Water Vapor Profiles Research Articles

Relationships Between HCl, H2O, Aerosols, and Temperature in the Martian Atmosphere: 2. Quantitative Correlations

AbstractThe detection of hydrogen chloride (HCl) in the atmosphere of Mars was among the primary objectives of the ExoMars Trace Gas Orbiter (TGO) mission. Its discovery using the Atmospheric Chemistry Suite mid‐infrared channel (ACS MIR) showed a distinct seasonality and possible link to dust activity. This paper is part 2 of a study investigating the link between HCl and aerosols by comparing gas measurements made with TGO to dust and water ice opacities measured with the Mars Climate Sounder (MCS). In part 1, we showed, and compared, the seasonal evolution of vertical profiles of HCl, water vapor, temperature, dust opacity, and water ice opacity over the dusty periods around perihelion (solar longitudes 180°–360°) across Mars years 34–36. In part 2, we investigated the quantitative correlations in the vertical distribution between each quantity, as well as ozone. We show that there is a strong positive correlation between HCl and water vapor, which is expected due to fast photochemical production rates for HCl when reacting with water vapor photolysis products. We also show a strong positive correlation between water vapor and temperature, but are unable to show any correlation between temperature and HCl. There are weak correlations between the opacities of dust and water ice, and dust and water vapor, but only very low correlations between dust and HCl. We close with a discussion of possible sources and sinks and that interactions between HCl and water ice are the most likely for both, given the inter‐comparison.

Sensitivity analysis of space-based water vapor differential absorption lidar at 823 nm

Measurements of water vapor are important for understanding the hydrological cycle, the thermodynamic structure of the lower troposphere, and broader atmospheric circulation. Subsequently, many scientific communities have emphasized a need for high-accuracy and spatial resolution profiles of water vapor within and above the planetary boundary layer (PBL). Advancements in lidar technologies at the NASA Langley Research Center are ongoing to enable the first space-based water vapor differential absorption lidar (DIAL) that can provide high-accuracy and vertical resolution retrievals of moisture in the PBL and through the mid-troposphere. The performance of this space-based DIAL is assessed here for sensitivity throughout the troposphere and globally with representative canonical cases of water vapor and aerosol loading. The specific humidity retrieval sensitivity to systematic and random errors is assessed, and measurement resolutions and capabilities are provided. We show that tunable operation along the side of the 823-nm absorption line allows for the optimization of the lower-tropospheric water vapor retrievals across different meteorological regimes and latitudes and provides the operational flexibility needed to dynamically optimize random errors for different scientific applications. The analysis presented here suggests that baseline and threshold systematic error requirements of <1.5% and <2.5%, respectively, are achievable. Random error is shown to dominate the retrieval, with errors on the order of 5% within the PBL being achievable with 300-m vertical 50-km horizontal resolutions over open ocean and on the order of 10%–15% over high-albedo surfaces. The flexibility of the DIAL method to trade retrieval precision for spatial resolution is shown, highlighting its strengths over passive techniques to tailor retrievals to different scientific applications. Combined, the total error budget demonstrated here indicates a high impact for space-based DIAL, with technologies being advanced for space missions within the next 5–10 years.

Sensitivity of thermodynamic profiles retrieved from ground-based microwave and infrared observations to additional input data from active remote sensing instruments and numerical weather prediction models

Abstract. Accurate and continuous estimates of the thermodynamic structure of the lower atmosphere are highly beneficial to meteorological process understanding and its applications, such as weather forecasting. In this study, the Tropospheric Remotely Observed Profiling via Optimal Estimation (TROPoe) physical retrieval is used to retrieve temperature and humidity profiles from various combinations of input data collected by passive and active remote sensing instruments, in situ surface platforms, and numerical weather prediction models. Among the employed instruments are microwave radiometers (MWRs), infrared spectrometers (IRSs), radio acoustic sounding systems (RASSs), ceilometers, and surface sensors. TROPoe uses brightness temperatures and/or radiances from MWRs and IRSs, as well as other observational inputs (virtual temperature from the RASS, cloud-base height from the ceilometer, pressure, temperature, and humidity from the surface sensors) in a physical iterative retrieval approach. This starts from a climatologically reasonable profile of temperature and water vapor, with the radiative transfer model iteratively adjusting the assumed temperature and humidity profiles until the derived brightness temperatures and radiances match those observed by the MWR and/or IRS instruments within a specified uncertainty, as well as within the uncertainties of the other observations, if used as input. In this study, due to the uniqueness of the dataset that includes all the abovementioned sensors, TROPoe is tested with different observational input combinations, some of which also include information higher than 4 km above ground level (a.g.l.) from the operational Rapid Refresh numerical weather prediction model. These temperature and humidity retrievals are assessed against independent collocated radiosonde profiles under non-cloudy conditions to assess the sensitivity of the TROPoe retrievals to different input combinations.

