Kazım Kaba

This study examines the spatial and temporal dynamics of light pollution in Erzurum, Türkiye, by integrating satellite-based VIIRS Night-time Light (NTL) data with ground-based Sky Quality Meter (SQM) observations. A logarithmic regression model was developed to quantify the relationship between radiance and SQM readings at 25 locations in 2021, revealing a strong correlation (R² = 0.722). This confirms that satellite data reliably represent measurements taken directly on-site. By applying the model to VIIRS datasets from 2014, 2021, and January 2025, spatial maps were produced to visualize the increasing trend of artificial lighting. Change detection analysis revealed substantial radiance growth, particularly in the northern and southeastern urban areas. These findings underscore the escalating impact of light pollution and highlight the urgent need for effective mitigation strategies.

Atmosferde akışkan hava içinde sıvı ve/veya katı halde asılı bulunan parçacıklar “Atmosferik Aerosol” olarak tanımlanmaktadır. Aerosol hava, iklim, iklim değişikliği, hava kalitesi, halk sağlığı ve astronomi gibi pek çok disiplini etkileyen önemli bir olgudur. Bu çalışmada uzaktan algılama verileriyle İstanbul ili için atmosferik aerosollerin konumsal, zamansal ve spektral özellikleri incelenmiştir. Bu kapsamda İstanbul’un uzun dönem ortalama Aerosol Optik Derinliği (AOD), Angstrom Katsayısı, spektral AOD ve zamansal (aylık, mevsimlik ve yıllık) haritaları üretilerek konumsal, spektral ve zamansal değerlendirmeler yapılmıştır. Çalışmada Suomi-NPP uydusundaki VIIRS algılayıcısından elde edilen aerosol verileri kullanılmıştır. Bu çalışma ile İstanbul için nispeten fazla detay içeren yüksek çözünürlükte, alansal ve zamansal sürekliliğe sahip, en güncel ve pek çok disiplinde yapılan çalışmalara katkı sağlayacak AOD haritaları sunulmuştur. İstanbul ilinin yüksek AOD değerleri kentin güneyinde Marmara Denizi kıyı şeritleri ve nüfus yoğunluğunun yüksek olduğu kıyıya yakın yerler ile Kuzeyde Sarıyer kıyıları ve nispeten Karadeniz’in kara ile buluştuğu kıyı kesimleridir. Kara üzerinde kentin nüfus yoğunluğu ve bitki örtüsü ile ilintili bir AOD değişimi vardır.

In this study, we have presented the results of the precipitable water vapor (PWV) for the Eastern Anatolia Observatory (in Turkish: Doğu Anadolu Gözlemevi, the acronym is DAG) site in Erzurum, Türkiye. The DAG has Türkiye’s largest and the first near infrared (NIR) telescope with a mirror diameter of 4 meters at the altitude of 3170 m. The DAG telescope is going to take the first light in the end of summer 2024. This study is focused on the examining of the precipitable water vapor data for the NIR observations at the DAG. In this context, the NWC SAF Total Precipitable Water (TPW) data obtained by both the satellite based and the radiosonde balloon validated with six radiosonde stations were examined by temporal, vertical and horizontal analyses for the DAG site between June 2019 to December 2020. The results obtained from these analyzes indicate that the mean and median TPW values at the DAG site were approximately 7 mm and the minimum and maximum values were 0.59 mm and 24.12 mm, respectively. The monthly median TPW values at the DAG site varied between approximately 3-10 mm, with a decreasing trend from June to January and an increase in the first seven months of 2020. These results also indicate that the TPW data obtained by its 15 minutes temporal resolution, aligns closely with the radiosonde measurements. Furthermore, the values of PWV at both lower and upper levels of the atmosphere are minimal while the values increase slightly in the middle layer of the atmosphere. As a result, the effective monitoring of the PWV in a site would result in the generation of higher quality astronomical IR observations and be important in terms of the optimum operating cost for an observatory.

Sunshine duration (SD) is one of the critical meteorological parameters used in different fields of application such as climate, renewable energy and agriculture. In this respect, determination and/or estimation of the temporal and spatial variability of SD is critical. Meteorological satellite data/products can be used for estimating SD and in constructing their maps due to their frequent observation of large areas at once. In this study, a multilayer perceptron type artificial neural network model was built to estimate the monthly mean SD for Türkiye using the EUMETSAT CM SAF (Satellite Application Facility on Climate Monitoring) CFC (Cloud Fractional Coverage) and CTY (Cloud Type) data, GMTED2010 (Global Multi-resolution Terrain Elevation Data) data, month number and daylength. The datasets of 45 stations, spanning nine years (2005–2013), were used for training the model and 12 stations for testing and validating the simulated values. We have compared the results of our model with the ground-measured values for the whole period under consideration and the root mean square error (RMSE), mean absolute error (MAE), mean bias error (MBE) and the coefficient of determination (R²) were found as 0.7803 h, 0.6206 h, 0.1751 h and 0.9387, respectively. It has been shown that using the new generation cloud products such as CFC and CTY, elevation data such as GMTED2010 and daylength, it is possible to predict the SD for regions under the coverage of the satellite, in case no measurement is possible or may be unreliable, without needing any measured meteorological data.

