Campania Climate Hub
The Campania Climate Hub is the climate service on Dataclime developed for the Campania Region to interactively explore the regional climate framework and support the planning of climate change adaptation policies and interventions. The service collects a set of climate indicators selected through co-design with regional offices, consistent with the national adaptation guidelines.
Objectives
- Understanding how the climate is changing in Campania.
- Evaluating the evolution of extreme events relevant to territories and sectors.
- Supporting analysis and technical documents with downloadable maps and data.
The service allows users to explore dynamic maps at the regional scale, consult results at the provincial and municipal scales (ISTAT base units), select indicators, periods and administrative levels, and download outputs in CSV/PNG.
All data used in this product comes from public and open access sources. In each specific section you can consult the terms of use of the different data sources used.
Complete ReportVHR-REA_IT Dataset
High resolution climate data. This section provides a comprehensive mapping of climate indicators defined under the Regional Climate Framework over the reference period (1981-2010 and 1991-2020) using the very high-resolution dataset (approximately 2 km) developed by the CMCC (VHR-REA_IT). The maps allow us to identify spatial trends in climate indicators and analyze variations up to the municipal scale, highlighting any localized critical issues.
Filters
Model Data
VHR-REA_IT
VHR-REA_IT
Download the selected map in Zip format.
Accumulated Precipitation in wet days (PRCPTOT)
(PRCPTOT)
Daily precipitation sum in wet days (days with precipitation greater than or equal to 1 mm).
Season: Yearly
Measurement unit: mm
Time series of the selected indicator
The time series shows the trend of anomalies from 1981 to 2024. Anomalies represent the deviation from the baseline climatology calculated over the reference period (1981-2010 or 1991-2020). The thick black line represents the trend calculated using a 5-year moving average.
| Value | Standard deviation |
|---|---|
| 828 mm | 244 mm |
Stripes of the selected indicator
The "Climate stripe" shows the trend of annual anomalies of the selected indicator over time, from 1981 to 2024. Anomalies are calculated against a standard reference period (1981-2010 or 1991-2020). The colour variation of the stripes (on a scale from blue to red) is directly related to the intensity of the indicator’s anomaly. The stripes visually represent the deviation of each year from the thirty-year reference average.
Scarica il file Zip della mappa selezionata.
Cite Dataclime
Users are kindly requested to mention the use of Dataclime, cite the website www.dataclime.com, the CMCC Foundation and the references listed below in any publication or presentation resulting from the use of this data.
The information provided on this page was generated using the VHR-REA_IT
(Very High Resolution Dynamical Downscaling of ERA5 Reanalysis over Italy by COSMO-CLM)
dataset, and freely available from the CMCC DDS.
Users of this content are kindly encouraged to consult official sources such as
scientific papers (Raffa et al., 2021, https://doi.org/10.3390/data6080088)
and CMCC DDS (https://doi.org/10.25424/cmcc/era5-2km_i).
It is important to note that the CMCC Foundation and the Dataclime developers assume
no responsibility for the use, interpretation, or consequences of the data presented
in any material. Users are advised to exercise due diligence in their applications
and interpretations of the data and are encouraged to consult the official documentation
provided by Dataclime and the CMCC Foundation for citation and acknowledgment guidelines.
The user assumes full responsibility, excluding any form of liability on the part of
the Foundation, for any decision taken and for any direct or indirect damage that may
result from the use of the data and information contained on this site, and will
indemnify and hold the Foundation harmless from any claims that may be made, including
by third parties.