Integrated Water Vapor Estimates Research Articles

The Novel Copernicus Global Dataset of Atmospheric Total Water Vapour Content with Related Uncertainties from GNSS Observations

A novel algorithm has been designed and implemented in the Climate Data Store (CDS) frame of the Copernicus Climate Change Service (C3S) with the main goal of providing high-quality GNSS-based integrated water vapour (IWV) datasets for climate research and applications. For this purpose, the related CDS GNSS datasets were primarily obtained from GNSS reprocessing campaigns, given their highest quality in adjusting systematic effects due to changes in instrumentation and data processing. The algorithm is currently applied to the International GNSS Service (IGS) tropospheric products, which are consistently extended in near real-time and date back to 2000, and to the results of a reprocessing campaign conducted by the EUREF Permanent GNSS Network (EPN repro2), covering the period from 1996 to 2014. The GNSS IWV retrieval employs ancillary meteorological data sourced from ERA5. Moreover, IWV estimates are provided with associated uncertainty, using an approach similar to that used for the Global Climate Observing System Reference Upper-Air Network (GRUAN) GNSS data product. To assess the quality of the newly introduced GNSS IWV datasets, a comparison is made against the radiosonde data from GRUAN and the Radiosounding HARMonization (RHARM) dataset as well as with the IGS repro3, which will be the next GNSS-based extension of IWV time series at CDS. The comparison indicates that the average difference in IWV among the reprocessed GNSS datasets is less than 0.1 mm. Compared to RHARM and GRUAN IWV values, a small dry bias of less than 1 mm for the GNSS IWV is detected. Additionally, the study compares GNSS IWV trends with the corresponding values derived from RHARM at selected radiosonde sites with more than ten years of data. The trends are mostly statistically significant and in good agreement.

An enhanced integrated water vapour dataset from more than 10 000 global ground-based GPS stations in 2020

Abstract. We developed a high-quality global integrated water vapour (IWV) dataset from 12 552 ground-based global positioning system (GPS) stations in 2020. It consists of 5 min GPS IWV estimates with a total number of 1 093 591 492 data points. The completeness rates of the IWV estimates are higher than 95 % at 7253 (58 %) stations. The dataset is an enhanced version of the existing operational GPS IWV dataset provided by the Nevada Geodetic Laboratory (NGL). The enhancement is reached by employing accurate meteorological information from the fifth generation of European ReAnalysis (ERA5) for the GPS IWV retrieval with a significantly higher spatiotemporal resolution. A dedicated data screening algorithm is also implemented. The GPS IWV dataset has a good agreement with in situ radiosonde observations at 182 collocated stations worldwide. The IWV biases are within ±3.0 kg m−2 with a mean absolute bias (MAB) value of 0.69 kg m−2. The standard deviations (SD) of IWV differences are no larger than 3.4 kg m−2. In addition, the enhanced IWV product shows substantial improvements compared to NGL's operational version, and it is thus recommended for high-accuracy applications, such as research of extreme weather events and diurnal variations of IWV and intercomparisons with other IWV retrieval techniques. Taking the radiosonde-derived IWV as reference, the MAB and SD of IWV differences are reduced by 19.5 % and 6.2 % on average, respectively. The number of unrealistic negative GPS IWV estimates is also substantially reduced by 92.4 % owing to the accurate zenith hydrostatic delay (ZHD) derived by ERA5. The dataset is available at https://doi.org/10.5281/zenodo.6973528 (Yuan et al., 2022).

A Back Propagation Neural Network-Based Calibration Approach for Sentinel-3 OLCI Near-Infrared Water Vapor Product

