Variations in the radiothermal radiation of the ice cover of Lake Arakhley as a geo-indicator of deformation and cracking

In January-March, 2020-2021, radiophysical studies were conducted of radiothermal radiation intensity for the testing site for Lake Arakhley, Transbaikalia, Russia. The set of equipment consisting of four microwave radiometers for the wavelengths from 0.3 to 2 cm was placed on the shore of the lake mounted on a stationary platform. The temperature and deformation of ice were simultaneously measured at the depth of 0.4 meters in two orthogonal directions: west-east and north-south. The temperature was measured with heat gauges in a vertical profile at the depths of 5, 10, 15, 20 and 40 cm. In the process of contact measurements in the period of cracking, signal impulses were recorded in the channel of the deformation sensor placed in the direction of the lake center (west-east). The measurement results were used in monitoring of the condition of the water body. It turned out that in the periods of registering the deformation impulses, changes in the radio brightness temperature and decrease in the ice temperature were observed. The microwave characteristics correlate with the temperature and deformation of the ice cover and may serve as an indicator of the meteorological conditions of the region.

Assimilation of Ground-Based Microwave Radiometer on Heavy Rainfall Forecast in Beijing

Ground-based microwave radiometers (MWRPS) can provide continuous atmospheric temperature and relative humidity profiles for a weather prediction model. We investigated the impact of assimilation of ground-based microwave radiometers based on the rapid-refresh multiscale analysis and prediction system-short term (RMAPS-ST). In this study, five MWRP-retrieved profiles were assimilated for the precipitation enhancement that occurred in Beijing on 21 May 2020. To evaluate the influence of their assimilation, two experiments with and without the MWRPS assimilation were set. Compared to the control experiment, which only assimilated conventional observations and radar data, the MWRPS experiment, which assimilated conventional observations, the ground-based microwave radiometer profiles and the radar data, had a positive impact on the forecasts of the RMAPS-ST. The results show that in comparison with the control test, the MWRPS experiment reproduced the heat island phenomenon in the observation better. The MWRPS assimilation reduced the bias and RMSE of two-meter temperature and two-meter specific humidity forecasting in the 0–12 h of the forecast range. Furthermore, assimilating the MWRPS improved both the distribution and the intensity of the hourly rainfall forecast, as compared with that of the control experiment, with observations that predicted the process of the precipitation enhancement in the urban area of Beijing.

Evaluating daytime planetary boundary-layer height estimations resolved by both active and passive remote sensing instruments during the CHEESEHEAD19 field campaign

During the Chequamegon Heterogeneous Ecosystem Energy-balance Study Enabled by a High-density Extensive Array of Detectors 2019 (CHEESEHEAD19) field campaign, held in the summer of 2019 in northern Wisconsin, U.S.A., active and passive ground-based remote sensing instruments were deployed to understand the response of the planetary boundary layer to heterogeneous land surface forcing. These instruments include Radar Wind Profilers, Microwave Radiometers, Atmospheric Emitted Radiance Interferometers, Ceilometers, High Spectral Resolution Lidars, Doppler Lidars, and Collaborative Lower Atmospheric Modelling Profiling Systems that combine several of these instruments. In this study, these ground-based remote sensing instruments are used to estimate the height of the daytime planetary boundary layer, and their performance is compared against independent boundary-layer depth estimates obtained from radiosondes launched as part of the field campaign. The impact of clouds (in particular boundary layer clouds) on boundary-layer depth is also investigated. We found that while overall all instruments are able to provide reasonable boundary-layer depth estimates, each of them shows strengths and weaknesses under certain conditions. For example, Radar Wind Profilers perform well during cloud free conditions, and Microwave Radiometers and Atmospheric Emitted Radiance Interferometers have a very good agreement during all conditions, but are limited by the smoothness of the retrieved thermodynamic profiles. The estimates from Ceilometers and High Spectral Resolution Lidars can be hindered by the presence of elevated aerosol layers or clouds, and the multi-instrument retrieval from the Collaborative Lower Atmospheric Modelling Profiling Systems can be constricted to a limited height range in low aerosol conditions.

Water vapour radiometry in geodetic very long baseline interferometry telescopes: assessed through simulations