Mesoscale and Large-Eddy Simulation of the Boundary Layer Process of Cumulus Development over Naqu, Tibetan Plateau Part A: Comparison Between Simulation and Observation

Cumulus clouds are of great interest in numerical weather prediction. However, the scarcity of observed data on the Tibetan Plateau (TP) has not allowed a correct interpretation of their development. The Third TP Atmospheric Science Experiment provided experimental data to address this challenge. The objective of this study was to ascertain the effective utilization of observation-nudging techniques for the implementation of combined weather research and forecasting large-eddy simulation (WRF-LES) for further experimental designs. This study simulated cumulus clouds over southern TP on July 19, 2014, using the WRF-LES model and final reanalysis data from the Global Forecast System. We applied observation nudging and one-way nesting strategies to influence the optimality of WRF-LES runs. The study performed simulations with six different scenarios in comparison with observational data. The findings demonstrated that, despite being locally initiated and growing upscale, cumulus clouds were nonetheless subject to large-scale forcing. Simulations with observation nudging produced more accurate and trustworthy results than simulations without nudging when compared to observations. While the observed time series were misleading, LES with mesoscale forcing produced a microphysical evolution that was consistent with the observations and an accurate water vapor profile. Without mesoscale forcing, LES provided the best ABL water vapor and sensible heat flux; however, it failed to provide a good microphysics field. In this aspect, large-scale forcing played an important role in cumulus development during the model experiment. The study recommended focusing on the model's response to the boundary conditions to improve the application of one-way nesting in separate iterations and observational nudging techniques

The investigation of retrieval method for aerosol and water vapor profiles based on MAX-DOAS technology

Simultaneously obtaining the vertical distribution and profile of aerosol and water vapor is crucial for in-depth understanding of the Earth's radiation balance, regional water cycle, and the causes of frequent haze weather in China. This study developed a system and inversion method based on multi-axis differential optical absorption spectroscopy (MAX-DOAS) to simultaneously retrieve tropospheric aerosol and water vapor profiles. The absorption of dioxy (O4) was obtained by multi-elevation measurement using the developed ground-based MAX-DOAS system. By minimizing a cost function combining an atmospheric radiative transfer model, aerosol extinction profiles were first inverted, followed by water vapor profiles. Optimized parameter selection in the look-up table method reduced reliance on prior profile information, enhancing pollutant distribution retrieval accuracy. In the monitoring period in Huaibei region, aerosols were mainly below 1.5 km, while water vapor concentrations decreased with altitude. Comparisons of water vapor vertical column densities (VCDs) retrieved through the look-up table method with the European Centre for Medium-Range Weather Forecasts(ECMWF) ERA5 model and geometric approximation showed good agreement, with correlation coefficients of 0.93 and 0.98, respectively. To comprehend water vapor sources at various vertical layers, a 24-h backward trajectory clustering analysis was conducted using the HYSPLIT model based on observed wind fields. Findings revealed that at 500 m altitude, water vapor primarily emanated from the southeast, whereas at 1 km and 2 km altitudes, it predominantly originated from the southwest. The study advances simultaneous tropospheric aerosol and water vapor profile retrieval, providing reliable technical support for the investigation of regional pollution.

Characterization of Surface Spectral Emissivity Retrieved from EE9-FORUM Simulated Measurements

