Articles | Volume 13, issue 6
https://doi.org/10.5194/essd-13-2801-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/essd-13-2801-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
A high-resolution gridded dataset of daily temperature and precipitation records (1980–2018) for Trentino-South Tyrol (north-eastern Italian Alps)
Institute for Earth Observation, Eurac Research, Bolzano, 39100, Italy
Michael Matiu
Institute for Earth Observation, Eurac Research, Bolzano, 39100, Italy
Giacomo Bertoldi
Institute for Alpine Environment, Eurac Research, Bolzano, 39100,
Italy
Marcello Petitta
Institute for Earth Observation, Eurac Research, Bolzano, 39100, Italy
SSPT-MET-CLIM, ENEA, Rome, 00196, Italy
Marc Zebisch
Institute for Earth Observation, Eurac Research, Bolzano, 39100, Italy
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We studied a severe compound drought and heatwave event in the Adige River basin in May 2022 and found that similar events are now hotter and drier due to current warming. These changes worsen water stress and river drying. We show that timing matters: events in June are now more critical than in April, as the snowmelt contribution to streamflow in June has become much lower than in the past. However, many climate models still fail to capture these changes.
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EEAR-Clim is a new and unprecedented observational dataset gathering in situ daily measurements of air temperature and precipitation from a network of about 9000 weather stations covering the European Alps. Data collected, including time series from recordings up to 2020 and time series significantly enhancing data coverage at high elevations, were tested for quality and homogeneity. The dataset aims to serve as a powerful tool for better understanding climate change over the European Alpine region.
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We studied a severe compound drought and heatwave event in the Adige River basin in May 2022 and found that similar events are now hotter and drier due to current warming. These changes worsen water stress and river drying. We show that timing matters: events in June are now more critical than in April, as the snowmelt contribution to streamflow in June has become much lower than in the past. However, many climate models still fail to capture these changes.
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EEAR-Clim is a new and unprecedented observational dataset gathering in situ daily measurements of air temperature and precipitation from a network of about 9000 weather stations covering the European Alps. Data collected, including time series from recordings up to 2020 and time series significantly enhancing data coverage at high elevations, were tested for quality and homogeneity. The dataset aims to serve as a powerful tool for better understanding climate change over the European Alpine region.
Raul-David Şerban, Huijun Jin, Mihaela Şerban, Giacomo Bertoldi, Dongliang Luo, Qingfeng Wang, Qiang Ma, Ruixia He, Xiaoying Jin, Xinze Li, Jianjun Tang, and Hongwei Wang
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A particular observational network for ground surface temperature (GST) has been established on the northeastern Qinghai–Tibet Plateau, covering various environmental conditions and scales. This analysis revealed the substantial influences of the land cover on the spatial variability in GST over short distances (<16 m). Improving the monitoring of GST is important for the biophysical processes at the land–atmosphere boundary and for understanding the climate change impacts on cold environments.
Valentina Premier, Carlo Marin, Giacomo Bertoldi, Riccardo Barella, Claudia Notarnicola, and Lorenzo Bruzzone
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The large amount of information regularly acquired by satellites can provide important information about SWE. We explore the use of multi-source satellite data, in situ observations, and a degree-day model to reconstruct daily SWE at 25 m. The results show spatial patterns that are consistent with the topographical features as well as with a reference product. Being able to also reproduce interannual variability, the method has great potential for hydrological and ecological applications.
Stefan Steger, Mateo Moreno, Alice Crespi, Peter James Zellner, Stefano Luigi Gariano, Maria Teresa Brunetti, Massimo Melillo, Silvia Peruccacci, Francesco Marra, Robin Kohrs, Jason Goetz, Volkmar Mair, and Massimiliano Pittore
Nat. Hazards Earth Syst. Sci., 23, 1483–1506, https://doi.org/10.5194/nhess-23-1483-2023, https://doi.org/10.5194/nhess-23-1483-2023, 2023
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We present a novel data-driven modelling approach to determine season-specific critical precipitation conditions for landslide occurrence. It is shown that the amount of precipitation required to trigger a landslide in South Tyrol varies from season to season. In summer, a higher amount of preparatory precipitation is required to trigger a landslide, probably due to denser vegetation and higher temperatures. We derive dynamic thresholds that directly relate to hit rates and false-alarm rates.