A back propagation neural network (BPNN)-based calibration method is developed to enhance the all-weather quality of official integrated water vapor (IWV) products from near-infrared (NIR) observations of the Ocean and Land Color Instrument (OLCI) onboard Sentinel-3A and Sentinel-3B satellites. The model utilizes multiple variables that link with the derivation of satellite NIR IWV products, including official OLCI NIR IWV, latitude, land quality and science flag, month, and solar zenith angle. The in situ IWV observations, collected from 100 Global Positioning System (GPS) stations, are employed as the desired IWV estimates. The model is evaluated using one-year water vapor data at additional 114 GPS stations and 97 radiosonde stations from June 1, 2019 to May 31, 2020 in China and its surrounding regions. The results show that the BPNN-based calibration model reduces the root-mean-square error (RMSE) of official OLCI NIR all-weather IWV products by 24.52% from 3.10 to 2.34 mm for Sentinel-3A and by 25.00% from 3.44 to 2.58 mm for Sentinel-3B, when compared with in situ GPS-observed reference IWV. When compared with in situ radiosonde-observed IWV, the RMSE reduces 21.01% from 4.57 to 3.61 mm and 20.81% from 5.19 to 4.11 mm for Sentinel-3A and Sentinel-3B, respectively.

Routine Measurement of Water Vapour Using GNSS in the Framework of the Map-Io Project

The “Marion Dufresne Atmospheric Program-Indian Ocean” (MAP-IO) project is a research program that aims to collect long-term atmospheric observations in the under-instrumented Indian and Austral Oceans. As part of this project, a Global Navigation Satellite System (GNSS) antenna was installed on the research vessel (R/V) Marion Dufresne in October 2020. GNSS raw data is intended to be used to retrieve Integrated Water Vapour (IWV) content along the Marion Dufresne route, which cruises more than 300 days per year in the tropical and austral Indian Ocean. This paper presents a first assessment of this GNSS-based IWV retrieval, based on the analysis of 9 months of GNSS raw data acquired along the route of the R/V Marion Dufresne in the Indian Ocean. A first investigation of GNSS raw data collected during the first 5 months of operation has highlighted the bad positioning of the antenna on the R/V that makes it prone to interference. Changing the location of the antenna has been shown to improve the quality of the raw data. Then, ship-borne GNSS-IWV are compared with IWV estimates deduced using more conventional techniques such as European Centre for Medium-range Weather Forecasts (ECMWF) fifth reanalysis (ERA5), ground-launched radiosondes and permanent ground GNSS stations operating close to the route of the R/V Marion Dufresne. The rms difference of 2.79 kg m−2 shows a good match with ERA5 and subsequently improved after the change in location of the GNSS antenna (2.49 kg m−2). The match with ground-based permanent GNSS stations fluctuates between 1.30 and 3.63 kg m−2, which is also shown to be improved after the change in location of the GNSS antenna. However, differences with ground-launched radiosondes still exhibit large biases (larger than 2 kg m−2). Finally, two operational daily routine analyses (at day+1 and day+3) are presented and assessed: the rms of the differences are shown to be quite low (1 kg m−2 for the day+1 analyses, 0.7 kg m−2 for the day+3 analysis), which confirms the quality of these routine analysis. These two routine analyses are intended to provide a continuous monitoring of water vapour above the Indian Ocean and deliver ship-borne IWV with a low latency for the entire scientific community.

An Observational Study of GPS-Derived Integrated Water Vapor over India

This study describes the process of deriving integrated water vapor (IWV) from (a) a set of 18 GPS receivers that were installed at different airports across India and (b) a pair of GPS receivers located in Ahmedabad situated around 8 km apart. The Zenith Tropospheric Delay was estimated from the GPS observations using the GAMIT software. Further, IWV was estimated from the ZTD values using surface temperature and pressure from ERA-I reanalysis as additional inputs. The IWV estimates for 1 year—March 2013 to February 2014—were compared with ECMWF Reanalysis Interim (ERA-I) reanalysis as well as radiosonde soundings. The Root Mean Squared Error (RMSE) was ≈6 mm or better for most stations. The IWV estimates for July 2013 were assimilated into the WRF model and had a positive impact on model analysis of IWV. The forecasted rain improved by up to 3–4 mm/day in some regions as a result of GPS-derived IWV estimates. For the Ahmedabad receivers, the GPS-derived IWV was compared with IWV from ERA-I reanalysis and was found to have a RMSE of ≈7.7 mm which is <20% of the mean value. The study demonstrates that the observed IWV variation is consistent with rainfall patterns over Ahmedabad. The rise and dips in the IWV correlate well with the active-break cycle in the monsoon rain. The study demonstrates the value of local measurements of IWV with high temporal frequency, as they are more likely to respond to fast-moving weather phenomena such as rainfall. Thus, the GPS-derived IWV measurements are likely to have significant value in the short-term forecasts of precipitation.