FORUM (Far-infrared Outgoing Radiation Understanding and Monitoring) has been approved to be the ninth Earth Explorer mission of the European Space Agency and is scheduled for launch in 2027. The core FORUM instrument is a Fourier transform spectrometer, which will, for the first time, measure the upwelling spectral radiance in the far-infrared (FIR) and mid-infrared (MIR) portions of the Earth’s spectrum. These radiances will be processed up to level 2, to determine mainly the vertical profile of water vapor, surface spectral emissivity, and cloud parameters. In this paper, we assess the performance of the FORUM surface spectral emissivity product based on all-sky sensitivity study. In the FIR, we find that the retrieval error is mainly driven by the precipitable water vapor (PWV) in clear-sky conditions. In dry atmospheres, FIR emissivity can be retrieved with an error less than 0.01. In cloudy conditions, small errors can be achieved for optically thin clouds, especially for small values of the PWV. In the MIR, we observe that a large thermal contrast between the surface and the lowest atmospheric layers increases the sensitivity of the measurements to the surface emissivity in clear-sky conditions and an emissivity retrieval error less than 0.01 can usually be achieved. In cloudy conditions, small errors can be achieved for optically thin clouds, especially for large values of the surface temperature. Applying a coarser retrieval grid further reduces retrieval error, at the expense of an increased emissivity smoothing error.

Water vapor measurements inside clouds and storms using a differential absorption radar

Abstract. NASA's Vapor In-cloud Profiling Radar (VIPR) is a tunable G-band radar designed for in-cloud and precipitation humidity remote sensing. VIPR estimates humidity using the differential absorption radar (DAR) technique. This technique exploits the difference between atmospheric attenuation at different frequencies (“on” and “off” an absorption line) and combines it with the ranging capabilities of the radar to estimate the absorbing gas concentration along the radar path. We analyze the VIPR humidity measurements during two NASA field campaigns: (1) the Investigation of Microphysics and Precipitation for Atlantic Coast-Threatening Snowstorms (IMPACTS) campaign, with the objective of studying wintertime snowstorms focusing on east coast cyclones; and (2) the Synergies Of Active optical and Active microwave Remote Sensing Experiment (SOA2RSE) campaign, which studied the synergy between DAR (VIPR) and differential absorption lidar (DIAL, the High altitude Lidar Observatory – HALO) measurements. We discuss a comparison with dropsondes launched during these campaigns as well as an intercomparison against the ERA5 reanalysis fields. Thus, this study serves as an additional evaluation of ERA5 lower tropospheric humidity fields. Overall, in-cloud and in-snowstorm comparisons suggest that ERA5 and VIPR agree within 20 % or better against the dropsondes. The exception is during SOA2RSE (i.e., in fair weather), where ERA5 exhibits up to a 50 % underestimation above 4 km. We also show a smooth transition in water vapor profiles between the in-cloud and clear-sky measurements obtained from VIPR and HALO respectively, which highlights the complementary nature of these two measurement techniques for future airborne and space-based missions.

On the use of routine airborne observations for evaluation and monitoring of satellite observations of thermodynamic profiles

Abstract. Satellite-based observations require independent sources of data to monitor and evaluate their precision and accuracy. For the temperature and water vapor profiles produced by satellite-based sounders, this typically results in comparisons to operational radiosonde observations. However, polar-orbiting satellite overpasses are frequently misaligned with the global synoptic launch times. The routine airborne in situ observations of temperature and water vapor from the Airborne Meteorological Data Relay (AMDAR) program and the Water Vapor Sensing System-II (WVSS-II) instrument greatly enhance opportunities to make precise matchups due to the far greater temporal frequency and spatial density of aircraft flights. The potential for the use of aircraft-based observations as a source of evaluation of tropospheric satellite sounder profiles is explored through a year-long intercomparison with the Infrared Atmospheric Sounding Interferometer (IASI) level-2 profiles produced from both the Metop-A and Metop-B satellites. Results using 1 h and 50 km match criteria indicating good agreement between the satellites and the aircraft-based observations with temperature, specific humidity, and relative humidity biases generally less than 0.5 K, 0.8 g kg−1, and 5 %, respectively; both IASI instruments perform nearly identically. While the intercomparisons are generally limited to the troposphere as aircraft typically reach their maximum height at the tropopause, the substantially larger number of intercomparison points enable characterization as a function of season, scan angle, and other characteristics heretofore unexplored due to a lack of sufficient validation data.

