scholarly journals Analysis of Climate Change Effects on Surface Temperature in Central-Italy Lakes Using Satellite Data Time-Series

2021 ◽  
Vol 14 (1) ◽  
pp. 117
Author(s):  
Davide De Santis ◽  
Fabio Del Frate ◽  
Giovanni Schiavon
Keyword(s):  
Climate Change ◽  
Time Series ◽  
Surface Temperature ◽  
Satellite Data ◽  
Water Surface ◽  
Central Italy ◽  
Large Lakes ◽  
Climate Change Effects ◽  
Surface Temperatures ◽  
The Impact

Evaluation of the impact of climate change on water bodies has been one of the most discussed open issues of recent years. The exploitation of satellite data for the monitoring of water surface temperatures, combined with ground measurements where available, has already been shown in several previous studies, but these studies mainly focused on large lakes around the world. In this work the water surface temperature characterization during the last few decades of two small–medium Italian lakes, Lake Bracciano and Lake Martignano, using satellite data is addressed. The study also takes advantage of the last space-borne platforms, such as Sentinel-3. Long time series of clear sky conditions and atmospherically calibrated (using a simplified Planck’s Law-based algorithm) images were processed in order to derive the lakes surface temperature trends from 1984 to 2019. The results show an overall increase in water surface temperatures which is more evident on the smallest and shallowest of the two test sites. In particular, it was observed that, since the year 2000, the surface temperature of both lakes has risen by about 0.106 °C/year on average, which doubles the rate that can be retrieved by considering the whole period 1984–2019 (0.053 °C/year on average).

Analysis of radar and thermal satellite data time-series for understanding the long-term impact of land surface temperature changes on forests

2020 ◽  
Author(s):  
Maria Prodromou ◽  
Anastasia Yfantidou ◽  
Christos Theocharidis ◽  
Milto Miltiadou ◽  
Chris Danezis
Keyword(s):  
Climate Change ◽  
Time Series ◽  
Surface Temperature ◽  
Land Surface Temperature ◽  
Satellite Data ◽  
Forest Fires ◽  
Land Surface ◽  
Forest Canopy ◽  
Development Fund ◽  
The Impact

<p>Forests are globally an important environmental and ecological resource since they retrain water through their routes and therefore limit flooding events and soil erosion from moderate rainfall. They also act as carbon sinks, provide food, clean water and natural habitat for humans and other species, including threatened ones. Recent reports stressed the vulnerability of EU forest ecosystem to climate change impacts (EEA, 2012) (IPPC, et al., 2014). Climate change is a significant factor in the increasing forest fires and tree species being unable to adapt to the severity and frequency of drought during the summer period. Consequently, the possibility of increased insect pests and tree diseases is high as trees have been weakened by the extreme weather conditions. In Cyprus, there are two types of pine trees that exists on Troodos mountains, Pinus Nigra and Pinus Brutia, that may have been influenced by the reduced snowfall and extended summer droughts during the last decades.</p><p> </p><p>The overarching aim of this project is to research the impact of Land Surface Temperature on Cypriot forests on Troodos mountains by analysing time-series of radar and thermal satellite data. Impacts may include forest decline that does not relate to fire events, decreased forest density and alternations to timing of forest blooming initiation, duration and termination. Radar systems emitted pulses that can penetrate forest canopy due to the size of its wavelength and, therefore, collect information between tree branches without being affected by clouds. This presentation will focus on radar analysis conducted; testing of various methods, and how the processing pipeline has been automated.</p><p> </p><p>The project ‘ASTARTE’ (EXCELLENCE/0918/0341) is co-financed by the European Regional Development Fund and the Republic of Cyprus through the Research Innovation Foundation.</p>

scholarly journals A Transient Stochastic Rainfall Generator for Climate Changes Analysis at Hydrological Scales in Central Italy

Atmosphere ◽  
2020 ◽  
Vol 11 (12) ◽  
pp. 1292
Author(s):  
Davide Luciano De Luca ◽  
Andrea Petroselli ◽  
Luciano Galasso
Keyword(s):  
Climate Change ◽  
Time Series ◽  
Climate Changes ◽  
Probability Distributions ◽  
Central Italy ◽  
Kendall Test ◽  
Rain Gauge ◽  
Rainfall Series ◽  
Rainfall Time Series ◽  
Climate Change Effects

In this work, a comprehensive methodology for trend investigation in rainfall time series, in a climate-change context, is proposed. The crucial role played by a Stochastic Rainfall Generator (SRG) is highlighted. Indeed, SRG application is particularly suitable to obtain rainfall series that are representative of future rainfall series at hydrological scales. Moreover, the methodology investigates the climate change effects on several timescales, considering the well-known Mann–Kendall test and analyzing the variation of probability distributions of extremes and hazard. The hypothesis is that the effects of climate changes could be more evident only for specific time resolutions, and only for some considered aspects. Applications regarded the rainfall time series of the Viterbo rain gauge in Central Italy.

