The Superconducting Submillimeter-Wave Limb-Emission Sounder (SMILES) onboard the International Space Station provided global measurements of ozone profiles in the middle atmosphere from 12 October 2009 to 21 April 2010. We present validation studies of the SMILES version 2.1 ozone product based on coincidence statistics with satellite observations and outputs of chemistry and transport models (CTMs). Comparisons of the stratospheric ozone with correlative data show agreements that are generally within 10%. In the mesosphere, the agreement is also good and better than 30% even at a high altitude of 73 km, and the SMILES measurements with their local time coverage also capture the diurnal variability very well. The recommended altitude range for scientific use is from 16 to 73 km. We note that the SMILES ozone values for altitude above 26 km are smaller than some of the correlative satellite datasets; conversely the SMILES values in the lower stratosphere tend to be larger than correlative data, particularly in the tropics, with less than 8% difference below ~24 km. The larger values in the lower stratosphere are probably due to departure of retrieval results between two detection bands at altitudes below 28 km; it is ~3% at 24 km and is increasing rapidly down below.
Understanding and quantifying the natural processes that occur along coasts are critical components of managing environmental resources and planning and executing coastal operations, from humanitarian relief to military actions. However, the coastal ocean is complicated, with dissolved and suspended matter that hinders water transparency, phytoplankton blooms that can be toxic, and bathymetry and bottom types that vary over spatial scales of tens of meters, all of which affect processes in an area that spans millions of square kilometers. A hyperspectral imager collects the spectrum of the light received from each pixel in an image. For environmental characterization the wavelength range typically spans the visible and shortwave infrared wavelengths, and the spectrum is collected in contiguous spectral intervals 1–10 nanometers wide. This spectral information is exploited to provide significantly more information about vegetation, minerals, and other components in the scene than can be retrieved from panchromatic or even multispectral imagery, which rely primarily on the shape of the object for detection [Goetz et al., 1985]. Such technology can also work over shallow seas. Over the past 2 decades, experiments with hyperspectral imagers on airborne platforms have demonstrated the ability to characterize the coastal environment [Davis et al., 2002, Davis et al. 2006] and produce maps of coastal bathymetry, in-water constituents, and bottom type.
The Hyperspectral Imager for the Coastal Ocean (HICO™) environmental littoral imaging from the International Space Station
The Hyperspectral Imager for the Coastal Ocean (HICO), launched to the International Space Station in September 2009, is the first spaceborne hyperspectral imager optimized for environmental characterization of the coastal ocean. Building on the heritage of airborne hyperspectral imagers, HICO; combines high signal-to-noise ratio, contiguous 10 nm wide spectral channels over the range 400 to 900 nm, and a scene size of 42 × 190 km to capture the scale of coastal dynamics. HICO; image data is being exploited to produce maps of coastal ocean properties including bathymetry, in-water suspended and dissolved matter, and bottom characteristics, offering a new remote sensing capability for coastal environments worldwide. In this paper we discuss the development and performance characteristics of the HICO™ imager, and present example HICO™ data products.
The Navy has a requirement to rapidly and covertly characterize the coastal environment in support of Joint Strike Initiatives. Over the past 15 years we have demonstrated that spaceborne hyperspectral remote sensing is the best approach to covertly acquire data on shallow water bathymetry, bottom types, hazards to navigation, water clarity and beach and shore trafficability to meet those requirements. The long term goal of this work is to put a hyperspectral imager capable of making the appropriate measurements in space to demonstrate this capability.
Coastal Features and River Plumes as Seen with the Hyperspectral Imager for the Coastal Ocean (HICO)
The Hyperspectral Imager for the Coastal Ocean (HICO) is now operating on the International Space Station. Here we review the processing of HICO data and its application to study coastal features and river plumes.
The Hyperspectral Imager for the Coastal Ocean (HICO) is the first spaceborne imaging spectrometer designed to sample the coastal ocean. HICO samples selected coastal regions at 92 m ground sample distance with full spectral coverage (88 channels covering 400 to 900 nm) and a high signal-to-noise ratio to resolve the complexity of the coastal ocean. HICO has been operating on the International Space Station since October 2009 and collected over 8000 scenes for more than 50 users. We have been using HICO data to study major rivers and estuaries in the US and Asia. Our results show the advantages of HICO’s additional spectral channels and higher spatial resolution for studying these complex coastal waters. We use these data to suggest requirements for spatial and spectral sampling for future ocean color sensors.
