Detection of sea‐breeze events around London using a fuzzy‐logic algorithm

Coceal, Omduth; Bohnenstengel, Sylvia I.; Kotthaus, Simone

doi:10.1002/asl.846

Cited by 9 publications

(13 citation statements)

References 11 publications

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“…As discussed in the previous section, the strong variability of the monsoon flow depth observed on some days, like 27-28 June, is associated with a large wind-sheared layer and a low wind. However, the intra-seasonal variability of the monsoon depth (from a few hundred meters to 4 km) and strength (from almost zero wind to 10 m s −1 ) can often be linked to synoptic conditions (Couvreux et al, 2010). Several days in a row, such as 20-23 June and 10-12 July, exhibited consistent monsoon flow characteristics over time with a particularly large monsoon flow depth and strong wind speed.…”

Section: Monsoon Flow Characteristicsmentioning

confidence: 99%

“…These changes should be the signature of the MI arrival time. This method, based on the fuzzy logic method, was used by Coceal et al (2018) to detect the sea-breeze front around London, in the south of England. Our method for MI detection at Savè follows three steps: (1) the rate of changes of temperature (T ) and horizontal wind speed (ws) (termed r T and r ws , respectively) are calculated using 30 min averaged T and ws in the 200-550 and 150-525 m layers, respectively; (2) fuzzy logic functions for T and ws, termed FLF T and FLF ws , respectively, are computed using Eq.…”

Section: Monsoon Flow Characteristicsmentioning

confidence: 99%

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Low-level stratiform clouds and dynamical features observed within the southern West African monsoon

et al. 2019

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Abstract. During the boreal summer, the monsoon season that takes place in West Africa is accompanied by low stratus clouds over land that stretch from the Guinean coast several hundred kilometers inland. Numerical climate and weather models need finer description and knowledge of cloud macrophysical characteristics and of the dynamical and thermodynamical structures occupying the lowest troposphere, in order to be properly evaluated in this region. The Dynamics-Aerosol-Chemistry-Cloud Interactions in West Africa (DACCIWA) field experiment, which took place in summer 2016, addresses this knowledge gap. Low-level atmospheric dynamics and stratiform low-level cloud macrophysical properties are analyzed using in situ and remote sensing measurements continuously collected from 20 June to 30 July at Savè, Benin, roughly 180 km from the coast. The macrophysical characteristics of the stratus clouds are deduced from a ceilometer, an infrared cloud camera, and cloud radar. Onset times, evolution, dissipation times, base heights, and thickness are evaluated. The data from an ultra-high-frequency (UHF) wind profiler, a microwave radiometer, and an energy balance station are used to quantify the occurrence and characteristics of the monsoon flow, the nocturnal low-level jet, and the cold air mass inflow propagating northward from the coast of the Gulf of Guinea. The results show that these dynamical structures are very regularly observed during the entire 41 d documented period. Monsoon flow is observed every day during our study period. The so-called “maritime inflow” and the nocturnal low-level jet are also systematic features in this area. According to synoptic atmospheric conditions, the maritime inflow reaches Savè around 18:00–19:00 UTC on average. This timing is correlated with the strength of the monsoon flow. This time of arrival is close to the time range of the nocturnal low-level jet settlement. As a result, these phenomena are difficult to distinguish at the Savè site. The low-level jet occurs every night, except during rain events, and is associated 65 % of the time with low stratus clouds. Stratus clouds form between 22:00 and 06:00 UTC at an elevation close to the nocturnal low-level jet core height. The cloud base height, 310±30 m above ground level (a.g.l.), is rather stationary during the night and remains below the jet core height. The cloud top height, at 640±100 m a.g.l., is typically found above the jet core. The nocturnal low-level jet, low-level stratiform clouds, monsoon flow, and maritime inflow reveal significant day-to-day and intra-seasonal variability during the summer given the importance of the different monsoon phases and synoptic atmospheric conditions. Distributions of strength, depth, onset time, breakup time, etc. are quantified here. These results contribute to satisfy the main goals of DACCIWA and allow a conceptual model of the dynamical structures in the lowest troposphere over the southern part of West Africa.

