Weather radar: Operation and phenomenology

Reed, Jenny L.; Lanterman, Aaron D.; Trostel, John M.

doi:10.1109/maes.2017.150178

Cited by 4 publications

(4 citation statements)

References 23 publications

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“…There are a large number of existing data products, such as highresolution radar data, e.g. from NEXRAD over the United States and similar networks in several other regions of the world (Reed et al, 2017), that would be most suited for use with tobac. Furthermore, the application of tobac is not strictly limited to the analysis of clouds, and it can also be applied to study other features of the Earth system that can be identified as well-defined time-evolving regions, such as distinct aerosol plumes in the atmosphere or plankton in the surface layer of the ocean.…”

Section: Discussionmentioning

confidence: 99%

“…The identification of individual cloud objects in satellite data is one aspect of cloud tracking and has been used to investigate the spatial scaling of clouds on a global scale (Wilcox and Ramanathan, 2001;Wood and Field, 2011), including studies on the representation of these distributions in global atmospheric mod-els (Wilcox, 2003;O'Brien et al, 2013). The use of satellite data from active sensors (Nesbitt et al, 2000;Bacmeister and Stephens, 2011;Riley et al, 2011;Igel et al, 2014;Guillaume et al, 2018) allows for the inclusion of information about the vertical extent of identified cloud objects, which provides an improved classification of cloud types and understanding of important physical processes.…”

Section: Introductionmentioning

confidence: 99%

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tobac 1.2: towards a flexible framework for tracking and analysis of clouds in diverse datasets

Heikenfeld¹,

Marinescu²,

Christensen³

et al. 2019

Geosci. Model Dev.

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Abstract. We introduce tobac (Tracking and Object-Based Analysis of Clouds), a newly developed framework for tracking and analysing individual clouds in different types of datasets, such as cloud-resolving model simulations and geostationary satellite retrievals. The software has been designed to be used flexibly with any two- or three-dimensional time-varying input. The application of high-level data formats, such as Iris cubes or xarray arrays, for input and output allows for convenient use of metadata in the tracking analysis and visualisation. Comprehensive analysis routines are provided to derive properties like cloud lifetimes or statistics of cloud properties along with tools to visualise the results in a convenient way. The application of tobac is presented in two examples. We first track and analyse scattered deep convective cells based on maximum vertical velocity and the three-dimensional condensate mixing ratio field in cloud-resolving model simulations. We also investigate the performance of the tracking algorithm for different choices of time resolution of the model output. In the second application, we show how the framework can be used to effectively combine information from two different types of datasets by simultaneously tracking convective clouds in model simulations and in geostationary satellite images based on outgoing longwave radiation. The tobac framework provides a flexible new way to include the evolution of the characteristics of individual clouds in a range of important analyses like model intercomparison studies or model assessment based on observational data.

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Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

tobac 1.2: towards a flexible framework for tracking and analysis of clouds in diverse datasets

Heikenfeld¹,

Marinescu²,

Christensen³

et al. 2019

Geosci. Model Dev.

View full text Add to dashboard Cite

show abstract

“…There are a large number of existing data products, such as high-resolution radar data, e.g. from NEXRAD over the United States or similar networks in several other regions of the world (Reed et al, 2017), that would be most suited for the use with tobac. Furthermore, the application of tobac is not strictly limited to the analysis of clouds, and it can also be applied to study other features of the Earth system that can be identified as well-defined time evolving regions, such as distinct aerosol plumes in the atmosphere or plankton in the surface layer of the ocean.…”

Section: Discussionmentioning

confidence: 99%

tobac v1.0: towards a flexible framework for tracking and analysis of clouds in diverse datasets

Heikenfeld¹,

Marinescu²,

Christensen³

et al. 2019

Preprint

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Abstract. We introduce tobac (Tracking and Object-Based Analysis of Clouds), a newly developed framework for tracking and analysing individual clouds in different types of datasets, such as cloud-resolving model simulations and geostationary satellite retrievals. The software has been designed to be used flexibly with any two- or three-dimensional time-varying input. The application of high-level data formats, such as iris cubes or xarray arrays, for input and output allows for convenient use of metadata in the tracking analysis and visualisation. Comprehensive analysis routines are provided to derive properties like cloud lifetimes or statistics of cloud properties along with tools to visualise the results in a convenient way. The application of tobac is presented in two examples. We first track and analyse scattered deep convective cells based on maximum vertical velocity and the three-dimensional condensate mixing ratio field in cloud-resolving model simulations. We also investigate the performance of the tracking algorithm for different choices of time resolution of the model output. In the second application, we show how the framework can be used to effectively combine information from two different types of datasets by simultaneously tracking convective clouds in model simulations and in geostationary satellite images based on outgoing longwave radiation. tobac provides a flexible new way to include the evolution of the characteristics of individual clouds in a range of important analyses like model intercomparison studies or model assessment based on observational data.

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“…Radar‐rainfall estimates are critical to inform decision‐making in a broad range of sectors in Nepal, including water‐related infrastructure development, energy, construction, transportation, tourism, and agriculture (e.g. Krajewski and Smith, 2002; Smith et al ., 2002; Krajewski et al ., 2010; Reed et al ., 2017; Thorndahl et al ., 2017). Continuous rainfall monitoring through the weather radar could improve flood forecasts, provide tornado or cyclone warnings, enhance aviation safety, increase the operational efficiency of the air transport industry, inform agricultural planning, help hydropower operations, provide landslide and soil erosion alerts, and plan recreational activities (e.g.…”

Section: Opportunities and Challengesmentioning

confidence: 99%

Weather radar in Nepal: opportunities and challenges in a mountainous region

Talchabhadel¹,

Ghimire

Sharma

et al. 2021

Weather

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Extreme rainfall is one of the major causes of natural hazards (for example flood, landslide, and debris flow) in the central Himalayan region, Nepal. The performance of strategies to manage these risks relies on the accuracy of quantitative rainfall estimates. Rain gauges have traditionally been used to measure the amount of rainfall at a given location. The point measurement often misrepresents the basin estimates, because of limited density and high spatial variability of rainfall fields across the Himalayas. The Department of Hydrology and Meteorology (DHM), Nepal has planned to install a network of three weather radars that cover the entire country. So far, the first weather radar has been installed in 2019 in the western region of the country. Two more radars will be added for the planned radar network in the near future covering the central and eastern regions of the country. Here we introduce the first installed weather radar in Nepal. We highlight both the opportunities and challenges with the radar observation in the mountainous regions. Radar rainfall estimates across the Himalayas are critical to issue severe weather warnings; forecast floods and landslides; and inform decision making in a broad range of sectors, including water and energy, construction, transportation, and agriculture.

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Weather radar: Operation and phenomenology

Cited by 4 publications

References 23 publications

tobac 1.2: towards a flexible framework for tracking and analysis of clouds in diverse datasets

tobac 1.2: towards a flexible framework for tracking and analysis of clouds in diverse datasets

tobac v1.0: towards a flexible framework for tracking and analysis of clouds in diverse datasets

Weather radar in Nepal: opportunities and challenges in a mountainous region

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