Community Earth System Model Simulations Research Articles

The Role of Sea Ice Insulation Effects on the Probability of AMOC Transitions

Abstract Recent simulations performed with the Community Earth System Model (CESM) have suggested a crucial role of sea ice processes in Atlantic meridional overturning circulation (AMOC) hysteresis behavior under varying surface freshwater forcing. Here, we further investigate this issue using additional CESM simulations and a novel conceptual ocean–sea ice box model. The CESM simulations suggest that the presence of sea ice gives rise to the existence of statistical equilibria with a weak AMOC strength. This is confirmed in the conceptual model, which captures similar AMOC hysteresis behavior as in the CESM simulation and where steady states are computed versus freshwater forcing parameters. In the conceptual model, transition probabilities between the different equilibrium states are determined using rare event techniques. The transition probabilities from a strong AMOC state to a weak AMOC state increase when considering sea ice insulation effects and indicate that sea ice promotes these transitions. On the other hand, sea ice insulation effects strongly reduce the probabilities of the reverse transition from a weak AMOC state to a strong AMOC state and this implies that sea ice also limits AMOC recovery. The results here indicate that sea ice effects play a dominant role in AMOC hysteresis width and influence transition probabilities between the different equilibrium states. Significance Statement We develop a novel conceptual ocean–sea ice box model to explain AMOC hysteresis behavior recently found in a modern complex climate model (the Community Earth System Model) and determine how sea ice insulation effects influence the hysteresis width and the probability of AMOC transitions.

Projections and Physical Drivers of Extreme Precipitation in Greenland & Baffin Bay

AbstractExtreme precipitation events can have substantial impacts on communities and the climate system in the warming Arctic, but their changes are not well understood. In this study, the characteristics of extreme precipitation days in the eastern Canadian Arctic and Greenland are examined in historical (1980–1999) and future (2080–2099, SSP5‐8.5) variable‐resolution Community Earth System Model simulations. Comparisons between the simulations illustrate potential changes in the frequency and intensity of these events in the region. Extreme precipitation is expected to increase broadly across the region. The frequency of the most intense daily precipitation rates is projected to rise, particularly in the northernmost areas. The seasonality of extremes does not shift substantially in the future simulation with most areas receiving the highest accumulations and increases during the summer. However, southeastern Greenland is projected to see decreases in extreme precipitation. Algorithms detecting atmospheric rivers and cyclones are employed to assess how their changes may factor into changes in extreme precipitation. Cyclone frequency remains largely consistent with slight decreases near southeastern Greenland, which may explain decreased extreme precipitation seen in the region. Atmospheric rivers are projected to become more frequent across the domain, largely during the summer. Although the majority of the region's extreme precipitation is associated with cyclones, this suggests that atmospheric rivers become more important in a warming climate. These results provide insight into potential changes in impactful precipitation events in the region and how the processes driving them may change.

A Multi-level Surrogate-assisted Algorithm for Expensive Optimization Problems

With the development of computer science, more and more complex problems rely on the help of computers for solving. When facing the parameter optimization problem of complex models, traditional intelligent optimization algorithms often require multiple iterations on the target problem. It can bring unacceptable costs and resource costs in dealing with these complex problems. In order to solve the parameter optimization of complex problems, in this paper we propose a multi-level surrogate-assisted optimization algorithm (MLSAO). By constructing surrogate models at different levels, the algorithm effectively explores the parameter space, avoiding local optima and enhancing optimization efficiency. The method combines two optimization algorithms, differential evolution (DE) and Downhill simplex method. DE is focused on global level surrogate model optimization. Downhill simplex is concentrated on local level surrogate model update. Random forest and inverse distance weighting (IDW) are constructed for global and local level surrogate model respectively. These methods leverage their respective advantages at different stages of the algorithm. The MLSAO algorithm is evaluated against other state-of-the-art approaches using benchmark functions of varying dimensions. Comprehensive results from the comparisons showcase the superior performance of the MLSAO algorithm in addressing expensive optimization problems. Moreover, we implement the MLSAO algorithm for tuning precipitation parameters in the Community Earth System Model (CESM). The outcomes reveal its effective enhancement of CESM's simulation accuracy for precipitation in the North Indian Ocean and the North Pacific region. These experiments demonstrate that MLSAO can better address parameter optimization problems under complex conditions.

