Formation Of Convective Clouds Research Articles

The Decline in Summer Fallow in the Northern Great Plains Cooled Near‐Surface Climate but had Minimal Impacts on Precipitation

AbstractLand management can moderate or intensify the impacts of a warming atmosphere. Since the early 1980s, nearly 116,000 km2 of cropland that was once held in fallow during the summer is now planted in the northern North American Great Plains. To simulate the impacts of this substantial land cover change on regional climate processes, convection‐permitting model experiments using the Weather Research and Forecasting model were performed to simulate modern and historical amounts of summer fallow. The control simulation was extensively validated using multiple observational data products as well as eddy covariance tower observations. Results of these simulations show that the transition from summer fallow to modern land cover led to ∼1.5°C cooler temperatures and decreased vapor pressure deficit by ∼0.15 kPa during the growing season across the study region, which is consistent with observed cooling trends. The cooler and wetter land surface with vegetation led to a shallower planetary boundary layer and lower lifted condensation level, creating conditions more conducive to convective cloud formation and precipitation. Our model simulations however show little widespread evidence of land surface changes effects on precipitation. The observed precipitation increase in this region is more likely related to increased moisture transport by way of the Great Plains Low Level Jet as revealed by the ERA5 reanalysis. Our results demonstrate that land cover change is consistent with observed regional cooling in the northern North American Great Plains but changes in precipitation cannot be explained by land management alone.

Analysis of the Gálvez–Davison Index for the Forecasting Formation and Evolution of Convective Clouds in the Tropics: Western Cuba

The Gálvez–Davison Index (GDI) is an atmospheric stability index recently developed to improve the prediction of thunderstorms and shallower types of moist convection in the tropics. Because of its novelty, its use for tropical regions remains largely unexplored. Cuba is a region that suffers extreme weather events, such as tropical storms and hurricanes, some of them worsened by climate change. This research analyzes the effectiveness of the GDI in detecting the potential for convective cloud development, using forecast data from the Weather Research and Forecasting (WRF) model for Western Cuba. To accomplish this, here, we evaluated the performance of the GDI in ten study cases from the dry and wet seasons. As part of our study, we researched how GDI correlates with brightness temperatures (BTs) measured using GOES-16. In addition, the GDI results with the WRF model are compared with results using the Global Forecast System (GFS). Our results show a high correlation between the GDI and BT, concluding that the GDI is a robust tool for forecasting both synoptic and mesoscale convective phenomena over the region studied. In addition, the GDI is able to adequately forecast stability conditions. Finally, the GDI values computed from the WRF model perform much better than those from the GFS, probably because of the greater horizontal resolution in the WRF model.

Analisis Citra Satelit Himawari-8 Terkait Kejadian Puting Beliung Di Kabupaten Bogor (Studi Kasus 02 November 2021)


 Puting Beliung is a strong-rotating wind originating from Cumulonimbus clouds with a speed of more than 34.8 knots or 64.4 km/hour that occurs short time. Puting Beliung occurred on November 2, 2021, at 2 pm in the Kampung Dukuh area, Pasirmukti Village, Citeureup District, Bogor Regency (106° 53' 47.99"E and 6° 31' 5.2"S). The research data are surface air observation data from Bogor Climatology Station, Himawari-8 satellite data, and Copernicus CDS reanalysis data. This study aims to analyze the dynamics of the atmosphere during the occurrence of wind phenomena in a tornado in the Kampung Dukuh area, Pasirmukti Village, Citeureup District, Bogor Regency. This study method is a descriptive analysis of Himawari-8 satellite imagery using SATAID software. The results of this study indicate that tornadoes occur due to shear lines and strong-atmospheric lability in the Bogor and surrounding areas, thus triggering the formation of local convective clouds characterized by cloud peak temperatures reaching -69oC.

