Generation and Detection of Dynamic Gravitational‐Gradient Fields

Regional climate change in Ukraine in recent decades is accompanied by an increase in the repetitiveness of intense waves, both heat and cold; there is a tendency to increase the frequency of warm winters, but sometimes there are periods with significant decreases in temperature. The aim of the study is to determine the specifics of the formation of air temperature anomalies in the cold period 2010–2019. According to the distribution of the average monthly air temperature at the stations Odessa, Kiev, Kharkiv, Lviv investigated positive and negative deviations from the climate norm. In January, the average monthly air temperature in most cases was above normal, except for 1–3 years. The maximum positive anomaly was 4–5°C in Kyiv and Lviv (2015), the largest negative deviations were 3.8°C. In February, the trend continues – only 2–3 years with negative anomalies, the largest deviations to 3–6°C in 2011 and 2012, and positive deviations maximum in 2016. In March, negative temperature anomalies were observed 3–4 years, with a maximum of 2–3°C in 2018, positive anomalies in 4–6°C were observed in 2014, 2017. Temperatures in November were variable, with the prevailing positive anomaly, a high of 6–8°C in 2010. The distribution of air temperature in December was characterized by positive deviations of a maximum of 5–6°C in 2011, 2015, 2017 and 2019. Months of the greatest positive and negative air temperature anomalies over Europe have been highlighted. Among the colder months, the biggest anomaly stood out in January 2010 and February 2012 to 5–6°C. Among the warm months, the temperature anomaly was observed in February 2016, positive deviations from the norm to 8°C. Heat waves formed in winter with a zonal type of circulation, when warm moist air from the Atlantic shifted across the periphery of the Icelandic low. In March, waves of heat formed in low–gradient fields. Powerful waves of cold over the European sector were mainly formed under the influence of “eastern processes” in the spread of the Siberian anticyclone to Europe. In some years, significant cooling over Ukraine is formed in cyclonic systems with a high–altitude thermobaric field characterized by polar or ultrapolar hollow.

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Hydrodynamic Modeling of Cerebrospinal Fluid Motion Within the Spinal Cavity

10.1115/imece2000-2625 ◽

2000 ◽

Author(s):

M. Atif Yardimci ◽

Francis Loth ◽

Noam Alperin

Keyword(s):

Pressure Gradient ◽

Spinal Canal ◽

Fluid Motion ◽

Velocity Shear ◽

Sectional Area ◽

Flow Waveform ◽

Cross Sectional ◽

Gradient Fields ◽

Gradient Waveform

Abstract In the present work, a geometric and hydrodynamic characterization of an anatomically relevant spinal canal model is presented. A numerical model was employed to investigate effects of cross-sectional geometry and spinal cord motion on unsteady velocity, shear stress, and pressure gradient fields. The velocity field was shown to be blunt, due to the inertial character of the flow, with velocity peaks located near the boundaries of the spinal canal rather than at the midpoint between boundaries. The pressure gradient waveform was found to be almost exclusively dependent on the flow waveform and cross-sectional area.

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Automated dynamic motion correction using normalized gradient fields for 82rubidium PET myocardial blood flow quantification

Journal of Nuclear Cardiology ◽

10.1007/s12350-018-01471-4 ◽

2018 ◽

Vol 27 (6) ◽

pp. 1982-1998 ◽

Cited By ~ 9

Author(s):

Benjamin C. Lee ◽

Jonathan B. Moody ◽

Alexis Poitrasson-Rivière ◽

Amanda C. Melvin ◽

Richard L. Weinberg ◽

...

Keyword(s):

Blood Flow ◽

Myocardial Blood Flow ◽

Motion Correction ◽

Flow Quantification ◽

Blood Flow Quantification ◽

Dynamic Motion ◽

Myocardial Blood Flow Quantification ◽

Gradient Fields ◽

Normalized Gradient

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Using adjoint sensitivity as a local structure function in variational data assimilation

Nonlinear Processes in Geophysics ◽

10.5194/npg-8-347-2001 ◽

2001 ◽

Vol 8 (6) ◽

pp. 347-355 ◽

Cited By ~ 10

Author(s):

G. Hello ◽

F. Bouttier

Keyword(s):

Data Assimilation ◽

Structure Function ◽

Local Structure ◽

Initial Conditions ◽

Storm Track ◽

Variational Data Assimilation ◽

Sensitive Area ◽

Adjoint Sensitivity ◽

Weather Events ◽

Gradient Fields

Abstract. One approach recently proposed in order to improve the forecast of weather events, such as cyclogenesis, is to increase the number of observations in areas depending on the flow configuration. These areas are obtained using, for example, the sensitivity to initial conditions of a selected predicted cyclone. An alternative or complementary way is proposed here. The idea is to employ such an adjoint sensitivity field as a local structure function within variational data assimilation, 3D-Var in this instance. Away from the sensitive area, observation increments project on the initial fields with the usual climatological (or weakly flow-dependent, in the case of 4D-Var) structure functions. Within the sensitive area, the gradient fields are projected using all the available data in the zone, conventional or extra, if any. The formulation of the technique is given and the approach is further explained by using a simple 1D scheme. The technique is implemented in the ARPEGE/IFS code and applied to 11 FASTEX (Fronts and Atlantic Storm-Track Experiment) cyclone cases, together with the targeted observations performed at the time of the campaign. The new approach is shown to allow for the desired stronger impact of the available observations and to systematically improve the forecasts of the FASTEX cyclones, unlike the standard 3D-Var.

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