Climate — Open Access Climate Science Journal

Cities generally adopt territorial- or production-based rather than consumption-based emissions accounting systems but they find difficult to adopt a specific emissions standard. Due to the diverse calculation methodologies cities use, inter-city emission reductions and climate action comparisons remain challenging. It is crucial to learn how cities address climate change mitigation and adaptation in terms of the emissions accounting methodologies they use, their links to existing city-level international emission standards, and the consistency of those methods used by cities to improve the quality of emissions standards. Normative case study method was applied to explore these issues in three different case cities: Helsinki (Finland), Stockholm (Sweden), and Copenhagen (Denmark). The current calculation methods used in these cities exclude many indirect emissions, and these cities have not adopted consumption-based emissions. Cities also face several dilemmas in system boundaries and baseline year setting, emissions factors calculations, and data collection methods using current calculation methods. All three case cities have adopted amendable emissions accounting systems which exclude certain amounts of emissions from several sectors. Therefore, emission calculation methods must be improved to include all possible sectors and to produce more robust and transparent calculation methods. Full article

The marine surface wind field (10 m) over the Greek seas is analyzed in this study using The RegCM. The model’s spatial resolution is dynamically downscaled to 10 km × 10 km, in order to simulate more efficiently the complex coastlines and the numerous islands of Greece. Wind data for the 1980–2000 and 2080–2100 periods are produced and evaluated against real observational data from 15 island and coastal meteorological stations in order to assess the model’s ability to reproduce the main characteristics of the surface wind fields. RegCM model shows a higher simulating skill to project seasonal wind speeds and direction during summer and the lowest simulating skill in the cold period of the year. Extreme wind speed thresholds were estimated using percentiles indices and three Peak Over Threshold (POT) techniques. The mean threshold values of the three POT methods are used to examine the inter-annual distribution of extreme winds in the study region. The highest thresholds were observed in three poles; the northeast, the southeast, and the southwest of Aegean Sea. Future changes in extreme speeds show a general increase in the Aegean Sea, while lower thresholds are expected in the Ionian Sea. Return levels for periods of 20, 50, 100, and 200 years are estimated. Full article

Rainfall variability has strong impact on food security, livelihood and socio-economic activities as farming in West Africa is mainly rain-fed. The annual, seasonal and decadal rainfall variability over Ghana has been studied and their periodicities analysed using wavelet analysis. A rainfall time series from 1901–2010 from the Global Precipitation Climatology Center (GPCC) was used in this analysis. It was observed that high mean annual rainfall totals ranging from 900–1900mm are recorded over the entire country. In addition, very high totals between 1500–1900mmare recorded at the South-Western part of the country whereas low totals (900–1200 mm) are recorded in the Savannah and East coast of the country. In general, a decreasing trend was observed for the annual rainfall over all the agro-ecological zones except for the coastal zone, where a slight increasing trend of 0.1600mm per year was seen. The seasonal trend analysis revealed a significant decreasing trend at 0.01 significance level in all the agro-ecological zones except for the Savannah during the DJF season indicating an intensification of the Harmattan. The Coastal zone recorded the lowest mean rainfall values for all seasons with the highest of about 150 mm in MAM. The Forest zone on the other hand recorded very high rainfall values for all seasons with the maximum of about 200 mm in JJA. The Transition zone, however, recorded almost quite stable rainfall amount for all seasons except for DJF. On the decadal time scale, below normal rainfall values were observed between the 1901–1920 and 1980–2010 periods for almost all the agro-ecological zones except for the Savannah which showed above normal rainfall values within the 1901–1940 period. Indicating that, the decreasing trend observed in recent years is not solely due to antropogenic factors but have a strong contribution from a natural climate variability. The wavelet analysis also revealed a strong annual periodicity over all the agro-ecological zones except for the Coastal and Forest zones where the annual periodicity was accompanied by 4–8 months signal. The results of both the 5 year moving average and the decadal anomaly confirm a significant decrease in rainfall amount. This will have negative consequences on agricultural practices, water resource management and food security. Full article