A review of atmospheric water vapor lidar calibration methods

AbstractAtmospheric water vapor is a crucial factor in the Earth's water cycle. As an important greenhouse gas, changes in the spatio‐temporal distribution of atmospheric water vapor can contribute to the occurrence of various extreme weather phenomena. Lidar, with its high spatial and temporal resolutions, has great potential for applications in water vapor profile detection. Raman lidar and differential absorption lidar (DIAL) have been successfully used to detect atmospheric water vapor. System calibration is crucial to ensure that the measured profile accurately represents the concentration profile of atmospheric water vapor. Choosing an effective system calibration method can ensure the accuracy of long‐term lidar measurements. This paper reviews the latest progress and applications of atmospheric water vapor lidar calibration in recent years. The basic principles of Raman lidar and DIAL calibration are introduced. Various methods and benefits of system calibration are discussed. Raman lidar has three commonly used calibration methods: external calibration, internal calibration, and hybrid calibration methods. The most commonly used method is external calibration based on radiosondes. DIAL is usually implemented with an advantageous self‐calibration method. Finally, potential development directions for atmospheric water vapor lidar and calibration technology are discussed.This article is categorized under: Science of Water > Methods Engineering Water > Methods Human Water > Value of Water

Troposphere Sensing Using Grazing‐Angle GNSS‐R Measurement From LEO Satellites

AbstractThis paper studies a new concept of using global navigation satellite system (GNSS) signals coherently reflected over relatively smooth ocean and ice surfaces from very low elevation angles (below ∼8°) and received by low Earth orbit (LEO) satellites to retrieve the tropospheric information. This approach can provide horizontal profiles of tropospheric zenith delay and total column water vapor (TCWV) with centimeter‐level high precision and spatial resolutions of tens of km by ∼1 km, depending on the elevation angle, with a sampling spacing of ∼100 m. This approach can potentially be applied to most sea ice and calm ocean areas and provide tropospheric sensing data, which can complement and augment existing observation systems. A few case studies are conducted in this paper using the Spire grazing‐angle GNSS‐R data. The retrieved TCWV is compared to ERA5 products and the Sentinel‐3 Ocean and Land Color Instrument measurements and shows promising performances. The errors associated with the GNSS‐R tropospheric measurements are also discussed.

Structure-function relationships in the nasal cavity of Arctic and subtropical seals

The heating and moistening of inhaled air, and the cooling and moisture removal from exhaled air, are crucial for the survival of animals under severe environmental conditions. Arctic mammals have evolved specific adaptive mechanisms to retain warmth and water and restrict heat loss during breathing. Here, the role of the porous turbinates of the nasal cavities of Arctic and subtropical seals is studied with this in mind. Mass and energy balance equations are used to compute the time-dependent temperature and water vapor profiles along the nasal passage. A quasi-1D model based on computed tomography images of seal nasal cavities is used in numerical simulations. Measured cross-sectional areas of the air channel and the perimeters of the computed tomography slices along the nasal cavities of the two seal species are used. The model includes coupled heat and vapor transfer at the air-mucus interface and heat transfer at the interfaces between the tissues and blood vessels. The model, which assumes constant blood flow to the nose, can be used to predict the temperature of the exhaled air as a function of ambient temperature. The energy dissipation (entropy production) in the nasal passages was used to measure the relative importance of structural parameters for heat and water recovery. We found that an increase in perimeter led to significant decreases in the total energy dissipation. This is explained by improved conditions for heat and water transfer with a larger complexity of turbinates. Owing to differences in their nasal cavity morphology, the Arctic seal is expected to be advantaged in these respects relative to the subtropical seal.

The Sun and the Troposphere Control the Earth’s Temperature

The basis for this study is the flow of energy from the Troposphere to space and the role that water vapor and carbon dioxide (CO2) play in affecting the flow. Then, it analyzes the radiation profiles and compares them to the ratio of water molecules to CO2 molecules. Examining the radiation profiles of water vapor and CO2 showed the overlap made it virtually impossible to separate the warming effects. Calculating the ratio of water vapor molecules to CO2 molecules by proven physics and chemistry is accurate for separating the individual warming effects. The results of a quantitative examination show water vapor has 1,000 to 7,000 times more impact on the Earth's temperature than CO2. The warming effect of CO2 versus concentration is linear. In contrast, the warming effect of water vapor versus concentration is curved. The lowest level of the atmosphere, the Troposphere, has most of the air mass and water vapor and exercises control over the Earth's temperature. Energy leaving the Troposphere flows virtually unhindered to space. The Sun is Earth's primary energy source, and its natural variations control its temperature.

