Intraseasonal Variability Research Articles

Propagation pathways of Indo-Pacific rainfall extremes are modulated by Pacific sea surface temperatures

Intraseasonal variation of rainfall extremes within boreal summer in the Indo-Pacific region is driven by the Boreal Summer Intraseasonal Oscillation (BSISO), a quasi-periodic north-eastward movement of convective precipitation from the Indian Ocean to the Western Pacific. Predicting the spatiotemporal location of the BSISO is essential for subseasonal prediction of rainfall extremes but still remains a major challenge due to insufficient understanding of its propagation pathway. Here, using unsupervised machine learning, we characterize how rainfall extremes travel within the region and reveal three distinct propagation modes: north-eastward, eastward-blocked, and quasi-stationary. We show that Pacific sea surface temperatures modulate BSISO propagation — with El Niño-like (La Niña-like) conditions favoring quasi-stationary (eastward-blocked) modes—by changing the background moist static energy via local overturning circulations. Finally, we demonstrate the potential for early warning of rainfall extremes in the region up to four weeks in advance.

An Analysis of Intra-Seasonal Variability and Predictability of Atmospheric Processes of Regional Scale in the Northern Hemisphere Mid-Latitudes

The issues related to the intra-seasonal variability and predictability of the atmospheric processes of a regional scale in the Northern Hemisphere are considered. To identify the latter, the circulation indices characterizing the large-scale modes of the atmospheric variability are used. An assessment of the regional intra-seasonal variability of the atmospheric processes in the summer and winter seasons of 1991–2020 is given. A study of the practical predictability of the regional atmospheric processes is carried out using the global semi-Lagrangian model developed at the INM RAS jointly with the Hydrometeorological Center of Russia, as well as the reanalysis of the European Center for Medium-Range Weather Forecasts on a weekly and monthly time scales. It is concluded that beyond of the first forecast week, the quality of deterministic (ensemble mean) forecasts drops sharply. In winter, the exception is the Pacific-North American oscillation region, where a useful signal is traced not only for the first prognostic week, but also for the second one. The use of the probabilistic forecasts makes it possible to increase the time interval of predictability compared to the deterministic approach from one week to a month. The biggest errors are noted in the forecasts of the circulation regimes in the west of the North Atlantic and in the west of the northern part of the Pacific, in the regions of the most significant intra-seasonal variability. The obtained results are supposed to be used in the operational practice of the intra-seasonal forecasting of the North Eurasian Climate Center (NEACC).

20–60-day intraseasonal variation of summer rainfall in Thailand and its associated large-scale atmospheric moisture circulation

20–60-day intraseasonal variation of summer rainfall in Thailand and its associated large-scale atmospheric moisture circulation

Comparative evaluation of penalized regression models with multiple linear regression for predicting rapeseed-mustard yield: Weather-indices based approach

Rapeseed-mustard (Brassica spp.) is one of the important edible oilseeds crops in India. The same level of weather condition impacts the growth and establishment of rapeseed-mustard plant differently in different stages of crop which lead to large intra-seasonal yield variations. Hence it is essential to give weightage to weekly weather conditions while fitting predictive model. In this present study, path-coefficient based weighted index was proposed along with existing unweighted and correlation based weighted index. The performance of penalized regression models viz. Ridge Regression, Least Absolute Shrinkage and Selection Operator (LASSO) and Elastic Net (ENET) were compared with Multiple Linear Regression (MLR) for predicting rapeseed-mustard yield using weather-indices. The results revealed that the path-coefficient based weighting of weather parameters to the yield were stable than correlation based weighted-indices. Path-coefficient based weighted indices of maximum temperature, minimum temperature and windspeed were important variables in projection of yield. The performance of MLR was poor during validation of model due to overfitting issue. The performance of penalized models was stable in both calibration and validation of the model. The LASSO and ENET models that accompanied with coefficient shrinkage and variable selection were found to be the best fitted models for predicting Rapeseed-Mustard yield.