Sunshine duration (SD) is one of the critical meteorological parameters used in different fields of application such as climate, renewable energy and agriculture. In this respect, determination and/or estimation of the temporal and spatial variability of SD is critical. Meteorological satellite data/products can be used for estimating SD and in constructing their maps due to their frequent observation of large areas at once. In this study, a multilayer perceptron type artificial neural network model was built to estimate the monthly mean SD for Turkey using the EUMETSAT CM SAF (Satellite Application Facility on Climate Monitoring) CFC (Cloud Fractional Coverage) and CTY (Cloud Type) data, GMTED2010 (Global Multi-resolution Terrain Elevation Data) data, month number and daylength. The datasets of 45 stations, spanning nine years (2005–2013), were used for training the model and 12 stations for testing and validating the simulated values. We have compared the results of our model with the ground-measured values for the whole period under consideration and the root mean square error (RMSE), mean absolute error (MAE), mean bias error (MBE) and the coefficient of determination (R²) were found as 0.7803 h, 0.6206 h, 0.1751 h and 0.9387, respectively. It has been shown that using the new generation cloud products such as CFC and CTY, elevation data such as GMTED2010 and daylength, it is possible to predict the SD for regions under the coverage of the satellite, in case no measurement is possible or may be unreliable, without needing any measured meteorological data.

Doğu Anadolu Gözlemevi (DAG) projesi 2011 yılında Erzurum’da başlatılmıştır. DAG’da 2021 yılı sonunda ilk ışığın alınmasıyla Türkiye'nin en büyük (4 m) optik ve ilk kızılötesi teleskobunun kurulum sürecini tamamlaması planlanmaktadır. Yer tabanlı astronomik gözlemevleri için bulutluluk en hayati atmosferik parametredir. Bulutluluk oranı, bulut türleri ve bulut değişimi yer tabanlı bir gözlemevinde astronomik gözlemlerin yapılmasını kısıtlayabilir veya tamamen engelleyebilir. Bu nedenle bu çalışma DAG yerleşkesinin bulutluluk değerlerine odaklanmıştır. Bu kapsamda DAG yerleşkesi için bulutluluk değerleri analiz edilerek yerleşkenin yıllık açık gün sayıları belirlenmiştir. Bu amaç için çalışmamızda sabit yörüngeli meteorolojik uydu olan ve Türkiye’yi de kapsayan METEOSAT uydu verileri kullanılmıştır. EUMETSAT’ın (European Organisation for the Exploitation of Meteorological Satellites; Avrupa Birliği Meteorolojik Uydu İşletme Teşkilatı) denetim ve koordinasyonunda olan CM SAF (Satellite Application Facility on Climate Monitoring; İklim Yönetimi Üzerine Uydu Uygulama Birimi), METEOSAT verilerinden iklimsel çalışmalar için atmosferimize ait çeşitli veri setleri üretmektedir. Bu verilerden biri olan ve 1991 - 2015 yılları arasını kapsayan CFC (Cloud Fractional Cover; Oransal Bulut Kapalılığı) verisinin öncelikle Türkiye için tutarlılık testi yapılarak ürünün başarımı araştırılmıştır. Test sonuçları bu ürünün tutarlılığının bazı kentlerimiz (Adana, Ankara ve Erzurum) için nispeten düşük kaldığını göstermiştir. Sonraki aşamada DAG için CFC verisinden saatlik, günlük, aylık, mevsimlik ve yıllık bulutluluk analizleri yapılarak DAG yerleşkesinin açık gün sayısı belirlenmiştir.

Eastern Anatolia Observatory (DAG) project was initiated in Erzurum/Turkey in 2011. DAG will have Turkey’s largest (4 m) and first infrared telescope. The installation process is planned to be by taking its first light in the end of 2021. This study was focused on a new analysis method about the atmospheric properties of DAG site in terms of the cloudiness as known the most vital atmospheric parameter for ground-based astronomical observatories. In this regard, the cloudiness for DAG site is comprehensively examined using the “Cloud Mask” (CMa) and “Cloud Type” (CT) products from Satellite Application Facility on Support to Nowcasting and Very Short-Range Forecasting (NWC SAF). Firstly, the cloudiness and the cloud types over DAG site were determined. Secondly, NWC SAF CMa and CT data have been redefined for astronomical purposes, and the pixel values/meanings in CMa and CT images have been reduced from 6 to 4 and from 21 to 4 pixels, respectively. Thirdly, these new data were used to define a new index named as “Astronomical Clearness Index” (ACI), and finally, the observable days for DAG site were determined using this newly defined index.