903 resultados para Google earth
Resumo:
Earth observations (EO) represent a growing and valuable resource for many scientific, research and practical applications carried out by users around the world. Access to EO data for some applications or activities, like climate change research or emergency response activities, becomes indispensable for their success. However, often EO data or products made of them are (or are claimed to be) subject to intellectual property law protection and are licensed under specific conditions regarding access and use. Restrictive conditions on data use can be prohibitive for further work with the data. Global Earth Observation System of Systems (GEOSS) is an initiative led by the Group on Earth Observations (GEO) with the aim to provide coordinated, comprehensive, and sustained EO and information for making informed decisions in various areas beneficial to societies, their functioning and development. It seeks to share data with users world-wide with the fewest possible restrictions on their use by implementing GEOSS Data Sharing Principles adopted by GEO. The Principles proclaim full and open exchange of data shared within GEOSS, while recognising relevant international instruments and national policies and legislation through which restrictions on the use of data may be imposed.The paper focuses on the issue of the legal interoperability of data that are shared with varying restrictions on use with the aim to explore the options of making data interoperable. The main question it addresses is whether the public domain or its equivalents represent the best mechanism to ensure legal interoperability of data. To this end, the paper analyses legal protection regimes and their norms applicable to EO data. Based on the findings, it highlights the existing public law statutory, regulatory, and policy approaches, as well as private law instruments, such as waivers, licenses and contracts, that may be used to place the datasets in the public domain, or otherwise make them publicly available for use and re-use without restrictions. It uses GEOSS and the particular characteristics of it as a system to identify the ways to reconcile the vast possibilities it provides through sharing of data from various sources and jurisdictions on the one hand, and the restrictions on the use of the shared resources on the other. On a more general level the paper seeks to draw attention to the obstacles and potential regulatory solutions for sharing factual or research data for the purposes that go beyond research and education.
Resumo:
The Earth's bow shock is very efficient in accelerating ions out of the incident solar wind distribution to high energies (≈ 200 keV/e). Fluxes of energetic ions accelerated at the quasi-parallel bow shock, also known as diffuse ions, are best represented by exponential spectra in energy/charge, which require additional assumptions to be incorporated into these model spectra. One of these assumptions is a so-called "free escape boundary" along the interplanetary magnetic field into the upstream direction. Locations along the IBEX orbit are ideally suited for in situ measurements to investigate the existence of an upstream free escape boundary for bow shock accelerated ions. In this study we use 2 years of ion measurements from the background monitor on the IBEX spacecraft, supported by ACE solar wind observations. The IBEX Background Monitor is sensitive to protons > 14 keV, which includes the energy of the maximum flux for diffuse ions. With increasing distance from the bow shock along the interplanetary magnetic field, the count rates for diffuse ions stay constant for ions streaming away from the bow shock, while count rates for diffuse ions streaming toward the shock gradually decrease from a maximum value to ~1/e at distances of about 10 RE to 14 RE. These observations of a gradual decrease support the transition to a free escape continuum for ions of energy >14 keV at distances from 10 RE to 14 RE from the bow shock.
Resumo:
An ever increasing number of low Earth orbiting (LEO) satellites is, or will be, equipped with retro-reflectors for Satellite Laser Ranging (SLR) and on-board receivers to collect observations from Global Navigation Satellite Systems (GNSS) such as the Global Positioning Sys- tem (GPS) and the Russian GLONASS and the European Galileo systems in the future. At the Astronomical Insti- tute of the University of Bern (AIUB) LEO precise or- bit determination (POD) using either GPS or SLR data is performed for a wide range of applications for satellites at different altitudes. For this purpose the classical numeri- cal integration techniques, as also used for dynamic orbit determination of satellites at high altitudes, are extended by pseudo-stochastic orbit modeling techniques to effi- ciently cope with potential force model deficiencies for satellites at low altitudes. Accuracies of better than 2 cm may be achieved by pseudo-stochastic orbit modeling for satellites at very low altitudes such as for the GPS-based POD of the Gravity field and steady-state Ocean Circula- tion Explorer (GOCE).