GNSS-based water vapor estimation and validation during the MOSAiC expedition

Abstract. Within the transpolar drifting expedition MOSAiC (Multidisciplinary drifting Observatory for the Study of Arctic Climate), the Global Navigation Satellite System (GNSS) was used among other techniques to monitor variations in atmospheric water vapor. Based on 15 months of continuously tracked GNSS data including GPS, GLONASS and Galileo, epoch-wise coordinates and hourly zenith total delays (ZTDs) were determined using a kinematic precise point positioning (PPP) approach. The derived ZTD values agree to 1.1 ± 0.2 mm (root mean square (rms) of the differences 10.2 mm) with the numerical weather data of ECMWF's latest reanalysis, ERA5, computed for the derived ship's locations. This level of agreement is also confirmed by comparing the on-board estimates with ZTDs derived for terrestrial GNSS stations in Bremerhaven and Ny-Ålesund and for the radio telescopes observing very long baseline interferometry in Ny-Ålesund. Preliminary estimates of integrated water vapor derived from frequently launched radiosondes are used to assess the GNSS-derived integrated water vapor estimates. The overall difference of 0.08 ± 0.04 kg m−2 (rms of the differences 1.47 kg m−2) demonstrates a good agreement between GNSS and radiosonde data. Finally, the water vapor variations associated with two warm-air intrusion events in April 2020 are assessed.

Integrated water vapour observations in the Caribbean arc from a network of ground-based GNSS receivers during EUREC<sup>4</sup>A

Abstract. Ground-based Global Navigation Satellite System (GNSS) measurements from nearly 50 stations distributed over the Caribbean arc have been analysed for the period 1 January–29 February 2020 in the framework of the EUREC4A (Elucidate the Couplings Between Clouds, Convection and Circulation) field campaign. The aim of this effort is to deliver high-quality integrated water vapour (IWV) estimates to investigate the moisture environment of mesoscale cloud patterns in the trade winds and their feedback on the large-scale circulation and energy budget. This paper describes the GNSS data processing procedures and assesses the quality of the GNSS IWV retrievals from four operational streams and one reprocessed research stream which is the main data set used for offline scientific applications. The uncertainties associated with each of the data sets, including the zenith tropospheric delay (ZTD)-to-IWV conversion methods and auxiliary data, are quantified and discussed. The IWV estimates from the reprocessed data set are compared to the Vaisala RS41 radiosonde measurements operated from the Barbados Cloud Observatory (BCO) and to the measurements from the operational radiosonde station at Grantley Adams International Airport (GAIA), Bridgetown, Barbados. A significant dry bias is found in the GAIA humidity observations with respect to the BCO sondes (−2.9 kg m−2) and the GNSS results (−1.2 kg m−2). A systematic bias between the BCO sondes and GNSS is also observed (1.7 kg m−2), where the Vaisala RS41 measurements are moister than the GNSS retrievals. The IWV estimates from a collocated microwave radiometer agree with the BCO soundings after an instrumental update on 27 January, while they exhibit a dry bias compared to the soundings and to GNSS before that date. IWV estimates from the ECMWF fifth-generation reanalysis (ERA5) are overall close to the GAIA observations, probably due to the assimilation of these observations in the reanalysis. However, during several events where strong peaks in IWV occurred, ERA5 is shown to significantly underestimate the GNSS-derived IWV peaks. Two successive peaks are observed on 22 January and 23–24 January which were associated with heavy rain and deep moist layers extending from the surface up to altitudes of 3.5 and 5 km, respectively. ERA5 significantly underestimates the moisture content in the upper part of these layers. The origins of the various moisture biases are currently being investigated. We classified the cloud organization for five representative GNSS stations across the Caribbean arc using visible satellite images. A statistically significant link was found between the cloud patterns and the local IWV observations from the GNSS sites as well as the larger-scale IWV patterns from the ECMWF ERA5 reanalysis. The reprocessed ZTD and IWV data sets from 49 GNSS stations used in this study are available from the French data and service centre for atmosphere (AERIS) (https://doi.org/10.25326/79; Bock, 2020b).