The Observed Effects of Cold Pools on Convection Triggering and Organization During DYNAMO/AMIE

AbstractCold pools that form from existing convection can generate new clouds nearby, a process that has been suggested to contribute to cloud organization. However, some disagreement exists on the role of cold pools in cloud organization over tropical oceans, and much remains to be understood on how this role depends on the state of large‐scale disturbances such as the Madden‐Julian Oscillation (MJO). This study addresses this question by examining the intraseasonal variability in the properties of cold pools and their effects on convection triggering using observations. The unique set of surface meteorology data and ground‐based radars deployed during the DYNAMO/AMIE field campaign are used to identify cold pools and the associated spatiotemporal evolution of rainfall. The results suggest that cold pools enhance rainfall at their expected speed of 3–8 m s−1, which includes the Doppler‐shifting effect by the background wind. The cold pools also enhance rainfall mainly within a 20 km radius, especially in the direction of boundary‐layer vertical wind shear. However, gravity waves appear to contribute predominantly to the propagation of convection over a wider range of distances due to their faster propagation speeds. The interface of convection triggering and propagation at different speeds of cold pools and gravity waves seems to contribute to cloud organization. The effectiveness of cold pools and gravity waves on cloud organization also depends highly on the MJO due to the combined effects of changes in environmental humidity and boundary to lower‐tropospheric wind.

Interannual Variations in the Intraseasonal Variability of Spring Precipitation over Southern China and the Possible Mechanisms

Abstract This study first investigates the interannual variations in spring precipitation intraseasonal variability over southern China (SC). The results show that SC spring precipitation exhibits distinct intraseasonal variations with a period of 7–25 days. The first mode of 7–25-day precipitation intraseasonal variability (PIV) displays a monopole pattern over SC, and the PIV magnitude is largely determined by the upward motion intensity during intraseasonal precipitation events. Further analysis suggests that two atmospheric wave trains are observed during intraseasonal precipitation events, which propagate eastward from the North Atlantic along the northern and southern paths. In strong PIV years, the two wave trains can propagate to East Asia and show coordinated influences. The resultant low pressure to the west of SC causes strong upward motion and PIV over SC by bringing strong zonal vorticity and meridional temperature advection. In weak PIV years, the southern wave train can only propagate to the Bay of Bengal; therefore, the northern wave train plays a major role. The resultant low pressure is now over the upper to middle reaches of the Yangtze River, which causes relatively weak upward motion and PIV over SC by bringing weak meridional vorticity and temperature advection. Further analysis indicates that the sea surface temperature (SST) condition over the tropical Indian Ocean and the South China Sea is essential for southern wave train propagation. The warming SST over the regions can intensify westerlies to its north and consequently favors the propagation of the southern wave train to SC, eventually contributing to strong PIV over SC.

Influence of the Madden-Julian Oscillation on the diurnal cycles of convection and precipitation over the Congo Basin

The Congolese rainforest is a hotspot for convection where thunderstorms and rainfall exhibit a strong diurnal cycle. Previous studies have shown that various modes of variability such as the Madden-Julian Oscillation (MJO), the leading mode of intraseasonal variability in the tropics, can impact the diurnal cycles of precipitation and convection over tropical land areas. Thus, this study analyzes the influence of the MJO on diurnal variations of convection and precipitation over the Congo and explores possible mechanisms leading to the observed changes, using Gridded Satellite (GridSat-B1), Tropical Rainfall Measuring Mission (TRMM), and ERA5 reanalysis data. Results show that convection and precipitation are increased during the MJO enhanced convective phase (RMM phases 1 and 2) and decreased during the suppressed convective phase (RMM phases 5 and 6), where the differences are found to be largest during the morning hours when convection is weakest. Convection is generally deeper during the enhanced phase and shallower during the suppressed phase, accompanied by a slower decay of convective clouds and anvils during the enhanced phase. Furthermore, the influence of the MJO was found to be stronger on stratiform precipitation compared to convective precipitation. While the diurnal cycles of convective precipitation fractions are similar during both MJO phases, the fraction of stratiform precipitation is higher during the enhanced phase, mainly in the morning hours. Suggested atmospheric drivers contributing to the observed differences between the two MJO phases include enhanced upward air motion in the mid- and upper levels and strong divergence in the upper levels during the enhanced phase, and strong mid-level divergence and upper- to mid-level subsidence during the suppressed phase, mainly during the nighttime and morning hours. Furthermore, decreased mid-level wind speed, increased upper-level wind speed, and enhanced relative humidity may be contributing factors to the increased formation of stratiform precipitation during the enhanced phase. These results enhance our understanding of the MJO's impacts on precipitation and convection variability, ultimately improving predictions of MJO modulated rainfall over the Congo.

