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Climate, Volume 6, Issue 2 (June 2018)

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Cover Story (view full-size image) Of fruit crops, grape is the most largely cultivated and has the highest economic importance [...] Read more.
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Open AccessArticle Air-Temperature Response to Neighborhood-Scale Variations in Albedo and Canopy Cover in the Real World: Fine-Resolution Meteorological Modeling and Mobile Temperature Observations in the Los Angeles Climate Archipelago
Climate 2018, 6(2), 53; https://doi.org/10.3390/cli6020053
Received: 11 May 2018 / Revised: 12 June 2018 / Accepted: 14 June 2018 / Published: 17 June 2018
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Abstract
To identify and characterize localized urban heat- and cool-island signals embedded within the temperature field of a large urban-climate archipelago, fine-resolution simulations with a modified urbanized version of the WRF meteorological model were carried out as basis for siting fixed weather monitors and
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To identify and characterize localized urban heat- and cool-island signals embedded within the temperature field of a large urban-climate archipelago, fine-resolution simulations with a modified urbanized version of the WRF meteorological model were carried out as basis for siting fixed weather monitors and designing mobile-observation transects. The goal was to characterize variations in urban heat during summer in Los Angeles, California. Air temperatures measured with a shielded sensor mounted atop an automobile in the summers of 2016 and 2017 were compared to model output and also correlated to surface physical properties focusing on neighborhood-scale albedo and vegetation canopy cover. The study modeled and measured the temperature response to variations in surface properties that already exist in the real world, i.e., realistic variations in albedo and canopy cover that are attainable through current building and urban design practices. The simulated along-transect temperature from a modified urbanized WRF model was compared to the along-transect observed temperature from 15 mobile traverses in one area near downtown Los Angeles and another in an inland basin (San Fernando Valley). The observed transect temperature was also correlated to surface physical properties characterizations that were developed for input to the model. Both comparisons were favorable, suggesting that (1) the model can reliably be used in siting fixed weather stations and designing mobile-transect routes to characterize urban heat and (2) that except for a few cases with opposite co-varying influences, the correlations between observed temperature and albedo and between observed temperature and canopy cover were each negative, ranging from −1.0 to −9.0 °C per 0.1 increase in albedo and from −0.1 to −2.2 °C per 0.1 increase in canopy cover. Observational data from the analysis domains pointed to a wind speed threshold of 3 m/s. Below this threshold the variations in air temperature could be explained by land use and surface properties within a 500-m radius of each observation point. Above the threshold, air temperature was influenced by the properties of the surface within a 1-km upwind fetch. Of relevance to policy recommendations, the study demonstrates the significant real-world cooling effects of increasing urban albedo and vegetation canopy cover. Based on correlations between the observed temperature (from mobile transects) and surface physical properties in the study domains, the analysis shows that neighborhood-scale (500-m) cooling of up to 2.8 °C during the daytime can be achieved by increasing albedo. A neighborhood can also be cooled by up to 2.3 °C during the day and up to 3.3 °C at night by increasing canopy cover. The analysis also demonstrates the suitability of using fine-resolution meteorological models to design mobile-transect routes or site-fixed weather monitors in order to quantify urban heat and the efficacy of albedo and canopy cover countermeasures. The results also show that the model is capable of accurately predicting the geographical locations and the magnitudes of localized urban heat and cool islands. Thus the model results can also be used to devise urban-heat mitigation measures. Full article
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Open AccessArticle A New Radiative Model Derived from Solar Insolation, Albedo, and Bulk Atmospheric Emissivity: Application to Earth and Other Planets
Climate 2018, 6(2), 52; https://doi.org/10.3390/cli6020052
Received: 18 April 2018 / Revised: 23 May 2018 / Accepted: 27 May 2018 / Published: 14 June 2018
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Abstract
This study develops an equilibrium radiative model based on a quasi-adiabatic atmosphere that quantifies the average surface flux of a planetary body as a function of absorbed solar radiation P and the bulk emissivity of the atmosphere with respect to surface radiation  
