The statistic illustrates the average monthly maximum temperature in Italy in selected months between August 2017 and March 2019. According to data, the lowest maximum temperature, 8.2 degrees Celsius, was measured in February 2018.

Abstract

The AGROCLIMA gridded dataset provides the values of the main agroclimatic variables (minimum, maximum and mean temperature, precipitation and reference evapotranspiration according to the Hargreaves-Samani equation) for the WMO Climate Standard Normal period 1981-2010 (CliNo8110) across the Italian domain. The dataset is provided at a 0.14°/0.10° longitude and latitude resolution (approximately 10 km) with a monthly, seasonal and annual climate timestep granularity. Moreover, it includes climate's statistics at 10-days temporal resolution at Italian NUTS 0, 2 and 3 levels for minimum and maximum temperature, and precipitation. All data have been obtained from the historical daily weather series stored in the METEOGRID dataset, covering 1961 to 2017 period, that derives from the national agro-meteorological database of the Italian Ministry of Agriculture. The METEOGRID data are freely accessibile by APIs provided by the developer portal of the AgriDigit Project (AgriDigit-Agromodelli, DM n. 36502 of 20/12/2018).

Further details about the AGROCLIMA gridded dataset are published on the specific page of the Italian National Rural Network website (Italian language).

The file ‘AGROCLIMA_grid_cells.csv’ contains metadata for each grid cell centre, such as the identifier code (ID_CELL), the altitude (ELEVATION, meters above sea level), the coordinates (LONGITUDE and LATITUDE, in E.P.S.G. 4326), the codes of the Nomenclature of territorial units for statistics at levels 2 and 3 (NUTS 2_CODE and NUTS 3_CODE), and the province name (NUTS 3_NAME).

Attached content

The dataset is composed by 3 files:

• AGROCLIMA_grid_cells.csv
• AGROCLIMA_gridded_data_v1.1.zip
• AGROCLIMA_Italian_NUTS_levels_v1.1.zip

Daily minimum and maximum temperature observations collected in Padua, Italy, between 1774 and 2024 and daily mean temperatures between 1725 and 1773, are reported. By means of the paleo-reanalysis dataset ModE-RA, it has been possible to homogenize the ancient part of the series, 1725-1773, mainly composed of only 1 or, less frequently, 2 or 3 observations per day, to the rest of the series. The period 1774-2024 has been homogenized by means of trasfer functions to the most recent period. The original observations and the final complete corrected time series with the associated metadata are reported.PD_Poleni contains daily temperatures at noon derived from the observations of Giovanni Poleni and his son Francesco between 12/01/1725 and 31/12/1764;PD_Morgagni contains daily temperatures at noon derived from the observations of Giambattista Morgagni between 01/01/1740 and 31/12/1768;PD_Toaldo contains daily temperatures near the sunrise collected by Giuseppe Toaldo between 01/05/1766 and 31/12/1773;PD_Specola contains daily minimum and maximum temperatures collected at the Astronomical Observatory "Specola" between 01/01/1774 and 31/12/1955;PD_Idrografico contains daily minimum and maximum temperatures collected at the Magrini Observatory of the "Ufficio Idrografico" between 01/01/1920 and 31/12/1996;PD_AM contains daily minimum and maximum temperatures collected at the airport of Padua by the Air Force between 01/01/1951 and 29/12/1990;PD_OB contains daily minimum and maximum temperatures collected at the Botanical Garden between 01/01/1980 and 31/12/2024. This is the result of a recent work, for further details see: Stefanini et al. 2023 (https://doi.org/10.3390/cli11120244);PD_hom contains the homogenized daily minimum, maximum and mean temperatures between 12/01/1725 and 31/12/2024, using PD_OB as reference. Metadata are also indicated, reporting the source of each value. The meaning of the metadata codes is reported in PD_hom_metadata.

