Sophisticated monitoring and control of virtually any available combination of meteorological, hydrological and industrial sensors. The industry standard and heart of hundreds of monitoring stations in New Zealand based around Campbell Scientific's CR1000 or CR800 dataloggers they are completely configurable to individual requirements with the users choice of both sensors and programming. Regularly stored data is retrieved to PC either directly or via telephone or radio telemetry. Campbell Scientific weather stations are used extensively around the world for any application where the quality, accuracy and reliability of data collected is paramount. In New Zealand they have been used traditionally for research, climate stations and hydrological monitoring. Increasingly, they are being used for horticultural and agricultural applications, environmental monitoring for consent purposes and fire risk determination. They can be built up with any combination of sensors and programming depending on the application. Below is a summary of the different components of a modern fully automated weather station. We have also included examples of the following Campbell stations in New Zealand to give you an idea of how we put them together in real life!
We supply sensors from the following international manufacturers: Apogee, Campbell Scientific, Hukseflux, Hydrological Services, Li-cor, Maximum, Met-One, NRG, Pronamic, REBS, RM Young, Skye, Streat Instruments, Texas Electronics, Vaisala and Windspeed (Vector).
The datalogger is pre-programmed, to accept data from the sensors, carry out any necessary calculations and log the required output data at regular pre-set intervals. There are a range of dataloggers available depending on the number of sensors you wish to measure and type of processing. The most common are the CR800 and CR1000. Campbell Scientific Dataloggers
Data can be stored as raw values or processed for retrieval. Complex calculations can be carried out within the datalogger.
Real Time Values
Average, Minimum, Maximum, Total Values over a set period