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This study develops an equilibrium radiative model based on a quasi-adiabatic atmosphere that quantifies the average surface flux of a planetary body as a function of absorbed solar radiation P and the bulk emissivity of the atmosphere with respect to surface radiation  ε. The surface flux is then given by  P/(1ε), and I define the scaling term 1/(1ε) as the greenhouse factor. The model is applied to all of the rocky planets in the solar system to determine their greenhouse factors, and accounts for the diversity of planetary surface fluxes. The model is modified to allow for a top of atmosphere non-equilibrium state, which when compared with a recent observation-based model of the Earth energy budget, predicts the Earth’s radiative fluxes to within the uncertainty ranges of that model. The model developed in this study is able to quantify the changes in Earth’s surface flux caused by changes in bond albedo and atmospheric bulk emissivity by using the surface temperature, ocean heat content, incoming solar radiation and outgoing longwave radiation records. The model indicates an increase in absorbed solar radiation over the time period from 1979–2015 of the order of 3 W/m2, which was caused by a decrease in planetary bond albedo. The time-series albedo generated by the model is in agreement with Clouds and Earth’s Radiant Energy System (CERES) derived albedo over the period from 2000–2015. The model also indicates a slight decrease in atmospheric bulk emissivity over the same period. Since atmospheric bulk emissivity is a function of the sum of all of the greenhouse gas species, a simultaneous decrease in atmospheric water vapor may offset the effect of the well-documented increase in the non-condensing greenhouse gases over the period, and result in an overall net decrease in bulk emissivity. Atmospheric water vapor datasets partially support the conclusion, with the International Satellite Cloud Climatology Project (ISCCP) data supporting a decrease. The NASA Water Vapor Project (NVAP-M) data supports a decrease in atmospheric water content over the period 1998–2008, but not over the longer period of 1988–2008. The model indicates that the decrease in planetary albedo was the driver for the increased surface flux over the stated period. Full article
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Open AccessFeature PaperArticle Multi-Decadal Trend and Decadal Variability of the Regional Sea Level over the Indian Ocean since the 1960s: Roles of Climate Modes and External Forcing
Climate 2018, 6(2), 51; https://doi.org/10.3390/cli6020051
Received: 1 May 2018 / Revised: 5 June 2018 / Accepted: 6 June 2018 / Published: 8 June 2018
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Abstract
Previous studies suggest that anthropogenic warming has affected the multi-decadal trend patterns of sea level over the Indian Ocean (IO). This effect, however, has not been quantified. Using observational datasets combined with large ensemble experiments from two climate models, this paper assesses the
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Previous studies suggest that anthropogenic warming has affected the multi-decadal trend patterns of sea level over the Indian Ocean (IO). This effect, however, has not been quantified. Using observational datasets combined with large ensemble experiments from two climate models, this paper assesses the effects of natural internal variability versus external forcing on the observed, multi-decadal trend pattern and the decadal sea level anomaly (SLA) of the IO since the 1960s. Because the global mean sea level rise (SLR), which results largely from external forcing, has been removed before the examination, the paper focuses on the regionally uneven distribution of trend and SLA. The impacts of climate modes are quantified using a Bayesian Dynamic Linear Model. For the regional trend pattern of 1958–2005, the effects of internal variability dominate external forcing. Over the Seychelles area where sea-level variations obtain the maximum, internal variability (external forcing) contributes 81% (19 ± 2.4%) of the observed trend. For decadal SLA, internal variability is the predominant cause, with a standard deviation (STD) ratio of externally forced/observed SLA being 18 ± 17% over Seychelles and 17 ± 11% near the Indonesian Throughflow (ITF) area. Climate modes account for most observed SLA during boreal winter, with the total effects of decadal ENSO, Indian Ocean Dipole (IOD), and monsoon accounting for 78–86% of the observed STD near the Seychelles region, ITF area, and coasts of Sumatra and the Bay of Bengal. During summer, climate modes explain 95% of observed STD near the ITF but only 58–67% in other regions. Decadal ENSO dominates the SLA in the south tropical IO for both seasons and near the coasts of Sumatra and the Bay during winter. Decadal IOD and monsoon, however, control the coastal SLA during summer. Remote and local winds over the IO are the main drivers for decadal SLA, while the Pacific influence via the ITF is strong mainly in the southeast basin. Full article
(This article belongs to the Special Issue Decadal Variability and Predictability of Climate)
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Open AccessFeature PaperArticle Multifractal Analysis of High-Frequency Temperature Time Series in the Urban Environment
