2022 - on going
RAMI4ATM is a new initiative dedicated to the benchmarking of coupled surface-atmosphere radiative transfer models. RAMI4ATM will thus expand RAdiation transfer Model Intercomparison (RAMI) to the simulation of satellite observations.
Compared to previous RAMI benchmarks, the major difference is that RAMI4ATM will account for atmospheric radiative effects occurring between the surface and the simulated signal reaching a given spaceborne radiometer. Sentinel-2A/MSI spectral bands has been chosen for that purpose. Models participating in RAMI4ATM should support the simulation of radiative processes at the surface, in the atmosphere and account for the radiative coupling between the two.
Over the past decades, many radiative transfer models have been developed and are widely used in Earth Observation for e.g., vicarious calibration, lookup table generation for atmospheric correction or sensitivity analyses. Many of these models ship atmospheric property databases. Subcomponents of these models have been extensively tested in ideal conditions but so far, no long-term initiative similar to RAMI has been undertaken to systematically compare models when they are used to simulate actual remote sensing observations. The uncertainties of these models have not been clearly assessed in realistic usage conditions when supporting typical Earth Observation applications by remote sensing scientists. Surface properties will be defined by the simple homogeneous scenes as defined in previous RAMI phases.
This new phase is oriented toward the support of calibration and validation activities relying on the use of radiative transfer models for the simulation of satellite observations in the visible, near and shortwave infrared spectral regions. It is therefore primarily directed at model users involved in calibration and validation activities. Participation from radiative transfer model developers is however also welcome. They are referenced as expert users in RAMI4ATM. When relevant in the various scenarios descriptions, specific information for model and expert users are made available.
Finally, during this RAMI phase, special care will be taken to provide a computation priority order so that teams that do not have time to generate all the scenarios can focus on the most relevant ones.
Similarly to RAMI-1, the primary expected outcome of RAMI4ATM will be to document the variability between coupled surface-atmosphere models when run under well-controlled, but realistic, conditions. A second objective will be to quantify the impact of relying on models build-in features as opposed to a rigorous model comparions. This outcome might be particularly relevant for modelling studies concerning radiometric vicarious calibration activities.
RAMI4ATM covers various scenarios resulting from a combination of surface and atmospheric properties. Specifically, the following cases are foreseen:
As already stressed, specifc information is provided to the model users and expert users when relevant. It is expected that model users rely as much as possible on built-in features of the models they are using to perform the simulations. Detailed information is provided to the expert users to allow them to simulate the scenarios in a rigorous and controlled way.
These simulations should be performed in the specified MSI bands. The simulated observation geometry does not correspond to the one of MSI but has been restricted to the principal and orthogonal planes as for RAMI-I to -IV phases for fixed sun angles. Such configuration eases a first model comparisons.
A combination of different atmospheric properties are regrouped in seven atmosphere types. These types are illustrated in Figure 1 and described in more details in the Atmospheres section.
The different surfaces are represented with the symbols in Figure 2. They are described in the Surfaces section.
The overall combinations of surface and atmospheric properties are represented in this Figure 3:
Due to the large number of experiments, a priority order is proposed for each parameter (either in atmospheres, surfaces or bands) to make sure that we benchmark enough RAMI4ATM models with this set of priority 1 experiments.
| Parameter X | Priority |
|---|---|
| value1 | 2 |
| value2 | 1 |
| value3 | 3 |
Following the priority order, value2 should be computed first, then value1 and finally value3.
In RAMI4ATM each individual experiment is identified as a combination of a scenario, a band, an illumination geometry and a measurement.
Access to descriptions of the various scenario contents and measurements can be obtained by clicking on the each specific item.
As in previous RAMI phases the model results should be submitted accordingly to a common filename and content format.
A JSON file is a file that stores simple data structures and objects in JavaScript Object Notation (JSON) format, which is a standard data interchange format.
The scenarios described on this website are also available in RAMI4ATM experiments description JSON file: here is an example of a scenario written in JSON format.
{
"name": "HOM00_BLA_S00S_M02_z30a000",
"observations": [
{
"name": "HOM00_BLA_S00S_M02_z30a000",
"atmosphere": {
"name": "S00S",
"atmosphere_type": "Rayleigh",
"atmospheric_profile": "US Standard",
"concentrations": null,
"levels": [],
"aerosols": []
},
"surface": {
"name": "BLA",
"surface_type": "Lambertian",
"surface_parameters": { "reflectance": 0.0 }
},
"illumination": {
"name": "z30a000",
"sza": { "value": 30.0, "units": "degree" },
"saa": { "value": 0.0, "units": "degree"}
},
"canopy": null,
"measures": [
{
"name": "brfpp",
"satellite": "Sentinel-2A",
"instrument": "MSI",
"bands": ["2"],
"measure_type": "brfpp",
"delta_vaa": { "value": 180.0, "units": "degree" },
"vza_start": { "value": 1.0, "units": "degree"},
"vza_end": { "value": 75.0, "units": "degree"},
"vza_step": { "value": 2.0, "units": "degree"},
"height": { "value": 120, "units": "km" }
},
{
"name": "brfpp",
"satellite": "Sentinel-2A",
"instrument": "MSI",
"bands": ["2"],
"measure_type": "brfpp",
"delta_vaa": { "value": 0.0, "units": "degree" },
"vza_start": { "value": 1.0, "units": "degree"},
"vza_end": { "value": 75.0, "units": "degree"},
"vza_step": { "value": 2.0, "units": "degree"},
"height": { "value": 120, "units": "km" }
},
...
]
}
]
}
This example is a simple atmosphere scenario with only molecular (or Rayleigh) scattering involved on top of a black surface, without any canopy or aerosol layers. Observation is performed in the principal plane within MSI band M02 for a sun zenith angle of 30°.
The dotted notation is also used in the RAMI4ATM pages to refer to the parameters present in the JSON scenario file. For instance, the surface type of the above example can be refered by scenario.observations.surface.surface_type. The value of this surface type is Lambertian. The reflectance of this surface is at location scenario.observations.surface.surface_parameters.reflectance, and its value is 0.0. The dotted notation is also used in the RAMI4ATM pages to refer to the parameters present in the JSON scenario file. For instance, the surface type of the above example can be refered by scenario.observations.surface.surface_type. The value of this surface type is Lambertian. The reflectance of this surface is at location scenario.observations.surface.surface_parameters.reflectance, and its value is 0.0.
Using the link below it is possible to examine:
After checking model results files, using the previous tool, participants can submit their results by clicking on Model Submission link to open the dedicated page.
RAMI4ATM is co-sponsored by Copernicus through Eradiate project (Rayference/ESA).
