44 resultados para Space Weather


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Recent studies of the variation of geomagnetic activity over the past 140 years have quantified the "coronal source" or "open" magnetic flux F-s that leaves the solar atmosphere and enters the heliosphere and have shown that it has risen, on average, by 34% since 1963 and by 140% since 1900. This variation is reflected in studies of the heliospheric field using isotopes deposited in ice sheets and meteorites by the action of galactic comic rays. The variation has also been reproduced using a model that demonstrates how the open flux accumulates and decays, depending on the rate of flux emergence in active regions and on the length of the solar cycle. The cosmic ray flux at energies > 3 GeV is found to have decayed by about 15% during the 20(th) century (and by about 4% at > 13 GeV). We show that the changes in the open flux do reflect changes in the photospheric and sub-surface field which offers an explanation of why open flux appears to be a good proxy for solar irradiance extrapolation. Correlations between F-s, solar cycle length, L, and 11-year smoothed sunspot number, R-11, explain why the various irradiance reconstructions for the last 150 years are similar in form. Possible implications of the inferred changes in cosmic ray flux and irradiance for global temperatures on Earth are discussed.

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The polar cap boundary is a subject of central importance to current magnetosphere-ionosphere research and its applications in “space weather” activities. The problems are that it has a number of definitions, and that the most physically meaningful definition (namely the open-closed field line boundary) is very difficult to identify in observations. New understanding of the importance of the structure and dynamics of the boundary region made the time right for a meeting reviewing our knowledge in this area. The Advanced Study Institute (ASI) on Svalbard in June 1997 discussed the boundary on both the dayside and the nightside, mapping magnetically to the dayside magnetopause and to tail plasma sheet/lobe interface, respectively. We held a “brainstorming” session, in which different ideas which arose from the presented papers were discussed and developed, and a summary session, in which session convenors gave a personal view of progress that has been made and problems which still need solving. Both were designed as ways of promoting further discussion. This paper attempts to distil some of the themes that emerged from these discussions.

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Between December 2010 and March 2013, volunteers for the Solar Stormwatch (SSW) Citizen Science project have identified and analyzed coronal mass ejections (CMEs) in the near real-time Solar Terrestrial Relations Observatory Heliospheric Imager observations, in order to make “Fearless Forecasts” of CME arrival times and speeds at Earth. Of the 60 predictions of Earth-directed CMEs, 20 resulted in an identifiable Interplanetary CME (ICME) at Earth within 1.5–6 days, with an average error in predicted transit time of 22 h, and average transit time of 82.3 h. The average error in predicting arrival speed is 151 km s−1, with an average arrival speed of 425km s−1. In the same time period, there were 44 CMEs for which there are no corresponding SSW predictions, and there were 600 days on which there was neither a CME predicted nor observed. A number of metrics show that the SSW predictions do have useful forecast skill; however, there is still much room for improvement. We investigate potential improvements by using SSW inputs in three models of ICME propagation: two of constant acceleration and one of aerodynamic drag. We find that taking account of interplanetary acceleration can improve the average errors of transit time to 19 h and arrival speed to 77 km s−1.

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A Hale cycle, one complete magnetic cycle of the Sun, spans two complete Schwabe cycles (also referred to as sunspot and, more generally, solar cycles). The approximately 22-year Hale cycle is seen in magnetic polarities of both sunspots and polar fields, as well as in the intensity of galactic cosmic rays reaching Earth, with odd- and even-numbered solar cycles displaying qualitatively different waveforms. Correct numbering of solar cycles also underpins empirical cycle-to-cycle relations which are used as first-order tests of stellar dynamo models. There has been much debate about whether the unusually long solar cycle 4 (SC4), spanning- 1784–1799, was actually two shorter solar cycles combined as a result of poor data coverage in the original Wolf sunspot number record. Indeed, the group sunspot number does show a small increase around 1794–1799 and there is evidence of an increase in the mean latitude of sunspots at this time, suggesting the existence of a cycle ‘‘4b’’. In this study, we use cosmogenic radionuclide data and associated reconstructions of the heliospheric magnetic field (HMF) to show that the Hale cycle has persisted over the last 300 years and that data prior to 1800 are more consistent with cycle 4 being a single long cycle (the ‘‘no SC4b’’ scenario). We also investigate the effect of cycle 4b on the HMF using an open solar flux (OSF) continuity model, in which the OSF source term is related to sunspot number and the OSF loss term is determined by the heliospheric current sheet tilt, assumed to be a simple function of solar cycle phase. The results are surprising; Without SC4b, the HMF shows two distinct peaks in the 1784–1799 interval, while the addition of SC4b removes the secondary peak, as the OSF loss term acts in opposition to the later rise in sunspot number. The timing and magnitude of the main SC4 HMF peak is also significantly changed by the addition of SC4b. These results are compared with the cosmogenic isotope reconstructions of HMF and historical aurora records. These data marginally favour the existence of SC4b (the ‘‘SC4b’’ scenario), though the result is less certain than that based on the persistence of the Hale cycle. Thus while the current uncertainties in the observations preclude any definitive conclusions, the data favour the ‘‘no SC4b’’ scenario. Future improvements to cosmogenic isotope reconstructions of the HMF, through either improved modelling or additional ice cores from well-separated geographic locations, may enable questions of the existence of SC4b and the phase of Hale cycle prior to the Maunder minimum to be settled conclusively.

