Time scale bias in erosion rates of glaciated landscapes

PubMed Central

Ganti, Vamsi; von Hagke, Christoph; Scherler, Dirk; Lamb, Michael P.; Fischer, Woodward W.; Avouac, Jean-Philippe

2016-01-01

Deciphering erosion rates over geologic time is fundamental for understanding the interplay between climate, tectonic, and erosional processes. Existing techniques integrate erosion over different time scales, and direct comparison of such rates is routinely done in earth science. On the basis of a global compilation, we show that erosion rate estimates in glaciated landscapes may be affected by a systematic averaging bias that produces higher estimated erosion rates toward the present, which do not reflect straightforward changes in erosion rates through time. This trend can result from a heavy-tailed distribution of erosional hiatuses (that is, time periods where no or relatively slow erosion occurs). We argue that such a distribution can result from the intermittency of erosional processes in glaciated landscapes that are tightly coupled to climate variability from decadal to millennial time scales. In contrast, we find no evidence for a time scale bias in spatially averaged erosion rates of landscapes dominated by river incision. We discuss the implications of our findings in the context of the proposed coupling between climate and tectonics, and interpreting erosion rate estimates with different averaging time scales through geologic time. PMID:27713925

Time scale bias in erosion rates of glaciated landscapes.

PubMed

Ganti, Vamsi; von Hagke, Christoph; Scherler, Dirk; Lamb, Michael P; Fischer, Woodward W; Avouac, Jean-Philippe

2016-10-01

Deciphering erosion rates over geologic time is fundamental for understanding the interplay between climate, tectonic, and erosional processes. Existing techniques integrate erosion over different time scales, and direct comparison of such rates is routinely done in earth science. On the basis of a global compilation, we show that erosion rate estimates in glaciated landscapes may be affected by a systematic averaging bias that produces higher estimated erosion rates toward the present, which do not reflect straightforward changes in erosion rates through time. This trend can result from a heavy-tailed distribution of erosional hiatuses (that is, time periods where no or relatively slow erosion occurs). We argue that such a distribution can result from the intermittency of erosional processes in glaciated landscapes that are tightly coupled to climate variability from decadal to millennial time scales. In contrast, we find no evidence for a time scale bias in spatially averaged erosion rates of landscapes dominated by river incision. We discuss the implications of our findings in the context of the proposed coupling between climate and tectonics, and interpreting erosion rate estimates with different averaging time scales through geologic time.

Paleoclimate

USGS Publications Warehouse

Bartlein, Patrick J.; Hostetler, Steven W.; Alder, Jay R.; Ohring, G.

2014-01-01

As host to one of the major continental-scale ice sheets, and with considerable spatial variability of climate related to its physiography and location, North America has experienced a wide range of climates over time. The aim of this chapter is to review the history of those climate variations, focusing in particular on the continental-scale climatic variations between the Last Glacial Maximum (LGM, ca. 21,000 years ago or 21 ka) and the present, which were as large in amplitude as any experienced over a similar time span during the past several million years. As background to that discussion, the climatic variations over the Cenozoic (the past 65.5 Myr, or 65.5 Ma to present) that led ultimately to the onset of Northern Hemisphere glaciation at 2.59 Ma will also be discussed. Superimposed on the large-amplitude, broad-scale variations from the LGM to present, are climatic variations on millennial-to-decadal scales, and these will be reviewed in particular for the Holocene (11.7 ka to present) and the past millennium.

The weather and Climate: emergent laws and multifractal cascades

NASA Astrophysics Data System (ADS)

Lovejoy, S.

2016-12-01

In the atmosphere, nonlinear terms are typically about a trillion times larger than linear ones; we anticipate the emergence of high level turbulence laws. The classical turbulence laws were restricted to homogeneous and isotropic systems; to apply them to the atmosphere they must be generalized to account for strong anisotropy (especially stratification) and variability (intermittency). Over the last 30 years, using scaling symmetry principles and multifractal cascades, this has been done. While hitherto they were believed applicable only up to ≈ 100 m, (generalized) turbulence laws now anisotropic and multifractal, they cover spatial scales up planetary in extent and in time well beyond weather scales to include the climate. These higher level laws are stochastic in nature and provide the theoretical basis both for stochastic parametrizations as well as stochastic forecasting. In the time domain the emergent laws for fluctuations DT (for example in temperature T) have means T > ≈ DtH i.e. they are scaling (power laws) in the time interval Dt. We find find exponents H>0 (fluctuations increase with scale) up to ≈ Dt ≈10 days (the lifetime of planetary scale structures, the analogous transition in the ocean is at Dt ≈ 1 year on Mars it is Dt ≈ 2 sols). At larger Dt, there is a transition to a new "macroweather" regime with H<0: successive fluctuations tend cancel each; at Dt >≈30 years (anthropocene; larger in the pre-industrial epoch), new climate processes begin to dominate, leading to H>0. "The climate is what you expect, the weather is what you get": the climate is thought to be a kind of "average weather". However this "expected" behavior is macroweather, not the climate. On the contrary, the climate is the new even lower frequency regime at scales Dt> 30 yrs and it has statistical properties very similar to the weather. At these scales, "macroweather is what you expect, the climate is what you get". The scaling in the macroweather regime implies that there is a long-term memory. We show how the memory can be exploited for more accurate monthly, seasonal, interannual and decadal forecasts. For a review, see Lovejoy, S., D. Schertzer, 2013: The weather and Climate: emergent laws and multifractal cascades, 496pp, Cambridge U. Press.

Evaluating the uncertainty of predicting future climate time series at the hourly time scale

NASA Astrophysics Data System (ADS)

Caporali, E.; Fatichi, S.; Ivanov, V. Y.

2011-12-01

A stochastic downscaling methodology is developed to generate hourly, point-scale time series for several meteorological variables, such as precipitation, cloud cover, shortwave radiation, air temperature, relative humidity, wind speed, and atmospheric pressure. The methodology uses multi-model General Circulation Model (GCM) realizations and an hourly weather generator, AWE-GEN. Probabilistic descriptions of factors of change (a measure of climate change with respect to historic conditions) are computed for several climate statistics and different aggregation times using a Bayesian approach that weights the individual GCM contributions. The Monte Carlo method is applied to sample the factors of change from their respective distributions thereby permitting the generation of time series in an ensemble fashion, which reflects the uncertainty of climate projections of future as well as the uncertainty of the downscaling procedure. Applications of the methodology and probabilistic expressions of certainty in reproducing future climates for the periods, 2000 - 2009, 2046 - 2065 and 2081 - 2100, using the 1962 - 1992 period as the baseline, are discussed for the location of Firenze (Italy). The climate predictions for the period of 2000 - 2009 are tested against observations permitting to assess the reliability and uncertainties of the methodology in reproducing statistics of meteorological variables at different time scales.

Mountain Plant Community Sentinels: AWOL

NASA Astrophysics Data System (ADS)

Malanson, G. P.

2017-12-01

Mountain plant communities are thought to be sensitive to climate change. Because climatic gradients are steep on mountain slopes, the spatial response of plant communities to climate change should be compressed and easier to detect. These expectations have led to identifying mountain plant communities as sentinels for climate change. This idea has, however, been criticized. Two critiques, for alpine treeline and alpine tundra, are rehearsed and supplemented. The critique of alpine treeline as sentinel is bolstered with new model results on the confounding role of dispersal mechanisms and sensitivity to climatic volatility. In alpine tundra, for which background turnover rates have yet to be established, community composition may reflect environmental gradients only for extremes where effects of climate are most indirect. Both plant communities, while primarily determined by energy at broad scales, may respond to water as a proximate driver at local scales. These plant communities may not be in equilibrium with climate, and differently scaled time lags may mean that ongoing vegetation change may not signal ongoing climate change (or lack thereof). In both cases a double-whammy is created by scale dependence for time lags and for drivers leading to confusion, but these cases present opportunities for insights into basic ecology.

Greenhouse gas scenario sensitivity and uncertainties in precipitation projections for central Belgium

NASA Astrophysics Data System (ADS)

Van Uytven, E.; Willems, P.

2018-03-01

Climate change impact assessment on meteorological variables involves large uncertainties as a result of incomplete knowledge on the future greenhouse gas concentrations and climate model physics, next to the inherent internal variability of the climate system. Given that the alteration in greenhouse gas concentrations is the driver for the change, one expects the impacts to be highly dependent on the considered greenhouse gas scenario (GHS). In this study, we denote this behavior as GHS sensitivity. Due to the climate model related uncertainties, this sensitivity is, at local scale, not always that strong as expected. This paper aims to study the GHS sensitivity and its contributing role to climate scenarios for a case study in Belgium. An ensemble of 160 CMIP5 climate model runs is considered and climate change signals are studied for precipitation accumulation, daily precipitation intensities and wet day frequencies. This was done for the different seasons of the year and the scenario periods 2011-2040, 2031-2060, 2051-2081 and 2071-2100. By means of variance decomposition, the total variance in the climate change signals was separated in the contribution of the differences in GHSs and the other model-related uncertainty sources. These contributions were found dependent on the variable and season. Following the time of emergence concept, the GHS uncertainty contribution is found dependent on the time horizon and increases over time. For the most distinct time horizon (2071-2100), the climate model uncertainty accounts for the largest uncertainty contribution. The GHS differences explain up to 18% of the total variance in the climate change signals. The results point further at the importance of the climate model ensemble design, specifically the ensemble size and the combination of climate models, whereupon climate scenarios are based. The numerical noise, introduced at scales smaller than the skillful scale, e.g. at local scale, was not considered in this study.

Fractionaly Integrated Flux model and Scaling Laws in Weather and Climate

NASA Astrophysics Data System (ADS)

Schertzer, Daniel; Lovejoy, Shaun

2013-04-01

The Fractionaly Integrated Flux model (FIF) has been extensively used to model intermittent observables, like the velocity field, by defining them with the help of a fractional integration of a conservative (i.e. strictly scale invariant) flux, such as the turbulent energy flux. It indeed corresponds to a well-defined modelling that yields the observed scaling laws. Generalised Scale Invariance (GSI) enables FIF to deal with anisotropic fractional integrations and has been rather successful to define and model a unique regime of scaling anisotropic turbulence up to planetary scales. This turbulence has an effective dimension of 23/9=2.55... instead of the classical hypothesised 2D and 3D turbulent regimes, respectively for large and small spatial scales. It therefore theoretically eliminates a non plausible "dimension transition" between these two regimes and the resulting requirement of a turbulent energy "mesoscale gap", whose empirical evidence has been brought more and more into question. More recently, GSI-FIF was used to analyse climate, therefore at much larger time scales. Indeed, the 23/9-dimensional regime necessarily breaks up at the outer spatial scales. The corresponding transition range, which can be called "macroweather", seems to have many interesting properties, e.g. it rather corresponds to a fractional differentiation in time with a roughly flat frequency spectrum. Furthermore, this transition yields the possibility to have at much larger time scales scaling space-time climate fluctuations with a much stronger scaling anisotropy between time and space. Lovejoy, S. and D. Schertzer (2013). The Weather and Climate: Emergent Laws and Multifractal Cascades. Cambridge Press (in press). Schertzer, D. et al. (1997). Fractals 5(3): 427-471. Schertzer, D. and S. Lovejoy (2011). International Journal of Bifurcation and Chaos 21(12): 3417-3456.

Range-wide reproductive consequences of ocean climate variability for the seabird Cassin's Auklet.

PubMed

Wolf, Shaye G; Sydeman, William J; Hipfner, J Mark; Abraham, Christine L; Tershy, Bernie R; Croll, Donald A

2009-03-01

We examine how ocean climate variability influences the reproductive phenology and demography of the seabird Cassin's Auklet (Ptychoramphus aleuticus) across approximately 2500 km of its breeding range in the oceanographically dynamic California Current System along the west coast of North America. Specifically, we determine the extent to which ocean climate conditions and Cassin's Auklet timing of breeding and breeding success covary across populations in British Columbia, central California, and northern Mexico over six years (2000-2005) and test whether auklet timing of breeding and breeding success are similarly related to local and large-scale ocean climate indices across populations. Local ocean foraging environments ranged from seasonally variable, high-productivity environments in the north to aseasonal, low-productivity environments to the south, but covaried similarly due to the synchronizing effects of large-scale climate processes. Auklet timing of breeding in the southern population did not covary with populations to the north and was not significantly related to local oceanographic conditions, in contrast to northern populations, where timing of breeding appears to be influenced by oceanographic cues that signal peaks in prey availability. Annual breeding success covaried similarly across populations and was consistently related to local ocean climate conditions across this system. Overall, local ocean climate indices, particularly sea surface height, better explained timing of breeding and breeding success than a large-scale climate index by better representing heterogeneity in physical processes important to auklets and their prey. The significant, consistent relationships we detected between Cassin's Auklet breeding success and ocean climate conditions across widely spaced populations indicate that Cassin's Auklets are susceptible to climate change across the California Current System, especially by the strengthening of climate processes that synchronize oceanographic conditions. Auklet populations in the northern and central regions of this ecosystem may be more sensitive to changes in the timing and variability of ocean climate conditions since they appear to time breeding to take advantage of seasonal productivity peaks.

Millennial-scale climate variations recorded in Early Pliocene colour reflectance time series from the lacustrine Ptolemais Basin (NW Greece)

NASA Astrophysics Data System (ADS)

Steenbrink, J.; Kloosterboer-van Hoeve, M. L.; Hilgen, F. J.

2003-03-01

Quaternary climate proxy records show compelling evidence for climate variability on time scales of a few thousand years. The causes for these millennial-scale or sub-Milankovitch cycles are still poorly understood, not least due to the complex feedback mechanisms of large ice sheets during the Quaternary. We present evidence of millennial-scale climate variability in Early Pliocene lacustrine sediments from the intramontane Ptolemais Basin in northwestern Greece. The sediments are well exposed in a series of open-pit lignite mines and exhibit a distinct millennial-scale sedimentary cyclicity of alternating lignites and lacustrine marl beds that resulted from precession-induced variations in climate. The higher-frequency, millennial-scale cyclicity is particularly prominent within the grey-coloured marl segment of individual cycles. A stratigraphic interval of ˜115 ka, covering five precession-induced sedimentary cycles, was studied in nine parallel sections from two open-pit lignite mines located several km apart. High-resolution colour reflectance records were used to quantify the within-cycle variability and to determine its lateral continuity. Much of the within-cycle variability could be correlated between the parallel sections, even in fine detail, which suggests that these changes reflect basin-wide variations in environmental conditions related to (regional) climate fluctuations. Interbedded volcanic ash beds demonstrate the synchronicity of these fluctuations and spectral analysis of the reflectance time series shows a significant concentration of within-cycle variability at periods of ˜11, ˜5.5 and ˜2 ka. The occurrence of variability at such time scales at times before the intensification of the Northern Hemisphere glaciation suggests that they cannot solely have resulted from internal ice-sheet dynamics. Possible candidates include harmonics or combination tones of the main orbital cycles, variations in solar output or periodic motions of the Earth and Moon.

Validation of the group nuclear safety climate questionnaire.

PubMed

Navarro, M Felisa Latorre; Gracia Lerín, Francisco J; Tomás, Inés; Peiró Silla, José María

2013-09-01

Group safety climate is a leading indicator of safety performance in high reliability organizations. Zohar and Luria (2005) developed a Group Safety Climate scale (ZGSC) and found it to have a single factor. The ZGSC scale was used as a basis in this study with the researchers rewording almost half of the items on this scale, changing the referents from the leader to the group, and trying to validate a two-factor scale. The sample was composed of 566 employees in 50 groups from a Spanish nuclear power plant. Item analysis, reliability, correlations, aggregation indexes and CFA were performed. Results revealed that the construct was shared by each unit, and our reworded Group Safety Climate (GSC) scale showed a one-factor structure and correlated to organizational safety climate, formalized procedures, safety behavior, and time pressure. This validation of the one-factor structure of the Zohar and Luria (2005) scale could strengthen and spread this scale and measure group safety climate more effectively. Copyright © 2013 National Safety Council and Elsevier Ltd. All rights reserved.

Paleoecology and high-resolution paleohydrology of a kettle peatland in upper Michigan

NASA Astrophysics Data System (ADS)

Booth, Robert K.; Jackson, Stephen T.; Gray, Catherine E. D.

2004-01-01

We investigated the developmental and hydrological history of a Sphagnum-dominated, kettle peatland in Upper Michigan using testate amoebae, plant macrofossils, and pollen. Our primary objective was to determine if the paleohydrological record of the peatland represents a record of past climate variability at subcentennial to millennial time scales. To assess the role of millennial-scale climate variability on peatland paleohydrology, we compared the timing of peatland and upland vegetation changes. To investigate the role of higher-frequency climate variability on peatland paleohydrology, we used testate amoebae to reconstruct a high-resolution, hydrologic history of the peatland for the past 5100 years, and compared this record to other regional records of paleoclimate and vegetation. Comparisons revealed coherent patterns of hydrological, vegetational, and climatic changes, suggesting that peatland paleohydrology responded to climate variability at millennial to sub-centennial time scales. Although ombrotrophic peatlands have been the focus of most high-resolution peatland paleoclimate research, paleohydrological records from Sphagnum-dominated, closed-basin peatlands record high-frequency and low-magnitude climatic changes and thus represent a significant source of unexplored paleoclimate data.

Web based visualization of large climate data sets

USGS Publications Warehouse

Alder, Jay R.; Hostetler, Steven W.

2015-01-01

We have implemented the USGS National Climate Change Viewer (NCCV), which is an easy-to-use web application that displays future projections from global climate models over the United States at the state, county and watershed scales. We incorporate the NASA NEX-DCP30 statistically downscaled temperature and precipitation for 30 global climate models being used in the Fifth Assessment Report (AR5) of the Intergovernmental Panel on Climate Change (IPCC), and hydrologic variables we simulated using a simple water-balance model. Our application summarizes very large, complex data sets at scales relevant to resource managers and citizens and makes climate-change projection information accessible to users of varying skill levels. Tens of terabytes of high-resolution climate and water-balance data are distilled to compact binary format summary files that are used in the application. To alleviate slow response times under high loads, we developed a map caching technique that reduces the time it takes to generate maps by several orders of magnitude. The reduced access time scales to >500 concurrent users. We provide code examples that demonstrate key aspects of data processing, data exporting/importing and the caching technique used in the NCCV.

Climate and wildfires in the North American boreal forest.

PubMed

Macias Fauria, Marc; Johnson, E A

2008-07-12

The area burned in the North American boreal forest is controlled by the frequency of mid-tropospheric blocking highs that cause rapid fuel drying. Climate controls the area burned through changing the dynamics of large-scale teleconnection patterns (Pacific Decadal Oscillation/El Niño Southern Oscillation and Arctic Oscillation, PDO/ENSO and AO) that control the frequency of blocking highs over the continent at different time scales. Changes in these teleconnections may be caused by the current global warming. Thus, an increase in temperature alone need not be associated with an increase in area burned in the North American boreal forest. Since the end of the Little Ice Age, the climate has been unusually moist and variable: large fire years have occurred in unusual years, fire frequency has decreased and fire-climate relationships have occurred at interannual to decadal time scales. Prolonged and severe droughts were common in the past and were partly associated with changes in the PDO/ENSO system. Under these conditions, large fire years become common, fire frequency increases and fire-climate relationships occur at decadal to centennial time scales. A suggested return to the drier climate regimes of the past would imply major changes in the temporal dynamics of fire-climate relationships and in area burned, a reduction in the mean age of the forest, and changes in species composition of the North American boreal forest.

Multi-scale enhancement of climate prediction over land by increasing the model sensitivity to vegetation variability in EC-Earth

NASA Astrophysics Data System (ADS)

Alessandri, Andrea; Catalano, Franco; De Felice, Matteo; Van Den Hurk, Bart; Doblas Reyes, Francisco; Boussetta, Souhail; Balsamo, Gianpaolo; Miller, Paul

2016-04-01

The EC-Earth earth system model has been recently developed to include the dynamics of vegetation. In its original formulation, vegetation variability is simply operated by the Leaf Area Index (LAI), which affects climate basically by changing the vegetation physiological resistance to evapotranspiration. This coupling has been found to have only a weak effect on the surface climate modeled by EC-Earth. In reality, the effective sub-grid vegetation fractional coverage will vary seasonally and at interannual time-scales in response to leaf-canopy growth, phenology and senescence. Therefore it affects biophysical parameters such as the albedo, surface roughness and soil field capacity. To adequately represent this effect in EC-Earth, we included an exponential dependence of the vegetation cover on the LAI. By comparing two sets of simulations performed with and without the new variable fractional-coverage parameterization, spanning retrospective predictions at the decadal (5-years), seasonal and sub-seasonal time-scales, we show for the first time a significant multi-scale enhancement of vegetation impacts in climate simulation and prediction over land. Particularly large effects at multiple time scales are shown over boreal winter middle-to-high latitudes over Canada, West US, Eastern Europe, Russia and eastern Siberia due to the implemented time-varying shadowing effect by tree-vegetation on snow surfaces. Over Northern Hemisphere boreal forest regions the improved representation of vegetation cover tends to correct the winter warm biases, improves the climate change sensitivity, the decadal potential predictability as well as the skill of forecasts at seasonal and sub-seasonal time-scales. Significant improvements of the prediction of 2m temperature and rainfall are also shown over transitional land surface hot spots. Both the potential predictability at decadal time-scale and seasonal-forecasts skill are enhanced over Sahel, North American Great Plains, Nordeste Brazil and South East Asia, mainly related to improved performance in the surface evapotranspiration.

Multi-scale enhancement of climate prediction over land by increasing the model sensitivity to vegetation variability in EC-Earth

NASA Astrophysics Data System (ADS)

Alessandri, A.; Catalano, F.; De Felice, M.; van den Hurk, B.; Doblas-Reyes, F. J.; Boussetta, S.; Balsamo, G.; Miller, P. A.

2016-12-01

The European consortium earth system model (EC-Earth; http://www.ec-earth.org) has been recently developed to include the dynamics of vegetation. In its original formulation, vegetation variability is simply operated by the Leaf Area Index (LAI), which affects climate basically by changing the vegetation physiological resistance to evapotranspiration. This coupling has been found to have only a weak effect on the surface climate modeled by EC-Earth. In reality, the effective sub-grid vegetation fractional coverage will vary seasonally and at interannual time-scales in response to leaf-canopy growth, phenology and senescence. Therefore it affects biophysical parameters such as the albedo, surface roughness and soil field capacity. To adequately represent this effect in EC-Earth, we included an exponential dependence of the vegetation cover on the LAI. By comparing two sets of simulations performed with and without the new variable fractional-coverage parameterization, spanning from centennial (20th Century) simulations and retrospective predictions to the decadal (5-years), seasonal and weather time-scales, we show for the first time a significant multi-scale enhancement of vegetation impacts in climate simulation and prediction over land. Particularly large effects at multiple time scales are shown over boreal winter middle-to-high latitudes over Canada, West US, Eastern Europe, Russia and eastern Siberia due to the implemented time-varying shadowing effect by tree-vegetation on snow surfaces. Over Northern Hemisphere boreal forest regions the improved representation of vegetation cover tends to correct the winter warm biases, improves the climate change sensitivity, the decadal potential predictability as well as the skill of forecasts at seasonal and weather time-scales. Significant improvements of the prediction of 2m temperature and rainfall are also shown over transitional land surface hot spots. Both the potential predictability at decadal time-scale and seasonal-forecasts skill are enhanced over Sahel, North American Great Plains, Nordeste Brazil and South East Asia, mainly related to improved performance in the surface evapotranspiration.

Multi-scale enhancement of climate prediction over land by increasing the model sensitivity to vegetation variability in EC-Earth

NASA Astrophysics Data System (ADS)

Alessandri, Andrea; Catalano, Franco; De Felice, Matteo; Van Den Hurk, Bart; Doblas Reyes, Francisco; Boussetta, Souhail; Balsamo, Gianpaolo; Miller, Paul A.

2017-08-01

The EC-Earth earth system model has been recently developed to include the dynamics of vegetation. In its original formulation, vegetation variability is simply operated by the Leaf Area Index (LAI), which affects climate basically by changing the vegetation physiological resistance to evapotranspiration. This coupling has been found to have only a weak effect on the surface climate modeled by EC-Earth. In reality, the effective sub-grid vegetation fractional coverage will vary seasonally and at interannual time-scales in response to leaf-canopy growth, phenology and senescence. Therefore it affects biophysical parameters such as the albedo, surface roughness and soil field capacity. To adequately represent this effect in EC-Earth, we included an exponential dependence of the vegetation cover on the LAI. By comparing two sets of simulations performed with and without the new variable fractional-coverage parameterization, spanning from centennial (twentieth century) simulations and retrospective predictions to the decadal (5-years), seasonal and weather time-scales, we show for the first time a significant multi-scale enhancement of vegetation impacts in climate simulation and prediction over land. Particularly large effects at multiple time scales are shown over boreal winter middle-to-high latitudes over Canada, West US, Eastern Europe, Russia and eastern Siberia due to the implemented time-varying shadowing effect by tree-vegetation on snow surfaces. Over Northern Hemisphere boreal forest regions the improved representation of vegetation cover tends to correct the winter warm biases, improves the climate change sensitivity, the decadal potential predictability as well as the skill of forecasts at seasonal and weather time-scales. Significant improvements of the prediction of 2 m temperature and rainfall are also shown over transitional land surface hot spots. Both the potential predictability at decadal time-scale and seasonal-forecasts skill are enhanced over Sahel, North American Great Plains, Nordeste Brazil and South East Asia, mainly related to improved performance in the surface evapotranspiration.

Multi-scale enhancement of climate prediction over land by increasing the model sensitivity to vegetation variability in EC-Earth

NASA Astrophysics Data System (ADS)

Alessandri, Andrea; Catalano, Franco; De Felice, Matteo; Van Den Hurk, Bart; Doblas Reyes, Francisco; Boussetta, Souhail; Balsamo, Gianpaolo; Miller, Paul A.

2017-04-01

The EC-Earth earth system model has been recently developed to include the dynamics of vegetation. In its original formulation, vegetation variability is simply operated by the Leaf Area Index (LAI), which affects climate basically by changing the vegetation physiological resistance to evapotranspiration. This coupling has been found to have only a weak effect on the surface climate modeled by EC-Earth. In reality, the effective sub-grid vegetation fractional coverage will vary seasonally and at interannual time-scales in response to leaf-canopy growth, phenology and senescence. Therefore it affects biophysical parameters such as the albedo, surface roughness and soil field capacity. To adequately represent this effect in EC-Earth, we included an exponential dependence of the vegetation cover on the LAI. By comparing two sets of simulations performed with and without the new variable fractional-coverage parameterization, spanning from centennial (20th Century) simulations and retrospective predictions to the decadal (5-years), seasonal and weather time-scales, we show for the first time a significant multi-scale enhancement of vegetation impacts in climate simulation and prediction over land. Particularly large effects at multiple time scales are shown over boreal winter middle-to-high latitudes over Canada, West US, Eastern Europe, Russia and eastern Siberia due to the implemented time-varying shadowing effect by tree-vegetation on snow surfaces. Over Northern Hemisphere boreal forest regions the improved representation of vegetation cover tends to correct the winter warm biases, improves the climate change sensitivity, the decadal potential predictability as well as the skill of forecasts at seasonal and weather time-scales. Significant improvements of the prediction of 2m temperature and rainfall are also shown over transitional land surface hot spots. Both the potential predictability at decadal time-scale and seasonal-forecasts skill are enhanced over Sahel, North American Great Plains, Nordeste Brazil and South East Asia, mainly related to improved performance in the surface evapotranspiration.

High-resolution regional climate model evaluation using variable-resolution CESM over California

NASA Astrophysics Data System (ADS)

Huang, X.; Rhoades, A.; Ullrich, P. A.; Zarzycki, C. M.

2015-12-01

Understanding the effect of climate change at regional scales remains a topic of intensive research. Though computational constraints remain a problem, high horizontal resolution is needed to represent topographic forcing, which is a significant driver of local climate variability. Although regional climate models (RCMs) have traditionally been used at these scales, variable-resolution global climate models (VRGCMs) have recently arisen as an alternative for studying regional weather and climate allowing two-way interaction between these domains without the need for nudging. In this study, the recently developed variable-resolution option within the Community Earth System Model (CESM) is assessed for long-term regional climate modeling over California. Our variable-resolution simulations will focus on relatively high resolutions for climate assessment, namely 28km and 14km regional resolution, which are much more typical for dynamically downscaled studies. For comparison with the more widely used RCM method, the Weather Research and Forecasting (WRF) model will be used for simulations at 27km and 9km. All simulations use the AMIP (Atmospheric Model Intercomparison Project) protocols. The time period is from 1979-01-01 to 2005-12-31 (UTC), and year 1979 was discarded as spin up time. The mean climatology across California's diverse climate zones, including temperature and precipitation, is analyzed and contrasted with the Weather Research and Forcasting (WRF) model (as a traditional RCM), regional reanalysis, gridded observational datasets and uniform high-resolution CESM at 0.25 degree with the finite volume (FV) dynamical core. The results show that variable-resolution CESM is competitive in representing regional climatology on both annual and seasonal time scales. This assessment adds value to the use of VRGCMs for projecting climate change over the coming century and improve our understanding of both past and future regional climate related to fine-scale processes. This assessment is also relevant for addressing the scale limitation of current RCMs or VRGCMs when next-generation model resolution increases to ~10km and beyond.

A Power Efficient Exaflop Computer Design for Global Cloud System Resolving Climate Models.

NASA Astrophysics Data System (ADS)

Wehner, M. F.; Oliker, L.; Shalf, J.

2008-12-01

Exascale computers would allow routine ensemble modeling of the global climate system at the cloud system resolving scale. Power and cost requirements of traditional architecture systems are likely to delay such capability for many years. We present an alternative route to the exascale using embedded processor technology to design a system optimized for ultra high resolution climate modeling. These power efficient processors, used in consumer electronic devices such as mobile phones, portable music players, cameras, etc., can be tailored to the specific needs of scientific computing. We project that a system capable of integrating a kilometer scale climate model a thousand times faster than real time could be designed and built in a five year time scale for US$75M with a power consumption of 3MW. This is cheaper, more power efficient and sooner than any other existing technology.

A decadal glimpse on climate and burn severity influences on ponderosa pine post-fire recovery

NASA Astrophysics Data System (ADS)

Newingham, B. A.; Hudak, A. T.; Bright, B. C.; Smith, A.; Khalyani, A. H.

2016-12-01

Climate change is predicted to affect plants at the margins of their distribution. Thus, ecosystem recovery after fire is likely to vary with climate and may be slowest in drier and hotter areas. However, fire regime characteristics, including burn severity, may also affect vegetation recovery. We assessed vegetation recovery one and 9-15 years post-fire in North American ponderosa pine ecosystems distributed across climate and burn severity gradients. Using climate predictors derived from downscaled 1993-2011 climate normals, we predicted vegetation recovery as indicated by Normalized Burn Ratio derived from 1984-2012 Landsat time series imagery. Additionally, we collected field vegetation measurements to examine local topographic controls on burn severity and post-fire vegetation recovery. At a regional scale, we hypothesized a positive relationship between precipitation and recovery time and a negative relationship between temperature and recovery time. At the local scale, we hypothesized southern aspects to recovery slower than northern aspects. We also predicted higher burn severity to slow recovery. Field data found attenuated ponderosa pine recovery in hotter and drier regions across all burn severity classes. We concluded that downscaled climate data and Landsat imagery collected at commensurate scales may provide insight into climate effects on post-fire vegetation recovery relevant to ponderosa pine forest managers.

