A Method for the Initialization of the Anelastic Equations: Implications for Matching Models with Observations

Gal-Chen, Tzvi

doi:10.1175/1520-0493(1978)106<0587:amftio>2.0.co;2

Cited by 133 publications

(38 citation statements)

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“…Techniques for retrieving thermodynamical and microphysical fields from dual-Doppler synthesized winds were developed in the past (Gal-Chen 1978;Roux 1985;Ziegler 1985). Therefore, if the 3D wind fields can be determined from single-Doppler observations, the other fields can be retrieved by applying these techniques.…”

Section: Review Of Data Assimilation Techniques Used For the Convectimentioning

confidence: 99%

Convective‐scale assimilation of radar data: progress and challenges

Sun

2005

Quart J Royal Meteoro Soc

134

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SUMMARYActive research has been carried out in recent years to assimilate high-resolution observations into numerical models to improve precipitation forecasting. Considerable progress has been made although great scientific and technological challenges still exist. This paper reviews techniques used in convective-scale data assimilation research. Experiences in the assimilation of radar observations into high-resolution numerical models are presented. A number of future challenges in convective-scale data assimilation are discussed.

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Section: Review Of Data Assimilation Techniques Used For the Convectimentioning

confidence: 99%

Convective‐scale assimilation of radar data: progress and challenges

Sun

2005

Quart J Royal Meteoro Soc

134

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“…Although dozens of dual-Doppler datasets have been obtained by mobile radars in convective storms in field projects (e.g., Wakimoto and Atkins 1996;Wakimoto et al 1998;Trapp 1999;Wakimoto and Cai 2000;Ziegler et al 2001;Dowell and Bluestein 2002;Beck et al 2006;Wurman et al 2007aWurman et al ,b, 2010Marquis et al 2008Marquis et al , 2012Frame et al 2009;Markowski et al 2011Markowski et al , 2012Kosiba et al 2013;Calhoun et al 2013;Potvin et al 2013;Skinner et al 2014;Davenport and Parker 2015;Klees et al 2016;Betten et al 2017), complementary thermodynamic observations mostly have been limited to in situ measurements by automobiles, termed mobile mesonets (Straka et al 1996;Waugh and Fredrickson 2010), and rapidly deployable surface stations, such as the Texas Tech University StickNet . Although pressure and buoyancy fields can be retrieved from dual-Dopplerderived wind fields (e.g., Gal-Chen 1978;Hane et al 1981;Brandes 1984;Hauser et al 1988), the retrieved fields (especially buoyancy) have not been found to be sufficiently accurate for the quantitative study of severe convective storms, owing to the large sensitivity of the retrievals to observation errors and boundary conditions (e.g., Majcen et al 2008). Buoyancy retrievals are especially error prone owing to their sensitivity to vertical gradients of retrieved pressure and the time derivative of the vertical velocity field.…”

Section: Aboveground Thermodynamic Observations In Convective Storms mentioning

confidence: 99%

Aboveground Thermodynamic Observations in Convective Storms from Balloonborne Probes Acting as Pseudo-Lagrangian Drifters

Markowski

Richardson

et al. 2018

Bulletin of the American Meteorological Society

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The severe storms research community lacks reliable, aboveground, thermodynamic observations (e.g., temperature, humidity, and pressure) in convective storms. These missing observations are crucial to understanding the behavior of both supercell storms (e.g., the generation, reorientation, and amplification of vorticity necessary for tornado formation) and larger-scale (mesoscale) convective systems (e.g., storm maintenance and the generation of damaging straight-line winds). This paper describes a novel way to use balloonborne probes to obtain aboveground thermodynamic observations. Each probe is carried by a pair of balloons until one of the balloons is jettisoned; the remaining balloon and probe act as a pseudo-Lagrangian drifter that is drawn through the storm. Preliminary data are presented from a pair of deployments in supercell storms in Oklahoma and Kansas during May 2017. The versatility of the observing system extends beyond severe storms applications into any area of mesoscale meteorology in which a large array of aboveground, in situ thermodynamic observations are needed.

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“…[55] The theory for dynamic retrieval was first implemented by Gal-Chen [1978] and has since been used to generate pressure fields from Doppler radar observations [e.g., Gal-Chen and Kropfli, 1984;Parsons et al, 1987;Liou, 2001]. In the present case, we assume that the horizontal pressure gradient above the planetary boundary layer is given by…”

Section: Appendix A: Dynamic Retrieval Of the Pressure Fieldsmentioning

confidence: 99%

Predicting the frequency of storm surges and extreme sea levels in the northwest Atlantic

Bernier

Thompson

2006

J. Geophys. Res.

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[1] A 40 year hindcast of storm surges in the northwest Atlantic and adjacent shelf seas is performed using a 2-D nonlinear barotropic ocean model forced by realistic 6 hourly winds and air pressures. This hindcast is used to generate spatial maps of the return level of storm surges and also to estimate the return period of extreme total sea levels. The accuracy of the hindcast is assessed in two ways. First, the standard deviation of the difference between the observed residuals (total sea level minus tide) and the hindcast is calculated at 24 tide gauge locations. A typical error standard deviation is 8 cm. Second, the 40 year return level of observed residuals is compared to that of the hindcast surges. The predicted 40 year return levels are typically within 10 cm of observed return levels at the 24 observation locations. A spatial map of the 40 year return level of surges is presented for the northwest Atlantic. It identifies the regions exposed to the largest surges. Total sea levels are reconstructed using (1) the hindcast surges and (2) tides and higher-frequency variability predicted from short, observed sea level records. An extremal analysis of the reconstructed total sea levels shows that their 40 year return levels are in good agreement (within about 10 cm) with the levels calculated from multidecadal observed sea level records. This means that given a short record anywhere within the model domain, or results from a good tidal model, 40 year return levels can be estimated.

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A Method for the Initialization of the Anelastic Equations: Implications for Matching Models with Observations

Cited by 133 publications

References 0 publications

Convective‐scale assimilation of radar data: progress and challenges

Convective‐scale assimilation of radar data: progress and challenges

Aboveground Thermodynamic Observations in Convective Storms from Balloonborne Probes Acting as Pseudo-Lagrangian Drifters

Predicting the frequency of storm surges and extreme sea levels in the northwest Atlantic

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