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Report

Teaser, summary, work performed and final results

Periodic Reporting for period 1 - CLARITY (Uncovering information in fluctuating CLimate systems: An oppoRtunity for solving climate modeling nodes and assIst local communiTY adaptation measures)

Teaser

Summary

CLARITY is a multidisciplinary collaboration at the Caâ€™ Foscari University of Venice (UNIVE) Department of Environmental Sciences, Informatics and Statistics (DAIS) deliberated as an attempt to incorporate physical perspectives of complex systems into climate modeling strategies, so as to help advance our understanding of climate variability and improve our ability to simulate climate evolution.

CLARITY is designed around three specific goals:

1) try to deepen the understanding of fluctuations inherent in climate data,
2) try to incorporate obtained and already existent information on observational data dynamics into climate modelling, and
3) try to apply such created analysis and modeling strategies to obtain more accurate models of the microclimatology of the city of Venice.

Worldwide, the city of Venice is of particular importance in terms of urban sustainability and resilience. As a part of this project we were applying our collaborative knowledge to develop more accurate models to assess the impact of climate change on future ultraviolet radiation (UVR) exposure of cityâ€™s populations. We aimed to achieve the results that can be useful to plan the future of the city and, if successful, could be replicated in other communities in Europe.

Work performed

The first specific objective (SO1) of CLARITY was to deepen the understanding of fluctuations inherent in climate data.
In the course of CLARITY realization, and in order to accomplish realization of this specific objective, we focused our analysis on: a) two prominent sources of global temperature monthly data, the UK Meteorological Office HadCRUT4 and the NASA Goddard Institute for Space Studies (GISS) LOTI gridded monthly historical records, b) land stations absolute temperature monthly records, c) historical daily flow records of the river Danube in the vicinity of the two dams â€“ Iron Gates or Djerdap I and II, and d) ambient UVR in schools and public places in the city of Venice and its surrounding (islands and the mainland) and personal exposure to solar UVR collected by the groups of tourists visiting the city of Venice during the summer of 2017.
We used the 2nd order DFA analysis in combination with the wavelet transform power spectral (WTS) analysis to investigate our data. We applied both monofractal and multifractal formalisms to study our data.
Figure 1. attached to this report gives an example the results of the scaling analysis of the global temperature data.
Outputs:
- two research articles, outlying the new methodological procedures and framework used in data analysis of global temperature data, published in the peer-reviewed journals:
StratimiroviÄ‡, Dj., Sarvan, D., MiljkoviÄ‡, V. & BlesiÄ‡, S. Analysis of cyclical behavior in time series of stock market returns. Commun. Nonlinear Sci. Numer. Simul. 54, 21â€“33 (2018) (CiteScore2017: 3.37, citations: 2),
Sarvan, D., StratimiroviÄ‡, Dj., BlesiÄ‡, S., DjurdjeviÄ‡, V., MiljkoviÄ‡, V. & AjtiÄ‡ J. Dynamics of beryllium-7 specific activity in relation to meteorological variables, tropopause height, teleconnection indices and sunspot number. Phys. A Stat. Mech. its Appl. 469, 813â€“823 (2017). (CiteScore2017: 2.28, citations: 2);
- one research article submitted to the peer-reviewed journal:
BlesiÄ‡, S., Zanchettin, D. & Rubino, A. Heterogeneity of scaling of the observed global temperature data, submitted to the Journal of Climate (IF2016: 4.161);
- eight oral presentations given at five international conferences and two international workshop: European Geosciences Union 2017 and 2018 annual conferences, Data Science Challenges 2016 and 2017 annual conference, the SIGMAPHI2017 â€“ European Physics Society International Conference on Statistical Physics, and THEMES 2016 and 2017 workshop;
- three research articles in preparation to be submitted to the peer-reviewed scientific journals (the Journal of Hydrology, the Journal of Statistical Physics, and the Journal of Exposure Science and Environmental Epidemiology);
- a public presentation of results of the analysis of Venetian tourists data held at the occasion of the Veneto Researcherâ€™s Night 2017: BlesiÄ‡, S., (A Sunny Day of) A Venetian Tourist. Natural History Museum, Veneto Researcherâ€™s Night 2017, http://www.venetonight.it/a-sunny-day-of-a-venetian-tourist/;
- a radio podcast at the Radio Caâ€™Foscari on the of results of the analysis of Venetian tourists data at www.radiocafoscari.it.

This part of CLARITY brought together research groups from South Africa, New Zealand, Serbia, and Italy.

The second specific objective (SO2) of CLARITY was to incorporate information on data dynamics into climate modelling strategies developed by DAIS\'s research group of CLARITY realization supervisor.
In the summer of 2017 the CLARITY DAIS\'s group finalized their modelling approach based on an unified statistical Bayesian framework. They used it in combination with the coupled ROMS-PISCES global ocean biogeochemical model.
As a part of CLARITY realization, two research tasks were realized, connected to this modelling efforts: 1) analysis of modelled Tropical Atlantic fisheries data, and 2) production of recommendations, based on the results of scaling analysis, for the changes in ROMS-PISCES simulation. As an output

Final results

The methodology developed and the results obtained in the framework of CLARITY have multiple contributions to both the time series analysis and complex systems modelling literature, and to the efforts to build up meaningful population solar UVR exposure patterns that could further be used in epidemiology and in public health assessments and policies. CLARITY firstly addresses a number of methodological and technical issues related to the estimation and understanding of scaling in complex climate data. It furthermore highlights the usefulness of time series analysis methods used to suggests additional modelling options in the framework of complexity of climate. Finally, it provides an open source valuable data of great potential usefulness for future assessments of individual exposure to the solar UVR and its multiple beneficial and adverse health effects.