Global Climate Change and Regional Vulnerability: Quantifying CO₂–Temperature–Precipitation Interactions with a Focus on Armenia

Abstract

Understanding how global climate drivers manifest at regional scales is critical for designing targeted adaptation strategies, particularly in vulnerable mountainous countries. This study provides an integrated assessment of atmospheric CO₂ concentrations, surface temperature, and precipitation trends at both global and Armenian levels from the early 20th century to 2024. Using long-term observational datasets and ordinary least squares regression models with HAC-robust errors, this study quantifies the magnitude and statistical significance of historical climate shifts. Results confirm pronounced global warming (+0.021 °C/year) alongside a moderate rise in global precipitation (+1.13 mm/year). Armenia, however, exhibits substantially accelerated warming (+0.052 °C/year) coupled with a non-significant and spatially heterogeneous precipitation trend, including notable declines in humid regions. CO₂ emissions per capita strongly predict temperature change both globally (0.59 °C/ton) and, even more prominently, in Armenia (1.33 °C/ton), indicating heightened regional climate sensitivity. These findings align closely with Armenia’s Fourth National Communication to the UNFCCC, reinforcing the robustness of the analysis. By revealing how global climate forcings translate into region-specific outcomes—and by discussing the emerging thermal contribution of digital infrastructure—this study underscores the urgency of localized climate adaptation, water resource planning, and agricultural resilience measures.

1. Introduction

Climate change has emerged as one of the defining global challenges of the twenty-first century, with far-reaching implications for environmental stability, economic development, and societal well-being. Multiple independent datasets unequivocally demonstrate a rapid intensification of global warming, with the period 2015–2024 now recognized as the warmest decade on record. Rising temperatures have amplified the occurrence of extreme climatic events—including prolonged droughts, floods, heat waves, and shifting precipitation regimes—disrupting ecosystems, threatening biodiversity, and undermining agricultural productivity and public health [1,2,3,4].

The dominant driver of this accelerated change is the anthropogenic increase of greenhouse gas emissions, particularly carbon dioxide (CO₂), resulting from fossil fuel combustion, industrial activity, land-use change, and expanding global energy demand. Notably, the rapid growth of digital infrastructure—cloud computing, artificial intelligence, and the Internet of Things—represents an emerging and often underestimated contributor to energy consumption. Data centers, responsible for roughly 1% of global electricity demand, convert massive quantities of electrical energy into heat, further intensifying localized warming pressures and complicating global mitigation efforts.

Understanding the quantitative relationship between CO₂ emissions and climate responses has become a central focus of contemporary research. Numerous models confirm the strong link between emissions, surface temperature, and hydrological change [5,6,7,8]. Yet, despite substantial progress in global assessments, regional climate responses often diverge sharply from global averages, particularly in countries with complex topography, high climatic variability, and limited adaptive capacity. As a result, global trends—such as the well-documented increase in extreme precipitation—do not always translate directly into regional realities, where observational records reveal inconsistent or even opposite tendencies depending on data sources, study periods, and methodological differences.

Although the global climate system demonstrates consistent large-scale warming and shifts in precipitation patterns, the translation of these trends into local conditions depends heavily on regional geography and climatic structure. For Armenia, global warming signals are superimposed on a highly irregular terrain where elevation, continentality, and microclimatic variation shape how temperature and precipitation changes are actually experienced on the ground. For example, global increases in extreme rainfall do not necessarily manifest uniformly across Armenia’s marzes; instead, some regions exhibit declining precipitation or altered seasonality, while others show only modest change. Likewise, global heating disproportionately intensifies existing national vulnerabilities—such as reliance on snowmelt for water supply, exposure to drought, and the sensitivity of mountain ecosystems—making Armenia’s climate response both a reflection of global forcings and a product of its own environmental constraints.

Armenia, as a mountainous, landlocked country in the South Caucasus, Armenia faces disproportionate climate risks, including water scarcity, agricultural vulnerability, and ecological sensitivity. While existing literature highlights global precipitation increases and temperature anomalies, region-specific analyses for Armenia remain comparatively scarce, fragmented, or limited to narrow periods. This gap poses significant constraints for evidence-based climate policy, water resource management, and long-term socioeconomic planning.

This study addresses these shortcomings by providing a comprehensive, multiscale assessment of climate dynamics, integrating global and Armenian datasets on CO₂ concentrations, temperature, and precipitation. Through visual analytics and regression-based trend estimation with robust standard errors, we (1) quantify long-term climate trajectories, (2) compare Armenia’s climate responses to global patterns, (3) identify spatial heterogeneity across Armenian marzes (regions), and (4) evaluate the sensitivity of regional climate variables to CO₂ emissions. We also discuss the emerging role of digital technologies—and their thermal footprint—as a complementary driver of localized warming.

