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Climate (ISSN 2225-1154; CODEN: CLIMC9) is a scientific peer-reviewed open access journal of climate science published online quarterly by MDPI.
- Open Access - free for readers, with article processing charges (APC) paid by authors or their institutions.
- High visibility: Indexed in the Emerging Sources Citation Index (ESCI - Web of Science), Scopus (from Vol. 1) and other databases.
- Rapid publication: manuscripts are peer-reviewed and a first decision provided to authors approximately 17 days after submission; acceptance to publication is undertaken in 4.9 days (median values for papers published in the first six months of 2018).
- Recognition of reviewers: reviewers who provide timely, thorough peer-review reports receive vouchers entitling them to a discount on the APC of their next publication in any MDPI journal, in appreciation of the work done.
Latest Articles
Climate and the Decline and Fall of the Western Roman Empire: A Bibliometric View on an Interdisciplinary Approach to Answer a Most Classic Historical Question
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Climate 2018, 6(4), 90; https://doi.org/10.3390/cli6040090 - 15 November 2018
Abstract
This bibliometric analysis deals with research on the decline and fall of the Western Roman Empire in connection with climate change. Based on the Web of Science (WoS) database, we applied a combination of three different search queries for retrieving the relevant literature:
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This bibliometric analysis deals with research on the decline and fall of the Western Roman Empire in connection with climate change. Based on the Web of Science (WoS) database, we applied a combination of three different search queries for retrieving the relevant literature: (1) on the decline and fall of the Roman Empire in general, (2) more specifically on the downfall in connection with a changing climate, and (3) on paleoclimatic research in combination with the time period of the Roman Empire and Late Antiquity. Additionally, we considered all references cited by an ensemble of selected key papers and all citing papers of these key papers, whereby we retrieved additional publications (in particular, books and book chapters). We merged the literature retrieved, receiving a final publication set of 85 publications. We analyzed this publication set by applying a toolset of bibliometric methods and visualization programs. A co-authorship map of all authors, a keyword map for a rough content analysis, and a citation network based on the publication set of 85 papers are presented. We also considered news mentions in this study to identify papers with impacts beyond science. According to the literature retrieved, a multitude of paleoclimatic data from various geographical sites for the time of late antiquity indicate a climatic shift away from the stability of previous centuries. Recently, some scholars have argued that drought in Central Asia and the onset of a cooler climate in North-West Eurasia may have put Germanic tribes, Goths, and Huns on the move into the Roman Empire, provoking the Migration Period and eventually leading to the downfall of the Western Roman Empire. However, climate is only one variable at play; a combination of many factors interacting with each other is a possible explanation for the pattern of long-lasting decline and final collapse. Currently, the number of records from different locations, the toolbox of suitable analytic methods, and the precision of dating are evolving rapidly, contributing to an answer for one of the most classic of all historical questions. However, these studies still lack the inevitable collaboration of the major disciplines involved: archeology, history, and climatology. The articles of the publication set analyzed mainly result from research in the geosciences.
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Selecting and Downscaling a Set of Climate Models for Projecting Climatic Change for Impact Assessment in the Upper Indus Basin (UIB)
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Climate 2018, 6(4), 89; https://doi.org/10.3390/cli6040089 - 14 November 2018
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
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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.
