The Global Navigation Satellite System (GNSS) Radio Occultation (RO) is a key technique for obtaining thermodynamic profiles of temperature, humidity, pressure, and density in the Earth’s troposphere. However, due to refraction effects of both the dry air and water vapor at low altitudes, retrieval of accurate profiles is challenging. Here we introduce a new moist air retrieval algorithm aiming to improve the quality of RO-retrieved profiles in moist air and including uncertainty estimation in a clear sequence of steps. The algorithm first uses RO dry temperature and pressure and background temperature/humidity and their uncertainties to retrieve humidity/temperature and their uncertainties. These temperature and humidity profiles are then combined with their corresponding background profiles by optimal estimation employing inverse-variance weighting. Finally, based on the optimally estimated temperature and humidity profiles, pressure and density profiles are computed using hydrostatic and equation-of-state formulas. The input observation and background uncertainties are dynamically estimated, accounting for spatial and temporal variations. We show results from applying the algorithm on test datasets, deriving insights from both individual profiles and statistical ensembles, and from comparison to independent 1D-Variational (1DVar) algorithm-derived moist air retrieval results from Radio Occultation Meteorology Satellite Application Facility Copenhagen (ROM-SAF) and University Corporation for Atmospheric Research (UCAR) Boulder RO processing centers. We find that the new scheme is comparable in its retrieval performance and features advantages in the integrated uncertainty estimation that includes both estimated random and systematic uncertainties and background bias correction. The new algorithm can therefore be used to obtain high-quality tropospheric climate data records including uncertainty estimation.

We developed a new approach to monitor sudden stratospheric warming (SSW) events under climate change since 1980 based on reanalysis data verified by radio occultation data. We constructed gridded daily mean temperature anomalies from the input fields at different vertical resolutions (basic-case full resolution, cross-check with reanalysis at 10 stratospheric standard pressure levels or 10 and 50 hPa levels only) and employed the concept of threshold exceedance areas (TEAs), the geographic areas wherein the anomalies exceed predefined thresholds (such as 30 K), to monitor the phenomena. We derived main-phase TEAs, representing combined middle- and lower-stratospheric warming, to monitor SSWs on a daily basis. Based on the main-phase TEAs, three key metrics, including main-phase duration, area, and strength, are estimated and used for the detection and classification of SSW events. An SSW is defined to be detected if the main-phase warming lasts at least 6 d. According to the strength, SSW events are classified into minor, major, and extreme. An informative 42 winters' SSW climatology (1980–2021) was developed, including the three key metrics as well as onset date, maximum-warming-anomaly location, and other valuable SSW characterization information. The results and validation against previous studies underpin that the new method is robust for SSW detection and monitoring and that it can be applied to any quality-assured reanalysis, observational and model temperature data that cover the polar region and winter timeframes of interest, either using high-vertical-resolution input data (preferable basic case), coarser standard-pressure-levels resolution, or (at least) 10 and 50 hPa pressure level data. Within the 42 winters, 43 SSW events were detected for the basic case, yielding a frequency of about 1 event per year. In the 1990s, where recent studies showed gaps, we detected several events. Over 95 % of event onset dates occurred in deep winter (December–January–February timeframe, about 50 % in January), and more than three-quarters have their onset location over northern Eurasia and the adjacent polar ocean. Regarding long-term change, we found a statistically significant increase in the duration of SSW main-phase warmings of about 5(±2) d over the climate change period from the 1980s to the 2010s, raising the average duration by nearly 50 % from about 10 d to 15 d and inducing an SSW strength increase of about 40(±25) million km² days from about 100 to 140 million km² days. The results are robust (consistent within uncertainties) across the use of different input data resolutions. They can hence be used as a reference for further climate-change-related studies and as a valuable basis for studying SSW impacts and links to other weather and climate phenomena, such as changes in polar-vortex dynamics and in mid-latitude extreme weather.

The Global Navigation Satellite System (GNSS) Radio Occultation (RO) retrieved temperature and specific humidity profiles can be widely used for weather and climate studies in troposphere. However, some aspects, such as the influences of background data on these retrieved moist profiles have not been discussed yet. This research evaluates RO retrieved temperature and specific humidity profiles from Wegener Center for Climate and Global Change (WEGC), Radio Occultation Meteorology Satellite Application Facility (ROM SAF) and University Corporation for Atmospheric Research (UCAR) Boulder RO processing centers by comparing with measurements from 10 selected Integrated Global Radiosonde Archive (IGRA) radiosonde stations in different latitudinal bands over 2007 to 2010. The background profiles used for producing their moist profiles are also compared with radiosonde. We found that RO retrieved temperature profiles from all centers agree well with radiosonde. Mean differences at polar, mid-latitudinal and tropical stations are varying within ±0.2 K, ±0.5 K and from −1 to 0.2 K, respectively, with standard deviations varying from 1 to 2 K for most pressure levels. The differences between RO retrieved and their background temperature profiles for WEGC are varying within ±0.5 K at altitudes above 300 hPa, and the differences for ROM SAF are within ±0.2 K, and that for UCAR are within 0.5 K at altitudes below 300 hPa. Both RO retrieved and background specific humidity above 600 hPa are found to have large positive differences (up to 40%) against most radiosonde measurements. Discrepancies of moist profiles among the three centers are overall minor at altitudes above 300 hPa for temperature and at altitudes above 700 hPa for specific humidity. Specific humidity standard deviations are largest at tropical stations in June July August months. It is expected that the outcome of this research can help readers to understand the characteristics of moist products among centers.