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Observations from the Heliospheric Imager (HI) instruments aboard the twin STEREO spacecraft have enabled the compilation of several catalogues of coronal mass ejections (CMEs), each characterizing the propagation of CMEs through the inner heliosphere. Three such catalogues are the Rutherford Appleton Laboratory (RAL)-HI event list, the Solar Stormwatch CME catalogue, and, presented here, the J-tracker catalogue. Each catalogue uses a different method to characterize the location of CME fronts in the HI images: manual identification by an expert, the statistical reduction of the manual identifications of many citizen scientists, and an automated algorithm. We provide a quantitative comparison of the differences between these catalogues and techniques, using 51 CMEs common to each catalogue. The time-elongation profiles of these CME fronts are compared, as are the estimates of the CME kinematics derived from application of three widely used single-spacecraft-fitting techniques. The J-tracker and RAL-HI profiles are most similar, while the Solar Stormwatch profiles display a small systematic offset. Evidence is presented that these differences arise because the RAL-HI and J-tracker profiles follow the sunward edge of CME density enhancements, while Solar Stormwatch profiles track closer to the antisunward (leading) edge. We demonstrate that the method used to produce the time-elongation profile typically introduces more variability into the kinematic estimates than differences between the various single-spacecraft-fitting techniques. This has implications for the repeatability and robustness of these types of analyses, arguably especially so in the context of space weather forecasting, where it could make the results strongly dependent on the methods used by the forecaster.

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Southward Interplanetary Magnetic Field (IMF) in the Geocentric Solar Magnetospheric (GSM) reference frame is the key element that controls the level of space-weather disturbance in Earth’s magnetosphere, ionosphere and thermosphere. We discuss the relation of this geoeffective IMF component to the IMF in the Geocentric Solar Ecliptic (GSE) frame and, using the almost continuous interplanetary data for 1996-2015 (inclusive), we show that large geomagnetic storms are always associated with strong southward, out-of-ecliptic field in the GSE frame: dipole tilt effects, that cause the difference between the southward field in the GSM and GSE frames, generally make only a minor contribution to these strongest storms. The time-of-day/time-of-year response patterns of geomagnetic indices and the optimum solar wind coupling function are both influenced by the timescale of the index response. We also study the occurrence spectrum of large out-of-ecliptic field and show that for one-hour averages it is, surprisingly, almost identical in ICMEs (Interplanetary Coronal Mass Ejections), around CIRs/SIRs (Corotating and Stream Interaction Regions) and in the “quiet” solar wind (which is shown to be consistent with the effect of weak SIRs). However, differences emerge when the timescale over which the field remains southward is considered: for longer averaging timescales the spectrum is broader inside ICMEs, showing that these events generate longer intervals of strongly southward average IMF and consequently stronger geomagnetic storms. The behavior of out-of-ecliptic field with timescale is shown to be very similar to that of deviations from the predicted Parker spiral orientation, suggesting the two share common origins.

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This paper provides for the first time an objective short-term (8 yr) climatology of African convective weather systems based on satellite imagery. Eight years of infrared International Satellite Cloud Climatology Project-European Space Agency's Meteorological Satellite (ISCCP-Meteosat) satellite imagery has been analyzed using objective feature identification, tracking, and statistical techniques for the July, August, and September periods and the region of Africa and the adjacent Atlantic ocean. This allows various diagnostics to be computed and used to study the distribution of mesoscale and synoptic-scale convective weather systems from mesoscale cloud clusters and squall lines to tropical cyclones. An 8-yr seasonal climatology (1983-90) and the seasonal cycle of this convective activity are presented and discussed. Also discussed is the dependence of organized convection for this region, on the orography, convective, and potential instability and vertical wind shear using European Centre for Medium-Range Weather Forecasts reanalysis data.

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The coarse spacing of automatic rain gauges complicates near-real- time spatial analyses of precipitation. We test the possibility of improving such analyses by considering, in addition to the in situ measurements, the spatial covariance structure inferred from past observations with a denser network. To this end, a statistical reconstruction technique, reduced space optimal interpolation (RSOI), is applied over Switzerland, a region of complex topography. RSOI consists of two main parts. First, principal component analysis (PCA) is applied to obtain a reduced space representation of gridded high- resolution precipitation fields available for a multiyear calibration period in the past. Second, sparse real-time rain gauge observations are used to estimate the principal component scores and to reconstruct the precipitation field. In this way, climatological information at higher resolution than the near-real-time measurements is incorporated into the spatial analysis. PCA is found to efficiently reduce the dimensionality of the calibration fields, and RSOI is successful despite the difficulties associated with the statistical distribution of daily precipitation (skewness, dry days). Examples and a systematic evaluation show substantial added value over a simple interpolation technique that uses near-real-time observations only. The benefit is particularly strong for larger- scale precipitation and prominent topographic effects. Small-scale precipitation features are reconstructed at a skill comparable to that of the simple technique. Stratifying the reconstruction method by the types of weather type classifications yields little added skill. Apart from application in near real time, RSOI may also be valuable for enhancing instrumental precipitation analyses for the historic past when direct observations were sparse.

