Water Vapor Fields Research Articles

The Life Cycles of Ice Crystals Detrained From the Tops of Deep Convection

AbstractExtensive anvil cirrus clouds generated by deep convection have important impacts on the Earth's radiation budget and climate. We use growth‐sedimentation trajectory calculations to investigate the life cycles of anvil ice crystals as they are advected downwind from their convective source. Temperature, water vapor, and wind fields from a cloud‐resolving model simulation of an isolated cumulonimbus cloud are used to drive the calculations. Ice crystals are initialized in the main upper‐level detrainment zone with a size distribution based on in situ measurements made in a convective core at about 12 km. Advection, deposition growth, and sedimentation of thousands of sample ice crystals are tracked over about 2.5 hr; neither aggregation of ice crystals nor radiative effects are included. Results support the importance of deposition growth and gravitational size sorting in the evolution of the anvil cirrus. Most ice crystals initialized with maximum dimensions larger than about 200 μm fall out of the anvil and sublimate in subsaturated air below within about 2 hr. Few small ice crystals are present in the lower part of the mature anvil. Vapor deposition growth accounts for about 50% of the ice mass remaining after about 2 hr. Ice crystals larger than about 50 μm in the mature anvil have grown substantially by deposition of vapor. This result is consistent with the predominance of bullet rosette habits observed in mature anvils. Variations in ice crystal fall speeds and growth rates associated with ice crystal habit assumptions have little impact on the ice crystal life cycles.

Influence of Irregularities of Water Vapor Field in Surface Layer of the Atmosphere on the Results of Satellite Monitoring of Hydropower Structures in Region of Reservoirs

Results are presented for the modeling of coordinate errors in the projected GNSS system of monitoring the Zagorsk GAES-2 that are caused by local atmospheric irregularities in the surface layer. It has been established that for mean meteorological conditions, these errors can reach 0.8 mm for elevation and 0.1 mm for horizontal position. It is noted that actual instantaneous irregularities exceed mean values by an order of magnitude and can thus cause larger errors in coordinates.

Troposphere Water Vapour Tomography: A Horizontal Parameterised Approach

Global Navigation Satellite System (GNSS) troposphere tomography has become one of the most cost-effective means to obtain three-dimensional (3-d) image of the tropospheric water vapour field. Traditional methods divide the tomography area into a number of 3-d voxels and assume that the water vapour density at any voxel is a constant during the given period. However, such behaviour breaks the spatial continuity of water vapour density in a horizontal direction and the number of unknown parameters needing to be estimated is very large. This is the focus of the paper, which tries to reconstruct the water vapor field using the tomographic technique without imposing empirical horizontal and vertical constraints. The proposed approach introduces the layered functional model in each layer vertically and only an a priori constraint is imposed for the water vapor information at the location of the radiosonde station. The elevation angle mask of 30° is determined according to the distribution of intersections between the satellite rays and different layers, which avoids the impact of ray bending and the error in slant water vapor (SWV) at low elevation angles on the tomographic result. Additionally, an optimal weighting strategy is applied to the established tomographic model to obtain a reasonable result. The tomographic experiment is performed using Global Positioning System (GPS) data of 12 receivers derived from the Satellite Positioning Reference Station Network (SatRef) in Hong Kong. The quality of the established tomographic model is validated under different weather conditions and compared with the conventional tomography method using 31-day data, respectively. The numerical result shows that the proposed method is applicable and superior to the traditional one. Comparisons of integrated water vapour (IWV) of the proposed method with that derived from radiosonde and European Centre for Medium-Range Weather Forecasts (ECMWF) ERA-Interim data show that the root mean square (RMS)/Bias of their differences are 3.2/−0.8 mm and 3.3/−1.7 mm, respectively, while the values of traditional method are 5.1/−3.9 mm and 6.3/−5.9 mm, respectively. Furthermore, the water vapour density profiles are also compared with radiosonde and ECMWF data, and the values of RMS/Bias error for the proposed method are 0.88/0.06 g/m3 and 0.92/−0.08 g/m3, respectively, while the values of the traditional method are 1.33/0.38 g/m3 and 1.59/0.40 g/m3, respectively.