Optimizing Boundary Conditions in GNSS Tomography: A Continuous 7‐Month Case Study in the Amazon

AbstractDifferent estimates of the regional water vapor scale height, taken from ERA5 reanalysis, in situ observations and the direct optimization of retrieved water vapor profiles in GNSS tomography, are found to have major impact in the performance of tomographic inversions, with the better results displaying mean errors comparable to radiosondes. The analysis uses 7 months of GNSS (Global Navigation Satellite Systems) observations in the Amazon Dense GNSS Network near Manaus, Brazil, in 2011–2012, to compute a time series of water vapor profiles, with a tomographic technique capable of producing quasi‐instantaneous inversions with minimal external data or constraints. Results compare very well with 12‐hourly in situ radiosondes, especially in the lower troposphere above 2 km, and its daily‐to‐seasonal variability compares well with WRF (Weather Research and Forecasting) convective‐permitting simulations driven by ERA5 boundary conditions, suggesting that GNSS tomography may be an important source of atmospheric water vapor data for different applications.

Atmospheric Thermodynamic Profiling through the Use of a Micro-Pulse Raman Lidar System: Introducing the Compact Raman Lidar MARCO.

It was for a long time believed that lidar systems based on the use of high-repetition micro-pulse lasers could be effectively used to only stimulate atmospheric elastic backscatter echoes, and thus were only exploited in elastic backscatter lidar systems. Their application to stimulate rotational and roto-vibrational Raman echoes, and consequently, their exploitation in atmospheric thermodynamic profiling, was considered not feasible based on the technical specifications possessed by these laser sources until a few years ago. However, recent technological advances in the design and development of micro-pulse lasers, presently achieving high UV average powers (1-5 W) and small divergences (0.3-0.5 mrad), in combination with the use of large aperture telescopes (0.3-0.4 m diameter primary mirrors), allow one to presently develop micro-pulse laser-based Raman lidars capable of measuring the vertical profiles of atmospheric thermodynamic parameters, namely water vapor and temperature, both in the daytime and night-time. This paper is aimed at demonstrating the feasibility of these measurements and at illustrating and discussing the high achievable performance level, with a specific focus on water vapor profile measurements. The technical solutions identified in the design of the lidar system and their technological implementation within the experimental setup of the lidar prototype are also carefully illustrated and discussed.

Using the Commercial GNSS RO Spire Data in the Neutral Atmosphere for Climate and Weather Prediction Studies

Recently, the NOAA has included GNSS (Global Navigation Satellite System) Radio Occultation (RO) data as one of the crucial long-term observables for weather and climate applications. To include more GNSS RO data in its numerical weather prediction systems, the NOAA Commercial Weather Data Pilot program (CWDP) started to explore the commercial RO data available on the market. After two rounds of pilot studies, the CWDP decided to award the first Indefinite Delivery Indefinite Quantity (IDIQ) contract to GeoOptics and Spire Incs. in 2020. This study examines the quality of Spire RO data products for weather and climate applications. Spire RO data collected from commercial CubeSats are carefully compared with data from Formosa Satellite Mission 7–Constellation Observing System for Meteorology, Ionosphere, and Climate-2 (COSMIC-2), the fifth-generation European Centre for Medium-Range Weather Forecasts (ECMWF) atmospheric reanalysis (ERA5), and high-quality radiosonde data. The results demonstrate that, despite their generally lower Signal-Noise-Ratio (SNR), Spire RO data show a pattern of lowest penetration height similar to that of COSMIC-2. The Spire and COSMIC-2 penetration heights are between 0.6 and 0.8 km altitude over tropical oceans. Although using different GNSS RO receivers, the precision of Spire STRATOS receivers is of the same quality as those of the COSMIC-2 TriG (Global Positioning System—GPS, GALILEO, and GLObal NAvigation Satellite System—GLONASS) RO Receiver System (TGRS) receivers. Furthermore, the Spire and COSMIC-2 retrieval accuracies are quite comparable. We validate the Spire temperature and water vapor profiles by comparing them with collocated radiosonde observation (RAOB) data. Generally, over the height region between 8 km and 16.5 km, the Spire temperature profiles match those from RS41 RAOB very well, with temperature biases of <0.02 K. Over the height range from 17.8 to 26.4 km, the temperature differences are ~−0.034 K, with RS41 RAOB being warmer. We also estimate the error covariance matrix for Spire, COSMIC-2, and KOMPSAT-5. The results show that the COSMIC-2 estimated error covariance values are slightly more significant than those from Spire over the oceans at the mid-latitudes (45°N–30°N and 30°S–45°S), which may be owing to COSMIC-2 SNR being relatively lower at those latitudinal zones.

