Diagnosing eclipse-induced wind changes

Responses in surface winds to solar eclipses have an almost mystical status but are difficult to detect in observations because of their transient nature. High spatial resolution (approx. 1.5 km grid) meteorological models now provide a new technique for their investigation. Measurements from the southern UK meteorological network during the 11 August 1999 total solar eclipse are compared with a high-resolution model ignorant of the lunar shadow's influence. Differences between the model output and measurements at the eclipse time show transient eclipse zone temperature decreases of up to 3 ° C, which also depressed the day's maximum temperature compared with the model prediction. Coherent responses in temperature, and wind speed and direction measurements are detected in the inland cloud-free region (from 51 ° to 52 ° N and −2 ° to 0 ° E). A mean regional wind speed decrease of 0.7 m s −1 during the maximum eclipse hour is apparent with a mean anticlockwise wind direction change of 17 ° ; no such changes occurred in the model output. Such regional circulation changes are consistent with Clayton's 1901 cold-cored eclipse cyclone hypothesis, which may be related to the anecdotal ‘eclipse wind’.

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iGen: the automated generation of a parameterisation of entrainment in marine stratocumulus

Geoscientific Model Development Discussions ◽

10.5194/gmdd-4-971-2011 ◽

2011 ◽

Vol 4 (2) ◽

pp. 971-995 ◽

Cited By ~ 2

Author(s):

D. F. Tang ◽

S. Dobbie

Keyword(s):

Large Scale ◽

Source Code ◽

Marine Stratocumulus ◽

Automated Generation ◽

Entrainment Velocity ◽

Cloud Resolving Model ◽

Resolution Model ◽

High Resolution Model ◽

The Mean ◽

A New Technique

Abstract. In a previous paper we described a new technique for automatically generating parameterisations using a program called iGen. iGen generates parameterisations by analysing the source code of a high resolution model that resolves the physics to be parameterised. In order to demonstrate that this technique scales up to deal with models of realistic complexity we have used iGen to generate a parameterisation of entrainment in marine stratocumulus. We present details of our technique in which iGen was used to analyse the source code of a cloud resolving model and generate a parameterisation of the mean and standard deviation of entrainment velocity in marine stratocumulus in terms of the large-scale state of the boundary layer. The parameterisation was tested against results from the DYCOMS-II intercomparison of cloud resolving models and iGen's parameterisation of mean entrainment velocity was found to be 5.27 × 10−3 ± 0.62 × 10−3 m s−1 compared to 5.2 × 10−3 ± 0.8 × 10−3 m s−1 for the DYCOMS-II ensemble of cloud resolving models.

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A deep learning based approach for inferring the distribution of potential extreme events from coarse resolution climate model output

10.5194/egusphere-egu2020-7559 ◽

2020 ◽

Author(s):

Leroy Bird ◽

Greg Bodeker ◽

Jordis Tradowsky

Keyword(s):

Deep Learning ◽

High Resolution ◽

Computational Cost ◽

Extreme Weather Events ◽

Precipitation Event ◽

Model Output ◽

Coarse Resolution ◽

Extreme Precipitation Events ◽

Resolution Model ◽

High Resolution Model

<p>Frequency based climate change attribution of extreme weather events requires thousands of years worth of model output in order to obtain a statistically sound result. Additionally, extreme precipitation events in particular require a high resolution model as they can occur over a relatively small area. Unfortunately due storage and computational restrictions it is not feasible to run traditional models at a sufficiently high spatial resolution for the complete duration of these simulations. Instead, we suggest that deep learning could be used to emulate a proportion of a high resolution model, at a fraction of the computational cost. More specifically, we use a U-Net, a type of convolutional neural network. The U-Net takes as input, several fields from coarse resolution model output and is trained to predict corresponding high resolution precipitation fields. Because there are many potential precipitation fields associated with the coarse resolution model output, stochasticity is added to the U-Net and a generative adversarial network is employed in order to help create a realistic distribution of events. By sampling the U-Net many times, an estimate of the probability of a heavy precipitation event occurring on the sub-grid scale can be derived.</p>