By revealing how global climate forcings translate into Armenia’s unique environmental context, this paper contributes new empirical evidence to the broader climate science literature and highlights the necessity of region-specific adaptation strategies.

2. Literature Review

Climate change research has expanded significantly over the past two decades, producing a large body of evidence on global warming, greenhouse gas emissions, hydrological variability, and socio-economic impacts. However, despite extensive global analyses, regional climate responses remain unevenly understood, particularly in countries with complex topography such as Armenia. This literature review synthesizes current knowledge along three major thematic axes—(1) observed climate impacts and carbon emissions, (2) mitigation strategies and technological innovations, and (3) policy, governance, and societal responses—before identifying critical gaps that motivate the present study.

2.1. Observed Impacts of Climate Change and Carbon Emissions

A substantial body of literature confirms the tangible impacts of escalating carbon dioxide (CO₂) concentrations on global ecosystems and human well-being.

Furthermore, the burgeoning field of digital innovation, while offering solutions, also contributes to air pollution and global warming, presenting a complex challenge that warrants further investigation.

Data centers, which house computer systems and related components such as telecommunications and storage systems, are a prime example of a technology’s thermal footprint. According to a report by the International Energy Agency, data centres alone account for around 1% of global electricity demand [9]. This figure could potentially increase dramatically as cloud computing, artificial intelligence and the Internet of Things (IoT) become more widespread. These centres use large amounts of energy and emit considerable heat into the environment. Most data centres use air ventilation systems to maintain optimal operating conditions for heat-generating machines, but these systems are not always effective. At the same time, they convert electrical energy into thermal energy, requiring reliable cooling solutions. The result is a cyclical dependence on electricity generation and consumption that exacerbates heat emissions and causes local temperatures to rise—a consequence of our new digital lifestyles.

Studies specifically focusing on indoor air quality highlight the adverse effects of pollutants such as particulate matter, carbon dioxide, and elevated temperatures on public health, often exacerbated by the extensive data transmission between computers and servers [10]. In urban contexts, mobile monitoring systems, deployed on public transport, offer a dynamic and effective approach to assessing air pollution levels across different areas and times, providing critical real-time information to individuals with health vulnerabilities, thereby surpassing the limitations of traditional fixed networks [11]. Projections indicate a significant increase in winter CO₂ levels by 2100—17% under a moderate mitigation scenario (Representative Concentration Pathway 4.5) and a substantial 41% under a business-as-usual emissions scenario (Representative Concentration Pathway 8.5) [12] (pp. 852–857).

2.2. Mitigation Strategies and Technological Innovations

The imperative to mitigate climate change has spurred extensive research into various policy and technological interventions. The China Dynamic Computable General Equilibrium Model (CEEGE) has been utilized to propose 1295 distinct policy scenarios, demonstrating the feasibility of achieving an 84% reduction in carbon emissions by 2060, aligning with carbon neutrality targets [13] (pp. 1–6). This underscores the critical role of well-defined mitigation pathways in achieving ambitious climate goals. However, a significant research gap persists in fully understanding the intricate economic and energy impacts of carbon mitigation strategies at both macroeconomic and sectoral levels [14].

The effective deployment of green technologies is recognized as a cornerstone of carbon mitigation efforts, particularly within the Chinese context. It is crucial that the qualitative benefits of these technologies outweigh their quantitative proliferation to ensure genuine environmental impact [15] (pp. 13342–13358), [16] (pp. 484–517). Furthermore, the development of hydrogen as a clean energy source faces challenges, with current programs in northern China requiring accelerated technological progress and improved incentive policies to effectively reduce CO₂ emissions [17] (pp. 1–13), [18] (pp. 1–16). The broader impact of technological progress on global warming also gives rise to complex international environmental issues, necessitating innovative assessment frameworks, such as the improved analogue method (AM), which adeptly identifies spatial temperature differences and emphasizes the importance of high-quality proxy data [19] (pp. 1–20), [20].

