Integrated Water Vapor Content Research Articles

Histograms of the Caspian Sea Hydrometeorological Parameters

The article analyzes histograms of the distribution of the main hydrometeorological parameters of the Caspian Sea for 1980–2021 – air temperature, atmospheric pressure, absolute humidity, atmospheric precipitation and wind speed according to the MERRA-2 atmospheric reanalysis. Histograms were constructed for the entire study region of the Caspian Sea (36◦–48◦N, 45.625◦–55◦E), as well as separately for land and sea areas. The extremeness criteria were calculated based on the normal distribution and the real histogram for all 5 main meteorological parameters. A comparison was made of histograms obtained from MERRA-2 data and from weather station at Derbent located on the coast of the Caspian Sea. Distributions of average monthly wind speed, integral water vapor content and water vapor content in clouds over the Caspian Sea were also constructed according to microwave radiometry (SMMR, SSM/I) data for the time interval 1980–2021.

A Novel Physics-Statistical Coupled Paradigm for Retrieving Integrated Water Vapor Content Based on Artificial Intelligence

Retrieval of integrated water vapor content (WVC) from remote sensing data is often ill-posed because of insufficient observational information. There are many factors that cause WVC changes, which yield instability in the accuracy of many traditional algorithms. To overcome this problem, we developed a novel fully-coupled paradigm for the robust retrieval of WVC from thermal infrared remote sensing data. Through the derivation of the physical radiative transfer equation, we determined two conditions that need to be satisfied for the deep learning retrieval paradigm of WVC. The first condition is that the input parameters and output parameters of the deep learning need to be able to build a complete set of solvable equations in theory. The second condition is that, if there is a strong relationship between input parameters and output parameters, it can be directly retrieved. If it is a weak relationship, we need to use prior knowledge to improve the portability and accuracy of the algorithm. The training and test data of deep learning is composed of representative solutions of physical methods and solutions of statistical methods. The representative solutions of the physical methods were obtained from the physical forward model, and the statistical solutions were obtained from multi-source data which can compensate for the defect that the physical model cannot simulate mixed pixels. MODIS L1B data was used for case analysis of paradigm retrieval, and the analysis indicated that four thermal infrared bands were usually needed as the input parameters of deep learning and the integrated water vapor content as the output parameter. When land surface temperature and emissivity were taken as prior knowledge, the root-mean-square error (RMSE) of the retrieved WVC was 0.07 g/cm2. The optimal accuracy RMSE was 0.27 g/cm2. When there was a strong correlation between input parameters and output parameters, i.e., if there were two bands that were very sensitive to WVC in the band combination, high-precision retrieval could also be achieved without prior knowledge. All the analyses show that the paradigm of deep learning coupling physics and statistics can accurately retrieve WVC, which is a significant improvement on the traditional method and solves the problem of lack of physical interpretation of deep learning.

Comparison of the Integral Water Vapor Content of the Atmosphere by Data of the Global Forecast System (GFS) and GNSS Observations (Primorski Krai, Russia)

Comparison of the Integral Water Vapor Content of the Atmosphere by Data of the Global Forecast System (GFS) and GNSS Observations (Primorski Krai, Russia)

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.

IWV retrieval from ground GNSS receivers during NAWDEX

Abstract. A ground-based network of more than 1200 Global Navigation Satellite System (GNSS) Continuously Operating Reference Stations (CORS) was analysed using GIPSY-OASIS II software package for the documentation of time and space variations of water vapor in atmosphere during the North Atlantic Waveguide and Downstream impact EXperiment (NAWDEX) during fall 2016. The network extends throughout the North Atlantic, from the Caribbeans to Morocco through Greenland. This paper presents the methodology used for GNSS data processing, screening, and conversion of Zenith Tropospheric Delay (ZTD) estimates to Integrated Water Vapor content (IWV) using surface parameters from reanalysis. The retrieved IWV are used to evaluate the European Centre for Medium-Range Weather Forecasts (ECMWF) reanalyses ERAI and ERA5. ERA5 shows an overall improvement over ERAI in representing the spatial and temporal variability of IWV over the study area. The mean bias is decreased from 0.31±0.63 to 0.19±0.56 kg m−2 (mean ±1σ over all stations) and the standard deviation reduced from 2.17±0.67 to 1.64±0.53 kg m−2 combined with a slight improvement in correlation coefficient from 0.95 to 0.97. At regional scale, both reanalyses show a general wet bias at mid and northern latitudes but a dry bias in the Caribbeans. We hypothesize this results from the different nature of data being assimilated over the tropical oceans. This GNSS IWV data set is intended to be used for a better description of the high impact weather events that occurred during the NAWDEX experiment.