This paper examines the effects of climatic and non-climatic factors on cassava yields in Togo using an Autoregressive Distributed Lag (ARDL) modelling approach and pairwise Granger Causality tests. Secondary data on production statistics, rural population, climate variables, prices and nominal exchange rate for the period 1978–2009 are used. Results for estimated short- and long-run models indicate that cassava yield is affected by both ‘normal’ climate variables and within-season rainfall variability. An inverse relationship is found between area harvested and yield of cassava, but a significant positive and elastic effect of labour availability on yield in the long run. Increasing within-lean-season rainfall variability and high lean-season mean temperature are detrimental to cassava yields, while increasing main-season rainfall and mean-temperature enhance cassava yields. Through Granger Causality tests, a bilateral causality is found between area harvested and yield of cassava, and four unidirectional causalities from labour availability, real producer price ratio between yam and cassava, main-season rainfall and lean-season mean temperature to cassava yields. Based on the findings from this study, investment in low-cost irrigation facilities and water harvesting is recommended to enhance the practice of supplemental irrigation. Research efforts should as well be made to breed for drought, heat and flood tolerance in cassava. In addition, coupling area expansion with increasing availability of labour is advised, through the implementation of measures to minimize rural–urban migration. Full article

Climate is one of the single most important factors affecting watershed ecosystems and water resources. The effect of climate variability and change has been studied extensively in some places; in many places, however, assessments are hampered by limited availability of long-term continuous climate data. Weather generators provide a means of synthesizing long-term climate data that can then be used in natural resource assessments. Given their potential, there is the need to evaluate the performance of the generators; in this study, three commonly used weather generators—CLImate GENerator (CLIGEN), Long Ashton Research Station Weather Generator (LARS-WG), and Weather Generators (WeaGETS) were compared with regard to their ability to capture the essential statistical characteristics of observed data (distribution, occurrence of wet and dry spells, number of snow days, growing season temperatures, and growing degree days). The study was based on observed 1966–2015 weather station data from the Western Lake Erie Basin (WLEB), from which 50 different realizations were generated, each spanning 50 years. Both CLIGEN and LARS-WG performed fairly well with respect to representing the statistical characteristics of observed precipitation and minimum and maximum temperatures, although CLIGEN tended to overestimate values at the extremes. This generator also overestimated dry sequences by 18%–30% and snow-day counts by 12%–19% when considered over the entire WLEB. It (CLIGEN) was, however, well able to simulate parameters specific to crop growth such as growing degree days and had an added advantage over the other generators in that it simulates a larger number of weather variables. LARS-WG overestimated wet sequence counts across the basin by 15%–38%. In addition, the optimal growth period simulated by LARS-WG also exceeded that obtained from observed data by 16%–29% basin-wide. Preliminary results with WeaGETS indicated that additional evaluation is needed to better define its parameters. Results provided insights into the suitability of both CLIGEN and LARS-WG for use with water resource applications. Full article

The risks posed by climate change to Sub Saharan Africa’s (SSA) smallholder fresh export fruit and vegetables production are amplifying the significance of farmers’ climate change perceptions in enhancing adoption of suitable adaptation strategies. Production of fresh export fruit and vegetables in Kenya has increasingly been done under the Global-GAP standard scheme by smallholder farmers to improve both environmental conservation and market access. The objective of this study was to determine the effect of Global-GAP policy on climate change perceptions of smallholder French beans farmers. The analysis was based on data collected from a random sample of 616 households interviewed in the Central and Eastern regions of Kenya. The study used principal component analysis (PCA) to extract farmers’ key prevailing climate change perceptions and logit regression model to examine the effect of Global-GAP policy on climate change perceptions among other socio-economic factors. The PCA analysis extracted three components proxying for ‘droughts’, ‘delay in rainy seasons’, ‘diseases and pests’ and three proxying for ‘hot days’, ‘floods’, and ‘diseases and pests’ as summarizing maximum variance in the perceptions in the Central and Eastern region respectively. The common, study area-wide climate change perception was identified as incidence of diseases and pest. Logit regression analysis found that Global-GAP policy significantly influenced and improved farmers’ probability of perceiving climate change. Other factors found to influence farmers’ probability of having the identified climate change perceptions included regional specificity, access to agricultural extension service, access to credit, plot size, and soil fertility. The policy implication of this study is that the government and service providers should mainstream factors like Global-GAP compliance and regional considerations found to improve probability of perceiving climate change in awareness creation extension strategies, towards enhancing adoption of adaptation measures in the smallholder fruits and vegetables farming sector. Full article