Climate 2018, 6(2), 50; https://doi.org/10.3390/cli6020050
Received: 2 May 2018 / Revised: 5 June 2018 / Accepted: 5 June 2018 / Published: 8 June 2018
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Abstract
Continuous monitoring systems have been regarded as a very useful tool to provide continuous high-frequency measurements of many parameters. Here, we analyze high-frequency time series of air temperature measurements, recorded every 10 min during 2003 in Athens (Greece) by an online monitoring system
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Continuous monitoring systems have been regarded as a very useful tool to provide continuous high-frequency measurements of many parameters. Here, we analyze high-frequency time series of air temperature measurements, recorded every 10 min during 2003 in Athens (Greece) by an online monitoring system for the urban environment. We propose a set of time series analysis techniques, where missing data are well respected and information concerning the system’s dynamics is preserved. A power spectral density analysis is performed over time scales spanning from 10 min to several days. A scale-invariant behavior of the form E ( f ) f β is revealed for scales below 9 h. Over this scaling range, we have performed structure functions analysis, and shown that air temperature data exhibit turbulent-like intermittent properties with multi-fractal statistics. The multifractal exponents obtained possess some similarities with passive scalar turbulence results. Although we illustrate the proposed approach using air temperature data, the method can be used as an efficient tool to analyse other environmental parameters monitored in urban environment. Full article
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Open AccessArticle An Empirical Comparison of Carbon Credit Projects under the Clean Development Mechanism and Verified Carbon Standard
Climate 2018, 6(2), 49; https://doi.org/10.3390/cli6020049
Received: 2 May 2018 / Revised: 24 May 2018 / Accepted: 29 May 2018 / Published: 4 June 2018
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Abstract
Carbon credit projects generate carbon credits by abating greenhouse gas emissions. Carbon credits can then be traded on carbon markets or immobilized in order to compensate for caused emissions. The Clean Development Mechanism (CDM) and Verified Carbon Standard (VCS), as the two most
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Carbon credit projects generate carbon credits by abating greenhouse gas emissions. Carbon credits can then be traded on carbon markets or immobilized in order to compensate for caused emissions. The Clean Development Mechanism (CDM) and Verified Carbon Standard (VCS), as the two most important carbon credit mechanisms, are investigated and compared regarding the success of projects. We define success as the fulfilling of the ex-ante emission abatement estimation and apply regression analyses to explain its variation on a project level by technology, location, scale, duration and participation. The results are discussed in detail on technology level for wind power, energy efficiency, hydro power as well as biomass projects and are compared with regard to CDM and VCS. Our main results indicate that large scale projects often compensate for their under-performance due to economies of time. Furthermore, the duration of projects, their location and structure of participants have significant influence on the success of the projects. The sign of the coefficients of explanatory variables are broadly in line with intuition and related literature, although, due to data availability, they are not always highly significant statistically. Full article
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Open AccessArticle Seasonal Drought Forecasting for Latin America Using the ECMWF S4 Forecast System
Climate 2018, 6(2), 48; https://doi.org/10.3390/cli6020048
Received: 4 May 2018 / Revised: 28 May 2018 / Accepted: 31 May 2018 / Published: 1 June 2018
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Abstract
Meaningful seasonal prediction of drought conditions is key information for end-users and water managers, particularly in Latin America where crop and livestock production are key for many regional economies. However, there are still not many studies of the feasibility of such a forecasts