Increased amplitude of atmospheric rivers and associated extreme precipitation in ultra-high-resolution greenhouse warming simulations

Atmospheric rivers play an integral role in the global water cycle, but predicting their future changes remains uncertain due to inter-model and inter-detection-method differences. Using ultra-high-resolution Community Earth System Model simulations and a novel detection algorithm based on geometric shape extraction, we quantify global changes in atmospheric rivers and the associated precipitation events in response to doubling and quadrupling of atmospheric CO2 concentrations. We find that, atmospheric rivers are projected to become more frequent and more likely to be associated with extreme precipitation events, increasing their contribution to global mean precipitation. While the water vapor transport within these structures follow Clausius-Clapeyron scaling, the changes in maximum precipitation intensity resemble other saturated atmospheric environments like tropical cyclone cores. The increased amplitude of atmospheric rivers and the associated increase in mean and extreme precipitation have important implications for future water management and adaptation policies.

Extreme atmospheric rivers in a warming climate

Extreme atmospheric rivers (EARs) are responsible for most of the severe precipitation and disastrous flooding along the coastal regions in midlatitudes. However, the current non-eddy-resolving climate models severely underestimate (~50%) EARs, casting significant uncertainties on their future projections. Here, using an unprecedented set of eddy-resolving high-resolution simulations from the Community Earth System Model simulations, we show that the models’ ability of simulating EARs is significantly improved (despite a slight overestimate of ~10%) and the EARs are projected to increase almost linearly with temperature warming. Under the Representative Concentration Pathway 8.5 warming scenario, there will be a global doubling or more of the occurrence, integrated water vapor transport and precipitation associated with EARs, and a more concentrated tripling for the landfalling EARs, by the end of the 21st century. We further demonstrate that the coupling relationship between EARs and storms will be reduced in a warming climate, potentially influencing the predictability of future EARs.

Machine Learning‐Based Detection of Weather Fronts and Associated Extreme Precipitation in Historical and Future Climates

AbstractExtreme precipitation events, including those associated with weather fronts, have wide‐ranging impacts across the world. Here we use a deep learning algorithm to identify weather fronts in high resolution Community Earth System Model (CESM) simulations over the contiguous United States (CONUS), and evaluate the results using observational and reanalysis products. We further compare results between CESM simulations using present‐day and future climate forcing, to study how these features might change with climate change. We find that detected front frequencies in CESM have seasonally varying spatial patterns and responses to climate change and are found to be associated with modeled changes in large scale circulation such as the jet stream. We also associate the detected fronts with precipitation and find that total and extreme frontal precipitation mostly decreases with climate change, with some seasonal and regional differences. Decreases in Northern Hemisphere summer frontal precipitation are largely driven by changes in the frequency of different front types, especially cold and stationary fronts. On the other hand, Northern Hemisphere winter exhibits some regional increases in frontal precipitation that are largely driven by changes in frontal precipitation intensity. While CONUS mean and extreme precipitation generally increase during all seasons in these climate change simulations, the likelihood of frontal extreme precipitation decreases, demonstrating that extreme precipitation has seasonally varying sources and mechanisms that will continue to evolve with climate change.

Exacerbation of Indian Summer Monsoon Breaks by the Indirect Effect of Regional Dust Aerosols

AbstractEvaluation of century‐long simulations of the Community Earth System Model (CESM) reveals model fidelity in capturing characteristics of aerosols, clouds, convection, rainfall and circulation over India associated with the active/break phase with wetter/drier than average rainfall within the summer monsoon season. During the breaks, aerosols build up over central India due to desert dust transported from the west by anomalous circulation, the trapping of dust emissions from the Thar‐desert and the increased aerosol lifetime in dry conditions. Break spells exhibit reduced cloud effective radius and enhanced lower atmospheric warming over central India as potential evidence for the indirect effect induced by dust aerosols. Consistently, break spells intensify in CESM simulation with increased loading of dust aerosols. The indirect effect of dust aerosols in warming the atmosphere and exacerbating the severity of breaks is conspicuous in simulations forced with the indirect effect of aerosols alone, both for present‐day and pre‐industrial periods.

