The satellite systems provide a global coverage but doesn’t exist a single space borne platform that can carry all the suitable instruments to ensure a comprehensive description of a given phenomenon. Regarding platforms, geosynchronous earth orbit (GEO) satellites can ensure a coverage with a high temporal sampling (15 min) from a flight altitude of about 36000 km, while low earth orbit (LEO) satellites have the advantage to fly at a lower altitude (from 400–800 km), thus enabling the use of sensors without losing too much in spatial resolution (order of kilometres to tens of kilometres). The major drawback of LEOs is the low temporal sampling, only twice a day in a given place at mid-latitude.

The general idea behind the MACE is to combine, by means of statistical integration techniques, the appealing spatial and temporal sampling of GEO-IR sensors, mounted on geo-stationary platforms, with the higher sensitivity of passive/active VIS/IR/MW methods for LEO-based ash retrieval and ground-based instruments.

The statistical integration techniques used in MACE are applied within a procedure which is supposed to run continuously on global scale. This procedure is based on a background process and a foreground process.

The background process consists first in estimating the volcanic ash from available GEO measurements by means of either empirical retrieval algorithms or inversion schemes based on parametric cloud radiative models (inversion step). This means that we are considering an estimator which enables the inversion a set of radiation measurements at a given frequency. This step can include ground-based data (e.g., weather radars and/or lidars) as well, if available. The second step of the background process pursues the combination of LEO (and ground) sensor data with data coming from GEO sensor in space and time on a global scale (collocation step, COL). The first step of the background process is to locate temporally the GEO data within the past few tens of minutes of the LEO (and ground) data time and to re-map into the geographic coordinates both GEO-VIS/IR and LEO-VIS/IR/MW measurements available observations. Note that, since spatial resolution of MW data is generally worse than VIS/IR ones, a MW field-of-view of nominal area A generally includes more than one IR pixel. Thus, for a given MW-based ash-observable attributed to a nominal area A, we can compute several spatial moments of the corresponding LEO and/or GEO retrieval: i) average value within A; ii) minimum value within A; iii) standard deviation within A. As a result of the background process, a data set is generated, containing the co-located per-pixel ash retrievals derived from LEO and GEO data, and the pixel geo-location. This process is continuously ongoing, since new LEO and GEO data are continuously ingested on a global scale depending on available satellite platforms. A pre-processing (PRE) stage is accomplished after each background process.

A foreground process is started to derive the ash-observable (e.g., ash mass, effective radius, AOD, height and thickness of the ash cloud) inverse relationship once the data set has been updated. The entire globe is divided in sub-regions S which are equally sized and uniformly spaced. The sub-region centres are generally chosen so that to assure a smooth transition between adjacent sub-regions. The GEO-based retrieval relationships are updated every time a new set of combined LEO-based data have been added to the data set relative to that sub-region, and are derived using data archived in a time window of several hours (integration step, INT). As a matter of fact, to assure that only the most recent ash history is captured and to guarantee a statistical significance of the training set, the ash-observable inverse relationship for a given sub-region is derived using only the most recent combined data. The last step is represented by the prediction of the ash from GEO-IR measurements in a given sub-region by applying the derived ash retrieval algorithm (retrieval step, RET).


The figure represents the MACE temporal flow diagram. For each defined time interval, all the satellite and ground available measurements are at first spatially collocated (COL), preprocessed (PRE), integrated (INT) and finally the new retrieval product released (RET).



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