Ruth Stephan, Stefano Terzi, Mathilde Erfurt, Silvia Cocuccioni, Kerstin Stahl, and Marc Zebisch
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This study maps agriculture's vulnerability to drought in the European pre-Alpine regions of Thurgau (CH) and Podravska (SI). We combine region-specific knowledge with quantitative data mapping; experts of the study regions, far apart, identified a few common but more region-specific factors that we integrated in two vulnerability scenarios. We highlight the benefits of the participatory approach in improving the quantitative results and closing the gap between science and practitioners.
Michael Matiu and Florian Hanzer
Hydrol. Earth Syst. Sci., 26, 3037–3054, https://doi.org/10.5194/hess-26-3037-2022, https://doi.org/10.5194/hess-26-3037-2022, 2022
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Regional climate models not only provide projections on temperature and precipitation, but also on snow. Here, we employed statistical post-processing using satellite observations to reduce bias and uncertainty from model projections of future snow-covered area and duration under different greenhouse gas concentration scenarios for the European Alps. Snow cover area/duration decreased overall in the future, three times more strongly with 4–5° global warming as compared to 1.5–2°.
Michael Matiu, Alice Crespi, Giacomo Bertoldi, Carlo Maria Carmagnola, Christoph Marty, Samuel Morin, Wolfgang Schöner, Daniele Cat Berro, Gabriele Chiogna, Ludovica De Gregorio, Sven Kotlarski, Bruno Majone, Gernot Resch, Silvia Terzago, Mauro Valt, Walter Beozzo, Paola Cianfarra, Isabelle Gouttevin, Giorgia Marcolini, Claudia Notarnicola, Marcello Petitta, Simon C. Scherrer, Ulrich Strasser, Michael Winkler, Marc Zebisch, Andrea Cicogna, Roberto Cremonini, Andrea Debernardi, Mattia Faletto, Mauro Gaddo, Lorenzo Giovannini, Luca Mercalli, Jean-Michel Soubeyroux, Andrea Sušnik, Alberto Trenti, Stefano Urbani, and Viktor Weilguni
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The first Alpine-wide assessment of station snow depth has been enabled by a collaborative effort of the research community which involves more than 30 partners, 6 countries, and more than 2000 stations. It shows how snow in the European Alps matches the climatic zones and gives a robust estimate of observed changes: stronger decreases in the snow season at low elevations and in spring at all elevations, however, with considerable regional differences.
Cited articles
Aadhar, S. and Mishra, V.: High-resolution near real-time drought monitoring
in South Asia, Sci. Data, 4, 170145, https://doi.org/10.1038/sdata.2017.145, 2017.
Adler, R. F., Sapiano, M. R. P., Huffman, G. J., Wang, J.-J., Gu, G., Bolvin,
D., Chiu, L., Schneider, U., Becker, A., Nelkin, E., Xie, P., Ferraro, R.,
and Shin, D.-B.: The Global Precipitation Climatology Project (GPCP) Monthly
Analysis (New Version 2.3) and a Review of 2017 Global Precipitation,
Atmosphere, 9, 138, https://doi.org/10.3390/atmos9040138, 2018.
Adler, S., Chimani, B., Drechsel, S., Haslinger, K., Hiebl, J., Meyer, V.,
Resch, G., Rudolph, J., Vergeiner, J., Zingerle, C., Marigo, G., Fischer, A., and Seiser, B.: Das Klima: Von
Tirol-Sudtirol-Belluno, ZAMG, Autonome Provinz Bozen, ARPAV,
available at: http://www.3pclim.eu/images/Das_Klima_von_Tirol-Suedtirol-Belluno.pdf
(last access: 12 October 2020), 2015.