2.3. Policy, Governance, and Societal Responses

The increasingly internationalized nature of climate change necessitates a robust interplay between theoretical knowledge and collective action. Effective climate policy requires a deep understanding of past experiences and a proactive approach to decision-making [21] (pp. 759–784). Economic research has significantly contributed to this understanding, with top economics journals publishing extensive studies on climate change dynamics and consequences between 1975 and 2023 [22]. One of the prominent consequences of global warming is altered precipitation patterns. While the consensus confirms changes in extreme precipitation, variations in assessment methodologies, databases, and study periods can lead to divergent findings regarding change patterns and rates [23] (pp. 4901–4914). Long-term data analysis is crucial for accurate assessment of precipitation changes at global, continental, and regional scales. Urban areas, particularly their lower sections, have experienced significant shifts in precipitation intensity and frequency, often linked to thermal high air currents [24] (pp. 243–258).

Agriculture, a sector highly vulnerable to climate change, is profoundly impacted by unpredictable weather events, affecting crop quality and yield. Scientific research and the adoption of cutting-edge technologies are vital for the sustainable development and regulation of this sector [25] (pp. 372–379), [26]. The disproportionate impact of climate change on agricultural output is particularly evident in developing and low-income countries, which often lack the adaptive infrastructure present in more developed nations [4] (pp. 151–174), [27]. Global warming-induced droughts exacerbate food insecurity and malnutrition, as evidenced by studies on their impact on diverse age and gender groups in rural Bangladesh [28].

Environmental innovation is a powerful tool for climate change mitigation. Policies such as the European Union Emissions Trading System (EU ETS) actively promote investment in innovative, low-carbon technologies, recognizing that a fundamental transformation of traditional high-emission technologies is essential for achieving carbon neutrality [29,30] (pp. 1–17). However, analyses of climate policy integration and financing in donor countries reveal concerning trends, with several nations failing to prioritize climate change and policy development within their economic agendas [31] (pp. 1–21).

The legal dimension of climate adaptation policy is equally crucial, necessitating consideration of potential financial, social, and environmental impacts during policy formulation. Furthermore, establishing robust legal frameworks and supporting infrastructure is vital for effective sectoral regulation. While state-led initiatives are important, successful climate policy implementation requires broad public engagement. Studies demonstrate that providing adequate information and fostering public support significantly enhances the effectiveness of climate change mitigation efforts [32] (pp. 1474–1487). The once-predicted effects of global warming are now undeniable realities, and ineffective climate change management poses a severe threat to sustainable development. A prevailing critique suggests that current climate policy is often rooted in a neoclassical development paradigm, leading to market interventions that are insufficient in addressing the scale and systemic nature of the climate challenge [33].

Therefore, this review leads to several important insights:

• Global trends are well-documented, especially regarding rising CO₂ emissions, global warming, and increased extreme precipitation.
• Digital technologies are emerging as a new contributor to energy consumption and localized heat emissions, but their integration into climate analyses remains limited.
• Regional climatic responses are highly heterogeneous, with significant discrepancies—particularly for precipitation—across studies, datasets, and regions.
• Existing literature on the South Caucasus and Armenia is limited, often fragmented, or lacking long-term, integrated assessments that link CO₂ dynamics with temperature and precipitation trends.
• Policy-making increasingly demands localized evidence, yet the available research often focuses on global or continental scales, leaving critical knowledge gaps for smaller, mountainous countries.

Therefore, a clear research gap emerges: There is insufficient integrated, long-term analysis of how global climate drivers—specifically CO₂ emissions—translate into regional temperature and precipitation changes in Armenia, and how these patterns diverge from global trends. This gap directly motivates the present study.

By combining global and Armenian datasets and applying consistent statistical methodologies, this research aims to answer the following core questions:

Q1: How have global CO₂ concentrations, surface temperature, and precipitation evolved over the last century, and what are their quantitative relationships?

Q2: To what extent does Armenia follow or diverge from these global trends?

Q3: How strongly do CO₂ emissions predict temperature and precipitation dynamics at both global and regional levels?

Q4: What do these findings imply for Armenia’s climate vulnerability and for the development of targeted adaptation strategies?

By addressing these questions, this study bridges the gap between global climate science and regional climate policy needs, offering an empirically grounded foundation for understanding Armenia’s climate trajectory and supporting evidence-based adaptation planning.

3. Materials and Methods

This study employs a multiscale research design to investigate the relationships between atmospheric CO₂ levels, temperature trends, and precipitation dynamics at both global and regional (Armenian) scales. The methodology integrates long-term observational datasets, geospatial information, data visualization techniques, and regression-based statistical modelling. The combination of these approaches enables a comprehensive assessment of historical climate trajectories and the extent to which global patterns are reflected—or diverge—within Armenia.

