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Global Navigation Satellite System radio occultation (GNSS-RO) and microwave radiometry (MWR) are two of the most impactful spaceborne remote sensing techniques for numerical weather prediction (NWP). These two techniques provide complementary information about atmospheric temperature and water vapor structure. GNSS-RO provides high vertical resolution measurements with cloud penetration capability, but the temperature and moisture are coupled in the GNSS-RO retrieval process and their separation requires the use of a priori information or auxiliary observations. On the other hand, the MWR measures brightness temperature (Tb) in numerous frequency bands related to the temperature and water vapor structure but is limited by poor vertical resolution (> 2 km) and precipitation. In this study, we combine these two technologies in an optimal estimation approach, 1D variation method (1DVar), to improve the characterization of the complex thermodynamic structures in the lower troposphere. This study employs both simulated and operational observations. GNSS-RO bending angle and MWR Tb observations are used as inputs to the joint retrieval, where bending can be modeled by an Abel integral and Tb can be modeled by a radiative transfer model (RTM) that takes into account atmospheric absorption, as well as surface reflection and emission. By incorporating the forward operators into the 1DVar method, the strength of both techniques can be combined to bridge individual weaknesses. Applying 1DVar to the data simulated from large eddy simulation (LES) is shown to reduce GNSS-RO temperature and water vapor retrieval biases at the lower troposphere while simultaneously capturing the fine-scale variability that MWR cannot resolve. A sensitivity analysis is also conducted to quantify the impact of the a priori information and error covariance used in different retrieval scenarios. The applicability of 1DVar joint retrieval to the actual GNSS-RO and MWR observations is also demonstrated through combining collocated COSMIC-2 and Suomi-NPP (National Polar-orbiting Partnership) measurements.

We have performed an analysis of reprocessed GPS/MET data spanning 1995–1997 generated by the COSMIC Data Analysis and Archive Center (CDAAC) in 2007. CDAAC developed modified dual-frequency processing methods for the encrypted data (anti-spoofing (AS)-on) during 1995–1997. We compared the CDAAC data set to the Modern-Era Retrospective Analysis for Research and Applications-2 (MERRA-2) reanalysis, separately for AS-on and AS-off, focusing on the altitude range 10–30 km. MERRA-2 did not assimilate GPS/MET data in the period 1995–1997. To gain insight into the CDAAC data set, we developed a single-frequency data set for GPS/MET, which is unaffected by the presence of encryption. We find excellent agreement between the more limited single-frequency data set and the CDAAC data set: the bias between these two data sets is consistently less than 0.25 % in refractivity, whether or not AS is on. Given the different techniques applied between the CDAAC and the new data set presented here (designated JPL), agreement suggests that the CDAAC AS-on processing and the single-frequency processing are not biased in an aggregate sense greater than 0.25 % in refractivity, which corresponds approximately to a temperature bias less than 0.5 K. Since the profiles contained in the new single-frequency data set are not a subset of the CDAAC profiles, the combination of the CDAAC data set, consisting of 9579 profiles, and the new single-frequency data set, consisting of 4729 profiles, yields a total number of 11 531 unique profiles from combining the JPL and CDAAC data sets. All numbers are after quality control has been applied by the respective processing activities.

Atmospheric climate monitoring requires observations of high quality that conform to the criteria of the Global Climate Observing System (GCOS). Radio occultation (RO) data based on Global Positioning System (GPS) signals are available since 2001 from several satellite missions with global coverage, high accuracy, and high vertical resolution in the troposphere and lower stratosphere. We assess the consistency and long-term stability of multi-satellite RO observations for use as climate data records. As a measure of long-term stability, we quantify the structural uncertainty of RO data products arising from different processing schemes. We analyze atmospheric variables from bending angle to temperature for four RO missions, CHAMP, Formosat-3/COSMIC, GRACE, and Metop, provided by five data centers. The comparisons are based on profile-to-profile differences aggregated to monthly medians. Structural uncertainty in trends is found to be lowest from 8 to 25 km of altitude globally for all inspected RO variables and missions. For temperature, it is

This paper presents the calibration and validation studies for the Radio Occultation and Heavy Precipitation experiment aboard the PAZ satellite. These studies, necessary to assess and characterize the noise level and robustness of the differential phase shift (ΔΦ) observable of polarimetric radio occultations (PROs), confirm the good performance of the experiment and the capability of this technique in sensing precipitation. It is shown how all the predicted effects that could have an impact into the PRO observables (e.g., effect of metallic structures nearby the antenna, the Faraday rotation at the ionosphere, signal impurities in the transmission, and altered cross-polarization isolation) are effectively calibrated and corrected, and they have a negligible effect on the final observable. The on-orbit calibration, performed using an extensive dataset of free-of-rain and low-ionospheric activity observations, is successfully used to correct all the collected observations, which are further validated against independent precipitation observations confirming the sensitivity of the observables to the presence of hydrometeors. The validation results also show how vertically averaged ΔΦ can be used as a proxy for precipitation.

