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Bruce T. Anderson
,
Catherine Reifen
, and
Ralf Toumi

Abstract

Projections of human-induced climate change impacts arising from the emission of atmospheric chemical constituents such as carbon dioxide typically utilize multiple integrations (or ensembles) of numerous numerical climate change models to arrive at multimodel ensembles from which mean and median values and probabilities can be inferred about the response of various components of the observed climate system. Some responses are considered reliable in as much as the simulated responses show consistency within ensembles and across models. Other responses—particularly at regional levels and for certain parameters such as precipitation—show little intermodel consistency even in the sign of the projected climate changes. The authors’ results show that in these regions the consistency in the sign of projected precipitation variations is greater for intramodel runs (e.g., runs from the same model) than intermodel runs (e.g., runs from different models), indicating that knowledge of the internal “dynamics” of the climate system can provide additional skill in making projections of climate change. Given the consistency provided by the governing dynamics of the model, the authors test whether persistence from an individual model trajectory serves as a good predictor for its own behavior by the end of the twenty-first century. Results indicate that, in certain regions where intermodel consistency is low, the short-term trends of individual model trajectories do provide additional skill in making projections of long-term climate change. The climate forcing for which this forecast skill becomes relatively large (e.g., correct in 75% of the individual model runs) is equivalent to the anthropogenic climate forcing imposed over the past century, suggesting that observed changes in precipitation in these regions can provide guidance about the direction of future precipitation changes over the course of the next century.

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Bruce T. Anderson
,
Catherine Reifen
, and
Ralf Toumi

Abstract

While most projections of climate change and its regional impacts focus on overall changes in the state of the climate system, useful information can also be found in the evolution of the climate system from one state to another. Here the authors introduce one method for identifying regions in which significant and systematic long-term nonlinear evolutions may be present, even given quasi-linear anthropogenic forcing. Using climate change projections taken from simulations of NCAR’s Community Climate System Model, version 3 (CCSM3), the authors then employ the technique to isolate systematic nonlinear behavior of soil moisture variations over the United States. While the projections presented here only represent the results from one model system, it is argued that such nonlinear behavior is an important characteristic of future climate change that should be considered when discussing both short-term and long-term impacts of anthropogenic climate forcing.

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Weile Wang
,
Bruce T. Anderson
,
Nathan Phillips
,
Robert K. Kaufmann
,
Christopher Potter
, and
Ranga B. Myneni

Abstract

Feedbacks of vegetation on summertime climate variability over the North American Grasslands are analyzed using the statistical technique of Granger causality. Results indicate that normalized difference vegetation index (NDVI) anomalies early in the growing season have a statistically measurable effect on precipitation and surface temperature later in summer. In particular, higher means and/or decreasing trends of NDVI anomalies tend to be followed by lower rainfall but higher temperatures during July through September. These results suggest that initially enhanced vegetation may deplete soil moisture faster than normal and thereby induce drier and warmer climate anomalies via the strong soil moisture–precipitation coupling in these regions. Consistent with this soil moisture–precipitation feedback mechanism, interactions between temperature and precipitation anomalies in this region indicate that moister and cooler conditions are also related to increases in precipitation during the preceding months. Because vegetation responds to soil moisture variations, interactions between vegetation and precipitation generate oscillations in NDVI anomalies at growing season time scales, which are identified in the temporal and the spectral characteristics of the precipitation–NDVI system. Spectral analysis of the precipitation–NDVI system also indicates that 1) long-term interactions (i.e., interannual and longer time scales) between the two anomalies tend to enhance one another, 2) short-term interactions (less than 2 months) tend to damp one another, and 3) intermediary-period interactions (4–8 months) are oscillatory. Together, these results support the hypothesis that vegetation may influence summertime climate variability via the land–atmosphere hydrological cycles over these semiarid grasslands.

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Arindam Samanta
,
Bruce T. Anderson
,
Sangram Ganguly
,
Yuri Knyazikhin
,
Ramakrishna R. Nemani
, and
Ranga B. Myneni

Abstract

Recent research indicates that the warming of the climate system resulting from increased greenhouse gas (GHG) emissions over the next century will persist for many centuries after the cessation of these emissions, principally because of the persistence of elevated atmospheric carbon dioxide (CO2) concentrations and their attendant radiative forcing. However, it is unknown whether the responses of other components of the climate system—including those related to Greenland and Antarctic ice cover, the Atlantic thermohaline circulation, the West African monsoon, and ecosystem and human welfare—would be reversed even if atmospheric CO2 concentrations were to recover to 1990 levels. Here, using a simple set of experiments employing a current-generation numerical climate model, the authors examine the response of the physical climate system to decreasing CO2 concentrations following an initial increase. Results indicate that many characteristics of the climate system, including global temperatures, precipitation, soil moisture, and sea ice, recover as CO2 concentrations decrease. However, other components of the Earth system may still exhibit nonlinear hysteresis. In these experiments, for instance, increases in stratospheric water vapor, which initially result from increased CO2 concentrations, remain present even as CO2 concentrations recover. These results suggest that identification of additional threshold behaviors in response to human-induced global climate change should focus on subcomponents of the full Earth system, including cryosphere, biosphere, and chemistry.

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Weile Wang
,
Bruce T. Anderson
,
Dara Entekhabi
,
Dong Huang
,
Yin Su
,
Robert K. Kaufmann
, and
Ranga B. Myneni

Abstract

This paper uses statistical and analytical techniques to investigate intraseasonal interactions between temperature and vegetation [surrogated by the normalized difference vegetation index (NDVI)] over the boreal forests. Results indicate that interactions between the two fields may be approximated as a coupled second-order system, in which the variability of NDVI and temperature of the current month is significantly regulated by lagged NDVI anomalies from the preceding two months. In particular, the influence from the one-month lagged NDVI anomalies upon both temperature and vegetation variability is generally positive, but the influence from the second-month lagged NDVI anomalies is often negative. Such regulations lead to an intrinsic oscillatory variability of vegetation at growing-season time scales across the study domain. The regulation of temperature variability by NDVI anomalies is most significant over interior Asia (Siberia), suggesting strong vegetation–atmosphere couplings over these regions. Physical mechanisms for these statistical results are investigated further with a stochastic model. The model suggests that the oscillatory variability of the temperature–NDVI system may reflect the dynamic adjustments between the two fields as they maintain a thermal balance within the soil and lower boundary layer of the atmosphere; the particular role vegetation plays in this scenario is mainly to dissipate heat and therefore reduce surface temperatures.

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Weile Wang
,
Bruce T. Anderson
,
Dara Entekhabi
,
Dong Huang
,
Robert K. Kaufmann
,
Christopher Potter
, and
Ranga B. Myneni

Abstract

A coupled linear model is derived to describe interactions between anomalous precipitation and vegetation over the North American Grasslands. The model is based on biohydrological characteristics in the semiarid environment and has components to describe the water-related vegetation variability, the long-term balance of soil moisture, and the local soil–moisture–precipitation feedbacks. Analyses show that the model captures the observed vegetation dynamics and characteristics of precipitation variability during summer over the region of interest. It demonstrates that vegetation has a preferred frequency response to precipitation forcing and has intrinsic oscillatory variability at time scales of about 8 months. When coupled to the atmospheric fields, such vegetation signals tend to enhance the magnitudes of precipitation variability at interannual or longer time scales but damp them at time scales shorter than 4 months; the oscillatory variability of precipitation at the growing season time scale (i.e., the 8-month period) is also enhanced. Similar resonance and oscillation characteristics are identified in the power spectra of observed precipitation datasets. The model results are also verified using Monte Carlo experiments.

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