Millimeter-wave Radiometer Research Articles

Assessing synergistic radar and radiometer capability in retrieving ice cloud microphysics based on hybrid Bayesian algorithms

Abstract. The 2017 National Academy of Sciences Decadal Survey highlighted several high-priority objectives to be pursued in the decadal timeframe, and the next-generation Cloud, Convection and Precipitation (CCP) observing system is thereby contemplated. In this study, we develop a suite of hybrid Bayesian algorithms to evaluate two CCP remote sensor candidates including a W-band cloud radar and a (sub)millimeter-wave radiometer with channels in the 118–880 GHz frequency range for capability in constraining ice cloud microphysical quantities. The algorithms address active-only, passive-only, and synergistic active–passive retrievals. The hybrid Bayesian algorithms combine the Bayesian Monte Carlo integration and optimization process to retrieve quantities with uncertainty estimates. The radar-only retrievals employ the optimal estimation methodology, while the radiometer-involved retrievals employ ensemble approaches to maximize the posterior probability density function. A priori information is obtained from the Tropical Composition, Cloud and Climate Coupling (TC4) in situ data and CloudSat radar observations. End-to-end simulation experiments are conducted to evaluate the retrieval accuracies by comparing the retrieved parameters with known values. The experiment results suggest that the radiometer measurements possess high sensitivity to ice cloud particles with large water content. The radar-only retrievals demonstrate capability in reproducing ice water content profiles, but the performance in retrieving number concentration is poor. The synergistic observations enable improved pixel-level retrieval accuracies, and the improvements in ice water path retrievals are significant. The proposed retrieval algorithms could serve as alternative methods for exploring the synergistic active and passive concept, and the algorithm framework could be extended to the inclusion of other remote sensors to further assess the CCP observing system in future studies.

Cross Validation of TEMPEST-D and RainCube Observations Over Precipitation Systems

This paper presents cross-validation of nearly simultaneous observations between the Temporal Experiment for Storms and Tropical Systems<b>&#x00A0;-</b>Demonstration<b>&#x00A0;(</b>TEMPEST-D) and RainCube (Radar in a CubeSat) satellite microwave sensors over precipitation systems. RainCube senses the atmosphere using a Ka-band nadir-pointing radar, and TEMPEST-D senses using multi-frequency millimeter-wave radiometers. Nine precipitation systems were used in this cross-validation study. Occurring over nearly a two-year period, these storms were scattered over many regions of the world from the Tropics to the mid-latitudes. A shift correction algorithm was developed to remove the uncertainty between the two sensors&#x0027; observations due to the time difference and the storm motion between the two instrument overpasses. Correlation coefficients were calculated between self-normalized, inverted RainCube cumulative reflectivity and self-normalized TEMPEST-D brightness temperatures. As expected, these correlation coefficients are consistently higher for the four TEMPEST-D high-frequency channels than for the single low-frequency channel. The shift correction algorithm improved the average correlation coefficient by 19&#x0025; for the four high-frequency channels and by 58&#x0025; for the single low-frequency channel. The average correlation coefficient after shift correction is 0.76 for TEMPEST-D&#x0027;s four high-frequency channels and 0.54 for the single low-frequency channel. The comparisons demonstrated high consistency between the TEMPEST-D and RainCube observations, even though the two microwave sensors&#x0027; fundamental physics is different; one is passive, and the other is active.

Derived Observations From Frequently Sampled Microwave Measurements of Precipitation—Part III: Convoys of mm-Wave Radiometers