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Meaningful seasonal prediction of drought conditions is key information for end-users and water managers, particularly in Latin America where crop and livestock production are key for many regional economies. However, there are still not many studies of the feasibility of such a forecasts at continental level in the region. In this study, precipitation predictions from the European Centre for Medium Range Weather (ECMWF) seasonal forecast system S4 are combined with observed precipitation data to generate forecasts of the standardized precipitation index (SPI) for Latin America, and their skill is evaluated over the hindcast period 1981–2010. The value-added utility in using the ensemble S4 forecast to predict the SPI is identified by comparing the skill of its forecasts with a baseline skill based solely on their climatological characteristics. As expected, skill of the S4-generated SPI forecasts depends on the season, location, and the specific aggregation period considered (the 3- and 6-month SPI were evaluated). Added skill from the S4 for lead times equaling the SPI accumulation periods is primarily present in regions with high intra-annual precipitation variability, and is found mostly for the months at the end of the dry seasons for 3-month SPI, and half-yearly periods for 6-month SPI. The ECMWF forecast system behaves better than the climatology for clustered grid points in the North of South America, the Northeast of Argentina, Uruguay, southern Brazil and Mexico. The skillful regions are similar for the SPI3 and -6, but become reduced in extent for the severest SPI categories. Forecasting different magnitudes of meteorological drought intensity on a seasonal time scale still remains a challenge. However, the ECMWF S4 forecasting system does capture the occurrence of drought events for the aforementioned regions and seasons reasonably well. In the near term, the largest advances in the prediction of meteorological drought for Latin America are obtainable from improvements in near-real-time precipitation observations for the region. In the longer term, improvements in precipitation forecast skill from dynamical models, like the fifth generation of the ECMWF seasonal forecasting system, will be essential in this effort. Full article
(This article belongs to the Special Issue Climate and Atmospheric Dynamics and Predictability)
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Open AccessArticle Defining the Requirements of an Information System for Climate Change Adaptation in the Mountain Communities of Dolakha, Nepal
Climate 2018, 6(2), 47; https://doi.org/10.3390/cli6020047
Received: 30 April 2018 / Revised: 21 May 2018 / Accepted: 28 May 2018 / Published: 1 June 2018
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Abstract
Community-based Adaptation Programs (CAPs) that involve the participation of communities are being actively promoted in mountainous areas. These areas are climate sensitive and are often heavily influenced by landslides, floods, and drought. This research indicates that designers of adaptation programs seek to develop
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Community-based Adaptation Programs (CAPs) that involve the participation of communities are being actively promoted in mountainous areas. These areas are climate sensitive and are often heavily influenced by landslides, floods, and drought. This research indicates that designers of adaptation programs seek to develop and implement CAPs based on international viewpoint and their obligations, but not community requirements. Such CAPs create uneven access to information resources for communities and do not implicitly reduce community vulnerability. In response, the research proposes the establishment of an Information System (IS) to support delivery of reliable climate adaptation services to mountain communities. This research uses Nepal as a case study that experiences a lack of effective adaptation programs due to its varied topography, prevalent climate-related disasters, and barriers in capacity building and institutional development. The results of the analyses indicate that the national level focuses on preparing adaptation action plans, whilst district levels and Non-Governmental Organization (NGO) focus on facilitating adaptation implementation for community and individuals. Additionally, the results reveal that an IS can enhance the design and implementation of CAP. Finally, the results are used to articulate prioritized services for an IS to assist communities who are in the greatest need of climate service delivery. Full article
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Open AccessArticle Temporal and Spatial Ozone Distribution over Egypt
Climate 2018, 6(2), 46; https://doi.org/10.3390/cli6020046
Received: 21 May 2018 / Revised: 25 May 2018 / Accepted: 27 May 2018 / Published: 29 May 2018
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Abstract
The long-term temporal trends and spatial distribution of Ozone (O3) over Egypt is presented using monthly data from both the Atmospheric Infrared Sounder (AIRS) and the model Modern-Era Retrospective analysis for Research and Applications (MERRA) datasets. The twelve-year monthly record (2005–2016)
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The long-term temporal trends and spatial distribution of Ozone (O3) over Egypt is presented using monthly data from both the Atmospheric Infrared Sounder (AIRS) and the model Modern-Era Retrospective analysis for Research and Applications (MERRA) datasets. The twelve-year monthly record (2005–2016) of the Total Ozone Column (TOC) has a spatial resolution of 1 × 1° from AIRS and 0.5 × 0.625° from the MERRA-2 dataset. The average monthly, seasonal and interannual time series are analyzed for their temporal trends, while the seasonal average spatial distributions are compared. It was found that MERRA-2 underestimated AIRS measurements. Both AIRS and MERRA-2 have their minimum monthly averages of TOC in February 2013. The maximum monthly average TOC from AIRS is 321.48 DU in July 2012, while that from MERRA-2 is 303.48 in April 2011. Full article
