The role of mesoscale cloud organization in the daily cycle of trade-wind cumuli

2021 ◽  
Author(s):  
Jessica Vial ◽  
Raphaela Vogel ◽  
Hauke Schulz
Keyword(s):  
Cloud Cover ◽  
Large Scale ◽  
Spatial Organization ◽  
Surface Wind ◽  
Specific Pattern ◽  
Trade Wind ◽  
Daily Cycle ◽  
Diurnal Variability ◽  
Near Surface

<p>The role of spatial organization of clouds at mesoscale in the daily cycle of shallow cumulus clouds and precipitation is here explored, for the first time, using three years of high-frequency satellite- and ground-based observations. We focus on the four prominent patterns of cloud organization – Sugar, Gravel, Flowers and Fish – which were found recently to characterize well the variability of the North Atlantic winter trades. Our analysis is based on a simple framework to disentangle the parts of the daily cycle of trade cloudiness that are due to changes in (i) the occurrence frequency of patterns and (ii) cloud cover for a given pattern. Our investigation reveals that the contribution of mesoscale organization to the daily cycle in cloudiness is largely mediated by the frequency of pattern occurrence. All forms of mesoscale organization exhibit a pronounced daily cycle in their frequency of occurrence, with distinct 24-hour phasing. The patterns Fish and Sugar can be viewed as daytime patterns, with a frequency peak around noon for Fish and towards sunset for Sugar. The patterns Gravel and Flowers appear rather as nighttime patterns, with a peak occurrence around midnight for Gravel and before sunrise for Flowers. The cloud cover for a given pattern, however, always maximizes at nighttime (between 00LT and 03LT), regardless of the specific pattern. The daily variability in the occurrence of Sugar, Gravel and Flowers together seem to reflect the evolution of the daytime shallow cloud population (peaking around sunset) and of the nighttime population of deeper cumuli (peaking near dawn), which were identified in previous work. Finally, some insight on the role of large-scale environmental conditions shows that the near-surface wind speed can explain a large part of the diurnal variability in pattern frequency and cloudiness. </p>

scholarly journals Multiple Regimes of Wind, Stratification, and Turbulence in the Stable Boundary Layer

2015 ◽  
Vol 72 (8) ◽  
pp. 3178-3198 ◽  
Author(s):  
Adam H. Monahan ◽  
Tim Rees ◽  
Yanping He ◽  
Norman McFarlane
Keyword(s):  
Boundary Layer ◽  
Wind Speed ◽  
Cloud Cover ◽  
Large Scale ◽  
Potential Temperature ◽  
Surface Wind ◽  
Geostrophic Wind ◽  
Gradient Force ◽  
Pressure Gradient Force ◽  
Near Surface

Abstract A long time series of temporally high-resolution wind and potential temperature data from the 213-m tower at Cabauw in the Netherlands demonstrates the existence of two distinct regimes of the stably stratified nocturnal boundary layer at this location. Hidden Markov model (HMM) analysis is used to objectively characterize these regimes and classify individual observed states. The first regime is characterized by strongly stable stratification, large wind speed differences between 10 and 200 m, and relatively weak turbulence. The second is associated with near-neutral stratification, weaker wind speed differences between 10 and 200 m, and relatively strong turbulence. In this second regime, the state of the boundary layer is similar to that during the day. The occupation statistics of these regimes are shown to covary with the large-scale pressure gradient force and cloud cover such that the first regime predominates under clear skies with weak geostrophic wind speed and the second regime predominates under conditions of extensive cloud cover or large geostrophic wind speed. These regimes are not distinguished by standard measures of stability, such as the Obukhov length or the bulk Richardson number. Evidence is presented that the mechanism generating these distinct regimes is associated with a previously documented feedback resulting from the existence of an upper limit on the maximum downward heat flux that can be sustained for a given near-surface wind speed.

scholarly journals The role of serial European windstorm clustering for extreme seasonal losses as determined from multi-centennial simulations of high-resolution global climate model data

2018 ◽  
Vol 18 (11) ◽  
pp. 2991-3006 ◽  
Author(s):  
Matthew D. K. Priestley ◽  
Helen F. Dacre ◽  
Len C. Shaffrey ◽  
Kevin I. Hodges ◽  
Joaquim G. Pinto
Keyword(s):  
High Resolution ◽  
Return Period ◽  
Large Scale ◽  
Climate Model ◽  
Global Climate ◽  
Global Climate Model ◽  
Geographic Region ◽  
Near Surface ◽  
Short Period