Auer, I., Böhm, R., Jurkovic, A., Lipa, W., Orlik, A., Potzmann, R.,
Schöner, W., Ungersböck, M., Matulla, C., Briffa, K., Jones, P.,
Efthymiadis, D., Brunetti, M., Nanni, T., Maugeri, M., Mercalli, L., Mestre,
O., Moisselin, J., Begert, M., Müller-Westermeier, G., Kveton, V.,
Bochnicek, O., Stastny, P., Lapin, M., Szalai, S., Szentimrey, T., Cegnar,
T., Dolinar, M., Gajic-Capka, M., Zaninovic, K., Majstorovic, Z., and
Nieplova, E.: HISTALP – Historical instrumental climatological surface time
series of the Greater Alpine Region HISTALP, Int. J. Climatol., 27, 17–46,
https://doi.org/10.1002/joc.1377, 2007.
Beven, K., Cloke, H., Pappenberger, F., Lamb, R., and Hunter, N.:
Hyperresolution information and hyperresolution ignorance in modelling the
hydrology of the land surface, Science China Earth Sciences, 58, 25–35,
https://doi.org/10.1007/s11430-014-5003-4, 2015.
Brugnara, Y., Brunetti, M., Maugeri, M., Nanni, T., and Simolo, C.:
High-resolution analysis of daily precipitation trends in the central Alps
over the last century, Int. J. Climatol., 32, 1406–1422,
https://doi.org/10.1002/joc.2363, 2012.
Brunetti, M., Maugeri, M., Monti, F., and Nanni, T.: Temperature and
precipitation variability in Italy in the last two centuries from
homogenised instrumental time series, Int. J. Climatol., 26, 345–381,
https://doi.org/10.1002/joc.1251, 2006.
Brunetti, M., Lentini, G., Maugeri, M., Nanni, T. and Spinoni, J.:
Projecting North Eastern Italy temperature and precipitation secular records
onto a high-resolution grid, Phys. Chem. Earth, 40–41, 9–22,
https://doi.org/10.1016/j.pce.2009.12.005, 2012.
Brunetti, M., Maugeri, M., Nanni, T., Simolo, C., and Spinoni, J.:
High-resolution temperature climatology for Italy: interpolation method
intercomparison, Int. J. Climatol., 34, 1278–1296, https://doi.org/10.1002/joc.3764,
2014.
Brunsdon, C., McClatchey, J., and Unwin, D.: Spatial variations in the
average rainfall–altitude relationship in Great Britain: an approach using
geographically weighted regression, Int. J. Climatol., 21, 455–466,
https://doi.org/10.1002/joc.614, 2001.
Camera, C., Bruggeman, A., Hadjinicolaou, P., Pashiardis, S., and Lange, M.
A.: Evaluation of interpolation techniques for the creation of gridded daily
precipitation (1×1 km2); Cyprus, 1980–2010, J. Geophys.
Res.-Atmos., 119, 693–712, https://doi.org/10.1002/2013JD020611, 2014.
Chimani, B., Matulla, C., Böhm, R., and Hofstätter, M.: A new high
resolution absolute temperature grid for the Greater Alpine Region back to
1780, Int. J. Climatol., 33, 2129–2141, https://doi.org/10.1002/joc.3574, 2013.
Craddock, J.: Methods of comparing annual rainfall records for climatic
purposes, Weather, 34, 332–346, https://doi.org/10.1002/j.1477-8696.1979.tb03465.x,
1979.
Crespi, A., Brunetti, M., Lentini, G., and Maugeri, M.: 1961–1990
high-resolution monthly precipitation climatologies for Italy, Int. J.
Climatol., 3, 878–895, https://doi.org/10.1002/joc.5217, 2018.
Crespi, A., Matiu, M., Bertoldi, G., Petitta, M., and Zebisch, M.:
High-resolution daily series (1980–2018) and monthly climatologies (1981–1010) of mean temperature and precipitation for Trentino – South Tyrol
(north-eastern Italian Alps), PANGAEA, https://doi.org/10.1594/PANGAEA.924502, 2020.
Crespi, A., Brunetti, M., Ranzi, R., Tomirotti, M., and Maugeri, M.: A
multi-century meteo-hydrological analysis for the Adda river basin (Central
Alps). Part I: Gridded monthly precipitation (1800–2016) records, Int. J.
