Ground-based Microwave Radiometry Research Articles

Diurnal variations in middle-atmospheric water vapor by ground-based microwave radiometry

Abstract. In this paper, we compare the diurnal variations in middle-atmospheric water vapor as measured by two ground-based microwave radiometers in the Alpine region near Bern, Switzerland. The observational data set is also compared to data from the chemistry–climate model WACCM. Due to the small diurnal variations of usually less than 1%, averages over extended time periods are required. Therefore, two time periods of five months each, December to April and June to October, were taken for the comparison. The diurnal variations from the observational data agree well with each other in amplitude and phase. The linear correlation coefficients range from 0.8 in the upper stratosphere to 0.5 in the upper mesosphere. The observed diurnal variability is significant at all pressure levels within the sensitivity of the instruments. Comparing our observations with WACCM, we find that the agreement of the phase of the diurnal cycle between observations and model is better from December to April than from June to October. The amplitudes of the diurnal variations for both time periods increase with altitude in WACCM, but remain approximately constant at 0.05 ppm in the observations. The WACCM data are used to separate the processes that lead to diurnal variations in middle-atmospheric water vapor above Bern. The dominating processes were found to be meridional advection below 0.1 hPa, vertical advection between 0.1 and 0.02 hPa and (photo-)chemistry above 0.02 hPa. The contribution of zonal advection is small. The highest diurnal variations in water vapor as seen in the WACCM data are found in the mesopause region during the time period from June to October with diurnal amplitudes of 0.2 ppm (approximately 5% in relative units).

Operational profiling of temperature using ground-based microwave radiometry at Payerne: prospects and challenges

Abstract. The motivation of this study is to verify theoretical expectations placed on ground-based microwave radiometer (MWR) techniques and to confirm whether they are suitable for supporting key missions of national weather services, such as timely and accurate weather advisories and warnings. We evaluate reliability and accuracy of atmospheric temperature profiles retrieved continuously by the microwave profiler system HATPRO (Humidity And Temperature PROfiler) operated at the aerological station of Payerne (MeteoSwiss) in the time period August 2006–December 2009. Assessment is performed by comparing temperatures from the radiometer against temperature measurements from a radiosonde accounting for a total of 2107 quality-controlled all-season cases. In the evaluated time period, the MWR delivered reliable temperature profiles in 86% of all-weather conditions on a temporal resolution of 12–13 min. Random differences between MWR and radiosonde are down to 0.5 K in the lower boundary layer and increase to 1.7 K at 4 km height. The differences observed between MWR and radiosonde in the lower boundary layer are similar to the differences observed between the radiosonde and another in-situ sensor located on a close-by 30 m tower. Temperature retrievals from above 4 km contain less than 5% of the total information content of the measurements, which makes clear that this technique is mainly suited for continuous observations in the boundary layer. Systematic temperature differences are also observed throughout the retrieved profile and can account for up to ±0.5 K. These errors are due to offsets in the measurements of the microwave radiances that have been corrected for in data post-processing and lead to nearly bias-free overall temperature retrievals. Different reasons for the radiance offsets are discussed, but cannot be unambiguously determined retrospectively. Monitoring and, if necessary, corrections for radiance offsets as well as a real-time rigorous automated data quality control are mandatory for microwave profiler systems that are designated for operational temperature profiling. In the analysis of a subset of different atmospheric situations, it is shown that lifted inversions and data quality during precipitation present the largest challenges for operational MWR temperature profiling.

CO at 40–80 km above Kiruna observed by the ground-based microwave radiometer KIMRA and simulated by the Whole Atmosphere Community Climate Model