To ensure analytical robustness, we assembled a diverse set of reputable international and national climate data sources:

• World Bank Climate Change Knowledge Portal—long-term monthly and annual temperature and precipitation data for Armenia [34];
• Our World in Data (OWID)—global precipitation datasets and annual CO₂ emissions per capita [35];
• Cosmic Ray Division of the Yerevan Physics Institute—localized seasonal temperature observations for Yerevan [36];
• NASA Goddard Institute for Space Studies (GISS)—global land–ocean temperature anomalies and atmospheric CO₂ concentration data [37];
• NOAA National Centers for Environmental Information—global climate indicators including temperature and precipitation [1];
• Data Catalog Armenia—shapefiles, climate zone data, and average temperature/precipitation by marz [38].

The dataset spans approximately 1900 to 2024, depending on source availability. Global time series are continuous, while Armenian datasets vary modestly by region and climate indicator. Each analysis relies on a specific subset of variables and data sources, which results in differing temporal coverage across figures; these ranges are clearly displayed on the time axes of all visualizations to ensure transparency and reproducibility.

Data were obtained in multiple formats, including CSV, Excel, tabular web extractions, and GIS shapefiles. All datasets were cleaned and standardized to harmonize temporal units, measurement scales, and missing-value structures.

Analyses were conducted using R (version 4.5.1), selected for its robust statistical and graphical capabilities. The following packages were used:

• dplyr, tidyr—data cleaning and transformation;
• ggplot2—generation of time-series and comparative visualizations;
• sf—processing of GIS shapefiles and creation of spatial climate maps;
• openair—climatic data handling;
• sandwich, lmtest—regression models with HAC-robust standard errors.

The methodological framework is structured to answer the research questions related to (1) long-term climate trends, (2) regional deviations from global patterns, and (3) the statistical relationship between CO₂ emissions and climate indicators.

Analysis proceeded in three stages:

Stage 1: Global Trend Analysis, where examined century-scale global trends in:

• atmospheric CO₂ concentration (ppm),
• global land–ocean temperature anomalies (°C),
• global average annual precipitation (mm).

Visual analysis allowed identification of major climate transitions, such as post-1980 temperature acceleration. Trends were then quantified with linear models.

Stage 2: Regional Climate Assessment for Armenia with the same structure, evaluating:

• average annual and monthly temperatures,
• seasonal patterns in Yerevan,
• maximum/minimum temperatures (extremes),
• annual precipitation for each marz,
• climate zone characteristics and their influence on precipitation patterns.

Armenia’s unique topography—reflected in ten climate zones defined by the country’s national climatic classification—required disaggregated analysis [39]. For example, marzes such as Lori and Shirak (humid/cooler zones) were contrasted with Armavir and Ararat (arid/low-precipitation zones).

We also constructed comparative maps showing the average temperature and precipitation of the previous decade versus the most recent decade, enabling visual detection of regional shifts.

To quantify long-term climate change, we employed ordinary least squares (OLS) linear trend models for both global and Armenian datasets:

$${\mathrm{T}\mathrm{e}\mathrm{m}\mathrm{p}}_t={\beta }_0+{\beta }_{1}t+{\epsilon }_t$$

$${\mathrm{P}\mathrm{r}\mathrm{e}\mathrm{c}\mathrm{i}\mathrm{p}}_t={\beta }_0+{\beta }_{1}t+{\epsilon }_t$$

where:

• t—year;
• β₁—estimated yearly change (slope);
• ε_t—residual error.

Given that climate time series typically exhibit autocorrelation and heteroscedasticity, we applied Newey–West HAC-robust standard errors to ensure valid inference. This step corrects for serial correlation and variance inconsistency that would otherwise bias p-values and confidence intervals.

To examine how emissions relate to climate indicators, we estimated:

$${\mathrm{T}\mathrm{e}\mathrm{m}\mathrm{p}}_t={\alpha }_0+{\alpha }_1{\mathrm{C}{\mathrm{O}}_{2}pc}_t+u_t$$

$${\mathrm{P}\mathrm{r}\mathrm{e}\mathrm{c}\mathrm{i}\mathrm{p}}_t={\alpha }_0+a_1{\mathrm{C}{\mathrm{O}}_{2}pc}_t+u_t$$

where

• CO₂pc_t—CO₂ emissions per capita (tons/year);
• α₁—change in climate variable per 1-ton increase in CO₂ emissions;
• u_t—HAC-corrected error term.

These models were estimated for both global and Armenian datasets, allowing direct comparison of climate sensitivity to emissions.

In addition to empirical modelling, the study applied the historical–logical method, commonly used in environmental and economic research. This method allows to synthesize historical climate patterns with contemporary theoretical insights; identifies long-term drivers and turning points; and contextualizes anomalies such as the CO₂ decline in 2020 due to COVID-19 economic contraction.

