Verification of LTPP Virtual Weather Stations Phase I Report: Accuracy and Reliability of Virtual Weather Stations
During this project, the LTPP virtual weather data for SMP- and
AWS-instrumented sites were compared with the measured data.
Different methods of developing climatic estimates for the SMP,
AWS, and NCDC weather stations were considered and evaluated.
Factors affecting the precision and bias of the climatic estimates
were investigated. The following are the major findings of this
- Daily, monthly, and yearly climatic estimates for anywhere in
North America can be developed with reasonable accuracy.
- Using several nearby weather stations for estimating the
climatic parameters for a project site provides more accurate
estimates than using the closest weather station.
- A simple average of the data (without a weight) for the five
closest weather stations provides the best overall estimate for
temperature. Weighting the average by the inverse distance provides
closer estimates than weighting by the inverse square
- Elevation differences (between the project site and the nearby
weather station) of more than 250 m significantly affect the
climatic estimates. In this case, temperatures could be corrected
to reduce the bias of the estimate. A relationship was proposed for
correcting the maximum temperature by the elevation
- The estimated climatic parameters are not severely affected by
either the distance or the latitude (north-south distance) of the
contributing weather stations within the 60-km range.
- The variation of the measured climatic data (calculated from
two or more instruments in one location) was around 40 percent of
the variation of the estimated data from the five nearby weather
- Significant year-to-year variation in climatic data was
observed. The year-to-year variation (COV) of the yearly
precipitation was 21 percent and the FI was 34 percent. On average,
the year-to-year variation of the monthly temperature data was 6
- Review of the VWS data for completeness showed that the quality
and quantity of the windspeed and humidity data are significantly
lower than the temperature and precipitation data.
- Several data anomalies in VWS, SMP, and AWS data were found and
- LTPP VWS estimates were found to be within a reasonable range,
considering the within-site variation of the measured data and also
the year-to-year variation of the data.