Abstract. Extratropical cyclones are the most damaging natural hazard to affect western Europe. Serial clustering occurs when many intense cyclones affect one specific geographic region in a short period of time which can potentially lead to very large seasonal losses. Previous studies have shown that intense cyclones may be more likely to cluster than less intense cyclones. We revisit this topic using a high-resolution climate model with the aim to determine how important clustering is for windstorm-related losses. The role of windstorm clustering is investigated using a quantifiable metric (storm severity index, SSI) that is based on near-surface meteorological variables (10 m wind speed) and is a good proxy for losses. The SSI is used to convert a wind footprint into losses for individual windstorms or seasons. 918 years of a present-day ensemble of coupled climate model simulations from the High-Resolution Global Environment Model (HiGEM) are compared to ERA-Interim reanalysis. HiGEM is able to successfully reproduce the wintertime North Atlantic/European circulation, and represent the large-scale circulation associated with the serial clustering of European windstorms. We use two measures to identify any changes in the contribution of clustering to the seasonal windstorm loss as a function of return period. Above a return period of 3 years, the accumulated seasonal loss from HiGEM is up to 20 % larger than the accumulated seasonal loss from a set of random resamples of the HiGEM data. Seasonal losses are increased by 10 %–20 % relative to randomized seasonal losses at a return period of 200 years. The contribution of the single largest event in a season to the accumulated seasonal loss does not change with return period, generally ranging between 25 % and 50 %. Given the realistic dynamical representation of cyclone clustering in HiGEM, and comparable statistics to ERA-Interim, we conclude that our estimation of clustering and its dependence on the return period will be useful for informing the development of risk models for European windstorms, particularly for longer return periods.

scholarly journals Fifty-Seven-Year California Reanalysis Downscaling at 10 km (CaRD10). Part I: System Detail and Validation with Observations

2007 ◽  
Vol 20 (22) ◽  
pp. 5553-5571 ◽  
Author(s):  
Masao Kanamitsu ◽  
Hideki Kanamaru
Keyword(s):  
Time Scales ◽  
Large Scale ◽  
Global Analysis ◽  
Regional Climate ◽  
Regional Scale ◽  
Surface Wind ◽  
Lateral Boundary ◽  
Climate Change Research ◽  
Near Surface ◽  
Precipitation Analysis

Abstract For the purpose of producing datasets for regional-scale climate change research and application, the NCEP–NCAR reanalysis for the period 1948–2005 was dynamically downscaled to hourly, 10-km resolution over California using the Regional Spectral Model. This is Part I of a two-part paper, describing the details of the downscaling system and comparing the downscaled analysis [California Reanalysis Downscaling at 10 km (CaRD10)] against observation and global analysis. An extensive validation of the downscaled analysis was performed using station observations, Higgins gridded precipitation analysis, and Precipitation-Elevation Regression on Independent Slopes Model (PRISM) precipitation analysis. In general, the CaRD10 near-surface wind and temperature fit better to regional-scale station observations than the NCEP–NCAR reanalysis used to force the regional model, supporting the premise that the regional downscaling is a viable method to attain regional detail from large-scale analysis. This advantage of CaRD10 was found on all time scales, ranging from hourly to decadal scales (i.e., from diurnal variation to multidecadal trend). Dynamically downscaled analysis provides ways to study various regional climate phenomena of different time scales because all produced variables are dynamically, physically, and hydrologically consistent. However, the CaRD10 is not free from problems. It suffers from positive bias in precipitation for heavy precipitation events. The CaRD10 is inaccurate near the lateral boundary where regional detail is damped by the lateral boundary relaxation. It is important to understand these limitations before the downscaled analysis is used for research.

