Faculty Opinions recommendation of Separating the influence of temperature, drought, and fire on interannual variability in atmospheric CO2.

2015 ◽  
Author(s):  
Richard Houghton
Keyword(s):  
Interannual Variability ◽  
Atmospheric Co2 ◽  
Influence Of Temperature

Interannual variability of atmospheric CO2 in the Mediterranean: measurements at the island of Lampedusa

Tellus B ◽  
2003 ◽  
Vol 55 (2) ◽  
pp. 83-93 ◽  
Author(s):  
P. CHAMARD ◽  
F. THIERY ◽  
A. DI SARRA ◽  
L. CIATTAGLIA ◽  
L. DE SILVESTRI ◽  
...  
Keyword(s):  
Interannual Variability ◽  
Atmospheric Co2 ◽  
The Mediterranean

scholarly journals Climatic controls on interannual variability of precipitation δ18O: Simulated influence of temperature, precipitation amount, and vapor source region

1999 ◽  
Vol 104 (D12) ◽  
pp. 14223-14235 ◽  
Author(s):  
Julia E. Cole ◽  
David Rind ◽  
Robert S. Webb ◽  
Jean Jouzel ◽  
Richard Healy
Keyword(s):  
Interannual Variability ◽  
Source Region ◽  
Precipitation Amount ◽  
Vapor Source ◽  
Influence Of Temperature ◽  
Precipitation Δ18o

scholarly journals A worldwide analysis of trends in water-balance evapotranspiration

2013 ◽  
Vol 10 (5) ◽  
pp. 5739-5765 ◽  
Author(s):  
A. M. Ukkola ◽  
I. C. Prentice
Keyword(s):  
Water Balance ◽  
Interannual Variability ◽  
Land Surface ◽  
Time Series Data ◽  
Hydrological Cycle ◽  
Atmospheric Co2 ◽  
Series Data ◽  
Additional Control ◽  
Terrestrial Water ◽  
Strong Control

Abstract. Climate change is expected to alter the global hydrological cycle, with inevitable consequences for freshwater availability to people and ecosystems. But the attribution of recent trends in the terrestrial water balance remains disputed. This study attempts to account statistically for both trends and interannual variability in water-balance evapotranspiration (ET), estimated from the annual observed streamflow in 109 river basins during "water years" 1961–1999 and two gridded precipitation datasets. The basins were chosen based on the availability of streamflow time-series data in the Dai et al. (2009) synthesis. They were divided into water-limited "dry" and energy-limited "wet" basins following the Budyko framework. We investigated the potential roles of precipitation, aerosol-corrected solar radiation, land-use change, wind speed, air temperature, and atmospheric CO2. Both trends and variability in ET show strong control by precipitation. There is some additional control of ET trends by vegetation processes, but little evidence for control by other factors. Interannual variability in ET was overwhelmingly dominated by precipitation, which accounted on average for 52–54% of the variation in wet basins (ranging from 0 to 99%) and 84–85% in dry basins (ranging from 13 to 100%). Precipitation accounted for 39–42% of ET trends in wet basins and 69–79% in dry basins. Cropland expansion increased ET in dry basins. Net atmospheric CO2 effects on transpiration, estimated using the Land-surface Processes and eXchanges (LPX) model, did not contribute to observed trends in ET because declining stomatal conductance was counteracted by slightly but significantly increasing foliage cover.

scholarly journals Contrasting behaviors of the atmospheric CO<sub>2</sub> interannual variability during two types of El Niños

2018 ◽  
Author(s):  
Jun Wang ◽  
Ning Zeng ◽  
Meirong Wang ◽  
Fei Jiang ◽  
Jingming Chen ◽  
...  
Keyword(s):  
Interannual Variability ◽  
El Niño ◽  
El Nino ◽  
Ecosystem Respiration ◽  
Atmospheric Co2 ◽  
Occurrence Rate ◽  
Central Pacific ◽  
Cp El Niño ◽  
El Niño Events ◽  
El Nino Events

