In the 1990s, a photo taken by the probe Voyager showed the Earth as a small island right in the middle of an infinite black ocean 6 billion kilometres away. A ‘Blue Marble’ turned into a ‘Pale Blue Dot’ and initiated a public discourse about a sustainable handling of our resources. Therefore, ‘Blue Dot – Shaping the Future’ became the title of the mission of Alexander Gerst’s space flight. From 28 May to 10 November 10, 2014 the ESA Astronaut fascinated the German public with his live-impressions from the International Space Station (ISS). Simultaneously, the project ‘Columbus Eye – Live-Imagery from the ISS in Schools’ established a learning portal on earth observation from the ISS (www.columbuseye.uni-bonn.de). The portal makes use of NASA’s High Definition Earth Viewing (HDEV) experiment which features four cameras observing the earth 24/7. Columbus Eye is carried out at the University of Bonn and sponsored by the German Aerospace Center (DLR) Space Administration. The main goal of Columbus Eye is to enable children to observe our planet from the astronaut’s perspective while applying professional remote sensing analysis tools. During the IAC 2014, we published a concept on how the fascination of technology and environment should be bundled in order to ignite the pupil’s interest on spaceflight and earth observation. Following up on this, in 2015 we are proud to present the implementations of this concept: the HDEV archive and, even more important, the observatory. While the archive provides spectacular footage of e.g. the Mediterranean Sea, the Himalaya, and sunrises available for everybody, the observatory was specifically constructed for pupils and teachers. Here, it is possible to learn about processes and phenomena of the coupled human- environment system in an interactive manner. The pupils can conduct easy-to-use image processing analyses on their own. In doing so, they get the opportunity to derive a map out of an HDEV image and hence turn a continuous spatial texture into a discrete spatial pattern of land uses. The presentation explains how teachers can be taught to apply the Columbus Eye learning tools in their everyday school lessons. Additionally, we present the next mission of the project: HDEV videos will be edited in order to perceive them in virtual reality. Witnessing geospatial analysis turns into experience and enters our understanding.
Research Containing: Earth Observation
Imaging Observation of the Earth's Plasmasphere and Ionosphere by EUVI of ISS-IMAP on the International Space Station
At the end of previous century, we succeeded to image the Earth's plasmasphere from the space by EUV spectral range. Then, spacecraft missions were carried out to image the terrestrial EUV emissions. The extreme ultraviolet imagers (EUVIs) on the international space station (ISS) will be launched in 2012. At the altitude of approximately 400 km, two telescopes direct toward the Earth's limb to look the ionosphere and plasmasphere from the inside-out. One telescope detects the terrestrial EUV emission at O+ (83.4 nm), and the other is He+ (30.4 nm). These two EUV emissions are solar-scattered by ionized oxygen and helium, respectively. The maximum spatial and time resolutions are 0.1 degree and 1 minute, respectively. Our observation methods will become standard to probe the Earth's upper atmosphere.
We estimate the capability of ozone (O3) retrieval with the Superconducting Submillimeter-Wave Limb-Emission Sounder (SMILES) instrument attached to the Exposed Facility of the Japanese Experiment Module (JEM) on the International Space Station (ISS). SMILES carries a 4-K mechanical refrigerator to cool superconducting devices in space. Since SMILES has high sensitivity thanks to the superconducting receiver, it is expected that SMILES has ability to retrieve O3 profiles more precisely than the previous millimeter–submillimeter limb measurements from satellites. We examine the random error and the systematic error of O3 vertical profiles based on the launch-ready retrieval algorithm developed for SMILES. The best random error with single-scan spectra is 0.4% at an altitude of 30 km with 3 km vertical resolution in the mid-latitudes. The random error is better than 5% in the altitude region from 15 to 70 km in the nighttime and from 15 to 55 km in the daytime with 3 km vertical resolution in the mid-latitudes. By averaging ten profiles, the random error is improved to 1% at 70 km altitude in the nighttime and to 5% in the daytime. Using SMILES, we expect to determine the diurnal variation of O3 vertical profiles with high precision in the upper stratosphere. Finally, the retrieval capability of O3 in the lower stratosphere is estimated. When retrieving spectral data using two receiver bands (624.32–626.32 GHz and 649.12–650.32 GHz) the random error above 13 km in the mid-latitudes and above 15 km in the tropics is expected to be better than 5% under clear sky conditions.