Role of dynamic and thermodynamic processes for the propagation of organized convection in a large-scale flow

2020 ◽  
Author(s):  
Hyunju Jung ◽  
Ann Kristin Naumann ◽  
Bjorn Stevens
Keyword(s):  
Dynamic Process ◽  
Large Scale ◽  
Surface Wind ◽  
Propagation Speed ◽  
Background Wind ◽  
Near Surface ◽  
Large Scale Flow ◽  
Model Setup ◽  
Self Aggregation ◽  
Organized Convection

<p>Convective self-aggregation in radiative convective equilibrium has been studied due to its similarities to organized convection in the tropics. As tropical atmospheric phenomena are embedded in a large-scale flow, we impose a background wind to the model setup using convection-permitting simulation to analyze the interaction of convective self-aggregation with the background wind. The simulations show that when imposing a background wind, the convective cluster propagates in the direction of the imposed wind but slows down compared to what pure advection would suggest, and eventually becomes stationary. The dynamic process dominates slowing down the propagation speed of the cluster because the surface momentum flux acts as a drag on the near-surface wind, terminating the propagation. The thermodynamic process through the wind-induce surface feedback contributes to only 6% of the propagation speed of the convective cluster and is strongly modified by the dynamic process.</p>

On the understanding of the trade-wind cumuli daily cycle: the role of convective mixing and mesoscale organization of convection

2020 ◽  
Author(s):  
Jessica Vial ◽  
Hauke Schulz ◽  
Raphaela Vogel
Keyword(s):  
Trade Wind ◽  
Daily Cycle ◽  
Convective Clouds ◽  
Tropical Variability ◽  
Convective Mixing ◽  
Atlantic Trade ◽  
The North ◽  
Wide Range ◽  
Large Eddy

<p>Oceanic shallow convective clouds, which prevail in the trade-wind regions, have long been of great interest, because they strongly impact climate on a wide range of scales and they are critical in the estimation of the magnitude and pace of global warming. But surprisingly, the most fundamental mode of tropical variability, that is the daily cycle, has received very little attention for this cloud category, so that our knowledge of the diurnal processes in this oceanic shallow cumulus regime and their influence on climate at broader scales remains extremely limited. We recently relaunched the exploration of this topic. New investigating tools have been used, including large-eddy simulations run over large domains in realistic configurations and in-situ observations from the Barbados Cloud Observatory, which have helped study this daily cycle in the North Atlantic trade-wind region with a lot more details than was possible 40 years ago when it was first documented. Important features of this daily cycle have been found, which can have far reaching implications for climate change studies. Our hypothesis is that understanding the processes that control trade-wind cumuli on the diurnal timescale will benefit to our understanding of the mechanisms that are involved in the tropical marine low-level cloud feedbacks. In this regard, the wealth of observational data that will be collected during the EUREC4A campaign is unprecedented and offers a tremendous opportunity to enrich the characterisation and understanding of the mechanisms of the trade-wind daily cycle. Preliminary results will be discussed with a focus on the role of the shallow convective mixing and mesoscale organization in the daily cycle of trade-wind cumuli.</p>

scholarly journals On the imprint of the mesoscale organization of tradewind clouds at cloud base and below

2021 ◽  
Author(s):  
Sandrine Bony ◽  
Pierre-Etienne Brilouet ◽  
Patrick Chazette ◽  
Pierre Coutris ◽  
Julien Delanoë ◽  
...  
Keyword(s):  
Large Scale ◽  
Lower Troposphere ◽  
Cloud Base ◽  
Trade Wind ◽  
Tropical Atlantic ◽  
Lidar Measurements ◽  
Research Aircraft ◽  
Cloud Patterns

<p><span>Trade-wind clouds </span><span>can </span><span>exhibit </span><span>different</span><span> patterns of mesoscale organization. These patterns were observed during the EUREC</span><sup><span>4</span></sup><span>A </span><span>(Elucidating the role of cloud-circulation coupling in climate) </span><span>field campaign that took place in Jan-Feb 2020 over the western tropical Atlantic near Barbados: </span><span>w</span><span>hile the HALO aircraft </span><span>was observing clouds from</span> <span>above</span><span> and </span><span>was </span><span>characteri</span><span>z</span><span>ing</span> <span>the </span><span>large-scale</span><span> environment</span> <span>with</span><span> dropsondes</span><span>, the ATR-42 research aircraft was flying </span><span>in</span><span> the </span><span>lower troposphere</span><span>,</span> <span>characteriz</span><span>ing</span><span> cloud</span><span>s </span><span>and turbulence </span><span>with horizontal radar-lidar measurements and in-situ </span><span>probes and </span><span>sensors</span><span>. </span><span>By</span><span> analyz</span><span>ing</span> <span>these data </span><span>for different cloud patterns</span><span>, </span><span>we</span> <span>investigate the </span><span>extent to which the </span><span>cloud</span><span> organization </span><span>i</span><span>s imprinted </span><span>in</span><span> cloud-base </span><span>properties </span><span>and</span><span> subcloud-layer </span><span>heterogeneities</span><span>. </span><span>The implications of our findings for understanding the roots of the mesoscale organization </span><span>of tradewind clouds</span><span> will be discussed.</span></p>