Analysis Of Spearman Rank Correlation & Linear Regression Of Atmospheric Stability And Cloud Tops Temperature Of Himawari-8 IR Satellite Images (Case Study Of Hail On May 22, 2022)

This research is based on cases of hail that caused flooding in Binjai City on May 22, 2022. This study aims to see the correlation and regression of the Atmospheric Stability index value on cloud top temperature data from the Himawari-8 satellite imagery. So that the ERA-5 reanalysis data can be used to obtain cloud top temperatures in predicting hail events. The indices used in this study are CAPE, KI and TTI. The data used is located in Binjai City with correlation testing from 00UTC – 24UTC on May 22, 2022. Supported data is used in the form of sea surface temperature and wind conditions and looks at the causes of hail at the research location. The method used is Spearman's rank correlation with the results obtained in the form of a correlation value at the K index of -0.651, a correlation of the TT index of -0.563, and a correlation of the CAPE index of -0.348. The simple linear regression results also show a negative gradient line. This shows that the increase in the value of the stability index is in line with the decrease in cloud top temperature. So that the stability index data can be used as a benchmark in estimating cloud top temperatures in the case of convective cloud formation which causes hail.

Monthly variation of local land–atmosphere coupling over the Tibetan Plateau in the rainy season and its relationship with the South Asian summer monsoon

AbstractThe local land–atmosphere coupling (LoCo) over the Tibetan Plateau (TP) in the rainy season and the possible influence of the South Asian monsoon (SAM) on LoCo characteristics are investigated by applying two LoCo diagnostic metrics to 12‐year observational data at six stations over the TP and the ERA5 from June to September (JJAS) from 1980 to 2018. The validation of ERA5 in estimating monthly mean diurnal evolutions of T2m, q2m, and surface fluxes (Hsfc and LEsfc) at the six stations reveals that these variables in the ERA5 are relatively reliable for the LoCo analysis. The mixing diagram analysis based on the observational data and ERA5 suggests that the monthly variations in the planetary boundary layer (PBL) energy budget are strong and vary from station to station, revealing the complexity of the influence of the SAM on the PBL energy budget over TP. The relationship between Hsfc and PBL height (PBLH) and lifted condensation level (LCL) deficit at the six stations based on the ERA5 reveal a strong influence of soil moisture on PBL growth and convective cloud formation, although the topography may also exert its influence. Analyses of the correlations of the PBL energy budget, PBLH, and LCL deficit over the TP with the SAM in JJAS indicate that the LoCo characteristics over the TP show large spatial variability between the southeastern and central‐western parts of the TP. Such spatial variability can be attributed to the spatial differences in monthly mean soil moisture and rainfall closely related to the evolution of SAM's influence and the complex topography of the TP. The topography of the TP can also affect the LoCo characteristics in JJAS, but the mechanisms in the areas dominated by SAM and by the westerly winds are different.

Dust Aerosol Impacts on the Time of Cloud Formation in the Badain Jaran Desert Area

AbstractDust, as absorbing aerosols, can change the stability of the atmosphere through radiative effects, thereby affecting the formation and characteristics of clouds. In order to explore the influence of dust aerosols on cloud formation, this study takes the Badain Jaran Desert area as the research area where cloud formation is less disturbed by human activities compared to other densely populated areas such as the North China Plain, and uses the high temporal resolution Himawari‐8 satellite data to identify 469 cases with cloud formation after 03:00 UTC (11:00 Beijing time). Through the analysis of individual cases, we find that the cloud formation time is dominated by the low tropospheric stability (LTS) when the total precipitable water (TPW) is less than about 18.5 kg/m2, and greatly affected by the TPW when it is larger than 18.5 kg/m2. Dust aerosols near the ground absorb shortwave solar radiation, making the atmospheric structure unstable (decreased LTS) and conducive to cloud formation. Statistically, for every 0.1 increase in aerosol optical depth, the cloud formation time is advanced about 138 min compared to low aerosol cases. Further analysis shows that dust aerosols actually inhibit the formation of convective clouds through microphysical processes when the TPW is small, while promote the formation of convective clouds through radiative processes when the TPW is large. This study reveals the effects of dust aerosols on the time of cloud formation along with the underlying mechanisms, which provides observational support for improving cloud parameterization in numerical models.