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This dissertation deals with aspects of sequential data assimilation (in particular ensemble Kalman filtering) and numerical weather forecasting. In the first part, the recently formulated Ensemble Kalman-Bucy (EnKBF) filter is revisited. It is shown that the previously used numerical integration scheme fails when the magnitude of the background error covariance grows beyond that of the observational error covariance in the forecast window. Therefore, we present a suitable integration scheme that handles the stiffening of the differential equations involved and doesn’t represent further computational expense. Moreover, a transform-based alternative to the EnKBF is developed: under this scheme, the operations are performed in the ensemble space instead of in the state space. Advantages of this formulation are explained. For the first time, the EnKBF is implemented in an atmospheric model. The second part of this work deals with ensemble clustering, a phenomenon that arises when performing data assimilation using of deterministic ensemble square root filters in highly nonlinear forecast models. Namely, an M-member ensemble detaches into an outlier and a cluster of M-1 members. Previous works may suggest that this issue represents a failure of EnSRFs; this work dispels that notion. It is shown that ensemble clustering can be reverted also due to nonlinear processes, in particular the alternation between nonlinear expansion and compression of the ensemble for different regions of the attractor. Some EnSRFs that use random rotations have been developed to overcome this issue; these formulations are analyzed and their advantages and disadvantages with respect to common EnSRFs are discussed. The third and last part contains the implementation of the Robert-Asselin-Williams (RAW) filter in an atmospheric model. The RAW filter is an improvement to the widely popular Robert-Asselin filter that successfully suppresses spurious computational waves while avoiding any distortion in the mean value of the function. Using statistical significance tests both at the local and field level, it is shown that the climatology of the SPEEDY model is not modified by the changed time stepping scheme; hence, no retuning of the parameterizations is required. It is found the accuracy of the medium-term forecasts is increased by using the RAW filter.

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The currently available model-based global data sets of atmospheric circulation are a by-product of the daily requirement of producing initial conditions for numerical weather prediction (NWP) models. These data sets have been quite useful for studying fundamental dynamical and physical processes, and for describing the nature of the general circulation of the atmosphere. However, due to limitations in the early data assimilation systems and inconsistencies caused by numerous model changes, the available model-based global data sets may not be suitable for studying global climate change. A comprehensive analysis of global observations based on a four-dimensional data assimilation system with a realistic physical model should be undertaken to integrate space and in situ observations to produce internally consistent, homogeneous, multivariate data sets for the earth's climate system. The concept is equally applicable for producing data sets for the atmosphere, the oceans, and the biosphere, and such data sets will be quite useful for studying global climate change.

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Biodiversity has been defined as the totality of genes, species, and ecosystems that inhabit the earth with the field contributing to many aspects of our lives and livelihoods by providing us with food, drink, medicines and shelter, as well as contributing to improving our surrounding environment. Benefits include providing life services through improved horticultural production, improving the business and service of horticulture as well as our environment, as well as improving our health and wellbeing, and our social and cultural relationships. Threats to biodiversity can include fragmentation, degradation and deforestation of habitat, introduction of invasive and exotic species, climate change and extreme weather events, over-exploitation of our natural resources, hybridisation, genetic pollution/erosion and food security issues and human overpopulation. This chapter examines a series of examples that provide the dual aims of biodiversity conservation and horticultural production and service; namely organic horticultural cropping, turf management, and nature-based tourism, and ways of valuing biological biodiversity such as the payment of environmental services and bio-prospecting. Horticulture plays a major role in the preserving of biodiversity.

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Remotely sensed rainfall is increasingly being used to manage climate-related risk in gauge sparse regions. Applications based on such data must make maximal use of the skill of the methodology in order to avoid doing harm by providing misleading information. This is especially challenging in regions, such as Africa, which lack gauge data for validation. In this study, we show how calibrated ensembles of equally likely rainfall can be used to infer uncertainty in remotely sensed rainfall estimates, and subsequently in assessment of drought. We illustrate the methodology through a case study of weather index insurance (WII) in Zambia. Unlike traditional insurance, which compensates proven agricultural losses, WII pays out in the event that a weather index is breached. As remotely sensed rainfall is used to extend WII schemes to large numbers of farmers, it is crucial to ensure that the indices being insured are skillful representations of local environmental conditions. In our study we drive a land surface model with rainfall ensembles, in order to demonstrate how aggregation of rainfall estimates in space and time results in a clearer link with soil moisture, and hence a truer representation of agricultural drought. Although our study focuses on agricultural insurance, the methodological principles for application design are widely applicable in Africa and elsewhere.