The Monitoring Network of the Vancouver 2010 Olympics

Joe, Paul; Scott, Bill; Doyle, Chris; Isaac, George A.; Gültepe, Ismail; Forsyth, Douglas E.; Cober, Stewart G.; Campos, Edwin; Heckman, Ivan; Donaldson, Norman; Hudak, David; Rasmussen, Roy; Kucera, Paul A.; Stewart, Ron; Thériault, Julie M.; Fisico, Teresa; Rasmussen, Kristen L.; Carmichael, Hannah; Laplante, Alex; Bailey, Monika; Boudala, Faisal S.

doi:10.1007/s00024-012-0588-z

Cited by 28 publications

(15 citation statements)

References 32 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Similar intensive field campaigns are needed in complex terrain that is frequently characterized by highly dynamic and spatially variable hydrometeorological conditions. Such campaigns are expensive to conduct, but can be implemented as part of operational nowcasting to develop rich data resources to advance scientific understanding as was very effectively done during the Vancouver Olympic Games in 2010 Joe et al, 2014). The research community should utilize existing datasets and capitalize on similar opportunities and expand environmental monitoring networks to simultaneously advance both atmospheric and hydrological understanding, especially in complex terrain spanning the rain-snow transition zone.…”

Section: Conduct Focused Field Campaignsmentioning

confidence: 99%

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

Harpold

Kaplan

Klos

et al. 2017

Hydrol. Earth Syst. Sci.

154

106

View full text Add to dashboard Cite

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.

show abstract

Section: Conduct Focused Field Campaignsmentioning

confidence: 99%

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

Harpold

Kaplan

Klos

et al. 2017

Hydrol. Earth Syst. Sci.

154

106

View full text Add to dashboard Cite

show abstract

“…This special set of instrumentation was deployed as part of the Science of Nowcasting Winter Weather for Vancouver 2010 (SNOW-V10) research demonstration project . Details of the instrumentation can be found in JOE et al (2012) and GULTEPE et al (2012). Radar reflectivities and Doppler wind velocities along the cross-section towards Whistler Mountain, indicated by the dashed line in Fig.…”

Section: Case Overviewmentioning

confidence: 99%

Modeling the Phase Transition Associated with Melting Snow in a 1D Kinematic Framework: Sensitivity to the Microphysics

Milbrandt

Thériault

2012

Pure Appl. Geophys.

View full text Add to dashboard Cite

Abstract-A simple 1D kinematic cloud model coupled to a two-moment bulk microphysics scheme is used to perform quasiidealized simulations of snow, with a prescribed upper boundary snow field based on observed radar reflectivity and temperature, falling into a low-level melting layer. The model realistically simulates the formation of a nearly isothermal layer below the melting level, the surface precipitation rate, and the phase transition from liquid to solid, consistent with observations for this case. A series of test runs is performed to examine the sensitivity of modeling the timing and duration of the phase transition period to details of specific parameterization aspects related to snow in the microphysics scheme. The sensitivity tests include varying the number of prognostic moments, the mass-diameter relation, the fall velocity-diameter relation, the treatment of aggregation, and the lower limit for the slope of the size distribution. It is shown that the simulated transition period, for such a case with the initial melting level being close to the surface, can be quite sensitive to model parameters specified within realistic ranges and/or ranges within our physical understanding.

show abstract

“…The HoloGondel platform is designed to be mounted on a cable car to measure vertical profiles of cloud properties. Previous studies have already made use of cable cars to obtain vertical profiles of temperature and relative humidity (Reiter, 1967;Reiter and Carnuth, 1975;Gultepe and Zhou, 2011;Joe et al, 2012), aerosol measurements (Reiter and Carnuth, 1975) or ozone soundings (Reiter, 1967;Baumann et al, 2001;Piringer et al, 2001). The HoloGondel platform is equipped with instruments to observe the meteorological parameters of temperature, relative humidity, wind speed and direction.…”

mentioning

confidence: 99%

HoloGondel: in situ cloud observations on a cable car in the Swiss Alps using a holographic imager

et al. 2017

View full text Add to dashboard Cite

Abstract. In situ observations of cloud properties in complex alpine terrain where research aircraft cannot sample are commonly conducted at mountain-top research stations and limited to single-point measurements. The HoloGondel platform overcomes this limitation by using a cable car to obtain vertical profiles of the microphysical and meteorological cloud parameters. The main component of the HoloGondel platform is the HOLographic Imager for Microscopic Objects (HOLIMO 3G), which uses digital in-line holography to image cloud particles. Based on two-dimensional images the microphysical cloud parameters for the size range from small cloud particles to large precipitation particles are obtained for the liquid and ice phase. The low traveling velocity of a cable car on the order of 10 m s −1 allows measurements with high spatial resolution; however, at the same time it leads to an unstable air speed towards the HoloGondel platform. Holographic cloud imagers, which have a sample volume that is independent of the air speed, are therefore well suited for measurements on a cable car. Example measurements of the vertical profiles observed in a liquid cloud and a mixed-phase cloud at the Eggishorn in the Swiss Alps in the winters 2015 and 2016 are presented. The HoloGondel platform reliably observes cloud droplets larger than 6.5 µm, partitions between cloud droplets and ice crystals for a size larger than 25 µm and obtains a statistically significantly size distribution for every 5 m in vertical ascent.

show abstract

The Monitoring Network of the Vancouver 2010 Olympics

Cited by 28 publications

References 32 publications

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

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

Modeling the Phase Transition Associated with Melting Snow in a 1D Kinematic Framework: Sensitivity to the Microphysics

HoloGondel: in situ cloud observations on a cable car in the Swiss Alps using a holographic imager

Contact Info

Product

Resources

About