TROPICAL NIGHTS

Descrizione 1
Update date
Authors

Piero Fraschetti, Francesca Lena, Walter Perconti, Emanuela Piervitali, Giulio Settanta

Abstract

The indicator describes the trend in extreme heat events in Italy, specifically representing the number of days with a minimum daily air temperature exceeding 20 °C. In 2023, an increase of approximately 14 tropical nights was observed compared to the climatological average for the 1991–2020 reference period.

Description

The occurrence of extreme temperature events and the presence of significant trends are assessed through the analysis of absolute minimum and maximum daily air temperature values. Specifically, the indicator “tropical nights”, as defined by the CCL/CLIVAR Working Group on Climate Change Detection, refers to the number of days when the daily minimum air temperature remains above 20 °C.

Purpose

The annual time series of the average number of tropical nights, expressed as the deviation from a climatological baseline, enables the estimation of the frequency of extreme heat events and the assessment of significant trends over time.

Policy relevance and utility for users
It is of national scope or it is applicable to environmental issues at the regional level but of national relevance.
It can describe the trend without necessarily evaluating it.
It is simple and easy to interpret.
It provides a representative picture of environmental conditions, environmental pressures, and societal responses
It provides a basis for international comparisons.
Analytical soundness
Be based on international standards and international consensus about its validity;
Be theoretically well founded in technical and scientific terms
Presents reliability and validity of measurement and data collection methods
Temporal comparability
Spatial comparability
Measurability (data)
Adequately documented and of known quality
Updated at regular intervals in accordance with reliable procedures
Readily available or made available at a reasonable cost/benefit ratio
An “adequate” spatial coverage
An “appropriate” temporal coverage
Main regulatory references and objectives

The indicator is not directly linked to any regulatory or legislative framework

DPSIR
State
Impact
Indicator type
Descriptive (A)
References

https://scia.isprambiente.it; 

SNPA, 2024, Il clima in Italia nel 2023; 

ISPRA, 2022, I normali climatici 1991-2020 di temperatura e precipitazione in Italia;

ISPRA, 2018, Variazioni della temperatura in Italia: estensione della base dati e aggiornamento della metodologia di calcolo;

ISPRA, 2016, Controlli di qualità delle serie di temperatura e precipitazione; 

ISPRA, 2015, Valori climatici normali di temperatura e precipitazione in Italia; 

ISPRA, 2014, Focus on "Le città e la sfida ai cambiamenti climatici"; 

ISPRA, 2013, Variazioni e tendenze degli estremi di temperatura e precipitazione in Italia; 

ISPRA, 2012, Elaborazione delle serie temporali per la stima delle tendenze climatiche;

Peterson T.C ., Folland C , Gruza G, Hogg W, Mokssit A e Plummer N., 2001, Report on the activities of the Working Group on Climate Change Detection and Related Rapporteurs 1998-2001.;

World Meteorological Organization, Rep. WC DMP-47, WMO -TD 1071, Geneva, Switzerland, 143 pp.; 

Toreti A. e Desiato F., 2007, Changes in temperature extremes over Italy in the last 44 years, Int. J. Climatology, DO I 10.1002/joc.1576; 

APAT-OMS, 2007, Cambiamenti climatici ed eventi estremi: rischi per la salute in Italia.

Further actions

Improvements in the estimation of tropical nights in Italy could stem from expanding the indicator calculation system to include additional sources of raw temperature data, in order to enhance the availability of historical temperature series that meet the criteria of duration, continuity, and completeness of time series.

Frequenza di rilevazione dei dati
Annuale
Fonte dei dati
ISPRA
Data availabilty

SCIA – Sistema nazionale per l’elaborazione e diffusione di dati climatici (https://scia.isprambiente.it)

Spatial coverage

Italy
Time coverage

1961-2023
Processing methodology

To determine whether a given calendar day qualifies as a tropical night, the daily minimum air temperature is compared with the threshold of 20°C. This requires access to validated daily minimum temperature data. The SCIA system (National System for the Processing and Dissemination of Climate Data) processes raw meteorological data and outputs a daily minimum temperature value, which is accepted as valid only if it passes quality control checks. If the daily minimum temperature is validated, it is compared with the 20°C threshold to establish whether the day is classified as a tropical night. The annual indicator value is calculated as the total number of tropical nights recorded in a given year. This annual value is considered valid only if at least 75% of the daily data for that year are available and validated. The climatological baseline used to calculate anomalies has been updated to the most recent 30-year reference period, 1991–2020. This choice aligns with the latest recommendations from the World Meteorological Organization (WMO), which advises updating climatological baselines every ten years for operational climatology purposes.

Update frequency
Year
Qualità dell'informazione

The indicator adequately describes the trend of extreme heat events in Italy. The calculation of the indicator follows a standardized methodology and adheres to the general criteria outlined by the World Meteorological Organization (WMO). The methodology is consistent over time and space. Both the input data and the indicator itself undergo validity checks carried out by the entities responsible for the raw data (CRA-CMA (Research Unit for Climatology and Meteorology Applied to Agriculture), Synoptic Network (AM and ENAV), Regional Networks) and by the SCIA system (National System for the Processing and Dissemination of Climate Data) of ISPRA. The use of average anomaly values across the entire national territory allows for an adequate response to the information needs related to this indicator. The measurement stations from which the anomaly is calculated and the ongoing trend is estimated meet the requirements of duration, continuity, completeness, and homogeneity of the time series.

State
Poor
Trend
Negative
State assessment/description

In 2023, an increase of about 14 tropical nights was observed compared to the average value calculated for the reference thirty-year period 1991-2020.
Trend assessment/description

In the last 10 years, tropical nights have consistently been higher than the reference thirty-year period 1991-2020, with the exception of 2014 and 2016. Since the main international climate change strategies and political programs aim to counteract the ongoing warming of the climate system, the evaluation of an unfavorable trend and the assignment of the corresponding icon can be considered in terms of deviation from this goal.
Comments

The time series of annual average anomalies for the number of tropical nights in Italy indicates that 2023, with an increase of approximately 14 nights compared to the average value calculated for the reference thirty-year period (1991-2020), ranks 3rd among the hottest years in the entire series (Figure 1

Data
Headline

Figure 1: Time series of annual mean anomalies of the number of tropical nights in Italy compared to the 1991-2020 reference value.

Data source

ISPRA

English