The city of Kasserine, had the lowest minimum temperature in Tunisia in 2019. That year, the area recorded a minimum of minus 4.1 degrees Celsius. The capital city, Tunis-Carthage, registered a minimum of 4.1 degrees Celsius in the same year. On the other hand, the highest minimum temperatures were in Kelibia and Mahdia.

The cities of Medenine and Tozeur recorded the highest maximum temperature in Tunisia in 2020. That year, the areas recorded a peak of 46.7 degrees Celsius. On the other hand, the lowest maximum temperature in the country was registered in Mahdia at around 34.5 degrees Celsius.

Temperature in Tunisia decreased to 21.21 celsius in 2023 from 21.44 celsius in 2022. This dataset includes a chart with historical data for Tunisia Average Temperature.

Tunisia Heating Degree Days data was reported at 1,325.520 Degrees Celsius in 2020. This records a decrease from the previous number of 1,628.280 Degrees Celsius for 2019. Tunisia Heating Degree Days data is updated yearly, averaging 1,642.850 Degrees Celsius from Dec 1970 (Median) to 2020, with 51 observations. The data reached an all-time high of 2,214.400 Degrees Celsius in 1973 and a record low of 1,242.700 Degrees Celsius in 2016. Tunisia Heating Degree Days data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Tunisia – Table TN.World Bank.WDI: Environmental: Climate Risk. A heating degree day (HDD) is a measurement designed to track energy use. It is the number of degrees that a day's average temperature is below 18°C (65°F). Daily degree days are accumulated to obtain annual values.;World Bank, Climate Change Knowledge Portal. https://climateknowledgeportal.worldbank.org;;

Tunisia Maximum 5-day Rainfall: 25-year Return Level data was reported at 0.941 mm in 2050. Tunisia Maximum 5-day Rainfall: 25-year Return Level data is updated yearly, averaging 0.941 mm from Dec 2050 (Median) to 2050, with 1 observations. The data reached an all-time high of 0.941 mm in 2050 and a record low of 0.941 mm in 2050. Tunisia Maximum 5-day Rainfall: 25-year Return Level data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Tunisia – Table TN.World Bank.WDI: Environmental: Climate Risk. A 25-year return level of the 5-day cumulative precipitation is the maximum precipitation sum over any 5-day period that can be expected once in an average 25-year period.;World Bank, Climate Change Knowledge Portal (https://climateknowledgeportal.worldbank.org);;

The city of Tabarka had the highest rainfall in Tunisia in 2020. That year, the area recorded around 919.6 millimeters of rainfall. The capital city, Tunis-Carthage, registered 505.5 millimeters of rain in the same year. On the other hand, the driest areas were Remada and El-Borma.

========================================================

Dataset: CM-RWL1-O15S16

Daily refugee arrivals and weather data
Italy/Central Med., Oct.2015 - Sept.2016

Release Notes

Copyright (c) 2018 by Harris V. Georgiou

========================================================
Release: Apr 14, 2018

- Version: 1.1a
- Format: .xlsx/.csv/.txt
========================================================

This file contains important information about the
current version of the dataset package.

Downloading and using this material hints that you
accept the EULA/Terms-of-Use (please read carefully).

We welcome your comments and suggestions.

_
WHAT'S IN THIS PACKAGE?

- Overview
- Available file formats
- Files and Datasets
- License Agreement

_
OVERVIEW

Since early January 2015, Europe has witnessed an unprecedented influx of refugees
from regions of war and conflict in the Middle East, primarily Syria, Afghanistan
and Iraq. The rapid allocation of proper resources is the most critical factor in
the success or failure of any rescue and relief operations, especially in the "hot"
zones. In order to do so, proper tools of predictive analytics mus be available,
specifically for forecasting the intensity and, if possible, the location of the
next refugee influx waves, so that the rescue elements and the logistical support
is properly prepared beforehand.

This package contains a set of data regarding daily refugee arrivals at the general
area of the Central Mediterranean Sea, more specifically towards Italy, for the most
intense period of influx waves, from the beginning of October 2015 until the end of
September 2016 (one full year).

The sources of the data are:
1) For daily arrivals (Italy):
UNHCR Refugees/Migrants Emergency Response (Data mashups)
http://data2.unhcr.org/en/situations/mediterranean/location/5205
2) For weather:
Weather Underground Database (mashup of NOAA, aviation, local)
https://www.wunderground.com/about/data

The datasets from (1) have already been used in various publications describing
such predictive analytics models. Detailed description and related conclusions
can be found at:

* Harris V. Georgiou, "Identification of refugee influx patterns in Greece via
model-theoretic analysis of daily arrivals" (9-May-2016),
https://arxiv.org/abs/1605.02784

_
AVAILABLE FILE FORMATS

The datasets are available in the following formats (included):

*.xlsx : MS-Excel/LibreOffice native spreadsheets
*.csv : comma-separated plaintext spreadsheets
*.txt : raw plaintext files with full column headers

These data formats are equivalent, i.e., they contain the exact same
sets of data. Normally, at least one of them should be compatible
with any major programming platform (e.g. Matlab, Octave, R) or any
native programming language for arbitrary handling (e.g. C, Java).

_
FILES AND DATASETS

Root folder: CM-RWL1-O15S16\

Dataset 1: Arrivals\(csv,xlsx)
"Italy-DailyArrivals-Oct2015Sept2016.*"
: Complete data series for refugee influx arrivals for Italy

Dataset 2: Weather\(xlsx,txt)
Habib Bourguiba, Tunisia
Sfax El-Maou, Tunisia
Lampedusa, Italy
Luqa, Malta
Tripoli Mitiga, Libya
: Weather data (temp,wind,gust,w.dir,...) at local airports

The Mitiga airport station at Tripoli, Libya, is the most critical regarding
the construction of analytics and predictive modeling of the daily influx series
towards Italy. However, due to adverse conditions and lack of maintenance,
there are several blocks of consecutive days with missing weather data. Thus,
the other four reliable weather stations in the area should be used to build
regression models for filling-in these gaps.

The satellite map(*) in the \Suppl folder shows the situation of Search & Rescue
(SAR) operations, density of shipwrecks by the end of Sept. 2015, as well as
the location of these weather stations and how these relate spatially to the
target area of Tripoli, which is still the departing spot with the highest
density of boats.

(*) SAR map source: https://blamingtherescuers.org/report/

_
LICENSE AGREEMENT

This program was produced primarily for academic research and educational purposes.
Downloading and using this material implies acceptance of the Creative Commons
License: Attribution-NonCommercial-ShareAlike 4.0 International (BY-NC-SA), 2016.
* http://creativecommons.org/licenses/by-nc-sa/4.0/

Copyright (c) 2018 by Harris V. Georgiou (MSc,PhD) -- http://xgeorgio.info

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