Climatol., 41, 162–180, https://doi.org/10.1002/joc.6614, 2021.
Dalponte, M., Marzini, S., Solano-Correa, Y. T., Tonon, G., Vescovo, L., and
Gianelle, D.: Mapping forest windthrows using high spatial resolution
multispectral satellite images, Int. J. Appl. Earth Obs. Geoinf., 93,
102206, https://doi.org/10.1016/j.jag.2020.102206, 2020.
Daly, C., Gibson, W. P., Taylor, G. H., Johnson, G. L., and Pasteris, P.: A
knowledge-based approach to the statistical mapping of climate, Clim. Res.,
22, 99–113, https://doi.org/10.3354/cr022099, 2002.
Daly, C., Smith, J. W., Smith, J. I., and McKane, R. B.: High-Resolution
Spatial Modeling of Daily Weather Elements for a Catchment in the Oregon
Cascade Mountains, United States, J. Appl. Meteorol. Clim., 46, 1565–1586,
https://doi.org/10.1175/JAM2548.1, 2007.
Davolio, S., Della Fera, S., Laviola, S., Miglietta, M. M., and Levizzani,
V.: Heavy Precipitation over Italy from the Mediterranean Storm “Vaia” in
October 2018: Assessing the Role of an Atmospheric River, Mon. Weather Rev.,
148, 3571–3588, https://doi.org/10.1175/MWR-D-20-0021.1, 2020.
Di Piazza, A., Conti, F. L., Noto, L., Viola, F., and La Loggia, G.:
Comparative analysis of different techniques for spatial interpolation of
rainfall data to create a serially complete monthly time series of
precipitation for Sicily, Italy, Int. J. Appl. Earth Obs. Geoinf., 13,
396–408, https://doi.org/10.1016/j.jag.2011.01.005, 2011.
Duan, Z., Liu, J. Z., Tuo, Y., Chiogna, G., and Disse, M.: Evaluation of
eight high spatial resolution gridded precipitation products in Adige Basin
(Italy) at multiple temporal and spatial scales, Sci. Total Environ., 573,
1536–1553, https://doi.org/10.1016/j.scitotenv.2016.08.213, 2016.
Durre, I., Menne, M. J., Gleason, B. E., Houston, T. G., and Vose, R. S.:
Comprehensive Automated Quality Assurance of Daily Surface Observations, J.
Appl. Meteorol. Clim., 49, 1615–1633, https://doi.org/10.1175/2010JAMC2375.1, 2010.
Engelhardt, M., Schuler, T. V., and Andreassen, L. M.: Contribution of snow and glacier melt to discharge for highly glacierised catchments in Norway, Hydrol. Earth Syst. Sci., 18, 511–523, https://doi.org/10.5194/hess-18-511-2014, 2014.
Foresti, L., Sideris, I., Panziera, L., Nerini, D., and Germann, U.: A
10-year radar-based analysis of orographic precipitation growth and decay
patterns over the Swiss Alpine region, Q. J. Roy. Meteor. Soc., 144,
2277–2301, https://doi.org/10.1002/qj.3364, 2018.
Frei, C. and Schär, C.: A precipitation climatology of the Alps from
high-resolution rain-gauge observations, Int. J. Climatol., 18, 873–900,
https://doi.org/10.1002/(SICI)1097-0088(19980630)18:8<873::AID-JOC255>3.0.CO;2-9, 1998.
Funk, C., Peterson, P., Landsfeld, M., Pedreros, D., Verdin, J., Shukla, S.,
Husak, G., Rowland, J., Harrison, L., Hoell, A., and Michaelsen, J.: The
climate hazards group infrared precipitation with stations – A new
environmental record for monitoring extremes, Sci. Data, 2, 150066,
https://doi.org/10.1038/sdata.2015.66, 2015.
Grasso, L. D.: The differentiation between grid spacing and resolution and
their application to numerical modeling, B. Am. Meteorol. Soc., 81,
579–580, https://doi.org/10.1175/1520-0477(2000)081<0579:CAA>2.3.CO;2, 2000.
