Search Results
You are looking at 1 - 9 of 9 items for :
- Author or Editor: Pierre Kirstetter x
- Bulletin of the American Meteorological Society x
- Refine by Access: All Content x
Abstract
In meteorological investigations, the reference variable or “ground truth” typically comes from an instrument. This study uses human observations of surface precipitation types to evaluate the same variables that are estimated from an automated algorithm. The NOAA/National Severe Storms Laboratory’s Multi-Radar Multi-Sensor (MRMS) system relies primarily on observations from the Next Generation Radar (NEXRAD) network and model analyses from the Earth System Research Laboratory’s Rapid Refresh (RAP) system. Each hour, MRMS yields quantitative precipitation estimates and surface precipitation types as rain or snow. To date, the surface precipitation type product has received little attention beyond case studies. This study uses precipitation type reports collected by citizen scientists who have contributed observations to the meteorological Phenomena Identification Near the Ground (mPING) project. Citizen scientist reports of rain and snow during the winter season from 19 December 2012 to 30 April 2013 across the United States are compared to the MRMS precipitation type products. Results show that while the mPING reports have a limited spatial distribution (they are concentrated in urban areas), they yield similar critical success indexes of MRMS precipitation types in different cities. The remaining disagreement is attributed to an MRMS algorithmic deficiency of yielding too much rain, as opposed to biases in the mPING reports. The study also shows reduced detectability of snow compared to rain, which is attributed to lack of sensitivity at S band and the shallow nature of winter storms. Some suggestions are provided for improving the MRMS precipitation type algorithm based on these findings.
Abstract
In meteorological investigations, the reference variable or “ground truth” typically comes from an instrument. This study uses human observations of surface precipitation types to evaluate the same variables that are estimated from an automated algorithm. The NOAA/National Severe Storms Laboratory’s Multi-Radar Multi-Sensor (MRMS) system relies primarily on observations from the Next Generation Radar (NEXRAD) network and model analyses from the Earth System Research Laboratory’s Rapid Refresh (RAP) system. Each hour, MRMS yields quantitative precipitation estimates and surface precipitation types as rain or snow. To date, the surface precipitation type product has received little attention beyond case studies. This study uses precipitation type reports collected by citizen scientists who have contributed observations to the meteorological Phenomena Identification Near the Ground (mPING) project. Citizen scientist reports of rain and snow during the winter season from 19 December 2012 to 30 April 2013 across the United States are compared to the MRMS precipitation type products. Results show that while the mPING reports have a limited spatial distribution (they are concentrated in urban areas), they yield similar critical success indexes of MRMS precipitation types in different cities. The remaining disagreement is attributed to an MRMS algorithmic deficiency of yielding too much rain, as opposed to biases in the mPING reports. The study also shows reduced detectability of snow compared to rain, which is attributed to lack of sensitivity at S band and the shallow nature of winter storms. Some suggestions are provided for improving the MRMS precipitation type algorithm based on these findings.
Abstract
This study introduces the Flooded Locations and Simulated Hydrographs (FLASH) project. FLASH is the first system to generate a suite of hydrometeorological products at flash flood scale in real-time across the conterminous United States, including rainfall average recurrence intervals, ratios of rainfall to flash flood guidance, and distributed hydrologic model–based discharge forecasts. The key aspects of the system are 1) precipitation forcing from the National Severe Storms Laboratory (NSSL)’s Multi-Radar Multi-Sensor (MRMS) system, 2) a computationally efficient distributed hydrologic modeling framework with sufficient representation of physical processes for flood prediction, 3) capability to provide forecasts at all grid points covered by radars without the requirement of model calibration, and 4) an open-access development platform, product display, and verification system for testing new ideas in a real-time demonstration environment and for fostering collaborations.
This study assesses the FLASH system’s ability to accurately simulate unit peak discharges over a 7-yr period in 1,643 unregulated gauged basins. The evaluation indicates that FLASH’s unit peak discharges had a linear and rank correlation of 0.64 and 0.79, respectively, and that the timing of the peak discharges has errors less than 2 h. The critical success index with FLASH was 0.38 for flood events that exceeded action stage. FLASH performance is demonstrated and evaluated for case studies, including the 2013 deadly flash flood case in Oklahoma City, Oklahoma, and the 2015 event in Houston, Texas—both of which occurred on Memorial Day weekends.
Abstract
This study introduces the Flooded Locations and Simulated Hydrographs (FLASH) project. FLASH is the first system to generate a suite of hydrometeorological products at flash flood scale in real-time across the conterminous United States, including rainfall average recurrence intervals, ratios of rainfall to flash flood guidance, and distributed hydrologic model–based discharge forecasts. The key aspects of the system are 1) precipitation forcing from the National Severe Storms Laboratory (NSSL)’s Multi-Radar Multi-Sensor (MRMS) system, 2) a computationally efficient distributed hydrologic modeling framework with sufficient representation of physical processes for flood prediction, 3) capability to provide forecasts at all grid points covered by radars without the requirement of model calibration, and 4) an open-access development platform, product display, and verification system for testing new ideas in a real-time demonstration environment and for fostering collaborations.