The role of internal climate variability for interpreting climate change scenarios

NASA Astrophysics Data System (ADS)

Maraun, Douglas

2013-04-01

When communicating information on climate change, the use of multi-model ensembles has been advocated to sample uncertainties over a range as wide as possible. To meet the demand for easily accessible results, the ensemble is often summarised by its multi-model mean signal. In rare cases, additional uncertainty measures are given to avoid loosing all information on the ensemble spread, e.g., the highest and lowest projected values. Such approaches, however, disregard the fundamentally different nature of the different types of uncertainties and might cause wrong interpretations and subsequently wrong decisions for adaptation. Whereas scenario and climate model uncertainties are of epistemic nature, i.e., caused by an in principle reducible lack of knowledge, uncertainties due to internal climate variability are aleatory, i.e., inherently stochastic and irreducible. As wisely stated in the proverb "climate is what you expect, weather is what you get", a specific region will experience one stochastic realisation of the climate system, but never exactly the expected climate change signal as given by a multi model mean. Depending on the meteorological variable, region and lead time, the signal might be strong or weak compared to the stochastic component. In cases of a low signal-to-noise ratio, even if the climate change signal is a well defined trend, no trends or even opposite trends might be experienced. Here I propose to use the time of emergence (TOE) to quantify and communicate when climate change trends will exceed the internal variability. The TOE provides a useful measure for end users to assess the time horizon for implementing adaptation measures. Furthermore, internal variability is scale dependent - the more local the scale, the stronger the influence of internal climate variability. Thus investigating the TOE as a function of spatial scale could help to assess the required spatial scale for implementing adaptation measures. I exemplify this proposal with a recently published study on the TOE for mean and heavy precipitation trends in Europe. In some regions trends emerge only late in the 21st century or even later, suggesting that in these regions adaptation to internal variability rather than to climate change is required. Yet in other regions the climate change signal is strong, urging for timely adaptation. Douglas Maraun, When at what scale will trends in European mean and heavy precipitation emerge? Env. Res. Lett., in press, 2013.

The Nested Regional Climate Model: An Approach Toward Prediction Across Scales

NASA Astrophysics Data System (ADS)

Hurrell, J. W.; Holland, G. J.; Large, W. G.

2008-12-01

The reality of global climate change has become accepted and society is rapidly moving to questions of consequences on space and time scales that are relevant to proper planning and development of adaptation strategies. There are a number of urgent challenges for the scientific community related to improved and more detailed predictions of regional climate change on decadal time scales. Two important examples are potential impacts of climate change on North Atlantic hurricane activity and on water resources over the intermountain West. The latter is dominated by complex topography, so that accurate simulations of regional climate variability and change require much finer spatial resolution than is provided with state-of-the-art climate models. Climate models also do not explicitly resolve tropical cyclones, even though these storms have dramatic societal impacts and play an important role in regulating climate. Moreover, the debate over the impact of global warming on tropical cyclones has at times been acrimonious, and the lack of hard evidence has left open opportunities for misinterpretation and justification of pre-existing beliefs. These and similar topics are being assessed at NCAR, in partnership with university colleagues, through the development of a Nested Regional Climate Model (NRCM). This is an ambitious effort to combine a state of the science mesoscale weather model (WRF), a high resolution regional ocean modeling system (ROMS), and a climate model (CCSM) to better simulate the complex, multi-scale interactions intrinsic to atmospheric and oceanic fluid motions that are limiting our ability to predict likely future changes in regional weather statistics and climate. The NRCM effort is attracting a large base of earth system scientists together with societal groups as diverse as the Western Governor's Association and the offshore oil industry. All of these groups require climate data on scales of a few kilometers (or less), so that the NRCM program is producing unique data sets of climate change scenarios of immense interest. In addition, all simulations are archived in a form that will be readily accessible to other researchers, thus enabling a wider group to investigate these important issues.

Records of millennial-scale climate change from the Great Basin of the Western United States

NASA Astrophysics Data System (ADS)

Benson, Larry

High-resolution (decadal) records of climate change from the Owens, Mono, and Pyramid Lake basins of California and Nevada indicate that millennialscale oscillations in climate of the Great Basin occurred between 52.6 and 9.2 14C ka. Climate records from the Owens and Pyramid Lake basins indicate that most, but not all, glacier advances (stades) between 52.6 and ˜15.0 14C ka occurred during relatively dry times. During the last alpine glacial period (˜60.0 to ˜14.0 14C ka), stadial/interstadial oscillations were recorded in Owens and Pyramid Lake sediments by the negative response of phytoplankton productivity to the influx of glacially derived silicates. During glacier advances, rock flour diluted the TOC fraction of lake sediments and introduction of glacially derived suspended sediment also increased the turbidity of lake water, decreasing light penetration and photosynthetic production of organic carbon. It is not possible to correlate objectively peaks in the Owens and Pyramid Lake TOC records (interstades) with Dansgaard-Oeschger interstades in the GISP2 ice-core δ18O record given uncertainties in age control and difference in the shapes of the OL90, PLC92 and GISP2 records. In the North Atlantic region, some climate records have clearly defined variability/cyclicity with periodicities of 102 to 103 yr; these records are correlatable over several thousand km. In the Great Basin, climate proxies also have clearly defined variability with similar time constants, but the distance over which this variability can be correlated remains unknown. Globally, there may be minimal spatial scales (domains) within which climate varies coherently on centennial and millennial scales, but it is likely that the sizes of these domains vary with geographic setting and time. A more comprehensive understanding of the mechanisms of climate forcing and the physical linkages between climate forcing and system response is needed in order to predict the spatial scale(s) over which climate varies coherently.

Sensitivity of proxies on non-linear interactions in the climate system

PubMed Central

Schultz, Johannes A.; Beck, Christoph; Menz, Gunter; Neuwirth, Burkhard; Ohlwein, Christian; Philipp, Andreas

2015-01-01

Recent climate change is affecting the earth system to an unprecedented extent and intensity and has the potential to cause severe ecological and socioeconomic consequences. To understand natural and anthropogenic induced processes, feedbacks, trends, and dynamics in the climate system, it is also essential to consider longer timescales. In this context, annually resolved tree-ring data are often used to reconstruct past temperature or precipitation variability as well as atmospheric or oceanic indices such as the North Atlantic Oscillation (NAO) or the Atlantic Multidecadal Oscillation (AMO). The aim of this study is to assess weather-type sensitivity across the Northern Atlantic region based on two tree-ring width networks. Our results indicate that nonstationarities in superordinate space and time scales of the climate system (here synoptic- to global scale, NAO, AMO) can affect the climate sensitivity of tree-rings in subordinate levels of the system (here meso- to synoptic scale, weather-types). This scale bias effect has the capability to impact even large multiproxy networks and the ability of these networks to provide information about past climate conditions. To avoid scale biases in climate reconstructions, interdependencies between the different scales in the climate system must be considered, especially internal ocean/atmosphere dynamics. PMID:26686001

Data-driven Climate Modeling and Prediction

NASA Astrophysics Data System (ADS)

Kondrashov, D. A.; Chekroun, M.

2016-12-01

Global climate models aim to simulate a broad range of spatio-temporal scales of climate variability with state vector having many millions of degrees of freedom. On the other hand, while detailed weather prediction out to a few days requires high numerical resolution, it is fairly clear that a major fraction of large-scale climate variability can be predicted in a much lower-dimensional phase space. Low-dimensional models can simulate and predict this fraction of climate variability, provided they are able to account for linear and nonlinear interactions between the modes representing large scales of climate dynamics, as well as their interactions with a much larger number of modes representing fast and small scales. This presentation will highlight several new applications by Multilayered Stochastic Modeling (MSM) [Kondrashov, Chekroun and Ghil, 2015] framework that has abundantly proven its efficiency in the modeling and real-time forecasting of various climate phenomena. MSM is a data-driven inverse modeling technique that aims to obtain a low-order nonlinear system of prognostic equations driven by stochastic forcing, and estimates both the dynamical operator and the properties of the driving noise from multivariate time series of observations or a high-end model's simulation. MSM leads to a system of stochastic differential equations (SDEs) involving hidden (auxiliary) variables of fast-small scales ranked by layers, which interact with the macroscopic (observed) variables of large-slow scales to model the dynamics of the latter, and thus convey memory effects. New MSM climate applications focus on development of computationally efficient low-order models by using data-adaptive decomposition methods that convey memory effects by time-embedding techniques, such as Multichannel Singular Spectrum Analysis (M-SSA) [Ghil et al. 2002] and recently developed Data-Adaptive Harmonic (DAH) decomposition method [Chekroun and Kondrashov, 2016]. In particular, new results by DAH-MSM modeling and prediction of Arctic Sea Ice, as well as decadal predictions of near-surface Earth temperatures will be presented.

Intercomparison of model response and internal variability across climate model ensembles

NASA Astrophysics Data System (ADS)

Kumar, Devashish; Ganguly, Auroop R.

2017-10-01

Characterization of climate uncertainty at regional scales over near-term planning horizons (0-30 years) is crucial for climate adaptation. Climate internal variability (CIV) dominates climate uncertainty over decadal prediction horizons at stakeholders' scales (regional to local). In the literature, CIV has been characterized indirectly using projections of climate change from multi-model ensembles (MME) instead of directly using projections from multiple initial condition ensembles (MICE), primarily because adequate number of initial condition (IC) runs were not available for any climate model. Nevertheless, the recent availability of significant number of IC runs from one climate model allows for the first time to characterize CIV directly from climate model projections and perform a sensitivity analysis to study the dominance of CIV compared to model response variability (MRV). Here, we measure relative agreement (a dimensionless number with values ranging between 0 and 1, inclusive; a high value indicates less variability and vice versa) among MME and MICE and find that CIV is lower than MRV for all projection time horizons and spatial resolutions for precipitation and temperature. However, CIV exhibits greater dominance over MRV for seasonal and annual mean precipitation at higher latitudes where signals of climate change are expected to emerge sooner. Furthermore, precipitation exhibits large uncertainties and a rapid decline in relative agreement from global to continental, regional, or local scales for MICE compared to MME. The fractional contribution of uncertainty due to CIV is invariant for precipitation and decreases for temperature as lead time progresses towards the end of the century.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Collins, William D; Johansen, Hans; Evans, Katherine J

We present a survey of physical and computational techniques that have the potential to con- tribute to the next generation of high-fidelity, multi-scale climate simulations. Examples of the climate science problems that can be investigated with more depth include the capture of remote forcings of localized hydrological extreme events, an accurate representation of cloud features over a range of spatial and temporal scales, and parallel, large ensembles of simulations to more effectively explore model sensitivities and uncertainties. Numerical techniques, such as adaptive mesh refinement, implicit time integration, and separate treatment of fast physical time scales are enabling improved accuracy andmore » fidelity in simulation of dynamics and allow more complete representations of climate features at the global scale. At the same time, part- nerships with computer science teams have focused on taking advantage of evolving computer architectures, such as many-core processors and GPUs, so that these approaches which were previously considered prohibitively costly have become both more efficient and scalable. In combination, progress in these three critical areas is poised to transform climate modeling in the coming decades.« less

Managing the Nation's water in a changing climate

USGS Publications Warehouse

Lins, H.F.; Stakhiv, E.Z.

1998-01-01

Among the many concerns associated with global climate change, the potential effects on water resources are frequently cited as the most worrisome. In contrast, those who manage water resources do not rate climatic change among their top planning and operational concerns. The difference in these views can be associated with how water managers operate their systems and the types of stresses, and the operative time horizons, that affect the Nation's water resources infrastructure. Climate, or more precisely weather, is an important variable in the management of water resources at daily to monthly time scales because water resources systems generally are operated on a daily basis. At decadal to centennial time scales, though, climate is much less important because (1) forecasts, particularly of regional precipitation, are extremely uncertain over such time periods, and (2) the magnitude of effects due to changes in climate on water resources is small relative to changes in other variables such as population, technology, economics, and environmental regulation. Thus, water management agencies find it difficult to justify changing design features or operating rules on the basis of simulated climatic change at the present time, especially given that reservoir-design criteria incorporate considerable buffering capacity for extreme meteorological and hydrological events.

Atmospheric CO2 variations on millennial-scale during MIS 6

NASA Astrophysics Data System (ADS)

Shin, Jinhwa; Grilli, Roberto; Chappellaz, Jérôme; Teste, Grégory; Nehrbass-Ahles, Christoph; Schmidely, Loïc; Schmitt, Jochen; Stocker, Thomas; Fischer, Hubertus

2017-04-01

Understanding natural carbon cycle / climate feedbacks on various time scales is highly important for predicting future climate changes. Paleoclimate records of Antarctic temperatures, relative sea level and foraminiferal isotope and pollen records in sediment cores from the Portuguese margin have shown climate variations on millennial time scale over the Marine Isotope Stage 6 (MIS 6; from approximately 135 to 190 kyr BP). These proxy data suggested iceberg calving in the North Atlantic result in cooling in the Northern hemisphere and warming in Antarctica by changes in the Atlantic Meridional Overturning Circulation, which is explained by a bipolar see-saw trend in the ocean (Margari et al., 2010). Atmospheric CO2 reconstruction from Antarctic ice cores can provide key information on how atmospheric CO2 concentrations are linked to millennial-scale climate changes. However, existing CO2 records cannot be used to address this relationship because of the lack of suitable temporal resolution. In this work, we will present a new CO2 record with an improved time resolution, obtained from the Dome C ice core (75˚ 06'S, 123˚ 24'E) spanning the MIS 6 period, using dry extraction methods. We will examine millennial-scale features in atmospheric CO2, and their possible links with other proxies covering MIS 6. Margari, V., Skinner, L. C., Tzedakis, P. C., Ganopolski, A., Vautravers, M., and Shackleton, N. J.: The nature of millennial scale climate variability during the past two glacial periods, Nat.Geosci., 3, 127-131, 2010.

The effects of monsoons and climate teleconnections on the Niangziguan Karst Spring discharge in North China

NASA Astrophysics Data System (ADS)

Zhang, Juan; Hao, Yonghong; Hu, Bill X.; Huo, Xueli; Hao, Pengmei; Liu, Zhongfang

2017-01-01

Karst aquifers supply drinking water for 25 % of the world's population, and they are, however, vulnerable to climate change. This study is aimed to investigate the effects of various monsoons and teleconnection patterns on Niangziguan Karst Spring (NKS) discharge in North China for sustainable exploration of the karst groundwater resources. The monsoons studied include the Indian Summer Monsoon, the West North Pacific Monsoon and the East Asian Summer Monsoon. The climate teleconnection patterns explored include the Indian Ocean Dipole, E1 Niño Southern Oscillation, and the Pacific Decadal Oscillation. The wavelet transform and wavelet coherence methods are used to analyze the karst hydrological processes in the NKS Basin, and reveal the relations between the climate indices with precipitation and the spring discharge. The study results indicate that both the monsoons and the climate teleconnections significantly affect precipitation in the NKS Basin. The time scales that the monsoons resonate with precipitation are strongly concentrated on the time scales of 0.5-, 1-, 2.5- and 3.5-year, and that climate teleconnections resonate with precipitation are relatively weak and diverged from 0.5-, 1-, 2-, 2.5-, to 8-year time scales, respectively. Because the climate signals have to overcome the resistance of heterogeneous aquifers before reaching spring discharge, with high energy, the strong climate signals (e.g. monsoons) are able to penetrate through aquifers and act on spring discharge. So the spring discharge is more strongly affected by monsoons than the climate teleconnections. During the groundwater flow process, the precipitation signals will be attenuated, delayed, merged, and changed by karst aquifers. Therefore, the coherence coefficients between the spring discharge and climate indices are smaller than those between precipitation and climate indices. Further, the fluctuation of the spring discharge is not coincident with that of precipitation in most situations. Karst spring discharge as a proxy can represent groundwater resource variability at a regional scale, and is more strongly influenced by climate variation.

Century to Millennium-Scale Late Quaternary Natural Climate Variability in the Midwestern United States

NASA Astrophysics Data System (ADS)

Jaumann, Peter Josef

1995-01-01

Estimates of past natural climatic variability on long time scales (centuries to millennia) are crucial in testing climate models. The process of model validation takes advantage of long general circulation model (GCM) integrations, instrumental and satellite observations, and paleoclimatic records. Here I use paleoclimatic proxy records from central North America spanning the last 150 ka to characterize climatic variability on sub-orbital time scales. A terrestrial last interglacial (~ 130 to 75 kyr BP) pollen sequence from south-central Illinois, U.S.A., contains climatic variance in frequency bands between 1 cycle/10 kyr and 1 cycle/1 kyr. The temporal variance is best developed as alternating cycles of pollen assemblages indicative of wet and dry conditions. Spectral cross-correlations between selected pollen types and potential forcings (ETP (eccentricity, tilt, precession), SPECMAP delta^{18}O) implicate oceanic and solar processes as possible mechanisms driving last interglacial vegetation and climate change in the Midwestern U.S. During the last glacial stage (LGS; 20 to 16 kyr BP) a lacustrine sequence from the central Mississippi River valley experienced major flooding events caused by intermittent melting of the Laurentide ice sheet. Rock -magnetic and grain size data confirm the physical record of flood clays. Correlation of the flood clays to the Greenland (GRIP) ice core is weak. However, the Laurentide melting events seem to fall temporally between the releases of minor LGS iceberg discharges into the North Atlantic. The GRIP delta^{18}O and the Midwestern U.S. magnetic susceptibility time series indicate sub-Milankovitch climate variability modes. Mapping, multivariate, and time series analyses of Holocene (8 to 1 ka) pollen sequences from central North America suggest spatial patterns of vegetation and climate change on sub-orbital to millennial time scales. The rate, magnitude, and spatial patterns of change varied considerably over the study region. Major climatic variance contained in several well-dated pollen time series ranges between 1 cycle/6 kyr and 1 cycle/0.6 kyr. Singular and cross -spectral analyses, again, suggest solar and oceanic forcing. Although it is difficult to attribute past climatic changes to specific forcings, the geologic record of past global change will prove invaluable in the assessment of long-term future climate change and prediction.

Understanding climate: A strategy for climate modeling and predictability research, 1985-1995

NASA Technical Reports Server (NTRS)

Thiele, O. (Editor); Schiffer, R. A. (Editor)

1985-01-01

The emphasis of the NASA strategy for climate modeling and predictability research is on the utilization of space technology to understand the processes which control the Earth's climate system and it's sensitivity to natural and man-induced changes and to assess the possibilities for climate prediction on time scales of from about two weeks to several decades. Because the climate is a complex multi-phenomena system, which interacts on a wide range of space and time scales, the diversity of scientific problems addressed requires a hierarchy of models along with the application of modern empirical and statistical techniques which exploit the extensive current and potential future global data sets afforded by space observations. Observing system simulation experiments, exploiting these models and data, will also provide the foundation for the future climate space observing system, e.g., Earth observing system (EOS), 1985; Tropical Rainfall Measuring Mission (TRMM) North, et al. NASA, 1984.

Changes and Relationships of Climatic and Hydrological Droughts in the Jialing River Basin, China.

PubMed

Zeng, Xiaofan; Zhao, Na; Sun, Huaiwei; Ye, Lei; Zhai, Jianqing

2015-01-01

The comprehensive assessment of climatic and hydrological droughts in terms of their temporal and spatial evolutions is very important for water resources management and social development in the basin scale. To study the spatial and temporal changes of climatic and hydrological droughts and the relationships between them, the SPEI and SDI are adopted to assess the changes and the correlations of climatic and hydrological droughts by selecting the Jialing River basin, China as the research area. The SPEI and SDI at different time scales are assessed both at the entire Jialing River basin and at the regional levels of the three sub basins. The results show that the SPEI and SDI are very suitable for assessing the changes and relationships of climatic and hydrological droughts in large basins. Based on the assessment, for the Jialing River basin, climatic and hydrological droughts have the increasing tendency during recent several decades, and the increasing trend of climatic droughts is significant or extremely significant in the western and northern basin, while hydrological drought has a less significant increasing trend. Additionally, climatic and hydrological droughts tend to increase in the next few years. The results also show that on short time scales, climatic droughts have one or two months lag impact on hydrological droughts in the north-west area of the basin, and have one month lag impact in south-east area of the basin. The assessment of climatic and hydrological droughts based on the SPEI and SDI could be very useful for water resources management and climate change adaptation at large basin scale.

Changes and Relationships of Climatic and Hydrological Droughts in the Jialing River Basin, China

PubMed Central

Zeng, Xiaofan; Zhao, Na; Sun, Huaiwei; Ye, Lei; Zhai, Jianqing

2015-01-01

The comprehensive assessment of climatic and hydrological droughts in terms of their temporal and spatial evolutions is very important for water resources management and social development in the basin scale. To study the spatial and temporal changes of climatic and hydrological droughts and the relationships between them, the SPEI and SDI are adopted to assess the changes and the correlations of climatic and hydrological droughts by selecting the Jialing River basin, China as the research area. The SPEI and SDI at different time scales are assessed both at the entire Jialing River basin and at the regional levels of the three sub basins. The results show that the SPEI and SDI are very suitable for assessing the changes and relationships of climatic and hydrological droughts in large basins. Based on the assessment, for the Jialing River basin, climatic and hydrological droughts have the increasing tendency during recent several decades, and the increasing trend of climatic droughts is significant or extremely significant in the western and northern basin, while hydrological drought has a less significant increasing trend. Additionally, climatic and hydrological droughts tend to increase in the next few years. The results also show that on short time scales, climatic droughts have one or two months lag impact on hydrological droughts in the north-west area of the basin, and have one month lag impact in south-east area of the basin. The assessment of climatic and hydrological droughts based on the SPEI and SDI could be very useful for water resources management and climate change adaptation at large basin scale. PMID:26544070

Model simulations and proxy-based reconstructions for the European region in the past millennium (Invited)

NASA Astrophysics Data System (ADS)

Zorita, E.

2009-12-01

One of the objectives when comparing simulations of past climates to proxy-based climate reconstructions is to asses the skill of climate models to simulate climate change. This comparison may accomplished at large spatial scales, for instance the evolution of simulated and reconstructed Northern Hemisphere annual temperature, or at regional or point scales. In both approaches a 'fair' comparison has to take into account different aspects that affect the inevitable uncertainties and biases in the simulations and in the reconstructions. These efforts face a trade-off: climate models are believed to be more skillful at large hemispheric scales, but climate reconstructions are these scales are burdened by the spatial distribution of available proxies and by methodological issues surrounding the statistical method used to translate the proxy information into large-spatial averages. Furthermore, the internal climatic noise at large hemispheric scales is low, so that the sampling uncertainty tends to be also low. On the other hand, the skill of climate models at regional scales is limited by the coarse spatial resolution, which hinders a faithful representation of aspects important for the regional climate. At small spatial scales, the reconstruction of past climate probably faces less methodological problems if information from different proxies is available. The internal climatic variability at regional scales is, however, high. In this contribution some examples of the different issues faced when comparing simulation and reconstructions at small spatial scales in the past millennium are discussed. These examples comprise reconstructions from dendrochronological data and from historical documentary data in Europe and climate simulations with global and regional models. These examples indicate that the centennial climate variations can offer a reasonable target to assess the skill of global climate models and of proxy-based reconstructions, even at small spatial scales. However, as the focus shifts towards higher frequency variability, decadal or multidecadal, the need for larger simulation ensembles becomes more evident. Nevertheless,the comparison at these time scales may expose some lines of research on the origin of multidecadal regional climate variability.

Simulation of an ensemble of future climate time series with an hourly weather generator

NASA Astrophysics Data System (ADS)

Caporali, E.; Fatichi, S.; Ivanov, V. Y.; Kim, J.

2010-12-01

There is evidence that climate change is occurring in many regions of the world. The necessity of climate change predictions at the local scale and fine temporal resolution is thus warranted for hydrological, ecological, geomorphological, and agricultural applications that can provide thematic insights into the corresponding impacts. Numerous downscaling techniques have been proposed to bridge the gap between the spatial scales adopted in General Circulation Models (GCM) and regional analyses. Nevertheless, the time and spatial resolutions obtained as well as the type of meteorological variables may not be sufficient for detailed studies of climate change effects at the local scales. In this context, this study presents a stochastic downscaling technique that makes use of an hourly weather generator to simulate time series of predicted future climate. Using a Bayesian approach, the downscaling procedure derives distributions of factors of change for several climate statistics from a multi-model ensemble of GCMs. Factors of change are sampled from their distributions using a Monte Carlo technique to entirely account for the probabilistic information obtained with the Bayesian multi-model ensemble. Factors of change are subsequently applied to the statistics derived from observations to re-evaluate the parameters of the weather generator. The weather generator can reproduce a wide set of climate variables and statistics over a range of temporal scales, from extremes, to the low-frequency inter-annual variability. The final result of such a procedure is the generation of an ensemble of hourly time series of meteorological variables that can be considered as representative of future climate, as inferred from GCMs. The generated ensemble of scenarios also accounts for the uncertainty derived from multiple GCMs used in downscaling. Applications of the procedure in reproducing present and future climates are presented for different locations world-wide: Tucson (AZ), Detroit (MI), and Firenze (Italy). The stochastic downscaling is carried out with eight GCMs from the CMIP3 multi-model dataset (IPCC 4AR, A1B scenario).

Developing perturbations for Climate Change Impact Assessments

NASA Astrophysics Data System (ADS)

Hewitson, Bruce

Following the 2001 Intergovernmental Panel on Climate Change (IPCC) Third Assessment Report [TAR; IPCC, 2001], and the paucity of climate change impact assessments from developing nations, there has been a significant growth in activities to redress this shortcoming. However, undertaking impact assessments (in relation to malaria, crop stress, regional water supply, etc.) is contingent on available climate-scale scenarios at time and space scales of relevance to the regional issues of importance. These scales are commonly far finer than even the native resolution of the Global Climate Models (GCMs) (the principal tools for climate change research), let alone the skillful resolution (scales of aggregation at which GCM observational error is acceptable for a given application) of GCMs.Consequently, there is a growing demand for regional-scale scenarios, which in turn are reliant on techniques to downscale from GCMs, such as empirical downscaling or nested Regional Climate Models (RCMs). These methods require significant skill, experiential knowledge, and computational infrastructure in order to derive credible regional-scale scenarios. In contrast, it is often the case that impact assessment researchers in developing nations have inadequate resources with limited access to scientists in the broader international scientific community who have the time and expertise to assist. However, where developing effective downscaled scenarios is problematic, it is possible that much useful information can still be obtained for impact assessments by examining the system sensitivity to largerscale climate perturbations. Consequently, one may argue that the early phase of assessing sensitivity and vulnerability should first be characterized by evaluation of the first-order impacts, rather than immediately addressing the finer, secondary factors that are dependant on scenarios derived through downscaling.

Autogenic geomorphic processes determine the resolution and fidelity of terrestrial paleoclimate records.

PubMed

Foreman, Brady Z; Straub, Kyle M

2017-09-01

Terrestrial paleoclimate records rely on proxies hosted in alluvial strata whose beds are deposited by unsteady and nonlinear geomorphic processes. It is broadly assumed that this renders the resultant time series of terrestrial paleoclimatic variability noisy and incomplete. We evaluate this assumption using a model of oscillating climate and the precise topographic evolution of an experimental alluvial system. We find that geomorphic stochasticity can create aliasing in the time series and spurious climate signals, but these issues are eliminated when the period of climate oscillation is longer than a key time scale of internal dynamics in the geomorphic system. This emergent autogenic geomorphic behavior imparts regularity to deposition and represents a natural discretization interval of the continuous climate signal. We propose that this time scale in nature could be in excess of 10 4 years but would still allow assessments of the rates of climate change at resolutions finer than the existing age model techniques in isolation.

Autogenic geomorphic processes determine the resolution and fidelity of terrestrial paleoclimate records

PubMed Central

Foreman, Brady Z.; Straub, Kyle M.

2017-01-01

Terrestrial paleoclimate records rely on proxies hosted in alluvial strata whose beds are deposited by unsteady and nonlinear geomorphic processes. It is broadly assumed that this renders the resultant time series of terrestrial paleoclimatic variability noisy and incomplete. We evaluate this assumption using a model of oscillating climate and the precise topographic evolution of an experimental alluvial system. We find that geomorphic stochasticity can create aliasing in the time series and spurious climate signals, but these issues are eliminated when the period of climate oscillation is longer than a key time scale of internal dynamics in the geomorphic system. This emergent autogenic geomorphic behavior imparts regularity to deposition and represents a natural discretization interval of the continuous climate signal. We propose that this time scale in nature could be in excess of 104 years but would still allow assessments of the rates of climate change at resolutions finer than the existing age model techniques in isolation. PMID:28924607

Drought forecasting in Luanhe River basin involving climatic indices

NASA Astrophysics Data System (ADS)

Ren, Weinan; Wang, Yixuan; Li, Jianzhu; Feng, Ping; Smith, Ronald J.

2017-11-01

Drought is regarded as one of the most severe natural disasters globally. This is especially the case in Tianjin City, Northern China, where drought can affect economic development and people's livelihoods. Drought forecasting, the basis of drought management, is an important mitigation strategy. In this paper, we evolve a probabilistic forecasting model, which forecasts transition probabilities from a current Standardized Precipitation Index (SPI) value to a future SPI class, based on conditional distribution of multivariate normal distribution to involve two large-scale climatic indices at the same time, and apply the forecasting model to 26 rain gauges in the Luanhe River basin in North China. The establishment of the model and the derivation of the SPI are based on the hypothesis of aggregated monthly precipitation that is normally distributed. Pearson correlation and Shapiro-Wilk normality tests are used to select appropriate SPI time scale and large-scale climatic indices. Findings indicated that longer-term aggregated monthly precipitation, in general, was more likely to be considered normally distributed and forecasting models should be applied to each gauge, respectively, rather than to the whole basin. Taking Liying Gauge as an example, we illustrate the impact of the SPI time scale and lead time on transition probabilities. Then, the controlled climatic indices of every gauge are selected by Pearson correlation test and the multivariate normality of SPI, corresponding climatic indices for current month and SPI 1, 2, and 3 months later are demonstrated using Shapiro-Wilk normality test. Subsequently, we illustrate the impact of large-scale oceanic-atmospheric circulation patterns on transition probabilities. Finally, we use a score method to evaluate and compare the performance of the three forecasting models and compare them with two traditional models which forecast transition probabilities from a current to a future SPI class. The results show that the three proposed models outperform the two traditional models and involving large-scale climatic indices can improve the forecasting accuracy.

Grasping time scales from galactic life cycles to personal life projects at a linear scale of 1 mm per 100 years

NASA Astrophysics Data System (ADS)

Holm Jacobsen, Bo

2010-05-01

The ambition is to make the citizen (i.e. pupil/student/scholar/voter/journalist/politician) comprehend better and more scientifically all time scales from the lifespan of the universe to the personal life project by a consistent geographical mapping of time at a scale of 1 mm per 100 years. The processes which change earth systems like life, climate, topography and plate tectonics operate at very different timescales. The understanding of these systems is essential not only for students and scholars of earth science but also for pupils, voters and politicians who make decisions of possibly significant consequence to climate and biodiversity not only for our generation but for thousands or even millions of years ahead. With a consistent linear mapping of time to a scale of 1 millimetre per 100 years, historical time (

Towards a More Biologically-meaningful Climate Characterization: Variability in Space and Time at Multiple Scales

NASA Astrophysics Data System (ADS)

Christianson, D. S.; Kaufman, C. G.; Kueppers, L. M.; Harte, J.

