Climate2014, 2(4), 296-309; doi:10.3390/cli2040296 - published 15 October 2014 Show/Hide Abstract
Abstract: In this study, the influence of the East Atlantic/Western Russia teleconnection pattern on the hydroclimatology of Europe, from mid-winter to late spring, is investigated. The influence of EAWR on the variability of precipitation (PP), temperature (TT) and standardized precipitation-evapotranspiration index (SPEI) is investigated on the base of correlation and stability maps. It is shown that EAWR has a strong impact on the coupling between the sub-tropical Atlantic Jet and the African Jet, which in turn affects the climate variability over Europe from mid-winter to late spring. The strongest impact of the mid-winter EAWR over the European precipitation is found to be in mid-winter and early spring over the northern part of the Scandinavian Peninsula and the central and eastern part of Europe; while the influence of the mid-winter EAWR on European temperature persists from mid-winter to late spring, giving the possibility of a potential predictability for spring temperature over extended European regions.
Climate2014, 2(4), 279-295; doi:10.3390/cli2040279 - published 29 September 2014 Show/Hide Abstract
Abstract: Soil temperature, soil moisture, skin temperature and 2-m air temperature are examined from both ground observations and the offline community land model (CLM4). Two-layer soil moisture and three-layer soil temperature observations from six-year (2003–2008) ground measurements at the Lamont, Oklahoma site supported by the Atmospheric Radiation Measurement(ARM)Program of the Department of Energy (DOE) show clear vertical and temporal relations between soil temperature and soil moisture with surface skin temperature and 2-m air temperature. First, daily means reveal that all of these variables have clear seasonal variations, with temperatures peaking in summer and minimizing in winter as a result of surface insolation. Nevertheless, the 2-m air temperature and upper soil temperature (−0.05 m) peak at 2 h after that of surface skin temperature because of the lag of transport of heat from the skin level to the 2-m air and to underground respectively. As a result of such lag, at the monthly annual cycle scale, 2-m air temperature has higher correlation with upper soil temperature than skin temperature does. Second, there are little diurnal and annual variations at the lowest soil layer (−0.25 m). Third, a negative correlation (~−0.40) between skin temperature and soil moisture is observed, consistent with the expectation that heat flux and evaporation are competing physical processes for redistributing surface net radiation. Soil moisture, however, minimizes in March and maximizes in winter due to the local rainfall cycle. All of these key observed relations are qualitatively reproduced in the offline CLM4 using the atmosphere forcing derived from ARM observations. Nevertheless, CLM4 is too dry at the upper layer and has less variation at the lower layer than observed. In addition, CLM4 shows stronger correlation between Tsoil and Tskin (r = 0.96) than the observations (r = 0.64), while the predicted nighttime Tskin is 0.5–2 °C higher than the observations.
Climate2014, 2(4), 264-278; doi:10.3390/cli2040264 - published 26 September 2014 Show/Hide Abstract
Abstract: Based on 56 rainfall stations, which cover the period 1961–2008, we analyzed the presence of trends in the drought-affected area over southern South America (SSA) at different time scales. In order to define drought conditions, we used the standardized precipitation index, which was calculated on time scales of 1, 3, 6, 9 and 12 months. The trends were estimated following both a linear and a non-linear approach. The non-linear approach was based on the residual of the empirical mode decomposition, a recently proposed methodology, which is robust in presence of non-stationary data. This assessment indicates the existence of reversals in the trends of the drought affected, area around the 1990s, from decreasing trends during the first period to increasing trends during the recent period. This is indicative of the existence of a low-frequency variability that modulates regional precipitation patterns at different temporal scales, and warns about possible future consequences in the social and economic sectors if trends towards an increase in the drought affected area continue.