Daily minimum and maximum temperature measurements collected in Padua, Italy, between 1980 and 2022, are reported. Over this period, the weather station of Padua center underwent many changes, in location or instrument; therefore, some homogeneity tests have been used to identify and remove the effects of these variations and obtain a homogeneous time series. Both absolute and relative tests have been applied and several nearby stations and two reanalysis datasets (ERA5 and MERIDA) have been considered, to enhance the picture of the local situation and provide more robust conclusions. The original observations and the final complete corrected time series with the associated metadata are reported.OB_UNIPD contains daily minimum and maximum temperature collected at the Botanical Garden between 01/01/1980 and 31/12/1993 by the University of Padua;OB_micros_UNIPD contains daily minimum and maximum temperatures collected at the Botanical Garden between 01/10/1993 and 13/12/2001 by the University of Padua using a MICROS weather station;OB_ARPAV contains daily minimum and maximum temperatures collected at the Botanical Garden between 01/05/2000 and 10/03/2019 by ARPAV;CUS_ARPAV contains daily minimum and maximum temperatures collected at the University Sports Center between 11/03/2019 and 30/06/2023 by ARPAV;OB_FINAL_SERIES contains the homogenized daily minimum and maximum temperatures between 01/01/1980 and 30/06/2023, using OB_ARPAV as reference. Metadata are also indicated, reporting the source of each value. The meaning of the metadata codes is reported in OB_FINAL_SERIES_metadataFurther details are available in Stefanini et al. 2023, https://doi.org/10.3390/cli11120244.Corrigendum: the transfer functions reported in the supplementary material of https://doi.org/10.3390/cli11120244 must be replaced with those listed in OB_FINAL_SERIES_metadata.

Chironomid headcapsules were used to reconstruct late glacial and early-Holocene summer temperatures at Lago Piccolo di Avigliana (LPA). Two training sets (northern Sweden, North America) were used to infer temperatures. The reconstructed patterns of temperature change agreed well with the GRIP and NGRIP d18O records. Inferred temperatures were high during the Bølling (ca 19 °C), slowly decreased to ca 17.5 °C during the Allerød, reached lowest temperatures (ca 16 °C) during the Younger Dryas, and increased to ca. 18.5 °C during the Preboreal. The amplitudes of change at climate transitions (i.e. Oldest Dryas/Bølling: 3 °C, Allerød/Younger Dryas: 1.5 °C, and Younger Dryas/Preboreal: 2.5 °C) were smaller than in the northern Alps but similar to those recorded at another site in northeastern Italy. Our results suggest that (1) Allerød temperatures were higher in the southern Alps and (2) higher during the Preboreal (1 °C) than during the Allerød. These differences might provide an explanation for the different responses of terrestrial-vegetation to late glacial and early-Holocene climatic changes in the two regions. Other sites on both sides of the Alps should be studied to confirm these two hypotheses.

Chironomid headcapsules were used to reconstruct late glacial and early-Holocene summer temperatures at Lago Piccolo di Avigliana (LPA). Two training sets (northern Sweden, North America) were used to infer temperatures. The reconstructed patterns of temperature change agreed well with the GRIP and NGRIP d18O records. Inferred temperatures were high during the Bølling (ca 19 °C), slowly decreased to ca 17.5 °C during the Allerød, reached lowest temperatures (ca 16 °C) during the Younger Dryas, and increased to ca. 18.5 °C during the Preboreal. The amplitudes of change at climate transitions (i.e. Oldest Dryas/Bølling: 3 °C, Allerød/Younger Dryas: 1.5 °C, and Younger Dryas/Preboreal: 2.5 °C) were smaller than in the northern Alps but similar to those recorded at another site in northeastern Italy. Our results suggest that (1) Allerød temperatures were higher in the southern Alps and (2) higher during the Preboreal (1 °C) than during the Allerød. These differences might provide an explanation for the different responses of terrestrial-vegetation to late glacial and early-Holocene climatic changes in the two regions. Other sites on both sides of the Alps should be studied to confirm these two hypotheses.

The dataset is the supplementary material for the following journal paper:

Parisse B.*, Alilla R., Pepe A.G., De Natale F., MADIA - Meteorological variables for Agriculture: a Dataset for the Italian Area, Data in Brief, 46 (2023), 108843, 10.1016/j.dib.2022.108843, (https://www.sciencedirect.com/science/article/pii/S2352340922010460)

Abstract

The MADIA gridded dataset provides the series of the main agro-meteorological variables derived from ERA5 hourly surface data, across the Italian domain for the period 1981-2022, and their respective 1981-2010 and 1991-2020 climate normals, as well as the following statistics on the 30-year dekadal values of each variable: absolute minimum and maximum, 5th, 10th, 50th, 90th, 95th percentiles. Temporal and spatial resolutions are 10-daily and 0.25 degrees respectively. The dataset contains time series of minimum, average and maximum air temperature, minimum and maximum air relative humidity, wind speed, solar radiation, precipitation and reference evapotranspiration according to the FAO Penman-Monteith method. The dataset is provided in both NetCDF and csv format. In addition, discovery and description metadata are provided. In order to facilitate the data reuse for computing statistics at Italian NUTS 2 and 3 levels, a complementary vector file is provided which reports the cell weight in terms of fraction covered of each administrative unit considered. Another vector file is included with the ERA5 cell polygons covering the Italian country for visualizing and mapping csv data.

