Reactive nitrogen species (NOy) are involved in the formation of secondary pollutants, thus following their interconversions is crucial for understanding their impact on air quality. While nitric oxide (NO) and nitrogen dioxide (NO2) are important contributors to total NOy, further constituents such as the nitrate radical (NO3) and dinitrogen pentoxide (N2O5), formed from NO2 oxidation, are key intermediates in nocturnal oxidation processes. Even though NO3 and N2O5 affect the NOy budget in the following day, their role is poorly constrained in isolated measurements. We present the “NOyBOx”, a new instrumental framework combining measurements of NO, NO2 and NOy from commercial analyzers with a custom-built incoherent broadband cavity-enhanced absorption spectrometer (IBBCEAS) that measures NO3 directly and N2O5 via a thermal dissociation inlet (TDI) and channel differencing. We describe the design of the IBBCEAS subsystem, characterize the TDI, cavity optics, transmission losses, and, using a synthetic spectra simulation approach, the bias of ambient NO2 and water vapor on our concentration retrieval procedure. Under optimal laboratory conditions we find a limit of detection (LOD) of 1.5 and 2.2 pptv (1σ Allan deviation, 15 s) for NO3 and N2O5, respectively. Under field conditions, interference by water vapor and NO2 worsens these LODs to 3.1 pptv with a total measurement uncertainty (TMU) of 12 % for NO3, and to 4.4 pptv with a mean TMU of 21 % for N2O5. Exemplary results from its first deployment during a field campaign in a temperate forest atop a 40 m tall tower are discussed.
Simultaneous profiling of atmospheric wind and temperature is essential for investigating atmospheric dynamics and wave–mean flow interactions. However, conventional molecular Rayleigh lidar techniques generally retrieve temperature and wind using different measurement principles, such as hydrostatic integration for temperature retrieval and double-edge discrimination for wind measurement. Direct retrieval of both quantities from a single spectrally resolved molecular backscatter signal remains less commonly demonstrated, particularly in the troposphere and lower stratosphere. To explore this approach, we developed a high-spectral-resolution lidar (HSRL) receiver based on a Fizeau interferometer and a 32-channel linear photomultiplier-tube array. The receiver spatially resolves the Rayleigh–Brillouin (RB) spectrum across the detector array, enabling the Doppler shift and thermally induced spectral broadening to be determined from the same measured spectrum for joint wind and temperature retrieval without frequency scanning. Numerical simulations were first performed to optimize the spectral sampling characteristics of the receiver, identifying the 32-channel configuration as a favorable compromise between spectral resolution and signal-to-noise ratio (SNR) over the 2 to 20 km altitude range. Wind profiles were retrieved from 2 to 20 km with a temporal resolution of 10 min, while temperature profiles were retrieved from 5.3 to 20 km with a temporal resolution of 5 min. Temperature retrieval was performed where the Mie scattering signal fraction was below approximately 8 %, which corresponded to a lower retrieval altitude of about 5.3 km under the observed atmospheric conditions. The vertical resolutions were 60 m below 10 km and 300 m above 10 km. Compared with radiosonde measurements, the retrieved temperatures showed mean absolute temperature differences of 1.19 K at 5.3–10 km and 2.10 K above 10 km. Below 5.3 km, wind retrieval used model temperature as an auxiliary input, yielding mean absolute differences of 2.34 and 2.50 m s−1 for the zonal and meridional wind components, respectively. In the fully lidar-based joint-retrieval region above 5.3 km, the corresponding wind differences were 1.84 and 2.97 m s−1 at 5.3–10 km and 3.02 and 3.08 m s−1 above 10 km. These results demonstrate that the proposed scan-free multichannel Fizeau-interferometer HSRL enables reliable temperature profiling from the middle troposphere to the lower stratosphere and extends wind measurements into the lower troposphere, while offering a compact spectral architecture with potential for future airborne and spaceborne Doppler lidar applications.
