Abstract: Tropical Cyclone (TC) systems affect global ocean heat transport due to mixing of the upper ocean and impact climate dynamics. A higher Sea Surface Temperature (SST), other influencing factors remaining supportive, fuels TC genesis and intensification. The atmospheric thermodynamic profile, especially the sea-air temperature contrast (SAT), also contributes due to heat transfer and affects TC’s maximum surface wind speed (Vmax) explained by enthalpy exchange processes. Studies have shown that SST can approximately be used as a proxy for SAT. As a part of an ongoing effort in this work, we simplistically explored the connection between SST and Vmax from a climatological perspective. Subsequently, estimated Vmax is applied to compute Power Dissipation Index (an upper limit on TC’s destructive potential). The model is developed using long-term observational SST reconstructions employed on three independent SST datasets and validated against an established model. This simple approach excluded physical parameters, such as mixing ratio and atmospheric profile, however, renders it generally suitable to compute potential intensity associated with TCs spatially and weakly temporally and performs well for stronger storms. A futuristic prediction by the HadCM3 climate model under doubled CO2 indicates stronger storm surface wind speeds and rising SST, especially in the Northern Hemisphere.
Abstract: In this study, the hourly air temperature differences between City hall (urban) and Okoafo (rural) in Lagos, Nigeria, were calculated using one year of meteorological observations, from June 2014 to May 2015. The two sites considered for this work were carefully selected to represent their climate zones. The city core, City hall, is within the Local Climate Zone (LCZ 2) (Compact midrise) while the rural location, Okoafo, falls within LCZ B (Scattered Trees) in the south-western part on the outskirt of the city. This study is one of very few to investigate urban temperature conditions in Lagos, the largest city in Africa and one of the most rapidly urbanizing megacities in the world; findings show that maximum nocturnal UHI magnitudes in Lagos can exceed 7 °C during the dry season, and during the rainy season, wet soils in the rural environment supersede regional wind speed as the dominant control over UHI magnitude.
Abstract: The precise role of air pollution on the climate and local weather has been an issue for quite a long time. Among the diverse issues, the effects of air pollution on lightning are of recent interest. Exploration over several years (2004 to 2011) has been made over Gangetic West Bengal of India using lightning flash data from TRMM-LIS (Tropical Rainfall Measuring Mission-Lightning Imaging Sensor), atmospheric pollutants, and rainfall data during pre-monsoon (April and May) and monsoon (June, July, August and September) seasons. Near-surface pollutants such as PM10 and SO2 have a good positive association with aerosol optical depth (AOD) for both the pre-monsoon and monsoon months. High atmospheric aerosol loading correlates well with pre-monsoon and monsoon lightning flashes. However, rainfall has a dissimilar effect on lightning flashes. Flash count is positively associated with pre-monsoon rainfall (r = 0.64), but the reverse relation (r = −0.4) is observed for monsoon rainfall. Apart from meteorological factors, wet deposition of atmospheric pollutant may be considered a crucial factor for decreased lightning flash count in monsoon. The variation in the monthly average tropospheric column amount of NO2, from the Tropospheric Emission Monitoring Internet Service (TEMIS), is synchronic with average lightning flash rate. It has a good linear association with flash count for both pre-monsoon and monsoon seasons. The effect of lightning on tropospheric NO2 production is evident from the monthly average variation in NO2 on lightning and non-lightning days.
Abstract: The impact of global climate change on Lebanon’s society, environment, and economy is expected to be tremendous. Indices have been developed to help in the identification and monitoring of drought and characterization of its severity. In this context, this work aimed at assessing the temporal variability of the Standardized Precipitation Index in Lebanon for improved understanding of drought occurrence. This is expected to help in mitigation and response actions to future drought circumstances across the country. The methodology of work involved the calculation of the Standardized Precipitation Index over different time series from four regions across the country using both the Variability Analysis of Surface Climate Observations (VASClimO) gridded rainfall dataset for the period 1951–2000 and the European rainfall dataset E-OBS for the period 1950–2014. In general, higher precipitation values were recorded by the VASClimO dataset than those coming from the E-OBS dataset. Intra-annual precipitation changes showed increasing precipitation starting in September-October and decreasing precipitation starting in February. The VASClimO dataset showed a 50% increase in the frequency of severe drought conditions, while the E-OBS dataset indicated a 60% increase in the frequency of moderate drought conditions. In addition, it was observed that the winter of 2014, characterized by extreme drought conditions, was the driest in the past 56 years. Although specific years were commonly characterized by severe to extreme drought conditions with the use of both datasets, considerable differences between the two datasets were observed with respect to the identification of the degree of wet and dry conditions for some other years. Overall, trend lines for the Standardized Precipitation Index values, as derived from VASClimO and E-OBS datasets, commonly point to a relatively slight increase in drought conditions mainly in the winter-spring season; however, the situation on the ground could vary greatly given that many other environmental factors (e.g., changes in land cover) may also play an important role in affecting drought conditions.
Abstract: Climate change adds an additional layer of complexity that needs to be considered in business strategy. For firms in the food industry, many of the important climate impacts are not directly related to food processing so a value chain approach to adaptation is recommended. However, there is a general lack of operational tools to support this. In this study, carbon and water footprints were conducted at a low-precision screening level in three case studies in Australia: Smith’s potato chips, OneHarvest Calypso™ mango and selected Treasury Wine Estates products. The approach was cost-effective when compared to high-definition studies intended to support environmental labels and declarations, yet provided useful identification of physical, financial, regulatory and reputational hotspots related to climate change. A combination of diagnostic footprinting, downscaled climate projection and semi-quantitative value chain analysis is proposed as a practical and relevant toolkit to inform climate adaptation strategies.
Climate2016, 4(2), 25; doi:10.3390/cli4020025 - published 28 April 2016 Show/Hide Abstract
Abstract: Meteorological extreme events have great potential for damaging railway infrastructure and posing risks to the safety of train passengers. In the future, climate change will presumably have serious implications on meteorological hazards in the Alpine region. Hence, attaining insights on future frequencies of meteorological extremes with relevance for the railway operation in Austria is required in the context of a comprehensive and sustainable natural hazard management plan of the railway operator. In this study, possible impacts of climate change on the frequencies of so-called critical meteorological conditions (CMCs) between the periods 1961–1990 and 2011–2040 are analyzed. Thresholds for such CMCs have been defined by the railway operator and used in its weather monitoring and early warning system. First, the seasonal climate change signals for air temperature and precipitation in Austria are described on the basis of an ensemble of high-resolution Regional Climate Model (RCM) simulations for Europe. Subsequently, the RCM-ensemble was used to investigate changes in the frequency of CMCs. Finally, the sensitivity of results is analyzed with varying threshold values for the CMCs. Results give robust indications for an all-season air temperature rise, but show no clear tendency in average precipitation. The frequency analyses reveal an increase in intense rainfall events and heat waves, whereas heavy snowfall and cold days are likely to decrease. Furthermore, results indicate that frequencies of CMCs are rather sensitive to changes of thresholds. It thus emphasizes the importance to carefully define, validate, and—if needed—to adapt the thresholds that are used in the weather monitoring and warning system of the railway operator. For this, continuous and standardized documentation of damaging events and near-misses is a pre-requisite.