The accuracy of geodetic Very Long Baseline Interferometry (VLBI) is affected by water vapour in the atmosphere in terms of variations in the signal propagation delay at the different stations. This “wet” delay may be estimated directly from the VLBI data, as well as from independent instruments, such as collocated microwave radiometers. Rather than having stand-alone microwave radiometers we have, through simulations, evaluated the possibility to use radiometric data from the VLBI receiver in the VGOS telescopes at the Onsala Space Observatory. The advantage is that the emission from water vapour, as sensed by the radiometer, originates from the same atmospheric volume that delays the VLBI signal from the extra-galactic object. We use simulations of the sky brightness temperature and the wet delay together with an assumption of a root-mean-square (rms) noise of the receiver of 1 K, and observations evenly spread between elevation angles of 10$$^\circ $$ ∘ –90$$^\circ $$ ∘ . This results in an rms error of the estimated equivalent zenith wet delay of the order of 3 mm for a one frequency algorithm, used under cloud free conditions, and 4 mm for a two frequency algorithm, used during conditions with liquid water clouds. The results exclude rainy conditions when the method does not work. These errors are reduced by a factor of 3 if the receiver error is 0.1 K meaning that the receivers’ measurements of the sky brightness temperature is the main error source. We study the impact of ground-noise pickup by using a model of an existing wideband feed. Taking the algorithm uncertainty and the ground noise pickup into account we conclude that the method presented will be useful as an independent estimate of the wet delay to assess the quality of the wet delays and linear horizontal gradients estimated from the VLBI data themselves.

Snow depth product over Antarctic sea ice from 2002 to 2020 using multisource passive microwave radiometers

Snow over sea ice controls energy budgets and affects sea ice growth/melting, and thus has essential effects on the climate. Passive microwave radiometers can be used for basin-scale snow depth estimation at a daily scale; however, previously published methods applied to Antarctica clearly underestimated snow depth, limiting their further application. Here, we estimated snow depth using microwave radiometers and a newly constructed, robust method by incorporating lower frequencies, which have been available from AMSR-E and AMSR-2 since 2002. A regression analysis using 7 years of Operation IceBridge (OIB) airborne snow depth measurements showed that the gradient ratio (GR) calculated using brightness temperatures in vertically polarized 37 and 19 GHz, i.e., GR(37/7), was optimal for deriving Antarctic snow depth, with a correlation coefficient of −0.64. We hence derive new coefficients based on GR(37/7) to improve the current snow depth estimation from passive microwave radiometers. Comparing the new retrieval with in situ measurements from the Australian Antarctic Data Centre showed that this method outperformed the previously available method, with a mean difference of 5.64 cm and an RMSD of 13.79 cm, compared to values of −14.47 cm and 19.49 cm, respectively. A comparison to shipborne observations from Antarctic Sea Ice Processes and Climate indicated that in thin ice regions, the proposed method performed slightly better than the previous method (with RMSDs of 16.85 cm and 17.61 cm, respectively). Comparable performances during the growth and melting seasons suggest that the proposed method can still be used during the melting season. Gaussian error propagation found an average snow depth uncertainty of 3.81 cm, which accounted for 12 % of the estimated mean snow depth. We generated a complete snow depth product over Antarctic sea ice from 2002 to 2020 on a daily scale, and negative trends could be found in all sea sectors and seasons. This dataset (including both snow depth and snow depth uncertainty) can be downloaded from National Tibetan Plateau Data Center, Institute of Tibetan Plateau Research, Chinese Academy of Sciences at http://data.tpdc.ac.cn/en/disallow/61ea8177-7177-4507-aeeb-0c7b653d6fc3/ (Shen and Ke, 2021, DOI: 10.11888/Snow.tpdc.271653).

Measurement of Solar Absolute Brightness Temperature Using a Ground-Based Multichannel Microwave Radiometer

Ground-based multichannel microwave radiometers (GMRs) can observe the atmospheric microwave radiation brightness temperature at K-bands and V-bands and provide atmospheric temperature and humidity profiles with a relatively high temporal resolution. Currently, microwave radiometers are operated in many countries to observe the atmospheric temperature and humidity profiles. However, a theoretical analysis showed that a radiometer can be used to observe solar radiation. In this work, we improved the control algorithm and software of the antenna servo control system of the GMR so that it could track and observe the sun and we use this upgraded GMR to observe solar microwave radiation. During the observation, the GMR accurately tracked the sun and responded to the variation in solar radiation. Furthermore, we studied the feasibility for application of the GMR to measure the absolute brightness temperature (TB) of the sun. The results from the solar observation data at 22.235, 26.235, and 30.000 GHz showed that the GMR could accurately measure the TB of the sun. The derived solar TB measurements were 9950 ± 334, 10,351 ± 370, and 9217 ± 375 K at three frequencies. In a comparison with previous studies, we obtained average percentage deviations of 9.1%, 5.3%, and 4.5% at 22.235, 26.235, and 30.0 GHz, respectively. The results demonstrated that the TB of the sun retrieved from the GMR agreed well with the previous results in the literature. In addition, we also found that the GMR responded to the variation in sunspots and a positive relationship existed between the solar TB and the sunspot number. According to these results, it was demonstrated that the solar observation technique can broaden the field usage of GMR.