Meteorological OSSEs for New Zenith Total Delay Observations: Impact Assessment for the Hydroterra Geosynchronous Satellite on the October 2019 Genoa Event

Along the Mediterranean coastlines, intense and localized rainfall events are responsible for numerous casualties and several million euros of damage every year. Numerical forecasts of such events are rarely skillful, because they lack information in their initial and boundary conditions at the relevant spatio-temporal scales, namely O(km) and O(h). In this context, the tropospheric delay observations (strongly related to the vertically integrated water vapor content) of the future geosynchronous Hydroterra satellite could provide valuable information at a high spatio-temporal resolution. In this work, Observing System Simulation Experiments (OSSEs) are performed to assess the impact of assimilating this new observation in a cloud-resolving meteorological model, at different grid spacing and temporal frequencies, and with respect to other existent observations. It is found that assimilating the Hydroterra observations at 2.5 km spacing every 3 or 6 h has the largest positive impact on the forecast of the event under study. In particular, a better spatial localization and extent of the heavy rainfall area is achieved and a realistic surface wind structure, which is a crucial element in the forecast of such heavy rainfall events, is modeled.

Адаптивный алгоритм обнаружения и мониторинга атмосферных рек.

A new adaptive method for detecting and monitoring atmospheric rivers (ARs) over the ocean surface is proposed. ARs is the filamentous structures in the field of atmospheric water vapor, which provide a rapid transfer of moisture from the tropics to mid and high latitudes. Currently, certain difficulties remain in their detection and monitoring. The method is based on an adaptive algorithm for calculating the Jeffreys - Matusita distance between areas of the ocean with a high integral water vapor content and the places surrounding these areas with its background low values. The efficiency of the developed method is confirmed by the results of analysis of real data on the integral content of water vapor in the North Pacific Ocean. For the purpose of a qualitative comparative analysis, the authors give a brief overview of the methods used for the detection and monitoring of ARs, summarized the work on the study of the influence of ARs on regional weather conditions, singled out and characterized individual stages of these studies, indicated the most promising hardware for AR remote sensing. The results of the work are proposed to be used to improve the accuracy and reliability of automated AR detection by server means of a geoportal of satellite radio-thermal imaging (https://fireras.su/tpw/). The results of the work are of interest for multidisciplinary research, in particular, for predicting medium-term atmospheric processes.

Analysis of diurnal to seasonal variability of Integrated Water Vapour in the South Indian Ocean basin using ground‐based GNSS and fifth‐generation ECMWF reanalysis (ERA5) data

AbstractThe spatial and temporal distribution of tropospheric water vapour in the South Indian Ocean (SIO) basin is investigated using observations collected from twelve GNSS stations spanning the basin. The comparison of GNSS‐derived integrated water vapour (IWV) content against radiosoundings and satellite‐borne microwave radiometer data shows good agreement, with global uncertainties ranging from 0.76 to 1.17 kg·m−2, depending on GNSS station locations. GNSS‐derived IWV contents show a strong seasonal cycle, characterized by higher water vapour content during the austral summer, when the InterTropical Convergence Zone (ITCZ) is located in the Southern Hemisphere. At the seasonal time‐scale, the observed annual IWV amplitude varies from 10 to 15 kg·m−2 near the Equator to 20 to 30 kg·m−2 in the Subtropics. The GNSS IWV signature of the Madden–Julian Oscillation (MJO) is hardly noticeable during the Austral winter, but varies from 1–2 to 4 kg·m−2 between the active and suppressed phases of the MJO during austral summer. At diurnal time‐scales, GNSS IWV shows larger diurnal amplitude over land (2–3 kg·m−2) than over open ocean (1–2 kg·m−2), with highest amplitudes (up to 7 kg·m−2) observed over large and mountainous islands. The phase analysis of the IWV diurnal cycle indicates that the diurnal maximum (minimum) is reached in the late afternoon/evening (morning) over land, at night (mid‐day) over ocean and in the early morning (late afternoon) at coastal locations. A comparison of GNSS‐derived IWV contents against fifth‐generation European Centre for Medium‐range Weather Forecasts (ECMWF) Reanalysis (ERA5) data shows that ERA5 generally correctly reproduces the IWV content at both seasonal, intra‐seasonal and diurnal time‐scales, although some discrepancies can be noticed over small islands characterised by steep orography. The signature of the MJO in ERA5 also shows good agreement with GNSS observations at most studied locations.