Resumo:
The time variable Earth’s gravity field provides the information about mass transport within the system Earth, i.e., the relationship of mass transport between atmosphere, oceans, and land hydrology. We recover the low-degree parameters of the time variable gravity field using microwave observations from GPS and GLONASS satellites and from SLR data to five geodetic satellites, namely LAGEOS-1/2, Starlette, Stella, and AJISAI. GPS satellites are particularly sensitive to specific coefficients of the Earth's gravity field, because of the deep 2:1 orbital resonance with Earth rotation (two revolutions of the GPS satellites per sidereal day). The resonant coefficients cause, among other, a “secular” drift (actually periodic variations of very long periods) of the semi-major axes of up to 5.3 m/day of GPS satellites. We processed 10 years of GPS and GLONASS data using the standard orbit models from the Center of Orbit Determination in Europe (CODE) with a simultaneous estimation of the Earth gravity field coefficients and other parameters, e.g., satellite orbit parameters, station coordinates, Earth rotation parameters, troposphere delays, etc. The weekly GNSS gravity solutions up to degree and order 4/4 are compared to the weekly SLR gravity field solutions. The SLR-derived geopotential coefficients are compared to monthly GRACE and CHAMP results.
Resumo:
Surface temperature is a key aspect of weather and climate, but the term may refer to different quantities that play interconnected roles and are observed by different means. In a community-based activity in June 2012, the EarthTemp Network brought together 55 researchers from five continents to improve the interaction between scientific communities who focus on surface temperature in particular domains, to exploit the strengths of different observing systems and to better meet the needs of different communities. The workshop identified key needs for progress towards meeting scientific and societal requirements for surface temperature understanding and information, which are presented in this community paper. A "whole-Earth" perspective is required with more integrated, collaborative approaches to observing and understanding Earth's various surface temperatures. It is necessary to build understanding of the relationships between different surface temperatures, where presently inadequate, and undertake large-scale systematic intercomparisons. Datasets need to be easier to obtain and exploit for a wide constituency of users, with the differences and complementarities communicated in readily understood terms, and realistic and consistent uncertainty information provided. Steps were also recommended to curate and make available data that are presently inaccessible, develop new observing systems and build capacities to accelerate progress in the accuracy and usability of surface temperature datasets.
Resumo:
Both historical and idealized climate model experiments are performed with a variety of Earth system models of intermediate complexity (EMICs) as part of a community contribution to the Intergovernmental Panel on Climate Change Fifth Assessment Report. Historical simulations start at 850 CE and continue through to 2005. The standard simulations include changes in forcing from solar luminosity, Earth's orbital configuration, CO2, additional greenhouse gases, land use, and sulphate and volcanic aerosols. In spite of very different modelled pre-industrial global surface air temperatures, overall 20th century trends in surface air temperature and carbon uptake are reasonably well simulated when compared to observed trends. Land carbon fluxes show much more variation between models than ocean carbon fluxes, and recent land fluxes appear to be slightly underestimated. It is possible that recent modelled climate trends or climate–carbon feedbacks are overestimated resulting in too much land carbon loss or that carbon uptake due to CO2 and/or nitrogen fertilization is underestimated. Several one thousand year long, idealized, 2 × and 4 × CO2 experiments are used to quantify standard model characteristics, including transient and equilibrium climate sensitivities, and climate–carbon feedbacks. The values from EMICs generally fall within the range given by general circulation models. Seven additional historical simulations, each including a single specified forcing, are used to assess the contributions of different climate forcings to the overall climate and carbon cycle response. The response of surface air temperature is the linear sum of the individual forcings, while the carbon cycle response shows a non-linear interaction between land-use change and CO2 forcings for some models. Finally, the preindustrial portions of the last millennium simulations are used to assess historical model carbon-climate feedbacks. Given the specified forcing, there is a tendency for the EMICs to underestimate the drop in surface air temperature and CO2 between the Medieval Climate Anomaly and the Little Ice Age estimated from palaeoclimate reconstructions. This in turn could be a result of unforced variability within the climate system, uncertainty in the reconstructions of temperature and CO2, errors in the reconstructions of forcing used to drive the models, or the incomplete representation of certain processes within the models. Given the forcing datasets used in this study, the models calculate significant land-use emissions over the pre-industrial period. This implies that land-use emissions might need to be taken into account, when making estimates of climate–carbon feedbacks from palaeoclimate reconstructions.