Spatial Structure of Vertical Motions and Associated Heat Flux Induced by Mesoscale Eddies in the Upper Kuroshio‐Oyashio Extension

AbstractVertical motions induced by mesoscale eddies in the upper ocean play a vital role in the heat transport over the global ocean. However, the spatial structure of vertical eddy velocity and associated heat flux remains unclear. This study addresses this issue in the Kuroshio‐Oyashio Extension based on an eddy‐rich Community Earth System Model simulation. Adopting a mesoscale eddy composite analysis, we show that the vertical eddy velocity is enhanced at edges of mesoscale eddies with a maximum magnitude of 0.8 m day−1 in the upper ocean for anticyclonic eddies (AEs) and 0.5 m day−1 for cyclonic eddies (CEs). The associated vertical heat flux is upward, reaching 52 and 32 W m−2 along AEs' and CEs' periphery, respectively. Diagnostic analysis suggests that the enhanced vertical eddy motions at eddy edges are primarily attributed to the ageostrophic secondary circulation (ASC) under the turbulent thermal wind balance that accounts for more than 70% of the vertical eddy velocity and 80% of vertical eddy heat flux in the upper ocean. This ASC is stronger in winter than summer due to the intense turbulent mixing induced by strong surface cooling and wind stirring in winter. Accordingly, the vertical eddy velocity and associated heat flux exhibit a distinct seasonal cycle.

Atmospheric Contributions to the Reversal of Surface Temperature Anomalies Between Early and Late Winter Over Eurasia

AbstractObservations have shown subseasonal reversal of temperature anomalies between early and late winter over Eurasia, which is distinct from the seasonal mean condition. Based on the reanalysis data, the 1800‐year control simulation and the 40‐member ensemble simulations in 1920–2100 from the Community Earth System Model (CESM) Large Ensemble (CESM‐LE), this study reveals that the reversal of surface air temperature (SAT) anomalies between early and late winter is one of the dominant and intrinsic features of the Arctic‐Eurasian winter climate. Such a reversal is characterized by “colder Arctic, warmer Eurasia” in December (January–February) and “warmer Arctic, colder Eurasia” in January–February (December). Robust climate dynamic processes associated with the reversal of SAT anomalies, including subseasonal reversals of anomalies in the Ural blocking, midlatitude westerlies, and stratospheric polar vortex, are found in both reanalysis data and CESM simulations, indicating the important role of internal atmospheric variability. Further analysis reveals that the reversal of Ural blocking anomalies in late December can be a potential precursor for the reversal of SAT anomalies in late winter. The reversal of midlatitude westerly wind anomalies associated with the Ural blocking can affect upward propagation of planetary‐scale waves especially with wavenumber 1, subsequently promoting the contribution of stratospheric polar vortex to the reversal of SAT anomalies in late winter over the Arctic‐Eurasian regions. Such a troposphere‐stratosphere pathway triggered by the perturbation of tropospheric circulations is confirmed by the CESM‐LE simulations, and it may be useful for the prediction of subseasonal reversal of SAT anomalies.

Drivers of Last Millennium Antarctic Climate Evolution in an Ensemble of Community Earth System Model Simulations

Improved understanding of the drivers of climate variability, particularly over the last millennium, and its influence on Antarctic ice melt have important implications for projecting ice sheet resilience in a changing climate. Here, we investigated the variability in Antarctic climate and sea ice extent during the last millennium (850–1850 CE) by comparing paleoenvironmental reconstructions with simulations from the Community Earth System Model Last Millennium Ensemble (CESM-LME). Atmospheric and oceanic response to external forcing in CESM-LME simulations typically take the form of an Antarctic dipole: cooling over most of Antarctica and warming east of the Antarctic Peninsula. This configuration is also observed in ice core records. Unforced variability and a dipole response to large volcanic eruptions contribute to weaker cooling in the Antarctic than the Arctic, consistent with the absence of a strong volcanic signal in Antarctic ice core records. The ensemble does not support a clear link between the dipole pattern and baseline shifts in the Southern Annular Mode and El Niño-Southern Oscillation proposed by some paleoclimate reconstructions. Our analysis provides a point of comparison for paleoclimate reconstructions and highlights the role of internal climate variability in driving modeled last millennium climate evolution in the Antarctic.