A positive bias at heights between 3 and 8 km has been observed when comparing the radio-occultation (RO)-retrieved refractivity with that of meteorological analyses and reanalyses in cases where heavy precipitation is present. The effect of precipitation in RO retrievals has been investigated as a potential cause of the bias, using precipitation measurements interpolated into the actual three-dimensional RO ray paths to calculate the excess phase induced by precipitation. The study consisted of comparing the retrievals when such extra delay is removed from the actual measurement and when it is not. The results show how precipitation itself is not the cause of the positive bias. Instead, we show that the positive bias is linked to high specific-humidity conditions regardless of precipitation. This study also shows a regional dependence of the bias. Furthermore, different analyses and reanalyses show a disagreement under high specific-humidity conditions and, in consequence, heavy precipitation.

Lower-tropospheric moisture and temperature measurements are crucial for understanding weather prediction and climate change. Global Positioning System radio occultation (GPS RO) has been demonstrated as a high-quality observation technique with high vertical resolution and sub-kelvin temperature precision from the upper troposphere to the stratosphere. In the tropical lower troposphere, particularly the lowest 2 km, the quality of RO retrievals is known to be degraded and is a topic of active research. However, it is not clear whether similar problems exist at high latitudes, particularly over the Arctic, which is characterized by smooth ocean surface and often negligible moisture in the atmosphere. In this study, 3-year (2008–2010) GPS RO soundings from COSMIC (Constellation Observing System for Meteorology, Ionosphere, and Climate) over the Arctic (65–90° N) show uniform spatial sampling with average penetration depth within 300 m above the ocean surface. Over 70 % of RO soundings penetrate deep into the lowest 300 m of the troposphere in all non-summer seasons. However, the fraction of such deeply penetrating profiles reduces to only about 50–60 % in summer, when near-surface moisture and its variation increase. Both structural and parametric uncertainties of GPS RO soundings were also analyzed. The structural uncertainty (due to different data processing approaches) is estimated to be within ∼ 0.07 % in refractivity, ∼ 0.72 K in temperature, and ∼ 0.05 g kg−1 in specific humidity below 10 km, which is derived by comparing RO retrievals from two independent data processing centers. The parametric uncertainty (internal uncertainty of RO sounding) is quantified by comparing GPS RO with near-coincident radiosonde and European Centre for Medium-Range Weather Forecasts (ECMWF) ERA-Interim profiles. A systematic negative bias up to ∼ 1 % in refractivity below 2 km is only seen in the summer, which confirms the moisture impact on GPS RO quality.

We construct a 9-year data record (2007–2015) of the tropospheric specific humidity using Global Positioning System radio occultation (GPS RO) observations from the Constellation Observing System for Meteorology, Ionosphere, and Climate (COSMIC) mission. This record covers the ±40° latitude belt and includes estimates of the zonally averaged monthly mean specific humidity from 700 up to 400 hPa. It includes three major climate zones: (a) the deep tropics (±15°), (b) the trade winds belts (±15–30°), and (c) the subtropics (±30–40°). We find that the RO observations agree very well with the European Centre for Medium-Range Weather Forecasts Re-Analysis Interim (ERA-Interim), the Modern-Era Retrospective Analysis for Research and Applications (MERRA), and the Atmospheric Infrared Sounder (AIRS) by capturing similar magnitudes and patterns of variability in the monthly zonal mean specific humidity and interannual anomaly over annual and interannual timescales. The JPL and UCAR specific humidity climatologies differ by less than 15 % (depending on location and pressure level), primarily due to differences in the retrieved refractivity. In the middle-to-upper troposphere, in all climate zones, JPL is the wettest of all data sets, AIRS is the driest of all data sets, and UCAR, ERA-Interim, and MERRA are in very good agreement, lying between the JPL and AIRS climatologies. In the lower-to-middle troposphere, we present a complex behavior of discrepancies, and we speculate that this might be due to convection and entrainment. Conclusively, the RO observations could potentially be used as a climate variable, but more thorough analysis is required to assess the structural uncertainty between centers and its origin.