2013-12-01

Sampling limitations and current modeling capacity justify the common use of mean temperature values in summaries of historical climate and future projections. However, a monthly mean temperature representing a 1-km2 area on the landscape is often unable to capture the climate complexity driving organismal and ecological processes. Estimates of variability in addition to mean values are more biologically meaningful and have been shown to improve projections of range shifts for certain species. Historical analyses of variance and extreme events at coarse spatial scales, as well as coarse-scale projections, show increasing temporal variability in temperature with warmer means. Few studies have considered how spatial variance changes with warming, and analysis for both temporal and spatial variability across scales is lacking. It is unclear how the spatial variability of fine-scale conditions relevant to plant and animal individuals may change given warmer coarse-scale mean values. A change in spatial variability will affect the availability of suitable habitat on the landscape and thus, will influence future species ranges. By characterizing variability across both temporal and spatial scales, we can account for potential bias in species range projections that use coarse climate data and enable improvements to current models. In this study, we use temperature data at multiple spatial and temporal scales to characterize spatial and temporal variability under a warmer climate, i.e., increased mean temperatures. Observational data from the Sierra Nevada (California, USA), experimental climate manipulation data from the eastern and western slopes of the Rocky Mountains (Colorado, USA), projected CMIP5 data for California (USA) and observed PRISM data (USA) allow us to compare characteristics of a mean-variance relationship across spatial scales ranging from sub-meter2 to 10,000 km2 and across temporal scales ranging from hours to decades. Preliminary spatial analysis at fine-spatial scales (sub-meter to 10-meter) shows greater temperature variability with warmer mean temperatures. This is inconsistent with the inherent assumption made in current species distribution models that fine-scale variability is static, implying that current projections of future species ranges may be biased -- the direction and magnitude requiring further study. While we focus our findings on the cross-scaling characteristics of temporal and spatial variability, we also compare the mean-variance relationship between 1) experimental climate manipulations and observed conditions and 2) temporal versus spatial variance, i.e., variability in a time-series at one location vs. variability across a landscape at a single time. The former informs the rich debate concerning the ability to experimentally mimic a warmer future. The latter informs space-for-time study design and analyses, as well as species persistence via a combined spatiotemporal probability of suitable future habitat.

Verification of GCM-generated regional seasonal precipitation for current climate and of statistical downscaling estimates under changing climate conditions

DOE Office of Scientific and Technical Information (OSTI.GOV)

Busuioc, A.; Storch, H. von; Schnur, R.

Empirical downscaling procedures relate large-scale atmospheric features with local features such as station rainfall in order to facilitate local scenarios of climate change. The purpose of the present paper is twofold: first, a downscaling technique is used as a diagnostic tool to verify the performance of climate models on the regional scale; second, a technique is proposed for verifying the validity of empirical downscaling procedures in climate change applications. The case considered is regional seasonal precipitation in Romania. The downscaling model is a regression based on canonical correlation analysis between observed station precipitation and European-scale sea level pressure (SLP). Themore » climate models considered here are the T21 and T42 versions of the Hamburg ECHAM3 atmospheric GCM run in time-slice mode. The climate change scenario refers to the expected time of doubled carbon dioxide concentrations around the year 2050. Generally, applications of statistical downscaling to climate change scenarios have been based on the assumption that the empirical link between the large-scale and regional parameters remains valid under a changed climate. In this study, a rationale is proposed for this assumption by showing the consistency of the 2 x CO{sub 2} GCM scenarios in winter, derived directly from the gridpoint data, with the regional scenarios obtained through empirical downscaling. Since the skill of the GCMs in regional terms is already established, it is concluded that the downscaling technique is adequate for describing climatically changing regional and local conditions, at least for precipitation in Romania during winter.« less

Climate-FVS Version 2: Content, users guide, applications, and behavior

Treesearch

Nicholas L. Crookston

2014-01-01

Climate change in the 21st Century is projected to cause widespread changes in forest ecosystems. Climate-FVS is a modification to the Forest Vegetation Simulator designed to take climate change into account when predicting forest dynamics at decadal to century time scales. Individual tree climate viability scores measure the likelihood that the climate at a given...

Information transfer across the scales of climate variability: The effect of the 7-8 year cycle on the annual and interannual scales

NASA Astrophysics Data System (ADS)

Palus, Milan; Jajcay, Nikola; Hlinka, Jaroslav; Kravtsov, Sergey; Tsonis, Anastasios

2016-04-01

Complexity of the climate system stems not only from the fact that it is variable over a huge range of spatial and temporal scales, but also from the nonlinear character of the climate system that leads to interactions of dynamics across scales. The dynamical processes on large time scales influence variability on shorter time scales. This nonlinear phenomenon of cross-scale causal interactions can be observed due to the recently introduced methodology [1] which starts with a wavelet decomposition of a multi-scale signal into quasi-oscillatory modes of a limited bandwidth, described using their instantaneous phases and amplitudes. Then their statistical associations are tested in order to search for interactions across time scales. An information-theoretic formulation of the generalized, nonlinear Granger causality [2] uncovers causal influence and information transfer from large-scale modes of climate variability with characteristic time scales from years to almost a decade to regional temperature variability on short time scales. In analyses of air temperature records from various European locations, a quasioscillatory phenomenon with the period around 7-8 years has been identified as the factor influencing variability of surface air temperature (SAT) on shorter time scales. Its influence on the amplitude of the SAT annual cycle was estimated in the range 0.7-1.4 °C and the effect on the overall variability of the SAT anomalies (SATA) leads to the changes 1.5-1.7 °C in the annual SATA means. The strongest effect of the 7-8 year cycle was observed in the winter SATA means where it reaches 4-5 °C in central European station and reanalysis data [3]. This study is supported by the Ministry of Education, Youth and Sports of the Czech Republic within the Program KONTAKT II, Project No. LH14001. [1] M. Palus, Phys. Rev. Lett. 112 078702 (2014) [2] M. Palus, M. Vejmelka, Phys. Rev. E 75, 056211 (2007) [3] N. Jajcay, J. Hlinka, S. Kravtsov, A. A. Tsonis, M. Palus, Time-scales of the European surface air temperature variability: The role of the 7-8 year cycle. Geophys. Res. Lett., in press, DOI: 10.1002/2015GL067325

Toward a U.S. National Phenological Assessment

NASA Astrophysics Data System (ADS)

Henebry, Geoffrey M.; Betancourt, Julio L.

2010-01-01

Third USA National Phenology Network (USA-NPN) and Research Coordination Network (RCN) Annual Meeting; Milwaukee, Wisconsin, 5-9 October 2009; Directional climate change will have profound and lasting effects throughout society that are best understood through fundamental physical and biological processes. One such process is phenology: how the timing of recurring biological events is affected by biotic and abiotic forces. Phenology is an early and integrative indicator of climate change readily understood by nonspecialists. Phenology affects the planting, maturation, and harvesting of food and fiber; pollination; timing and magnitude of allergies and disease; recreation and tourism; water quantity and quality; and ecosystem function and resilience. Thus, phenology is the gateway to climatic effects on both managed and unmanaged ecosystems. Adaptation to climatic variability and change will require integration of phenological data and models with climatic forecasts at seasonal to decadal time scales. Changes in phenologies have already manifested myriad effects of directional climate change. As these changes continue, it is critical to establish a comprehensive suite of benchmarks that can be tracked and mapped at local to continental scales with observations and climate models.

Changing climate shifts timing of European floods.

PubMed

Blöschl, Günter; Hall, Julia; Parajka, Juraj; Perdigão, Rui A P; Merz, Bruno; Arheimer, Berit; Aronica, Giuseppe T; Bilibashi, Ardian; Bonacci, Ognjen; Borga, Marco; Čanjevac, Ivan; Castellarin, Attilio; Chirico, Giovanni B; Claps, Pierluigi; Fiala, Károly; Frolova, Natalia; Gorbachova, Liudmyla; Gül, Ali; Hannaford, Jamie; Harrigan, Shaun; Kireeva, Maria; Kiss, Andrea; Kjeldsen, Thomas R; Kohnová, Silvia; Koskela, Jarkko J; Ledvinka, Ondrej; Macdonald, Neil; Mavrova-Guirguinova, Maria; Mediero, Luis; Merz, Ralf; Molnar, Peter; Montanari, Alberto; Murphy, Conor; Osuch, Marzena; Ovcharuk, Valeryia; Radevski, Ivan; Rogger, Magdalena; Salinas, José L; Sauquet, Eric; Šraj, Mojca; Szolgay, Jan; Viglione, Alberto; Volpi, Elena; Wilson, Donna; Zaimi, Klodian; Živković, Nenad

2017-08-11

A warming climate is expected to have an impact on the magnitude and timing of river floods; however, no consistent large-scale climate change signal in observed flood magnitudes has been identified so far. We analyzed the timing of river floods in Europe over the past five decades, using a pan-European database from 4262 observational hydrometric stations, and found clear patterns of change in flood timing. Warmer temperatures have led to earlier spring snowmelt floods throughout northeastern Europe; delayed winter storms associated with polar warming have led to later winter floods around the North Sea and some sectors of the Mediterranean coast; and earlier soil moisture maxima have led to earlier winter floods in western Europe. Our results highlight the existence of a clear climate signal in flood observations at the continental scale. Copyright © 2017 The Authors, some rights reserved; exclusive licensee American Association for the Advancement of Science. No claim to original U.S. Government Works.

Using Scaling to Understand, Model and Predict Global Scale Anthropogenic and Natural Climate Change

NASA Astrophysics Data System (ADS)

Lovejoy, S.; del Rio Amador, L.

2014-12-01

The atmosphere is variable over twenty orders of magnitude in time (≈10-3 to 1017 s) and almost all of the variance is in the spectral "background" which we show can be divided into five scaling regimes: weather, macroweather, climate, macroclimate and megaclimate. We illustrate this with instrumental and paleo data. Based the signs of the fluctuation exponent H, we argue that while the weather is "what you get" (H>0: fluctuations increasing with scale), that it is macroweather (H<0: fluctuations decreasing with scale) - not climate - "that you expect". The conventional framework that treats the background as close to white noise and focuses on quasi-periodic variability assumes a spectrum that is in error by a factor of a quadrillion (≈ 1015). Using this scaling framework, we can quantify the natural variability, distinguish it from anthropogenic variability, test various statistical hypotheses and make stochastic climate forecasts. For example, we estimate the probability that the warming is simply a giant century long natural fluctuation is less than 1%, most likely less than 0.1% and estimate return periods for natural warming events of different strengths and durations, including the slow down ("pause") in the warming since 1998. The return period for the pause was found to be 20-50 years i.e. not very unusual; however it immediately follows a 6 year "pre-pause" warming event of almost the same magnitude with a similar return period (30 - 40 years). To improve on these unconditional estimates, we can use scaling models to exploit the long range memory of the climate process to make accurate stochastic forecasts of the climate including the pause. We illustrate stochastic forecasts on monthly and annual scale series of global and northern hemisphere surface temperatures. We obtain forecast skill nearly as high as the theoretical (scaling) predictability limits allow: for example, using hindcasts we find that at 10 year forecast horizons we can still explain ≈ 15% of the anomaly variance. These scaling hindcasts have comparable - or smaller - RMS errors than existing GCM's. We discuss how these be further improved by going beyond time series forecasts to space-time.

Climate impact of beef: an analysis considering multiple time scales and production methods without use of global warming potentials

NASA Astrophysics Data System (ADS)

Pierrehumbert, R. T.; Eshel, G.

2015-08-01

An analysis of the climate impact of various forms of beef production is carried out, with a particular eye to the comparison between systems relying primarily on grasses grown in pasture (‘grass-fed’ or ‘pastured’ beef) and systems involving substantial use of manufactured feed requiring significant external inputs in the form of synthetic fertilizer and mechanized agriculture (‘feedlot’ beef). The climate impact is evaluated without employing metrics such as {{CO}}2{{e}} or global warming potentials. The analysis evaluates the impact at all time scales out to 1000 years. It is concluded that certain forms of pastured beef production have substantially lower climate impact than feedlot systems. However, pastured systems that require significant synthetic fertilization, inputs from supplemental feed, or deforestation to create pasture, have substantially greater climate impact at all time scales than the feedlot and dairy-associated systems analyzed. Even the best pastured system analyzed has enough climate impact to justify efforts to limit future growth of beef production, which in any event would be necessary if climate and other ecological concerns were met by a transition to primarily pasture-based systems. Alternate mitigation options are discussed, but barring unforseen technological breakthroughs worldwide consumption at current North American per capita rates appears incompatible with a 2 °C warming target.

State dependence of climatic instability over the past 720,000 years from Antarctic ice cores and climate modeling.

PubMed

Kawamura, Kenji; Abe-Ouchi, Ayako; Motoyama, Hideaki; Ageta, Yutaka; Aoki, Shuji; Azuma, Nobuhiko; Fujii, Yoshiyuki; Fujita, Koji; Fujita, Shuji; Fukui, Kotaro; Furukawa, Teruo; Furusaki, Atsushi; Goto-Azuma, Kumiko; Greve, Ralf; Hirabayashi, Motohiro; Hondoh, Takeo; Hori, Akira; Horikawa, Shinichiro; Horiuchi, Kazuho; Igarashi, Makoto; Iizuka, Yoshinori; Kameda, Takao; Kanda, Hiroshi; Kohno, Mika; Kuramoto, Takayuki; Matsushi, Yuki; Miyahara, Morihiro; Miyake, Takayuki; Miyamoto, Atsushi; Nagashima, Yasuo; Nakayama, Yoshiki; Nakazawa, Takakiyo; Nakazawa, Fumio; Nishio, Fumihiko; Obinata, Ichio; Ohgaito, Rumi; Oka, Akira; Okuno, Jun'ichi; Okuyama, Junichi; Oyabu, Ikumi; Parrenin, Frédéric; Pattyn, Frank; Saito, Fuyuki; Saito, Takashi; Saito, Takeshi; Sakurai, Toshimitsu; Sasa, Kimikazu; Seddik, Hakime; Shibata, Yasuyuki; Shinbori, Kunio; Suzuki, Keisuke; Suzuki, Toshitaka; Takahashi, Akiyoshi; Takahashi, Kunio; Takahashi, Shuhei; Takata, Morimasa; Tanaka, Yoichi; Uemura, Ryu; Watanabe, Genta; Watanabe, Okitsugu; Yamasaki, Tetsuhide; Yokoyama, Kotaro; Yoshimori, Masakazu; Yoshimoto, Takayasu

2017-02-01

Climatic variabilities on millennial and longer time scales with a bipolar seesaw pattern have been documented in paleoclimatic records, but their frequencies, relationships with mean climatic state, and mechanisms remain unclear. Understanding the processes and sensitivities that underlie these changes will underpin better understanding of the climate system and projections of its future change. We investigate the long-term characteristics of climatic variability using a new ice-core record from Dome Fuji, East Antarctica, combined with an existing long record from the Dome C ice core. Antarctic warming events over the past 720,000 years are most frequent when the Antarctic temperature is slightly below average on orbital time scales, equivalent to an intermediate climate during glacial periods, whereas interglacial and fully glaciated climates are unfavourable for a millennial-scale bipolar seesaw. Numerical experiments using a fully coupled atmosphere-ocean general circulation model with freshwater hosing in the northern North Atlantic showed that climate becomes most unstable in intermediate glacial conditions associated with large changes in sea ice and the Atlantic Meridional Overturning Circulation. Model sensitivity experiments suggest that the prerequisite for the most frequent climate instability with bipolar seesaw pattern during the late Pleistocene era is associated with reduced atmospheric CO 2 concentration via global cooling and sea ice formation in the North Atlantic, in addition to extended Northern Hemisphere ice sheets.

State dependence of climatic instability over the past 720,000 years from Antarctic ice cores and climate modeling

PubMed Central

Kawamura, Kenji; Abe-Ouchi, Ayako; Motoyama, Hideaki; Ageta, Yutaka; Aoki, Shuji; Azuma, Nobuhiko; Fujii, Yoshiyuki; Fujita, Koji; Fujita, Shuji; Fukui, Kotaro; Furukawa, Teruo; Furusaki, Atsushi; Goto-Azuma, Kumiko; Greve, Ralf; Hirabayashi, Motohiro; Hondoh, Takeo; Hori, Akira; Horikawa, Shinichiro; Horiuchi, Kazuho; Igarashi, Makoto; Iizuka, Yoshinori; Kameda, Takao; Kanda, Hiroshi; Kohno, Mika; Kuramoto, Takayuki; Matsushi, Yuki; Miyahara, Morihiro; Miyake, Takayuki; Miyamoto, Atsushi; Nagashima, Yasuo; Nakayama, Yoshiki; Nakazawa, Takakiyo; Nakazawa, Fumio; Nishio, Fumihiko; Obinata, Ichio; Ohgaito, Rumi; Oka, Akira; Okuno, Jun’ichi; Okuyama, Junichi; Oyabu, Ikumi; Parrenin, Frédéric; Pattyn, Frank; Saito, Fuyuki; Saito, Takashi; Saito, Takeshi; Sakurai, Toshimitsu; Sasa, Kimikazu; Seddik, Hakime; Shibata, Yasuyuki; Shinbori, Kunio; Suzuki, Keisuke; Suzuki, Toshitaka; Takahashi, Akiyoshi; Takahashi, Kunio; Takahashi, Shuhei; Takata, Morimasa; Tanaka, Yoichi; Uemura, Ryu; Watanabe, Genta; Watanabe, Okitsugu; Yamasaki, Tetsuhide; Yokoyama, Kotaro; Yoshimori, Masakazu; Yoshimoto, Takayasu

2017-01-01

Climatic variabilities on millennial and longer time scales with a bipolar seesaw pattern have been documented in paleoclimatic records, but their frequencies, relationships with mean climatic state, and mechanisms remain unclear. Understanding the processes and sensitivities that underlie these changes will underpin better understanding of the climate system and projections of its future change. We investigate the long-term characteristics of climatic variability using a new ice-core record from Dome Fuji, East Antarctica, combined with an existing long record from the Dome C ice core. Antarctic warming events over the past 720,000 years are most frequent when the Antarctic temperature is slightly below average on orbital time scales, equivalent to an intermediate climate during glacial periods, whereas interglacial and fully glaciated climates are unfavourable for a millennial-scale bipolar seesaw. Numerical experiments using a fully coupled atmosphere-ocean general circulation model with freshwater hosing in the northern North Atlantic showed that climate becomes most unstable in intermediate glacial conditions associated with large changes in sea ice and the Atlantic Meridional Overturning Circulation. Model sensitivity experiments suggest that the prerequisite for the most frequent climate instability with bipolar seesaw pattern during the late Pleistocene era is associated with reduced atmospheric CO2 concentration via global cooling and sea ice formation in the North Atlantic, in addition to extended Northern Hemisphere ice sheets. PMID:28246631

The impact of ARM on climate modeling

DOE PAGES

Randall, David A.; Del Genio, Anthony D.; Donner, Lee J.; ...

2016-07-15

Climate models are among humanity’s most ambitious and elaborate creations. They are designed to simulate the interactions of the atmosphere, ocean, land surface, and cryosphere on time scales far beyond the limits of deterministic predictability and including the effects of time-dependent external forcings. The processes involved include radiative transfer, fluid dynamics, microphysics, and some aspects of geochemistry, biology, and ecology. The models explicitly simulate processes on spatial scales ranging from the circumference of Earth down to 100 km or smaller and implicitly include the effects of processes on even smaller scales down to a micron or so. In addition, themore » atmospheric component of a climate model can be called an atmospheric global circulation model (AGCM).« less

Spatial variability of the response to climate change in regional groundwater systems -- examples from simulations in the Deschutes Basin, Oregon

USGS Publications Warehouse

Waibel, Michael S.; Gannett, Marshall W.; Chang, Heejun; Hulbe, Christina L.

2013-01-01

We examine the spatial variability of the response of aquifer systems to climate change in and adjacent to the Cascade Range volcanic arc in the Deschutes Basin, Oregon using downscaled global climate model projections to drive surface hydrologic process and groundwater flow models. Projected warming over the 21st century is anticipated to shift the phase of precipitation toward more rain and less snow in mountainous areas in the Pacific Northwest, resulting in smaller winter snowpack and in a shift in the timing of runoff to earlier in the year. This will be accompanied by spatially variable changes in the timing of groundwater recharge. Analysis of historic climate and hydrologic data and modeling studies show that groundwater plays a key role in determining the response of stream systems to climate change. The spatial variability in the response of groundwater systems to climate change, particularly with regard to flow-system scale, however, has generally not been addressed in the literature. Here we simulate the hydrologic response to projected future climate to show that the response of groundwater systems can vary depending on the location and spatial scale of the flow systems and their aquifer characteristics. Mean annual recharge averaged over the basin does not change significantly between the 1980s and 2080s climate periods given the ensemble of global climate models and emission scenarios evaluated. There are, however, changes in the seasonality of groundwater recharge within the basin. Simulation results show that short-flow-path groundwater systems, such as those providing baseflow to many headwater streams, will likely have substantial changes in the timing of discharge in response changes in seasonality of recharge. Regional-scale aquifer systems with flow paths on the order of many tens of kilometers, in contrast, are much less affected by changes in seasonality of recharge. Flow systems at all spatial scales, however, are likely to reflect interannual changes in total recharge. These results provide insights into the possible impacts of climate change to other regional aquifer systems, and the streams they support, where discharge points represent a range of flow system scales.

Wavelet-based time series bootstrap model for multidecadal streamflow simulation using climate indicators

NASA Astrophysics Data System (ADS)

Erkyihun, Solomon Tassew; Rajagopalan, Balaji; Zagona, Edith; Lall, Upmanu; Nowak, Kenneth

2016-05-01

A model to generate stochastic streamflow projections conditioned on quasi-oscillatory climate indices such as Pacific Decadal Oscillation (PDO) and Atlantic Multi-decadal Oscillation (AMO) is presented. Recognizing that each climate index has underlying band-limited components that contribute most of the energy of the signals, we first pursue a wavelet decomposition of the signals to identify and reconstruct these features from annually resolved historical data and proxy based paleoreconstructions of each climate index covering the period from 1650 to 2012. A K-Nearest Neighbor block bootstrap approach is then developed to simulate the total signal of each of these climate index series while preserving its time-frequency structure and marginal distributions. Finally, given the simulated climate signal time series, a K-Nearest Neighbor bootstrap is used to simulate annual streamflow series conditional on the joint state space defined by the simulated climate index for each year. We demonstrate this method by applying it to simulation of streamflow at Lees Ferry gauge on the Colorado River using indices of two large scale climate forcings: Pacific Decadal Oscillation (PDO) and Atlantic Multi-decadal Oscillation (AMO), which are known to modulate the Colorado River Basin (CRB) hydrology at multidecadal time scales. Skill in stochastic simulation of multidecadal projections of flow using this approach is demonstrated.

Sub-Milankovitch millennial-scale climate variability in Middle Eocene deep-marine sediments

NASA Astrophysics Data System (ADS)

Scotchman, J. I.; Pickering, K. T.; Robinson, S. A.

2009-12-01

Sub-Milankovitch millennial scale climate variability appears ubiquitous throughout the Quaternary and Pleistocene palaeoenvironmental records (e.g. McManus et al., 1999) yet the driving mechanism remains elusive. Possible mechanisms are generally linked to Quaternary-specific oceanic and cryospheric conditions (e.g. Maslin et al., 2001). An alternative external control, such as solar forcing, however, remains a compelling alternative hypothesis (e.g. Bond et al., 2001). This would imply that millennial-scale cycles are an intrinsic part of the Earth’s climatic system and not restricted to any specific period of time. Determining which of these hypotheses is correct impacts on our understanding of the climate system and its role as a driver of cyclic sedimentation during both icehouse and greenhouse climates. Here we show that Middle Eocene, laminated deep-marine sediments deposited in the Ainsa Basin, Spanish Pyrenees, contain 1,565-year (469 mm) cycles modulated by a 7,141-year (2157 mm) period. Climatic oscillations of 1,565-years recorded by element/Al ratios, are interpreted as representing climatically driven variation in sediment supply (terrigenous run-off) to the Ainsa basin. Climatic oscillations with this period are comparable to Quaternary Bond (~1,500-year), Dansgaard-Oeschger (~1,470-year) and Heinrich (~7,200-year) climatic events. Recognition of similar millennial-scale oscillations in the greenhouse climate of the Middle Eocene would appear inconsistent with an origin dependent upon Quaternary-specific conditions. Our observations lend support for pervasive millennial-scale climatic variability present throughout geologic time likely driven by an external forcing mechanism such as solar forcing. References Bond, G., Kromer, B., Beer, J., Muscheler, R., Evans, M.N., Showers, W., Hoffmann, S., Lotti-Bond, R., Hajdas, I., Bonani, G. 2001. Persistent Solar Influence on North Atlantic Climate During the Holocene. Science, 294, 2130-2136 Maslin, M., Seidov, D., Lowe, J. 2001. Synthesis of the nature and causes of rapid climate transitions during the Quaternary. In: The Oceans and rapid climate change: Past, present and future, (Seidov, D., Haupt, B. J. & Maslin, M., Eds.), AGU, Washington, D. C. McManus, J.F., Oppo, D.W. & Cullen, J.L. 1999. A 0.5-Million-Year Record of Millennial-Scale Climate Variability in the North Atlantic. Science, 283, 971-975

The joint space-time statistics of macroweather precipitation, space-time statistical factorization and macroweather models.

PubMed

Lovejoy, S; de Lima, M I P

2015-07-01

Over the range of time scales from about 10 days to 30-100 years, in addition to the familiar weather and climate regimes, there is an intermediate "macroweather" regime characterized by negative temporal fluctuation exponents: implying that fluctuations tend to cancel each other out so that averages tend to converge. We show theoretically and numerically that macroweather precipitation can be modeled by a stochastic weather-climate model (the Climate Extended Fractionally Integrated Flux, model, CEFIF) first proposed for macroweather temperatures and we show numerically that a four parameter space-time CEFIF model can approximately reproduce eight or so empirical space-time exponents. In spite of this success, CEFIF is theoretically and numerically difficult to manage. We therefore propose a simplified stochastic model in which the temporal behavior is modeled as a fractional Gaussian noise but the spatial behaviour as a multifractal (climate) cascade: a spatial extension of the recently introduced ScaLIng Macroweather Model, SLIMM. Both the CEFIF and this spatial SLIMM model have a property often implicitly assumed by climatologists that climate statistics can be "homogenized" by normalizing them with the standard deviation of the anomalies. Physically, it means that the spatial macroweather variability corresponds to different climate zones that multiplicatively modulate the local, temporal statistics. This simplified macroweather model provides a framework for macroweather forecasting that exploits the system's long range memory and spatial correlations; for it, the forecasting problem has been solved. We test this factorization property and the model with the help of three centennial, global scale precipitation products that we analyze jointly in space and in time.

A new reference frame for astronomically-tuned Plio-Pleistocene climate variability derived from a benthic oxygen isotope splice of the Mediterranean

NASA Astrophysics Data System (ADS)

Lourens, L. J.; Ziegler, M.; Konijnendijk, T. Y. M.; Hilgen, F. J.; Bos, R.; Beekvelt, B.; van Loevezijn, A.; Collin, S.

2017-12-01

The astronomical theory of climate has revolutionized our understanding of past climate change and the development of highly accurate geologic time scales for the entire Cenozoic. Most of this understanding has come from the construction of astronomically tuned global ocean benthic foraminiferal oxygen isotope (δ18O) stacked record, derived by the international drilling operations of DSDP, ODP and IODP. The tuning includes fixed phase relationships between the obliquity and precession cycles and the inferred high-latitude climate, i.e. glacial-interglacial, response, which hark back to SPECMAP, using simple ice sheet models and a limited number of radiometric dates. This approach was largely implemented in the widely applied LR04 stack, though LR04 assumed shorter response times for the smaller ice caps during the Pliocene. In the past decades, an astronomically calibrated time scale for the Pliocene and Pleistocene of the Mediterranean has been developed, which has become the reference for the standard Geologic Time Scale. Typical of the Mediterranean marine sediments are the cyclic lithological alternations, reflecting the interference between obliquity and precession-paced low latitude climate variability, such as the African monsoon. Here we present the first benthic foraminiferal based oxygen isotope record of the Mediterranean reference scale, which strikingly mirrors the LR04. We will use this record to discuss the assumed open ocean glacial-interglacial related phase relations over the past 5.3 million years.

Smoothing of millennial scale climate variability in European Loess (and other records)

NASA Astrophysics Data System (ADS)

Zeeden, Christian; Obreht, Igor; Hambach, Ulrich; Veres, Daniel; Marković, Slobodan B.; Lehmkuhl, Frank

2017-04-01

Millennial scale climate variability is seen in various records of the northern hemisphere in the last glacial cycle, and their expression represents a correlation tool beyond the resolution of e.g. luminescence dating. Highest (correlative) dating accuracy is a prerequisite of comparing different geoarchives, especially when related to archaeological findings. Here we attempt to constrain the timing of loess geoarchives representing the environmental context of early humans in south-eastern Europe, and discuss the challenge of dealing with smoothed records. In this contribution, we present rock magnetic and grain size data from the Rasova loess record in the Lower Danube basin (Romania), showing millennial scale climate variability. Additionally, we summarize similar data from the Lower and Middle Danube Basins. A comparison of these loess data and reference records from Greenland ice cores and the Mediterranean-Black Sea region indicates a rather unusual expression of millennial scale climate variability recorded in loess. To explain the observed patterns, we experiment with low-pass filters of reference records to simulate a signal smoothing by natural processes such as e.g. bioturbation and pervasive diagenesis. Low-pass filters avoid high frequency oscillations and focus on the longer period (lower frequency) variability, here using cut-off periods from 1-15 kyr. In our opinion low-pass filters represent simple models for the expression of millennial scale climate variability in low sedimentation environments, and in sediments where signals are smoothed by e.g. bioturbation and/or diagenesis. Using different low-pass filter thresholds allows us to (a) explain observed patterns and their relation to millennial scale climate variability, (b) propose these filtered/smoothed signals as correlation targets for records lacking millennial scale recording, but showing smoothed climate variability on supra-millennial scales, and (c) determine which time resolution specific (loess) records can reproduce. Comparing smoothed records to reference data may be a step forward especially for last glacial stratigraphies, where millennial scale patterns are certainly present but not directly recorded in some geoarchives. Interestingly, smoothed datasets from Greenland and the Black Sea-Mediterranean region are most similar in the last ca. 15 ka and again from ca. 30-50 ka. During the cold phase from ca. 30-15 ka records show dissimilarities, challenging robust correlative time scales in this age range. A potential explanation may be related to the expansion of Northern European and Alpine ice sheets influencing atmospheric systems in the North Atlantic and Eurasian regions and thus leading to regionally and temporally differentiated climatic responses.

Environmental hydro-refugia demonstrated by vegetation vigour in the Okavango Delta, Botswana

PubMed Central

Reynolds, S. C.; Marston, C. G.; Hassani, H.; King, G. C. P.; Bennett, M. R.

2016-01-01

Climate shifts at decadal scales can have environmental consequences, and therefore, identifying areas that act as environmental refugia is valuable in understanding future climate variability. Here we illustrate how, given appropriate geohydrology, a rift basin and its catchment can buffer vegetation response to climate signals on decadal time-scales, therefore exerting strong local environmental control. We use time-series data derived from Normalised Difference Vegetation Index (NDVI) residuals that record vegetation vigour, extracted from a decadal span of MODIS images, to demonstrate hydrogeological buffering. While this has been described previously it has never been demonstrated via remote sensing and results in relative stability in vegetation vigour inside the delta, compared to that outside. As such the Delta acts as a regional hydro-refugium. This provides insight, not only to the potential impact of future climate in the region, but also demonstrates why similar basins are attractive to fauna, including our ancestors, in regions like eastern Africa. Although vertebrate evolution operates on time scales longer than decades, the sensitivity of rift wetlands to climate change has been stressed by some authors, and this work demonstrates another example of the unique properties that such basins can afford, given the right hydrological conditions. PMID:27775028

Climate change impact on the annual water balance in the northwest Florida coastal

NASA Astrophysics Data System (ADS)

Alizad, K.; Wang, D.; Alimohammadi, N.; Hagen, S. C.