Municipalities are important actors in the field of local climate change adaptation. Stakeholders need scientifically sound information tailored to their needs to make local assessment of climate change effects. To provide tailored data to support municipal decision-making, climate scientists must know the state of municipal climate change adaptation, and the climate parameters relevant to decisions about such adaptation. The results of an empirical study in municipalities in the state of Baden-Wuerttemberg in Southwestern Germany showed that adaptation is a relatively new topic, but one of increasing importance. Therefore, past weather events that caused problems in a municipality can be a starting point in adaptation considerations. Deduction of tailored climate parameters has shown that, for decisions on the implementation of specific adaptation measures, it also is necessary to have information on specific parameters not yet evaluated in climate model simulations. We recommend intensifying the professional exchange between climate scientists and stakeholders in collaborative projects with the dual goals of making practical adaptation experience and knowledge accessible to climate science, and providing municipalities with tailored information about climate change and its effects. Full article

The Global Climate Model (GCM) run at a coarse spatial resolution cannot be directly used for climate impact studies. Downscaling is required to extract the sub-grid and local scale information. This paper investigates if the artificial neural network (ANN) is better than the widely-used regression-based statistical downscaling model (SDSM) for downscaling climate for a site in Colombo, Sri Lanka. Based on seasonal and annual model biases and the root mean squared error (RMSE), the ANN performed better than the SDSM for precipitation. This paper proposes a novel methodology for improving climate predictions by combining SDSM with neural networks. This method will allow a user to apply SDSM with a neural network model for higher skills in downscaling. The study uses the Canadian Earth System Model (CanESM2) of the IPCC Fifth Assessment Report, reanalysis from the National Center for Environmental Prediction (NCEP), and the Asian Precipitation Highly Resolved Observational Data Integration towards Evaluation of Water Resources (APHRODITE) project data as the observation. SDSM and the focused time-delayed neural network (TDNN) models are used for the downscaling. The projected annual increase for Representative Concentration Pathway (RCP) is 8.5; the average temperature is 2.83 °C (SDSM) and 3.03 °C (TDNN), and rainfall is 33% (SDSM) and 63% (TDNN) for 2080’s. Full article

The present study presents a brief discussion regarding the evolution of meteorology from the sixteenth to the twenty-first century, throughout antiquitiy, Aristotle’s legacy, and contemporaneity. Part of the text is dedicated to illustrating the emergence of Brazilian climatology and a new paradigm, postulating physical geography and the French School of Climatology and Meteorology. Full article

Lake Hawassa is a topographically closed lake in the Central Main Ethiopian Rift Valley. The water level of this lake has been reported to dramatically rise without falling back to the original level. The cause of this rise is not yet sufficiently investigated and subjected to this study. This study argues that the general variability in the lake level and its resultant rise has significant linkage to the temperature variability at the Pacific Ocean. The linkage between water level dynamics and climate variability was analyzed through the application of diverse statistical techniques. It comprises the Mann-Kendall trend analysis to test monotonic variations over time; sequential regime shift index (RSI) to detect significant shifts in the mean values of time-series records of lake level; and coherence analysis to investigate the linear relationship between ENSO index and records of local hydrology. Despite the multiple rises and falls, the results of the trend analysis revealed that the lake level experienced a significant resultant upward trend with Mann-Kendall τ values of 0.558, 0.629, and 0.545 (at α = 0.05 and p < 0.01%) for monthly maximum, average and minimum values respectively. The sequential regime shift evidenced that most of the significant shifts coincide with the occurrences of ENSO events. Generally, the lake level tends to be high during El Niño and low during La Niña episodes. The typical examples are the coincidence of extreme historical maximum lake level to the strongest El Niño event of the century that occurred in 1997/98 and the lowest lake level record in the year 1975 with a strong La Niña year. The coincidence of climate regime shift in the Pacific Ocean in 1976/77 with an equivalent regime shift in the lake level is an additional confirmation for the possible climate-hydrology linkage. The likely involvement of anthropogenic factors (at least in modifying the effect of climate) is justified by the interplay between the non-trending rainfall and potential evapotranspiration and trending streamflow. The coherence analysis between 492 pairs of monthly step datasets of 3.4ENSO index and lake level changes is also found to have a significant linear relationship over frequencies ranging from 0.13 to 0.14 cycles/month or 1.56 to 1.68 cycles/year. This corresponds to a dominant average periodicity (coincident cycle) of about 7.4 months which is thought to be related to the time span of the two rainy season in the locality. Full article