Data Processing and First Products from the Hyperspectral Imager for the Coastal Ocean (HICO) on the International Space Station
The Hyperspectral Imager for the Coastal Ocean (HICO) was installed on the International Space Station on September 24, 2009. HICO is the first spaceborne hyperspectral imager optimized for environmental characterization of the coastal zone. HICO data are collected and processed to produce maps including coastal bathymetry, bottom characteristics, and water column optical properties. Here we describe the HICO data processing system and give examples of HICO products.
Evaluation of ionospheric densities using coincident OII 83.4 nm airglow and the Millstone Hill Radar
We test the utility of the OII 83.4 nm emission feature as a measure of ionospheric parameters. Observed with the Remote Atmospheric and Ionospheric Detection System (RAIDS) Extreme Ultraviolet Spectrograph on the International Space Station (ISS), limb profiles of 83.4 nm emissions are compared to predicted dayglow emission profiles from a theoretical model incorporating ground-based electron density profiles measured by the Millstone Hill radar and parameterized by a best-fit Chapman-α function. Observations and models are compared for periods of conjunction between Millstone Hill and the RAIDS fields-of-view. These RAIDS observations show distinct differences in topside morphology between two days, 15 January and 10 March 2010, closely matching the forward model morphology and demonstrating that 83.4 nm emission is sensitive to changes in the ionospheric density profile from the 340 km altitude of the ISS during solar minimum. We find no significant difference between 83.4 nm emission profiles modeled assuming a constant scale height Chapman-α best-fit to the ISR measurements and those assuming varying scale height.
Nightsat is a concept for a satellite system capable of global observation of the location, extent and brightness of night‐time lights at a spatial resolution suitable for the delineation of primary features within human settlements. Based on requirements from several fields of scientific inquiry, Nightsat should be capable of producing a complete cloud‐free global map of lights on an annual basis. We have used a combination of high‐resolution field spectra of outdoor lighting, moderate resolution colour photography of cities at night from the International Space Station, and high‐resolution airborne camera imagery acquired at night to define a range of spatial, spectral, and detection limit options for a future Nightsat mission. The primary findings of our study are that Nightsat should collect data from a near‐synchronous orbit in the early evening with 50 to 100 m spatial resolution and have detection limits of 2.5E−8 Watts cm−2sr−1µm−1 or better. Although panchromatic low‐light imaging data would be useful, multispectral low‐light imaging data would provide valuable information on the type or character of lighting; potentially stronger predictors of variables such as ambient population density and economic activity; and valuable information to predict response of other species to artificial night lighting. The Nightsat mission concept is unique in its focus on observing a human activity, in contrast to traditional Earth observing systems that focus on natural systems.
Overview and sample applications of SMILES and Odin-SMR retrievals of upper tropospheric humidity and cloud ice mass
Retrievals of cloud ice mass and humidity from the Superconducting Submillimeter-Wave Limb-Emission Sounder (SMILES) and the Odin-SMR (Sub-Millimetre Radiometer) limb sounder are presented and example applications of the data are given. SMILES data give an unprecedented view of the diurnal variation of cloud ice mass. Mean regional diurnal cycles are reported and compared to some global climate models. Some improvements in the models regarding diurnal timing and relative amplitude were noted, but the models' mean ice mass around 250 hPa is still low compared to the observations. The influence of the ENSO (El Niño–Southern Oscillation) state on the upper troposphere is demonstrated using 12 years of Odin-SMR data. The same retrieval scheme is applied for both sensors, and gives low systematic differences between the two data sets. A special feature of this Bayesian retrieval scheme, of Monte Carlo integration type, is that values are produced for all measurements but for some atmospheric states retrieved values only reflect a priori assumptions. However, this "all-weather" capability allows a direct statistical comparison to model data, in contrast to many other satellite data sets. Another strength of the retrievals is the detailed treatment of "beam filling" that otherwise would cause large systematic biases for these passive cloud ice mass retrievals. The main retrieval inputs are spectra around 635/525 GHz from tangent altitudes below 8/9 km for SMILES/Odin-SMR, respectively. For both sensors, the data cover the upper troposphere between 30° S and 30° N. Humidity is reported as both relative humidity and volume mixing ratio. The vertical coverage of SMILES is restricted to a single layer, while Odin-SMR gives some profiling capability between 300 and 150 hPa. Ice mass is given as the partial ice water path above 260 hPa, but for Odin-SMR ice water content, estimates are also provided. Besides a smaller contrast between most dry and wet cases, the agreement with Aura MLS (Microwave Limb Sounder) humidity data is good. In terms of tropical mean humidity, all three data sets agree within 3.5 %RHi. Mean ice mass is about a factor of 2 lower compared to CloudSat. This deviation is caused by the fact that different particle size distributions are assumed, combined with saturation and a priori influences in the SMILES and Odin-SMR data.