Radiance Simulations in Support of Climate Services

AbstractClimate services are largely supported by climate reanalyses and by satellite Fundamental (Climate) Data Records (F(C)DRs). This paper demonstrates how the development and the uptake of F(C)DR benefit from radiance simulations, using reanalyses and radiative transfer models. We identify three classes of applications, with examples for each application class. The first application is to validate assumptions during F(C)DR development. Hereto we show the value of applying advanced quality controls to geostationary European (Meteosat) images. We also show the value of a cloud mask to study the spatio‐temporal coherence of the impact of the Mount Pinatubo volcanic eruption between Advanced Very High Resolution Radiometer (AVHRR) and the High‐resolution Infrared Radiation Sounder (HIRS) data. The second application is to assess the coherence between reanalyses and observations. Hereto we show the capability of reanalyses to reconstruct spectra observed by the Spektrometer Interferometer (SI‐1) flown on a Soviet satellite in 1979. We also present a first attempt to estimate the random uncertainties from this instrument. Finally, we investigate how advanced bias correction can help to improve the coherence between reanalysis and Nimbus‐3 Medium‐Resolution Infrared Radiometer (MRIR) in 1969. The third application is to inform F(C)DR users about particular quality aspects. We show how simulations can help to make a better‐informed use of the corresponding F(C)DR, taking as examples the Nimbus‐7 Scanning Multichannel Microwave Radiometer (SMMR), the Meteosat Second Generation (MSG) imager, and the Defense Meteorological Satellite Program (DMSP) Special Sensor Microwave Water Vapor Profiler (SSM/T‐2).

Retrieval of temperature and humidity profiles from ground-based high-resolution infrared observations using an adaptive fast iterative algorithm

Abstract. Various retrieval algorithms have been developed for retrieving temperature and water vapor profiles from Atmospheric Emitted Radiance Interferometer (AERI) observations. The physical retrieval algorithm, named AERI Optimal Estimation (AERIoe), outperforms other retrieval algorithms in many aspects except the retrieval time, which is significantly increased due to the complex radiative transfer process. The calculation of the Jacobian matrix is the most computationally intensive step of the physical retrieval algorithm. Interestingly, an analysis of the change in AERI observations' information content with respect to Jacobians revealed that the AERIoe algorithm's performance presents negligible dependence on these metrics. Thus, the Jacobian matrix could remain unchanged when the variation in the atmospheric state is small in the retrieval process to reduce the most time-consuming computation. On the basis of the above findings, a fast physical–iterative retrieval algorithm was proposed by adaptively recalculating Jacobians in keeping with the changes in the atmospheric state. Experiments with synthetic observations demonstrate that the proposed method experiences an average reduction in retrieval time by an impressive 59 % compared to the original AERIoe algorithm while achieving maximum root-mean-square errors of less than 0.95 K and 0.22 log(ppmv) for heights below 3 km for the temperature and water vapor profile, respectively. Further analyses revealed that the fast-retrieval algorithm reached an acceptable convergence rate of 98.7 %, marginally lower than AERIoe's 99.9 % convergence rate for the 826 cases used in this study.

An evaluation of GNSS radio occultation atmospheric profiles from Sentinel-6

The Global Navigation Satellite System (GNSS) radio occultation (RO) significantly impacts climate change monitoring. GNSS RO is based mainly on the refraction of the GNSS signals transmitted by satellites and received by a receiver on a Low Earth Orbit (LEO) satellite. Sentinel-6 (S6) is the first satellite from the Sentinel missions to retrieve atmospheric parameters using the RO technique. Temperature, pressure, and water vapor profiles can be retrieved using S6 based on the refraction of GNSS signals. This research evaluated the distribution and coverage of GNSS RO data from S6. This research also aims to evaluate the results of GNSS RO products, especially temperature from S6, from January 2022 to June 2022. The results of S6 are compared with the results from the Meteorological Operational Polar Satellite series (MetOp-B and MetOp-C) and the European Centre for Medium-Range Weather Forecasts (ECMWF) Reanalysis v5 (ERA5) dataset. Our results indicate that S6 allows for many RO observations in space by receiving signals from the Global Positioning System (GPS) and Russia's Global Navigation Satellite System (GLONASS). S6 provides monthly RO profiles from GPS that are greater than monthly RO profiles from GLONASS. Results show that S6 provides more GNSS RO data than MetOp-B and MetOp-C. The findings indicate that the distribution of GNSS RO events from S6 over the globe is uniform in longitude and non-uniform at latitude, with the minimum number at the poles. This paper makes a significant contribution to exploring the atmosphere with the S6 as a promising satellite for weather forecasting and monitoring climate change.