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Section: Monsoon Flow Characteristicsmentioning

confidence: 99%

Section: Monsoon Flow Characteristicsmentioning

confidence: 99%

Low-level stratiform clouds and dynamical features observed within the southern West African monsoon

et al. 2019

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“…This is linked to a sea‐breeze intrusion over London (also found by Coceal et al . ). The SCM is unable to capture this event because the momentum advection is imposed in 6‐hr blocks.…”

Section: Model Evaluationmentioning

confidence: 97%

“…Between 39 hr and 45 hr in the model simulation a sudden change of wind direction occurs. This is linked to a sea-breeze intrusion over London (also found by Coceal et al, 2018). The SCM is unable to capture this event because the momentum advection is imposed in 6-hr blocks.…”

Section: Model Evaluationmentioning

confidence: 99%

On‐ and off‐line evaluation of the single‐layer urban canopy model in London summertime conditions

Tsiringakis

Steeneveld

Holtslag

et al. 2019

Quart J Royal Meteoro Soc

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Urban canopy models are essential tools for forecasting weather and air quality in cities. However, they require many surface parameters, which are uncertain and can reduce model performance if inappropriately prescribed. Here, we evaluate the model sensitivity of the single‐layer urban canopy model (SLUCM) in the Weather Research and Forecasting (WRF) model to surface parameters in two different configurations, one coupled to the overlying atmosphere (on‐line) in a 1D configuration and one without coupling (off‐line). A two‐day summertime period in London is used as a case study, with clear skies and low wind speeds. Our sensitivity tests indicate that the SLUCM reacts differently when coupled to the atmosphere. For certain surface parameters, atmospheric feedback effects can outweigh the variations caused by surface parameter settings. Hence, in order to fully understand the model sensitivity, atmospheric feedback should be considered.

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“…They also rely significantly on the thresholds of the meteorological variables used. Coceal et al (2018) proposed a new method for sea-breeze detection in station observations using fuzzy logic, 1 but still relying on thresholds of the meteorological variables affected by the sea-breeze passage. There is need for a more general identification method that makes use of a minimum number of key variables that can in principle be applied to any coastal region of the world, as long as a cross-coastal direction can be found.…”

Section: Sea Breeze Identification and Predictionmentioning

confidence: 99%

The added value of convection‐permitting ensemble forecasts of sea breeze compared to a Bayesian forecast driven by the global ensemble

Cafaro

Frame

Methven

et al. 2019

Quart J Royal Meteoro Soc

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Dynamical downscaling of ensemble forecasts to convection‐permitting resolutions aims to improve forecast skill by explicitly resolving mesoscale dynamical features. The success of this approach is dependent on the ability of the model to spin up smaller features embedded in the larger‐scale flow and provide more local information than could be inferred from knowledge of the climatological response to the large‐scale flow alone. Here we test whether such additional information is obtained from the Met Office Global and Regional Ensemble Prediction Systems (MOGREPS) for the sea‐breeze phenomenon which is resolved properly only at convection‐permitting resolutions but is driven by large‐sale conditions that are well represented in the global driving model. The sea breeze is detected using a new automatic tracking algorithm suitable for use in convective‐scale forecast data. The skill of probabilistic forecasts of sea‐breeze occurrence from the high‐resolution ensemble is compared to that of a Bayesian forecast trained on paired high/low‐resolution ensemble members. This creates a statistical forecast of the high‐resolution ensemble member given knowledge of the global forecast ensemble alone. The aim of this paper is twofold: firstly to assess whether the information about sea‐breeze occurrence is encoded in a few large‐scale parameters and can be forecast by a statistical method, and secondly to estimate what information is gained by running the high‐resolution forecast beyond that which is contained in these large‐scale flow parameters. Comparison of the two forecasting methods using a variety of verification methods all lead to the same conclusion: although both the Bayesian forecast and convection‐permitting ensemble provide information about sea‐breeze occurrence, the convection‐permitting ensemble is significantly more able to discriminate between sea‐breeze events and non‐events for all lead times.

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Detection of sea‐breeze events around London using a fuzzy‐logic algorithm

Cited by 9 publications

References 11 publications

Low-level stratiform clouds and dynamical features observed within the southern West African monsoon

Low-level stratiform clouds and dynamical features observed within the southern West African monsoon

On‐ and off‐line evaluation of the single‐layer urban canopy model in London summertime conditions

The added value of convection‐permitting ensemble forecasts of sea breeze compared to a Bayesian forecast driven by the global ensemble

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