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Copyright of Informe Gepec is the property of Informe Gepec and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Informe Gepec is the property of Informe Gepec and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

A declining trend in Indian summer monsoon precipitation (ISMP) in the latter half of the 20th century is a scientifically challenging and societally relevant research issue. Heavy aerosol loading over India is one of the key factors in modulating the ISMP. Using the state-of-the-state-of-the-art chemistry-climate model, ECHAM6-HAMMOZ, the impacts of South Asian anthropogenic sulfate aerosols on the Indian summer monsoon precipitation were investigated against: (1) 2010 La Niña (excess monsoon), (2) 2015 El Niño (deficit monsoon) in comparison to (3) normal monsoon 2016. Sensitivity simulations were designed with 48% enhancement in South Asian SO 2 emissions based on a trend estimated from Ozone Monitoring Instrument (OMI) satellite observations during 2006–2017. The model simulations showed that sulfate aerosols reduce ISMP by 27.5%–43.3 %, while simulations without sulfate loading enhanced ISMP by 23% in 2010 La Niña and reduction by 35% in 2015 El Niño. This paper reports that sulfate aerosols loading over India reduce precipitation by aerosol-induced direct and indirect effects by inducing atmospheric cooling, weakening in the convection, and reduction in moisture transport to Indian landmass. This paper emphasizes the necessity of alternate use of energy to reduce sulfate aerosol emissions to solve water issues in South Asia. [Display omitted] • Sulfate emission reduces Indian summer monsoon precipitation through aerosol-radiation and aerosol-cloud interactions. • Over 27% of the summer monsoon rainfall deficit in a normal year are linked to Asian anthropogenic sulfate emissions. • Sulfate-induced rainfall reduction is the maximum for La Niña year. • SO 2 loading increases atmospheric stability and weakens moisture transport to India. [ABSTRACT FROM AUTHOR]

Lake surface water temperature (LSWT) is sensitive to long-term changes in thermal structure of lakes. This paper investigates the association of LSWT with meteorological parameters and its impact during El Nino and La Nina events over the Himalayan lake region, using Moderate Resolution Imaging Spectroradiometer (MODIS) satellite data from 2001 to 2017. The observed daytime rates of change of LSWT was −0.05°C/year whereas it was +0.01°C/year for nighttime. The cooling of lake during daytime could be attributed to increase in rainfall and decrease in solar radiation, whereas increase in nighttime LSWT is due to increasing lowest temperature. The variability in LSWT with respect to meteorological variables during El Nino Southern Oscillation period was highest for cold phase than warm phase. There was only 1% increase in LSWT in the El Nino years (2002 and 2009), due to decreased rainfall by 95% and 56% respectively. On the other hand, the LSWT decreased in strong La Nina years of 2007 (2%) and 2010 (6%) due to the drastically increased rainfall, decreased maximum temperature and solar radiation. The correlation revealed that, in addition to the increase in temperature, the LSWT warming is consistent with the decrease in rainfall and increase in solar radiation. [ABSTRACT FROM AUTHOR]

Rainfall erosivity (RE) is the ability of rainfall to cause soil or regolith erosion. Understanding the spatial distribution and temporal trends of RE is critical for assessing soil erosion risk and improving upon soil conservation planning. The aim of this paper is to study the temporal and spatial changes in RE in the Huaihe River Basin, China. This will be based on daily precipitation data from 67 meteorological stations in the Huaihe River Basin for the period 1971 to 2016. The assessment of the resulting RE values involved inverse distance-weighted (IDW) interpolation, Sen's slope estimation, and the Mann-Kendall nonparametric test. In addition, the possible influence of the El Niño – Southern Oscillation (ENSO) on RE in the Huaihe River Basin will be examined by the use of Cross Wavelet Transform (XWT) and Wavelet Coherence (WTC), where the relationship between RE and the multivariate ENSO index (MEI) are analyzed. The results showed that the spatial distribution of RE is characterized by it increasing from west to east and north to south. In most areas, the annual RE has increased slightly, while this upward trend in the southeastern part of the study area was more significant. The rainfall erosivity of rainstorms (RE-SM) in the Huaihe River Basin played a leading role in the annual RE, and 97% of the stations displayed the order of importance of the different categories of rainfall as rainfall erosivity of rainstorms (RE-SM) > rainfall erosivity of heavy rain (RE-HR) > rainfall erosivity of moderate rain (RE-MR). Over monthly time scales, the RE was the highest in July, while it was lowest in December, with the monthly differences being apparent. The RE in the Huaihe River Basin were relatively large during non-El Niño/La Niña periods and relatively small during El Niño/La Niña periods. Finally, correlations between RE and the MEI in various parts of the basin showed different characteristics over time and space, with both displaying similarities and differences. • Spatial–temporal variations in rainfall erosivity in the study area were quantified. • Rainfall erosivity of rainstorms (RE-SM) dominates in different categories of rainfall erosivity. • El Niño and La Niña events have different impacts on rainfall erosivity in the Huaihe River Basin. [ABSTRACT FROM AUTHOR]

Copyright of Boletim de Geografia is the property of Universidade Estadual de Maringa and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Revista de la Academia Colombiana de Ciencias Exactas, Físicas y Naturales is the property of Academia Colombiana de Ciencias Exactas, Fisicas y Naturales and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Abstract: The effects of El Nino and La Nina have been considered as the major variables in weather changes in the Middle East. This issue has been shown by regression indexes in a number of papers. The presented study has proven that the El Nino and La Nina should be added to the weather forecast variables because of their major effects. Weather forecasts could be influenced by some variables that have uncertainty, so the deterministic approaches may lead to incorrect predictions. The proposed algorithm can be used when some variables have uncertainty. In this study, a probabilistic approach has been chosen to show the effect of El Nino and La Nina on the monthly maximum temperature. Different ENSO Indices have been proposed for El Nino or La Nina occurrences but each of them has some deficiencies. In order to overcome the drawback of using one of the ENSO Indices, the fuzzy based analysis approach has been chosen in this paper. Data from Chabahar, one of the stations in the south of Iran, has been chosen for the algorithm to be applied on. MATLAB has been used to run the algorithm on the data. The results show that El Nino and La Nina lead to major effect on the amount of monthly maximum temperature in the south of Iran. [Copyright &y& Elsevier]

Copyright of Atmosphere -- Ocean (Taylor & Francis Ltd) is the property of Taylor & Francis Ltd and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Climate is the primary determinant of agricultural productivity. It is believed that in many parts of the world, including the United States, much of the year-to-year variation in climate can be traced to the El Nino-Southern Oscillation phenomenon. In 1997-98 the world experienced a severe El Nino event and this was followed by a strong La Nina in 1998-99. This paper develops estimates of the economic consequences of such events on US agriculture using a stochastic economic model of the US agricultural sector. Both phases result in economic damages to US agriculture--a $1.5 to $1.7 billion loss for El Nino and a$2.2 to $6.5 billion loss for La Nina. The range in these damage estimates reflects assumptions concerning the relationship between yields and ENSO weather patterns and how farmers respond to these potential yield differentials. [ABSTRACT FROM AUTHOR]