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A Synoptic Study of Low Troposphere Wind at the Israeli Coast

The Open Atmospheric Science Journal ◽

10.2174/1874282301812010080 ◽

2018 ◽

Vol 12 (1) ◽

pp. 80-106

Author(s):

Sigalit Berkovic ◽

Pinhas Alpert

Keyword(s):

Wind Speed ◽

Wind Direction ◽

Interim Analysis ◽

Surface Wind ◽

Radiosonde Data ◽

Good Prediction ◽

Wind Vector ◽

The West ◽

Resolution Model ◽

High Resolution Model

Objective:This research is dedicated to the study of the feasibility of surface wind downscaling from 925 or 850 hPa winds according to synoptic class, season and hour.Methods:Two aspects are examined: low tropospheric wind veering and wind speed correlation and verification of the ERA-Interim analysis wind by comparison to radiosonde data at Beit Dagan, a station on the Israeli coast.Results:Relatively small (< 60°) cross angles between the 1000 hPa wind vector and the 925 hPa or 850 hPa wind vector at 12Z and high correlation (0.6-0.8) between the wind speed at the two levels were found only under winter lows. Relatively small cross angles and small wind speed correlation were found under highs to the west and Persian troughs.The verification of ERA-Interim analysis in comparison with radiosonde data has shown good prediction of wind direction at 12Z at 1000, 925 and 850 hPa levels (RMSE 20°-60°) and lower prediction quality at 1000 hPa at 0Z (RMSE 60°-90°). The analysis under-predicts the wind speed, especially at 1000 hPa. The wind speed RMSE is 1-2 m/s, except for winter lows with 2-3 m/s RMSE at 0Z, 12Z at all levels.Conclusion:Inference of surface wind may be possible at 12Z from 925 or 825 hPa winds under winter lows. Inference of wind direction from 925 hPa winds may be possible under highs to the west and Persian troughs. Wind speed should be inferred by interpolation, according to historical data of measurements or high resolution model.

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Simulation and analysis of wind speed and direction of unmanned aerial vehicle route in the Beijing-Tianjin-Hebei region based on high resolution model

地理科学进展 ◽

10.18306/dlkxjz.2021.09.008 ◽

2021 ◽

Vol 40 (9) ◽

pp. 1528-1539

Author(s):

Ruomei ZHONG ◽

Xiaohang WEN ◽

Chenchen XU ◽

Keyword(s):

High Resolution ◽

Wind Speed ◽

Unmanned Aerial Vehicle ◽

Vehicle Route ◽

Resolution Model ◽

Aerial Vehicle ◽

High Resolution Model

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iGen 0.1: the automated generation of a parameterisation of entrainment in marine stratocumulus

Geoscientific Model Development ◽

10.5194/gmd-4-797-2011 ◽

2011 ◽

Vol 4 (3) ◽

pp. 797-807 ◽

Cited By ~ 2

Author(s):

D. F. Tang ◽

S. Dobbie

Keyword(s):

Large Scale ◽

Source Code ◽

Marine Stratocumulus ◽

Automated Generation ◽

Entrainment Velocity ◽

Eddy Simulation ◽

Large Eddy ◽

Resolution Model ◽

High Resolution Model ◽

A New Technique

Abstract. In a previous paper we described a new technique for automatically generating parameterisations using a program called iGen. iGen generates parameterisations by analysing the source code of a~high resolution model that resolves the physics to be parameterised. In order to demonstrate that this technique scales up to deal with models of realistic complexity we have used iGen to generate a parameterisation of entrainment in marine stratocumulus. We describe how iGen was used to analyse the source code of an eddy resolving model (ERM) and generate a parameterisation of entrainment velocity in marine stratocumulus in terms of the large-scale state of the boundary layer. The parameterisation was tested against results from the DYCOMS-II intercomparison of ERM models and iGen's parameterisation of mean entrainment velocity was found to be 5.27 × 10−3 ± 0.62 × 10−3 m s−1 compared to 5.2 × 10−3 ± 0.8 × 10−3 m s−1 for the DYCOMS-II ensemble of large eddy simulation (LES) models.

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