An optimal tropospheric tomography approach with the support of an auxiliary area

Abstract. Among most current tropospheric tomography studies, only the signals crossing out from the top boundary of the tomographic area are used for reconstructing the three-dimensional water vapour field, while signals penetrating from the side faces of the tomographic body are ignored as invalid information. Such a method wastes the valuable Global Navigation Satellite System (GNSS) observations and decreases the utilisation efficiency of GNSS rays. This is the focus of this paper, which tries to effectively use signals penetrating from the side faces of the tomographic body for water vapour reconstruction. An optimised tropospheric tomography method is proposed using an auxiliary area. The top height of the tomography body is determined based on the average water vapour distribution derived from the Constellation Observing System for Meteorology, Ionosphere, and Climate (COSMIC) radio occultation (RO) products. In addition, the coefficients of a negative exponential function between the adjacent layers for vertical constraints are fitted using the COSMIC RO profiles. Thirteen GPS stations are selected in the CORS Network of Texas to perform the tomographic experiment and validate the performance of the proposed method at 00:00 and 12:00 UTC daily using the radiosonde data for a period of 15 days. Compared to the conventional method, the accuracy of the reconstructed water vapour information derived from the proposed method is increased by 14.37 % and 16.13 %, respectively, in terms of mean root mean square (rms) and mean absolute error (MAE). The tomographic results obtained from the proposed method are further validated with the slant water vapour (SWV) data derived using the GAMIT (GNSS processing software package). Results show that the rms and MAE accuracy of SWV values has been improved by 18.18 % and 27.62 %, respectively, when compared to the conventional method. Keywords. History of geophysics (atmospheric sciences)

Validation of the Advanced Infra-Red Water Vapour Estimator (AIRWAVE) Total Column Water Vapour using Satellite and Radiosonde products.

The Along Track Scanning Radiometer (ATSR) instrument series, on board the European Space Agency (ESA)’s European Remote Sensing (ERS) satellites, ERS-1/2 and the ENVIronmental SATellite (ENVISAT), covered the time period from 1991 to 2012. Using the infra-red channels at 11 and 12 microns (available for both day and night and for all the three instruments) and combining nadir and forward geometries, Total Column Water Vapour (TCWV) fields have been obtained over the sea in cloud free scenarios. The retrieval scheme, named Advanced InfraRed Water Vapor Estimator (AIRWAVE), exploits the instrument physical characteristics (dual view and two channels), in combination with advanced radiative transfer models and a sea surface spectral emissivity database. The algorithm makes use of a set of tabulated parameters, fixed along the whole globe. Here, the AIRWAVE dataset is compared with the satellite data of the Special Sensor Microwave/Imager (SSM/I) and with available stations from the Analyzed RadioSoundings Archive (ARSA). Both comparisons demonstrated the good quality of the AIRWAVE dataset. However, they also highlighted the presence of a dry bias at high latitudes. Globally, we found an average correlative-AIRWAVE bias of 0.72 kg/m2 (RMSE=5.79 kg/m2) vs SSM/I and 0.80 kg/m2 (RMSE=7.77 kg/m2) vs ARSA.

The Role of the Water Vapor Feedback in the ITCZ Response to Hemispherically Asymmetric Forcings

In comprehensive and idealized general circulation models, hemispherically asymmetric forcings lead to shifts in the latitude of the intertropical convergence zone (ITCZ). Prior studies using comprehensive GCMs (with complicated parameterizations of radiation, clouds, and convection) suggest that the water vapor feedback tends to amplify the movement of the ITCZ in response to a given hemispherically asymmetric forcing, but this effect has yet to be elucidated in isolation. This study uses an idealized moist model, coupled to a full radiative transfer code, but without clouds, to examine the role of the water vapor feedback in a targeted manner.In experiments with interactive water vapor and radiation, the ITCZ latitude shifts roughly twice as much off the equator as in cases with the water vapor field seen by the radiation code prescribed to a static hemisperically symmetric control distribution. Using energy flux equator theory for the latitude of the ITCZ, the amplification of the ITCZ shift is attributed primarily to the longwave water vapor absorption associated with the movement of the ITCZ into the warmer hemisphere, further increasing the net column heating asymmetry. Local amplification of the imposed forcing by the shortwave water vapor feedback plays a secondary role. Experiments varying the convective relaxation time, an important parameter in the convection scheme used in the idealized moist model, yield qualitatively similar results, suggesting some degree of robustness to the model physics; however, the sensitivity experiments do not preclude that more extreme modifications to the convection scheme could lead to qualitatively different behavior.

