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GPS receivers onboard low-Earth orbiting (LEO) satellites receive occulted signals from GPS satellites, which have been delayed and bent due to atmospheric refraction. The observed phase delays are converted to [...]

A newly released, novel ionospheric data set of global gridded vertical total electron content (VTEC) is introduced in this paper. This VTEC data set, provided by Los Alamos National Laboratory (LANL), is derived from very high frequency (VHF; defined as 30–300 MHz) broadband radio‐frequency (RF) measurements of lightning made by U.S. Department of Defense sensing systems on board Global Positioning System (GPS) satellites. This paper presents the new data set (LANL VTEC), discusses the errors inherent in VHF TEC estimation due to ionospheric dispersion, and compares the LANL VTEC to two community standard VTEC gridded products: Jet Propulsion Laboratory's Global Ionospheric Model (JPL GIM) and the CEDAR community's Open Madrigal VTEC gridded measurements of L‐band GNSS (global navigation satellite systems) TEC. We find that the LANL VTEC data have an offset of 3 TECU from CEDAR Madrigal GNSS VTEC and a full‐width‐half‐maximum (FWHM) of 6 TECU. In comparison, the offset between LANL VTEC and the JPL GIM model is −3 TECU, but with a FWHM of 5 TECU. We also compare to Jason‐3 VTEC measurements over the ocean, finding an offset of less than 0.5 TECU and an FWHM of <5 TECU. Because this technique uses a completely different methodology to determine TEC, the sources of errors are distinct from the typical ground‐based GNSS L‐band (GHz) TEC measurements. Also, because it is derived from RF lightning signals, this data set provides measurements in regions that are not well covered by ground‐based GPS measurements, such as over oceans and over central Africa. Plain Language Summary: The ionosphere is a region of the atmosphere that is very important in communications between ground and satellite. For that reason, decades of scientific effort have been put toward developing models of the ionosphere so that we can more accurately predict what the state of the ionosphere is at any given location and time. A general product produced by many of these models is the vertical total electron content (VTEC), which is the vertically integrated electron density at a particular location at a particular time. The majority of these models use measurements of TEC from ground‐based receivers or instruments, meaning that abundant measurements that go into the models often lack data from over the oceans or in technologically limited regions of the world (e.g., Africa). Here, we present a new VTEC data set that is derived from lightning strokes detected with U.S. Department of Defense sensing systems on GPS satellites. Because the data set uses naturally occurring lightning for its source, it does not have the same limitations as ground‐based TEC measurements and can provide an additional source of validation data for ionospheric models. We introduce the data set and compare it with community‐accepted VTEC models and measurements. Key Points: New global gridded vertical total electron content (VTEC) data set derived from radio‐frequency measurements from lightning emissions during the entire year of 2018 has been releasedVTEC product adds new global coverage in areas with few global navigation satellite systems receivers (ocean and continental Africa)The VTEC values, generated from very high frequency radio‐frequency data, show bias in Madrigral data set and differences to Jet propulsion laboratory's global ionospheric model model‐derived VTEC [ABSTRACT FROM AUTHOR]