(This article belongs to the Special Issue Air Pollution and Plant Ecosystems)
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Open AccessArticle Sensitivity of the Madden Julian Oscillation to Ocean Warming in a Lagrangian Atmospheric Model
Climate 2018, 6(2), 45; https://doi.org/10.3390/cli6020045
Received: 12 April 2018 / Revised: 12 May 2018 / Accepted: 17 May 2018 / Published: 28 May 2018
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Abstract
The Madden Julian Oscillation (MJO) is the largest contributor to intraseasonal weather variations in the tropics. It is associated with a broad region of enhanced rainfall that moves slowly eastward over the Indian and western Pacific Oceans, which has global impacts on atmospheric
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The Madden Julian Oscillation (MJO) is the largest contributor to intraseasonal weather variations in the tropics. It is associated with a broad region of enhanced rainfall that moves slowly eastward over the Indian and western Pacific Oceans, which has global impacts on atmospheric circulations. A number of recent observational and modeling studies have suggested that the MJO is becoming stronger as the oceans warm. In this study, the author explores the sensitivity of the MJO to ocean warming in a recently developed Lagrangian Atmospheric Model (LAM), which has been shown to simulate robust and realistic MJOs in previous work. Numerical simulations suggest that ocean warming leads to more frequent and intense MJOs that propagate more rapidly and cover a larger region of the tropics. The strengthening of the MJO is attributed to enhanced surface fluxes of moisture coming from the warmer ocean waters. While the LAM simulations have a number of limitations owing to idealized physical parameterizations and the use of prescribed sea surface temperatures, they provide additional evidence that the MJO will strengthen if the oceans continue to warm, and they also shed light on the mechanism of this strengthening. Full article
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Open AccessArticle Farmer Perceptions and Climate Change Adaptation in the West Africa Sudan Savannah: Reality Check in Dassari, Benin, and Dano, Burkina Faso
Climate 2018, 6(2), 44; https://doi.org/10.3390/cli6020044
Received: 9 May 2018 / Revised: 9 May 2018 / Accepted: 19 May 2018 / Published: 25 May 2018
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Abstract
Climate change is a great threat to the already climate-unstable West Africa. Current and potential impacts are especially hard on farming in the Sudan savannah, thus adaptation is widely advised and encouraged, and already occurring. In the study sites Dassari, Benin, and Dano,
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Climate change is a great threat to the already climate-unstable West Africa. Current and potential impacts are especially hard on farming in the Sudan savannah, thus adaptation is widely advised and encouraged, and already occurring. In the study sites Dassari, Benin, and Dano, Burkina Faso, farmers’ climate change perceptions and practiced coping measures were qualitatively and quantitatively recorded. Analyses included statistical testing to detach anecdotal responses from factual decisions. Results reveal that responses regarding climate change perception and adaptation are frequently subjective, conjectural and inconsistent. Farmers’ acknowledge that adaptations to climate change impacts are diverse, but site specific. Measures do not causally respond to the type of hazard, nor to its impacts, but instead tend to address wide-ranging demands, such as household food security, income generation and capitalization. Hence, causally linking hazards, impacts and responses can be misleading, and measures can thus be ineffective. After our findings, key qualities of effective coping measures are short-term economic returns, compatibility with local ecological, social and institutional settings and agreeing with the customary farming traditions. With respect to operability, the national agricultural extension services are still the most relevant instances. Considering these aspects can support local farming adaptation and also increase the general resilience of the households. Full article
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Open AccessArticle Influence of Decadal Climate Variability on Growing Degree Day, Precipitation, and Drought in Crop-Growing Seasons
Climate 2018, 6(2), 43; https://doi.org/10.3390/cli6020043
Received: 12 February 2018 / Revised: 8 May 2018 / Accepted: 9 May 2018 / Published: 18 May 2018
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Abstract
Knowledge on the impact of climate variability on the decadal timescale is important for policy makers and planners in order for them to make decisions in a range of sectors, including agriculture, water resources, energy, and infrastructure. This study estimates the effects of