Lee wave detection over the Mediterranean Sea using the Advanced Infra-Red WAter Vapour Estimator (AIRWAVE) total column water vapour (TCWV) dataset

Abstract. Atmospheric gravity waves generated downstream by orography in a stratified airflow are known as lee waves. In the present study, such mesoscale patterns have been detected, over water and in clear-sky conditions, using the Advanced Infra-Red WAter Vapour Estimator (AIRWAVE) total column water vapour (TCWV) dataset, which contains about 20 years of day and night products, obtained from the thermal infrared measurements of the Along Track Scanning Radiometer (ATSR) instrument series. The high accuracy of such data, along with the native 1 km×1 km spatial resolution, allows the investigation of small-scale features such as lee waves. In this work, we focused on the Mediterranean Sea, the largest semi-enclosed basin on the Earth. The peculiarities of this area, which is characterised by complex orography and rough coastlines, lead to the development of these structures over both land and sea. We developed an automatic tool for the rapid detection of areas with high probability of lee wave occurrence, exploiting the TCWV variability in spatial regions with a 0.15∘×0.15∘ area. Through this analysis, several occurrences of structures connected with lee waves have been observed. The waves are detected in spring, autumn and summer seasons, with TCWV values usually falling in the range of 15 to 35 kg m−2. In this article, we describe some cases over the central (Italy) and the Eastern Mediterranean Basin (Greece, Turkey and Cyprus). We compared a case of perturbed AIRWAVE TCWV fields due to lee waves occurring over the Tyrrhenian Sea on 18 July 1997 with the sea surface winds from the synthetic aperture radar (SAR), which sounded the same geographical area, finding a good agreement. Another case has been investigated in detail: on 2 August 2002 the Aegean Sea region was almost simultaneously sounded by both the second sensor of the ATSR series (ATSR-2) and the Advanced ATSR (AATSR) instruments. The AIRWAVE TCWV fields derived from the two sensors were successfully compared with the vertically integrated water vapour content simulated with the Weather Research and Forecasting (WRF) numerical model for the same time period, confirming our findings. Wave parameters such as amplitude, wavelength and phase are described through the use of the Morlet continuous wavelet transformation (CWT). The performed analysis derived typical wavelengths from 6 to 8 km and amplitudes of up to 20 kg m−2.

Validation of Integrated Water-Vapor Content from GNSS Data of Ground-Based Measurements

Time series of integrated water-vapor (IWV) content for 2015–2017 at eight paired GNSS stations and solar photometry data from the AERONET network in Europe have been compared. The distance between station pairs was no more than 20 km. The average and standard deviations of discrepancies have been shown to vary seasonally. The GNSS–photometer bias in winter was from –0.61 to 0.34 mm. The IWV content in summer is overestimated by the GNSS relative to photometers by 0.52 to 2.26 mm. The standard deviation is from 1.31 to 1.64 mm with a maximum in summer and decreases to 0.49–0.86 mm in winter, which is 5–6% of IWV.

Forecasting of poor visibility episodes in the vicinity of Tenerife Norte Airport

Aviation safety is a priority that may be compromised by adverse weather conditions. This is the case for poor visibility in the vicinity of airports, which can pose a risk during takeoff and landing. For airports that are prone to fog because of their location, an accurate forecast of poor-visibility episodes is vital. However, the forecasting of low clouds is still a challenge in numerical weather prediction, especially when an airport is near complex terrain for which the use of non-hydrostatic mesoscale models is mandatory. All these factors are present at Tenerife Norte Airport, which is commonly affected by poor visibility from low clouds related to persistent trade winds and moist flows from the Atlantic Ocean.In this paper, several methods for estimating visibility based on mesoscale model outputs are tested. Use of the HARMONIE-AROME model is encouraged because of its excellent performance in the detection of poor-visibility episodes (False Alarm Ratio = 0.34–0.38; Frequency Of Misses = 0.22–0.38, depending on the model version and method used). In addition, the use of satellite application facilities is proposed for the nowcasting of low clouds affecting the airport area. Specifically, we used products that estimate cloud type, cloud top altitude, and integrated water vapor content in the boundary layer. Finally, an application is presented for the monitoring of weather conditions in real time to estimate poor-visibility risk.