Climate2014, 2(4), 242-263; doi:10.3390/cli2040242 - published 26 September 2014 Show/Hide Abstract
Abstract: Daily rainfall totals are analyzed for the main agro-climatic zones of Sri Lanka for the period 1976–2006. The emphasis is on daily rainfall rather than on longer-period totals, in particular the number of daily falls exceeding given threshold totals. For one station (Mapalana), where a complete daily series is available from 1950, a longer-term perspective on changes over half a century is provided. The focus here is particularly on rainfall in March and April, given the sensitivity of agricultural decisions to early southwest monsoon rainfall at the beginning of the Yala cultivation season but other seasons are also considered, in particular the northeast monsoon. Rainfall across Sri Lanka over three decades is investigated in relation to the main atmospheric drivers known to affect climate in the region: sea surface temperatures in the Pacific and Indian Oceans, of which the former are shown to be more important. The strong influence of El Niño and La Niña phases on various aspects of the daily rainfall distribution in Sri Lanka is confirmed: positive correlations with Pacific sea-surface temperatures during the north east monsoon and negative correlations at other times. It is emphasized in the discussion that Sri Lanka must be placed in its regional context and it is important to draw on regional-scale research across the Indian subcontinent and the Bay of Bengal.
Climate2014, 2(4), 223-241; doi:10.3390/cli2040223 - published 26 September 2014 Show/Hide Abstract
Abstract: Offering a case study of coastal Bangladesh, this study examines the adaptation of agriculturalists to degrading environmental conditions likely to be caused or exacerbated under global climate change. It examines four central components: (1) the rate of self-reported adoption of adaptive mechanisms (coping strategies) as a result of changes in climate; (2) ranking the potential coping strategies based on their perceived importance to agricultural enterprises; (3) identification the socio-economic factors associated with adoption of coping strategies, and (4) ranking potential constraints to adoption of coping strategies based on farmers’ reporting on the degree to which they face these constraints. As a preliminary matter, this paper also reports on the perceptions of farmers in the study about their experiences with climatic change. The research area is comprised of three villages in the coastal region (Sathkhira district), a geographic region which climate change literature has highlighted as prone to accelerated degradation. One-hundred (100) farmers participated in the project’s survey, from which the data was used to calculate weighted indexes for rankings and to perform logistic regression. The rankings, model results, and descriptive statistics, are reported here. Results showed that a majority of the farmers self-identified as having engaged in adaptive behavior. Out of 14 adaptation strategies, irrigation ranked first among farm adaptive measures, while crop insurance has ranked as least utilized. The logit model explained that out of eight factors surveyed, age, education, family size, farm size, family income, and involvement in cooperatives were significantly related to self-reported adaptation. Despite different support and technological interventions being available, lack of available water, shortage of cultivable land, and unpredictable weather ranked highest as the respondent group’s constraints to coping with environmental degradation and change effects. These results provide policy makers and development service providers with important insight, which can be used to better target interventions which build promote or facilitate the adoption of coping mechanisms with potential to build resiliency to changing climate and resulting environmental impacts.
Climate2014, 2(3), 206-222; doi:10.3390/cli2030206 - published 17 September 2014 Show/Hide Abstract
Abstract: In Northeastern Nigeria seasonal rainfall is critical for the availability of water for domestic use through surface and sub-surface recharge and agricultural production, which is mostly rain fed. Variability in rainfall over the last 60 years is the main cause for crop failure and water scarcity in the region, particularly, due to late onset of rainfall, short dry spells and multi-annual droughts. In this study, we analyze 27 years (1980–2006) of gridded daily rainfall data obtained from a merged dataset by the National Centre for Environmental Prediction and Climate Research Unit reanalysis data (NCEP-CRU) for spatial-temporal variability of monthly amounts and frequency in rainfall and rainfall trends. Temporal variability was assessed using the percentage coefficient of variation and temporal trends in rainfall were assessed using maps of linear regression slopes for the months of May through October. These six months cover the period of the onset and cessation of the wet season throughout the region. Monthly rainfall amount and frequency were then predicted over a 24-month period using the Auto Regressive Integrated Moving Average (ARIMA) Model. The predictions were evaluated using NCEP-CRU data for the same period. Kolmogorov Smirnov test results suggest that despite there are some months during the wet season (May–October) when there is no significant agreement (p < 0.05) between the monthly distribution of the values of the model and the corresponding 24-month NCEP-CRU data, the model did better than simply replicating the long term mean of the data used for the prediction. Overall, the model does well in areas and months with lower temporal rainfall variability. Maps of the coefficient of variation and regression slopes are presented to indicate areas of high rainfall variability and water deficit over the period under study. The implications of these results for future policies on Agriculture and Water Management in the region are highlighted.