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Knowledge on the impact of climate variability on the decadal timescale is important for policy makers and planners in order for them to make decisions in a range of sectors, including agriculture, water resources, energy, and infrastructure. This study estimates the effects of the ocean-related decadal climate variability (DCV) on growing degree day, precipitation, and drought in the crop-growing seasons of major crops in the United States. The empirical results illustrate that DCV phase combinations are associated with variations in growing degree day, precipitation, and drought across the country using county-level data from 1950 to 2015. There are spatially-differentiated effects on the climate of major production areas of corn, soybeans, and wheat. The annual oscillations in growing degree day, precipitation, and drought reach extreme severity in some DCV scenarios. The results would facilitate the adoption of coping mechanisms with the potential to develop climate risk resiliency for agricultural planning and policy. Full article
(This article belongs to the Special Issue Decadal Variability and Predictability of Climate)
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Open AccessArticle Feasibility of Predicting Vietnam’s Autumn Rainfall Regime Based on the Tree-Ring Record and Decadal Variability
Climate 2018, 6(2), 42; https://doi.org/10.3390/cli6020042
Received: 24 March 2018 / Revised: 4 May 2018 / Accepted: 10 May 2018 / Published: 16 May 2018
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Abstract
We investigate the feasibility of developing decadal prediction models for autumn rainfall ( RA ) over Central Vietnam by utilizing a published tree-ring reconstruction of October–November (ON) rainfall derived from the earlywood width measurements from a type of Douglas-fir (Pseudotsuga sinensis
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We investigate the feasibility of developing decadal prediction models for autumn rainfall ( R A ) over Central Vietnam by utilizing a published tree-ring reconstruction of October–November (ON) rainfall derived from the earlywood width measurements from a type of Douglas-fir (Pseudotsuga sinensis). Autumn rainfall for this region accounts for a large percentage of the annual total, and is often the source of extreme flooding. Central Vietnam’s R A is characterized by a pronounced decadal oscillation signal. We use the decadal mode of R A along with its notable autocorrelation and significant cross-correlation with basin-wide Pacific sea surface temperature (SST) variability, to develop four discrete time-series models. The sparse autoregressive model, with Pacific SST as an external variable, accounts for most of the autoregressive R A , while taking advantage of the predictability from the basin-wide Pacific climate oscillation. Using this model, the decadal prediction of R A can be reasonably achieved with a 10-year-ahead forecasting skill score (SS) about 0.46. We therefore suggest, with this paper, that forecasting R A for Central Vietnam for multiple years ahead is possible using a time-series model. Full article
(This article belongs to the Special Issue Decadal Variability and Predictability of Climate)
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Open AccessReview Effect of Climate Change on the Yield of Cereal Crops: A Review
Climate 2018, 6(2), 41; https://doi.org/10.3390/cli6020041
Received: 29 April 2018 / Revised: 11 May 2018 / Accepted: 13 May 2018 / Published: 15 May 2018
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Abstract
By the end of this century, the average global temperature is predicted to rise due to the increasing release of greenhouse gases (GHGs) into the atmosphere. This change in climate can reduce agricultural yields, resulting in food insecurity. However, agricultural activities are one
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By the end of this century, the average global temperature is predicted to rise due to the increasing release of greenhouse gases (GHGs) into the atmosphere. This change in climate can reduce agricultural yields, resulting in food insecurity. However, agricultural activities are one of the major contributors of GHGs and lower yields can trigger increased activity to meet the demand for food, resulting in higher quantities of GHGs released into the atmosphere. In this paper, we discuss the growth requirements and greenhouse gas release potential of staple cereal crops and assess the impact of climate change on their yields. Potential solutions for minimizing the influence of climate change on crop productivity are discussed. These include breeding to obtain cereals that are more tolerant to conditions caused by climate change, increased production of these new cultivars, improved irrigation, and more effective use of fertilizers. Furthermore, different predictive models inferred that climate change would reduce production of major cereal crops, except for millets due to their ability to grow in variable climatic conditions, and in dry areas due to a strong root system. Moreover, millets are not resource-intensive crops and release fewer greenhouse gases compared to other cereals. Therefore, in addition to addressing food security, millets have an enormous potential use for reducing the impact of agriculture on global warming and should be grown on a global scale as an alternative to major cereals and grains. Full article