In the upper troposphere (UT), Global Navigation Satellite System (GNSS) Radio Occultations (ROs) provide accurate air temperatures (<0.5 K) every ∼200 m vertically. We use RO observations from 01/2002 until 12/2018 at 300, 250, and 200 hPa to quantify the tropical upper tropospheric amplification (defined as the ratio of temperature trends in the UT relative to the surface). We compare the RO‐derived results against Atmospheric Infrared Sounder (AIRS), Coupled Model Intercomparison Project Phase 6 (CMIP6) Atmospheric Model Intercomparison Project (AMIP) models, Modern‐Era Retrospective Analysis for Research and Applications version 2 (MERRA‐2), and European Center for Medium‐range Weather Forecasts Re‐Analysis Interim (ERA‐Interim) data. We find that CMIP6 AMIP models show excellent agreement with independent AIRS and RO observations on the magnitude of the UT warming and show warming that is significantly faster than both reanalyses above 250 hPa. Additionally, AIRS and CMIP6 AMIP present excellent agreement with the RO‐measured tropical tropospheric amplification. Plain Language Summary: In the upper troposphere, Global Navigation Satellite System Radio Occultations (GNSS‐RO) measure the air's refractive index, which depends primarily on the air's temperature. We use these GNSS‐RO temperatures from 01/2002 until 12/2018 at 200, 250, and 300 hPa in the tropics (where the atmosphere experiences the largest amplification in response to surface warming). Routinely, climate models are used to simulate how much the upper atmosphere has warmed in response to surface warming. However, there appears to be a disagreement between observations and models, which today we try to understand. The GNSS‐RO observations have a unique feature of being able to measure the air temperature every 200 m, and show us that that climate models are in close agreement with the GNSS‐RO and other infrared observations. In other words, GNSS‐RO observations show that the upper atmosphere warms faster and the amplification due to surface warming is stronger than what current reanalysis estimate. Independent infrared observations of the Earth's upper troposphere also support the GNSS‐RO findings and are also in very close agreement with the climate models. Interestingly, the reanalysis indicates that at 200 hPa there is no warming observed, contrary to what GNSS‐RO, infrared, and climate models reveal. Key points: Coupled model intercomparison project phase 6 (cmip6) atmospheric model intercomparison project (AMIP) models agree with independent radio occultation and infrared data on the magnitude of the tropical upper tropospheric temperature trendsRadio occultations reveal faster tropical upper tropospheric warming than both modern‐era retrospective analysis for research and applications version 2 (MERRA‐2) and European Center for Medium‐Range Weather Forecasts Re‐Analysis Interim (ERA‐Interim) (above 250 hPa) reanalysesERA‐Interim presents decreasing tropical upper troposphere amplification with altitude, unlike the amplification shown by radio occultations [ABSTRACT FROM AUTHOR]

Launched in 2006, the Formosa Satellite Mission 3-Constellation Observing System for Meteorology, Ionosphere and Climate (FORMOSAT-3/COSMIC) was the first constellation of microsatellites carrying global positioning system (GPS) radio occultation (RO) receivers. Radio occultation is an active remote sensing technique that provides valuable information on the vertical variations of electron density in the ionosphere, and temperature, pressure, and water vapor in the stratosphere and troposphere. COSMIC has demonstrated the great value of RO data in ionosphere, climate, and meteorological research and operational weather forecasting. However, there are still challenges using RO data, particularly in the moist lower troposphere and upper stratosphere. A COSMIC follow-on constellation, COSMIC-2, was launched into equatorial orbit in 2019. With increased signal-to-noise ratio (SNR) from improved receivers and digital beam steering antennas, COSMIC-2 will produce at least 5,000 high-quality RO profiles daily in the tropics and subtropics. In this paper, we summarize 1) recent (since 2011 when the last review was published) contributions of COSMIC and other RO observations to weather, climate, and space weather science; 2) the remaining challenges in RO applications; and 3) potential contributions to research and operations of COSMIC-2. [ABSTRACT FROM AUTHOR]

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 < 0.05 K per decade in the global mean and < 0.1 K per decade at all latitudes. Above 25 km, the uncertainty increases for CHAMP, while data from the other missions – based on advanced receivers – are usable to higher altitudes for climate trend studies: dry temperature to 35 km, refractivity to 40 km, and bending angle to 50 km. Larger differences in RO data at high altitudes and latitudes are mainly due to different implementation choices in the retrievals. The intercomparison helped to further enhance the maturity of the RO record and confirms the climate quality of multi-satellite RO observations towards establishing a GCOS climate data record. [ABSTRACT FROM AUTHOR]

Atmospheric climate monitoring requires observations of high-quality conforming 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 means. Structural uncertainty in trends is found lowest from 8 km to 25 km altitude globally for all inspected RO variables and missions. For temperature, it is < 0.05 K per decade in the global mean and < 0.1 K per decade at all latitudes. Above 25 km, the uncertainty increases for CHAMP while data from the other missions are based on advanced receivers and are usable to higher altitudes for climate trend studies: dry temperature to 35 km, refractivity to 40 km, and bending angle to 50 km. Larger differences in RO data at high altitudes and latitudes are mainly due to different implementation choices in the retrievals. The intercomparison helped to further enhance the maturity of the RO record and confirms the climate quality of multi-satellite RO observations towards establishing a GCOS climate data record. [ABSTRACT FROM AUTHOR]