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Are Energy Security Concerns Dominating Environmental Concerns? Evidence from Stakeholder Participation Processes on Energy Transition in Jordan
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Climate 2018, 6(4), 88; https://doi.org/10.3390/cli6040088 - 1 November 2018
Abstract
To satisfy Jordan’s growing demand for electricity and to diversify its energy mix, the Jordanian government is considering a number of electricity-generation technologies that would allow for locally available resources to be used alongside imported energy. Energy policy in Jordan aims to address
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To satisfy Jordan’s growing demand for electricity and to diversify its energy mix, the Jordanian government is considering a number of electricity-generation technologies that would allow for locally available resources to be used alongside imported energy. Energy policy in Jordan aims to address both climate change mitigation and energy security by increasing the share of low-carbon technologies and domestically available resources in the Jordanian electricity mix. Existing technological alternatives include the scaling up of renewable energy sources, such as solar and wind; the deployment of nuclear energy; and shale oil exploration. However, the views, perceptions, and opinions regarding these technologies—their benefits, risks, and costs—vary significantly among different social groups both inside and outside the country. Considering the large-scale policy intervention that would be needed to deploy these technologies, a compromise solution must be reached. This paper is based on the results of a four-year research project that included extensive stakeholder processes in Jordan, involving several social groups and the application of various methods of participatory governance research, such as multi-criteria decision-making. The results show the variety of opinions expressed and provide insights into each type of electricity-generation technology and its relevance for each stakeholder group. There is a strong prevalence of economic rationality in the results, given that electricity-system costs are prioritized by almost all stakeholder groups.
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Spatio-Temporal Trend Analysis of Rainfall and Temperature Extremes in the Vea Catchment, Ghana
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Climate 2018, 6(4), 87; https://doi.org/10.3390/cli6040087 - 31 October 2018
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This study examined the trends in annual rainfall and temperature extremes over the Vea catchment for the period 1985–2016, using quality-controlled stations and a high resolution (5 km) Climate Hazards Group InfraRed Precipitation with Station (CHIRPS) data. The CHIRPS gridded precipitation data’s ability
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This study examined the trends in annual rainfall and temperature extremes over the Vea catchment for the period 1985–2016, using quality-controlled stations and a high resolution (5 km) Climate Hazards Group InfraRed Precipitation with Station (CHIRPS) data. The CHIRPS gridded precipitation data’s ability in reproducing the climatology of the catchment was evaluated. The extreme rainfall and temperature indices were computed using a RClimdex package by considering seventeen (17) climate change indices from the Expert Team on Climate Change Detection Monitoring Indices (ETCCDMI). Trend detection and quantification in the rainfall (frequency and intensity) and temperature extreme indices were analyzed using the non-parametric Mann–Kendall (MK) test and Sen’s slope estimator. The results show a very high seasonal correlation coefficient (r = 0.99), Nash–Sutcliff efficiency (0.98) and percentage bias (4.4% and −8.1%) between the stations and the gridded data. An investigation of dry and wet years using Standardized Anomaly Index shows 45.5% frequency of drier than normal periods compared to 54.5% wetter than normal periods in the catchment with 1999 and 2003 been extremely wet years while the year 1990 and 2013 were extremely dry. The intensity and magnitude of extreme rainfall indices show a decreasing trend for more than 78% of the rainfall locations while positive trends were observed in the frequency of extreme rainfall indices (R10mm, R20mm, and CDD) with the exception of consecutive wet days (CWD) that shows a decreasing trend. A general warming trend over the catchment was observed through the increase in the annual number of warm days (TX90p), warm nights (TN90p) and warm spells (WSDI). The spatial distribution analysis shows a high frequency and intensity of extremes rainfall indices in the south of the catchment compared to the middle and northern of part of the catchment, while temperature extremes were uniformly distributed over the catchment.
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The Nexus of Weather Extremes to Agriculture Production Indexes and the Future Risk in Ghana
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Climate 2018, 6(4), 86; https://doi.org/10.3390/cli6040086 - 31 October 2018
Abstract
The agricultural industry employs a large workforce in Ghana and remains the primary source of food security and income. The consequences of extreme weather in this sector can be catastrophic. A consistent picture of meteorological risk and adaptation patterns can lead to useful
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The agricultural industry employs a large workforce in Ghana and remains the primary source of food security and income. The consequences of extreme weather in this sector can be catastrophic. A consistent picture of meteorological risk and adaptation patterns can lead to useful information, which can help local farmers make informed decisions to advance their livelihoods. We modelled historical data using extreme value theory and structural equation modelling. Subsequently, we studied extreme weather variability and its relationship to composite indicators of agricultural production and the long-term trend of weather risk. Minimum and maximum annual temperatures have negligible heterogeneity in their trends, while the annual maximum rainfall is homogenous in trend. Severe rainfall affects cereals and cocoa production, resulting in reduced yields. Cereals and cocoa grow well when there is even distribution of rainfall. The return levels for the next 20–100 years are gradually increasing with the long-term prediction of extreme weather. Also, heavy rains affect cereals and cocoa production negatively. All indicators of agriculture had a positive relationship with maximum extreme weather.