This is the third of three papers that quantify the high added value of frequent satellite microwave observations of the atmosphere (with a “refresh” time on the order of one minute) to capture the dynamics of weather systems. Recent advances in small-satellite and microwave miniaturization, such as the “Temporal Experiment for Storms and Tropical systems” (TempEST) millimeter-wave radiometer developed at the Jet Propulsion Laboratory, are paving the way for the design of convoys of spaceborne radars that can directly observe the evolution of severe weather at very fine temporal scales. The analyses presented here are to establish the relation between passive microwave observations and their change in time and the underlying cloud variables and processes, and to evaluate the sensitivity to the different physical and instrument parameters. In this third part, simulations are used to demonstrate and quantify the direct sensitivity of a time sequence of mm-wave radiances to the vertical structure of the vertical updrafts in convective storms. It is demonstrated that the brightness temperatures from a pair of low-Earth-orbit radiometers maintaining a separation of one or two minutes can indeed be used to retrieve the column-maximum magnitude of the vertical wind as well as the height of the maximum. While such passive retrievals do not provide the vertical detail that a pair of radars would produce, the radiometers have a vast swath and therefore enable the observation of an entire storm. The application is therefore quite different from the case of a convoy of radars: rather than compiling radar statistics over multiple years, the radiometer-convoy measurements can be used to analyze every storm that is observed.

Calibration of the space-borne microwave humidity sounder based on real-time thermal emission from lunar surface

Calibration is a key issue for quantitative application of meteorological satellite data. The complex space environment may cause many uncertainties in data calibration. A highly stable and reliable calibrator in flight is needed. Because the Moon has no atmosphere and no environmental variation, the physical and chemical properties of its surface are stable in the long term. The Moon might be an ideal candidate for in-flight thermal calibration. In advanced satellite-borne microwave remote sensing such as NOAA-18, the deep space view (DSV) of the microwave humidity sounder (MHS) has viewed the Moon many times every year. Using the thermal-physical properties of the lunar regolith derived from the Diviner infrared (IR) brightness temperature (TB) data, we solve the one-dimensional heat conduction equation to obtain the temperature profile of the near side of the lunar regolith medium. The loss tangents of the regolith medium are retrieved from microwave TB data of the Chinese satellite Chang’e-2. The integrated radiative transfer equation is used to simulate the weighted disk-average TB of the lunar surface for the MHS channels at 89, 157, and 183 GHz for the year 2011. The Moon is taken as an extended circular target. The simulated TBs are used to correct the full width at half maximum (FWHM) fitted with the MHS counts. We analyze the influences of the distance between the satellite and the Moon, the lunar phase angle, and the FWHM of the radiometer on the inverted FWHM. The corrected TB data are compared with the simulation. This paper presents a new method for thermal calibration of spaceborne in-flight microwave and millimeter-wave radiometers with the weighted disk-average TB of the lunar surface.

TEMPEST-D Radiometer: Instrument Description and Prelaunch Calibration

The Temporal Experiment for Storms and Tropical Systems Technology Demonstration (TEMPEST-D) instrument is a five-frequency millimeter-wave radiometer operating from 87 to 181 GHz. The cross-track scanning radiometer has been operating on a 6U CubeSat in low Earth orbit since September 5, 2018. The direct-detection architecture of the radiometer reduces its mass and power consumption by eliminating the need for a local oscillator and mixer, also reducing system complexity. The instrument includes a scanning reflector and ambient calibration target. The reflector rotates continuously to scan the antenna beams in the cross-track direction, first across the blackbody calibration target, then toward the Earth over the full range of incidence angles, and finally to cosmic microwave background radiation at 2.73 K. This enables precision end-to-end calibration of the millimeter-wave receivers during every 2-s scan period. The TEMPEST-D millimeter-wave radiometers are based on 35-nm indium phosphide (InP) high-electron-mobility transistor (HEMT) low-noise amplifiers. This article describes the instrument and its characterization prior to launch.

Assessing the Spaceborne 183.31-GHz Radiometric Channel Geolocation Using High-Altitude Lakes, Ice Shelves, and SAR Imagery

