Historical trends and high-resolution future climate projections in northern Tuscany (Italy)

D’Oria, Marco; Ferraresi, M.; Tanda, Maria Giovanna

doi:10.1016/j.jhydrol.2017.10.054

Cited by 33 publications

(36 citation statements)

References 26 publications

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“…Mountains up to about 2,000 m high (Apuan Alps) and the presence of the coastline contribute to a high heterogeneity in the spatial distribution of the climate variables (see D'Oria et al, , for more details). Snow accumulation and melting can occur in some portion of the area, but perennial snow masses are uncommon.…”

Section: Study Areamentioning

confidence: 99%

“…However, the climate model data may have a low spatial resolution and systematic errors (bias) such that they could be unsuitable to be directly used in impact assessment studies (Teutschbein & Seibert, ). For these reasons, the climate model projections need to be downscaled and bias corrected, to obtain local and high‐resolution climate scenarios, before applying them to quantify the impacts on the watershed hydrology (D'Oria, Ferraresi, & Tanda, ; Teutschbein & Seibert, ).…”

Section: Introductionmentioning

confidence: 99%

“…In this context, in the present work, we investigate the potential impacts of climate change on water resources in the northern part of Tuscany, Italy, in an area served by a local water company interested in developing effective adaptation strategies. For this area, D'Oria et al () analysed the present, past, and future meteorological variables providing a detailed understanding of the local climate. Beside the observed data, the authors used 13 RCM projections, developed within the EURO‐CORDEX programme (Jacob et al, ), to provide downscaled/bias‐corrected daily mean temperature and precipitation time series for three decades: a recent past period 2003–2012, a medium‐term (2031–2040), and a long‐term (2051–2060) decade.…”

Section: Introductionmentioning

confidence: 99%

“…Two scenarios adopted in AR5 by the IPCC (the representative concentration pathways [RCPs], RCP4.5 and RCP8.5) were considered. This work makes use of the climate model projections analysed by D'Oria et al () to drive a hydrological model for each of the seven hydrographic units that are within the area of interest. In particular, calibrated, continuous, and semidistributed models have been used to evaluate the effects of climate change on water resources, looking at the rainfall, streamflow, and groundwater recharge and highlighting the uncertainty in the results.…”

Section: Introductionmentioning

confidence: 99%

“…This paper is organized as follows: Section 2 presents the study area, whereas Section 3 reports the available meteorological (observed and RCM projections) and discharge data, together with the main finding of D'Oria et al (). Section 4 describes the hydrological model set‐up, with particular attention to the definition of the initial model parameters and the calibration method.…”

Section: Introductionmentioning

confidence: 99%

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Quantifying the impacts of climate change on water resources in northern Tuscany, Italy, using high‐resolution regional projections

D’Oria

Ferraresi

Tanda

2019

Hydrological Processes

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This paper investigates the potential impacts of climate change on water resources in northern Tuscany, Italy. A continuous hydrological model for each of the seven river basins within the study area was calibrated using historical data. The models were then driven by downscaled and bias‐corrected climate projections of an ensemble of 13 regional climate models (RCMs), under two different scenarios of representative concentration pathway (RCP4.5 and RCP8.5). The impacts were examined at medium term (2031–2040) and long term (2051–2060) in comparison with a reference period (2003–2012); the changes in rainfall, streamflow, and groundwater recharge were investigated. A high degree of uncertainty characterized the results with a significant intermodel variability, the period being equal. For the sake of brevity, only the results for the Serchio River basin were presented in detail. According to the RCM ensemble mean and the RCP4.5, a moderate decrease in rainfall, with reference to 2003–2012, is expected at medium term (−0.6%) and long term (−2.8%). Due to the warming of the study area, the reduction in the streamflow volume is two times the precipitation decrease (−1.1% and −6.8% at medium and long term, respectively). The groundwater recharge is mainly affected by the changes in climate with expected percolation volume variations of −3.3% at 2031–2040 and −8.1% at 2051–2060. The impacts on the Serchio River basin water resources are less significant under the RCP8.5 scenario. The presence of artificial structures, such as dam‐reservoir systems, can contribute to mitigate the effects of climate change on water resources through the implementation of appropriate regulation strategies.