Grossi, G., Lendvai, A., Peretti, G., and Ranzi, R.: Snow Precipitation
Measured by Gauges: Systematic Error Estimation and Data Series Correction
in the Central Italian Alps, Water, 9, 461, https://doi.org/10.3390/w9070461, 2017.
Harris, I., Osborn, T. J., Jones, P., and Lister, D.: Version 4 of the CRU TS
monthly high-resolution gridded multivariate climate dataset, Sci. Data, 7,
109, https://doi.org/10.1038/s41597-020-0453-3, 2020.
Haylock, M. R., Hofstra, N., Klein Tank, A. M. G., Klok, E. J., Jones, P.
D., and New, M.: A European daily high-resolution gridded data set of
surface temperature and precipitation for 1950–2006, J. Geophys. Res., 113,
D20119, https://doi.org/10.1029/2008JD010201, 2008.
Hengl, T.: A Practical Guide to Geostatistical Mapping, ISBN
978–90–9024981-0, available at:
https://library.wur.nl/isric/fulltext/isricu_i27272_001.pdf (last access: 14 June 2021), 2009.
Hiebl, J. and Frei, C.: Daily precipitation grids for Austria since
1961 – development and evaluation of a spatial dataset for hydroclimatic
monitoring and modelling, Theor. Appl. Climatol., 132, 327–345,
https://doi.org/10.1007/s00704-017-2093-x, 2018.
Hofstra, N., Haylock, M., New, M., Jones, P., and Frei, C.: Comparison of
six methods for the interpolation of daily European climate data, J.
Geophys. Res., 113, D21110, https://doi.org/10.1029/2008JD010100, 2008.
Hofstra, N., New, M., and McSweeney, C.: The influence of interpolation and
station network density on the distributions and trends of climate variables
in gridded daily data, Clim. Dyn., 35, 841–858.
https://doi.org/10.1007/s00382-009-0698-1, 2010.
Huffman, G. J., Bolvin, D. T., Nelkin, E. J., Wolff, D. B., Adler, R. F.,
Gu, G., Hong, Y., Bowman, K. P., and Stocker, E. F.: The TRMM Multisatellite
Precipitation Analysis (TMPA): Quasi-Global, Multiyear, Combined-Sensor
Precipitation Estimates at Fine Scales, J. Hydrometeorol., 8, 38–55,
https://doi.org/10.1175/JHM560.1, 2007.
Immerzeel, W. W., Lutz, A. F., Andrade, M., Bahl, A., Biemans, H., Bolch,
T., Hyde, S., Brumby, S., Davies, B. J., Elmore, A. C., Emmer, A., Feng, M.,
Fernández, A., Haritashya, U., Kargel, J. S., Koppes, M., Kraaijenbrink,
P. D. A., Kulkarni, A. V., Mayewski, P. A., Nepal, S., Pacheco, P., Painter,
T. H., Pellicciotti, F., Rajaram, H., Rupper, S., Sinisalo, A., Shrestha, A.
B., Viviroli, D., Wada, Y., Xiao, C., Yao, T., and Baillie J. E.
M.: Importance and vulnerability of the world's water
towers, Nature, 577, 364–369, https://doi.org/10.1038/s41586-019-1822-y, 2020.
Isotta, F. A., Frei, C., Weilguni, V., Perčec Tadić, M.,
Lassègues, P., Rudolf, B., Pavan, V., Cacciamani, C., Antolini, G.,
Ratto, S. M., Munari, M., Micheletti, S., Bonati, V., Lussana, C., Ronchi,
C., Panettieri, E., Marigo, G., and Vertačnik, G.: The climate of daily
precipitation in the Alps: development and analysis of a high-resolution
grid dataset from pan-Alpine rain-gauge data, Int. J. Climatol., 34,
1657–1675, https://doi.org/10.1002/joc.3794, 2014.
Isotta, F. A., Begert, M., and Frei, C.: Long-term consistent monthly
temperature and precipitation grid data sets for Switzerland over the past
150 years, J. Geophys. Res.-Atmos., 124, 3783–3799,
https://doi.org/10.1029/2018JD029910, 2019.