The goal of this work is to perform the geolocation error assessment of the channel imagery at 183.31 GHz of the Special Sensor Microwave Imager/Sounder (SSMIS). The frequency around 183.31 GHz still represents the highest channel frequency of current spaceborne microwave and millimeter-wave radiometers. The latter will be extended to frequencies up to 664 GHz, as in the case of EUMETSAT Ice Cloud Imager (ICI). This use of submillimeter observations unfortunately prevents a straightforward geolocation error assessment using landmark-based techniques. We used SSMIS data at 183.31 GHz as a submillimeter proxy to identify the most suitable targets for geolocation error validation in very dry atmospheric conditions, as suggested by radiative transfer modeling. Using a yearly SSMIS data set, three candidates’ landmark targets are selected: 1) high-altitude lakes and high-latitude bays using a coastline reference database and 2) Antarctic ice shelves using coastlines derived from Sentinel-1 Synthetic Aperture Radar (SAR) imagery. Data processing is carried out by using spatial cross correlation methods in the spatial frequency domain and performing a numerical sensitivity analysis to contour displacement. Cloud masking, based on a fuzzy-logic approach, is applied to automatically selected clear-air days. The results show that the average geolocation error is about 6.2 km for mountainous lakes and sea bays and 5.4 km for ice shelves, with a standard deviation of about 2.7 and 2.0 km, respectively. The results are in line with SSMIS previous estimates, whereas annual clear-air days are about 10% for mountainous lakes and sea bays and 18% for ice shelves.

Calibration and Validation of the TEMPEST-D CubeSat Radiometer

Temporal Experiment for Storms and Tropical Systems-Demonstration (TEMPEST-D) is a 6U CubeSat satellite with a cross-track scanning millimeter-wave radiometer measuring at five frequencies from 87 to 181 GHz. It employs a direct-detection architecture with InP HEMT monolithic microwave integrated circuit (MMIC) low-noise amplifiers and related new technologies. An end-to-end two-point external calibration is performed every 2-s rotation of the scanning mirror, based on observations of the cosmic microwave background and an internal blackbody calibration target, with three thermistors to monitor the target physical temperature. Corrections for antenna pattern effects and cross-scan biases based on prelaunch measured values were updated using data from an on-orbit calibration pitch maneuver. Validation of the observed brightness temperatures ( T <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">B</sub> ) is performed by comparing to coincident nonprecipitating ocean observations from five well-calibrated on-orbit instruments, including Global Precipitation Measurement (GPM) mission Microwave Imager (GMI) and four Microwave Humidity Sounder (MHS) sensors on board NOAA-19, MetOp-A, MetOp-B, and MetOp-C satellites. Absolute calibration accuracy is within 1 K for all channels, well within the 4-K requirement. Calibration precision, or stability over time, is within 0.6 K for all channels, also well within the 2-K requirement. The intrinsic noise of TEMPEST-D is lower than MHS, resulting in similar on-orbit noise equivalent differential temperatures (NEDTs), even though TEMPEST-D has a much shorter integration time of 5 ms as compared to 18 ms for MHS. As a result, although the TEMPEST-D radiometer is substantially smaller, lower power, and lower cost than similar current operational radiometers, it has comparable or better performance in terms of instrument noise, calibration accuracy, and calibration stability or precision.

Average Brightness Temperature of Lunar Surface for Calibration of Multichannel Millimeter-Wave Radiometer From 89 to 183 GHz and Data Validation

Calibration of satellite-borne radiometer is a key issue for quantitative remote sensing. Its accuracy depends on the stability of the calibration source. Because of no atmosphere and biological activity, the Moon surface keeps stable in the long term and may be a good candidate for thermal calibration. Observation of microwave humidity sounder (MHS) onboard the NOAA-18 made measurements of the disk-integrated brightness temperature (TB) of the Moon for the phase angle between -800 and 500. The measurement of NOAA-18 has been studied to validate the TB model of lunar surface. In this article, the near side of the Moon surface is divided into 900 subregions with a span of 60 x 60 in longitude and latitude. By solving 1-D heat conductive equation with the thermophysical parameters validated by the Diviner data of the Lunar Reconnaissance Orbiter (LRO), the temperature profiles of the regolith media in all 900 subregions are obtained. The loss tangents are inversed from the Chang'e-2 (CE-2) 37-GHz microwave TB data at noontime. Employing the fluctuation-dissipation theorem and the Wentzel-Kramer-Brillouin (WKB) approach, the microwave and millimeter-wave TBs of each subregion are simulated. Then, the weighted average TB can be disk-integrated from 900 TBs of all subregions versus the phase angle. These simulations well demonstrate diurnal TB variation and its dependence upon the frequency channels. It is found that the disk-integrated TB of the Moon in MHS channels is sensitive to the full-width at half-maximum (FWHM) of the deep space view (DSV), which is corrected in our simulation, where the Moon is now taken as an extended target, instead of a point-like object. Simulated integrated TBs are compared with the corrected MHS TB data at 89, 157, and 183 GHz. The simulated TB is well consistent with these MHS TB data at 89 and 183 GHz at various phase angles. But the maximum TB of MHS data at 157 GHz is unusually lower than that of 89 GHz. The influence of the loss tangent, emissivity, and the pointing error is analyzed. Some more careful design to observe the Moon TB and technical parameters, especially the FWHM should be well determined. Our model and numerical simulation provides a tool for TB calibration and validation.