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Section: Study Areamentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

Quantifying the impacts of climate change on water resources in northern Tuscany, Italy, using high‐resolution regional projections

D’Oria

Ferraresi

Tanda

2019

Hydrological Processes

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Projected spatial patterns in precipitation and air temperature for China's northwest region derived from high‐resolution regional climate models

Yin

Feng

Deo

et al. 2019

Intl Journal of Climatology

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Derived from realistic global warming scenarios, long‐term projections of spatial patterns in precipitation and temperature in hydrology and climatology can serve to evaluate climate risk, explore sources of renewable energies and allow local‐scale data to inform decisions regarding agricultural, ecosystem, social, recreational and economic activities. Under the CORDEX‐EA project, the precipitation and temperature projections (2020–2045) for the economically and socially important region of Northwestern China were derived from high‐resolution regional climate model (RCM) simulations for RCP 4.5 and 8.5 scenarios, and compared against a historical period or baseline of 1980–2005. Drawing data from four key RCMs [Weather Research and Forecasting (WRF); Regional Spectral Model (RSM); Regional Climate Model version 4.0 (RegCM4); Mesoscale Model version 5 (MM5)], reliable local‐scale projections were generated by applying suitable bias correction that accords with the multivariate bias correction (MBC) approach. To validate this approach and then evaluate climate change impacts, the adjusted precipitation and temperature estimated from bias‐corrected models for the historical period were compared to the observed data. The results showed that the simulated spatiotemporal distribution of multiyear average precipitation and temperature appear to fit relatively well with the observations, however, the wet‐cold and dry‐warm climate‐related biases were still evident for the high altitude regions. Bias‐corrected future projections of RCMs indicated spatially averaged annual precipitation is expected to rise by about 23.6 and 35.3 mm under the RCP 4.5 and 8.5 scenarios, respectively, while spatially averaged annual temperature is expected to rise by about 1.95 and 1.10°C. Precipitation is projected to increase in all seasons, albeit, more so in the cold season (i.e., boreal winter and spring) than the warm season (i.e., boreal summer and autumn). The annual increase is expected to be about 56.7% under the RCP 4.5 scenario, compared to 67.6% under the RCP 8.5 scenario. The changes of mean temperature in winter are expected to be significant, −37.8% under both RCP scenarios. For spring, the mean temperature will rise by 23.1% (28.9%) under the RCP 4.5 (8.5) scenario. A MBC approach was found to be effective in yielding reliable projected changes in precipitation and temperature variables. The proposed approach has important implications for climatological studies and evaluation of climate change impacts on localized regions, not only in China, but also in other similar areas of the world, where decisions for managing climate risk must be implemented by policy makers, government, industry and stakeholders.

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A review of studies on observed precipitation trends in Italy

Caporali

Lompi

Pacetti

et al. 2020

Intl Journal of Climatology

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Research to detect changes in precipitation variables has become a topic of particular interest to understand modifications in water resources availability. The review is focused on the Italian territory, outlining the "state of the art" of changes in precipitation regime through a review of 54 published studies on observed rainfall trend analyses, in the period 1999-2018. The aim is to combine a large body of knowledge in a single review and to explain the main patterns of rainfall changes occurred in Italy over the last decades. The analysis focused on the Total Precipitation (TP) and the number of Wet Days (WDs) indices at the annual and seasonal scale. A weight factor is introduced to take into account the differences among studies in geographical area, time series length, and number of stations. The review is accompanied by the discussion of other rainfall related variables, that is, precipitation intensity, extreme rainfall events and meteorological droughts, which are useful to provide a broader picture of rainfall changes. Overall, there is an agreement about the tendency of a decrease in wet days on the entire Italy, with limited discrepancies in the various regions. A decrease in wet days is accompanied by a negative trend (although less evident) in total precipitation, especially in winter. Nevertheless, a univocal direction of trends (or lack of thereof) in annual total precipitation and mostly hydrological extreme events is difficult to achieve.

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Historical trends and high-resolution future climate projections in northern Tuscany (Italy)

Cited by 33 publications

References 26 publications

Quantifying the impacts of climate change on water resources in northern Tuscany, Italy, using high‐resolution regional projections

Quantifying the impacts of climate change on water resources in northern Tuscany, Italy, using high‐resolution regional projections

Projected spatial patterns in precipitation and air temperature for China's northwest region derived from high‐resolution regional climate models

A review of studies on observed precipitation trends in Italy

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