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Estimating the Impact of Artificially Injected Stratospheric Aerosols on the Global Mean Surface Temperature in the 21th Century
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Climate 2018, 6(4), 85; https://doi.org/10.3390/cli6040085 - 28 October 2018
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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
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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.
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Relationship between City Size, Coastal Land Use, and Summer Daytime Air Temperature Rise with Distance from Coast
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Climate 2018, 6(4), 84; https://doi.org/10.3390/cli6040084 - 27 October 2018
Abstract
The relationship between city size, coastal land use, and air temperature rise with distance from coast during summer day is analyzed using the meso-scale weather research and forecasting (WRF) model in five coastal cities in Japan with different sizes and coastal land use
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The relationship between city size, coastal land use, and air temperature rise with distance from coast during summer day is analyzed using the meso-scale weather research and forecasting (WRF) model in five coastal cities in Japan with different sizes and coastal land use (Tokyo, Osaka, Nagoya, Hiroshima, and Sendai) and inland cities in Germany (Berlin, Essen, and Karlsruhe). Air temperature increased as distance from the coast increased, reached its maximum, and then decreased slightly. In Nagoya and Sendai, the amount of urban land use in coastal areas is less than the other three cities, where air temperature is a little lower. As a result, air temperature difference between coastal and inland urban area is small and the curve of air temperature rise is smaller than those in Tokyo and Osaka. In Sendai, air temperature in the inland urban area is the same as in the other cities, but air temperature in the coastal urban area is a little lower than the other cities, due to an approximate one degree lower sea surface temperature being influenced by the latitude. In three German cities, the urban boundary layer may not develop sufficiently because the fetch distance is not enough.
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Patterns in Indices of Daily and Seasonal Rainfall Extremes: Southwest Florida Gulf Coastal Zone
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Climate 2018, 6(4), 83; https://doi.org/10.3390/cli6040083 - 25 October 2018
Abstract
Extreme events have the most adverse impacts on society and infrastructure, and present the greatest challenges with respect to impacts. Information on the status and trends of these events is, thus, important for system design, management, and policy decision-making. In this study, variations
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Extreme events have the most adverse impacts on society and infrastructure, and present the greatest challenges with respect to impacts. Information on the status and trends of these events is, thus, important for system design, management, and policy decision-making. In this study, variations in daily and seasonal rainfall extremes were explored with a focus on the southwest Florida Gulf coastal zone for the period 1950–2016. Rainfall occurring on very wet days accounted for about 50% of the seasonal rainfall in the area (regardless of the season), while about 25% of the seasonal rainfall came from extremely wet days except in the period between October and December for which this latter value was about 40%. No significant changes were seen in the maximum one-day rainfall at any of the stations regardless of the time scale. However, there was a significant increase in the number of wet days in the rainy season at Myakka River (p = 0.0062) and Naples (p = 0.0027) and during October–December at Myakka River (p = 0.0204). These two stations also experienced significant increases in the number of wet days in a year. Significant increases in the contribution to rainy season rainfall from very wet days (rainfall > 25.4 mm, 1 in) were seen at Arcadia (p = 0.0055). Regional results point to an increasingly wetter climate with increasing contributions from extreme events in some areas, both of which have implications for design and management decision making.