This approach allowed us to interpret numerical results in light of real-world processes and to highlight linkages between economic activity and climatic impacts.

4. Results

4.1. Global Trends of Climate Change

We begin by outlining the critical threat posed by rising global carbon dioxide (CO₂) emissions, primarily stemming from the combustion of fossil fuels for energy production, industrial processes, and deforestation. Our analysis reveals that these emissions have driven a significant increase in average global CO₂ emissions per person, rising from approximately 4 to 5 tonnes per capita over the depicted period, as shown by the brown solid line in Figure 1. In parallel with these emission trends, atmospheric CO₂ concentrations have escalated from roughly 325 parts per million (ppm) in 1970 to about 425 ppm today, a rise largely attributable to industrial development and other human activities [40,41].

This increase in CO₂ directly correlates with global mean land-ocean temperature trends. Our data illustrate a modest warming through the early and mid-20th century, followed by a more pronounced increase beginning in the 1980s (Figure 2). Currently, the temperature anomaly stands at nearly +1.3 °C, reflecting a substantial rise in Earth’s average surface temperature compared to the 1951–1980 long-term average [37].

We note several well-documented global consequences of rising temperatures.

Ecosystems and biodiversity: Many habitats are becoming inhospitable, forcing species migration and contributing to losses in sensitive ecosystems such as coral reefs [42] (pp. 139–159).

Public health: Higher temperatures increase heat-related illnesses, worsen air quality, and facilitate the spread of vector-borne diseases [43] (pp. 112–120).

Socioeconomic impacts: Climate change disproportionately affects vulnerable communities, intensifying droughts, floods, and economic instability, while raising critical issues of climate justice [44] (pp. 285–305).

Our visualization of global average annual precipitation from the 1940s through 2024 reveals an upward tendency, with annual precipitation increasing over the years to approximately 1080 mm in the most recent period (Figure 3). This indicates a general increase in global rainfall and snowfall [35].

4.2. Regional Analysis: Armenia’s Climate Trends

After analyzing the global trends of climate change, we now turn to the regional level to understand the situation in Armenia. The country is located in the southern part of the Caucasus Mountains. To provide geographical context, a general world map showing Armenia’s location can be accessed [45], and a detailed labeled map of Armenia’s marzes is shown in Figure 4 [46].

Our analysis of the average temperature in Armenia from 1900 to the present shows a noticeable increase, with a significantly higher rate of temperature increase observed starting from the 1980s (Figure 5). We consider temperature a crucial factor for maintaining stable agricultural yields and various other aspects of the country’s development, where even slight deviations can cause significant effects [34].

When examining monthly temperatures for different time intervals, our main observation is that for almost all months, temperatures appear higher for the period from 1991 to 2020 (Figure 6). This is an important finding, as it contradicts some claims of globally colder winters and warmer summers, demonstrating that in Armenia, the air warms uniformly throughout the year [34].

Furthermore, while some studies suggest an increase in climate anomalies and greater variation in extreme temperatures over time, our graph shows that the maximum and minimum temperatures over the past 50 years do not change drastically. Although we do observe some anomalies (in 1953, 1982, 1998), the trend line remains consistent. We note an increase in average temperatures when comparing values in 1950 and 2000, but no major changes in temperature extremes are witnessed (Figure 7) [34]. The trend lines in Figure 7 are based on LOESS smoothing (span = 0.4), providing a non-parametric estimate of long-term patterns in December temperature extremes.

In Yerevan, our graphs illustrate average seasonal temperatures. We observe a noticeable increase in Fall, Summer, and Winter temperatures from the year 2013. However, the Spring season presents an opposite picture, showing a decrease. This observation has various explanations, influenced by both the natural environment and human activities. For instance, the increased frequency of sunspots, a natural phenomenon releasing more heat, contributes to global warming (Figure 7).

Human activities, ranging from transportation to industrial factories, also cause warming due to the release of gases like CO₂. The cooling in Spring can be directly correlated with the fact that during spring months, trees and vegetation grow and consume CO₂. We found that in Yerevan (capital of Armenia), after 2013, tree cover has actually been increasing, which could possibly cause this temperature decrease [36].

The preceding figures in this section presented long-term historical temperature trends spanning several decades; however, the investigation of seasonal patterns (Figure 8) is conducted over a narrower, more recent interval—taking 2013 as the baseline—to capture short-term fluctuations and emerging seasonal shifts that may not be visible in multi-decade averages.

