NO2), and sulphur dioxide (SO2). On average, RR increased by 2.6, 3.8 and 1.5% for the respective pollutants between the ≤64 and ≥85 age categories. Conversely, mean ozone estimates remained relatively consistent with age. Elevated levels of air pollution were found to be detrimental to the health of elderly individuals for all weather types. However, the entire population was negatively effected by air pollution on the hot dry (DT) and hot humid (MT) days. We identified a significant modification of RR for mortality due to air pollution by age, which is enhanced under specific weather types. Efforts should be targeted at minimizing pollutant exposure to the elderly and/or all age groups with respect to weather type in question. Crown Copyright © 2013 Published by Elsevier Inc. All rights reserved.

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.

Towards a Better Understanding of Biomas Burning and Large Scale Climate Dynamics on the West African Monsoon

NASA Astrophysics Data System (ADS)

Ajoku, O.; Norris, J. R.; Miller, A. J.

2017-12-01

Seasonal biomass burning and resulting black carbon (BC) emissions have been well documented to effect regional weather patterns, especially including low level convection. These effects can be due to the hydrophilic and radiative qualities of the aerosols emitted from such burning. This project focuses on utilizing observation and reanalysis data in order to understand the effects of BC advected from the Southern hemisphere impact the dynamics of the West African Monsoon. Our results show that, of all monsoon months, BC advection has a direct impact on precipitation in July. Early analysis indicates that biomass burning occuring near Angola/Congo advects over the Gulf of Guinea, towards the Intertropical Convergence Zone at around 850mb and stabalizes the atmosphere. For a broader impact, this region is home to more than 200 million people and thus understanding these climate patterns may carry great importance.

Large-Scale, Extratropical Weather Systems within Mars' Atmosphere

NASA Astrophysics Data System (ADS)

Hollingsworth, Jeffery L.

2013-04-01

During late autumn through early spring, extratropical regions on Mars exhibit profound mean zonal equator-to-pole thermal contrasts. The imposition of this strong meridional temperature variation supports intense eastward-traveling, synoptic weather systems (i.e., transient baroclinic/barotropic waves) within Mars' extratropical atmosphere. Such disturbances grow, mature and decay within the east-west varying seasonal-mean midlatitude jet stream (i.e., the polar vortex) on the planet. Near the surface, the weather disturbances indicated large-scale spiraling "comma"-shaped dust cloud structures and scimitar-shaped dust fronts, indicative of processes associated with cyclo-/fronto-genesis. The weather systems occur during specific seasons on Mars, and in both hemispheres. The northern hemisphere (NH) disturbances are significantly more intense than their counterparts in the southern hemisphere (SH). Further, the NH weather systems and accompanying frontal waves appear to have significant impacts on the transport of tracer fields (e.g., particularly dust and to some extent water species (vapor/ice) as well). And regarding dust, frontal waves appear to be key agents in the lifting, lofting, organization and transport of this particular atmospheric aerosol. In this paper, a brief background and supporting observations of Mars' extratropical weather systems is presented. This is followed by a short review of the theory and various modeling studies (i.e., ranging from highly simplified, mechanistic and full global circulation modeling investigations) which have been pursued. Finally, a discussion of outstanding issues and questions regarding the character and nature of Mars' extratropical traveling weather systems is offered.

Large-Scale Extratropical Weather Systems in Mars' Atmosphere

NASA Technical Reports Server (NTRS)

Hollingsworth, Jeffery L.

2013-01-01

During late autumn through early spring, extratropical regions on Mars exhibit profound mean zonal equator-to-pole thermal contrasts. The imposition of this strong meridional temperature variation supports intense eastward-traveling, synoptic weather systems (i.e., transient baroclinic/barotropic waves) within Mars' extratropical atmosphere. Such disturbances grow, mature and decay within the east-west varying seasonal-mean midlatitude jet stream (i.e., the polar vortex) on the planet. Near the surface, the weather disturbances indicated large-scale spiraling "comma"-shaped dust cloud structures and scimitar-shaped dust fronts, indicative of processes associated with cyclo-/fronto-genesis. The weather systems occur during specific seasons on Mars, and in both hemispheres. The northern hemisphere (NH) disturbances are significantly more intense than their counterparts in the southern hemisphere (SH). Further, the NH weather systems and accompanying frontal waves appear to have significant impacts on the transport of tracer fields (e.g., particularly dust and to some extent water species (vapor/ice) as well). And regarding dust, frontal waves appear to be key agents in the lifting, lofting, organization and transport of this particular atmospheric aerosol. In this paper, a brief background and supporting observations of Mars' extratropical weather systems is presented. This is followed by a short review of the theory and various modeling studies (i.e., ranging from highly simplified, mechanistic and full global circulation modeling investigations) which have been pursued. Finally, a discussion of outstanding issues and questions regarding the character and nature of Mars' extratropical traveling weather systems is offered.

On wildfire complexity, simple models and environmental templates for fire size distributions

NASA Astrophysics Data System (ADS)

Boer, M. M.; Bradstock, R.; Gill, M.; Sadler, R.

2012-12-01

Vegetation fires affect some 370 Mha annually. At global and continental scales, fire activity follows predictable spatiotemporal patterns driven by gradients and seasonal fluctuations of primary productivity and evaporative demand that set constraints for fuel accumulation rates and fuel dryness, two key ingredients of fire. At regional scales, fires are also known to affect some landscapes more than others and within landscapes to occur preferentially in some sectors (e.g. wind-swept ridges) and rarely in others (e.g. wet gullies). Another common observation is that small fires occur relatively frequent yet collectively burn far less country than relatively infrequent large fires. These patterns of fire activity are well known to management agencies and consistent with their (informal) models of how the basic drivers and constraints of fire (i.e. fuels, ignitions, weather) vary in time and space across the landscape. The statistical behaviour of these landscape fire patterns has excited the (academic) research community by showing some consistency with that of complex dynamical systems poised at a phase transition. The common finding that the frequency-size distributions of actual fires follow power laws that resemble those produced by simple cellular models from statistical mechanics has been interpreted as evidence that flammable landscapes operate as self-organising systems with scale invariant fire size distributions emerging 'spontaneously' from simple rules of contagious fire spread and a strong feedback between fires and fuel patterns. In this paper we argue that the resemblance of simulated and actual fire size distributions is an example of equifinality, that is fires in model landscapes and actual landscapes may show similar statistical behaviour but this is reached by qualitatively different pathways or controlling mechanisms. We support this claim with two key findings regarding simulated fire spread mechanisms and fire-fuel feedbacks. Firstly, we demonstrate that the power law behaviour of fire size distributions in the widely used Drossel and Schwabl (1992) Forest Fire Model (FFM) is strictly conditional on simulating fire spread as a cell-to-cell contagion over a fixed distance; the invariant scaling of fire sizes breaks down under the slightest variation in that distance, suggesting that pattern formation in the FFM is irreconcilable with the reality of disparate rates and modes of fire spread observed in the field. Secondly, we review field evidence showing that fuel age effects on the probability of fire spread, a key assumption in simulation models like the FFM, do not generally apply across flammable environments. Finally, we explore alternative explanations for the formation of scale invariant fire sizes in real landscapes. Using observations from southern Australian forest regions we demonstrate that the spatiotemporal patterns of fuel dryness and magnitudes of fire driving weather events set strong environmental templates for regional fire size distributions.

A south equatorial African precipitation dipole and the associated atmospheric circulation

NASA Astrophysics Data System (ADS)

Dezfuli, A. K.; Zaitchik, B.; Gnanadesikan, A.

2013-12-01

South Equatorial Africa (SEA) is a climatically diverse region that includes a dramatic topographic and vegetation contrast between the lowland, humid Congo basin to the west and the East African Plateau to the east. Due to lack of conventional weather data and a tendency for researchers to treat East and western Africa as separate regions, dynamics of the atmospheric water cycle across SEA have received relatively little attention, particularly at subseasonal timescales. Both western and eastern sectors of SEA are affected by large-scale drivers of the water cycle associated with Atlantic variability (western sector), Indian Ocean variability (eastern sector) and Pacific variability (both sectors). However, a specific characteristic of SEA is strong heterogeneity in interannual rainfall variability that cannot be explained by large-scale climatic phenomena. For this reason, this study examines regional climate dynamics on daily time-scale with a focus on the role that the abrupt topographic contrast between the lowland Congo and the East African highlands plays in driving rainfall behavior on short timescales. Analysis of daily precipitation data during November-March reveals a zonally-oriented dipole mode over SEA that explains the leading pattern of weather-scale precipitation variability in the region. The separating longitude of the two poles is coincident with the zonal variation of topography. An anomalous counter-clockwise atmospheric circulation associated with the dipole mode appears over the entire SEA. The circulation is triggered by its low-level westerly component, which is in turn generated by an interhemispheric pressure gradient. These enhanced westerlies hit the East African highlands and produce topographically-driven low-level convergence and convection that further intensifies the circulation. Recent studies have shown that under climate change the position and intensity of subtropical highs in both hemispheres and the intensity of precipitation over equatorial Africa are projected to change. Both of these trends have implications for the manner in which large-scale dynamics will interact with regional topography, affecting the intensity and frequency of the dipole mode characterized in this study and the occurrence of extreme wet and dry spells in the region.

Characterization of fire regime in Sardinia (Italy)

NASA Astrophysics Data System (ADS)

Bacciu, V. M.; Salis, M.; Mastinu, S.; Masala, F.; Sirca, C.; Spano, D.

2012-12-01

In the last decades, a number of Authors highlighted the crucial role of forest fires within Mediterranean ecosystems, with impacts both negative and positive on all biosphere components and with reverberations on different scales. Fire determines the landscape structure and plant composition, but it is also the cause of enormous economic and ecological damages, beside the loss of human life. In Sardinia (Italy), the second largest island of the Mediterranean Basin, forest fires are perceived as one of the main environmental and social problems, and data are showing that the situation is worsening especially within the rural-urban peripheries and the increasing number of very large forest fires. The need for information concerning forest fire regime has been pointed out by several Authors (e.g. Rollins et al., 2002), who also emphasized the importance of understanding the factors (such as weather/climate, socio-economic, and land use) that determine spatial and temporal fire patterns. These would be used not only as a baseline to predict the climate change effect on forest fires, but also as a fire management and mitigation strategy. The main aim of this paper is, thus, to analyze the temporal and spatial patterns of fire occurrence in Sardinia (Italy) during the last three decades (1980-2010). For the analyzed period, fire statistics were provided by the Sardinian Forest Service (CFVA - Corpo Forestale e di Vigilanza Ambientale), while weather data for eight weather stations were obtained from the web site www.tutiempo.it. For each station, daily series of precipitation, mean, maximum and minimum temperature, relative humidity and wind speed were available. The present study firstly analyzed fire statistics (burned area and number of fires) according to the main fire regime characteristics (seasonality, fire return interval, fire incidence, fire size distribution). Then, fire and weather daily values were averaged to obtain monthly, seasonal and annual values, and a set of parametric and not parametric statistical tests were used to analyze the fire-weather relationships. Results showed a high inter- and intra-annual variability, also considering the different type of affected vegetation. As for other Mediterranean areas, a smaller number of large fires caused a high proportion of burned area. Land cover greatly influenced fire occurrence and fire size distribution across the landscape. Furthermore, fire activity (number of fires and area burned) showed significant correlations with weather variables, especially summer precipitation and wind, which seemed to drive the fire seasons and the fire propagation, respectively.

Solar EUV irradiance for space weather applications

NASA Astrophysics Data System (ADS)

Viereck, R. A.

2015-12-01

Solar EUV irradiance is an important driver of space weather models. Large changes in EUV and x-ray irradiances create large variability in the ionosphere and thermosphere. Proxies such as the F10.7 cm radio flux, have provided reasonable estimates of the EUV flux but as the space weather models become more accurate and the demands of the customers become more stringent, proxies are no longer adequate. Furthermore, proxies are often provided only on a daily basis and shorter time scales are becoming important. Also, there is a growing need for multi-day forecasts of solar EUV irradiance to drive space weather forecast models. In this presentation we will describe the needs and requirements for solar EUV irradiance information from the space weather modeler's perspective. We will then translate these requirements into solar observational requirements such as spectral resolution and irradiance accuracy. We will also describe the activities at NOAA to provide long-term solar EUV irradiance observations and derived products that are needed for real-time space weather modeling.

Below-ground attributes on reclaimed surface minelands over a 40-year chronosequence

NASA Astrophysics Data System (ADS)

Limb, Ryan; Bohrer, Stefanie; Volk, Jay

2017-04-01

Reclamation following mining activities often aims to restore stable soils that support productive and diverse native plant communities. The soil re-spread process increases soil compaction, which may alter soil water, plant composition, rooting depths and soil organic matter. This may have a direct impact on vegetation establishment and species recruitment. Seasonal wet/dry and freeze/thaw patterns are thought to alleviate soil compaction over time. However, this has not been formally evaluated on reclaimed landscapes at large scales. Our objectives were to (1) determine soil compaction alleviation, (2) rooting depth and (3) spatial patterns of soil water content over a time-since-reclamation gradient. Soil resistance to penetration varied by depth, with shallow compaction remaining unchanged, but deeper compaction increased over time rather than being alleviated. Root biomass and depth did not increase with time and was consistently less than reference locations. Plant communities initially had a strong native component, but quickly became dominated by invasive species following reclamation and soil water content became increasingly homogeneous over the 40-year chronosequence. Seasonal weather patterns and soil organic matter additions can reduce soil compaction if water infiltration is not limited. Shallow and strongly fibrous-rooted grasses present in reclaimed sites added organic matter to shallow soil layers, but did not penetrate the compacted layers and allow water infiltration. Strong linkages between land management strategies, soil properties and vegetation composition can advance reclamation efforts and promote heterogeneous landscapes. However, current post-reclamation management strategies are not facilitating natural seasonal weather patterns to reducing soil compaction.

High potential for weathering and climate effects of non-vascular vegetation in the Late Ordovician

NASA Astrophysics Data System (ADS)

Porada, Philipp; Lenton, Tim; Pohl, Alexandre; Weber, Bettina; Mander, Luke; Donnadieu, Yannick; Beer, Christian; Pöschl, Ulrich; Kleidon, Axel

2017-04-01

Early non-vascular vegetation in the Late Ordovician may have strongly increased chemical weathering rates of surface rocks at the global scale. This could have led to a drawdown of atmospheric CO2 and, consequently, a decrease in global temperature and an interval of glaciations. Under current climatic conditions, usually field or laboratory experiments are used to quantify enhancement of chemical weathering rates by non-vascular vegetation. However, these experiments are constrained to a small spatial scale and a limited number of species. This complicates the extrapolation to the global scale, even more so for the geological past, where physiological properties of non-vascular vegetation may have differed from current species. Here we present a spatially explicit modelling approach to simulate large-scale chemical weathering by non-vascular vegetation in the Late Ordovician. For this purpose, we use a process-based model of lichens and bryophytes, since these organisms are probably the closest living analogue to Late Ordovician vegetation. The model explicitly represents multiple physiological strategies, which enables the simulated vegetation to adapt to Ordovician climatic conditions. We estimate productivity of Ordovician vegetation with the model, and relate it to chemical weathering by assuming that the organisms dissolve rocks to extract phosphorus for the production of new biomass. Thereby we account for limits on weathering due to reduced supply of unweathered rock material in shallow regions, as well as decreased transport capacity of runoff for dissolved weathered material in dry areas. We simulate a potential global weathering flux of 2.8 km3 (rock) per year, which we define as volume of primary minerals affected by chemical transformation. Our estimate is around 3 times larger than today's global chemical weathering flux. Furthermore, chemical weathering rates simulated by our model are highly sensitive to atmospheric CO2 concentration, which implies a strong negative feedback between weathering by non-vascular vegetation and Ordovician climate.

Change in Weather Research and Forecasting (WRF) Model Accuracy with Age of Input Data from the Global Forecast System (GFS)

DTIC Science & Technology

2016-09-01

Laboratory Change in Weather Research and Forecasting (WRF) Model Accuracy with Age of Input Data from the Global Forecast System (GFS) by JL Cogan...analysis. As expected, accuracy generally tended to decline as the large-scale data aged , but appeared to improve slightly as the age of the large...19 Table 7 Minimum and maximum mean RMDs for each WRF time (or GFS data age ) category. Minimum and

An adaptive two-stage analog/regression model for probabilistic prediction of small-scale precipitation in France

NASA Astrophysics Data System (ADS)

Chardon, Jérémy; Hingray, Benoit; Favre, Anne-Catherine

2018-01-01

Statistical downscaling models (SDMs) are often used to produce local weather scenarios from large-scale atmospheric information. SDMs include transfer functions which are based on a statistical link identified from observations between local weather and a set of large-scale predictors. As physical processes driving surface weather vary in time, the most relevant predictors and the regression link are likely to vary in time too. This is well known for precipitation for instance and the link is thus often estimated after some seasonal stratification of the data. In this study, we present a two-stage analog/regression model where the regression link is estimated from atmospheric analogs of the current prediction day. Atmospheric analogs are identified from fields of geopotential heights at 1000 and 500 hPa. For the regression stage, two generalized linear models are further used to model the probability of precipitation occurrence and the distribution of non-zero precipitation amounts, respectively. The two-stage model is evaluated for the probabilistic prediction of small-scale precipitation over France. It noticeably improves the skill of the prediction for both precipitation occurrence and amount. As the analog days vary from one prediction day to another, the atmospheric predictors selected in the regression stage and the value of the corresponding regression coefficients can vary from one prediction day to another. The model allows thus for a day-to-day adaptive and tailored downscaling. It can also reveal specific predictors for peculiar and non-frequent weather configurations.

NOAA's world-class weather and climate prediction center opens at

Science.gov Websites

StumbleUpon Digg More Destinations NOAA's world-class weather and climate prediction center opens at currents and large-scale rain and snow storms. Billions of earth observations from around the world flow operations. Investing in this center is an investment in our human capital, serving as a world class facility

Observational evidence of European summer weather patterns predictable from spring

NASA Astrophysics Data System (ADS)

Ossó, Albert; Sutton, Rowan; Shaffrey, Len; Dong, Buwen

2018-01-01

Forecasts of summer weather patterns months in advance would be of great value for a wide range of applications. However, seasonal dynamical model forecasts for European summers have very little skill, particularly for rainfall. It has not been clear whether this low skill reflects inherent unpredictability of summer weather or, alternatively, is a consequence of weaknesses in current forecast systems. Here we analyze atmosphere and ocean observations and identify evidence that a specific pattern of summertime atmospheric circulation––the summer East Atlantic (SEA) pattern––is predictable from the previous spring. An index of North Atlantic sea-surface temperatures in March–April can predict the SEA pattern in July–August with a cross-validated correlation skill above 0.6. Our analyses show that the sea-surface temperatures influence atmospheric circulation and the position of the jet stream over the North Atlantic. The SEA pattern has a particularly strong influence on rainfall in the British Isles, which we find can also be predicted months ahead with a significant skill of 0.56. Our results have immediate application to empirical forecasts of summer rainfall for the United Kingdom, Ireland, and northern France and also suggest that current dynamical model forecast systems have large potential for improvement.

Increases in residential and energy development are associated with reductions in recruitment for a large ungulate.

PubMed

Johnson, Heather E; Sushinsky, Jessica R; Holland, Andrew; Bergman, Eric J; Balzer, Trevor; Garner, James; Reed, Sarah E

2017-02-01

Land-use change due to anthropogenic development is pervasive across the globe and commonly associated with negative consequences for biodiversity. While land-use change has been linked to shifts in the behavior and habitat-use patterns of wildlife species, little is known about its influence on animal population dynamics, despite the relevance of such information for conservation. We conducted the first broad-scale investigation correlating temporal patterns of land-use change with the demographic rates of mule deer, an iconic species in the western United States experiencing wide-scale population declines. We employed a unique combination of long-term (1980-2010) data on residential and energy development across western Colorado, in conjunction with congruent data on deer recruitment, to quantify annual changes in land-use and correlate those changes with annual indices of demographic performance. We also examined annual variation in weather conditions, which are well recognized to influence ungulate productivity, and provided a basis for comparing the relative strength of different covariates in their association with deer recruitment. Using linear mixed models, we found that increasing residential and energy development within deer habitat were correlated with declining recruitment rates, particularly within seasonal winter ranges. Residential housing had two times the magnitude of effect of any other factor we investigated, and energy development had an effect size similar to key weather variables known to be important to ungulate dynamics. This analysis is the first to correlate a demographic response in mule deer with residential and energy development at large spatial extents relevant to population performance, suggesting that further increases in these development types on deer ranges are not compatible with the goal of maintaining highly productive deer populations. Our results underscore the significance of expanding residential development on mule deer populations, a factor that has received little research attention in recent years, despite its rapidly increasing footprint across the landscape. © 2016 The Authors. Global Change Biology Published by John Wiley & Sons Ltd.

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

Simulation of seasonal US precipitation and temperature by the nested CWRF-ECHAM system

NASA Astrophysics Data System (ADS)

Chen, Ligang; Liang, Xin-Zhong; DeWitt, David; Samel, Arthur N.; Wang, Julian X. L.

2016-02-01

This study investigates the refined simulation skill that results when the regional Climate extension of the Weather Research and Forecasting (CWRF) model is nested in the ECMWF Hamburg version 4.5 (ECHAM) atmospheric general circulation model over the United States during 1980-2009, where observed sea surface temperatures are used in both models. Over the contiguous US, for each of the four seasons from winter to fall, CWRF reduces the root mean square error of the ECHAM seasonal mean surface air temperature simulation by 0.19, 0.82, 2.02 and 1.85 °C, and increases the equitable threat score of seasonal mean precipitation by 0.18, 0.11, 0.09 and 0.12. CWRF also simulates much more realistically daily precipitation frequency and heavy precipitation events, typically over the Central Great Plains, Cascade Mountains and Gulf Coast States. These CWRF skill enhancements are attributed to the increased spatial resolution and physics refinements in representing orographic, terrestrial hydrology, convection, and cloud-aerosol-radiation effects and their interactions. Empirical orthogonal function analysis of seasonal mean precipitation and surface air temperature interannual variability shows that, in general, CWRF substantially improves the spatial distribution of both quantities, while temporal evolution (i.e. interannual variability) of the first 3 primary patterns is highly correlated with that of the driving ECHAM (except for summer precipitation), and they both have low temporal correlations against observations. During winter, when large-scale forcing dominates, both models also have similar responses to strong ENSO signals where they successfully capture observed precipitation composite anomalies but substantially fail to reproduce surface air temperature anomalies. When driven by the ECMWF Reanalysis Interim, CWRF produces a very realistic interannual evolution of large-scale precipitation and surface air temperature patterns where the temporal correlations with observations are significant. These results indicate that CWRF can greatly improve mesoscale regional climate structures but it cannot change interannual variations of the large-scale patterns, which are determined by the driving lateral boundary conditions.

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.

Large-scale climate variation modifies the winter grouping behavior of endangered Indiana bats

USGS Publications Warehouse

Thogmartin, Wayne E.; McKann, Patrick C.

2014-01-01

Power laws describe the functional relationship between 2 quantities, such as the frequency of a group as the multiplicative power of group size. We examined whether the annual size of well-surveyed wintering populations of endangered Indiana bats (Myotis sodalis) followed a power law, and then leveraged this relationship to predict whether the aggregation of Indiana bats in winter was influenced by global climate processes. We determined that Indiana bat wintering populations were distributed according to a power law (mean scaling coefficient α = −0.44 [95% confidence interval {95% CI} = −0.61, −0.28). The antilog of these annual scaling coefficients ranged between 0.67 and 0.81, coincident with the three-fourths power found in many other biological phenomena. We associated temporal patterns in the annual (1983–2011) scaling coefficient with the North Atlantic Oscillation (NAO) index in August (βNAOAugust = −0.017 [90% CI = −0.032, −0.002]), when Indiana bats are deciding when and where to hibernate. After accounting for the strong effect of philopatry to habitual wintering locations, Indiana bats aggregated in larger wintering populations during periods of severe winter and in smaller populations in milder winters. The association with August values of the NAO indicates that bats anticipate future winter weather conditions when deciding where to roost, a heretofore unrecognized role for prehibernation swarming behavior. Future research is needed to understand whether the three-fourths–scaling patterns we observed are related to scaling in metabolism.

A method to encapsulate model structural uncertainty in ensemble projections of future climate: EPIC v1.0

NASA Astrophysics Data System (ADS)

Lewis, Jared; Bodeker, Greg E.; Kremser, Stefanie; Tait, Andrew

2017-12-01

A method, based on climate pattern scaling, has been developed to expand a small number of projections of fields of a selected climate variable (X) into an ensemble that encapsulates a wide range of indicative model structural uncertainties. The method described in this paper is referred to as the Ensemble Projections Incorporating Climate model uncertainty (EPIC) method. Each ensemble member is constructed by adding contributions from (1) a climatology derived from observations that represents the time-invariant part of the signal; (2) a contribution from forced changes in X, where those changes can be statistically related to changes in global mean surface temperature (Tglobal); and (3) a contribution from unforced variability that is generated by a stochastic weather generator. The patterns of unforced variability are also allowed to respond to changes in Tglobal. The statistical relationships between changes in X (and its patterns of variability) and Tglobal are obtained in a training phase. Then, in an implementation phase, 190 simulations of Tglobal are generated using a simple climate model tuned to emulate 19 different global climate models (GCMs) and 10 different carbon cycle models. Using the generated Tglobal time series and the correlation between the forced changes in X and Tglobal, obtained in the training phase, the forced change in the X field can be generated many times using Monte Carlo analysis. A stochastic weather generator is used to generate realistic representations of weather which include spatial coherence. Because GCMs and regional climate models (RCMs) are less likely to correctly represent unforced variability compared to observations, the stochastic weather generator takes as input measures of variability derived from observations, but also responds to forced changes in climate in a way that is consistent with the RCM projections. This approach to generating a large ensemble of projections is many orders of magnitude more computationally efficient than running multiple GCM or RCM simulations. Such a large ensemble of projections permits a description of a probability density function (PDF) of future climate states rather than a small number of individual story lines within that PDF, which may not be representative of the PDF as a whole; the EPIC method largely corrects for such potential sampling biases. The method is useful for providing projections of changes in climate to users wishing to investigate the impacts and implications of climate change in a probabilistic way. A web-based tool, using the EPIC method to provide probabilistic projections of changes in daily maximum and minimum temperatures for New Zealand, has been developed and is described in this paper.

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.

Use of observational and model-derived fields and regime model output statistics in mesoscale forecasting

NASA Technical Reports Server (NTRS)

Forbes, G. S.; Pielke, R. A.

1985-01-01

Various empirical and statistical weather-forecasting studies which utilize stratification by weather regime are described. Objective classification was used to determine weather regime in some studies. In other cases the weather pattern was determined on the basis of a parameter representing the physical and dynamical processes relevant to the anticipated mesoscale phenomena, such as low level moisture convergence and convective precipitation, or the Froude number and the occurrence of cold-air damming. For mesoscale phenomena already in existence, new forecasting techniques were developed. The use of cloud models in operational forecasting is discussed. Models to calculate the spatial scales of forcings and resultant response for mesoscale systems are presented. The use of these models to represent the climatologically most prevalent systems, and to perform case-by-case simulations is reviewed. Operational implementation of mesoscale data into weather forecasts, using both actual simulation output and method-output statistics is discussed.

Simulating the convective precipitation diurnal cycle in a North American scale convection-permitting model

NASA Astrophysics Data System (ADS)

Scaff, L.; Li, Y.; Prein, A. F.; Liu, C.; Rasmussen, R.; Ikeda, K.

2017-12-01

A better representation of the diurnal cycle of convective precipitation is essential for the analysis of the energy balance and the water budget components such as runoff, evaporation and infiltration. Convection-permitting regional climate modeling (CPM) has been shown to improve the models' performance of summer precipitation, allowing to: (1) simulate the mesoscale processes in more detail and (2) to provide more insights in future changes in convective precipitation under climate change. In this work we investigate the skill of the Weather Research and Forecast model (WRF) in simulating the summer precipitation diurnal cycle over most of North America. We use 4 km horizontal grid spacing in a 13-years long current and future period. The future scenario is assuming no significant changes in large-scale weather patterns and aims to answer how the weather of the current climate would change if it would reoccur at the end of the century under a high-end emission scenario (Pseudo Global Warming). We emphasize on a region centered on the lee side of the Canadian Rocky Mountains, where the summer precipitation amount shows a regional maximum. The historical simulations are capable to correctly represent the diurnal cycle. At the lee-side of the Canadian Rockies the increase in the convective available potential energy as well as pronounced low-level moisture flux from the southeast Prairies explains the local maximum in summer precipitation. The PGW scenario shows an increase in summer precipitation amount and intensity in this region, consistently with a stronger source of moisture and convective energy.

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.

Thresholds for soil cover and weathering in mountainous landscapes

NASA Astrophysics Data System (ADS)

Dixon, Jean; Benjaram, Sarah

2017-04-01

The patterns of soil formation, weathering, and erosion shape terrestrial landscapes, forming the foundation on which ecosystems and human civilizations are built. Several fundamental questions remain regarding how soils evolve, especially in mountainous landscapes where tectonics and climate exert complex forcings on erosion and weathering. In these systems, quantifying weathering is made difficult by the fact that soil cover is discontinuous and heterogeneous. Therefore, studies that attempt to measure soil weathering in such systems face a difficult bias in measurements towards more weathered portions of the landscape. Here, we explore current understanding of erosion-weathering feedbacks, and present new data from mountain systems in Western Montana. Using field mapping, analysis of LiDAR and remotely sensed land-cover data, and soil chemical analyses, we measure soil cover and surface weathering intensity across multiple spatial scales, from the individual soil profile to a landscape perspective. Our data suggest that local emergence of bedrock cover at the surface marks a landscape transition from supply to kinetic weathering regimes in these systems, and highlights the importance of characterizing complex critical zone architecture in mountain landscapes. This work provides new insight into how landscape morphology and erosion may drive important thresholds for soil cover and weathering.

Distant Influence of Kuroshio Eddies on North Pacific Weather Patterns?

PubMed

Ma, Xiaohui; Chang, Ping; Saravanan, R; Montuoro, Raffaele; Hsieh, Jen-Shan; Wu, Dexing; Lin, Xiaopei; Wu, Lixin; Jing, Zhao

2015-12-04

High-resolution satellite measurements of surface winds and sea-surface temperature (SST) reveal strong coupling between meso-scale ocean eddies and near-surface atmospheric flow over eddy-rich oceanic regions, such as the Kuroshio and Gulf Stream, highlighting the importance of meso-scale oceanic features in forcing the atmospheric planetary boundary layer (PBL). Here, we present high-resolution regional climate modeling results, supported by observational analyses, demonstrating that meso-scale SST variability, largely confined in the Kuroshio-Oyashio confluence region (KOCR), can further exert a significant distant influence on winter rainfall variability along the U.S. Northern Pacific coast. The presence of meso-scale SST anomalies enhances the diabatic conversion of latent heat energy to transient eddy energy, intensifying winter cyclogenesis via moist baroclinic instability, which in turn leads to an equivalent barotropic downstream anticyclone anomaly with reduced rainfall. The finding points to the potential of improving forecasts of extratropical winter cyclones and storm systems and projections of their response to future climate change, which are known to have major social and economic impacts, by improving the representation of ocean eddy-atmosphere interaction in forecast and climate models.

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

Introducing the Global Fire WEather Database (GFWED)

NASA Astrophysics Data System (ADS)

Field, R. D.

2015-12-01

The Canadian Fire Weather Index (FWI) System is the mostly widely used fire danger rating system in the world. We have developed a global database of daily FWI System calculations beginning in 1980 called the Global Fire WEather Database (GFWED) gridded to a spatial resolution of 0.5° latitude by 2/3° longitude. Input weather data were obtained from the NASA Modern Era Retrospective-Analysis for Research (MERRA), and two different estimates of daily precipitation from rain gauges over land. FWI System Drought Code calculations from the gridded datasets were compared to calculations from individual weather station data for a representative set of 48 stations in North, Central and South America, Europe, Russia, Southeast Asia and Australia. Agreement between gridded calculations and the station-based calculations tended to be most different at low latitudes for strictly MERRA-based calculations. Strong biases could be seen in either direction: MERRA DC over the Mato Grosso in Brazil reached unrealistically high values exceeding DC=1500 during the dry season but was too low over Southeast Asia during the dry season. These biases are consistent with those previously-identified in MERRA's precipitation and reinforce the need to consider alternative sources of precipitation data. GFWED is being used by researchers around the world for analyzing historical relationships between fire weather and fire activity at large scales, in identifying large-scale atmosphere-ocean controls on fire weather, and calibration of FWI-based fire prediction models. These applications will be discussed. More information on GFWED can be found at http://data.giss.nasa.gov/impacts/gfwed/

Large-Scale Aerosol Modeling and Analysis

DTIC Science & Technology

2008-09-30

novel method of simultaneous real- time measurements of ice-nucleating particle concentrations and size- resolved chemical composition of individual...is to develop a practical predictive capability for visibility and weather effects of aerosol particles for the entire globe for timely use in...prediction follows that used in numerical weather prediction, namely real- time assessment for initialization of first-principles models. The Naval

Process-based evaluation of the ÖKS15 Austrian climate scenarios: First results

NASA Astrophysics Data System (ADS)

Mendlik, Thomas; Truhetz, Heimo; Jury, Martin; Maraun, Douglas

2017-04-01

The climate scenarios for Austria from the ÖKS15 project consists of 13 downscaled and bias-corrected RCMs from the EURO-CORDEX project. This dataset is meant for the broad public and is now available at the central national archive for climate data (CCCA Data Center). Because of this huge public outreach it is absolutely necessary to objectively discuss the limitations of this dataset and to publish these limitations, which should also be understood by a non-scientific audience. Even though systematical climatological biases have been accounted for by the Scaled-Distribution-Mapping (SDM) bias-correction method, it is not guaranteed that the model biases have been removed for the right reasons. If climate scenarios do not get the patterns of synoptic variability right, biases will still prevail in certain weather patterns. Ultimately this will have consequences for the projected climate change signals. In this study we derive typical weather types in the Alpine Region based on patterns from mean sea level pressure from ERA-INTERIM data and check the occurrence of these synoptic phenomena in EURO-CORDEX data and their corresponding driving GCMs. Based on these weather patterns we analyze the remaining biases of the downscaled and bias-corrected scenarios. We argue that such a process-based evaluation is not only necessary from a scientific point of view, but can also help the broader public to understand the limitations of downscaled climate scenarios, as model errors can be interpreted in terms of everyday observable weather.

Towards Large-area Field-scale Operational Evapotranspiration for Water Use Mapping

NASA Astrophysics Data System (ADS)

Senay, G. B.; Friedrichs, M.; Morton, C.; Huntington, J. L.; Verdin, J.

2017-12-01

Field-scale evapotranspiration (ET) estimates are needed for improving surface and groundwater use and water budget studies. Ideally, field-scale ET estimates would be at regional to national levels and cover long time periods. As a result of large data storage and computational requirements associated with processing field-scale satellite imagery such as Landsat, numerous challenges remain to develop operational ET estimates over large areas for detailed water use and availability studies. However, the combination of new science, data availability, and cloud computing technology is enabling unprecedented capabilities for ET mapping. To demonstrate this capability, we used Google's Earth Engine cloud computing platform to create nationwide annual ET estimates with 30-meter resolution Landsat ( 16,000 images) and gridded weather data using the Operational Simplified Surface Energy Balance (SSEBop) model in support of the National Water Census, a USGS research program designed to build decision support capacity for water management agencies and other natural resource managers. By leveraging Google's Earth Engine Application Programming Interface (API) and developing software in a collaborative, open-platform environment, we rapidly advance from research towards applications for large-area field-scale ET mapping. Cloud computing of the Landsat image archive combined with other satellite, climate, and weather data, is creating never imagined opportunities for assessing ET model behavior and uncertainty, and ultimately providing the ability for more robust operational monitoring and assessment of water use at field-scales.

The impact of synoptic weather on UK surface ozone and implications for premature mortality

NASA Astrophysics Data System (ADS)

Pope, R. J.; Butt, E. W.; Chipperfield, M. P.; Doherty, R. M.; Fenech, S.; Schmidt, A.; Arnold, S. R.; Savage, N. H.

2016-12-01

Air pollutants, such as ozone, have adverse impacts on human health and cause, for example, respiratory and cardiovascular problems. In the United Kingdom (UK), peak surface ozone concentrations typically occur in the spring and summer and are controlled by emission of precursor gases, tropospheric chemistry and local meteorology which can be influenced by large-scale synoptic weather regimes. In this study we composite surface and satellite observations of summer-time (April to September) ozone under different UK atmospheric circulation patterns, as defined by the Lamb weather types. Anticyclonic conditions and easterly flows are shown to significantly enhance ozone concentrations over the UK relative to summer-time average values. Anticyclonic stability and light winds aid the trapping of ozone and its precursor gases near the surface. Easterly flows (NE, E, SE) transport ozone and precursor gases from polluted regions in continental Europe (e.g. the Benelux region) to the UK. Cyclonic conditions and westerly flows, associated with unstable weather, transport ozone from the UK mainland, replacing it with clean maritime (North Atlantic) air masses. Increased cloud cover also likely decrease ozone production rates. We show that the UK Met Office regional air quality model successfully reproduces UK summer-time ozone concentrations and ozone enhancements under anticyclonic and south-easterly conditions for the summer of 2006. By using established ozone exposure-health burden metrics, anticyclonic and easterly condition enhanced surface ozone concentrations pose the greatest public health risk.

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.

Asynchronous vegetation phenology enhances winter body condition of a large mobile herbivore.

PubMed

Searle, Kate R; Rice, Mindy B; Anderson, Charles R; Bishop, Chad; Hobbs, N T

2015-10-01

Understanding how spatial and temporal heterogeneity influence ecological processes forms a central challenge in ecology. Individual responses to heterogeneity shape population dynamics, therefore understanding these responses is central to sustainable population management. Emerging evidence has shown that herbivores track heterogeneity in nutritional quality of vegetation by responding to phenological differences in plants. We quantified the benefits mule deer (Odocoileus hemionus) accrue from accessing habitats with asynchronous plant phenology in northwest Colorado over 3 years. Our analysis examined both the direct physiological and indirect environmental effects of weather and vegetation phenology on mule deer winter body condition. We identified several important effects of annual weather patterns and topographical variables on vegetation phenology in the home ranges of mule deer. Crucially, temporal patterns of vegetation phenology were linked with differences in body condition, with deer tending to show poorer body condition in areas with less asynchronous vegetation green-up and later vegetation onset. The direct physiological effect of previous winter precipitation on mule deer body condition was much less important than the indirect effect mediated by vegetation phenology. Additionally, the influence of vegetation phenology on body fat was much stronger than that of overall vegetation productivity. In summary, changing annual weather patterns, particularly in relation to seasonal precipitation, have the potential to alter body condition of this important ungulate species during the critical winter period. This finding highlights the importance of maintaining large contiguous areas of spatially and temporally variable resources to allow animals to compensate behaviourally for changing climate-driven resource patterns.

Carbon dioxide efficiency of terrestrial enhanced weathering.

PubMed

Moosdorf, Nils; Renforth, Phil; Hartmann, Jens

2014-05-06

Terrestrial enhanced weathering, the spreading of ultramafic silicate rock flour to enhance natural weathering rates, has been suggested as part of a strategy to reduce global atmospheric CO2 levels. We budget potential CO2 sequestration against associated CO2 emissions to assess the net CO2 removal of terrestrial enhanced weathering. We combine global spatial data sets of potential source rocks, transport networks, and application areas with associated CO2 emissions in optimistic and pessimistic scenarios. The results show that the choice of source rocks and material comminution technique dominate the CO2 efficiency of enhanced weathering. CO2 emissions from transport amount to on average 0.5-3% of potentially sequestered CO2. The emissions of material mining and application are negligible. After accounting for all emissions, 0.5-1.0 t CO2 can be sequestered on average per tonne of rock, translating into a unit cost from 1.6 to 9.9 GJ per tonne CO2 sequestered by enhanced weathering. However, to control or reduce atmospheric CO2 concentrations substantially with enhanced weathering would require very large amounts of rock. Before enhanced weathering could be applied on large scales, more research is needed to assess weathering rates, potential side effects, social acceptability, and mechanisms of governance.

Nocturnal activity patterns of northern myotis (Myotis septentrionalis) during the maternity season in West Virginia (USA)

Treesearch

Joshua B. Johnson; John W. Edwards; W. Mark Ford

2011-01-01

Nocturnal activity patterns of northern myotis (Myotis septentrionalis) at diurnal roost trees remain largely uninvestigated. For example, the influence of reproductive status, weather, and roost tree and surrounding habitat characteristics on timing of emergence, intra-night activity, and entrance at their roost trees is poorly known. We examined...

Modeling the influence of organic acids on soil weathering

NASA Astrophysics Data System (ADS)

Lawrence, Corey; Harden, Jennifer; Maher, Kate

2014-08-01

Biological inputs and organic matter cycling have long been regarded as important factors in the physical and chemical development of soils. In particular, the extent to which low molecular weight organic acids, such as oxalate, influence geochemical reactions has been widely studied. Although the effects of organic acids are diverse, there is strong evidence that organic acids accelerate the dissolution of some minerals. However, the influence of organic acids at the field-scale and over the timescales of soil development has not been evaluated in detail. In this study, a reactive-transport model of soil chemical weathering and pedogenic development was used to quantify the extent to which organic acid cycling controls mineral dissolution rates and long-term patterns of chemical weathering. Specifically, oxalic acid was added to simulations of soil development to investigate a well-studied chronosequence of soils near Santa Cruz, CA. The model formulation includes organic acid input, transport, decomposition, organic-metal aqueous complexation and mineral surface complexation in various combinations. Results suggest that although organic acid reactions accelerate mineral dissolution rates near the soil surface, the net response is an overall decrease in chemical weathering. Model results demonstrate the importance of organic acid input concentrations, fluid flow, decomposition and secondary mineral precipitation rates on the evolution of mineral weathering fronts. In particular, model soil profile evolution is sensitive to kaolinite precipitation and oxalate decomposition rates. The soil profile-scale modeling presented here provides insights into the influence of organic carbon cycling on soil weathering and pedogenesis and supports the need for further field-scale measurements of the flux and speciation of reactive organic compounds.

Modeling the influence of organic acids on soil weathering

USGS Publications Warehouse

Lawrence, Corey R.; Harden, Jennifer W.; Maher, Kate

2014-01-01

Biological inputs and organic matter cycling have long been regarded as important factors in the physical and chemical development of soils. In particular, the extent to which low molecular weight organic acids, such as oxalate, influence geochemical reactions has been widely studied. Although the effects of organic acids are diverse, there is strong evidence that organic acids accelerate the dissolution of some minerals. However, the influence of organic acids at the field-scale and over the timescales of soil development has not been evaluated in detail. In this study, a reactive-transport model of soil chemical weathering and pedogenic development was used to quantify the extent to which organic acid cycling controls mineral dissolution rates and long-term patterns of chemical weathering. Specifically, oxalic acid was added to simulations of soil development to investigate a well-studied chronosequence of soils near Santa Cruz, CA. The model formulation includes organic acid input, transport, decomposition, organic-metal aqueous complexation and mineral surface complexation in various combinations. Results suggest that although organic acid reactions accelerate mineral dissolution rates near the soil surface, the net response is an overall decrease in chemical weathering. Model results demonstrate the importance of organic acid input concentrations, fluid flow, decomposition and secondary mineral precipitation rates on the evolution of mineral weathering fronts. In particular, model soil profile evolution is sensitive to kaolinite precipitation and oxalate decomposition rates. The soil profile-scale modeling presented here provides insights into the influence of organic carbon cycling on soil weathering and pedogenesis and supports the need for further field-scale measurements of the flux and speciation of reactive organic compounds.

Identifying the Threshold of Dominant Controls on Fire Spread in a Boreal Forest Landscape of Northeast China

PubMed Central

Liu, Zhihua; Yang, Jian; He, Hong S.

2013-01-01

The relative importance of fuel, topography, and weather on fire spread varies at different spatial scales, but how the relative importance of these controls respond to changing spatial scales is poorly understood. We designed a “moving window” resampling technique that allowed us to quantify the relative importance of controls on fire spread at continuous spatial scales using boosted regression trees methods. This quantification allowed us to identify the threshold value for fire size at which the dominant control switches from fuel at small sizes to weather at large sizes. Topography had a fluctuating effect on fire spread across the spatial scales, explaining 20–30% of relative importance. With increasing fire size, the dominant control switched from bottom-up controls (fuel and topography) to top-down controls (weather). Our analysis suggested that there is a threshold for fire size, above which fires are driven primarily by weather and more likely lead to larger fire size. We suggest that this threshold, which may be ecosystem-specific, can be identified using our “moving window” resampling technique. Although the threshold derived from this analytical method may rely heavily on the sampling technique, our study introduced an easily implemented approach to identify scale thresholds in wildfire regimes. PMID:23383247

Nocturnal activity patterns of northern myotis (Myotis septentrionalis) during the maternity season in West Virginia (USA)

USGS Publications Warehouse

Johnson, J.B.; Edwards, J.W.; Ford, W.M.

2011-01-01

Nocturnal activity patterns of northern myotis (Myotis septentrionalis) at diurnal roost trees remain largely uninvestigated. For example, the influence of reproductive status, weather, and roost tree and surrounding habitat characteristics on timing of emergence, intra-night activity, and entrance at their roost trees is poorly known. We examined nocturnal activity patterns of northern myotis maternity colonies during pregnancy and lactation at diurnal roost trees situated in areas that were and were not subjected to recent prescribed fires at the Fernow Experimental Forest, West Virginia from 2007 to 2009. According to exit counts and acoustic data, northern myotis colony sizes were similar between reproductive periods and roost tree settings. However, intra-night activity patterns differed slightly between reproductive periods and roost trees in burned and non-burned areas. Weather variables poorly explained variation in activity patterns during pregnancy, but precipitation and temperature were negatively associated with activity patterns during lactation. ?? Museum and Institute of Zoology PAS.

RE-Europe, a large-scale dataset for modeling a highly renewable European electricity system

PubMed Central

Jensen, Tue V.; Pinson, Pierre

2017-01-01

Future highly renewable energy systems will couple to complex weather and climate dynamics. This coupling is generally not captured in detail by the open models developed in the power and energy system communities, where such open models exist. To enable modeling such a future energy system, we describe a dedicated large-scale dataset for a renewable electric power system. The dataset combines a transmission network model, as well as information for generation and demand. Generation includes conventional generators with their technical and economic characteristics, as well as weather-driven forecasts and corresponding realizations for renewable energy generation for a period of 3 years. These may be scaled according to the envisioned degrees of renewable penetration in a future European energy system. The spatial coverage, completeness and resolution of this dataset, open the door to the evaluation, scaling analysis and replicability check of a wealth of proposals in, e.g., market design, network actor coordination and forecasting of renewable power generation. PMID:29182600

RE-Europe, a large-scale dataset for modeling a highly renewable European electricity system.