Climate Responses to Tambora‐Size Volcanic Eruption and the Impact of Warming Climate

AbstractThe climatic consequences of large volcanic eruptions depend on the direct radiative perturbation and the climate variability that amplifies or dampens the initial perturbation. Potential climate responses to future eruptions, however, have been rarely studied. Here we show perturbation of Tambora‐size causes significant but no inter‐scenario different global average climate responses, by using Community Earth System Model simulations under preindustrial and RCP8.5 scenarios. Regionally we find severe reduction in African and Asian‐Australian monsoon rainfall and emerge of El Niño‐like responses, largely due to the land‐ocean thermal contrast mechanism. Global warming significantly amplifies such El Niño‐like responses, which feed on the enhanced climatology atmospheric moisture and cause higher sensitivity of monsoon circulation to radiative forcing in the tropics. We also find prolonged Asian‐Australian monsoon suppression associated with the enhanced westerly anomalies over the Pacific, suggesting the complexity of climate responses and feedbacks to external forcing under future climate.

On the Intermittent Occurrence of Open‐Ocean Polynyas in a Multi‐Century High‐Resolution Preindustrial Earth System Model Simulation

AbstractA 500‐year‐long high‐resolution Community Earth System Model simulation under preindustrial radiative forcing produces Maud Rise Polynyas (MRPs) and Weddell Sea Polynya (WSP) events intermittently from decadal (MRP) to multidecadal (WSP) timescales. This periodicity is correlated with the variation of a regional Southern Annular Mode (SAM) index (evaluated regionally instead of circum‐Antarctic) with corresponding variations of precipitation and winds over the Weddell Sea. A negative index causes the upper‐ocean salinity to increase over multiple decades. Ultimately, brine rejection during seasonal sea‐ice formation superimposed on the multidecadal increase raises the upper‐ocean salinity beyond the tipping point for triggering deep convection that leads to polynyas. The initiation of polynya events is thus controlled by surface properties while the location of initiation is determined by bathymetric features. The persistent Taylor column effect, which is well represented by the high‐resolution model topography of the Maud Rise seamount, preconditions this region for MRP initiation. Therefore, MRPs form more frequently than WSPs in the simulation. When the upper‐ocean salinity is high, deep convection in the MRP region tends to be stronger, in which case MRPs are also more likely to grow into WSPs. Once WSPs emerge, they affect the regional atmospheric circulation and associated variables. We propose a regional coupled ocean‐atmosphere mechanism to explain both the periodic emergence of polynyas and the periodic variation of the regional SAM index. Although the temperature and salinity of Weddell Deep Water show upward trends due to model drift, these density‐compensating changes do not affect the frequency of polynya formation.

Changes in rainfall erosivity over mainland China under stabilized 1.5 ℃ and 2 ℃ warming futures

Soil erosion is one of the major threats to the environment and agriculture in the world and rainfall erosivity is the most active factor to lead changes in soil erosion. Here, we use statistically downscaled, bias-corrected Community Earth System Model (CESM) low-warming simulations to investigate the future changes in rainfall erosivity in mainland China under the Paris Agreement global warming targets. The downscaled simulations evidently outperform the original CESM simulations in capturing the spatial distribution, magnitudes and annual cycle of rainfall erosivity in China in the present day (1986–2005). The rainfall erosivity will be significantly increased in most regions of China under the 1.5 °C and 2 °C warming targets and the regional mean increases are approximately 33% and 40%, respectively. In addition, the corresponding increases are even larger than 60% and 75%, respectively, in a quarter of mainland China. The increase in rainfall erosivity is resulted from the joint contributions of increases in frequency and intensity of erosive rainfall. However, it is dominated by the increase in the frequency. Compared with annual rainfall amount, the future warming will bring a four times greater impact on the soil erosion potentially caused by rainfall. Limiting global warming to 1.5 °C instead of 2 °C would reduce 17% of the increase in rainfall erosivity in China. For grain producing areas like Sichuan Basin, the middle and lower reaches of Yangtze River and South China, the values are approximately 20%. The future warming will significantly increase the potential risk of soil loss in China, and it is beneficial to relief this risk if the global warming is limited to 1.5 °C rather than 2 °C.