Finally, our two Armenia map graphs, comparing the average temperatures of the previous ten years with those of the most recent ten years, confirm that all Armenian regions are experiencing a consistent warming trend (Figure 9). Areas that were previously cooler (shown in darker purple) have shifted toward lighter shades, while already warmer regions (in red tones) appear even more intense, underscoring the widespread increase in temperature across the country [47].

To analyze precipitation data in Armenia, we first needed to understand the country’s diverse climate zones, as precipitation varies significantly more than temperature (from 100 mm up to 1000). Armenia comprises 10 different climate zones, with most marzes including many of them (Figure 10). Arid areas exhibit much higher average temperatures and much lower average precipitation compared to more humid and moderate areas. We therefore structured our comparison of precipitation by examining marzes with contrasting and less varying climate zones, such as Armavir and Gegharqunik versus Shirak and Lori [48].

Our analysis of the data from each marz reveals distinct findings (Figure 11):

More humid marzes experience a somewhat noticeable decrease in precipitation. For example, Lori, which has higher overall precipitation, has seen a decline over the years.

Hotter and arid places, such as Armavir, show very little precipitation (only about 400 mm/y) and have seen almost no major variation, remaining stable since 1900.

However, for highly diverse regions like Syunik, we were unable to obtain a lot of valuable information [48].

These findings suggest that instead of uniform variation in precipitation across Armenia, we see a more nuanced picture. Our graphs show that precipitation in humid marzes, where it is already quite high, has actually decreased over the years. Nonetheless, arid and hot marzes do not show any significant variation or decrease; their precipitation has remained largely unchanged (Figure 12) [48].

Moreover, our comparison of average annual precipitation between the previous and the most recent ten-year periods reveals a noticeable shift. In the earlier decade, several Armenian marzes displayed higher precipitation levels, illustrated by darker purple areas, whereas the more recent map shows lighter shades corresponding to reduced rainfall. This visual change indicates a general decline in average annual precipitation across Armenia in recent years.

To statistically evaluate our findings, we conducted the linear trend analysis using OLS regression models implemented through the lm() function in R on temperature and precipitation data for both global and Armenian contexts. The linear trend analysis was conducted using data from the 1985–2023 period. The results align with our earlier visual observations. Both global and Armenian temperatures show statistically significant upward trends, with Armenia warming at a faster rate (~0.052 °C/year) compared to the global average (~0.021 °C/year). Global precipitation also increases significantly (~1.13 mm/year), while Armenian precipitation shows no clear trend (not statistically significant as p > 0.3; low R²), reflecting its high variability.

Table 1. Trend analysis results for temperature and precipitation based on OLS regression. Source: authoring based on trend analysis model outputs.

Dataset	Variable	Slope	p-Value	R2
Global Temperature	Temp (°C)	0.021	<0.001	0.87
Global Precipitation	Precip (mm)	1.125	<0.001	0.54
Armenia Temperature	Temp (°C)	0.052	<0.001	0.39
Armenia Precipitation	Precip (mm)	−1.272	<0.3346	0.03

summarizes the results of these regression models, including the estimated slopes (yearly change), p-values, and R² values that indicate how well the model explains the variation in the data.

The estimated warming rate for Armenia (~0.052 °C/year) reflects the trend over this specific analysis interval, during which temperature increases have been particularly pronounced across the South Caucasus. Because Armenia is a mountainous, continental, and climatically heterogeneous region, short-period regression slopes are often higher than global averages and are more sensitive to interannual variability.

To complement the visual analysis of global and regional climate trends, we applied regression models using carbon dioxide emissions per capita as the predictor variable. These models revealed statistically significant relationships for temperature, both globally and in Armenia. At the global level, each additional ton of CO₂ per person was associated with an average increase of 0.59 °C in temperature (p = 0.006), while global precipitation increased by approximately 37 mm per ton of CO₂ per capita (p = 0.007). In Armenia, the results followed a similar pattern but indicated even greater temperature sensitivity: a one-ton increase in CO₂ per capita corresponded to an average 1.33 °C rise in annual temperature (p = 0.025), suggesting that Armenia may be experiencing accelerated warming relative to global trends.

However, the relationship between CO₂ emissions and Armenian precipitation was not statistically significant. The estimated effect was small and uncertain (p = 0.867), indicating that local precipitation patterns may be influenced by additional factors beyond emissions. All regression models were estimated using HAC-robust standard errors to correct for autocorrelation in the annual climate data, ensuring reliable statistical inference in a time-series context [49].