Turbulence analysis on the flight of Etihad airways in Bangka Island using the WRF case study May 4, 2016

<p>Accurate weather forecasts should support the increase in safety of aviation operations in Indonesia. This weather forecast is needed, especially in detecting turbulence, considering that geographically Indonesia has effective solar radiation resulting in convective cloud formation. Convective clouds can trigger turbulence then produce disruption and even accidents on flights. This research uses a case study on the Etihad Airways flight on Bangka Island on May 4, 2016. At the time of the incident, there was turbulence at 39,000 feet altitude, and the aircraft did not enter the cloudy area. The Weather Research and Forecasting (WRF) model is used to simulate the turbulence in this study, which is downscaled up to 3 km with a microphysics parameterization of WRF Single Moment 6 Class (WSM6). The results were then verified using correlation and linear regression for temperature, wind direction, wind speed, and pattern resemblance between cloud fraction and the convective nuclei distribution. The turbulence is analyzed from the south-north and west-east vertical airflow. The turbulence spotted at 06.40 UTC when there is a quite strong updraft which can cause turbulence. The turbulence parameters used, such as the eddy dissipation rate (EDR) parameter, which has a value of 0.05 , Richardson number with a value of less than 0.25, and turbulence index (TI 1) with a maximum value of 4 x 10<sup>-7</sup> s<sup>-2</sup> found that turbulence was in a strong category. The turbulence that occurs in this study is identified as near cloud turbulence (NCT) event due to cloud formation observed in the west of the turbulence and intense updraft activity at the location of turbulence.</p>

Impacts of regional uplift of the Tibetan Plateau on local summer precipitation and downstream moisture budget: A simulation study

AbstractUsing the Weather Research and Forecasting (WRF) model, a series of sensitivity experiments were conducted to study the individual and overall effects of the various topographic uplifts of the Tibetan Plateau (TP) on regional climate variability. The presence of the southern slope of the TP facilitates the maintenance and development of the South Asia High (SAH), which produces a positive cyclic response between local precipitation and SAH, so that the northern branch of the South Asian summer monsoon (SASM) maintains the water vapor supply. At the same time, the southern slope of the TP has a positive effect on the mid‐latitude tropospheric anomalous cyclone and anticyclone systems which promotes the downstream advancement of the East Asian summer monsoon (EASM) and is favourable for the transfer of water vapor and convective clouds downstream. The role of the TP platform is mainly due to the lifting of moisture generated by its local heating, which favours the formation of local convective clouds and precipitation while causing nonadiabatic warming of the troposphere. Water vapor transported from the TP could affect precipitation in central‐eastern China (CEC). However, the supply of water vapor in Southern East China (SEC) mainly comes from the southeast coast of China. The Tibetan Plateau sensitive areas (TPSA) have impacts on the water vapor transport path. Removing the TPSA favours an increase in precipitation and convective clouds in SEC. The removal of topographic disturbances favours the convergence and dispersion of water vapor at mid‐latitudes. The mid‐latitude dynamical anomaly may form a standoff with the low‐latitude dynamical system. This leads to inefficient precipitation and convective generation processes, a weakened monsoon advance over land, and a southward shift in the rainfall belt.

Identification of the Puting Beliung Event by Utilizing the Interpretations of Radar Products and Himawari-8 Weather Satellite (Case Study: Puting Beliung Incident, November 22, 2018 in Jakarta)