Convective systems and rainfall in East Africa

AbstractEast Africa is particularly vulnerable to weather extremes, with severe weather linked to thousands of deaths per year. Improved forecasts of convective events in this region are urgently needed, from both nowcasting and numerical weather prediction models. Improving these forecasts requires further knowledge of convection in this region. This study aims to improve understanding of convective events in East Africa, based on a six‐year climatology of convective life cycles and the associated precipitation. Convective systems are identified as contiguous areas of cold cloud in geostationary satellite measurements over East Africa. A tracking algorithm is used to trace the evolution of the properties of these systems through time and space. Matching the systems to surface precipitation obtained from satellite microwave observations provides insight into how the life cycles of these systems relate to precipitation at the surface. Over the region as a whole, 59% of the accumulated precipitation can be attributed to the tracked convective systems. The majority (81%) of heavy precipitation events (10 mmhr−1) are attributable to convective systems, while light rainfall events (1 mmhr−1) are not (1.8%). Most of the tracked convective systems have an area less than 400 km2 and last for less than an hour. However, the less frequent larger longer‐lived systems produce the majority of the regional accumulated precipitation. Composite life cycles of the tracked systems show rapid intensification and the heaviest precipitation initially, followed by a steady increase in area and weakening in intensity before the system decays. Finally, the Madden–Julian oscillation, which plays a key role in intraseasonal rainfall variability in the region, is also linked to the amount of rainfall due to convective systems through changes in the frequency and properties of these systems.

Intraseasonal variation of the association between heat exposure and mortality risk in Shandong province, China

Exposure to ambient high temperature has been associated with numerous health outcomes. It remains largely unclear whether the heat effect may vary in the course of the warm season. This study aimed to explore the intraseasonal variation of the association between heat exposure and mortality risk during the warm season in Shandong province between 2013 and 2018. Daily data on mortality and meteorological conditions were collected from each of the 1822 sub-districts in Shandong Province during the 2013–2018 warm seasons (June–September). Conditional logistic regression with a distributed lag non-linear model was used to fit the heat-mortality association over lag 0–10 days from early (June–July) to late (August–September). The extreme heat effect was defined as the cumulative odds ratio (OR) at the 97.5th percentile of the temperature range compared to the minimum mortality temperature (MMT). Stratified analysis was conducted by sex, age-group, educational level, and cause of mortality. A J-shaped association between ambient heat and mortality risk was consistently observed across the warm season, with the MMT located at 22.5 °C. The extreme heat effect (OR) decreased significantly from 3.52 (95%CI: 3.10, 4.00) in the early warm season to 2.85 (95%CI: 2.48, 3.28) in the late warm season (P = 0.028). Females, elderly aged over 75 years, individuals with junior high school education or lower, and cardiorespiratory patients were more vulnerable to heat exposure compared to other population subgroups, especially in the early warm season. In conclusion, this study observed a J-shaped association between ambient warm temperature and mortality risk, with the effect size of extreme heat decreasing substantially from the early to the late warm season. The findings highlight the importance of developing health promotion strategies to offset the adverse impact of early heat.

Variability of the Deep Western Boundary Current in the Northern Philippine Sea

Abstract The deep western boundary current (DWBC) was studied based on a full-depth mooring east of Luzon Island in the Northern Philippine Sea deep basin during the period from January 2018 to May 2020. On average, the DWBC in the Philippine Sea flows southward with a velocity of approximately 1.18 cm s−1 at a depth of 3050 m. Significant intraseasonal and seasonal variations of the DWBC are identified. The intraseasonal variations have multiple spectral peaks in the range of 30–200 days, with the most obvious peak at approximately 120 days. On the seasonal time scale, the DWBC intensifies in summer/autumn and weakens in winter/spring, corresponding well with the seasonal variation of the ocean bottom pressure (OBP) from the Gravity Recovery and Climate Experiment. Both intraseasonal and seasonal variations have no significant correlation with the temporal variations in the upper and middle layers but have a certain correlation with transport through the Yap–Mariana Junction (YMJ). A set of experiments based on an inverted-reduced-gravity model and the OBP data reveal that the temporal variations originating from the YMJ could propagate counterclockwise along the boundary of the deep basin to the western boundary of the deep Philippine Sea, dominating the temporal variations of DWBC.