Assessing reasons for skilful predictions of winter windstorms over the Atlantic/European region

2020 ◽  
Author(s):  
Lisa Degenhardt ◽  
Gregor Leckebusch ◽  
Adam Scaife
Keyword(s):  
Large Scale ◽  
Surface Wind ◽  
Forecast Model ◽  
Surface Wind Speed ◽  
Seasonal Forecast ◽  
Forecast Skill ◽  
Seasonal Forecasts ◽  
Financial Industry ◽  
Near Surface ◽  
Skill Scores

<p>Severe Atlantic winter storms are affecting densely populated regions of Europe (e.g. UK, France, Germany, etc.). Consequently, different parts of the society, financial industry (e.g., insurance) and last but not least the general public are interested in skilful forecasts for the upcoming storm season (usually December to March). To allow for a best possible use of steadily improved seasonal forecasts, the understanding which factors contribute to realise forecast skill is essential and will allow for an assessment whether to expect a forecast to be skilful or not.</p><p>This study analyses the predictability of the seasonal forecast model of the UK MetOffice, the GloSea5. Windstorm events are identified and tracked following Leckebusch et al. (2008) via the exceedance of the 98<sup>th</sup> percentile of the near surface wind speed.</p><p>Seasonal predictability of windstorm frequency in comparison to observations (based e.g., on ERA5 reanalysis) are calculated and different statistical methods (skill scores) are compared.</p><p>Large scale patterns (e.g., NAO, AO, EAWR, etc.) and dynamical factors (e.g., Eady Growth Rate) are analysed and their predictability is assessed in comparison to storm frequency forecast skill. This will lead to an idea how the forecast skill of windstorms is depending on the forecast skill of forcing factors conditional to the phase of large-scale variability modes. Thus, we deduce information, which factors are most important to generate seasonal forecast skill for severe extra-tropical windstorms.</p><p>The results can be used to get a better understanding of the resulting skill for the upcoming windstorm season.</p>

Dependence of mesoscale patterns of Trade-wind clouds on environmental conditions: an investigation using satellite and in-situ observations

2020 ◽  
Author(s):  
Sandrine Bony ◽  
Hauke Schulz ◽  
Jessica Vial ◽  
Bjorn Stevens ◽  
Keyword(s):  
Meteorological Data ◽  
Surface Wind ◽  
Cloud Amount ◽  
Surface Wind Speed ◽  
Trade Wind ◽  
Shallow Convection ◽  
Western Atlantic ◽  
Near Surface ◽  
Cloud Patterns

<p>Trade-wind clouds exhibit a large diversity of spatial organizations at the mesoscale. Over the tropical western Atlantic, a recent study has visually identified four prominent mesoscale patterns of shallow convection, referred to as Flowers, Fish, Gravel and Sugar. By using 19 years of satellite and meteorological data, we show that these four patterns can be identified objectively from satellite observations, and that on daily and interannual timescales, the near-surface wind speed and the strength of the lower-tropospheric stability discriminate the occurrence of the different organization patterns. Moreover, we point out a tight relationship between cloud patterns, low-level cloud amount and cloud-radiative effects. The EUREC4A field study taking place upwind of Barbados in Jan-Feb 2020 offers an opportunity to investigate these relationships from an in-situ and process-oriented perspective. Preliminary results will be discussed.</p>

The influence of the large-scale circulation on the thermodynamic profiles in the trades from a Lagrangian perspective

2020 ◽  
Author(s):  
Leonie Villiger ◽  
Franziska Aemisegger ◽  
Maxi Boettcher ◽  
Heini Wernli
Keyword(s):  
Large Scale ◽  
Surface Wind ◽  
Cloud Amount ◽  
Phase Changes ◽  
Stable Water Isotopes ◽  
Geophysical Research ◽  
Large Scale Circulation ◽  
Near Surface ◽  
Diabatic Processes ◽  
The Impact