On the impact of the hydrological model and catchment hydrology on the design flood estimation in a small catchment in Central Italy affected by the recent 2016 earthquake events

2020 ◽  
Author(s):  
Shima Azimi ◽  
Silvia Barbetta ◽  
Tommaso Moramarco ◽  
Angelica Tarpanelli ◽  
Stefania Camici ◽  
...  
Keyword(s):  
Climate Change ◽  
Time Series ◽  
River Discharge ◽  
Hydrological Model ◽  
Central Italy ◽  
Change Scenario ◽  
Catchment Hydrology ◽  
Design Flood ◽  
Flood Estimation ◽  
The Impact

<p>Flood is one of the most frequent disasters which dangerously impacts societies and economies worldwide. Floodplain management and hydraulic risk analysis based on design flood estimation are essential tools to reduce damages and save human lives. Flood Frequency Analysis (FFA) has been classically used to derive design river discharge estimates, however, the scarce availability of discharge observations, especially in small catchments (<150 km2), makes its application not always possible. In addition, with the projections foreseen by the International Panel on Climate Change (IPCC) the use of FFA might lead to incorrect estimates of design river discharge as FFA is based on the concept of stationarity. Generally, long rainfall and temperature time series are much more available than discharge observations but their temporal coverage is often not sufficient for carrying out FFA via a hydrological simulation.</p><p>To handle these drawbacks, the combination of a stochastic generation of rainfall and temperature time series, Regional Circulation Model (RCM) projections and continuous hydrological models provides a reliable tool for obtaining long river discharge time series to implement FFA. However, design flood estimations can be significantly uncertain due to several factors such as 1) the specific model structure, parameterizations and processes representation, 2) the catchment hydrology and 3) the specific climate change scenario.</p><p>The primary objective of this study is to explore the sensitivity of the design river discharge estimates to the hydrological model complexity and parameterization. For this, three continuous hydrological distributed models named the Modello Idrologico SemiDistribuito in continuo (MISDc), the Soil & Water Assessment Tool (SWAT) and GEOFrame NewAGE model are forced with long timeseries of rainfall and temperature obtained via the Neyman-Scott rectangular pulse model (NSRP) for stochastic rainfall generation, and the fractionally differenced ARIMA model (FARIMA) for stochastic temperature generation. A secondary objective is to understand the impact of climate change and the catchment hydrology on the design river discharge estimates via the use of different RCM projections.</p><p>The study is carried in the Upper Nera catchment in Central Italy which was impacted by the recent 2016 earthquake and for which is necessary to identify hydraulic risk mitigation measures and adaptation for a forward planning in the floodplain areas where new settlements will be rebuilt.</p><p>Preliminary results suggest the high dependency of the design river discharge estimates to the chosen hydrological model and a different response of the sub-catchments to the climate change scenario.</p>

scholarly journals Surface Heat Budget estimation for Laurance Lake, US

2021 ◽  
Vol 877 (1) ◽  
pp. 012005
Author(s):  
Dahlia S. Abed-Zaid ◽  
Hussein A. M. Al-Zubaidi
Keyword(s):  
Surface Temperature ◽  
Water Surface ◽  
Heat Budget ◽  
Meteorological Data ◽  
Longwave Radiation ◽  
Atmospheric Conditions ◽  
Large Lakes ◽  
Water Surface Temperature ◽  
Maximum Water ◽  
The Many

Abstract Estimating heat budget factors are important to understand the many physical processes of large lakes and their reaction to the atmosphere. Some of these components are affected by water temperature, while the other depends on atmospheric conditions. This paper estimates the total heat flux for Lawrence lake via a code developed in MATLAB environment. The code can deal with different time resolutions if the lake water surface temperature data were at different time resolutions from the meteorological data. Results showed that solar energy peaks at 842 Watt/m2 at 540 Julian day, which is very normal for a sunny summer day, while the longwave radiation has 204 Watt/m2 as a min value. The back radiation did not make any reaction for the variation, but it revealed a small gradient. Furthermore, evaporation recorded - 67 Watt/m2 as a minimum value at 659 Julian day and 360 Watt/m2 as a maximum value at 578.43 Julian day close to the maximum water surface temperature event.

scholarly journals Evaluation of a Global Vegetation Model using time series of satellite vegetation indices

2011 ◽  
Vol 4 (4) ◽  
pp. 1103-1114 ◽  
Author(s):  
F. Maignan ◽  
F.-M. Bréon ◽  
F. Chevallier ◽  
N. Viovy ◽  
P. Ciais ◽  
...  
Keyword(s):  
Climate Change ◽  
Time Series ◽  
Vegetation Index ◽  
Vegetation Indices ◽  
Global Scale ◽  
Vegetation Dynamic ◽  
Rate Of Increase ◽  
Vegetation Models ◽  
Global Vegetation ◽  
The Impact