Overall, the statistical findings are consistent with our visual analysis, reinforcing the evidence of a clear and measurable link between rising CO₂ emissions and evolving global and regional climate trends. This agreement between visual and quantitative assessments strengthens the reliability of our conclusions and provides further support for the observed climate patterns.

Finally, changes in temperature and precipitation patterns directly influence crop yields. While some regions may benefit from longer growing seasons, the net impact often leans toward negative outcomes, particularly in developing nations that lack the resources for adaptive measures. Such climate change not only causes significant damage to agricultural production but also negatively affects the national economy of any country.

5. Discussion

The objective of this study was to examine how global climate dynamics—particularly rising CO₂ concentrations, temperature anomalies, and changing precipitation patterns—translate into regional climate responses within Armenia. Our analysis has yielded unique results for both global and regional (Armenian) climate dynamics, some of which do not consistently align with interpretations found in certain climate reviews by other authors [5] (pp. 188–195), [7] (pp. 59–68), [8,10]. This divergence prompted us to seek possible explanations, causes, and supporting evidence for our findings. In particular, several of our empirical results—such as Armenia’s higher recent-period warming rate and the contrasting precipitation trends between global and regional datasets—emerged as central elements requiring deeper contextual interpretation.

Among the key sources considered for validating regional findings, a particularly important reference is Armenia’s Fourth National Communication on Climate Change, officially submitted to the UNFCCC by the Ministry of Environment with support from UNDP and the Global Environment Facility [50]. The report presents verified national analyses of temperature and precipitation trends based on data from Armenia’s Hydrometeorology and Monitoring Center, which operates a network of 47 meteorological and hydrological observation stations. Our results are consistent with the findings of this official document, providing additional validation and supporting the reliability of our conclusions. The consistency between our regression-based trend estimates and those reported in the National Communication further reinforces the robustness of our empirical findings.

We first discuss the observed temperature shifts, addressing our initial hypothesis, which, as stated, presented a contradiction to some existing literature. While climate researchers frequently employ various models to predict weather events based on current data [20,50] (p. 26), our findings on overall warming largely concur with the established understanding that global temperatures have been rising for a considerable period, with accelerating rates of change in recent years. This acceleration is well-supported by our data. However, we note a disagreement with certain authors who project an even greater rise in air temperature in winter by the year 2100 [12] (pp. 852–857). Our regional findings are consistent with other recent regional studies [51,52], while we observe anomalies, i.e., warmer summer temperatures but not necessarily colder winters, suggesting a more uniform annual warming trend in Armenia. This conclusion is supported by our seasonal analysis, which shows marked warming in summer, fall, and winter, contrasted with a spring cooling effect likely linked to increased vegetation activity and CO₂ uptake.

The Fourth National Communication on Climate Change reports a consistent rise in Armenia’s average annual air temperature across multiple observation periods: an increase of 0.4 °C during 1929–1996, 0.85 °C during 1929–2007, 1.03 °C during 1929–2012, and 1.23 °C by 2016 [50] (p. 112). These results confirm a steady and accelerating warming trend throughout the twentieth and early twenty-first centuries. Our analysis, based on both visual and statistical methods, identified a comparable rate of increase of approximately 0.052 °C per year over the period 1985 to 2023, which closely aligns with the cumulative changes presented in the national report, further validating the observed long-term warming in Armenia.

Regarding precipitation, our research generally does not align with some expert forecasts and reviews [24] (pp. 243–258). It is widely understood that average warmer temperatures increase evaporation and atmospheric moisture, leading to more frequent precipitation globally [53]. Our global precipitation visualization supports this, showing an overall increase worldwide. According to global findings, the global average precipitation has risen by approximately 0.8 mm (mm) every ten years since 1901. Although this may appear small, it constitutes a noticeable overall increase over decades, with global temperature change being the primary driver. These precipitation changes have crucial effects on natural processes, including society, agriculture, and animal life [50] (pp. 26–29), [54]. Our empirical results show no statistically significant long-term precipitation trend for Armenia, highlighting a clear divergence from global patterns and underscoring the dominant role of regional climatic variability in shaping precipitation behavior.

The overall global increase in precipitation does not imply a consistent behavior in every part of the world. Some sources describe the climatic conditions of Armenia as regionally distinct, with excess precipitation in some regions and severe drought in others [50] (pp. 72–77), [55]. According to the Fourth National Communication on Climate Change, Armenia experienced a decrease in average annual precipitation of about 6% between 1935 and 1996, and 9% between 1935 and 2016, with the long-term average reaching 558 mm, compared to the 1961–1990 baseline of 592 mm [50] (p. 114). These findings are consistent with our results, which indicate a generally stable but slightly declining precipitation trend, particularly in the wetter regions, contrasting with the global pattern of increasing average precipitation.