Effects of strongly eddying oceans on multidecadal climate variability in the Community Earth System Model

Abstract. Climate variability on multidecadal timescales appears to be organized in pronounced patterns with clear expressions in sea surface temperature, such as the Atlantic Multidecadal Variability and the Pacific Decadal Oscillation. These patterns are now well studied both in observations and global climate models and are important in the attribution of climate change. Results from CMIP5 models have indicated large biases in these patterns with consequences for ocean heat storage variability and the global mean surface temperature. In this paper, we use two multi-century Community Earth System Model simulations at coarse (1∘) and fine (0.1∘) ocean model horizontal grid spacing to study the effects of the representation of mesoscale ocean flows on major patterns of multidecadal variability. We find that resolving mesoscale ocean flows both improves the characteristics of the modes of variability with respect to observations and increases the amplitude of the heat content variability in the individual ocean basins. In the strongly eddying model, multidecadal variability increases compared to sub-decadal variability. This shift of spectral power is seen in sea surface temperature indices, basin-scale surface heat fluxes, and the global mean surface temperature. This implies that the current CMIP6 model generation, which predominantly does not resolve the ocean mesoscale, may systematically underestimate multidecadal variability.

Contribution of the Two Types of Ekman Pumping Induced Eddy Heat Flux to the Total Vertical Eddy Heat Flux

AbstractBased on eddy‐rich (0.1° horizontal resolution for ocean) Community Earth System Model simulations, we compute the Ekman pumping induced vertical eddy heat flux using two formulations: the classical and the Stern‐Ekman pumping. The two mechanisms yield similar patterns in the eddy‐induced vertical heat flux, showing strong upward heat flux in ocean frontal regions such as the western boundary current regions. Using the Gulf Stream Extension region as an example, we estimate (1) the Stern‐Ekman pumping induced eddy heat flux is 23% and 12% of the total vertical eddy heat flux at 50 m depth during summer and winter, respectively; (2) the classical Ekman pumping accounts for 82% and 88% of the Stern‐Ekman pumping induced eddy heat flux at 50 m during summer and winter, respectively. The second finding indicates eddy current feedback on wind stress is the primary cause for the upward eddy heat flux generated by Ekman pumping.

Implications of warming on western United States landfalling atmospheric rivers and their flood damages

Atmospheric rivers (ARs) are critical to the hydrological cycle of the western United States with both favorable and formidable impacts to society based on their landfalling characteristics. In this study, we provide a first-of-its-kind evaluation of how landfalling ARs may respond to several stabilized warming scenarios. To do this we combine a recently developed AR detection workflow with an ensemble of uniform high-resolution (0.25°) Community Earth System Model simulations designed to facilitate detection and attribution of extreme events with global warming. These simulations include a world that might have been in the absence of anthropogenic warming (+0◦C), a world that corresponds to present day warming (+0.85◦C), and several future worlds corresponding to +1.5◦C, +2◦C and +3◦C global warming. We show that warming increases the number of water management relevant landfalling ARs from 19.1 ARs per year at +0◦C to 23.6 ARs per year at +3◦C. Additionally, this warming intensifies the amount of water transported by landfalling ARs resulting in a decrease in the fraction of ARs that are “mostly to primarily beneficial” to water resource management (i.e., 91% of ARs at +0◦C to 78% at +3◦C) and an increase in the fraction of ARs that are “mostly or primarily hazardous” to water resource management (i.e., 2% of ARs at +0◦C to 8% at +3◦C). Shifts in AR character also have important ramifications on flood damages, whereby for every +1◦C of additional warming from present conditions annual average flood damages increase by ~$1 billion. These findings highlight the pragmatic implications of climate mitigation aimed at limiting global warming to under +2◦C.

Energy Flux into Near-Inertial Internal Waves Below the Surface Boundary Layer in the Global Ocean

AbstractNear-inertial internal waves (NIWs) are thought to play an important role in powering the turbulent diapycnal mixing in the ocean interior. Nevertheless, the energy flux into NIWs below the surface boundary layer (SBL) in the global ocean is still poorly understood. This key problem is addressed in this study based on a Community Earth System Model (CESM) simulation with a horizontal resolution of ~0.1° for its oceanic component and ~0.25° for its atmospheric component.The CESM shows good skill in simulating NIWs globally, reproducing the observed magnitude and spatial pattern of surface NIW currents and wind power on NIWs (WI). The simulated downward flux of NIW energy (FSBL) at the SBL base is positive everywhere. Its quasi-global integral (excluding the region within 5°S-5°N) is 0.13 TW, about one-third the value of WI. The ratio of local FSBL to WI varies substantially over the space. It exhibits an increasing trend with the enstrophy of balanced motions (BMs) and a decreasing trend with WI.The kinetic energy transfer from model-resolved BMs to NIWs is positive from the SBL base to 600 m but becomes negative further downwards. The quasi-global integral of energy transfer below the SBL base is two orders of magnitude smaller than that of FSBL, suggesting the resolved BMs in the CESM simulations making negligible contributions to power NIWs in the ocean interior.

