Special Issue "Climate Variability and Change in the 21th Century"

A special issue of Climate (ISSN 2225-1154).

Deadline for manuscript submissions: closed (31 January 2019)

Special Issue Editors

Guest Editor
Dr. Stefanos Stefanidis

Laboratory of Mountainous Water Management and Control, Faculty of Forestry and Natural Environment, Aristotle University of Thessaloniki, Thessaloníki, Greece
Website | E-Mail
Interests: soil erosion and mountainous catchment degrafation; landslide management and control; cause and mechanism of debris and mud flow phenomena; torrent control works; check dams design and dimmensioning; sediment sources areas; flash floods phenomena; forest hydrology
Guest Editor
Dr. Konstantia Tolika

Department of Meteorology and Climatology, School of Geology, Aristotle University of Thessaloniki,University Campus, 54124, Thessaloniki, Greece
Website | E-Mail
Interests: climate change, climate variability, regional climate models, extreme events, atmospheric circulation, artificial neural networks

Special Issue Information

Dear Colleagues,

During the last decades, there is a growing interest in climate variability and change by scientific community, due to their economic, social and ecological impacts. Knowledge of spatial and temporal climate distribution is fundamental to several disciplines such as geography, hydrology, forest management, agriculture, ecology and others. Moreover future climate projections is essential for rural development and planning and infrastructure works programming.

Topics of interest include, but are not limited to:

  • Regional Climate Models
  • Climate Variability
  • Climate Change Impacts
  • Dynamic and Statistical Downscaling Techniques
  • Spatial Mapping of Meteorological Parameters

Mr. Stefanos Stefanidis
Dr. Konstantia Tolika
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All papers will be peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Climate is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 550 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • climate change
  • spatial and temporal distribution

Published Papers (14 papers)

View options order results:
result details:
Displaying articles 1-14
Export citation of selected articles as:

Research

Open AccessFeature PaperArticle Constraints to Vegetation Growth Reduced by Region-Specific Changes in Seasonal Climate
Climate 2019, 7(2), 27; https://doi.org/10.3390/cli7020027
Received: 31 October 2018 / Revised: 7 January 2019 / Accepted: 10 January 2019 / Published: 1 February 2019
PDF Full-text (6797 KB) | HTML Full-text | XML Full-text
Abstract
We qualitatively and quantitatively assessed the factors related to vegetation growth using Earth system models and corroborated the results with historical climate observations. The Earth system models showed a systematic greening by the late 21st century, including increases of up to 100% in [...] Read more.
We qualitatively and quantitatively assessed the factors related to vegetation growth using Earth system models and corroborated the results with historical climate observations. The Earth system models showed a systematic greening by the late 21st century, including increases of up to 100% in Gross Primary Production (GPP) and 60% in Leaf Area Index (LAI). A subset of models revealed that the radiative effects of CO2 largely control changes in climate, but that the CO2 fertilization effect dominates the greening. The ensemble of Earth system model experiments revealed that the feedback of surface temperature contributed to 17% of GPP increase in temperature-limited regions, and radiation increase accounted for a 7% increase of GPP in radiation-limited areas. These effects are corroborated by historical observations. For example, observations confirm that cloud cover has decreased over most land areas in the last three decades, consistent with a CO2-induced reduction in transpiration. Our results suggest that vegetation may thrive in the starkly different climate expected over the coming decades, but only if plants harvest the sort of hypothesized physiological benefits of higher CO2 depicted by current Earth system models. Full article
(This article belongs to the Special Issue Climate Variability and Change in the 21th Century)
Figures