It has been widely predicted that Southeast Asia is among the regions facing the most severe climate change impacts. Despite this forecast, little research has been published on the potential impacts of climate change on soil erosion in this region. This study focused on the impact of climate change on spatial and temporal patterns of soil erosion in the Laos–Vietnam transnational Upper Ca River Watershed. The Soil and Water Assessment Tool (SWAT) coupled with downscaled global climate models (GCMs) was employed for simulation. Soil erosion in the watershed was mostly found as “hill-slope erosion”, which occurred seriously in the upstream area where topography is dominated by numerous steep hills with sparse vegetation cover. However, under the impact of climate change, it is very likely that soil erosion rate in the downstream area will increase at a higher rate than in its upstream area due to a greater increase in precipitation. Seasonally, soil erosion is predicted to increase significantly in the warmer and wetter climate of the wet season, when higher erosive power of an increased amount and intensity of rainfall is accompanied by higher sediment transport capacity. The results of this study provide useful information for decision makers to plan where and when soil conservation practice should be focused. Full article

Malaria is a major public health challenge in Ghana and adversely affects the productivity and economy of the country. Although malaria is climate driven, there are limited studies linking climate variability and disease transmission across the various agro-ecological zones in Ghana. We used the VECTRI (vector-borne disease community model of the International Centre for Theoretical Physics, Trieste) model with a new surface hydrology scheme to investigate the spatio-temporal variability in malaria transmission patterns over the four agro-ecological zones in Ghana. The model is driven using temperature and rainfall datasets obtained from the GMet (Ghana Meteorological Agency) synoptic stations between 1981 and 2010. In addition, the potential of the VECTRI model to simulate seasonal pattern of local scale malaria incidence is assessed. The model results reveal that the simulated malaria transmission follows rainfall peaks with a two-month time lag. Furthermore, malaria transmission ranges from eight to twelve months, with minimum transmission occurring between February and April. The results further reveal that the intra- and inter-agro-ecological variability in terms of intensity and duration of malaria transmission are predominantly controlled by rainfall. The VECTRI simulated EIR (Entomological Inoculation Rate) tends to agree with values obtained from field surveys across the country. Furthermore, despite being a regional model, VECTRI demonstrates useful skill in reproducing monthly variations in reported malaria cases from Emena hospital (a peri urban town located within Kumasi metropolis). Although further refinements in this surface hydrology scheme may improve VECTRI performance, VECTRI still possesses the potential to provide useful information for malaria control in the tropics. Full article

Low-flow is the flow of water in a river during prolonged dry weather. This paper investigated the uncertainty originating from hydrological model calibration and structure in low-flow simulations under climate change conditions. Two hydrological models of contrasting complexity, GR4J and SWAT, were applied to four sub-watersheds of the Yamaska River, Canada. The two models were calibrated using seven different objective functions including the Nash-Sutcliffe coefficient (NSE_Q) and six other objective functions more related to low flows. The uncertainty in the model parameters was evaluated using a PARAmeter SOLutions procedure (PARASOL). Twelve climate projections from different combinations of General Circulation Models (GCMs) and Regional Circulation Models (RCMs) were used to simulate low-flow indices in a reference (1970–2000) and future (2040–2070) horizon. Results indicate that the NSE_Q objective function does not properly represent low-flow indices for either model. The NSE objective function applied to the log of the flows shows the lowest total variance for all sub-watersheds. In addition, these hydrological models should be used with care for low-flow studies, since they both show some inconsistent results. The uncertainty is higher for SWAT than for GR4J. With GR4J, the uncertainties in the simulations for the 7Q2 index (the 7-day low-flow value with a 2-year return period) are lower for the future period than for the reference period. This can be explained by the analysis of hydrological processes. In the future horizon, a significant worsening of low-flow conditions was projected. Full article

