Sensors
- ERA5 reanalysis (ECMWF): Hourly global atmospheric profiles at 0.25-degree (~31 km) horizontal resolution and 137 pressure levels from 1940 to near-real-time. Wet-term refractivity N_wet can be computed directly from specific humidity and temperature profiles, giving the primary input to ITU-R P.618 scintillation models.
- GNSS precipitable water vapour (GNSS-PWV) networks: Ground-based GNSS receivers (IGS, EUREF, regional networks) recover zenith total delay with sub-millimetre precision, convertible to precipitable water vapour (PWV) at sub-hourly cadence. Point measurements but high temporal resolution; best used to validate and bias-correct reanalysis estimates at candidate sites.
- MODIS MOD05 total precipitable water: Terra and Aqua MODIS retrieve column water vapour at 1 km (near-infrared, clear-sky only) and 5 km (infrared, day and night) resolution, with twice-daily global coverage per satellite. Useful for spatial mapping of PWV gradients across a candidate site region, though the clear-sky restriction is a real limit for persistently humid areas.
- Sentinel-5P TROPOMI: Daily global coverage at 5.5 km x 3.5 km pixel resolution (post-2019 upgrade). TROPOMI retrieves total water vapour column in the near-infrared; the dataset is freely accessible via the Copernicus Data Space. Useful for multi-year trend analysis and for regions where GNSS network density is low.
Why scintillation is not rain fade wearing a different hat
Rain fade and tropospheric scintillation share a frequency dependency but have almost nothing else in common. Rain fade requires liquid water in the path. Scintillation does not. It is caused by small-scale turbulent mixing of air parcels with different refractive indices, driven by humidity gradients in the boundary layer. At Ka-band (26.5 to 40 GHz) and Q-band (33 to 50 GHz), the wet term of the refractivity equation dominates, so humid tropical and subtropical regions suffer most. The effect is worst at low elevation angles, where the signal traverses a longer path through the turbulent boundary layer.
The ITU-R P.618-14 model quantifies scintillation fade depth as a function of elevation angle, antenna diameter, frequency and a site-specific parameter: the long-term standard deviation of wet-term refractivity fluctuations, derived from surface meteorological data or, more reliably, from the integrated water vapour profile. Getting that site parameter right is the whole problem. A site that looks identical on a rain-rate map may differ by several tenths of a dB in scintillation fade depth from a site 50 km away, simply because of local boundary-layer humidity variance.
What the reanalysis actually gives you, and what it does not
ERA5 provides hourly specific humidity, temperature and pressure on 137 model levels from the surface to 0.01 hPa. From these, N_wet (the wet refractivity term) can be integrated through the troposphere to compute the Cn2 proxy that feeds scintillation intensity estimates. Run across a 10- to 20-year ERA5 archive, this produces a climatology of scintillation standard deviation at each grid point, which can then be fed into the P.618 availability model for any elevation angle and link frequency of interest.
The honest limit is spatial resolution. At 0.25 degrees, ERA5 cannot resolve orographic channelling of humid air, sea-breeze fronts, or the micro-scale boundary-layer structure that a coastal site might experience differently from an inland site 20 km away. For flat, homogeneous terrain, the reanalysis is generally adequate for site ranking. For coastal, estuarine or hilly terrain, GNSS-PWV measurements at the actual candidate locations are necessary to validate and correct the reanalysis estimate. MODIS MOD05 and TROPOMI water vapour columns help map spatial gradients between candidate sites but add no vertical profile information.
Building a site-ranking climatology
The workflow has four stages. First, extract ERA5 wet-term profiles at each candidate site for a minimum 10-year period; shorter archives underweight inter-annual variability driven by ENSO or monsoon anomalies. Second, compute the monthly and annual cumulative distribution functions of the integrated wet refractivity standard deviation. Third, apply the P.618-14 scintillation model at the planned elevation angle and frequency to convert those distributions into predicted fade depth at target availability percentages, typically 99.0, 99.5 and 99.9 percent of the year. Fourth, cross-check against any available GNSS-PWV or radiosonde data to assess whether the reanalysis is biased at that location.
The output is a ranked table of candidate sites with predicted scintillation fade margins. A site in a semi-arid highland may show 0.5 to 0.8 dB of scintillation fade at 99.9 percent availability on a Ka-band link at 10-degree elevation. A coastal tropical site at the same elevation angle might show 1.5 to 2.5 dB. That difference directly affects the link budget and, consequently, the antenna aperture or transmit power required to close the link. Getting this wrong at the design stage is expensive.