Figure 1

Open AccessArticle Influence of Bias Correction Methods on Simulated Köppen−Geiger Climate Zones in Europe
Climate 2019, 7(2), 18; https://doi.org/10.3390/cli7020018
Received: 7 December 2018 / Revised: 18 January 2019 / Accepted: 19 January 2019 / Published: 22 January 2019
PDF Full-text (7095 KB) | HTML Full-text | XML Full-text
Abstract
Our goal was to investigate the influence of bias correction methods on climate simulations over the European domain. We calculated the Köppen−Geiger climate classification using five individual regional climate models (RCM) of the ENSEMBLES project in the European domain during the period 1961−1990. [...] Read more.
Our goal was to investigate the influence of bias correction methods on climate simulations over the European domain. We calculated the Köppen−Geiger climate classification using five individual regional climate models (RCM) of the ENSEMBLES project in the European domain during the period 1961−1990. The simulated precipitation and temperature data were corrected using the European daily high-resolution gridded dataset (E-OBS) observed data by five methods: (i) the empirical quantile mapping of precipitation and temperature, (ii) the quantile mapping of precipitation and temperature based on gamma and Generalized Pareto Distribution of precipitation, (iii) local intensity scaling, (iv) the power transformation of precipitation and (v) the variance scaling of temperature bias corrections. The individual bias correction methods had a significant effect on the climate classification, but the degree of this effect varied among the RCMs. Our results on the performance of bias correction differ from previous results described in the literature where these corrections were implemented over river catchments. We conclude that the effect of bias correction may depend on the region of model domain. These results suggest that distribution free bias correction approaches are the most suitable for large domain sizes such as the pan-European domain. Full article
(This article belongs to the Special Issue Climate Variability and Change in the 21th Century)
Figures

Figure 1

Open AccessArticle Analysis of Climate Change in the Caucasus Region: End of the 20th–Beginning of the 21st Century
Climate 2019, 7(1), 11; https://doi.org/10.3390/cli7010011
Received: 15 December 2018 / Revised: 29 December 2018 / Accepted: 4 January 2019 / Published: 10 January 2019
PDF Full-text (3401 KB) | HTML Full-text | XML Full-text
Abstract
The study of climate, in such a diverse climatic region as the Caucasus, is necessary in order to evaluate the influence of local factors on the formation of temperature and precipitation regimes in its various climatic zones. This study is based on the [...] Read more.
The study of climate, in such a diverse climatic region as the Caucasus, is necessary in order to evaluate the influence of local factors on the formation of temperature and precipitation regimes in its various climatic zones. This study is based on the instrumental data (temperatures and precipitation) from 20 weather stations, located on the territory of the Caucasian region during 1961–2011. Mathematical statistics, trend analysis, and rescaled range Methods were used. It was found that the warming trend prevailed in all climatic zones, it intensified since the beginning of global warming (since 1976), while the changes in precipitation were not so unidirectional. The maximum warming was observed in the summer (on average by 0.3 °C/10 years) in all climatic zones. Persistence trends were investigated using the Hurst exponent H (range of variation 0–1), which showed a higher trend persistence of annual mean temperature changes (H = 0.8) compared to annual sum precipitations (H = 0.64). Spatial-correlation analysis performed for precipitations and temperatures showed a rapid decrease in the correlation between precipitations at various weather stations from R = 1 to R = 0.5, on a distance scale from 0 to 200 km. In contrast to precipitation, a high correlation (R = 1.0–0.7) was observed between regional weather stations temperatures at a distance scale from 0 to 1000 km, which indicates synchronous temperature changes in all climatic zones (unlike precipitation). Full article
(This article belongs to the Special Issue Climate Variability and Change in the 21th Century)
Figures

Figure 1

Open AccessArticle Assessing Heat Waves over Greece Using the Excess Heat Factor (EHF)
Climate 2019, 7(1), 9; https://doi.org/10.3390/cli7010009
Received: 23 November 2018 / Revised: 21 December 2018 / Accepted: 29 December 2018 / Published: 7 January 2019
PDF Full-text (5562 KB) | HTML Full-text | XML Full-text
Abstract
Heat waves are considered one of the most noteworthy extreme events all over the world due to their crucial impacts on both society and the environment. For the present article, a relatively new heat wave index, which was primarily introduced for the study [...] Read more.
Heat waves are considered one of the most noteworthy extreme events all over the world due to their crucial impacts on both society and the environment. For the present article, a relatively new heat wave index, which was primarily introduced for the study of extreme warming conditions over Australia (Excess Heat Factor (EHF, hereafter)), was applied over Greece (eastern Mediterranean) for a 55-year period in order to examine its applicability to a region with different climatic characteristics (compared to Australia) and its ability to define previous exceptional heat waves. The computation of the EHF index for the period 1958–2012 demonstrated that, during the warm period of the year (June, July, August, and September (JJAS)), Greece experiences approximately 20 days per year with positive anomalous conditions (EHF > 0) with positive statistically significant trends for all stations under study. Moreover, an average of 128 spells with a duration of 3 to 10 consecutive days with positive EHF values were found during the examined 55-year period. As the duration of the spell was extended, their frequency lessened. Finally, it was found that the EHF index not only detected, identified, and described efficiently the characteristics of the heat waves, but it also provided additional useful information regarding the impact of these abnormal warming conditions on the human ability to adapt to them. Full article
(This article belongs to the Special Issue Climate Variability and Change in the 21th Century)
Figures