PubMed

Jensen, Tue V; Pinson, Pierre

2017-11-28

Future highly renewable energy systems will couple to complex weather and climate dynamics. This coupling is generally not captured in detail by the open models developed in the power and energy system communities, where such open models exist. To enable modeling such a future energy system, we describe a dedicated large-scale dataset for a renewable electric power system. The dataset combines a transmission network model, as well as information for generation and demand. Generation includes conventional generators with their technical and economic characteristics, as well as weather-driven forecasts and corresponding realizations for renewable energy generation for a period of 3 years. These may be scaled according to the envisioned degrees of renewable penetration in a future European energy system. The spatial coverage, completeness and resolution of this dataset, open the door to the evaluation, scaling analysis and replicability check of a wealth of proposals in, e.g., market design, network actor coordination and forecasting of renewable power generation.

RE-Europe, a large-scale dataset for modeling a highly renewable European electricity system

NASA Astrophysics Data System (ADS)

Jensen, Tue V.; Pinson, Pierre

2017-11-01

Future highly renewable energy systems will couple to complex weather and climate dynamics. This coupling is generally not captured in detail by the open models developed in the power and energy system communities, where such open models exist. To enable modeling such a future energy system, we describe a dedicated large-scale dataset for a renewable electric power system. The dataset combines a transmission network model, as well as information for generation and demand. Generation includes conventional generators with their technical and economic characteristics, as well as weather-driven forecasts and corresponding realizations for renewable energy generation for a period of 3 years. These may be scaled according to the envisioned degrees of renewable penetration in a future European energy system. The spatial coverage, completeness and resolution of this dataset, open the door to the evaluation, scaling analysis and replicability check of a wealth of proposals in, e.g., market design, network actor coordination and forecasting of renewable power generation.

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

Patterns in coupled water and energy cycle: Modeling, synthesis with observations, and assessing the subsurface-landsurface interactions

NASA Astrophysics Data System (ADS)

Rahman, A.; Kollet, S. J.; Sulis, M.

2013-12-01

In the terrestrial hydrological cycle, the atmosphere and the free groundwater table act as the upper and lower boundary condition, respectively, in the non-linear two-way exchange of mass and energy across the land surface. Identifying and quantifying the interactions among various atmospheric-subsurface-landsurface processes is complicated due to the diverse spatiotemporal scales associated with these processes. In this study, the coupled subsurface-landsurface model ParFlow.CLM was applied over a ~28,000 km2 model domain encompassing the Rur catchment, Germany, to simulate the fluxes of the coupled water and energy cycle. The model was forced by hourly atmospheric data from the COSMO-DE model (numerical weather prediction system of the German Weather Service) over one year. Following a spinup period, the model results were synthesized with observed river discharge, soil moisture, groundwater table depth, temperature, and landsurface energy flux data at different sites in the Rur catchment. It was shown that the model is able to reproduce reasonably the dynamics and also absolute values in observed fluxes and state variables without calibration. The spatiotemporal patterns in simulated water and energy fluxes as well as the interactions were studied using statistical, geostatistical and wavelet transform methods. While spatial patterns in the mass and energy fluxes can be predicted from atmospheric forcing and power law scaling in the transition and winter months, it appears that, in the summer months, the spatial patterns are determined by the spatially correlated variability in groundwater table depth. Continuous wavelet transform techniques were applied to study the variability of the catchment average mass and energy fluxes at varying time scales. From this analysis, the time scales associated with significant interactions among different mass and energy balance components were identified. The memory of precipitation variability in subsurface hydrodynamics acts at the 20-30 day time scale, while the groundwater contribution to sustain the long-term variability patterns in evapotranspiration acts at the 40-60 day scale. Diurnal patterns in connection with subsurface hydrodynamics were also detected. Thus, it appears that the subsurface hydrodynamics respond to the temporal patterns in land surface fluxes due to the variability in atmospheric forcing across multiple space and time scales.

Temporal and spatial structure in a daily wildfire-start data set from the western United States (198696)

USGS Publications Warehouse

Bartlein, P.J.; Hostetler, S.W.; Shafer, S.L.; Holman, J.O.; Solomon, A.M.

2008-01-01

The temporal and spatial structure of 332 404 daily fire-start records from the western United States for the period 1986 through 1996 is illustrated using several complimentary visualisation techniques. We supplement maps and time series plots with Hovmo??ller diagrams that reduce the spatial dimensionality of the daily data in order to reveal the underlying space?time structure. The mapped distributions of all lightning- and human-started fires during the 11-year interval show similar first-order patterns that reflect the broad-scale distribution of vegetation across the West and the annual cycle of climate. Lightning-started fires are concentrated in the summer half-year and occur in widespread outbreaks that last a few days and reflect coherent weather-related controls. In contrast, fires started by humans occur throughout the year and tend to be concentrated in regions surrounding large-population centres or intensive-agricultural areas. Although the primary controls of human-started fires are their location relative to burnable fuel and the level of human activity, spatially coherent, weather-related variations in their incidence can also be noted. ?? IAWF 2008.

Developing and applying uncertain global climate change projections for regional water management planning

NASA Astrophysics Data System (ADS)

Groves, David G.; Yates, David; Tebaldi, Claudia

2008-12-01

Climate change may impact water resources management conditions in difficult-to-predict ways. A key challenge for water managers is how to incorporate highly uncertain information about potential climate change from global models into local- and regional-scale water management models and tools to support local planning. This paper presents a new method for developing large ensembles of local daily weather that reflect a wide range of plausible future climate change scenarios while preserving many statistical properties of local historical weather patterns. This method is demonstrated by evaluating the possible impact of climate change on the Inland Empire Utilities Agency service area in southern California. The analysis shows that climate change could impact the region, increasing outdoor water demand by up to 10% by 2040, decreasing local water supply by up to 40% by 2040, and decreasing sustainable groundwater yields by up to 15% by 2040. The range of plausible climate projections suggests the need for the region to augment its long-range water management plans to reduce its vulnerability to climate change.

Interaction effects between weather and space use on harvesting effort and patterns in red deer.

PubMed

Rivrud, Inger M; Meisingset, Erling L; Loe, Leif E; Mysterud, Atle

2014-12-01

Most cervid populations in Europe and North America are managed through selective harvesting, often with age- and sex-specific quotas, with a large influence on the population growth rate. Less well understood is how prevailing weather affects harvesting selectivity and off-take indirectly through changes in individual animal and hunter behavior. The behavior and movement patterns of hunters and their prey are expected to be influenced by weather conditions. Furthermore, habitat characteristics like habitat openness are also known to affect movement patterns and harvesting vulnerability, but how much such processes affect harvest composition has not been quantified. We use harvest data from red deer (Cervus elaphus) to investigate how weather and habitat characteristics affect behavioral decisions of red deer and their hunters throughout the hunting season. More specifically, we look at how sex and age class, temperature, precipitation, moon phase, and day of week affect the probability of being harvested on farmland (open habitat), hunter effort, and the overall harvest numbers. Moon phase and day of week were the strongest predictors of hunter effort and harvest numbers, with higher effort during full moon and weekends, and higher numbers during full moon. In general, the effect of fall weather conditions and habitat characteristics on harvest effort and numbers varied through the season. Yearlings showed the highest variation in the probability of being harvested on farmland through the season, but there was no effect of sex. Our study is among the first to highlight that weather may affect harvesting patterns and off-take indirectly through animal and hunter behavior, but the interaction effects of weather and space use on hunter behavior are complicated, and seem less important than hunter preference and quotas in determining hunter selection and harvest off-take. The consideration of hunter behavior is therefore key when forming management rules for sustainable harvesting.

Interaction effects between weather and space use on harvesting effort and patterns in red deer

PubMed Central

Rivrud, Inger M; Meisingset, Erling L; Loe, Leif E; Mysterud, Atle

2014-01-01

Most cervid populations in Europe and North America are managed through selective harvesting, often with age- and sex-specific quotas, with a large influence on the population growth rate. Less well understood is how prevailing weather affects harvesting selectivity and off-take indirectly through changes in individual animal and hunter behavior. The behavior and movement patterns of hunters and their prey are expected to be influenced by weather conditions. Furthermore, habitat characteristics like habitat openness are also known to affect movement patterns and harvesting vulnerability, but how much such processes affect harvest composition has not been quantified. We use harvest data from red deer (Cervus elaphus) to investigate how weather and habitat characteristics affect behavioral decisions of red deer and their hunters throughout the hunting season. More specifically, we look at how sex and age class, temperature, precipitation, moon phase, and day of week affect the probability of being harvested on farmland (open habitat), hunter effort, and the overall harvest numbers. Moon phase and day of week were the strongest predictors of hunter effort and harvest numbers, with higher effort during full moon and weekends, and higher numbers during full moon. In general, the effect of fall weather conditions and habitat characteristics on harvest effort and numbers varied through the season. Yearlings showed the highest variation in the probability of being harvested on farmland through the season, but there was no effect of sex. Our study is among the first to highlight that weather may affect harvesting patterns and off-take indirectly through animal and hunter behavior, but the interaction effects of weather and space use on hunter behavior are complicated, and seem less important than hunter preference and quotas in determining hunter selection and harvest off-take. The consideration of hunter behavior is therefore key when forming management rules for sustainable harvesting. PMID:25558369

Integrating weather and geotechnical monitoring data for assessing the stability of large scale surface mining operations

NASA Astrophysics Data System (ADS)

Steiakakis, Chrysanthos; Agioutantis, Zacharias; Apostolou, Evangelia; Papavgeri, Georgia; Tripolitsiotis, Achilles

2016-01-01

The geotechnical challenges for safe slope design in large scale surface mining operations are enormous. Sometimes one degree of slope inclination can significantly reduce the overburden to ore ratio and therefore dramatically improve the economics of the operation, while large scale slope failures may have a significant impact on human lives. Furthermore, adverse weather conditions, such as high precipitation rates, may unfavorably affect the already delicate balance between operations and safety. Geotechnical, weather and production parameters should be systematically monitored and evaluated in order to safely operate such pits. Appropriate data management, processing and storage are critical to ensure timely and informed decisions. This paper presents an integrated data management system which was developed over a number of years as well as the advantages through a specific application. The presented case study illustrates how the high production slopes of a mine that exceed depths of 100-120 m were successfully mined with an average displacement rate of 10- 20 mm/day, approaching an almost slow to moderate landslide velocity. Monitoring data of the past four years are included in the database and can be analyzed to produce valuable results. Time-series data correlations of movements, precipitation records, etc. are evaluated and presented in this case study. The results can be used to successfully manage mine operations and ensure the safety of the mine and the workforce.

Modelling unsaturated/saturated flow in weathered profiles

NASA Astrophysics Data System (ADS)

Ireson, A. M.; Ali, M. A.; Van Der Kamp, G.

2016-12-01

Vertical weathering profiles are a common feature of many geological materials, where the fracture or macropore porosity decreases progressively below the ground surface. The weathered near surface zone (WNSZ) has an enhanced storage and permeability. When the water table is deep, the WNSZ can act to buffer recharge. When the water table is shallow, intersecting the WNSZ, transmissivity and lateral saturated flow, increase with increasing water table elevation. Such a situation exists in the glacial till dominated landscapes of the Canadian prairies, effectively resulting in dynamic patterns of subsurface connectivity. Using dual permeability hydraulic properties with vertically scaled macroporosity, we show how the WNSZ can be represented in models. The resulting model can be more parsimonious than an equivalent model with two or more discrete layers, and more physically realistic. We implement our model in PARFLOW-CLM, and apply the model to a field site in the Canadian prairies. We are able to convincingly simulate shallow groundwater dynamics, and spatio-temporal patterns of groundwater connectivity.

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.

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

Overview of current research on atmospheric interactions with wildland fires

Treesearch

Warren E. Heilman

1996-01-01

Changes in the large-scale mean thermal structure of the atmosphere have the potential for affecting the dynamics of the atmosphere across the entire spectrum of scales that govern atmospheric processes. Inherent in these changes are interactions among the scales that could change, resulting in an alteration in the frequency of regional weather systems conducive to...

Atlas of the global distribution of atmospheric heating during the global weather experiment

NASA Technical Reports Server (NTRS)

Schaack, Todd K.; Johnson, Donald R.

1991-01-01

Global distributions of atmospheric heating for the annual cycle of the Global Weather Experiment are estimated from the European Centre for Medium-Range Weather Forecasts (ECMWF) Level 3b data set. Distributions of monthly, seasonally, and annually averaged heating are presented for isentropic and isobaric layers within the troposphere and for the troposphere as a whole. The distributions depict a large-scale structure of atmospheric heating that appears spatially and temporally consistent with known features of the global circulation and the seasonal evolution.

Integrated climate-chemical indicators of diffuse pollution from land to water.

PubMed

Mellander, Per-Erik; Jordan, Phil; Bechmann, Marianne; Fovet, Ophélie; Shore, Mairead M; McDonald, Noeleen T; Gascuel-Odoux, Chantal

2018-01-17

Management of agricultural diffuse pollution to water remains a challenge and is influenced by the complex interactions of rainfall-runoff pathways, soil and nutrient management, agricultural landscape heterogeneity and biogeochemical cycling in receiving water bodies. Amplified cycles of weather can also influence nutrient loss to water although they are less considered in policy reviews. Here, we present the development of climate-chemical indicators of diffuse pollution in highly monitored catchments in Western Europe. Specifically, we investigated the influences and relationships between weather processes amplified by the North Atlantic Oscillation during a sharp upward trend (2010-2016) and the patterns of diffuse nitrate and phosphorus pollution in rivers. On an annual scale, we found correlations between local catchment-scale nutrient concentrations in rivers and the influence of larger, oceanic-scale climate patterns defined by the intensity of the North Atlantic Oscillation. These influences were catchment-specific showing positive, negative or no correlation according to a typology. Upward trends in these decadal oscillations may override positive benefits of local management in some years or indicate greater benefits in other years. Developing integrated climate-chemical indicators into catchment monitoring indicators will provide a new and important contribution to water quality management objectives.

Global weather and local butterflies: variable responses to a large-scale climate pattern along an elevational gradient.

PubMed

Pardikes, Nicholas A; Shapiro, Arthur M; Dyer, Lee A; Forister, Matthew L

2015-11-01

Understanding the spatial and temporal scales at which environmental variation affects populations of plants and animals is an important goal for modern population biology, especially in the context of shifting climatic conditions. The El Niño Southern Oscillation (ENSO) generates climatic extremes of interannual variation, and has been shown to have significant effects on the diversity and abundance of a variety of terrestrial taxa. However, studies that have investigated the influence of such large-scale climate phenomena have often been limited in spatial and taxonomic scope. We used 23 years (1988-2010) of a long-term butterfly monitoring data set to explore associations between variation in population abundance of 28 butterfly species and variation in ENSO-derived sea surface temperature anomalies (SSTA) across 10 sites that encompass an elevational range of 2750 m in the Sierra Nevada mountain range of California. Our analysis detected a positive, regional effect of increased SSTA on butterfly abundance (wetter and warmer years predict more butterfly observations), yet the influence of SSTA on butterfly abundances varied along the elevational gradient, and also differed greatly among the 28 species. Migratory species had the strongest relationships with ENSO-derived SSTA, suggesting that large-scale climate indices are particularly valuable for understanding biotic-abiotic relationships of the most mobile species. In general, however, the ecological effects of large-scale climatic factors are context dependent between sites and species. Our results illustrate the power of long-term data sets for revealing pervasive yet subtle climatic effects, but also caution against expectations derived from exemplar species or single locations in the study of biotic-abiotic interactions.

Spatio-temporal characteristics of the diurnal precipitation cycle over Sweden and the linkage to large-scale circulation

NASA Astrophysics Data System (ADS)

Walther, A.; Jeong, J.-H.; Chen, D.

2009-04-01

Rainfall events exhibit diurnal cycle in both frequency and amount, of which phase and amplitude show substantial geographic and seasonal variation. Although the diurnal cycle of precipitation is one of the fundamental characteristics to determine local weather and climate, most of sophisticated climate models still have great deficiencies in reproducing it. Thus more exact understanding of the diurnal precipitation cycle and its mechanisms is thought to be very important to improve climate models and their prediction results. In this work we investigate the diurnal cycle of precipitation in Sweden using ground based hourly observations for 1996-2008. For the precipitation amount and frequency, mean diurnal cycles are computed, and the peak timing and amplitude of the diurnal and semi-diurnal cycle of precipitation are estimated by the harmonic analysis method. Clear mean diurnal precipitation cycles as well as distinct spatial patterns for all seasons are derived. In summer, showing the most distinct pattern, the majority of the stations show a clear rainfall maximum in the afternoon (12-18 LST) except for the coastal part of Central Sweden where we see an early-morning peak (00-06 LST) and the east coast of southern Sweden where we find a morning peak (06-12 LST). The clear afternoon peak may be due to high insolation accumulated during the day time in summer leading to a local convection activity later on that day. These coastal bands mostly consist of the stations closest to the Baltic Sea. Meso-scale convection connected to temperature differences between sea and land combined with a favorable wind pattern seems to play a role here. In the transition seasons, spring and autumn, the amplitude is weaker and the spatial pattern of peak timing is less distinct than in summer. In spring the westcoast stations have a morning peak and stations in southeastern Sweden show an afternoon peak. In autumn we see a zonal division with a clear afternoon peak in southern Sweden. This might be due to a steeply decreasing energy input from the solar insolation in the northern parts causing less convection activity but still enough insolation to cause an afternoon peak in southern Sweden. In both seasons, spring and autumn, north of 60 degrees the pattern is mixed showing early-morning, morning and afternoon peaks. The winter pattern is characterized by afternoon peaks along the eastcoast and central South Sweden and morning peaks over the most of the other parts of the country. However, the amplitude of the diurnal cycle is much weaker compared to that in summer or autumn. In order to examine the large scale circulation which might modulate the diurnal cycle, the Lamb weather types are computed based on sea level pressure fields from the NCEP/NCAR reanalysis 2 dataset with daily and 6-hourly resolution, respectively. The Lamb types based on 6-hourly SLP underline the high temporal variability of atmospheric conditions over the research area. Throughout all seasons, on about 45% of the days two or more circulation classes are different. In 6.3% (JJA) to 8.4% (DJF) of the days can observe 4 different Lamb classes. Using Lamb types with 6-hourly resolution leads to a somewhat finer classification. On average, for about one third of the days with precipitation the daily Lamb type and the appropriate 6-hourly one are different. The most frequent large-scale circulation classes coupled to precipitation events are of cyclonic or directional type. The atmospheric circulation patterns do not follow a diurnal cycle, whereas the local observed precipitation does. Knowledge about the timing of the rainfall is important in order to assign the right underlying circulation patterns to precipitation events.

Causal inference between bioavailability of heavy metals and environmental factors in a large-scale region.

PubMed

Liu, Yuqiong; Du, Qingyun; Wang, Qi; Yu, Huanyun; Liu, Jianfeng; Tian, Yu; Chang, Chunying; Lei, Jing

2017-07-01

The causation between bioavailability of heavy metals and environmental factors are generally obtained from field experiments at local scales at present, and lack sufficient evidence from large scales. However, inferring causation between bioavailability of heavy metals and environmental factors across large-scale regions is challenging. Because the conventional correlation-based approaches used for causation assessments across large-scale regions, at the expense of actual causation, can result in spurious insights. In this study, a general approach framework, Intervention calculus when the directed acyclic graph (DAG) is absent (IDA) combined with the backdoor criterion (BC), was introduced to identify causation between the bioavailability of heavy metals and the potential environmental factors across large-scale regions. We take the Pearl River Delta (PRD) in China as a case study. The causal structures and effects were identified based on the concentrations of heavy metals (Zn, As, Cu, Hg, Pb, Cr, Ni and Cd) in soil (0-20 cm depth) and vegetable (lettuce) and 40 environmental factors (soil properties, extractable heavy metals and weathering indices) in 94 samples across the PRD. Results show that the bioavailability of heavy metals (Cd, Zn, Cr, Ni and As) was causally influenced by soil properties and soil weathering factors, whereas no causal factor impacted the bioavailability of Cu, Hg and Pb. No latent factor was found between the bioavailability of heavy metals and environmental factors. The causation between the bioavailability of heavy metals and environmental factors at field experiments is consistent with that on a large scale. The IDA combined with the BC provides a powerful tool to identify causation between the bioavailability of heavy metals and environmental factors across large-scale regions. Causal inference in a large system with the dynamic changes has great implications for system-based risk management. Copyright © 2017 Elsevier Ltd. All rights reserved.

Titan's seasonal weather patterns, associated surface modification, and geological implications

NASA Astrophysics Data System (ADS)

Turtle, E. P.; Perry, J. E.; Barnes, J. W.; McEwen, A. S.; Barbara, J. M.; Del Genio, A. D.; Hayes, A. G.; West, R. A.; Lorenz, R. D.; Schaller, E. L.; Lunine, J. I.; Ray, T. L.; Lopes, R. M. C.; Stofan, E. R.

2013-09-01

Model predictions [e.g., 1-3] and observations [e.g., 4,5] illustrate changes in Titan's weather patterns related to the seasons (Fig. 1). In two cases, surface changes were documented following large cloud outbursts (Figs. 2, 3): the first in Arrakis Planitia at high southern latitudes in Fall 2004, during Titan's late southern summer [6]; and the second at lows southern latitudes in Concordia and Hetpet Regiones, Yalaing Terra (Fig. 3), and Adiri, in Fall 2010, just over a year after Titan's northern vernal equinox [4, 7, 8]. Not only do these storms demonstrate Titan's atmospheric conditions and processes, they also have important implications for Titan's surface process, its methane cycle, and its geologic history.

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

Kitada, Toshihiro; Okamura, Kiyoshi; Tanaka, Setsu

Japanese large cities, mostly located in coastal region, have rapidly expanded in the last three decades. People in the region now experience warmer and unpleasant thermal environment in summer season, supposedly because of the extensive urbanization. Especially, under fine weather with light synoptic-scale gradient wind, the highest temperature often appears in rather inland area. An explanation to this phenomenon is horizontal transport of heat by the sea breeze which is strongly heated during its passage over the coastal urban area. This study investigated how and how much urbanization in Nohbi Plain of central Japan influences local wind and temperature distributionmore » over the plain and its surrounding region, Nohbi Plain which faces to the Pacific Ocean and is surrounded by the Japanese Alps, and thus is in a typical topographic situation in Japan. For the study we performed numerical simulations using our meso-scale meteorological model which includes k-c model for turbulence. One of the major results obtained is to have clarified a hierarchy in natural and artificial topography of various scales on their contributions to formation of characteristic diurnal pattern of wind and temperature distributions in the plain area. The Japanese Alps, the largest topographic feature in central Japan and often called the roof of Japan, gave the most important influence on the wind, although the mountains are located quite far, around 200 km, from Nohbi Plain. The way for the influence of the high mountains was to warm air mass in upper layer but below 2 km in altitude, over the Nohbi Plain through heat transport due to a large scale circulation consisting of the {open_quotes}flows from plain to plateau in lower layer and plateau to plain in upper layer{close_quotes}. Urbanization in the coastal Nohbi Plain showed little effect on the flow pattern, but caused large temperature rises at surface level in the inland area because of horizontal heat transfer by the sea breeze.« less

Large-Scale, Synoptic-Period Weather Systems in Mars' Atmosphere

NASA Astrophysics Data System (ADS)

Hollingsworth, Jeffery L.; Kahre, M.

2013-10-01

During late autumn through early spring, extratropical regions on Mars exhibit profound mean zonal equator-to-pole thermal contrasts associated with its waxing and waning seasonal polar ice caps. The imposition of this strong meridional temperature gradient supports intense eastward-traveling, synoptic-period weather systems (i.e., transient baroclinic/barotropic waves) within Mars' extratropical atmosphere. These disturbances grow, mature and decay within the east-west varying seasonal-mean middle and high-latitude westerly jet stream (i.e., the polar vortex) on the planet. Near the surface, such weather disturbances indicated distinctive, spiraling "comma"-shaped dust cloud structures of large scale, and scimitar-shaped dust fronts, indicative of processes associated with cyclo- and fronto-genesis. The weather systems are most intense during specific seasons on Mars, and in both hemispheres. The northern hemisphere (NH) disturbances appear to be significantly more vigorous than their counterparts in the southern hemisphere (SH). Further, the NH weather systems and accompanying frontal waves appear to have significant impacts on the transport of tracer fields (e.g., particularly dust and to some extent water species (vapor/ice) as well). Regarding dust, frontal waves appear to be key agents in the lifting, lofting, organization and transport of this atmospheric aerosol. A brief background and supporting observations of Mars' extratropical weather systems is presented. This is followed by various modeling studies (i.e., ranging from highly simplified, mechanistic and fully complex global circulation modeling investigations) that we are pursuing. In particular, transport of scalar quantities (e.g., tracers and high-order dynamically revealing diagnostic fields) are investigated. A discussion of outstanding issues and future modeling pursuits is offered related to Mars' extratropical traveling weather systems.

Improving the representation of clouds, radiation, and precipitation using spectral nudging in the Weather Research and Forecasting model

EPA Science Inventory

Spectral nudging – a scale-selective interior constraint technique – is commonly used in regional climate models to maintain consistency with large-scale forcing while permitting mesoscale features to develop in the downscaled simulations. Several studies have demonst...

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.

Forcing, properties, structure, and antecedent synoptic climatology of the Snake River Plain Convergence Zone of eastern Idaho: Analyses of observations and numerical simulations

NASA Astrophysics Data System (ADS)

Andretta, Thomas A.

The Snake River Plain Convergence Zone (SPCZ) is a convergent shear zone generated by synoptic-scale post cold-frontal winds in the planetary boundary layer (PBL) interacting with the complex topography of eastern Idaho. The SPCZ produces clouds and occasional precipitation over time scales of 6--12 hours in a significant area of mesoscale dimensions (10--50 x 10 3 km2). This meso-beta-scale feature also contributes to the precipitation climatology in a semi-arid plain. The SPCZ is climatologically linked to the passage of synoptic-scale cold fronts and typically occurs in the fall and winter months with the highest frequencies in October, November, and January. The Snake River Plain of eastern Idaho is covered by a dense surface mesonetwork of towers with sensible weather measurements, single Doppler weather radar, regional soundings, and operational model sources. The ability of numerical weather prediction models to simulate the SPCZ depends on several factors: the accuracy of the large scale flow upstream of the zone, terrain resolution, grid scale, boundary layer parameterizations of stability, cumulus parameterizations, and microphysics schemes. This dissertation explores several of these issues with the aforementioned observations and with the Weather Research and Forecasting-Advanced Research WRF (WRF-ARW) model simulations of selected SPCZ events. This dissertation first explains the conceptual models of the flow patterns related to the genesis of the SPCZ in light of other well-documented topographically-generated zones. The study then explores the links between the theoretical models and observations of the SPCZ in several episodes. With this foundation, the dissertation then tests several hypotheses relating to the horizontal and vertical zone structure, topographic sensitivity on the zone structure, and boundary layer evolution of the zone through the use of high resolution nested grid numerical simulations. The SPCZ consists of windward and leeward flow regimes in Idaho which form under low Froude number (stable blocked flow) in a post cold-frontal environment. The SPCZ is a weak baroclinic feature. The formation of the zone is independent of the vertical wind shear in the middle to upper troposphere. With a grid scale of 4 km, the WRF-ARW model adequately reproduces the post cold-frontal environment, windward and leeward convergence zones, relative vertical vorticity belts, and precipitation bands in several SPCZ cases. The vertical structure of the SPCZ reveals upright reflectivity towers with circulations that tilt slightly with height into the colder air aloft. Topographic sensitivity analyses of the SPCZ indicate that the terrain-driven circulations and resulting snow bands are more defined at the finer terrain scales. The ambient horizontal wind shear in the tributary valleys of the Central Mountains creates potential vorticity (PV) banners. The PV banner maintenance and strength are directly tied to the terrain resolution. An environment of convective instability sometimes occurs as a layer of air is lifted along the gentle elevation rise of the eastern Magic Valley and lower plain. An environment of inertial instability forms within the anticyclonic (negative) vorticity belts in the upper plain. Potential symmetric instability (PSI) may be released in a moist environment near the vorticity banners. The planetary boundary layer perturbed by the SPCZ inside the Snake River Plain is characterized by a deeper mixed layer with stronger vertical motions relative to a PBL in a sheltered valley outside the plain. Finally, a 10-year antecedent synoptic climatology of 78 SPCZ events reveals two pattern types: Type N (wet and warm) and Type S (dry and cold). The 40° N parallel divides these two synoptic patterns.

NSF's Perspective on Space Weather Research for Building Forecasting Capabilities

NASA Astrophysics Data System (ADS)

Bisi, M. M.; Pulkkinen, A. A.; Bisi, M. M.; Pulkkinen, A. A.; Webb, D. F.; Oughton, E. J.; Azeem, S. I.

2017-12-01

Space weather research at the National Science Foundation (NSF) is focused on scientific discovery and on deepening knowledge of the Sun-Geospace system. The process of maturation of knowledge base is a requirement for the development of improved space weather forecast models and for the accurate assessment of potential mitigation strategies. Progress in space weather forecasting requires advancing in-depth understanding of the underlying physical processes, developing better instrumentation and measurement techniques, and capturing the advancements in understanding in large-scale physics based models that span the entire chain of events from the Sun to the Earth. This presentation will provide an overview of current and planned programs pertaining to space weather research at NSF and discuss the recommendations of the Geospace Section portfolio review panel within the context of space weather forecasting capabilities.

The relationship between birch pollen, air pollution and weather types and their effect on antihistamine purchase in two Swedish cities.

PubMed

Grundström, Maria; Dahl, Åslög; Ou, Tinghai; Chen, Deliang; Pleijel, Håkan

2017-01-01

Exposure to elevated air pollution levels can aggravate pollen allergy symptoms. The aim of this study was to investigate the relationships between airborne birch ( Betula ) pollen, urban air pollutants NO 2 , O 3 and PM 10 and their effects on antihistamine demand in Gothenburg and Malmö, Sweden, 2006-2012. Further, the influence of large-scale weather pattern on pollen-/pollution-related risk, using Lamb weather types (LWTs), was analysed. Daily LWTs were obtained by comparing the atmospheric pressure over a 16-point grid system over southern Sweden (scale ~3000 km). They include two non-directional types, cyclonic (C) and anticyclonic (A) and eight directional types depending on the wind direction (N, NE, E…). Birch pollen levels were exceptionally high under LWTs E and SE in both cities. Furthermore, LWTs with dry and moderately calm meteorological character (A, NE, E, SE) were associated with strongly elevated air pollution (NO 2 and PM 10 ) in Gothenburg. For most weather situations in both cities, simultaneously high birch pollen together with high air pollution had larger over-the-counter (OTC) sales of antihistamines than situations with high birch pollen alone. LWTs NE, E, SE and S had the highest OTC sales in both cities. In Gothenburg, the city with a higher load of both birch pollen and air pollution, the higher OTC sales were especially obvious and indicate an increased effect on allergic symptoms from air pollution. Furthermore, Gothenburg LWTs A, NE, E and SE were associated with high pollen and air pollution levels and thus classified as high-risk weather types. In Malmö, corresponding high-risk LWTs were NE, E, SE and S. Furthermore, occurrence of high pollen and air pollutants as well as OTC sales correlated strongly with vapour pressure deficit and temperature in Gothenburg (much less so in Malmö). This provides evidence that the combination of meteorological properties associated with LWTs can explain high levels of birch pollen and air pollution. Our study shows that LWTs represent a useful tool for integrated daily air quality forecasting/warning.

Application of wildfire spread and behavior models to assess fire probability and severity in the Mediterranean region

NASA Astrophysics Data System (ADS)

Salis, Michele; Arca, Bachisio; Bacciu, Valentina; Spano, Donatella; Duce, Pierpaolo; Santoni, Paul; Ager, Alan; Finney, Mark

2010-05-01

Characterizing the spatial pattern of large fire occurrence and severity is an important feature of the fire management planning in the Mediterranean region. The spatial characterization of fire probabilities, fire behavior distributions and value changes are key components for quantitative risk assessment and for prioritizing fire suppression resources, fuel treatments and law enforcement. Because of the growing wildfire severity and frequency in recent years (e.g.: Portugal, 2003 and 2005; Italy and Greece, 2007 and 2009), there is an increasing demand for models and tools that can aid in wildfire prediction and prevention. Newer wildfire simulation systems offer promise in this regard, and allow for fine scale modeling of wildfire severity and probability. Several new applications has resulted from the development of a minimum travel time (MTT) fire spread algorithm (Finney, 2002), that models the fire growth searching for the minimum time for fire to travel among nodes in a 2D network. The MTT approach makes computationally feasible to simulate thousands of fires and generate burn probability and fire severity maps over large areas. The MTT algorithm is imbedded in a number of research and fire modeling applications. High performance computers are typically used for MTT simulations, although the algorithm is also implemented in the FlamMap program (www.fire.org). In this work, we described the application of the MTT algorithm to estimate spatial patterns of burn probability and to analyze wildfire severity in three fire prone areas of the Mediterranean Basin, specifically Sardinia (Italy), Sicily (Italy) and Corsica (France) islands. We assembled fuels and topographic data for the simulations in 500 x 500 m grids for the study areas. The simulations were run using 100,000 ignitions under weather conditions that replicated severe and moderate weather conditions (97th and 70th percentile, July and August weather, 1995-2007). We used both random ignition locations and ignition probability grids (1000 x 1000 m) built from historical fire data (1995-2007). The simulation outputs were then examined to understand relationships between burn probability and specific vegetation types and ignition sources. Wildfire threats to specific values of human interest were quantified to map landscape patterns of wildfire risk. The simulation outputs also allowed us to differentiate between areas of the landscape that were progenitors of fires versus "victims" of large fires. The results provided spatially explicit data on wildfire likelihood and intensity that can be used in a variety of strategic and tactical planning forums to mitigate wildfire threats to human and other values in the Mediterranean Basin.

Simulation of all-scale atmospheric dynamics on unstructured meshes

NASA Astrophysics Data System (ADS)

Smolarkiewicz, Piotr K.; Szmelter, Joanna; Xiao, Feng

2016-10-01

The advance of massively parallel computing in the nineteen nineties and beyond encouraged finer grid intervals in numerical weather-prediction models. This has improved resolution of weather systems and enhanced the accuracy of forecasts, while setting the trend for development of unified all-scale atmospheric models. This paper first outlines the historical background to a wide range of numerical methods advanced in the process. Next, the trend is illustrated with a technical review of a versatile nonoscillatory forward-in-time finite-volume (NFTFV) approach, proven effective in simulations of atmospheric flows from small-scale dynamics to global circulations and climate. The outlined approach exploits the synergy of two specific ingredients: the MPDATA methods for the simulation of fluid flows based on the sign-preserving properties of upstream differencing; and the flexible finite-volume median-dual unstructured-mesh discretisation of the spatial differential operators comprising PDEs of atmospheric dynamics. The paper consolidates the concepts leading to a family of generalised nonhydrostatic NFTFV flow solvers that include soundproof PDEs of incompressible Boussinesq, anelastic and pseudo-incompressible systems, common in large-eddy simulation of small- and meso-scale dynamics, as well as all-scale compressible Euler equations. Such a framework naturally extends predictive skills of large-eddy simulation to the global atmosphere, providing a bottom-up alternative to the reverse approach pursued in the weather-prediction models. Theoretical considerations are substantiated by calculations attesting to the versatility and efficacy of the NFTFV approach. Some prospective developments are also discussed.

Optimizing Fukushima Emissions Through Pattern Matching and Genetic Algorithms

NASA Astrophysics Data System (ADS)

Lucas, D. D.; Simpson, M. D.; Philip, C. S.; Baskett, R.

2017-12-01

Hazardous conditions during the Fukushima Daiichi nuclear power plant (NPP) accident hindered direct observations of the emissions of radioactive materials into the atmosphere. A wide range of emissions are estimated from bottom-up studies using reactor inventories and top-down approaches based on inverse modeling. We present a new inverse modeling estimate of cesium-137 emitted from the Fukushima NPP. Our estimate considers weather uncertainty through a large ensemble of Weather Research and Forecasting model simulations and uses the FLEXPART atmospheric dispersion model to transport and deposit cesium. The simulations are constrained by observations of the spatial distribution of cumulative cesium deposited on the surface of Japan through April 2, 2012. Multiple spatial metrics are used to quantify differences between observed and simulated deposition patterns. In order to match the observed pattern, we use a multi-objective genetic algorithm to optimize the time-varying emissions. We find that large differences with published bottom-up estimates are required to explain the observations. This work was performed under the auspices of the U.S. Department of Energy by Lawrence Livermore National Laboratory under Contract DE-AC52-07NA27344.

Distribution of lithium in agricultural and grazing land soils at European continental scale (GEMAS project)

NASA Astrophysics Data System (ADS)

Negrel, Philippe; Reimann, Clemens; Ladenberger, Anna; Birke, Manfred

2017-04-01

The environmental chemistry of Li has received attention because Li has been shown to have numerous and important implications for human health and agriculture and the stable isotope composition of lithium is a powerful geochemical tool that provides quantitative information about Earth processes such as sediment recycling, global chemical weathering and its role in the carbon cycle, hydrothermal alteration, and groundwater evolution. However, the role of bedrock sources, weathering and climate changes in the repartition of Li at the continental scale has been scarcely investigated. Agricultural soil (Ap-horizon, 0-20 cm) and grazing land soil (Gr-horizon, 0-10 cm) samples were collected from a large part of Europe (33 countries, 5.6 million km2) as a part of the GEMAS (GEochemical Mapping of Agricultural and grazing land Soil) soil mapping project. GEMAS soil data have been used to provide a general view of element mobility and source rocks at the continental scale, either by reference to average crustal abundances or to normalized patterns of element mobility during weathering processes. The survey area includes a diverse group of soil parent materials with varying geological history, a wide range of climate zones and landscapes. The concentrations of Li in European soil were determined by ICP-MS after a hot aqua regia extraction, and their spatial distribution patterns generated by means of a GIS software. Due to the partial nature of the aqua regia extraction, the mean concentration of Li in the European agricultural soil (ca 11.4 mg/kg in Ap and Gr soils) is about four times lower than in the Earth's upper continental crust (UCC = 41 mg/kg). The combined plot histogram - density trace one- dimensional scattergram - boxplot of the aqua regia data displays the univariate data distribution of Li. The one-dimensional scattergram and boxplot highlight the existence of many outliers at the lower end of the Li distribution and very few at the upper end. Though the density trace, histogram and boxplot suggest a slight skew, the data distributions are still rather symmetrical in the log-scale. The median values of the Ap and Gr samples do overlap, demonstrating they are not statistically different at the 5 % significance level. The maps of Li in the aqua regia extraction show a distinct difference between northern Europe with predominantly low concentrations (median 6.4 mg/kg) and southern Europe with significantly higher values (median 15 mg/kg). The maximum extent of the last glaciation is visible as a discrete concentration break on the maps. The principal Li anomalies occur spatially associated with the granitic rocks and Li-pegmatites and their weathering products throughout Europe, e.g. in central Sweden (Central Scandinavian Clay Belt) and in the western part of the Alpine Region (higher Li concentrations). Even the new Li-deposit near Wolfsberg, Austria is marked by a clear anomaly. In southern Europe, high Li values occurring over limestone areas can be attributed to secondary Li enrichment during weathering controlled by climate (temperature and precipitation).

Spatial and temporal variations of Rb/Sr ratios of the bulk surface sediments in Lake Qinghai

PubMed Central

2010-01-01

The Rb/Sr ratios of lake sediments have been suggested as indicators of weathering intensity by increasing work. However, the geochemistry of Rb/Sr ratios of lake sediments is variable between different lakes. In this study, we investigated the spatial and temporal patterns of Rb/Sr ratios, as well as those of other major elements in surface sediments of Lake Qinghai. We find that the spatial pattern of Rb/Sr ratios of the bulk sediments correlates well with that of the mass accumulation rate, and those of the terrigenous fractions, e.g., SiO2, Ti, and Fe. The temporal variations of Rb/Sr ratios also synchronize with those of SiO2, Ti, and Fe of each individual core. These suggest that Rb/Sr ratios of the surface sediments are closely related to terrigenous input from the catchment. Two out of eight cores show similar trends between Rb/Sr ratios and precipitation indices on decadal scales; however, the other cores do not show such relationship. The result of this study suggests that physical weathering and chemical weathering in Lake Qinghai catchment have opposite influence on Rb/Sr ratios of the bulk sediments, and they compete in dominating the Rb/Sr ratios of lake sediments on different spatial and temporal scales. Therefore, it is necessary to study the geochemistry of Rb/Sr ratio of lake sediments (especially that on short term timescales) particularly before it is used as an indicator of weathering intensity of the catchment. PMID:20615264

Identifying and Analyzing Uncertainty Structures in the TRMM Microwave Imager Precipitation Product over Tropical Ocean Basins

NASA Technical Reports Server (NTRS)

Liu, Jianbo; Kummerow, Christian D.; Elsaesser, Gregory S.

2016-01-01

Despite continuous improvements in microwave sensors and retrieval algorithms, our understanding of precipitation uncertainty is quite limited, due primarily to inconsistent findings in studies that compare satellite estimates to in situ observations over different parts of the world. This study seeks to characterize the temporal and spatial properties of uncertainty in the Tropical Rainfall Measuring Mission Microwave Imager surface rainfall product over tropical ocean basins. Two uncertainty analysis frameworks are introduced to qualitatively evaluate the properties of uncertainty under a hierarchy of spatiotemporal data resolutions. The first framework (i.e. 'climate method') demonstrates that, apart from random errors and regionally dependent biases, a large component of the overall precipitation uncertainty is manifested in cyclical patterns that are closely related to large-scale atmospheric modes of variability. By estimating the magnitudes of major uncertainty sources independently, the climate method is able to explain 45-88% of the monthly uncertainty variability. The percentage is largely resolution dependent (with the lowest percentage explained associated with a 1 deg x 1 deg spatial/1 month temporal resolution, and highest associated with a 3 deg x 3 deg spatial/3 month temporal resolution). The second framework (i.e. 'weather method') explains regional mean precipitation uncertainty as a summation of uncertainties associated with individual precipitation systems. By further assuming that self-similar recurring precipitation systems yield qualitatively comparable precipitation uncertainties, the weather method can consistently resolve about 50 % of the daily uncertainty variability, with only limited dependence on the regions of interest.

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).

US regional tornado outbreaks and their links to spring ENSO phases and North Atlantic SST variability

NASA Astrophysics Data System (ADS)

Lee, Sang-Ki; Wittenberg, Andrew T.; Enfield, David B.; Weaver, Scott J.; Wang, Chunzai; Atlas, Robert

2016-04-01

Recent violent and widespread tornado outbreaks in the US, such as occurred in the spring of 2011, have caused devastating societal impact with significant loss of life and property. At present, our capacity to predict US tornado and other severe weather risk does not extend beyond seven days. In an effort to advance our capability for developing a skillful long-range outlook for US tornado outbreaks, here we investigate the spring probability patterns of US regional tornado outbreaks during 1950-2014. We show that the four dominant springtime El Niño-Southern Oscillation (ENSO) phases (persistent versus early-terminating El Niño and resurgent versus transitioning La Niña) and the North Atlantic sea surface temperature tripole variability are linked to distinct and significant US regional patterns of outbreak probability. These changes in the probability of outbreaks are shown to be largely consistent with remotely forced regional changes in the large-scale atmospheric processes conducive to tornado outbreaks. An implication of these findings is that the springtime ENSO phases and the North Atlantic SST tripole variability may provide seasonal predictability of US regional tornado outbreaks.

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.

Rapid Conversion from Carbohydrates to Large-Scale Carbon Quantum Dots for All-Weather Solar Cells.

PubMed

Tang, Qunwei; Zhu, Wanlu; He, Benlin; Yang, Peizhi

2017-02-28

A great challenge for state-of-the-art solar cells is to generate electricity in all weather. We present here the rapid conversion of carbon quantum dots (CQDs) from carbohydrates (including glucose, maltol, sucrose) for an all-weather solar cell, which comprises a CQD-sensitized mesoscopic titanium dioxide/long-persistence phosphor (m-TiO 2 /LPP) photoanode, a I - /I 3 - redox electrolyte, and a platinum counter electrode. In virtue of the light storing and luminescent behaviors of LPP phosphors, the generated all-weather solar cells can not only convert sunlight into electricity on sunny days but persistently realize electricity output in all dark-light conditions. The maximized photoelectric conversion efficiency is as high as 15.1% for so-called all-weather CQD solar cells in dark conditions.

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.

Synoptic climatological analysis of persistent cold air pools over the Carpathian Basin

NASA Astrophysics Data System (ADS)

Szabóné André, Karolina; Bartholy, Judit; Pongrácz, Rita

2016-04-01

A persistent cold air pool (PCAP) is a winter-time, anticyclone-related weather event over a relatively large basin. During this time the air is colder near the surface than aloft. This inversion near the surface can last even for weeks. As the cold air cools down, relative humidity increases and fog forms. The entire life cycle of a PCAP depends on the large scale circulation pattern. PCAP usually appears when an anticyclone builds up after a cold front passed over the examined basin, and it is usually destructed by a coming strong cold front of another midlatitude cyclone. Moreover, the intensity of the anticyclone affects the intensity of the PCAP. PCAP may result in different hazards for the population: (1) Temperature inversion in the surface layers together with weak wind may lead to severe air pollution causing health problems for many people, especially, elderly and children. (2) The fog and/or smog during chilly weather conditions often results in freezing rain. Both fog and freezing rain can distract transportation and electricity supply. Unfortunately, the numerical weather prediction models have difficulties to predict PCAP formation and destruction. One of the reasons is that PCAP is not defined objectively with a simple formula, which could be easily applied to the numerical output data. However, according to some recommendations from the synoptic literature, the shallow convective potential energy (SCPE) can be used to mathematically describe PCAP. In this study, we used the ERA-Interim reanalysis datasets to examine this very specific weather event (i.e., PCAP) over the Carpathian Basin. The connection between the mean sea level pressure and some PCAP measures (e.g., SCPE, energy deficit, etc.) is evaluated. For instance, we used logistic regression to identify PCAP periods over the Carpathian Basin. Then, further statistical analysis includes the evaluation of the length and intensity of these PCAP periods.