We introduce a new method to detect and monitor sudden stratospheric warming (SSW) events using Global Navigation Satellite System (GNSS) radio occultation (RO) data at high northern latitudes and demonstrate it for the well-known January–February 2009 event. We first construct RO temperature, density, and bending angle anomaly profiles and estimate vertical-mean anomalies in selected altitude layers. These mean anomalies are then averaged into a daily updated 5^∘ latitude × 20^∘ longitude grid over 50–90^∘ N. Based on the gridded mean anomalies, we employ the concept of threshold exceedance areas (TEAs), the geographic areas wherein the anomalies exceed predefined threshold values such as 40 K or 40 %. We estimate five basic TEAs for selected altitude layers and thresholds and use them to derive primary-, secondary-, and trailing-phase TEA metrics to detect SSWs and to monitor in particular their main-phase (primary- plus secondary-phase) evolution on a daily basis. As an initial setting, the main phase requires daily TEAs to exceed 3×10⁶ km², based on which main-phase duration, area, and overall event strength are recorded. Using the January–February 2009 SSW event for demonstration, and employing RO data plus cross-evaluation data from analysis fields of the European Centre for Medium-Range Weather Forecasts (ECMWF), we find the new approach has strong potential for detecting and monitoring SSW events. The primary-phase metric shows a strong SSW emerging on 20 January, reaching a maximum on 23 January and fading by 30 January. On 22–23 January, temperature anomalies over the middle stratosphere exceeding 40 K cover an area of more than 10×10⁶ km². The geographic tracking of the SSW showed that it was centered over east Greenland, covering Greenland entirely and extending from western Iceland to eastern Canada. The secondary- and trailing-phase metrics track the further SSW development, where the thermodynamic anomaly propagated downward and was fading with a transient upper stratospheric cooling, spanning until the end of February and beyond. Given the encouraging demonstration results, we expect the method to be very suitable for long-term monitoring of how SSW characteristics evolve under climate change and polar vortex variability, using both RO and reanalysis data.

Fengyun-3C (FY-3C) is the first Chinese satellite that is capable of using the Radio Occultation (RO) technique to retrieve atmospheric profiles. This research evaluates the quality of FY-3C RO profiles including refractivity, temperature, and specific humidity by comparing with corresponding information from the European Centre for Medium-Range Weather Forecasts (ECMWF) Interim Reanalysis (ERA-Interim) data over the period of 2015–2018. The evaluation is carried out by calculating and analyzing mean systematic differences between FY-3C and ERA-Interim profiles and corresponding standard deviations over a selected spatial and temporal domain. Results show that the FY-3C RO profiles are overall with good agreements with the ERA-Interim data. Global mean refractivity systematic differences are within ±0.2% from 5 to 30 km altitude range with relative standard deviations of less than 2%. Global temperature mean systematic differences vary within ±0.2 K from a 10- to 20-km altitude range with standard deviations of less than 2 K. Global mean specific humidity differences are found to be within ±0.2 g/kg from 2 to 20 km with standard deviations of less than 1 g/kg. FY-3C profiles show visible latitudinal and altitudinal variations, while the seasonal variations are minor. Sampling errors of refractivity and temperature are also found to be larger at higher latitudinal regions due to RO events being less sampled in the polar region.

We used Global Navigation Satellite System (GNSS) radio occultation (RO) temperature, density, and bending angle profiles to monitor tropical atmospheric anomalies during the January–February 2009 sudden stratospheric warming (SSW) event on a daily basis. We constructed RO anomaly profiles (tropical mean (30°S–30°N)) and gridded mean anomalies, as well as tropopause height and temperature anomalies. Based on the anomalies, we investigated the response time and region of the tropical atmosphere to SSW. It was found that the GNSS RO data were robust in monitoring tropical atmospheric anomalies during SSW. The tropical stratosphere revealed cooling simultaneously with polar stratospheric warming, although the magnitudes of the maximum tropical mean anomalies were 6–7 times smaller than the polar mean. Altitude variations showed that tropical stratospheric anomalies were largest within 35–40 km, which were 5 km higher than those in the polar region. On the onset day of 23 January, temperature anomalies over 0–30°N were mostly more than −5 K, which were larger than those of −2 K detected over the 0–30°S band, and the largest anomalies were detected over northern Africa with values more than −10 K. RO density and bending angle anomalies responded to SSW in a similar way as temperature but were 20 km higher. Following cooling, the tropical upper stratosphere and lower mesosphere revealed visible warming, with anomalies more than 10 K in the sector of 15°S–15°N. Tropopause anomalies revealed the largest variations over 20°N–30°N, further confirming that the extratropical region of the northern hemisphere is a key region for the dynamical coupling between the polar and tropical regions. Tropopause height anomalies had clear increase trends from 16 January to 8 February, with anomalies of the 20°N–30°N band that were −2 km on Jan 16 and increased to −0.5 km on Feb 6 with a variation of 1.5 km, while variations in other bands were within 0.5 km. Tropopause temperature anomalies had clear decrease trends over the same period, with anomalies at 20°N–30°N of 4 K on 16 January and decreasing to about −1 K on 8 February, while anomalies in other bands showed variations within 3 K.