A Climatology of Strong Large-Scale Ocean Evaporation Events. Part I: Identification, Global Distribution, and Associated Climate Conditions

AbstractThis paper presents an object-based, global climatology (1979–2014) of strong large-scale ocean evaporation (SLOE) and its associated climatic properties. SLOE is diagnosed using an “atmospheric moisture uptake efficiency” criterion related to the ratio of surface evaporation and integrated water vapor content in the near-surface atmosphere. The chosen Eulerian identification procedure focuses on events that strongly contribute to the available near-surface atmospheric humidity. SLOE is particularly frequent along the warm ocean western boundary currents, downstream of large continental areas, and at the sea ice edge in polar regions with frequent cold-air outbreaks. Furthermore, wind-driven SLOE occurs in regions with topographically enforced winds. On a global annual average, SLOE occurs only 6% of the time but explains 22% of total ocean evaporation. An analysis of the past history and fate of air parcels involved in cold season SLOE in the North Atlantic and south Indian Oceans shows that cold-air advection is the main mechanism that induces these events. Extratropical cyclones thereby play an important role in setting the necessary equatorward synoptic flow. Consequently, the interannual variability of SLOE associated with the North Atlantic Oscillation and the southern annular mode reveals a very high sensitivity of SLOE with respect to the location of the storm tracks. This study highlights the strong link between transient synoptic events and the spatiotemporal variability in ocean evaporation patterns, which cannot be deduced from thermodynamic steady-state and climate mean state considerations alone.

Diurnal variation of the tropospheric water vapour over a coastal and an inland station in Southern Indian Peninsula

Diurnal variation of atmospheric water vapour in the troposphere over two tropical stations Trivandrum (8.5°N, 76.9°E) and Gadanki (13.5°N, 79.2°E) are studied using radiosonde observations for three years (December 2010–March 2014) carried out as part of Tropical Tropopause dynamics (TTD) campaigns under CAWSES (Climate And Weather of the Sun-Earth System) India Phase II program. Trivandrum is a coastal station and Gadanki an inland station in the Indian Peninsula. Even though the absolute value of columnar integrated water vapour content (IWV) is higher over Trivandrum in all the seasons, the amplitude of its diurnal variation is almost the same (∼± 5–8 kg m−2) at both the stations with lower values during the day and higher values during night. Though the absolute humidity decreases exponentially with altitude, the amplitude of normalized diurnal anomaly is more-or-less the same (15–20%) from the surface up to 10 km in all the seasons. There exists a time difference in the peaking hours of water vapour density between the two stations with Gadanki always leading Trivandrum. While the water vapour density maximizes around midnight over Trivandrum, it peaks in the late evening over Gadanki. Harmonic analysis shows that the diurnal and semi-diurnal components together account for almost all the sub-daily variations in IWV and absolute humidity. The contribution of semi-diurnal component is only 25% of that of the diurnal component. Diurnal variation of surface wind speed and direction together with the vertical motion associated with convection regulated by the diurnal variation in temperature seems to play the lead role in causing the diurnal variation in water vapour. While the diurnal variation over Gadanki is mainly controlled by the convectively induced vertical motion, the diurnal variation in the rate of evaporation due to surface wind and local circulation also plays a significant role over Trivandrum.

