Using AVHRR lunar observations for NDVI long-term climate change detection

2009 ◽  
Vol 114 (D20) ◽  
Author(s):  
Changyong Cao ◽  
Eric Vermote ◽  
Xiaoxiong Xiong
2021 ◽  
Vol 14 (6) ◽  
pp. 3378
Author(s):  
Pedro Hugo Oliveira Moreira ◽  
Alan Cavalcanti da Cunha ◽  
Antonio Carlos Lola da Costa

Esta pesquisa tem como objetivo analisar a variabilidade e a tendência de variáveis meteorológicas no longo prazo para caracterizar o clima urbano da cidade de Macapá-AP. Compreender a variabilidade  dos índices climáticos em ambientes urbanos tende a mostrar possíveis interferências na qualidade de vida dos moradores locais, bem como torna possível comparar a realidade das cidades amazônicas em um contexto regional, nacional e mundial, contribuindo ao debate acadêmico. No presente caso as variáveis-chave são a temperatura do ar e a precipitação pluviométrica. A metodologia consiste nas seguintes etapas: a) coleta e consistência da série de dados por um período contínuo de 52 anos para o Estado do Amapá (1968 – 2020), b) a utilização do aplicativo RClimDex 1.1/IPCC para estimar as variações e as tendências climáticas locais utilizando-se 27 parâmetros climáticos extremos previstos pela equipe de peritos do CCI/CLIVAR e Climate Change Detection Monitoring and Indices (ETCCDMI). Os resultados obtidos acusaram treze indicadores estatísticos significativos (p<0,05), sugerindo tendência generalizada da elevação da temperatura média do ar na zona urbana da cidade. Como consequência, estes indicadores mostraram não somente uma significativa elevação das temperaturas máximas, médias e mínimas, mas também quais são os indicadores mais coerentemente associados com tendências de aquecimento temporal de cidades amazônicas, tanto para períodos diurnos quanto para períodos noturnos. Esse comportamento dos indicadores confirma a hipótese de predisposição a formação de ilha de calor em Macapá. Esta tendência mudou significativamente a partir de 2010.   Index of Long Term Climate Trends in Urban Area in the Eastern AmazonA B S T R A C T This research aims to analyze the variability and trend of meteorological variables in the long term to characterize the urban climate of the city of Macapá-AP. Understanding the variability of climate indices in urban environments reveals possible interferences in the quality of life of the inhabitants, especially in urban locations. However, it has been relatively difficult to quantify trends in historical series that reliably represent climate indices relevant to the reality of Amazonian cities, both at a local and regional level. In the present case, the key variables analyzed were air temperature and rainfall. The methodology followed the following steps: a) collection and consistency of the data series over a continuous period of 52 years for the State of Amapá (1968–2020), b) using the data series by the RClimDex 1.1/IPCC application to estimate the local climate variations and trends using 27 extreme weather parameters predicted by the CCI/CLIVAR and Climate Change Detection Monitoring and Indices (ETCCDMI) team of experts. The results showed thirteen significant statistical indicators (p<0.05), suggesting a general trend towards an increase in the average air temperature in the urban area of the city. As a consequence, these indicators showed not only a significant increase in maximum, average and minimum temperatures, but also the indicators most coherently associated with temporal warming trends in Amazonian cities. So many that these effects seem to affect both the day and night periods, confirming the hypothesis of a predisposition to the formation of an urban heat island, with a significant change in this trend from 2010 onwards. Keywords: RClimDex 1.1, climate change indice, Macapá, Amapá


2011 ◽  
Vol 24 (20) ◽  
pp. 5275-5291 ◽  
Author(s):  
Bettina C. Lackner ◽  
Andrea K. Steiner ◽  
Gabriele C. Hegerl ◽  
Gottfried Kirchengast

Abstract The detection of climate change signals in rather short satellite datasets is a challenging task in climate research and requires high-quality data with good error characterization. Global Navigation Satellite System (GNSS) radio occultation (RO) provides a novel record of high-quality measurements of atmospheric parameters of the upper-troposphere–lower-stratosphere (UTLS) region. Because of characteristics such as long-term stability, self calibration, and a very good height resolution, RO data are well suited to investigate atmospheric climate change. This study describes the signals of ENSO and the quasi-biennial oscillation (QBO) in the data and investigates whether the data already show evidence of a forced climate change signal, using an optimal-fingerprint technique. RO refractivity, geopotential height, and temperature within two trend periods (1995–2010 intermittently and 2001–10 continuously) are investigated. The data show that an emerging climate change signal consistent with the projections of three global climate models from the Coupled Model Intercomparison Project cycle 3 (CMIP3) archive is detected for geopotential height of pressure levels at a 90% confidence level both for the intermittent and continuous period, for the latter so far in a broad 50°S–50°N band only. Such UTLS geopotential height changes reflect an overall tropospheric warming. 90% confidence is not achieved for the temperature record when only large-scale aspects of the pattern are resolved. When resolving smaller-scale aspects, RO temperature trends appear stronger than GCM-projected trends, the difference stemming mainly from the tropical lower stratosphere, allowing for climate change detection at a 95% confidence level. Overall, an emerging trend signal is thus detected in the RO climate record, which is expected to increase further in significance as the record grows over the coming years. Small natural changes during the period suggest that the detected change is mainly caused by anthropogenic influence on climate.


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