A daily version of the MADIA dataset (only in csv format) is also available on Zenodo at https://doi.org/10.5281/zenodo.7621453.

Both MADIA datasets will be periodically updated.

Attached content

A ZIP archive composed by the following folders

nc_data: annual time series from 1981 to 2022 and climate normals (1981-2010 and 1991-2020) in NetCDF format

csv_data: annual time series from 1981 to 2022 and climate normals (1981-2010 and 1991-2020) in csv format

metadata: discovery and description metadata

shp_data: two complementary vector layers with the NUTS2-3 cover fractions and the ERA5 cell polygons for Italy

Acknowledgments

This work was supported by the Italian Ministry of Agricultural, Food and Forestry Policies (AgriDigit-Agromodelli, DM n. 36502 of 20/12/2018)

Ocean acidification (OA) is likely to exert selective pressure on natural populations. Our ability to predict which marine species will adapt to OA, and what underlies this adaptive potential, are of high conservation and resource management priority. Using a naturally low pH vent site in the Mediterranean Sea (Castello Aragonese, Ischia) mirroring projected future OA conditions, we carried out a reciprocal transplant experiment to investigate the relative importance of phenotypic plasticity and local adaptation in two populations of the sessile, calcifying polychaete /Simplaria /sp. (Annelida, Serpulidae, Spirorbinae): one residing in low pH and the other from a nearby ambient (i.e. high) pH site. We measured a suite of fitness related traits (i.e. survival, reproductive output, maturation, population growth) and tube growth rates in laboratory-bred F2 generation individuals from both populations reciprocally transplanted back into both ambient and low pH /in situ/ habitats. Both populations showed lower expression in all traits, but increased tube growth rates, when exposed to low pH compared to high pH conditions, regardless of their site of origin suggesting that local adaptation to low pH conditions has not occurred. We also found comparable levels of plasticity in the two populations investigated, suggesting no influence of long-term exposure to low pH on the ability of populations to adjust their phenotype. Despite high variation in trait values among sites and the relatively extreme conditions at sites close to the vents (pH < 7.36), response trends were consistent across traits. Hence, our data suggest that, for /Simplaria /and possibly other calcifiers, neither local adaptations nor sufficient phenotypic plasticity levels appear to suffice in order to compensate for the negative impacts of OA on long-term survival. Our work also underlines the utility of field experiments in natural environments subjected to high level of /p/CO_2 for elucidating the potential for adaptation to future scenarios of OA.

On 5 September 2015 a violent hailstorm hit the Gulf and the city of Naples in Italy. The storm originated over the Tyrrhenian Sea dropping 7–10 cm diameter hailstones along its path. The event was observed by a dual-polarization Doppler C-band, namely the Monte il Monte radar operated by the Italian Department of Civil Protection, being part of the Italian radar network (IT-RAD).

The dataset is composed by high-resolution polar volumes of the following radar parameters: Uncorrected reflectivity Z (UZ), Corrected reflectivity Z (CZ), differential reflectivity (ZDR), uncorrected differential phase shift (PHIDP), co-polar correlation coefficient (RHOHV), Doppler Velocity (V), Doppler Width (W). The scan strategy is based on inverse elevation mode (from the highest to the lowest elevation angle) with variable PRF. The different phases of the event were well captured by the weather radar of “Monte il Monte” (lat = 41.9394 °, lon = 14.6208 °, altitude = 710 m) which, at the time of the event, was affected by a differential bias (on ZDR) of about 0.8 dB to be algebraically subtracted from the measured quantities. The user should be informed about some spot regions of missing data that might be present in the radar variables, especially on the V and differential phase. This is caused by the thresholding approach applied at RSP level on the signal quality index (SQI) to compensate for W-LAN interferences.

The dataset, consisting of 44 raw radar data volumes with 5 minutes sampling rate, is provided in a proprietary format (“Datamet”) that is manageable by using the python code named read_datamet.py that is available at https://zenodo.org/record/4897245.

