# NASA Global Satellite and Model Data Products and Services for Tropical Meteorology and Climatology
## 3 Data Services
### Giovanni  
To be able to evaluate and visualize data, preferably without downloading data and software, has become quite popular these days. For some, handling and processing satellite remote data can be a daunting task due to a number of issues such as data format or data structure. Giovanni is to facilitate users to analyze and visualize satellite data without downloading data and software. Giovanni [20; 21] is a Web-based tool where frequently-used Level-3 datasets at GES DISC are included [50]. As of this writing, over 1500 variables are available in Giovanni [50]. Figure 2 shows the Web interface or landing page of Giovanni [50]. A dataset normally contains structured variables with metadata. Users usually use one or more variables in their studies. Unlike the \begin{table}
\begin{tabular}{c c} \hline \hline
**Service** & **Description** \\ \hline Online Archive & Original archived data files accessible only by the Hypertext \\  & Transfer Protocol Secure (HTITPS). \\ \hline Giovanni & Analyze and visualize gridded data interactively online without having to download any data and software. \\ \hline OpeNDAP & The Open-source Project for a Network Data Access Protocol (OPeNDAP) provides remote access to individual variables within datasets in a form usable by many tools, such as the Integrated Data Viewer (IDV), the Man computer Interactive Data Access System–5 th generation (McIDAS-V), Panoply, Ferret, and the Grid Analysis and Display System (GrADS). \\ \hline GrADS Data Server (GDS) & Stable, secure data server that provides subsetting and analysis services across the Internet. The core of GDS is OPeNDAP (also known as the Distributed Oceanographic Data Systems (DODS)), a software framework used for data networking that makes local data accessible to remote locations. \\ \hline OGC Web Map Service & The Open Geospatial Consortium (OGC) Web Map Service (WMS) provides map depictions over the network via a standard protocol, enabling clients to build customized maps based on data coming from a variety of distributed sources. \\ \hline Data Rods for Hydrology & Provide time series data in American Standard Code for Information Interchange (ASCII) for hydrology datasets. \\ \hline \hline \end{tabular}
\end{table} 
Table 4: Data services at GES DISC (note: data services may not be available for some datasets). data collection search mentioned earlier, only selected variables from their datasets are presented and analyzed in Giovanni, which helps the data analysis and visualization because users in general are more familiar with variable names. However, their associated dataset names and landing pages are linked in case extra information is needed. Searching, filtering and sorting make finding a variable easier. For example, a search for \"precipitation\" in Giovanni returns 104 precipitation-related variables. Users can filter the results based on different criteria (e.g., spatial and temporal resolutions). Twenty-two functions are available for analysis and visualization and they are categorized into five groups including maps, comparisons, vertical, time series, and miscellaneous. Users can select a time span and spatial domain for analysis. Shapefiles including countries, U.S. states, land/sea masks, and major watersheds are included. Unit conversion is available for some popular variables such as precipitation. Although few climatology datasets are generated from their archived datasets, a function called monthly and seasonal averages in Giovanni (2016) provides a fast and easy way to generate monthly and seasonal averages from over 1500 parameters for a quick look or evaluation. Users can compute monthly or seasonal averages using different time ranges to see their differences. In the output window, options can be used to fine tune the graphic such as adjusting the min/max values of the color bar. There is a list of different color bars for selection. Maps can be zoomed in or out. Data can be downloaded in different popular formats (e.g., NetCDF, GeoTIFF, and CSV (Comma-Separated Values)).