As societal dependence on transionospheric radio signals grows, space weather impact on these signals becomes increasingly important yet our understanding of the effects remains inadequate. This challenge is particularly acute at high latitudes where the effects of space weather are most direct and no reliable predictive capability exists. We take advantage of a large volume of data from Global Navigation Satellite Systems (GNSS) signals, increasingly sophisticated tools for data‐driven discovery, and a machine learning algorithm known as the support vector machine (SVM) to develop a novel predictive model for high‐latitude ionospheric phase scintillation. This work, to our knowledge, represents the first time an SVM model has been created to predict high‐latitude phase scintillation. We use the true skill score to evaluate the SVM model and to establish a benchmark for high‐latitude ionospheric phase scintillation prediction. The SVM model significantly outperforms persistence (i.e., current and future scintillation are identical), doubling the predictive skill according to the true skill score for a 1‐hr lead time. For a 3‐hr lead time, persistence is comparable to a random chance prediction, suggesting that the memory of the ionosphere in terms of high‐latitude plasma irregularities is on the order of, or shorter than, a few hours. The SVM model predictive skill only slightly decreases between the 1‐ and 3‐hr predictive tasks, pointing to the potential of this method. Our findings can serve as a foundation on which to evaluate future predictive models, a critical development toward the resolution of space weather impact on transionospheric radio signals. Plain Language Summary: Society is increasingly dependent on radio signals, particularly those from the Global Navigation Satellite Systems (GNSS), and the technologies (e.g., navigation and financial transactions) that they enable. The integrity and reliability of these signals is threatened by their travel from the GNSS satellites to the ground, which includes passage through a charged region between 100 and 1,000 km known as the ionosphere. Disturbances to the ionosphere from solar energy, or space weather, cause variations in GNSS signals that adversely affect the dependent systems and technologies. Currently, the effect of the ionosphere on these signals cannot be reliably predicted, and the challenge is particularly important at latitudes above 45° where space weather impacts are most direct. We have compiled a large volume of data from the regions important to space weather (i.e., from the Sun to the Earth) to develop a novel machine learning model capable of skillfully predicting disruptions to GNSS signals at high latitudes. To our knowledge, this model is the first of its kind. We find that the new model is capable of more accurate predictions than current methods and position this model as a benchmark on which future predictive models can be measured. Key Points: Support vector machine yields predictive performance roughly double that of persistence; the benefit increases with longer prediction timesElectron precipitation information is critical to the prediction of high‐latitude phase scintillationA benchmark is established for high‐latitude ionospheric phase scintillation using the robust true skill score (TSS) metric [ABSTRACT FROM AUTHOR]

To numerically simulate earthquake‐induced ionospheric disturbances, we extend the Wave Perturbation‐Global Ionosphere‐Thermosphere Model, which was originally developed for tsunami‐ionosphere coupling via gravity waves, to the case of earthquake‐ionosphere coupling via acoustic‐gravity waves. The new Wave Perturbation‐Global Ionosphere‐Thermosphere Model represents epicentral crustal movements by a point source specified with the ground motion data from seismic measurements. The model then solves for the neutral atmospheric perturbations generated by spherical acoustic‐gravity waves and the resulting ionospheric plasma perturbations over the epicentral area. We apply the model to simulate the near‐field ionospheric disturbances during two major earthquake events: the 2011 Tohoku‐Oki, Japan, and the 2015 Illapel, Chile, events. To validate the results, we extract receiver‐to‐satellite total electron content perturbations from the simulations and compare them to the corresponding slant total electron content perturbations from Global Positioning System observations. We find good agreement on magnitudes and arrival times between the simulations and observations. Key Points: We have developed a novel earthquake‐ionosphere coupling model based on a state‐of‐the‐art upper atmospheric modelThe model is capable of simulating ionospheric signatures induced by epicentral crustal movementsModel validation with two earthquake events shows reasonable agreement with observations [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

We construct a 9-year data record (2007-2015) of the tropospheric specific humidity (SH) 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 SH from 700 hPa 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°). Our objective is to compare the RO observations with the European Center 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) to examine the consistency among the data sets. We present RO SHs from both JPL and UCAR processing centers to provide an estimate of the structural uncertainty of the RO SH products. The results show that the RO observations capture the seasonal and interannual SH variability as all other data sets. On average, the JPL-RO SH agrees with both reanalyses to within 10 %, is overall larger than all data sets, having maximum differences with AIRS by ~ 10-30 %, and is almost twice as wet as all other data sets in the middle-to-upper troposphere at the subtropics. The UCAR-RO SH also agrees with both reanalyses and AIRS, but is systematically drier than all other data sets. Provided the estimated differences between the RO observations and the rest of the data sets, together with the retrieval uncertainty of the SH products from all data sets, we conclude that RO observations are a valuable independent observing system, which could augment independent reanalyses and satellite platforms. We anticipate that the COSMIC-2 mission will increase the observational sampling; thus, improving the coverage and quality of the observed SH climatology. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

