Advancing understanding, modelling and prediction of extreme events in a changing climate

Expected Outcome: Project results are expected to contribute to all of the following expected outcomes: Improved understanding of past and present extreme events in the context of climate change in Europe and globally, as well as the interaction between different hazards, their cumulative and/or cascading effects. Enhanced seamless prediction and projection modelling and attribution capabilities for extreme events and their likelihood to support preparedness, response and resilience to climate change by EU and national and regional actors. The EU Union Preparedness Strategy, the EU Adaptation Strategy and the European Climate Adaptation Plan can act as a guidance in these efforts. Up-to-date contributions towards latest climate science, risk assessments, adaptation strategies and policies and improved early warning systems for single and multi-hazard events. Scope: Climate change is inte… devamı

1. %48
   BARBAROS GÖNENÇGİL

   Profesörİstanbul Üniversitesi

   Ortak konular: Climate variability and models

   Örtüşen yayınlar: Forest fires in southern Turkey July-August 2021 (2023) · Assessing Agricultural Vulnerability to Climate Change in High-Altitude Himalayan Regions: A Composite Index Approach in Lahaul and Spiti, India (2025)

2. %48
   MUSTAFA NURİ

   Doktor Öğretim Üyesiİstanbul Gelişim Üniversitesi

   Ortak konular: Climate variability and models · Climate change impacts on agriculture

   Örtüşen yayınlar: Influence of Climate Change on the Flood Disasters in Bursa, Turkey (2021) · Frequency analyses of extreme precipitation events in Western Black Sea Basin (Turkey) based on climate change projections (2019)

3. %44
   DENİZHAN MERSİN

   Araştırma GörevlisiYaşar Üniversitesi

   Ortak konular: Climate variability and models

   Örtüşen yayınlar: Historical Trends Associated with Annual Temperature and Precipitation in Aegean Turkey, Where Are We Heading? (2022)

Uyum oranı kodla, her istekte hesaplanır. Çağrı metni (başlık, anahtar kelimeler, resmi açıklamanın başı) şu üç kaynakla karşılaştırılır: akademisyen profiliyle anlamsal yakınlık (%50), YÖKSİS anahtar kelimeleri ve OpenAlex konularındaki ortak ayırt edici terimler (%25) ve yayın içeriği — başlıklar, İngilizce özetler ve bunların Türkçe çevirileri (%25). Çeviriler sayesinde Türkçe çağrılar İngilizce yayınlarla da eşleşir. Yaygın kelimeler düşük ağırlıklıdır; %40 altı gösterilmez. Bir konu önerisidir; başvuru uygunluğu, kapasite ya da başarı değerlendirmesi değildir. Gizli profiller listelenmez.