Different vertical heat transport induced by submesoscale motions in the shelf and open sea of the northwestern South China Sea

Submesoscale currents are known to be associated with strong vertical velocities (O (10) m/day), regulating the redistributions of energy and matter balances. The northern South China Sea (SCS) is fulfilled with submesoscale motions, which might induce strong vertical heat transport (VHT). We set up a 1-km horizontal resolution Massachusetts Institute of Technology General Circulation Model (MITgcm) to study the seasonal variations in submesoscale vertical heat transport in shelf regions and open seas. Spectrum analysis shows that the spatial scale separating submesoscale and mesoscale motions are 14 and 30 km for the shelf and open regions, respectively. The submesoscale VHT in the shelf region is one order of magnitude larger than that in the open ocean. The former has the largest value in summer and winter, which might be induced by summer upwelling and winter downwelling, while the latter is strongest in winter and weakest in summer in open regions. The submesoscale VHT also appears to have intra-seasonal variations and might be attributed to the disturbances of tropical cyclones and life stages of submesoscale eddies. The submesoscale VHT is strongest in the pregeneration phase of the eddies, and the maximum VHT belt has an entrainment type at the developing and mature stages. The chlorophyll-a concentration also has the same temporal variation as the different life-stage of eddies. This study provides local VHT induced by submesoscale motions, which is expected to improve our understanding of submesoscale air–sea interactions and their biological effects.

Correction to: Intraseasonal and synoptic climate variability of surface solar radiation over South‐West Indian Ocean: Regional climate modelling

Correction to: Intraseasonal and synoptic climate variability of surface solar radiation over <scp>South‐West</scp> Indian Ocean: Regional climate modelling

Low-level jets drive the summer intra-seasonal variability of the Canary upwelling system

The role of low-level jets in the intra-seasonal variability of the Canary upwelling system during summer is assessed with a fully coupled, high resolution (3km) ocean-atmosphere numerical simulation. Here, low-level jets include the main continental coastal jet, the tip jets of Madeira and the tip-jets of the steep Canary Islands. The coastline shape, orography of northwest Africa and the proximity of Canary islands lead to complex interactions between the jets, that result in strong surface wind intra-seasonal variability on the multiweek time scale. That variability is forced by oscillations in the shape and position of the Azores subtropical anticyclone, through a strong oscillation in the atmospheric boundary layer height. At the coast, coastal-trapped oscillations with a propagation speed, planetary boundary height, offshore extension, and surface pressure compatible with a Kelvin wave occasionally propagate northward, against the synoptic scale surface pressure. While similar processes have already been observed in California, the mechanisms here described appear to result from interactions of continental coastal processes with a set of steep islands close to the coast. The sensitivity of these dynamics to climate change is a challenging question.

Variations in the 30–60‐Day Intra‐Seasonal Variability of Spring Precipitation Over the Mid‐Low Reaches of the Yangtze River and the Possible Mechanism

AbstractThe precipitation intra‐seasonal variability (ISV) has an important influence on extreme precipitation events, profoundly influencing agricultural activities over the mid‐low reaches of the Yangtze River (MLRYR). Spectrum analysis reveals the existence of 30–60‐day ISV in the MLRYR spring precipitation. The mechanism analysis indicates that, on the intra‐seasonal time scale, the MLRYR precipitation ISV is primarily driven by a wave train over the Eurasian continent. The wave train, with an anomalous anticyclone (cyclone) over the East European Plain and an anomalous cyclone (anticyclone) over Central Asia, could cause more (less) precipitation over the MLRYR. On the inter‐annual and inter‐decadal time scales, the precipitation ISV intensity is influenced by a meridional dipole pattern of the westerly jet stream (WJS) over the Eurasian continent. The positive WJS pattern facilitates the barotropic instability generation and 30–60‐day ISV growth over the East European Plain. Therefore, the ISV intensity of the pronounced wave train is enhanced and further intensifies the MLRYR spring precipitation ISV. In contrast, the negative WJS pattern is unfavorable for regional barotropic instability generation, and therefore the spring precipitation ISV intensity over the MLRYR would be weak. Further analysis shows that the underlying snow cover and soil temperature anomalies could have a contribution to forming the WJS dipole pattern through changing the meridional temperature gradient. The results of this study could deepen our understanding of the spring precipitation ISV over the MLRYR and the mechanisms.