Integrated water vapour content retrievals from ship-borne GNSS receivers during EUREC<sup>4</sup>A

Abstract. In the framework of the EUREC4A (Elucidating the role of clouds–circulation coupling in climate) campaign that took place in January and February 2020, integrated water vapour (IWV) contents were retrieved over the open tropical Atlantic Ocean using Global Navigation Satellite System (GNSS) data acquired from three research vessels (R/Vs): R/V Atalante, R/V Maria S. Merian and R/V Meteor. This paper describes the GNSS processing method and compares the GNSS IWV retrievals with IWV estimates from the European Centre for Medium-range Weather Forecasts (ECMWF) fifth reanalysis (ERA5), from the Moderate Resolution Imaging Spectroradiometer (MODIS) infrared products and from terrestrial GNSS stations located along the tracks of the ships. The ship-borne GNSS IWV retrievals from R/V Atalante and R/V Meteor compare well with ERA5, with small biases (−1.62 kg m−2 for R/V Atalante and +0.65 kg m−2 for R/V Meteor) and a root mean square (rms) difference of about 2.3 kg m−2. The results for the R/V Maria S. Merian are found to be of poorer quality, with an rms difference of 6 kg m−2, which is very likely due to the location of the GNSS antenna on this R/V prone to multipath effects. The comparisons with ground-based GNSS data confirm these results. The comparisons of all three R/V IWV retrievals with MODIS infrared products show large rms differences of 5–7 kg m−2, reflecting the enhanced uncertainties in these satellite products in the tropics. These ship-borne IWV retrievals are intended to be used for the description and understanding of meteorological phenomena that occurred during the campaign, east of Barbados, Guyana and northern Brazil. Both the raw GNSS measurements and the IWV estimates are available through the AERIS data centre (https://en.aeris-data.fr/, last access: 20 September 2020). The digital object identifiers (DOIs) for R/V Atalante IWV and raw datasets are https://doi.org/10.25326/71 (Bosser et al., 2020a) and https://doi.org/10.25326/74 (Bosser et al., 2020d), respectively. The DOIs for the R/V Maria S. Merian IWV and raw datasets are https://doi.org/10.25326/72 (Bosser et al., 2020b) and https://doi.org/10.25326/75 (Bosser et al., 2020e), respectively. The DOIs for the R/V Meteor IWV and raw datasets are https://doi.org/10.25326/73 (Bosser et al., 2020c) and https://doi.org/10.25326/76 (Bosser et al., 2020f), respectively.

Integrated water vapor and liquid water path retrieval using a single-channel radiometer

Abstract. Microwave radiometers are widely used for the retrieval of liquid water path (LWP) and integrated water vapor (IWV) in the context of cloud and precipitation studies. This paper presents a new site-independent retrieval algorithm for LWP and IWV, relying on a single-frequency 89 GHz ground-based radiometer. A statistical approach is used based on a neural network, which is trained and tested on a synthetic dataset constructed from radiosonde profiles worldwide. In addition to 89 GHz brightness temperature, the input features include surface measurements of temperature, pressure, and humidity, as well as geographical information and, when available, estimates of IWV and LWP from reanalysis data. An analysis of the algorithm is presented to assess its accuracy, the impact of the various input features, its sensitivity to radiometer calibration, and its stability across geographical locations. While 89 GHz brightness temperature is crucial to LWP retrieval, it only moderately contributes to IWV estimation, which is more constrained by the additional input features. The algorithm is shown to be quite robust, although its accuracy is inevitably lower than that obtained with state-of-the-art multi-channel radiometers, with a relative error of 18 % for LWP (in cloudy cases with LWP >30 g m−2) and 6.5 % for IWV. The highest accuracy is obtained in midlatitude environments with a moderately moist climate, which are more represented in the training dataset. The new method is then implemented and evaluated on real data that were collected during a field deployment in Switzerland and during the ICE-POP 2018 campaign in South Korea.

