scholarly journals TIME SERIES FLUCTUATION CHARACTERISTICS OF THE ATMOSPHERIC CO2 CONCENTRATION BASED ON COVARIANCE STRUCTURE ANALYSIS

2006 ◽  
Vol 50 ◽  
pp. 457-462
Author(s):  
Ayano TOMINAGA ◽  
Tamotsu SHIMIZU ◽  
Masahiko HASEBE ◽  
Yoshiharu SUZUKI
Keyword(s):  
Time Series ◽  
Structure Analysis ◽  
Covariance Structure ◽  
Co2 Concentration ◽  
Atmospheric Co2 ◽  
Covariance Structure Analysis ◽  
Atmospheric Co2 Concentration

scholarly journals Using OCO-2 Satellite Data for Investigating the Variability of Atmospheric CO2 Concentration in Relationship with Precipitation, Relative Humidity, and Vegetation over Oman

Water ◽  
2019 ◽  
Vol 12 (1) ◽  
pp. 101
Author(s):  
Foroogh Golkar ◽  
Malik Al-Wardy ◽  
Seyedeh Fatemeh Saffari ◽  
Kathiya Al-Aufi ◽  
Ghazi Al-Rawas
Keyword(s):  
Time Series ◽  
Relative Humidity ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Co2 Concentration ◽  
Atmospheric Co2 ◽  
Monsoon Region ◽  
Annual Cycles ◽  
Atmospheric Co2 Concentration ◽  
Carbon Dioxide Co2

Recognition of the carbon dioxide (CO2) concentration variations over time is critical for tracing the future changes in climate both globally and regionally. In this study, a time series analysis of atmospheric CO2 concentration and its relationship with precipitation, relative humidity (RH), and vegetation is investigated over Oman. The daily XCO2 data from OCO-2 satellite was obtained from September 2014 to March 2019. The daily RH and precipitation data were also collected from the ground weather stations, and the Normalized Difference Vegetation Index was obtained from MODIS. Oman was studied in four distinct regions where the main emphasis was on the Monsoon Region in the far south. The CO2 concentration time series indicated a significant upward trend over different regions for the study period, with annual cycles being the same for all regions except the Monsoon Region. This is indicative of RH, precipitation, and consequently vegetation cover impact on atmospheric CO2 concentration, resulting in an overall lower annual growth in the Monsoon Region. Simple and multiple correlation analyses of CO2 concentration with mentioned parameters were performed in zero to three-month lags over Oman. They showed high correlations mainly during the rainfall period in the Monsoon Region.

scholarly journals Response of simulated burned area to historical changes in environmental and anthropogenic factors: a comparison of seven fire models

2019 ◽  
Vol 16 (19) ◽  
pp. 3883-3910 ◽  
Author(s):  
Lina Teckentrup ◽  
Sandy P. Harrison ◽  
Stijn Hantson ◽  
Angelika Heil ◽  
Joe R. Melton ◽  
...  
Keyword(s):  
Land Use ◽  
Co2 Concentration ◽  
Fire Regimes ◽  
Atmospheric Co2 ◽  
Anthropogenic Factors ◽  
Burned Area ◽  
Earth System ◽  
Atmospheric Co2 Concentration ◽  
Fire Models ◽  
The Impact

Abstract. Understanding how fire regimes change over time is of major importance for understanding their future impact on the Earth system, including society. Large differences in simulated burned area between fire models show that there is substantial uncertainty associated with modelling global change impacts on fire regimes. We draw here on sensitivity simulations made by seven global dynamic vegetation models participating in the Fire Model Intercomparison Project (FireMIP) to understand how differences in models translate into differences in fire regime projections. The sensitivity experiments isolate the impact of the individual drivers on simulated burned area, which are prescribed in the simulations. Specifically these drivers are atmospheric CO2 concentration, population density, land-use change, lightning and climate. The seven models capture spatial patterns in burned area. However, they show considerable differences in the burned area trends since 1921. We analyse the trajectories of differences between the sensitivity and reference simulation to improve our understanding of what drives the global trends in burned area. Where it is possible, we link the inter-model differences to model assumptions. Overall, these analyses reveal that the largest uncertainties in simulating global historical burned area are related to the representation of anthropogenic ignitions and suppression and effects of land use on vegetation and fire. In line with previous studies this highlights the need to improve our understanding and model representation of the relationship between human activities and fire to improve our abilities to model fire within Earth system model applications. Only two models show a strong response to atmospheric CO2 concentration. The effects of changes in atmospheric CO2 concentration on fire are complex and quantitative information of how fuel loads and how flammability changes due to this factor is missing. The response to lightning on global scale is low. The response of burned area to climate is spatially heterogeneous and has a strong inter-annual variation. Climate is therefore likely more important than the other factors for short-term variations and extremes in burned area. This study provides a basis to understand the uncertainties in global fire modelling. Both improvements in process understanding and observational constraints reduce uncertainties in modelling burned area trends.

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