An Active Microwave Limb Sounder for Profiling Water Vapor, Ozone, Temperature, Geopotential, Clouds, Isotopes and Stratospheric Winds

Kursinski, E. R.; Feng, D.; Flittner, D. E.; Hajj, G. A.; Herman, Benjamin M.; Romberg, F. W.; Syndergaard, Stig; Ward, D.; Yunck, T. P.

doi:10.1007/978-3-662-09041-1_17

Cited by 13 publications

(20 citation statements)

References 13 publications

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“…The accuracy requirements by Larsen et al [2009] specify to meet the humidity requirements globally; in subglobal regions, especially dry ones where such a specification would not be sensible, they are not required to be met. Evidently, in line with Kursinski et al [2002, 2004, 2009] and Herman et al [2004], a 22 + 183 GHz design is clearly preferable. However, also the (least cost) 22 GHz design following the ESA [2004a, 2004b] and the recent ACCURATE concept (in least cost demonstration version) [ Kirchengast et al , 2010] reaches sufficiently up in absorption sensitivity, to 10 to 12 km, in order to ensure full sensitivity coverage of the heights with temperature‐humidity ambiguity in GRO refractivity so that the LMO data enable separate retrieval of temperature and humidity beyond the GRO capacity.…”

Section: Analysis Results and Discussionmentioning

confidence: 93%

“…The two differential channels of the 22 GHz Case provide adequate sensitivity up to about 12 to 13 km only (and less if the upper troposphere is drier such as typically at high latitudes). As introduced by Kursinski et al [2002, 2004] and Herman et al [2004] based on more simplified climatological simulations, the channels near 183 GHz are thus needed for extending LMO water vapor sounding across the tropopause into the lower stratosphere. The absolute transmissions are shown as a backdrop to indicate, as a link from the top to the middle panels of Figure 6, that the background attenuation consumes additional dynamic range.…”

Section: Analysis Results and Discussionmentioning

confidence: 99%

“…The microwave occultation technique using intersatellite centimeter‐ and millimeter‐wave signals between low Earth orbit (LEO) satellites [ Kursinski et al 2002, 2004; Herman et al , 2004; Kirchengast and Hoeg , 2004; Gorbunov and Kirchengast , 2005, 2007], termed LMO hereafter, enables us to jointly retrieve atmospheric profiles of temperature and humidity without auxiliary background information, in addition to profiles of refractivity, pressure, and geopotential height. LMO thus allows retrieval of all fundamental thermodynamic state variables (pressure, temperature, and humidity), as a function of height, and with added dedicated signals also other variables, in particular ozone [ Herman et al , 2004].…”

Section: Introductionmentioning

confidence: 99%

“…It then took about 3 decades, and the intermediate advent of GRO as of the late 1980s, until the first LMO concepts with GRO‐type geometry (i.e., with fast near‐vertical scanning via transmitter and receiver satellite motion) had been proposed. These were described by Yunck et al [2000], Kursinski et al [2002, 2004], and Herman et al [2004] for U.S.‐led (NASA) concepts and by Kirchengast and Hoeg [2004] for European‐led (European Space Agency, ESA) concepts.…”

Section: Introductionmentioning

confidence: 99%

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Thermodynamic state retrieval from microwave occultation data and performance analysis based on end-to-end simulations

et al. 2011

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Microwave occultation using centimeter‐ and millimeter‐wave signals between low Earth orbit (LEO) satellites (LEO microwave occultation, LMO) is an advancement of GPS radio occultation (GRO) exploiting in addition to refraction also absorption of signals. Beyond the successful GRO refractivity profiling capability, which leaves a temperature‐humidity ambiguity in the troposphere where moisture cannot be neglected, LMO enables joint retrieval of pressure, temperature, and humidity profiles without auxiliary background information. Here we focus on the upper troposphere/lower stratosphere and advance the LMO method in two ways: (1) we introduce a new retrieval algorithm for processing LMO excess phase and amplitude data from multiple frequencies, complementing existing GRO retrieval algorithms, and (2) we employ the algorithm in an ensemble‐based end‐to‐end performance analysis and assess the accuracy of pressure, temperature, and humidity profiles retrieved from the LMO data. The end‐to‐end simulations were carried out under quasi‐realistic conditions for a day of LEO‐LEO occultation events, based on a high‐resolution atmospheric analysis of the European Centre for Medium‐Range Weather Forecasts (ECMWF) and accounting for scintillation noise from turbulence and instrumental errors. The new algorithm was found robust, fast, and versatile to adequately process LMO data under all conditions from dry and clear to moist and cloudy air as contained in the ECMWF analysis. The retrieved pressure, temperature, and humidity profiles were generally found unbiased and within target accuracy requirements, set by scientific objectives of atmosphere and climate research going to be supported by the data, of <0.2% (pressure), <0.5 K (temperature), and <10% (humidity). Extending a “minimum” LMO design with three frequencies near 22 GHz with two added frequencies near 183 GHz favorably provides humidity retrieval into the lower stratosphere but already the “minimum” design resolves the temperature‐humidity ambiguity of GRO in the upper troposphere (frequencies <15 GHz might extend this into the lower troposphere). The results are encouraging for future LMO implementation, both stand‐alone and combined with novel LEO‐LEO infrared laser occultation.