Abstract. This study compares CO in the Arctic stratosphere and mesosphere measured by ground-based microwave radiometry with simulations made with the Whole Atmosphere Community Climate Model driven with specified dynamical fields (SD-WACCM4) for the Arctic winters 2008/2009 and 2009/2010. CO is a tracer for polar winter middle atmosphere dynamics, hence the representation of polar dynamics in the model is examined indirectly. Measurements were taken with the KIruna Microwave RAdiometer (KIMRA). The instrument, which is located in Kiruna, Northern Sweden (67.8° N, 20.4° E), provides CO profiles between 40 and 80 km altitude. The present comparison, which is one of the first between SD-WACCM4 and measurements, is performed on the smallest space and time scales currently simulated by the model; the global model is evaluated daily at the particular model grid-point closest to Kiruna. As a guide to what can generally be expected from such a comparison, the same analysis is repeated for observations of CO from the Microwave Limb Sounder (MLS), a microwave radiometer onboard NASA's Aura satellite, which has global coverage. First, time-mean profiles of CO are compared, revealing that the profile shape of KIMRA deviates from SD-WACCM4 and MLS, especially in the upper mesosphere. SD-WACCM4 and MLS are mostly consistent throughout the range of altitude considered; however, SD-WACCM4 shows slightly lower values in the upper mesosphere. Second, the time evolution is compared for the complete time series, as well as for the slowly and rapidly evolving parts alone. Overall, the agreement among the datasets is very good and the model is almost as consistent with the measurements as the measurements are with each other. Mutual correlation coefficients of the slowly varying part of the CO time series are ≥0.9 over a wide altitude range. This demonstrates that the polar winter middle atmosphere dynamics is very well represented in SD-WACCM4 and that the relaxation to analyzed meteorological fields below 50 km constrains the behavior of the simulation sufficiently, even at higher altitudes, such that the simulation above 50 km is close to the measurements. However, above 50 km, the model-measurement correlation for the rapidly varying part of the CO time series is lower (0.3) than the measurement-measurement correlation (0.6). This is attributed to the fact that the gravity wave parametrization in WACCM is based on a generic gravity wave spectrum and cannot be expected to capture the instantaneous behavior of the actual gravity wave field present in the atmosphere.

Identification of rainy periods from ground based microwave radiometry

In this paper the authors present the results of a study aiming at detecting rainy data in measurements collected by a dual band ground-based radiometer.The proposed criterion is based on the ratio of the brightness temperatures observed in the 20–30 GHz band without need of any ancillary information. A major result obtained from the probability density of the ratio computed over one month of data is the identification of threshold values between clear sky, cloudy sky and rainy sky, respectively. A linear fit performed by using radiometric data and concurrent rain gauge measurements shows a correlation coefficient equal to 0.56 between the temperature ratio and the observed precipitation.

Thermodynamic Atmospheric Profiling During the 2010 Winter Olympics Using Ground-Based Microwave Radiometry

Ground-based microwave radiometer profilers in the 20–60-GHz range operate continuously at numerous sites in different climate regions. Recent work suggests that a 1-D variational (1-DVAR) technique, coupling radiometric observations with outputs from a numerical weather prediction model, may outperform traditional retrieval methods for temperature and humidity profiling. The 1-DVAR technique is applied here to observations from a commercially available microwave radiometer deployed at Whistler, British Columbia, which was operated by Environment Canada to support nowcasting and short-term weather forecasting during the Vancouver 2010 Winter Olympic and Paralympic Winter Games. The analysis period included rain, sleet, and snow events ( <formula formulatype="inline" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex Notation="TeX">$\sim$</tex></formula> 235-mm total accumulation and rates up to 18 mm/h). The 1-DVAR method is applied “quasi-operationally,” i.e., as it could have been applied in real time, as no data were culled. The 1-DVAR-achieved accuracy has been evaluated by using simultaneous radiosonde and ceilometer observations as reference. For atmospheric profiling from the surface to 10 km, we obtain retrieval errors within 1.5 K for temperature and 0.5 <formula formulatype="inline" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex Notation="TeX">$\hbox{g/m}^{3}$</tex></formula> for water vapor density. The retrieval accuracy for column-integrated water vapor is 0.8 <formula formulatype="inline" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex Notation="TeX">$ \hbox{kg/m}^{2}$</tex></formula> , with small bias <formula formulatype="inline" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex Notation="TeX">$(-0.1\ \hbox{kg/m}^{2})$</tex> </formula> and excellent correlation (0.96). The retrieval of cloud properties shows a high probability of detection of cloud/no cloud (0.8/0.9, respectively), low false-alarm ratio (0.1), and cloud-base height estimate error within <formula formulatype="inline" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex Notation="TeX">$\sim$</tex></formula> 0.60 km.