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Open AccessArticle Vulnerability of Structural Concrete to Extreme Climate Variances
Climate 2018, 6(2), 40; https://doi.org/10.3390/cli6020040
Received: 15 April 2018 / Revised: 30 April 2018 / Accepted: 10 May 2018 / Published: 12 May 2018
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Abstract
For modern infrastructures, structural concrete has been widely adopted for various components and structures such as railway stations, platforms, walkways, railway bridges, tunnelling, concrete sleepers, concrete foundation of overhead wiring structures, etc. These infrastructures are subject to various changes of time, operation, and
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For modern infrastructures, structural concrete has been widely adopted for various components and structures such as railway stations, platforms, walkways, railway bridges, tunnelling, concrete sleepers, concrete foundation of overhead wiring structures, etc. These infrastructures are subject to various changes of time, operation, and environment. Environmental conditions are a considerably influential factor to life cycle and durability of concrete structures. This study aims at identifying the influence of climate change on the performance and durability of concrete structures using statistical regression analysis of a number of pertinent experimental and field data. The study into the influence of elevated temperature on compressive strength and splitting tensile strength also has been carried out using experimental data on the basis of environmental temperature and relative humidity, as well as CO2 concentration to the concrete carbonation and steel corrosion rates. The results indicate that environmental temperature, CO2 concentration, and a certain range of relative humidity play an important role in the concrete carbonation rates. Temperature and relative humidity affect the rate of steel corrosion as well. In addition, it is found that there exists a nearly direct correlation between the environmental temperature and the concrete carbonation rates, as well as the corrosion rate of steel embedded in concrete from 25 °C to 60 °C, and a nearly inverse proportion between the environmental relative humidity and the concrete carbonization from 48.75% to 105%. Indeed, the results exhibit that even in extreme natural high temperature, the capacity of compressive strength and splitting tensile strength is not affected significantly. Full article
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Open AccessArticle Clustering Indian Ocean Tropical Cyclone Tracks by the Standard Deviational Ellipse
Climate 2018, 6(2), 39; https://doi.org/10.3390/cli6020039
Received: 25 November 2017 / Revised: 21 April 2018 / Accepted: 7 May 2018 / Published: 11 May 2018
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Abstract
The standard deviational ellipse is useful to analyze the shape and the length of a tropical cyclone (TC) track. Cyclone intensity at each six-hour position is used as the weight at that location. Only named cyclones in the Indian Ocean since 1981 are
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The standard deviational ellipse is useful to analyze the shape and the length of a tropical cyclone (TC) track. Cyclone intensity at each six-hour position is used as the weight at that location. Only named cyclones in the Indian Ocean since 1981 are considered for this study. The K-means clustering algorithm is used to cluster Indian Ocean cyclones based on the five parameters: x-y coordinates of the mean center, variances along zonal and meridional directions, and covariance between zonal and meridional locations of the cyclone track. Four clusters are identified across the Indian Ocean; among them, only one cluster is in the North Indian Ocean (NIO) and the rest of them are in the South Indian Ocean (SIO). Other characteristics associated with each cluster, such as wind speed, lifespan, track length, track orientation, seasonality, landfall, category during landfall, total accumulated cyclone energy (ACE), and cyclone trend, are analyzed and discussed. Cyclone frequency and energy of Cluster 4 (in the NIO) have been following a linear increasing trend. Cluster 4 also has a higher number of landfall cyclones compared to other clusters. Cluster 2, located in the middle of the SIO, is characterized by the long track, high intensity, long lifespan, and high accumulated energy. Sea surface temperature (SST) and outgoing longwave radiation (OLR) associated with genesis of TCs are also examined in each cluster. Cyclone genesis is co-located with the negative OLR anomaly and the positive SST anomaly. Localized SST anomalies are associated with clusters in the SIO; however, TC geneses of Cluster 4 are associated with SSTA all over the Indian Ocean (IO). Full article
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