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Understanding the Recent Global Surface Warming Slowdown: A Review
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Climate 2018, 6(4), 82; https://doi.org/10.3390/cli6040082 - 24 October 2018
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The Intergovernmental Panel on Climate Change (IPCC) noted a recent 15-year period (1998–2012) when the rate of surface global warming was a factor of 4 smaller than the mean of the state-of-art climate model projections and than that observed in the previous three
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The Intergovernmental Panel on Climate Change (IPCC) noted a recent 15-year period (1998–2012) when the rate of surface global warming was a factor of 4 smaller than the mean of the state-of-art climate model projections and than that observed in the previous three decades. When updated to include 2014 by Karl et al. using the new version of NOAA data, the observed warming trend is higher, but is still half or less, depending on dataset used, that of previous decades and the multi-model mean projections. This period is called a surface warming slowdown. Intense community efforts devoted to understanding this puzzling phenomenon—puzzling because atmospheric greenhouse gas accumulation has not abated while surface warming slowed—have yielded insights on our climate system, and this may be an opportune time to take stock of what we have learned. Proposed explanations differ on whether it is forced by counteracting agents (such as volcanic and pollution aerosols and stratospheric water vapor) or is an internal variability, and if the latter, on which ocean basin is responsible (Pacific, Indian, or Atlantic Ocean). Here we critically review the observational records, their analyses and interpretations, and offer interpretations of model simulations, with emphasis on sorting through the rather confusing signals at the ocean’s surface, and reconciling them with the subsurface signals.
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Solving Multi-Objective Problems for Multifunctional and Sustainable Management in Maritime Pine Forest Landscapes
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Climate 2018, 6(4), 81; https://doi.org/10.3390/cli6040081 - 15 October 2018
Abstract
Forest management based on sustainability and multifunctionality requires reliable and user-friendly tools to address several objectives simultaneously. In this work we present FlorNExT Pro®, a multiple-criteria landscape-scale forest planning and management computer tool, and apply it in a region in the
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Forest management based on sustainability and multifunctionality requires reliable and user-friendly tools to address several objectives simultaneously. In this work we present FlorNExT Pro®, a multiple-criteria landscape-scale forest planning and management computer tool, and apply it in a region in the north of Portugal to find optimized management solutions according to objectives such as maximization of net present value (NPV), volume growth, and carbon storage, and minimization of losses due to fire. Comparisons made among single- and multi-objective solutions were made to explore the range of possible indicators provided by the tool such as carbon sequestered, volume growth, probability of fire occurrence, volume of wood extracted, and evenness of harvesting in the management period. Results show that FlorNExT Pro® is a reliable, flexible, and useful tool to incorporate multiple criteria and objectives into spatially explicit complex management problems and to prepare sustainable and multifunctional forest management plans at the landscape level. FlorNExT Pro® is also suited to guiding and adapting forest management for uncertainty scenarios for the assessment of ecosystem services and fire risk, therefore playing an important role in the maintenance of sustainable landscapes in the south of Europe.
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New Breeding Techniques for Greenhouse Gas (GHG) Mitigation: Plants May Express Nitrous Oxide Reductase
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Climate 2018, 6(4), 80; https://doi.org/10.3390/cli6040080 - 27 September 2018
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Nitrous oxide (N2O) is a potent greenhouse gas (GHG). Although it comprises only 0.03% of total GHGs produced, N2O makes a marked contribution to global warming. Much of the N2O in the atmosphere issues from incomplete bacterial
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Nitrous oxide (N2O) is a potent greenhouse gas (GHG). Although it comprises only 0.03% of total GHGs produced, N2O makes a marked contribution to global warming. Much of the N2O in the atmosphere issues from incomplete bacterial denitrification processes acting on high levels of nitrogen (N) in the soil due to fertilizer usage. Using less fertilizer is the obvious solution for denitrification mitigation, but there is a significant drawback (especially where not enough N is available for the crop via N deposition, irrigation water, mineral soil N, or mineralization of organic matter): some crops require high-N fertilizer to produce the yields necessary to help feed the world’s increasing population. Alternatives for denitrification have considerable caveats. The long-standing promise of genetic modification for N fixation may be expanded now to enhance dissimilatory denitrification via genetic engineering. Biotechnology may solve what is thought to be a pivotal environmental challenge of the 21st century, reducing GHGs. Current approaches towards N2O mitigation are examined here, revealing an innovative solution for producing staple crops that can ‘crack’ N2O. The transfer of the bacterial nitrous oxide reductase gene (nosZ) into plants may herald the development of plants that express the nitrous oxide reductase enzyme (N2OR). This tactic would parallel the precedents of using the molecular toolkit innately offered by the soil microflora to reduce the environmental footprint of agriculture.
