IUFRO 7.01CONFERENCE Adaptation of Forest Ecosystems to Air Pollution and Climate Change, Antalya, Turkey, 22 - 26 March 2010, pp.94
Long-term systematic observations are of vital importance in order to understand natural variability of climate, determine human impacts of climate system, parameterise the main processes required in models and verify model simulations. Instrumental records span only a tiny fraction of the Earth's climatic history and so provide inadequate perspective on climatic variation and evolution of climate today. A longer perspective on climatic variability can be obtained by the studies of natural phenomena which are climate-dependent, and which incorporate in to their structure a measure of this dependency. Tree-rings as a proxy records have their precise dating to the calendar year, which allows them to be compared directly with instrumental records.
Dendroclimatological studies, performed to understand past climate using tree ring records in Turkey, revealed mainly reconstruction of spring-summer precipitation, which is the most important limiting factor for the growth of tree rings in this region. Although these studies revealed past dry and wet years in many parts of Anatolia, a temperature reconstruction in Anatolia is still missing. For that reason the goals of this study are: (1} to built a new site chronologies for Abies nordmanniana and Picea orienta/is (2} to perform temperature reconstruction for Artvin, and then describe past cool and warm events.
Stem disks were taken from Abies nordmanniana (Stev.) Mattf. and Picea orienta/is (L.} Link. trees
from Artvin - Borkc;:a - Baler - Kayabar Plateau and Kaynarca sites by chainsaw. The width of each annual ring on cross-sections was measured with the precision to the nearest 0.01mm. Because of high correlation between individual series, a site chronology was built including Abies nordmanniana and Picea orienta/is tree ring information for Baler. To identify climate-tree growth relationship, response function analysis was calculated. Monthly precipitation and temperature records obtained from climate dataset CRU TS 2.1for the grid 40°00'-41°50' N, 40°.50'-42°.50' E were used as climate data. The response function analysis identified that March temperature as the most appropriate seasonal predictand for reconstructions. Based on this result, March temperature reconstruction for the period between AD1620-2006 were built, and extreme events were identified. In this period, the coldest year was determined to be AD 1680, and the warmest year was determined to be AD 1702 in March.