The current study was conducted to examine the impact of climate change on rainfall in Jharkhand state of India. It deals with the analysis of the historical spatiotemporal variability of rainfall on the annual, seasonal and monthly scale in 18 districts of the state Jharkhand over a period of 102 years (1901–2002). Mann-Kendall trend test and Sen’s slope method were applied to detect trends and the magnitude of change over the time period of 102 years (1901–2002). Mann Whitney Pettit’s method and Cumulative deviations test were applied for detection of shift point in the series. The results obtained year 1951 to be the most probable shift point in annual rainfall. The trend analysis along with the percent change for the data series before (1901–1951) and after the shift point (1952–2002) was also done. A significant downward rainfall trend was found in annual, monsoon and winter rainfall over the period of 102 years. The maximum decrease was found for the Godda (19.77%) and minimum at Purbi Singhbum station (1.95%). Trend analysis before shift point, i.e., during 1901–1951 showed an upward trend in annual rainfall and after shift point (1952–2002) a downward trend. The trend analysis for entire Jharkhand demonstrated a significant downward trend in annual and monsoon rainfall with a decrease of 14.11% and 15.65% respectively. A downward trend in seasonal rainfall will have a more pronounced effect on agricultural activities in the area as it may affect the growth phase of the kharif crops (May–October) in the region. Full article

This paper examines the relationship between the Antarctic Oscillation (AAO), cold waves and occurrence of frosts in the state of Santa Catarina, Brazil, during the winter quarter. Research on this topic can assist different spheres of society, such as public health and agriculture, since cold waves can influence and/or aggravate health problems and frosts can inflict economic losses especially in the agricultural sector. For the purpose of this paper, cold wave is considered as the event in which the daily average surface air temperature was at least two standard deviations below the average value of the series on the day and for two consecutive days or more. The data on the average air temperature and frost occurrences are provided by the Company of Agricultural Research and Rural Extension of Santa Catarina/Center for Environmental Information and Hydrometeorology (EPAGRI/CIRAM). The AAO was subjected to statistical analysis using significance tests for the averages (Student’s t-test) and variances (F-test) with a significance level of α = 5%. The results show that cold waves are unevenly distributed in the agroecological zones of Santa Catarina. It is found that the AAO is associated with the occurrence of frosts (in the agroecological zones represented by the municipalities of Itajaí and São José) in the state of Santa Catarina. Full article

We studied climate trends and the occurrence of rare and extreme temperature and precipitation events in northern Fennoscandia in 1914–2013. Weather data were derived from nine observation stations located in Finland, Norway, Sweden and Russia. The results showed that spring and autumn temperatures and to a lesser extent summer temperatures increased significantly in the study region, the observed changes being the greatest for daily minimum temperatures. The number of frost days declined both in spring and autumn. Rarely cold winter, spring, summer and autumn seasons had a low occurrence and rarely warm spring and autumn seasons a high occurrence during the last 20-year interval (1994–2013), compared to the other 20-year intervals. That period was also characterized by a low number of days with extremely low temperature in all seasons (4–9% of all extremely cold days) and a high number of April and October days with extremely high temperature (36–42% of all extremely warm days). A tendency of exceptionally high daily precipitation sums to grow even higher towards the end of the study period was also observed. To summarize, the results indicate a shortening of the cold season in northern Fennoscandia. Furthermore, the results suggest significant declines in extremely cold climate events in all seasons and increases in extremely warm climate events particularly in spring and autumn seasons. Full article

Abstract: A 15-year (1997–2011) climatology of dust events at the NASA DFRC in Lancaster, California, USA, was performed to evaluate how the extratropical systems were associated with dust storms over this region. For this study, we collected meteorological data for Edwards Air Force Base (EAFB) in Lancaster, California, which is very close to NASA DFRC, from wunderground.com, National Centers for Environmental Prediction (NCEP)/North American Regional Reanalysis (NARR), NCEP/Hydro-meteorological Prediction Center/National Weather Service (NWS), and Unisys analyses. We find that the dust events were associated with the development of a deep convective boundary layer, turbulence kinetic energy (TKE) ≥3 J/kg, a deep unstable lapse rate layer, a wind speed above the frictional threshold wind speed necessary to ablate dust from the surface (≥7.3 m/s), a presence of a cold trough above the deep planetary boundary layer (PBL), a strong cyclonic jet, an influx of vertical sensible heat from the surrounding area, and a low volumetric soil moisture fraction <0.3. The annual mean number of dust events, their mean duration, and the unit duration per number of event for each visibility range, when binned as <11.2 km, <8 km, <4.8 km, <1.6 km, and <1 km were calculated. The visibility range values were positively correlated with the annual mean number of dust events, duration of dust events, and the ratio of duration of dust events. The percentage of the dust events by season shows that most of the dust events occurred in autumn (44.7%), followed by spring (38.3%), and equally in summer and winter with these seasons each accounting for 8.5% of events. This study also shows that the summer had the highest percentage (10%) of the lowest visibility condition (<1 km) followed by autumn (2%). Neither of the other two seasons—winter and spring—experienced such a low visibility condition during the entire dust events over 15 years. Winter had the highest visibility (<11.2 km) percentage, which was 67% followed by spring (55%). Wind speed increasing to a value within the range of 3.6–11 m/s was typically associated with the dust events. Full article

