Long-range robust multifilament arrays from terawatt femtosecond beam

Multiple filament’s formation on a long atmospheric path was studied for an amplitude modulation of the terawatt femtosecond beam with the four and six hole masks. Filaments appeared at the distance that is determined by the Fresnel lens formed by a hole, not by the self focusing theory for the unrestricted (Gaussian like) beam. This lens focuses 1/3 of the energy passing through the hole to the beam spot ≈1 mm in diameter. The robust multifilament array 10–15 m in length was observed if the energy per hole was ≈1-1.5 mJ (pulse duration 50 fs), while each hole produces bundle of a few filaments at higher energies.

Refining Atmosphere Profiles for Aerial Target Detection Models

Atmospheric path radiance in the infrared is an extremely important quantity in calculating system performance in certain infrared detection systems. For infrared search and track (IRST) system performance calculations, the path radiance competes with the target for precious detector well electrons. In addition, the radiance differential between the target and the path radiance defines the signal level that must be detected. Long-range, high-performance, offensive IRST system design depends on accurate path radiance predictions. In addition, in new applications such as drone detection where a dim unresolved target is embedded into a path radiance background, sensor design and performance are highly dependent on atmospheric path radiance. Being able to predict the performance of these systems under particular weather conditions and locations has long been an important topic. MODTRAN has been a critical tool in the analysis of systems and prediction of electro-optical system performance. The authors have used MODTRAN over many years for an average system performance using the typical “pull-down” conditions in the software. This article considers the level of refinement required for a custom MODTRAN atmosphere profile to satisfactorily model an infrared camera’s performance for a specific geographic location, date, and time. The average difference between a measured sky brightness temperature and a MODTRAN predicted value is less than 0.5 °C with sufficient atmosphere profile updates. The agreement between experimental results and MODTRAN predictions indicates the effectiveness of including updated atmospheric composition, radiosonde, and air quality data from readily available Internet sources to generate custom atmosphere profiles.

Numerical-analytical method for calculating the refraction of radio waves in a chaotic upper atmosphere

An operational method is proposed for calculating the refraction of decameter radio waves in a randomly-inhomogeneous upper atmosphere. The method is based on the numerical-analytical solution of stochastic equations of geometric optics. An integral expression is obtained for the dispersion of the refraction angle of a radio wave on the atmospheric path using the approximation of the perturbation method. For a quick calculation of the statistical moment of the refraction angle, the integral expression is reduced to an ordinary first-order differential equation. The joint numerical solution of the unperturbed ray equations and the equations for the statistical moment allows doing an operational estimate of beam width of radio waves arriving at the observation point. The results of numerical calculations of the standard deviations of the refraction angles of radio waves on paths of various lengths are presented.

Improving atmospheric path attenuation estimates for radio propagation applications by microwave radiometric profiling

Ground-based microwave radiometer (MWR) observations of downwelling brightness temperature (TB) are commonly used to estimate atmospheric attenuation at relative transparent channels for radio propagation and telecommunication purposes. The atmospheric attenuation is derived from TB by inverting the radiative transfer equation with a priori knowledge of the mean radiating temperature (TMR). TMR is usually estimated by either time-variant site climatology (e.g., monthly average computed from atmospheric thermodynamical profiles) or condition-variant estimation from surface meteorological sensors. However, information on TMR may also be extracted directly from MWR measurements at channels other than those used to estimate atmospheric attenuation. This paper proposes a novel approach to estimate TMR in clear and cloudy sky from independent MWR profiler measurements. A linear regression algorithm is trained with a simulated dataset obtained by processing 1 year of radiosonde observations of atmospheric thermodynamic profiles. The algorithm is trained to estimate TMR at K- and V–W-band frequencies (22–31 and 72–82 GHz, respectively) from independent MWR observations at the V band (54–58 GHz). The retrieval coefficients are then applied to a 1-year dataset of real V-band observations, and the estimated TMR at the K and V–W band is compared with estimates from nearly colocated and simultaneous radiosondes. The proposed method provides TMR estimates in better agreement with radiosondes than a traditional method, with 32 %–38 % improvement depending on frequency. This maps into an expected improvement in atmospheric attenuation of 10 %–20 % for K-band channels and ∼30 % for V–W-band channels.