O3, NO2, PM1, PM2.5, PM10, temperature, relative humidity, atmospheric pressure and solar radiation low-cost sensors have been co-located with the certified air quality monitoring station of Bolzano - Italy (UTM 46°49′44″ N, 11°34′24″ E, 262 m a.s.l.) managed by the local environmental agency (APPA). The filed campaign is aimed at comparing the low-cost sensors' timeseries to high-resolution instruments, which comply with the protocol for standardized acquisition released by the European Environmental Agency. The core unit of the low-cost sensors acquisition system is a Raspberry Pi 4, which couples to the sensors via the I2C bus. Specifically, the low-cost sensors involved in the campaign are: O3 (Alphasense OX-A431), NO2 (Alphasense NO2-A431) and PM1, 2.5, 10 (Alphasense OPC-N3), Tin/RHin (Sensirion SHT31), Tout/RHout (Galtech PM15PS), atmospheric pressure (Bosch Sensortech BMP388), and SR (Apogee SP 420 Smart).

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Geothermal Heat Pump Market Size 2025-2029

The geothermal heat pump market size is forecast to increase by USD 6.48 billion at a CAGR of 8.9% between 2024 and 2029.

The Geothermal Heat Pump (GHP) market presents an attractive investment opportunity for energy-conscious businesses and homeowners, particularly in regions with consistent subsurface temperatures. Key drivers for this market's growth include the operational benefits of GHPs over conventional heating and cooling systems, such as energy efficiency, reduced greenhouse gas emissions, and lower maintenance costs. A significant trend influencing market growth is the integration of Building Energy Management Systems (BEMS) with GHPs. BEMS optimize energy consumption and improve overall system performance, making GHPs a more cost-effective and sustainable solution for temperature control. However, the high upfront cost of installing a GHP system remains a challenge for market penetration, especially in residential applications. Companies seeking to capitalize on this market's potential should focus on innovative financing solutions, such as incentives, subsidies, and leasing options, to offset the initial investment. Additionally, collaborating with BEMS providers to offer integrated solutions can enhance competitiveness and provide value-added services to customers.

What will be the Size of the Geothermal Heat Pump Market during the forecast period?

Request Free SampleThe market is experiencing significant growth due to the increasing demand for renewable energy sources and the desire for energy-efficient heating solutions. Geothermal heat pumps (GHPs) offer several advantages, including low maintenance costs and high durability, making them an attractive alternative to traditional heating systems. These systems utilize a closed-loop or open-loop design, with interconnected pipes filled with an antifreeze solution, to transfer heat from the ground to buildings. The closed-loop vertical design is particularly popular due to its smaller space requirement. The market is segmented into closed-loop and open-loop GHPs. Renewable energy initiatives and rising heating costs are driving the market's expansion, with The market projected to reach substantial growth in the coming years. The technology's ability to provide consistent heating and cooling, while reducing carbon emissions, further enhances its appeal.

How is this Geothermal Heat Pump Industry segmented?

The geothermal heat pump industry research report provides comprehensive data (region-wise segment analysis), with forecasts and estimates in 'USD million' for the period 2025-2029, as well as historical data from 2019-2023 for the following segments. End-userResidentialNon-residentialTypeClosed loop systemOpen loop systemApplicationHorizontal loopVertical loopPond loopGeographyEuropeFranceGermanyItalyUKNorth AmericaUSCanadaAPACChinaIndiaJapanSouth KoreaSouth AmericaMiddle East and Africa

By End-user Insights

The residential segment is estimated to witness significant growth during the forecast period.The Geothermal Heat Pump (GHP) market experienced substantial growth in the residential segment in 2024, driven by the recovery of the construction industry following the economic downturn. This sector's significance stems from the integral role of GHPs in modern residential buildings. The global construction market's expansion is anticipated to boost demand for these energy-efficient products in the residential sector. Geothermal heat pumps offer advantages such as low maintenance costs, high durability, and interconnected pipes filled with an antifreeze solution. They provide heating and hot water generation through heat transfer from the ground using either horizontal or vertical closed loops. Open-loop GHPs, utilizing local water sources, have limited availability due to geographical and local restrictions. Economic conditions and tax rebates continue to influence market growth. Geothermal heat pumps contribute to sustainable heating and cooling solutions, reducing carbon emissions and offering operational benefits over traditional HVAC systems.

Get a glance at the market report of share of various segments Request Free Sample

The Residential segment was valued at USD 5.19 billion in 2019 and showed a gradual increase during the forecast period.

Regional Analysis

Europe is estimated to contribute 47% to the growth of the global market during the forecast period.Technavio’s analysts have elaborately explained the regional trends and drivers that shape the market during the forecast period.

For more insights on the market size of various regions, Request Free Sample

The Geothermal Heat Pump (GHP) market in Europe is projected to remain the largest market segment globally due to the region's economic recovery and increasing focus on renewable energy sources for space heating and hot water genera