Urban heat islands (UHIs) in large cities and different climatic regions have been thoroughly studied; however, their effects are becoming a common concern in smaller cities as well. We assessed UHIs in three tropical cities, analyzing how synoptic conditions, urban morphology, and land cover affect the heat island magnitude. Data gathering involved mobile surveys across Paranavaí (Paraná), Rancharia (São Paulo), and Presidente Prudente (São Paulo), Brazil, during summer evenings (December 2013–January 2014). Temperature data collected over five days in each city point to heat islands with magnitudes up to 6 °C, under calm synoptic conditions, whereas summer average UHI magnitudes peak at 3.7 °C. In addition, UHI magnitudes were higher in areas with closely spaced buildings and few or no trees and building materials that are not appropriate for the region’s climate and thermal comfort. Full article

Kenya’s water abstraction must meet the projected growth in municipal and irrigation demand by the end of 2030 in order to achieve the country’s industrial and economic development plan. The Masinga dam, on the Tana River, is the key to meeting this goal to satisfy the growing demands whilst also continuing to provide hydroelectric power generation. This study quantitatively assesses the reliability and robustness of the Masinga dam system under uncertain future supply and demand using probabilistic climate and population projections, and examines how long-term planning may improve the longevity of the dam. River flow and demand projections are used alongside each other as inputs to the dam system simulation model linked to an optimisation engine to maximise water availability. Water availability after demand satisfaction is assessed for future years, and the projected reliability of the system is calculated for selected years. The analysis shows that maximising power generation on a short-term year-by-year basis achieves 80%, 50% and 1% reliability by 2020, 2025 and 2030 onwards, respectively. Longer term optimal planning, however, has increased system reliability to up to 95% in 2020, 80% in 2025, and more than 40% in 2030 onwards. In addition, increasing the capacity of the reservoir by around 25% can significantly improve the robustness of the system for all future time periods. This study provides a platform for analysing the implication of different planning and management of Masinga dam and suggests that careful consideration should be given to account for growing municipal needs and irrigation schemes in both the immediate and the associated Tana River basin. Full article

The growth of urban areas has a significant impact on land use by replacing areas of vegetation with residential and commercial areas and their related infrastructure; this escalates the land surface temperature (LST). Rapid urban growth has occurred in Duhok City due to enhanced political and economic growth during the period of this study. The objective is to investigate the effect of land use changes on LST; this study depends on data from three Landsat images (two Landsat 5-TM and Landsat OLI_TIRS-8) from 1990, 2000 and 2016. Supervised classification was used to compute land use/cover categories, and to generate the land surface temperature (LST) maps the Mono-window algorithm was used. Images were also used to create the normalized difference vegetation index (NDVI), normalized difference built-up index (NDBI), normalized difference bareness index (NDBAI) and normalized difference water index (NDWI) maps. Linear regression analysis was used to generate relationships between LST with NDVI, NDBI, NDBAI and NDWI. The study outcome proves that the changes in land use/cover have a significant role in the escalation of land surface temperatures. The highest temperatures are associated with barren land and built-up areas, ranging from 47°C, 50°C, 56°C while lower temperatures are related to water bodies and forests, ranging from 25°C, 26°C, 29°C respectively, in 1990, 2000 and 2016. This study also proves that NDVI and NDWI correlate negatively with low temperatures while NDBI and NDBAI correlate positively with high temperatures. Full article