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Section: Analysis Results and Discussionmentioning

confidence: 93%

Section: Analysis Results and Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Thermodynamic state retrieval from microwave occultation data and performance analysis based on end-to-end simulations

et al. 2011

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“…More details on this technique, its capabilities and the quality of retrieval results can be found in Feng et al (2000); Herman et al (2004); Kursinski et al (2002Kursinski et al ( , 2004; Kirchengast and Høeg (2004); Kirchengast (2005, 2007); Kursinski et al (2009) ;Schweitzer et al (2011). A closely related occultation method is the GNSS-LEO radio occultation (GRO), which uses L-band signals from the US Global Positioning System (GPS) system.…”

Section: Introductionmentioning

confidence: 99%

Atmospheric influences on infrared-laser signals used for occultation measurements between Low Earth Orbit satellites

2011

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Abstract. LEO-LEO infrared-laser occultation (LIO) is a new occultation technique between Low Earth Orbit (LEO)satellites, which applies signals in the short wave infrared spectral range (SWIR) within 2 µm to 2.5 µm. It is part of the LEO-LEO microwave and infrared-laser occultation (LMIO) method that enables to retrieve thermodynamic profiles (pressure, temperature, humidity) and altitude levels from microwave signals and profiles of greenhouse gases and further variables such as line-of-sight wind speed from simultaneously measured LIO signals. Due to the novelty of the LMIO method, detailed knowledge of atmospheric influences on LIO signals and of their suitability for accurate trace species retrieval did not yet exist. Here we discuss these influences, assessing effects from refraction, trace species absorption, aerosol extinction and Rayleigh scattering in detail, and addressing clouds, turbulence, wind, scattered solar radiation and terrestrial thermal radiation as well. We show that the influence of refractive defocusing, foreign species absorption, aerosols and turbulence is observable, but can be rendered small to negligible by use of the differential transmission principle with a close frequency spacing of LIO absorption and reference signals within 0.5 %. The influences of Rayleigh scattering and terrestrial thermal radiation are found negligible. Cloud-scattered solar radiation can be observable under bright-day conditions, but this influence can be made negligible by a close time spacing (within 5 ms) of interleaved laser-pulse and background signals. Cloud extinction loss generally blocks SWIR signals, except very thin or sub-visible cirrus clouds, which can be addressed by retrieving a cloud layering profile and exploiting it in the trace species retrieval. Wind can have a small influence on the trace species absorption, which can be made negligible by using a simultaneously retrieved or a moderately accurate

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An Abel transform for deriving line‐of‐sight wind profiles from LEO‐LEO infrared laser occultation measurements

Syndergaard

Kirchengast

2016

JGR Atmospheres

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We have developed a formula for the retrieval of the line‐of‐sight (l.o.s.) wind speed from future low Earth orbit (LEO) satellite‐to‐satellite infrared laser occultation measurements. The formula involves an Abelian integral transform akin to the Abel transform widely used for deriving refractive index from bending angle in Global Navigation Satellite System radio occultation measurements. Besides the Abelian integral transform, the formula is derived from a truncated series expansion of the volume absorption coefficient as a function of frequency and includes a simple absorption‐line‐asymmetry correction term. A first‐order formulation (referred to as the standard formula) is complemented by higher‐order terms that can be used for high‐accuracy computations. Under the assumptions of spherical symmetry and perfect knowledge of spectroscopy, the residual l.o.s. wind error from using the standard formula rather than the high‐accuracy formula is assessed to be small compared to that anticipated from measurement errors in a real experiment. Applying the new formula just in standard form to future infrared laser transmission profiles would therefore enable the retrieval of l.o.s. stratospheric wind profiles with an accuracy limited mainly by measurement errors, residual spectroscopic errors, and deviations from spherical symmetry.

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An Active Microwave Limb Sounder for Profiling Water Vapor, Ozone, Temperature, Geopotential, Clouds, Isotopes and Stratospheric Winds

Cited by 13 publications

References 13 publications

Thermodynamic state retrieval from microwave occultation data and performance analysis based on end-to-end simulations

Thermodynamic state retrieval from microwave occultation data and performance analysis based on end-to-end simulations

Atmospheric influences on infrared-laser signals used for occultation measurements between Low Earth Orbit satellites

An Abel transform for deriving line‐of‐sight wind profiles from LEO‐LEO infrared laser occultation measurements

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