Abstract. El Niño has two different flavors: eastern Pacific (EP) and central Pacific (CP) El Niños, with different global teleconnections. However, their different impacts on carbon cycle interannual variability remain unclear. We here compared the behaviors of the atmospheric CO2 interannual variability and analyzed their terrestrial mechanisms during these two types of El Niños, based on Mauna Loa (MLO) CO2 growth rate (CGR) and Dynamic Global Vegetation Models (DGVMs) historical simulations. Composite analysis shows that evolutions of MLO CGR anomaly have three clear differences in terms of (1) negative and neutral precursors in boreal spring of El Niño developing years (denoted as “yr0”), (2) strong and weak amplitudes, and (3) durations of peak from December (yr0) to April of El Niño decaying year (denoted as “yr1”) and from October (yr0) to January (yr1) during EP and CP El Niños, respectively. Models simulated global land–atmosphere carbon flux (FTA) is able to capture the essentials of these characteristics. We further find that the gross primary productivity (GPP) over the tropics and extratropical southern hemisphere (Trop+SH) generally dominates the global FTA variations during both El Niño types. Regionally, significant anomalous carbon uptake caused by more precipitation and colder temperature, corresponding to the negative precursor, occurs between 30° S and 20° N from January (yr0) to June (yr0), while the strongest anomalous carbon releases, due largely to the reduced GPP induced by low precipitation and warm temperature, happen between equator and 20° N from February (yr1) to August (yr1) during EP El Niño events. In contrast, during CP El Niño events, clear carbon releases exist between 10° N and 20° S from September (yr0) to September (yr1), resulted from the widespread dry and warm climate conditions. Different spatial patterns of land temperature and precipitation in different seasons associated with EP and CP El Niños account for the characteristics in evolutions of GPP, terrestrial ecosystem respiration (TER), and resultant FTA. Understanding these different behaviors of the atmospheric CO2 interannual variability along with their terrestrial mechanisms during EP and CP El Niños is important because CP El Niño occurrence rate might increase under global warming.

scholarly journals Timing of cod reproduction: interannual variability and the influence of temperature

1994 ◽  
Vol 108 ◽  
pp. 21-31 ◽  
Author(s):  
JA Hutchings ◽  
RA Myers
Keyword(s):  
Interannual Variability ◽  
Influence Of Temperature

scholarly journals Sea–air CO<sub>2</sub> fluxes in the Indian Ocean between 1990 and 2009

2013 ◽  
Vol 10 (11) ◽  
pp. 7035-7052 ◽  
Author(s):  
V. V. S. S. Sarma ◽  
A. Lenton ◽  
R. M. Law ◽  
N. Metzl ◽  
P. K. Patra ◽  
...  
Keyword(s):  
Indian Ocean ◽  
Carbon Cycle ◽  
Interannual Variability ◽  
Southern Annular Mode ◽  
Atmospheric Co2 ◽  
Co2 Uptake ◽  
Co2 Fluxes ◽  
Biogeochemical Models ◽  
The Indian Ocean ◽  
Atmospheric Inversions

Abstract. The Indian Ocean (44° S–30° N) plays an important role in the global carbon cycle, yet it remains one of the most poorly sampled ocean regions. Several approaches have been used to estimate net sea–air CO2 fluxes in this region: interpolated observations, ocean biogeochemical models, atmospheric and ocean inversions. As part of the RECCAP (REgional Carbon Cycle Assessment and Processes) project, we combine these different approaches to quantify and assess the magnitude and variability in Indian Ocean sea–air CO2 fluxes between 1990 and 2009. Using all of the models and inversions, the median annual mean sea–air CO2 uptake of −0.37 ± 0.06 PgC yr−1 is consistent with the −0.24 ± 0.12 PgC yr−1 calculated from observations. The fluxes from the southern Indian Ocean (18–44° S; −0.43 ± 0.07 PgC yr−1 are similar in magnitude to the annual uptake for the entire Indian Ocean. All models capture the observed pattern of fluxes in the Indian Ocean with the following exceptions: underestimation of upwelling fluxes in the northwestern region (off Oman and Somalia), overestimation in the northeastern region (Bay of Bengal) and underestimation of the CO2 sink in the subtropical convergence zone. These differences were mainly driven by lack of atmospheric CO2 data in atmospheric inversions, and poor simulation of monsoonal currents and freshwater discharge in ocean biogeochemical models. Overall, the models and inversions do capture the phase of the observed seasonality for the entire Indian Ocean but overestimate the magnitude. The predicted sea–air CO2 fluxes by ocean biogeochemical models (OBGMs) respond to seasonal variability with strong phase lags with reference to climatological CO2 flux, whereas the atmospheric inversions predicted an order of magnitude higher seasonal flux than OBGMs. The simulated interannual variability by the OBGMs is weaker than that found by atmospheric inversions. Prediction of such weak interannual variability in CO2 fluxes by atmospheric inversions was mainly caused by a lack of atmospheric data in the Indian Ocean. The OBGM models suggest a small strengthening of the sink over the period 1990–2009 of −0.01 PgC decade−1. This is inconsistent with the observations in the southwestern Indian Ocean that shows the growth rate of oceanic pCO2 was faster than the observed atmospheric CO2 growth, a finding attributed to the trend of the Southern Annular Mode (SAM) during the 1990s.

scholarly journals Anthropogenic and biophysical contributions to increasing atmospheric CO<sub>2</sub> growth rate and airborne fraction