Observation of strato-mesospheric CO above Kiruna with ground-based microwave radiometry – retrieval and satellite comparison

Abstract. CO serves as a tracer for dynamics in the polar winter middle atmosphere. This work presents the retrieval and the characterization of ground-based CO measurements from the winters 2008/2009 and 2009/2010 by the Kiruna microwave radiometer KIMRA, located in northern Sweden (67.8° N, 20.4° E). Furthermore, the dataset is used for an extensive comparison to the recent satellite instruments MLS on Aura, ACE-FTS, and MIPAS on Envisat. The vmr profiles are retrieved using the optimal estimation approach. A detailed analysis of the averaging kernel functions is carried out, showing sensitivity of the measurements between 40 and 80 km altitude, a vertical resolution of 16 to 22 km, as well as a residual influence of the region up to 130 km altitude. An error assessment reveals a total error of the retrieved profile that increases with altitude and is approx. ±0.1 ppmv at 50 km altitude and ±3 ppmv at 80 km altitude. The main contributions to this total error arise from the measurement noise and the uncertainty of the used temperature profiles. The expected dynamical features of the polar winter middle atmosphere are qualitatively identified in the retrieved time series, but are not quantitatively analyzed here. The dense MLS dataset is used to investigate the influence of the collocation criteria on the satellite comparison, showing that relaxing the distance criterion causes a high bias for MLS. The comparison including the other instruments is difficult because of the small number of coincidences. However, it suggests that there is a general agreement between KIMRA and the satellite instruments below 65 km altitude, but a high bias for KIMRA above this altitude. Furthermore, the shape of the KIMRA profile appears to be systematically different from the satellite profiles.

Monitoring Snow Characteristics With Ground-Based Multifrequency Microwave Radiometry

Long-term microwave and infrared radiometric measurements of snowpack were carried out with ground-based sensors in winter 2006-2007 and 2007-2008, together with conventional measurements of snow-cover profiles. The first experiment focused on the behavior of snow emission during the destructive and constructive metamorphisms. The second involved a correlation analysis of the small fluctuations related to diurnal solar cycle in order to obtain the time delay of microwave brightness temperatures Tb with respect to the snow surface temperature. From this analysis, it was possible to estimate an effective (weighed average) temperature and the thickness of the layer that mostly contributed to microwave emission at 19 and 37 GHz. The ratio of the brightness temperature to the effective temperature can be assumed to be an equivalent emissivity of the snowpack. Data collected in both years have been compared with simulations carried out using the advanced Institute of Applied Physics (IFAC) Radiative Advanced Dry Snow Emission (IRIDE) model driven by data collected on ground. The model is based on the advanced integral equation method to represent soil, coupled to a layer of dry snow whose electromagnetic properties are described by the dense medium radiative transfer theory with quasi-crystalline approximation applied to a medium (air) filled with sticky particles. Simulations performed by using ground data as inputs to the model have been found to be well in agreement with experimental data. Moreover, the comparison of model simulations with experimental data allowed one to understand some peculiar characteristics of microwave emission from the snowpack related to its physical conditions.

Inner-tropical ozone measurements at the Mérida Atmospheric Research Station (MARS) using ground-based microwave radiometry

Since March 2004 the ground-based 268–280 GHz radiometer MIRA 2 has been in quasi-continuous operation at the inner-tropical Mérida Atmospheric Research Station (MARS) on Pico Espejo (8.58°N, 71.15°W, 4765 m above sea level) in the Venezuelan Andes. Using the optimal estimation method concentration profiles of ozone have been retrieved in the stratosphere and mesosphere. In the middle stratosphere variations of ozone on a time scale of several months were revealed in the resulting time series that probably result from the turnaround of the Brewer–Dobson circulation. In the mesosphere photochemistry plays the most important role for the ozone concentration. Therefore a diurnal cycle is observed in the upper part of the retrieved ozone profiles. The measurements are used to verify model results of ozone in the mesosphere obtained by a photochemistry model, which reproduces the diurnal variation of ozone very well. Also an inter-annual variation of mesospheric ozone during the month of November in 2004–2007 was observed, primarily during the night. As the time series is still too short to clearly distinguish solar or QBO signals, the cause of this inter-annual variation cannot yet be related to one or the other. In November 2006 an unusual decrease of the ozone partial columns above 60 km was measured; the cause of this decrease is also not identified so far.