2012-12-01

As the largest tributary to the Apalachicola River, the Chipola River originates in southern Alabama, flows through Florida Panhandle and ended to Gulf of Mexico. The Chipola watershed is located in an intermediate climate environment with aridity index around one. Watershed provides habitat for a number of threatened and endangered animal and plant species. However, climate change affects hydrologic cycle of Chipola River watershed at various temporal and spatial scales. Studying the effects of climate variations is of great importance for water and environmental management purposes in this catchment. This research is mainly focuses on assessing climate change impact on the partitioning pattern of rainfall from mean annual to inter-annual and to seasonal scales. At the mean annual scale, rainfall is partitioned into runoff and evaporation assuming negligible water storage changes. Mean annual runoff is controlled by both mean annual precipitation and potential evaporation. Changes in long term mean runoff caused by variations of long term mean precipitation and potential evaporation will be evaluated based on Budyko hypothesis. At the annual scale, rainfall is partitioned into runoff, evaporation, and storage change. Inter-annual variability of runoff and evaporation are mainly affected by the changes of mean annual climate variables as well as their inter-annual variability. In order to model and evaluate each component of water balance at the annual scale, parsimonious but reliable models, are developed. Budyko hypothesis on the existing balance between available water and energy supply is reconsidered and redefined for the sub-annual time scale and reconstructed accordingly in order to accurately model seasonal hydrologic balance of the catchment. Models are built in the seasonal time frame with a focus on the role of storage change in water cycle. Then for Chipola catchment, models are parameterized based on a sufficient time span of historical data and the their coefficients are quantified. For necessary future predictions, data obtained from climate regional models starting 2040 to 2069 will be utilized. To accommodate the inherent uncertainty of climate projections, an ensemble of regional climate models will be used to assess changes of rainfall and potential evaporation. Then, the climate change impact on seasonal and annual runoff, evaporation, and water storage changes will be projected.

Analysis of the historical precipitation in the South East Iberian Peninsula at different spatio-temporal scale. Study of the meteorological drought

NASA Astrophysics Data System (ADS)

Fernández-Chacón, Francisca; Pulido-Velazquez, David; Jiménez-Sánchez, Jorge; Luque-Espinar, Juan Antonio

2017-04-01

Precipitation is a fundamental climate variable that has a pronounced spatial and temporal variability on a global scale, as well as at regional and sub-regional scales. Due to its orographic complexity and its latitude the Iberian Peninsula (IP), located to the west of the Mediterranean Basin between the Atlantic Ocean and the Mediterranean Sea, has a complex climate. Over the peninsula there are strong north-south and east-west gradients, as a consequence of the different low-frequency atmospheric patterns, and he overlap of these over the year will be determinants in the variability of climatic variables. In the southeast of the Iberian Peninsula dominates a dry Mediterranean climate, the precipitation is characterized as being an intermittent and discontinuous variable. In this research information coming from the Spain02 v4 database was used to study the South East (SE) IP for the 1971-2010 period with a spatial resolution of 0.11 x 0.11. We analysed precipitation at different time scale (daily, monthly, seasonal, annual,…) to study the spatial distribution and temporal tendencies. The high spatial, intra-annual and inter-annual climatic variability observed makes it necessary to propose a climatic regionalization. In addition, for the identified areas and subareas of homogeneous climate we have analysed the evolution of the meteorological drought for the same period at different time scales. The standardized precipitation index has been used at 12, 24 and 48 month temporal scale. The climatic complexity of the area determines a high variability in the drought characteristics, duration, intensity and frequency in the different climatic areas. This research has been supported by the GESINHIMPADAPT project (CGL2013-48424-C2-2-R) with Spanish MINECO funds. We would also like to thank Spain02 project for the data provided for this study.

Elevation Gradients and Climatic Consequences

NASA Astrophysics Data System (ADS)

Redmond, K. T.

2006-12-01

Steep topography usually results in gradients in surface meteorological elements. Sometimes these gradients are extremely sharp. Frequent or persistent gradients are expressed in climatic statistics as well. Most commonly, higher elevations are wetter and cooler than lower elevations. The magnitude of these climate gradients vary both spatially and temporally, generally on smaller scales for the former and on a greater variety of scales for the latter. Orographic contributions to precipitation vary on hourly to annual scales, and temperature inversions of different durations can alter or reverse the vertical temperature lapse rate normally found in the atmosphere. The presence of these factors affects the probability distributions of climate elements as a function of elevation. This leads in turn to consequences for ecology, resource management, and data. Orographic enhancement of Sierra precipitation varies by a factor of about three on seasonal time scales, and more on shorter scales. Particularly strong gradients in temperature climate are observed along the California coast, resulting in large changes in long-term climatological probability distributions over quite short distances in elevation. These have significant implications for plant life. For specific noteworthy events, such as the California heat wave of July 2006, striking differences were seen over a horizontal distance of merely 2-3 km along the Big Sur Coast, related entirely to elevation. There is evidence of differential warming with elevation between California's Central Valley and the Sierra Nevada. As a practical matter, the three-dimensional correlation fields of weather and climate elements in topographically diverse regions, on differing time scales, have complex structure, but also have certain regularities. This makes quality control of weather and climate data sets in highly diverse topography much more challenging. Quality control decisions that do not properly take this correlation structure (which varies in time) into account can result in degraded data sets, a variety of Type I and Type II errors, and paradoxically, hinder or prevent the discovery and description of the effects of climate gradients by incorrectly altering the data sets needed to uncover and quantify the relationships.

Controls on Arctic sea ice from first-year and multi-year ice survival rates

NASA Astrophysics Data System (ADS)

Armour, K.; Bitz, C. M.; Hunke, E. C.; Thompson, L.

2009-12-01

The recent decrease in Arctic sea ice cover has transpired with a significant loss of multi-year (MY) ice. The transition to an Arctic that is populated by thinner first-year (FY) sea ice has important implications for future trends in area and volume. We develop a reduced model for Arctic sea ice with which we investigate how the survivability of FY and MY ice control various aspects of the sea-ice system. We demonstrate that Arctic sea-ice area and volume behave approximately as first-order autoregressive processes, which allows for a simple interpretation of September sea-ice in which its mean state, variability, and sensitivity to climate forcing can be described naturally in terms of the average survival rates of FY and MY ice. This model, used in concert with a sea-ice simulation that traces FY and MY ice areas to estimate the survival rates, reveals that small trends in the ice survival rates explain the decline in total Arctic ice area, and the relatively larger loss of MY ice area, over the period 1979-2006. Additionally, our model allows for a calculation of the persistence time scales of September area and volume anomalies. A relatively short memory time scale for ice area (~ 1 year) implies that Arctic ice area is nearly in equilibrium with long-term climate forcing at all times, and therefore observed trends in area are a clear indication of a changing climate. A longer memory time scale for ice volume (~ 5 years) suggests that volume can be out of equilibrium with climate forcing for long periods of time, and therefore trends in ice volume are difficult to distinguish from its natural variability. With our reduced model, we demonstrate the connection between memory time scale and sensitivity to climate forcing, and discuss the implications that a changing memory time scale has on the trajectory of ice area and volume in a warming climate. Our findings indicate that it is unlikely that a “tipping point” in September ice area and volume will be reached as the climate is further warmed. Finally, we suggest novel model validation techniques based upon comparing the characteristics of FY and MY ice within models to observations. We propose that keeping an account of FY and MY ice area within sea ice models offers a powerful new way to evaluate model projections of sea ice in a greenhouse warming climate.

Millennial-scale Climate Variations Recorded As Far Back As The Early Pliocene

NASA Astrophysics Data System (ADS)

Steenbrink, J.; Hilgen, F. J.; Lourens, L. J.

Quaternary climate proxy records show compelling evidence for climate variability on time scales of a few thousand years. The causes for these millennial-scale or sub- Milankovitch cycles are yet poorly understood, not in the least due to the complex feedback mechanisms of large ice-sheets during the Quaternary. We present evidence of millennial-scale climate variability in Early Pliocene lacustrine sediments from the intramontane Ptolemais Basin in northwestern Greece. The sediments are well ex- posed in a series of open-pit lignite mines and exhibit a distinct m-scale sedimentary cyclicity of alternating lignites and lacustrine marl beds that result from precession- induced variations in climate. A higher-frequency cyclicity is particular prominent within the marl segment of individual cycles. A stratigraphic interval of~115 kyr, cov- ering five precession-induced sedimentary cycles, was studied in nine parallel sections from two quarries located several km apart. Colour reflectance records were used to quantify the within-cycle variability and to determine its lateral continuity. Much of the within-cycle variability could be correlated between the parallel sections, even in fine detail, which suggests that these changes reflect basin-wide variations in environ- mental conditions related to (regional) climate fluctuations. Interbedded volcanic ash beds demonstrate the synchronicity of these fluctuations and spectral analysis of the reflectance time series shows a significant concentration of variability at periods of ~11,~5.5 and~2 kyr. Their occurrence at times before the intensification of the North- ern Hemisphere glaciation suggests that they cannot solely have resulted from internal ice-sheet dynamics. Possible candidates include harmonics or combination tones of the main orbital cycles, variations in solar output or periodic motions of the Earth and moon.

Characterizing and understanding the climatic determinism of high- to low-frequency variations in precipitation in northwestern France using a coupled wavelet multiresolution/statistical downscaling approach

NASA Astrophysics Data System (ADS)

Massei, Nicolas; Dieppois, Bastien; Hannah, David; Lavers, David; Fossa, Manuel; Laignel, Benoit; Debret, Maxime

2017-04-01

Geophysical signals oscillate over several time-scales that explain different amount of their overall variability and may be related to different physical processes. Characterizing and understanding such variabilities in hydrological variations and investigating their determinism is one important issue in a context of climate change, as these variabilities can be occasionally superimposed to long-term trend possibly due to climate change. It is also important to refine our understanding of time-scale dependent linkages between large-scale climatic variations and hydrological responses on the regional or local-scale. Here we investigate such links by conducting a wavelet multiresolution statistical dowscaling approach of precipitation in northwestern France (Seine river catchment) over 1950-2016 using sea level pressure (SLP) and sea surface temperature (SST) as indicators of atmospheric and oceanic circulations, respectively. Previous results demonstrated that including multiresolution decomposition in a statistical downscaling model (within a so-called multiresolution ESD model) using SLP as large-scale predictor greatly improved simulation of low-frequency, i.e. interannual to interdecadal, fluctuations observed in precipitation. Building on these results, continuous wavelet transform of simulated precipiation using multiresolution ESD confirmed the good performance of the model to better explain variability at all time-scales. A sensitivity analysis of the model to the choice of the scale and wavelet function used was also tested. It appeared that whatever the wavelet used, the model performed similarly. The spatial patterns of SLP found as the best predictors for all time-scales, which resulted from the wavelet decomposition, revealed different structures according to time-scale, showing possible different determinisms. More particularly, some low-frequency components ( 3.2-yr and 19.3-yr) showed a much wide-spread spatial extentsion across the Atlantic. Moreover, in accordance with other previous studies, the wavelet components detected in SLP and precipitation on interannual to interdecadal time-scales could be interpreted in terms of influence of the Gulf-Stream oceanic front on atmospheric circulation. Current works are now conducted including SST over the Atlantic in order to get further insights into this mechanism.

Worksite health and safety climate: scale development and effects of a health promotion intervention.

PubMed

Basen-Engquist, K; Hudmon, K S; Tripp, M; Chamberlain, R

1998-01-01

Environmental influences on health and health behavior have an important place in research on worksite health promotion. We tested the validity and internal consistency of a new measure of organizational health and safety climate that was used in a large randomized trial of a worksite cancer prevention program (the Working Well Trial). The resulting scales then were applied to assess intervention effects. This study uses data from a subset of 40 worksites in the Working Well Trial. Employees at 20 natural gas pipeline worksite and 20 rural electrical cooperatives completed a cross-sectional questionnaire at baseline and 3-year follow-up. A factor analysis of this self-report instrument produced a two-factor solution. The resulting health and safety climate scales had good internal consistency (Cronbach's alpha = 0.74 and 0.82, respectively) and concurrent validity. The health climate scale was correlated more highly with organizational measures that were indicative of a supportive health climate than those indicating supportive safety climate, while the reverse was true of the safety climate scale. Changes in health climate were associated with the number of smoking and smokeless tobacco programs offered at the worksites at the time of the 3-year follow-up (r = 0.46 and 0.42, respectively). The scales were not correlated with most employee health behaviors. The health climate scores increased at intervention worksites, compared with scores at control worksites (F[1,36] = 7.57, P = 0.009). The health and safety climate scales developed for this study provide useful instruments for measuring organizational change related to worksite health promotion activities. The Working Well Intervention resulted in a significant improvement in worksite health climate.

Evidence for Large Decadal Variability in the Tropical Mean Radiative Energy Budget

NASA Technical Reports Server (NTRS)

Wielicki, Bruce A.; Wong, Takmeng; Allan, Richard; Slingo, Anthony; Kiehl, Jeffrey T.; Soden, Brian J.; Gordon, C. T.; Miller, Alvin J.; Yang, Shi-Keng; Randall, David R.;

Time Scales and Sources of European Temperature Variability

NASA Astrophysics Data System (ADS)

Årthun, Marius; Kolstad, Erik W.; Eldevik, Tor; Keenlyside, Noel S.

2018-04-01

Skillful predictions of continental climate would be of great practical benefit for society and stakeholders. It nevertheless remains fundamentally unresolved to what extent climate is predictable, for what features, at what time scales, and by which mechanisms. Here we identify the dominant time scales and sources of European surface air temperature (SAT) variability during the cold season using a coupled climate reanalysis, and a statistical method that estimates SAT variability due to atmospheric circulation anomalies. We find that eastern Europe is dominated by subdecadal SAT variability associated with the North Atlantic Oscillation, whereas interdecadal and multidecadal SAT variability over northern and southern Europe are thermodynamically driven by ocean temperature anomalies. Our results provide evidence that temperature anomalies in the North Atlantic Ocean are advected over land by the mean westerly winds and, hence, provide a mechanism through which ocean temperature controls the variability and provides predictability of European SAT.

New Perspectives on the Role of Internal Variability in Regional Climate Change and Climate Model Evaluation

NASA Astrophysics Data System (ADS)

Deser, C.

2017-12-01

Natural climate variability occurs over a wide range of time and space scales as a result of processes intrinsic to the atmosphere, the ocean, and their coupled interactions. Such internally generated climate fluctuations pose significant challenges for the identification of externally forced climate signals such as those driven by volcanic eruptions or anthropogenic increases in greenhouse gases. This challenge is exacerbated for regional climate responses evaluated from short (< 50 years) data records. The limited duration of the observations also places strong constraints on how well the spatial and temporal characteristics of natural climate variability are known, especially on multi-decadal time scales. The observational constraints, in turn, pose challenges for evaluation of climate models, including their representation of internal variability and assessing the accuracy of their responses to natural and anthropogenic radiative forcings. A promising new approach to climate model assessment is the advent of large (10-100 member) "initial-condition" ensembles of climate change simulations with individual models. Such ensembles allow for accurate determination, and straightforward separation, of externally forced climate signals and internal climate variability on regional scales. The range of climate trajectories in a given model ensemble results from the fact that each simulation represents a particular sequence of internal variability superimposed upon a common forced response. This makes clear that nature's single realization is only one of many that could have unfolded. This perspective leads to a rethinking of approaches to climate model evaluation that incorporate observational uncertainty due to limited sampling of internal variability. Illustrative examples across a range of well-known climate phenomena including ENSO, volcanic eruptions, and anthropogenic climate change will be discussed.

A Generalized Framework for Non-Stationary Extreme Value Analysis

NASA Astrophysics Data System (ADS)

Ragno, E.; Cheng, L.; Sadegh, M.; AghaKouchak, A.

2017-12-01

Empirical trends in climate variables including precipitation, temperature, snow-water equivalent at regional to continental scales are evidence of changes in climate over time. The evolving climate conditions and human activity-related factors such as urbanization and population growth can exert further changes in weather and climate extremes. As a result, the scientific community faces an increasing demand for updated appraisal of the time-varying climate extremes. The purpose of this study is to offer a robust and flexible statistical tool for non-stationary extreme value analysis which can better characterize the severity and likelihood of extreme climatic variables. This is critical to ensure a more resilient environment in a changing climate. Following the positive feedback on the first version of Non-Stationary Extreme Value Analysis (NEVA) Toolbox by Cheng at al. 2014, we present an improved version, i.e. NEVA2.0. The upgraded version herein builds upon a newly-developed hybrid evolution Markov Chain Monte Carlo (MCMC) approach for numerical parameters estimation and uncertainty assessment. This addition leads to a more robust uncertainty estimates of return levels, return periods, and risks of climatic extremes under both stationary and non-stationary assumptions. Moreover, NEVA2.0 is flexible in incorporating any user-specified covariate other than the default time-covariate (e.g., CO2 emissions, large scale climatic oscillation patterns). The new feature will allow users to examine non-stationarity of extremes induced by physical conditions that underlie the extreme events (e.g. antecedent soil moisture deficit, large-scale climatic teleconnections, urbanization). In addition, the new version offers an option to generate stationary and/or non-stationary rainfall Intensity - Duration - Frequency (IDF) curves that are widely used for risk assessment and infrastructure design. Finally, a Graphical User Interface (GUI) of the package is provided, making NEVA accessible to a broader audience.

Holocene multidecadal- to millennial-scale variations in Iceland-Scotland overflow and their relationship to climate

NASA Astrophysics Data System (ADS)

Mjell, Tor Lien; Ninnemann, Ulysses S.; Eldevik, Tor; Kleiven, Helga Kikki F.

2015-05-01

The Nordic Seas overflows are an important part of the Atlantic thermohaline circulation. While there is growing evidence that the overflow of dense water changed on orbital time scales during the Holocene, less is known about the variability on shorter time scales beyond the instrumental record. Here we reconstruct the relative changes in flow strength of Iceland-Scotland Overflow Water (ISOW), the eastern branch of the overflows, on multidecadal-millennial time scales. The reconstruction is based on mean sortable silt (SS>¯) from a sediment core on the Gardar Drift (60°19'N, 23°58'W, 2081 m). Our SS>¯ record reveals that the main variance in ISOW vigor occurred on millennial time scales (1-2 kyr) with particularly prominent fluctuations after 8 kyr. Superimposed on the millennial variability, there were multidecadal-centennial flow speed fluctuations during the early Holocene (10-9 kyr) and one prominent minimum at 0.9 kyr. We find a broad agreement between reconstructed ISOW and regional North Atlantic climate, where a strong (weak) ISOW is generally associated with warm (cold) climate. We further identify the possible contribution of anomalous heat and freshwater forcing, respectively, related to reconstructed overflow variability. We infer that ocean poleward heat transport can explain the relationship between regional climate and ISOW during the middle to late Holocene, whereas freshwater input provides a possible explanation for the reduced overflow during early Holocene (8-10 kyr).

Geodynamic contributions to global climatic change

NASA Technical Reports Server (NTRS)

Bills, Bruce G.

1992-01-01

Orbital and rotational variations perturb the latitudinal and seasonal pattern of incident solar radiation, producing major climatic change on time scales of 10(exp 4)-10(exp 6) years. The orbital variations are oblivious to internal structure and processes, but the rotational variations are not. A program of investigation whose objective would be to explore and quantify three aspects of orbital, rotational, and climatic interactions is described. An important premise of this investigation is the synergism between geodynamics and paleoclimate. Better geophysical models of precessional dynamics are needed in order to accurately reconstruct the radiative input to climate models. Some of the paleoclimate proxy records contain information relevant to solid Earth processes, on time scales which are difficult to constrain otherwise. Specific mechanisms which will be addressed include: (1) climatic consequences of deglacial polar motion; and (2) precessional and climatic consequences of glacially induced perturbations in the gravitational oblateness and partial decoupling of the mantle and core. The approach entails constructing theoretical models of the rotational, deformational, radiative, and climatic response of the Earth to known orbital perturbations, and comparing these with extensive records of paleoclimate proxy data. Several of the mechanisms of interest may participate in previously unrecognized feed-back loops in the climate dynamics system. A new algorithm for estimating climatically diagnostic locations and seasons from the paleoclimate time series is proposed.

Climate fails to predict wood decomposition at regional scales

NASA Astrophysics Data System (ADS)

Bradford, Mark A.; Warren, Robert J., II; Baldrian, Petr; Crowther, Thomas W.; Maynard, Daniel S.; Oldfield, Emily E.; Wieder, William R.; Wood, Stephen A.; King, Joshua R.

2014-07-01

Decomposition of organic matter strongly influences ecosystem carbon storage. In Earth-system models, climate is a predominant control on the decomposition rates of organic matter. This assumption is based on the mean response of decomposition to climate, yet there is a growing appreciation in other areas of global change science that projections based on mean responses can be irrelevant and misleading. We test whether climate controls on the decomposition rate of dead wood--a carbon stock estimated to represent 73 +/- 6 Pg carbon globally--are sensitive to the spatial scale from which they are inferred. We show that the common assumption that climate is a predominant control on decomposition is supported only when local-scale variation is aggregated into mean values. Disaggregated data instead reveal that local-scale factors explain 73% of the variation in wood decomposition, and climate only 28%. Further, the temperature sensitivity of decomposition estimated from local versus mean analyses is 1.3-times greater. Fundamental issues with mean correlations were highlighted decades ago, yet mean climate-decomposition relationships are used to generate simulations that inform management and adaptation under environmental change. Our results suggest that to predict accurately how decomposition will respond to climate change, models must account for local-scale factors that control regional dynamics.

Reconstruction of Past Mediterranean Climate

NASA Astrophysics Data System (ADS)

García-Herrera, Ricardo; Luterbacher, Jürg; Lionello, Piero; Gonzáles-Rouco, Fidel; Ribera, Pedro; Rodó, Xavier; Kull, Christoph; Zerefos, Christos

2007-02-01

First MEDCLIVAR Workshop on Reconstruction of Past Mediterranean Climate; Pablo de Olavide University, Carmona, Spain, 8-11 November 2006; Mediterranean Climate Variability and Predictability (MEDCLIVAR; http://www.medclivar.eu) is a program that coordinates and promotes research on different aspects of Mediterranean climate. The main MEDCLIVAR goals include the reconstruction of past climate, describing patterns and mechanisms characterizing climate space-time variability, extremes at different time and space scales, coupled climate model/empirical reconstruction comparisons, seasonal forecasting, and the identification of the forcings responsible for the observed changes. The program has been endorsed by CLIVAR (Climate Variability and Predictability project) and is funded by the European Science Foundation.

Orbital forcing of climate 1.4 billion years ago.

PubMed

Zhang, Shuichang; Wang, Xiaomei; Hammarlund, Emma U; Wang, Huajian; Costa, M Mafalda; Bjerrum, Christian J; Connelly, James N; Zhang, Baomin; Bian, Lizeng; Canfield, Donald E

2015-03-24

Fluctuating climate is a hallmark of Earth. As one transcends deep into Earth time, however, both the evidence for and the causes of climate change become difficult to establish. We report geochemical and sedimentological evidence for repeated, short-term climate fluctuations from the exceptionally well-preserved ∼1.4-billion-year-old Xiamaling Formation of the North China Craton. We observe two patterns of climate fluctuations: On long time scales, over what amounts to tens of millions of years, sediments of the Xiamaling Formation record changes in geochemistry consistent with long-term changes in the location of the Xiamaling relative to the position of the Intertropical Convergence Zone. On shorter time scales, and within a precisely calibrated stratigraphic framework, cyclicity in sediment geochemical dynamics is consistent with orbital control. In particular, sediment geochemical fluctuations reflect what appear to be orbitally forced changes in wind patterns and ocean circulation as they influenced rates of organic carbon flux, trace metal accumulation, and the source of detrital particles to the sediment.

Assessing global vegetation activity using spatio-temporal Bayesian modelling

NASA Astrophysics Data System (ADS)

Mulder, Vera L.; van Eck, Christel M.; Friedlingstein, Pierre; Regnier, Pierre A. G.

2016-04-01

This work demonstrates the potential of modelling vegetation activity using a hierarchical Bayesian spatio-temporal model. This approach allows modelling changes in vegetation and climate simultaneous in space and time. Changes of vegetation activity such as phenology are modelled as a dynamic process depending on climate variability in both space and time. Additionally, differences in observed vegetation status can be contributed to other abiotic ecosystem properties, e.g. soil and terrain properties. Although these properties do not change in time, they do change in space and may provide valuable information in addition to the climate dynamics. The spatio-temporal Bayesian models were calibrated at a regional scale because the local trends in space and time can be better captured by the model. The regional subsets were defined according to the SREX segmentation, as defined by the IPCC. Each region is considered being relatively homogeneous in terms of large-scale climate and biomes, still capturing small-scale (grid-cell level) variability. Modelling within these regions is hence expected to be less uncertain due to the absence of these large-scale patterns, compared to a global approach. This overall modelling approach allows the comparison of model behavior for the different regions and may provide insights on the main dynamic processes driving the interaction between vegetation and climate within different regions. The data employed in this study encompasses the global datasets for soil properties (SoilGrids), terrain properties (Global Relief Model based on SRTM DEM and ETOPO), monthly time series of satellite-derived vegetation indices (GIMMS NDVI3g) and climate variables (Princeton Meteorological Forcing Dataset). The findings proved the potential of a spatio-temporal Bayesian modelling approach for assessing vegetation dynamics, at a regional scale. The observed interrelationships of the employed data and the different spatial and temporal trends support our hypothesis. That is, the change of vegetation in space and time may be better understood when modelling vegetation change as both a dynamic and multivariate process. Therefore, future research will focus on a multivariate dynamical spatio-temporal modelling approach. This ongoing research is performed within the context of the project "Global impacts of hydrological and climatic extremes on vegetation" (project acronym: SAT-EX) which is part of the Belgian research programme for Earth Observation Stereo III.

Climate Information Responding to User Needs (CIRUN)

NASA Astrophysics Data System (ADS)

Busalacchi, A. J.

2009-05-01

For the past several decades many different US agencies have been involved in collecting Earth observations, e.g., NASA, NOAA, DoD, USGS, USDA. More recently, the US has led the international effort to design a Global Earth Observation System of Systems (GEOSS). Yet, there has been little substantive progress at the synthesis and integration of the various research and operational, space-based and in situ, observations. Similarly, access to such a range of observations across the atmosphere, ocean, and land surface remains fragmented. With respect to prediction of the Earth System, the US has not developed a comprehensive strategy. For climate, the US (e.g., NOAA, NASA, DoE) has taken a two-track strategy. At the more immediate time scale, coupled ocean-atmosphere models of the physical climate system have built upon the tradition of daily numerical weather prediction in order to extend the forecast window to seasonal to interannual times scales. At the century time scale, the nascent development of Earth System models, combining components of the physical climate system with biogeochemical cycles, are being used to provide future climate change projections in response to anticipated greenhouse gas forcings. Between these to two approaches to prediction lies a key deficiency of interest to decision makers, especially as it pertains to adaptation, i.e., deterministic prediction of the Earth System at time scales from days to decades with spatial scales from global to regional. One of many obstacles to be overcome is the design of present day observation and prediction products based on user needs. To date, most of such products have evolved from the technology and research "push" rather than the user or stakeholder "pull". In the future as planning proceeds for a national climate service, emphasis must be given to a more coordinated approach in which stakeholders' needs help design future Earth System observational and prediction products, and similarly, such products need to be tailored to provide decision support.

Do GCM's predict the climate.... Or the low frequency weather?

NASA Astrophysics Data System (ADS)

Lovejoy, S.; Schertzer, D.; Varon, D.

2012-04-01

Over twenty-five years ago, a three-regime scaling model was proposed describing the statistical variability of the atmosphere over time scales ranging from weather scales out to ≈ 100 kyrs. Using modern in situ data reanalyses, monthly surface series (at 5ox5o), 8 "multiproxy" (yearly) series of the Northern hemisphere from 1500 - 1980, and GRIP and Vostok paleotemperatures at 5.2 and ≈ 100 year resolutions (over the past 91-420 kyrs), we refine the model and show how it can be understood with the help of new developments in nonlinear dynamics, especially multifractals and cascades. In a scaling range, mean fluctuations in state variables such as temperature ΔT vary in power law manners ≈ Δt**H the where Δt is the duration. At small (weather) scales the fluctuation exponents are generally H>0; they grow with scale (Δt). At longer scales Δt >τw (≈ 10 days) H changes sign, the fluctuations decrease with scale; this is the low variability, "low frequency weather" regime. In this regime, the spectrum is a relatively flat "plateau", it's variability is low, stable, corresponding to our usual idea of "long term weather statistics". Finally for longer times, Δt>τc ≈ 10 - 100 years, once again H>0, so that the variability increases with scale: the true climate regime. These scaling regimes allow us to objectively define the weather as fluctuations over periods <τw, to define "climate states" as fluctuations at scale τc and then "climate change" as the fluctuations at longer periods (Δt>τc). We show that the intermediate low frequency weather regime is the result of the weather regime undergoing a "dimensional transition": at temporal scales longer than the typical lifetime of planetary structures (τw), the spatial degrees of freedom are rapidly quenched so that only the temporal degrees of freedom are important. This low frequency weather regime has statistical properties well reproduced not only by stochastic cascade models of weather, but also by control runs (i.e. without climate forcing) of GCM based climate forecasting systems including those of the Institut Pierre Simon Laplace (Paris) and the Earth Forecasting System (Hamburg). In order for these systems to go beyond simply predicting low frequency weather i.e. in order for them to predict the climate, they need appropriate climate forcings and/ or new internal mechanisms of variability. Using statistical scaling techniques we examine the scale dependence of fluctuations from forced and unforced GCM outputs, including from the ECHO-G and EFS simulations in the Millenium climate reconstruction project and compare this with data, multiproxies and paleo data. Our general conclusion is that the models systematically underestimate the multidecadal, multicentennial scale variability.

Coordinated Approaches to Quantify Long-Term Ecosystem dynamics in Response to Global Change

USDA-ARS?s Scientific Manuscript database

Climate change and its impact on ecosystems are usually assessed at decadal and century time scales. Ecological responses to climate change at those scales are strongly regulated by long-term processes, such as changes in species composition, carbon dynamics in soil and by big trees, and nutrient r...

Influences of Regional Climate Change on Air Quality Across the Continental U.S. Projected from Downscaling IPCC AR5 Simulations. Chapter 2

NASA Technical Reports Server (NTRS)

Nolte, Christopher; Otte, Tanya; Pinder, Robert; Bowden, J.; Herwehe, J.; Faluvegi, Gregory; Shindell, Drew

2013-01-01

Projecting climate change scenarios to local scales is important for understanding, mitigating, and adapting to the effects of climate change on society and the environment. Many of the global climate models (GCMs) that are participating in the Intergovernmental Panel on Climate Change (IPCC) Fifth Assessment Report (AR5) do not fully resolve regional-scale processes and therefore cannot capture regional-scale changes in temperatures and precipitation. We use a regional climate model (RCM) to dynamically downscale the GCM's large-scale signal to investigate the changes in regional and local extremes of temperature and precipitation that may result from a changing climate. In this paper, we show preliminary results from downscaling the NASA/GISS ModelE IPCC AR5 Representative Concentration Pathway (RCP) 6.0 scenario. We use the Weather Research and Forecasting (WRF) model as the RCM to downscale decadal time slices (1995-2005 and 2025-2035) and illustrate potential changes in regional climate for the continental U.S. that are projected by ModelE and WRF under RCP6.0. The regional climate change scenario is further processed using the Community Multiscale Air Quality modeling system to explore influences of regional climate change on air quality.

An effective online data monitoring and saving strategy for large-scale climate simulations

DOE Office of Scientific and Technical Information (OSTI.GOV)

Xian, Xiaochen; Archibald, Rick; Mayer, Benjamin

Large-scale climate simulation models have been developed and widely used to generate historical data and study future climate scenarios. These simulation models often have to run for a couple of months to understand the changes in the global climate over the course of decades. This long-duration simulation process creates a huge amount of data with both high temporal and spatial resolution information; however, how to effectively monitor and record the climate changes based on these large-scale simulation results that are continuously produced in real time still remains to be resolved. Due to the slow process of writing data to disk,more » the current practice is to save a snapshot of the simulation results at a constant, slow rate although the data generation process runs at a very high speed. This study proposes an effective online data monitoring and saving strategy over the temporal and spatial domains with the consideration of practical storage and memory capacity constraints. Finally, our proposed method is able to intelligently select and record the most informative extreme values in the raw data generated from real-time simulations in the context of better monitoring climate changes.« less

An effective online data monitoring and saving strategy for large-scale climate simulations

DOE PAGES

Xian, Xiaochen; Archibald, Rick; Mayer, Benjamin; ...