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A Proposal to Evaluate Drought Characteristics Using Multiple Climate Models for Multiple Timescales
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Climate 2018, 6(4), 79; https://doi.org/10.3390/cli6040079 - 26 September 2018
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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
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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.
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Possible Scenarios of Winter Wheat Yield Reduction of Dryland Qazvin Province, Iran, Based on Prediction of Temperature and Precipitation Till the End of the Century
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Climate 2018, 6(4), 78; https://doi.org/10.3390/cli6040078 - 23 September 2018
Abstract
The climate of the Earth is changing. The Earth’s temperature is projected to maintain its upward trend in the next few decades. Temperature and precipitation are two very important factors affecting crop yields, especially in arid and semi-arid regions. There is a need
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The climate of the Earth is changing. The Earth’s temperature is projected to maintain its upward trend in the next few decades. Temperature and precipitation are two very important factors affecting crop yields, especially in arid and semi-arid regions. There is a need for future climate predictions to protect vulnerable sectors like agriculture in drylands. In this study, the downscaling of two important climatic variables—temperature and precipitation—was done by the CanESM2 and HadCM3 models under five different scenarios for the semi-arid province of Qazvin, located in Iran. The most efficient scenario was selected to predict the dryland winter wheat yield of the province for the three periods: 2010–2039, 2040–2069, and 2070–2099. The results showed that the models are able to satisfactorily predict the daily mean temperature and annual precipitation for the three mentioned periods. Generally, the daily mean temperature and annual precipitation tended to decrease in these periods when compared to the current reference values. However, the scenarios rcp2.6 and B2, respectively, predicted that the precipitation will fall less or even increase in the period 2070–2099. The scenario rcp2.6 seemed to be the most efficient to predict the dryland winter wheat yield of the province for the next few decades. The grain yield is projected to drop considerably over the three periods, especially in the last period, mainly due to the reduction in precipitation in March. This leads us to devise some adaptive strategies to prevent the detrimental impacts of climate change on the dryland winter wheat yield of the province.
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The Value of Tactical Adaptation to El Niño–Southern Oscillation for East Australian Wheat
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Climate 2018, 6(3), 77; https://doi.org/10.3390/cli6030077 - 11 September 2018
Abstract
El Niño–Southern Oscillation strongly influences rainfall and temperature patterns in Eastern Australia, with major impacts on frost, heat, and drought stresses, and potential consequences for wheat production. Wheat phenology is a key factor to adapt to the risk of frost, heat, and drought
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El Niño–Southern Oscillation strongly influences rainfall and temperature patterns in Eastern Australia, with major impacts on frost, heat, and drought stresses, and potential consequences for wheat production. Wheat phenology is a key factor to adapt to the risk of frost, heat, and drought stresses in the Australian wheatbelt. This study explores broad and specific options to adapt wheat cropping systems to El Niño–Southern Oscillation, and more specifically, to the Southern Oscillation Index (SOI) phases ahead of the season (i.e., April forecast) in Eastern Australia, when wheat producers make their most crucial management decisions. Crop model simulations were performed for commercially-grown wheat varieties, as well as for virtual genotypes representing possible combinations of phenology alleles that are currently present in the Australian wheat germplasm pool. Different adaptation strategies were tested at the site level, across Eastern Australia, for a wide range of sowing dates and nitrogen applications over long-term historical weather records (1900–2016). The results highlight that a fixed adaptation system, with genotype maturities, sowing time, and nitrogen application adapted to each location would greatly increase wheat productivity compared to sowing a mid-maturity genotype, mid-season, using current practices for nitrogen applications. Tactical adaptation of both genotype and management to the different SOI phases and to different levels of initial Plant Available Water (‘PAW & SOI adaptation’) resulted in further yield improvement. Site long-term increases in yield and gross margin were up to 1.15 t·ha−1 and AU$ 223.0 ha−1 for fixed adaptation (0.78 t·ha−1 and AU$ 153 ha−1 on average across the whole region), and up to an extra 0.26 t·ha−1 and AU$ 63.9 ha−1 for tactical adaptation. For the whole eastern region, these results correspond to an annual AU$ 440 M increase for the fixed adaptation, and an extra AU$ 188 M for the PAW & SOI tactical adaptation. The benefits of PAW & SOI tactical adaptation could be useful for growers to adjust farm management practices according to pre-sowing seasonal conditions and the seasonal climate forecast.