Revising shortwave and longwave radiation archives in view of possible revisions of the WSG and WISG reference scales: methods and implications

Abstract. A large number of radiometers are traceable to the World Standard Group (WSG) for shortwave radiation and the interim World Infrared Standard Group (WISG) for longwave radiation, hosted by the Physikalisch-Meteorologisches Observatorium Davos/World Radiation Centre (PMOD/WRC, Davos, Switzerland). The WSG and WISG have recently been found to over- and underestimate radiation values, respectively (Fehlmann et al., 2012; Gröbner et al., 2014), although research is still ongoing. In view of a possible revision of the reference scales of both standard groups, this study discusses the methods involved and the implications on existing archives of radiation time series, such as the Baseline Surface Radiation Network (BSRN). Based on PMOD/WRC calibration archives and BSRN data archives, the downward longwave radiation (DLR) time series over the 2006–2015 period were analysed at four stations (polar and mid-latitude locations). DLR was found to increase by up to 3.5 and 5.4 W m−2 for all-sky and clear-sky conditions, respectively, after applying a WISG reference scale correction and a minor correction for the dependence of pyrgeometer sensitivity on atmospheric integrated water vapour content. Similar increases in DLR may be expected at other BSRN stations. Based on our analysis, a number of recommendations are made for future studies.

Improvements in Atmospheric Water Vapor Content Retrievals Over Open Oceans From Satellite Passive Microwave Radiometers

The study is dedicated to the development of an improved algorithm for integrated water vapor content (WVC) retrieval from the advanced microwave sounding radiometer 2 (AMSR2) measurement data over open ocean areas. The algorithm is based on physical modeling of the brightness temperature (BT) of the upwelling radiation of the atmosphere – ocean system. The BT inversion is carried out with neural networks (NNs), trained on an ensemble of BTs, calculated using the dataset of the atmospheric and oceanic parameters. The improvement in the WVC retrieval algorithm as compared to previously developed one is associated, first, with the usage of the new ocean emissivity empirical model and, second, with the exclusion of the vertically polarized BT from NNs inputs. The new model was incorporated into the BT geophysical model and a new set of NNs coefficients was obtained for WVC algorithm. Though the results of the numerical experiment demonstrate higher retrieval accuracy for the old version of the NN model, real-valued validation with global positioning system (GPS) WVC shows better performance of the new NN model with the excluded vertically polarized AMSR2 BT from the NNs algorithm inputs. The advantages of the new algorithm are the most remarkable under conditions of high winds. This is confirmed by the validation based on the database of GPS WVC measurements under extreme winds. The improved WVC retrieval algorithm is mostly beneficial for the studies of extreme weather events such as polar lows, extratropical and tropical cyclones, associated with high winds.

Algorithm for Recovery of Integrated Water Vapor Content in the Atmosphere over Land Surfaces Based on Satellite Spectroradiometer Data

An algorithm is proposed for making charts of the distribution of water vapor in the atmosphere based on multispectral images of the earth by the Ocean and Land Color Instrument (OLCI) on board of the European research satellite Sentinel-3. The algorithm is based on multiple regression fits of the spectral brightness coefficients at the upper boundary of the atmosphere, the geometric parameters of the satellite location (solar and viewing angles), and the total water vapor content in the atmosphere. A regression equation is derived from experimental data on the variation in the optical characteristics of the atmosphere and underlying surface, together with Monte-Carlo calculations of the radiative transfer characteristics. The equation includes the brightness coefficients in the near IR channels of the OLCI for the absorption bands of water vapor and oxygen, as well as for the transparency windows of the atmosphere. Together these make it possible to eliminate the effect of the reflection spectrum of the underlying surface and air pressure on the accuracy of the measurements. The algorithm is tested using data from a prototype OLCI, the medium resolution imaging spectrometer (MERIS). A sample chart of the distribution of water vapor in the atmosphere over Eastern Europe is constructed without using subsatellite data and digital models of the surface relief. The water vapor contents in the atmosphere determined using MERIS images and data provided by earthbound measurements with the aerosol robotic network (AERONET) are compared with a mean square deviation of 1.24 kg/m2.

