University of Isfahan Geography and Environmental Planning 2008-5362 36 3 2025 09 23 Impacts of Solar Irradiance and Geopotential Height on Snow Cover in the Karun and Marun River Basins Impacts of Solar Irradiance and Geopotential Height on Snow Cover in the Karun and Marun River Basins 93 126 29671 10.22108/gep.2025.142875.1668 FA Nezam Tani Ph.D. student, Department of Meteorology, University of Yazd, Yazd, Iran Kamal Omidvar Ph.D., Department of Meteorology, University of Yazd, Yazd, Iran Golamali Mozafari Mozafari Ph.D., Department of Meteorology, University of Yazd, Yazd, Iran Ahmad Mazidi Associate Professor, Department of Meteorology, Yazd University, Yazd, Iran Journal Article 2024 09 23 Abstract Solar irradiance and synoptic patterns are critical factors influencing the distribution of snow cover in a region. Variations in these elements can significantly impact regional snow cover. This study explored the effects of downward and upward solar radiation, as well as geopotential height, on the snow cover extent of the Karun and Marun river basins. Daily snow cover data were extracted from MODIS Terra satellite observations and compiled on a monthly basis. Data on geopotential height and solar radiation (both downward and upward) were sourced from the NOAA National Centers for Environmental Prediction over a 22-year period (2001–2022) and subsequently processed. The synoptic analysis confirmed that atmospheric patterns, geopotential height, and solar radiation significantly influenced the snow cover in the study area, particularly during colder months. Specifically, a negative correlation was observed between geopotential height and downward solar radiation at the 0.05 and 0.01 significance levels. Conversely, during the cold months, an increase in upward solar radiation was directly associated with an expansion of snow cover extent. Notably, synoptic maps indicated higher upward solar radiation values during periods of substantial snow cover compared to those with diminished snow cover. Overall, from November to March, a decrease in geopotential height and solar radiation correlated with an increase in snow cover. This study highlighted a robust relationship between fluctuations in snow cover and variations in geopotential height and solar radiation within the examined watershed. The ability to predict these variables offered valuable insights for forecasting snow cover changes, which is crucial for effective water resource management, especially in tackling challenges, such as droughts and floods. Keywords: Snow Cover, Karun and Marun River Basins, Geopotential Height, Solar Radiation Flux. Introduction Solar radiation, or solar irradiance, refers to the radiant energy emitted by the sun. This energy is a fundamental component of the Earth's climate system and plays a crucial role in various biological and physical processes on our planet. Both solar irradiance and synoptic patterns are essential for determining the distribution of snow cover in a region as changes in either factor can significantly affect regional snow cover. The primary objective of this research was to evaluate the impact of shifting atmospheric circulation patterns on fluctuations in snow cover within the Karun and Marun river basins with a particular focus on key parameters, such as geopotential height and solar irradiance. The findings of this study will provide valuable insights for both short-term and long-term planning, addressing challenges posed by climate change, including droughts and floods. Materials & Methods This study examined the relationship between atmospheric patterns—including geopotential height, downward and upward solar irradiance, and snow cover extent—in the Karun and Marun river basins located in the southern Zagros region. Data were collected as outlined in Table 1. Utilizing MODIS satellite data with a spatial resolution of 500 m and the powerful Google Earth Engine (GEE) platform, we analyzed the river basins over a time series from 2001 to 2022. After applying necessary corrections to the data, satellite images were processed on a monthly, seasonal, and annual basis. These images were then converted into binary formats to distinguish between snow-covered and snow-free areas. The Normalized Difference Snow Index (NDSI) was calculated for each pixel to assess snow cover extent. Following this, snow cover images were converted from pixel values to binary values (0 and 1) and the NDSI snow cover was categorized into 6 distinct classifications. To further investigate the atmospheric structure at upper levels and its relationship with snow cover in the study area, we obtained data on geopotential height, downward solar irradiance, and upward solar irradiance with a spatial resolution of 2.5° x 2.5° from the NCEP/NCAR database. The quantitative relationship between snow cover across various categories (low, medium, high, dense, and total snow cover) and the synoptic patterns corresponding to the Karun and Marun river basins was analyzed using Pearson correlation methods. Research Findings In this study, data related to snow cover in the Karun and Marun river basins were collected from the MODIS satellite, along with information on geopotential height and upward and downward solar irradiance at various atmospheric levels. The data were organized and analyzed accordingly. The results revealed a significant relationship at the 0.05 and 0.01 confidence levels between geopotential height, downward solar irradiance, and snow cover extent, particularly during the winter months, especially in January and February. This correlation persisted throughout most of the cold season. In contrast to the previous two variables, upward solar irradiance—which reflected energy from the snow surface—exhibited a direct relationship with increasing snow cover. For instance, in January 2014, snow cover extent was above the normal average, while in January 2019, it was below average. During this same period, the average geopotential height in January 2019 was notably