I have a large growing dataset of water and climate observations for several years in regular hourly time-step. The number of locations is cca. 1000 locations with latitude, longitude coordinates. At each location up to 5 parameters (water level, discharge, rainfall, snow depth, temperature) are measured at regular hourly time-step (gaps in time-series are labeled with a special "nodatavalue" code).
Currently I am using a Microsoft SQL Server database with a following main tables:
stations (id, name, latitude, longitude, elevation) parameters(id, name, units, scalefactor, nodatavalue) stations_parameters (station_id, parameter_id, start_time, end_time) waterlevel (station_id, time_utc, value) discharge (station_id, time_utc, value) temperature (station_id, time_utc, value) rainfall (station_id, time_utc, value) snow (station_id, time_utc, value)
The size of my database is 2 GB. For various reasons mainly due to database size limitation on my webhost and interoperability issues I need to move away from MS SQL Server. I would like to use the NetCDF format because I read that it is suitable for multi-dimensional data, and that it has built-in support for space and time queries. Specifically I need to run the following types of queries very fast:
Query 1: For a time-range give me the average, max, min or sum of a parameter for all stations. For example create a map of maximum temperature between 2013-07-25 and 2013-07-26.
Query 2: For a time-range, point location and parameter, give me the time-series. For example hourly time-series of temperature at station 777 from 2013-01-01 to 2013-07-25.
- Is it possible to use NetCDF for this type of multi-dimensional data? (note that the space is not a regular grid but rather sparse point-locations)
- Is there any free software tool that has built-in support for visualizing a point time-series NetCDF data file? I have used Panoply and IDV but only with regular NetCDF grids.
- If yes - What would be the structure of my NetCDF data file (dimensions, variables and their order)?