Nowcasting for a high-resolution weather radar network

NASA Astrophysics Data System (ADS)

Ruzanski, Evan

Short-term prediction (nowcasting) of high-impact weather events can lead to significant improvement in warnings and advisories and is of great practical importance. Nowcasting using weather radar reflectivity data has been shown to be particularly useful. The Collaborative Adaptive Sensing of the Atmosphere (CASA) radar network provides high-resolution reflectivity data amenable to producing valuable nowcasts. The high-resolution nature of CASA data requires the use of an efficient nowcasting approach, which necessitated the development of the Dynamic Adaptive Radar Tracking of Storms (DARTS) and sinc kernel-based advection nowcasting methodology. This methodology was implemented operationally in the CASA Distributed Collaborative Adaptive Sensing (DCAS) system in a robust and efficient manner necessitated by the high-resolution nature of CASA data and distributed nature of the environment in which the nowcasting system operates. Nowcasts up to 10 min to support emergency manager decision-making and 1--5 min to steer the CASA radar nodes to better observe the advecting storm patterns for forecasters and researchers are currently provided by this system. Results of nowcasting performance during the 2009 CASA IP experiment are presented. Additionally, currently state-of-the-art scale-based filtering methods were adapted and evaluated for use in the CASA DCAS to provide a scale-based analysis of nowcasting. DARTS was also incorporated in the Weather Support to Deicing Decision Making system to provide more accurate and efficient snow water equivalent nowcasts for aircraft deicing decision support relative to the radar-based nowcasting method currently used in the operational system. Results of an evaluation using data collected from 2007--2008 by the Weather Service Radar-1988 Doppler (WSR-88D) located near Denver, Colorado, and the National Center for Atmospheric Research Marshall Test Site near Boulder, Colorado, are presented. DARTS was also used to study the short-term predictability of precipitation patterns depicted by high-resolution reflectivity data observed at microalpha (0.2--2 km) to mesobeta (20--200 km) scales by the CASA radar network. Additionally, DARTS was used to investigate the performance of nowcasting rainfall fields derived from specific differential phase estimates, which have been shown to provide more accurate and robust rainfall estimates compared to those made from radar reflectivity data.

Assessing Weather Curiosity in University Students

NASA Astrophysics Data System (ADS)

Stewart, A. E.

2017-12-01

This research focuses upon measuring an individual's level of trait curiosity about the weather using the Weather Curiosity Scale (WCS). The measure consists of 15 self-report items that describe weather preferences and/or behaviors that people may perform more or less frequently. The author reports on two initial studies of the WCS that have used the responses of 710 undergraduate students from a large university in the southeastern United States. In the first study, factor analysis of the 15 items indicated that the measure was unidimensional - suggesting that its items singularly assessed weather curiosity. The WCS also was internally consistent as evidenced by an acceptable Cronbach's alpha, a = .81). The second study sought to identify other personality variables that may relate with the WCS scores and thus illuminate the nature of weather curiosity. Several clusters of personality variables appear to underlie the curiosity levels people exhibited, the first of which related to perceptual curiosity (r = .59). Being curious about sights, sounds, smells, and textures generally related somewhat to curiosity about weather. Two measures of trait sensitivity to environmental stimulation, the Highly Sensitive Person Scale (r = .47) and the Orientation Sensitivity Scale of the Adult Temperament Questionnaire (r = .43), also predicted weather curiosity levels. Finally, possessing extraverted personality traits (r = .34) and an intense style of experiencing one's emotions (r = .33) related to weather curiosity. How can this measure be used in K-12 or post-secondary settings to further climate literacy? First, the WCS can identify students with natural curiosities about weather and climate so these students may be given more challenging instruction that will leverage their natural interests. Second, high-WCS students may function as weather and climate ambassadors during inquiry-based learning activities and thus help other students who are not as oriented to the atmosphere. Finally the results of this study reveal some of the underlying psychological mechanisms that are associated with weather curiosity. Building greater perceptual curiosity or increasing perceptual sensitivity and discrimination skills may make it possible to increase students' levels of weather curiosity.

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.

Diagnosing the Atmospheric/Oceanic Phenomena Associated with the Onset, Demise and Mid-Summer Drought of the Rainy Season in Mesoamerica

NASA Astrophysics Data System (ADS)

Groenen, D.; Bourassa, M. A.

2017-12-01

The rainfall in Mesoamerica (Mexico and Central America) has influences from two bodies of water, interesting topography, and complex wind patterns, which complicates weather forecasting. Knowing the approximate onset and demise of the rainy season is critical for the optimal growth and development of key crops in this region such as coffee, bananas, rice, and maize. This study compares three methods to calculate the onset/demise dates of the individual years' rainy season, using area-averaged rainfall data (7-28 °N/77-109 °W) from two datasets. After these onset/demise dates are obtained using rainfall data, the atmospheric and oceanic phenomena associated with the timing is analyzed using MERRA-2 reanalysis data. The objective is to link the large-scale phenomena to the individual years' onset/demise dates, as well as link the weather phenomena to the interannual variability of the onset/demise dates. In addition, the broad scale rainy season will be connected with regional onset/demise dates on the scale of 400km. Linking the broad scale rainfall regimes to the regional regimes will allow a more cohesive view of the dynamics related to rainfall variability in the Mesoamerican region. A smoothing method will be used to analyze the timing and intensity of the mid-summer drought (MSD), a minimum in rainfall typically occurring during July and August. The goal of this research is to link the physical and dynamical mechanisms that cause the Mesoamerican rainy season and mid-summer drought (MSD) in order to better understand the predictability of Mesoamerican rainfall and ensure the health and safety of key crops.

Global views of energetic particle precipitation and their sources: Combining large-scale models with observations during the 21-22 January 2005 magnetic storm (Invited)

NASA Astrophysics Data System (ADS)

Kozyra, J. U.; Brandt, P. C.; Cattell, C. A.; Clilverd, M.; de Zeeuw, D.; Evans, D. S.; Fang, X.; Frey, H. U.; Kavanagh, A. J.; Liemohn, M. W.; Lu, G.; Mende, S. B.; Paxton, L. J.; Ridley, A. J.; Rodger, C. J.; Soraas, F.

2010-12-01

Energetic ions and electrons that precipitate into the upper atmosphere from sources throughout geospace carry the influences of space weather disturbances deeper into the atmosphere, possibly contributing to climate variability. The three-dimensional atmospheric effects of these precipitating particles are a function of the energy and species of the particles, lifetimes of reactive species generated during collisions in the atmosphere, the nature of the driving space weather disturbance, and the large-scale transport properties (meteorology) of the atmosphere in the region of impact. Unraveling the features of system-level coupling between solar magnetic variability, space weather and stratospheric dynamics requires a global view of the precipitation, along with its temporal and spatial variation. However, observations of particle precipitation at the system level are sparse and incomplete requiring they be combined with other observations and with large-scale models to provide the global context that is needed to accelerate progress. We compare satellite and ground-based observations of geospace conditions and energetic precipitation (at ring current, radiation belt and auroral energies) to a simulation of the geospace environment during 21-22 January 2005 by the BATS-R-US MHD model coupled with a self-consistent ring current solution. The aim is to explore the extent to which regions of particle precipitation track global magnetic field distortions and ways in which global models enhance our understanding of linkages between solar wind drivers and evolution of energetic particle precipitation.

A Geosynchronous Lidar System for Atmospheric Winds and Moisture Measurements

NASA Technical Reports Server (NTRS)

Emmitt, G. D.

2001-01-01

An observing system comprised of two lidars in geosychronous orbit would enable the synoptic and meso-scale measurement of atmospheric winds and moisture both of which are key first-order variables of the Earth's weather equation. Simultaneous measurement of these parameters at fast revisit rates promises large advancements in our weather prediction skills. Such capabilities would be unprecedented and a) yield greatly improved and finer resolution initial conditions for models, b) make existing costly and cumbersome measurement approaches obsolete, and c) obviate the use of numerical techniques needed to correct data obtained using present observing systems. Additionally, simultaneous synoptic wind and moisture observations would lead to improvements in model parameterizations, and in our knowledge of small-scale weather processes. Technology and science data product assessments are ongoing. Results will be presented during the conference.

Attic or Roof? An Evaluation of Two Advanced Weatherization Packages

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

Neuhauser, Ken

2012-06-01

This project examines implementation of advanced retrofit measures in the context of a large-scale weatherization program and the archetypal Chicago brick bungalow. One strategy applies best practice air sealing methods and a standard insulation method to the attic floor. The other strategy creates an unvented roof assembly using materials and methods typically available to weatherization contractors. Through implementations of the retrofit strategies in a total of eight (8) test homes, the research found that the two different strategies achieve similar reductions in air leakage measurement (55%) and predicted energy performance (18%) relative to the pre-retrofit conditions.

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.

Relationships between CO 2, thermodynamic limits on silicate weathering, and the strength of the silicate weathering feedback

DOE PAGES

Winnick, Matthew J.; Maher, Kate

2018-01-27

Recent studies have suggested that thermodynamic limitations on chemical weathering rates exert a first-order control on riverine solute fluxes and by extension, global chemical weathering rates. As such, these limitations may play a prominent role in the regulation of carbon dioxide levels (pCO 2) over geologic timescales by constraining the maximum global weathering flux. In this study, we develop a theoretical scaling relationship between equilibrium solute concentrations and pCO 2 based on equilibrium constants and reaction stoichiometry relating primary mineral dissolution and secondary mineral precipitation. Here, we test this theoretical scaling relationship against reactive transport simulations of chemical weathering profilesmore » under open-and closed-system conditions, representing partially and fully water-saturated regolith, respectively. Under open-system conditions, equilibrium bicarbonate concentrations vary as a power-law function of pCO 2(y =kx n)where nis dependent on reaction stoichiometry and kis dependent on both reaction stoichiometry and the equilibrium constant. Under closed-system conditions, bicarbonate concentrations vary linearly with pCO 2 at low values and approach open-system scaling at high pCO 2. To describe the potential role of thermodynamic limitations in the global silicate weathering feedback, we develop a new mathematical framework to assess weathering feedback strength in terms of both (1) steady-state atmospheric pCO 2 concentrations, and (2) susceptibility to secular changes in degassing rates and transient carbon cycle perturbations, which we term 1st and 2nd order feedback strength, respectively. Finally, we discuss the implications of these results for the effects of vascular land plant evolution on feedback strength, the potential role of vegetation in controlling modern solute fluxes, and the application of these frameworks to a more complete functional description of the silicate weathering feedback. Most notably, the dependence of equilibrium solute concentrations on pCO 2 may represent a direct weathering feedback largely independent of climate and modulated by belowground organic carbon respiration.« less

Relationships between CO 2, thermodynamic limits on silicate weathering, and the strength of the silicate weathering feedback

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

Winnick, Matthew J.; Maher, Kate

Recent studies have suggested that thermodynamic limitations on chemical weathering rates exert a first-order control on riverine solute fluxes and by extension, global chemical weathering rates. As such, these limitations may play a prominent role in the regulation of carbon dioxide levels (pCO 2) over geologic timescales by constraining the maximum global weathering flux. In this study, we develop a theoretical scaling relationship between equilibrium solute concentrations and pCO 2 based on equilibrium constants and reaction stoichiometry relating primary mineral dissolution and secondary mineral precipitation. Here, we test this theoretical scaling relationship against reactive transport simulations of chemical weathering profilesmore » under open-and closed-system conditions, representing partially and fully water-saturated regolith, respectively. Under open-system conditions, equilibrium bicarbonate concentrations vary as a power-law function of pCO 2(y =kx n)where nis dependent on reaction stoichiometry and kis dependent on both reaction stoichiometry and the equilibrium constant. Under closed-system conditions, bicarbonate concentrations vary linearly with pCO 2 at low values and approach open-system scaling at high pCO 2. To describe the potential role of thermodynamic limitations in the global silicate weathering feedback, we develop a new mathematical framework to assess weathering feedback strength in terms of both (1) steady-state atmospheric pCO 2 concentrations, and (2) susceptibility to secular changes in degassing rates and transient carbon cycle perturbations, which we term 1st and 2nd order feedback strength, respectively. Finally, we discuss the implications of these results for the effects of vascular land plant evolution on feedback strength, the potential role of vegetation in controlling modern solute fluxes, and the application of these frameworks to a more complete functional description of the silicate weathering feedback. Most notably, the dependence of equilibrium solute concentrations on pCO 2 may represent a direct weathering feedback largely independent of climate and modulated by belowground organic carbon respiration.« less

Relationships between CO2, thermodynamic limits on silicate weathering, and the strength of the silicate weathering feedback

NASA Astrophysics Data System (ADS)

Winnick, Matthew J.; Maher, Kate

2018-03-01

Recent studies have suggested that thermodynamic limitations on chemical weathering rates exert a first-order control on riverine solute fluxes and by extension, global chemical weathering rates. As such, these limitations may play a prominent role in the regulation of carbon dioxide levels (pCO2) over geologic timescales by constraining the maximum global weathering flux. In this study, we develop a theoretical scaling relationship between equilibrium solute concentrations and pCO2 based on equilibrium constants and reaction stoichiometry relating primary mineral dissolution and secondary mineral precipitation. We test this theoretical scaling relationship against reactive transport simulations of chemical weathering profiles under open- and closed-system conditions, representing partially and fully water-saturated regolith, respectively. Under open-system conditions, equilibrium bicarbonate concentrations vary as a power-law function of pCO2 (y = kxn) where n is dependent on reaction stoichiometry and k is dependent on both reaction stoichiometry and the equilibrium constant. Under closed-system conditions, bicarbonate concentrations vary linearly with pCO2 at low values and approach open-system scaling at high pCO2. To describe the potential role of thermodynamic limitations in the global silicate weathering feedback, we develop a new mathematical framework to assess weathering feedback strength in terms of both (1) steady-state atmospheric pCO2 concentrations, and (2) susceptibility to secular changes in degassing rates and transient carbon cycle perturbations, which we term 1st and 2nd order feedback strength, respectively. Finally, we discuss the implications of these results for the effects of vascular land plant evolution on feedback strength, the potential role of vegetation in controlling modern solute fluxes, and the application of these frameworks to a more complete functional description of the silicate weathering feedback. Most notably, the dependence of equilibrium solute concentrations on pCO2 may represent a direct weathering feedback largely independent of climate and modulated by belowground organic carbon respiration.

Spatial synchrony of local populations has increased in association with the recent Northern Hemisphere climate trend.

PubMed

Post, Eric; Forchhammer, Mads C

2004-06-22

According to ecological theory, populations whose dynamics are entrained by environmental correlation face increased extinction risk as environmental conditions become more synchronized spatially. This prediction is highly relevant to the study of ecological consequences of climate change. Recent empirical studies have indicated, for example, that large-scale climate synchronizes trophic interactions and population dynamics over broad spatial scales in freshwater and terrestrial systems. Here, we present an analysis of century-scale, spatially replicated data on local weather and the population dynamics of caribou in Greenland. Our results indicate that spatial autocorrelation in local weather has increased with large-scale climatic warming. This increase in spatial synchrony of environmental conditions has been matched, in turn, by an increase in the spatial synchrony of local caribou populations toward the end of the 20th century. Our results indicate that spatial synchrony in environmental conditions and the populations influenced by them are highly variable through time and can increase with climatic warming. We suggest that if future warming can increase population synchrony, it may also increase extinction risk.

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.

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.

Comparison of Grid Nudging and Spectral Nudging Techniques for Dynamical Climate Downscaling within the WRF Model

NASA Astrophysics Data System (ADS)

Fan, X.; Chen, L.; Ma, Z.

2010-12-01

Climate downscaling has been an active research and application area in the past several decades focusing on regional climate studies. Dynamical downscaling, in addition to statistical methods, has been widely used in downscaling as the advanced modern numerical weather and regional climate models emerge. The utilization of numerical models enables that a full set of climate variables are generated in the process of downscaling, which are dynamically consistent due to the constraints of physical laws. While we are generating high resolution regional climate, the large scale climate patterns should be retained. To serve this purpose, nudging techniques, including grid analysis nudging and spectral nudging, have been used in different models. There are studies demonstrating the benefit and advantages of each nudging technique; however, the results are sensitive to many factors such as nudging coefficients and the amount of information to nudge to, and thus the conclusions are controversy. While in a companion work of developing approaches for quantitative assessment of the downscaled climate, in this study, the two nudging techniques are under extensive experiments in the Weather Research and Forecasting (WRF) model. Using the same model provides fair comparability. Applying the quantitative assessments provides objectiveness of comparison. Three types of downscaling experiments were performed for one month of choice. The first type is serving as a base whereas the large scale information is communicated through lateral boundary conditions only; the second is using the grid analysis nudging; and the third is using spectral nudging. Emphases are given to the experiments of different nudging coefficients and nudging to different variables in the grid analysis nudging; while in spectral nudging, we focus on testing the nudging coefficients, different wave numbers on different model levels to nudge.

Distant Influence of Kuroshio Eddies on North Pacific Weather Patterns?

PubMed Central

Ma, Xiaohui; Chang, Ping; Saravanan, R.; Montuoro, Raffaele; Hsieh, Jen-Shan; Wu, Dexing; Lin, Xiaopei; Wu, Lixin; Jing, Zhao

2015-01-01

High-resolution satellite measurements of surface winds and sea-surface temperature (SST) reveal strong coupling between meso-scale ocean eddies and near-surface atmospheric flow over eddy-rich oceanic regions, such as the Kuroshio and Gulf Stream, highlighting the importance of meso-scale oceanic features in forcing the atmospheric planetary boundary layer (PBL). Here, we present high-resolution regional climate modeling results, supported by observational analyses, demonstrating that meso-scale SST variability, largely confined in the Kuroshio-Oyashio confluence region (KOCR), can further exert a significant distant influence on winter rainfall variability along the U.S. Northern Pacific coast. The presence of meso-scale SST anomalies enhances the diabatic conversion of latent heat energy to transient eddy energy, intensifying winter cyclogenesis via moist baroclinic instability, which in turn leads to an equivalent barotropic downstream anticyclone anomaly with reduced rainfall. The finding points to the potential of improving forecasts of extratropical winter cyclones and storm systems and projections of their response to future climate change, which are known to have major social and economic impacts, by improving the representation of ocean eddy–atmosphere interaction in forecast and climate models. PMID:26635077

Multiscale Geophysical Characterization of Weathering Fronts Along a Climate and Vegetation Gradient in Chile

NASA Astrophysics Data System (ADS)

Dal Bo, I.; Klotzsche, A.; Schaller, M.; Ehlers, T. A.; Vereecken, H.; Van Der Kruk, J.

2017-12-01

Understanding how weathering processes act is non-trivial. Direct methods are spatially restricted, time consuming, and expensive. Here, we show how to upscale and extend the point-scale layering information from dug pits deploying a multi-scale geophysical approach. Many studies have recently shown the potential of geophysics in bridging the gap between scales, although limited to specific environments. We applied Electromagnetic Induction (EMI), Ground Penetrating Radar (GPR), and Electrical Resistivity Tomography (ERT) in four study areas separated by 1600 km in the Chilean Coastal Cordillera, and ranging from the arid Atacama Desert in the north and temperate forests in the south. The main goals were to understand how the soil profile and the weathering front vary: 1) from north to south along these gradients, 2) in north- and south-facing hillslopes, and 3) within a single hillslope. We measured at the large-scale (EMI), at the profile scale (EMI, ERT, and GPR), and at the point-scale (GPR). The total length of the EMI, GPR and ERT measurements was 28.95 km, 3.67 km, and 0.27 km. GPR wide angle reflection and refraction measurements were the link between ground-truth data and geophysics. The low electrical conductivity (EC) regime limited the applicability of the EMI and ERT. However, still relative patterns of apparent electrical conductivity (ECa) from EMI could be used. Generally, ECa increased moving uphill and from north to south. Due to the low EC values in the study areas, GPR could image several reflections up to 8 m depth partially confirmed by the pit layering. Thicker layers on GPR profiles were present going from north to south and in the bottom-mid part of the hillslopes, as confirmed by ground-truth data. The main recognizable feature in the GPR profiles was the transition between B and C horizon. Here, hyperbolic-shape signatures were observed that probably were related to the presence of heterogeneities. The soil pits showed deeper layers in more vegetated south-facing hillslopes, which could be correlated with increased signal penetration and reflection depths in the GPR profiles. Soil depths and their interaction with biota in soil-mantled landscapes will be better characterized by combining geophysics with more environmental parameters within the interdisciplinary EarthShape project.

Cache Coherence Protocols for Large-Scale Multiprocessors

DTIC Science & Technology

1990-09-01

and is compared with the other protocols for large-scale machines. In later analysis, this coherence method is designated by the acronym OCPD , which...private read misses 2 6 6 ( OCPD ) private write misses 2 6 6 Table 4.2: Transaction Types and Costs. the performance of the memory system. These...methodologies. Figure 4-2 shows the processor utiliza- tions of the Weather program, with special code in the dyn-nic post-mortem sched- 94 OCPD DlrINB

Effect of weather on temporal pain patterns in patients with temporomandibular disorders and migraine.

PubMed

Cioffi, I; Farella, M; Chiodini, P; Ammendola, L; Capuozzo, R; Klain, C; Vollaro, S; Michelotti, A

2017-05-01

Patients with masticatory muscle pain and migraine typically report that the intensity of pain fluctuates over time and is affected by weather changes. Weather variables, such as ambient temperature and humidity, may vary significantly depending on whether the individual is outdoor or indoor. It is, therefore, important to assess these variables at the individual level using portable monitors, during everyday life. This study aimed to determine and compare the temporal patterns of pain in individuals affected with facial and head pain and to investigate its relation with weather changes. Eleven patients (27·3 ± 7·4 years) with chronic masticatory muscle pain (MP) and twenty (33·1 ± 8·7 years) with migraine headache (MH) were asked to report their current pain level on a visual analogue scale (VAS) every hour over fourteen consecutive days. The VAS scores were collected using portable data-loggers, which were also used to record temperature, atmospheric pressure and relative humidity. VAS scores varied markedly over time in both groups. Pain VAS scores fluctuate less in the MP group than in the MH group, but their mean, minimum and maximum values were higher than those of migraine patients (all P < 0·05). Pain scores <2 cm were more common in the MH than in the MP group (P < 0·001). Perceived intensity of pain was negatively associated with atmospheric pressure in the MP group and positively associated with temperature and atmospheric in the MH group. Our results reveal that patients with masticatory muscle pain and patients with migraine present typical temporal pain patterns that are influenced in a different way by weather changes. © 2017 John Wiley & Sons Ltd.

An analysis of the synoptic and climatological applicability of circulation type classifications for Ireland

NASA Astrophysics Data System (ADS)

Broderick, Ciaran; Fealy, Rowan

2013-04-01

Circulation type classifications (CTCs) compiled as part of the COST733 Action, entitled 'Harmonisation and Application of Weather Type Classifications for European Regions', are examined for their synoptic and climatological applicability to Ireland based on their ability to characterise surface temperature and precipitation. In all 16 different objective classification schemes, representative of four different methodological approaches to circulation typing (optimization algorithms, threshold based methods, eigenvector techniques and leader algorithms) are considered. Several statistical metrics which variously quantify the ability of CTCs to discretize daily data into well-defined homogeneous groups are used to evaluate and compare different approaches to synoptic typing. The records from 14 meteorological stations located across the island of Ireland are used in the study. The results indicate that while it was not possible to identify a single optimum classification or approach to circulation typing - conditional on the location and surface variables considered - a number of general assertions regarding the performance of different schemes can be made. The findings for surface temperature indicate that that those classifications based on predefined thresholds (e.g. Litynski, GrossWetterTypes and original Lamb Weather Type) perform well, as do the Kruizinga and Lund classification schemes. Similarly for precipitation predefined type classifications return high skill scores, as do those classifications derived using some optimization procedure (e.g. SANDRA, Self Organizing Maps and K-Means clustering). For both temperature and precipitation the results generally indicate that the classifications perform best for the winter season - reflecting the closer coupling between large-scale circulation and surface conditions during this period. In contrast to the findings for temperature, spatial patterns in the performance of classifications were more evident for precipitation. In the case of this variable those more westerly synoptic stations open to zonal airflow and less influenced by regional scale forcings generally exhibited a stronger link with large-scale circulation.

Field significance of performance measures in the context of regional climate model evaluation. Part 2: precipitation

NASA Astrophysics Data System (ADS)

Ivanov, Martin; Warrach-Sagi, Kirsten; Wulfmeyer, Volker

2018-04-01

A new approach for rigorous spatial analysis of the downscaling performance of regional climate model (RCM) simulations is introduced. It is based on a multiple comparison of the local tests at the grid cells and is also known as `field' or `global' significance. The block length for the local resampling tests is precisely determined to adequately account for the time series structure. New performance measures for estimating the added value of downscaled data relative to the large-scale forcing fields are developed. The methodology is exemplarily applied to a standard EURO-CORDEX hindcast simulation with the Weather Research and Forecasting (WRF) model coupled with the land surface model NOAH at 0.11 ∘ grid resolution. Daily precipitation climatology for the 1990-2009 period is analysed for Germany for winter and summer in comparison with high-resolution gridded observations from the German Weather Service. The field significance test controls the proportion of falsely rejected local tests in a meaningful way and is robust to spatial dependence. Hence, the spatial patterns of the statistically significant local tests are also meaningful. We interpret them from a process-oriented perspective. While the downscaled precipitation distributions are statistically indistinguishable from the observed ones in most regions in summer, the biases of some distribution characteristics are significant over large areas in winter. WRF-NOAH generates appropriate stationary fine-scale climate features in the daily precipitation field over regions of complex topography in both seasons and appropriate transient fine-scale features almost everywhere in summer. As the added value of global climate model (GCM)-driven simulations cannot be smaller than this perfect-boundary estimate, this work demonstrates in a rigorous manner the clear additional value of dynamical downscaling over global climate simulations. The evaluation methodology has a broad spectrum of applicability as it is distribution-free, robust to spatial dependence, and accounts for time series structure.

Extreme weather: Subtropical floods and tropical cyclones

NASA Astrophysics Data System (ADS)

Shaevitz, Daniel A.

Extreme weather events have a large effect on society. As such, it is important to understand these events and to project how they may change in a future, warmer climate. The aim of this thesis is to develop a deeper understanding of two types of extreme weather events: subtropical floods and tropical cyclones (TCs). In the subtropics, the latitude is high enough that quasi-geostrophic dynamics are at least qualitatively relevant, while low enough that moisture may be abundant and convection strong. Extratropical extreme precipitation events are usually associated with large-scale flow disturbances, strong ascent, and large latent heat release. In the first part of this thesis, I examine the possible triggering of convection by the large-scale dynamics and investigate the coupling between the two. Specifically two examples of extreme precipitation events in the subtropics are analyzed, the 2010 and 2014 floods of India and Pakistan and the 2015 flood of Texas and Oklahoma. I invert the quasi-geostrophic omega equation to decompose the large-scale vertical motion profile to components due to synoptic forcing and diabatic heating. Additionally, I present model results from within the Column Quasi-Geostrophic framework. A single column model and cloud-revolving model are forced with the large-scale forcings (other than large-scale vertical motion) computed from the quasi-geostrophic omega equation with input data from a reanalysis data set, and the large-scale vertical motion is diagnosed interactively with the simulated convection. It is found that convection was triggered primarily by mechanically forced orographic ascent over the Himalayas during the India/Pakistan flood and by upper-level Potential Vorticity disturbances during the Texas/Oklahoma flood. Furthermore, a climate attribution analysis was conducted for the Texas/Oklahoma flood and it is found that anthropogenic climate change was responsible for a small amount of rainfall during the event but the intensity of this event may be greatly increased if it occurs in a future climate. In the second part of this thesis, I examine the ability of high-resolution global atmospheric models to simulate TCs. Specifically, I present an intercomparison of several models' ability to simulate the global characteristics of TCs in the current climate. This is a necessary first step before using these models to project future changes in TCs. Overall, the models were able to reproduce the geographic distribution of TCs reasonably well, with some of the models performing remarkably well. The intensity of TCs varied widely between the models, with some of this difference being due to model resolution.

Effective and efficient analysis of spatio-temporal data

NASA Astrophysics Data System (ADS)

Zhang, Zhongnan

Spatio-temporal data mining, i.e., mining knowledge from large amount of spatio-temporal data, is a highly demanding field because huge amounts of spatio-temporal data have been collected in various applications, ranging from remote sensing, to geographical information systems (GIS), computer cartography, environmental assessment and planning, etc. The collection data far exceeded human's ability to analyze which make it crucial to develop analysis tools. Recent studies on data mining have extended to the scope of data mining from relational and transactional datasets to spatial and temporal datasets. Among the various forms of spatio-temporal data, remote sensing images play an important role, due to the growing wide-spreading of outer space satellites. In this dissertation, we proposed two approaches to analyze the remote sensing data. The first one is about applying association rules mining onto images processing. Each image was divided into a number of image blocks. We built a spatial relationship for these blocks during the dividing process. This made a large number of images into a spatio-temporal dataset since each image was shot in time-series. The second one implemented co-occurrence patterns discovery from these images. The generated patterns represent subsets of spatial features that are located together in space and time. A weather analysis is composed of individual analysis of several meteorological variables. These variables include temperature, pressure, dew point, wind, clouds, visibility and so on. Local-scale models provide detailed analysis and forecasts of meteorological phenomena ranging from a few kilometers to about 100 kilometers in size. When some of above meteorological variables have some special change tendency, some kind of severe weather will happen in most cases. Using the discovery of association rules, we found that some special meteorological variables' changing has tight relation with some severe weather situation that will happen very soon. This dissertation is composed of three parts: an introduction, some basic knowledges and relative works, and my own three contributions to the development of approaches for spatio-temporal data mining: DYSTAL algorithm, STARSI algorithm, and COSTCOP+ algorithm.

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

Changes in the Winter-Time Storminess over the North Atlantic, Associated with the 1.5°C and 2°C Levels of Global Warming.

NASA Astrophysics Data System (ADS)

Barcikowska, M. J.; Weaver, S. J.; Feser, F.; Schenk, F.

2017-12-01

This study investigates the changes in extreme winter-time weather conditions over the NH midlatitudes. These conditions are to a large degree caused by extratropical storms, often associated with very intense and hazardous precipitation and wind. Although the skill of CMIP5 models in capturing these extremes is improved when compared to the previous generations, the spatial and temporal resolution of the models still remains a primary reason for the deficiencies. Therefore, many features of the storms projected for the future remain inconsistent. Here we are using the high-res horizontal (0.25° lat x lon) and temporal (3hr) output of the HAPPI experiment. This output facilitates not only an implicit extraction of storm tracks but also an analysis of the storm intensity, in terms of their maximum wind and rainfall, at subdaily time-scales. The analysis of simulated present climate shows an improved spatial pattern of large-scale circulation over North America and Europe, as compared to the CMIP5-generation models, and consequently a reduced zonal bias in storm tracks pattern. The information provided at subdaily time scale provides much more realistic representation of the magnitude of the extremes. These advances significantly contribute to our understanding of differential climate impacts between 1.5°C and 2°C levels of global warming. The spatial pattern of the north-eastward shift of storm tracks, derived from the recent CMIP5 future projections, is remarkably refined here. For example, increasing storminess expands towards Scandinavia, and not towards the north-central Europe. Derived spatial features of the storm intensity, e.g. increase in wind and precipitation on the west coasts of both the British Isles and Scandinavia underlines the relevancy of the results for the local communities and potential climate change adaptation initiatives.

Local-scale analysis of temperature patterns over Poland during heatwave events

NASA Astrophysics Data System (ADS)

Krzyżewska, Agnieszka; Dyer, Jamie

2018-01-01

Heatwaves are predicted to increase in frequency, duration, and severity in the future, including over Central Europe where populations are sensitive to extreme temperature. This paper studies six recent major heatwave events over Poland from 2006 through 2015 using regional-scale simulations (10-km grid spacing, hourly frequency) from the Weather Research and Forecast (WRF) model to define local-scale 2-m temperature patterns. For this purpose, a heatwave is defined as at least three consecutive days with maximum 2-m air temperature exceeding 30 °C. The WRF simulations were validated using maximum daily 2-m temperature observations from 12 meteorological stations in select Polish cities, which were selected to have even spatial coverage across the study area. Synoptic analysis of the six study events shows that the inflow of tropical air masses from the south is the primary driver of heatwave onset and maintenance, the highest temperatures (and most vulnerable areas) occur over arable land and artificial surfaces in central and western Poland, while coastal areas in the north, mountain areas in the south, and forested and mosaic areas of smaller fields and pastures of the northwest, northeast, and southeast are less affected by prolonged periods of elevated temperatures. In general, regional differences in 2-m temperature between the hottest and coolest areas is about 2-4 °C. Large urban areas like Warsaw, or the large complex of artificial areas in the conurbation of Silesian cities, are also generally warmer than surrounding areas by roughly 2-4 °C, and even up to 6 °C, especially during the night. Additionally, hot air from the south of Poland flows through a low-lying area between two mountain ranges (Sudetes and Carpathian Mountains)—the so-called Moravian Gate—hitting densely populated urban areas (Silesian cities) and Cracow. These patterns occur only during high-pressure synoptic conditions with low cloudiness and wind and without any active fronts or mesoscale convective disturbances.

The Dynamics of a Semi-Arid Region in Response to Climate and Water - Use Policy

NASA Technical Reports Server (NTRS)

Mustard, John F.; Hamburg, Steve; Grant, John A.; Manning, Sara J.; Steinwand, Aaron; Howard, Chris

2000-01-01

The objectives of this project were to determine the response of semi-arid ecosystems to the combined forcings of climate variability and anthropogenic stress. Arid and semi-arid systems encompass close to 40% of the worlds land surface. The ecology of these regions are principally limited by water, and as the water resources wax and wane, so should the health and vigor of the ecosystems. Water, however, is a necessary and critical resource for humans living in these same regions. Thus for many and and semi-arid regions the natural systems and human systems are in direct competition for a limited resource. Increasing competition through development of and and semi-arid regions, export of water resources, as well as potential persistent changes in weather patterns are likely to lead to fundamental changes in carrying capacity, resilience, and ecology of these regions. A detailed understanding of these systems respond to forcing on a regional and local scale is required in order to better prepare for and manage future changes in the availability of water. In the Owens Valley CA, decadal changes in rainfall and increased use of groundwater resources by Los Angles (which derives 60-70% of its water from this region) have resulted in a large-scale experiment on the impacts of these changes in semi-arid ecosystems. This project works directly with the Inyo County Water Department (local water authority) and the Los Angles Department of Water and Power (regional demand on water resources) to understand changes, their causes, and impacts. Very detailed records have been kept for a number of selected sites in the valley which provide essential ground truth. These results are then scaled up through remote sensed data to regions scale to assess large scale patterns and link them to the fundamental decisions regarding the water resources of this region. A fundamental goal is to understand how resilient the native ecosystems are to large changes in water resources. Are they are on a spring (remove and return resources, do the systems return to the original state) or a vector (when water returns have the systems fundamentally changed).

Synoptic-scale fire weather conditions in Alaska

NASA Astrophysics Data System (ADS)

Hayasaka, Hiroshi; Tanaka, Hiroshi L.; Bieniek, Peter A.

2016-09-01

Recent concurrent widespread fires in Alaska are evaluated to assess their associated synoptic-scale weather conditions. Several periods of high fire activity from 2003 to 2015 were identified using Moderate Resolution Imaging Spectroradiometer (MODIS) hotspot data by considering the number of daily hotspots and their continuity. Fire weather conditions during the top six periods of high fire activity in the fire years of 2004, 2005, 2009, and 2015 were analyzed using upper level (500 hPa) and near surface level (1000 hPa) atmospheric reanalysis data. The top four fire-periods occurred under similar unique high-pressure fire weather conditions related to Rossby wave breaking (RWB). Following the ignition of wildfires, fire weather conditions related to RWB events typically result in two hotspot peaks occurring before and after high-pressure systems move from south to north across Alaska. A ridge in the Gulf of Alaska resulted in southwesterly wind during the first hotspot peak. After the high-pressure system moved north under RWB conditions, the Beaufort Sea High developed and resulted in relatively strong easterly wind in Interior Alaska and a second (largest) hotspot peak during each fire period. Low-pressure-related fire weather conditions occurring under cyclogenesis in the Arctic also resulted in high fire activity under southwesterly wind with a single large hot-spot peak.

Introducing GFWED: The Global Fire Weather Database

NASA Technical Reports Server (NTRS)

Field, R. D.; Spessa, A. C.; Aziz, N. A.; Camia, A.; Cantin, A.; Carr, R.; de Groot, W. J.; Dowdy, A. J.; Flannigan, M. D.; Manomaiphiboon, K.;

Colluvial deposits as a possible weathering reservoir in uplifting mountains

NASA Astrophysics Data System (ADS)

Carretier, Sébastien; Goddéris, Yves; Martinez, Javier; Reich, Martin; Martinod, Pierre

2018-03-01

The role of mountain uplift in the evolution of the global climate over geological times is controversial. At the heart of this debate is the capacity of rapid denudation to drive silicate weathering, which consumes CO2. Here we present the results of a 3-D model that couples erosion and weathering during mountain uplift, in which, for the first time, the weathered material is traced during its stochastic transport from the hillslopes to the mountain outlet. To explore the response of weathering fluxes to progressively cooler and drier climatic conditions, we run model simulations accounting for a decrease in temperature with or without modifications in the rainfall pattern based on a simple orographic model. At this stage, the model does not simulate the deep water circulation, the precipitation of secondary minerals, variations in the pH, below-ground pCO2, and the chemical affinity of the water in contact with minerals. Consequently, the predicted silicate weathering fluxes probably represent a maximum, although the predicted silicate weathering rates are within the range of silicate and total weathering rates estimated from field data. In all cases, the erosion rate increases during mountain uplift, which thins the regolith and produces a hump in the weathering rate evolution. This model thus predicts that the weathering outflux reaches a peak and then falls, consistent with predictions of previous 1-D models. By tracking the pathways of particles, the model can also consider how lateral river erosion drives mass wasting and the temporary storage of colluvial deposits on the valley sides. This reservoir is comprised of fresh material that has a residence time ranging from several years up to several thousand years. During this period, the weathering of colluvium appears to sustain the mountain weathering flux. The relative weathering contribution of colluvium depends on the area covered by regolith on the hillslopes. For mountains sparsely covered by regolith during cold periods, colluvium produces most of the simulated weathering flux for a large range of erosion parameters and precipitation rate patterns. In addition to other reservoirs such as deep fractured bedrock, colluvial deposits may help to maintain a substantial and constant weathering flux in rapidly uplifting mountains during cooling periods.

Predicting the size and elevation of future mountain forests: Scaling macroclimate to microclimate

NASA Astrophysics Data System (ADS)

Cory, S. T.; Smith, W. K.

2017-12-01

Global climate change is predicted to alter continental scale macroclimate and regional mesoclimate. Yet, it is at the microclimate scale that organisms interact with their physiochemical environments. Thus, to predict future changes in the biota such as biodiversity and distribution patterns, a quantitative coupling between macro-, meso-, and microclimatic parameters must be developed. We are evaluating the impact of climate change on the size and elevational distribution of conifer mountain forests by determining the microclimate necessary for new seedling survival at the elevational boundaries of the forest. This initial life stage, only a few centimeters away from the soil surface, appears to be the bottleneck to treeline migration and the expansion or contraction of a conifer mountain forest. For example, survival at the alpine treeline is extremely rare and appears to be limited to facilitated microsites with low sky exposure. Yet, abundant mesoclimate data from standard weather stations have rarely been scaled to the microclimate level. Our research is focusing on an empirical downscaling approach linking microclimate measurements at favorable seedling microsites to the meso- and macro-climate levels. Specifically, mesoclimate values of air temperature, relative humidity, incident sunlight, and wind speed from NOAA NCEI weather stations can be extrapolated to the microsite level that is physiologically relevant for seedling survival. Data will be presented showing a strong correlation between incident sunlight measured at 2-m and seedling microclimate, despite large differences from seedling/microsite temperatures. Our downscaling approach will ultimately enable predictions of microclimate from the much more abundant mesoclimate data available from a variety of sources. Thus, scaling from macro- to meso- to microclimate will be possible, enabling predictions of climate change models to be translated to the microsite level. This linkage between measurement scales will enable a more precise prediction of the effects of climate change on the future extent and elevational distribution of our mountain forests and an accompanying array of critical ecosystem services.

Evaluating climate models: Should we use weather or climate observations?

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

Oglesby, Robert J; Erickson III, David J

2009-12-01

Calling the numerical models that we use for simulations of climate change 'climate models' is a bit of a misnomer. These 'general circulation models' (GCMs, AKA global climate models) and their cousins the 'regional climate models' (RCMs) are actually physically-based weather simulators. That is, these models simulate, either globally or locally, daily weather patterns in response to some change in forcing or boundary condition. These simulated weather patterns are then aggregated into climate statistics, very much as we aggregate observations into 'real climate statistics'. Traditionally, the output of GCMs has been evaluated using climate statistics, as opposed to their abilitymore » to simulate realistic daily weather observations. At the coarse global scale this may be a reasonable approach, however, as RCM's downscale to increasingly higher resolutions, the conjunction between weather and climate becomes more problematic. We present results from a series of present-day climate simulations using the WRF ARW for domains that cover North America, much of Latin America, and South Asia. The basic domains are at a 12 km resolution, but several inner domains at 4 km have also been simulated. These include regions of complex topography in Mexico, Colombia, Peru, and Sri Lanka, as well as a region of low topography and fairly homogeneous land surface type (the U.S. Great Plains). Model evaluations are performed using standard climate analyses (e.g., reanalyses; NCDC data) but also using time series of daily station observations. Preliminary results suggest little difference in the assessment of long-term mean quantities, but the variability on seasonal and interannual timescales is better described. Furthermore, the value-added by using daily weather observations as an evaluation tool increases with the model resolution.« less

Storm-tracks interannual variability and large-scale climate modes

NASA Astrophysics Data System (ADS)

Liberato, Margarida L. R.; Trigo, Isabel F.; Trigo, Ricardo M.

2013-04-01

In this study we focus on the interannual variability and observed changes in northern hemisphere mid-latitude storm-tracks and relate them to large scale atmospheric circulation variability modes. Extratropical storminess, cyclones dominant paths, frequency and intensity have long been the object of climatological studies. The analysis of storm characteristics and historical trends presented here is based on the cyclone detecting and tracking algorithm first developed for the Mediterranean region (Trigo et al. 1999) and recently extended to a larger Euro-Atlantic region (Trigo 2006). The objective methodology, which identifies and follows individual lows as minima in SLP fields, fulfilling a set of conditions regarding the central pressure and the pressure gradient, is applied to the northern hemisphere 6-hourly geopotential data at 1000 hPa from the 20th Century Reanalyses (20CRv2) project and from reanalyses datasets provided by the European Centre for Medium-Range Weather Forecasts (ECMWF): ERA-40 and ERA Interim reanalyses. First, we assess the interannual variability and cyclone frequency trends for each of the datasets, for the 20th century and for the period between 1958 and 2002 using the highest spatial resolution available (1.125° x 1.125°) from the ERA-40 data. Results show that winter variability of storm paths, cyclone frequency and travel times is in agreement with the reported variability in a number of large-scale climate patterns (including the North Atlantic Oscillation, the East Atlantic Pattern and the Scandinavian Pattern). In addition, three storm-track databases are built spanning the common available extended winter seasons from October 1979 to March 2002. Although relatively short, this common period allows a comparison of systems represented in reanalyses datasets with distinct horizontal resolutions. This exercise is mostly focused on the key areas of cyclogenesis and cyclolysis and main cyclone characteristics over the northern hemisphere. Trigo IF., TD Davies, GR Bigg (1999) Objective climatology of cyclones in the Mediterranean region. J. Climate 12: 1685-1696. Trigo IF (2006) Climatology and interannual variability of storm-tracks in the Euro-Atlantic sector: a comparison between ERA-40 and NCEP/NCAR reanalyses. Clim. Dyn. 26: 127-143.

Large-Scale Antecedent Conditions Associated with 2014-2015 Winter Onset over North America and mid-Winter Storminess Along the North Atlantic Coast

NASA Astrophysics Data System (ADS)

Bosart, L. F.; Papin, P. P.; Bentley, A. M.; Benjamin, M.; Winters, A. C.

2015-12-01

Winter 2014-2015 was marked by the coldest November weather in 35 years east of the Rockies and record-breaking snowstorms and cold from the eastern Great Lakes to Atlantic Canada in January and February 2015. Record-breaking warmth prevailed across the Intermountain West and Rockies beneath a persistent upper-level ridge. Winter began with a series of arctic air mass surges that culminated in an epic lake-effect snowstorm occurred over western New York before Thanksgiving and was followed by a series of snow and ice storms that disrupted Thanksgiving holiday travel widely. Winter briefly abated in part of December, but returned with a vengeance between mid-January and mid-February 2015 when multiple extreme weather events that featured record-breaking monthly and seasonal snowfalls and record-breaking daily minimum temperatures were observed. This presentation will show how: (1) the recurvature and extratropical transition (ET) of Supertyphoon (STY) Nuri in the western Pacific in early November 2014, and its subsequent explosive reintensification as an extratropical cyclone (EC), disrupted the North Pacific jet stream and downstream Northern Hemisphere (NH) circulation, produced high-latitude ridging and the formation of an omega block over western North America, triggered downstream baroclinic development and the formation of a deep trough over eastern North America, and ushered in winter 2014-2015, (2) the ET/EC of STY Nuri increased subsequent week two predictability over the North Pacific and North America in association with diabatically influenced high-latitude ridge building, and (3) the amplification of the large-scale NH flow pattern beginning in January 2015 resulted in the formation of persistent high-amplitude ridges over northeastern Russia, Alaska, western North America, and the North Atlantic while deep troughs formed over the eastern North Pacific and eastern North America. This persistent amplified flow pattern supported the occurrence of frequent heavy snowstorms, including blizzards, over parts of the northeastern United States and adjacent Atlantic Canada during the latter part of January and much of February 2015.