Global Positioning System (GPS) radio occultation (RO) has provided continuous observations of the Earth's atmosphere since 2001 with global coverage, all-weather capability, and high accuracy and vertical resolution in the upper troposphere and lower stratosphere (UTLS). Precise time measurements enable long-term stability but careful processing is needed. Here we provide climate-oriented atmospheric scientists with multicenter-based results on the long-term stability of RO climatological fields for trend studies. We quantify the structural uncertainty of atmospheric trends estimated from the RO record, which arises from current processing schemes of six international RO processing centers, DMI Copenhagen, EUM Darmstadt, GFZ Potsdam, JPL Pasadena, UCAR Boulder, and WEGC Graz. Monthlymean zonal-mean fields of bending angle, refractivity, dry pressure, dry geopotential height, and dry temperature from the CHAMP mission are compared for September 2001 to September 2008.We find that structural uncertainty is lowest in the tropics and mid-latitudes (50° S to 50° N) from 8 km to 25 km for all inspected RO variables. In this region, the structural uncertainty in trends over 7 yr is <0.03%for bending angle, refractivity, and pressure, <3m for geopotential height of pressure levels, and <0.06K for temperature; low enough for detecting a climate change signal within about a decade. Larger structural uncertainty above about 25 km and at high latitudes is attributable to differences in the processing schemes, which undergo continuous improvements. Though current use of RO for reliable climate trend assessment is bound to 50° S to 50° N, our results show that quality, consistency, and reproducibility are favorable in the UTLS for the establishment of a climate benchmark record. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

Abstract: In the coming years, opportunities for remote sensing of electron density in the Earth’s ionosphere will expand with the advent of Galileo, which will become part of the global navigation satellite system (GNSS). Methods for accurate electron density retrieval from radio occultation data continue to improve. We describe a new method of electron density retrieval using total electron content measurements obtained in low Earth orbit. This method can be applied to data from dual-frequency receivers tracking the GPS or Galileo transmitters. This simulation study demonstrates that the method significantly improves retrieval accuracy compared to the standard Abel inversion approach that assumes a spherically symmetric ionosphere. Our method incorporates horizontal gradient information available from global maps of Total Electron Content (TEC), which are available from the International GNSS Service (IGS) on a routine basis. The combination of ground and space measurements allows us to improve the accuracy of electron density profiles near the occultation tangent point in the E and F regions of the ionosphere. [Copyright &y& Elsevier]

The four-dimensional Global Assimilative Ionospheric Model (GAIM) is applied to a study of ionospheric disturbances. The investigation is focused on disturbance features, particularly in the altitude and latitude dimensions, at low latitudes during a geomagnetic storm on 7 August 2006, under solar minimum conditions. The modeling of storm-time ionospheric state (electron density) is conducted by assimilating an unprecedented volume of line-of-sight TEC data collected by the Global Positioning System (GPS) occultation receivers on board six FORMOSAT-3/COSMIC satellites and geodetic-quality GPS receivers at two hundred globally-distributed ground tracking stations. With a band-limited Kalman filter technique to update the ionospheric state, the assimilative modeling reveals a pronounced enhancement in the equatorial anomaly in the East Asia sector during dusk and evening hours. The disturbance characteristics, obtained by comparing with the quiet conditions prior to the storm also modeled in this study through data assimilation, include lifted F layer and reduced electron density in the equatorial region, enhanced density at the magnetically conjugate anomaly latitudes, and tilted feature of density increase towards higher altitudes at lower latitudes. The characteristics are attributed to the enhanced plasma fountain effect driven by an enhanced eastward zonal electric field. These results enable us to distinguish the storm-time electric field perturbations clearly from other sources during the storm. The possible origins of electric field perturbations are also discussed, including penetration of the magnetospheric electric field and wind dynamo disturbances. [ABSTRACT FROM AUTHOR]