A method is disclosed for identifying a sediment accumulation from an image of a part of the earth's surface. The method includes identifying a topographic discontinuity from the image. A river which crosses the discontinuity is identified from the image. From the image, paleocourses of the river are identified which diverge from a point where the river crosses the discontinuity. The paleocourses are disposed on a topographically low side of the discontinuity. A smooth surface which emanates from the point is identified. The smooth surface is also disposed on the topographically low side of the point.
Astronaut photography of cities collected during Apollo, Skylab, Shuttle, Mir, and International Space Station missions provides a useful dataset for urban analysis that complements the satellite data archive. Recent astronaut photography acquired with digital cameras is now approaching the ground resolutions of commercial satellites such as IKONOS (i.e. less than 6 m/pixel). Astronaut photographs are a relevant source of data for urban analyses, particularly for studies that do not have the resources to purchase commercial-quality data. The CCD image sensors in the cameras currently used for astronaut photography are sensitive to the infrared portion of the electromagnetic spectrum, but infrared signal is filtered out above 700 μm. As such, the digital camera data contain less information on actively synthesizing vegetation than they would with an infrared signal included. We present an analysis of aboveground biomass (i.e. actively photosynthesizing vegetation) derived from astronaut photography of the Paris, France metropolitan area acquired on April 24, 2002 using a Kodak DCS 760C electronic still camera aboard the International Space Station. The accuracy of biomass estimation obtained from the digital camera data is demonstrated by comparison with Advanced Spaceborne Thermal Emission and Reflection Radiometer visible to near infrared data for Paris acquired on April 8, 2002. Correlations of bands between the two instruments allow interpretation of the identified vegetation and soil classes. Collection of astronaut photography over global urban centers is ongoing and planned for future orbital missions, and will be a useful addition to ongoing studies of urban ecosystem change, sustainability, and resilience.
Early Results From 4K-Cooled Superconducting Submm Wave Limb Emission Sounder SMILES Onboard ISS/JEM
Early comparison of O3, HCl, and HNO3 L2 products (ver. 005-06-0032) of the Superconducting Submillimeter-Wave Limb-Emission Sounder (SMILES) onboard International Space Station has been conducted. Good agreements are observed among SMILES, SVISAT-1/ACE-FTS, AURA/MLS, and ENVISAT.MIPAS, for O3 and HCl below 45 km. SMILES HNO3 profiles are statistically ~20% higher than ACE-FTS and MIPAS. At higher altitude region, 45-60 km, SMILES O3 and HCl are considerably different from ACE-FTS and/or MLS. It is concluded, although future data updates will be necessary, SMILES O3 and HCl below 45 km are both useful for scientific application with special cautions to the SMILES data quality.
Calving and ice-shelf break-up processes investigated by proxy: Antarctic tabular iceberg evolution during northward drift
Using a combination of satellite sensors, field measurements and satellite-uplinked in situ observing stations, we examine the evolution of several large icebergs drifting east of the Antarctic Peninsula towards South Georgia Island. Three styles of calving are observed during drift: 'rift calvings', 'edge wasting' and 'rapid disintegration'. Rift calvings exploit large pre-existing fractures generated in the shelf environment and can occur at any stage of drift. Edge wasting is calving of the iceberg perimeter by numerous small edge-parallel, sliver-shaped icebergs, preserving the general shape of the main iceberg as it shrinks. This process is observed only in areas north of the sea-ice edge. Rapid disintegration, where numerous small calvings occur in rapid succession, is consistently associated with indications of surface melt saturation (surface lakes, firn-pit ponding). Freeboard measurements by ICESat indicate substantial increases in ice-thinning rates north of the sea-ice edge (from <10ma−1 to >30ma−1), but surface densification is shown to be an important correction (>2m freeboard loss before the firn saturates). Edge wasting of icebergs in 'warm' surface water (sea-ice-free, >−1.8 °C) implies a mechanism based on waterline erosion. Rapid disintegration ('Larsen B-style' break-up) is likely due to the effects of surface or saturated-firn water acting on pre-existing crevasses, or on wave- or tidally induced fractures. Changes in microwave backscatter of iceberg firn as icebergs drift into warmer climate and experience increased surface melt suggest a means of predicting when floating ice plates are evolving towards disintegration.