2018-01-22

Large-scale climate simulation models have been developed and widely used to generate historical data and study future climate scenarios. These simulation models often have to run for a couple of months to understand the changes in the global climate over the course of decades. This long-duration simulation process creates a huge amount of data with both high temporal and spatial resolution information; however, how to effectively monitor and record the climate changes based on these large-scale simulation results that are continuously produced in real time still remains to be resolved. Due to the slow process of writing data to disk,more » the current practice is to save a snapshot of the simulation results at a constant, slow rate although the data generation process runs at a very high speed. This study proposes an effective online data monitoring and saving strategy over the temporal and spatial domains with the consideration of practical storage and memory capacity constraints. Finally, our proposed method is able to intelligently select and record the most informative extreme values in the raw data generated from real-time simulations in the context of better monitoring climate changes.« less

Impacts of climate change on the future of biodiversity.

PubMed

Bellard, Céline; Bertelsmeier, Cleo; Leadley, Paul; Thuiller, Wilfried; Courchamp, Franck

2012-04-01

Many studies in recent years have investigated the effects of climate change on the future of biodiversity. In this review, we first examine the different possible effects of climate change that can operate at individual, population, species, community, ecosystem and biome scales, notably showing that species can respond to climate change challenges by shifting their climatic niche along three non-exclusive axes: time (e.g. phenology), space (e.g. range) and self (e.g. physiology). Then, we present the principal specificities and caveats of the most common approaches used to estimate future biodiversity at global and sub-continental scales and we synthesise their results. Finally, we highlight several challenges for future research both in theoretical and applied realms. Overall, our review shows that current estimates are very variable, depending on the method, taxonomic group, biodiversity loss metrics, spatial scales and time periods considered. Yet, the majority of models indicate alarming consequences for biodiversity, with the worst-case scenarios leading to extinction rates that would qualify as the sixth mass extinction in the history of the earth. © 2012 Blackwell Publishing Ltd/CNRS.

Impacts of climate change on the future of biodiversity

PubMed Central

Leadley, Paul; Thuiller, Wilfried; Courchamp, Franck

2013-01-01

Many studies in recent years have investigated the effects of climate change on the future of biodiversity. In this review, we first examine the different possible effects of climate change that can operate at individual, population, species, community, ecosystem and biome scales, notably showing that species can respond to climate change challenges by shifting their climatic niche along three non-exclusive axes: time (e.g., phenology), space (e.g., range) and self (e.g., physiology). Then, we present the principal specificities and caveats of the most common approaches used to estimate future biodiversity at global and sub-continental scales and we synthesize their results. Finally, we highlight several challenges for future research both in theoretical and applied realms. Overall, our review shows that current estimates are very variable, depending on the method, taxonomic group, biodiversity loss metrics, spatial scales and time periods considered. Yet, the majority of models indicate alarming consequences for biodiversity, with the worst-case scenarios leading to extinction rates that would qualify as the sixth mass extinction in the history of the earth. PMID:22257223

CPC - Monitoring & Data: Rest of the World Climate Data

Science.gov Websites

produces maps and time series for precipitation and surface temperatures for Africa, Asia, Europe, South - The CPC monitors weather and climate in real time with the aid of satellite animations, conventional , intraseasonal, seasonal and annual time scales are highlighted. The CPC also collects time series of accumulated

Exploring the impact of climate variability during the Last Glacial Maximum on the pattern of human occupation of Iberia.

PubMed

Burke, Ariane; Levavasseur, Guillaume; James, Patrick M A; Guiducci, Dario; Izquierdo, Manuel Arturo; Bourgeon, Lauriane; Kageyama, Masa; Ramstein, Gilles; Vrac, Mathieu

2014-08-01

The Last Glacial Maximum (LGM) was a global climate event, which had significant repercussions for the spatial distribution and demographic history of prehistoric populations. In Eurasia, the LGM coincides with a potential bottleneck for modern humans and may mark the divergence date for Asian and European populations (Keinan et al., 2007). In this research, the impact of climate variability on human populations in the Iberian Peninsula during the Last Glacial Maximum (LGM) is examined with the aid of downscaled high-resolution (16 × 16 km) numerical climate experiments. Human sensitivity to short time-scale (inter-annual) climate variability during this key time period, which follows the initial modern human colonisation of Eurasia and the extinction of the Neanderthals, is tested using the spatial distribution of archaeological sites. Results indicate that anatomically modern human populations responded to small-scale spatial patterning in climate variability, specifically inter-annual variability in precipitation levels as measured by the standard precipitation index. Climate variability at less than millennial scale, therefore, is shown to be an important component of ecological risk, one that played a role in regulating the spatial behaviour of prehistoric human populations and consequently affected their social networks. Copyright © 2014 Elsevier Ltd. All rights reserved.

Regional Climate Change across the Continental U.S. Projected from Downscaling IPCC AR5 Simulations

NASA Astrophysics Data System (ADS)

Otte, T. L.; Nolte, C. G.; Otte, M. J.; Pinder, R. W.; Faluvegi, G.; Shindell, D. T.

2011-12-01

Projecting climate change scenarios to local scales is important for understanding and mitigating the effects of climate change on society and the environment. Many of the general circulation models (GCMs) that are participating in the Intergovernmental Panel on Climate Change (IPCC) Fifth Assessment Report (AR5) do not fully resolve regional-scale processes and therefore cannot capture local changes in temperature and precipitation extremes. We seek to project the GCM's large-scale climate change signal to the local scale using a regional climate model (RCM) by applying dynamical downscaling techniques. The RCM will be used to better understand the local changes of temperature and precipitation extremes that may result from a changing climate. Preliminary results from downscaling NASA/GISS ModelE simulations of the IPCC AR5 Representative Concentration Pathway (RCP) scenario 6.0 will be shown. The Weather Research and Forecasting (WRF) model will be used as the RCM to downscale decadal time slices for ca. 2000 and ca. 2030 and illustrate potential changes in regional climate for the continental U.S. that are projected by ModelE and WRF under RCP6.0.

The joint space-time statistics of macroweather precipitation, space-time statistical factorization and macroweather models

DOE Office of Scientific and Technical Information (OSTI.GOV)

Lovejoy, S., E-mail: lovejoy@physics.mcgill.ca; Lima, M. I. P. de; Department of Civil Engineering, University of Coimbra, 3030-788 Coimbra

2015-07-15

Over the range of time scales from about 10 days to 30–100 years, in addition to the familiar weather and climate regimes, there is an intermediate “macroweather” regime characterized by negative temporal fluctuation exponents: implying that fluctuations tend to cancel each other out so that averages tend to converge. We show theoretically and numerically that macroweather precipitation can be modeled by a stochastic weather-climate model (the Climate Extended Fractionally Integrated Flux, model, CEFIF) first proposed for macroweather temperatures and we show numerically that a four parameter space-time CEFIF model can approximately reproduce eight or so empirical space-time exponents. In spitemore » of this success, CEFIF is theoretically and numerically difficult to manage. We therefore propose a simplified stochastic model in which the temporal behavior is modeled as a fractional Gaussian noise but the spatial behaviour as a multifractal (climate) cascade: a spatial extension of the recently introduced ScaLIng Macroweather Model, SLIMM. Both the CEFIF and this spatial SLIMM model have a property often implicitly assumed by climatologists that climate statistics can be “homogenized” by normalizing them with the standard deviation of the anomalies. Physically, it means that the spatial macroweather variability corresponds to different climate zones that multiplicatively modulate the local, temporal statistics. This simplified macroweather model provides a framework for macroweather forecasting that exploits the system's long range memory and spatial correlations; for it, the forecasting problem has been solved. We test this factorization property and the model with the help of three centennial, global scale precipitation products that we analyze jointly in space and in time.« less

Impact of Desiccation of Aral Sea on the Regional Climate of Central Asia Using WRF Model

NASA Astrophysics Data System (ADS)

Sharma, Ashish; Huang, Huei-Ping; Zavialov, Peter; Khan, Valentina

2018-01-01

This study explores the impacts of the desiccation of the Aral Sea and large-scale climate change on the regional climate of Central Asia in the post-1960 era. A series of climate downscaling experiments for the 1960's and 2000's decades were performed using the Weather Research and Forecast model at 12-km horizontal resolution. To quantify the impacts of the changing surface boundary condition, a set of simulations with an identical lateral boundary condition but different extents of the Aral Sea were performed. It was found that the desiccation of the Aral Sea leads to more snow (and less rain) as desiccated winter surface is relatively much colder than water surface. In summer, desiccation led to substantial warming over the Aral Sea. These impacts were largely confined to within the area covered by the former Aral Sea and its immediate vicinity, although desiccation of the Sea also led to minor cooling over the greater Central Asia in winter. A contrasting set of simulations with an identical surface boundary condition but different lateral boundary conditions produced more identifiable changes in regional climate over the greater Central Asia which was characterized by a warming trend in both winter and summer. Simulations also showed that while the desiccation of the Aral Sea has significant impacts on the local climate over the Sea, the climate over the greater Central Asia on inter-decadal time scale was more strongly influenced by the continental or global-scale climate change on that time scale.

Reconstruction of late Holocene climate based on tree growth and mechanistic hierarchical models

USGS Publications Warehouse

Tipton, John; Hooten, Mevin B.; Pederson, Neil; Tingley, Martin; Bishop, Daniel

2016-01-01

Reconstruction of pre-instrumental, late Holocene climate is important for understanding how climate has changed in the past and how climate might change in the future. Statistical prediction of paleoclimate from tree ring widths is challenging because tree ring widths are a one-dimensional summary of annual growth that represents a multi-dimensional set of climatic and biotic influences. We develop a Bayesian hierarchical framework using a nonlinear, biologically motivated tree ring growth model to jointly reconstruct temperature and precipitation in the Hudson Valley, New York. Using a common growth function to describe the response of a tree to climate, we allow for species-specific parameterizations of the growth response. To enable predictive backcasts, we model the climate variables with a vector autoregressive process on an annual timescale coupled with a multivariate conditional autoregressive process that accounts for temporal correlation and cross-correlation between temperature and precipitation on a monthly scale. Our multi-scale temporal model allows for flexibility in the climate response through time at different temporal scales and predicts reasonable climate scenarios given tree ring width data.

AIRS-Observed Interrelationships of Anomaly Time-Series of Moist Process-Related Parameters and Inferred Feedback Values on Various Spatial Scales

NASA Technical Reports Server (NTRS)

Molnar, Gyula I.; Susskind, Joel; Iredell, Lena

2011-01-01

In the beginning, a good measure of a GMCs performance was their ability to simulate the observed mean seasonal cycle. That is, a reasonable simulation of the means (i.e., small biases) and standard deviations of TODAY?S climate would suffice. Here, we argue that coupled GCM (CG CM for short) simulations of FUTURE climates should be evaluated in much more detail, both spatially and temporally. Arguably, it is not the bias, but rather the reliability of the model-generated anomaly time-series, even down to the [C]GCM grid-scale, which really matter. This statement is underlined by the social need to address potential REGIONAL climate variability, and climate drifts/changes in a manner suitable for policy decisions.

Assessment of regional climate change and development of climate adaptation decision aids in the Southwestern US

NASA Astrophysics Data System (ADS)

Darmenova, K.; Higgins, G.; Kiley, H.; Apling, D.

2010-12-01

Current General Circulation Models (GCMs) provide a valuable estimate of both natural and anthropogenic climate changes and variability on global scales. At the same time, future climate projections calculated with GCMs are not of sufficient spatial resolution to address regional needs. Many climate impact models require information at scales of 50 km or less, so dynamical downscaling is often used to estimate the smaller-scale information based on larger scale GCM output. To address current deficiencies in local planning and decision making with respect to regional climate change, our research is focused on performing a dynamical downscaling with the Weather Research and Forecasting (WRF) model and developing decision aids that translate the regional climate data into actionable information for users. Our methodology involves development of climatological indices of extreme weather and heating/cooling degree days based on WRF ensemble runs initialized with the NCEP-NCAR reanalysis and the European Center/Hamburg Model (ECHAM5). Results indicate that the downscale simulations provide the necessary detailed output required by state and local governments and the private sector to develop climate adaptation plans. In addition we evaluated the WRF performance in long-term climate simulations over the Southwestern US and validated against observational datasets.

Are Madrean ecosystems approaching tipping points? Anticipating interactions of landscape disturbance and climate change

Treesearch

Donald A. Falk

2013-01-01

Contemporary climate change is driving transitions in many Madrean ecosystems, but the time scale of these changes is accelerated greatly by severe landscape disturbances such as wildfires and insect outbreaks. Landscape-scale disturbance events such as wildfires interact with prior disturbance patterns and landscape structure to catalyze abrupt transitions to novel...

On the relationship between large-scale climate modes and regional synoptic patterns that drive Victorian rainfall

NASA Astrophysics Data System (ADS)

Verdon-Kidd, D.; Kiem, A. S.

2008-10-01

In this paper regional (synoptic) and large-scale climate drivers of rainfall are investigated for Victoria, Australia. A non-linear classification methodology known as self-organizing maps (SOM) is used to identify 20 key regional synoptic patterns, which are shown to capture a range of significant synoptic features known to influence the climate of the region. Rainfall distributions are assigned to each of the 20 patterns for nine rainfall stations located across Victoria, resulting in a clear distinction between wet and dry synoptic types at each station. The influence of large-scale climate modes on the frequency and timing of the regional synoptic patterns is also investigated. This analysis revealed that phase changes in the El Niño Southern Oscillation (ENSO), the Southern Annular Mode (SAM) and/or Indian Ocean Dipole (IOD) are associated with a shift in the relative frequency of wet and dry synoptic types. Importantly, these results highlight the potential to utilise the link between the regional synoptic patterns derived in this study and large-scale climate modes to improve rainfall forecasting for Victoria, both in the short- (i.e. seasonal) and long-term (i.e. decadal/multi-decadal scale). In addition, the regional and large-scale climate drivers identified in this study provide a benchmark by which the performance of Global Climate Models (GCMs) may be assessed.

The East Asian Jet Stream and Asian-Pacific-American Climate

NASA Technical Reports Server (NTRS)

Yang, Song; Lau, K.-M.; Kim, K.-M.

2000-01-01

The upper-tropospheric westerly jet stream over subtropical East Asia and western Pacific, often referred to as East Asian Jet (EAJ), is an important atmospheric circulation system in the Asian-Pacific-American (APA) region during winter. It is characterized by variabilities on a wide range of time scales and exerts a strong impact on the weather and climate of the region. On the synoptic scale, the jet stream is closely linked to many phenomena such as cyclogenesis, frontogenesis, blocking, storm track activity, and the development of other atmospheric disturbances. On the seasonal time scale, the variation of the EAJ determines many characteristics of the seasonal transition of the atmospheric circulation especially over East Asia. The variabilities of the EAJ on these time scales have been relatively well documented. It has also been understood since decades ago that the interannual. variability of the EAJ is associated with many climate signals in the APA region. These signals include the persistent anomalies of the East Asian winter monsoon and the changes in diabatic heating and in the Hadley circulation. However, many questions remain for the year-to-year variabilities of the EAJ and their relation to the APA climate. For example, what is the relationship between the EAJ and El Nino/Southern Oscillation (ENSO)? Will the EAJ and ENSO play different roles in modulating the APA climate? How is the jet stream linked to the non-ENSO-related sea surface temperature (SST) anomalies and to the Pacific/North American (PNA) teleconnection pattern?

Drought Predictability and Prediction in a Changing Climate: Assessing Current Predictive Knowledge and Capabilities, User Requirements and Research Priorities

NASA Technical Reports Server (NTRS)

Schubert, Siegfried

2011-01-01

Drought is fundamentally the result of an extended period of reduced precipitation lasting anywhere from a few weeks to decades and even longer. As such, addressing drought predictability and prediction in a changing climate requires foremost that we make progress on the ability to predict precipitation anomalies on subseasonal and longer time scales. From the perspective of the users of drought forecasts and information, drought is however most directly viewed through its impacts (e.g., on soil moisture, streamflow, crop yields). As such, the question of the predictability of drought must extend to those quantities as well. In order to make progress on these issues, the WCRP drought information group (DIG), with the support of WCRP, the Catalan Institute of Climate Sciences, the La Caixa Foundation, the National Aeronautics and Space Administration, the National Oceanic and Atmospheric Administration, and the National Science Foundation, has organized a workshop to focus on: 1. User requirements for drought prediction information on sub-seasonal to centennial time scales 2. Current understanding of the mechanisms and predictability of drought on sub-seasonal to centennial time scales 3. Current drought prediction/projection capabilities on sub-seasonal to centennial time scales 4. Advancing regional drought prediction capabilities for variables and scales most relevant to user needs on sub-seasonal to centennial time scales. This introductory talk provides an overview of these goals, and outlines the occurrence and mechanisms of drought world-wide.

Testing a growth efficiency hypothesis with continental-scale phenological variations of common and cloned plants.

PubMed

Liang, Liang; Schwartz, Mark D

2014-10-01

Variation in the timing of plant phenology caused by phenotypic plasticity is a sensitive measure of how organisms respond to weather and climate variability. Although continental-scale gradients in climate and consequential patterns in plant phenology are well recognized, the contribution of underlying genotypic difference to the geography of phenology is less well understood. We hypothesize that different temperate plant genotypes require varying amount of heat energy for resuming annual growth and reproduction as a result of adaptation and other ecological and evolutionary processes along climatic gradients. In particular, at least for some species, the growing degree days (GDD) needed to trigger the same spring phenology events (e.g., budburst and flower bloom) may be less for individuals originated from colder climates than those from warmer climates. This variable intrinsic heat energy requirement in plants can be characterized by the term growth efficiency and is quantitatively reflected in the timing of phenophases-earlier timing indicates higher efficiency (i.e., less heat energy needed to trigger phenophase transitions) and vice versa compared to a standard reference (i.e., either a uniform climate or a uniform genotype). In this study, we tested our hypothesis by comparing variations of budburst and bloom timing of two widely documented plants from the USA National Phenology Network (i.e., red maple-Acer rubrum and forsythia-Forsythia spp.) with cloned indicator plants (lilac-Syringa x chinensis 'Red Rothomagensis') at multiple eastern US sites. Our results indicate that across the accumulated temperature gradient, the two non-clonal plants showed significantly more gradual changes than the cloned plants, manifested by earlier phenology in colder climates and later phenology in warmer climates relative to the baseline clone phenological response. This finding provides initial evidence supporting the growth efficiency hypothesis, and suggests more work is warranted. More studies investigating genotype-determined phenological variations will be useful for better understanding and prediction of the continental-scale patterns of biospheric responses to climate change.

Information transfer across the scales of climate data variability

NASA Astrophysics Data System (ADS)

Palus, Milan; Jajcay, Nikola; Hartman, David; Hlinka, Jaroslav

2015-04-01

Multitude of scales characteristic of the climate system variability requires innovative approaches in analysis of instrumental time series. We present a methodology which starts with a wavelet decomposition of a multi-scale signal into quasi-oscillatory modes of a limited band-with, described using their instantaneous phases and amplitudes. Then their statistical associations are tested in order to search for interactions across time scales. In particular, an information-theoretic formulation of the generalized, nonlinear Granger causality is applied together with surrogate data testing methods [1]. The method [2] uncovers causal influence (in the Granger sense) and information transfer from large-scale modes of climate variability with characteristic time scales from years to almost a decade to regional temperature variability on short time scales. In analyses of daily mean surface air temperature from various European locations an information transfer from larger to smaller scales has been observed as the influence of the phase of slow oscillatory phenomena with periods around 7-8 years on amplitudes of the variability characterized by smaller temporal scales from a few months to annual and quasi-biennial scales [3]. In sea surface temperature data from the tropical Pacific area an influence of quasi-oscillatory phenomena with periods around 4-6 years on the variability on and near the annual scale has been observed. This study is supported by the Ministry of Education, Youth and Sports of the Czech Republic within the Program KONTAKT II, Project No. LH14001. [1] M. Palus, M. Vejmelka, Phys. Rev. E 75, 056211 (2007) [2] M. Palus, Entropy 16(10), 5263-5289 (2014) [3] M. Palus, Phys. Rev. Lett. 112, 078702 (2014)

The Mediterranean Plio-Pleistocene: A reference frame for astronomically paced low and high latitude climate changes (Jean Baptiste Lamarck Medal Lecture)

NASA Astrophysics Data System (ADS)

Lourens, Lucas

2016-04-01

The astronomical theory of climate has revolutionized our understanding of past climate change and the development of highly accurate geologic time scales for the entire Cenozoic. Most of this understanding has started with the construction of high-resolution stable oxygen isotope (18O) records from planktonic and benthic foraminifera of open ocean deep marine sediments explored by the international drilling operations of DSDP, ODP and IODP. These efforts culminated into global ocean isotopic stacked records, which give a clear picture of the evolution of the climate state through time. Fundamental for these reconstructions are the assumptions made between the astronomical forcing and the tuned time series and the accuracy of the astronomical solution. In the past decades, an astronomically calibrated time scale for the Pliocene and Pleistocene of the Mediterranean has been developed, which has become the reference for the standard Geologic Time Scale. Characteristic of the studied marine sediments are the cyclic lithological alternations, reflecting the interference between obliquity and precession-paced low latitude climate variability. These interference patterns allowed to evaluate the accuracy of astronomical solutions and to constrain the dynamical ellipticity of the Earth and tidal dissipation by the Sun and the Moon, which in turn provided the backbone for the widely applied LR04 open ocean benthic isotope stack of the past 5 Myr. So far, the assumed time lags between orbital forcing and the global climate response as reflected in LR04 have not been tested, while these assumptions hark back to SPECMAP, using simple ice sheet models and a limited number of radiometric dates. In addition, LR04 adopted a shorter response time for the smaller ice caps during the Pliocene. Here I present the first benthic 18O record of the Mediterranean reference scale, which strikingly mirrors the LR04. I will use this record to discuss the assumed phase relations and its potential to constrain global sea level changes and their cause over the past 5.3 million years.

Fine-scale variability in growth-climate relationships of Douglas-fir, North Cascade Range, Washington.

Treesearch

Michael J. Case; David L. Peterson

2005-01-01

Information about the sensitivity to climate of Douglas-fir (Pseudotsuga menziesii (Mirb.) Franco) is valuable because it will allow forest managers to maximize growth, better understand how carbon sequestration may change over time, and better model and predict future ecosystem responses to climatic change. We examined the effects of climatic...

Global assessment of experimental climate warming on tundra vegetation: heterogeneity over space and time

Treesearch

Sarah C. Elmendorf; Gregory H.R. Henry; Robert D. Hollister; Robert G. Björk; Anne D. Bjorkman; Terry V. Callaghan; [and others] NO-VALUE; William Gould; Joel Mercado

2012-01-01

Understanding the sensitivity of tundra vegetation to climate warming is critical to forecasting future biodiversity and vegetation feedbacks to climate. In situ warming experiments accelerate climate change on a small scale to forecast responses of local plant communities. Limitations of this approach include the apparent site-specificity of results and uncertainty...

Continent-scale global change attribution in European birds - combining annual and decadal time scales.

PubMed

Jørgensen, Peter Søgaard; Böhning-Gaese, Katrin; Thorup, Kasper; Tøttrup, Anders P; Chylarecki, Przemysław; Jiguet, Frédéric; Lehikoinen, Aleksi; Noble, David G; Reif, Jiri; Schmid, Hans; van Turnhout, Chris; Burfield, Ian J; Foppen, Ruud; Voříšek, Petr; van Strien, Arco; Gregory, Richard D; Rahbek, Carsten

2016-02-01

Species attributes are commonly used to infer impacts of environmental change on multiyear species trends, e.g. decadal changes in population size. However, by themselves attributes are of limited value in global change attribution since they do not measure the changing environment. A broader foundation for attributing species responses to global change may be achieved by complementing an attributes-based approach by one estimating the relationship between repeated measures of organismal and environmental changes over short time scales. To assess the benefit of this multiscale perspective, we investigate the recent impact of multiple environmental changes on European farmland birds, here focusing on climate change and land use change. We analyze more than 800 time series from 18 countries spanning the past two decades. Analysis of long-term population growth rates documents simultaneous responses that can be attributed to both climate change and land-use change, including long-term increases in populations of hot-dwelling species and declines in long-distance migrants and farmland specialists. In contrast, analysis of annual growth rates yield novel insights into the potential mechanisms driving long-term climate induced change. In particular, we find that birds are affected by winter, spring, and summer conditions depending on the distinct breeding phenology that corresponds to their migratory strategy. Birds in general benefit from higher temperatures or higher primary productivity early on or in the peak of the breeding season with the largest effect sizes observed in cooler parts of species' climatic ranges. Our results document the potential of combining time scales and integrating both species attributes and environmental variables for global change attribution. We suggest such an approach will be of general use when high-resolution time series are available in large-scale biodiversity surveys. © 2015 John Wiley & Sons Ltd.

Plague and Climate: Scales Matter

PubMed Central

Ben Ari, Tamara; Neerinckx, Simon; Gage, Kenneth L.; Kreppel, Katharina; Laudisoit, Anne; Leirs, Herwig; Stenseth, Nils Chr.

2011-01-01

Plague is enzootic in wildlife populations of small mammals in central and eastern Asia, Africa, South and North America, and has been recognized recently as a reemerging threat to humans. Its causative agent Yersinia pestis relies on wild rodent hosts and flea vectors for its maintenance in nature. Climate influences all three components (i.e., bacteria, vectors, and hosts) of the plague system and is a likely factor to explain some of plague's variability from small and regional to large scales. Here, we review effects of climate variables on plague hosts and vectors from individual or population scales to studies on the whole plague system at a large scale. Upscaled versions of small-scale processes are often invoked to explain plague variability in time and space at larger scales, presumably because similar scale-independent mechanisms underlie these relationships. This linearity assumption is discussed in the light of recent research that suggests some of its limitations. PMID:21949648

Regional Climate Change across North America in 2030 Projected from RCP6.0

NASA Astrophysics Data System (ADS)

Otte, T.; Nolte, C. G.; Faluvegi, G.; Shindell, D. T.

2012-12-01

Projecting climate change scenarios to local scales is important for understanding and mitigating the effects of climate change on society and the environment. Many of the general circulation models (GCMs) that are participating in the Intergovernmental Panel on Climate Change (IPCC) Fifth Assessment Report (AR5) do not fully resolve regional-scale processes and therefore cannot capture local changes in temperature and precipitation extremes. We seek to project the GCM's large-scale climate change signal to the local scale using a regional climate model (RCM) by applying dynamical downscaling techniques. The RCM will be used to better understand the local changes of temperature and precipitation extremes that may result from a changing climate. In this research, downscaling techniques that we developed with historical data are now applied to GCM fields. Results from downscaling NASA/GISS ModelE2 simulations of the IPCC AR5 Representative Concentration Pathway (RCP) scenario 6.0 will be shown. The Weather Research and Forecasting (WRF) model has been used as the RCM to downscale decadal time slices for ca. 2000 and ca. 2030 over North America and illustrate potential changes in regional climate that are projected by ModelE2 and WRF under RCP6.0. The analysis focuses on regional climate fields that most strongly influence the interactions between climate change and air quality. In particular, an analysis of extreme temperature and precipitation events will be presented.

Assessing the Dynamic Effects of Climate on Individual Tree Growth Across Time and Space

NASA Astrophysics Data System (ADS)

Itter, M.; Finley, A. O.; D'Amato, A. W.; Foster, J. R.; Bradford, J. B.

2015-12-01

The relationship between climate variability and an ecosystem process, such as forest growth, is frequently not fixed over time, but changes due to complex interactions between unobserved ecological factors and the process of interest. Climate data and forecasts are frequently spatially and temporally misaligned with ecological observations making inference regarding the effects of climate on ecosystem processes particularly challenging. Here we develop a Bayesian dynamic hierarchical model for annual tree growth increment that allows the effects of climate to evolve over time, applies climate data at a spatial-temporal scale consistent with observations, and controls for individual-level variability commonly encountered in ecological datasets. The model is applied to individual tree data from northern Minnesota using a modified Thornthwaite-type water balance model to transform PRISM temperature and precipitation estimates to physiologically relevant values of actual and potential evapotranspiration (AET, PET), and climatic water deficit. Model results indicate that mean tree growth is most sensitive to AET during the growing season and PET and minimum temperature in the spring prior to growth. The effects of these variables on tree growth, however, are not stationary with significant effects observed in only a subset of years during the 111-year study period. Importantly, significant effects of climate do not result from anomalous climate observations, but follow from large growth deviations unexplained by tree age and size, and time since forest disturbance. Results differ markedly from alternative models that assume the effects of climate are stationary over time or apply climate estimates at the individual scale. Forecasts of future tree growth as a function of climate follow directly from the dynamic hierarchical model allowing for assessment of forest change. Current work is focused on extending the model framework to include regional climate and ecosystem effects for application to a larger tree growth dataset spanning a latitudinal gradient within the US from Maine to Florida.

The Use of Climate Projections in the Modelling of Bud Burst

NASA Astrophysics Data System (ADS)

O'Neill, Bridget F.; Caffara, Amelia; Gleeson, Emily; Semmler, Tido; McGrath, Ray; Donnelly, Alison

2010-05-01

Recent changes in global climate, such as increasing temperature, have had notable effects on the phenology (timing of biological events) of plants. The effects are variable across habitats and between species, but increasing temperatures have been shown to advance certain key phenophases of trees, such as bud burst (beginning of leaf unfolding). This project considered climate change impacts on phenology of plants at a local scale in Ireland. The output from the ENSEMBLES climate simulations were down-scaled to Ireland and utilised by a phenological model to project changes over the next 50-100 years. This project helps to showcase the potential use of climate simulations in phenological research.

The scaling of population persistence with carrying capacity does not asymptote in populations of a fish experiencing extreme climate variability.

PubMed

White, Richard S A; Wintle, Brendan A; McHugh, Peter A; Booker, Douglas J; McIntosh, Angus R

2017-06-14

Despite growing concerns regarding increasing frequency of extreme climate events and declining population sizes, the influence of environmental stochasticity on the relationship between population carrying capacity and time-to-extinction has received little empirical attention. While time-to-extinction increases exponentially with carrying capacity in constant environments, theoretical models suggest increasing environmental stochasticity causes asymptotic scaling, thus making minimum viable carrying capacity vastly uncertain in variable environments. Using empirical estimates of environmental stochasticity in fish metapopulations, we showed that increasing environmental stochasticity resulting from extreme droughts was insufficient to create asymptotic scaling of time-to-extinction with carrying capacity in local populations as predicted by theory. Local time-to-extinction increased with carrying capacity due to declining sensitivity to demographic stochasticity, and the slope of this relationship declined significantly as environmental stochasticity increased. However, recent 1 in 25 yr extreme droughts were insufficient to extirpate populations with large carrying capacity. Consequently, large populations may be more resilient to environmental stochasticity than previously thought. The lack of carrying capacity-related asymptotes in persistence under extreme climate variability reveals how small populations affected by habitat loss or overharvesting, may be disproportionately threatened by increases in extreme climate events with global warming. © 2017 The Author(s).

The Effect of Large Scale Climate Oscillations on the Land Surface Phenology of the Northern Polar Regions and Central Asia

NASA Astrophysics Data System (ADS)

de Beurs, K.; Henebry, G. M.; Owsley, B.; Sokolik, I. N.