Global Navigation Satellite System (GNSS) radio occultation (RO) measurements are promising in sensing the vertical structure of the Earth's planetary boundary layer (PBL). However, large refractivity changes near the top of PBL can cause ducting and lead to a negative bias in the retrieved refractivity within the PBL (below ∼ 2 km). To remove the bias, a reconstruction method with assumption of linear structure inside the ducting layer models has been proposed by Xie et al. (2006). While the negative bias can be reduced drastically as demonstrated in the simulation, the lack of high-quality surface refractivity constraint makes its application to real RO data difficult. In this paper, we use the widely available precipitable water (PW) satellite observation as the external constraint for the bias correction. A new framework is proposed to incorporate optimization into the RO reconstruction retrievals in the presence of ducting conditions. The new method uses optimal estimation to select the best refractivity solution whose PW and PBL height best match the externally retrieved PW and the known a priori states, respectively. The near-coincident PW retrievals from AMSR-E microwave radiometer instruments are used as an external observational constraint. This new reconstruction method is tested on both the simulated GNSS-RO profiles and the actual GNSS-RO data. Our results show that the proposed method can greatly reduce the negative refractivity bias when compared to the traditional Abel inversion.

This study describes the first experimental observations showing that hydrometeors induce polarimetric signatures in global navigation satellite system (GNSS) signals. This evidence is relevant to the PAZ low Earth orbiter, which will test the concept and applications of polarimetric GNSS radio occultation (RO) (i.e. ROs obtained with a dual-polarization antenna). A ground field campaign was carried out in preparation for PAZ to verify the theoretical sensitivity studies on this concept (Cardellach et al., 2015). The main aim of the campaign is to identify and understand the factors that might affect the polarimetric GNSS observables. Studied for the first time, GNSS signals measured with two polarimetric antennas (H, horizontal, and V, vertical) are shown to discriminate between heavy rain events by comparing the measured phase difference between the H and V phase delays (ΔΦ) in different weather scenarios. The measured phase difference indicates higher dispersion under rain conditions. When individual events are examined, significant increases in ΔΦ occur when the radio signals cross rain cells. Moreover, the amplitude of such a signal is much higher than the theoretical prediction for precipitation; thus, other sources of polarimetric signatures have been explored and identified. Modelling of other hydrometeors, such as melting particles and ice crystals, have been proposed to explain the obtained measurements, with good agreement in more than 90 % of the cases.

The spatial variability of the tropical tropospheric relative humidity (RH) throughout the vertical extent of the troposphere is examined using Global Positioning System Radio Occultation (GPSRO) observations from the Constellation Observing System for Meteorology, Ionosphere, and Climate (COSMIC) mission. These high vertical resolution observations capture the detailed structure and moisture budget of the Hadley Cell circulation. We compare the COSMIC observations with the European Center for Medium-range Weather Forecast (ECMWF) Reanalysis Interim (ERA-Interim) and the Modern-Era Retrospective analysis for Research and Applications (MERRA) climatologies. Qualitatively, the spatial pattern of RH in all data sets matches up remarkably well, capturing distinct features of the general circulation. However, RH discrepancies exist between ERA-Interim and COSMIC data sets that are noticeable across the tropical boundary layer. Specifically, ERA-Interim shows a drier Intertropical Convergence Zone (ITCZ) by 15–20% compared to both COSMIC and MERRA data sets, but this difference decreases with altitude. Unlike ECMWF, MERRA shows an excellent agreement with the COSMIC observations except above 400 hPa, where GPSRO observations capture drier air by 5–10%. RH climatologies were also used to evaluate intraseasonal variability. The results indicate that the tropical middle troposphere at ±5–25° is most sensitive to seasonal variations. COSMIC and MERRA data sets capture the same magnitude of the seasonal variability, but ERA-Interim shows a weaker seasonal fluctuation up to 10% in the middle troposphere inside the dry air subsidence regions of the Hadley Cell. Over the ITCZ, RH varies by maximum 9% between winter and summer.