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Evaluation of Gridded Multi-Satellite Precipitation Estimation (TRMM-3B42-V7) Performance in the Upper Indus Basin (UIB)
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Climate 2018, 6(3), 76; https://doi.org/10.3390/cli6030076 - 7 September 2018
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The present study aims to evaluate the capability of the Tropical Rainfall Measurement Mission (TRMM), Multi-satellite Precipitation Analysis (TMPA), version 7 (TRMM-3B42-V7) precipitation product to estimate appropriate precipitation rates in the Upper Indus Basin (UIB) by analyzing the dependency of the estimates’ accuracies
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The present study aims to evaluate the capability of the Tropical Rainfall Measurement Mission (TRMM), Multi-satellite Precipitation Analysis (TMPA), version 7 (TRMM-3B42-V7) precipitation product to estimate appropriate precipitation rates in the Upper Indus Basin (UIB) by analyzing the dependency of the estimates’ accuracies on the time scale. To that avail, various statistical analyses and comparison of Multisatellite Precipitation Analysis (TMPA) products with gauge measurements in the UIB are carried out. The dependency of the TMPA estimates’ quality on the aggregation time scale is analyzed by comparisons of daily, monthly, seasonal and annual sums for the UIB. The results show considerable biases in the TMPA Tropical Rainfall Measurement Mission (TRMM) precipitation estimates for the UIB, as well as high numbers of false alarms and miss ratios. The correlation of the TMPA estimates with ground-based gauge data increases considerably and almost in a linear fashion with increasing temporal aggregation, i.e., time scale. There is a predominant trend of underestimation of the TRMM product across the UIB at most of the gauge stations, i.e., TRMM-estimated rainfall is generally lower than the gauge-measured rainfall. For the seasonal aggregates, the bias is mostly positive for the summer but predominantly negative for the winter season, thereby showing a slight overestimation of the precipitation in summer and underestimation in winter. The results of the study suggest that, in spite of these discrepancies between TMPA estimates and gauge data, the use of the former in hydrological watershed modeling undertaken by the authors may be a valuable alternative in data-scarce regions like the UIB, but still must be taken with a grain of salt.
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Spatial and Temporal Rainfall Variability over the Mountainous Central Pindus (Greece)
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Climate 2018, 6(3), 75; https://doi.org/10.3390/cli6030075 - 6 September 2018
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
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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.
