Influence of climate change on the frequency of daytime temperature inversions and stagnation events in the Po Valley: historical trend and future projections

Caserini, Stefano; Giani, Paolo; Cacciamani, C.; Ozgen, S.; Lonati, Giovanni

doi:10.1016/j.atmosres.2016.09.018

Cited by 64 publications

(45 citation statements)

References 8 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…This study indicated that all RCMs capture climatological features reasonably well, and could therefore be applied to evaluate future climate change (Endris et al ., ; Kim et al ., ; Alemseged and Tom, ), and develop response strategies (Waongo et al ., ). In a study of daily temperatures in Italy's Po valley, Med‐CORDEX model outputs showed that by the end of 21st century land surface temperatures could increase by 2.4 or 4.4°C under the RCP 4.5 or RCP 8.5 scenario, respectively (Caserini et al ., ). Applying the CORDEX Region 8 model with the RegCM 4.3.5 RCM in Central Asia, researchers noted that the land surface temperature was expected to increase by 3–7°C for the period of 2071–2100 compared to a 1971–2000 baseline (Ozturk et al ., ).…”

Section: Introductionmentioning

confidence: 97%

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

View full text Add to dashboard Cite

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.

show abstract

Section: Introductionmentioning

confidence: 97%

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

View full text Add to dashboard Cite

show abstract

“…As a consequence, the Po basin is one of the EU hotspots suffering from premature mortality associated to atmospheric pollution (EEA, 2015). In spite of the improvements in the last decades (e.g., Bigi and Ghermandi, 2016), the air quality in the Po Valley is still far from the standards established by the European Commission (EU Commission, 2008) and exceedances of these standards are expected to continue in the next years (Belis et al, 2017;Caserini et al, 2017; EEA, 2017; Guariso and Volta, 2017).…”

Section: Introductionmentioning

confidence: 99%

Transport of Po Valley aerosol pollution to the northwestern Alps. Part 1: phenomenology

Diémoz¹,

Barnaba²,

Magri³

et al. 2018

Preprint

View full text Add to dashboard Cite

Abstract. Mountainous regions are often considered pristine environments, however they can be affected by pollutants emitted in more populated and industrialised areas, transported by regional winds. Based on experimental evidence, further supported by modelling tools, we demonstrate and quantify here the impact of air masses transported from the Po Valley, a European atmospheric pollution hotspot, to the northwestern Alps. This is achieved through a detailed investigation of the phenomenology of near-range (few hundreds km), trans-regional transport, exploiting synergies of multi-sensor observations mainly focussed on particulate matter. The explored dataset includes vertically-resolved data from atmospheric profiling techniques (Automated LiDAR-Ceilometers, ALC), vertically-integrated aerosol properties from ground (sun photometer) and space, and in situ measurements (PM10 and PM2.5, relevant chemical analyses, and aerosol size distribution). During the frequent advection episodes from the Po basin, all the physical quantities observed by the instrumental setup are found to significantly increase: the scattering ratio from ALC reaches values > 30, AOD triplicates, surface PM10 reaches concentrations > 100 µg/m3 even in rural areas, secondary inorganic compounds such as nitrate, ammonium and sulfate increase up to 28 %, 8 % and 17 % of the total PM10 mass, respectively. Results also indicate that the advected aerosol is smaller in size and less light-absorbing compared to the aerosol type locally-emitted in the northwestern Italian Alps, and hygroscopic. In this work, the phenomenon is exemplified through detailed analysis and discussion of three case studies, selected for their clarity and relevance within the wider dataset, the latter being fully exploited in a companion paper quantifying the impact of this phenomenology over the long-term (Diémoz et al., 2018). For the three case studies investigated, a high-resolution numerical weather prediction model (COSMO) and a lagrangian tool (LAGRANTO) are employed to understand the meteorological mechanisms favouring the transport and to demonstrate the Po Valley origin of the air masses. In addition, a chemical transport model (FARM) is used to further support the observations and to partition the contributions of local and non-local sources. Results show that the simulations are not able to adequately reproduce the measurements (with modelled PM10 concentrations 4–5 times lower than the ones retrieved from the ALC, and maxima anticipated by 6–7 hours), likely owing to deficiencies in the emission inventory and particle water uptake not fully taken into account. The advected aerosol is shown to remarkably degrade the air quality of the Alpine region, with potential negative effects on human health, climate and ecosystems, as well as on the touristic development of the investigated area. The findings of the present study could also help design mitigation strategies at the trans–regional scale in the Po basin, and suggest an observations-based approach to evaluate the outcome of their implementation.