Improving atmospheric path-attenuation estimates for radiopropagation applications by microwave radiometric profiling

Ground-based microwave radiometer (MWR) observations of downwelling brightness temperature (TB) are commonly used to estimate the atmospheric attenuation at relative transparent channels for radiopropagation and telecommunication purposes. The atmospheric attenuation is derived from TB by inverting the radiative transfer equation with a priori knowledge of the mean radiating temperature (TMR). TMR is usually estimated by either time-variant site climatology (e.g., monthly average computed from atmospheric thermodynamical profiles) or condition-variant estimation from surface meteorological sensors. However, information on TMR may also be extracted directly from MWR measurements at other channels than those used to estimate atmospheric attenuation. This paper proposes a novel approach to estimate TMR in clear and cloudy sky from independent MWR profiler measurements. A linear regression algorithm is trained with a simulated dataset obtained by processing one year of radiosonde observations of atmospheric thermodynamic profiles. The algorithm is trained to estimate TMR at K-, and V/W-band frequencies (22–31 and 72–82 GHz, respectively) from independent MWR observations at V-band (54–58 GHz). The retrieval coefficients are then applied to a one-year dataset of real V-band observations, and the estimated TMR at K- and V/W-band are compared with estimates from nearly collocated and simultaneous radiosondes. The proposed method provides TMR estimates in better agreement with radiosondes than a traditional method, with 32–38 % improvement depending on frequency. This maps into an expected improvement in atmospheric attenuation of 10–20 % for K-band and ~ 30 % for V/W-band channels.

The use of the 1.27 µm O₂ absorption band for greenhouse gas monitoring from space and application to MicroCarb

Monitoring CO2 from space is essential to characterize the spatiotemporal distribution of this major greenhouse gas and quantify its sources and sinks. The mixing ratio of CO2 to dry air can be derived from the CO2∕O2 column ratio. The O2 column is usually derived from its absorption signature on the solar reflected spectra over the O2 A band (e.g. Orbiting Carbon Observatory-2 (OCO-2), Thermal And Near infrared Sensor for carbon Observation (TANSO)/Greenhouse Gases Observing Satellite (GOSAT), TanSat). As a result of atmospheric scattering, the atmospheric path length varies with the aerosols' load, their vertical distribution, and their optical properties. The spectral distance between the O2 A band (0.76 µm) and the CO2 absorption band (1.6 µm) results in significant uncertainties due to the varying spectral properties of the aerosols over the globe. There is another O2 absorption band at 1.27 µm with weaker lines than in the A band. As the wavelength is much closer to the CO2 and CH4 bands, there is less uncertainty when using it as a proxy of the atmospheric path length to the CO2 and CH4 bands. This O2 band is used by the Total Carbon Column Observing Network (TCCON) implemented for the validation of space-based greenhouse gas (GHG) observations. However, this absorption band is contaminated by the spontaneous emission of the excited molecule O2*, which is produced by the photo-dissociation of O3 molecules in the stratosphere and mesosphere. From a satellite looking nadir, this emission has a similar shape to the absorption signal that is used. In the frame of the CNES (Centre National d'Études Spatiales – the French National Centre for Space Studies) MicroCarb project, scientific studies have been performed in 2016–2018 to explore the problems associated with this O2* airglow contamination and methods to correct it. A theoretical synthetic spectrum of the emission was derived from an approach based on A21 Einstein coefficient information contained in the line-by-line high-resolution transmission molecular absorption (HITRAN) 2016 database. The shape of our synthetic spectrum is validated when compared to O2* airglow spectra observed by the Scanning Imaging Absorption Spectrometer for Atmospheric Chartography (SCIAMACHY)/Envisat in limb viewing. We have designed an inversion scheme of SCIAMACHY limb-viewing spectra, allowing to determine the vertical distribution of the volume emission rate (VER) of the O2* airglow. The VER profiles and corresponding integrated nadir intensities were both compared to a model of the emission based on the Reactive Processes Ruling the Ozone Budget in the Stratosphere (REPROBUS) chemical transport model. The airglow intensities depend mostly on the solar zenith angle (both in model and data), and the model underestimates the observed emission by ∼15 %. This is confirmed with SCIAMACHY nadir-viewing measurements over the oceans: in such conditions, we have disentangled and retrieved the nadir O2* emission in spite of the moderate spectral resolving power (∼860) and found that the nadir SCIAMACHY intensities are mostly dictated by solar zenith angle (SZA) and are larger than the model intensities by a factor of ∼1.13. At a fixed SZA, the model airglow intensities show very little horizontal structure, in spite of ozone variations. It is shown that with the MicroCarb spectral resolution power (25 000) and signal-to-noise ratio (SNR), the contribution of the O2* emission at 1.27 µm to the observed spectral radiance in nadir viewing may be disentangled from the lower atmosphere/ground absorption signature with a great accuracy. Indeed, simulations with 4ARCTIC radiative transfer inversion tool have shown that the CO2 mixing ratio may be retrieved with the accuracy required for quantifying the CO2 natural sources and sinks (pressure-level error ≤1 hPa; XCO2 accuracy better than 0.4 ppmv) with the O2 1.27 µm band only as the air proxy (without the A band). As a result of these studies (at an intermediate phase), it was decided to include this band (B4) in the MicroCarb design, while keeping the O2 A band for reference (B1). Our approach is consistent with the approach of Sun et al. (2018), who also analysed the potential of the O2 1.27 µm band and concluded favourably for GHG monitoring from space. We advocate for the inclusion of this O2 band on other GHG monitoring future space missions, such as GOSAT-3 and EU/European Space Agency (ESA) CO2-M missions, for a better GHG retrieval.