Abstract. Atmospheric CO2 drives most of the greenhouse effect increase. One major uncertainty on the future rate of increase of CO2 in the atmosphere is the impact of the anticipated climate change on the vegetation. Dynamic Global Vegetation Models (DGVM) are used to address this question. ORCHIDEE is such a DGVM that has proven useful for climate change studies. However, there is no objective and methodological way to accurately assess each new available version on the global scale. In this paper, we submit a methodological evaluation of ORCHIDEE by correlating satellite-derived Vegetation Index time series against those of the modeled Fraction of absorbed Photosynthetically Active Radiation (FPAR). A perfect correlation between the two is not expected, however an improvement of the model should lead to an increase of the overall performance. We detail two case studies in which model improvements are demonstrated, using our methodology. In the first one, a new phenology version in ORCHIDEE is shown to bring a significant impact on the simulated annual cycles, in particular for C3 Grasses and C3 Crops. In the second case study, we compare the simulations when using two different weather fields to drive ORCHIDEE. The ERA-Interim forcing leads to a better description of the FPAR interannual anomalies than the simulation forced by a mixed CRU-NCEP dataset. This work shows that long time series of satellite observations, despite their uncertainties, can identify weaknesses in global vegetation models, a necessary first step to improving them.

Effects of climate change on babesiosis vectors.

2021 ◽  
pp. 223-227
Author(s):  
Jeremy Gray
Keyword(s):  
Climate Change ◽  
Ixodes Ricinus ◽  
Climate Change Impact ◽  
Dermacentor Reticulatus ◽  
Impact Of Climate Change ◽  
Climate Change Effects ◽  
Haemaphysalis Punctata ◽  
Change Impact ◽  
Abundance And Distribution ◽  
The Impact

Abstract This chapter discusses the impact of climate change on the abundance and distribution of babesiosis vectors and, by implication, transmission of Babesia spp. It discusses evidence for climate change impact on the vectors Ixodes ricinus, Dermacentor reticulatus, Haemaphysalis punctata and Hyalomma spp. as well as the absence of evidence of the same climate change effects on the vectors Rhipicephalus spp. and I. scapularis.

scholarly journals A Novel Method for the Homogenization of Daily Temperature Series and Its Relevance for Climate Change Analysis

2010 ◽  
Vol 23 (19) ◽  
pp. 5325-5331 ◽  
Author(s):  
Andrea Toreti ◽  
Franz G. Kuglitsch ◽  
Elena Xoplaki ◽  
Jürg Luterbacher ◽  
Heinz Wanner
Keyword(s):  
Climate Change ◽  
Time Series ◽  
Eastern Mediterranean ◽  
Higher Order ◽  
Temperature Time Series ◽  
Daily Temperature ◽  
Change Analysis ◽  
Higher Order Moments ◽  
The Impact ◽  
Temperature Time

Abstract Instrumental daily series of temperature are often affected by inhomogeneities. Several methods are available for their correction at monthly and annual scales, whereas few exist for daily data. Here, an improved version of the higher-order moments (HOM) method, the higher-order moments for autocorrelated data (HOMAD), is proposed. HOMAD addresses the main weaknesses of HOM, namely, data autocorrelation and the subjective choice of regression parameters. Simulated series are used for the comparison of both methodologies. The results highlight and reveal that HOMAD outperforms HOM for small samples. Additionally, three daily temperature time series from stations in the eastern Mediterranean are used to show the impact of homogenization procedures on trend estimation and the assessment of extremes. HOMAD provides an improved correction of daily temperature time series and further supports the use of corrected daily temperature time series prior to climate change assessment.

scholarly journals The Impact of Climate Change on Material Degradation Criteria in Heritage over Iran: Regional Climate Model Evaluation

2020 ◽  
Vol 172 ◽  
pp. 02006
Author(s):  
Hamed Hedayatnia ◽  
Marijke Steeman ◽  
Nathan Van Den Bossche
Keyword(s):  
Climate Change ◽  
Climate Models ◽  
Climate Model ◽  
Regional Climate ◽  
Regional Climate Models ◽  
Salt Crystallization ◽  
Climate Modelling ◽  
Impact Of Climate Change ◽  
Climate Change Effects ◽  
The Impact

Understanding how climate change accelerates or slows down the process of material deterioration is the first step towards assessing adaptive approaches for the preservation of historical heritage. Analysis of the climate change effects on the degradation risk assessment parameters like salt crystallization cycles is of crucial importance when considering mitigating actions. Due to the vulnerability of cultural heritage in Iran to climate change, the impact of this phenomenon on basic parameters plus variables more critical to building damage like salt crystallization index needs to be analyzed. Regional climate modelling projections can be used to asses the impact of climate change effects on heritage. The output of two different regional climate models, the ALARO-0 model (Ghent University-RMI, Belgium) and the REMO model (HZG-GERICS, Germany), is analyzed to find out which model is more adapted to the region. So the focus of this research is mainly on the evaluation to determine the reliability of both models over the region. For model validation, a comparison between model data and observations was performed in 4 different climate zones for 30 years to find out how reliable these models are in the field of building pathology.

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