Large and local-scale influences on physical and chemical characteristics of coastal waters of Western Europe during winter

NASA Astrophysics Data System (ADS)

Tréguer, Paul; Goberville, Eric; Barrier, Nicolas; L'Helguen, Stéphane; Morin, Pascal; Bozec, Yann; Rimmelin-Maury, Peggy; Czamanski, Marie; Grossteffan, Emilie; Cariou, Thierry; Répécaud, Michel; Quéméner, Loic

2014-11-01

There is now a strong scientific consensus that coastal marine systems of Western Europe are highly sensitive to the combined effects of natural climate variability and anthropogenic climate change. However, it still remains challenging to assess the spatial and temporal scales at which climate influence operates. While large-scale hydro-climatic indices, such as the North Atlantic Oscillation (NAO) or the East Atlantic Pattern (EAP) and the weather regimes such as the Atlantic Ridge (AR), are known to be relevant predictors of physical processes, changes in coastal waters can also be related to local hydro-meteorological and geochemical forcing. Here, we study the temporal variability of physical and chemical characteristics of coastal waters located at about 48°N over the period 1998-2013 using (1) sea surface temperature, (2) sea surface salinity and (3) nutrient concentration observations for two coastal sites located at the outlet of the Bay of Brest and off Roscoff, (4) river discharges of the major tributaries close to these two sites and (5) regional and local precipitation data over the region of interest. Focusing on the winter months, we characterize the physical and chemical variability of these coastal waters and document changes in both precipitation and river runoffs. Our study reveals that variability in coastal waters is connected to the large-scale North Atlantic atmospheric circulation but is also partly explained by local river influences. Indeed, while the NAO is strongly related to changes in sea surface temperature at the Brest and Roscoff sites, the EAP and the AR have a major influence on precipitations, which in turn modulate river discharges that impact sea surface salinity at the scale of the two coastal stations.

Attribution of changes in precipitation patterns in African rainforests

NASA Astrophysics Data System (ADS)

Otto, F. E.; Jones, R. G.; Halladay, K.; Allen, M. R.

2013-12-01

The effects of projected future global and regional climate change on the water cycle and thus on global water security are amongst the most economically and politically important challenges that society faces in the 21st century. The provision of secure access to water resources and the protection of communities from water-related risks have emerged as top priorities amongst policymakers within the public and private sectors alike. Investment decisions on water infrastructure rely heavily on quantitative assessments of risks and uncertainties associated with future changes in water-related threats. Especially with the introduction of loss and damages on the agenda of the UNFCCC additionally the attribution of such changes to anthropogenic climate change and other external climate drivers is crucial. Probabilistic event attribution (PEA) provides a method of evaluating the extent to which human-induced climate change is affecting localised weather events and impacts of such events that relies on good observations as well as climate modelling. The overall approach is to simulate both, the statistics of observed weather, and the statistics of the weather that would have occurred had specific external drivers of climate change been absent. The majority of studies applying PEA have focused on quantifying attributable risk, with changes in risk depending on an assumption of 'all other things being equal', including natural drivers of climate change and vulnerability. Most previous attribution studies have focused on 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, with the rainforests in tropical Africa being some of the most under-researched regions in the world. Research in the Amazonian rainforest suggests potential vulnerability to climate change. We will present results from using the large ensemble of atmosphere-only general circulation model (AGCM) simulations within the weather@home project, and analysing statistics of precipitation in the dry season of the Congo Basin rainforests. Because observed data sets in that region are of very poor quality we show how validation methods not only relying on such data have been used to investigate the applicability of PEA analysis from large model ensembles to this tropical region. Additionally we will present results for the same region but generated with a very large ensemble of regional climate simulations which allows analysing the importance of a realistic simulation of small scale precipitation processes for attribution studies in a tropical climate. We highlight that PEA analysis has the potential to provide valuable scientific evidence of recent or anticipated climatological changes in the water cycle, especially in regions with sparse observational data and unclear projections of future changes. However, the strong influence of SST tele-connection patterns on tropical precipitation provides more challenges in the set-up of attribution studies than studies on mid-latitude rainfall.

A comparison of weather variables linked to infectious disease patterns using laboratory addresses and patient residence addresses.

PubMed

Djennad, Abdelmajid; Lo Iacono, Giovanni; Sarran, Christophe; Fleming, Lora E; Kessel, Anthony; Haines, Andy; Nichols, Gordon L

2018-04-27

To understand the impact of weather on infectious diseases, information on weather parameters at patient locations is needed, but this is not always accessible due to confidentiality or data availability. Weather parameters at nearby locations are often used as a proxy, but the accuracy of this practice is not known. Daily Campylobacter and Cryptosporidium cases across England and Wales were linked to local temperature and rainfall at the residence postcodes of the patients and at the corresponding postcodes of the laboratory where the patient's specimen was tested. The paired values of daily rainfall and temperature for the laboratory versus residence postcodes were interpolated from weather station data, and the results were analysed for agreement using linear regression. We also assessed potential dependency of the findings on the relative geographic distance between the patient's residence and the laboratory. There was significant and strong agreement between the daily values of rainfall and temperature at diagnostic laboratories with the values at the patient residence postcodes for samples containing the pathogens Campylobacter or Cryptosporidium. For rainfall, the R-squared was 0.96 for the former and 0.97 for the latter, and for maximum daily temperature, the R-squared was 0.99 for both. The overall mean distance between the patient residence and the laboratory was 11.9 km; however, the distribution of these distances exhibited a heavy tail, with some rare situations where the distance between the patient residence and the laboratory was larger than 500 km. These large distances impact the distributions of the weather variable discrepancies (i.e. the differences between weather parameters estimated at patient residence postcodes and those at laboratory postcodes), with discrepancies up to ±10 °C for the minimum and maximum temperature and 20 mm for rainfall. Nevertheless, the distributions of discrepancies (estimated separately for minimum and maximum temperature and rainfall), based on the cases where the distance between the patient residence and the laboratory was within 20 km, still exhibited tails somewhat longer than the corresponding exponential fits suggesting modest small scale variations in temperature and rainfall. The findings confirm that, for the purposes of studying the relationships between meteorological variables and infectious diseases using data based on laboratory postcodes, the weather results are sufficiently similar to justify the use of laboratory postcode as a surrogate for domestic postcode. Exclusion of the small percentage of cases where there is a large distance between the residence and the laboratory could increase the precision of estimates, but there are generally strong associations between daily weather parameters at residence and laboratory.

Quantifying Seasonal Dynamic Water Storage in a Fractured Bedrock Vadose Zone With Borehole Nuclear Magnetic Resonance

NASA Astrophysics Data System (ADS)

Schmidt, L.; Minton, B.; Soto-Kerans, N.; Rempe, D.; Heidari, Z.

2017-12-01

In many uplands landscapes, water is transiently stored in the weathered and fractured bedrock that underlies soils. The timing and spatial pattern of this "rock moisture" has strong implications for ecological and biogeochemical processes that influence global cycling of water and solutes. However, available technologies for direct monitoring of rock moisture are limited. Here, we quantify temporal and spatial changes in rock moisture at the field scale across thick (up to 20 m) fractured vadose zone profiles using a novel narrow diameter borehole nuclear magnetic resonance system (BNMR). Successive BNMR surveys were performed using the Vista Clara Inc. Dart system in a network of boreholes within two steep, intensively hydrologically monitored hillslopes associated with the Eel River Critical Zone Observatory (ERCZO) in Northern California. BNMR data showed agreement with estimates of the temporal and spatial pattern of rock moisture depletion over the dry season via downhole neutron and gamma density surveys, as well as permanently installed continuous time domain reflectometry. Observable shifts in the BNMR-derived T2 distribution over time provide a direct measure of changes in the amount of water held within different pore sizes (large vs. small) in fractured rock. Analysis of both BNMR and laboratory-scale NMR (using a 2MHz benchtop NMR spectrometer) measurements of ERCZO core samples at variable saturation suggest that rock moisture changes associated with summer depletion occur within both large (fracture) and small (matrix) pore sizes. Collectively, our multi-method field- and laboratory- scale measurements highlight the potential for BNMR to improve quantification of rock moisture storage for better understanding of the biogeochemical and ecohydrological implications of rock moisture circulation in the Critical Zone.

Influence of the Bermuda High on interannual variability of summertime ozone in the Houston-Galveston-Brazoria region

NASA Astrophysics Data System (ADS)

Wang, Yuxuan; Jia, Beixi; Wang, Sing-Chun; Estes, Mark; Shen, Lu; Xie, Yuanyu

2016-12-01

The Bermuda High (BH) quasi-permanent pressure system is the key large-scale circulation pattern influencing summertime weather over the eastern and southern US. Here we developed a multiple linear regression (MLR) model to characterize the effect of the BH on year-to-year changes in monthly-mean maximum daily 8 h average (MDA8) ozone in the Houston-Galveston-Brazoria (HGB) metropolitan region during June, July, and August (JJA). The BH indicators include the longitude of the BH western edge (BH-Lon) and the BH intensity index (BHI) defined as the pressure gradient along its western edge. Both BH-Lon and BHI are selected by MLR as significant predictors (p < 0.05) of the interannual (1990-2015) variability of the HGB-mean ozone throughout JJA, while local-scale meridional wind speed is selected as an additional predictor for August only. Local-scale temperature and zonal wind speed are not identified as important factors for any summer month. The best-fit MLR model can explain 61-72 % of the interannual variability of the HGB-mean summertime ozone over 1990-2015 and shows good performance in cross-validation (R2 higher than 0.48). The BH-Lon is the most important factor, which alone explains 38-48 % of such variability. The location and strength of the Bermuda High appears to control whether or not low-ozone maritime air from the Gulf of Mexico can enter southeastern Texas and affect air quality. This mechanism also applies to other coastal urban regions along the Gulf Coast (e.g., New Orleans, LA, Mobile, AL, and Pensacola, FL), suggesting that the BH circulation pattern can affect surface ozone variability through a large portion of the Gulf Coast.

Radiotelemetric analysis of the effects of prevailing wind direction on Mormon cricket migratory band movement.

PubMed

Sword, G A; Lorch, P D; Gwynne, D T

2008-08-01

During outbreaks, flightless Mormon crickets [Anabrus simplex Haldeman (Orthoptera: Tettigoniidae)] form large mobile groups known as migratory bands. These bands can contain millions of individuals that march en masse across the landscape. The role of environmental cues in influencing the movement direction of migratory bands is poorly understood and has been the subject of little empirical study. We examined the effect of wind direction on Mormon cricket migratory band movement direction by monitoring the local weather conditions and daily movement patterns of individual insects traveling in bands over the same time course at three close, but spatially distinct sites. Although weather conditions were relatively homogeneous across sites, wind directions tended to be more variable across sites during the morning hours, the period during which directional movement begins. Migratory bands at different sites traveled in distinctly different directions. However, we failed to find any evidence to suggest that the observed variation in migratory band movement direction was correlated with local wind direction at any time during the day. These results support the notion that the cues mediating migratory band directionality are likely to be group specific and that a role for landscape-scale environmental cues such as wind direction is unlikely.

Impact of seasonal synoptic weather types on local PM10 concentrations in Bavaria/Germany: recent conditions and future projections

NASA Astrophysics Data System (ADS)

Weitnauer, Claudia; Beck, Christoph; Jacobeit, Jucundus

2015-04-01

It is a matter of common knowledge that local concentrations of PM10 (fine particles in the air with a medium diameter less than 10 μm) vary with the seasons in Europe. These concentrations are influenced on the one hand by the amount of natural and anthropogenic emissions and on the other hand by large-scale and local meteorological conditions. In Bavaria (part of southern Germany) as the target region of the present study, the PM10 concentrations are particularly high in winter time. One reason for this are increased particle emissions due to domestic heating and traffic load in December, January and February. As several studies in other European regions indicated, a distinct effect of the large-scale synoptic weather situation in winter on local PM10 concentrations should be considered as another reason. The main task of this study is to use seasonal synoptic weather types, which are optimized with respect to daily mean PM10 data at 16 Bavarian cities, and therefore are classified by using daily gridded NCEP/NCAR reanalysis data (2.5° x 2.5° horizontal resolution) for the recent period 1980 - 2011 over a Central European spatial domain, to describe the impact of the large-scale meteorological conditions on the local particle concentrations. The weather types are related to monthly PM10 indices by using different transfer techniques like direct synoptic downscaling, multiple regression and generalized linear models as well as random forests. The PM10 indices are determined by averaging daily to monthly data (PMmean) or by counting the daily exceedances of a particular threshold (> 50 μg/m3, PMe50). The generated transfer models are evaluated in calibration and validation periods using several forecast skills, for example the mean squared skill score (MSSS) or the Heidke Skill Score (HSS). The sufficiently performing models are then applied to weather types derived from future climate change scenarios of the global climate model ECHAM 6 for the IPCC scenarios RCP 4.5 and 8.5 in order to estimate future climate-change induced modifications of local PM10 concentrations in Bavaria.

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.

Wireless in-situ Sensor Network for Agriculture and Water Monitoring on a River Basin Scale in Southern Finland: Evaluation from a Data User’s Perspective

PubMed Central

Kotamäki, Niina; Thessler, Sirpa; Koskiaho, Jari; Hannukkala, Asko O.; Huitu, Hanna; Huttula, Timo; Havento, Jukka; Järvenpää, Markku

2009-01-01

Sensor networks are increasingly being implemented for environmental monitoring and agriculture to provide spatially accurate and continuous environmental information and (near) real-time applications. These networks provide a large amount of data which poses challenges for ensuring data quality and extracting relevant information. In the present paper we describe a river basin scale wireless sensor network for agriculture and water monitoring. The network, called SoilWeather, is unique and the first of this type in Finland. The performance of the network is assessed from the user and maintainer perspectives, concentrating on data quality, network maintenance and applications. The results showed that the SoilWeather network has been functioning in a relatively reliable way, but also that the maintenance and data quality assurance by automatic algorithms and calibration samples requires a lot of effort, especially in continuous water monitoring over large areas. We see great benefits on sensor networks enabling continuous, real-time monitoring, while data quality control and maintenance efforts highlight the need for tight collaboration between sensor and sensor network owners to decrease costs and increase the quality of the sensor data in large scale applications. PMID:22574050

Relationships between fire frequency and woody canopy cover in a semi-arid African savanna

Treesearch

Andrew T. Hudak; Bruce H. Brockett

2003-01-01

Landscape-scale fire patterns result from complex interactions among weather, ignition sources, vegetation type and the biophysical environment (Hargrove et al. 2000, Morgan et al. 2001, Keane et al. 2002, Hudak, Fairbanks & Brockett in press). Patch characteristics (e.g. woody canopy cover) influence fire characteristics, which in turn influence patch...

Improving Air Quality (and Weather) Predictions using Advanced Data Assimilation Techniques Applied to Coupled Models during KORUS-AQ

NASA Astrophysics Data System (ADS)

Carmichael, G. R.; Saide, P. E.; Gao, M.; Streets, D. G.; Kim, J.; Woo, J. H.

2017-12-01

Ambient aerosols are important air pollutants with direct impacts on human health and on the Earth's weather and climate systems through their interactions with radiation and clouds. Their role is dependent on their distributions of size, number, phase and composition, which vary significantly in space and time. There remain large uncertainties in simulated aerosol distributions due to uncertainties in emission estimates and in chemical and physical processes associated with their formation and removal. These uncertainties lead to large uncertainties in weather and air quality predictions and in estimates of health and climate change impacts. Despite these uncertainties and challenges, regional-scale coupled chemistry-meteorological models such as WRF-Chem have significant capabilities in predicting aerosol distributions and explaining aerosol-weather interactions. We explore the hypothesis that new advances in on-line, coupled atmospheric chemistry/meteorological models, and new emission inversion and data assimilation techniques applicable to such coupled models, can be applied in innovative ways using current and evolving observation systems to improve predictions of aerosol distributions at regional scales. We investigate the impacts of assimilating AOD from geostationary satellite (GOCI) and surface PM2.5 measurements on predictions of AOD and PM in Korea during KORUS-AQ through a series of experiments. The results suggest assimilating datasets from multiple platforms can improve the predictions of aerosol temporal and spatial distributions.

Behavioral self-organization underlies the resilience of a coastal ecosystem.

PubMed

de Paoli, Hélène; van der Heide, Tjisse; van den Berg, Aniek; Silliman, Brian R; Herman, Peter M J; van de Koppel, Johan

2017-07-25

Self-organized spatial patterns occur in many terrestrial, aquatic, and marine ecosystems. Theoretical models and observational studies suggest self-organization, the formation of patterns due to ecological interactions, is critical for enhanced ecosystem resilience. However, experimental tests of this cross-ecosystem theory are lacking. In this study, we experimentally test the hypothesis that self-organized pattern formation improves the persistence of mussel beds ( Mytilus edulis ) on intertidal flats. In natural beds, mussels generate self-organized patterns at two different spatial scales: regularly spaced clusters of mussels at centimeter scale driven by behavioral aggregation and large-scale, regularly spaced bands at meter scale driven by ecological feedback mechanisms. To test for the relative importance of these two spatial scales of self-organization on mussel bed persistence, we conducted field manipulations in which we factorially constructed small-scale and/or large-scale patterns. Our results revealed that both forms of self-organization enhanced the persistence of the constructed mussel beds in comparison to nonorganized beds. Small-scale, behaviorally driven cluster patterns were found to be crucial for persistence, and thus resistance to wave disturbance, whereas large-scale, self-organized patterns facilitated reformation of small-scale patterns if mussels were dislodged. This study provides experimental evidence that self-organization can be paramount to enhancing ecosystem persistence. We conclude that ecosystems with self-organized spatial patterns are likely to benefit greatly from conservation and restoration actions that use the emergent effects of self-organization to increase ecosystem resistance to disturbance.

Behavioral self-organization underlies the resilience of a coastal ecosystem

PubMed Central

de Paoli, Hélène; van der Heide, Tjisse; van den Berg, Aniek; Silliman, Brian R.; Herman, Peter M. J.

2017-01-01

Self-organized spatial patterns occur in many terrestrial, aquatic, and marine ecosystems. Theoretical models and observational studies suggest self-organization, the formation of patterns due to ecological interactions, is critical for enhanced ecosystem resilience. However, experimental tests of this cross-ecosystem theory are lacking. In this study, we experimentally test the hypothesis that self-organized pattern formation improves the persistence of mussel beds (Mytilus edulis) on intertidal flats. In natural beds, mussels generate self-organized patterns at two different spatial scales: regularly spaced clusters of mussels at centimeter scale driven by behavioral aggregation and large-scale, regularly spaced bands at meter scale driven by ecological feedback mechanisms. To test for the relative importance of these two spatial scales of self-organization on mussel bed persistence, we conducted field manipulations in which we factorially constructed small-scale and/or large-scale patterns. Our results revealed that both forms of self-organization enhanced the persistence of the constructed mussel beds in comparison to nonorganized beds. Small-scale, behaviorally driven cluster patterns were found to be crucial for persistence, and thus resistance to wave disturbance, whereas large-scale, self-organized patterns facilitated reformation of small-scale patterns if mussels were dislodged. This study provides experimental evidence that self-organization can be paramount to enhancing ecosystem persistence. We conclude that ecosystems with self-organized spatial patterns are likely to benefit greatly from conservation and restoration actions that use the emergent effects of self-organization to increase ecosystem resistance to disturbance. PMID:28696313

Elevational species shifts in a warmer climate are overestimated when based on weather station data.

PubMed

Scherrer, Daniel; Schmid, Samuel; Körner, Christian

2011-07-01

Strong topographic variation interacting with low stature alpine vegetation creates a multitude of micro-habitats poorly represented by common 2 m above the ground meteorological measurements (weather station data). However, the extent to which the actual habitat temperatures in alpine landscapes deviate from meteorological data at different spatial scales has rarely been quantified. In this study, we assessed thermal surface and soil conditions across topographically rich alpine landscapes by thermal imagery and miniature data loggers from regional (2-km(2)) to plot (1-m(2)) scale. The data were used to quantify the effects of spatial sampling resolution on current micro-habitat distributions and habitat loss due to climate warming scenarios. Soil temperatures showed substantial variation among slopes (2-3 K) dependent on slope exposure, within slopes (3-4 K) due to micro-topography and within 1-m(2) plots (1 K) as a result of plant cover effects. A reduction of spatial sampling resolution from 1 × 1 m to 100 × 100 m leads to an underestimation of current habitat diversity by 25% and predicts a six-times higher habitat loss in a 2-K warming scenario. Our results demonstrate that weather station data are unable to reflect the complex thermal patterns of aerodynamically decoupled alpine vegetation at the investigated scales. Thus, the use of interpolated weather station data to describe alpine life conditions without considering the micro-topographically induced thermal mosaic might lead to misinterpretation and inaccurate prediction.

Thresholds in Soil Mineral Weathering and Relation to Streamwater Chemistry in Glaciated Catchments of the Northeastern USA

NASA Astrophysics Data System (ADS)

Bailey, S. W.; Ross, D. S.

2015-12-01

Primary mineral dissolution (i.e. weathering) is a critical process in forested catchments as an important consumer of acidity and CO2, the principle source of nutrients such as Ca, K, and P, as well as the source of toxic cations such as Al. Two common limitations of weathering studies are inadequate determination of mineralogic composition and insufficient sampling depth to determine location and advancement of weathering reactions. We determined mineral stocks through EPMA mapping of Al, Ca, Fe, P, and Si content of soil samples and development of an image analysis routine that assigned mineral composition based on the content of these five elements. Portions of the classified maps were confirmed by optical petrography and full elemental analysis by SEM-EDS. Samples were analyzed for soil profiles >2m depth (~1.5m past the upper boundary of the "unweathered" C horizon). Study sites spanned a range of weatherability found in catchments in glaciated northeastern USA including Winnisook, NY (sandstone parent material, 100 ppm Ca), Hubbard Brook, NH (granite, 0.9% Ca), and Sleepers River, VT (calcareous granulite, 3.5% Ca). All profiles exhibited a weathering front, or threshold above which the most reactive minerals (calcite, apatite) have been depleted. However, in all cases this threshold was below the rooting zone, and in many profiles, it was well below the C horizon interface. Catchment scale Ca exports reflect this deeper weathering source while rooting zone exchangeable Ca was highly variable, probably reflecting spatial patterns of hydrologic flowpaths which bring deeper weathering products to the surface only in certain landscape positions. These results suggest that nutrient cycling and critical loads models, which assume that ecologically relevant weathering is confined to the rooting zone, need to be refined to account for deeper weathering and spatial patterns of lateral and upward hydrologic fluxes. Similarly, recovery from cultural acidification may be limited in portions of catchments where hydrologic connections do not provide a vehicle for weathering products to recharge the biologically active portion of the subsurface.

Importance of scale, land cover, and weather on the abundance of bird species in a managed forest

USGS Publications Warehouse

Grinde, Alexis R.; Hiemi, Gerald J.; Sturtevant, Brian R.; Panci, Hannah; Thogmartin, Wayne E.; Wolter, Peter

2017-01-01

Climate change and habitat loss are projected to be the two greatest drivers of biodiversity loss over the coming century. While public lands have the potential to increase regional resilience of bird populations to these threats, long-term data are necessary to document species responses to changes in climate and habitat to better understand population vulnerabilities. We used generalized linear mixed models to determine the importance of stand-level characteristics, multi-scale land cover, and annual weather factors to the abundance of 61 bird species over a 20-year time frame in Chippewa National Forest, Minnesota, USA. Of the 61 species modeled, we were able to build final models with R-squared values that ranged from 26% to 69% for 37 species; the remaining 24 species models had issues with convergence or low explanatory power (R-squared < 20%). Models for the 37 species show that stand-level characteristics, land cover factors, and annual weather effects on species abundance were species-specific and varied within guilds. Forty-one percent of the final species models included stand-level characteristics, 92% included land cover variables at the 200 m scale, 51% included land cover variables at the 500 m scale, 46% included land cover variables at the 1000 m scale, and 38% included weather variables in best models. Three species models (8%) included significant weather and land cover interaction terms. Overall, models indicated that aboveground tree biomass and land cover variables drove changes in the majority of species. Of those species models including weather variables, more included annual variation in precipitation or drought than temperature. Annual weather variability was significantly more likely to impact abundance of species associated with deciduous forests and bird species that are considered climate sensitive. The long-term data and models we developed are particularly suited to informing science-based adaptive forest management plans that incorporate climate sensitivity, aim to conserve large areas of forest habitat, and maintain an historical mosaic of cover types for conserving a diverse and abundant avian assemblage.

A new framework to increase the efficiency of large-scale solar power plants.

NASA Astrophysics Data System (ADS)

Alimohammadi, Shahrouz; Kleissl, Jan P.

2015-11-01

A new framework to estimate the spatio-temporal behavior of solar power is introduced, which predicts the statistical behavior of power output at utility scale Photo-Voltaic (PV) power plants. The framework is based on spatio-temporal Gaussian Processes Regression (Kriging) models, which incorporates satellite data with the UCSD version of the Weather and Research Forecasting model. This framework is designed to improve the efficiency of the large-scale solar power plants. The results are also validated from measurements of the local pyranometer sensors, and some improvements in different scenarios are observed. Solar energy.

Helicity patterns on the Sun

NASA Astrophysics Data System (ADS)

Pevtsov, A.

Solar magnetic fields exhibit hemispheric preference for negative (pos- itive) helicity in northern (southern) hemisphere. The hemispheric he- licity rule, however, is not very strong, - the patterns of opposite sign helicity were observed on different spatial scales in each hemisphere. For instance, many individual sunspots exhibit patches of opposite he- licity inside the single polarity field. There are also helicity patterns on scales larger than the size of typical active region. Such patterns were observed in distribution of active regions with abnormal (for a give hemisphere) helicity, in large-scale photospheric magnetic fields and coronal flux systems. We will review the observations of large-scale pat- terns of helicity in solar atmosphere and their possible relationship with (sub-)photospheric processes. The emphasis will be on large-scale pho- tospheric magnetic field and solar corona.

Ground Level Ozone Regional Background Characteristics In North-west Pacific Rim

NASA Astrophysics Data System (ADS)

Chiang, C.; Fan, J.; Chang, J. S.

2007-12-01

Understanding the ground level ozone regional background characteristics is essential in understanding the contribution of long-range transport of pollutants from Asia Mainland to air quality in downwind areas. In order to understand this characteristic in north-west Pacific Rim, we conducted a coupled study using ozone observation from regional background stations and 3-D regional-scale chemical transport model simulations. We used O3, CO, wind speed and wind direction data from two regional background stations and ¡§other stations¡¨ over a ten year period and organized several numerical experiments to simulate one spring month in 2003 to obtain a deeper understanding. The so called ¡§other stations¡¨ had actually been named as background stations under various governmental auspices. But we found them to be often under strong influence of local pollution sources with strong diurnal or slightly longer time variations. We found that the Yonagunijima station (24.74 N, 123.02 E) and Heng-Chuen station (21.96 N,120.78 E), about a distance of 400 km apart, have almost the same ozone time series pattern. For these two stations in 2003, correlation coefficients (R2) for annual observed ozone concentration is about 0.64, in the springtime it is about 0.7, and in a one-month period at simulation days it is about 0.76. These two stations have very little small scale variations in all the variables studied. All variations are associated with large scale circulation changes. This is especially so at Yonagunijima station. Using a 3-D regional-scale chemical transport model for East Asia region including contribution from Asia continental outflow and neighboring island pollution areas we found that the Yonagunijima and HengChuen station are indeed free of pollutants from all neighboring areas keeping in mind that pollutants from Taiwan area is never far away. Ozone concentrations in these two stations are dominated by synoptic scale weather patterns, with diffused pollutant contribution from distant sources. When the weather system brings in air mass from the low latitude of western Pacific Ocean, ozone concentrations are about 10-20 ppb. When the China high pressure system moves eastward and with the accompanying Asian continental outflow plume, ozone concentrations are about 65-80 ppb.

Global daily reference evapotranspiration modeling and evaluation

USGS Publications Warehouse

Senay, G.B.; Verdin, J.P.; Lietzow, R.; Melesse, Assefa M.

2008-01-01

Accurate and reliable evapotranspiration (ET) datasets are crucial in regional water and energy balance studies. Due to the complex instrumentation requirements, actual ET values are generally estimated from reference ET values by adjustment factors using coefficients for water stress and vegetation conditions, commonly referred to as crop coefficients. Until recently, the modeling of reference ET has been solely based on important weather variables collected from weather stations that are generally located in selected agro-climatic locations. Since 2001, the National Oceanic and Atmospheric Administration’s Global Data Assimilation System (GDAS) has been producing six-hourly climate parameter datasets that are used to calculate daily reference ET for the whole globe at 1-degree spatial resolution. The U.S. Geological Survey Center for Earth Resources Observation and Science has been producing daily reference ET (ETo) since 2001, and it has been used on a variety of operational hydrological models for drought and streamflow monitoring all over the world. With the increasing availability of local station-based reference ET estimates, we evaluated the GDAS-based reference ET estimates using data from the California Irrigation Management Information System (CIMIS). Daily CIMIS reference ET estimates from 85 stations were compared with GDAS-based reference ET at different spatial and temporal scales using five-year daily data from 2002 through 2006. Despite the large difference in spatial scale (point vs. ∼100 km grid cell) between the two datasets, the correlations between station-based ET and GDAS-ET were very high, exceeding 0.97 on a daily basis to more than 0.99 on time scales of more than 10 days. Both the temporal and spatial correspondences in trend/pattern and magnitudes between the two datasets were satisfactory, suggesting the reliability of using GDAS parameter-based reference ET for regional water and energy balance studies in many parts of the world. While the study revealed the potential of GDAS ETo for large-scale hydrological applications, site-specific use of GDAS ETo in complex hydro-climatic regions such as coastal areas and rugged terrain may require the application of bias correction and/or disaggregation of the GDAS ETo using downscaling techniques.

The capacity of radar, crowdsourced personal weather stations and commercial microwave links to monitor small scale urban rainfall

NASA Astrophysics Data System (ADS)

Uijlenhoet, R.; de Vos, L. W.; Leijnse, H.; Overeem, A.; Raupach, T. H.; Berne, A.

2017-12-01

For the purpose of urban rainfall monitoring high resolution rainfall measurements are desirable. Typically C-band radar can provide rainfall intensities at km grid cells every 5 minutes. Opportunistic sensing with commercial microwave links yields rainfall intensities over link paths within cities. Additionally, recent developments have made it possible to obtain large amounts of urban in situ measurements from weather amateurs in near real-time. With a known high resolution simulated rainfall event the accuracy of these three techniques is evaluated, taking into account their respective existing layouts and sampling methods. Under ideal measurement conditions, the weather station networks proves to be most promising. For accurate estimation with radar, an appropriate choice for Z-R relationship is vital. Though both the microwave links and the weather station networks are quite dense, both techniques will underestimate rainfall if not at least one link path / station captures the high intensity rainfall peak. The accuracy of each technique improves when considering rainfall at larger scales, especially by increasing time intervals, with the steepest improvements found in microwave links.

Analysis of weather condition influencing fire regime in Italy

NASA Astrophysics Data System (ADS)

Bacciu, Valentina; Masala, Francesco; Salis, Michele; Sirca, Costantino; Spano, Donatella

2014-05-01

Fires have a crucial role within Mediterranean ecosystems, with both negative and positive impacts on all biosphere components and with reverberations on different scales. Fire determines the landscape structure and plant composition, but it is also the cause of enormous economic and ecological damages, beside the loss of human life. In addition, several authors are in agreement suggesting that, during the past decades, changes on fire patterns have occurred, especially in terms of fire-prone areas expansion and fire season lengthening. Climate and weather are two of the main controlling agents, directly and indirectly, of fire regime influencing vegetation productivity, causing water stress, igniting fires through lightning, or modulating fire behavior through wind. On the other hand, these relationships could be not warranted in areas where most ignitions are caused by people (Moreno et al. 2009). Specific analyses of the driving forces of fire regime across countries and scales are thus still required in order to better anticipate fire seasons and also to advance our knowledge of future fire regimes. The objective of this work was to improve our knowledge of the relative effects of several weather variables on forest fires in Italy for the period 1985-2008. Meteorological data were obtained through the MARS (Monitoring Agricultural Resources) database, interpolated at 25x25 km scale. Fire data were provided by the JRC (Join Research Center) and the CFVA (Corpo Forestale e di Vigilanza Ambientale, Sardinia). A hierarchical cluster analysis, based on fire and weather data, allowed the identification of six homogeneous areas in terms of fire occurrence and climate (pyro-climatic areas). Two statistical techniques (linear and non-parametric models) were applied in order to assess if inter-annual variability in weather pattern and fire events had a significant trend. Then, through correlation analysis and multi-linear regression modeling, we investigated the influence of weather variables on fire activity across a range of time- and spatial-scales. The analysis revealed a general decrease of both number of fires and burned area, although not everywhere with the same magnitude. Overall, regression models where highly significant (p<0.001), and the explained variance ranged from 36% to 80% for fire number and from 37% to 76% for burned area, depending on pyro-climatic area. Moreover, our results contributed in determining the relative importance of climate variables acting at different timescales as control on intrinsic (i.e. flammability and moisture) and extrinsic (i.e. fuel amount and structure) characteristics of vegetation, thus strongly influencing fire occurrence. The good performance of our models, especially in the most fire affected pyro-climatic areas of Italy, and the better understanding of the main driver of fire variability gained through this work could be of great help for fire management among the different pyro-climatic areas.

Are Clay Minerals a Climate Constraint? A Review of Prior Data and New Insights on Martian "Weathering Sequences"

NASA Astrophysics Data System (ADS)

Ehlmann, B. L.; Dundar, M.

2016-12-01

Most clay minerals on Mars are Fe/Mg smectites or chlorites, which typically form from mafic protoliths in aqueous chemical systems that are relatively closed and thus require liquid water but not large amounts of water throughput and large-scale chemical leaching. They may thus form either in the subsurface or under select conditions at the surface. However, Al clay minerals, discovered in multiple locations on Mars (Arabia Terra, Northeast Syrtis, Libya Montes Terra Sirenum, Eridania, circum-Hellas, Valles Marineris) may provide evidence of substantial water throughput, if their protolith materials were basaltic. This is because formation of Al clays from a mafic protolith requires removal of Mg and either formation of accompanying Fe oxides or removal of Fe. Thus, the observed sequences of Al clays atop Fe/Mg clays were proposed to represent open system weathering and possibly a late climate optimum around the late Noachian/early Hesperian [1]. Later, they were comprehensively cataloged and reported to represent "weathering sequences" similar to those in terrestrial tropical environments [2]. However, key questions remain; in particular, how much water throughput over what time scale is required? The answer to this question has substantial bearing on the climate of early Mars. Recently, we employed a newly developed, non-parametric Bayesian algorithm [3,4] for semi-automatic identification of rare spectral classes on 139 CRISM images in areas with reported regional-scale occurrences of Al clays. Dozens of detections of the minerals alunite and jarosite were made with the algorithm and then verified by manual analysis. These sulfate hydroxides form only at low pHs, and thus their presence tightly constrains water chemistry. Here, we discuss the evidence for low pH surface waters associated with the weathering sequences and their implications for the cumulative duration of surface weathering. [1] Ehlmann et al., 2011, Nature | [2] Carter et al., 2015, Icarus | [3] Dundar et al., 2016, IEEE WHISPERS proceedings | [4] Ehlmann & Dundar, submitted

Abiotic Versus Biotic Weathering Of Olivine As Possible Biosignatures

NASA Technical Reports Server (NTRS)

Longazo, Teresa G.; Wentworth, Susan J.; Clemett, Simon J.; Southam, Gordon; McKay, David S.

2001-01-01

We are investigating the weathering of silicate minerals by both purely inorganic, and biologically mediated processes using field-emission scanning electron microscopy (FESEM) and energy dispersive x-ray spectroscopy (EDS). By resolving surface textures and chemical compositions of weathered surfaces at the sub-micron scale we hope to be able to distinguish abiotic from biotic weathering processes and so establish a new biosignature applicable to the study of astromaterials including but not limited to the Martian meteorites. Sterilized olivine grains (San Carlos, Arizona) no more than 1-2 mm in their longest dimension were optically assayed to be uniform in color and free of inclusions were selected as weathering subjects. Prior to all experiments surface morphologies and Fe/Mg ratios were determined for each grain using FE-SEM and EDS. Experiments were divided into two categories abiotic and biotic and were compared with "naturally" weathered samples. For the preliminary experiments, two trials (open and closed to the ambient laboratory environment) were performed under abiotic conditions, and three trials under biotic conditions (control, day 1 and day 2). The open system abiotic trials used sterile grains heated at 98 C and 200 C for both 24 and 48 hours in 1L double distilled de-ionized water. The closed system abiotic trials were conducted under the same conditions but in a sealed two layer steel/Teflon "bomb" apparatus. The biotic trials used sterile grains mounted in a flow-through device attached to a wellhead on the Columbia River aquifer. Several discolored, altered, grains were selected to document "natural" weathering surface textures for comparison with the experimental samples. Preliminary results indicate there are qualitative differences in weathered surface textures among all the designed experiments. The olivine grains in abiotic trials displayed etching, pitting, denticulate margins, dissolution and clay formation. The scale of the features ranged from tens to a few microns with textures that remained relatively sharp and were crystallographically controlled. These results were comparable to that observed in the "naturally" weathered comparison/reference grains. Chemical analysis by EDS indicates these textures correlated with the relative loss of Mg and Fe cations by diffusional processes. In contrast the biotic results indicated changes in the etching patterns on the scale of hundreds of nm, which are neither sharp nor crystallographically controlled (nanoetching). Organisms, organic debris and/or extracellular polymeric substances (biofilm) were often in close proximity or direct contact with the nanoetching. While there are many poorly constrained variables in natural weathering experiments to contend with, such as the time scale, the chemistry of the fluids and degree of biologic participation, some preliminary observations can be made: (1) certain distinct surface textures appear correlated with the specific processes giving rise to these textures; (2) the process of diffusing cations can produce many similar styles of surface textural changes; and (3) the main difference between abiotic and biotically produced weathering is the scale (microns versus nanometers) and the style (crystallographically versus noncrystallographically controlled) of the textural features. Further investigation into nanosize scale surface textures should attempt to quantify both textures and chemical changes of the role of microorganisms in the weathering of silicates. Additional experiments addressing nanoscale textures of shock features for comparison with the current data set.

Weather and Death on Mount Everest: Is there a link between Storms and Human Physiology?

NASA Astrophysics Data System (ADS)

Moore, K.; Semple, J.

2004-05-01

Scientific interest in Mount Everest has been largely focused on the hypoxia caused by the summit's low barometric pressure. Although weather is recognized as a significant risk factor, it has not been extensively studied. Through the use of observations made at the mountain's South Col, elevation 7986m, and other datasets, we show that high impact weather events on Mount Everest, including the May 1996 storm in which 8 climbers perished, are often associated with continental-scale intrusions of stratospheric air into the upper-troposphere. The variability in wind speeds associated with these intrusions triggered convective activity that resulted in the high impact weather. In addition, the validation of existing meteorological data allows for useful insights into the possibility of forecasting these high impact weather events and their physiological impacts thereby mitigating deaths that occur on the exposed upper slopes of Mount Everest.

2010 weather and aeolian sand-transport data from the Colorado River corridor, Grand Canyon, Arizona

USGS Publications Warehouse

Dealy, Timothy P.; East, Amy E.; Fairley, Helen C.

2014-01-01

Measurements of weather parameters and aeolian sand transport were made in 2010 near selected archeological sites in the Colorado River corridor through Grand Canyon, Arizona. Data collected in 2010 indicate event- and seasonal-scale variations in rainfall, wind, temperature, humidity, and barometric pressure. Differences in weather patterns between 2009 and 2010 included a slightly later spring windy season, greater spring precipitation and annual rainfall totals, and a later onset and length of the reduced diurnal barometric-pressure fluctuations commonly associated with summer monsoon conditions. The increase in spring precipitation was consistent with the 2010 spring El Niño conditions compared to the 2009 spring La Niña conditions, whereas the subsequent transition to an El Niño-Southern Oscillation neutral phase appeared to delay the reduction in diurnal barometric fluctuations.

A High-Resolution WRF Tropical Channel Simulation Driven by a Global Reanalysis

NASA Astrophysics Data System (ADS)

Holland, G.; Leung, L.; Kuo, Y.; Hurrell, J.

2006-12-01

Since 2003, NCAR has invested in the development and application of Nested Regional Climate Model (NRCM) based on the Weather Research and Forecasting (WRF) model and the Community Climate System Model, as a key component of the Prediction Across Scales Initiative. A prototype tropical channel model has been developed to investigate scale interactions and the influence of tropical convection on large scale circulation and tropical modes. The model was developed based on the NCAR Weather Research and Forecasting Model (WRF), configured as a tropical channel between 30 ° S and 45 ° N, wide enough to allow teleconnection effects over the mid-latitudes. Compared to the limited area domain that WRF is typically applied over, the channel mode alleviates issues with reflection of tropical modes that could result from imposing east/west boundaries. Using a large amount of available computing resources on a supercomputer (Blue Vista) during its bedding in period, a simulation has been completed with the tropical channel applied at 36 km horizontal resolution for 5 years from 1996 to 2000, with large scale circulation provided by the NCEP/NCAR global reanalysis at the north/south boundaries. Shorter simulations of 2 years and 6 months have also been performed to include two-way nests at 12 km and 4 km resolution, respectively, over the western Pacific warm pool, to explicitly resolve tropical convection in the Maritime Continent. The simulations realistically captured the large-scale circulation including the trade winds over the tropical Pacific and Atlantic, the Australian and Asian monsoon circulation, and hurricane statistics. Preliminary analysis and evaluation of the simulations will be presented.

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.

A study on the integrity and authentication of weather observation data using Identity Based Encryption.

PubMed

Seo, Jung Woo; Lee, Sang Jin

2016-01-01

Weather information provides a safe working environment by contributing to the economic activity of the nation, and plays role of the prevention of natural disasters, which can cause large scaled casualties and damage of property. Especially during times of war, weather information plays a more important role than strategy, tactics and information about trends of the enemy. Also, it plays an essential role for the taking off and landing of fighter jet and the sailing of warships. If weather information, which plays a major role in national security and economy, gets misused for cyber terrorism resulting false weather information, it could be a huge threat for national security and the economy. We propose a plan to safely transmit the measured value from meteorological sensors through a meteorological telecommunication network in order to guarantee the confidentiality and integrity of the data despite cyber-attacks. Also, such a plan allows one to produce reliable weather forecasts by performing mutual authentication through authentication devices. To make sure of this, one can apply an Identity Based Signature to ensure the integrity of measured data, and transmit the encrypted weather information with mutual authentication about the authentication devices. There are merits of this research: It is not necessary to manage authentication certificates unlike the Public Key Infrastructure methodology, and it provides a powerful security measure with the capability to be realized in a small scale computing environment, such as the meteorological observation system due to the low burden on managing keys.

Development of a Global Fire Weather Database

NASA Technical Reports Server (NTRS)

Field, R. D.; Spessa, A. C.; Aziz, N. A.; Camia, A.; Cantin, A.; Carr, R.; de Groot, W. J.; Dowdy, A. J.; Flannigan, M. D.; Manomaiphiboon, K.;

Maple sugaring with vacuum pumping during the fall season

Treesearch

H. Clay Smith; Alan G., Jr. Snow

1971-01-01

Vacuum pumping of sugar maple trees during the late fall and early winter months is not advisable in northern Vermont. However, fall pumping may be profitable in other areas of the sugar maple range. It is recommended that the weather pattern in a given locale be observed; and if conditions are favorable, vacuum pumping should be tried on a small scale before...

A new Method for the Estimation of Initial Condition Uncertainty Structures in Mesoscale Models

NASA Astrophysics Data System (ADS)

Keller, J. D.; Bach, L.; Hense, A.

2012-12-01

The estimation of fast growing error modes of a system is a key interest of ensemble data assimilation when assessing uncertainty in initial conditions. Over the last two decades three methods (and variations of these methods) have evolved for global numerical weather prediction models: ensemble Kalman filter, singular vectors and breeding of growing modes (or now ensemble transform). While the former incorporates a priori model error information and observation error estimates to determine ensemble initial conditions, the latter two techniques directly address the error structures associated with Lyapunov vectors. However, in global models these structures are mainly associated with transient global wave patterns. When assessing initial condition uncertainty in mesoscale limited area models, several problems regarding the aforementioned techniques arise: (a) additional sources of uncertainty on the smaller scales contribute to the error and (b) error structures from the global scale may quickly move through the model domain (depending on the size of the domain). To address the latter problem, perturbation structures from global models are often included in the mesoscale predictions as perturbed boundary conditions. However, the initial perturbations (when used) are often generated with a variant of an ensemble Kalman filter which does not necessarily focus on the large scale error patterns. In the framework of the European regional reanalysis project of the Hans-Ertel-Center for Weather Research we use a mesoscale model with an implemented nudging data assimilation scheme which does not support ensemble data assimilation at all. In preparation of an ensemble-based regional reanalysis and for the estimation of three-dimensional atmospheric covariance structures, we implemented a new method for the assessment of fast growing error modes for mesoscale limited area models. The so-called self-breeding is development based on the breeding of growing modes technique. Initial perturbations are integrated forward for a short time period and then rescaled and added to the initial state again. Iterating this rapid breeding cycle provides estimates for the initial uncertainty structure (or local Lyapunov vectors) given a specific norm. To avoid that all ensemble perturbations converge towards the leading local Lyapunov vector we apply an ensemble transform variant to orthogonalize the perturbations in the sub-space spanned by the ensemble. By choosing different kind of norms to measure perturbation growth, this technique allows for estimating uncertainty patterns targeted at specific sources of errors (e.g. convection, turbulence). With case study experiments we show applications of the self-breeding method for different sources of uncertainty and different horizontal scales.

Measuring horizontal atmospheric turbulence at ground level from optical turbulence generator (OTG) using a 1D sensor

NASA Astrophysics Data System (ADS)

Tíjaro Rojas, Omar J.; Torres Moreno, Yezid; Rhodes, William T.

2017-06-01

Different theories including Kolmogorov have been valid to explain and model physic phenomenal like vertical atmospheric turbulence. In horizontal path, we still have many questions, due to weather problems and consequences that it generates. To emulate some conditions of environment, we built an Optical Turbulence Generator (OTG) having spatial, humidity and temperature, measurements that were captured in the same time from optical synchronization. This development was made using digital modules as ADC (Analog to Digital Converters) and communications protocol as SPI. We all made from microcontrollers. On the other hand, to measure optical signal, we used a photomultiplier tube (PMT) where captured the intensity of fringes that shifted with a known frequency. Outcomes show temporal shift and phase drive from dependent samples (in time domain) that correspond with frozen turbulence given by Taylor theory. Parameters studied were C2n, scintillation and inner scale in temporal patterns and analysis of their relationship with the physical associated variables. These patterns were taken from Young Interferometer in laboratory room scale. In the future, we hope with these studies, we will can implement an experiment to characterize atmospheric turbulence in a long distance, placed in the equatorial weather zone.

Evolution of porosity and diffusivity associated with chemical weathering of a basalt clast

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

Navarre-Sitchler, A.; Steefel, C.I.; Yang, L.