Bottom-water hypoxia in the Paracas Bay (Peru, 13.8°S) associated with seasonal and synoptic time scale variability of winds and water stratification

Coastal hypoxia can occur naturally in inshore areas of the Eastern Boundary Upwelling Systems, influenced by the nutrient-rich and low-oxygen upwelling waters. This study aims to explore the influence of water stratification and winds on bottom-water hypoxia of the Paracas Bay, an area subjected to the most intense alongshore winds and active coastal upwelling in the Peruvian coast. Monitoring data of the Pisco-Paracas water properties (dissolved oxygen, temperature, salinity and estimated stratification), the Pisco River flow, and the intensities of surface winds of the outside upwelling area, and of the local area, were analysed for the period 2006 to 2015. Bottom waters deeper than 8 m in the bay were shown undergoing a hypoxic regime (oxygen <1.4 mL L−1) that becomes more frequent towards austral summer and less frequent towards winter. This seasonal difference was associated with changes in the oxygen content of incoming upwelling waters and changes in the intensity of both local and upwelling winds that drive the hydrodynamics of the bay. High frequency data analysis revealed that synoptic time-scale fluctuations of the upwelling-favourable and local winds modulate the intra-seasonal variability of hypoxia. Fluctuations of the former drive the inshore expansion of mixed and less hypoxic upwelling waters during June–September, whereas fluctuations of the latter during December–April drive the entrance and circulation of more hypoxic upwelling waters, and the development of stratification events that contribute to the persistence of bottom hypoxia.

Global Simulation of the Madden–Julian Oscillation With Stochastic Unified Convection Scheme

AbstractA new spectral convection scheme, the stochastic unified convection scheme (stochastic UNICON), is implemented in a general circulation model. The global climate simulation using stochastic UNICON is evaluated and compared with UNICON, focusing on the simulation of the Madden–Julian oscillation (MJO). Stochastic UNICON extends the original UNICON by randomly sampling convective updrafts from the joint probability density function constructed at the near‐surface, generating a spectrum of convective updrafts in a physically based manner. The performances of UNICON and stochastic UNICON on simulating observed mean climates are comparable, while stochastic UNICON slightly reduces the mean bias of climate variables. For the simulation of intraseasonal variabilities, stochastic UNICON outperforms UNICON in many aspects. Stochastic UNICON improves the simulation of the intensity and propagation patterns of boreal winter MJO, which are too weakly simulated in UNICON. The coherency between MJO‐related convection and large‐scale circulation is also enhanced, which many climate models underestimate. The improvement of MJO simulation by stochastic UNICON is related to a better representation of the relationship between moisture and convection in the model. The increased frequency of shallow convection in stochastic UNICON leads to stronger moisture convergence that precedes convection activity peak and results in the more robust development of organized convection and more frequent intense precipitation. A precipitation budget analysis reveals that the moisture tendencies due to horizontal advection and convective process are consistently enhanced during MJO developing periods by stochastic UNICON.

Fusing time-varying mosquito data and continuous mosquito population dynamics models

Climate change is arguably one of the most pressing issues affecting the world today and requires the fusion of disparate data streams to accurately model its impacts. Mosquito populations respond to temperature and precipitation in a nonlinear way, making predicting climate impacts on mosquito-borne diseases an ongoing challenge. Data-driven approaches for accurately modeling mosquito populations are needed for predicting mosquito-borne disease risk under climate change scenarios. Many current models for disease transmission are continuous and autonomous, while mosquito data is discrete and varies both within and between seasons. This study uses an optimization framework to fit a non-autonomous logistic model with periodic net growth rate and carrying capacity parameters for 15 years of daily mosquito time-series data from the Greater Toronto Area of Canada. The resulting parameters accurately capture the inter-annual and intra-seasonal variability of mosquito populations within a single geographic region, and a variance-based sensitivity analysis highlights the influence each parameter has on the peak magnitude and timing of the mosquito season. This method can easily extend to other geographic regions and be integrated into a larger disease transmission model. This method addresses the ongoing challenges of data and model fusion by serving as a link between discrete time-series data and continuous differential equations for mosquito-borne epidemiology models.

