On the Performance of a Low-Cost K-Band Doppler Radar for Quantitative Rain Measurements

Löffler‐Mang, Martin; Kunz, Michael; Schmid, Willy A.

doi:10.1175/1520-0426(1999)016<0379:otpoal>2.0.co;2

Cited by 71 publications

(59 citation statements)

References 21 publications

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“…Although the most common application of disdrometer data is to determine the drop size distribution and other properties of rain, the phase of hydrometeors can be inferred by relating velocity and size to density. Some disdrometer technologies, which can be grouped into impact, imaging, and scattering approaches (Loffler-Mang et al, 1999), are better suited for describing snow than others. Impact disdrometers, first introduced by Joss and Waldvogel (1967), use an electromechanical sensor to convert the momentum of a hydrometeor into an electric pulse.…”

Section: In Situ Observationsmentioning

confidence: 99%

“…The 2DVD has been used to classify known rain and snow events, but little work has been performed to distinguish between liquid and solid precipitation. Scattering or optical disdrometers, measure the extinction of light passing between a source and a sensor (Hauser et al, 1984;Loffler-Mang et al, 1999). Like the other types, optical disdrometers were originally designed for rain, but have been periodically applied to snow (Battaglia et al, 2010;Lempio et al, 2007).…”

Section: In Situ Observationsmentioning

confidence: 99%

“…Like the other types, optical disdrometers were originally designed for rain, but have been periodically applied to snow (Battaglia et al, 2010;Lempio et al, 2007). In a comparison study by Caracciolo et al (2006), the PARSIVEL optical disdrometer, originally described by Loffler-Mang et al (1999), did not perform well against a 2DVD because of problems related to the detection of slow fall velocities for snow. It may be possible to use optical disdrometers to distinguish between rain, sleet, and snow based on the existence of distinct shapes of the size spectra for each precipitation type.…”

Section: In Situ Observationsmentioning

confidence: 99%

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Rain or snow: hydrologic processes, observations, prediction, and research needs

Harpold

Kaplan

Klos

et al. 2017

Hydrol. Earth Syst. Sci.

159

106

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Abstract. The phase of precipitation when it reaches the ground is a first-order driver of hydrologic processes in a watershed. The presence of snow, rain, or mixed-phase precipitation affects the initial and boundary conditions that drive hydrological models. Despite their foundational importance to terrestrial hydrology, typical phase partitioning methods (PPMs) specify the phase based on near-surface air temperature only. Our review conveys the diversity of tools available for PPMs in hydrological modeling and the advancements needed to improve predictions in complex terrain with large spatiotemporal variations in precipitation phase. Initially, we review the processes and physics that control precipitation phase as relevant to hydrologists, focusing on the importance of processes occurring aloft. There is a wide range of options for field observations of precipitation phase, but there is a lack of a robust observation networks in complex terrain. New remote sensing observations have the potential to increase PPM fidelity, but generally require assumptions typical of other PPMs and field validation before they are operational. We review common PPMs and find that accuracy is generally increased at finer measurement intervals and by including humidity information. One important tool for PPM development is atmospheric modeling, which includes microphysical schemes that have not been effectively linked to hydrological models or validated against near-surface precipitation-phase observations. The review concludes by describing key research gaps and recommendations to improve PPMs, including better incorporation of atmospheric information, improved validation datasets, and regional-scale gridded data products. Two key points emerge from this synthesis for the hydrologic community: (1) current PPMs are too simple to capture important processes and are not well validated for most locations, (2) lack of sophisticated PPMs increases the uncertainty in estimation of hydrological sensitivity to changes in precipitation phase at local to regional scales. The advancement of PPMs is a critical research frontier in hydrology that requires scientific cooperation between hydrological and atmospheric modelers and field scientists.

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Section: In Situ Observationsmentioning

confidence: 99%

Section: In Situ Observationsmentioning

confidence: 99%

Section: In Situ Observationsmentioning

confidence: 99%

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Rain or snow: hydrologic processes, observations, prediction, and research needs

Harpold

Kaplan

Klos

et al. 2017

Hydrol. Earth Syst. Sci.

159

106

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“…There were gaps in the measurement record however that were filled using an empirical approach (Marks and Dozier, 1979) based on air temperature, and relative humidity when these ancillary measurements were available. We note that this approach is optimal for clear skies and produces 35 Earth Syst. Sci.…”

Section: Energy Balancementioning

confidence: 99%

“…This sensor is equipped with a Doppler 15 radar and uses a mass fallspeed relationship to estimate precipitation rates. For liquid precipitation this method works quite well (Löffler-Mang et al, 1999), but for solid precipitation, this method requires assumptions about the snowflake mass and other properties, giving inaccurate snowfall rate (Matrosov, 2007). We have noted inaccurate results when comparing the WS600 estimates to the hand weighed estimates at Sesame.…”

mentioning

confidence: 99%

Hourly mass and snow energy balance measurements from Mammoth Mountain, CA USA, 2011–2017

Bair¹,

Davis²,

Dozier³

2017

Preprint

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Observed influence of riming, temperature, and turbulence on the fallspeed of solid precipitation

Garrett

Yuter

2014

Geophys. Res. Lett.

121

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Forecasts of the amount and geographic distribution of snow are highly sensitive to a model's parameterization of hydrometeor fallspeed. Riming is generally thought to lead to particles with a higher mass and terminal velocity. Yet models commonly assume that heavily rimed particles such as graupel have a fixed density and that their settling speed is unaffected by turbulence in storms. Here we show automated measurements of photographed hydrometeor shape and fallspeed using a new instrument placed in Utah's Wasatch Mountain Range. The data show that graupel in low‐turbulence conditions has a size‐dependent fallspeed distribution with a mode near 1 m s−1, a result that is generally consistent with prior observations. However, the distributions are broadened by turbulence and there is a correspondence between particle density and air temperature. In high turbulence and at low temperatures, any sensitivity of fallspeed to particle size disappears.

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On the Performance of a Low-Cost K-Band Doppler Radar for Quantitative Rain Measurements

Cited by 71 publications

References 21 publications

Rain or snow: hydrologic processes, observations, prediction, and research needs

Rain or snow: hydrologic processes, observations, prediction, and research needs

Hourly mass and snow energy balance measurements from Mammoth Mountain, CA USA, 2011–2017

Observed influence of riming, temperature, and turbulence on the fallspeed of solid precipitation

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