Developing Online Precipitation Visualization Systems for Education (original) (raw)

Nasa Precipitation Data in Virtual Globes: Moving Beyond 2D Representations

A prototype has been developed that enables Google Earth to access the ~13 terabyte precipitation archive of the Tropical Rainfall Measuring Mission (TRMM). While other organizations distribute TRMM satellite data for display in Google Earth, this prototype is the first application that allows Google Earth to examine single-orbit files at full resolution in 3D. This archive access tool is intended for researchers, but the paper also presents a separate Google Earth prototype intended for public outreach. The public outreach prototype provides detailed D visualization of a single precipitation event. The paper provides instructions for using the prototypes and explains the implementation issues. These prototypes demonstrate strengths and weaknesses of using Google Earth for archive access and scientific visualization. The Precipitation Processing System developed these prototypes as part of its support of the Global Precipitation Measurement (GPM) Mission.

NASA’s Remotely-sensed Precipitation: A Reservoir for Applications Users

Bulletin of the American Meteorological Society, 2016

Precipitation is the fundamental source of freshwater in the water cycle. It is critical for everyone, from subsistence farmers in Africa to weather forecasters around the world, to know when, where, and how much rain and snow is falling. The Global Precipitation Measurement (GPM) Core Observatory spacecraft, launched in February 2014, has the most advanced instruments to measure precipitation from space and, together with other satellite information, provides high-quality merged data on rain and snow worldwide every 30 min. Data from GPM and the predecessor Tropical Rainfall Measuring Mission (TRMM) have been fundamental to a broad range of applications and end-user groups and are among the most widely downloaded Earth science data products across NASA. End-user applications have rapidly become an integral component in translating satellite data into actionable information and knowledge used to inform policy and enhance decision-making at local to global scales. In this article, we...

Content-based browsing of data from the Tropical Rainfall Measuring Mission (TRMM)

Through content-based browsing, the TSDIS Orbit Viewer can help scientists decide which files to order from the TRMM archive. The Orbit Viewer's Mission Index can locate large-scale rain events in six terabytes of data. The Orbit Viewer's TRMM Tracker can locate coincidences between the TRMM orbit and a userdefined surface track.

Evaluation of the Compatibility of TRMM Satellite Data with Precipitation Observation Data

JOIV : International Journal on Informatics Visualization

The availability of hydrological data is one of the challenges associated with developing water infrastructure in different areas. This led to the TRMM (Tropical Precipitation Measurement Mission) design by NASA, which involves using satellite weather monitoring technology to monitor and analyze tropical precipitation in different parts of the world. Therefore, this validation study was conducted to compare TRMM precipitation data with observed precipitation to determine its application as an alternate source of hydrological data. The Kuranji watershed was selected as the study site due to the availability of suitable data. Moreover, the validation analyses applied include the Root Mean Squared Error (RMSE), Nash-Sutcliffe Efficiency (NSE), Coefficient Correlation (R), and Relative Error (RE). These used two calculation forms: one for the uncorrected data and another for the corrected data. The results showed that the best-adjusted data validation from the Gunung Nago station in 201...

The TRMM Multi-Satellite Precipitation Analysis (TMPA)

Springer eBooks, 2009

The Tropical Rainfall Measuring Mission (TRMM) Multi-satellite Precipitation Analysis (TMPA) is intended to provide a "best" estimate of quasi-global precipitation from the wide variety of modern satellite-borne precipitation-related sensors. Estimates are provided at relatively fine scales (0.25°x0.25°, 3-hourly) in both real and post-real time to accommodate a wide range of researchers. However, the errors inherent in the finest scale estimates are large. The most successful use of the TMPA data is when the analysis takes advantage of the fine-scale data to create time/space averages appropriate to the user's application. We review the conceptual basis for the TMPA, summarize the processing sequence, and focus on two new activities. First, a recent upgrade to the real-time version incorporates several additional satellite data sources and employs monthly climatological adjustments to approximate the bias characteristics of the research quality post-real-time product. Second, an upgrade of the research quality post-real-time TMPA from Version 6 to Version 7 (in beta test at press time) is designed to provide a variety of improvements that increase the list of input data sets and correct several issues. Future enhancements for the TMPA will include improved error estimation, extension to higher latitudes, and a shift to a Lagrangian time interpolation scheme.

Hydrodata.info: A Web Service for Hydrological Time Series Visualization

This paper introduces the concept of a free web service for generating hydrologic time-series charts from any combination of data sources available in the Consortium of Universities for Advancement of Hydrologic Science (CUAHSI)'s Hydrologic information System. The CUAHSI’s catalog of distributed services provides a growing volume of hydrological and meteorological data from many parts of the world using a standard WaterML format. By taking advantage of a Representational State Transfer (REST) API, the end user can specify the time period, data source, site and variable to be displayed in the chart. Several pre-defined charts frequently used in hydrology (logarithmic plot, rainfall accumulation plot, multiple season plot, combined rainfall-runoff plot) are supported by the API. Special care has been taken for handling periods of missing data, displaying sporadic observations, and combining multiple time series in the chart. The size, quality and format of the chart can also be specified by the user. Once a chart image is generated, it can be cached on the hydrodata.info server for improving the speed of repeated requests. The hydrological time series chart API is already used in the hydrodata.cz and grafy.plaveniny.cz web portals for providing user-friendly access to hydrologic information from the Czech Republic and neighboring countries.

Bridging the gap between NASA hydrological data and the geospatial community

American Society for Photogrammetry and Remote Sensing Annual Conference 2011, 2011

There is a vast and ever increasing amount of data on the Earth's interconnected energy and hydrological systems, and yet one challenge persists: increasing the usefulness of these data for, and thus their use by, the geospatial communities. The Hydrology Data and Information Services Center (HDISC), part of the Goddard Earth Sciences DISC, has continually worked to better understand the hydrological data needs of the geospatial end users, to thus better able to bridge the gap between NASA data and the geospatial communities. This paper will cover some of the hydrological data sets available from HDISC, and the various tools and services developed for data searching, data subsetting, format conversion, online visualization and analysis, interoperable access, etc., to facilitate the integration of NASA hydrological data by end users. The NASA Goddard data analysis and visualization system, Giovanni, is described. Two case examples of user-customized data services are given, involving the EPA BASINS (Better Assessment Science Integrating point & Non-point Sources) project and the CUAHSI Hydrologic Information System, with the common requirement of on-the-fly retrieval of long duration time series for a geographical point.