<em>Indonesia was shocked again by a Puting beliung or tornado-like incident on November 22, 2018, in the Jakarta area. This incident caused many losses. In this regard, a study was conducted to observe the reflectivity products to identifiy the hook echo or bow echo patterns, and the velocity products for mesocyclone patterns as the characteristic of the Puting Beliung used radar product. The study required the Cengkareng C-Band raw data radar that was processed to produce CMAX, VCUT, and CAPPI (V) at 0.5 km, 1.0 km, and 1.5 km elevations overlay by HWIND. The CMAX and VCUT radar products are used to identify the cloud structure that caused Puting Beliung, by observed the highest reflectivity of the Puting Beliung-producing clouds. Then the CAPPI product overlay by HWIND is used to identify the movement of the wind which is suspected to be the beginning of the formation of a Puting Beliung at that location which is characterized by the presence of a mesocyclone pattern in the form of wind components and radial velocity. It was suspected that there was a wind rotating in the Central Jakarta area which indicated a Puting Beliung in the area. The analysis of this radar interpretation was then validated using satellite imagery to detect the cumulonimbus clouds forming the Puting Beliung. From this research, it is known that the Puting Beliung occurred around 08.12 UTC. The growth of cyclone-producing clouds occurred rapidly with a reflectivity value between 35 - 45 dBZ and wind speed up to 35 knots. Analysis of satellite imagery showed a significant decrease in cloud peak temperature so that the formation of convective clouds in the form of Cumulonimbus clouds indicates the phenomenon of the Puting Beliung. However, in this case study the Puting Beliung phenomenon is indicated as seen from the mesocyclone pattern of the rotating radial velocity component, and not from the hook echo or bow echo pattern.</em>

CFD simulation of updrafts initiated by a vertically directed jet fed by the heat of water vapor condensation

This paper presents the results of the development of a mathematical model and numerical simulation of the ascent in the atmosphere of a vertically directed jet fed by the heat of condensation of water vapor on a hygroscopic aerosol introduced into the jet at the start. The possibility of creating artificial convective clouds depending on jet parameters, condensation heat value and vertical profiles of wind speed, air temperature and humidity has been evaluated. Numerical experiments showed that the motion of a high-speed and high-temperature jet in the atmosphere has a complex turbulent nature. As the jet ascends, it expands, losing superheat and velocity. The temperature of the jet decreases faster than the velocity, so the jet rises slightly above the level at which its superheat disappears. The jet's ascent height increases as the humidity of the air and the vertical temperature gradient increase. Wind causes the jet to deform, bend, and decrease the height of ascent. Feed the jet with condensation heat results in a significant increase in jet lift height. This is particularly effective in the case of introducing into the jet two-layer NaCl/TiO2 nanoaerosol, which is capable of absorbing water vapor in an amount significantly greater than its mass. The simulation results are encouraging in the possibility of creating artificial updrafts that can lead to the formation of convective clouds and precipitation on days with favorable atmospheric conditions, when wind speed in the sub-cloud layer is < 6 m/s, air humidity is > 65%, and the temperature lapse rate is > 7.5 °C/km.

Review: land, cloud, and climate change (in focus: Borneo)

This article discusses the salient findings of the Intergovernmental Panel on Climate Change Special Report on Climate Change and Land (2019). Local impacts of global warming in Borneo are discussed in terms of changes in temperature and precipitation. A drier and warmer climate is expected with the continued deforestation of Borneo. Changes in land surface characteristics of Borneo also affect the properties of cloud that forms over it. Deforested areas are generally associated with diffused clouds, small cloud particles, and thin and high clouds. Low vegetative areas are associated with a low evapotranspiration rate and low amount of latent heat release, which discourages the formation of convective clouds. The weak updraft associated with a non-convective cloud cannot support the formation of large cloud droplets. Moreover, the deforestation of primary forests of Borneo and replacing them with palm trees may cause larger cloud properties’ variability over the area.

FORECASTING RAINFALL IN PANGKALPINANG CITY USING SEASONAL AUTOREGRESSIVE INTEGRATED MOVING AVERAGE WITH EXOGENOUS (SARIMAX)

Changes in extreme rainfall can cause disasters or losses for the wider community, so information about future rainfall is also needed. Rainfall is included in the category of time series data. One of the time series methods that can be used is Autoregressive Integrated Moving Average (ARIMA) or Seasonal ARIMA (SARIMA). However, this model only involves one variable without involving its dependence on other variables. One of the factors that can affect rainfall is wind speed which can affect the formation of convective clouds. In this study, the ARIMA model was expanded by adding eXogen variables and seasonal elements, namely the SARIMAX model (Seasonal ARIMA with eXogenous input). Based on the analysis that has been carried out, the prediction of rainfall in Pangkalpinang City, Bangka Belitung Islands Province can be modeled with the SARIMAX model (0,1,3)(0,1,1){12} for monthly rainfall and SARIMAX (0,1,2 )(0,1,3){12} for maximum daily rainfall. When compared with the actual data and previous studies using ARIMAX, the SARIMAX model is still better in the forecasting process when compared to the ARIMAX model. If viewed based on the AIC value of the SARIMA model, the SARIMAX model is also more suitable to be used to predict rainfall in Pangkalpinang City.