To thoroughly investigate this, we emphasized the necessity of examining the various climate zones across Armenia’s marzes, as precipitation levels can vary significantly more than temperature from one region to another. The data of our research show that, as a rule, a high average temperature is recorded in arid regions, which is consistent with the results of other researchers [56]. These regions experience relatively lower average rainfall as opposed to humid and temperate climate zones. By combining information from maps detailing precipitation, temperature, and climate zones, we were able to identify which marzes experience fewer climate fluctuations. These spatial patterns detected in our maps directly reinforce our empirical conclusion that precipitation behavior in Armenia cannot be generalized at the national scale and must instead be interpreted through its diverse climate-zone structure.

These findings raise important questions about the underlying drivers of Armenia’s precipitation decline. Several hypotheses and explanations can clarify why Armenia exhibits a declining precipitation pattern despite the global increase. Armenia’s mountainous terrain is a key factor. Snowfall serves as a crucial water source, collecting in winter and melting during spring to supply water for agriculture and other needs [57]. As temperatures have risen over the years, snowfall has decreased, with more precipitation falling as rain instead of snow [58,59]. This reduction in snowfall negatively affects overall precipitation levels. Furthermore, Armenia’s specific mountainous terrain and unique wind patterns can override broader global trends, altering moisture flows and resulting in lower total precipitation.

Future research will build upon current analytical findings, focusing on deepening emerging insights through the application of cutting-edge agricultural technologies. Key areas of investigation will include the development of methodologies for precise grain yield prediction, robust quantitative calculations, and comprehensive deviation analysis.

6. Conclusions

This study provides a comprehensive, multiscale examination of long-term climate dynamics by integrating global evidence with a detailed regional analysis of Armenia. The findings demonstrate that while global patterns offer an essential backdrop for understanding climate change, they do not adequately describe the magnitude, timing, or character of regional climate responses—particularly in geographically complex, climate-sensitive countries such as Armenia.

Our results confirm three overarching insights:

• Armenia is warming significantly faster than the global average.

The statistically robust warming rate of 0.052 °C per year—more than double the global trend—positions Armenia among the regions experiencing accelerated climate change. This amplification aligns with national reports and recent climatological studies, underscoring a rising trajectory of heat stress, increased frequency of extreme temperatures, and growing risks for public health, agriculture, and ecosystems.

2.

Precipitation trends in Armenia diverge sharply from global hydrological intensification.

Whereas global precipitation has increased, Armenia exhibits no significant long-term trend, with a tendency toward decline in several humid northern marzes. The combination of declining snowfall, shifting atmospheric moisture pathways, and strong topographic influences explains this divergence. These patterns carry severe implications for water availability, irrigation security, hydropower potential, and regional development planning.

3.

Armenia exhibits heightened temperature sensitivity to CO₂ emissions.

The relationship between CO₂ emissions per capita and temperature is notably stronger in Armenia than in global estimates. This suggests that Armenia’s climatic system responds more sharply to radiative forcing—likely due to its semi-arid continental environment, snow-dependent hydrology, and limited climatic buffering capacity.

Together, these findings highlight Armenia’s growing climate vulnerability and the urgent need for localized, science-based adaptation strategies. The study demonstrates that reliance on global climate indicators alone is insufficient for national planning; instead, countries like Armenia require region-specific assessments that capture local trends, spatial variability, and climate–emission sensitivities.

The practical implications of the results are substantial. We can emphasize that policymakers should prioritize the following areas:

-

water resource resilience, particularly in regions exhibiting declining precipitation;

-

climate-smart agriculture and irrigation efficiency to offset heat-induced yield losses;

-

heat mitigation strategies in urban centres, including green infrastructure and energy-efficient digital systems;

-

enhanced climate monitoring, especially in mountainous zones where observational gaps remain.

Although the analysis draws on the best available international and national datasets, further progress requires expanding high-resolution meteorological observations, improving hydrological modelling, and integrating future climate scenario projections tailored to Armenia’s terrain and socio-economic structure.

In conclusion, this research provides a robust empirical foundation for understanding Armenia’s climate trajectory and illustrates the importance of linking global climate dynamics with detailed regional diagnostics. By revealing where Armenia aligns with global trends—and where it diverges—the study contributes essential insights for guiding climate resilience, sustainable development, and long-term strategic planning in a rapidly warming world.