Single-footprint retrievals of temperature, water vapor and cloud properties from AIRS

Abstract. Single-footprint Atmospheric Infrared Sounder spectra are used in an optimal estimation-based algorithm (AIRS-OE) for simultaneous retrieval of atmospheric temperature, water vapor, surface temperature, cloud-top temperature, effective cloud optical depth and effective cloud particle radius. In a departure from currently operational AIRS retrievals (AIRS V6), cloud scattering and absorption are in the radiative transfer forward model and AIRS single-footprint thermal infrared data are used directly rather than cloud-cleared spectra (which are calculated using nine adjacent AIRS infrared footprints). Coincident MODIS cloud data are used for cloud a priori data. Using single-footprint spectra improves the horizontal resolution of the AIRS retrieval from ∼ 45 to ∼ 13.5 km at nadir, but as microwave data are not used, the retrieval is not made at altitudes below thick clouds. An outline of the AIRS-OE retrieval procedure and information content analysis is presented. Initial comparisons of AIRS-OE to AIRS V6 results show increased horizontal detail in the water vapor and relative humidity fields in the free troposphere above the clouds. Initial comparisons of temperature, water vapor and relative humidity profiles with coincident radiosondes show good agreement. Future improvements to the retrieval algorithm, and to the forward model in particular, are discussed.

Spatial Heterodyne Observations of Water (SHOW) vapour in the upper troposphere and lower stratosphere from a high altitude aircraft: Modelling and sensitivity analysis

A spatial heterodyne spectrometer (SHS) has been developed to measure the vertical distribution of water vapour in the upper troposphere and the lower stratosphere with a high vertical resolution (∼500 m). The Spatial Heterodyne Observations of Water (SHOW) instrument combines an imaging system with a monolithic field-widened SHS to observe limb scattered sunlight in a vibrational band of water (1363 nm–1366 nm). The instrument has been optimized for observations from NASA's ER-2 aircraft as a proof-of-concept for a future low earth orbit satellite deployment. A robust model has been developed to simulate SHOW ER-2 limb measurements and retrievals. This paper presents the simulation of the SHOW ER-2 limb measurements along a hypothetical flight track and examines the sensitivity of the measurement and retrieval approach. Water vapour fields from an Environment and Climate Change Canada forecast model are used to represent realistic spatial variability along the flight path. High spectral resolution limb scattered radiances are simulated using the SASKTRAN radiative transfer model. It is shown that the SHOW instrument onboard the ER-2 is capable of resolving the water vapour variability in the UTLS from approximately 12 km – 18 km with ±1 ppm accuracy. Vertical resolutions between 500 m and 1 km are feasible. The along track sampling capability of the instrument is also discussed.

Accuracy and reliability of tropospheric wet refractivity tomography with GPS, BDS, and GLONASS observations

Tropospheric tomography has been developed as a promising tool with which to model the three-dimensional (3-d) spatio-temporal distribution of water vapour field using Global Positioning System (GPS) observations. With the development of multi-GNSS, the accuracy and reliability of tomography using multi-GNSS observations remains to be verified. The observed multi-GNSS (GPS, GLONASS, and BDS) data, are first used to validate the tomographic results derived from various multi-GNSS combined strategies and compared with radiosonde data. In addition, the top boundary of the tomography area is determined based on the variations of water vapour with altitude derived from the COSMIC RO profiles for the period from 2006 to 2016. Tomography experiments were carried out with the 7-day data from six stations in the CORS Network at Guiyang, China. Numerical results reveal that the use of multi-GNSS data can increase the number of satellite rays used and consequently improve the coverage rate of voxels crossed by rays. Tomographic results also show that multi-GNSS observations can increase the accuracy of 3-d wet refractivity reconstruction but not as well as was expected when using currently available techniques.