Investigating Water Vapor Variability by Ground-Based Microwave Radiometry: Evaluation Using Airborne Observations

This letter introduces a new approach to characterize small-scale humidity variations using ground-based microwave radiometry. For that purpose, a microwave profiler routinely performed different scan patterns during its deployment at the Atmospheric Radiation Measurement mobile facility in the Black Forest, Germany. Individual azimuth scans at 30deg elevation revealed spatial variations in integrated water vapor (IWV) up to plusmn10%. Aircraft observations were used to evaluate the performance of the microwave observations by comparing derived humidity fields with IWV retrieved along individual directions of the microwave radiometer. Distinct humidity signals were reproduced by both observations. Residual uncertainties can be attributed to the temporal variations during the time it took the aircraft to cover the boundary layer and uncertainties in the interpolation. Long-term scanning observations will be further explored to investigate land-surface interaction and to characterize subgrid variability.

Comparison and validation studies related to ground-based microwave observations of ozone in the stratosphere and mesosphere

Since November 1994, ozone profiles are continuously measured by ground-based microwave radiometry in Bern. The radiometer GROMOS receives the 142.175 GHz line emission of ozone in the stratosphere and lower mesosphere. The spectral line data are appropriate to determine the ozone profile up to an altitude of 75 km. Comparisons with other ground-based stations (microwave radiometer and lidar) as well as with satellite observations (SAGE and HALOE) are carried out, and the obtained results are discussed. After this validation procedure, the observed ozone distribution over Bern from January 1995 to December 2002 is presented.

Starting long-term stratospheric observations with RAMAS at Summit, Greenland

The new microwave Radiometer for Atmospheric Measurements at Summit (RAMAS) has started operation at Summit station, Greenland (72/spl deg/N, 38/spl deg/W, 3200 m), and is now being prepared for continuous measurements. RAMAS operates in the frequency band from 265-280 GHz with an instantaneous bandwidth of currently 1 GHz. It observes the emission of thermally induced rotational transitions of a variety of stratospheric trace gases, including O/sub 3/, ClO, N/sub 2/O, HNO/sub 3/, and HCN. Tropospheric water vapor content, a major constraint on ground-based microwave radiometry, is exceptionally low at Summit station. Initial measurements and retrieved profiles are presented, demonstrating the excellent measurement conditions.

Accuracy of cloud liquid water path from ground‐based microwave radiometry 2. Sensor accuracy and synergy

The influence of microwave radiometer accuracy on retrieved cloud liquid water path (LWP) was investigated. Sensor accuracy was assumed to be the sum of the relative (i.e., Gaussian noise) and the absolute accuracies of brightness temperatures. When statistical algorithms are developed the assumed noise should be as close as possible to the real measurements in order to avoid artifacts in the retrieved LWP distribution. Typical offset errors of 1 K in brightness temperatures can produce mean LWP errors of more than 30 g m−2 for a two‐channel radiometer retrieval, although positively correlated brightness temperature offsets in both channels reduce this error to 16 g m−2. Large improvements in LWP retrieval accuracy of about 50% can be achieved by adding a 90‐GHz channel to the two‐channel retrieval. The inclusion of additional measurements, like cloud base height from a lidar ceilometer and cloud base temperature from an infrared radiometer, is invaluable in detecting cloud free scenes allowing an indirect evaluation of LWP accuracy in clear sky cases. This method was used to evaluate LWP retrieval algorithms based on different gas absorption models. Using two months of measurements, the Liebe 93 model provided the best results when the 90‐GHz channel was incorporated into the standard two‐channel retrievals.