show abstract

“…In Modena, starting from the 1980s, climate change has exhibited the same trend as the global climate change. The changes cause extreme events such as jumps in temperature or increases in the distribution and amount of precipitation [57].…”

Section: Study Areamentioning

confidence: 99%

“…Normally precipitation is concentrated during autumn and spring. Summer and winter are the driest seasons [57,58,72,73]. In order to have a clear climate situation of the study area, Table 1 reports some climate information.…”

Section: Study Areamentioning

confidence: 99%

See 1 more Smart Citation

A Multi-Temporal Analyses of Land Surface Temperature Using Landsat-8 Data and Open Source Software: The Case Study of Modena, Italy

2018

View full text Add to dashboard Cite

Abstract:The Urban Heat Island (UHI) phenomenon, namely urban areas where the atmospheric temperature is significantly higher than in the surrounding rural areas, is currently a very well-known topic both in the scientific community and in public debates. Growing urbanization is one of the anthropic causes of UHI. The UHI phenomenon has a negative impact on the life quality of the local population (thermal discomfort, summer thermal shock, etc.), thus investigations and analyses on this topic are really useful and important for correct and sustainable urban planning; this study is included in this context. A multi-temporal analysis was performed in the municipality of Modena (Italy) to identify and estimate the Surface Urban Heat Island (SUHI, strictly correlated to the UHI phenomenon) from 2014 to 2017. For this purpose, Landsat-8 satellite images were processed with Quantum Geographic Information System (QGIS) to obtain the Land Surface Temperature (LST) and the Normalized Difference Vegetation Index (NDVI). For every pixel, LST and NDVI values of three regions of interest (ROI, i.e., Countryside, Suburbs, and City Center) were extracted and their correlations were investigated. A maximum variation of 6.4 • C in the LST values between City Center and Countryside was highlighted, confirming the presence of the SUHI phenomenon even in a medium-sized municipality like Modena. The implemented procedure demonstrates that satellite data are suitable for SUHI identification and estimation, therefore it could be a useful tool for public administration for urban planning policies.Keywords: urban heat island; land surface temperature; remote sensing; Landsat-8; semi-automatic classification plugin; QGIS; global warming; urbanization BackgroundAbout half of the world population lives in urban areas [1]. The global urbanization rate is expected to increase by 70% compared to the current world population [2], both because of the continued emergence of new urban areas [3] and because of the constant population migration from rural to urban and suburban areas [4,5]. It is not therefore surprising that the negative impacts of urbanization are an ever-growing global concern [6-10]. Urbanization has a negative impact on the environment, mainly due to pollution, changes in the physical and chemical properties of the atmosphere, and in the type of cover of the soil surface [11]. These phenomena lead to so-called Urban Heat Islands (UHI), namely urban areas where the atmospheric temperature is significantly higher than that in the surrounding rural areas [12]. The presence of UHIs is an increasing phenomenon studied by the international scientific community because of its dangerous and significant effects. In fact, the temperature increase has effects on the environment (higher temperatures cause higher energy consumption, photochemical smog, and worsening of the air quality), on the climate and on human health [13][14][15][16].

show abstract

Influence of climate change on the frequency of daytime temperature inversions and stagnation events in the Po Valley: historical trend and future projections

Cited by 64 publications

References 8 publications

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

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

Transport of Po Valley aerosol pollution to the northwestern Alps. Part 1: phenomenology

A Multi-Temporal Analyses of Land Surface Temperature Using Landsat-8 Data and Open Source Software: The Case Study of Modena, Italy

Contact Info

Product

Resources

About