Lagrangian condensation microphysics with Twomey CCN activation

Abstract. We report the development of a novel Lagrangian microphysics methodology for simulations of warm ice-free clouds. The approach applies the traditional Eulerian method for the momentum and continuous thermodynamic fields such as the temperature and water vapor mixing ratio, and uses Lagrangian super-droplets to represent condensed phase such as cloud droplets and drizzle or rain drops. In other applications of the Lagrangian warm-rain microphysics, the super-droplets outside clouds represent unactivated cloud condensation nuclei (CCN) that become activated upon entering a cloud and can further grow through diffusional and collisional processes. The original methodology allows for the detailed study of not only effects of CCN on cloud microphysics and dynamics, but also CCN processing by a cloud. However, when cloud processing is not of interest, a simpler and computationally more efficient approach can be used with super-droplets forming only when CCN is activated and no super-droplet existing outside a cloud. This is possible by applying the Twomey activation scheme where the local supersaturation dictates the concentration of cloud droplets that need to be present inside a cloudy volume, as typically used in Eulerian bin microphysics schemes. Since a cloud volume is a small fraction of the computational domain volume, the Twomey super-droplets provide significant computational advantage when compared to the original super-droplet methodology. Additional advantage comes from significantly longer time steps that can be used when modeling of CCN deliquescence is avoided. Moreover, other formulation of the droplet activation can be applied in case of low vertical resolution of the host model, for instance, linking the concentration of activated cloud droplets to the local updraft speed. This paper discusses the development and testing of the Twomey super-droplet methodology, focusing on the activation and diffusional growth. Details of the activation implementation, transport of super-droplets in the physical space, and the coupling between super-droplets and the Eulerian temperature and water vapor field are discussed in detail. Some of these are relevant to the original super-droplet methodology as well and to the ice phase modeling using the Lagrangian approach. As a computational example, the scheme is applied to an idealized moist thermal rising in a stratified environment, with the original super-droplet methodology providing a benchmark to which the new scheme is compared.

A Scheme to Assimilate “No Rain” Observations from Doppler Radar

Abstract Radar reflectivity observations contain valuable information on precipitation and have been assimilated into numerical weather prediction models for improved microphysics initialization. However, low-reflectivity (or so-called no rain) echoes have often been ignored or not effectively used in radar data assimilation schemes. In this paper, a scheme to assimilate no-rain radar observations is described within the framework of the Weather Research and Forecasting Model’s three-dimensional variational data assimilation (3DVar) system, and its impact on precipitation forecasts is demonstrated. The key feature of the scheme is a neighborhood-based approach to adjusting water vapor when a grid point is deemed as no rain. The performance of the scheme is first examined using a severe convective case in the Front Range of the Colorado Rocky Mountains and then verified by running the 3DVar system in the same region, with and without the no-rain assimilation scheme for 68 days and 3-hourly rapid update cycles. It is shown that the no-rain data assimilation method reduces the bias and false alarm ratio of precipitation over its counterpart without that assimilation. The no-rain assimilation also improved humidity, temperature, and wind fields, with the largest error reduction in the water vapor field, both near the surface and at upper levels. It is also shown that the advantage of the scheme is in its ability to conserve total water content in cycled radar data assimilation, which cannot be achieved by assimilating only precipitation echoes.

Comparison of 3DVar and EnSRF Data Assimilation Using Radar Observations for the Analysis and Prediction of an MCS

Using radar observations, the performances of the ensemble square root filter (EnSRF) and an indirect three-dimensional variational (3DVar) data assimilation method were compared for a mesoscale convective system (MCS) that occurred in the Front Range of the Rocky Mountains, Colorado (USA). The results showed that the root mean square innovations (RMSIs) of EnSRF were lower than 3DVar for radar reflectivity and radial velocity and that the spread of EnSRF was generally consistent with its RMSIs. EnSRF substantially improved the analysis of the MCS compared with an experiment without radar data assimilation, and it produced a slight but noticeable improvement over 3DVar in terms of both coverage and intensity. Forecast results initiated from the final analysis revealed that EnSRF generally produced the best prediction of the MCS, with improved quantitative reflectivity and precipitation forecast skills. EnSRF also demonstrated better performance than 3DVar in the prediction of neighborhood probability for reflectivity at thresholds of 20 and 35 dBZ, which better matched the observed radar reflectivity in terms of both shape and extension. Additionally, the humidity, temperature, and wind fields were also improved by EnSRF; the largest error reduction was found in the water vapor field near the surface and at upper levels.