A new convective parameterization applied to Jupiter: Implications for water abundance near the 24°N region

Jupiter’s atmosphere features a variety of clouds that are formed from the interplay of chemistry and atmospheric dynamics, from the deep red color of the Great Red Spot to the high altitude white ammonia clouds present in the zones (bright bands in Jupiter’s atmosphere). Beneath these upper level clouds, water condensation occurs, and sporadically leads to the formation of towering convective storms, driven by the release of large amounts of latent heat. These storms result in a widespread disruption of the cloud and dynamical structure of the atmosphere at the latitude where they form, making the study of these events paramount in understanding the dynamics at depth, and the role of water in the jovian atmosphere. In this work, we use the Explicit Planetary hybrid-Isentropic Coordinate (EPIC) General Circulation Model (GCM) to study the jovian atmosphere, with a focus on moist convective storm formation from water condensation. We present the addition of a sub-grid scale moist convective module to model convective water cloud formation. We focus on the 24°N latitude, the location of a high speed jetstream, where convective upwellings have been observed every 4–5 years. We find that the potential of convection, and vertical mass and energy flux of the atmosphere is strongly correlated with the amount of water, and we determine an upper limit of the amount of water in the region surrounding the jet as twice the solar [O/H] ratio.

Deep Eye Clouds in Tropical Cyclone Trami (2018) during T-PARCII Dropsonde Observations

Abstract The sporadic formation of short-lived convective clouds in the eye of Tropical Cyclone (TC) Trami (2018) is investigated using dropsonde data and simulation results from a coupled atmosphere–ocean model. According to the satellite data, top height of the convective clouds exceeds 9 km above mean sea level, considerably taller than that of typical hub clouds (2–3 km). These clouds are located 10–30 km away from the TC center. Hence, these convective clouds are called deep eye clouds (DECs) in this study. The dropsonde data reveal an increase in relative humidity in the eye region during the formation of DECs. Short-lived convective clouds are simulated up to the middle troposphere in the eye region in the coupled model. Investigation of thermodynamic conditions shows a weakened low-level warm core and associated favorable conditions for convection in the eye region during the formation of DECs. DECs are formed after the weakening and outward displacement of convective heating within the eyewall. To elucidate the influence of the changes in convective heating within the eyewall on the formation of DECs, we calculate secondary circulation and associated adiabatic warming induced by convective heating within the eyewall using the Sawyer–Eliassen equation. In the eye region, weakening of subsidence and associated vertical potential temperature advection is observed as DECs are formed. This suggests that the weakening and outward displacement of convective heating within the eyewall create favorable conditions for the sporadic formation of DECs.

Atmospheric thermodynamics and dynamics during convective, stratiform and nonprecipitating clouds over the metropolitan area of Rio de Janeiro – Brazil

Physical mechanisms involved in the development and forecast of clouds and precipitation are both quite complex and dependent on the local atmospheric environment, especially when severe weather conditions are imminent. Research aimed at understanding the environmental mechanisms favorable to the different atmospheric scenarios can help operational weather forecasters to issue warnings. This paper provides qualitative and quantitative contributions from radiosondes, radar, and numerical simulations to evaluate the formation of convective, stratiform, and nonprecipitating clouds over the metropolitan area of Rio de Janeiro, Brazil. The convective available potential energy (CAPE) and lifted index (LI), showed higher values on convective days (CAPE = 2600 J.Kg–1 and LI = –4 ºC), followed by nonprecipitating (CAPE = 1500 J.Kg–1 and LI = –2 ºC) and stratiform cloud days (CAPE = 1400 J.Kg–1 and LI = –1.5 ºC). High wind convergence was observed at low- (1000–850 hPa) and mid- (850–700 hPa) levels on convective days (–16.5 s–1 and –9.6 s–1, respectively). In contrast, wind divergence at the same levels was observed on stratiform (6.4 s–1 and 6.9 s–1) and nonprecipitating (9.7 s–1 and 7.3 s–1) days. Higher wind divergence (8.3 s–1) was observed on convective days at upper levels (300–200 hPa) compared with stratiform (3.2 s–1) and nonprecipitating (2.8 s–1) days. Results show a coupling of wind convergence, moisture and energy in the lower troposphere and divergence at upper levels on convective days. Despite moisture availability on stratiform days and thermodynamic energy on nonprecipitating days, the respective coupling between these conditions and dynamic triggers was not observed.