Weathering of rocks as a result of exposure to water and the atmosphere can cause significant changes in their chemistry and porosity. In low-porosity rocks, such as basalts, changes in porosity, resulting from chemical weathering, are likely to modify the rock's effective diffusivity and permeability, affecting the rate of solute transport and thus potentially the rate of overall weathering to the extent that transport is the rate limiting step. Changes in total porosity as a result of mineral dissolution and precipitation have typically been used to calculate effective diffusion coefficients through Archie's law for reactive transport simulations of chemical weathering,more » but this approach fails to account for unconnected porosity that does not contribute to transport. In this study, we combine synchrotron X-ray microcomputed tomography ({mu}CT) and laboratory and numerical diffusion experiments to examine changes in both total and effective porosity and effective diffusion coefficients across a weathering interface in a weathered basalt clast from Costa Rica. The {mu}CT data indicate that below a critical value of {approx}9%, the porosity is largely unconnected in the basalt clast. The {mu}CT data were further used to construct a numerical pore network model to determine upscaled, effective diffusivities as a function of total porosity (ranging from 3 to 30%) for comparison with diffusivities determined in laboratory tracer experiments. By using effective porosity as the scaling parameter and accounting for critical porosity, a model is developed that accurately predicts continuum-scale effective diffusivities across the weathering interface of the basalt clast.« less

Evaluating impacts of different longitudinal driver assistance systems on reducing multi-vehicle rear-end crashes during small-scale inclement weather.

PubMed

Li, Ye; Xing, Lu; Wang, Wei; Wang, Hao; Dong, Changyin; Liu, Shanwen

2017-10-01

Multi-vehicle rear-end (MVRE) crashes during small-scale inclement (SSI) weather cause high fatality rates on freeways, which cannot be solved by traditional speed limit strategies. This study aimed to reduce MVRE crash risks during SSI weather using different longitudinal driver assistance systems (LDAS). The impact factors on MVRE crashes during SSI weather were firstly analyzed. Then, four LDAS, including Forward collision warning (FCW), Autonomous emergency braking (AEB), Adaptive cruise control (ACC) and Cooperative ACC (CACC), were modeled based on a unified platform, the Intelligent Driver Model (IDM). Simulation experiments were designed and a large number of simulations were then conducted to evaluate safety effects of different LDAS. Results indicate that the FCW and ACC system have poor performance on reducing MVRE crashes during SSI weather. The slight improvement of sight distance of FCW and the limitation of perception-reaction time of ACC lead the failure of avoiding MVRE crashes in most scenarios. The AEB system has the better effect due to automatic perception and reaction, as well as performing the full brake when encountering SSI weather. The CACC system has the best performance because wireless communication provides a larger sight distance and a shorter time delay at the sub-second level. Sensitivity analyses also indicated that the larger number of vehicles and speed changes after encountering SSI weather have negative impacts on safety performances. Results of this study provide useful information for accident prevention during SSI weather. Copyright © 2017 Elsevier Ltd. All rights reserved.

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

A landscape scale decision support tool for monitoring bird and bat migration across Wisconsin

USGS Publications Warehouse

Suarez, Manuel J.; Heglund, Patricia J.; Kratt, Robert; Kirsch, Eileen

2008-01-01

This project was initiated to begin addressing the question, “Are there patterns in timing, location, and direction among migrating landbirds?” that have been at the forefront of discussion with our Federal, State, and County partners with regard to siting wind energy projects. Our goal was to explore the use of Nexrad weather data to see if examining 5 or more years’ worth of data would provide us with a sense of the general timing, movement patterns and habitat use by migrating landbirds.

Large-scale Meteorological Patterns Associated with Extreme Precipitation Events over Portland, OR

NASA Astrophysics Data System (ADS)

Aragon, C.; Loikith, P. C.; Lintner, B. R.; Pike, M.

2017-12-01

Extreme precipitation events can have profound impacts on human life and infrastructure, with broad implications across a range of stakeholders. Changes to extreme precipitation events are a projected outcome of climate change that warrants further study, especially at regional- to local-scales. While global climate models are generally capable of simulating mean climate at global-to-regional scales with reasonable skill, resiliency and adaptation decisions are made at local-scales where most state-of-the-art climate models are limited by coarse resolution. Characterization of large-scale meteorological patterns associated with extreme precipitation events at local-scales can provide climatic information without this scale limitation, thus facilitating stakeholder decision-making. This research will use synoptic climatology as a tool by which to characterize the key large-scale meteorological patterns associated with extreme precipitation events in the Portland, Oregon metro region. Composite analysis of meteorological patterns associated with extreme precipitation days, and associated watershed-specific flooding, is employed to enhance understanding of the climatic drivers behind such events. The self-organizing maps approach is then used to characterize the within-composite variability of the large-scale meteorological patterns associated with extreme precipitation events, allowing us to better understand the different types of meteorological conditions that lead to high-impact precipitation events and associated hydrologic impacts. A more comprehensive understanding of the meteorological drivers of extremes will aid in evaluation of the ability of climate models to capture key patterns associated with extreme precipitation over Portland and to better interpret projections of future climate at impact-relevant scales.

Moderate to heavy cold-weather precipitation occurrences in Tehran and the associated circulation types

NASA Astrophysics Data System (ADS)

Khansalari, Sakineh; Raziei, Tayeb; Mohebalhojeh, Ali Reza; Ahmadi-Givi, Farhang

2018-02-01

Large-scale atmospheric circulations associated with 133 moderate to heavy cold-weather precipitation events recorded at Mehrabad station in Tehran, Iran, during the period 1951-2013 are analysed. To this end, the performance of un-rotated, orthogonally rotated and obliquely rotated solutions of T-mode principal component analysis (PCA) is examined in classifying the atmospheric circulations into a few representative circulation types (CTs). The T-mode PCAs were applied to the 500-hPa geopotential height for the events in a domain from 10∘E to 70∘E and from 20∘N to 50∘N. The first six leading principal components were retained and then orthogonally and obliquely rotated using varimax and promax solutions, respectively. Statistical inter-comparison of the CTs obtained using the three solutions suggests that the obliquely rotated solution is the better choice for circulation classification in the present study. The six CTs obtained using the oblique rotation were then linked to the daily total precipitation and daily mean temperature variability at Tehran station as well as to the standardized anomalies of the daily total precipitation and mean daily temperature of a dense network of stations distributed across Iran. It is found that the CTs identified, though generally comparable in producing significant precipitation in Tehran, vary in their potential to bring cold weather and generate snowfall in Tehran specifically and in the country in general. While the first three CTs give rise to regional patterns of standardized precipitation anomalies centred in Tehran, the next three CTs leave a pronounced precipitation signature almost across the whole country. As regards the standardized temperature anomalies, with the exception of one CT that causes deep and widespread negative standardized anomalies over most parts of the country, the other CTs are characterized with a dipolar structure of a deep intrusion of cold weather to the west and prevailing warm weather to the east of the country.

Euro-Climhist - a data platform for weather-, climate- and disaster history

NASA Astrophysics Data System (ADS)

Pfister, Christian

2017-04-01

The Euro-Climhist data base (http://www.euroclimhist.unibe.ch/de)/ presents evidence about weather and climate in space and time mostly originating from the archives of societies. It facilitates the cross-checking of proxy data with contemporaneous high-resolution narrative weather reports. Contemporary and non-contemporary data are distinguished for quality control. The original Euro-Climhist database was established between 1992 and 1994 to investigate weather patterns in Europe during the cold period of the late Maunder Minimum (1675-1715). The present-day internet version of Euro-Climhist went online in November 2015 with the Module Switzerland. It currently provides 160'000 records from 1501 to present, available in German, French, Italian and English. The module serves as a pilot project for developing an adequate methodology and user-friendly software. Currently a module "Middle Ages" led by Christian Rohr from the Bern University is being worked out. It includes evidence for the whole of Europe prior to 1501. Further modules may be established by regional working groups. The classification scheme includes 300 categories. A complementary facility—COMP—has been also been created to permit a still more precise description of events. For example, the facility can be used to describe in detail the impacts of nature-induced hazards. Moreover, it makes possible to rate quantitative evidence such as phenological data or the frequency of rain-days at a given location according to standard criteria. The elements of COMP are translated and can be augmented to an almost unlimited extent. The data are mapped according to the administrative organization of a country and to geographical units. Results are presented in the form of text and geographical charts. The structure of Euro-Climhist may be readily adapted to amplifications in relationship to content, spatial dimension and translation into further languages. In the long term, it may be possible to release evidence on weather and climate on a large scale, in order to improve knowledge of interconnections between humans and climate.

Streamflow prediction using multi-site rainfall obtained from hydroclimatic teleconnection

NASA Astrophysics Data System (ADS)

Kashid, S. S.; Ghosh, Subimal; Maity, Rajib

2010-12-01

SummarySimultaneous variations in weather and climate over widely separated regions are commonly known as "hydroclimatic teleconnections". Rainfall and runoff patterns, over continents, are found to be significantly teleconnected, with large-scale circulation patterns, through such hydroclimatic teleconnections. Though such teleconnections exist in nature, it is very difficult to model them, due to their inherent complexity. Statistical techniques and Artificial Intelligence (AI) tools gain popularity in modeling hydroclimatic teleconnection, based on their ability, in capturing the complicated relationship between the predictors (e.g. sea surface temperatures) and predictand (e.g., rainfall). Genetic Programming is such an AI tool, which is capable of capturing nonlinear relationship, between predictor and predictand, due to its flexible functional structure. In the present study, gridded multi-site weekly rainfall is predicted from El Niño Southern Oscillation (ENSO) indices, Equatorial Indian Ocean Oscillation (EQUINOO) indices, Outgoing Longwave Radiation (OLR) and lag rainfall at grid points, over the catchment, using Genetic Programming. The predicted rainfall is further used in a Genetic Programming model to predict streamflows. The model is applied for weekly forecasting of streamflow in Mahanadi River, India, and satisfactory performance is observed.

Contribution of the infrasound technology to characterize large scale atmospheric disturbances and impact on infrasound monitoring

NASA Astrophysics Data System (ADS)

Blanc, Elisabeth; Le Pichon, Alexis; Ceranna, Lars; Pilger, Christoph; Charlton Perez, Andrew; Smets, Pieter

2016-04-01

The International Monitoring System (IMS) developed for the verification of the Comprehensive nuclear-Test-Ban Treaty (CTBT) provides a unique global description of atmospheric disturbances generating infrasound such as extreme events (e.g. meteors, volcanoes, earthquakes, and severe weather) or human activity (e.g. explosions and supersonic airplanes). The analysis of the detected signals, recorded at global scales and over near 15 years at some stations, demonstrates that large-scale atmospheric disturbances strongly affect infrasound propagation. Their time scales vary from several tens of minutes to hours and days. Their effects are in average well resolved by the current model predictions; however, accurate spatial and temporal description is lacking in both weather and climate models. This study reviews recent results using the infrasound technology to characterize these large scale disturbances, including (i) wind fluctuations induced by gravity waves generating infrasound partial reflections and modifications of the infrasound waveguide, (ii) convection from thunderstorms and mountain waves generating gravity waves, (iii) stratospheric warming events which yield wind inversions in the stratosphere, (iv)planetary waves which control the global atmospheric circulation. Improved knowledge of these disturbances and assimilation in future models is an important objective of the ARISE (Atmospheric dynamics Research InfraStructure in Europe) project. This is essential in the context of the future verification of the CTBT as enhanced atmospheric models are necessary to assess the IMS network performance in higher resolution, reduce source location errors, and improve characterization methods.

Decadal-Scale Forecasting of Climate Drivers for Marine Applications.

PubMed

Salinger, J; Hobday, A J; Matear, R J; O'Kane, T J; Risbey, J S; Dunstan, P; Eveson, J P; Fulton, E A; Feng, M; Plagányi, É E; Poloczanska, E S; Marshall, A G; Thompson, P A

Climate influences marine ecosystems on a range of time scales, from weather-scale (days) through to climate-scale (hundreds of years). Understanding of interannual to decadal climate variability and impacts on marine industries has received less attention. Predictability up to 10 years ahead may come from large-scale climate modes in the ocean that can persist over these time scales. In Australia the key drivers of climate variability affecting the marine environment are the Southern Annular Mode, the Indian Ocean Dipole, the El Niño/Southern Oscillation, and the Interdecadal Pacific Oscillation, each has phases that are associated with different ocean circulation patterns and regional environmental variables. The roles of these drivers are illustrated with three case studies of extreme events-a marine heatwave in Western Australia, a coral bleaching of the Great Barrier Reef, and flooding in Queensland. Statistical and dynamical approaches are described to generate forecasts of climate drivers that can subsequently be translated to useful information for marine end users making decisions at these time scales. Considerable investment is still needed to support decadal forecasting including improvement of ocean-atmosphere models, enhancement of observing systems on all scales to support initiation of forecasting models, collection of important biological data, and integration of forecasts into decision support tools. Collaboration between forecast developers and marine resource sectors-fisheries, aquaculture, tourism, biodiversity management, infrastructure-is needed to support forecast-based tactical and strategic decisions that reduce environmental risk over annual to decadal time scales. © 2016 Elsevier Ltd. All rights reserved.

Air pressure waves from Mount St. Helens eruptions

NASA Astrophysics Data System (ADS)

Reed, Jack W.

1987-10-01

Infrasonic recordings of the pressure wave from the Mount St. Helens (MSH) eruption on May 18, 1980, together with the weather station barograph records were used to estimate an equivalent explosion airblast yield for this eruption. Pressure wave amplitudes versus distance patterns were found to be comparable with patterns found for a small-scale nuclear explosion, the Krakatoa eruption, and the Tunguska comet impact, indicating that the MSH wave came from an explosion equivalent of about 5 megatons of TNT. The peculiar audibility pattern reported, with the blast being heard only at ranges beyond about 100 km, is explained by consideration of finite-amplitude shock propagation developments.

High-frequency and meso-scale winter sea-ice variability in the Southern Ocean in a high-resolution global ocean model

NASA Astrophysics Data System (ADS)

Stössel, Achim; von Storch, Jin-Song; Notz, Dirk; Haak, Helmuth; Gerdes, Rüdiger

2018-03-01

This study is on high-frequency temporal variability (HFV) and meso-scale spatial variability (MSV) of winter sea-ice drift in the Southern Ocean simulated with a global high-resolution (0.1°) sea ice-ocean model. Hourly model output is used to distinguish MSV characteristics via patterns of mean kinetic energy (MKE) and turbulent kinetic energy (TKE) of ice drift, surface currents, and wind stress, and HFV characteristics via time series of raw variables and correlations. We find that (1) along the ice edge, the MSV of ice drift coincides with that of surface currents, in particular such due to ocean eddies; (2) along the coast, the MKE of ice drift is substantially larger than its TKE and coincides with the MKE of wind stress; (3) in the interior of the ice pack, the TKE of ice drift is larger than its MKE, mostly following the TKE pattern of wind stress; (4) the HFV of ice drift is dominated by weather events, and, in the absence of tidal currents, locally and to a much smaller degree by inertial oscillations; (5) along the ice edge, the curl of the ice drift is highly correlated with that of surface currents, mostly reflecting the impact of ocean eddies. Where ocean eddies occur and the ice is relatively thin, ice velocity is characterized by enhanced relative vorticity, largely matching that of surface currents. Along the ice edge, ocean eddies produce distinct ice filaments, the realism of which is largely confirmed by high-resolution satellite passive-microwave data.

Modelling wildfire activity in Iberia with different Atmospheric Circulation WTs

NASA Astrophysics Data System (ADS)

Sousa, P. M.; Trigo, R.; Pereira, M. G.; Rasilla, D.; Gouveia, C.

2012-04-01

This work focuses on the spatial and temporal variability of burnt area (BA) for the entire Iberian Peninsula (IP) and on the construction of statistical models to reproduce the inter-annual variability, based on Weather Types Classification (WTC). A common BA dataset was assembled for the first time for the entire Iberian Peninsula, by merging BA records for the 66 administrative regions of Portugal and Spain. A normalization procedure was then applied to the various size regions before performing a k-means cluster analysis to identify large areas characterized by similar fire regimes. The most compelling results were obtained for 4 clusters (Northwestern, Northern, Southwestern and Eastern) whose spatial patterns and seasonal fire regimes are shown to be related with constraining factors such as topography, vegetation cover and climate conditions. The response of fire burnt surface at monthly time scales to both long-term climatic pre-conditions and short-term synoptic forcing was assessed through correlation and regression analysis using: (i) temperature and precipitation from 2 to 7 months in advance to fire peak season; (ii) synoptic weather patterns derived from 11 distinct classifications derived under the COSTaction-733. Different responses were obtained for each of the considered regions: (i) a relevant link between BA and short-term synoptic forcing (represented by monthly frequencies of WTC) was identified for all clusters; (ii) long-term climatic preconditioning was relevant for all but one cluster (Northern). Taking into account these links, we developed stepwise regression models with the aim of reproducing the observed BA series (i.e. in hindcast mode). These models were based on the best climatic and synoptic circulation predictors identified previously. All models were cross-validated and their performance varies between clusters, though models exclusively based on WTCs tend to better reproduce annual BA time series than those only based on pre-conditioning climatic information. Nevertheless, the best results are attained when both synoptic and climatic predictors are used simultaneously as predictors, in particular for the two western clusters, where correlation coefficient values are higher than 0.7. Finally, we have used WTC composite maps to characterize the typical synoptic configurations that favor high values of BA. These patterns correspond to dry and warm fluxes, associated with anticyclonic regimes, which foster fire ignition (Pereira et al., 2005). Pereira, M.G., Trigo, R.M., DaCamara, C.C., Pereira, J.M.C., Leite, S.M., 2005: "Synoptic patterns associated with large summer forest fires in Portugal". Agricultural and Forest Meteorology. 129, 11-25. COST733, 2011: "COST 733 Wiki - Harmonisation and Applications of Weather Type Classifications for European regions or COST733 spatial domains for Europe". Available at http://geo21.geo.uni-augsburg.de/cost733wiki/Cost733_Wiki_Main [accessed 1 September 2011].

Atmospheric conditions create freeways, detours and tailbacks for migrating birds.

PubMed

Shamoun-Baranes, Judy; Liechti, Felix; Vansteelant, Wouter M G

2017-07-01

The extraordinary adaptations of birds to contend with atmospheric conditions during their migratory flights have captivated ecologists for decades. During the 21st century technological advances have sparked a revival of research into the influence of weather on migrating birds. Using biologging technology, flight behaviour is measured across entire flyways, weather radar networks quantify large-scale migratory fluxes, citizen scientists gather observations of migrant birds and mechanistic models are used to simulate migration in dynamic aerial environments. In this review, we first introduce the most relevant microscale, mesoscale and synoptic scale atmospheric phenomena from the point of view of a migrating bird. We then provide an overview of the individual responses of migrant birds (when, where and how to fly) in relation to these phenomena. We explore the cumulative impact of individual responses to weather during migration, and the consequences thereof for populations and migratory systems. In general, individual birds seem to have a much more flexible response to weather than previously thought, but we also note similarities in migratory behaviour across taxa. We propose various avenues for future research through which we expect to derive more fundamental insights into the influence of weather on the evolution of migratory behaviour and the life-history, population dynamics and species distributions of migrant birds.

The interannual variability of the Haines Index over North America

Treesearch

Lejiang Yu; Shiyuan Zhong; Xindi Bian; Warren E. Heilman; Joseph J. Charney

2013-01-01

The Haines index (HI) is a fire-weather index that is widely used as an indicator of the potential for dry, low-static-stability air in the lower atmosphere to contribute to erratic fire behavior or large fire growth. This study examines the interannual variability of HI over North America and its relationship to indicators of large-scale circulation anomalies. The...

Weather and headache onset: a large-scale study of headache medicine purchases

NASA Astrophysics Data System (ADS)

Ozeki, Kayoko; Noda, Tatsuya; Nakamura, Mieko; Ojima, Toshiyuki

2015-04-01

It is widely recognized that weather changes can trigger headache onset. Most people who develop headaches choose to self-medicate rather than visit a hospital or clinic. We investigated the association between weather and headache onset using large-sample sales of the headache medicine, loxoprofen. We collected daily sales figures of loxoprofen and over-the-counter drugs over a 1-year period from a drugstore chain in western Shizuoka prefecture, Japan. To adjust for changes in daily sales of loxoprofen due to social environmental factors, we calculated a proportion of loxoprofen daily sales to over-the-counter drug daily sales. At the same time, we obtained weather data for the study region from the website of the Japan Meteorological Agency. We performed linear regression analysis to ascertain the association between weather conditions and the loxoprofen daily sales proportion. We also conducted a separate questionnaire survey at the same drugstores to determine the reason why people purchased loxoprofen. Over the study period, we surveyed the sale of hundreds of thousands of loxoprofen tablets. Most people purchased loxoprofen because they had a headache. We found that the sales proportion of loxoprofen increased when average barometric pressure decreased, and that precipitation, average humidity, and minimum humidity increased on loxoprofen purchase days compared to the previous day of purchases. This study, performed using a large dataset that was easy-to-collect and representative of the general population, revealed that sales of loxoprofen, which can represent the onset and aggravation of headache, significantly increased with worsening weather conditions.

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 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.

Dynamical complexity detection in geomagnetic activity indices using wavelet transforms and Tsallis entropy

NASA Astrophysics Data System (ADS)

Balasis, G.; Daglis, I. A.; Papadimitriou, C.; Kalimeri, M.; Anastasiadis, A.; Eftaxias, K.

2008-12-01

Dynamical complexity detection for output time series of complex systems is one of the foremost problems in physics, biology, engineering, and economic sciences. Especially in magnetospheric physics, accurate detection of the dissimilarity between normal and abnormal states (e.g. pre-storm activity and magnetic storms) can vastly improve space weather diagnosis and, consequently, the mitigation of space weather hazards. Herein, we examine the fractal spectral properties of the Dst data using a wavelet analysis technique. We show that distinct changes in associated scaling parameters occur (i.e., transition from anti- persistent to persistent behavior) as an intense magnetic storm approaches. We then analyze Dst time series by introducing the non-extensive Tsallis entropy, Sq, as an appropriate complexity measure. The Tsallis entropy sensitively shows the complexity dissimilarity among different "physiological" (normal) and "pathological" states (intense magnetic storms). The Tsallis entropy implies the emergence of two distinct patterns: (i) a pattern associated with the intense magnetic storms, which is characterized by a higher degree of organization, and (ii) a pattern associated with normal periods, which is characterized by a lower degree of organization.

Large-scale risk assessment of polycyclic aromatic hydrocarbons in shoreline sediments from Saudi Arabia: environmental legacy after twelve years of the Gulf war oil spill.

PubMed

Bejarano, Adriana C; Michel, Jacqueline

2010-05-01

A large-scale assessment of polycyclic aromatic hydrocarbons (PAHs) from the 1991 Gulf War oil spill was performed for 2002-2003 sediment samples (n = 1679) collected from habitats along the shoreline of Saudi Arabia. Benthic sediment toxicity was characterized using the Equilibrium Partitioning Sediment Benchmark Toxic Unit approach for 43 PAHs (ESBTU(FCV,43)). Samples were assigned to risk categories according to ESBTU(FCV,43) values: no-risk (< or = 1), low (>1 - < or = 2), low-medium (>2 - < or = 3), medium (>3 - < or = 5) and high-risk (>5). Sixty seven percent of samples had ESBTU(FCV,43) > 1 indicating potential adverse ecological effects. Sediments from the 0-30 cm layer from tidal flats, and the >30 - <60 cm layer from heavily oiled halophytes and mangroves had high frequency of high-risk samples. No-risk samples were characterized by chrysene enrichment and depletion of lighter molecular weight PAHs, while high-risk samples showed little oil weathering and PAH patterns similar to 1993 samples. North of Safaniya sediments were not likely to pose adverse ecological effects contrary to sediments south of Tanaqib. Landscape and geomorphology has played a role on the distribution and persistence in sediments of oil from the Gulf War. Copyright 2009 Elsevier Ltd. All rights reserved.

Geochemistry of loess-paleosol sediments of Kashmir Valley, India: Provenance and weathering

NASA Astrophysics Data System (ADS)

Ahmad, Ishtiaq; Chandra, Rakesh

2013-04-01

Middle to Late Pleistocene loess-paleosol sediments of Kashmir Valley, India, were analyzed for major, trace and REE elements in order to determine their chemical composition, provenance and intensity of palaeo-weathering of the source rocks. These sediments are generally enriched with Fe2O3, MgO, MnO, TiO2, Y, Ni, Cu, Zn, Th, U, Sc, V and Co while contents of SiO2, K2O, Na2O, P2O5, Sr, Nb and Hf are lower than the UCC. Chondrite normalized REE patterns are characterized by moderate enrichment of LREEs, relatively flat HREE pattern (GdCN/YbCN = 1.93-2.31) and lack of prominent negative Eu anomaly (Eu/Eu* = 0.73-1.01, average = 0.81). PAAS normalized REE are characterized by slightly higher LREE, depleted HREE and positive Eu anomaly. Various provenance discrimination diagrams reveal that the Kashmir Loess-Paleosol sediments are derived from the mixed source rocks suggesting large provenance with variable geological settings, which apparently have undergone weak to moderate recycling processes. Weathering indices such as CIA, CIW and PIA values (71.87, 83.83 and 80.57 respectively) and A-CN-K diagram imply weak to moderate weathering of the source material.

Development of thunderstorm monitoring technologies and algorithms by integration of radar, sensors, and satellite images

NASA Astrophysics Data System (ADS)

Adzhieva, Aida A.; Shapovalov, Vitaliy A.; Boldyreff, Anton S.

2017-10-01

In the context of rising the frequency of natural disasters and catastrophes humanity has to develop methods and tools to ensure safe living conditions. Effectiveness of preventive measures greatly depends on quality and lead time of the forecast of disastrous natural phenomena, which is based on the amount of knowledge about natural hazards, their causes, manifestations, and impact. To prevent them it is necessary to get complete and comprehensive information about the extent of spread and severity of natural processes that can act within a defined territory. For these purposes the High Mountain Geophysical Institute developed the automated workplace for mining, analysis and archiving of radar, satellite, lightning sensors information and terrestrial (automatic weather station) weather data. The combination and aggregation of data from different sources of meteorological data provides a more informativity of the system. Satellite data shows the global cloud region in visible and infrared ranges, but have an uncertainty in terms of weather events and large time interval between the two periods of measurements, which complicates the use of this information for very short range forecasts of weather phenomena. Radar and lightning sensors data provide the detection of weather phenomena and their localization on the background of the global pattern of cloudiness in the region and have a low period measurement of atmospheric phenomena (hail, thunderstorms, showers, squalls, tornadoes). The authors have developed the improved algorithms for recognition of dangerous weather phenomena, based on the complex analysis of incoming information using the mathematical apparatus of pattern recognition.

Variations in Global Precipitation: Climate-scale to Floods

NASA Technical Reports Server (NTRS)

Adler, Robert

2006-01-01

Variations in global precipitation from climate-scale to small scale are examined using satellite-based analyses of the Global Precipitation Climatology Project (GPCP) and information from the Tropical Rainfall Measuring Mission (TRMM). Global and large regional rainfall variations and possible long-term changes are examined using the 27- year (1979-2005) monthly dataset from the GPCP. In addition to global patterns associated with phenomena such as ENSO, the data set is explored for evidence of longterm change. Although the global change of precipitation in the data set is near zero, the data set does indicate a small upward trend in the Tropics (25S-25N), especially over ocean. Techniques are derived to isolate and eliminate variations due to ENS0 and major volcanic eruptions and the significance of the trend is examined. The status of TRMM estimates is examined in terms of evaluating and improving the long-term global data set. To look at rainfall variations on a much smaller scale TRMM data is used in combination with observations from other satellites to produce a 3-hr resolution, eight-year data set for examination of weather events and for practical applications such as detecting floods. Characteristics of the data set are presented and examples of recent flood events are examined.

North Atlantic SST Patterns and NAO Flavors

NASA Astrophysics Data System (ADS)

Rousi, E.; Rahmstorf, S.; Coumou, D.

2017-12-01

North Atlantic SST variability results from the interaction of atmospheric and oceanic processes. The North Atlantic Oscillation (NAO) drives changes in SST patterns but is also driven by them on certain time-scales. These interactions are not very well understood and might be affected by anthropogenic climate change. Paleo reconstructions indicate a slowdown of the Atlantic Meridional Overturning Circulation (AMOC) in recent decades leading to a pronounced cold anomaly ("cold blob") in the North Atlantic (Rahmstorf et al., 2015). The latter may favor NAO to be in its negative mode. In this work, sea surface temperature (SST) patterns are studied in relation to NAO variations, with the aim of discovering preferred states and understanding their interactions. SST patterns are analyzed with Self-Organizing Maps (SOM), a clustering technique that helps identify different spatial patterns and their temporal evolution. NAO flavors refer to different longitudinal positions and tilts of the NAO action centers, also defined with SOMs. This way the limitations of the basic, index-based, NAO-definition are overcome, and the method handles different spatially shapes associated with NAO. Preliminary results show the existence of preferred combinations of SSTs and NAO flavors, which in turn affect weather and climate of Europe and North America. The possible influence of the cold blob on European weather is discussed.

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.

Rock cities, periglacial mass-wasting, and honeycomb weathering in Warren County, northwestern Pennsylvania

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

Inners, J.D.; Sevon, W.D.; Moore, M.E.

1993-03-01

Imposing hilltop rock-cities developed from widely jointed outcrops of Olean conglomerate (Lower Pennsylvanian) create picturesque scenery on the Allegheny High Plateau in Warren Co., Pa. At least six such rock cities 2 to 5 acres in extent are associated with the Late Wisconsinan glacial border in the northern half of the county. Farther to the south, jumbled Olean and Knapp (Lower Mississippian) joint blocks occur on steep slopes below valley-wall cliffs. The rock cities and accumulations of displaced joint blocks are largely relics of Late Wisconsinan periglacial mass-wasting. Frost splitting initiated opening of bedrock joints to form buildings. Gravity, soilmore » wedging, and possibly gelifluction then widened the fissures into streets. Gelifluction moved blocks downslope and oriented their long axes parallel with slope (Warren Rocks). Forward toppling of high, unstable blocks contributed to mass-movement on some steep slopes (Rimrock). Today, rock cities and downslope blocks are stable in areas of gentle (less than 10 percent) slopes, but toppling, solifluction, creep, and debris flows cause continued slow movement of large blocks on moderately steep to steep (greater than 30 percent) slopes. Blocks of Olean and Knapp conglomerate have both stratabound pitting and intricate honeycomb weathering. Deep pitting is controlled largely by variations in silica cementation. Honeycomb weathering is most evident in sandy layers and results from patterns of iron-oxide impregnation. Both are Holocene surface-weathering processes.« less

Coronal mass ejections and their sheath regions in interplanetary space

NASA Astrophysics Data System (ADS)

Kilpua, Emilia; Koskinen, Hannu E. J.; Pulkkinen, Tuija I.

2017-11-01

Interplanetary coronal mass ejections (ICMEs) are large-scale heliospheric transients that originate from the Sun. When an ICME is sufficiently faster than the preceding solar wind, a shock wave develops ahead of the ICME. The turbulent region between the shock and the ICME is called the sheath region. ICMEs and their sheaths and shocks are all interesting structures from the fundamental plasma physics viewpoint. They are also key drivers of space weather disturbances in the heliosphere and planetary environments. ICME-driven shock waves can accelerate charged particles to high energies. Sheaths and ICMEs drive practically all intense geospace storms at the Earth, and they can also affect dramatically the planetary radiation environments and atmospheres. This review focuses on the current understanding of observational signatures and properties of ICMEs and the associated sheath regions based on five decades of studies. In addition, we discuss modelling of ICMEs and many fundamental outstanding questions on their origin, evolution and effects, largely due to the limitations of single spacecraft observations of these macro-scale structures. We also present current understanding of space weather consequences of these large-scale solar wind structures, including effects at the other Solar System planets and exoplanets. We specially emphasize the different origin, properties and consequences of the sheaths and ICMEs.

Problems in evaluating regional and local trends in temperature: An example from eastern Colorado, USA

USGS Publications Warehouse

Pielke, R.A.; Stohlgren, T.; Schell, L.; Parton, W.; Doesken, N.; Redmond, K.; Moeny, J.; McKee, T.; Kittel, T.G.F.

2002-01-01

We evaluated long-term trends in average maximum and minimum temperatures, threshold temperatures, and growing season in eastern Colorado, USA, to explore the potential shortcomings of many climate-change studies that either: (1) generalize regional patterns from single stations, single seasons, or a few parameters over short duration from averaging dissimilar stations: or (2) generalize an average regional pattern from coarse-scale general circulation models. Based on 11 weather stations, some trends were weakly regionally consistent with previous studies of night-time temperature warming. Long-term (80 + years) mean minimum temperatures increased significantly (P < 0.2) in about half the stations in winter, spring, and autumn and six stations had significant decreases in the number of days per year with temperatures ??? - 17.8 ??C (???0??F). However, spatial and temporal variation in the direction of change was enormous for all the other weather parameters tested, and, in the majority of tests, few stations showed significant trends (even at P < 0.2). In summer, four stations had significant increases and three stations had significant decreases in minimum temperatures, producing a strongly mixed regional signal. Trends in maximum temperature varied seasonally and geographically, as did trends in threshold temperature days ???32.2??C (???90??F) or days ???37.8??C (???100??F). There was evidence of a subregional cooling in autumn's maximum temperatures, with five stations showing significant decreasing trends. There were many geographic anomalies where neighbouring weather stations differed greatly in the magnitude of change or where they had significant and opposite trends. We conclude that sub-regional spatial and seasonal variation cannot be ignored when evaluating the direction and magnitude of climate change. It is unlikely that one or a few weather stations are representative of regional climate trends, and equally unlikely that regionally projected climate change from coarse-scale general circulation models will accurately portray trends at sub-regional scales. However, the assessment of a group of stations for consistent more qualitative trends (such as the number of days less than - 17.8??C, such as we found) provides a reasonably robust procedure to evaluate climate trends and variability. Copyright ?? 2002 Royal Meteorological Society.

On the relationship between large-scale climate modes and regional synoptic patterns that drive Victorian rainfall

NASA Astrophysics Data System (ADS)

Verdon-Kidd, D.; Kiem, A. S.

2008-10-01

In this paper regional (synoptic) and large-scale climate drivers of rainfall are investigated for Victoria, Australia. A non-linear classification methodology known as self-organizing maps (SOM) is used to identify 20 key regional synoptic patterns, which are shown to capture a range of significant synoptic features known to influence the climate of the region. Rainfall distributions are assigned to each of the 20 patterns for nine rainfall stations located across Victoria, resulting in a clear distinction between wet and dry synoptic types at each station. The influence of large-scale climate modes on the frequency and timing of the regional synoptic patterns is also investigated. This analysis revealed that phase changes in the El Niño Southern Oscillation (ENSO), the Southern Annular Mode (SAM) and/or Indian Ocean Dipole (IOD) are associated with a shift in the relative frequency of wet and dry synoptic types. Importantly, these results highlight the potential to utilise the link between the regional synoptic patterns derived in this study and large-scale climate modes to improve rainfall forecasting for Victoria, both in the short- (i.e. seasonal) and long-term (i.e. decadal/multi-decadal scale). In addition, the regional and large-scale climate drivers identified in this study provide a benchmark by which the performance of Global Climate Models (GCMs) may be assessed.

Weather Support for the 2002 Winter Olympic and Paralympic Games.

NASA Astrophysics Data System (ADS)

Horel, J.; Potter, T.; Dunn, L.; Steenburgh, W. J.; Eubank, M.; Splitt, M.; Onton, D. J.

2002-02-01

The 2002 Winter Olympic and Paralympic Games will be hosted by Salt Lake City, Utah, during February-March 2002. Adverse weather during this period may delay sporting events, while snow and ice-covered streets and highways may impede access by the athletes and spectators to the venues. While winter snowstorms and other large-scale weather systems typically have widespread impacts throughout northern Utah, hazardous winter weather is often related to local terrain features (the Wasatch Mountains and Great Salt Lake are the most prominent ones). Examples of such hazardous weather include lake-effect snowstorms, ice fog, gap winds, downslope windstorms, and low visibility over mountain passes.A weather support system has been developed to provide weather information to the athletes, games officials, spectators, and the interested public around the world. This system is managed by the Salt Lake Olympic Committee and relies upon meteorologists from the public, private, and academic sectors of the atmospheric science community. Weather forecasting duties will be led by National Weather Service forecasters and a team of private, weather forecasters organized by KSL, the Salt Lake City NBC television affiliate. Other government agencies, commercial firms, and the University of Utah are providing specialized forecasts and support services for the Olympics. The weather support system developed for the 2002 Winter Olympics is expected to provide long-term benefits to the public through improved understanding,monitoring, and prediction of winter weather in the Intermountain West.

Nesting large-eddy simulations within mesoscale simulations for wind energy applications

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

Lundquist, J K; Mirocha, J D; Chow, F K

2008-09-08

With increasing demand for more accurate atmospheric simulations for wind turbine micrositing, for operational wind power forecasting, and for more reliable turbine design, simulations of atmospheric flow with resolution of tens of meters or higher are required. These time-dependent large-eddy simulations (LES), which resolve individual atmospheric eddies on length scales smaller than turbine blades and account for complex terrain, are possible with a range of commercial and open-source software, including the Weather Research and Forecasting (WRF) model. In addition to 'local' sources of turbulence within an LES domain, changing weather conditions outside the domain can also affect flow, suggesting thatmore » a mesoscale model provide boundary conditions to the large-eddy simulations. Nesting a large-eddy simulation within a mesoscale model requires nuanced representations of turbulence. Our group has improved the Weather and Research Forecasting model's (WRF) LES capability by implementing the Nonlinear Backscatter and Anisotropy (NBA) subfilter stress model following Kosovic (1997) and an explicit filtering and reconstruction technique to compute the Resolvable Subfilter-Scale (RSFS) stresses (following Chow et al, 2005). We have also implemented an immersed boundary method (IBM) in WRF to accommodate complex terrain. These new models improve WRF's LES capabilities over complex terrain and in stable atmospheric conditions. We demonstrate approaches to nesting LES within a mesoscale simulation for farms of wind turbines in hilly regions. Results are sensitive to the nesting method, indicating that care must be taken to provide appropriate boundary conditions, and to allow adequate spin-up of turbulence in the LES domain.« less

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.

Integrating environmental covariates and crop modeling into the genomic selection framework to predict genotype by environment interactions.

PubMed

Heslot, Nicolas; Akdemir, Deniz; Sorrells, Mark E; Jannink, Jean-Luc

2014-02-01

Development of models to predict genotype by environment interactions, in unobserved environments, using environmental covariates, a crop model and genomic selection. Application to a large winter wheat dataset. Genotype by environment interaction (G*E) is one of the key issues when analyzing phenotypes. The use of environment data to model G*E has long been a subject of interest but is limited by the same problems as those addressed by genomic selection methods: a large number of correlated predictors each explaining a small amount of the total variance. In addition, non-linear responses of genotypes to stresses are expected to further complicate the analysis. Using a crop model to derive stress covariates from daily weather data for predicted crop development stages, we propose an extension of the factorial regression model to genomic selection. This model is further extended to the marker level, enabling the modeling of quantitative trait loci (QTL) by environment interaction (Q*E), on a genome-wide scale. A newly developed ensemble method, soft rule fit, was used to improve this model and capture non-linear responses of QTL to stresses. The method is tested using a large winter wheat dataset, representative of the type of data available in a large-scale commercial breeding program. Accuracy in predicting genotype performance in unobserved environments for which weather data were available increased by 11.1% on average and the variability in prediction accuracy decreased by 10.8%. By leveraging agronomic knowledge and the large historical datasets generated by breeding programs, this new model provides insight into the genetic architecture of genotype by environment interactions and could predict genotype performance based on past and future weather scenarios.

Distributed Power Systems for Sustainable Energy

DTIC Science & Technology

2012-10-01

capital investment in state-of- the-art cogeneration technologies, renewable sources, energy storage, and interconnection hardware and software. It is...8 capacity may not be well suited to support building or campus-scale microgrids. This is because new thermal and electrical energy storage devices...constraints, as well as the site location, weather, and consumption patterns. These factors change over the life of the energy microgrid. • Tradeoffs

Detection of large-scale concentric gravity waves from a Chinese airglow imager network

NASA Astrophysics Data System (ADS)

Lai, Chang; Yue, Jia; Xu, Jiyao; Yuan, Wei; Li, Qinzeng; Liu, Xiao

2018-06-01

Concentric gravity waves (CGWs) contain a broad spectrum of horizontal wavelengths and periods due to their instantaneous localized sources (e.g., deep convection, volcanic eruptions, or earthquake, etc.). However, it is difficult to observe large-scale gravity waves of >100 km wavelength from the ground for the limited field of view of a single camera and local bad weather. Previously, complete large-scale CGW imagery could only be captured by satellite observations. In the present study, we developed a novel method that uses assembling separate images and applying low-pass filtering to obtain temporal and spatial information about complete large-scale CGWs from a network of all-sky airglow imagers. Coordinated observations from five all-sky airglow imagers in Northern China were assembled and processed to study large-scale CGWs over a wide area (1800 km × 1 400 km), focusing on the same two CGW events as Xu et al. (2015). Our algorithms yielded images of large-scale CGWs by filtering out the small-scale CGWs. The wavelengths, wave speeds, and periods of CGWs were measured from a sequence of consecutive assembled images. Overall, the assembling and low-pass filtering algorithms can expand the airglow imager network to its full capacity regarding the detection of large-scale gravity waves.

Local weather, regional climate, and annual survival of the northern spotted owl

USGS Publications Warehouse

Glenn, E.M.; Anthony, R.G.; Forsman, E.D.; Olson, G.S.

2011-01-01

We used an information-theoretical approach and Cormack-Jolly-Seber models for open populations in program MARK to examine relationships between survival rates of Northern Spotted Owls and a variety of local weather variables and long-term climate variables. In four of the six populations examined, survival was positively associated with wetter than normal conditions during the growing season or high summer temperatures. At the three study areas located at the highest elevations, survival was positively associated with winter temperature but also had a negative or quadratic relation with the number of storms and winter precipitation. A metaanalysis of all six areas combined indicated that annual survival was most strongly associated with phase shifts in the Southern Oscillation and Pacific Decadal Oscillation, which reflect large-scale temperature and precipitation patterns in this region. Climate accounted for a variable amount (1-41%) of the total process variation in annual survival but for more year-to-year variation (3-66%) than did spatial variation among owl territories (0-7%). Negative associations between survival and cold, wet winters and nesting seasons were similar to those found in other studies of the Spotted Owl. The relationships between survival and growing-season precipitation and regional climate patterns, however, had not been reported for this species previously. Climate-change models for the first half of the 21st century predict warmer, wetter winters and hotter, drier summers for the Pacific Northwest. Our results indicate that these conditions could decrease Spotted Owl survival in some areas. Copyright ?? The Cooper Ornithological Society 2011.

Mediterranean climate patterns and wine quality in North and Central Italy.

PubMed

Dalu, John David; Baldi, Marina; Marta, Anna Dalla; Orlandini, Simone; Maracchi, Gianpiero; Dalu, Giovanni; Grifoni, Daniele; Mancini, Marco

2013-09-01

Results show that the year-to-year quality variation of wines produced in North and Central Italy depends on the large-scale climate variability, and that the wine quality improvement in the last four decades is partially due to an increase of temperature and to a decrease of precipitation in West and Central Mediterranean Europe (WME; CME). In addition, wine quality is positively correlated with air temperature throughout the entire active period of the grapevine, weakly negatively correlated with precipitation in spring, and well negatively correlated in summer and fall. The month-to-month composites of the NAO anomaly show that, in years of good quality wine, this anomaly is negative in late spring, oscillates around zero in summer, and is positive in early fall; while, in years of bad quality wine, it is positive in late spring and summer, and negative in early fall, i.e. its polarity has an opposite sign in spring and fall in good versus bad years. The composite seasonal maps show that good wines are produced when the spring jet stream over the Atlantic diverts most of the weather perturbations towards North Europe, still providing a sufficient amount of rainwater to CME; when summer warming induced by southerly winds is balanced by the cooling induced by westerly winds; and when a positive geopotential anomaly over WME shelters CME from fall Atlantic storms. Bad quality wines are produced when the jet stream favors the intrusion of the Atlantic weather perturbations into the Mediterranean. Results suggest that atmospheric pattern persistencies can be used as precursors for wine quality forecast.

Seasonal climate variation and caribou availability: Modeling sequential movement using satellite-relocation data

USGS Publications Warehouse

Nicolson, Craig; Berman, Matthew; West, Colin Thor; Kofinas, Gary P.; Griffith, Brad; Russell, Don; Dugan, Darcy

2013-01-01

Livelihood systems that depend on mobile resources must constantly adapt to change. For people living in permanent settlements, environmental changes that affect the distribution of a migratory species may reduce the availability of a primary food source, with the potential to destabilize the regional social-ecological system. Food security for Arctic indigenous peoples harvesting barren ground caribou (Rangifer tarandus granti) depends on movement patterns of migratory herds. Quantitative assessments of physical, ecological, and social effects on caribou distribution have proven difficult because of the significant interannual variability in seasonal caribou movement patterns. We developed and evaluated a modeling approach for simulating the distribution of a migratory herd throughout its annual cycle over a multiyear period. Beginning with spatial and temporal scales developed in previous studies of the Porcupine Caribou Herd of Canada and Alaska, we used satellite collar locations to compute and analyze season-by-season probabilities of movement of animals between habitat zones under two alternative weather conditions for each season. We then built a set of transition matrices from these movement probabilities, and simulated the sequence of movements across the landscape as a Markov process driven by externally imposed seasonal weather states. Statistical tests showed that the predicted distributions of caribou were consistent with observed distributions, and significantly correlated with subsistence harvest levels for three user communities. Our approach could be applied to other caribou herds and could be adapted for simulating the distribution of other ungulates and species with similarly large interannual variability in the use of their range.

Geographic patterns of seed mass are associated with climate factors, but relationships vary between species.

PubMed

Soper Gorden, Nicole L; Winkler, Katharine J; Jahnke, Matthew R; Marshall, Elizabeth; Horky, Joshua; Huddelson, Colton; Etterson, Julie R

2016-01-01

Seed size is a critical life history attribute with fitness effects that cascade throughout the lifespan of plants. Interspecific studies repeatedly report a negative correlation between seed mass and latitude. Yet, despite its importance, little is known about geographic variation in seed size within species' ranges. To improve our understanding of intraspecific geographic variation in seed size, we collected and weighed seeds by maternal line from 8 to 17 populations of seven herbaceous plant species spanning large geographic areas, and measured a dispersal trait, awn length, for two grass species. We examined the overall relationship between seed mass and latitude, then divided the data into species-specific subsets to compare the fit of three models to explain seed mass and awn length: (1) latitude and longitude, (2) long-term climate, and (3) collection-year weather. Like previous work, we found a negative relationship between interspecific seed mass and latitude. However, the best-fit models explaining seed size and awn length differed between individual species and often included significant interaction terms. For all species, the best model was either long-term or collection-year climate data instead of latitude and longitude. Intraspecific geographic patterns for seed traits were remarkably inconsistent, covarying both negatively and positively with temperature and precipitation. The only apparent generalization is that annual species' seed mass corresponded more with collection-year weather while perennial species covaried more with long-term climate. Overall, this study suggests that the scale of climate variation that molds seed traits is highly species-specific. © 2016 Botanical Society of America.