<p>In the tropical winter trades of the North Atlantic in the vicinity of Barbados four different mesoscale organisation patterns of clouds – sugar, gravel, flower, fish - are observed regularly. Each pattern is associated with a distinct cloud amount and radiative footprint. Therefore, the relative occurrence frequency of these patterns affects the global radiative budget. As shown by a recent study (Bony et al. 2019, Geophysical Research Letter), the occurrence of the four patterns is controlled by the near-surface wind speed and the strength of lower tropospheric instability. It is however not yet clear, whether these cloud patterns occur preferably in specific larger-scale flow configurations. These can be associated for example with upper-level wave breaking in the extratropics and different positions and strengths of low-level subtropical anticyclones.</p><p>Lower tropospheric air parcels at different altitudes in the trades are expected to have different transport histories associated with distinct diabatic processes such as radiative effects, phase changes within and below clouds and turbulent mixing. The diabatic processes encountered during transport modulate the thermodynamic properties of the air parcels and therefore influence the vertical thermodynamic structure of the atmosphere in the trades.</p><p>In this study, the impact of large-scale air mass advection on the thermodynamic profiles over Barbados is analysed for each of the four mesoscale organisation patterns observed during EUREC4A. The airmass transport history is characterised for different homogenous atmospheric layers. These layers are identified based on vertical pseudo-soundings above the Barbados Cloud Observatory (BCO) using ECMWF analysis data for cases where profiles agree well with independent observations from balloon soundings. The large-scale circulation within the 10 days prior to the sounding is considered for computing the trajectories of the air masses arriving in these layers. Backward trajectories are calculated with three-dimensional analysis wind fields. Thereby, the thermodynamic history and large-scale circulation configuration associated with the four cloud organisation patterns is described from a Lagrangian perspective. In addition, composites of the sea level pressure field provide information whether the four patterns co-occur with systematically differing positions and/or intensities of subtropical anticyclones. In future work, stable water isotopes will be used as observational tracers to find supportive evidence of the characterised transport history.</p>

scholarly journals High-resolution observations of the near-surface wind field over an isolated mountain and in a steep river canyon

2015 ◽  
Vol 15 (7) ◽  
pp. 3785-3801 ◽  
Author(s):  
B. W. Butler ◽  
N. S. Wagenbrenner ◽  
J. M. Forthofer ◽  
B. K. Lamb ◽  
K. S. Shannon ◽  
...  
Keyword(s):  
High Resolution ◽  
Large Scale ◽  
Surface Wind ◽  
Wind Data ◽  
Wind Flow ◽  
Surface Winds ◽  
Mean Flow ◽  
Near Surface ◽  
Wind Speeds ◽  
Synoptic Forcing

Abstract. A number of numerical wind flow models have been developed for simulating wind flow at relatively fine spatial resolutions (e.g., ~ 100 m); however, there are very limited observational data available for evaluating these high-resolution models. This study presents high-resolution surface wind data sets collected from an isolated mountain and a steep river canyon. The wind data are presented in terms of four flow regimes: upslope, afternoon, downslope, and a synoptically driven regime. There were notable differences in the data collected from the two terrain types. For example, wind speeds on the isolated mountain increased with distance upslope during upslope flow, but generally decreased with distance upslope at the river canyon site during upslope flow. In a downslope flow, wind speed did not have a consistent trend with position on the isolated mountain, but generally increased with distance upslope at the river canyon site. The highest measured speeds occurred during the passage of frontal systems on the isolated mountain. Mountaintop winds were often twice as high as wind speeds measured on the surrounding plain. The highest speeds measured in the river canyon occurred during late morning hours and were from easterly down-canyon flows, presumably associated with surface pressure gradients induced by formation of a regional thermal trough to the west and high pressure to the east. Under periods of weak synoptic forcing, surface winds tended to be decoupled from large-scale flows, and under periods of strong synoptic forcing, variability in surface winds was sufficiently large due to terrain-induced mechanical effects (speed-up over ridges and decreased speeds on leeward sides of terrain obstacles) that a large-scale mean flow would not be representative of surface winds at most locations on or within the terrain feature. These findings suggest that traditional operational weather model (i.e., with numerical grid resolutions of around 4 km or larger) wind predictions are not likely to be good predictors of local near-surface winds on sub-grid scales in complex terrain. Measurement data can be found at http://www.firemodels.org/index.php/windninja-introduction/windninja-publications.

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