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Past and Future Precipitation Trend Analysis for the City of Niamey (Niger): An Overview
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Climate 2018, 6(3), 73; https://doi.org/10.3390/cli6030073 - 5 September 2018
Abstract
Despite the interest in detecting the extremes of climate in the West African Sahel, few studies have been specifically conducted on the Republic of Niger. This research focuses on past, present, and future precipitation trends for the city of Niamey through the combined
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Despite the interest in detecting the extremes of climate in the West African Sahel, few studies have been specifically conducted on the Republic of Niger. This research focuses on past, present, and future precipitation trends for the city of Niamey through the combined assessment of WMO precipitation indices using RClimDex and the Standardized Precipitation Index. Past daily precipitation data were derived from a 60-year reconstructed meteorological dataset for the Niamey airport station for the period of 1950–2009 and validated through comparison with an observed time series at Niamey airport (1980–2012). Precipitation analysis confirms the literature’s findings, in particular, a decreasing trend in total precipitation over the period of 1950–2009, and a positive trend for data that spans over the period of 1980–2009, suggesting a precipitation recovery after the dry epoch (1968–1985), even if the deficit with the wettest years in the period of 1950–1968 has not been made up. Furthermore, WATCH-Forcing-Data-ERA-Interim projections, elaborated under RCP 4.5 and RCP 8.5 socio-economic conditions, show that precipitation will increase in the future. Therefore, the Nigerien population will benefit from increased rainfall, but will also have to cope with the exacerbation of both flood and drought risks due to a great interannual variability that can positively or negatively influence water availability.
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The Hiatus in Global Warming and Interactions between the El Niño and the Pacific Decadal Oscillation: Comparing Observations and Modeling Results
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Climate 2018, 6(3), 72; https://doi.org/10.3390/cli6030072 - 4 September 2018
Abstract
Ocean oscillations interact across large regions and these interactions may explain cycles in global temperature anomaly, including hiatus periods. Here, we examine ocean interaction measures and compare results from model simulations to observations for El Niño and the Pacific decadal oscillation (PDO). We
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Ocean oscillations interact across large regions and these interactions may explain cycles in global temperature anomaly, including hiatus periods. Here, we examine ocean interaction measures and compare results from model simulations to observations for El Niño and the Pacific decadal oscillation (PDO). We use the global climate model of the Met Office Hadley Centre. A relatively novel method for identifying running leading-agging LL-relations show that the observed El Niño generally leads the observed PDO and this pattern is strengthened in the simulations. However, LL-pattern in both observations and models shows that there are three periods, around 1910–1920, around 1960 and around 2000 where El Niño lags PDO, or the leading signature is weak. These periods correspond to hiatus periods in global warming. The power spectral density analysis, (PSD), identifies various ocean cycle lengths in El Niño and PDO, but the LL-algorithm picks out common cycles of 7–8 and 24 years that shows leading-lagging relations between them.
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Dominant Modes of Upper Ocean Heat Content in the North Indian Ocean
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Climate 2018, 6(3), 71; https://doi.org/10.3390/cli6030071 - 3 September 2018
Abstract
The thermal energy needed for the development of hurricanes and monsoons as well as any prolonged marine weather event comes from layers in the upper oceans, not just from the thin layer represented by sea surface temperature alone. Ocean layers have different modes
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The thermal energy needed for the development of hurricanes and monsoons as well as any prolonged marine weather event comes from layers in the upper oceans, not just from the thin layer represented by sea surface temperature alone. Ocean layers have different modes of thermal energy variability because of the different time scales of ocean–atmosphere interaction. Although many previous studies have focused on the influence of upper ocean heat content (OHC) on tropical cyclones and monsoons, no study thus far—particularly in the North Indian Ocean (NIO)—has specifically concluded the types of dominant modes in different layers of the ocean. In this study, we examined the dominant modes of variability of OHC of seven layers in the NIO during 1998–2014. We conclude that the thermal variability in the top 50 m of the ocean had statistically significant semiannual and annual modes of variability, while the deeper layers had the annual mode alone. Time series of OHC for the top four layers were analyzed separately for the NIO, Arabian Sea, and Bay of Bengal. For the surface to 50 m layer, the lowest and the highest values of OHC were present in January and May every year, respectively, which was mainly caused by the solar radiation cycle.
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News
30 October 2018
Institutional Open Access Agreement between Bill and Melinda Gates Foundation and MDPI
Institutional Open Access Agreement between Bill and Melinda Gates Foundation and MDPI
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