A 60-GHz SiGe Radiometer Calibration Switch Utilizing a Coupled Avalanche Noise Source

This letter presents a novel implementation of a ${V}$ -band single-pole double-throw switch that facilitates the internal calibration of radiometers by integrating an ambient noise source and an avalanche noise source. The switch is implemented in a 0.13- $\mu \text{m}$ SiGe bipolar-CMOS (BiCMOS) process and uses a shunt topology with $\lambda $ /4 directional couplers that inject noise from the avalanche source. The avalanche source is implemented using the collector-base junction of a SiGe heterojunction bipolar transistor (HBT) and attains a measured excess noise ratio of 18.7 dB at 60 GHz. The switch achieves a midband insertion loss of 2.0 dB and an isolation of 22 dB at 60 GHz. An excess input-referred noise temperature of 620 K is added with the noise source ON. To the best of our knowledge, this is the first avalanche noise source using a diode-configured SiGe HBT and the first monolithic two-reference switch for calibrating millimeter-wave radiometers.

Microwave Radiometer Instability Due to Infrequent Calibration

We directly quantify the effect of infrequent calibration on the stability of microwave radiometer temperature measurements (where a power measurement for the unknown source is acquired at a fixed time, but calibration data are acquired at variable earlier times) with robust and nonrobust implementations of a new metric. Based on our new metric, we also determine a component of uncertainty in a single measurement due to infrequent calibration effects. We apply our metric to experimental data acquired from experimental ground-based calibration data acquired from a NASA millimeter-wave imaging radiometer and a NIST radiometer (Noise Figure Radiometer-NFRad). Based on a stochastic model for the NFRad, we determine the random uncertainty of an empirical prediction model of our stability metric by a Monte Carlo method. For comparison purposes, we also present a secondary metric that quantifies stability for the case where calibration data are acquired at a fixed time, but power measurements for the unknown source are acquired at variable later times.

Deep Learning Calibration of the High-Frequency Airborne Microwave and Millimeter-Wave Radiometer (HAMMR) Instrument

Calibration plays an important role in improving the accuracy of the microwave and millimeter-wave radiometric measurements. Several calibration techniques have been used in radiometers including external calibration targets, vicarious sources, and internal calibrators such as noise diodes or matched reference load. A new calibration technique based on deep learning has recently been developed to calibrate microwave and millimeter-wave radiometers. The deep-learning calibrator has been previously demonstrated on a computer noise-wave modeled Dicke-switching radiometer. This article applies the new deep-learning calibration technique for the calibration of the high-frequency airborne microwave and millimeter-wave radiometer (HAMMR) instrument. A deep-learning neural network model is built to calibrate the 2014 West Coast Flight Campaign antenna temperature measurements of the HAMMR. The deep-learning calibrator antenna temperature estimates are obtained from the radiometric measurements. The deep-learning calibration results are compared with the existing conventional calibration techniques used in HAMMR 2014 field campaign. The results have shown that the deep-learning calibrator is in agreement with the conventional calibration techniques. In this article, it is demonstrated that the deep-learning calibrator can be employed for calibrating the radiometers with high accuracy.