Figure 1

Open AccessArticle Statistical Analysis of Recent and Future Rainfall and Temperature Variability in the Mono River Watershed (Benin, Togo)
Climate 2019, 7(1), 8; https://doi.org/10.3390/cli7010008
Received: 17 November 2018 / Revised: 23 December 2018 / Accepted: 27 December 2018 / Published: 6 January 2019
PDF Full-text (2912 KB) | HTML Full-text | XML Full-text
Abstract
This paper assessed the current and mid-century trends in rainfall and temperature over the Mono River watershed. It considered observation data for the period 1981–2010 and projection data from the regional climate model (RCM), REMO, for the period 2018–2050 under emission scenarios RCP4.5 [...] Read more.
This paper assessed the current and mid-century trends in rainfall and temperature over the Mono River watershed. It considered observation data for the period 1981–2010 and projection data from the regional climate model (RCM), REMO, for the period 2018–2050 under emission scenarios RCP4.5 and RCP8.5. Rainfall data were interpolated using ordinary kriging. Mann-Kendall, Pettitt and Standardized Normal Homogeneity (SNH) tests were used for trends and break-points detection. Rainfall interannual variability analysis was based on standardized precipitation index (SPI), whereas anomalies indices were considered for temperature. Results revealed that on an annual scale and all over the watershed, temperature and rainfall showed an increasing trend during the observation period. By 2050, both scenarios projected an increase in temperature compared to the baseline period 1981–2010, whereas annual rainfall will be characterized by high variabilities. Rainfall seasonal cycle is expected to change in the watershed: In the south, the second rainfall peak, which usually occurs in September, will be extended to October with a higher value. In the central and northern parts, rainfall regime is projected to be characterized by late onsets, a peak in September and lower precipitation until June and higher thereafter. The highest increase and decrease in monthly precipitation are expected in the northern part of the watershed. Therefore, identifying relevant adaptation strategies is recommended. Full article
(This article belongs to the Special Issue Climate Variability and Change in the 21th Century)
Figures

Figure 1

Open AccessArticle Multi-Model Forecasts of Very-Large Fire Occurences during the End of the 21st Century
Climate 2018, 6(4), 100; https://doi.org/10.3390/cli6040100
Received: 9 November 2018 / Revised: 12 December 2018 / Accepted: 13 December 2018 / Published: 19 December 2018
Cited by 1 | PDF Full-text (3221 KB) | HTML Full-text | XML Full-text | Supplementary Files
Abstract
Climate change is anticipated to influence future wildfire activity in complicated, and potentially unexpected ways. Specifically, the probability distribution of wildfire size may change so that incidents that were historically rare become more frequent. Given that fires in the upper tails of the [...] Read more.
Climate change is anticipated to influence future wildfire activity in complicated, and potentially unexpected ways. Specifically, the probability distribution of wildfire size may change so that incidents that were historically rare become more frequent. Given that fires in the upper tails of the size distribution are associated with serious economic, public health, and environmental impacts, it is important for decision-makers to plan for these anticipated changes. However, at least two kinds of structural uncertainties hinder reliable estimation of these quantities—those associated with the future climate and those associated with the impacts. In this paper, we incorporate these structural uncertainties into projections of very-large fire (VLF)—those in the upper 95th percentile of the regional size distribution—frequencies in the Continental United States during the last half of the 21st century by using Bayesian model averaging. Under both moderate and high carbon emission scenarios, large increases in VLF frequency are predicted, with larger increases typically observed under the highest carbon emission scenarios. We also report other changes to future wildfire characteristics such as large fire frequency, seasonality, and the conditional likelihood of very-large fire events. Full article
(This article belongs to the Special Issue Climate Variability and Change in the 21th Century)
Figures