Extra-Tropical Cyclones at Climate Scales: Comparing Models to Observations

NASA Astrophysics Data System (ADS)

Tselioudis, G.; Bauer, M.; Rossow, W.

2009-04-01

Climate is often defined as the accumulation of weather, and weather is not the concern of climate models. Justification for this latter sentiment has long been hidden behind coarse model resolutions and blunt validation tools based on climatological maps. The spatial-temporal resolutions of today's climate models and observations are converging onto meteorological scales, however, which means that with the correct tools we can test the largely unproven assumption that climate model weather is correct enough that its accumulation results in a robust climate simulation. Towards this effort we introduce a new tool for extracting detailed cyclone statistics from observations and climate model output. These include the usual cyclone characteristics (centers, tracks), but also adaptive cyclone-centric composites. We have created a novel dataset, the MAP Climatology of Mid-latitude Storminess (MCMS), which provides a detailed 6 hourly assessment of the areas under the influence of mid-latitude cyclones, using a search algorithm that delimits the boundaries of each system from the outer-most closed SLP contour. Using this we then extract composites of cloud, radiation, and precipitation properties from sources such as ISCCP and GPCP to create a large comparative dataset for climate model validation. A demonstration of the potential usefulness of these tools in process-based climate model evaluation studies will be shown.

Regional assessment of boreal forest productivity using an ecological process model and remote sensing parameter maps.

PubMed

Kimball, J. S.; Keyser, A. R.; Running, S. W.; Saatchi, S. S.

2000-06-01

An ecological process model (BIOME-BGC) was used to assess boreal forest regional net primary production (NPP) and response to short-term, year-to-year weather fluctuations based on spatially explicit, land cover and biomass maps derived by radar remote sensing, as well as soil, terrain and daily weather information. Simulations were conducted at a 30-m spatial resolution, over a 1205 km(2) portion of the BOREAS Southern Study Area of central Saskatchewan, Canada, over a 3-year period (1994-1996). Simulations of NPP for the study region were spatially and temporally complex, averaging 2.2 (+/- 0.6), 1.8 (+/- 0.5) and 1.7 (+/- 0.5) Mg C ha(-1) year(-1) for 1994, 1995 and 1996, respectively. Spatial variability of NPP was strongly controlled by the amount of aboveground biomass, particularly photosynthetic leaf area, whereas biophysical differences between broadleaf deciduous and evergreen coniferous vegetation were of secondary importance. Simulations of NPP were strongly sensitive to year-to-year variations in seasonal weather patterns, which influenced the timing of spring thaw and deciduous bud-burst. Reductions in annual NPP of approximately 17 and 22% for 1995 and 1996, respectively, were attributed to 3- and 5-week delays in spring thaw relative to 1994. Boreal forest stands with greater proportions of deciduous vegetation were more sensitive to the timing of spring thaw than evergreen coniferous stands. Similar relationships were found by comparing simulated snow depth records with 10-year records of aboveground NPP measurements obtained from biomass harvest plots within the BOREAS region. These results highlight the importance of sub-grid scale land cover complexity in controlling boreal forest regional productivity, the dynamic response of the biome to short-term interannual climate variations, and the potential implications of climate change and other large-scale disturbances.

Incorporating residual temperature and specific humidity in predicting weather-dependent warm-season electricity consumption

NASA Astrophysics Data System (ADS)

Guan, Huade; Beecham, Simon; Xu, Hanqiu; Ingleton, Greg

2017-02-01

Climate warming and increasing variability challenges the electricity supply in warm seasons. A good quantitative representation of the relationship between warm-season electricity consumption and weather condition provides necessary information for long-term electricity planning and short-term electricity management. In this study, an extended version of cooling degree days (ECDD) is proposed for better characterisation of this relationship. The ECDD includes temperature, residual temperature and specific humidity effects. The residual temperature is introduced for the first time to reflect the building thermal inertia effect on electricity consumption. The study is based on the electricity consumption data of four multiple-street city blocks and three office buildings. It is found that the residual temperature effect is about 20% of the current-day temperature effect at the block scale, and increases with a large variation at the building scale. Investigation of this residual temperature effect provides insight to the influence of building designs and structures on electricity consumption. The specific humidity effect appears to be more important at the building scale than at the block scale. A building with high energy performance does not necessarily have low specific humidity dependence. The new ECDD better reflects the weather dependence of electricity consumption than the conventional CDD method.

Contribution of human, climate and biophysical drivers to the spatial distribution of wildfires in a French Mediterranean area: where do wildfires start and spread?

NASA Astrophysics Data System (ADS)

Ruffault, Julien; Mouillot, Florent; Moebius, Flavia

2013-04-01

Understanding the contribution of biophysical and human drivers to the spatial distribution of fires at regional scale has many ecological and economical implications in a context of on-going global changes. However these fire drivers often interact in complex ways, such that disentangling and assessing the relative contribution of human vs. biophysical factors remains a major challenge. Indeed, the identification of biophysical conditions that promote fires are confused by the inherent stochasticity in fire occurrences and fire spread on the one hand and, by the influence of human factors -through both fire ignition and suppression - on the other. Moreover, different factors may drive fire ignition and fire spread, in such a way that the areas with the highest density of ignitions may not coincide with those where large fires occur. In the present study, we investigated the drivers of fires ignition and spread in a Mediterranean area of southern France. We used a 17 years fire database (the PROMETHEE database from 1989-2006) combined with a set of 8 explanatory variables describing the spatial pattern in ignitions, vegetation and fire weather. We first isolated the weather conditions affecting the fire occurrence and their spread using a statistical model of the weather/fuel water status for each fire event.. The results of these statistical models were used to map the fire weather in terms of average number of days with suitable conditions for burning. Then, we used Boosted regression trees (BRT) models to assess the relative importance of the different variables on the distribution of wildfire with different sizes and to assess the relationship between each variables and fire occurrence and spread probabilities. We found that human activities explained up to 50 % of the spatial distribution of fire ignitions (SDI). The distribution of large fire was chiefly explained by fuel characteristics (about 40%). Surprisingly, the weather indices explained only 20 % of the SDI and its contribution does no vary according to the size of considered fire events. These results suggest that changes in fuel characteristics and human settlements/ activities, rather than weather conditions are the most likely to modify the future distribution of fires in this Mediterranean area. These conclusions provide useful information on the scenarios that could arise from the interaction of changes in climate and land cover for the Mediterranean area in the near future.

2012/13 abnormal cold winter in Japan associated with Large-scale Atmospheric Circulation and Local Sea Surface Temperature over the Sea of Japan

NASA Astrophysics Data System (ADS)

Ando, Y.; Ogi, M.; Tachibana, Y.

2013-12-01

On Japan, wintertime cold wave has social, economic, psychological and political impacts because of the lack of atomic power stations in the era of post Fukushima world. The colder winter is the more electricity is needed. Wintertime weather of Japan and its prediction has come under the world spotlight. The winter of 2012/13 in Japan was abnormally cold, and such a cold winter has persisted for 3 years. Wintertime climate of Japan is governed by some dominant modes of the large-scale atmospheric circulations. Yasunaka and Hanawa (2008) demonstrated that the two dominant modes - Arctic Oscillation (AO) and Western Pacific (WP) pattern - account for about 65% of the interannual variation of the wintertime mean surface air temperature of Japan. A negative AO brings about cold winter in Japan. In addition, a negative WP also brings about cold winter in Japan. Looking back to the winter of 2012/13, both the negative AO and negative WP continued from October through December. If the previous studies were correct, it would have been extremely very cold from October through December. In fact, in December, in accordance with previous studies, it was colder than normal. Contrary to the expectation, in October and November, it was, however, warmer than normal. This discrepancy signifies that an additional hidden circumstance that heats Japan overwhelms these large-scale atmospheric circulations that cool Japan. In this study, we therefore seek an additional cause of wintertime climate of Japan particularly focusing 2012 as well as the AO and WP. We found that anomalously warm oceanic temperature surrounding Japan overwhelmed influences of the AO or WP. Unlike the inland climate, the island climate can be strongly influenced by surrounding ocean temperature, suggesting that large-scale atmospheric patterns alone do not determine the climate of islands. (a) Time series of a 5-day running mean AO index (blue) as defined by Ogi et al., (2004), who called it the SVNAM index. For reference, the conventional AO index is shown by the gray line. (b) a 5-day running mean WP index, (c) area-averaged Surface Air Temperature anomalies in Japan, (d) Air Temperature anomalies, (e) heat flux anomalies, and (f) Sea Surface Temperature anomalies. The boxed area on the Sea of Japan indicates the area in which the (d)-(f) indexes were calculated.

Natural disturbance production functions

Treesearch

Jeffrey P. Prestemon; D. Evan Mercer; John M. Pye

2008-01-01

Natural disturbances in forests are driven by physical and biological processes. Large, landscape scale disturbances derive primarily from weather (droughts, winds, ice storms, and floods), geophysical activities (earthquakes, volcanic eruptions), fires, insects, and diseases. Humans have invented ways to minimize their negative impacts and reduce their rates of...

Process, pattern and scale: hydrogeomorphology and plant diversity in forested wetlands across multiple spatial scales

NASA Astrophysics Data System (ADS)

Alexander, L.; Hupp, C. R.; Forman, R. T.

2002-12-01

Many geodisturbances occur across large spatial scales, spanning entire landscapes and creating ecological phenomena in their wake. Ecological study at large scales poses special problems: (1) large-scale studies require large-scale resources, and (2) sampling is not always feasible at the appropriate scale, and researchers rely on data collected at smaller scales to interpret patterns across broad regions. A criticism of landscape ecology is that findings at small spatial scales are "scaled up" and applied indiscriminately across larger spatial scales. In this research, landscape scaling is addressed through process-pattern relationships between hydrogeomorphic processes and patterns of plant diversity in forested wetlands. The research addresses: (1) whether patterns and relationships between hydrogeomorphic, vegetation, and spatial variables can transcend scale; and (2) whether data collected at small spatial scales can be used to describe patterns and relationships across larger spatial scales. Field measurements of hydrologic, geomorphic, spatial, and vegetation data were collected or calculated for 15- 1-ha sites on forested floodplains of six (6) Chesapeake Bay Coastal Plain streams over a total area of about 20,000 km2. Hydroperiod (day/yr), floodplain surface elevation range (m), discharge (m3/s), stream power (kg-m/s2), sediment deposition (mm/yr), relative position downstream and other variables were used in multivariate analyses to explain differences in species richness, tree diversity (Shannon-Wiener Diversity Index H'), and plant community composition at four spatial scales. Data collected at the plot (400-m2) and site- (c. 1-ha) scales are applied to and tested at the river watershed and regional spatial scales. Results indicate that plant species richness and tree diversity (Shannon-Wiener diversity index H') can be described by hydrogeomorphic conditions at all scales, but are best described at the site scale. Data collected at plot and site scales are tested for spatial heterogeneity across the Chesapeake Bay Coastal Plain using a geostatistical variogram, and multiple regression analysis is used to relate plant diversity, spatial, and hydrogeomorphic variables across Coastal Plain regions and hydrologic regimes. Results indicate that relationships between hydrogeomorphic processes and patterns of plant diversity at finer scales can proxy relationships at coarser scales in some, not all, cases. Findings also suggest that data collected at small scales can be used to describe trends across broader scales under limited conditions.

Using record player demonstrations as analog models for geophysical fluids

NASA Astrophysics Data System (ADS)

Grannan, A. M.; Cheng, J. S.; Hawkins, E. K.; Ribeiro, A.; Aurnou, J. M.

2015-12-01

All celestial bodies, including stars, planets, satellites, and asteroids, rotate. The influence of rotation on the fluid layers in these bodies plays an important and diverse role, affecting many processes including oceanic and atmospheric circulation at the surface and magnetic field generation occurring in the interior. To better understand these large-scale processes, record players and containers of water are used as analog models to demonstrate the basic interplay between rotation and fluid motions. To contrast between rotating and non-rotating fluid motions, coffee creamer and food coloring are used as fluid tracers to provide a hands-on method of understanding the influence of rotation on the shapes of the planets, weather patterns, and the alignment of magnetic fields with rotational axes. Such simple demonstrations have been successfully employed for children in public outreach events and for adults in graduate level fluid dynamics courses.

Predictability of short-range forecasting: a multimodel approach

NASA Astrophysics Data System (ADS)

García-Moya, Jose-Antonio; Callado, Alfons; Escribà, Pau; Santos, Carlos; Santos-Muñoz, Daniel; Simarro, Juan

2011-05-01

Numerical weather prediction (NWP) models (including mesoscale) have limitations when it comes to dealing with severe weather events because extreme weather is highly unpredictable, even in the short range. A probabilistic forecast based on an ensemble of slightly different model runs may help to address this issue. Among other ensemble techniques, Multimodel ensemble prediction systems (EPSs) are proving to be useful for adding probabilistic value to mesoscale deterministic models. A Multimodel Short Range Ensemble Prediction System (SREPS) focused on forecasting the weather up to 72 h has been developed at the Spanish Meteorological Service (AEMET). The system uses five different limited area models (LAMs), namely HIRLAM (HIRLAM Consortium), HRM (DWD), the UM (UKMO), MM5 (PSU/NCAR) and COSMO (COSMO Consortium). These models run with initial and boundary conditions provided by five different global deterministic models, namely IFS (ECMWF), UM (UKMO), GME (DWD), GFS (NCEP) and CMC (MSC). AEMET-SREPS (AE) validation on the large-scale flow, using ECMWF analysis, shows a consistent and slightly underdispersive system. For surface parameters, the system shows high skill forecasting binary events. 24-h precipitation probabilistic forecasts are verified using an up-scaling grid of observations from European high-resolution precipitation networks, and compared with ECMWF-EPS (EC).

Large-Scale Atmospheric Circulation Patterns Associated with Temperature Extremes as a Basis for Model Evaluation: Methodological Overview and Results

NASA Astrophysics Data System (ADS)

Loikith, P. C.; Broccoli, A. J.; Waliser, D. E.; Lintner, B. R.; Neelin, J. D.

2015-12-01

Anomalous large-scale circulation patterns often play a key role in the occurrence of temperature extremes. For example, large-scale circulation can drive horizontal temperature advection or influence local processes that lead to extreme temperatures, such as by inhibiting moderating sea breezes, promoting downslope adiabatic warming, and affecting the development of cloud cover. Additionally, large-scale circulation can influence the shape of temperature distribution tails, with important implications for the magnitude of future changes in extremes. As a result of the prominent role these patterns play in the occurrence and character of extremes, the way in which temperature extremes change in the future will be highly influenced by if and how these patterns change. It is therefore critical to identify and understand the key patterns associated with extremes at local to regional scales in the current climate and to use this foundation as a target for climate model validation. This presentation provides an overview of recent and ongoing work aimed at developing and applying novel approaches to identifying and describing the large-scale circulation patterns associated with temperature extremes in observations and using this foundation to evaluate state-of-the-art global and regional climate models. Emphasis is given to anomalies in sea level pressure and 500 hPa geopotential height over North America using several methods to identify circulation patterns, including self-organizing maps and composite analysis. Overall, evaluation results suggest that models are able to reproduce observed patterns associated with temperature extremes with reasonable fidelity in many cases. Model skill is often highest when and where synoptic-scale processes are the dominant mechanisms for extremes, and lower where sub-grid scale processes (such as those related to topography) are important. Where model skill in reproducing these patterns is high, it can be inferred that extremes are being simulated for plausible physical reasons, boosting confidence in future projections of temperature extremes. Conversely, where model skill is identified to be lower, caution should be exercised in interpreting future projections.

A new look at the decomposition of agricultural productivity growth incorporating weather effects.

PubMed

Njuki, Eric; Bravo-Ureta, Boris E; O'Donnell, Christopher J

2018-01-01

Random fluctuations in temperature and precipitation have substantial impacts on agricultural output. However, the contribution of these changing configurations in weather to total factor productivity (TFP) growth has not been addressed explicitly in econometric analyses. Thus, the key objective of this study is to quantify and to investigate the role of changing weather patterns in explaining yearly fluctuations in TFP. For this purpose, we define TFP to be a measure of total output divided by a measure of total input. We estimate a stochastic production frontier model using U.S. state-level agricultural data incorporating growing season temperature and precipitation, and intra-annual standard deviations of temperature and precipitation for the period 1960-2004. We use the estimated parameters of the model to compute a TFP index that has good axiomatic properties. We then decompose TFP growth in each state into weather effects, technological progress, technical efficiency, and scale-mix efficiency changes. This approach improves our understanding of the role of different components of TFP in agricultural productivity growth. We find that annual TFP growth averaged 1.56% between 1960 and 2004. Moreover, we observe substantial heterogeneity in weather effects across states and over time.

A new look at the decomposition of agricultural productivity growth incorporating weather effects

PubMed Central

Bravo-Ureta, Boris E.; O’Donnell, Christopher J.

2018-01-01

Random fluctuations in temperature and precipitation have substantial impacts on agricultural output. However, the contribution of these changing configurations in weather to total factor productivity (TFP) growth has not been addressed explicitly in econometric analyses. Thus, the key objective of this study is to quantify and to investigate the role of changing weather patterns in explaining yearly fluctuations in TFP. For this purpose, we define TFP to be a measure of total output divided by a measure of total input. We estimate a stochastic production frontier model using U.S. state-level agricultural data incorporating growing season temperature and precipitation, and intra-annual standard deviations of temperature and precipitation for the period 1960–2004. We use the estimated parameters of the model to compute a TFP index that has good axiomatic properties. We then decompose TFP growth in each state into weather effects, technological progress, technical efficiency, and scale-mix efficiency changes. This approach improves our understanding of the role of different components of TFP in agricultural productivity growth. We find that annual TFP growth averaged 1.56% between 1960 and 2004. Moreover, we observe substantial heterogeneity in weather effects across states and over time. PMID:29466461

Wildfires, mountain pine beetle and large-scale climate in Northern North America.

NASA Astrophysics Data System (ADS)

Macias Fauria, M.; Johnson, E. A.

2009-05-01

Research on the interactions between biosphere and atmosphere and ocean/atmosphere dynamics, concretely on the coupling between ecological processes and large-scale climate, is presented in two studies in Northern North America: the occurrence of large lightning wildfires and the forest area affected by mountain pine beetle (Dendroctonus ponderosae, MPB). In both cases, large-scale climatic patterns such as the Pacific Decadal Oscillation (PDO) and the Arctic Oscillation (AO) operate as low and low and high frequency frameworks, respectively, that control the occurrence, duration and spatial correlation over large areas of key local weather variables which affect specific ecological processes. Warm PDO phases tend to produce persistent (more than 10 days long) positive mid-troposphere anomalies (blocking highs) over western Canada and Alaska. Likewise, positive (negative) AO configurations increase the frequency of blocking highs at mid (high) latitudes of the Northern Hemisphere. Under these conditions, lack of precipitation and prevailing warm air meridional flow rapidly dry fuel over large areas and increase fire hazard. The spatiotemporal patterns of occurrence of large lightning wildfire in Canada and Alaska for 1959-1999 were largely explained by the action and possible interaction of AO and PDO, the AO being more influential over Eastern Canada, the PDO over Western Canada and Alaska. Changes in the dynamics of the PDO are linked to the occurrence of cold winter temperatures in British Columbia (BC), Western Canada. Reduced frequency of cold events during warm PDO winters is consistent with a northward-displaced polar jet stream inhibiting the outflow of cold Arctic air over BC. Likewise, the AO influences the occurrence of winter cold spells in the area. PDO, and to a lesser degree AO, were strongly related to MPB synchrony in BC during 1959-2002, operating through the control of the frequency of extreme cold winter temperatures that affect MPB larvae survival. The onset of a warm PDO phase in 1976 1) increased (decreased) the area burnt by wildfire in the Canadian Boreal Forest (BC) by increasing (decreasing) the frequency of blocking highs in the area, and 2) favored MPB outbreaks in BC by reducing the occurrence of extremely low winter temperatures. Likewise, the exceptionally high and persistent AO values of the late 1980s and 1990s increased area burned in Eastern Canada and MPB activity in the southern and northern parts of BC. A possible recent PDO phase shift may largely reverse these trends.

The Effects of Weather Patterns on the Spatio-Temporal Distribution of SO2 over East Asia as Seen from Satellite Measurements

NASA Astrophysics Data System (ADS)

Dunlap, L.; Li, C.; Dickerson, R. R.; Krotkov, N. A.

2015-12-01

Weather systems, particularly mid-latitude wave cyclones, have been known to play an important role in the short-term variation of near-surface air pollution. Ground measurements and model simulations have demonstrated that stagnant air and minimal precipitation associated with high pressure systems are conducive to pollutant accumulation. With the passage of a cold front, built up pollution is transported downwind of the emission sources or washed out by precipitation. This concept is important to note when studying long-term changes in spatio-temporal pollution distribution, but has not been studied in detail from space. In this study, we focus on East Asia (especially the industrialized eastern China), where numerous large power plants and other point sources as well as area sources emit large amounts of SO2, an important gaseous pollutant and a precursor of aerosols. Using data from the Aura Ozone Monitoring Instrument (OMI) we show that such weather driven distribution can indeed be discerned from satellite data by utilizing probability distribution functions (PDFs) of SO2 column content. These PDFs are multimodal and give insight into the background pollution level at a given location and contribution from local and upwind emission sources. From these PDFs it is possible to determine the frequency for a given region to have SO2 loading that exceeds the background amount. By comparing OMI-observed long-term change in the frequency with meteorological data, we can gain insights into the effects of climate change (e.g., the weakening of Asian monsoon) on regional air quality. Such insight allows for better interpretation of satellite measurements as well as better prediction of future pollution distribution as a changing climate gives way to changing weather patterns.

Weather-forced variations of Central and East Pacific ENSO events

NASA Astrophysics Data System (ADS)

Alexander, M. A.; Newman, M.; Shin, S.

2010-12-01

It has been suggested that a possible outcome of climate change is an increase in the occurrence of “Modoki” or central Pacific El Nino events relative to canonical eastern Pacific El Nino events, and that this change may already be occurring. Such a determination, however, is complicated by possible natural variations of the two types of events. How large a change in the relative occurrence can be expected from purely internal variability? To explore this question, a “patterns-based” red noise null hypothesis is constructed from 40 years of observed seasonally-averaged SST, 20 deg C thermocline depth, and surface zonal wind stress anomalies. Patterns-based (or multivariate) red noise differs from “local” (or univariate) red noise since it allows for non-local advective processes; for example, weather noise driving surface wind stress in one location to produce an ocean response in a different location. It is shown that natural random variations of the central Pacific to east Pacific El Nino occurrence ratio are large enough that they could account for all past observed differences as well as all differences found in the SRESA1B runs of all AR4 climate models. Additionally, the correlation between Nino3 and Nino4 SST indices over 30-yr periods can range between 0.7 and 0.9 simply due to such variations in noise, with apparent multidecadal “trends” during which the value increases or decreases. Further analysis shows the different spatial patterns of “noise” (i.e., random weather forcing) that can lead to the development of central vs. eastern Pacific ENSO events or various combinations thereof.

Large-scale mapping of hard-rock aquifer properties applied to Burkina Faso.

PubMed

Courtois, Nathalie; Lachassagne, Patrick; Wyns, Robert; Blanchin, Raymonde; Bougaïré, Francis D; Somé, Sylvain; Tapsoba, Aïssata

2010-01-01

A country-scale (1:1,000,000) methodology has been developed for hydrogeologic mapping of hard-rock aquifers (granitic and metamorphic rocks) of the type that underlie a large part of the African continent. The method is based on quantifying the "useful thickness" and hydrodynamic properties of such aquifers and uses a recent conceptual model developed for this hydrogeologic context. This model links hydrodynamic parameters (transmissivity, storativity) to lithology and the geometry of the various layers constituting a weathering profile. The country-scale hydrogeological mapping was implemented in Burkina Faso, where a recent 1:1,000,000-scale digital geological map and a database of some 16,000 water wells were used to evaluate the methodology.

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.

The weather and climate: emergent laws and multifractal cascades

NASA Astrophysics Data System (ADS)

Lovejoy, Shaun; Schertzer, Daniel

2013-04-01

Science in general and physics and geophysics in particular are hierarchies of interlocking theories and models with low level, fundamental laws such as quantum mechanics and statistical mechanics providing the underpinnings for the emergence of the qualitatively new, higher level laws of thermodynamics and continuum mechanics that provide the current bases for modelling the weather and climate. Yest it was the belief of generations of turbulence pioneers (notably Richardson, Kolmogorov, Obhukhov, Corrsin, Bolgiano) that at sufficiently high levels of nonlinearity (quantified by the Reynold's number, of the order 10**12 in the atmosphere) that new even higher level laws would emerge describing "fully developed turbulence". However for atmospheric applications, the pioneers' eponymous laws suffered from two basic restrictions - isotropy and homogeneity - that prevented them from being valid over wide ranges of scale. Over the last thirty years both of these restrictions have been overcome - the former with the generalization from isotropic to strongly anisotropic notions of scale (to account notably for stratification), and from homogeneity to strong heterogeneity (intermittency) via multifractal cascades. In this presentation we give an overview of recent developments and analyses covering huge ranges of space-time scales (including weather, macroweather and climate time scales). We show how the combination of strong anisotropy and strong intermittency commonly leads to the "phenomenological fallacy" in which morphology is confounded with mechanism. With the help of stochastic models, we show how processes with vastly different large and small scale morphologies can arise from a unique multifractal dynamical mechanisms [Lovejoy and Schertzer, 2013]. References: Lovejoy, S., and D. Schertzer (2013), The Weather and Climate: Emergent Laws and Multifractal Cascades, 480 pp., Cambridge University Press, Cambridge.

Observations of ionospheric electric fields above atmospheric weather systems

NASA Technical Reports Server (NTRS)

Farrell, W. M.; Aggson, T. L.; Rodgers, E. B.; Hanson, W. B.

1994-01-01

We report on the observations of a number of quasi-dc electric field events associated with large-scale atmospheric weather formations. The observations were made by the electric field experiment onboard the San Marco D satellite, operational in an equatorial orbit from May to December 1988. Several theoretical studies suggest that electric fields generated by thunderstorms are present at high altitudes in the ionosphere. In spite of such favorable predictions, weather-related events are not often observed since they are relatively weak. We shall report here on a set of likely E field candidates for atmospheric-ionospheric causality, these being observed over the Indonesian Basin, northern South America, and the west coast of Africa; all known sites of atmospheric activity. As we shall demonstrate, individual events often be traced to specific active weather features. For example, a number of events were associated with spacecraft passages near Hurricane Joan in mid-October 1988. As a statistical set, the events appear to coincide with the most active regions of atmospheric weather.

Spatio-Temporal Description of the Rainfall for Colombian Andean Mountainous Region for Weather Forecasting Purposes. Case Study: Manizales - Caldas, Colombia

NASA Astrophysics Data System (ADS)

Suarez Hincapie, J. N.

2014-12-01

Manizales is a city located in west-central Colombian Andes in the Caldas province, whose spatial location coincides with one of the most threatened areas of Colombia (landslides, earthquakes, volcanic eruptions, other). As a middle Andean mountainous city and for being located in the area of influence of the ITCZ presents an equatorial mountain climate with a bimodal rainfall regime, and with an average annual rainfall around 2000 mm, it shows very significant rates of precipitation, on average, 70% of the days of the year it is rainy. This situation favors the formation of large masses of clouds and the presence of macroclimatic phenomena such as ENSO, which has historically caused large-scale impacts in both warm and cold phase. Since last decade different entities have implemented a hydro-meteorological network which measures and transmits telemetrically every five minutes hydro-climatic variables. In general, the real-time weather monitoring should be used for a better understanding of our environmental urban environment and to establish indicators of quality of life and welfare for the community. Despite the city has telemetric data on atmospheric and hydrological variables, there is still no tool or a methodology able to generate a spatio-temporal description of these variables. So, the aim of this work is to establish guidelines to sort all this information of atmospheric variables monitored in real time with the help of data mining techniques, machine learning tools to improve the knowledge of atmospheric patterns at Manizales and to serve for territorial planning and decision makers. To reach this purpose the current data warehouse available at the National University of Colombia at Manizales will be used, and it will be fed with observed variables from hydro-meteorological monitoring stations that transmit in real-time. Then, as mentioned this information will make the corresponding processing with data mining techniques to describe the rainfall patterns. All this complemented with the application of statistical techniques for data analysis and exploration. The main contribution of this research is the creation of tools to be used in numerical modeling with forecasting purposes, aiming to improve the resolution given by mesoscale models, which are currently used for weather forecast in Colombia.

Effects of Lightning and Other Meteorological Factors on Fire Activity in the North American Boreal Forest: Implications for Fire Weather Forecasting

NASA Technical Reports Server (NTRS)

Peterson, D.; Wang, J.; Ichoku, C.; Remer, L. A.

2010-01-01

The effects of lightning and other meteorological factors on wildfire activity in the North American boreal forest are statistically analyzed during the fire seasons of 2000-2006 through an integration of the following data sets: the MODerate Resolution Imaging Spectroradiometer (MODIS) level 2 fire products, the 3-hourly 32-kin gridded meteorological data from North American Regional Reanalysis (NARR), and the lightning data collected by the Canadian Lightning Detection Network (CLDN) and the Alaska Lightning Detection Network (ALDN). Positive anomalies of the 500 hPa geopotential height field, convective available potential energy (CAPE), number of cloud-to-ground lightning strikes, and the number of consecutive dry days are found to be statistically important to the seasonal variation of MODIS fire counts in a large portion of Canada and the entirety of Alaska. Analysis of fire occurrence patterns in the eastern and western boreal forest regions shows that dry (in the absence of precipitation) lightning strikes account for only 20% of the total lightning strikes, but are associated with (and likely cause) 40% of the MODIS observed fire counts in these regions. The chance for ignition increases when a threshold of at least 10 dry strikes per NARR grid box and at least 10 consecutive dry days is reached. Due to the orientation of the large-scale pattern, complex differences in fire and lightning occurrence and variability were also found between the eastern and western sub-regions. Locations with a high percentage of dry strikes commonly experience an increased number of fire counts, but the mean number of fire counts per dry strike is more than 50% higher in western boreal forest sub-region, suggesting a geographic and possible topographic influence. While wet lightning events are found to occur with a large range of CAPE values, a high probability for dry lightning occurs only when 500 hPa geopotential heights are above 5700m and CAPE values are near the maximum observed level, underscoring the importance of low-level instability to boreal fire weather forecasts-

Study of Microburst Detection Performance during 1985 in Memphis, Tennessee.

DTIC Science & Technology

1987-08-05

downburst into two categories depending on the outbursts’ hori- zontal scale: 1) macroburst - a large downburst with its’ outburst winds extending in... Macroburst . University of Chicago, 122 pp. Merritt, M.W., 1987: Microburst Divergent Outflow Algorithm, Version 2. MIT Lincoln Laboratory Weather Radar

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.

The synoptic- and planetary-scale environments associated with significant 1000-hPa geostrophic wind events along the Beaufort Sea coast

NASA Astrophysics Data System (ADS)

Cooke, Melanie

The substantial interannual variability and the observed warming trend of the Beaufort Sea region are important motivators for the study of regional climate and weather there. In an attempt to further our understanding of strong wind events, which can drive sea ice dynamics and storm surges, their characteristic environments at the synoptic and planetary scales are defined and analysed using global reanalysis data. A dependency on an enhanced or suppressed Aleutian low is found. This produces either a strong southeasterly or north-westerly 1000-hPa geostrophic wind event. The characteristic mid-tropospheric patterns for these two distinct event types show similarities to the positive and negative Pacific/North American teleconnection patterns, but their correlations have yet to be assessed.

Tidal and atmospheric forcing of the upper ocean in the Gulf of California. I - Sea surface temperature variability

NASA Technical Reports Server (NTRS)

Paden, Cynthia A.; Winant, Clinton D.; Abbott, Mark R.

1991-01-01

SST variability in the northern Gulf of California is examined on the basis of findings of two years of satellite infrared imagery (1984-1986). Empirical orthogonal functions of the temporal and spatial SST variance for 20 monthly mean images show that the dominant SST patterns are generated by spatially varying tidal mixing in the presence of seasonal heating and cooling. Atmospheric forcing of the northern gulf appears to occur over large spatial scales. Area-averaged SSTs for the Guaymas Basin, island region, and northern basin exhibit significant fluctuations which are highly correlated. These fluctuations in SST correspond to similar fluctuations in the air temperature which are related to synoptic weather events over the gulf. A regression analysis of the SST relative to the fortnightly tidal range shows that tidal mixing occurs over the sills in the island region as well as on the shallow northern shelf. Mixing over the sills occurs as a result of large breaking internal waves of internal hydraulic jumps which mix over water in the upper 300-500 m.

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.

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.

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

Observational analysis and large-scale pattern associated with cold events moving up the equator line over South America

NASA Astrophysics Data System (ADS)

Viana, Liviany; Herdies, Dirceu; Muller, Gabriela

2017-04-01

An observational study was carried out to quantify the events of cold air outbreak moving above the Equator from 1980 to 2013 during the austral winter period (May, June, July, August and September), and later analyzed the behavior of the circulation responsible for this displacement. The observational datasets from the Sector of Climatological studies of the Institute of Airspace Control of the city of Iauarete (0.61N, 69.0W; 120m), located at the extreme northern of the Brazilian Amazon Basin, were used for the analyzes. The meteorological variables used were the temperatures minimum, maximum and maximum atmospheric pressure. A new methodology was used to identify these events, calculated by the difference between the monthly average and 2 (two) standard deviations for the extremes of the air temperature, and the sum of 1 (one) standard deviation for the maximum atmospheric pressure. As a result, a total of 11 cold events were recorded that reached the extreme northern of the Brazilian Amazon Basin, with values recorded at a minimum temperature of 17.8 °C, at the maximum temperature of 21.0 °C and maximum atmospheric pressure reaching 1021.2 hPa. These reductions and augmentation are equivalent to the negative anomalies of 5.9 and 8.7 °C at the minimum and maximum temperatures, respectively, while a positive anomaly of 7.1 hPa was observed at the maximum pressure. In relation to the dynamic behavior of large-scale circulation, a Rossby wave-type configuration propagating from west to east over subtropical latitudes was observed from the European Center for Medium-Range Weather Forecast (ECMWF) since the days before the arrival of the event in the city of Iauarete. This behavior was observed both in the anomalies of the gepotencial (250 hPa and 850 hPa) and in the southern component of the wind (250 hPa and 850 hPa), both presenting statistical significance of 99 % (Student's T test). Therefore, a new criterion for the identification of "friagens" in the tropical latitude has been able to represent the effects of colds air outbreak and the advancement of the cold air mass, which are subsidized by the large-scale circulation, and consequently contribute to the modifications in the weather and the life of the population over this Equatorial region.

Wildfire risk estimation in the Mediterranean area

Treesearch

A.A. Ager; H.K. Preisler; B. Arca; D Spano; M. Salis

2014-01-01

We analyzed wildland fire occurrence and size data from Sardinia, Italy, and Corsica, France, to examine spatiotemporal patterns of fire occurrence in relation to weather, land use, anthropogenic features, and time of year. Fires on these islands are largely human caused and can be attributed to negligence, agro-pastoral land use, and arson. Of particular interest was...

On the interest of combining an analog model to a regression model for the adaptation of the downscaling link. Application to probabilistic prediction of precipitation over France.

NASA Astrophysics Data System (ADS)

Chardon, Jérémy; Hingray, Benoit; Favre, Anne-Catherine

2016-04-01

Scenarios of surface weather required for the impact studies have to be unbiased and adapted to the space and time scales of the considered hydro-systems. Hence, surface weather scenarios obtained from global climate models and/or numerical weather prediction models are not really appropriated. Outputs of these models have to be post-processed, which is often carried out thanks to Statistical Downscaling Methods (SDMs). Among those SDMs, approaches based on regression are often applied. For a given station, a regression link can be established between a set of large scale atmospheric predictors and the surface weather variable. These links are then used for the prediction of the latter. However, physical processes generating surface weather vary in time. This is well known for precipitation for instance. The most relevant predictors and the regression link are also likely to vary in time. A better prediction skill is thus classically obtained with a seasonal stratification of the data. Another strategy is to identify the most relevant predictor set and establish the regression link from dates that are similar - or analog - to the target date. In practice, these dates can be selected thanks to an analog model. In this study, we explore the possibility of improving the local performance of an analog model - where the analogy is applied to the geopotential heights 1000 and 500 hPa - using additional local scale predictors for the probabilistic prediction of the Safran precipitation over France. For each prediction day, the prediction is obtained from two GLM regression models - for both the occurrence and the quantity of precipitation - for which predictors and parameters are estimated from the analog dates. Firstly, the resulting combined model noticeably allows increasing the prediction performance by adapting the downscaling link for each prediction day. Secondly, the selected predictors for a given prediction depend on the large scale situation and on the considered region. Finally, even with such an adaptive predictor identification, the downscaling link appears to be robust: for a same prediction day, predictors selected for different locations of a given region are similar and the regression parameters are consistent within the region of interest.

Estimates of lower-tropospheric divergence and average vertical motion in the Southern Great Plains region

NASA Astrophysics Data System (ADS)

Muradyan, P.; Coulter, R.; Kotamarthi, V. R.; Wang, J.; Ghate, V. P.

2016-12-01

Large-scale mean vertical motion affects the atmospheric stability and is an important component in cloud formation. Thus, the analysis of temporal variations in the long-term averages of large-scale vertical motion would provide valuable insights into weather and climate patterns. 915-MHz radar wind profilers (RWP) provide virtually unattended and almost uninterrupted long-term wind speed measurements. We use five years of RWP wind data from the Atmospheric Boundary Layer Experiments (ABLE) located within the Atmospheric Radiation Measurement (ARM) Southern Great Plains (SGP) site from 1999 to 2004. Wind speed data from a triangular array of SGP A1, A2, and A5 ancillary sites are used to calculate the horizontal divergence field over the profiler network area using the line integral method. The distance between each vertex of this triangle is approximately 60km. Thus, the vertical motion profiles deduced from the divergence/convergence of horizontal winds over these spatial scales are of relevance to mesoscale dynamics. The wind data from RWPs are averaged over 1 hour time slice and divergence is calculated at each range gate from the lowest at 82 m to the highest at 2.3 km. An analysis of temporal variations in the long-term averages of the atmospheric divergence and vertical air motion for the months of August/September indicates an overall vertical velocity of -0.002 m/s with a standard deviation of 0.013 m/s, agreeing well with previous studies. Overall mean of the diurnal variation of vertical velocity for the study period from surface to 500 m height is 0.0018 m/s with a standard error of 0.00095 m/s. Seasonal mean daytime vertical winds suggest generally downward motion in Winter and upward motion in Summer. Validation of the derived divergence and vertical motion against a regional climate model (Weather Forecast and Research, WRF) at a spatial resolution of 12 km, as well as clear-sky vs. cloudy conditions comparisons will also be presented.

Future sea ice conditions and weather forecasts in the Arctic: Implications for Arctic shipping.

PubMed

Gascard, Jean-Claude; Riemann-Campe, Kathrin; Gerdes, Rüdiger; Schyberg, Harald; Randriamampianina, Roger; Karcher, Michael; Zhang, Jinlun; Rafizadeh, Mehrad

2017-12-01

The ability to forecast sea ice (both extent and thickness) and weather conditions are the major factors when it comes to safe marine transportation in the Arctic Ocean. This paper presents findings focusing on sea ice and weather prediction in the Arctic Ocean for navigation purposes, in particular along the Northeast Passage. Based on comparison with the observed sea ice concentrations for validation, the best performing Earth system models from the Intergovernmental Panel on Climate Change (IPCC) program (CMIP5-Coupled Model Intercomparison Project phase 5) were selected to provide ranges of potential future sea ice conditions. Our results showed that, despite a general tendency toward less sea ice cover in summer, internal variability will still be large and shipping along the Northeast Passage might still be hampered by sea ice blocking narrow passages. This will make sea ice forecasts on shorter time and space scales and Arctic weather prediction even more important.

Precipitation Processes Derived from TRMM Satellite Data, Cloud Resolving Model and Field Campaigns

NASA Technical Reports Server (NTRS)

Tao, W.-K.; Lang, S.; Simpson, J.; Meneghini, R.; Halverson, J.; Johnson, R.; Adler, R.; Einaudi, Franco (Technical Monitor)

2001-01-01

Rainfall is a key link in the hydrologic cycle and is a primary heat source for the atmosphere. The vertical distribution of latent-heat release, which is accompanied by rainfall, modulates the large-scale circulations of the tropics and in turn can impact midlatitude weather. This latent heat release is a consequence of phase changes between vapor, liquid. and solid water. Present large-scale weather and climate models can simulate cloud latent heat release only crudely thus reducing their confidence in predictions on both global and regional scales. In this paper, NASA Tropical Rainfall Measuring (TRMM) precipitation radar (PR) derived rainfall information and the Goddard Convective and Stratiform Heating (CSH) algorithm used to estimate the four-dimensional structure of global monthly latent heating and rainfall profiles over the global tropics from December 1997 to October 2000. Rainfall latent heating and radar reflectively structure between ENSO (1997-1998 winter) and non-ENSO (1998-1999 winter) periods are examined and compared. The seasonal variation of heating over various geographic locations (i.e. Indian ocean vs west Pacific; Africa vs S. America) are also analyzed. In addition, the relationship between rainfall latent heating maximum heating level), radar reflectively and SST are examined.

Effects of synoptic patterns on atmospheric chemistry and aerosols during the Arctic Ocean Expedition 1996

NASA Astrophysics Data System (ADS)

Nilsson, E. Douglas; Barr, Sumner

2001-12-01

The atmospheric program on the Arctic Ocean Expedition of July through September 1996 (AOE-96) was focused on aerosol climate feedback. The expedition took place close to the saddle point between a semipersistent anticyclonic ridge from near Scandinavia to the Arctic coast of eastern Siberia and a trough from the Canadian archipelago across the pole to north central Siberia. The weather varied from anticyclonic clear-sky conditions to cyclonic cloudy conditions, and 13 identifiable migratory features (frontal bands, wave disturbances) clearly influenced local weather, clouds, atmospheric transport, and chemistry. This includes an explosive polar cyclone, born at the lateral heat gradient between Greenland and the pack ice rather than between open sea and the pack ice. The synoptic scale weather systems caused the strongest variability in trace gases (O3 in particular) and aerosols, and also strong variability in the cloud cover. The formation of air masses over the pack ice primarily depends on if there is cyclonic (convergent) or anticyclonic (divergent) flow. Cyclonic flow resulted in a modified marine air mass loaded with vapor, but with low aerosol number concentrations owing to frequent clouds and fogs and efficient cloud scavenging of the aerosol. Anticyclonic flow resulted in almost continental air masses with clear sky, long residence time over the pack ice and subsidence slowly replacing the boundary layer with free tropospheric air, low vapor concentrations, but large aerosol number in lack of efficient cloud scavenging. The synoptic variability and advection from south of the ice edge were weaker than during the predecessor International Arctic Ocean Expedition in 1991 (IAOE-91), when on average the sampled air spent 55 hours over the pack ice compared to more than 120 hours during AOE-96, owing to exceptionally high cyclone activity in 1991. This caused a large difference in atmospheric transport, chemistry, and aerosols between the two expeditions.

Weather and climate needs for Lidar observations from space and concepts for their realization. [wind, temperature, moisture, and pressure data needs

NASA Technical Reports Server (NTRS)

Atlas, D.; Korb, C. L.

1980-01-01

The spectrum of weather and climate needs for Lidar observations from space is discussed with emphasis on the requirements for wind, temperature, moisture, and pressure data. It is shown that winds are required to realistically depict all atmospheric scales in the tropics and the smaller scales at higher latitudes, where both temperature and wind profiles are necessary. The need for means to estimate air-sea exchanges of sensible and latent heat also is noted. A concept for achieving this through a combination of Lidar cloud top heights and IR cloud top temperatures of cloud streets formed during cold air outbreaks over the warmer ocean is outlined. Recent theoretical feasibility studies concerning the profiling of temperatures, pressure, and humidity by differential absorption Lidar (DIAL) from space and expected accuracies are reviewed. An alternative approach to Doppler Lidar wind measurements also is presented. The concept involves the measurement of the displacement of the aerosol backscatter pattern, at constant heights, between two successive scans of the same area, one ahead of the spacecraft and the other behind it a few minutes later. Finally, an integrated space Lidar system capable of measuring temperature, pressure, humidity, and winds which combines the DIAL methods with the aerosol pattern displacement concept is described.

Innovative Visualizations Shed Light on Avian Nocturnal Migration

PubMed Central

Farnsworth, Andrew; Aelterman, Bart; Alves, Jose A.; Azijn, Kevin; Bernstein, Garrett; Branco, Sérgio; Desmet, Peter; Dokter, Adriaan M.; Horton, Kyle; Kelling, Steve; Kelly, Jeffrey F.; Leijnse, Hidde; Rong, Jingjing; Sheldon, Daniel; Van den Broeck, Wouter; Van Den Meersche, Jan Klaas; Van Doren, Benjamin Mark; van Gasteren, Hans

2016-01-01

Globally, billions of flying animals undergo seasonal migrations, many of which occur at night. The temporal and spatial scales at which migrations occur and our inability to directly observe these nocturnal movements makes monitoring and characterizing this critical period in migratory animals’ life cycles difficult. Remote sensing, therefore, has played an important role in our understanding of large-scale nocturnal bird migrations. Weather surveillance radar networks in Europe and North America have great potential for long-term low-cost monitoring of bird migration at scales that have previously been impossible to achieve. Such long-term monitoring, however, poses a number of challenges for the ornithological and ecological communities: how does one take advantage of this vast data resource, integrate information across multiple sensors and large spatial and temporal scales, and visually represent the data for interpretation and dissemination, considering the dynamic nature of migration? We assembled an interdisciplinary team of ecologists, meteorologists, computer scientists, and graphic designers to develop two different flow visualizations, which are interactive and open source, in order to create novel representations of broad-front nocturnal bird migration to address a primary impediment to long-term, large-scale nocturnal migration monitoring. We have applied these visualization techniques to mass bird migration events recorded by two different weather surveillance radar networks covering regions in Europe and North America. These applications show the flexibility and portability of such an approach. The visualizations provide an intuitive representation of the scale and dynamics of these complex systems, are easily accessible for a broad interest group, and are biologically insightful. Additionally, they facilitate fundamental ecological research, conservation, mitigation of human–wildlife conflicts, improvement of meteorological products, and public outreach, education, and engagement. PMID:27557096

Innovative Visualizations Shed Light on Avian Nocturnal Migration.

