Atmosferik CO₂ Konsantrasyonu ile Yağış Arasındaki İlişkinin Uydu Verilerine Dayalı Olarak Türkiye Üzerinde Zamansal ve Mekânsal Analizi

Öz

Tablo verilerine dayalı karbon dioksit (CO₂) verileri, Türkiye üzerinde CO₂ ile yağış arasındaki ilişkiyi keşfetmek için kullanılmaktadır. CO₂ verileri, NASA'nın Yörüngedeki Karbon Gözlem Aracı-2 (OCO-2) misyonundan alınırken, yağış verileri, GPM için Entegre Çoklu Uydu Alımları (IMERG) veri setinden alınmıştır. Her iki veri seti de aynı zaman aralıklarına getirilmiş olup, bu sayede hem zamansal hem de mekansal analizler yapılabilmiştir. CO₂ ile yağış arasında çok zayıf bir pozitif korelasyon (r ≈ 0.17) bulunmuştur. Bu ilişki, 12 aylık bir gecikme ile en güçlü hale gelmektedir; doğrusal regresyon ile yapılan analizde ise bu ilişki yalnızca çok küçük bir değişkenlik oranını açıklamaktadır (R² ≈ 0.03). Bu sonuçlar, yağışlardaki değişimlerin yalnızca CO₂ ile açıklanamayacağını göstermektedir. Yenilikler, Türkiye için aynı dönemi kapsayan uydu verilerinin zamansal olarak kullanılması ve makine öğrenmesi modellerinin yanı sıra klasik istatistiksel yöntemlerin uygulanmasıdır. Test edilen modeller arasında Random Forest en iyi performansı sergileyerek (R² = 0.68), doğrusal regresyonun kaçırdığı desenleri yakalayabilen doğrusal olmayan yöntemlerin etkili olduğunu göstermektedir. Ancak bu sonuç, kısa zaman serisi ve sınırlı tahminci seti göz önünde bulundurularak dikkatlice yorumlanmalıdır. Bu araştırma, CO₂–yağış ilişkisine dair yeni bir yerel versiyon sunmakta ve CO₂'nin bu ilişkideki zayıf rolünü açıklamakta, aynı zamanda yağışların CO₂ ile açıklanamayacağını vurgulamaktadır.

Anahtar Kelimeler

• CO₂ konsantrasyonu
• yağış analizi
• OCO-2
• IMERG
• iklim değişikliği
• Türkiye

Temporal and Spatial Analysis of the Relationship Between Atmospheric CO₂ Concentration and Precipitation in Türkiye Based on Satellite Data

Öz

The satellite-based carbon dioxide data is used in discovering any relationship between CO₂ and precipitation over Türkiye. The CO₂ data have been obtained from NASA’s Orbiting Carbon Observatory-2 (OCO-2) mission, while precipitation data were taken from Integrated Multi-satellite Retrievals for GPM (IMERG). Both datasets have first been brought to the same time intervals; therefore, both temporal and spatial analyses could be conducted. There is a very weak positive correlation between CO₂ and rainfall (r ≈ 0.17). This becomes strongest with a 12-month lag as determined by Linear regression, which also explains only a very small proportion of the variability (R² ≈ 0.03). These results show that changes in precipitation cannot be explained by CO₂ alone. The novelties are temporally in using satellite datasets which cover the same period for Türkiye and applying machine learning models as well as classical statistical methods. Random Forest was the best performer among the tested models (R² = 0.68), suggesting that non-linear methods can capture patterns that simple linear regression misses; however, this result should be interpreted with caution given the short time series and limited set of predictors. This research contains a new local version of an updated CO₂–precipitation relationship with an explanation of its weak role and strongly emphasizes that precipitation cannot be explained by CO2.

Anahtar Kelimeler

• CO₂ concentration
• precipitation analysis
• OCO 2
• IMERG
• climate change
• Türkiye

Destekleyen Kurum

No institutional or financial support was received for this study.

Etik Beyan

This study does not involve human participants, animal testing, or any sensitive data. Therefore, ethical committee approval was not required.

Teşekkür

The authors gratefully acknowledge NASA for providing the OCO-2 and IMERG datasets used in this study.

Kaynakça

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