Intraseasonal variations in winter surface air temperature over China and its prediction skill in ECMWF System5

AbstractBased on the daily average temperature data of 2374 stations in China from 1993 to 2022 and the monthly average temperature data of European Centre for Medium‐Range Weather Forecasts (ECMWF) System5 in winter, this article analyses the intraseasonal variations of winter surface air temperature (SAT) over China by using seasonal empirical orthogonal function decomposition (S‐EOF) and compare the prediction skill differences of the first three dominant modes in ECMWF System5. The first mode (S‐EOF1) is characterized by out‐of‐phase changes in SAT anomalies (SATA) between December and January. Both the Siberian high (SH) and the central Pacific El Niño‐Southern Oscillation (CP ENSO) can impact S‐EOF1. The second mode (S‐EOF2) is characterized by consistency in warm anomalies over the Northeast and Qinghai‐Tibet Plateau's variation, while the other areas are characterized by the out‐of‐phase change in SATA. S‐EOF2 is closely related to Arctic oscillation (AO). The third mode is characterized by alternating changes over 3 months in winter, which is related to the Pacific meridional mode (PMM) and the North Atlantic SST tripole (NAT). Comparing the ECMWF System5 prediction skill for the first three leading modes for the intraseasonal variations in winter SAT, the prediction skill is not high. The model did not predict the extent of warm anomalies and the intraseasonal fluctuation in S‐EOF1, which may be due to the poor prediction skills for the range and intensity of the CP ENSO and the SH. The second mode has the highest prediction skill among the three modes. For the prediction skill of AO is good. The model can capture the intraseasonal reverse SATA between December and January but did not capture the reverse SATAs between January and February. Because the model does not predict obvious PMM and NAT well.

Factors influencing the meridional width of the equatorial deep jets

Abstract. Equatorial deep jets (EDJs) are vertically alternating, stacked zonal currents that flow along the Equator in all three ocean basins at intermediate depth. Their structure can be described quite well by the sum of high-baroclinic-mode equatorial Kelvin and Rossby waves. However, the EDJ meridional width is larger by a factor of 1.5 than inviscid theory predicts for such waves. Here, we use a set of idealised model configurations representing the Atlantic Ocean to investigate the contributions of different processes to the enhanced EDJ width. Corroborated by the analysis of shipboard velocity sections, we show that widening of the EDJs by momentum loss due to irreversible mixing or other processes contributes more to their enhanced time mean width than averaging over meandering of the jets. Most of the widening due to meandering can be attributed to the strength of intraseasonal variability in the jets' depth range, suggesting that the jets are meridionally advected by intraseasonal waves. A slightly weaker connection to intraseasonal variability is found for the EDJ widening by momentum loss. These results enhance our understanding of the dynamics of the EDJs and, more generally, of equatorial waves in the deep ocean.

Long-Term Measurements of the Atmospheric Boundary Layer Height in Central Amazonia Using Remote Sensing Instruments

The height (zi) of the Atmospheric Boundary Layer (ABL) is a fundamental parameter for several areas of knowledge, especially for weather and climate forecasting, pollutant dispersion and air quality. In this work, we used data from a remote sensing instrument (ceilometer), located at the experimental site of the Amazon Tall Tower Observatory (ATTO) in the Central Amazonia rainforest, in order to obtain the height of the ABL. Data used were obtained from 2014 to 2020, with the exception of the year 2017. The results showed that the zi average varies from year to year (interannual variability) and the average of the maximum zi values (zi_max) was approximately 1400 ± 277 m, occurring at 15:00 local time. In addition, it was found that these maximum heights are higher in the dry season and during El Niño years (about 1741 ± 242 m) and they are lower during the wet period and in La Niña years (1263 ± 229 m). Taking into account all the years investigated, the month with the highest zi_max value is September (1710 ± 253 m), and the month with the lowest value is May (1108 ± 152 m). Finally, it was observed that the growth rate of the ABL during the early hours after sunrise varies from month to month (intraseasonal variability), reaching its maximum values in September and October (about 210 ± 53 m h−1 and 217 ± 59 m h−1, respectively) and minimum values in April and July (approximately 159 ± 48 m h−1 and 159 ± 50 m h−1, respectively). It is concluded that the values of zi in Central Amazonia are influenced by several seasonal factors (temperature, cloud cover, turbulent heat flux, etc.) which gives it a wide variability in terms of heights and growth rates. Additionally, a linear regression was proposed in order to model the maximum zi value as a function of its growth rate from 08:00 LT (Local Time) up to 10:00 LT. The results showed a good correlation compared with the experimental values.