This paper describes a physically-based algorithm for estimating the mass-weighted raindrop diameter (Dm) and the corresponding Doppler velocities (VD) which are the radar reflectivity-weighted terminal velocities of the raindrops. The algorithm exploits the attenuation-corrected radar reflectivity (Ze) and the specific attenuation (k) observed by Ku- and W-band space-borne Doppler radars and estimate Dm assuming a specified drop size distribution DSD. The estimated Dm were examined using a Monte Carlo model which evolves DSDs by coalescence and breakup in a convective rain as well as measured data with a disdrometer. A detailed error analysis is also presented in the retrieved Dm arising from the measurement errors. While discrepancies between the assumed DSDs (DSDLUT) and actual DSDs introduce errors in the estimated values, the errors were generally small for small Dm values. The uncertainties related to the variability of DSD were reduced by selecting an appropriate DSDLUT using the dependence of Z–R relationship (R: rain rate) on Dm. Since k is the DSD-dependent value in the W-band, the influence of the DSD can be partially mitigated but is limited. Utilizing parameters representing the shape of DSD by k, Ze and VD offer the potential to reduce the DSD-related errors furthermore.
Despite containing up to half of the Earth's thermal emission to space, the far-infrared spectral region (FIR, defined here as 100–667 cm−1 or 15–100 µm) has seldom been observed from satellites. This has contributed to substantial uncertainties in the spectroscopy of water vapour, radiative properties of clouds, and surface spectral emissivity; these in turn limit confidence in modelled FIR energy flows. With the advent of the Polar Radiant Energy in the Far-InfraRed Experiment (PREFIRE), a step is taken towards new, systematic, spectral observations of the Earth in the FIR. Launched in 2024, the two PREFIRE CubeSats offer a new perspective of Earth's outgoing longwave energy with moderate spectral resolution. However, the observational uncertainty budget requires further consolidation. In this study we assess the accuracy of PREFIRE spectral measurements through a “ground-to-space” closure experiment. Using zenith-viewing observations from the ground-based Far INfrarEd Spectrometer for Surface Emissivity (FINESSE) recorded during the WHAFFFERS campaign, we constrain atmospheric data taken from in situ sensors. With this optimised profile data we simulate PREFIRE-observed radiances for an overflight of our field site in eastern Canada. Simulations of the FINESSE radiances are in very good agreement with observations, while those from PREFIRE indicate some bias beyond the calculated uncertainties. We find that atmospheric water vapour specification, uncertain surface properties, and instrument noise dominate the uncertainties. Based on these findings, we highlight proposed techniques for closure experiments using terrestrial and satellite instruments alike. Such experiments will provide a ground-truth for validation of future FIR satellite missions.
Ammonia (NH3) is an important atmospheric pollutant affecting air quality, ecosystems, and climate. Hyperspectral thermal infrared sounders such as IASI and CrIS combine broad coverage with high spectral sensitivity, but their kilometer-scale footprints limit facility-scale source attribution. Here we test whether high-spatial-resolution multispectral thermal infrared imaging can detect NH3 plumes at facility scale. We develop a physically based retrieval framework for the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER), combining radiative transfer calculations with lookup table (LUT) inversion. The method exploits the differential sensitivity of ASTER bands 13 and 14 to NH3 absorption in the ν2 band near 930–970 cm−1, retrieving NH3 column enhancements at 90 m spatial resolution with surface emissivity prescribed from a long-term ASTER emissivity climatology. NH3 absorption remains measurable after convolution with the ASTER spectral response functions, but retrieval performance depends strongly on thermal contrast between the surface and the NH3-bearing layer. The retrieval is applied to three industrial NH3 point sources: Khor Al Zubair, Tolyatti, and Piesteritz. Khor Al Zubair yields repeated source-connected plumes under favorable arid conditions; Tolyatti and Piesteritz show that detection is also possible in more heterogeneous environments. Source rates derived with the Integrated Mass Enhancement method are instantaneous estimates for individual detected scenes rather than annual mean emissions, with detected-scene medians of 56.6, 27.1, and 6.0 kt yr−1 at the three sites. These agree in order of magnitude with published satellite and airborne estimates, and at Khor Al Zubair to within a few per cent of the CrIS estimate once the differing NH3 lifetime assumptions are placed on a common basis. The reported uncertainties are dominated by the assumed effective wind speed and are not a complete error budget. Multispectral TIR imagers can therefore resolve NH3 plume structure and source location, complementing coarse-resolution sounders. Sampling is limited by revisit frequency, cloud cover and thermal contrast, so the approach suits episodic mapping of large, persistent sources and retrospective analysis of the ASTER archive.