2016-12-01

Land surface phenology metrics allow for the summarization of long image time series into a set of annual observations that describe the vegetated growing season. These metrics have been shown to respond to both large scale climatic and anthropogenic impacts. In this study we assemble a time series (2001 - 2014) of Moderate Resolution Imaging Spectroradiometer (MODIS) Nadir BRDF-Adjusted Reflectance data and land surface temperature data at 0.05º spatial resolution. We then derive land surface phenology metrics focusing on the peak of the growing season by fitting quadratic regression models using NDVI and Accumulated Growing Degree-Days (AGDD) derived from land surface temperature. We link the annual information on the peak timing, the thermal time to peak and the maximum of the growing season with five of the most important large scale climate oscillations: NAO, AO, PDO, PNA and ENSO. We demonstrate several significant correlations between the climate oscillations and the land surface phenology peak metrics for a range of different bioclimatic regions in both dryland Central Asia and the northern Polar Regions. We will then link the correlation results with trends derived by the seasonal Mann-Kendall trend detection method applied to several satellite derived vegetation and albedo datasets.

Centennial-scale winter climate variability over the last two millennia in the northern Gulf of Mexico based on paired δ18O and Mg/Ca in Globorotalia truncatulinoides

NASA Astrophysics Data System (ADS)

Fortiz, V.; Thirumalai, K.; Richey, J. N.; Quinn, T. M.

2014-12-01

We present a replicated record of paired foraminiferal δ18O and Mg/Ca variations in multi-cores collected from the Garrison Basin (26º43'N, 93º55'W) in the northern Gulf of Mexico (GOM). Using δ18O (sea surface temperature, SST; sea surface salinity, SSS proxy) and Mg/Ca (SST proxy) variations in non-encrusted planktic foraminifer Globorotalia truncatulinoides we produce time series spanning the last two millennia that is characterized by centennial-scale climate variability. We interpret geochemical variations in G. truncatulinoides to reflect winter climate variability because data from a sediment trap, located ~350 km east of the core site, reveal that annual flux of G. truncatulinoides is heavily weighted towards winter (peak production in January-February; Spear et al., 2011). Similar centennial-scale variability is also observed in the foraminiferal geochemistry of Globigerinoides ruber in the same multi-cores, which likely reflect mean annual climate variations. Our replicated results and comparisons to other SST reconstructions from the region lend confidence that the northern GOM surface ocean underwent large, centennial-scale variability, most likely dominated by changes in winter climate. This variability occurred in a time period where climate forcing is small and background conditions are similar to pre-industrial times. References: Spear, J.W.; Poore, R.Z., and Quinn, T.M., 2011, Globorotalia truncatulinoides (dextral) Mg/Ca as a proxy for Gulf of Mexico winter mixed-layer temperature: Evidence from a sediment trap in the northern Gulf of Mexico. Marine Micropaleontology, 80, 53-61.

An integrated, indicator framework for assessing large-scale variations and change in seasonal timing and phenology (Invited)

NASA Astrophysics Data System (ADS)

Betancourt, J. L.; Weltzin, J. F.

2013-12-01

As part of an effort to develop an Indicator System for the National Climate Assessment (NCA), the Seasonality and Phenology Indicators Technical Team (SPITT) proposed an integrated, continental-scale framework for understanding and tracking seasonal timing in physical and biological systems. The framework shares several metrics with the EPA's National Climate Change Indicators. The SPITT framework includes a comprehensive suite of national indicators to track conditions, anticipate vulnerabilities, and facilitate intervention or adaptation to the extent possible. Observed, modeled, and forecasted seasonal timing metrics can inform a wide spectrum of decisions on federal, state, and private lands in the U.S., and will be pivotal for international efforts to mitigation and adaptation. Humans use calendars both to understand the natural world and to plan their lives. Although the seasons are familiar concepts, we lack a comprehensive understanding of how variability arises in the timing of seasonal transitions in the atmosphere, and how variability and change translate and propagate through hydrological, ecological and human systems. For example, the contributions of greenhouse warming and natural variability to secular trends in seasonal timing are difficult to disentangle, including earlier spring transitions from winter (strong westerlies) to summer (weak easterlies) patterns of atmospheric circulation; shifts in annual phasing of daily temperature means and extremes; advanced timing of snow and ice melt and soil thaw at higher latitudes and elevations; and earlier start and longer duration of the growing and fire seasons. The SPITT framework aims to relate spatiotemporal variability in surface climate to (1) large-scale modes of natural climate variability and greenhouse gas-driven climatic change, and (2) spatiotemporal variability in hydrological, ecological and human responses and impacts. The hierarchical framework relies on ground and satellite observations, and includes metrics of surface climate seasonality, seasonality of snow and ice, land surface phenology, ecosystem disturbance seasonality, and organismal phenology. Recommended metrics met the following requirements: (a) easily measured by day-of-year, number of days, or in the case of species migrations, by the latitude of the observation on a given date; (b) are observed or can be calculated across a high density of locations in many different regions of the U.S.; and (c) unambiguously describe both spatial and temporal variability and trends in seasonal timing that are climatically driven. The SPITT framework is meant to provide climatic and strategic guidance for the growth and application of seasonal timing and phenological monitoring efforts. The hope is that additional national indicators based on observed phenology, or evidence-based algorithms calibrated with observational data, will evolve with sustained and broad-scale monitoring of climatically sensitive species and ecological processes.

Two Centuries of Climate Variability From a Gulf of Papua Coral Confirms a Coherent, Widespread Multidecadal Signal

NASA Astrophysics Data System (ADS)

Cole, J. E.; Lough, J.; Reed, E. V.; Schrag, D. P.

2016-12-01

The Indo-Pacific warm pool is intimately involved with large-scale climate variability on seasonal to secular time scales. The lack of long instrumental observations in this region has motivated paleoclimatic analyses using diverse proxy data sources. We present here new multicentury paleoclimate records from a Gulf of Papua coral that capture past variability with a Pacific-wide signature. We have developed stable isotope, Sr/Ca, skeletal density, and luminescence data from a coral core recovered at Bramble Cay, Australia (9°S, 144°E). The geochemical records span CE 1775-1993 and are dominated by low-frequency (decade-century scale) variability that is consistent with records from other proxies in the same region, and with other coral records from far-flung sites across the southwest Pacific. Unlike in many Pacific coral records, we observe no strong trend towards warmer conditions. Although skeletal density bands are clearly visible, they show inconsistent seasonal phasing with the geochemical tracers of sea surface temperature (SST; Sr/Ca and oxygen isotope content), and skeletal density does not correlate with these tracers on longer time scales. In this coral, density banding must be controlled by a more complex mix of internal and/or external factors. Luminescent banding and reconstructed salinity provide similar histories, suggesting a common hydroclimatic signal with significant variability at periods of decades and longer. The strong low-frequency behavior in these new climate records of SST and hydroclimate, from a remote region of the Indo-Pacific, confirms an important source of internal climate variability, on a poorly documented time scale, from a region with far-reaching climatic importance.

Climate change and social vicissitudes in China over the past two millennia

NASA Astrophysics Data System (ADS)

Yin, Jun; Su, Yun; Fang, Xiuqi

2016-09-01

The relation between climate change and historical rhythms has long been discussed. However, this type of study still faces the lack of high-resolution data concerning long-term socio-economic processes. In this study, we collected 1586 items of direct and proffered evidence from 29 Chinese history books. We used semantic analysis to reconstruct a quantitative series of the social vicissitudes of the past 2000 yr with a 10-yr resolution to express the phase transition of the social vicissitudes of the dynasties in China. Our reconstruction demonstrates that social vicissitudes have clear cyclical features on multiple time scales. Analysis of the association of social rise and fall with climate change indicates that temperature displayed more significant effects on social vicissitudes in the long term, while precipitation displayed more significant effects on the social vicissitudes in the short term. There are great overlaps between social and climatic variables around the predominant or periodic bands. Social rise mostly occurred in the centennial-scale warm periods, whereas social decline mostly occurred in the centennial-scale cold periods. Under warm-wet conditions, social rise occurred over 57% of the time; under cold-dry conditions, the social decline occurred over 66% of the time.

An abrupt centennial-scale drought event and mid-holocene climate change patterns in monsoon marginal zones of East Asia.

PubMed

Li, Yu; Wang, Nai'ang; Zhang, Chengqi

2014-01-01

The mid-latitudes of East Asia are characterized by the interaction between the Asian summer monsoon and the westerly winds. Understanding long-term climate change in the marginal regions of the Asian monsoon is critical for understanding the millennial-scale interactions between the Asian monsoon and the westerly winds. Abrupt climate events are always associated with changes in large-scale circulation patterns; therefore, investigations into abrupt climate changes provide clues for responses of circulation patterns to extreme climate events. In this paper, we examined the time scale and mid-Holocene climatic background of an abrupt dry mid-Holocene event in the Shiyang River drainage basin in the northwest margin of the Asian monsoon. Mid-Holocene lacustrine records were collected from the middle reaches and the terminal lake of the basin. Using radiocarbon and OSL ages, a centennial-scale drought event, which is characterized by a sand layer in lacustrine sediments both from the middle and lower reaches of the basin, was absolutely dated between 8.0-7.0 cal kyr BP. Grain size data suggest an abrupt decline in lake level and a dry environment in the middle reaches of the basin during the dry interval. Previous studies have shown mid-Holocene drought events in other places of monsoon marginal zones; however, their chronologies are not strong enough to study the mechanism. According to the absolutely dated records, we proposed a new hypothesis that the mid-Holocene dry interval can be related to the weakening Asian summer monsoon and the relatively arid environment in arid Central Asia. Furthermore, abrupt dry climatic events are directly linked to the basin-wide effective moisture change in semi-arid and arid regions. Effective moisture is affected by basin-wide precipitation, evapotranspiration, lake surface evaporation and other geographical settings. As a result, the time scales of the dry interval could vary according to locations due to different geographical features.

An Abrupt Centennial-Scale Drought Event and Mid-Holocene Climate Change Patterns in Monsoon Marginal Zones of East Asia

PubMed Central

Li, Yu; Wang, Nai'ang; Zhang, Chengqi

2014-01-01

The mid-latitudes of East Asia are characterized by the interaction between the Asian summer monsoon and the westerly winds. Understanding long-term climate change in the marginal regions of the Asian monsoon is critical for understanding the millennial-scale interactions between the Asian monsoon and the westerly winds. Abrupt climate events are always associated with changes in large-scale circulation patterns; therefore, investigations into abrupt climate changes provide clues for responses of circulation patterns to extreme climate events. In this paper, we examined the time scale and mid-Holocene climatic background of an abrupt dry mid-Holocene event in the Shiyang River drainage basin in the northwest margin of the Asian monsoon. Mid-Holocene lacustrine records were collected from the middle reaches and the terminal lake of the basin. Using radiocarbon and OSL ages, a centennial-scale drought event, which is characterized by a sand layer in lacustrine sediments both from the middle and lower reaches of the basin, was absolutely dated between 8.0–7.0 cal kyr BP. Grain size data suggest an abrupt decline in lake level and a dry environment in the middle reaches of the basin during the dry interval. Previous studies have shown mid-Holocene drought events in other places of monsoon marginal zones; however, their chronologies are not strong enough to study the mechanism. According to the absolutely dated records, we proposed a new hypothesis that the mid-Holocene dry interval can be related to the weakening Asian summer monsoon and the relatively arid environment in arid Central Asia. Furthermore, abrupt dry climatic events are directly linked to the basin-wide effective moisture change in semi-arid and arid regions. Effective moisture is affected by basin-wide precipitation, evapotranspiration, lake surface evaporation and other geographical settings. As a result, the time scales of the dry interval could vary according to locations due to different geographical features. PMID:24599259

Coincident scales of forest feedback on climate and conservation in a diversity hot spot

PubMed Central

Webb, Thomas J; Gaston, Kevin J; Hannah, Lee; Ian Woodward, F

2005-01-01

The dynamic relationship between vegetation and climate is now widely acknowledged. Climate influences the distribution of vegetation; and through a number of feedback mechanisms vegetation affects climate. This implies that land-use changes such as deforestation will have climatic consequences. However, the spatial scales at which such feedbacks occur remain largely unknown. Here, we use a large database of precipitation and tree cover records for an area of the biodiversity-rich Atlantic forest region in south eastern Brazil to investigate the forest–rainfall feedback at a range of spatial scales from ca 101–104 km2. We show that the strength of the feedback increases up to scales of at least 103 km2, with the climate at a particular locality influenced by the pattern of landcover extending over a large area. Thus, smaller forest fragments, even if well protected, may suffer degradation due to the climate responding to land-use change in the surrounding area. Atlantic forest vertebrate taxa also require large areas of forest to support viable populations. Areas of forest of ca 103 km2 would be large enough to support such populations at the same time as minimizing the risk of climatic feedbacks resulting from deforestation. PMID:16608697

Coincident scales of forest feedback on climate and conservation in a diversity hot spot.

PubMed

Webb, Thomas J; Gaston, Kevin J; Hannah, Lee; Ian Woodward, F

2006-03-22

The dynamic relationship between vegetation and climate is now widely acknowledged. Climate influences the distribution of vegetation; and through a number of feedback mechanisms vegetation affects climate. This implies that land-use changes such as deforestation will have climatic consequences. However, the spatial scales at which such feedbacks occur remain largely unknown. Here, we use a large database of precipitation and tree cover records for an area of the biodiversity-rich Atlantic forest region in south eastern Brazil to investigate the forest-rainfall feedback at a range of spatial scales from ca 10(1)-10(4) km2. We show that the strength of the feedback increases up to scales of at least 10(3) km2, with the climate at a particular locality influenced by the pattern of landcover extending over a large area. Thus, smaller forest fragments, even if well protected, may suffer degradation due to the climate responding to land-use change in the surrounding area. Atlantic forest vertebrate taxa also require large areas of forest to support viable populations. Areas of forest of ca 10(3) km2 would be large enough to support such populations at the same time as minimizing the risk of climatic feedbacks resulting from deforestation.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Chen, Gang

Mid-latitude extreme weather events are responsible for a large part of climate-related damage. Yet large uncertainties remain in climate model projections of heat waves, droughts, and heavy rain/snow events on regional scales, limiting our ability to effectively use these projections for climate adaptation and mitigation. These uncertainties can be attributed to both the lack of spatial resolution in the models, and to the lack of a dynamical understanding of these extremes. The approach of this project is to relate the fine-scale features to the large scales in current climate simulations, seasonal re-forecasts, and climate change projections in a very widemore » range of models, including the atmospheric and coupled models of ECMWF over a range of horizontal resolutions (125 to 10 km), aqua-planet configuration of the Model for Prediction Across Scales and High Order Method Modeling Environments (resolutions ranging from 240 km – 7.5 km) with various physics suites, and selected CMIP5 model simulations. The large scale circulation will be quantified both on the basis of the well tested preferred circulation regime approach, and very recently developed measures, the finite amplitude Wave Activity (FAWA) and its spectrum. The fine scale structures related to extremes will be diagnosed following the latest approaches in the literature. The goal is to use the large scale measures as indicators of the probability of occurrence of the finer scale structures, and hence extreme events. These indicators will then be applied to the CMIP5 models and time-slice projections of a future climate.« less

Challenges to Progress in Studies of Climate-Tectonic-Erosion Interactions

NASA Astrophysics Data System (ADS)

Burbank, D. W.

2016-12-01

Attempts to unravel the relative importance of climate and tectonics in modulating topography and erosion should compare relevant data sets at comparable temporal and spatial scales. Given that such data are uncommonly available, how can we compare diverse data sets in a robust fashion? Many erosion-rate studies rely on detrital cosmogenic nuclides. What time scales can such data address, and what landscape conditions do they require to provide accurate representations of long-term erosion rates? To what extent do large-scale, but infrequent erosional events impact long-term rates? Commonly, long-term erosion rates are deduced from thermochronologic data. What types of data are needed to test for consistency of rates across a given interval or change in rates through time? Similarly, spatial and temporal variability in precipitation or tectonics requires averaging across appropriate scales. How are such data obtained in deforming mountain belts, and how do we assess their reliability? This study describes the character and temporal duration of key variables that are needed to examine climate-tectonic-erosion interactions, explores the strengths and weaknesses of several study areas, and suggests the types of data requirements that will underpin enlightening "tests" of hypotheses related to the mutual impacts of climate, tectonics, and erosion.

The new climate data record of total and spectral solar irradiance: Current progress and future steps

NASA Astrophysics Data System (ADS)

Coddington, Odele; Lean, Judith; Rottman, Gary; Pilewskie, Peter; Snow, Martin; Lindholm, Doug

2016-04-01

We present a climate data record of Total Solar Irradiance (TSI) and Solar Spectral Irradiance (SSI), with associated time and wavelength dependent uncertainties, from 1610 to the present. The data record was developed jointly by the Laboratory for Atmospheric and Space Physics (LASP) at the University of Colorado Boulder and the Naval Research Laboratory (NRL) as part of the National Oceanographic and Atmospheric Administration's (NOAA) National Centers for Environmental Information (NCEI) Climate Data Record (CDR) Program, where the data record, source code, and supporting documentation are archived. TSI and SSI are constructed from models that determine the changes from quiet Sun conditions arising from bright faculae and dark sunspots on the solar disk using linear regression of proxies of solar magnetic activity with observations from the SOlar Radiation and Climate Experiment (SORCE) Total Irradiance Monitor (TIM), Spectral Irradiance Monitor (SIM), and SOlar Stellar Irradiance Comparison Experiment (SOLSTICE). We show that TSI can be separately modeled to within TIM's measurement accuracy from solar rotational to solar cycle time scales and we assume that SSI measurements are reliable on solar rotational time scales. We discuss the model formulation, uncertainty estimates, and operational implementation and present comparisons of the modeled TSI and SSI with the measurement record and with other solar irradiance models. We also discuss ongoing work to assess the sensitivity of the modeled irradiances to model assumptions, namely, the scaling of solar variability from rotational-to-cycle time scales and the representation of the sunspot darkening index.

Hydrogeologic controls on streamflow sensitivity to climate variation

Treesearch

Anne Jefferson; Anne Nolin; Sarah Lewis; Christina Tague

2008-01-01

Climate models project warmer temperatures for the north-west USA, which will result in reduced snowpacks and decreased summer streamflow. This paper examines how groundwater, snowmelt, and regional climate patterns control discharge at multiple time scales, using historical records from two watersheds with contrasting geological properties and drainage efficiencies....

Climate modifies response of non-native and native species richness to nutrient enrichment.

PubMed

Flores-Moreno, Habacuc; Reich, Peter B; Lind, Eric M; Sullivan, Lauren L; Seabloom, Eric W; Yahdjian, Laura; MacDougall, Andrew S; Reichmann, Lara G; Alberti, Juan; Báez, Selene; Bakker, Jonathan D; Cadotte, Marc W; Caldeira, Maria C; Chaneton, Enrique J; D'Antonio, Carla M; Fay, Philip A; Firn, Jennifer; Hagenah, Nicole; Harpole, W Stanley; Iribarne, Oscar; Kirkman, Kevin P; Knops, Johannes M H; La Pierre, Kimberly J; Laungani, Ramesh; Leakey, Andrew D B; McCulley, Rebecca L; Moore, Joslin L; Pascual, Jesus; Borer, Elizabeth T

2016-05-19

Ecosystem eutrophication often increases domination by non-natives and causes displacement of native taxa. However, variation in environmental conditions may affect the outcome of interactions between native and non-native taxa in environments where nutrient supply is elevated. We examined the interactive effects of eutrophication, climate variability and climate average conditions on the success of native and non-native plant species using experimental nutrient manipulations replicated at 32 grassland sites on four continents. We hypothesized that effects of nutrient addition would be greatest where climate was stable and benign, owing to reduced niche partitioning. We found that the abundance of non-native species increased with nutrient addition independent of climate; however, nutrient addition increased non-native species richness and decreased native species richness, with these effects dampened in warmer or wetter sites. Eutrophication also altered the time scale in which grassland invasion responded to climate, decreasing the importance of long-term climate and increasing that of annual climate. Thus, climatic conditions mediate the responses of native and non-native flora to nutrient enrichment. Our results suggest that the negative effect of nutrient addition on native abundance is decoupled from its effect on richness, and reduces the time scale of the links between climate and compositional change. © 2016 The Author(s).

Climate modifies response of non-native and native species richness to nutrient enrichment

PubMed Central

Flores-Moreno, Habacuc; Reich, Peter B.; Lind, Eric M.; Sullivan, Lauren L.; Seabloom, Eric W.; Yahdjian, Laura; MacDougall, Andrew S.; Reichmann, Lara G.; Alberti, Juan; Báez, Selene; Bakker, Jonathan D.; Cadotte, Marc W.; Caldeira, Maria C.; Chaneton, Enrique J.; D'Antonio, Carla M.; Fay, Philip A.; Firn, Jennifer; Hagenah, Nicole; Harpole, W. Stanley; Iribarne, Oscar; Kirkman, Kevin P.; Knops, Johannes M. H.; La Pierre, Kimberly J.; Laungani, Ramesh; Leakey, Andrew D. B.; McCulley, Rebecca L.; Moore, Joslin L.; Pascual, Jesus; Borer, Elizabeth T.

2016-01-01

Ecosystem eutrophication often increases domination by non-natives and causes displacement of native taxa. However, variation in environmental conditions may affect the outcome of interactions between native and non-native taxa in environments where nutrient supply is elevated. We examined the interactive effects of eutrophication, climate variability and climate average conditions on the success of native and non-native plant species using experimental nutrient manipulations replicated at 32 grassland sites on four continents. We hypothesized that effects of nutrient addition would be greatest where climate was stable and benign, owing to reduced niche partitioning. We found that the abundance of non-native species increased with nutrient addition independent of climate; however, nutrient addition increased non-native species richness and decreased native species richness, with these effects dampened in warmer or wetter sites. Eutrophication also altered the time scale in which grassland invasion responded to climate, decreasing the importance of long-term climate and increasing that of annual climate. Thus, climatic conditions mediate the responses of native and non-native flora to nutrient enrichment. Our results suggest that the negative effect of nutrient addition on native abundance is decoupled from its effect on richness, and reduces the time scale of the links between climate and compositional change. PMID:27114575

Hope for the Forests? Habitat Resiliency Illustrated in the Face of Climate Change Using Fine-Scale Modeling

NASA Astrophysics Data System (ADS)

Flint, L. E.; Flint, A. L.; Weiss, S. B.; Micheli, E. R.

2010-12-01

In the face of rapid climate change, fine-scale predictions of landscape change are of extreme interest to land managers that endeavor to develop long term adaptive strategies for maintaining biodiversity and ecosystem services. Global climate model (GCM) outputs, which generally focus on estimated increases in air temperature, are increasingly applied to species habitat distribution models. For sensitive species subject to climate change, habitat models predict significant migration (either northward or towards higher elevations), or complete extinction. Current studies typically rely on large spatial scale GCM projections (> 10 km) of changes in precipitation and air temperature: at this scale, these models necessarily neglect subtleties of topographic shading, geomorphic expression of the landscape, and fine-scale differences in soil properties - data that is readily available at meaningful local scales. Recent advances in modeling take advantage of available soils, geology, and topographic data to construct watershed-scale scenarios using GCM inputs and result in improved correlations of vegetation distribution with temperature. For this study, future climate projections were downscaled to 270-m and applied to a physically-based hydrologic model to calculate future changes in recharge, runoff, and climatic water deficit (CWD) for basins draining into the northern San Francisco Bay. CWD was analyzed for mapped vegetation types to evaluate the range of CWD for historic time periods in comparison to future time periods. For several forest communities (including blue oak woodlands, montane hardwoods, douglas-fir, and coast redwood) existing landscape area exhibiting suitable CWD diminishes by up 80 percent in the next century, with a trend towards increased CWD throughout the region. However, no forest community loses all suitable habitat, with islands of potential habitat primarily remaining on north facing slopes and deeper soils. Creation of new suitable habitat is also predicted throughout the region. Results have direct application to management issues of habitat connectivity, forest land protection and acquisition, and active management solutions such as transplanting or assisted migration. Although this analysis considers only one driver of forest habitat distribution, consideration of hydrologic derivatives at a fine scale explains current forest community distributions and provides a far more informed perspective on potential future forest distributions. Results demonstrate the utility of fine-scale modeling and provide landscape managers and conservation agencies valuable management tools in fine-scale future forest scenarios and a framework for evaluating forest resiliency in a changing climate.

Bioclimatic predictors for supporting ecological applications in the conterminous United States

USGS Publications Warehouse

O'Donnel, Michael S.; Ignizio, Drew A.

2012-01-01

The U.S. Geological Survey (USGS) has developed climate indices, referred to as bioclimatic predictors, which highlight climate conditions best related to species physiology. A set of 20 bioclimatic predictors were developed as Geographic Information Systems (GIS) continuous raster surfaces for each year between 1895 and 2009. The Parameter-elevation Regression on Independent Slopes Model (PRISM) and down-scaled PRISM data, which included both averaged multi-year and averaged monthly climate summaries, was used to develop these multi-scale bioclimatic predictors. Bioclimatic predictors capture information about annual conditions (annual mean temperature, annual precipitation, annual range in temperature and precipitation), as well as seasonal mean climate conditions and intra-year seasonality (temperature of the coldest and warmest months, precipitation of the wettest and driest quarters). Examining climate over time is useful when quantifying the effects of climate changes on species' distributions for past, current, and forecasted scenarios. These data, which have not been readily available to scientists, can provide biologists and ecologists with relevant and multi-scaled climate data to augment research on the responses of species to changing climate conditions. The relationships established between species demographics and distributions with bioclimatic predictors can inform land managers of climatic effects on species during decisionmaking processes.

Antarctic lakes suggest millennial reorganizations of Southern Hemisphere atmospheric and oceanic circulation

PubMed Central

Hall, Brenda L.; Denton, George H.; Fountain, Andrew G.; Hendy, Chris H.; Henderson, Gideon M.

2010-01-01

The phasing of millennial-scale oscillations in Antarctica relative to those elsewhere in the world is important for discriminating among models for abrupt climate change, particularly those involving the Southern Ocean. However, records of millennial-scale variability from Antarctica dating to the last glacial maximum are rare and rely heavily on data from widely spaced ice cores, some of which show little variability through that time. Here, we present new data from closed-basin lakes in the Dry Valleys region of East Antarctica that show high-magnitude, high-frequency oscillations in surface level during the late Pleistocene synchronous with climate fluctuations elsewhere in the Southern Hemisphere. These data suggest a coherent Southern Hemisphere pattern of climate change on millennial time scales, at least in the Pacific sector, and indicate that any hypothesis concerning the origin of these events must account for synchronous changes in both high and temperate latitudes. PMID:21115838

Antarctic lakes suggest millennial reorganizations of Southern Hemisphere atmospheric and oceanic circulation.

PubMed

Hall, Brenda L; Denton, George H; Fountain, Andrew G; Hendy, Chris H; Henderson, Gideon M

2010-12-14

The phasing of millennial-scale oscillations in Antarctica relative to those elsewhere in the world is important for discriminating among models for abrupt climate change, particularly those involving the Southern Ocean. However, records of millennial-scale variability from Antarctica dating to the last glacial maximum are rare and rely heavily on data from widely spaced ice cores, some of which show little variability through that time. Here, we present new data from closed-basin lakes in the Dry Valleys region of East Antarctica that show high-magnitude, high-frequency oscillations in surface level during the late Pleistocene synchronous with climate fluctuations elsewhere in the Southern Hemisphere. These data suggest a coherent Southern Hemisphere pattern of climate change on millennial time scales, at least in the Pacific sector, and indicate that any hypothesis concerning the origin of these events must account for synchronous changes in both high and temperate latitudes.

Tracing Multi-Scale Climate Change at Low Latitude from Glacier Shrinkage

NASA Astrophysics Data System (ADS)

Moelg, T.; Cullen, N. J.; Hardy, D. R.; Kaser, G.

2009-12-01

Significant shrinkage of glaciers on top of Africa's highest mountain (Kilimanjaro, 5895 m a.s.l.) has been observed between the late 19th century and the present. Multi-year data from our automatic weather station on the largest remaining slope glacier at 5873 m allow us to force and verify a process-based distributed glacier mass balance model. This generates insights into energy and mass fluxes at the glacier-atmosphere interface, their feedbacks, and how they are linked to atmospheric conditions. By means of numerical atmospheric modeling and global climate model simulations, we explore the linkages of the local climate in Kilimanjaro's summit zone to larger-scale climate dynamics - which suggests a causal connection between Indian Ocean dynamics, mesoscale mountain circulation, and glacier mass balance. Based on this knowledge, the verified mass balance model is used for backward modeling of the steady-state glacier extent observed in the 19th century, which yields the characteristics of local climate change between that time and the present (30-45% less precipitation, 0.1-0.3 hPa less water vapor pressure, 2-4 percentage units less cloud cover at present). Our multi-scale approach provides an important contribution, from a cryospheric viewpoint, to the understanding of how large-scale climate change propagates to the tropical free troposphere. Ongoing work in this context targets the millennium-scale relation between large-scale climate and glacier behavior (by downscaling precipitation), and the possible effects of regional anthropogenic activities (land use change) on glacier mass balance.

Climate Change Impacts of US Reactive Nitrogen Emissions

NASA Astrophysics Data System (ADS)

Pinder, R. W.; Davidson, E. A.; Goodale, C. L.; Greaver, T.; Herrick, J.; Liu, L.

2011-12-01

By fossil fuel combustion and fertilizer application, the US has substantially altered the nitrogen cycle, with serious effects on climate change. The climate effects can be short-lived, by impacting the chemistry of the atmosphere, or long-lived, by altering ecosystem greenhouse gas fluxes. Here, we develop a coherent framework for assessing the climate change impacts of US reactive nitrogen emissions. We use the global temperature potential (GTP) as a common metric, and we calculate the GTP at 20 and 100 years in units of CO2 equivalents. At both time-scales, nitrogen enhancement of CO2 uptake has the largest impact, because in the eastern US, areas of high nitrogen deposition are co-located with forests. In the short-term, the effect due to NOx altering ozone and methane concentrations is also substantial, but are not important on the 100 year time scale. Finally, the GTP of N2O emissions is substantial at both time scales. We have also attributed these impacts to combustion and agricultural sources, and quantified the uncertainty. Reactive nitrogen from combustion sources contribute more to cooling than warming. The impacts of agricultural sources tend to cancel each other out, and the net effect is uncertain. Recent trends show decreasing reactive nitrogen from US combustion sources, while agricultural sources are increasing. Fortunately, there are many mitigation strategies currently available to reduce the climate change impacts of US agricultural sources.

Radiometric & Geometric normalization of Sentinel optical data and VHR data to build-up time-series, an example in Tonga for the monitoring of mangrove health vs. climate change

NASA Astrophysics Data System (ADS)

Serra, Romain; Valette, Anne; Taji, Amine; Emsley, Stephen

2017-04-01

Building climate resilience (i.e. climate change adaptation or self-renew of ecosystems) or planning environment rehabilitations and nature-based solutions to address their vulnerabilities to disturbances has prerequisites: 1- identify the disorder, i.e. stresses caused by events such as hurricanes, tsunamis, heavy rains, hailstone falls, smog… or piled-up along-time such as warming, rainfalls, ocean acidification, soil salinization… and measured by trends; and 2- qualify its impact on the ecosystems, i.e. the resulting strains. Mitigation of threats is accordingly twofold, i. on locally temporal scales for protection, ii. on long scale for prevention and sustainability. For assessment and evaluation prior to design future scenarios, it requires concomitant acquisition of (a) climate data at global and local spatial scale which describe the changes at the various temporal scales of phenomena without signal aliasing, and of (b) the ecosystems' status at the scales of the forcing and of relaxation times, hysteresis lags, periodicities of orbits in chaotic systems, shifts from one attractor in ecosystems to the others, etc. Dissociating groups of timescales and spatial scales facilitates the analysis and help set-up monitoring schemes. The Sentinel-2 mission, with a revisit of the earth every few days and a 10m resolution on-ground is a good automatic spectro-analytical monitoring system because detecting changes in numerous optical & IR bands at proper spatial scales for the description of land parcels. Combined with photo-interpreted VHR data which describe the environment more crudely but with high precision of land parcels' border locations, it helps find the relationship between stress and strains to empirically understand the relationships. An example is provided for Tonga, courtesy of ESA support and ADB request, with a focus on time-series' consistency that requires radiometric and geometric normalisation of EO data sets. Methodologies have been developed in the frame of ESA programs and EC program (H2020 Co-Resyf).