Diurnal variations in integrated water vapor derived from a GPS ground network in the Volga–Ural region of Russia

Abstract. In this article, we present estimates of diurnal and semidiurnal harmonics of variations in integrated water vapor content (IWV) according to data from 16 GPS stations in the Volga–Ural region of Russia during 2013–2015. Amplitudes of diurnal harmonics are maximal in summer and reach values from 0.37 to 1.01 mm. Time at the maximum of diurnal harmonic is typically in the period from 14:00 to 17:00. Semidiurnal harmonics have the largest amplitudes in spring and autumn, but they do not exceed 0.19 mm. A comparison of the diurnal cycle from GPS data and ERA-Interim reanalysis has revealed significant differences in the phase. It is established that, as a result of evaporation from the underlying surface and convective lifting of moist air, the summer diurnal variations in IWV and surface density of water vapor are in antiphase. The diurnal cycle of IWV is determined by surface air temperature to be 88 % in summer and less than at 35 % in other seasons. It is noted that maximal amplitudes of diurnal harmonic of IWV are observed at stations located on the windward side of mountains.

Extreme daily precipitation in coastal western Norway and the link to atmospheric rivers

AbstractThis work investigates the link between the most extreme daily precipitation (EDP) events observed since 1900 on the west coast of Norway and the large‐scale moisture fluxes over the North Atlantic Ocean. Using station precipitation data, vertically integrated water vapor (IWV) from Special Sensors Microwave Imager/Sounder (SSMIS) satellite observations and the state of the art NOAA‐twentieth Century (NOAA‐20C) reanalysis, it is shown that 55 out of 58 EDPs are associated with narrow plumes of intense low‐level moisture defined as atmospheric rivers. Despite the high spatial correlation between IWV fields in the SSMIS and NOAA‐20C data sets, the significant positive relationship between the maximum amount of observed precipitation at all stations and the IWV content hitting the coastal terrain is only observed in the SSMIS data set. Further, the composite analyses of synoptic conditions show that the preferred circulation type consists of a mean sea level pressure (MSLP) dipole pattern where a high‐pressure system over central Europe and a series of low‐pressure systems to the east of Iceland and over the Norwegian Sea are present. The west coast of Norway is located in the exit region of the anticyclonically curved upper tropospheric polar jet stream implying that the coupling of upper troposphere and surface dynamics begins to weaken at the time of EDPs. It is also found that the primary synoptic‐scale precursors are persistent positive 500 hPa height geopotential and MSLP anomalies over central Europe up to 10 days before the occurrence of EDP events.

Modeling and Synthesis of 3-D Water Vapor Fields for EM Wave Propagation Applications

Stochastic model of water vapor (SMOV), a methodology to generate realistic 3-D spatially correlated water vapor fields, is presented, which is devised by investigating remote sensing observations acquired by the MODIS sensor (Aqua satellite). Synthetic water vapor fields are $200~\text {km} \times 200$ km, with $1~\text {km} \times 1$ km horizontal spatial resolution, while the water vapor content $v$ extends up to 20 km with a vertical sampling of 100 m. The field synthesis relies on the stochastic approach proposed by Bell and requires as input the average integrated water vapor content provided with coarse spatial and temporal resolution by numerical weather prediction (NWP) products. The vertical profile of $v$ is modeled as a simple exponential function decreasing with height, as observed from typical radiosonde observations and NWP data. Tests on the model’s accuracy show that both first-order (complementary cumulative distribution function) and second-order (spatial distribution) statistics of the integrated water vapor content are closely reproduced in several European sites. Results corroborate the use of SMOV as part of a comprehensive simulator of atmospheric impairments, which aims at taking into account all the constituents affecting the propagation of millimeter waves in different scenarios, including applications involving very low elevation links such as unmanned aerial vehicles and low Earth orbit satellites.

Improving the Accuracy in Predicting Water-Vapor Attenuation at Millimeter-Wave for Earth-Space Applications

This contribution focuses on improving the accuracy of the simplified method currently recommended by the ITU-R for the prediction of water-vapor attenuation at millimeter-wave on Earth-space links (Annex 2, paragraph 2.3 of recommendation ITU-R P.676-10), which receives as input only the local integrated water-vapor content $V$ . The main improvement to such model originates from taking into account the dependence of the water-vapor mass absorption coefficient $a_{V}$ on the reference site altitude, which is investigated by taking advantage of an extensive set of radiosonde observations (RAOBS) collected in several sites worldwide and characterized by high accuracy and reliability. Tested against attenuation estimates obtained from the mass absorption models coupled with the mentioned RAOBS data, the model’s prediction accuracy turns out to improve significantly with respect to the current recommendation and to be less dependent both on the operational frequency (20–100 GHz range) and on the considered site.