Accuracy of cloud liquid water path from ground‐based microwave radiometry 1. Dependency on cloud model statistics

This paper investigates the influence of cloud model statistics on the accuracy of statistical multiple‐frequency liquid water path (LWP) retrievals for a ground‐based microwave radiometer. Statistical algorithms were developed from a radiosonde data set in which clouds were modeled by using a relative humidity threshold and a modified adiabatic assumption. Evaluation of the algorithms was then performed by applying the algorithms to four data sets in which clouds were generated in different ways (i.e., threshold method, gradient method, and cloud microphysical model). While classical two‐channel algorithms, in this case using frequencies at 22.985 and 28.235 GHz, do not show a significant dependency on the cloud model, the inclusion of an additional 50‐GHz channel can introduce significant systematic errors. The addition of a 90‐GHz frequency to the two‐channel algorithm leads to a larger increase in LWP accuracy than in case of the 50‐GHz channel and is less sensitive to the choice of cloud model. A drizzle case from the cloud microphysical model shows no significant loss of accuracy for the microwave radiometer algorithms, in contrast to simple cloud radar retrievals of liquid water. In case of rain, however, the results deteriorate when the total liquid water path is larger than 700 g m−2.

Remote Sensing of the Thermodynamic State of the Atmospheric Boundary Layer by Ground-Based Microwave Radiometry

First results are presented of 18 months' experience with a microwave profiler that has been in operation in an unattended mode. Profiles of temperature and water vapor were retrieved without bias by a statistical regression method that was more accurate as opposed to a neural network approach, in particular for water vapor. Cloud liquid water was estimated by a neural network. The accuracy of the retrieved profiles estimated against quasisimultaneous radiosonde measurements are of comparable quality to that of the retrievals of ground-based Fourier transform infrared (FTIR) measurements. For temperature, the accuracy is about 0.6 K near the surface and less or equal to 1.6 K up to 7 km in summer and 4 km in winter. For water vapor, the corresponding values are 0.2–0.3 g m−3 near the surface and 0.8–1.0 g m−3 from 1- to 2-km altitude. The vertical resolution, however, is worse than that of FTIR measurements. Two case studies—a 1-week anticyclonic situation and 1 day with a cold front passage—demonstrate the capacity of microwave radiometry to sense the thermodynamic structure of the lower troposphere up to 3–4 km quasi-continuously with reasonable accuracy and height resolution, interrupted only during precipitation events. The diurnal course of temperature and humidity as well as the weakening of the amplitudes and decay with altitude was traced up to 4 km. Considerable structure was found, too, in the liquid water profile during the passage of the cold front. The cloud base retrieved from the microwave data corresponded well with collocated ceilometer measurements.

ミリ波地上分光観測による成層圏・中間圏オゾンの変動

Comparison of strato-mesospheric O 3 derived from ground-based microwave radiometry at Nagoya University with Umkehr measurements at Tsukuba by JMA (Japan Meteorological Agency) has been carried out for evaluation of microwave measurements. Good agreements between radio and Umkehr measurements have been found from Umkehr layer 6-9, which correspond to the pressure of 15.8-0.99 hPa. Layer ozone amounts in layer 10 from microwave measurements show short term enrichment in winter with time scale of about a week, which are not observed by Umkehr measurements. The difference is due to the saturation effect inherent in Umkehr measurements. Fourier coefficients, up to the 2nd harmonic of the seasonal variations of nighttime and daytime mixing ratios, are given in tables for the pressure P = 0.013,... 10 hPa (log P = -1.875,., 1.000). QBO type variations of O 3 in 1-0.1 hPa range described in our earlier paper are due to the superposition of the short term enrichment. The short term enrichment was especially remarkable in 1992-1993 and 1994-1995. The short term enrichment does not correlate with temperature. A plausible cause of the enrichment will be vertical circulation anomalies as is they case of QBO variations in O 3 at the lower-stratosphere, and in NO 2 at the middle-stratosphere proposed by Randel and Wu (1996).