Assessment of Integrated Water Vapor Estimates from the iGMAS and the Brazilian Network GNSS Ground-Based Receivers in Rio de Janeiro

There is pressing demand for knowledge improvement of the integrated water vapor (IWV) distribution in regions affected by heat islands that are associated with extreme rainfall events such as in the metropolitan area of Rio de Janeiro (MARJ). This work assessed the suitability and evaluation of the spatiotemporal distribution of Global Navigation Satellite Systems (GNSS) IWV from the cooperation of the International GNSS Monitoring and Assessment System (iGMAS) and the National Observatory (Observatório Nacional, ON) of Brazil, from the Brazilian Network for Continuous Monitoring (RBMC), and IWV products from Moderate Resolution Imaging Spectroradiometer (MODIS) and radiosonde, jointly with surface meteorological data, in two sectors of the state of Rio de Janeiro from February 2015–August 2018. High variability of the near surface air temperature (T) and relative humidity (RH) were observed among eight meteorological sites. The mean T differences between sites, up to 4.4 °C, led to mean differences as high as 3.1 K for weighted mean temperature (Tm) and hence 0.83 mm for IWV differences. Local grid points of MODIS IWV estimates had relatively good agreement with the GNSS-derived IWV, with mean differences from –2.4–1.1 mm for the daytime passages of the satellites TERRA and AQUA and underestimation from –9 mm to –3 mm during nighttime overpasses. A contrasting behavior was found in the radiosonde IWV estimates compared with the estimates from GNSS. There were dry biases of 1.4 mm (3.7% lower than expected) by radiosonde IWV during the daytime, considering that all other estimates were unbiased and the differences between IWVGNSS and IWVRADS were consistent. Based on the IWV comparisons between radiosonde and GNSS at nighttime, the atmosphere over the radiosonde site is about 1.2 mm and 2.3 mm wetter than that over the RBMC RIOD and iGMAS RDJN stations, respectively. The atmosphere over the site RIOD was 1.2 mm wetter than over that of RDJN for all three-hour means. These results showed that there were important variabilities in the meteorological conditions and in the distribution of water vapor in the MERJ. The data from the iGMAS RDJN station were feasible, together with those from the RBMC, MODIS, and radiosonde data, to investigate IWV in the region with occurrence of heat islands and peculiar physiographic and meteorological characteristics. This work recommends the magnification of the GNSS network in the state of Rio de Janeiro with the use of data from complete meteorological station collocated near every GNSS receiver, aiming to improve local IWV estimates and serving as additional support for operational numerical assimilation, weather forecast, and nowcast of extreme rainfall and flooding events.

Global ECMWF Analysis Data for Estimating the Water Vapor Content Between Two LEO Satellites Through NDSA Measurements

The normalized differential spectral attenuation (NDSA) approach was proposed years ago as an effective way to estimate the integrated water vapor (IWV) along a tropospheric propagation path between two low Earth orbit satellites. Two applications are possible: the retrieval of vertical profiles of WV if the sense of rotation is opposite and the retrieval of 2-D fields of WV over vertical tropospheric sections if the sense is the same. The method relies on the measurement of the so-called spectral sensitivity $S$ at given frequencies, and on IWV-S relationships that convert $S$ into an estimate of IWV along the radio link where $S$ is measured. In this paper, we recompute the IWV-S relationships using synthetic atmospheres generated by means of European Centre for Medium-Range Weather Forecasts (ECMWF) analysis data instead of radiosonde profiles as done by ourselves in the past. Thanks to the uniform spatial distribution of the ECMWF data on a global Earth scale, we were able to validate the IWV-S relationships in the Ku/K band previously found through synthetic atmospheres generated by means of the aforementioned irregularly spaced radiosonde data, and to define the IWV-S relationships at 179 and 181 GHz that are exploitable in the upper troposphere. Since the ECMWF data also include information about the liquid water (LW) content, we then show that an additional $S$ channel at 32 GHz can be exploited to detect and correct the bias induced by LW on IWV estimates made by applying the NDSA in the Ku/K band.