Rapid growth of anthropogenic organic nanoparticles greatly alters cloud life cycle in the Amazon rainforest.

Aerosol-cloud interactions remain uncertain in assessing climate change. While anthropogenic activities produce copious aerosol nanoparticles smaller than 10 nanometers, they are too small to act as efficient cloud condensation nuclei (CCN). The mechanisms responsible for particle growth to CCN-relevant sizes are poorly understood. Here, we present aircraft observations of rapid growth of anthropogenic nanoparticles downwind of an isolated metropolis in the Amazon rainforest. Model analysis reveals that the sustained particle growth to CCN sizes is predominantly caused by particle-phase diffusion-limited partitioning of semivolatile oxidation products of biogenic hydrocarbons. Cloud-resolving numerical simulations show that the enhanced CCN concentrations in the urban plume substantially alter the formation of shallow convective clouds, suppress precipitation, and enhance the transition to deep convective clouds. The proposed nanoparticle growth mechanism, expressly enabled by the abundantly formed semivolatile organics, suggests an appreciable impact of anthropogenic aerosols on cloud life cycle in previously unpolluted forests of the world.

A decadal climatology of cloud vertical structure over the Indo-Gangetic Plain using radiosonde and radar observations

The cloud vertical structure (CVS) over any place significantly impacts the boundary layer dynamics and horizontal/vertical temperature gradient at local scale, whereas on the synoptic scale it plays a crucial role in determining the atmospheric circulation and hydrological cycle. There is a notable lack of long-term comprehensive studies on CVS over Indian subcontinent. Here, we have done a comprehensive study of CVS over the Indo-Gangetic plain (IGP), in which we have studied the statistics of CVS over various urban agglomerations (UAs) lying within the IGP (using radiosonde data) coupled with CVS of the entire IGP (EIGP) which majorly includes rural and suburban areas (using CloudSat profiling radar data) from 2006 to 2017. Seasonal analysis shows that CVS is much different in monsoon season as compared to other seasons over both EIGP and UAs. The frequency of single layer clouds is ~91%, 87%, 76% and 91% over EIGP and ~ 81%, 80%, 58% and 82% over UAs in winter, pre-monsoon, monsoon and post-monsoon seasons, respectively. In the monsoon season, both data show significant increase in multi-layer clouds frequency, however, the frequency of multi-layer clouds is significantly higher over UAs (>40%) compared to that over EIGP (<26%). The average depth of single-layer clouds over EIGP (2.3–5 km) is higher than that over UAs (1.8–2.7 km). The average cloud top height of single layer clouds is slightly lower over UAs (6.4–7.8 km) as compared to EIGP (7.3–11.2 km), except in pre-monsoon. We infer that though the aerosol induced warming inhibits the convective cloud formation over UAs; aerosols tend to invigorate the convective clouds whenever sufficient moisture is present for cloud formation. The analysis of present study would be helpful in many applications related to radiation budget and climate studies.