Figure 1

Open AccessFeature PaperArticle Objective Definition of Climatologically Homogeneous Areas in the Southern Balkans Based on the ERA5 Data Set
Climate 2018, 6(4), 96; https://doi.org/10.3390/cli6040096
Received: 15 November 2018 / Revised: 5 December 2018 / Accepted: 5 December 2018 / Published: 7 December 2018
PDF Full-text (4425 KB) | HTML Full-text | XML Full-text
Abstract
An objective definition of climatologically homogeneous areas in the southern Balkans is attempted with the use of daily 0.25° × 0.25° ERA5 meteorological data of air temperature, dew point, zonal and meridional wind components, Convective Available Potential Energy, Convective Inhibition, and total cloud [...] Read more.
An objective definition of climatologically homogeneous areas in the southern Balkans is attempted with the use of daily 0.25° × 0.25° ERA5 meteorological data of air temperature, dew point, zonal and meridional wind components, Convective Available Potential Energy, Convective Inhibition, and total cloud cover. The classification of the various grid points into climatologically homogeneous areas is carried out by applying Principal Component Analysis and K-means Cluster Analysis on the mean spatial anomaly patterns of the above parameters for the 10-year period of 2008 to 2017. According to the results, 12 climatologically homogenous areas are found. From these areas, eight are mainly over the sea and four are mainly over the land. The mean intra-annual variations of the spatial anomalies of the above parameters reveal the main climatic characteristics of these areas for the above period. These characteristics refer, for example, to how much warmer or cloudy the climate of a specific area is in a specific season relatively to the rest of the geographical domain. The continentality, the latitude, the altitude, the orientation, and the seasonal variability of the thermal and dynamic factors affecting the Mediterranean region are responsible for the climate characteristics of the 12 areas and the differences among them. Full article
(This article belongs to the Special Issue Climate Variability and Change in the 21th Century)
Figures

Figure 1

Open AccessArticle Time Series Analysis of MODIS-Derived NDVI for the Hluhluwe-Imfolozi Park, South Africa: Impact of Recent Intense Drought
Climate 2018, 6(4), 95; https://doi.org/10.3390/cli6040095
Received: 8 October 2018 / Revised: 7 November 2018 / Accepted: 14 November 2018 / Published: 30 November 2018
PDF Full-text (8317 KB) | HTML Full-text | XML Full-text
Abstract
The variability of temperature and precipitation influenced by El Niño-Southern Oscillation (ENSO) is potentially one of key factors contributing to vegetation product in southern Africa. Thus, understanding large-scale ocean–atmospheric phenomena like the ENSO and Indian Ocean Dipole/Dipole Mode Index (DMI) is important. In [...] Read more.
The variability of temperature and precipitation influenced by El Niño-Southern Oscillation (ENSO) is potentially one of key factors contributing to vegetation product in southern Africa. Thus, understanding large-scale ocean–atmospheric phenomena like the ENSO and Indian Ocean Dipole/Dipole Mode Index (DMI) is important. In this study, 16 years (2002–2017) of Moderate Resolution Imaging Spectroradiometer (MODIS) Terra/Aqua 16-day normalized difference vegetation index (NDVI), extracted and processed using JavaScript code editor in the Google Earth Engine (GEE) platform was used to analyze the vegetation response pattern of the oldest proclaimed nature reserve in Africa, the Hluhluwe-iMfolozi Park (HiP) to climatic variability. The MODIS enhanced vegetation index (EVI), burned area index (BAI), and normalized difference infrared index (NDII) were also analyzed. The study used the Modern Retrospective Analysis for the Research Application (MERRA) model monthly mean soil temperature and precipitations. The Global Land Data Assimilation System (GLDAS) evapotranspiration (ET) data were used to investigate the HiP vegetation water stress. The region in the southern part of the HiP which has land cover dominated by savanna experienced the most impact of the strong El Niño. Both the HiP NDVI inter-annual Mann–Kendal trend test and sequential Mann–Kendall (SQ-MK) test indicated a significant downward trend during the El Niño years of 2003 and 2014–2015. The SQ-MK significant trend turning point which was thought to be associated with the 2014–2015 El Niño periods begun in November 2012. The wavelet coherence and coherence phase indicated a positive teleconnection/correlation between soil temperatures, precipitation, soil moisture (NDII), and ET. This was explained by a dominant in-phase relationship between the NDVI and climatic parameters especially at a period band of 8–16 months. Full article
(This article belongs to the Special Issue Climate Variability and Change in the 21th Century)
Figures