Kotlarski, S., Szabó, P., Herrera, S., Räty, O., Keuler, K., Soares,
P. M., Cardoso, R. M., Bosshard, T., Pagé, C., Boberg, F.,
Gutiérrez, J. M., Isotta, F. A., Jaczewski, A., Kreienkamp, F., Liniger,
M. A., Lussana, C., and Pianko-Kluczyńska, C.: Observational uncertainty
and regional climate model evaluation: A pan-European perspective, Int. J.
Climatol., 39, 3730–3749, https://doi.org/10.1002/joc.5249, 2019.
Laiti, L., Mallucci, S., Piccolroaz, S., Bellin, A., Zardi, D., Fiori, A.,
Nikulin, G., and Majone, B.: Testing the hydrological coherence of
high-resolution gridded precipitation and temperature data sets, Water
Resour. Res., 54, 1999–2016, https://doi.org/10.1002/2017WR021633, 2018.
Ledesma, J. L. J. and Futter, M. N.: Gridded climate data products are an
alternative to instrumental measurements as inputs to rainfall–runoff
models, Hydrol. Process., 31, 3283–3293, https://doi.org/10.1002/hyp.11269, 2017.
Longman, R. J., Frazier, A. G., Newman, A. J., Giambelluca, T. W.,
Schanzenbach, D., Kagawa-Viviani, A., Needham, H., Arnold, J. R., and Clark,
M. P.: High-Resolution Gridded Daily Rainfall and Temperature for the
Hawaiian Islands (1990–2014), J. Hydrometeorol., 20, 489–508,
https://doi.org/10.1175/JHM-D-18-0112.1, 2019.
Lussana, C., Tveito, O. E., Dobler, A., and Tunheim, K.: seNorge_2018, daily precipitation, and temperature datasets over Norway, Earth Syst. Sci. Data, 11, 1531–1551, https://doi.org/10.5194/essd-11-1531-2019, 2019.
Ly, S., Charles, C., and Degré, A.: Geostatistical interpolation of daily rainfall at catchment scale: the use of several variogram models in the Ourthe and Ambleve catchments, Belgium, Hydrol. Earth Syst. Sci., 15, 2259–2274, https://doi.org/10.5194/hess-15-2259-2011, 2011.
Mallucci, S., Majone, B., and Bellin, A.: Detection and attribution of
hydrological changes in a large Alpine river basin,
J. Hydrol., 575, 1214–1229, https://doi.org/10.1016/j.jhydrol.2019.06.020, 2019.
Marcolini, G., Bellin, A., Disse, M., and Chiogna, G.: Variability in snow
depth time series in the Adige catchment, J. Hydrol. Reg. Stud., 13,
240–254, https://doi.org/10.1016/j.ejrh.2017.08.007, 2017.
Matiu, M., Jacob, A., and Notarnicola, C.: Daily MODIS snow cover maps for
the European Alps from 2002 onwards at 250m horizontal resolution along with
a nearly cloud-free version (Version v1.0.2) [Data set], Zenodo,
https://doi.org/10.5281/zenodo.3601891, 2019.
Matiu, M., Jacob, A., and Notarnicola, C.: Daily MODIS Snow Cover Maps for
the European Alps from 2002 onwards at 250 m Horizontal Resolution Along
with a Nearly Cloud-Free Version, Data, 5, 1, https://doi.org/10.3390/data5010001, 2020.
Matiu, M., Crespi, A., Bertoldi, G., Carmagnola, C. M., Marty, C., Morin, S., Schöner, W., Cat Berro, D., Chiogna, G., De Gregorio, L., Kotlarski, S., Majone, B., Resch, G., Terzago, S., Valt, M., Beozzo, W., Cianfarra, P., Gouttevin, I., Marcolini, G., Notarnicola, C., Petitta, M., Scherrer, S. C., Strasser, U., Winkler, M., Zebisch, M., Cicogna, A., Cremonini, R., Debernardi, A., Faletto, M., Gaddo, M., Giovannini, L., Mercalli, L., Soubeyroux, J.-M., Sušnik, A., Trenti, A., Urbani, S., and Weilguni, V.: Observed snow depth trends in the European Alps: 1971 to 2019, The Cryosphere, 15, 1343–1382, https://doi.org/10.5194/tc-15-1343-2021, 2021.