Projected changes in the mean and intra-seasonal variability of the Indian summer monsoon in the RegCM CORDEX-CORE simulations under higher warming conditions

The present study employed the latest high-resolution regional climate model (RegCM4), driven by MPI-ESM-MR boundary conditions from the CORDEX-CORE South Asia framework to investigate the possible projected changes in the mean and intra-seasonal variability of the Indian summer monsoon (ISM) precipitation and their associated dynamics during near future (NF; 2041–2060) and far future (FF; 2080–2099) with respect to the historical period (1995–2014) under RCP8.5 scenario. Extensive evaluation analysis indicates that the RegCM4 is fairly able to simulate the spatial–temporal distribution of the observed mean and extreme precipitation, low-level jet, and intra-seasonal variability i.e. active and break composite patterns of the precipitation anomalies over India during the historical period. A substantial decline in the projected precipitation during ISM is estimated over central and northwest India in NF (about 10–30%) as well as in FF (upto 50%), which may be attributed to the weakening and northward shift of low-level winds. The occurrences as well as the intensity of the extreme precipitation events are expected to increase over India in the future. The precipitation during the projected active spells will escalate over the monsoon core region. This is supported by the decrease in sea level pressure over land, which favors the winds to transport more moisture from the adjoining seas for the formation of convective clouds, which is partly indicated through the decline in net surface longwave radiation. On the other hand, the precipitation intensity during the projected break spells is expected to further decrease in the future.

Assessing uncertainties from physical parameters and modelling choices in an atmospheric large eddy simulation model.

In this study, we investigate uncertainties in a large eddy simulation of the atmosphere, employing modern uncertainty quantification methods that have hardly been used yet in this context. When analysing the uncertainty of model results, one can distinguish between uncertainty related to physical parameters whose values are not exactly known, and uncertainty related to modelling choices such as the selection of numerical discretization methods, of the spatial domain size and resolution, and the use of different model formulations. While the former kind is commonly studied e.g. with forward uncertainty propagation, we explore the use of such techniques to also assess the latter kind. From a climate modelling perspective, uncertainties in the convective response and cloud formation are of particular interest, since these affect the cloud-climate feedback, one of the dominant sources of uncertainty in current climate models. Therefore we analyse the DALES model in the RICO case, a well-studied convection benchmark. We use the VECMA toolkit for uncertainty propagation, assessing uncertainties stemming from physical parameters as well as from modelling choices. We find substantial uncertainties due to small random initial state perturbations, and that the choice of advection scheme is the most influential of the modelling choices we assessed.This article is part of the theme issue ‘Reliability and reproducibility in computational science: implementing verification, validation and uncertainty quantification in silico’.

Description of mesoscale pattern formation in shallow convective cloud fields by using time-dependent Ginzburg-Landau and Swift-Hohenberg stochastic equations.

The time-dependent Ginzburg-Landau (or Allen-Cahn) equation and the Swift-Hohenberg equation, both added with a stochastic term, are proposed to describe cloud pattern formation and cloud regime phase transitions of shallow convective clouds organized in mesoscale systems. The starting point is the Hottovy-Stechmann linear spatiotemporal stochastic model for tropical precipitation, used to describe the dynamics of water vapor and tropical convection. By taking into account that shallow stratiform clouds are close to a self-organized criticality and that water vapor content is the order parameter, it is observed that sources must have nonlinear terms in the equation to include the dynamical feedback due to precipitation and evaporation. The nonlinear terms are derived by using the known mean field of the Ising model, as the Hottovy-Stechmann linear model presents the same probability distribution. The inclusion of this nonlinearity leads to a kind of time-dependent Ginzburg-Landau stochastic equation, originally used to describe superconductivity phases. By performing numerical simulations, pattern formation is observed. These patterns are better compared with real satellite observations than the pure linear model. This is done by comparing the spatial Fourier transform of real and numerical cloud fields. However, for highly ordered cellular convective phases, considered as a form of Rayleigh-Bénard convection in moist atmospheric air, the Ginzburg-Landau model does not allow us to reproduce such patterns. Therefore, a change in the form of the small-scale flux convergence term in the equation for moist atmospheric air is proposed. This allows us to derive a Swift-Hohenberg equation. In the case of closed cellular and roll convection, the resulting patterns are much more organized than the ones obtained from the Ginzburg-Landau equation and better reproduce satellite observations as, for example, horizontal convective fields.