Assessing the Skill of a High-Resolution Marine Biophysical Model Using Geostatistical Analysis of Mesoscale Ocean Chlorophyll Variability From Field Observations and Remote Sensing

High-resolution ocean biophysical models are now routinely being conducted at basin and global-scale, opening opportunities to deepen our understanding of the mechanistic coupling of physical and biological processes at the mesoscale. Prior to using these models to test scientific questions, we need to assess their skill. While progress has been made in validating the mean field, little work has been done to evaluate skill of the simulated mesoscale variability. Here we use geostatistical 2-D variograms to quantify the magnitude and spatial scale of chlorophyll a patchiness in a 1/10th-degree eddy-resolving coupled Community Earth System Model simulation. We compare results from satellite remote sensing and ship underway observations in the North Atlantic Ocean, where there is a large seasonal phytoplankton bloom. The coefficients of variation, i.e., the arithmetic standard deviation divided by the mean, from the two observational data sets are approximately invariant across a large range of mean chlorophyllavalues from oligotrophic and winter to subpolar bloom conditions. This relationship between the chlorophyllamesoscale variability and the mean field appears to reflect an emergent property of marine biophysics, and the high-resolution simulation does poorly in capturing this skill metric, with the model underestimating observed variability under low chlorophyllaconditions such as in the subtropics.

Seasonally changing contribution of sea ice and snow cover to uncertainty in multi-decadal Eurasian surface air temperature trends based on CESM simulations

This study investigates the impact of sea ice and snow changes on surface air temperature (SAT) trends on the multidecadal time scale over the mid- and high-latitudes of Eurasia during boreal autumn, winter and spring based on a 30-member ensemble simulations of the Community Earth System Model (CESM). A dynamical adjustment method is used to remove the internal component of circulation-induced SAT trends. The leading mode of dynamically adjusted SAT trends is featured by same-sign anomalies extending from northern Europe to central Siberia and to the Russian Far East, respectively, during boreal spring and autumn, and confined to western Siberia during winter. The internally generated component of sea ice concentration trends over the Barents-Kara Seas contributes to the differences in the thermodynamic component of internal SAT trends across the ensemble over adjacent northern Siberia during all the three seasons. The sea ice effect is largest in autumn and smallest in winter. Eurasian snow changes contribute to the spread in dynamically adjusted SAT trends as well around the periphery of snow covered region by modulating surface heat flux changes. The snow effect is identified over northeast Europe-western Siberia in autumn, north of the Caspian Sea in winter, and over eastern Europe-northern Siberia in spring. The effects of sea ice and snow on the SAT trends are realized mainly by modulating upward shortwave and longwave radiation fluxes.

Impacts of Large-Scale Soil Moisture Anomalies on the Hydroclimate of Southeastern South America

AbstractThe La Plata basin (LPB), located in southeastern South America (SESA), is a region of significant socioeconomic importance, particularly for agriculture. This area of South America exhibits strong land–atmosphere coupling in the warm season. In this work, we evaluate the impact of large-scale soil moisture (SM) anomalies on regional-scale atmospheric conditions. Multivariate empirical orthogonal function (EOF) analysis is used to extract the dominant modes of joint variability of monthly averaged root-zone SM and 1-month-lagged precipitation from atmospheric reanalyses. We find that the dominant EOF pattern is consistent with a positive correlation between antecedent SM and precipitation, while the second dominant EOF pattern is consistent with a negative correlation between these variables. To evaluate causality, the effects of large-scale SM anomalies on atmospheric variables are examined using the Community Earth System Model (CESM). CESM simulations suggest that anomalously dry SM is initially collocated with decreased precipitation. Subsequent changes in the atmospheric circulation associated with a thermal low draw moisture into the region, eventually promoting increased precipitation. This study investigates the pathways through which SM anomalies modulate precipitation in this region. For this reason, this study has potential atmospheric prediction applications that could benefit the population and the socioeconomic well-being of this important region.