Impact of single-point GPS integrated water vapor estimates on short-range WRF model forecasts over southern India

Specifying physically consistent and accurate initial conditions is one of the major challenges of numerical weather prediction (NWP) models. In this study, ground-based global positioning system (GPS) integrated water vapor (IWV) measurements available from the International Global Navigation Satellite Systems (GNSS) Service (IGS) station in Bangalore, India, are used to assess the impact of GPS data on NWP model forecasts over southern India. Two experiments are performed with and without assimilation of GPS-retrieved IWV observations during the Indian winter monsoon period (November–December, 2012) using a four-dimensional variational (4D-Var) data assimilation method. Assimilation of GPS data improved the model IWV analysis as well as the subsequent forecasts. There is a positive impact of ∼10 % over Bangalore and nearby regions. The Weather Research and Forecasting (WRF) model-predicted 24-h surface temperature forecasts have also improved when compared with observations. Small but significant improvements were found in the rainfall forecasts compared to control experiments.

Ground-based GNSS ZTD/IWV estimation system for numerical weather prediction in challenging weather conditions

The Global Navigation Satellite Systems (GNSS) are one of the very few tools that can provide continuous, unbiased, precise and robust atmosphere condition information. The extensive research of GNSS space-based segment (e.g. available precise, real-time satellite orbits and clocks), unlimited access to the ground-based Continuously Operating Reference Stations (CORS) GNSS networks along with the well established data processing methods provides an unprecedented opportunity to study the environmental impacts on the GNSS signal propagation. GNSS measurements have been successfully used in precise positioning, tectonic plate monitoring, ionosphere studies and troposphere monitoring. However all GNSS signals recorded on the ground by CORS are subject to ionosphere delay, troposphere delay, multipath and signal strength loss. Nowadays, the GNSS signal delays are gradually incorporated into the numerical weather prediction (NWP) models. Usually the Zenith Total Delay (ZTD) or Integrated Water Vapour (IWV) have been considered as an important source of water vapour contents and assimilated into the NWP models. However, successful assimilation of these products requires strict accuracy assessment, especially in the challenging severe weather conditions.In this study a number of GNSS signal processing strategies have been verified to obtain the best possible estimates of troposphere delays using a selection of International GNSS Service (IGS) orbit and clock products. Three different severe weather events (severe storm, flash flooding, flooding) have been investigated in this paper. The strategies considered are; 1) Double Differenced (DD) network solution with shortest baselines, 2) DD network solution with longest baselines, 3) DD baseline-by-baseline solution (tested but not considered), 4) Zero Differenced (ZD) Precise Point Positioning (PPP) based on ambiguity float solutions, all with precise orbits and clocks, and real time clocks and predicted orbits. The quality of the estimates obtained has been evaluated against radiosonde measurements, Automatic Weather Station (AWS) observations, NWP (assimilation step without ground-based GNSS data) and ZTD estimates from the well established IGS processing centre, the Center of Orbit Determination in Europe (CODE). It shows that the ZTD and IWV estimates from the DD short baseline solution are robust with usually a very small bias (−2.7 to −0.8mm) and errors of less than 10mm (7.6–8.5) (ZTD) or 3mm (2.6–2.7) (IWV). The DD short baseline network solution was found to be the most reliable method in the considered case studies, regardless of the type of orbits and clocks applied.

High-Resolution Vertical Profiles of X-Band Polarimetric Radar Observables during Snowfall in the Swiss Alps

AbstractAn X-band polarimetric radar was deployed in the eastern Swiss Alps at an altitude of 2133 m. Radar measurements were complemented with several weather stations deployed in an altitude range from 1500 to 3100 m as well as with a fixed GPS ground station that was used to infer integrated water vapor estimates. Around 8000 vertical profiles of polarimetric radar observables above the melting layer collected during two months are analyzed. First, the behavior of the mean profiles of reflectivity at horizontal polarization Zh, differential reflectivity Zdr, copolar cross correlation ρhv, and specific differential phase shift Kdp are interpreted from a microphysical point of view. It is shown that the whole evolution of snowflakes, from pristine crystals at temperatures around −30°C to dendritic crystals around −15°C, to large aggregates around 0°C, is well captured by the polarimetric radar variables. In a second step, the profiles are analyzed as functions of high and low water vapor and snow accumulation conditions. It is found that the vertical profiles of polarimetric radar variables have distinct features in low versus high water vapor conditions. High water vapor conditions appear to favor the occurrence of crystal aggregates at high altitudes/low temperatures. It is shown with a hydrometeor identification scheme that graupel-like particles are found to be dominant right above the melting layer for snow events with high accumulation intensities. The present analyses show that measurements from X-band dual-polarization radar can be useful to characterize the dominant microphysical processes during precipitation in mountainous regions.