National Climate Change and Wildlife Science Center project accomplishments: highlights

USGS Publications Warehouse

Holl, Sally

2011-01-01

The National Climate Change and Wildlife Science Center (NCCWSC) has invested more than $20M since 2008 to put cutting-edge climate science research in the hands of resource managers across the Nation. With NCCWSC support, more than 25 cooperative research initiatives led by U.S. Geological Survey (USGS) researchers and technical staff are advancing our understanding of habitats and species to provide guidance to managers in the face of a changing climate. Projects focus on quantifying and predicting interactions between climate, habitats, species, and other natural resources such as water. Spatial scales of the projects range from the continent of North America, to a regional scale such as the Pacific Northwest United States, to a landscape scale such as the Florida Everglades. Time scales range from the outset of the 20th century to the end of the 21st century. Projects often lead to workshops, presentations, publications and the creation of new websites, computer models, and data visualization tools. Partnership-building is also a key focus of the NCCWSC-supported projects. New and on-going cooperative partnerships have been forged and strengthened with resource managers and scientists at Federal, tribal, state, local, academic, and non-governmental organizations. USGS scientists work closely with resource managers to produce timely and relevant results that can assist managers and policy makers in current resource management decisions. This fact sheet highlights accomplishments of five NCCWSC projects.

Assessing climate change impact on complementarity between solar and hydro power in areas affected by glacier shrinkage

NASA Astrophysics Data System (ADS)

Diah Puspitarini, Handriyanti; François, Baptiste; Zoccatelli, Davide; Brown, Casey; Creutin, Jean-Dominique; Zaramella, Mattia; Borga, Marco

2017-04-01

Variable Renewable Energy (VRE) sources such as wind, solar and runoff sources are variable in time and space, following their driving weather variables. In this work we aim to analyse optimal mixes of energy sources, i.e. mixes of sources which minimize the deviation between energy load and generation, for a region in the Upper Adige river basin (Eastern Italian Alps) affected by glacier shrinking. The study focuses on hydropower (run of the river - RoR) and solar energy, and analyses the current situation as well different climate change scenarios. Changes in glacier extent in response to climate warming and/or altered precipitation regimes have the potential to substantially alter the magnitude and timing, as well as the spatial variation of watershed-scale hydrologic fluxes. This may change the complementarity with solar power as well. In this study, we analyse the climate change impact on complementarity between RoR and solar using the Decision Scaling approach (Brown et al. 2012). With this approach, the system vulnerability is separated from the climatic hazard that can come from any set of past or future climate conditions. It departs from conventional top-down impact studies because it explores the sensitivity of the system response to a plausible range of climate variations rather than its sensitivity to the time-varying outcome of individual GCM projections. It mainly relies on the development of Climate Response Functions that bring together i) the sensitivity of some system success and/or failure indicators to key external drivers (i.e. mean features of regional climate) and ii) the future values of these drivers as simulated from climate simulation chains. The main VRE sources used in the study region are solar- and hydro-power (with an important fraction of run-of-the river hydropower). The considered indicator of success is the 'energy penetration' coefficient, defined as the long-run percentage of energy demand naturally met by the VRE on an hourly basis. Climate response functions, developed in a 2D climate change space (change in mean temperature and precipitation), are built from multiple hydro-climatic scenarios obtained by perturbing the observed weather time series with the change factor method, and considering given glacier storage states. Climate experiments are further used for assessing these change factors from different emission scenarios, climate models and future prediction lead times. Their positioning on the Climate Response Function allows discussing the risk/opportunities pertaining to changes in VRE penetration in the future. Results show i) the large impact of glacier shrinkage on the complementarity between solar and RoR energy sources and ii) that the impact is decreasing with time, with the main alterations to be expected in the coming 30 years. Brown, C., Ghile, Y., Laverty, M., Li, K., (2012). Decision scaling: Linking bottom up vulnerability analysis with climate projections in the water sector. Water Resour Res 48. 515 doi:10.1029/2011WR011212

The significance of cloud-radiative forcing to the general circulation on climate time scales - A satellite interpretation

NASA Technical Reports Server (NTRS)

Sohn, Byung-Ju; Smith, Eric A.

1992-01-01

This paper focuses on the role of cloud- and surface-atmosphere forcing on the net radiation balance and their potential impact on the general circulation at climate time scales. The globally averaged cloud-forcing estimates and cloud sensitivity values taken from various recent studies are summarized. It is shown that the net radiative heating over the tropics is principally due to high clouds, while the net cooling in mid- and high latitudes is dominated by low and middle clouds.

Scale-dependent climatic drivers of human epidemics in ancient China.

PubMed

Tian, Huidong; Yan, Chuan; Xu, Lei; Büntgen, Ulf; Stenseth, Nils C; Zhang, Zhibin

2017-12-05

A wide range of climate change-induced effects have been implicated in the prevalence of infectious diseases. Disentangling causes and consequences, however, remains particularly challenging at historical time scales, for which the quality and quantity of most of the available natural proxy archives and written documentary sources often decline. Here, we reconstruct the spatiotemporal occurrence patterns of human epidemics for large parts of China and most of the last two millennia. Cold and dry climate conditions indirectly increased the prevalence of epidemics through the influences of locusts and famines. Our results further reveal that low-frequency, long-term temperature trends mainly contributed to negative associations with epidemics, while positive associations of epidemics with droughts, floods, locusts, and famines mainly coincided with both higher and lower frequency temperature variations. Nevertheless, unstable relationships between human epidemics and temperature changes were observed on relatively smaller time scales. Our study suggests that an intertwined, direct, and indirect array of biological, ecological, and societal responses to different aspects of past climatic changes strongly depended on the frequency domain and study period chosen.

Last millennium Northern Hemisphere summer temperatures from tree rings: Part II, spatially resolved reconstructions

NASA Astrophysics Data System (ADS)

Anchukaitis, Kevin J.; Wilson, Rob; Briffa, Keith R.; Büntgen, Ulf; Cook, Edward R.; D'Arrigo, Rosanne; Davi, Nicole; Esper, Jan; Frank, David; Gunnarson, Björn E.; Hegerl, Gabi; Helama, Samuli; Klesse, Stefan; Krusic, Paul J.; Linderholm, Hans W.; Myglan, Vladimir; Osborn, Timothy J.; Zhang, Peng; Rydval, Milos; Schneider, Lea; Schurer, Andrew; Wiles, Greg; Zorita, Eduardo

2017-05-01

Climate field reconstructions from networks of tree-ring proxy data can be used to characterize regional-scale climate changes, reveal spatial anomaly patterns associated with atmospheric circulation changes, radiative forcing, and large-scale modes of ocean-atmosphere variability, and provide spatiotemporal targets for climate model comparison and evaluation. Here we use a multiproxy network of tree-ring chronologies to reconstruct spatially resolved warm season (May-August) mean temperatures across the extratropical Northern Hemisphere (40-90°N) using Point-by-Point Regression (PPR). The resulting annual maps of temperature anomalies (750-1988 CE) reveal a consistent imprint of volcanism, with 96% of reconstructed grid points experiencing colder conditions following eruptions. Solar influences are detected at the bicentennial (de Vries) frequency, although at other time scales the influence of insolation variability is weak. Approximately 90% of reconstructed grid points show warmer temperatures during the Medieval Climate Anomaly when compared to the Little Ice Age, although the magnitude varies spatially across the hemisphere. Estimates of field reconstruction skill through time and over space can guide future temporal extension and spatial expansion of the proxy network.

The long-range correlation and evolution law of centennial-scale temperatures in Northeast China.

PubMed

Zheng, Xiaohui; Lian, Yi; Wang, Qiguang

2018-01-01

This paper applies the detrended fluctuation analysis (DFA) method to investigate the long-range correlation of monthly mean temperatures from three typical measurement stations at Harbin, Changchun, and Shenyang in Northeast China from 1909 to 2014. The results reveal the memory characteristics of the climate system in this region. By comparing the temperatures from different time periods and investigating the variations of its scaling exponents at the three stations during these different time periods, we found that the monthly mean temperature has long-range correlation, which indicates that the temperature in Northeast China has long-term memory and good predictability. The monthly time series of temperatures over the past 106 years also shows good long-range correlation characteristics. These characteristics are also obviously observed in the annual mean temperature time series. Finally, we separated the centennial-length temperature time series into two time periods. These results reveal that the long-range correlations at the Harbin station over these two time periods have large variations, whereas no obvious variations are observed at the other two stations. This indicates that warming affects the regional climate system's predictability differently at different time periods. The research results can provide a quantitative reference point for regional climate predictability assessment and future climate model evaluation.

Divergence of species responses to climate change

Treesearch

Songlin Fei; Johanna M. Desprez; Kevin M. Potter; Insu Jo; Jonathan A. Knott; Christopher M. Oswalt

2017-01-01

Climate change can have profound impacts on biodiversity and the sustainability of many ecosystems. Various studies have investigated the impacts of climate change, but large-scale, trait-specific impactsare less understood.Weanalyze abundance data over time for 86 tree species/groups across the eastern United States spanning the last three decades. We show that more...

Monthly means of selected climate variables for 1985 - 1989

NASA Technical Reports Server (NTRS)

Schubert, S.; Wu, C.-Y.; Zero, J.; Schemm, J.-K.; Park, C.-K.; Suarez, M.

1992-01-01

Meteorologists are accustomed to viewing instantaneous weather maps, since these contain the most relevant information for the task of producing short-range weather forecasts. Climatologists, on the other hand, tend to deal with long-term means, which portray the average climate. The recent emphasis on dynamical extended-range forecasting and, in particular measuring and predicting short term climate change makes it important that we become accustomed to looking at variations on monthly and longer time scales. A convenient toll for researchers to familiarize themselves with the variability which occurs in selected parameters on these time scales is provided. The format of the document was chosen to help facilitate the intercomparison of various parameters and highlight the year-to-year variability in monthly means.

Improving our fundamental understanding of the role of aerosol-cloud interactions in the climate system.

PubMed

Seinfeld, John H; Bretherton, Christopher; Carslaw, Kenneth S; Coe, Hugh; DeMott, Paul J; Dunlea, Edward J; Feingold, Graham; Ghan, Steven; Guenther, Alex B; Kahn, Ralph; Kraucunas, Ian; Kreidenweis, Sonia M; Molina, Mario J; Nenes, Athanasios; Penner, Joyce E; Prather, Kimberly A; Ramanathan, V; Ramaswamy, Venkatachalam; Rasch, Philip J; Ravishankara, A R; Rosenfeld, Daniel; Stephens, Graeme; Wood, Robert

2016-05-24

The effect of an increase in atmospheric aerosol concentrations on the distribution and radiative properties of Earth's clouds is the most uncertain component of the overall global radiative forcing from preindustrial time. General circulation models (GCMs) are the tool for predicting future climate, but the treatment of aerosols, clouds, and aerosol-cloud radiative effects carries large uncertainties that directly affect GCM predictions, such as climate sensitivity. Predictions are hampered by the large range of scales of interaction between various components that need to be captured. Observation systems (remote sensing, in situ) are increasingly being used to constrain predictions, but significant challenges exist, to some extent because of the large range of scales and the fact that the various measuring systems tend to address different scales. Fine-scale models represent clouds, aerosols, and aerosol-cloud interactions with high fidelity but do not include interactions with the larger scale and are therefore limited from a climatic point of view. We suggest strategies for improving estimates of aerosol-cloud relationships in climate models, for new remote sensing and in situ measurements, and for quantifying and reducing model uncertainty.

Improving Our Fundamental Understanding of the Role of Aerosol Cloud Interactions in the Climate System

NASA Technical Reports Server (NTRS)

Seinfeld, John H.; Bretherton, Christopher; Carslaw, Kenneth S.; Coe, Hugh; DeMott, Paul J.; Dunlea, Edward J.; Feingold, Graham; Ghan, Steven; Guenther, Alex B.; Kahn, Ralph;

Improving our fundamental understanding of the role of aerosol-cloud interactions in the climate system

DOE PAGES

Seinfeld, John H.; Bretherton, Christopher; Carslaw, Kenneth S.; ...

2016-05-24

The effect of an increase in atmospheric aerosol concentrations on the distribution and radiative properties of Earth’s clouds is the most uncertain component of the overall global radiative forcing from pre-industrial time. General Circulation Models (GCMs) are the tool for predicting future climate, but the treatment of aerosols, clouds, and aerosol-cloud radiative effects carries large uncertainties that directly affect GCM predictions, such as climate sensitivity. Predictions are hampered by the large range of scales of interaction between various components that need to be captured. Observation systems (remote sensing, in situ) are increasingly being used to constrain predictions but significant challengesmore » exist, to some extent because of the large range of scales and the fact that the various measuring systems tend to address different scales. Fine-scale models represent clouds, aerosols, and aerosol-cloud interactions with high fidelity but do not include interactions with the larger scale and are therefore limited from a climatic point of view. Lastly, we suggest strategies for improving estimates of aerosol-cloud relationships in climate models, for new remote sensing and in situ measurements, and for quantifying and reducing model uncertainty.« less

Improving our fundamental understanding of the role of aerosol−cloud interactions in the climate system

PubMed Central

Seinfeld, John H.; Bretherton, Christopher; Carslaw, Kenneth S.; Coe, Hugh; DeMott, Paul J.; Dunlea, Edward J.; Feingold, Graham; Ghan, Steven; Guenther, Alex B.; Kraucunas, Ian; Molina, Mario J.; Nenes, Athanasios; Penner, Joyce E.; Prather, Kimberly A.; Ramanathan, V.; Ramaswamy, Venkatachalam; Rasch, Philip J.; Ravishankara, A. R.; Rosenfeld, Daniel; Stephens, Graeme; Wood, Robert

2016-01-01

The effect of an increase in atmospheric aerosol concentrations on the distribution and radiative properties of Earth’s clouds is the most uncertain component of the overall global radiative forcing from preindustrial time. General circulation models (GCMs) are the tool for predicting future climate, but the treatment of aerosols, clouds, and aerosol−cloud radiative effects carries large uncertainties that directly affect GCM predictions, such as climate sensitivity. Predictions are hampered by the large range of scales of interaction between various components that need to be captured. Observation systems (remote sensing, in situ) are increasingly being used to constrain predictions, but significant challenges exist, to some extent because of the large range of scales and the fact that the various measuring systems tend to address different scales. Fine-scale models represent clouds, aerosols, and aerosol−cloud interactions with high fidelity but do not include interactions with the larger scale and are therefore limited from a climatic point of view. We suggest strategies for improving estimates of aerosol−cloud relationships in climate models, for new remote sensing and in situ measurements, and for quantifying and reducing model uncertainty. PMID:27222566

Spatial synchrony of local populations has increased in association with the recent Northern Hemisphere climate trend.

PubMed

Post, Eric; Forchhammer, Mads C

2004-06-22

According to ecological theory, populations whose dynamics are entrained by environmental correlation face increased extinction risk as environmental conditions become more synchronized spatially. This prediction is highly relevant to the study of ecological consequences of climate change. Recent empirical studies have indicated, for example, that large-scale climate synchronizes trophic interactions and population dynamics over broad spatial scales in freshwater and terrestrial systems. Here, we present an analysis of century-scale, spatially replicated data on local weather and the population dynamics of caribou in Greenland. Our results indicate that spatial autocorrelation in local weather has increased with large-scale climatic warming. This increase in spatial synchrony of environmental conditions has been matched, in turn, by an increase in the spatial synchrony of local caribou populations toward the end of the 20th century. Our results indicate that spatial synchrony in environmental conditions and the populations influenced by them are highly variable through time and can increase with climatic warming. We suggest that if future warming can increase population synchrony, it may also increase extinction risk.

The trend of the multi-scale temporal variability of precipitation in Colorado River Basin

NASA Astrophysics Data System (ADS)

Jiang, P.; Yu, Z.

2011-12-01

Hydrological problems like estimation of flood and drought frequencies under future climate change are not well addressed as a result of the disability of current climate models to provide reliable prediction (especially for precipitation) shorter than 1 month. In order to assess the possible impacts that multi-scale temporal distribution of precipitation may have on the hydrological processes in Colorado River Basin (CRB), a comparative analysis of multi-scale temporal variability of precipitation as well as the trend of extreme precipitation is conducted in four regions controlled by different climate systems. Multi-scale precipitation variability including within-storm patterns and intra-annual, inter-annual and decadal variabilities will be analyzed to explore the possible trends of storm durations, inter-storm periods, average storm precipitation intensities and extremes under both long-term natural climate variability and human-induced warming. Further more, we will examine the ability of current climate models to simulate the multi-scale temporal variability and extremes of precipitation. On the basis of these analyses, a statistical downscaling method will be developed to disaggregate the future precipitation scenarios which will provide a more reliable and finer temporal scale precipitation time series for hydrological modeling. Analysis results and downscaling results will be presented.

The 1,800-year oceanic tidal cycle: A possible cause of rapid climate change

PubMed Central

Keeling, Charles D.; Whorf, Timothy P.

2000-01-01

Variations in solar irradiance are widely believed to explain climatic change on 20,000- to 100,000-year time-scales in accordance with the Milankovitch theory of the ice ages, but there is no conclusive evidence that variable irradiance can be the cause of abrupt fluctuations in climate on time-scales as short as 1,000 years. We propose that such abrupt millennial changes, seen in ice and sedimentary core records, were produced in part by well characterized, almost periodic variations in the strength of the global oceanic tide-raising forces caused by resonances in the periodic motions of the earth and moon. A well defined 1,800-year tidal cycle is associated with gradually shifting lunar declination from one episode of maximum tidal forcing on the centennial time-scale to the next. An amplitude modulation of this cycle occurs with an average period of about 5,000 years, associated with gradually shifting separation-intervals between perihelion and syzygy at maxima of the 1,800-year cycle. We propose that strong tidal forcing causes cooling at the sea surface by increasing vertical mixing in the oceans. On the millennial time-scale, this tidal hypothesis is supported by findings, from sedimentary records of ice-rafting debris, that ocean waters cooled close to the times predicted for strong tidal forcing. PMID:10725399

Do GCM's Predict the Climate.... Or the Low Frequency Weather?

NASA Astrophysics Data System (ADS)

Lovejoy, S.; Varon, D.; Schertzer, D. J.

2011-12-01

Over twenty-five years ago, a three-regime scaling model was proposed describing the statistical variability of the atmosphere over time scales ranging from weather scales out to ≈ 100 kyrs. Using modern in situ data reanalyses, monthly surface series (at 5ox5o), 8 "multiproxy" (yearly) series of the Northern hemisphere from 1500- 1980, and GRIP and Vostok paleotemperatures at 5.2 and ≈ 100 year resolutions (over the past 91-420 kyrs), we refine the model and show how it can be understood with the help of new developments in nonlinear dynamics, especially multifractals and cascades. In a scaling range, mean fluctuations in state variables such as temperature ΔT ≈ ΔtH the where Δt is the duration. At small (weather) scales the fluctuation exponents are generally H>0; they grow with scale. At longer scales Δt >τw (≈ 10 days) they change sign, the fluctuations decrease with scale; this is the low variability, "low frequency weather" regime the spectrum is a relatively flat "plateau", it's variability is that of the usual idea of "long term weather statistics". Finally for longer times, Δt>τc ≈ 10 - 100 years, again H>0, the variability again increases with scale. This is the true climate regime. These scaling regimes allow us to objectively define the weather as fluctuations over periods <τw, "climate states", as fluctuations at scale τc and "climate change" as the fluctuations at longer periods >τc). We show that the intermediate regime is the result of the weather regime undergoing a "dimensional transition": at temporal scales longer than the typical lifetime of planetary structures (τw), the spatial degrees of freedom are rapidly quenched, only the temporal degrees of freedom are important. This low frequency weather regime has statistical properties well reproduced not only by weather cascade models, but also by control runs (i.e. without climate forcing) of GCM's (including IPSL and ECHAM GCM's). In order for GCM's to go beyond simply predicting this low frequency weather so as to predict the climate, they need appropriate climate forcings and/ or new internal mechanisms of variability. We examine this using wavelet analyses of forced and unforced GCM outputs, including the ECHO-G simulation used in the Millenium project. For example, we find that climate scenarios with large CO2 increases do give rise to a climate regime but that Hc>1 i.e. much larger than that of natural variability which for temperatures has Hc≈0.4. In comparison, the (largely volcanic) forcing of the ECHO-G Millenium simulation is fairly realistic (Hc≈0.4), although it is not clear that this mechanism can explain the even lower frequency variability found in the paleotemperature series, nor is it clear that this is compatible with low frequency solar or orbital forcings.

Making Scientific Data Available to Adaptation Practitioners - the Wallace Initiative

NASA Astrophysics Data System (ADS)

Price, J. T.; Warren, R. F.; Vanderwal, J.; Shoo, L.; Ramirez, J.; Jarvis, A.; Goswami, S.

2010-12-01

Conservation strategies have largely been developed under an assumption of a stationary climate. These strategies may fail with changing climates, especially when acting with existing anthropogenic pressures. The Wallace Initiative is a global effort to rapidly assess the potential impacts of climate change on nearly 50,000 plant and animal species. Climate change data from the Community Integrated Assessment System (CIAS) is then used to look at different future climate change scenarios. Governments and conservation organizations have dedicated extensive resources to protect biodiversity. These investments are at risk and efforts will need to take into account a dynamic climate. We used the species models to calculate projected changes in percent species richness - looking at areas likely to be refugia and areas likely to undergo the greatest loss. This information can provide guidance to natural resource managers on how they may need to adapt to climate change to avoid biodiversity loss. Managers will also need to take into account issues with spatial scale. While these models might project a species being “lost” in a 0.5° x 0.5° grid, thermal buffering (e.g., taking into account elevation, slope, aspect, distance to stream and canopy cover) provides guidance on areas that may allow a species to persist at more local scales (1-5 km). This approach may help alleviate the issues of downscaling climate and climate change data in data-poor areas. Understanding the vulnerability of biodiversity requires an understanding of the climate and projected climate changes. Thus, developing long term adaptation options requires robust vulnerability analyses at appropriate scales. These assessments are often hindered by data quality and availability, capacity and an understanding of appropriate scales, methods and tools. The program ClimaScope has been designed to help provide better access to climate data for modelers and practitioners, data that has also been linked to impacts. ClimaScope is a data visualization engine providing easy access to data without running the models. For a selected GCM pattern and emissions scenario, ClimaScope provides maps, charts and data on the projected climate changes with some indication of uncertainty range. Variables available include terrestrial temperature change (maximum, minimum and average), total precipitation, wet-day frequency, and sea-surface temperature. This data can be presented both as observed climate and/or projected climate for a user defined time period. Some of these data have been used in the Wallace Initiative and data from the Wallace Initiative are also available to users. So, practitioners can select family, genus, species, dispersal model, climate model, emission model, and time slice and get maps showing projected range of the species over time. These tools have been designed to help make scientific data more readily available to adaptation practitioners around the world, especially in developing countries.

Climate Change and Macro-Economic Cycles in Pre-Industrial Europe

PubMed Central

Pei, Qing; Zhang, David D.; Lee, Harry F.; Li, Guodong

2014-01-01

Climate change has been proven to be the ultimate cause of social crisis in pre-industrial Europe at a large scale. However, detailed analyses on climate change and macro-economic cycles in the pre-industrial era remain lacking, especially within different temporal scales. Therefore, fine-grained, paleo-climate, and economic data were employed with statistical methods to quantitatively assess the relations between climate change and agrarian economy in Europe during AD 1500 to 1800. In the study, the Butterworth filter was adopted to filter the data series into a long-term trend (low-frequency) and short-term fluctuations (high-frequency). Granger Causality Analysis was conducted to scrutinize the associations between climate change and macro-economic cycle at different frequency bands. Based on quantitative results, climate change can only show significant effects on the macro-economic cycle within the long-term. In terms of the short-term effects, society can relieve the influences from climate variations by social adaptation methods and self-adjustment mechanism. On a large spatial scale, temperature holds higher importance for the European agrarian economy than precipitation. By examining the supply-demand mechanism in the grain market, population during the study period acted as the producer in the long term, whereas as the consumer in the short term. These findings merely reflect the general interactions between climate change and macro-economic cycles at the large spatial region with a long-term study period. The findings neither illustrate individual incidents that can temporarily distort the agrarian economy nor explain some specific cases. In the study, the scale thinking in the analysis is raised as an essential methodological issue for the first time to interpret the associations between climatic impact and macro-economy in the past agrarian society within different temporal scales. PMID:24516601

Climate change and macro-economic cycles in pre-industrial europe.

PubMed

Pei, Qing; Zhang, David D; Lee, Harry F; Li, Guodong

2014-01-01

Climate change has been proven to be the ultimate cause of social crisis in pre-industrial Europe at a large scale. However, detailed analyses on climate change and macro-economic cycles in the pre-industrial era remain lacking, especially within different temporal scales. Therefore, fine-grained, paleo-climate, and economic data were employed with statistical methods to quantitatively assess the relations between climate change and agrarian economy in Europe during AD 1500 to 1800. In the study, the Butterworth filter was adopted to filter the data series into a long-term trend (low-frequency) and short-term fluctuations (high-frequency). Granger Causality Analysis was conducted to scrutinize the associations between climate change and macro-economic cycle at different frequency bands. Based on quantitative results, climate change can only show significant effects on the macro-economic cycle within the long-term. In terms of the short-term effects, society can relieve the influences from climate variations by social adaptation methods and self-adjustment mechanism. On a large spatial scale, temperature holds higher importance for the European agrarian economy than precipitation. By examining the supply-demand mechanism in the grain market, population during the study period acted as the producer in the long term, whereas as the consumer in the short term. These findings merely reflect the general interactions between climate change and macro-economic cycles at the large spatial region with a long-term study period. The findings neither illustrate individual incidents that can temporarily distort the agrarian economy nor explain some specific cases. In the study, the scale thinking in the analysis is raised as an essential methodological issue for the first time to interpret the associations between climatic impact and macro-economy in the past agrarian society within different temporal scales.

Higher climatological temperature sensitivity of soil carbon in cold than warm climates

NASA Astrophysics Data System (ADS)

Koven, Charles D.; Hugelius, Gustaf; Lawrence, David M.; Wieder, William R.

2017-11-01

The projected loss of soil carbon to the atmosphere resulting from climate change is a potentially large but highly uncertain feedback to warming. The magnitude of this feedback is poorly constrained by observations and theory, and is disparately represented in Earth system models (ESMs). To assess the climatological temperature sensitivity of soil carbon, we calculate apparent soil carbon turnover times that reflect long-term and broad-scale rates of decomposition. Here, we show that the climatological temperature control on carbon turnover in the top metre of global soils is more sensitive in cold climates than in warm climates and argue that it is critical to capture this emergent ecosystem property in global-scale models. We present a simplified model that explains the observed high cold-climate sensitivity using only the physical scaling of soil freeze-thaw state across climate gradients. Current ESMs fail to capture this pattern, except in an ESM that explicitly resolves vertical gradients in soil climate and carbon turnover. An observed weak tropical temperature sensitivity emerges in a different model that explicitly resolves mineralogical control on decomposition. These results support projections of strong carbon-climate feedbacks from northern soils and demonstrate a method for ESMs to capture this emergent behaviour.

Assessment of a stochastic downscaling methodology in generating an ensemble of hourly future climate time series

NASA Astrophysics Data System (ADS)

Fatichi, S.; Ivanov, V. Y.; Caporali, E.

2013-04-01

This study extends a stochastic downscaling methodology to generation of an ensemble of hourly time series of meteorological variables that express possible future climate conditions at a point-scale. The stochastic downscaling uses general circulation model (GCM) realizations and an hourly weather generator, the Advanced WEather GENerator (AWE-GEN). Marginal distributions of factors of change are computed for several climate statistics using a Bayesian methodology that can weight GCM realizations based on the model relative performance with respect to a historical climate and a degree of disagreement in projecting future conditions. A Monte Carlo technique is used to sample the factors of change from their respective marginal distributions. As a comparison with traditional approaches, factors of change are also estimated by averaging GCM realizations. With either approach, the derived factors of change are applied to the climate statistics inferred from historical observations to re-evaluate parameters of the weather generator. The re-parameterized generator yields hourly time series of meteorological variables that can be considered to be representative of future climate conditions. In this study, the time series are generated in an ensemble mode to fully reflect the uncertainty of GCM projections, climate stochasticity, as well as uncertainties of the downscaling procedure. Applications of the methodology in reproducing future climate conditions for the periods of 2000-2009, 2046-2065 and 2081-2100, using the period of 1962-1992 as the historical baseline are discussed for the location of Firenze (Italy). The inferences of the methodology for the period of 2000-2009 are tested against observations to assess reliability of the stochastic downscaling procedure in reproducing statistics of meteorological variables at different time scales.

Discriminating low frequency components from long range persistent fluctuations in daily atmospheric temperature variability

NASA Astrophysics Data System (ADS)

Lanfredi, M.; Simoniello, T.; Cuomo, V.; Macchiato, M.

2009-02-01

This study originated from recent results reported in literature, which support the existence of long-range (power-law) persistence in atmospheric temperature fluctuations on monthly and inter-annual scales. We investigated the results of Detrended Fluctuation Analysis (DFA) carried out on twenty-two historical daily time series recorded in Europe in order to evaluate the reliability of such findings in depth. More detailed inspections emphasized systematic deviations from power-law and high statistical confidence for functional form misspecification. Rigorous analyses did not support scale-free correlation as an operative concept for Climate modelling, as instead suggested in literature. In order to understand the physical implications of our results better, we designed a bivariate Markov process, parameterised on the basis of the atmospheric observational data by introducing a slow dummy variable. The time series generated by this model, analysed both in time and frequency domains, tallied with the real ones very well. They accounted for both the deceptive scaling found in literature and the correlation details enhanced by our analysis. Our results seem to evidence the presence of slow fluctuations from another climatic sub-system such as ocean, which inflates temperature variance up to several months. They advise more precise re-analyses of temperature time series before suggesting dynamical paradigms useful for Climate modelling and for the assessment of Climate Change.

Discriminating low frequency components from long range persistent fluctuations in daily atmospheric temperature variability

NASA Astrophysics Data System (ADS)

Lanfredi, M.; Simoniello, T.; Cuomo, V.; Macchiato, M.

2009-07-01

This study originated from recent results reported in literature, which support the existence of long-range (power-law) persistence in atmospheric temperature fluctuations on monthly and inter-annual scales. We investigated the results of Detrended Fluctuation Analysis (DFA) carried out on twenty-two historical daily time series recorded in Europe in order to evaluate the reliability of such findings in depth. More detailed inspections emphasized systematic deviations from power-law and high statistical confidence for functional form misspecification. Rigorous analyses did not support scale-free correlation as an operative concept for Climate modelling, as instead suggested in literature. In order to understand the physical implications of our results better, we designed a bivariate Markov process, parameterised on the basis of the atmospheric observational data by introducing a slow dummy variable. The time series generated by this model, analysed both in time and frequency domains, tallied with the real ones very well. They accounted for both the deceptive scaling found in literature and the correlation details enhanced by our analysis. Our results seem to evidence the presence of slow fluctuations from another climatic sub-system such as ocean, which inflates temperature variance up to several months. They advise more precise re-analyses of temperature time series before suggesting dynamical paradigms useful for Climate modelling and for the assessment of Climate Change.