Results of Year-Round Remotely Sensed Integrated Water Vapor by Ground-Based Microwave Radiometry

Based on two years of measurements with a time resolution of 1 min, some climatological findings on precipitable water vapor (PWV) and cloud liquid water (CLW) in central Europe are given. A weak diurnal cycle is apparent. The mean overall diurnal variation was about 0.15 cm in summer and 0.05 cm in winter, equivalent to 8% and 5%, respectively. The PWV increase starts in summer at about 0800 local time and has a maximum of about 0.02 cm h21 between 1000 and 1500 local time, equivalent to about 1% PWV h21. There was, on average, no PWV variation during the night in winter. PWV decreased in winter during the morning with a maximum of 0.01 cm h21 and increased in the afternoon with a maximum of 0.01 cm h21. Thus, the accuracy of the monthly means of PWV based on monitoring systems with low-time resolution (satellites, radiosondes) is only slightly affected by the diurnal course of PWV in central Europe. On average an increase in PWV and CLW was found in the 30-min interval before precipitation in summer. The PWV increase was, however, only about 0.1 cm or 5% of PWV within the last 2 h before rain. The corresponding CLW increase was 0.1 mm, which is considerable as precipitation was observed when CLW reached 0.3‐0.4 mm.

Atmospheric remote sensing by microwave radiometry

An Introduction to the Passive Microwave Remote Sensing of Atmospheres Absorption of Microwaves by Atmospheric Gases Microwave Radiative Transfer in Hydrometeors Ground-Based Microwave Remote Sensing of Meteorological Variable Tropospheric Radio Path Delay from Ground-Based Microwave Radiometry Remote Sensing of the Atmosphere from Satellites Using Microwave Radiometry Ground-Based Microwave Spectroscopy of the Earth's Stratosphere and Mesosphere Microwave Limb Sounding Retrieval of Atmospheric Parameters in Planetary Atmospheres from Microwave Spectroscopy Properties of the Deep Atmospheres of the Planets from Radio Astronomical Observations. @21 VA1, VB2, M3

The effect of turbulence on atmospheric gradient parameters estimated from ground‐based radiometric and space geodetic measurements

Spatial and temporal fluctuations in the refractive index of air affect estimates of atmospheric parameters determined from data obtained from radio signals which have propagated through the atmosphere. These effects will become increasingly important as we continue to improve the accuracy of microwave space geodetic techniques. Using a straightforward expression for the covariance of a general vector of atmospheric parameters, I calculate the effects on estimates of spatial gradients for a frozen Kolmogorov turbulence field moving over a site at constant velocity. Numerical calculations are performed to investigate the implications for three techniques: ground‐based microwave radiometry, geodesy with the Global Positioning System, and Very Long Baseline Interferometry. The results indicate that a prevailing wind with no true static gradients may give rise to apparent azimuthal asymmetries when gradient parameters are estimated. Moreover, care must be taken in comparing gradient parameters determined using data from these different techniques, because these techniques sample the atmosphere on different spatial and temporal scales.

Number of Nonredundant Frequencies for Ground-Based Microwave Radiometric Temperature Profiling

The information content of ground-based measurements of atmospheric microwave radiance in the 50–60 GHz band was studied, using a formulation due to Twomey. Weighting functions for ground-based microwave radiometry were constructed corresponding to measurements at various frequencies, and various elevation angles. Covariance matrices were computed for several sets of such weighting functions, and their eigenvalues were examined to estimate the degree of redundancy in the measurements.

Pilot Study of Methods to Decrease Measurement Errors of Tropospheric Inversions by Ground-Based Microwave Radiometry

Abstract Results of radiometer temperature profile simulations are analyzed in order to examine the hypothesis that knowledge of temperature inversion parameters obtained from other instruments would substantially improve the accuracy of radiometric temperature profiles. Five variations of a statistical retrieval method are used to produce radiometric temperature profiles. These profiles are then compared with radiosonde data under both inversion and noninversion conditions. The best algorithm yields consistently better results than the traditional (pure radiometric) technique, but still fails to correctly reproduce the radiosonde inversions.