As a calibrated and mapped geostationary satellite dataset, GridSat is easily accessible for both meteorological and climatological applications that allows a wide range of user-specified levels of sophistication.

The National Oceanic and Atmospheric Administration’s (NOAA) Big Data Partnership (BDP) was established in April 2015 through cooperative research agreements between NOAA and selected commercial and academic partners. The BDP is investigating how the value inherent in NOAA’s data may be leveraged to broaden their utilization through modern cloud infrastructures and advanced “big data” techniques. NOAA’s Next Generation Weather Radar (NEXRAD) data were identified as an ideal candidate for such collaborative efforts. NEXRAD Level II data are valuable yet challenging to utilize in their entirety, and recent advances in weather radar science can be applied to both the archived and real-time data streams. NOAA’s National Centers for Environmental Information (NCEI) transferred the complete NEXRAD Level II historical archive, originating in 1991, through North Carolina State University’s Cooperative Institute for Climate and Satellites (CICS-NC) to interested BDP collaborators. Amazon Web Services (AWS) has received and made freely available the complete archived Level II data through its AWS platform. AWS then partnered with Unidata/University Corporation for Atmospheric Research (UCAR) to establish a real-time NEXRAD feed, thereby providing on-demand dissemination of both archived and current data seamlessly through the same access mechanism by October 2015. To organize, verify, and utilize the NEXRAD data on its platform, AWS further partnered with the Climate Corporation. This collective effort among federal government, private industry, and academia has already realized a number of new and novel applications that employ NOAA’s NEXRAD data, at no net cost to the U.S. taxpayer. The volume of accessed NEXRAD data, including this new AWS platform service, has increased by 130%, while the amount of data delivered by NOAA/NCEI has decreased by 50%.

This paper presents a stewardship maturity assessment model in the form of a matrix for digital environmental datasets. Nine key components are identified based on requirements imposed on digital environmental data and information that are cared for and disseminated by U.S. Federal agencies by U.S. law, i.e., Information Quality Act of 2001, agencies' guidance, expert bodies' recommendations, and users. These components include: preservability, accessibility, usability, production sustainability, data quality assurance, data quality control/monitoring, data quality assessment, transparency/traceability, and data integrity. A five-level progressive maturity scale is then defined for each component associated with measurable practices applied to individual datasets, representing Ad Hoc, Minimal, Intermediate, Advanced, and Optimal stages. The rationale for each key component and its maturity levels is described. This maturity model, leveraging community best practices and standards, provides a unified framework for assessing scientific data stewardship. It can be used to create a stewardship maturity scoreboard of dataset(s) and a roadmap for scientific data stewardship improvement or to provide data quality and usability information to users, stakeholders, and decision makers.

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The main challenge of evaluating droughts in the context of climate change and linking these droughts to adverse societal outcomes is a lack of a uniform definition that identifies drought conditions at a location and time. The U.S. Drought Monitor (USDM), created in 1999, is a well-established composite index that combines drought indicators across the hydrological cycle (i.e., meteorological to hydrological) with information from local experts. This makes the USDM one of the most holistic measures for evaluating past drought conditions across the United States. In this study, the USDM was used to define drought events as consecutive periods in time where the USDM status met or exceeded D1 conditions over the past 20 years. This analysis was applied to 5 km grid cells covering the U.S. and Puerto Rico to characterize the frequency, duration, and intensification rates of drought, and the timing of onset, amelioration, and other measures for every drought event on record. Results from this analysis revealed stark contrasts in the evolution of drought across the United States. Over the western United States, droughts evolved much slower, resulting in longer-lasting but fewer droughts. The eastern United States experienced more frequent, shorter-duration events. Given the slower evolution from onset to drought peak, flash droughts, which made up 9.8% of all droughts, were less common across the western United States, with a greater frequency over the southern United States. The most severe drought event on record was the 2012 drought, when more than 21% of the United States experienced its largest number of weeks at or above extreme (D3) drought conditions. The availability of historical drought events would support future societal impacts studies relating drought to adverse outcomes and aid in the evaluation of mitigation strategies by providing a dataset to local decision makers to compare and evaluate past droughts.