Instrument Design and Performance of the High-Frequency Airborne Microwave and Millimeter-Wave Radiometer

The high-frequency airborne microwave and millimeter-wave radiometer (HAMMR) is a cross-track scanning airborne radiometer instrument with 25 channels from 18.7 to 183.3 GHz. HAMMR includes: low-frequency microwave channels at 18.7, 23.8, and 34.0 GHz at two linear-orthogonal polarizations; high-frequency millimeter-wave channels at 90, 130 and 168 GHz; and millimeter-wave sounding channels consisting of eight channels near the 118.75 GHz oxygen absorption line for temperature profiling and eight additional channels near the 183.31 GHz water vapor absorption line for water vapor profiling. HAMMR was deployed on a twin otter aircraft for a west coast flight campaign (WCFC) from November 4–17, 2014. During the WCFC, HAMMR collected radiometric observations for more than 53.5 h under diverse atmospheric conditions, including clear sky, scattered and dense clouds, as well as over a variety of surface types, including coastal ocean areas, inland water and land. These measurements provide a comprehensive dataset to validate the instrument.

A Deep Learning Approach for Microwave and Millimeter-Wave Radiometer Calibration

Deep learning artificial neural network techniques can be applied for on-orbit calibration of microwave and millimeter-wave radiometer spaceborne instruments, including those for small satellites. The noise-wave model has been employed for noise characterization and validation of the proposed deep learning calibration technique for a synthetically generated Dicke-switching radiometer. The developed deep learning neural network radiometer calibrator produces high accuracy estimates of antenna temperatures from the measurements of radiometer output voltage and thermistor readings. Tests with noise-free and noisy samples of the developed model have shown that the proposed calibration method does not add any significant noise to the radiometer calibration. The performance of the proposed method does not degrade with increased nonlinearity for a radiometer, while nonlinearity is a challenging issue for conventional calibration techniques. The deep learning calibration model learns the radiometer noise characteristics from radiometer prelaunch measurements during thermal vacuum chamber testing. The neural network calibrator proposed in this paper has self-learning capability during the on-orbit operation of a radiometer that can be used to improve the performance of on-orbit calibration. The proposed technique is demonstrated by comparing the residual uncertainty of the deep learning calibration with the theoretical value. No numerical study is presented to compare the performance with conventional calibration techniques. The new method may be solely applied to calibrate the radiometer or applied along with conventional calibration techniques.

Analysis of a southern sub-polar short-term ozone variation event using a millimetre-wave radiometer

Abstract. Subpolar regions in the Southern Hemisphere are influenced by the Antarctic polar vortex during austral spring, which induces high and short-term ozone variability at different altitudes, mainly into the stratosphere. This variation may affect considerably the total ozone column changing the harmful UV radiation that reaches the surface. With the aim of studying ozone with a high time resolution at different altitudes in subpolar regions, a millimetre-wave radiometer (MWR) was installed at the Observatorio Atmosférico de la Patagonia Austral (OAPA), Río Gallegos, Argentina (51.6∘ S, 69.3∘ W), in 2011. This instrument provides ozone profiles with a time resolution of ∼1 h, which enables studies of short-term ozone mixing ratio variability from 25 to ∼70 km in altitude. This work presents the MWR ozone observations between October 2014 and 2015, focusing on an atypical event of the polar vortex and Antarctic ozone hole influence over Río Gallegos detected from the MWR measurements at 27 and 37 km during November of 2014. During the event, the MWR observations at both altitudes show a decrease in ozone followed by a local peak of ozone amount of the order of hours. This local recovery is observed thanks to the high time resolution of the MWR mentioned. The advected potential vorticity (APV) calculated from the MIMOSA high-resolution advection model (Modélisation Isentrope du transport Méso-échelle de l'Ozone Stratosphérique par Advection) was also analysed at two isentropic levels (levels of constant potential temperature) of 675 and 950 K (∼27 and ∼37 km of altitude, respectively) to understand and explain the dynamics at both altitudes and correlate the ozone rapid recovery with the passage of a tongue with low PV values over Río Gallegos. In addition, the MWR dataset was compared for the first time with measurements obtained from the Microwave Limb Sounder (MLS) at individual altitude levels (27, 37 and 65 km) and with the differential absorption lidar (DIAL) installed in the OAPA to analyse the correspondence between the MWR and independent instruments. The MWR–MLS comparison presents a reasonable correlation with mean bias errors of +5 %, −11 % and −7 % at 27, 37 and 65 km, respectively. The MWR–DIAL comparison at 27 km also presents good agreement, with a mean bias error of −1 %.