To measure the thermal emission from stratospheric minor species with high sensitivity, the Superconducting Submillimeter-wave Limb-Emission Sounder (SMILES) aboard the Japanese Experiment Module (JEM) of the International Space Station (ISS) carries 4 K cooled Superconductor–Insulator–Superconductor (SIS) mixers. The major feature of the SMILES is its high-sensitive measurement ability with low system noise temperature less than 700 K. As a part of the ground system for the SMILES, a level 2 data processing system (DPS-L2) has been developed. It retrieves the density distributions of the target species from calibrated spectra in near-real-time. The retrieval process consists of two parts: the forward model, which computes radiative transfer, and the inverse model, which deduces atmospheric states. Since the forward model must provide the most accurate basis for results and be implemented under limited computing resources, the forward model algorithm for an operational system has to be accurate and fast. Hence, the algorithm is improved (1) by designing accurate instrument functions such as the instrumental field of view (FOV), sideband rejection ratio of sideband separator, and spectral responses of acousto-optic spectrometer (AOS) and (2) by optimizing radiative transfer calculation. This paper presents the development of the DPS-L2 along with the details on its algorithm and the algorithm performance. The accuracy of this algorithm is better than 1%, and the processing time for single-scan spectra is less than 1 min with eight parallel processings using a 3.16-GHz Quad-Core Intel Xeon processor. Thus, this algorithm is suitable for the SMILES measurement.
The use of SMILES data to study ozone loss in the Arctic winter 2009/2010 and comparison with Odin/SMR data using assimilation techniques
The Superconducting Submillimeter-Wave Limb-Emission Sounder (SMILES) on board the International Space Station observed ozone in the stratosphere with high precision from October 2009 to April 2010. Although SMILES measurements only cover latitudes from 38° S to 65° N, the combination of data assimilation methods and an isentropic advection model allows us to quantify the ozone depletion in the 2009/2010 Arctic polar winter by making use of the instability of the polar vortex in the northern hemisphere. Ozone data from both SMILES and Odin/SMR (Sub-Millimetre Radiometer) for the winter were assimilated into the Dynamical Isentropic Assimilation Model for OdiN Data (DIAMOND). DIAMOND is an off-line wind-driven transport model on isentropic surfaces. Wind data from the operational analyses of the European Centre for Medium- Range Weather Forecasts (ECMWF) were used to drive the model. In this study, particular attention is paid to the cross isentropic transport of the tracer in order to accurately assess the ozone loss. The assimilated SMILES ozone fields agree well with the limitation of noise induced variability within the SMR fields despite the limited latitude coverage of the SMILES observations. Ozone depletion has been derived by comparing the ozone field acquired by sequential assimilation with a passively transported ozone field initialized on 1 December 2009. Significant ozone loss was found in different periods and altitudes from using both SMILES and SMR data: The initial depletion occurred at the end of January below 550 K with an accumulated loss of 0.6–1.0 ppmv (approximately 20%) by 1 April. The ensuing loss started from the end of February between 575 K and 650 K. Our estimation shows that 0.8–1.3 ppmv (20–25 %) of O3 has been removed at the 600 K isentropic level by 1 April in volume mixing ratio (VMR).
Diurnal ozone variations in the stratosphere revealed in observations from the Superconducting Submillimeter-Wave Limb-Emission Sounder (SMILES) on board the International Space Station (ISS)
Considerable uncertainties remain in the global pattern of diurnal variation in stratospheric ozone, particularly lower to middle stratospheric ozone, which is the principal contributor to total column ozone. The Superconducting Submillimeter-Wave Limb-Emission Sounder (SMILES) attached to the Japanese Experiment Module (JEM) on board the International Space Station (ISS) was developed to gather high-quality global measurements of stratospheric ozone at various local times, with the aid of superconducting mixers cooled to 4K by a compact mechanical cooler. Using the SMILES dataset, as well as data from nudged chemistry-climate models (MIROC3.2-CTM and SD-WACCM), we show that the SMILES observational data have revealed the global pattern of diurnal ozone variations throughout the stratosphere. We also found that these variations can be explained by both photochemistry and dynamics. The peak-to-peak difference in the stratospheric ozone mixing ratio (total column ozone) reached 8% (1%) over the course of a day. This variation needs to be considered when merging ozone data from different satellite measurements and even from measurements made using one specific instrument at different local times.