2008 ◽  
Vol 5 (4) ◽  
pp. 2867-2896 ◽  
Author(s):  
M. R. Raupach ◽  
J. G. Canadell ◽  
C. Le Quéré
Keyword(s):  
Growth Rate ◽  
Interannual Variability ◽  
Capita Income ◽  
Southern Oscillation ◽  
Atmospheric Co2 ◽  
Total Carbon ◽  
Carbon Intensity ◽  
Positive Trend ◽  
Per Capita Income ◽  
Per Capita

Abstract. We quantify the relative roles of natural and anthropogenic influences on the growth rate of atmospheric CO2 and the CO2 airborne fraction, considering both interdecadal trends and interannual variability. A combined ENSO-Volcanic Index (EVI) relates most (~75%) of the interannual variability in CO2 growth rate to the El-Niño-Southern-Oscillation (ENSO) climate mode and volcanic activity. Analysis of several CO2 data sets with removal of the EVI-correlated component confirms a previous finding of a detectable increasing trend in CO2 airborne fraction (defined using total anthropogenic emissions including fossil fuels and land use change) over the period 1959–2006, at a proportional growth rate 0.24% y−1 with probability ~0.9 of a positive trend. This implies that the atmospheric CO2 growth rate increased slightly faster than total anthropogenic CO2 emissions. An extended form of the Kaya identity relates the increase in the CO2 growth rate (1.9% y−1 over 1959–2006) to the growth rates of four global driving factors: population (contributing +1.7% y−1); per capita income (+1.8% y−1); the total carbon intensity of the global economy (−1.7% y−1); and airborne fraction (averaging +0.2% y−1 with strong interannual variability). Together, the recent (post-2000) increase in growth of per capita income and decline in the negative growth (improvement) in the carbon intensity of the economy will drive a significant acceleration in the CO2 growth rate over coming decades, unless these recent trends reverse. To achieve an annual reduction rate in total emissions of −2% y−1 (which would halve emissions in 35 years) in the presence of a per-capita income growth rate of 2% y−1 and a population growth rate of 1% y−1, it is necessary to achieve a decline in total carbon intensity of the economy at a rate of around −5% y−1, three times the 1959–2006 average.

Direct and indirect controls of the interannual variability in atmospheric CO2 exchange of three contrasting ecosystems in Denmark

2017 ◽  
Vol 233 ◽  
pp. 12-31 ◽  
Author(s):  
Rasmus Jensen ◽  
Mathias Herbst ◽  
Thomas Friborg
Keyword(s):  
Interannual Variability ◽  
Co2 Exchange ◽  
Atmospheric Co2

scholarly journals Technical Note: The Simple Diagnostic Photosynthesis and Respiration Model (SDPRM)

2013 ◽  
Vol 10 (10) ◽  
pp. 6485-6508 ◽  
Author(s):  
B. Badawy ◽  
C. Rödenbeck ◽  
M. Reichstein ◽  
N. Carvalhais ◽  
M. Heimann
Keyword(s):  
Interannual Variability ◽  
Ecosystem Respiration ◽  
Spatial Scales ◽  
Gross Primary Production ◽  
Technical Note ◽  
Atmospheric Co2 ◽  
Limiting Factor ◽  
Respiration Model ◽  
Photosynthesis And Respiration ◽  
Process Based Models

Abstract. We present a Simple Diagnostic Photosynthesis and Respiration Model (SDPRM) that has been developed based on pre-existing formulations. The photosynthesis model is based on the light use efficiency logic for calculating the gross primary production (GPP), while the ecosystem respiration (Reco) is a modified version of an Arrhenius-type equation. SDPRM is driven by satellite-derived fAPAR (fraction of Absorbed Photosynthetically Active Radiation) and climate data from the National Center for Environmental Prediction/National Center for Atmospheric Research Reanalysis (NCEP/NCAR). The model estimates 3-hourly values of GPP for seven major biomes and daily Reco. The motivation is to provide a priori fields of surface CO2 fluxes with fine temporal and spatial scales for atmospheric CO2 inversions. The estimated fluxes from SDPRM showed that the model is capable of producing flux estimates consistent with the ones inferred from atmospheric CO2 inversion or simulated from process-based models. In this Technical Note, different analyses were carried out to test the sensitivity of the estimated fluxes of GPP and CO2 to their driving forces. The spatial patterns of the climatic controls (temperature, precipitation, water) on the interannual variability of GPP are consistent with previous studies, even though SDPRM has a very simple structure and few adjustable parameters and hence it is much easier to modify in an inversion than more sophisticated process-based models. In SDPRM, temperature is a limiting factor for the interannual variability of Reco over cold boreal forest, while precipitation is the main limiting factor of Reco over the tropics and the southern hemisphere, consistent with previous regional studies.

Sign in / Sign up

Export Citation Format

Share Document