Representative Height of the Low-Level Water Vapor Field for Examining the Initiation of Moist Convection Leading to Heavy Rainfall in East Asia

Representative Height of the Low-Level Water Vapor Field for Examining the Initiation of Moist Convection Leading to Heavy Rainfall in East Asia

An Observational View of Relationships Between Moisture Aggregation, Cloud, and Radiative Heating Profiles

Data from several coincident satellite sensors are analyzed to determine the dependence of cloud and precipitation characteristics of tropical regions on the variance in the water vapor field. Increased vapor variance is associated with decreased high cloud fraction and an enhancement of low-level radiative cooling in dry regions of the domain. The result is found across a range of sea surface temperatures and rain rates. This suggests the possibility of an enhanced low-level circulation feeding the moist convecting areas when vapor variance is large. These findings are consistent with idealized models of self-aggregation, in which the aggregation of convection is maintained by a combination of low-level radiative cooling in dry regions and mid-to-upper-level radiative warming in cloudy regions.

A Comprehensive Methodology to Assess Tropospheric Fade Affecting Earth–Space Communication Systems

ATMospheric simulator for PROPagation applications (ATM PROP), a comprehensive methodology to assess tropospheric effects affecting high-frequency earth–space communication systems, is presented. The model takes advantage of physically based approaches aimed at synthesizing high-resolution (1 km $\times1$ km horizontal, 100-m vertical) 3-D fields of rain, clouds, and water vapor (dimension: 200 km $\times200$ km horizontal, 20-km vertical), which are all merged so as to maintain their mutual correlation. This, in turn, enables a more realistic combination of the attenuation due to single constituents, if compared to the statistical approach currently recommended by the ITU-R. The accuracy of ATM PROP in predicting tropospheric effects on earth–space systems is initially validated against the large propagation data set collected at the experimental station of Spino d’Adda, Italy, during the ITALSAT propagation campaign. The preliminary results obtained suggest that ATM PROP can be used to predict, with a reasonable level of complexity and limited coarse-resolution Numerical Weather Prediction-derived inputs, the tropospheric fade affecting complex communication systems (e.g., site diversity schemes), especially those involving low elevation links (e.g., low earth orbit or geostationary orbit at high latitude), for which the spatial distribution of the relevant tropospheric constituents needs to be taken in due account.

Assessing the Accuracy of the Cloud and Water Vapor Fields in the Hurricane WRF (HWRF) Model Using Satellite Infrared Brightness Temperatures

Abstract In this study, cycled forecast experiments were performed to assess the ability of different cloud microphysics and cumulus parameterization schemes in the Hurricane Weather Research and Forecasting (HWRF) Model to accurately simulate the evolution of the cloud and moisture fields during the entire life cycle of Hurricane Edouard (2014). The forecast accuracy for each model configuration was evaluated through comparison of observed and simulated Geostationary Operational Environmental Satellite-13 (GOES-13) infrared brightness temperatures and satellite-derived tropical cyclone intensity estimates computed using the advanced Dvorak technique (ADT). Overall, the analysis revealed a large moist bias in the mid- and upper troposphere during the entire forecast period that was at least partially due to a moist bias in the initialization datasets but was also affected by the microphysics and cumulus parameterization schemes. Large differences occurred in the azimuthal brightness temperature distributions, with two of the microphysics schemes producing hurricane eyes that were much larger and clearer than observed, especially for later forecast hours. Comparisons to the forecast 10-m wind speeds showed reasonable agreement (correlations between 0.58 and 0.74) between the surface-based intensities and the ADT intensity estimates inferred via cloud patterns in the upper troposphere. It was also found that model configurations that had the smallest differences between the ADT and surface-based intensities had the most accurate track and intensity forecasts. Last, the cloud microphysics schemes had the largest impact on the forecast accuracy.

