Identification and separation of Mount Pinatubo and El Niño‐Southern Oscillation land surface temperature anomalies

Yang, Fanlin; Schlesinger, Michael E.

doi:10.1029/2001jd900146

Cited by 19 publications

(24 citation statements)

References 26 publications

(26 reference statements)

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The Pinatubo experiment indicates that this eruption reduced annual global surface temperature by a maximum of −0.12 • C (Figure 2). This effect is similar to the two year reduction (−0.19 and −0.18 • C) found by Yang and Schlesinger (2001) after they removed the temperature effects of the concurrent El Niño-Southern Oscillation. Both of these effects are slightly smaller than the temperature effects generated by Hansen et al (1992).…”

Section: The Effect Of Exogenous Variablessupporting

confidence: 70%

Emissions, Concentrations, & Temperature: A Time Series Analysis

2006

View full text Add to dashboard Cite

Abstract. We use recent advances in time series econometrics to estimate the relation among emissions of CO 2 and CH 4 , the concentration of these gases, and global surface temperature. These models are estimated and specified to answer two questions; (1) does human activity affect global surface temperature and; (2) does global surface temperature affect the atmospheric concentration of carbon dioxide and/or methane. Regression results provide direct evidence for a statistically meaningful relation between radiative forcing and global surface temperature. A simple model based on these results indicates that greenhouse gases and anthropogenic sulfur emissions are largely responsible for the change in temperature over the last 130 years. The regression results also indicate that increases in surface temperature since 1870 have changed the flow of carbon dioxide to and from the atmosphere in a way that increases its atmospheric concentration. Finally, the regression results for methane hint that higher temperatures may increase its atmospheric concentration, but this effect is not estimated precisely.

show abstract

Section: The Effect Of Exogenous Variablessupporting

confidence: 70%

Emissions, Concentrations, & Temperature: A Time Series Analysis

2006

View full text Add to dashboard Cite

show abstract

“…The global effect was still ϷϪ1 W/m 2 even a year after the event (11,12). As a result, an anomalous cooling of ϷϪ0.5 K was observed (13) in the northern high-latitude growing seasons of 1992-1993. The AVHRR data indicate a large negative anomaly of LAI in the boreal zone during these years.…”

mentioning

confidence: 81%

Climatic Control of the High-Latitude Vegetation Greening Trend and Pinatubo Effect

Lucht

Prentice

Myneni

et al. 2002

Science

682

508

View full text Add to dashboard Cite

A biogeochemical model of vegetation using observed climate data predicts the high northern latitude greening trend over the past two decades observed by satellites and a marked setback in this trend after the Mount Pinatubo volcano eruption in 1991. The observed trend toward earlier spring budburst and increased maximum leaf area is produced by the model as a consequence of biogeochemical vegetation responses mainly to changes in temperature. The post-Pinatubo decline in vegetation in 1992-1993 is apparent as the effect of temporary cooling caused by the eruption. High-latitude CO 2 uptake during these years is predicted as a consequence of the differential response of heterotrophic respiration and net primary production.Satellite observations over the past two decades indicate a trend toward longer growing seasons and greater annual net primary production (NPP) in high latitudes (1-3). Using a dynamic vegetation model that predicts leaf area index (LAI), primary production, and net ecosystem carbon exchange from first principles (4 -7), we show that the trend and variability in the satellite observations are consistent quantitatively with independent climate data and qualitatively with net ecosystem carbon exchange, which was independently calculated from atmospheric CO 2 concentration measurements (8).We analyzed data for a 1982-1998 interval for which we had access to both climate and satellite data. A previous analysis of 10 years of data from the Advanced Very High Resolution Radiometer (AVHRR) indicated a progressive greening of the boreal zone. A steady increase in annual maximum LAI during 1981-1991 was associated with a slight advance of spring budburst and delay of autumn abscission (1). Subsequent work spanning 1981-1999 has confirmed these findings (2, 9), but doubts about the validity of the trend have persisted because of the need for data corrections for instrumental and navigational drift, intercalibration of successive instruments, and consideration of aerosol effects (10). Such doubts could be dispelled if the interannual variations in greenness and growing season length were shown to be quantitatively consistent with independent expectations on the basis of climate variability and/or with independent reconstructions of changes in regional CO 2 balance. This analysis uses a climate-driven terrestrial carbon cycle model capable of simulating the interannual variability of LAI and the components of the terrestrial carbon balance.We compare monthly LAI anomalies for the boreal zone, derived from a recent version of the AVHRR data, with monthly LAI anomalies independently predicted by the LPJ Dynamic Global Vegetation Model (LPJ-DGVM), a biogeochemical process model driven by monthly climate observations and by the global mean CO 2 concentration increase (see Materials and Methods in supporting online material). Both simulated and observed LAI anomalies show an overall increasing trend, but periods lasting several years with positive or negative deviations from the trend can be discerned in the ob...

show abstract

“…The signal of the El Niñ oSouthern Oscillation (ENSO) in global surface temperatures has been estimated using linear regression based on lagged indices of the Southern Oscillation index or equatorial Pacific sea surface temperatures (e.g., Jones 1988;Mass and Portman 1989;Robock and Mao 1995;Kelly and Jones 1996;Wigley 2000;Santer et al 2001;Trenberth et al 2002), maximum covariance analysis between surface temperatures in the tropical Pacific and over the continents (Yang and Schlesinger 2001), complex ''patterns-based filters'' derived from linear inverse models (Penland and Matrosova 2006;Compo and Sardeshmukh 2008, manuscript submitted to J. Climate), and regression analyses with geographically dependent lag (Chen et al 2008).…”

Section: Introductionmentioning

confidence: 99%

Identifying Signatures of Natural Climate Variability in Time Series of Global-Mean Surface Temperature: Methodology and Insights

et al. 2009

View full text Add to dashboard Cite

Global-mean surface temperature is affected by both natural variability and anthropogenic forcing. This study is concerned with identifying and removing from global-mean temperatures the signatures of natural climate variability over the period January 1900-March 2009. A series of simple, physically based methodologies are developed and applied to isolate the climate impacts of three known sources of natural variability: the El Niñ o-Southern Oscillation (ENSO), variations in the advection of marine air masses over the highlatitude continents during winter, and aerosols injected into the stratosphere by explosive volcanic eruptions. After the effects of ENSO and high-latitude temperature advection are removed from the global-mean temperature record, the signatures of volcanic eruptions and changes in instrumentation become more clearly apparent. After the volcanic eruptions are subsequently filtered from the record, the residual time series reveals a nearly monotonic global warming pattern since ;1950. The results also reveal coupling between the land and ocean areas on the interannual time scale that transcends the effects of ENSO and volcanic eruptions. Globally averaged land and ocean temperatures are most strongly correlated when ocean leads land by ;2-3 months. These coupled fluctuations exhibit a complicated spatial signature with largest-amplitude sea surface temperature perturbations over the Atlantic Ocean.

show abstract

Identification and separation of Mount Pinatubo and El Niño‐Southern Oscillation land surface temperature anomalies

Cited by 19 publications

References 26 publications

Emissions, Concentrations, & Temperature: A Time Series Analysis

Emissions, Concentrations, & Temperature: A Time Series Analysis

Climatic Control of the High-Latitude Vegetation Greening Trend and Pinatubo Effect

Identifying Signatures of Natural Climate Variability in Time Series of Global-Mean Surface Temperature: Methodology and Insights

Contact Info

Product

Resources

About