Mei, Y., Anagnostou, E. N., Nikolopoulos, E. I., and Borga, M.: Error
analysis of satellite precipitation products in mountainous basins, J.
Hydrometeorol., 15, 1778–1793, https://doi.org/10.1175/JHM-D-13-0194.1, 2014.
Morán-Tejeda, E., López-Moreno, J. I., and Beniston, M.: The
changing roles of temperature and precipitation on snowpack variability in
Switzerland as a function of altitude, Geophys. Res. Lett., 40, 2131–2136,
https://doi.org/10.1002/grl.50463, 2013.
Navarro-Racines, C., Tarapues, J., Thornton, P., Jarvis, H., and
Ramirez-Villega, J.: High-resolution and bias-corrected CMIP5 projections
for climate change impact assessments, Sci. Data, 7, 7,
https://doi.org/10.1038/s41597-019-0343-8, 2020.
New, M., Todd, M., Hulme, M., and Jones, P.: Precipitation measurements and
trends in the twentieth century, Int. J. Climatol., 21, 1899–1922,
https://doi.org/10.1002/joc.680, 2001.
Notarnicola, C., Duguay, M., Moelg, N., Schellenberger, T., Tetzlaff, A.,
Monsorno, R., Costa, A., Steurer, C., and Zebisch, M.: Snow Cover Maps from
MODIS Images at 250 m Resolution, Part 2: Validation, Remote Sens., 5,
1568–1587, https://doi.org/10.3390/rs5041568, 2013.
Price, F. M.: Alpenatlas – Atlas des Alpes – Atlante delle Alpi – Atlas
Alp – Mapping the Alps: Society – Economy – Environment, Mt. Res. Dev., 29, 292–293,
https://doi.org/10.1659/mrd.mm057, 2009.
Schlögel, R., Kofler, C., Gariano, S. L., Van Campenhout, J., and
Plummer, S.: Changes in climate patterns and their association to natural
hazard distribution in South Tyrol (Eastern Italian Alps), Sci. Rep.,
10, 5022, https://doi.org/10.1038/s41598-020-61615-w, 2020.
Schöner, W., Koch, R., Matulla, C., Marty, C., and Tilg, A-M.:
Spatiotemporal patterns of snow depth within the Swiss-Austrian Alps for the
past half century (1961 to 2012) and linkages to climate change, Int. J.
Climatol., 39, 1589–1603, https://doi.org/10.1002/joc.5902, 2019.
Sekulić, A., Kilibarda, M., Protić, D., Perčec Tadić, M.,
and Bajat, B.: Spatio-temporal regression kriging model of mean daily
temperature for Croatia, Theor. Appl. Climatol., 140, 101–114,
https://doi.org/10.1007/s00704-019-03077-3, 2020.
Sevruk, B., Ondrás, M., and Chvíla, B.: The WMO precipitation
measurement intercomparisons, Atmos. Res., 92, 376–380,
https://doi.org/10.1016/j.atmosres.2009.01.016, 2009.
Stewart, S. B. and Nitschke, C. R.: Improving temperature interpolation
using MODIS LST and local topography: a comparison of methods in south east
Australia, Int. J. Climatol., 37, 3098–3110, https://doi.org/10.1002/joc.4902, 2017.
Short summary
A 250 m gridded dataset of 1980–2018 daily mean temperature and precipitation records for Trentino–South Tyrol (north-eastern Italian Alps) was derived from a quality-controlled and homogenized archive of station observations. The errors associated with the final interpolated fields were assessed and thoroughly discussed. The product will be regularly updated and is meant to support regional climate studies and local monitoring and applications in integration with other fine-resolution data.
A 250 m gridded dataset of 1980–2018 daily mean temperature and precipitation records for...
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