Where the ITU-R model has known gaps
P.618-14 was calibrated primarily against beacon measurement campaigns in mid-latitude Europe and North America. Its performance in equatorial regions, particularly below 10 degrees elevation, is less well validated. Published studies in the remote sensing literature have documented systematic underestimation of scintillation intensity in tropical coastal environments when the model is fed with standard climatological inputs rather than locally measured refractivity variance. This is not a reason to abandon the model; it is a reason to treat the reanalysis-derived site ranking as a screening tool rather than a final link budget.
TROPOMI water vapour columns can partially compensate for sparse GNSS coverage in data-poor regions. The 5.5 km pixel footprint resolves coastal gradients better than ERA5, and the Sentinel-5P archive from 2018 onwards is freely accessible. The limitation is that a column measurement gives no height information; a given PWV value could reflect a shallow, very humid boundary layer (high scintillation risk) or a deep, moderately humid column (lower risk). Radiosonde profiles, where available, remain the only way to resolve that ambiguity cleanly.
Turning climatology into a procurement decision
A scintillation climatology is most useful when it is expressed in terms the link budget team can directly use: predicted fade depth in dB at specified availability percentages, for the actual planned elevation angle to the target orbital slot, at the operating frequency. A site-comparison report should show those numbers for each candidate, together with the uncertainty range introduced by reanalysis resolution and model calibration limits. Sensitivity tables showing how the fade margin changes if the elevation angle shifts by two or three degrees (as it would for a different orbital slot) are also worth including, because satellite programmes change.
Satellize produces these climatological site-ranking analyses as part of its earth observation analytics service, drawing on ERA5, MODIS and TROPOMI archives. The Tonga crop-estimation programme is a different domain, but the underlying pipeline of extracting multi-year atmospheric statistics from open satellite data and reanalysis is the same class of work. If you are selecting sites for a sovereign Ka-band ground segment or a commercial VSAT hub, the analysis can be scoped to your candidate shortlist and delivered as a GIS layer plus a structured link-budget input table.
Typical figures
| ERA5 horizontal resolution | 0.25 degrees (~31 km at equator) |
| ERA5 vertical levels | 137 pressure levels, surface to 0.01 hPa |
| ERA5 temporal resolution and archive depth | Hourly; 1940 to near-real-time (~5-day latency) |
| MODIS MOD05 PWV spatial resolution | 1 km (near-infrared, clear-sky); 5 km (infrared, all-sky) |
| MODIS MOD05 revisit | Twice daily per satellite (Terra + Aqua combined: up to 4 passes) |
| Sentinel-5P TROPOMI water vapour pixel size | 5.5 km x 3.5 km (post-August 2019 upgrade) |
| Sentinel-5P TROPOMI revisit | Daily global coverage |
| GNSS-PWV temporal resolution | Sub-hourly (typically 5 to 30 min); point measurement at receiver location |
| Propagation model applied | ITU-R P.618-14 (scintillation and total tropospheric loss) |
| Recommended climatology archive length | Minimum 10 years to capture inter-annual variability |
Analytics Satellize can run
| Per-site scintillation fade climatology | ERA5 wet-term refractivity integration over 10-plus-year archive, fed into ITU-R P.618-14 scintillation model | Site-comparison table: predicted fade depth in dB at 99.0, 99.5 and 99.9 percent annual availability, per candidate location |
| Spatial PWV gradient map across candidate region | MODIS MOD05 and Sentinel-5P TROPOMI multi-year median and 90th-percentile water vapour column composites | GIS raster layers (GeoTIFF) showing spatial distribution of PWV percentiles across the candidate site region |
| ERA5 bias assessment at candidate sites | Comparison of ERA5-derived integrated water vapour against GNSS-PWV or radiosonde records where available; statistical bias and RMSE quantification | Bias-correction factors per site, with confidence intervals, delivered as a structured data table |
| Elevation-angle sensitivity analysis | P.618-14 applied across elevation angle range (5 to 30 degrees) for each candidate site, at Ka-band and Q-band frequencies | Sensitivity curves (PDF report and CSV) showing how scintillation fade margin varies with elevation angle and orbital slot geometry |
| Monthly scintillation severity climatology | Monthly disaggregation of ERA5 wet-term refractivity statistics to identify seasonal worst-case months, cross-referenced with monsoon or ENSO indices | 12-month climatological profile per site, formatted for direct import into link budget tools |
| Combined tropospheric impairment ranking | Composite scoring of scintillation, rain fade (ITU-R P.837/P.838) and gaseous absorption (P.676) contributions at candidate sites, weighted by planned link availability target | Ranked site shortlist with disaggregated impairment contributions, delivered as a GIS layer and structured PDF report |
Who does the work
We can get this done for you. Satellize runs its own analyst desk and a strong science team. You do not buy a data feed and work out what it means; our people source the imagery, run the analysis described on this page, and hand you the answer with its confidence limits stated. Discuss this requirement.