Graphical abstract

Open AccessArticle Selecting and Downscaling a Set of Climate Models for Projecting Climatic Change for Impact Assessment in the Upper Indus Basin (UIB)
Climate 2018, 6(4), 89; https://doi.org/10.3390/cli6040089
Received: 26 September 2018 / Revised: 26 October 2018 / Accepted: 10 November 2018 / Published: 14 November 2018
PDF Full-text (6935 KB) | HTML Full-text | XML Full-text | Supplementary Files
Abstract
This study focusses on identifying a set of representative climate model projections for the Upper Indus Basin (UIB). Although a large number of General Circulation Models (GCM) predictor sets are available nowadays in the CMIP5 archive, the issue of their reliability for specific [...] Read more.
This study focusses on identifying a set of representative climate model projections for the Upper Indus Basin (UIB). Although a large number of General Circulation Models (GCM) predictor sets are available nowadays in the CMIP5 archive, the issue of their reliability for specific regions must still be confronted. This situation makes it imperative to sort out the most appropriate single or small-ensemble set of GCMs for the assessment of climate change impacts in a region. Here a set of different approaches is adopted and applied for the step-wise shortlisting and selection of appropriate climate models for the UIB under two RCPs: RCP 4.5 and RCP 8.5, based on: (a) range of projected mean changes, (b) range of projected extreme changes, and (c) skill in reproducing the past climate. Furthermore, because of higher uncertainties in climate projection for high mountainous regions like the UIB, a wider range of future GCM climate projections is considered by using all possible extreme future scenarios (wet-warm, wet-cold, dry-warm, dry-cold). Based on this two-fold procedure, a limited number of climate models is pre-selected, from of which the final selection is done by assigning ranks to the weighted score for each of the mentioned selection criteria. The dynamically downscaled climate projections from the Coordinated Regional Downscaling Experiment (CORDEX) available for the top-ranked GCMs are further statistically downscaled (bias-corrected) over the UIB. The downscaled projections up to the year 2100 indicate temperature increases ranging between 2.3 °C and 9.0 °C and precipitation changes that range from a slight annual increase of 2.2% under the drier scenarios to as high as 15.9% in the wet scenarios. Moreover, for all scenarios, future precipitation will be more extreme, as the probability of wet days will decrease, while, at the same time, precipitation intensities will increase. The spatial distribution of the downscaled predictors across the UIB also shows similar patterns for all scenarios, with a distinct precipitation decrease over the south-eastern parts of the basin, but an increase in the northeastern parts. These two features are particularly intense for the “Dry-Warm” and the “Median” scenarios over the late 21st century. Full article
(This article belongs to the Special Issue Climate Variability and Change in the 21th Century)
Figures

Figure 1

Open AccessArticle Estimating the Impact of Artificially Injected Stratospheric Aerosols on the Global Mean Surface Temperature in the 21th Century
Climate 2018, 6(4), 85; https://doi.org/10.3390/cli6040085
Received: 28 September 2018 / Revised: 24 October 2018 / Accepted: 26 October 2018 / Published: 28 October 2018
PDF Full-text (3611 KB) | HTML Full-text | XML Full-text
Abstract
In this paper, we apply the optimal control theory to obtain the analytic solutions of the two-component globally averaged energy balance model in order to estimate the influence of solar radiation management (SRM) operations on the global mean surface temperature in the 21st [...] Read more.
In this paper, we apply the optimal control theory to obtain the analytic solutions of the two-component globally averaged energy balance model in order to estimate the influence of solar radiation management (SRM) operations on the global mean surface temperature in the 21st century. It is assumed that SRM is executed via injection of sulfur aerosols into the stratosphere to limit the global temperature increase in the year 2100 by 1.5 °C and keeping global temperature over the specified period (2020–2100) within 2 °C as required by the Paris climate agreement. The radiative forcing produced by the rise in the atmospheric concentrations of greenhouse gases is defined by the Representative Concentration Pathways and the 1pctCO2 (1% per year CO2 increase) scenario. The goal of SRM is formulated in terms of extremal problem, which entails finding a control function (the albedo of aerosol layer) that minimizes the amount of aerosols injected into the upper atmosphere to satisfy the Paris climate target. For each climate change scenario, the optimal albedo of the aerosol layer and the corresponding global mean surface temperature changes were obtained. In addition, the aerosol emission rates required to create an aerosol cloud with optimal optical properties were calculated. Full article
(This article belongs to the Special Issue Climate Variability and Change in the 21th Century)
Figures