The Inclusion of IWV Estimates from AIRS/AMSU and SSM/I Sensors into the CPTEC/INPE Global Data Assimilation System

Abstract Water vapor plays a crucial role in atmospheric processes and its distribution is associated with cloud-cover fraction and rainfall. The inclusion of integrated water vapor (IWV) estimates in numerical weather prediction improves the vertical structure of the humidity analysis and consequently contributes to obtaining a more realistic atmospheric state. Currently, satellite remote sensing is the most important source of humidity measurements in the Southern Hemisphere, providing information with good horizontal resolution and global coverage. In this study, the inclusion of IWV retrieved from the Atmospheric Infrared Sounder/Advanced Microwave Sounding Unit-A (AIRS/AMSU) and Special Sensor Microwave Imager (SSM/I) were investigated as additional information in the Physical-space Statistical Analysis System (PSAS), which is the operational data assimilation system at the Center for Weather Forecasting and Climate Studies of the Brazilian National Institute for Space Research (CPTEC/INPE). Experiments were carried out with and without the assimilation of IWV values from both sensors. Results show that, in general, the IWV assimilation reduces the error in short-range forecasts of humidity profile, particularly over tropical regions. In these experiments, an analysis of the impact of the inclusion of IWV values from SSM/I and AIRS/AMSU sensors was done. Results indicated that the impact of the SSM/I values is significant over high-latitude oceanic regions in the Southern Hemisphere, while the impact of AIRS/AMSU values is more significant over continental regions where surface measurements are scarce, such as the Amazonian region. In that area the assimilation of IWV values from the AIRS/AMSU sensor shows a tendency to reduce the overestimate of the precipitation in short-range forecasts.

Trends in the Atmospheric Water Vapor Content From Ground-Based GPS: The Impact of the Elevation Cutoff Angle

We used 14 years of data from 12 GPS sites in Sweden and Finland to estimate trends in the atmospheric integrated water vapor (IWV) for 8 different elevation cutoff angles, from 5° to 40°, for the observations used in the analyses. These trends were compared to the corresponding trends obtained from radiosonde data at 7 nearby (<;120 km) sites. The results show a variation in the correlation of the trends between the two techniques for different elevation cutoff angles. The highest correlation coefficient of 0.88 is obtained for the 25^ solution, whereas the smallest root-mean-square (RMS) differences between the IWV estimates themselves are obtained mainly for elevation cutoff angles of 10° and 15°. The results show that elevation-angle-dependent systematic errors vary with time. Therefore the elevation cutoff angle giving the best agreement between radiosonde and GPS for individual IWV estimates is not necessarily the optimum when estimating linear trends. The correlation between the trends from the two completely independent techniques is strong evidence that the two techniques provide information on the IWV trends although the true individual values are too small to be uniquely detected. In addition, we found that the choice of mapping functions is not critical for the IWV trend estimation.

Ground-Based GPS for Validation of Climate Models: The Impact of Satellite Antenna Phase Center Variations

The amount of water vapor in the atmosphere is an important indicator for climate change. Using the Global Positioning System (GPS), it is possible to estimate the integrated water vapor (IWV) above the ground-based GPS receiver. In order to optimally determine the IWV, a correct model of the received signal phase is essential. We have studied the effect of the satellite antenna phase center variations (PCVs) on the IWV estimates by simulating the effect and by studying the estimates of the IWV based on the observed GPS signals. During a period of five years, from 2003 to 2008, a new satellite type was introduced, and it steadily grew in numbers. The antenna PCVs for these satellites deviate from the earlier satellite types and contribute to excess IWV estimates. We find that ignoring satellite antenna phase variations for this time period can lead to an additional IWV trend of about 0.15 kg/m2/year for regular GPS processing.