This study assesses the FLASH system’s ability to accurately simulate unit peak discharges over a 7-yr period in 1,643 unregulated gauged basins. The evaluation indicates that FLASH’s unit peak discharges had a linear and rank correlation of 0.64 and 0.79, respectively, and that the timing of the peak discharges has errors less than 2 h. The critical success index with FLASH was 0.38 for flood events that exceeded action stage. FLASH performance is demonstrated and evaluated for case studies, including the 2013 deadly flash flood case in Oklahoma City, Oklahoma, and the 2015 event in Houston, Texas—both of which occurred on Memorial Day weekends.
Despite flash flooding being one of the most deadly and costly weather-related natural hazards worldwide, individual datasets to characterize them in the United States are hampered by limited documentation and can be difficult to access. This study is the first of its kind to assemble, reprocess, describe, and disseminate a georeferenced U.S. database providing a long-term, detailed characterization of flash flooding in terms of spatiotemporal behavior and specificity of impacts. The database is composed of three primary sources: 1) the entire archive of automated discharge observations from the U.S. Geological Survey that has been reprocessed to describe individual flooding events, 2) flash-flooding reports collected by the National Weather Service from 2006 to the present, and 3) witness reports obtained directly from the public in the Severe Hazards Analysis and Verification Experiment during the summers 2008–10. Each observational data source has limitations; a major asset of the unified flash flood database is its collation of relevant information from a variety of sources that is now readily available to the community in common formats. It is anticipated that this database will be used for many diverse purposes, such as evaluating tools to predict flash flooding, characterizing seasonal and regional trends, and improving understanding of dominant flood-producing processes. We envision the initiation of this community database effort will attract and encompass future datasets.
Despite flash flooding being one of the most deadly and costly weather-related natural hazards worldwide, individual datasets to characterize them in the United States are hampered by limited documentation and can be difficult to access. This study is the first of its kind to assemble, reprocess, describe, and disseminate a georeferenced U.S. database providing a long-term, detailed characterization of flash flooding in terms of spatiotemporal behavior and specificity of impacts. The database is composed of three primary sources: 1) the entire archive of automated discharge observations from the U.S. Geological Survey that has been reprocessed to describe individual flooding events, 2) flash-flooding reports collected by the National Weather Service from 2006 to the present, and 3) witness reports obtained directly from the public in the Severe Hazards Analysis and Verification Experiment during the summers 2008–10. Each observational data source has limitations; a major asset of the unified flash flood database is its collation of relevant information from a variety of sources that is now readily available to the community in common formats. It is anticipated that this database will be used for many diverse purposes, such as evaluating tools to predict flash flooding, characterizing seasonal and regional trends, and improving understanding of dominant flood-producing processes. We envision the initiation of this community database effort will attract and encompass future datasets.
Abstract
The scientific community has expressed interest in the potential of phased array radars (PARs) to observe the atmosphere with finer spatial and temporal scales. Although convergence has occurred between the meteorological and engineering communities, the need exists to increase access of PAR to meteorologists. Here, we facilitate these interdisciplinary efforts in the field of ground-based PARs for atmospheric studies. We cover high-level technical concepts and terminology for PARs as applied to studies of the atmosphere. A historical perspective is provided as context along with an overview of PAR system architectures, technical challenges, and opportunities. Envisioned scan strategies are summarized because they are distinct from traditional mechanically scanned radars and are the most advantageous for high-resolution studies of the atmosphere. Open access to PAR data is emphasized as a mechanism to educate the future generation of atmospheric scientists. Finally, a vision for the future of operational networks, research facilities, and expansion into complementary radar wavelengths is provided.
Abstract
The scientific community has expressed interest in the potential of phased array radars (PARs) to observe the atmosphere with finer spatial and temporal scales. Although convergence has occurred between the meteorological and engineering communities, the need exists to increase access of PAR to meteorologists. Here, we facilitate these interdisciplinary efforts in the field of ground-based PARs for atmospheric studies. We cover high-level technical concepts and terminology for PARs as applied to studies of the atmosphere. A historical perspective is provided as context along with an overview of PAR system architectures, technical challenges, and opportunities. Envisioned scan strategies are summarized because they are distinct from traditional mechanically scanned radars and are the most advantageous for high-resolution studies of the atmosphere. Open access to PAR data is emphasized as a mechanism to educate the future generation of atmospheric scientists. Finally, a vision for the future of operational networks, research facilities, and expansion into complementary radar wavelengths is provided.
