The occurrence of a sudden stratospheric warming (SSW) excites disturbances in the mesosphere-lower thermospheric (MLT) wind and temperature. Here, we have examined the high frequency (HF) radar wind data from the South African National Antarctic Expedition, SANAE (72° S, 3° W), a radar which is part of the Super Dual Auroral Radar Network (SuperDARN). Sounding of the Atmosphere using Broadband Emission Radiometry (SABER) on board the Thermosphere-Ionosphere-Mesosphere-Energetics and Dynamics (TIMED) satellite temperature data and National Centre for Environmental Prediction (NCEP) temperature and wind data are used to investigate the dynamical effects of the unprecedented September 2002 SSW in the Antarctica stratosphere and MLT. The mean zonal wind (from SANAE HF radar) at the MLT shows reversal approximately 7 days before the reversal at 10 hPa (from NCEP). This indicates that there was a downwards propagation of circulation disturbance. Westerly zonal winds dominate the winter MLT, but during the 2002 winter there are many periods of westward winds observed compared to other years. The normalised power spectrums of both meridional and zonal winds show presence of planetary waves (of ~14-day period) before the occurrence of the SSW. The SABER vertical temperature profiles indicated the cooling of the MLT region before the SSW event
Abstract. This paper presents 23 years of quasi-continuous measurements of the total ozone column (TOC) over the Southern Space Observatory (SSO) in São Martinho da Serra, Brazil (29.26 • S, 53.48 • and 488 m altitude). The TOC was measured by a Brewer spectrometer, and the results are also compared to daily and monthly observations from the TOMS (Total Ozone Mapping Spectrometer) and OMI (Ozone Monitoring Instrument) satellite instruments. Analyses of the main interannual modes of variability computed using the wavelet transform method were performed. A favorable agreement between the Brewer spectrophotometer and satellite datasets was found. The seasonal TOC variation is dominated by an annual cycle, with a minimum of approximately 260 DU in April and a maximum of approximately 295 DU in September. The wavelet analysis applied in the SSO TOC anomaly time series revealed that the Quasi-Biennial Oscillation (QBO) modulation was the main mode of interannual variability. The comparison between the SSO TOC anomaly time series with the QBO index revealed that the two are in opposite phases.
The variability of temperature and precipitation influenced by El Niño-Southern Oscillation (ENSO) is potentially one of key factors contributing to vegetation product in southern Africa. Thus, understanding large-scale ocean-atmospheric phenomena like the ENSO and Indian Ocean Dipole/Dipole Mode Index (DMI) is important. In this study, 16 years (2002)(2003)(2004)(2005)(2006)(2007)(2008)(2009)(2010)(2011)(2012)(2013)(2014)(2015)(2016)(2017) of Moderate Resolution Imaging Spectroradiometer (MODIS) Terra/Aqua 16-day normalized difference vegetation index (NDVI), extracted and processed using JavaScript code editor in the Google Earth Engine (GEE) platform was used to analyze the vegetation response pattern of the oldest proclaimed nature reserve in Africa, the Hluhluwe-iMfolozi Park (HiP) to climatic variability. The MODIS enhanced vegetation index (EVI), burned area index (BAI), and normalized difference infrared index (NDII) were also analyzed. The study used the Modern Retrospective Analysis for the Research Application (MERRA) model monthly mean soil temperature and precipitations. The Global Land Data Assimilation System (GLDAS) evapotranspiration (ET) data were used to investigate the HiP vegetation water stress. The region in the southern part of the HiP which has land cover dominated by savanna experienced the most impact of the strong El Niño. Both the HiP NDVI inter-annual Mann-Kendal trend test and sequential Mann-Kendall (SQ-MK) test indicated a significant downward trend during the El Niño years of 2003 and 2014-2015. The SQ-MK significant trend turning point which was thought to be associated with the 2014-2015 El Niño periods begun in November 2012. The wavelet coherence and coherence phase indicated a positive teleconnection/correlation between soil temperatures, precipitation, soil moisture (NDII), and ET. This was explained by a dominant in-phase relationship between the NDVI and climatic parameters especially at a period band of 8-16 months. Climate 2018, 6, 95 2 of 24The influence of drought on vegetation varies in the spatial and temporal scales, and these are projected to increase with climate change [6,7]. This behavior affects wildlife, particularly in semi-arid and arid environments where herbivory is strongly restricted by vegetation extent and water availability [8]. In the north-east part of KwaZulu-Natal, South Africa, for example, droughts are becoming a recurrent and prominent feature [9,10], affecting vegetation, water and wildlife resources notably in the Hluhluwe-iMfolozi Park (HiP), the oldest proclaimed game reserve in Africa, as reported in this paper. Furthermore, these impacts have potential consequences that could incapacitate this game reserve's support of its specialist grazers such as rhinos [11].Understanding the association between vegetation productivity and climatic variables such as precipitation and temperature has, therefore, become a high priority. To address this, spatiotemporal tools that can integrate climate data with other information of interest are required....
Abstract. This paper presents comparison results of the total column ozone (TCO) data product over 13 southern tropical and subtropical sites recorded from the Infrared Atmospheric Sounder Interferometer (IASI) onboard the EU-METSAT (European organization for the exploitation of METeorological SATellite) MetOp (Meteorological Operational satellite program) satellite. TCO monthly averages obtained from IASI between June 2008 and December 2012 are compared with collocated TCO measurements from the Ozone Monitoring Instrument (OMI) on the OMI/Aura satellite and the Dobson and SAOZ (Système d'Analyse par Observation Zénithale) ground-based instruments. The results show that IASI displays a positive bias with an average less than 2 % with respect to OMI and Dobson observations, but exhibits a negative bias compared to SAOZ over Bauru with a bias around 2.63 %. There is a good agreement between IASI and the other instruments, especially from 15 • S southward where a correlation coefficient higher than 0.87 is found. IASI exhibits a seasonal dependence, with an upward trend in autumn and a downward trend during spring, especially before September 2010. After September 2010, the autumn seasonal bias is considerably reduced due to changes made to the retrieval algorithm of the IASI level 2 (L2) product.The L2 product released after August (L2 O 3 version 5 (v5)) matches TCO from the other instruments better compared to version 4 (v4), which was released between June 2008 and August 2010. IASI bias error recorded from September 2010 is estimated to be at 1.5 % with respect to OMI and less than ±1 % with respect to the other groundbased instruments. Thus, the improvement made by O 3 L2 version 5 (v5) product compared with version 4 (v4), allows IASI TCO products to be used with confidence to study the distribution and interannual variability of total ozone in the southern tropics and subtropics.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.