PubMed

Shamoun-Baranes, Judy; Farnsworth, Andrew; Aelterman, Bart; Alves, Jose A; Azijn, Kevin; Bernstein, Garrett; Branco, Sérgio; Desmet, Peter; Dokter, Adriaan M; Horton, Kyle; Kelling, Steve; Kelly, Jeffrey F; Leijnse, Hidde; Rong, Jingjing; Sheldon, Daniel; Van den Broeck, Wouter; Van Den Meersche, Jan Klaas; Van Doren, Benjamin Mark; van Gasteren, Hans

2016-01-01

Globally, billions of flying animals undergo seasonal migrations, many of which occur at night. The temporal and spatial scales at which migrations occur and our inability to directly observe these nocturnal movements makes monitoring and characterizing this critical period in migratory animals' life cycles difficult. Remote sensing, therefore, has played an important role in our understanding of large-scale nocturnal bird migrations. Weather surveillance radar networks in Europe and North America have great potential for long-term low-cost monitoring of bird migration at scales that have previously been impossible to achieve. Such long-term monitoring, however, poses a number of challenges for the ornithological and ecological communities: how does one take advantage of this vast data resource, integrate information across multiple sensors and large spatial and temporal scales, and visually represent the data for interpretation and dissemination, considering the dynamic nature of migration? We assembled an interdisciplinary team of ecologists, meteorologists, computer scientists, and graphic designers to develop two different flow visualizations, which are interactive and open source, in order to create novel representations of broad-front nocturnal bird migration to address a primary impediment to long-term, large-scale nocturnal migration monitoring. We have applied these visualization techniques to mass bird migration events recorded by two different weather surveillance radar networks covering regions in Europe and North America. These applications show the flexibility and portability of such an approach. The visualizations provide an intuitive representation of the scale and dynamics of these complex systems, are easily accessible for a broad interest group, and are biologically insightful. Additionally, they facilitate fundamental ecological research, conservation, mitigation of human-wildlife conflicts, improvement of meteorological products, and public outreach, education, and engagement.

Prospects for Improved Forecasts of Weather and Short-Term Climate Variability on Subseasonal (2-Week to 2-Month) Times Scales

NASA Technical Reports Server (NTRS)

Schubert, Siegfried; Dole, Randall; vandenDool, Huug; Suarez, Max; Waliser, Duane

2002-01-01

This workshop, held in April 2002, brought together various Earth Sciences experts to focus on the subseasonal prediction problem. While substantial advances have occurred over the last few decades in both weather and seasonal prediction, progress in improving predictions on these intermediate time scales (time scales ranging from about two weeks to two months) has been slow. The goals of the workshop were to get an assessment of the "state of the art" in predictive skill on these time scales, to determine the potential sources of "untapped" predictive skill, and to make recommendations for a course of action that will accelerate progress in this area. One of the key conclusions of the workshop was that there is compelling evidence for predictability at forecast lead times substantially longer than two weeks. Tropical diabatic heating and soil wetness were singled out as particularly important processes affecting predictability on these time scales. Predictability was also linked to various low-frequency atmospheric "phenomena" such as the annular modes in high latitudes (including their connections to the stratosphere), the Pacific/North American (PNA) pattern, and the Madden Julian Oscillation (MJO). The latter, in particular, was highlighted as a key source of untapped predictability in the tropics and subtropics, including the Asian and Australian monsoon regions.

Weather And Death On Mount Everest: An Analysis Of The Into Thin Air Storm.

NASA Astrophysics Data System (ADS)

Moore, G. W. K.; Semple, John L.

2006-04-01

Scientific interest in Mount Everest has been largely focused on the physiology of hypoxia caused by the summit's low barometric pressure. Although weather is recognized as a significant risk for climbers on the mountain, it has not been extensively studied. In this paper, we reconstruct the meteorological conditions associated with the deadly outbreak of high-impact weather on Mount Everest that occurred in May 1996 and was the subject of the best-selling book Into Thin Air. The authors show that during this event, two jet streaks—an upper-level short-wave trough and an intrusion of stratospheric air into the upper troposphere—were present in the vicinity of Mount Everest. Meanwhile, in the lower troposphere, there was convergence of water vapor transport from both the Arabian Sea and the Bay of Bengal into the region to the south of Mount Everest. The authors propose that the ageostrophic circulation associated with the upper-level features resulted in a region of large-scale ascent near Mount Everest that, in combination with the anomalous availability of moisture in the region, triggered convective activity. The resulting high-impact weather trapped over 20 climbers on Mount Everest's exposed upper slopes leading to the deaths of 8. These synoptic-scale characteristics provide some expectation of predicting life-threatening high-altitude storms in the Himalayas. In addition, the authors argue that the falling barometric pressure and the presence of ozone-rich stratospheric air that occurred near the summit of Mount Everest during this event could have shifted a coping climber from a state of brittle tolerance to physiological distress.

Altered carbon cycling and coupled changes in Early Cretaceous weathering patterns: Evidence from integrated carbon isotope and sandstone records of the western Tethys

NASA Astrophysics Data System (ADS)

Wortmann, Ulrich Georg; Herrle, Jens Olaf; Weissert, Helmut

2004-03-01

In this study we investigate if a major perturbation of the Early Cretaceous carbon cycle was accompanied by altered weathering and erosion rates. The large Aptian carbon isotope anomaly records the response of the biosphere to widespread volcanic activity and probably resulting changes in atmospheric pCO2 levels. Elevated pCO2 levels should also result in an accelerated hydrological cycle and increased silicate weathering, creating a negative feedback loop removing CO2 from the atmosphere. We propose to interpret the widespread occurrence of quartz sandstones in the Tethys-Atlantic seaway as a result of altered weathering and erosion rates in the wake of the Aptian carbon cycle excursion. We challenge the traditional notion that these are 'flysch' deposits associated with Early Cretaceous orogenic movements in the western Tethys. We propose that these sandstones were most likely part of a large conveyor belt system, acting along the Iberian and European margin of the Tethys seaway. Using chemostratigraphic correlations, we show that the activity of this system was only short-lived and coeval with changes in coastal ecology and the Aptian carbon cycle perturbations. We tentatively relate the existence of this system to a transient climate regime, characterized by fluctuating pCO2 levels.

Humidity Bias and Effect on Simulated Aerosol Optical Properties during the Ganges Valley Experiment

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

Feng, Yan; Cadeddu, M.; Kotamarthi, V. R.

2016-07-10

The radiosonde humidity profiles available during the Ganges Valley Experiment were compared to those simulated from the regional Weather Research and Forecasting (WRF) model coupled with a chemistry module (WRF -Chern) and the global reanalysis datasets. Large biases were revealed. On a monthly mean basis at Nainital, located in northern India, the WRFChern model simulates a large moist bias in the free troposphere (up to +20%) as well as a large dry bias in the boundary layer (up to -30%). While the overall pattern of the biases is similar, the magnitude of the biases varies from time to time andmore » from one location to another. At Thiruvananthapuram, the magnitude of the dry bias is smaller, and in contrast to Nainital, the higher-resolution regional WRF -Chern model generates larger moist biases in the upper troposphere than the global reanalysis data. Furthermore, the humidity biases in the upper troposphere, while significant, have little impact on the model estimation of column aerosol optical depth (AOD). The frequent occurrences of the dry boundary-layer bias simulated by the large-scale models tend to lead to the underestimation of AOD. It is thus important to quantify the humidity vertical profiles for aerosol simulations over South Asia.« less

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 ...

Quantifying the variability of potential black carbon transport from cropland burning in Russia driven by atmospheric blocking events

NASA Astrophysics Data System (ADS)

Hall, Joanne; Loboda, Tatiana

2018-05-01

The deposition of short-lived aerosols and pollutants on snow above the Arctic Circle transported from northern mid-latitudes have amplified the short term warming in the Arctic region. Specifically, black carbon has received a great deal of attention due to its absorptive efficiency and its fairly complex influence on the climate. Cropland burning in Russia is a large contributor to the black carbon emissions deposited directly onto the snow in the Arctic region during the spring when the impact on the snow/ice albedo is at its highest. In this study, our focus is on identifying a possible atmospheric pattern that may enhance the transport of black carbon emissions from cropland burning in Russia to the snow-covered Arctic. Specifically, atmospheric blocking events are large-scale patterns in the atmospheric pressure field that are nearly stationary and act to block migratory cyclones. The persistent low-level wind patterns associated with these mid-latitude weather patterns are likely to accelerate potential transport and increase the success of transport of black carbon emissions to the snow-covered Arctic during the spring. Our results revealed that overall, in March, the transport time of hypothetical black carbon emissions from Russian cropland burning to the Arctic snow is shorter (in some areas over 50 hours less at higher injection heights) and the success rate is also much higher (in some areas up to 100% more successful) during atmospheric blocking conditions as compared to conditions without an atmospheric blocking event. The enhanced transport of black carbon has important implications for the efficacy of deposited black carbon. Therefore, understanding these relationships could lead to possible mitigation strategies for reducing the impact of deposition of black carbon from crop residue burning in the Arctic.

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.

Optimizing Placement of Weather Stations: Exploring Objective Functions of Meaningful Combinations of Multiple Weather Variables

NASA Astrophysics Data System (ADS)

Snyder, A.; Dietterich, T.; Selker, J. S.

2017-12-01

Many regions of the world lack ground-based weather data due to inadequate or unreliable weather station networks. For example, most countries in Sub-Saharan Africa have unreliable, sparse networks of weather stations. The absence of these data can have consequences on weather forecasting, prediction of severe weather events, agricultural planning, and climate change monitoring. The Trans-African Hydro-Meteorological Observatory (TAHMO.org) project seeks to address these problems by deploying and operating a large network of weather stations throughout Sub-Saharan Africa. To design the TAHMO network, we must determine where to place weather stations within each country. We should consider how we can create accurate spatio-temporal maps of weather data and how to balance the desired accuracy of each weather variable of interest (precipitation, temperature, relative humidity, etc.). We can express this problem as a joint optimization of multiple weather variables, given a fixed number of weather stations. We use reanalysis data as the best representation of the "true" weather patterns that occur in the region of interest. For each possible combination of sites, we interpolate the reanalysis data between selected locations and calculate the mean average error between the reanalysis ("true") data and the interpolated data. In order to formulate our multi-variate optimization problem, we explore different methods of weighting each weather variable in our objective function. These methods include systematic variation of weights to determine which weather variables have the strongest influence on the network design, as well as combinations targeted for specific purposes. For example, we can use computed evapotranspiration as a metric that combines many weather variables in a way that is meaningful for agricultural and hydrological applications. We compare the errors of the weather station networks produced by each optimization problem formulation. We also compare these errors to those of manually designed weather station networks in West Africa, planned by the respective host-country's meteorological agency.

Dynamic soil properties in response to anthropogenic disturbance

NASA Astrophysics Data System (ADS)

Vanacker, Veerle; Ortega, Raúl

2013-04-01

Anthropogenic disturbance of natural vegetation can profoundly alter the physical, chemical and biological processes within soils. Rapid removal of topsoil during intense farming can result in an imbalance between soil production through chemical weathering and physical erosion, with direct implications on local biogeochemical cycling. However, the feedbacks between soil erosion, chemical weathering and biogeochemical cycling in response to anthropogenic forcing are not yet fully understood. Here, we study dynamic soil properties for a rapidly changing anthropogenic landscape, and focus on the coupling between physical erosion, soil production and soil chemical weathering. The archaeological site of Santa Maria de Melque (Toledo, Central Spain) was selected for its remarkably long occupation history dating back to the 7th century AD. As part of the agricultural complex, four retention reservoirs were built in the Early Middle Ages. The sedimentary archive was used to track the evolution in sedimentation rates and geochemical properties of the sediment. Catchment-wide soil erosion rates vary slightly between the various occupation phases (7th century-now), but are of the same magnitude as the cosmogenic nuclide-derived erosion rates. However, there exists large spatial variation in physical erosion rates that are coupled with chemical weathering intensities. The sedimentary records suggest that there are important changes in the spatial pattern of sediment source areas through time as a result of changing land use patterns

The NASA-Goddard Multi-Scale Modeling Framework - Land Information System: Global Land/atmosphere Interaction with Resolved Convection

NASA Technical Reports Server (NTRS)

Mohr, Karen Irene; Tao, Wei-Kuo; Chern, Jiun-Dar; Kumar, Sujay V.; Peters-Lidard, Christa D.

2013-01-01

The present generation of general circulation models (GCM) use parameterized cumulus schemes and run at hydrostatic grid resolutions. To improve the representation of cloud-scale moist processes and landeatmosphere interactions, a global, Multi-scale Modeling Framework (MMF) coupled to the Land Information System (LIS) has been developed at NASA-Goddard Space Flight Center. The MMFeLIS has three components, a finite-volume (fv) GCM (Goddard Earth Observing System Ver. 4, GEOS-4), a 2D cloud-resolving model (Goddard Cumulus Ensemble, GCE), and the LIS, representing the large-scale atmospheric circulation, cloud processes, and land surface processes, respectively. The non-hydrostatic GCE model replaces the single-column cumulus parameterization of fvGCM. The model grid is composed of an array of fvGCM gridcells each with a series of embedded GCE models. A horizontal coupling strategy, GCE4fvGCM4Coupler4LIS, offered significant computational efficiency, with the scalability and I/O capabilities of LIS permitting landeatmosphere interactions at cloud-scale. Global simulations of 2007e2008 and comparisons to observations and reanalysis products were conducted. Using two different versions of the same land surface model but the same initial conditions, divergence in regional, synoptic-scale surface pressure patterns emerged within two weeks. The sensitivity of largescale circulations to land surface model physics revealed significant functional value to using a scalable, multi-model land surface modeling system in global weather and climate prediction.

Kinematic dynamo action in square and hexagonal patterns.

PubMed

Favier, B; Proctor, M R E

2013-11-01

We consider kinematic dynamo action in rapidly rotating Boussinesq convection just above onset. The velocity is constrained to have either a square or a hexagonal pattern. For the square pattern, large-scale dynamo action is observed at onset, with most of the magnetic energy being contained in the horizontally averaged component. As the magnetic Reynolds number increases, small-scale dynamo action becomes possible, reducing the overall growth rate of the dynamo. For the hexagonal pattern, the breaking of symmetry between up and down flows results in an effective pumping velocity. For intermediate rotation rates, this additional effect can prevent the growth of any mean-field dynamo, so that only a small-scale dynamo is eventually possible at large enough magnetic Reynolds number. For very large rotation rates, this pumping term becomes negligible, and the dynamo properties of square and hexagonal patterns are qualitatively similar. These results hold for both perfectly conducting and infinite magnetic permeability boundary conditions.

Large-Scale Disasters

NASA Astrophysics Data System (ADS)

Gad-El-Hak, Mohamed

"Extreme" events - including climatic events, such as hurricanes, tornadoes, and drought - can cause massive disruption to society, including large death tolls and property damage in the billions of dollars. Events in recent years have shown the importance of being prepared and that countries need to work together to help alleviate the resulting pain and suffering. This volume presents a review of the broad research field of large-scale disasters. It establishes a common framework for predicting, controlling and managing both manmade and natural disasters. There is a particular focus on events caused by weather and climate change. Other topics include air pollution, tsunamis, disaster modeling, the use of remote sensing and the logistics of disaster management. It will appeal to scientists, engineers, first responders and health-care professionals, in addition to graduate students and researchers who have an interest in the prediction, prevention or mitigation of large-scale disasters.

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.

A Big Data Approach for Situation-Aware estimation, correction and prediction of aerosol effects, based on MODIS Joint Atmosphere product (collection 6) time series data

NASA Astrophysics Data System (ADS)

Singh, A. K.; Toshniwal, D.

2017-12-01

The MODIS Joint Atmosphere product, MODATML2 and MYDATML2 L2/3 provided by LAADS DAAC (Level-1 and Atmosphere Archive & Distribution System Distributed Active Archive Center) re-sampled from medium resolution MODIS Terra /Aqua Satellites data at 5km scale, contains Cloud Reflectance, Cloud Top Temperature, Water Vapor, Aerosol Optical Depth/Thickness, Humidity data. These re-sampled data, when used for deriving climatic effects of aerosols (particularly in case of cooling effect) still exposes limitations in presence of uncertainty measures in atmospheric artifacts such as aerosol, cloud, cirrus cloud etc. The effect of uncertainty measures in these artifacts imposes an important challenge for estimation of aerosol effects, adequately affecting precise regional weather modeling and predictions: Forecasting and recommendation applications developed largely depend on these short-term local conditions (e.g. City/Locality based recommendations to citizens/farmers based on local weather models). Our approach inculcates artificial intelligence technique for representing heterogeneous data(satellite data along with air quality data from local weather stations (i.e. in situ data)) to learn, correct and predict aerosol effects in the presence of cloud and other atmospheric artifacts, defusing Spatio-temporal correlations and regressions. The Big Data process pipeline consisting correlation and regression techniques developed on Apache Spark platform can easily scale for large data sets including many tiles (scenes) and over widened time-scale. Keywords: Climatic Effects of Aerosols, Situation-Aware, Big Data, Apache Spark, MODIS Terra /Aqua, Time Series

Numerical study of Asian dust transport during the springtime of 2001 simulated with the Chemical Weather Forecasting System (CFORS) model

NASA Astrophysics Data System (ADS)

Uno, Itsushi; Satake, Shinsuke; Carmichael, Gregory R.; Tang, Youhua; Wang, Zifa; Takemura, Toshihiko; Sugimoto, Nobuo; Shimizu, Atsushi; Murayama, Toshiyuki; Cahill, Thomas A.; Cliff, Steven; Uematsu, Mitsuo; Ohta, Sachio; Quinn, Patricia K.; Bates, Timothy S.

2004-10-01

The regional-scale aerosol transport model Chemical Weather Forecasting System (CFORS) is used for analysis of large-scale dust phenomena during the Asian Pacific Regional Characterization Experiment (ACE-Asia) intensive observation. Dust modeling results are examined with the surface weather reports, satellite-derived dust index (Total Ozone Mapping Spectrometer (TOMS) Aerosol Index (AI)), Mie-scattering lidar observation, and surface aerosol observations. The CFORS dust results are shown to accurately reproduce many of the important observed features. Model analysis shows that the simulated dust vertical loading correlates well with TOMS AI and that the dust loading is transported with the meandering of the synoptic-scale temperature field at the 500-hPa level. Quantitative examination of aerosol optical depth shows that model predictions are within 20% difference of the lidar observations for the major dust episodes. The structure of the ACE-Asia Perfect Dust Storm, which occurred in early April, is clarified with the help of the CFORS model analysis. This storm consisted of two boundary layer components and one elevated dust (>6-km height) feature (resulting from the movement of two large low-pressure systems). Time variation of the CFORS dust fields shows the correct onset timing of the elevated dust for each observation site, but the model results tend to overpredict dust concentrations at lower latitude sites. The horizontal transport flux at 130°E longitude is examined, and the overall dust transport flux at 130°E during March-April is evaluated to be 55 Tg.

Improving Large-scale Biomass Burning Carbon Consumption and Emissions Estimates in the Former Soviet Union based on Fire Weather

NASA Astrophysics Data System (ADS)

Westberg, D. J.; Soja, A. J.; Tchebakova, N.; Parfenova, E. I.; Kukavskaya, E.; de Groot, B.; McRae, D.; Conard, S. G.; Stackhouse, P. W., Jr.

2012-12-01

Estimating the amount of biomass burned during fire events is challenging, particularly in remote and diverse regions, like those of the Former Soviet Union (FSU). Historically, we have typically assumed 25 tons of carbon per hectare (tC/ha) is emitted, however depending on the ecosystem and severity, biomass burning emissions can range from 2 to 75 tC/ha. Ecosystems in the FSU span from the tundra through the taiga to the forest-steppe, steppe and desserts and include the extensive West Siberian lowlands, permafrost-lain forests and agricultural lands. Excluding this landscape disparity results in inaccurate emissions estimates and incorrect assumptions in the transport of these emissions. In this work, we present emissions based on a hybrid ecosystem map and explicit estimates of fuel that consider the depth of burning based on the Canadian Forest Fire Weather Index System. Specifically, the ecosystem map is a fusion of satellite-based data, a detailed ecosystem map and Alexeyev and Birdsey carbon storage data, which is used to build carbon databases that include the forest overstory and understory, litter, peatlands and soil organic material for the FSU. We provide a range of potential carbon consumption estimates for low- to high-severity fires across the FSU that can be used with fire weather indices to more accurately estimate fire emissions. These data can be incorporated at ecoregion and administrative territory scales and are optimized for use in large-scale Chemical Transport Models. Additionally, paired with future climate scenarios and ecoregion cover, these carbon consumption data can be used to estimate potential emissions.

Ground-water recharge in the arid and semiarid southwestern United States - Climatic and geologic framework: Chapter A in Ground-water recharge in the arid and semiarid southwestern United States (Professional Paper 1703)

USGS Publications Warehouse

Stonestrom, David A.; Harrill, James R.; Stonestrom, David A.; Constantz, Jim; Ferré, Ty P.A.; Leake, Stanley A.

2007-01-01

Ground-water recharge in the arid and semiarid southwestern United States results from the complex interplay of climate, geology, and vegetation across widely ranging spatial and temporal scales. Present-day recharge tends to be narrowly focused in time and space. Widespread water-table declines accompanied agricultural development during the twentieth century, demonstrating that sustainable ground-water supplies are not guaranteed when part of the extracted resource represents paleorecharge. Climatic controls on ground-water recharge range from seasonal cycles of summer monsoonal and winter frontal storms to multimillennial cycles of glacial and interglacial periods. Precipitation patterns reflect global-scale interactions among the oceans, atmosphere, and continents. Large-scale climatic influences associated with El Niño and Pacific Decadal Oscillations strongly but irregularly control weather in the study area, so that year-to-year variations in precipitation and ground-water recharge are large and difficult to predict. Proxy data indicate geologically recent periods of multidecadal droughts unlike any in the modern instrumental record. Anthropogenically induced climate change likely will reduce ground-water recharge through diminished snowpack at higher elevations, and perhaps through increased drought. Future changes in El Niño and monsoonal patterns, both crucial to precipitation in the study area, are highly uncertain in current models. Land-use modifications influence ground-water recharge directly through vegetation, irrigation, and impermeable area, and indirectly through climate change. High ranges bounding the study area—the San Bernadino Mountains and Sierra Nevada to the west, and the Wasatch and southern Colorado Rocky Mountains to the east—provide external geologic controls on ground-water recharge. Internal geologic controls stem from tectonic processes that led to numerous, variably connected alluvial-filled basins, exposure of extensive Paleozoic aquifers in mountainous recharge areas, and distinct modes of recharge in the Colorado Plateau and Basin and Range subregions.

A two-tier atmospheric circulation classification scheme for the European-North Atlantic region

NASA Astrophysics Data System (ADS)

Guentchev, Galina S.; Winkler, Julie A.

A two-tier classification of large-scale atmospheric circulation was developed for the European-North-Atlantic domain. The classification was constructed using a combination of principal components and k-means cluster analysis applied to reanalysis fields of mean sea-level pressure for 1951-2004. Separate classifications were developed for the winter, spring, summer, and fall seasons. For each season, the two classification tiers were identified independently, such that the definition of one tier does not depend on the other tier having already been defined. The first tier of the classification is comprised of supertype patterns. These broad-scale circulation classes are useful for generalized analyses such as investigations of the temporal trends in circulation frequency and persistence. The second, more detailed tier consists of circulation types and is useful for numerous applied research questions regarding the relationships between large-scale circulation and local and regional climate. Three to five supertypes and up to 19 circulation types were identified for each season. An intuitive nomenclature scheme based on the physical entities (i.e., anomaly centers) which dominate the specific patterns was used to label each of the supertypes and types. Two example applications illustrate the potential usefulness of a two-tier classification. In the first application, the temporal variability of the supertypes was evaluated. In general, the frequency and persistence of supertypes dominated by anticyclonic circulation increased during the study period, whereas the supertypes dominated by cyclonic features decreased in frequency and persistence. The usefulness of the derived circulation types was exemplified by an analysis of the circulation associated with heat waves and cold spells reported at several cities in Bulgaria. These extreme temperature events were found to occur with a small number of circulation types, a finding that can be helpful in understanding past variability and projecting future changes in the occurrence of extreme weather and climate events.

Climatological aspects of mesoscale cyclogenesis over the Ross Sea and Ross Ice shelf regions of Antarctica

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

Carrasco, J.F.; Bromwich, D.H.

1994-11-01

A one-year (1988) statistical study of mesoscale cyclogenesis near Terra Nova Bay and Byrd Glacier, Antarctica, was conducted using high-resolution digital satellite imagery and automatic weather station data. Results indicate that on average two (one) mesoscale cyclones form near Terra Nova Bay (Byrd Glacier) each week, confirming these two locations as mesoscale cyclogeneis areas. The maximum (minimum) weekly frequency of mesoscale cyclones occurred during the summer (winter). The satellite survey of mesoscale vortices was extended over the Ross Sea and Ross Ice Shelf. Results suggest southern Marie Byrd Land as another area of mesoscale cyclone formation. Also, frequent mesoscale cyclonicmore » activity was noted over the Ross Sea and Ross Ice Shelf, where, on average, six and three mesoscale vortices were observed each week, respectively, with maximum (minimum) frequency during summer (winter) in both regions. The majority (70-80%) of the vortices were of comma-cloud type and were shallow. Only around 10% of the vortices near Terra Nova Bay and Byrd Glacier were classified as deep vortices, while over the Ross Sea and Ross Ice Shelf around 20% were found to be deep. The average large-scale pattern associated with cyclogenesis days near Terra Nova Bay suggests a slight decrease in the sea level pressure and 500-hPa geopotential height to the northwest of this area with respect to the annual average. This may be an indication of the average position of synoptic-scale cyclones entering the Ross Sea region. Comparison with a similar study but for 1984-85 shows that the overall mesoscale cyclogenesis activity was similar during the three years, but 1985 was found to be the year with greater occurrence of {open_quotes}significant{close_quotes} mesoscales cyclones. The large-scale pattern indicates that this greater activity is related to a deeper circumpolar trough and 500-hPa polar vortex for 1985 in comparison to 1984 and 1988. 64 refs., 13 figs., 5 tabs.« less

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.

Evidence for mechanical and chemical alteration of iron-nickel meteorites on Mars: Process insights for Meridiani Planum

USGS Publications Warehouse

Ashley, James W.; Golombek, M.P.; Christensen, P.R.; Squyres, S. W.; McCoy, T.J.; Schroder, C.; Fleischer, I.; Johnson, J. R.; Herkenhoff, K. E.; Parker, T.J.

2011-01-01

The weathering of meteorites found on Mars involves chemical and physical processes that can provide clues to climate conditions at the location of their discovery. Beginning on sol 1961, the Opportunity rover encountered three large iron meteorites within a few hundred meters of each other. In order of discovery, these rocks have been assigned the unofficial names Block Island, Shelter Island, and Mackinac Island. Each rock presents a unique but complimentary set of features that increase our understanding of weathering processes at Meridiani Planum. Significant morphologic characteristics interpretable as weathering features include (1) a large pit in Block Island, lined with delicate iron protrusions suggestive of inclusion removal by corrosive interaction; (2) differentially eroded kamacite and taenite lamellae in Block Island and Shelter Island, providing relative timing through crosscutting relationships with deposition of (3) an iron oxide-rich dark coating; (4) regmaglypted surfaces testifying to regions of minimal surface modification, with other regions in the same meteorites exhibiting (5) large-scale, cavernous weathering (in Shelter Island and Mackinac Island). We conclude that the current size of the rocks is approximate to their original postfall contours. Their morphology thus likely results from a combination of atmospheric interaction and postfall weathering effects. Among our specific findings is evidence supporting (1) at least one possible episode of aqueous acidic exposure for Block Island; (2) ripple migration over portions of the meteorites; (3) a minimum of two separate episodes of wind abrasion; alternating with (4) at least one episode of coating-forming chemical alteration, most likely at subzero temperatures. Copyright 2011 by the American Geophysical Union.

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.

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...

Evaluation of the WRF model for precipitation downscaling on orographic complex islands

NASA Astrophysics Data System (ADS)

Díaz, Juan P.; González, Albano; Expósito, Francisco; Pérez, Juan C.

2010-05-01

General Circulation Models (GCMs) have proven to be an effective tool to simulate many aspects of large-scale and global climate. However, their applicability to climate impact studies is limited by their capabilities to resolve regional scale situations. In this sense, dynamical downscaling techniques are an appropriate alternative to estimate high resolution regional climatologies. In this work, the Weather Research and Forecasting model (WRF) has been used to simulate precipitations over the Canary Islands region during 2009. The precipitation patterns over Canary Islands, located at North Atlantic region, show large gradients over a relatively small geographical area due to large scale factors such as Trade Winds regime predominant in the area and mesoscale factors mainly due to the complex terrain. Sensitivity study of simulated WRF precipitations to variations in model setup and parameterizations was carried out. Thus, WRF experiments were performed using two way nesting at 3 km horizontal grid spacing and 28 vertical levels in the Canaries inner domain. The initial and lateral and lower boundary conditions for the outer domain were provided at 6 hourly intervals by NCEP FNL (Final) Operational Global Analysis data on 1.0x1.0 degree resolution interpolated onto the WRF model grid. Numerous model options have been tested, including different microphysics schemes, cumulus parameterizations and nudging configuration Positive-definite moisture advection condition was also checked. Two integration approaches were analyzed: a 1-year continuous long-term integration and a consecutive short-term monthly reinitialized integration. To assess the accuracy of our simulations, model results are compared against observational datasets obtained from a network of meteorological stations in the region. In general, we can observe that the regional model is able to reproduce the spatial distribution of precipitation, but overestimates rainfall, mainly during strong precipitation events.

Spring Soil Temperature Anomalies over Northwest U.S. and later Spring-Summer Droughts/Floods over Southern Plains and Adjacent Areas

NASA Astrophysics Data System (ADS)

Xue, Y.; Diallo, I.; Li, W.; Neelin, J. D.; Chu, P. C.; Vasic, R.; Zhu, Y.; LI, Q.; Robinson, D. A.

2017-12-01

Recurrent droughts/floods are high-impact meteorological events. Many studies have attributed these episodes to variability and anomaly of global sea surface temperatures (SST). However, studies have consistently shown that SST along is unable to fully explain the extreme climate events. Remote effects of large-scale spring land surface temperature (LST) and subsurface temperature (SUBT) variability in Northwest U.S. over the Rocky Mountain area on later spring-summer droughts/floods over the Southern Plains and adjacent areas, however, have been largely ignored. In this study, evidence from climate observations and model simulations addresses these effects. The Maximum Covariance Analysis of observational data identifies that a pronounce spring LST anomaly pattern over Northwest U.S. is closely associated with summer precipitation anomalies in Southern Plains: negative/positive spring LST anomaly is associated with the summer drought/flood over the Southern Plains. The global and regional weather forecast models were used to demonstrate a causal relationship. The modeling study suggests that the observed LST and SUBT anomalies produced about 29% and 31% of observed May 2015 heavy precipitation and June 2011 precipitation deficit, respectively. The analyses discovered that the LST/SUBT's downstream effects are associated with a large-scale atmospheric stationary wave extending eastward from the LST/SUBT anomaly region. For comparison, the SST effect was also tested and produced about 31% and 45% of the May 2015 heavy precipitation and June 2011 drought conditions, respectively. This study suggests that consideration of both SST and LST/SUBT anomalies are able to explain a substantial amount of variance in precipitation at sub-seasonal scale and inclusion of the LST/SUBT effect is essential to make reliable sub-seasonal and seasonal North American drought/flood predictions.

Data Mining for Understanding and Impriving Decision-Making Affecting Ground Delay Programs

NASA Technical Reports Server (NTRS)

Kulkarni, Deepak; Wang, Yao Xun; Sridhar, Banavar

2013-01-01

The continuous growth in the demand for air transportation results in an imbalance between airspace capacity and traffic demand. The airspace capacity of a region depends on the ability of the system to maintain safe separation between aircraft in the region. In addition to growing demand, the airspace capacity is severely limited by convective weather. During such conditions, traffic managers at the FAA's Air Traffic Control System Command Center (ATCSCC) and dispatchers at various Airlines' Operations Center (AOC) collaborate to mitigate the demand-capacity imbalance caused by weather. The end result is the implementation of a set of Traffic Flow Management (TFM) initiatives such as ground delay programs, reroute advisories, flow metering, and ground stops. Data Mining is the automated process of analyzing large sets of data and then extracting patterns in the data. Data mining tools are capable of predicting behaviors and future trends, allowing an organization to benefit from past experience in making knowledge-driven decisions. The work reported in this paper is focused on ground delay programs. Data mining algorithms have the potential to develop associations between weather patterns and the corresponding ground delay program responses. If successful, they can be used to improve and standardize TFM decision resulting in better predictability of traffic flows on days with reliable weather forecasts. The approach here seeks to develop a set of data mining and machine learning models and apply them to historical archives of weather observations and forecasts and TFM initiatives to determine the extent to which the theory can predict and explain the observed traffic flow behaviors.

Numerical simulation and analysis of the April 2013 Chicago floods

DOE PAGES

Campos, Edwin; Wang, Jiali

2015-09-08

The weather event associated to record Chicago floods on April 2013 is investigated by using the Weather Research and Forecasting (WRF) model. Observations at Argonne National Laboratory and multi-sensor (weather radar and rain gauge) precipitation data from the National Weather Service were employed to evaluate the model’s performance. The WRF model captured the synoptic-scale atmospheric features well, but the simulated 24-h accumulated precipitation and short-period temporal evolution of precipitation over the heavy-rain region were less successful. To investigate the potential reasons for the model bias, four supplementary sensitivity experiments using various microphysics schemes and cumulus parameterizations were designed. Of themore » five tested parameterizations, the WRF Single-Moment 6-class (WSM6) graupel scheme and Kain-Fritsch (KF) cumulus parameterization outperformed the others, such as Grell-Dévényi (GD) cumulus parameterization, which underestimated the precipitation by 30–50% on a regional-average scale. Morrison microphysics and KF outperformed the others for the spatial patterns of 24-h accumulated precipitation. The spatial correlation between observation and Morrison-KF was 0.45, higher than those for other simulations. All of the simulations underestimated the precipitation over northeastern Illinois (especially at Argonne) during 0400–0800 UTC 18 April because of weak ascending motion or small moisture. In conclusion, all of the simulations except WSM6-GD also underestimated the precipitation during 1200–1600 UTC 18 April because of weak southerly flow.« less

Spatio-temporal analysis of sub-hourly rainfall over Mumbai, India: Is statistical forecasting futile?

NASA Astrophysics Data System (ADS)

Singh, Jitendra; Sekharan, Sheeba; Karmakar, Subhankar; Ghosh, Subimal; Zope, P. E.; Eldho, T. I.

2017-04-01

Mumbai, the commercial and financial capital of India, experiences incessant annual rain episodes, mainly attributable to erratic rainfall pattern during monsoons and urban heat-island effect due to escalating urbanization, leading to increasing vulnerability to frequent flooding. After the infamous episode of 2005 Mumbai torrential rains when only two rain gauging stations existed, the governing civic body, the Municipal Corporation of Greater Mumbai (MCGM) came forward with an initiative to install 26 automatic weather stations (AWS) in June 2006 (MCGM 2007), which later increased to 60 AWS. A comprehensive statistical analysis to understand the spatio-temporal pattern of rainfall over Mumbai or any other coastal city in India has never been attempted earlier. In the current study, a thorough analysis of available rainfall data for 2006-2014 from these stations was performed; the 2013-2014 sub-hourly data from 26 AWS was found useful for further analyses due to their consistency and continuity. Correlogram cloud indicated no pattern of significant correlation when we considered the closest to the farthest gauging station from the base station; this impression was also supported by the semivariogram plots. Gini index values, a statistical measure of temporal non-uniformity, were found above 0.8 in visible majority showing an increasing trend in most gauging stations; this sufficiently led us to conclude that inconsistency in daily rainfall was gradually increasing with progress in monsoon. Interestingly, night rainfall was lesser compared to daytime rainfall. The pattern-less high spatio-temporal variation observed in Mumbai rainfall data signifies the futility of independently applying advanced statistical techniques, and thus calls for simultaneous inclusion of physics-centred models such as different meso-scale numerical weather prediction systems, particularly the Weather Research and Forecasting (WRF) model.

Do GCM's predict the climate.... Or the low frequency weather?

NASA Astrophysics Data System (ADS)

Lovejoy, S.; Schertzer, D.; Varon, D.

2012-04-01

Over twenty-five years ago, a three-regime scaling model was proposed describing the statistical variability of the atmosphere over time scales ranging from weather scales out to ≈ 100 kyrs. Using modern in situ data reanalyses, monthly surface series (at 5ox5o), 8 "multiproxy" (yearly) series of the Northern hemisphere from 1500 - 1980, and GRIP and Vostok paleotemperatures at 5.2 and ≈ 100 year resolutions (over the past 91-420 kyrs), we refine the model and show how it can be understood with the help of new developments in nonlinear dynamics, especially multifractals and cascades. In a scaling range, mean fluctuations in state variables such as temperature ΔT vary in power law manners ≈ Δt**H the where Δt is the duration. At small (weather) scales the fluctuation exponents are generally H>0; they grow with scale (Δt). At longer scales Δt >τw (≈ 10 days) H changes sign, the fluctuations decrease with scale; this is the low variability, "low frequency weather" regime. In this regime, the spectrum is a relatively flat "plateau", it's variability is low, stable, corresponding to our usual idea of "long term weather statistics". Finally for longer times, Δt>τc ≈ 10 - 100 years, once again H>0, so that the variability increases with scale: the true climate regime. These scaling regimes allow us to objectively define the weather as fluctuations over periods <τw, to define "climate states" as fluctuations at scale τc and then "climate change" as the fluctuations at longer periods (Δt>τc). We show that the intermediate low frequency weather regime is the result of the weather regime undergoing a "dimensional transition": at temporal scales longer than the typical lifetime of planetary structures (τw), the spatial degrees of freedom are rapidly quenched so that only the temporal degrees of freedom are important. This low frequency weather regime has statistical properties well reproduced not only by stochastic cascade models of weather, but also by control runs (i.e. without climate forcing) of GCM based climate forecasting systems including those of the Institut Pierre Simon Laplace (Paris) and the Earth Forecasting System (Hamburg). In order for these systems to go beyond simply predicting low frequency weather i.e. in order for them to predict the climate, they need appropriate climate forcings and/ or new internal mechanisms of variability. Using statistical scaling techniques we examine the scale dependence of fluctuations from forced and unforced GCM outputs, including from the ECHO-G and EFS simulations in the Millenium climate reconstruction project and compare this with data, multiproxies and paleo data. Our general conclusion is that the models systematically underestimate the multidecadal, multicentennial scale variability.

On the relationship between large-scale climate modes and regional synoptic patterns that drive Victorian rainfall

NASA Astrophysics Data System (ADS)

Verdon-Kidd, D. C.; Kiem, A. S.

2009-04-01

In this paper regional (synoptic) and large-scale climate drivers of rainfall are investigated for Victoria, Australia. A non-linear classification methodology known as self-organizing maps (SOM) is used to identify 20 key regional synoptic patterns, which are shown to capture a range of significant synoptic features known to influence the climate of the region. Rainfall distributions are assigned to each of the 20 patterns for nine rainfall stations located across Victoria, resulting in a clear distinction between wet and dry synoptic types at each station. The influence of large-scale climate modes on the frequency and timing of the regional synoptic patterns is also investigated. This analysis revealed that phase changes in the El Niño Southern Oscillation (ENSO), the Indian Ocean Dipole (IOD) and/or the Southern Annular Mode (SAM) are associated with a shift in the relative frequency of wet and dry synoptic types on an annual to inter-annual timescale. In addition, the relative frequency of synoptic types is shown to vary on a multi-decadal timescale, associated with changes in the Inter-decadal Pacific Oscillation (IPO). Importantly, these results highlight the potential to utilise the link between the regional synoptic patterns derived in this study and large-scale climate modes to improve rainfall forecasting for Victoria, both in the short- (i.e. seasonal) and long-term (i.e. decadal/multi-decadal scale). In addition, the regional and large-scale climate drivers identified in this study provide a benchmark by which the performance of Global Climate Models (GCMs) may be assessed.

Space Weather Tools of the Trade - A Changing Mix

NASA Astrophysics Data System (ADS)

Kunches, J.; Crowley, G.; Pilinski, M.; Winkler, C.; Fish, C. S.; Hunton, D.; Reynolds, A.; Azeem, I.

2014-12-01

Historically, operational space weather tools have focused on the large-scale. The Sun, solar wind, magnetosphere, and ionosphere were the domains that, rightly so, needed the attention of experimentalists and scientists to fashion the best sensors and physics-based models available. These initiatives resulted in significant improvements for operational forecasters. For example, geomagnetic storm predictions now do not have to rely on proxies for CMEs, such as type II sweep, but rather make use of available actual observations of CMEs from which the true velocity vector may be determined. The users of space weather services profited from the better large-scale observations, but now have expressed their desire for even better spatially and time-resolved granularity of products and services. This natural evolution towards refining products has ushered in the era of the smaller mission, the more efficient sensor. CubeSats and compact ionospheric monitors are examples of the instrumental suite now emerging to bring in this new era. This presentation will show examples of the new mix of smaller systems that enable finer, more well-resolved products and services for the operational world. A number of technologies are now in the marketplace demonstrating the value of more observations at a decreasing cost. In addition, new models are looming to take advantage of these better observations. Examples of models poised to take advantage of new observations will be given.

Weather is not significantly correlated with destination-specific transport-related physical activity among adults: A large-scale temporally matched analysis.

PubMed

Durand, Casey P; Zhang, Kai; Salvo, Deborah

2017-08-01

Weather is an element of the natural environment that could have a significant effect on physical activity. Existing research, however, indicates only modest correlations between measures of weather and physical activity. This prior work has been limited by a failure to use time-matched weather and physical activity data, or has not adequately examined the different domains of physical activity (transport, leisure, occupational, etc.). Our objective was to identify the correlation between weather variables and destination-specific transport-related physical activity in adults. Data were sourced from the California Household Travel Survey, collected in 2012-3. Weather variables included: relative humidity, temperature, wind speed, and precipitation. Transport-related physical activity (walking) was sourced from participant-recorded travel diaries. Three-part hurdle models were used to analyze the data. Results indicate statistically or substantively insignificant correlations between the weather variables and transport-related physical activity for all destination types. These results provide the strongest evidence to date that transport-related physical activity may occur relatively independently of weather conditions. The knowledge that weather conditions do not seem to be a significant barrier to this domain of activity may potentially expand the universe of geographic locations that are amenable to environmental and programmatic interventions to increase transport-related walking. Copyright © 2017 Elsevier Inc. All rights reserved.

Linkages between large-scale climate patterns and the dynamics of Alaskan caribou populations

Treesearch

Kyle Joly; David R. Klein; David L. Verbyla; T. Scott Rupp; F. Stuart Chapin

2011-01-01

Recent research has linked climate warming to global declines in caribou and reindeer (both Rangifer tarandus) populations. We hypothesize large-scale climate patterns are a contributing factor explaining why these declines are not universal. To test our hypothesis for such relationships among Alaska caribou herds, we calculated the population growth...

Potential use of weather radar to study movements of wintering waterfowl

USGS Publications Warehouse

Randall, Lori A.; Diehl, Robert H.; Wilson, Barry C.; Barrow, Wylie C.; Jeske, Clinton W.

2011-01-01

To protect and restore wintering waterfowl habitat, managers require knowledge of routine wintering waterfowl movements and habitat use. During preliminary screening of Doppler weather radar data we observed biological movements consistent with routine foraging flights of wintering waterfowl known to occur near Lacassine National Wildlife Refuge (NWR), Louisiana. During the winters of 2004–2005 and 2005–2006, we conducted field surveys to identify the source of the radar echoes emanating from Lacassine NWR. We compared field data to weather radar reflectivity data. Spatial and temporal patterns consistent with foraging flight movements appeared in weather radar data on all dates of field surveys. Dabbling ducks were the dominant taxa flying within the radar beam during the foraging flight period. Using linear regression, we found a positive log-linear relationship between average radar reflectivity (Z) and number of birds detected over the study area (P r2 = 0.62, n = 40). Ground observations and the statistically significant relationship between radar data and field data confirm that Doppler weather radar recorded the foraging flights of dabbling ducks. Weather radars may be effective tools for wintering waterfowl management because they provide broad-scale views of both diurnal and nocturnal movements. In addition, an extensive data archive enables the study of wintering waterfowl response to habitat loss, agricultural practices, wetland restoration, and other research questions that require multiple years of data.

Forecasting of monsoon heavy rains: challenges in NWP

NASA Astrophysics Data System (ADS)

Sharma, Kuldeep; Ashrit, Raghavendra; Iyengar, Gopal; Bhatla, R.; Rajagopal, E. N.

2016-05-01

Last decade has seen a tremendous improvement in the forecasting skill of numerical weather prediction (NWP) models. This is attributed to increased sophistication in NWP models, which resolve complex physical processes, advanced data assimilation, increased grid resolution and satellite observations. However, prediction of heavy rains is still a challenge since the models exhibit large error in amounts as well as spatial and temporal distribution. Two state-of-art NWP models have been investigated over the Indian monsoon region to assess their ability in predicting the heavy rainfall events. The unified model operational at National Center for Medium Range Weather Forecasting (NCUM) and the unified model operational at the Australian Bureau of Meteorology (Australian Community Climate and Earth-System Simulator -- Global (ACCESS-G)) are used in this study. The recent (JJAS 2015) Indian monsoon season witnessed 6 depressions and 2 cyclonic storms which resulted in heavy rains and flooding. The CRA method of verification allows the decomposition of forecast errors in terms of error in the rainfall volume, pattern and location. The case by case study using CRA technique shows that contribution to the rainfall errors come from pattern and displacement is large while contribution due to error in predicted rainfall volume is least.