Figure 1

Open AccessArticle A Proposal to Evaluate Drought Characteristics Using Multiple Climate Models for Multiple Timescales
Climate 2018, 6(4), 79; https://doi.org/10.3390/cli6040079
Received: 23 August 2018 / Revised: 16 September 2018 / Accepted: 18 September 2018 / Published: 26 September 2018
PDF Full-text (1936 KB) | HTML Full-text | XML Full-text | Supplementary Files
Abstract
This study presents a method to investigate meteorological drought characteristics using multiple climate models for multiple timescales under two representative concentration pathway (RCP) scenarios, RCP4.5 and RCP8.5, during 2021–2050. The methods of delta change factor, unequal weights, standardized precipitation index, Mann–Kendall and Sen’s [...] Read more.
This study presents a method to investigate meteorological drought characteristics using multiple climate models for multiple timescales under two representative concentration pathway (RCP) scenarios, RCP4.5 and RCP8.5, during 2021–2050. The methods of delta change factor, unequal weights, standardized precipitation index, Mann–Kendall and Sen’s slope are proposed and applied with the main purpose of reducing uncertainty in climate projections and detection of the projection trends in meteorological drought. Climate simulations of three regional climate models driven by four global climate models are used to estimate weights for each run on the basic of rank sum. The reliability is then assessed by comparing a weighted ensemble climate output with observations during 1989–2008. Timescales of 1, 3, 6, 9, 12, and 24 months are considered to calculate the standardized precipitation index, taking the Vu Gia-Thu Bon (VG-TB) as a pilot basin. The results show efficient precipitation simulations using unequal weights. In the same timescales, the occurrence of moderately wet events is smaller than that of moderately dry events under the RCP4.5 scenario during 2021–2050. Events classified as “extremely wet”, “extremely dry”, “very wet” and “severely dry” are expected to rarely occur under the RCP8.5 scenario. Full article
(This article belongs to the Special Issue Climate Variability and Change in the 21th Century)
Figures

Figure 1

Open AccessArticle Spatial and Temporal Rainfall Variability over the Mountainous Central Pindus (Greece)
Climate 2018, 6(3), 75; https://doi.org/10.3390/cli6030075
Received: 19 July 2018 / Revised: 2 September 2018 / Accepted: 5 September 2018 / Published: 6 September 2018
Cited by 1 | PDF Full-text (2383 KB) | HTML Full-text | XML Full-text
Abstract
In this study, the authors evaluated the spatial and temporal variability of rainfall over the central Pindus mountain range. To accomplish this, long-term (1961–2016) monthly rainfall data from nine rain gauges were collected and analyzed. Seasonal and annual rainfall data were subjected to [...] Read more.
In this study, the authors evaluated the spatial and temporal variability of rainfall over the central Pindus mountain range. To accomplish this, long-term (1961–2016) monthly rainfall data from nine rain gauges were collected and analyzed. Seasonal and annual rainfall data were subjected to Mann–Kendall tests to assess the possible upward or downward statistically significant trends and to change-point analyses to detect whether a change in the rainfall time series mean had taken place. Additionally, Sen’s slope method was used to estimate the trend magnitude, whereas multiple regression models were developed to determine the relationship between rainfall and geomorphological factors. The results showed decreasing trends in annual, winter, and spring rainfalls and increasing trends in autumn and summer rainfalls, both not statistically significant, for most stations. Rainfall non-stationarity started to occur in the middle of the 1960s for the annual, autumn, spring, and summer rainfalls and in the early 1970s for the winter rainfall in most of the stations. In addition, the average magnitude trend per decade is approximately −1.9%, −3.2%, +0.7%, +0.2%, and +2.4% for annual, winter, autumn, spring, and summer rainfalls, respectively. The multiple regression model can explain 62.2% of the spatial variability in annual rainfall, 58.9% of variability in winter, 75.9% of variability in autumn, 55.1% of variability in spring, and 32.2% of variability in summer. Moreover, rainfall spatial distribution maps were produced using the ordinary kriging method, through GIS software, representing the major rainfall range within the mountainous catchment of the study area. Full article
(This article belongs to the Special Issue Climate Variability and Change in the 21th Century)
Figures

