Posts by Collection

publications

Future Holiday Climate Index (HCI) Performance of Urban and Beach Destinations in the Mediterranean

Published in Atmosphere, 2020

HCI scores for the reference (1971–2000) and future (2021–2050, 2070–2099) periods were computed with the use of two latest greenhouse gas concentration trajectories, RCP 4.5 and 8.5, based on the Middle East North Africa (MENA) Coordinated Regional Downscaling Experiment (CORDEX) domain and data.

Recommended citation: Demiroglu, O. C., Saygili-Araci, F. S., Pacal, A., Hall, C. M., & Kurnaz, M. L. (2020). "Future Holiday Climate Index (HCI) Performance of Urban and Beach Destinations in the Mediterranean." Atmosphere. 11(9), 911. https://www.mdpi.com/2073-4433/11/9/911

Earth System Model Evaluation Tool (ESMValTool) v2.0 – diagnostics for extreme events, regional and impact evaluation, and analysis of Earth system models in CMIP

Published in Geoscientific Model Development, 2021

This paper complements a series of now four publications that document the release of the Earth System Model Evaluation Tool (ESMValTool) v2.0.

Recommended citation: Weigel, K., Bock, L., Gier, B. K., Lauer, A., Righi, M., Schlund, M., Adeniyi, K., Andela, B., Arnone, E., Berg, P., Caron, L.-P., Cionni, I., Corti, S., Drost, N., Hunter, A., Lledó, L., Mohr, C. W., Paçal, A., Pérez-Zanón, N., Predoi, V., Sandstad, M., Sillmann, J., Sterl, A., Vegas-Regidor, J., von Hardenberg, J., and Eyring, V. (2020). "Earth System Model Evaluation Tool (ESMValTool) v2.0 – diagnostics for extreme events, regional and impact evaluation, and analysis of Earth system models in CMIP.", Geosci. Model Dev., 14, 3159–3184. https://gmd.copernicus.org/articles/14/3159/2021/

Detecting Extreme Temperature Events Using Gaussian Mixture Models

Published in Journal of Geophysical Research: Atmospheres, 2023

Extreme temperature events are detected with Gaussian Mixture Models to follow a multimodal rather than a unimodal distribution.

Recommended citation: Paçal, A., Hassler, B., Weigel, K., Kurnaz, M. L., Wehner, M. F., & Eyring, V. (2023). Detecting Extreme Temperature Events Using Gaussian Mixture Models. Journal of Geophysical Research: Atmospheres, 128, e2023JD038906. https://doi.org/10.1029/2023JD038906

talks

Determination of Exposures of Mediterranean Touristic Resources by Using Regional Climate Modeling

Published:

Summer tourism in the Mediterranean Basin is one of the most important contributors to the countries’ GDPs, and is highly dependent on the climatic conditions. In this study, it is aimed to determine the exposures of the most visited touristic resources in the Mediterranean Basin via Tourism Climate Index [1] which is an ideal indicator of tourism exposure to the hazard of changes to the mean climate [2]. For this purpose, the outputs of the MPI-ESM-MR global climate model of the Max Planck Institute for Meteorology are downscaled to 50km by the use of Regional Climate Model (RegCM4. 4) of the Abdus Salam International Centre for Theoretical Physics (ICTP). To make future projections for the period of 2021-2050 and 2070-2099 with respect to the reference period of 1971-2000, RCP 4.5 and RCP 8.5 scenarios are used. Tourism Climate Index (TCI) for projected periods are computed by using the 30-year monthly mean temperature, relative humidity, precipitation, wind and sunshine outputs of the RegCM4. 4. Thereafter, the TCI values are plotted to see the changes throughout the months.

Detecting Extreme Temperature Events Using Gaussian Mixture Models

Published:

Extreme events are rare atmospheric phenomena that cause significant damage to humans and natural systems, but detecting extreme events in the future in a changing climate can be challenging. Traditionally, temperature distributions were assumed to follow a normal distribution and certain thresholds were used to define extreme events. However, the mean and the variance of temperatures are expected to change in a future climate, which might limit the application of traditional methods for detecting extreme events.

teaching

Teaching experience 1

Undergraduate course, University 1, Department, 2014

This is a description of a teaching experience. You can use markdown like any other post.

Teaching experience 2

Workshop, University 1, Department, 2015

This is a description of a teaching experience. You can use markdown like any other post.