Sensitivity of proxies on non-linear interactions in the climate system

PubMed Central

Schultz, Johannes A.; Beck, Christoph; Menz, Gunter; Neuwirth, Burkhard; Ohlwein, Christian; Philipp, Andreas

2015-01-01

Recent climate change is affecting the earth system to an unprecedented extent and intensity and has the potential to cause severe ecological and socioeconomic consequences. To understand natural and anthropogenic induced processes, feedbacks, trends, and dynamics in the climate system, it is also essential to consider longer timescales. In this context, annually resolved tree-ring data are often used to reconstruct past temperature or precipitation variability as well as atmospheric or oceanic indices such as the North Atlantic Oscillation (NAO) or the Atlantic Multidecadal Oscillation (AMO). The aim of this study is to assess weather-type sensitivity across the Northern Atlantic region based on two tree-ring width networks. Our results indicate that nonstationarities in superordinate space and time scales of the climate system (here synoptic- to global scale, NAO, AMO) can affect the climate sensitivity of tree-rings in subordinate levels of the system (here meso- to synoptic scale, weather-types). This scale bias effect has the capability to impact even large multiproxy networks and the ability of these networks to provide information about past climate conditions. To avoid scale biases in climate reconstructions, interdependencies between the different scales in the climate system must be considered, especially internal ocean/atmosphere dynamics. PMID:26686001

Contributions of the ARM Program to Radiative Transfer Modeling for Climate and Weather Applications

NASA Technical Reports Server (NTRS)

Mlawer, Eli J.; Iacono, Michael J.; Pincus, Robert; Barker, Howard W.; Oreopoulos, Lazaros; Mitchell, David L.

2016-01-01

Accurate climate and weather simulations must account for all relevant physical processes and their complex interactions. Each of these atmospheric, ocean, and land processes must be considered on an appropriate spatial and temporal scale, which leads these simulations to require a substantial computational burden. One especially critical physical process is the flow of solar and thermal radiant energy through the atmosphere, which controls planetary heating and cooling and drives the large-scale dynamics that moves energy from the tropics toward the poles. Radiation calculations are therefore essential for climate and weather simulations, but are themselves quite complex even without considering the effects of variable and inhomogeneous clouds. Clear-sky radiative transfer calculations have to account for thousands of absorption lines due to water vapor, carbon dioxide, and other gases, which are irregularly distributed across the spectrum and have shapes dependent on pressure and temperature. The line-by-line (LBL) codes that treat these details have a far greater computational cost than can be afforded by global models. Therefore, the crucial requirement for accurate radiation calculations in climate and weather prediction models must be satisfied by fast solar and thermal radiation parameterizations with a high level of accuracy that has been demonstrated through extensive comparisons with LBL codes. See attachment for continuation.

Crash Frequency Modeling Using Real-Time Environmental and Traffic Data and Unbalanced Panel Data Models

PubMed Central

Chen, Feng; Chen, Suren; Ma, Xiaoxiang

2016-01-01

Traffic and environmental conditions (e.g., weather conditions), which frequently change with time, have a significant impact on crash occurrence. Traditional crash frequency models with large temporal scales and aggregated variables are not sufficient to capture the time-varying nature of driving environmental factors, causing significant loss of critical information on crash frequency modeling. This paper aims at developing crash frequency models with refined temporal scales for complex driving environments, with such an effort providing more detailed and accurate crash risk information which can allow for more effective and proactive traffic management and law enforcement intervention. Zero-inflated, negative binomial (ZINB) models with site-specific random effects are developed with unbalanced panel data to analyze hourly crash frequency on highway segments. The real-time driving environment information, including traffic, weather and road surface condition data, sourced primarily from the Road Weather Information System, is incorporated into the models along with site-specific road characteristics. The estimation results of unbalanced panel data ZINB models suggest there are a number of factors influencing crash frequency, including time-varying factors (e.g., visibility and hourly traffic volume) and site-varying factors (e.g., speed limit). The study confirms the unique significance of the real-time weather, road surface condition and traffic data to crash frequency modeling. PMID:27322306

Global Climate Models Intercomparison of Anthropogenic Aerosols Effects on Regional Climate over North Pacific

NASA Astrophysics Data System (ADS)

Hu, J.; Zhang, R.; Wang, Y.; Ming, Y.; Lin, Y.; Pan, B.

2015-12-01

Aerosols can alter atmospheric radiation and cloud physics, which further exert impacts on weather and global climate. With the development and industrialization of the developing Asian countries, anthropogenic aerosols have received considerable attentions and remain to be the largest uncertainty in the climate projection. Here we assess the performance of two stat-of-art global climate models (National Center for Atmospheric Research-Community Atmosphere Model 5 (CAM5) and Geophysical Fluid Dynamics Laboratory Atmosphere Model 3 (AM3)) in simulating the impacts of anthropogenic aerosols on North Pacific storm track region. By contrasting two aerosol scenarios, i.e. present day (PD) and pre-industrial (PI), both models show aerosol optical depth (AOD) enhanced by about 22%, with CAM5 AOD 40% lower in magnitude due to the long range transport of anthropogenic aerosols. Aerosol effects on the ice water path (IWP), stratiform precipitation, convergence and convection strengths in the two models are distinctive in patterns and magnitudes. AM3 shows qualitatively good agreement with long-term satellite observations, while CAM5 overestimates convection and liquid water path resulting in an underestimation of large-scale precipitation and IWP. Due to coarse resolution and parameterization in convection schemes, both models' performance on convection needs to be improved. Aerosols performance on large-scale circulation and radiative budget are also examined in this study.

Evidence for climate change in the satellite cloud record.

PubMed

Norris, Joel R; Allen, Robert J; Evan, Amato T; Zelinka, Mark D; O'Dell, Christopher W; Klein, Stephen A

2016-08-04

Clouds substantially affect Earth's energy budget by reflecting solar radiation back to space and by restricting emission of thermal radiation to space. They are perhaps the largest uncertainty in our understanding of climate change, owing to disagreement among climate models and observational datasets over what cloud changes have occurred during recent decades and will occur in response to global warming. This is because observational systems originally designed for monitoring weather have lacked sufficient stability to detect cloud changes reliably over decades unless they have been corrected to remove artefacts. Here we show that several independent, empirically corrected satellite records exhibit large-scale patterns of cloud change between the 1980s and the 2000s that are similar to those produced by model simulations of climate with recent historical external radiative forcing. Observed and simulated cloud change patterns are consistent with poleward retreat of mid-latitude storm tracks, expansion of subtropical dry zones, and increasing height of the highest cloud tops at all latitudes. The primary drivers of these cloud changes appear to be increasing greenhouse gas concentrations and a recovery from volcanic radiative cooling. These results indicate that the cloud changes most consistently predicted by global climate models are currently occurring in nature.

Thunderstorm-environment interactions determined with three-dimensional trajectories

NASA Technical Reports Server (NTRS)

Wilson, G. S.

1980-01-01

Diagnostically determined three dimensional trajectories were used to reveal some of the scale interaction processes that occur between convective storms and their environment. Data from NASA's fourth Atmospheric Variability Experiment are analyzed. Two intense squall lines and numerous reports of severe weather occurred during the period. Convective storm systems with good temporal and spatial continuity are shown to be related to the development and movement of short wave circulation systems aloft that propagate eastward within a zonal mid tropospheric wind pattern. These short wave systems are found to produce the potential instability and dynamic triggering needed for thunderstorm formation. The environmental flow patterns, relative to convective storm systems, are shown to produce large upward air parcel movements in excess of 50 mb/3h in the immediate vicinity of the storms. The air undergoing strong lifting originates as potentially unstable low level air traveling into the storm environment from southern and southwestern directions. The thermo and hydrodynamical processes that lead to changes in atmospheric structure before, during, and after convective storm formation are described using total time derivatives of pressure or net vertical displacement, potential temperature, and vector wind calculated by following air parcels.

Evidence for climate change in the satellite cloud record

NASA Astrophysics Data System (ADS)

Norris, Joel R.; Allen, Robert J.; Evan, Amato T.; Zelinka, Mark D.; O'Dell, Christopher W.; Klein, Stephen A.

2016-08-01

Clouds substantially affect Earth’s energy budget by reflecting solar radiation back to space and by restricting emission of thermal radiation to space. They are perhaps the largest uncertainty in our understanding of climate change, owing to disagreement among climate models and observational datasets over what cloud changes have occurred during recent decades and will occur in response to global warming. This is because observational systems originally designed for monitoring weather have lacked sufficient stability to detect cloud changes reliably over decades unless they have been corrected to remove artefacts. Here we show that several independent, empirically corrected satellite records exhibit large-scale patterns of cloud change between the 1980s and the 2000s that are similar to those produced by model simulations of climate with recent historical external radiative forcing. Observed and simulated cloud change patterns are consistent with poleward retreat of mid-latitude storm tracks, expansion of subtropical dry zones, and increasing height of the highest cloud tops at all latitudes. The primary drivers of these cloud changes appear to be increasing greenhouse gas concentrations and a recovery from volcanic radiative cooling. These results indicate that the cloud changes most consistently predicted by global climate models are currently occurring in nature.

Pattern-based, multi-scale segmentation and regionalization of EOSD land cover

NASA Astrophysics Data System (ADS)

Niesterowicz, Jacek; Stepinski, Tomasz F.

2017-10-01

The Earth Observation for Sustainable Development of Forests (EOSD) map is a 25 m resolution thematic map of Canadian forests. Because of its large spatial extent and relatively high resolution the EOSD is difficult to analyze using standard GIS methods. In this paper we propose multi-scale segmentation and regionalization of EOSD as new methods for analyzing EOSD on large spatial scales. Segments, which we refer to as forest land units (FLUs), are delineated as tracts of forest characterized by cohesive patterns of EOSD categories; we delineated from 727 to 91,885 FLUs within the spatial extent of EOSD depending on the selected scale of a pattern. Pattern of EOSD's categories within each FLU is described by 1037 landscape metrics. A shapefile containing boundaries of all FLUs together with an attribute table listing landscape metrics make up an SQL-searchable spatial database providing detailed information on composition and pattern of land cover types in Canadian forest. Shapefile format and extensive attribute table pertaining to the entire legend of EOSD are designed to facilitate broad range of investigations in which assessment of composition and pattern of forest over large areas is needed. We calculated four such databases using different spatial scales of pattern. We illustrate the use of FLU database for producing forest regionalization maps of two Canadian provinces, Quebec and Ontario. Such maps capture the broad scale variability of forest at the spatial scale of the entire province. We also demonstrate how FLU database can be used to map variability of landscape metrics, and thus the character of landscape, over the entire Canada.

Stress Testing Water Resource Systems at Regional and National Scales with Synthetic Drought Event Sets

NASA Astrophysics Data System (ADS)

Hall, J. W.; Mortazavi-Naeini, M.; Coxon, G.; Guillod, B. P.; Allen, M. R.

2017-12-01

Water resources systems can fail to deliver the services required by water users (and deprive the environment of flow requirements) in many different ways. In an attempt to make systems more resilient, they have also been made more complex, for example through a growing number of large-scale transfers, optimized storages and reuse plants. These systems may be vulnerable to complex variants of hydrological variability in space and time, and behavioural adaptations by water users. In previous research we have used non-parametric stochastic streamflow generators to test the vulnerability of water resource systems. Here we use a very large ensemble of regional climate model outputs from the weather@home crowd-sourced citizen science project, which has generated more than 30,000 years of synthetic weather for present and future climates in the UK and western Europe, using the HadAM3P regional climate model. These simulations have been constructed in order to preserve prolonged drought characteristics, through treatment of long-memory processes in ocean circulations and soil moisture. The weather simulations have been propagated through the newly developed DynaTOP national hydrological for Britain, in order to provide low flow simulations at points of water withdrawal for public water supply, energy and agricultural abstractors. We have used the WATHNET water resource simulation model, set up for the Thames Basin and for all of the large water resource zones in England, to simulate the frequency, severity and duration of water shortages in all of these synthetic weather conditions. In particular, we have sought to explore systemic vulnerabilities associated with inter-basin transfers and the trade-offs between different water users. This analytical capability is providing the basis for (i) implementation of the Duty of Resilience, which has been placed upon the water industry in the 2014 Water Act and (ii) testing reformed abstraction arrangements which the UK government is committed to implementing.

Attribution of Large-Scale Climate Patterns to Seasonal Peak-Flow and Prospects for Prediction Globally

NASA Astrophysics Data System (ADS)

Lee, Donghoon; Ward, Philip; Block, Paul

2018-02-01

Flood-related fatalities and impacts on society surpass those from all other natural disasters globally. While the inclusion of large-scale climate drivers in streamflow (or high-flow) prediction has been widely studied, an explicit link to global-scale long-lead prediction is lacking, which can lead to an improved understanding of potential flood propensity. Here we attribute seasonal peak-flow to large-scale climate patterns, including the El Niño Southern Oscillation (ENSO), Pacific Decadal Oscillation (PDO), North Atlantic Oscillation (NAO), and Atlantic Multidecadal Oscillation (AMO), using streamflow station observations and simulations from PCR-GLOBWB, a global-scale hydrologic model. Statistically significantly correlated climate patterns and streamflow autocorrelation are subsequently applied as predictors to build a global-scale season-ahead prediction model, with prediction performance evaluated by the mean squared error skill score (MSESS) and the categorical Gerrity skill score (GSS). Globally, fair-to-good prediction skill (20% ≤ MSESS and 0.2 ≤ GSS) is evident for a number of locations (28% of stations and 29% of land area), most notably in data-poor regions (e.g., West and Central Africa). The persistence of such relevant climate patterns can improve understanding of the propensity for floods at the seasonal scale. The prediction approach developed here lays the groundwork for further improving local-scale seasonal peak-flow prediction by identifying relevant global-scale climate patterns. This is especially attractive for regions with limited observations and or little capacity to develop flood early warning systems.

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...

Flood and Weather Monitoring Using Real-time Twitter Data Streams

NASA Astrophysics Data System (ADS)

Demir, I.; Sit, M. A.; Sermet, M. Y.

2016-12-01

Social media data is a widely used source to making inference within public crisis periods and events in disaster times. Specifically, since Twitter provides large-scale data publicly in real-time, it is one of the most extensive resources with location information. This abstract provides an overview of a real-time Twitter analysis system to support flood preparedness and response using a comprehensive information-centric flood ontology and natural language processing. Within the scope of this project, we deal with acquisition and processing of real-time Twitter data streams. System fetches the tweets with specified keywords and classifies them as related to flooding or heavy weather conditions. The system uses machine learning algorithms to discover patterns using the correlation between tweets and Iowa Flood Information System's (IFIS) extensive resources. The system uses these patterns to forecast the formation and progress of a potential future flood event. While fetching tweets, predefined hashtags are used for filtering and enhancing the relevancy for selected tweets. With this project, tweets can also be used as an alternative data source where other data sources are not sufficient for specific tasks. During the disasters, the photos that people upload alongside their tweets can be collected and placed to appropriate locations on a mapping system. This allows decision making authorities and communities to see the most recent outlook of the disaster interactively. In case of an emergency, concentration of tweets can help the authorities to determine a strategy on how to reach people most efficiently while providing them the supplies they need. Thanks to the extendable nature of the flood ontology and framework, results from this project will be a guide for other natural disasters, and will be shared with the community.

High-Resolution Modeling to Assess Tropical Cyclone Activity in Future Climate Regimes

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

Lackmann, Gary

2013-06-10

Applied research is proposed with the following objectives: (i) to determine the most likely level of tropical cyclone intensity and frequency in future climate regimes, (ii) to provide a quantitative measure of uncertainty in these predictions, and (iii) to improve understanding of the linkage between tropical cyclones and the planetary-scale circulation. Current mesoscale weather forecasting models, such as the Weather Research and Forecasting (WRF) model, are capable of simulating the full intensity of tropical cyclones (TC) with realistic structures. However, in order to accurately represent both the primary and secondary circulations in these systems, model simulations must be configured withmore » sufficient resolution to explicitly represent convection (omitting the convective parameterization scheme). Most previous numerical studies of TC activity at seasonal and longer time scales have not utilized such explicit convection (EC) model runs. Here, we propose to employ the moving nest capability of WRF to optimally represent TC activity on a seasonal scale using a downscaling approach. The statistical results of a suite of these high-resolution TC simulations will yield a realistic representation of TC intensity on a seasonal basis, while at the same time allowing analysis of the feedback that TCs exert on the larger-scale climate system. Experiments will be driven with analyzed lateral boundary conditions for several recent Atlantic seasons, spanning a range of activity levels and TC track patterns. Results of the ensemble of WRF simulations will then be compared to analyzed TC data in order to determine the extent to which this modeling setup can reproduce recent levels of TC activity. Next, the boundary conditions (sea-surface temperature, tropopause height, and thermal/moisture profiles) from the recent seasons will be altered in a manner consistent with various future GCM/RCM scenarios, but that preserves the large-scale shear and incipient disturbance activity. This will allow (i) a direct comparison of future TC activity that could be expected for an active or inactive season in an altered climate regime, and (ii) a measure of the level of uncertainty and variability in TC activity resulting from different carbon emission scenarios.« less

Sub-kilometer Numerical Weather Prediction in complex urban areas

NASA Astrophysics Data System (ADS)

Leroyer, S.; Bélair, S.; Husain, S.; Vionnet, V.

2013-12-01

A Sub-kilometer atmospheric modeling system with grid-spacings of 2.5 km, 1 km and 250 m and including urban processes is currently being developed at the Meteorological Service of Canada (MSC) in order to provide more accurate weather forecasts at the city scale. Atmospheric lateral boundary conditions are provided with the 15-km Canadian Regional Deterministic Prediction System (RDPS). Surface physical processes are represented with the Town Energy Balance (TEB) model for the built-up covers and with the Interactions between the Surface, Biosphere, and Atmosphere (ISBA) land surface model for the natural covers. In this study, several research experiments over large metropolitan areas and using observational networks at the urban scale are presented, with a special emphasis on the representation of local atmospheric circulations and their impact on extreme weather forecasting. First, numerical simulations are performed over the Vancouver metropolitan area during a summertime Intense Observing Period (IOP of 14-15 August 2008) of the Environmental Prediction in Canadian Cities (EPiCC) observational network. The influence of the horizontal resolution on the fine-scale representation of the sea-breeze development over the city is highlighted (Leroyer et al., 2013). Then severe storms cases occurring in summertime within the Greater Toronto Area (GTA) are simulated. In view of supporting the 2015 PanAmerican and Para-Pan games to be hold in GTA, a dense observational network has been recently deployed over this region to support model evaluations at the urban and meso scales. In particular, simulations are conducted for the case of 8 July 2013 when exceptional rainfalls were recorded. Leroyer, S., S. Bélair, J. Mailhot, S.Z. Husain, 2013: Sub-kilometer Numerical Weather Prediction in an Urban Coastal Area: A case study over the Vancouver Metropolitan Area, submitted to Journal of Applied Meteorology and Climatology.

A Synoptic- and Planetary-Scale Analysis of Widespread North American Ice Storms

NASA Astrophysics Data System (ADS)

McCray, C.; Gyakum, J. R.; Atallah, E.

2017-12-01

Freezing rain can have devastating impacts, particularly when it persists for many hours. Predicting the precise temperature stratification necessary for long duration freezing rain events remains an important forecast challenge. To better elucidate the conditions responsible for the most severe events, we concentrate on surface observations of long-duration (6 or more hours) freezing rain events over North America from 1979-2016. Furthermore, we analyze cases in which multiple stations observe long-duration events simultaneously. Following these cases over successive days allows us to generate maps of freezing rain "tracks." We then categorize recurring geographic patterns to examine the meteorological conditions leading to these events. While freezing rain is most frequently observed in the northeastern United States and southeastern Canada, long-duration events have affected areas as far south as the Gulf Coast. Notably, a disproportionately large number of very long duration (18 or more hours) events have occurred in the Southern Plains states relative to the climatological annual frequency of freezing rain there. Classification of individual cases shows that most of these very long duration events are associated with a recurring pattern which produces freezing rain along a southwest-northeast swath from Texas/Oklahoma into the northeastern U.S. and eastern Canada. Storms classified within this pattern include the January 1998 and December 2013 ice storms. While this pattern is the most widespread, additional spatially extensive patterns occur. One of these areas extends from the Southern Plains eastward along the Gulf Coast to Georgia and the Carolinas. A third category of events extends from the Upper Midwest into the northeastern U.S. and southeastern Canada. The expansive areal extent and long duration of these events make them especially problematic. An analysis of the planetary- to synoptic-scale settings responsible for these cases and the differences among individual storms is performed to provide forecasters with additional tools/insight towards the prediction of these damaging weather events.

Large-Scale Constraint-Based Pattern Mining

ERIC Educational Resources Information Center

Zhu, Feida

2009-01-01

We studied the problem of constraint-based pattern mining for three different data formats, item-set, sequence and graph, and focused on mining patterns of large sizes. Colossal patterns in each data formats are studied to discover pruning properties that are useful for direct mining of these patterns. For item-set data, we observed robustness of…

SCALE PROBLEMS IN REPORTING LANDSCAPE PATTERN AT THE REGIONAL SCALE

EPA Science Inventory

Remotely sensed data for Southeastern United States (Standard Federal Region 4) are used to examine the scale problems involved in reporting landscape pattern for a large, heterogeneous region. Frequency distributions of landscape indices illustrate problems associated with the g...

Relationships between sudden weather changes in summer and mortality in the Czech Republic, 1986-2005

NASA Astrophysics Data System (ADS)

Plavcová, Eva; Kyselý, Jan

2010-09-01

The study examines the relationship between sudden changes in weather conditions in summer, represented by (1) sudden air temperature changes, (2) sudden atmospheric pressure changes, and (3) passages of strong atmospheric fronts; and variations in daily mortality in the population of the Czech Republic. The events are selected from data covering 1986-2005 and compared with the database of daily excess all-cause mortality for the whole population and persons aged 70 years and above. Relative deviations of mortality, i.e., ratios of the excess mortality to the expected number of deaths, were averaged over the selected events for days D-2 (2 days before a change) up to D+7 (7 days after), and their statistical significance was tested by means of the Monte Carlo method. We find that the periods around weather changes are associated with pronounced patterns in mortality: a significant increase in mortality is found after large temperature increases and on days of large pressure drops; a decrease in mortality (partly due to a harvesting effect) occurs after large temperature drops, pressure increases, and passages of strong cold fronts. The relationship to variations in excess mortality is better expressed for sudden air temperature/pressure changes than for passages of atmospheric fronts. The mortality effects are usually more pronounced in the age group 70 years and above. The impacts associated with large negative changes of pressure are statistically independent of the effects of temperature; the corresponding dummy variable is found to be a significant predictor in the ARIMA model for relative deviations of mortality. This suggests that sudden weather changes should be tested also in time series models for predicting excess mortality as they may enhance their performance.

Dependence of Snowmelt Simulations on Scaling of the Forcing Processes (Invited)

NASA Astrophysics Data System (ADS)

Winstral, A. H.; Marks, D. G.; Gurney, R. J.

2009-12-01

The spatial organization and scaling relationships of snow distribution in mountain environs is ultimately dependent on the controlling processes. These processes include interactions between weather, topography, vegetation, snow state, and seasonally-dependent radiation inputs. In large scale snow modeling it is vital to know these dependencies to obtain accurate predictions while reducing computational costs. This study examined the scaling characteristics of the forcing processes and the dependency of distributed snowmelt simulations to their scaling. A base model simulation characterized these processes with 10m resolution over a 14.0 km2 basin with an elevation range of 1474 - 2244 masl. Each of the major processes affecting snow accumulation and melt - precipitation, wind speed, solar radiation, thermal radiation, temperature, and vapor pressure - were independently degraded to 1 km resolution. Seasonal and event-specific results were analyzed. Results indicated that scale effects on melt vary by process and weather conditions. The dependence of melt simulations on the scaling of solar radiation fluxes also had a seasonal component. These process-based scaling characteristics should remain static through time as they are based on physical considerations. As such, these results not only provide guidance for current modeling efforts, but are also well suited to predicting how potential climate changes will affect the heterogeneity of mountain snow distributions.

Identification of scintillation signatures on GPS signals originating from plasma structures detected with EISCAT incoherent scatter radar along the same line of sight

NASA Astrophysics Data System (ADS)

Forte, Biagio; Coleman, Chris; Skone, Susan; Häggström, Ingemar; Mitchell, Cathryn; Da Dalt, Federico; Panicciari, Tommaso; Kinrade, Joe; Bust, Gary

2017-01-01

Ionospheric scintillation originates from the scattering of electromagnetic waves through spatial gradients in the plasma density distribution, drifting across a given propagation direction. Ionospheric scintillation represents a disruptive manifestation of adverse space weather conditions through degradation of the reliability and continuity of satellite telecommunication and navigation systems and services (e.g., European Geostationary Navigation Overlay Service, EGNOS). The purpose of the experiment presented here was to determine the contribution of auroral ionization structures to GPS scintillation. European Incoherent Scatter (EISCAT) measurements were obtained along the same line of sight of a given GPS satellite observed from Tromso and followed by means of the EISCAT UHF radar to causally identify plasma structures that give rise to scintillation on the co-aligned GPS radio link. Large-scale structures associated with the poleward edge of the ionospheric trough, with auroral arcs in the nightside auroral oval and with particle precipitation at the onset of a substorm were indeed identified as responsible for enhanced phase scintillation at L band. For the first time it was observed that the observed large-scale structures did not cascade into smaller-scale structures, leading to enhanced phase scintillation without amplitude scintillation. More measurements and theory are necessary to understand the mechanism responsible for the inhibition of large-scale to small-scale energy cascade and to reproduce the observations. This aspect is fundamental to model the scattering of radio waves propagating through these ionization structures. New insights from this experiment allow a better characterization of the impact that space weather can have on satellite telecommunications and navigation services.

Identification of scintillation signatures on GPS signals originating from plasma structures detected with EISCAT incoherent scatter radar along the same line of sight.

PubMed

Forte, Biagio; Coleman, Chris; Skone, Susan; Häggström, Ingemar; Mitchell, Cathryn; Da Dalt, Federico; Panicciari, Tommaso; Kinrade, Joe; Bust, Gary

2017-01-01

Ionospheric scintillation originates from the scattering of electromagnetic waves through spatial gradients in the plasma density distribution, drifting across a given propagation direction. Ionospheric scintillation represents a disruptive manifestation of adverse space weather conditions through degradation of the reliability and continuity of satellite telecommunication and navigation systems and services (e.g., European Geostationary Navigation Overlay Service, EGNOS). The purpose of the experiment presented here was to determine the contribution of auroral ionization structures to GPS scintillation. European Incoherent Scatter (EISCAT) measurements were obtained along the same line of sight of a given GPS satellite observed from Tromso and followed by means of the EISCAT UHF radar to causally identify plasma structures that give rise to scintillation on the co-aligned GPS radio link. Large-scale structures associated with the poleward edge of the ionospheric trough, with auroral arcs in the nightside auroral oval and with particle precipitation at the onset of a substorm were indeed identified as responsible for enhanced phase scintillation at L band. For the first time it was observed that the observed large-scale structures did not cascade into smaller-scale structures, leading to enhanced phase scintillation without amplitude scintillation. More measurements and theory are necessary to understand the mechanism responsible for the inhibition of large-scale to small-scale energy cascade and to reproduce the observations. This aspect is fundamental to model the scattering of radio waves propagating through these ionization structures. New insights from this experiment allow a better characterization of the impact that space weather can have on satellite telecommunications and navigation services.

Monitoring Surface Climate With its Emissivity Derived From Satellite Measurements

NASA Technical Reports Server (NTRS)

Zhou, Daniel K.; Larar, Allen M.; Liu, Xu

2012-01-01

Satellite thermal infrared (IR) spectral emissivity data have been shown to be significant for atmospheric research and monitoring the Earth fs environment. Long-term and large-scale observations needed for global monitoring and research can be supplied by satellite-based remote sensing. Presented here is the global surface IR emissivity data retrieved from the last 5 years of Infrared Atmospheric Sounding Interferometer (IASI) measurements observed from the MetOp-A satellite. Monthly mean surface properties (i.e., skin temperature T(sub s) and emissivity spectra epsilon(sub v) with a spatial resolution of 0.5x0.5-degrees latitude-longitude are produced to monitor seasonal and inter-annual variations. We demonstrate that surface epsilon(sub v) and T(sub s) retrieved with IASI measurements can be used to assist in monitoring surface weather and surface climate change. Surface epsilon(sub v) together with T(sub s) from current and future operational satellites can be utilized as a means of long-term and large-scale monitoring of Earth 's surface weather environment and associated changes.

Seismic refraction studies of volcanic crust in Costa Rica and of critical zones in the southern Sierra Nevada, California and Laramie Range, Wyoming

NASA Astrophysics Data System (ADS)

Hayes, Jorden L.

This work demonstrates the utility of seismic refraction surveys to understanding geologic processes at a range of scales. Each chapter presents subsurface maps of seismic p-wave velocities, which vary due to contrasts in elastic material properties. In the following chapters we examine seismic p-wave velocity variations that result from volcanic and tectonic processes within Earth's crust and chemical and physical weathering processes within Earth's near-surface environment. Chapter one presents results from an across-arc wide-angle seismic refraction survey of the Costa Rican volcanic front. These results support the hypothesis that juvenile continental crust may form along volcanic island arcs if built upon relatively thick substrates (i.e., large igneous provinces). Comparisons of velocity-depth functions show that velocities within the active arc of Costa Rica are lower than other modern island arcs (i.e., volcanic arcs built upon oceanic crust) and within the high-velocity extreme of bulk continental crust. Chapter two shows that physical processes can dominate over chemical processes in generating porosity in the deep critical zone and outlines a new framework for interpreting subsurface chemical and physical weathering at the landscape scale. Direct measurements of saprolite from boreholes at the Southern Sierra Nevada Critical Zone Observatory show that, contrary to convention, saprolite may experience high levels of volumetric strain (>35%) and uniform mass loss in the upper 11 m. By combining observations from boreholes and seismic refraction surveys we create a map of volumetric strain across the landscape. Variations in inferred volumetric strain are consistent with opening-mode fracture patterns predicted by topographic and tectonic stress models. Chapter three is a characterization of fracture distribution in the deep critical zone from geophysical and borehole observations in the Laramie Mountains, Wyoming. Data from core and down-hole acoustic televiewer images show that fracture density not only decreases with depth but also varies with topography. Comparisons of seismic p-wave velocities and fracture density show that increases in seismic velocity at our site (i.e., from 1-4 km/s) correspond to decreasing fracture density. Observations of a seismological boundary layer coupled with weathering interpreted in borehole images suggest a significant change in chemical weathering with depth. These results emphasize the complex interplay of chemical and physical processes in the deep critical zone.

Temporal Associations between Weather and Headache: Analysis by Empirical Mode Decomposition

PubMed Central

Yang, Albert C.; Fuh, Jong-Ling; Huang, Norden E.; Shia, Ben-Chang; Peng, Chung-Kang; Wang, Shuu-Jiun

2011-01-01

Background Patients frequently report that weather changes trigger headache or worsen existing headache symptoms. Recently, the method of empirical mode decomposition (EMD) has been used to delineate temporal relationships in certain diseases, and we applied this technique to identify intrinsic weather components associated with headache incidence data derived from a large-scale epidemiological survey of headache in the Greater Taipei area. Methodology/Principal Findings The study sample consisted of 52 randomly selected headache patients. The weather time-series parameters were detrended by the EMD method into a set of embedded oscillatory components, i.e. intrinsic mode functions (IMFs). Multiple linear regression models with forward stepwise methods were used to analyze the temporal associations between weather and headaches. We found no associations between the raw time series of weather variables and headache incidence. For decomposed intrinsic weather IMFs, temperature, sunshine duration, humidity, pressure, and maximal wind speed were associated with headache incidence during the cold period, whereas only maximal wind speed was associated during the warm period. In analyses examining all significant weather variables, IMFs derived from temperature and sunshine duration data accounted for up to 33.3% of the variance in headache incidence during the cold period. The association of headache incidence and weather IMFs in the cold period coincided with the cold fronts. Conclusions/Significance Using EMD analysis, we found a significant association between headache and intrinsic weather components, which was not detected by direct comparisons of raw weather data. Contributing weather parameters may vary in different geographic regions and different seasons. PMID:21297940

The dust cloud of the century

NASA Astrophysics Data System (ADS)

Robock, A.

1983-02-01

The structure and composition of the dust cloud from the 4 April 1982 eruption of the El Chichon volcano in Chiapas state, Mexico, is examined and the possible effects of the dust cloud on the world's weather patterns are discussed. Observations of the cloud using a variety of methods are evaluated, including data from the GOES and NOAA-7 weather satellites, vertically pointing lidar measurements, the SME satellite, and the Nimbus-7 satellite. Studies of the gaseous and particulate composition of the cloud reveal the presence of large amounts of sulfuric acid particles, which have a long mean residence time in the atmosphere and have a large effect on the amount of solar radiation received at the earth's surface by scattering several percent of the radiation back to space. Estimates of the effect of this cloud on surface air temperature changes are presented based on findings from climate models.

Permeability Changes in Reaction Induced Fracturing

NASA Astrophysics Data System (ADS)

Ulven, Ole Ivar; Malthe-Sørenssen, Anders; Kalia, Rajiv

2013-04-01

The process of fracture formation due to a volume increasing chemical reaction has been studied in a variety of different settings, e.g. weathering of dolerites by Røyne et al.[4], serpentinization and carbonation of peridotite by Rudge et al.[3] and replacement reactions in silica-poor igneous rocks by Jamtveit et al.[1]. It is generally assumed that fracture formation will increase the net permeability of the rock, and thus increase the reactant transport rate and subsequently the total reaction rate, as summarised by Kelemen et al.[2]. Røyne et al.[4] have shown that transport in fractures will have an effect on the fracture pattern formed. Understanding the feedback process between fracture formation and permeability changes is essential in assessing industrial scale CO2 sequestration in ultramafic rock, but little is seemingly known about how large the permeability change will be in reaction-induced fracturing under compression, and it remains an open question how sensitive a fracture pattern is to permeability changes. In this work, we study the permeability of fractures formed under compression, and we use a 2D discrete element model to study the fracture patterns and total reaction rates achieved with different permeabilities. We achieve an improved understanding of the feedback processes in reaction-driven fracturing, thus improving our ability to decide whether industrial scale CO2 sequestration in ultramafic rock is a viable option for long-term handling of CO2. References [1] Jamtveit, B, Putnis, C. V., and Malthe-Sørenssen, A., "Reaction induced fracturing during replacement processes," Contrib. Mineral Petrol. 157, 2009, pp. 127 - 133. [2] Kelemen, P., Matter, J., Streit, E. E., Rudge, J. F., Curry, W. B., and Blusztajn, J., "Rates and Mechanisms of Mineral Carbonation in Peridotite: Natural Processes and Recipes for Enhanced, in situ CO2 Capture and Storage," Annu. Rev. Earth Planet. Sci. 2011. 39:545-76. [3] Rudge, J. F., Kelemen, P. B., and Spiegelman, M., "A simple model of reaction induced cracking applied to serpentinization and carbonation of peridotite," Earth Planet. Sci. Lett. 291, Issues 1-4, 2010, pp. 215 - 227. [4] Røyne, A., Jamtveit, B., and Malthe-Sørenssen, A., "Controls on rock weathering rates by reaction-induced hierarchial fracturing," Earth Planet. Sci. Lett. 275, 2008, pp. 364 - 369.

Olivine Dissolution in Seawater: Implications for CO2 Sequestration through Enhanced Weathering in Coastal Environments

PubMed Central

2017-01-01

Enhanced weathering of (ultra)basic silicate rocks such as olivine-rich dunite has been proposed as a large-scale climate engineering approach. When implemented in coastal environments, olivine weathering is expected to increase seawater alkalinity, thus resulting in additional CO2 uptake from the atmosphere. However, the mechanisms of marine olivine weathering and its effect on seawater–carbonate chemistry remain poorly understood. Here, we present results from batch reaction experiments, in which forsteritic olivine was subjected to rotational agitation in different seawater media for periods of days to months. Olivine dissolution caused a significant increase in alkalinity of the seawater with a consequent DIC increase due to CO2 invasion, thus confirming viability of the basic concept of enhanced silicate weathering. However, our experiments also identified several important challenges with respect to the detailed quantification of the CO2 sequestration efficiency under field conditions, which include nonstoichiometric dissolution, potential pore water saturation in the seabed, and the potential occurrence of secondary reactions. Before enhanced weathering of olivine in coastal environments can be considered an option for realizing negative CO2 emissions for climate mitigation purposes, these aspects need further experimental assessment. PMID:28281750

Examining Chaotic Convection with Super-Parameterization Ensembles

NASA Astrophysics Data System (ADS)

Jones, Todd R.

This study investigates a variety of features present in a new configuration of the Community Atmosphere Model (CAM) variant, SP-CAM 2.0. The new configuration (multiple-parameterization-CAM, MP-CAM) changes the manner in which the super-parameterization (SP) concept represents physical tendency feedbacks to the large-scale by using the mean of 10 independent two-dimensional cloud-permitting model (CPM) curtains in each global model column instead of the conventional single CPM curtain. The climates of the SP and MP configurations are examined to investigate any significant differences caused by the application of convective physical tendencies that are more deterministic in nature, paying particular attention to extreme precipitation events and large-scale weather systems, such as the Madden-Julian Oscillation (MJO). A number of small but significant changes in the mean state climate are uncovered, and it is found that the new formulation degrades MJO performance. Despite these deficiencies, the ensemble of possible realizations of convective states in the MP configuration allows for analysis of uncertainty in the small-scale solution, lending to examination of those weather regimes and physical mechanisms associated with strong, chaotic convection. Methods of quantifying precipitation predictability are explored, and use of the most reliable of these leads to the conclusion that poor precipitation predictability is most directly related to the proximity of the global climate model column state to atmospheric critical points. Secondarily, the predictability is tied to the availability of potential convective energy, the presence of mesoscale convective organization on the CPM grid, and the directive power of the large-scale.

Density dependence, spatial scale and patterning in sessile biota.

PubMed

Gascoigne, Joanna C; Beadman, Helen A; Saurel, Camille; Kaiser, Michel J

2005-09-01

Sessile biota can compete with or facilitate each other, and the interaction of facilitation and competition at different spatial scales is key to developing spatial patchiness and patterning. We examined density and scale dependence in a patterned, soft sediment mussel bed. We followed mussel growth and density at two spatial scales separated by four orders of magnitude. In summer, competition was important at both scales. In winter, there was net facilitation at the small scale with no evidence of density dependence at the large scale. The mechanism for facilitation is probably density dependent protection from wave dislodgement. Intraspecific interactions in soft sediment mussel beds thus vary both temporally and spatially. Our data support the idea that pattern formation in ecological systems arises from competition at large scales and facilitation at smaller scales, so far only shown in vegetation systems. The data, and a simple, heuristic model, also suggest that facilitative interactions in sessile biota are mediated by physical stress, and that interactions change in strength and sign along a spatial or temporal gradient of physical stress.

Disentangling oil weathering using GC x GC. 1. chromatogram analysis.

PubMed

Arey, J Samuel; Nelson, Robert K; Reddy, Christopher M

2007-08-15

Historically, the thousands of compounds found in oils constituted an "unresolved complex mixture" that frustrated efforts to analyze oil weathering. Moreover, different weathering processes inflict rich and diverse signatures of compositional change in oil, and conventional methods do not effectively decode this elaborate record. Using comprehensive two-dimensional gas chromatography (GC x GC), we can separate thousands of hydrocarbon components and simultaneously estimate their chemical properties. We investigated 13 weathered field samples collected from the Bouchard 120 heavy fuel oil spill in Buzzards Bay, Massachusetts in 2003. We first mapped hydrocarbon vapor pressures and aqueous solubilities onto the compositional space explored by GC x GC chromatograms of weathered samples. Then we developed methods to quantitatively decouple mass loss patterns associated with evaporation and dissolution. The compositional complexity of oil, traditionally considered an obstacle, was now an advantage. We exploited the large inventory of chemical information encoded in oil to robustly differentiate signatures of mass transfer to air and water. With this new approach, we can evaluate mass transfer models (the Part 2 companion to this paper) and more properly account for evaporation, dissolution, and degradation of oil in the environment.

A conditional stochastic weather generator for seasonal to multi-decadal simulations

NASA Astrophysics Data System (ADS)

Verdin, Andrew; Rajagopalan, Balaji; Kleiber, William; Podestá, Guillermo; Bert, Federico

2018-01-01

We present the application of a parametric stochastic weather generator within a nonstationary context, enabling simulations of weather sequences conditioned on interannual and multi-decadal trends. The generalized linear model framework of the weather generator allows any number of covariates to be included, such as large-scale climate indices, local climate information, seasonal precipitation and temperature, among others. Here we focus on the Salado A basin of the Argentine Pampas as a case study, but the methodology is portable to any region. We include domain-averaged (e.g., areal) seasonal total precipitation and mean maximum and minimum temperatures as covariates for conditional simulation. Areal covariates are motivated by a principal component analysis that indicates the seasonal spatial average is the dominant mode of variability across the domain. We find this modification to be effective in capturing the nonstationarity prevalent in interseasonal precipitation and temperature data. We further illustrate the ability of this weather generator to act as a spatiotemporal downscaler of seasonal forecasts and multidecadal projections, both of which are generally of coarse resolution.

Predicting the effect of fire on large-scale vegetation patterns in North America.

Treesearch

Donald McKenzie; David L. Peterson; Ernesto. Alvarado

1996-01-01

Changes in fire regimes are expected across North America in response to anticipated global climatic changes. Potential changes in large-scale vegetation patterns are predicted as a result of altered fire frequencies. A new vegetation classification was developed by condensing Kuchler potential natural vegetation types into aggregated types that are relatively...

Emissions of CO2 and criteria air pollutants from mobile sources: Insights from integrating real-time traffic data into local air quality models

NASA Astrophysics Data System (ADS)

Gately, Conor; Hutyra, Lucy

2016-04-01

In 2013, on-road mobile sources were responsible for over 26% of U.S. fossil fuel carbon dioxide (ffCO2) emissions, and over 34% of both CO and NOx emissions. However, accurate representations of these emissions at the scale of urban areas remains a difficult challenge. Quantifying emissions at the scale of local streets and highways is critical to provide policymakers with the information needed to develop appropriate mitigation strategies and to guide research into the underlying process that drive mobile emissions. Quantification of vehicle ffCO2 emissions at high spatial and temporal resolutions requires a detailed synthesis of data on traffic activity, roadway attributes, fleet characteristics and vehicle speeds. To accurately characterize criteria air pollutant emissions, information on local meteorology is also critical, as the temperature and relative humidity can affect emissions rates of these pollutants by as much as 400%. As the health impacts of air pollutants are more severe for residents living in close proximity (<500m) to road sources, it is critical that inventories of these emissions rely on highly resolved source data to locate potential hot-spots of exposure. In this study we utilize real-time GPS estimates of vehicle speeds to estimate ffCO2 and criteria air pollutant emissions at multiple spatial and temporal scales across a large metropolitan area. We observe large variations in emissions associated with diurnal activity patterns, congestion, sporting and civic events, and weather anomalies. We discuss the advantages and challenges of using highly-resolved source data to quantify emissions at a roadway scale, and the potential of this methodology for forecasting the air quality impacts of changes in infrastructure, urban planning policies, and regional climate.

Emissions of CO2 and criteria air pollutants from mobile sources: Insights from integrating real-time traffic data into local air quality models

NASA Astrophysics Data System (ADS)

Gately, C.; Hutyra, L.; Sue Wing, I.; Peterson, S.; Janetos, A.

2015-12-01

In 2013, on-road mobile sources were responsible for over 26% of U.S. fossil fuel carbon dioxide (ffCO2) emissions, and over 34% of both CO and NOx emissions. However, accurate representations of these emissions at the scale of urban areas remains a difficult challenge. Quantifying emissions at the scale of local streets and highways is critical to provide policymakers with the information needed to develop appropriate mitigation strategies and to guide research into the underlying process that drive mobile emissions. Quantification of vehicle ffCO2 emissions at high spatial and temporal resolutions requires a detailed synthesis of data on traffic activity, roadway attributes, fleet characteristics and vehicle speeds. To accurately characterize criteria air pollutant emissions, information on local meteorology is also critical, as the temperature and relative humidity can affect emissions rates of these pollutants by as much as 400%. As the health impacts of air pollutants are more severe for residents living in close proximity (<500m) to road sources, it is critical that inventories of these emissions rely on highly resolved source data to locate potential hot-spots of exposure. In this study we utilize real-time GPS estimates of vehicle speeds to estimate ffCO2 and criteria air pollutant emissions at multiple spatial and temporal scales across a large metropolitan area. We observe large variations in emissions associated with diurnal activity patterns, congestion, sporting and civic events, and weather anomalies. We discuss the advantages and challenges of using highly-resolved source data to quantify emissions at a roadway scale, and the potential of this methodology for forecasting the air quality impacts of changes in infrastructure, urban planning policies, and regional climate.

Examination of Daily Weather in the NCAR CCM

NASA Astrophysics Data System (ADS)

Cocke, S. D.

2006-05-01

The NCAR CCM is one of the most extensively studied climate models in the scientific community. However, most studies focus primarily on the long term mean behavior, typically monthly or longer time scales. In this study we examine the daily weather in the GCM by performing a series of daily or weekly 10 day forecasts for one year at moderate (T63) and high (T126) resolution. The model is initialized with operational "AVN" and ECMWF analyses, and model performance is compared to that of major operational centers, using conventional skill scores used by the major centers. Such a detailed look at the CCM at shorter time scales may lead to improvements in physical parameterizations, which may in turn lead to improved climate simulations. One finding from this study is that the CCM has a significant drying tendency in the lower troposphere compared to the operational analyses. Another is that the large scale predictability of the GCM is competitive with most of the operational models, particularly in the southern hemisphere.

Cost Factors in Scaling in SfM Collections and Processing Solutions

NASA Astrophysics Data System (ADS)

Cherry, J. E.

2015-12-01

In this talk I will discuss the economics of scaling Structure from Motion (SfM)-style collections from 1 km2 and below to 100's and 1000's of square kilometers. Considerations include the costs of the technical equipment: comparisons of small, medium, and large-format camera systems, as well as various GPS-INS systems and their impact on processing accuracy for various Ground Sampling Distances. Tradeoffs between camera formats and flight time are central. Weather conditions and planning high altitude versus low altitude flights are another economic factor, particularly in areas of persistently bad weather and in areas where ground logistics (i.e. hotel rooms and pilot incidentals) are expensive. Unique costs associated with UAS collections and experimental payloads will be discussed. Finally, the costs of equipment and labor differs in SfM processing than in conventional orthomosaic and LiDAR processing. There are opportunities for 'economies of scale' in SfM collections under certain circumstances but whether the accuracy specifications are firm/fixed or 'best effort' makes a difference.