The typical atmospheric boundary layer (ABL) over the southeast (SE) Pacific Ocean is featured with a strong temperature inversion and a sharp moisture gradient across the ABL top. The strong moisture and temperature gradients result in a sharp refractivity gradient that can be precisely detected by the Global Positioning System (GPS) radio occultation (RO) measurements. In this paper, the Constellation Observing System for Meteorology, Ionosphere & Climate (COSMIC) GPS RO soundings, radiosondes and the high-resolution ECMWF analysis over the SE Pacific are analyzed. COSMIC RO is able to detect a wide range of ABL height variations (1–2 km) as observed from the radiosondes. However, the ECMWF analysis systematically underestimates the ABL heights. The sharp refractivity gradient at the ABL top frequently exceeds the critical refraction (e.g., −157 N-unit km−1) and becomes the so-called ducting condition, which results in a systematic RO refractivity bias (or called N-bias) inside the ABL. Simulation study based on radiosonde profiles reveals the magnitudes of the N-biases are vertical resolution dependent. The $N$-bias is also the primary cause of the systematically smaller refractivity gradient (rarely exceeding −110 N-unit km−1) at the ABL top from RO measurement. However, the N-bias seems not affect the ABL height detection. Instead, the very large RO bending angle and the sharp refractivity gradient due to ducting allow reliable detection of the ABL height from GPS RO. The seasonal mean climatology of ABL heights derived from a nine-month composite of COSMIC RO soundings over the SE Pacific reveals significant differences from the ECMWF analysis. Both show an increase of ABL height from the shallow stratocumulus near the coast to a much higher trade wind inversion further off the coast. However, COSMIC RO shows an overall deeper ABL and reveals different locations of the minimum and maximum ABL heights as compared to the ECMWF analysis. At low latitudes, despite the decreasing number of COSMIC RO soundings and the lower percentage of soundings that penetrate into the lowest 500-m above the mean-sea-level, there are small sampling errors in the mean ABL height climatology. The difference of ABL height climatology between COSMIC RO and ECMWF analysis over SE Pacific is significant and requires further studies.

We study the impact of large-scale ionospheric structure on the accuracy of radio occultation (RO) retrievals. We use a climatological model of the ionosphere as well as an ionospheric data assimilation model to compare quiet and geomagnetically disturbed conditions. The presence of ionospheric electron density gradients during disturbed conditions increases the physical separation of the two GPS frequencies as the GPS signal traverses the ionosphere and atmosphere. We analyze this effect in detail using ray-tracing and a full geophysical retrieval system. During quiet conditions, our results are similar to previously published studies. The impact of a major ionospheric storm is analyzed using data from the 30 October 2003 "Halloween" superstorm period. At 40 km altitude, the refractivity bias under disturbed conditions is approximately three times larger than quiet time. These results suggest the need for ionospheric monitoring as part of an RO-based climate observation strategy. We find that even during quiet conditions, the magnitude of retrieval bias depends critically on assumed ionospheric electron density structure, which may explain variations in previously published bias estimates that use a variety of assumptions regarding large scale ionospheric structure. We quantify the impact of spacecraft orbit altitude on the magnitude of bending angle and retrieval error. Satellites in higher altitude orbits (700+ km) tend to have lower residual biases due to the tendency of the residual bending to cancel between the top and bottomside ionosphere. Another factor affecting accuracy is the commonly-used assumption that refractive index is unity at the receiver. We conclude with remarks on the implications of this study for long-term climate monitoring using RO.

The diurnal variation, driven by solar forcing, is a fundamental mode in the Earth's weather and climate system. Radio occultation (RO) measurements from the six COSMIC satellites (Constellation Observing System for Meteorology, Ionosphere and Climate) provide nearly uniform global coverage with high vertical resolution, all-weather and diurnal sampling capability. This paper analyzes the diurnal variations of temperature and refractivity from three-year (2007–2009) COSMIC RO measurements in the troposphere and stratosphere between 30° S and 30° N. The RO observations reveal both propagating and trapped vertical structures of diurnal variations, including transition regions near the tropopause where data with high vertical resolution are critical. In the tropics the diurnal amplitude in refractivity shows the minimum around 14 km and increases to a local maximum around 32 km in the stratosphere. The upward propagating component of the migrating diurnal tides in the tropics is clearly captured by the GPS RO measurements, which show a downward progression in phase from stratopause to the upper troposphere with a vertical wavelength of about 25 km. At ~32 km the seasonal variation of the tidal amplitude maximizes at the opposite side of the equator relative to the solar forcing. The vertical structure of tidal amplitude shows strong seasonal variations and becomes asymmetric along the equator and tilted toward the summer hemisphere in the solstice months. Such asymmetry becomes less prominent in equinox months.

Infections in orthopaedic surgery are a serious issue. Antibiotic-loaded bone cement was developed for the treatment of infected joint arthroplasties and for prophylaxes in total joint replacement in selected cases. Despite the widespread use of the antibiotic-loaded bone cement in orthopedics, many issues are still unclear or controversial: bacterial adhesion and antibiotic resistance, modification of mechanical properties which follows the addition of the antibiotic, factors influencing the release of the antibiotic from the cement and the role of the surface, the method for mixing the cement and the antibiotic, the choice and the effectiveness of the antibiotic, the combination of two or more antibiotics, and the toxicity. This review discusses all these topics, focusing on properties, merits, and defects of the antibiotic loaded cement. The final objective is to provide the orthopaedic surgeons clear and concise information for the correct choice of cement in their clinical practice.