Development of 90 GHz Microwave Radiometer Sensor in Snow/ice Studies Over the Himalaya as Input for Disaster Monitoring

In this study, a sensor is designed based on a basic radiometer system at 18.8 GHz for ground-based testing and operations. Initially a generic radiometer will be designed in total power radiometer configuration (Phase 1) that is more appropriate for remote sensing platforms for operations in a campaign mode, such as an airborne mission. The same radiometer is proposed to be modified as a null-balancing Dicke radiometer (Phase 2) that is more suitable for long-term field operations over a range of temperatures and environmental conditions. This system is also useful for long-term propagation experiments in communication. The development of a millimeter-wave radiometer is in several hardware realization phases identified as Phases 1 and 2. The present proposal is expected to facilitate realization and utilization of microwave radiometers for space applications. The team at Jain University, Bengaluru will complement activities at ISRO in remote sensing applications through any campaigns proposed by the latter. Any future incremental development activities such as augmentation at higher frequencies as well testing newer concepts such as phased-array antenna for electronic scanning at lower frequencies, dichroic antennas at very high frequencies, etc. may be attempted based on the trends in technology/hardware.

Brightness Temperature of Lunar Surface for Calibration of Multichannel Millimeter-Wave Radiometer of Geosynchronous FY-4M

One of Chinese meteorological satellites, Feng Yun-4M (FY-4M), as one the of new generation of geosynchronous series satellites, is planning to upload multichannel millimeter-wave radiometers, e.g., from 50 to 430 GHz. Due to long-period stability and no atmospheric interference, brightness temperature (TB) of the lunar surface can be seen as a good candidate for thermal calibration of FY-4M radiometers. In this paper, the physical temperature profile of lunar regolith media is first derived by resolving 1-D heat transfer equation with validation of the measurements of the Diviner lunar radiometer experiment onboard the lunar reconnaissance orbiter. Then, the loss tangent is fit and validated using the TiO2 abundances, which is derived from Clementine five-band multispectral data and Chinese Chang’e-2 37-GHz TB data. Multichannel TB of a lunar surface region along the moon equator at certain lunar time (noon and midnight) is numerically derived for all FY-4M channels. TB of lunar equator center area (0°N, 0°E) is presented with variation of the lunar local time. These results can be well applied to calibration of FY-4M, with a sustainable error in the range of 1.8 (425 GHz) to 3.8 K (89 GHz).

Active Millimeter-Wave Radiometry for Nondestructive Testing/Evaluation of Composites—Glass Fiber Reinforced Polymer

Manufacture and in-service assessment of composite materials can be challenging since there is, yet, no standard method for testing them. Nevertheless, regular inspection is necessary to maintain the structural integrity. This paper describes a nondestructive, broadband noise mapping method that uses a millimeter-wave radiometer to detect defects in composite materials. The $W$ -band system is configured for transmission mode measurement in which an amplified photonic source illuminates a glass fiber reinforced polymer containing machined defects. A high sensitivity radiometer is used for imaging the sample. The radiometer consists of a Schottky diode-based frequency tripler and a fundamental mixer.