High resolution spatio‐temporal water vapour mapping using GPS and MERIS observations

Improved knowledge of atmospheric water vapour and its temporal and spatial variability is of great scientific interest for climate research and weather prediction. Moreover, the availability of fine resolution water vapour maps is expected to reduce significant errors in applications using the Global Positioning System, GPS, or radar interferometry. Several methods exist to estimate water vapour using satellite systems. Combining radiances as measured in two spectral bands of the Medium Resolution Imaging Spectrometer (MERIS) results in an Integrated Water Vapor (IWV) product with high spatial resolution, up to 300 m, but a limited temporal resolution of about three days, in case of cloud free conditions. On the other hand, IWV estimates can be derived from the zenith total delays as observed by continuous GPS networks. The GPS IWV estimates have a higher temporal resolution of typically 1 hour, but, even in Western Europe, inter‐station distances are at least tenths of kilometres. Here we describe how to obtain IWV products with high spatio‐temporal resolution by combining GPS and MERIS IWV estimates. For this purpose an analysis is made of MERIS and GPS based IWV data, retrieved at the same day over Western Europe. A variance–covariance analysis is performed and is subsequently applied to produce time series of combined high‐resolution water vapour maps using Kriging. The research presented here is a first step towards near real‐time fine resolution water vapour products.

Intercomparison of Integrated Water Vapor Estimates from Multisensors in the Amazonian Region

Abstract Water vapor is an atmospheric component of major interest in atmospheric science because it affects the energy budget and plays a key role in several atmospheric processes. The Amazonian region is one of the most humid on the planet, and land use change is able to affect the hydrologic cycle in several areas and consequently to generate severe modifications in the global climate. Within this context, accessing the error associated with atmospheric humidity measurement and the validation of the integrated water vapor (IWV) quantification from different techniques is very important in this region. Using data collected during the Radiation, Cloud, and Climate Interactions in Amazonia during the Dry-to-Wet Transition Season (RACCI/DRY-TO-WET), an experiment carried out in southwestern Amazonia in 2002, this paper presents quality analysis of IWV measurements from RS80 radiosondes, a suite of GPS receivers, an Aerosol Robotic Network (AERONET) solar radiometer, and humidity sounding from the Humidity Sounder for Brazil (HSB) aboard the Aqua satellite. When compared to RS80 IWV values, the root-mean-square (RMS) from the AERONET and GPS results are of the order of 2.7 and 3.8 kg m−2, respectively. The difference generated between IWV from the GPS receiver and RS80 during the daytime was larger than that of the nighttime period because of the combination of the influence of high ionospheric activity during the RACCI experiment and a daytime drier bias from the RS80.

Normalized differential spectral attenuation (NDSA): a novel approach to estimate atmospheric water vapor along a LEO-LEO satellite link in the ku/K bands

We introduce here the normalized differential attenuation (NDSA) approach, which is a novel differential measurement way for estimating the total content of water vapor integrated water vapor (IWV) along a tropospheric propagation path between two Low Earth Orbit (LEO) satellites. The NDSA approach requires a transmitter onboard the first LEO satellite and a receiver onboard the second one. It is based on the simultaneous measurement of the total attenuation at two relatively close frequencies in the Ku/K bands, and on the estimate of a spectral sensitivity that can be directly converted into IWV. NDSA is potentially able to emphasize the water vapor contribution, to cancel out all spectrally flat unwanted contributions and to limit the impairments due to tropospheric scintillation. The objective of the paper is to analyze the level of correlation between the sensitivity parameter and the IWV at a given altitude from ground of the LEO-LEO link (tangent altitude), in order to single out the best performing frequencies. Simulation results are based on microwave propagation models and on radiosonde data. The results shows the potential of the NDSA approach to provide direct estimates of IWV along LEO-LEO tropospheric propagation paths in the 15-25 GHz frequency range, under different atmospheric conditions.