ABSTRACT Greenhouse gases play a vital role in the climate system by absorbing the longwave infrared radiation and cause warming of the earth’s atmosphere. Therefore, it is important to be aware of the spatial and temporal distribution of carbon dioxide (CO2) both regionally and globally. In this study, the column-averaged CO2 dry air mole fraction (XCO2) data from Greenhouse Gases Observing Satellite (GOSAT) is used to investigate the spatial and temporal distribution of CO2 over Iran for the period May 2009 to June 2016. Based on the De Martonne climate classification and topography features, six regions were identified for spatial analysis of CO2 concentration. The amount of CO2 concentration over northwest to southwest is relatively higher than other parts of the study area because of natural conditions such as the interaction of topography and prevailing wind direction, and human activities. The CO2 concentration for all regions shows a seasonal cycle such that generally the lowest (highest) level of CO2 occurs in summer (winter) season. The results indicate an upward trend in CO2 concentration over different regions such that the increasing rate of monthly spatial average was 0.18 ppm per month. Moreover, seasonal autoregressive integrated moving average (SARIMA) models were developed to predict the monthly spatial average of CO2 concentration over Iran. The SARIMA models were also constructed for predicting CO2 concentration for the identified six regions. For all fitted SARIMA models, the correlation coefficients between the satellite observations and the predicted CO2 concentration were statistically significant at the 5% significance level such that the Pearson’s correlation coefficient (r) for the spatial average of CO2 concentration was equal to 0.9, 0.88, and 0.65 for the lead times of 1, 2, and 3 months, respectively.

中文翻译：

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伊朗上空二氧化碳浓度卫星测量的时空分布和季节预测

摘要 温室气体通过吸收长波红外辐射并导致地球大气变暖，在气候系统中起着至关重要的作用。因此，了解区域和全球二氧化碳 (CO2) 的空间和时间分布非常重要。在这项研究中，来自温室气体观测卫星 (GOSAT) 的柱平均 CO2 干空气摩尔分数 (XCO2) 数据用于调查 2009 年 5 月至 2016 年 6 月期间伊朗上空的 CO2 时空分布。 De Martonne 气候分类和地形特征，确定了六个区域用于 CO2 浓度的空间分析。由于地形和盛行风向的相互作用以及人类活动等自然条件的影响，西北至西南地区的CO2浓度相对高于研究区其他地区。所有地区的 CO2 浓度都显示出季节性循环，因此通常最低（最高）水平的 CO2 出现在夏季（冬季）季节。结果表明，不同地区的二氧化碳浓度呈上升趋势，月空间平均增长率为每月 0.18 ppm。此外，开发了季节性自回归综合移动平均 (SARIMA) 模型来预测伊朗二氧化碳浓度的月空间平均值。还构建了 SARIMA 模型，用于预测已确定的六个区域的 CO2 浓度。对于所有安装的 SARIMA 型号，