Ozone profiles above Kiruna from two ground-based radiometers

Abstract. This paper presents new atmospheric ozone concentration profiles retrieved from measurements made with two ground-based millimetre-wave radiometers in Kiruna, Sweden. The instruments are the Kiruna Microwave Radiometer (KIMRA) and the Millimeter wave Radiometer 2 (MIRA 2). The ozone concentration profiles are retrieved using an optimal estimation inversion technique, and they cover an altitude range of ∼ 16–54 km, with an altitude resolution of, at best, 8 km. The KIMRA and MIRA 2 measurements are compared to each other, to measurements from balloon-borne ozonesonde measurements at Sodankylä, Finland, and to measurements made by the Microwave Limb Sounder (MLS) aboard the Aura satellite. KIMRA has a correlation of 0.82, but shows a low bias, with respect to the ozonesonde data, and MIRA 2 shows a smaller magnitude low bias and a 0.98 correlation coefficient. Both radiometers are in general agreement with each other and with MLS data, showing high correlation coefficients, but there are differences between measurements that are not explained by random errors. An oscillatory bias with a peak of approximately ±1 ppmv is identified in the KIMRA ozone profiles over an altitude range of ∼ 18–35 km, and is believed to be due to baseline wave features that are present in the spectra. A time series analysis of KIMRA ozone for winters 2008–2013 shows the existence of a local wintertime minimum in the ozone profile above Kiruna. The measurements have been ongoing at Kiruna since 2002 and late 2012 for KIMRA and MIRA 2, respectively.

Observations of stratospheric and mesospheric O3 with a millimeter-wave radiometer at Rikubetsu, Japan

We have been measuring brightness temperature spectra of the atmospheric ozone (O3) emission at 110.83 GHz with a millimeter-wave radiometer (MWR) located at Rikubetsu, Japan, since November 1999. Tropospheric opacities, which were also measured with the MWR and were used to take into account attenuation of the O3 signal from the stratosphere and mesosphere, were corrected using the tropospheric opacity calculated from radiosonde data. Temporal variations of the measured spectral intensity of O3, likely due to degradations of the superconductor–insulator–superconductor receiver and of the vessel for cold calibration load, were also corrected using scaling factors derived from ozonesonde data up to an average height of 35 km and Microwave Limb Sounder (MLS) monthly mean climatology above the sonde height. The vertical profiles of the O3 mixing ratio in the altitude range from 24 to 56 km were retrieved from the spectra with the optimal estimation approach. The retrieval errors from uncertainties in the scaling factor, the corrected tropospheric opacity, and atmospheric temperature, as well as those from spectral noise, were evaluated, and we found that the main retrieval errors resulted from uncertainties in the scaling factor and tropospheric opacity. The retrieved O3 profiles were compared with those from the Solar Backscatter Ultraviolet (SBUV/2), the Sounding of the Atmosphere using Broadband Emission Radiometry (SABER), and the MLS instruments onboard satellites. The retrieved O3 mixing ratios at individual levels agreed with the MLS version 3.3 or 3.4 data with an average difference better than ±5 % and a standard deviation of 4–9 %. Additionally, the retrieved O3 profiles were in reasonable agreement with the SABER version 2.0 O3 profiles and the SBUV/2 version 8.6 O3 profiles, in line with the validation results of their satellite data in the earlier literature.

Intercomparison of Ozone and Temperature Profiles During OZITOS+ 2014 Campaign in Río Gallegos, Argentina

In the framework of SAVER-Net project, the OZ one profI le aT Rio GallegOS (OZITOS+) campaign was held in the city of Rio Gallegos, Argentina (51.5 S; 69.1 W). This experiment was conducted on October 14 -18, 2014 and its main goal was to compare the ozone and temperature profiles using three different measurement techniques such as Differential Absorption Lidar (DIAL), ozonesonde and Millimeter Wave Radiometer (MWR). Also other ground-based and satellite-based instruments were included in the experiment but in this work we only present preliminary results from ground-based instruments deployed in the site. The DIAL instrument is part of Network Data for Atmospheric Composition Change (NDACC) network, and the usual protocols of quality assurance imposed for the network involve regular validation/comparisons experiments. The lidar ozone profiles measured with the lidar are compared with ozone profiles obtained with independent techniques, usually with higher or same resolution as lidar. The experiment are made collocated spatial and temporally. For that reason the Chilean team joined to Japanese and Argentine team at Rio Gallegos to develop the experiment.On October 2014, the Rio Gallegos Observatory station was inside the polar vortex during first two weeks and after that polar vortex have moved far away from Rio Gallegos during the 3rd week of October, when the intercomparison campaign was held.In this paper we are present a preliminary results of the campaign, computing the ozone and temperature profiles from DIAL with ozonesondes and MWR.