Figure 1

Open AccessArticle Intercomparison of Univariate and Joint Bias Correction Methods in Changing Climate From a Hydrological Perspective
Climate 2018, 6(2), 33; https://doi.org/10.3390/cli6020033
Received: 26 February 2018 / Revised: 20 April 2018 / Accepted: 23 April 2018 / Published: 26 April 2018
Cited by 3 | PDF Full-text (3899 KB) | HTML Full-text | XML Full-text | Supplementary Files
Abstract
In this paper, the ability of two joint bias correction algorithms to adjust biases in daily mean temperature and precipitation is compared against two univariate quantile mapping methods when constructing projections from years 1981–2010 to early (2011–2040) and late (2061–2090) 21st century periods. [...] Read more.
In this paper, the ability of two joint bias correction algorithms to adjust biases in daily mean temperature and precipitation is compared against two univariate quantile mapping methods when constructing projections from years 1981–2010 to early (2011–2040) and late (2061–2090) 21st century periods. Using both climate model simulations and the corresponding hydrological model simulations as proxies for the future in a pseudo-reality framework, these methods are inter-compared in a cross-validation manner in order to assess to what extent the more sophisticated methods have added value, particularly from the hydrological modeling perspective. By design, bi-variate bias correction methods improve the inter-variable relationships in the baseline period. Cross-validation results show, however, that both in the early and late 21st century conditions the additional benefit of using bi-variate bias correction methods is not obvious, as univariate methods have a comparable performance. From the evaluated hydrological variables, the added value is most clearly seen in the simulated snow water equivalent. Although not having the best performance in adjusting the temperature and precipitation distributions, quantile mapping applied as a delta change method performs well from the hydrological modeling point of view, particularly in the early 21st century conditions. This suggests that retaining the observed correlation structures of temperature and precipitation might in some cases be sufficient for simulating future hydrological climate change impacts. Full article
(This article belongs to the Special Issue Climate Variability and Change in the 21th Century)
Figures

Figure 1

Open AccessArticle Projected Changes in Precipitation, Temperature, and Drought across California’s Hydrologic Regions in the 21st Century
Climate 2018, 6(2), 31; https://doi.org/10.3390/cli6020031
Received: 21 March 2018 / Revised: 14 April 2018 / Accepted: 20 April 2018 / Published: 23 April 2018
Cited by 1 | PDF Full-text (6729 KB) | HTML Full-text | XML Full-text
Abstract
This study investigated potential changes in future precipitation, temperature, and drought across 10 hydrologic regions in California. The latest climate model projections on these variables through 2099 representing the current state of the climate science were applied for this purpose. Changes were explored [...] Read more.
This study investigated potential changes in future precipitation, temperature, and drought across 10 hydrologic regions in California. The latest climate model projections on these variables through 2099 representing the current state of the climate science were applied for this purpose. Changes were explored in terms of differences from a historical baseline as well as the changing trend. The results indicate that warming is expected across all regions in all temperature projections, particularly in late-century. There is no such consensus on precipitation, with projections mostly ranging from −25% to +50% different from the historical baseline. There is no statistically significant increasing or decreasing trend in historical precipitation and in the majority of the projections on precipitation. However, on average, precipitation is expected to increase slightly for most regions. The increases in late-century are expected to be more pronounced than the increases in mid-century. The study also shows that warming in summer and fall is more significant than warming in winter and spring. The study further illustrates that, compared to wet regions, dry regions are projected to become more arid. The inland eastern regions are expecting higher increases in temperature than other regions. Particularly, the coolest region, North Lahontan, tends to have the highest increases in both minimum and maximum temperature and a significant amount of increase in wet season precipitation, indicative of increasing flood risks in this region. Overall, these findings are meaningful from both scientific and practical perspectives. From a scientific perspective, these findings provide useful information that can be utilized to improve the current flood and water supply forecasting models or develop new predictive models. From a practical perspective, these findings can help decision-makers in making different adaptive strategies for different regions to address adverse impacts posed by those potential changes. Full article
(This article belongs to the Special Issue Climate Variability and Change in the 21th Century)
Figures

Figure 1

Climate EISSN 2225-1154 Published by MDPI AG, Basel, Switzerland RSS E-Mail Table of Contents Alert
Back to Top