Evaluating the Impacts of COSMIC-2 GNSS RO Bending Angle Assimilation on Atlantic Hurricane Forecasts Using the HWRF Model

Abstract This study evaluates the impact of assimilating Global Navigation Satellite System (GNSS) radio occultation (RO) bending angles from Formosa Satellite Mission-7/Constellation Observing System for Meteorology, Ionosphere, and Climate-2 (COSMIC-2) receiver satellites on Hurricane Weather Research and Forecasting (HWRF) Model tropical cyclone (TC) forecasts. Launched in June 2019, the COSMIC-2 mission provides significantly higher tropics data coverage compared to its predecessor COSMIC constellation. GNSS RO measurements yield information about atmospheric pressure, temperature, and water vapor profiles. HWRF is cycled with and without COSMIC-2 bending angle data assimilation for six 2020 Atlantic hurricane cases. COSMIC-2 assimilation has little impact on HWRF track forecasts, consistent with HWRF’s design limiting cycled data assimilation impacts on surrounding large-scale flows; however, COSMIC-2 assimilation results in a statistically significant ∼8%–12% mean absolute forecast error reduction in minimum central sea level pressure for t = 36-, 54-, 60-, and 108–120-h lead times. Forecasts initialized from analyses assimilating COSMIC-2 observations also have a 1%–4% smaller 600–700-hPa specific humidity (SPFH) root-mean-squared deviation compared to radiosondes and dropwindsondes for most lead times. While not all HWRF intensity forecasts benefit from COSMIC-2 assimilation, a few show notable improvement. For example, assimilating two COSMIC-2 profiles within the inner core of developing Hurricane Hanna (2020) increases 800-hPa SPFH by up to 1 g kg−1 locally, helping to correct a dry bias. The forecast initialized from this analysis better captures Hanna’s observed intensification rate, likely because its moister inner core facilitates development of persistent deep convection near the TC center, where diabatic heating is more efficiently converted to cyclonic wind kinetic energy. Significance Statement Tropical cyclone (TC) intensification can be strongly sensitive to the lower-to-midtropospheric water vapor distribution near the storm. The COSMIC-2 GNSS radio occultation (RO) receiver satellite mission provides denser spatial coverage of atmospheric water vapor and temperature profiles over the tropics compared to other GNSS RO observation platforms. Herein, using six 2020 Atlantic TC cases, we evaluate the impacts of assimilating COSMIC-2 RO bending angles into a regional forecast model that already assimilates clear-sky satellite radiances. It is shown that COSMIC-2 assimilation yields a modest ∼10% intensity forecast skill improvement for several lead times, although more substantial intensity forecast improvement is found for a few forecasts where the COSMIC-2 observation assimilation helps correct a lower-to-midtropospheric water vapor bias.

An improved GNSS remote sensing technique for 3D distribution of tropospheric water vapor

AbstractWater vapor plays an extremely important role in the monitoring and prediction of weather, and GNSS tomography can obtain 3D spatiotemporal change information and reliable water vapor profiles. In this paper, an improved global navigation satellite system (GNSS) tropospheric tomography technique using an ERA5 (the fifth generation ECMWF reanalysis) product is developed. First, the ERA5 product was adopted to analyze the spatiotemporal distribution of water vapor, and a water vapor density threshold defining the top of the tomography was determined; then, the height of the grid top (GT) of different seasons was obtained through linear fitting; finally, the water vapor value between GT and tropopause is constrained using the data of the ERA5 product as the initial value. The new method for using the ERA5 product to determine the height of the GT of the tomographic grid reduces the height of the top layer of the grid and increases the number of effective GNSS rays. Data from nine CORS stations in Hong Kong in 2019 were selected for experiments. The results showed that the new algorithm increased the number of effective satellite signals by 14%. In addition, the ERA5 data, the radiosonde data, and the COSMIC‐2 data were used as reference values. The accuracy of the water vapor density obtained by the algorithm was improved by 25%, 17% and 9%, respectively.