Tangent linear superparameterization of convection in a 10 layer global atmosphere with calibrated climatology

AbstractThis paper describes a new intermediate global atmosphere model in which synoptic and planetary dynamics including the advection of water vapor are explicit in 10 layers, the time‐mean flow is centered near a realistic state through the use of carefully calibrated time‐independent 3‐D forcings, and temporal anomalies of convective tendencies of heat and moisture in each column are represented as a linear matrix acting on the anomalous temperature and moisture profiles. Currently, this matrix is Kuang's [] linear response function (LRF) of a cyclic convection‐permitting model (CCPM) in equilibrium with specified atmospheric cooling (i.e., without radiation or WISHE interactions, so it conserves column moist static energy exactly). The goal of this effort is to cleanly test the role of convection's free‐tropospheric moisture sensitivity in tropical waves, without incurring large changes of mean climate that confuse the interpretation of experiments with entrainment parameters in the convection schemes of full‐physics GCMs. When the sensitivity to free‐tropospheric moisture is multiplied by a factor ranging from 0 to 2, the model's variability ranges from: (1) moderately strong convectively coupled Kelvin waves with speeds near 20 m s−1; to (0) similar but much weaker waves; to (2) similar but stronger and slightly faster waves as the water vapor field plays an increasingly important role. Longitudinal structure in the model's time‐mean tropical flow is not fully realistic, and does change significantly with matrix‐coupled variability, but further work on editing the anomaly physics matrix and calibrating the mean state could improve this class of models.

Relationships between radiation, clouds, and convection during DYNAMO.

The relationships between radiation, clouds, and convection on an intraseasonal time scale are examined with data taken during the Dynamics of the Madden-Julian Oscillation (MJO) field campaign. Specifically, column-net, as well as vertical profiles of radiative heating rates, computed over Gan Island in the central Indian Ocean (IO) are used along with an objective analysis of large-scale fields to examine three MJO events that occurred during the 3 month period (October to December 2011) over this region. Longwave (LW) and shortwave radiative heating rates exhibit tilted structures, reflecting radiative effects associated with the prevalence of shallow cumulus during the dry, suppressed MJO phase followed by increasing deep convection leading into the active phase. As the convection builds going into the MJO active phase, there are increasingly top-heavy anomalous radiative heating rates while the column-net radiative cooling rate <Qr > progressively decreases. Temporal fluctuations in the cloud radiative forcing, being quite sensitive to changes in high cloudiness, are dominated by LW effects with an intraseasonal variation of ~0.4-0.6 K/d. While both the water vapor and cloud fields are inextricably linked, it appears that the tilted radiative structures are more related to water vapor effects. The intraseasonal variation of column-net radiative heating <Qr > enhances the convective signal in the mean by ~20% with a minimum in this enhancement ~10 days prior to peak MJO rainfall and maximum ~7 days after. This suggests that as MJO convective envelope weakens over the central IO, cloud-radiative feedbacks help maintain the mature MJO as it moves eastward.

Generation of real‐time mode high‐resolution water vapor fields from GPS observations

AbstractPointwise GPS measurements of tropospheric zenith total delay can be interpolated to provide high‐resolution water vapor maps which may be used for correcting synthetic aperture radar images, for numeral weather prediction, and for correcting Network Real‐time Kinematic GPS observations. Several previous studies have addressed the importance of the elevation dependency of water vapor, but it is often a challenge to separate elevation‐dependent tropospheric delays from turbulent components. In this paper, we present an iterative tropospheric decomposition interpolation model that decouples the elevation and turbulent tropospheric delay components. For a 150 km × 150 km California study region, we estimate real‐time mode zenith total delays at 41 GPS stations over 1 year by using the precise point positioning technique and demonstrate that the decoupled interpolation model generates improved high‐resolution tropospheric delay maps compared with previous tropospheric turbulence‐ and elevation‐dependent models. Cross validation of the GPS zenith total delays yields an RMS error of 4.6 mm with the decoupled interpolation model, compared with 8.4 mm with the previous model. On converting the GPS zenith wet delays to precipitable water vapor and interpolating to 1 km grid cells across the region, validations with the Moderate Resolution Imaging Spectroradiometer near‐IR water vapor product show 1.7 mm RMS differences by using the decoupled model, compared with 2.0 mm for the previous interpolation model. Such results are obtained without differencing the tropospheric delays or water vapor estimates in time or space, while the errors are similar over flat and mountainous terrains, as well as for both inland and coastal areas.

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.