On 05. June 2015 at 14:15 in Physicums aud A106 will defend Hannes Keernik his doctoral theses "Estimating methods and variability of atmospheric humidity over the Baltic Region and the Arctic".
Dr Hanno Ohvril, University of Tartu, Institute of Physics
Dr Erko Jakobson, University of Tartu, Institute of Physics / Tartu Observatory
Prof Sirje Keevallik (Tallinn University of Technology)
Dr Irina Melnikova (University of St. Petersburg, Russian Federation)
Water vapour provides the largest greenhouse effect on the Earth’s climate. Its distribution influences precipitation, clouds, chemical reactions, incoming solar radiation, outgoing heat, etc. In current meteorological practice, a significant challenge in measurements is related to estimation of its spatial and temporal distribution. However, despite of several estimation techniques for column water vapour amount or simply, precipitable water (PW), no method or model is yet identified as the most accurate or the reference one. This drives a necessity to continuously perform intercomparisons, which help to evaluate strengths and weaknesses, accuracy and biases of different methods.
The aims of the thesis are to investigate long-term variability and trends in vertical humidity profiles in Estonia and Finland since 1980s, describe diurnal cycle of PW in the Baltic Region at summer, estimate the accuracy of different PW methods available in Estonia, and validate global reanalyses humidity profiles for the lowermost Arctic’s atmosphere.
It is revealed that troposphere above Estonia and Finland has become warmer at all altitudes up to 7 km and more moist below the altitude of 2 km. The diurnal cycle of PW depends on whether the area of investigation is located above the Baltic Sea and larger lakes, or above the land. Humidity content above the water reaches a peak and decreases to the minimum at midnight and late evening, respectively. Above the land the peak is reached in the evening and the minimum is detected in the morning. The study suggests that besides radiosonde, as a traditional meteorological tool, the most reliable PW estimation can be made by GPS.