higher than in January 2014, indicating differing atmospheric patterns for that month. This trend also applied to February. A comparative analysis of maps and atmospheric diagrams confirmed an inverse correlation between fluctuations in geopotential height and downward solar irradiance with snow cover extent in April. Specifically, an increase in geopotential height at the 700-hPa level in April, similar to the patterns observed in colder months, was associated with greater atmospheric stability and a reduction in snow cover extent. Conversely, an increase in downward solar irradiance resulted in higher temperatures and accelerated snowmelt, leading to a decrease in snow cover. From May to October, a significant reduction in snow cover occurred as temperatures rose and the rainy season receded, resulting in no notable correlation between the studied variables. However, starting in November, as precipitation increased and snow cover expanded, the correlation between the variables strengthened. In November, a negative correlation was observed between snow cover extent and both geopotential height and upward solar irradiance. Specifically, as geopotential height increased, there was a confirmed decrease in snow cover extent, particularly in the medium category. Additionally, during this month, an increase in downward solar irradiance corresponded to a decline in snow cover across all classifications. Conversely, an increase in low-class snow cover showed a significant correlation with rising upward solar irradiance. Thus, during the cold period from November to March, a decrease in geopotential height and solar irradiance was associated with an increase in snow cover. From December onwards, the correlation between these variables and snow cover reached its peak. In essence, varying atmospheric patterns during periods of high and low snow cover significantly influenced the overall snow cover extent. Discussion of Results & Conclusion Overall, the strength of the correlation between the variables fluctuated across different seasons. This correlation was notably stronger in autumn and winter. The analysis indicated that geopotential height and solar radiation were two primary factors influencing snow cover. A decrease in geopotential height, along with a reduction in downward solar irradiance, contributed to an increase in snow cover. During the cold months, snow acted as a reflective surface, reflecting a significant portion of solar radiation back into space. This reflection resulted in higher upward solar irradiance, which helped maintain lower temperatures and supported the persistence of snow. The findings from the synoptic analysis reinforced the impact of geopotential height and atmospheric patterns of solar irradiance on snow cover in the study basin, particularly during colder periods. In essence, geopotential height and downward solar irradiance demonstrated a negative correlation with snow cover extent at the 0.05 and 0.01 confidence levels. Conversely, during the cold months, an increase in upward solar irradiance was directly associated with an increase in snow cover extent. This relationship was evident as the rise in upward solar irradiance values observed in synoptic maps during periods of high snow cover was markedly distinct compared to periods of low snow cover in the study basin. Abstract Solar irradiance and synoptic patterns are critical factors influencing the distribution of snow cover in a region. Variations in these elements can significantly impact regional snow cover. This study explored the effects of downward and upward solar radiation, as well as geopotential height, on the snow cover extent of the Karun and Marun river basins. Daily snow cover data were extracted from MODIS Terra satellite observations and compiled on a monthly basis. Data on geopotential height and solar radiation (both downward and upward) were sourced from the NOAA National Centers for Environmental Prediction over a 22-year period (2001–2022) and subsequently processed. The synoptic analysis confirmed that atmospheric patterns, geopotential height, and solar radiation significantly influenced the snow cover in the study area, particularly during colder months. Specifically, a negative correlation was observed between geopotential height and downward solar radiation at the 0.05 and 0.01 significance levels. Conversely, during the cold months, an increase in upward solar radiation was directly associated with an expansion of snow cover extent. Notably, synoptic maps indicated higher upward solar radiation values during periods of substantial snow cover compared to those with diminished snow cover. Overall, from November to March, a decrease in geopotential height and solar radiation correlated with an increase in snow cover. This study highlighted a robust relationship between fluctuations in snow cover and variations in geopotential height and solar radiation within the examined watershed. The ability to predict these variables offered valuable insights for forecasting snow cover changes, which is crucial for effective water resource management, especially in tackling challenges, such as droughts and floods. Keywords: Snow Cover, Karun and Marun River Basins, Geopotential Height, Solar Radiation Flux. Introduction Solar radiation, or solar irradiance, refers to the radiant energy emitted by the sun. This energy is a fundamental component of the Earth's climate system and plays a crucial role in various biological and physical processes on our planet. Both solar irradiance and synoptic patterns are essential for determining the distribution of snow cover in a region as changes in either factor can significantly affect regional snow cover. The primary objective of this research was to evaluate the impact of shifting atmospheric circulation patterns on fluctuations in snow cover within the Karun and Marun river basins with a particular focus on key parameters, such as geopotential height and solar irradiance. The findings of this study will provide