Relative humidity interpolation algorithm.
This is an implementation of the method described in (Liston & Elder, 2006): for each input point, the dew point temperature is calculated. Then, the dew point temperatures are spatially interpolated using IDWLapseAlgorithm (if only one station is available, no altitudinal trends will be applied). Finally, each local dew point temperature is converted back to a local relative humidity. As a side effect, the user must have defined algorithms to be used for air temperature (since this is needed for dew point to RH conversion). It takes the following arguments:
- SCALE: this is a scaling parameter to smooth the IDW distribution. In effect, this is added to the distance in order to move into the tail of the 1/d distribution (default: 1000m);
- ALPHA: this is an exponent to the 1/d distribution (default: 1);
- all the trend-controlling arguments supported by Trend::Trend().
RH::algorithms = LISTON_RH
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const std::string | algo |
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std::vector< double > | getData (const Date &i_date, const std::string &i_param) |
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size_t | getData (const Date &i_date, const std::string &i_param, std::vector< double > &o_vecData, std::vector< StationData > &o_vecMeta) |
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TimeSeriesManager & | tsmanager |
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Date | date |
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std::vector< MeteoData > | vecMeteo |
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std::vector< double > | vecData |
| store the measurement for the given parameter
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std::vector< StationData > | vecMeta |
| store the station data for the given parameter
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std::ostringstream | info |
| to store some extra information about the interplation process
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const std::string | param |
| the parameter that we will interpolate
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size_t | nrOfMeasurments |
| Number of stations that have been used, so this can be reported to the user.
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