Search Results
You are looking at 1 - 2 of 2 items for :
- Author or Editor: Erin Jones x
- Bulletin of the American Meteorological Society x
- Refine by Access: All Content x
The growth of the wind industry in recent years has motivated investigation into wind farm interference with the operation of the nationwide Weather Surveillance Radar-1988 Doppler (WSR-88D) network. Observations of a wind farm were taken with a Doppler on Wheels (DOW) during the DOW Radar Observations at Purdue Study (DROPS), a largely studentled field program that took place in the fall of 2009. The DOW sampled clear-air weather and precipitation at locations within 5 km of the Benton County, Indiana, wind farm to determine the wind turbines' effect on Doppler velocity and ref lectivity data. These data were analyzed and compared with data from the Indianapolis WSR-88D (KIND) and a local television station (WLFI) radar. In precipitation, the DOW data show velocity couplets that have the appearance of isolated tornadic vortices. Under clear-air sampling, significant multipath scattering is evident, but no velocity couplets would meet the DOW-equivalent tornado detection algorithm criteria. Broader impacts of these findings are discussed, and suggestions are made for additional studies that would explore how to mitigate these impacts.
The growth of the wind industry in recent years has motivated investigation into wind farm interference with the operation of the nationwide Weather Surveillance Radar-1988 Doppler (WSR-88D) network. Observations of a wind farm were taken with a Doppler on Wheels (DOW) during the DOW Radar Observations at Purdue Study (DROPS), a largely studentled field program that took place in the fall of 2009. The DOW sampled clear-air weather and precipitation at locations within 5 km of the Benton County, Indiana, wind farm to determine the wind turbines' effect on Doppler velocity and ref lectivity data. These data were analyzed and compared with data from the Indianapolis WSR-88D (KIND) and a local television station (WLFI) radar. In precipitation, the DOW data show velocity couplets that have the appearance of isolated tornadic vortices. Under clear-air sampling, significant multipath scattering is evident, but no velocity couplets would meet the DOW-equivalent tornado detection algorithm criteria. Broader impacts of these findings are discussed, and suggestions are made for additional studies that would explore how to mitigate these impacts.
Abstract
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 present NASA precipitation data, capabilities, and opportunities from the perspective of end users. We outline some key examples of how TRMM and GPM data are being applied across a broad range of sectors, including numerical weather prediction, disaster modeling, agricultural monitoring, and public health research. This work provides a discussion of some of the current needs of the community as well as future plans to better support end-user communities across the globe to utilize this data for their own applications.
Abstract
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 present NASA precipitation data, capabilities, and opportunities from the perspective of end users. We outline some key examples of how TRMM and GPM data are being applied across a broad range of sectors, including numerical weather prediction, disaster modeling, agricultural monitoring, and public health research. This work provides a discussion of some of the current needs of the community as well as future plans to better support end-user communities across the globe to utilize this data for their own applications.