Integrated Water Vapor during Rain and Rain-Free Conditions above the Swiss Plateau

Water vapor column density, or vertically-integrated water vapor (IWV), is monitored by ground-based microwave radiometers (MWR) and ground-based receivers of the Global Navigation Satellite System (GNSS). For rain periods, the retrieval of IWV from GNSS Zenith Wet Delay (ZWD) neglects the atmospheric propagation delay of the GNSS signal by rain droplets. Similarly, it is difficult for ground-based dual-frequency single-polarisation microwave radiometers to separate the microwave emission of water vapor and cloud droplets from the rather strong microwave emission of rain. For ground-based microwave radiometry at Bern (Switzerland), we take the approach that IWV during rain is derived from linearly interpolated opacities before and after the rain period. The intermittent rain periods often appear as spikes in the time series of integrated liquid water (ILW) and are indicated by ILW ≥ 0.4 mm. In the present study, we assume that IWV measurements from radiosondes are not affected by rain. We intercompare the climatologies of IWV(rain), IWV(no rain), and IWV(all) obtained by radiosonde, ground-based GNSS atmosphere sounding, ground-based MWR, and ECMWF reanalysis (ERA5) at Payerne and Bern in Switzerland. In all seasons, IWV(rain) is 3.75 to 5.94 mm greater than IWV(no rain). The mean IWV differences between GNSS and radiosonde at Payerne are less than 0.26 mm. The datasets at Payerne show a better agreement than the datasets at Bern. However, the MWR at Bern agrees with the radiosonde at Payerne within 0.41 mm for IWV(rain) and 0.02 mm for IWV(no rain). Using the GNSS and rain gauge measurements at Payerne, we find that IWV(rain) increases with increase of the precipitation rate during summer as well as during winter. IWV(rain) above the Swiss Plateau is quite well estimated by GNSS and MWR though the standard retrievals are limited or hampered during rain periods.

Towards operational assimilation of surface based remote sensing temperature and humidity profiler data at MeteoSwiss

<p>The current atmospheric observing systems fail to provide observations of temperature and humidity in the planetary boundary layer (PBL) with satisfactory spatial and temporal resolutions despite their potential positive impact on numerical weather prediction (NWP). This is particularly critical for humidity, which exhibits a very high variability in space and time, and for the vertical profile of temperature, which determines the atmospheric stability. Therefore, the analyzed thermodynamic structure of the PBL can be prone to errors, leading to poor forecasts of warnings for relevant phenomena, such as severe storms due to intense summer convection or winter fog and low stratus.</p><p>One approach to improve the model’s representation of the PBL is to include novel, ground-based remote sensing profiler observations in the data assimilation system to improve the forecast initial conditions. This also improves the quality of downstream applications relying on a good representation of the PBL in the model, such as dispersion modelling for emergency response after nuclear, chemical or biological incidents.</p><p>In this contribution, we present results of the MeteoSwiss effort to include observations from Raman lidar and microwave radiometers into the 1km mesh-size ensemble data assimilation system KENDA-1. To this end, we have developed a forward operator for water vapor mixing ratio and temperature to assimilate profiles from the Raman lidar. Brightness temperatures from the microwave radiometers are assimilated using the RTTOV-gb forward operator. We produced extensive O-B statistics to validate the observations with respect to the model and to derive the error covariance matrices of the observations. Furthermore, we will present results of several data assimilation cycling experiments during summer-time convective situations.</p>

An upcoming European network of microwave radiometers for operational temperature profiling and humidity observations

<p>From the perspective of numerical weather prediction and nowcasting, the atmospheric boundary layer (ABL) is one of the most undersampled regions of the atmosphere due to difficulties of spaceborne remote sensing at these altitudes. Ground-based microwave radiometers (MWR) have the potential to contribute to the closing of this gap. Indeed, commercial K- and V-band (20-60 GHz) radiometers provide observations of temperature profile, water vapour and liquid water and are most sensitive to the ABL due to their choice of spectral channels and observation geometry.<br>EUMETNET's E-PROFILE observation programme has thus evaluated the potential for a European network of ground-based microwave radiometers. The stakeholder needs were inferred from WMO and EUMETNET Statements of Guidance, OSCAR and a dedicated user survey. The maturity and effectivity of the technology was assessed through a literature review and experts judgements comprising recent large-scale campaigns, experiences with long-term usage and assimilation trials and outcomes of the recent COST action TOPROF. Last but not least, the availability of existing instrumentation from which a European network could be built up was investigated. <br>Based on this study, EUMETNET decided to establish an operational MWR network by 2023 with continuous near real-time provision of brightness temperatures, humidity and temperature information from a centralised retrieval as well as forecast indices for fore- and nowcasting. The products will come along with different monitoring quality control stages at timescales from near real-time to monthly. Special care will be dedicated to ensure reliable absolute calibration results by accounting for the recent developments and recommendations from TOPROF. In the setting up and operation of the network as well as in the implementation of retrievals and monitoring, important synergies with the ACTRIS programme and the scientific community gathered in the COST action PROBE are expected.<br>The presentation will briefly outline the reasoning for setting up the network but mainly focusses on the operational aspects and services that E-PROFILE MWR will provide. Moreover, the first steps taken towards an operational network will be discussed and the general roadmap outlined.</p>