Abstract
Phased array radars (PARs) are a promising observing technology, at the cusp of being available to the broader meteorological community. PARs offer near-instantaneous sampling of the atmosphere with flexible beam forming, multifunctionality, and low operational and maintenance costs and without mechanical inertia limitations. These PAR features are transformative compared to those offered by our current reflector-based meteorological radars. The integration of PARs into meteorological research has the potential to revolutionize the way we observe the atmosphere. The rate of adoption of PARs in research will depend on many factors, including (i) the need to continue educating the scientific community on the full technical capabilities and trade-offs of PARs through an engaging dialogue with the science and engineering communities and (ii) the need to communicate the breadth of scientific bottlenecks that PARs can overcome in atmospheric measurements and the new research avenues that are now possible using PARs in concert with other measurement systems. The former is the subject of a companion article that focuses on PAR technology while the latter is the objective here.
Abstract
Phased array radars (PARs) are a promising observing technology, at the cusp of being available to the broader meteorological community. PARs offer near-instantaneous sampling of the atmosphere with flexible beam forming, multifunctionality, and low operational and maintenance costs and without mechanical inertia limitations. These PAR features are transformative compared to those offered by our current reflector-based meteorological radars. The integration of PARs into meteorological research has the potential to revolutionize the way we observe the atmosphere. The rate of adoption of PARs in research will depend on many factors, including (i) the need to continue educating the scientific community on the full technical capabilities and trade-offs of PARs through an engaging dialogue with the science and engineering communities and (ii) the need to communicate the breadth of scientific bottlenecks that PARs can overcome in atmospheric measurements and the new research avenues that are now possible using PARs in concert with other measurement systems. The former is the subject of a companion article that focuses on PAR technology while the latter is the objective here.
Abstract
Precipitation is a key source of freshwater; therefore, observing global patterns of precipitation and its intensity is important for science, society, and understanding our planet in a changing climate. In 2014, the National Aeronautics and Space Administration (NASA) and the Japan Aerospace Exploration Agency (JAXA) launched the Global Precipitation Measurement (GPM) Core Observatory (CO) spacecraft. The GPM CO carries the most advanced precipitation sensors currently in space including a dual-frequency precipitation radar provided by JAXA for measuring the three-dimensional structures of precipitation and a well-calibrated, multifrequency passive microwave radiometer that provides wide-swath precipitation data. The GPM CO was designed to measure rain rates from 0.2 to 110.0 mm h−1 and to detect moderate to intense snow events. The GPM CO serves as a reference for unifying the data from a constellation of partner satellites to provide next-generation, merged precipitation estimates globally and with high spatial and temporal resolutions. Through improved measurements of rain and snow, precipitation data from GPM provides new information such as details on precipitation structure and intensity; observations of hurricanes and typhoons as they transition from the tropics to the midlatitudes; data to advance near-real-time hazard assessment for floods, landslides, and droughts; inputs to improve weather and climate models; and insights into agricultural productivity, famine, and public health. Since launch, GPM teams have calibrated satellite instruments, refined precipitation retrieval algorithms, expanded science investigations, and processed and disseminated precipitation data for a range of applications. The current status of GPM, its ongoing science, and its future plans are presented.
Abstract
Precipitation is a key source of freshwater; therefore, observing global patterns of precipitation and its intensity is important for science, society, and understanding our planet in a changing climate. In 2014, the National Aeronautics and Space Administration (NASA) and the Japan Aerospace Exploration Agency (JAXA) launched the Global Precipitation Measurement (GPM) Core Observatory (CO) spacecraft. The GPM CO carries the most advanced precipitation sensors currently in space including a dual-frequency precipitation radar provided by JAXA for measuring the three-dimensional structures of precipitation and a well-calibrated, multifrequency passive microwave radiometer that provides wide-swath precipitation data. The GPM CO was designed to measure rain rates from 0.2 to 110.0 mm h−1 and to detect moderate to intense snow events. The GPM CO serves as a reference for unifying the data from a constellation of partner satellites to provide next-generation, merged precipitation estimates globally and with high spatial and temporal resolutions. Through improved measurements of rain and snow, precipitation data from GPM provides new information such as details on precipitation structure and intensity; observations of hurricanes and typhoons as they transition from the tropics to the midlatitudes; data to advance near-real-time hazard assessment for floods, landslides, and droughts; inputs to improve weather and climate models; and insights into agricultural productivity, famine, and public health. Since launch, GPM teams have calibrated satellite instruments, refined precipitation retrieval algorithms, expanded science investigations, and processed and disseminated precipitation data for a range of applications. The current status of GPM, its ongoing science, and its future plans are presented.
