# The HD(CP)\({}^{2}\) Data Archive for Atmospheric Measurement Data
## 2 Standardized Data for the HD(CP)2 Archive  
In the beginning there were lively discussions within the HD(CP)2 observation community about which data should be reasonably integrated, how to create sensible products out of it, and how to make the data reusable for other scientists, as simply and easily as possible, without technical barriers. Further discussions took place about the term 'easy-to-use'. What does an 'easy-to-use' data archive mean, not only for users from the observation community who intend to share their data, but also for project partners without experience in special instrument types or processing observation data? Every data producer has her/his own preferred data format. Starting from these needs, the archive would have to serve many different data formats. A user might want to retrieve a specific variable, ideally an output variable of a specific model with a specific resolution. In this case the archive would have to serve an endless number of variedly parameterized variables. Neither of these kinds of archiving observation data are either practicable or desirable. Therefore, we had to find a balance between different positions, considering the wide range of instruments, variables, and levels, as well as the temporal and spatial scales of the measurements. The discussion results were summarized in the HD(CP)\({}^{2}\) observation data product standard (HOPS) [13]. This document now serves as a guide for all data producers, describing in detail the binding conventions for the datasets and their associated metadata (see Section 3). Currently the HD(CP)\({}^{2}\) data archive provides standardized data of typical atmospheric observations and specific cloud parameters, measured and derived at different observation instruments. The spatial resolution of the data varies from regular and irregular geographical grids, such as satellite or ceilometer network data, to local observations (supersites) and four-dimensional data of scanning instruments such as the cloud radar. The data cover long-term measurement cycles as well as intensive short-term observation campaigns (see Figure 1). The long-term observations are based on full-domain observations and local observations. One will find datasets of different satellite-based instruments (such as SEVIRI on the MeteoSat second-generation (MSG) satellites), as well as datasets of ground-based instrument networks (such as the C-band rain radar network of the German Weather Service, RADOLAN), as well as datasets from the so-called supersites. Currently there is no common definition of the term \"meteorological supersite\"; the meaning depends on the project and the instrument focus. For the HD(CP)\({}^{2}\) data archive, a supersite means an  
Figure 1: Overview of observations in HD(CP)\({}^{2}\). The underlying map of Germany shows the locations of the supersites and the GNSS and Ceilometer network stations. Example of short-term observations: Instrumentation during the HOPE campaign in Juelich (**A**); Of long-term observations: satellite observations (**B**); schematic instrumentation of Supersites (**C**); precipitation from C-Band rain radar network of the German Weather Service (**D**). observatory for long-term measurements including at least a cloud radar, a microwave radiometer and a LIDAR system. Each additional instrument, such as a meteorological tower, is a bonus. At the moment, datasets of four supersites in central Europe are collected and processed consistently: Cabauw Experimental Site for Atmospheric Research (CESAR), Juelich Observatory for Cloud Evolution (JOYCE), Leipzig Aerosol and Cloud Remote Observations System (LACROS), and Richard-A\(\&\)mann Observatory in Lindenberg (RAO). The data archive also provides short-term observations such as the data derived out of the HD(CP)\({}^{2}\) Observational Prototype Experiment (HOPE). The HOPE campaign took place in April and May 2013 in the region around the Juelich Research Center, which includes the supersite JOYCE.