valuable insights for both short-term and long-term planning, addressing challenges posed by climate change, including droughts and floods. Materials & Methods This study examined the relationship between atmospheric patterns—including geopotential height, downward and upward solar irradiance, and snow cover extent—in the Karun and Marun river basins located in the southern Zagros region. Data were collected as outlined in Table 1. Utilizing MODIS satellite data with a spatial resolution of 500 m and the powerful Google Earth Engine (GEE) platform, we analyzed the river basins over a time series from 2001 to 2022. After applying necessary corrections to the data, satellite images were processed on a monthly, seasonal, and annual basis. These images were then converted into binary formats to distinguish between snow-covered and snow-free areas. The Normalized Difference Snow Index (NDSI) was calculated for each pixel to assess snow cover extent. Following this, snow cover images were converted from pixel values to binary values (0 and 1) and the NDSI snow cover was categorized into 6 distinct classifications. To further investigate the atmospheric structure at upper levels and its relationship with snow cover in the study area, we obtained data on geopotential height, downward solar irradiance, and upward solar irradiance with a spatial resolution of 2.5° x 2.5° from the NCEP/NCAR database. The quantitative relationship between snow cover across various categories (low, medium, high, dense, and total snow cover) and the synoptic patterns corresponding to the Karun and Marun river basins was analyzed using Pearson correlation methods. Research Findings In this study, data related to snow cover in the Karun and Marun river basins were collected from the MODIS satellite, along with information on geopotential height and upward and downward solar irradiance at various atmospheric levels. The data were organized and analyzed accordingly. The results revealed a significant relationship at the 0.05 and 0.01 confidence levels between geopotential height, downward solar irradiance, and snow cover extent, particularly during the winter months, especially in January and February. This correlation persisted throughout most of the cold season. In contrast to the previous two variables, upward solar irradiance—which reflected energy from the snow surface—exhibited a direct relationship with increasing snow cover. For instance, in January 2014, snow cover extent was above the normal average, while in January 2019, it was below average. During this same period, the average geopotential height in January 2019 was notably higher than in January 2014, indicating differing atmospheric patterns for that month. This trend also applied to February. A comparative analysis of maps and atmospheric diagrams confirmed an inverse correlation between fluctuations in geopotential height and downward solar irradiance with snow cover extent in April. Specifically, an increase in geopotential height at the 700-hPa level in April, similar to the patterns observed in colder months, was associated with greater atmospheric stability and a reduction in snow cover extent. Conversely, an increase in downward solar irradiance resulted in higher temperatures and accelerated snowmelt, leading to a decrease in snow cover. From May to October, a significant reduction in snow cover occurred as temperatures rose and the rainy season receded, resulting in no notable correlation between the studied variables. However, starting in November, as precipitation increased and snow cover expanded, the correlation between the variables strengthened. In November, a negative correlation was observed between snow cover extent and both geopotential height and upward solar irradiance. Specifically, as geopotential height increased, there was a confirmed decrease in snow cover extent, particularly in the medium category. Additionally, during this month, an increase in downward solar irradiance corresponded to a decline in snow cover across all classifications. Conversely, an increase in low-class snow cover showed a significant correlation with rising upward solar irradiance. Thus, during the cold period from November to March, a decrease in geopotential height and solar irradiance was associated with an increase in snow cover. From December onwards, the correlation between these variables and snow cover reached its peak. In essence, varying atmospheric patterns during periods of high and low snow cover significantly influenced the overall snow cover extent. Discussion of Results & Conclusion Overall, the strength of the correlation between the variables fluctuated across different seasons. This correlation was notably stronger in autumn and winter. The analysis indicated that geopotential height and solar radiation were two primary factors influencing snow cover. A decrease in geopotential height, along with a reduction in downward solar irradiance, contributed to an increase in snow cover. During the cold months, snow acted as a reflective surface, reflecting a significant portion of solar radiation back into space. This reflection resulted in higher upward solar irradiance, which helped maintain lower temperatures and supported the persistence of snow. The findings from the synoptic analysis reinforced the impact of geopotential height and atmospheric patterns of solar irradiance on snow cover in the study basin, particularly during colder periods. In essence, geopotential height and downward solar irradiance demonstrated a negative correlation with snow cover extent at the 0.05 and 0.01 confidence levels. Conversely, during the cold months, an increase in upward solar irradiance was directly associated with an increase in snow cover extent. This relationship was evident as the rise in upward solar irradiance values observed in synoptic maps during periods of high snow cover was markedly distinct compared to periods of low snow cover in the study basin.

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