Evaluating synoptic systems in the CMIP5 climate models over the Australian region

NASA Astrophysics Data System (ADS)

Gibson, Peter B.; Uotila, Petteri; Perkins-Kirkpatrick, Sarah E.; Alexander, Lisa V.; Pitman, Andrew J.

2016-10-01

Climate models are our principal tool for generating the projections used to inform climate change policy. Our confidence in projections depends, in part, on how realistically they simulate present day climate and associated variability over a range of time scales. Traditionally, climate models are less commonly assessed at time scales relevant to daily weather systems. Here we explore the utility of a self-organizing maps (SOMs) procedure for evaluating the frequency, persistence and transitions of daily synoptic systems in the Australian region simulated by state-of-the-art global climate models. In terms of skill in simulating the climatological frequency of synoptic systems, large spread was observed between models. A positive association between all metrics was found, implying that relative skill in simulating the persistence and transitions of systems is related to skill in simulating the climatological frequency. Considering all models and metrics collectively, model performance was found to be related to model horizontal resolution but unrelated to vertical resolution or representation of the stratosphere. In terms of the SOM procedure, the timespan over which evaluation was performed had some influence on model performance skill measures, as did the number of circulation types examined. These findings have implications for selecting models most useful for future projections over the Australian region, particularly for projections related to synoptic scale processes and phenomena. More broadly, this study has demonstrated the utility of the SOMs procedure in providing a process-based evaluation of climate models.

Modeling distributional changes in winter precipitation of Canada using Bayesian spatiotemporal quantile regression subjected to different teleconnections

NASA Astrophysics Data System (ADS)

Tan, Xuezhi; Gan, Thian Yew; Chen, Shu; Liu, Bingjun

2018-05-01

Climate change and large-scale climate patterns may result in changes in probability distributions of climate variables that are associated with changes in the mean and variability, and severity of extreme climate events. In this paper, we applied a flexible framework based on the Bayesian spatiotemporal quantile (BSTQR) model to identify climate changes at different quantile levels and their teleconnections to large-scale climate patterns such as El Niño-Southern Oscillation (ENSO), Pacific Decadal Oscillation (PDO), North Atlantic Oscillation (NAO) and Pacific-North American (PNA). Using the BSTQR model with time (year) as a covariate, we estimated changes in Canadian winter precipitation and their uncertainties at different quantile levels. There were some stations in eastern Canada showing distributional changes in winter precipitation such as an increase in low quantiles but a decrease in high quantiles. Because quantile functions in the BSTQR model vary with space and time and assimilate spatiotemporal precipitation data, the BSTQR model produced much spatially smoother and less uncertain quantile changes than the classic regression without considering spatiotemporal correlations. Using the BSTQR model with five teleconnection indices (i.e., SOI, PDO, PNA, NP and NAO) as covariates, we investigated effects of large-scale climate patterns on Canadian winter precipitation at different quantile levels. Winter precipitation responses to these five teleconnections were found to occur differently at different quantile levels. Effects of five teleconnections on Canadian winter precipitation were stronger at low and high than at medium quantile levels.

Tracing society in climate change: Societal negotiations and physical dynamics of water under climate change conditions in the Cordillera Blanca region, Peru

NASA Astrophysics Data System (ADS)

Neuburger, Martina; Gurgiser, Wolfgang; Maussion, Fabien; Singer, Katrin; Kaser, Georg

2017-04-01

Natural scientists observe and project changes in precipitation and temperature at different spatio-temporal scales and investigate impacts on glaciers and hydrological regimes. Simultaneously, social groups experience ecological phenomena as linked to climate change and integrate them into their understanding of nature and their logics of action, while political actors refer to scientific results as legitimization to focus on adaptation and mitigation strategies on global, national and regional/local level. However, natural and socio-political changes on various scales (regarding time and space) are not directly interlinked, but are communicated by energy and material flows, by discourses, power relations and institutional regulations. In this context, it remains still unclear how natural dynamics are (dis)entangled with societal processes in their historical dimensions and in their interrelations from global via national to regional and local scales. Considering the Cordillera Blanca region in Peru as an example, we analyze the intertwining of scales (global, national, regional, local) and spheres (natural, political, societal) to detect entanglements and disconnections of observed processes. Using the methodology of a time line, we present precipitation variability and glacier recession at different scales, estimate qualitative water availability and investigate the links to the implementation of international and national political programs on climate change adaptation in the Cordillera Blanca region focusing on water and agrarian programs. Finally, we include supposedly contradictory reports of rural population on climate change and related impacts on water availability and agricultural production to analyze the (dis)entanglement due to changing power relations and dominant discourses.

Space-time dependence between energy sources and climate related energy production

NASA Astrophysics Data System (ADS)

Engeland, Kolbjorn; Borga, Marco; Creutin, Jean-Dominique; Ramos, Maria-Helena; Tøfte, Lena; Warland, Geir

2014-05-01

The European Renewable Energy Directive adopted in 2009 focuses on achieving a 20% share of renewable energy in the EU overall energy mix by 2020. A major part of renewable energy production is related to climate, called "climate related energy" (CRE) production. CRE production systems (wind, solar, and hydropower) are characterized by a large degree of intermittency and variability on both short and long time scales due to the natural variability of climate variables. The main strategies to handle the variability of CRE production include energy-storage, -transport, -diversity and -information (smart grids). The three first strategies aim to smooth out the intermittency and variability of CRE production in time and space whereas the last strategy aims to provide a more optimal interaction between energy production and demand, i.e. to smooth out the residual load (the difference between demand and production). In order to increase the CRE share in the electricity system, it is essential to understand the space-time co-variability between the weather variables and CRE production under both current and future climates. This study presents a review of the literature that searches to tackle these problems. It reveals that the majority of studies deals with either a single CRE source or with the combination of two CREs, mostly wind and solar. This may be due to the fact that the most advanced countries in terms of wind equipment have also very little hydropower potential (Denmark, Ireland or UK, for instance). Hydropower is characterized by both a large storage capacity and flexibility in electricity production, and has therefore a large potential for both balancing and storing energy from wind- and solar-power. Several studies look at how to better connect regions with large share of hydropower (e.g., Scandinavia and the Alps) to regions with high shares of wind- and solar-power (e.g., green battery North-Sea net). Considering time scales, various studies consider wind and solar power production and their co-fluctuation at small time scales. The multi-scale nature of the variability is less studied, i.e., the potential adverse or favorable co-fluctuation at intermediate time scales involving water scarcity or abundance, is less present in the literature.Our review points out that it could be especially interesting to promote research on how the pronounced large-scale fluctuations in inflow to hydropower (intra-annual run-off) and smaller scale fluctuations in wind- and solar-power interact in an energy system. There is a need to better represent the profound difference between wind-, solar- and hydro-energy sources. On the one hand, they are all directly linked to the 2-D horizontal dynamics of meteorology. On the other hand, the branching structure of hydrological systems transforms this variability and governs the complex combination of natural inflows and reservoir storage.Finally, we note that the CRE production is, in addition to weather, also influenced by the energy system and market, i.e., the energy transport and demand across scales as well as changes of market regulation. The CRE production system lies thus in this nexus between climate, energy systems and market regulations. The work presented is part of the FP7 project COMPLEX (Knowledge based climate mitigation systems for a low carbon economy; http://www.complex.ac.uk)

Forcing of Climate Variations by Mev-gev Particles

NASA Technical Reports Server (NTRS)

Tinsley, Brian A.

1990-01-01

Changes in ionization production in the lower stratosphere by a few percent during Forbush decreases have been shown to correlate well with changes in winter tropospheric dynamics by a similar relatively small amount. Changes in ionization production by tens of percent on the decadal time scale have been shown to be correlated with changes in winter storm frequencies by tens of percent in the western North Atlantic. Changes in total solar irradiance or solar UV do not have time variations to match the tropospheric variations on the day to day time scales discussed here. Forcing related to magnetic activity is not supported. Thus solar wind/MeV-GeV particle changes appear to be the only viable forcing function for these day to day variations. If solar wind/particle forcing of a few percent amplitude can produce short term weather responses, then observed changes by tens of percent on the decadal and centennial time scale could produce climate changes on these longer time scales. The changes in circulation involved would produce regional climate changes, as observed. At present the relations between stratospheric ionization, electric fields and chemistry and aerosol and cloud microphysics are as poorly known as the relations between the latter and storm feedback processes. However, the capability for investigating these relationships now exists and has recently been most successfully used for elucidating the stratospheric chemistry and cloud microphysics associated with the Antarctic ozone hole. The economic benefits of being able to predict winter severity on an interannual basis, and the extent to which climate change related to solar variability will add to or substract from the greenhouse effect, should be more than adequate to justify support for research in this area.

New watershed-based climate forecast products for hydrologists and water managers

NASA Astrophysics Data System (ADS)

Baker, S. A.; Wood, A.; Rajagopalan, B.; Lehner, F.; Peng, P.; Ray, A. J.; Barsugli, J. J.; Werner, K.

2017-12-01

Operational sub-seasonal to seasonal (S2S) climate predictions have advanced in skill in recent years but are yet to be broadly utilized by stakeholders in the water management sector. While some of the challenges that relate to fundamental predictability are difficult or impossible to surmount, other hurdles related to forecast product formulation, translation, relevance, and accessibility can be directly addressed. These include products being misaligned with users' space-time needs, products disseminated in formats users cannot easily process, and products based on raw model outputs that are biased relative to user climatologies. In each of these areas, more can be done to bridge the gap by enhancing the usability, quality, and relevance of water-oriented predictions. In addition, water stakeholder impacts can benefit from short-range extremes predictions (such as 2-3 day storms or 1-week heat waves) at S2S time-scales, for which few products exist. We present interim results of a Research to Operations (R2O) effort sponsored by the NOAA MAPP Climate Testbed to (1) formulate climate prediction products so as to reduce hurdles to in water stakeholder adoption, and to (2) explore opportunities for extremes prediction at S2S time scales. The project is currently using CFSv2 and National Multi-­Model Ensemble (NMME) reforecasts and forecasts to develop real-time watershed-based climate forecast products, and to train post-processing approaches to enhance the skill and reliability of raw real-time S2S forecasts. Prototype S2S climate data products (forecasts and associated skill analyses) are now being operationally staged at NCAR on a public website to facilitate further product development through interactions with water managers. Initial demonstration products include CFSv2-based bi-weekly climate forecasts (weeks 1-2, 2-3, and 3-4) for sub-regional scale hydrologic units, and NMME-based monthly and seasonal prediction products. Raw model mean skill at these time-space resolutions for some periods (e.g., weeks 3-4) is unusably low, but for other periods, and for multi-month leads with NMME, precipitation and particularly temperature forecasts exhibit useful skill. Website: http://hydro.rap.ucar.edu/s2s/

Regional hydro-climatic impacts of contemporary Amazonian deforestation

NASA Astrophysics Data System (ADS)

Khanna, Jaya

More than 17% of the Amazon rainforest has been cleared in the past three decades triggering important climatological and societal impacts. This thesis is devoted to identifying and explaining the regional hydroclimatic impacts of this change employing multidecadal satellite observations and numerical simulations providing an integrated perspective on this topic. The climatological nature of this study motivated the implementation and application of a cloud detection technique to a new geostationary satellite dataset. The resulting sub daily, high spatial resolution, multidecadal time series facilitated the detection of trends and variability in deforestation triggered cloud cover changes. The analysis was complemented by satellite precipitation, reanalysis and ground based datasets and attribution with the variable resolution Ocean-Land-Atmosphere-Model. Contemporary Amazonian deforestation affects spatial scales of hundreds of kilometers. But, unlike the well-studied impacts of a few kilometers scale deforestation, the climatic response to contemporary, large scale deforestation is neither well observed nor well understood. Employing satellite datasets, this thesis shows a transition in the regional hydroclimate accompanying increasing scales of deforestation, with downwind deforested regions receiving 25% more and upwind deforested regions receiving 25% less precipitation from the deforested area mean. Simulations robustly reproduce these shifts when forced with increasing deforestation alone, suggesting a negligible role of large-scale decadal climate variability in causing the shifts. Furthermore, deforestation-induced surface roughness variations are found necessary to reproduce the observed spatial patterns in recent times illustrating the strong scale-sensitivity of the climatic response to Amazonian deforestation. This phenomenon, inconsequential during the wet season, is found to substantially affect the regional hydroclimate in the local dry and parts of transition seasons, hence occurring in atmospheric conditions otherwise less conducive to thermal convection. Evidence of this phenomenon is found at two large scale deforested areas considered in this thesis. Hence, the 'dynamical' mechanism, which affects the seasons most important for regional ecology, emerges as an impactful convective triggering mechanism. The phenomenon studied in this thesis provides context for thinking about the climate of a future, more patchily forested Amazonia, by articulating relationships between climate and spatial scales of deforestation.

Potential for added value in precipitation simulated by high-resolution nested Regional Climate Models and observations

NASA Astrophysics Data System (ADS)

di Luca, Alejandro; de Elía, Ramón; Laprise, René

2012-03-01

Regional Climate Models (RCMs) constitute the most often used method to perform affordable high-resolution regional climate simulations. The key issue in the evaluation of nested regional models is to determine whether RCM simulations improve the representation of climatic statistics compared to the driving data, that is, whether RCMs add value. In this study we examine a necessary condition that some climate statistics derived from the precipitation field must satisfy in order that the RCM technique can generate some added value: we focus on whether the climate statistics of interest contain some fine spatial-scale variability that would be absent on a coarser grid. The presence and magnitude of fine-scale precipitation variance required to adequately describe a given climate statistics will then be used to quantify the potential added value (PAV) of RCMs. Our results show that the PAV of RCMs is much higher for short temporal scales (e.g., 3-hourly data) than for long temporal scales (16-day average data) due to the filtering resulting from the time-averaging process. PAV is higher in warm season compared to cold season due to the higher proportion of precipitation falling from small-scale weather systems in the warm season. In regions of complex topography, the orographic forcing induces an extra component of PAV, no matter the season or the temporal scale considered. The PAV is also estimated using high-resolution datasets based on observations allowing the evaluation of the sensitivity of changing resolution in the real climate system. The results show that RCMs tend to reproduce relatively well the PAV compared to observations although showing an overestimation of the PAV in warm season and mountainous regions.

From GCM Output to Local Hydrologic and Ecological Impacts: Integrating Climate Change Projections into Conservation Lands

NASA Astrophysics Data System (ADS)

Weiss, S. B.; Micheli, L.; Flint, L. E.; Flint, A. L.; Thorne, J. H.

2014-12-01

Assessment of climate change resilience, vulnerability, and adaptation options require downscaling of GCM outputs to local scales, and conversion of temperature and precipitation forcings into hydrologic and ecological responses. Recent work in the San Francisco Bay Area, and California demonstrate a practical approach to this process. First, climate futures (GCM x Emissions Scenario) are screened using cluster analysis for seasonal precipitation and temperature, to select a tractable subset of projections that still represent the range of climate projections. Second, monthly climate projections are downscaled to 270m and the Basin Characterization Model (BCM) applied, to generate fine-scale recharge, runoff, actual evapotranspiration (AET), and climatic water deficit (CWD) accounting for soils, bedrock geology, topography, and local climate. Third, annual time-series are used to derive 30-year climatologies and recurrence intervals of extreme events (including multi-year droughts) at the scale of small watersheds and conservation parcels/networks. We take a "scenario-neutral" approach where thresholds are defined for system "failure," such as water supply shortfalls or drought mortality/vegetation transitions, and the time-window for hitting those thresholds is evaluated across all selected climate projections. San Francisco Bay Area examples include drought thresholds (CWD) for specific vegetation-types that identify leading/trailing edges and local refugia, evaluation of hydrologic resources (recharge and runoff) provided by conservation lands, and productivity of rangelands (AET). BCM outputs for multiple futures are becoming available to resource managers through on-line data extraction tools. This approach has wide applicability to numerous resource management issues.

Weak climatic control of stand-scale fire history during the late holocene.

PubMed

Gavin, Daniel G; Hu, Feng Sheng; Lertzman, Kenneth; Corbett, Peter

2006-07-01

Forest fire occurrence is affected by multiple controls that operate at local to regional scales. At the spatial scale of forest stands, regional climatic controls may be obscured by local controls (e.g., stochastic ignitions, topography, and fuel loads), but the long-term role of such local controls is poorly understood. We report here stand-scale (<100 ha) fire histories of the past 5000 years based on the analysis of sediment charcoal at two lakes 11 km apart in southeastern British Columbia. The two lakes are today located in similar subalpine forests, and they likely have experienced the same late-Holocene climatic changes because of their close proximity. We evaluated two independent properties of fire history: (1) fire-interval distribution, a measure of the overall incidence of fire, and (2) fire synchroneity, a measure of the co-occurrence of fire (here, assessed at centennial to millennial time scales due to the resolution of sediment records). Fire-interval distributions differed between the sites prior to, but not after, 2500 yr before present. When the entire 5000-yr period is considered, no statistical synchrony between fire-episode dates existed between the two sites at any temporal scale, but for the last 2500 yr marginal levels of synchrony occurred at centennial scales. Each individual fire record exhibited little coherency with regional climate changes. In contrast, variations in the composite record (average of both sites) matched variations in climate evidenced by late-Holocene glacial advances. This was probably due to the increased sample size and spatial extent represented by the composite record (up to 200 ha) plus increased regional climatic variability over the last several millennia, which may have partially overridden local, non-climatic controls. We conclude that (1) over past millennia, neighboring stands with similar modern conditions may have experienced different fire intervals and asynchronous patterns in fire episodes, likely because local controls outweighed the synchronizing effect of climate; (2) the influence of climate on fire occurrence is more strongly expressed when climatic variability is relatively great; and (3) multiple records from a region are essential if climate-fire relations are to be reliably described.

Quantification of scaling exponents and dynamical complexity of microwave refractivity in a tropical climate

NASA Astrophysics Data System (ADS)

Fuwape, Ibiyinka A.; Ogunjo, Samuel T.

2016-12-01

Radio refractivity index is used to quantify the effect of atmospheric parameters in communication systems. Scaling and dynamical complexities of radio refractivity across different climatic zones of Nigeria have been studied. Scaling property of the radio refractivity across Nigeria was estimated from the Hurst Exponent obtained using two different scaling methods namely: The Rescaled Range (R/S) and the detrended fluctuation analysis(DFA). The delay vector variance (DVV), Largest Lyapunov Exponent (λ1) and Correlation Dimension (D2) methods were used to investigate nonlinearity and the results confirm the presence of deterministic nonlinear profile in the radio refractivity time series. The recurrence quantification analysis (RQA) was used to quantify the degree of chaoticity in the radio refractivity across the different climatic zones. RQA was found to be a good measure for identifying unique fingerprint and signature of chaotic time series data. Microwave radio refractivity was found to be persistent and chaotic in all the study locations. The dynamics of radio refractivity increases in complexity and chaoticity from the Coastal region towards the Sahelian climate. The design, development and deployment of robust and reliable microwave communication link in the region will be greatly affected by the chaotic nature of radio refractivity in the region.

On the relationship between large-scale climate modes and regional synoptic patterns that drive Victorian rainfall

NASA Astrophysics Data System (ADS)

Verdon-Kidd, D. C.; Kiem, A. S.

2009-04-01

In this paper regional (synoptic) and large-scale climate drivers of rainfall are investigated for Victoria, Australia. A non-linear classification methodology known as self-organizing maps (SOM) is used to identify 20 key regional synoptic patterns, which are shown to capture a range of significant synoptic features known to influence the climate of the region. Rainfall distributions are assigned to each of the 20 patterns for nine rainfall stations located across Victoria, resulting in a clear distinction between wet and dry synoptic types at each station. The influence of large-scale climate modes on the frequency and timing of the regional synoptic patterns is also investigated. This analysis revealed that phase changes in the El Niño Southern Oscillation (ENSO), the Indian Ocean Dipole (IOD) and/or the Southern Annular Mode (SAM) are associated with a shift in the relative frequency of wet and dry synoptic types on an annual to inter-annual timescale. In addition, the relative frequency of synoptic types is shown to vary on a multi-decadal timescale, associated with changes in the Inter-decadal Pacific Oscillation (IPO). Importantly, these results highlight the potential to utilise the link between the regional synoptic patterns derived in this study and large-scale climate modes to improve rainfall forecasting for Victoria, both in the short- (i.e. seasonal) and long-term (i.e. decadal/multi-decadal scale). In addition, the regional and large-scale climate drivers identified in this study provide a benchmark by which the performance of Global Climate Models (GCMs) may be assessed.

Two sides of the same coin? Exploring the relationship between Petén-Itzá and Cariaco Basin pollen records

NASA Astrophysics Data System (ADS)

Gonzalez, C.; Correa-Metrio, A.

2013-05-01

Millennial time-scale climate changes from the high latitudes seem to have had a profound effect on Neotropical terrestrial and marine biota during the last glacial cycle. By comparing high resolution palynological data from the Yucatán Peninsula (Lake Petén-Itzá) and Cariaco Basin off Venezuelan coast during the last 70,000 years, we Intend to gain insight into the climatic linkages that existed between both regions. Specifically, we examine the role of atmospheric linking mechanisms like the ITCZ in driving synchronous changes in both palynological records. At millennial time-scales striking similarities appear between the dynamics of drought-indicative taxa (e.g. Poaceae) in Yucatán and riverine input-indicative taxa (Spiniferites) in Cariaco Basin suggesting that both systems responded to the same forcing almost simultaneously. At orbital time-scales, we explore the profound ecological changes that occurred in both sites at ca. 60 kyr that might be related to the shift from glacial to interglacial climatic conditions.

Real-time monitoring of smallholder farmer responses to intra-seasonal climate variability in central Kenya

NASA Astrophysics Data System (ADS)

Krell, N.; Evans, T. P.; Estes, L. D.; Caylor, K. K.

2017-12-01

While international metrics of food security and water availability are generated as spatial averages at the regional to national levels, climate variability impacts are differentially felt at the household level. This project investigated scales of variability of climate impacts on smallholder farmers using social and environmental data in central Kenya. Using sub-daily real-time environmental measurements to monitor smallholder agriculture, we investigated how changes in seasonal precipitation affected food security around Laikipia county from September 2015 to present. We also conducted SMS-based surveys of over 700 farmers to understand farmers' decision-making within the growing season. Our results highlight field-scale heterogeneity in biophysical and social factors governing crop yields using locally sensed real-time environmental data and weekly farmer-reported information about planting, harvesting, irrigation, and crop yields. Our preliminary results show relationships between changes in seasonal precipitation, NDVI, and soil moisture related to crop yields and decision-making at several scales. These datasets present a unique opportunity to collect highly spatially and temporally resolved information from data-poor regions at the household level.

Green roofs'retention performances in different climates

NASA Astrophysics Data System (ADS)

Viola, Francesco; Hellies, Matteo; Deidda, Roberto

2017-04-01

The ongoing process of global urbanization contributes to increasing stormwater runoff from impervious surfaces, threatening also water quality. Green roofs have been proved to be an innovative stormwater management tool to partially restore natural state, enhancing interception, infiltration and evapotranspiration fluxes. The amount of water that is retained within green roofs depends mainly on both soil properties and climate. The evaluation of the retained water is not trivial since it depends on the stochastic soil moisture dynamics. The aim of this work is to explore performances of green roofs, in terms of water retention, as a function of their depth considering different climate regimes. The role of climate in driving water retention has been mainly represented by rainfall and potential evapotranspiration dynamics, which are simulated by a simple conceptual weather generator at daily time scale. The model is able to describe seasonal (in-phase and counter-phase) and stationary behaviors of climatic forcings. Model parameters have been estimated on more than 20,000 historical time series retrieved worldwide. Exemplifying cases are discussed for five different climate scenarios, changing the amplitude and/or the phase of daily mean rainfall and evapotranspiration forcings. The first scenario represents stationary climates, in two other cases the daily mean rainfall or the potential evapotranspiration evolve sinusoidally. In the latter two cases, we simulated the in-phase or in counter-phase conditions. Stochastic forcings have been then used as an input to a simple conceptual hydrological model which simulate soil moisture dynamics, evapotranspiration fluxes, runoff and leakage from soil pack at daily time scale. For several combinations of annual rainfall and potential evapotranspiration, the analysis allowed assessing green roofs' retaining capabilities, at annual time scale. Provided abacus allows a first approximation of possible hydrological benefits deriving from the implementation of intensive or extensive green roofs in different world areas, i.e. less input to sewer systems.

Polar process and world climate /A brief overview/

NASA Technical Reports Server (NTRS)

Goody, R.

1980-01-01

A review is presented of events relating polar regions to the world climate, the mechanisms of sea ice and polar ice sheets, and of two theories of the Pleistocene Ice Ages. The sea ice which varies over time scales of one or two years and the polar ice sheets with time changes measured in tens or hundreds of thousands of years introduce two distinct time constants into global time changes; the yearly Arctic sea ice variations affect northern Europe and have some effect over the entire Northern Hemisphere; the ice-albedo coupling in the polar ice sheets is involved in major climatic events such as the Pleistocene ice ages. It is concluded that climate problems require a global approach including the atmosphere, the oceans, and the cryosphere.

Correlation Lengths for Estimating the Large-Scale Carbon and Heat Content of the Southern Ocean

NASA Astrophysics Data System (ADS)

Mazloff, M. R.; Cornuelle, B. D.; Gille, S. T.; Verdy, A.

2018-02-01

The spatial correlation scales of oceanic dissolved inorganic carbon, heat content, and carbon and heat exchanges with the atmosphere are estimated from a realistic numerical simulation of the Southern Ocean. Biases in the model are assessed by comparing the simulated sea surface height and temperature scales to those derived from optimally interpolated satellite measurements. While these products do not resolve all ocean scales, they are representative of the climate scale variability we aim to estimate. Results show that constraining the carbon and heat inventory between 35°S and 70°S on time-scales longer than 90 days requires approximately 100 optimally spaced measurement platforms: approximately one platform every 20° longitude by 6° latitude. Carbon flux has slightly longer zonal scales, and requires a coverage of approximately 30° by 6°. Heat flux has much longer scales, and thus a platform distribution of approximately 90° by 10° would be sufficient. Fluxes, however, have significant subseasonal variability. For all fields, and especially fluxes, sustained measurements in time are required to prevent aliasing of the eddy signals into the longer climate scale signals. Our results imply a minimum of 100 biogeochemical-Argo floats are required to monitor the Southern Ocean carbon and heat content and air-sea exchanges on time-scales longer than 90 days. However, an estimate of formal mapping error using the current Argo array implies that in practice even an array of 600 floats (a nominal float density of about 1 every 7° longitude by 3° latitude) will result in nonnegligible uncertainty in estimating climate signals.

Calibration of decadal ensemble predictions

NASA Astrophysics Data System (ADS)

Pasternack, Alexander; Rust, Henning W.; Bhend, Jonas; Liniger, Mark; Grieger, Jens; Müller, Wolfgang; Ulbrich, Uwe

2017-04-01

Decadal climate predictions are of great socio-economic interest due to the corresponding planning horizons of several political and economic decisions. Due to uncertainties of weather and climate, forecasts (e.g. due to initial condition uncertainty), they are issued in a probabilistic way. One issue frequently observed for probabilistic forecasts is that they tend to be not reliable, i.e. the forecasted probabilities are not consistent with the relative frequency of the associated observed events. Thus, these kind of forecasts need to be re-calibrated. While re-calibration methods for seasonal time scales are available and frequently applied, these methods still have to be adapted for decadal time scales and its characteristic problems like climate trend and lead time dependent bias. Regarding this, we propose a method to re-calibrate decadal ensemble predictions that takes the above mentioned characteristics into account. Finally, this method will be applied and validated to decadal forecasts from the MiKlip system (Germany's initiative for decadal prediction).

Climate effects of non-compliant Volkswagen diesel cars

NASA Astrophysics Data System (ADS)

Tanaka, Katsumasa; Lund, Marianne T.; Aamaas, Borgar; Berntsen, Terje

2018-04-01

On-road operations of Volkswagen light-duty diesel vehicles equipped with defeat devices cause emissions of NOx up to 40 times above emission standards. Higher on-road NOx emissions are a widespread problem not limited to Volkswagen vehicles, but the Volkswagen violations brought this issue under the spotlight. While several studies investigated the health impacts of high NOx emissions, the climatic impacts have not been quantified. Here we show that such diesel cars generate a larger warming on the time scale of several years but a smaller warming on the decadal time scale during actual on-road operations than in vehicle certification tests. The difference in longer-term warming levels, however, depends on underlying driving conditions. Furthermore, in the presence of defeat devices, the climatic advantage of ‘clean diesel’ cars over gasoline cars, in terms of global-mean temperature change, is in our view not necessarily the case.

Short-term climate change impacts on Mara basin hydrology

NASA Astrophysics Data System (ADS)

Demaria, E. M.; Roy, T.; Valdés, J. B.; Lyon, B.; Valdés-Pineda, R.; Serrat-Capdevila, A.; Durcik, M.; Gupta, H.

2017-12-01

The predictability of climate diminishes significantly at shorter time scales (e.g. decadal). Both natural variability as well as sampling variability of climate can obscure or enhance climate change signals in these shorter scales. Therefore, in order to assess the impacts of climate change on basin hydrology, it is important to design climate projections with exhaustive climate scenarios. In this study, we first create seasonal climate scenarios by combining (1) synthetic precipitation projections generated from a Vector Auto-Regressive (VAR) model using the University of East Anglia Climate Research Unit (UEA-CRU) data with (2) seasonal trends calculated from 31 models in the Coupled Model Intercomparison Project Phase 5 (CMIP). The seasonal climate projections are then disaggregated to daily level using the Agricultural Modern-Era Retrospective Analysis for Research and Applications (AgMERRA) data. The daily climate data are then bias-corrected and used as forcings to the land-surface model, Variable Infiltration Capacity (VIC), to generate different hydrological projections for the Mara River basin in East Africa, which are then evaluated to study the hydrologic changes in the basin in the next three decades (2020-2050).

Using decadal climate prediction to characterize and manage changing drought and flood risks in Colorado

NASA Astrophysics Data System (ADS)

Lazrus, H.; Done, J.; Morss, R. E.

2017-12-01

A new branch of climate science, known as decadal prediction, seeks to predict the time-varying trajectory of climate over the next 3-30 years and not just the longer-term trends. Decadal predictions bring climate information into the time horizon of decision makers, particularly those tasked with managing water resources and floods whose master planning is often on the timescale of decades. Information from decadal predictions may help alleviate some aspects of vulnerability by helping to inform decisions that reduce drought and flood exposure and increase adaptive capacities including preparedness, response, and recovery. This presentation will highlight an interdisciplinary project - involving atmospheric and social scientists - on the development of decadal climate information and its use in decision making. The presentation will explore the skill and utility of decadal drought and flood prediction along Colorado's Front Range, an area experiencing rapid population growth and uncertain climate variability and climate change impacts. Innovative statistical and dynamical atmospheric modeling techniques explore the extent to which Colorado precipitation can be predicted on decadal scales using remote Pacific Ocean surface temperature patterns. Concurrently, stakeholder interviews with flood managers in Colorado are being used to explore the potential utility of decadal climate information. Combining the modeling results with results from the stakeholder interviews shows that while there is still significant uncertainty surrounding precipitation on decadal time scales, relevant and well communicated decadal information has potential to be useful for drought and flood management.

Disentangling the effects of climate variability and functional change on ecosystem carbon dynamics using semi-empirical modelling

NASA Astrophysics Data System (ADS)

Wu, J.; van der Linden, L.; Lasslop, G.; Carvalhais, N.; Pilegaard, K.; Beier, C.; Ibrom, A.

2012-04-01

The ecosystem carbon balance is affected by both external climatic forcing (e.g. solar radiation, air temperature and humidity) and internal dynamics in the ecosystem functional properties (e.g. canopy structure, leaf photosynthetic capacity and carbohydrate reserve). In order to understand to what extent and at which temporal scale, climatic variability and functional changes regulated the interannual variation (IAV) in the net ecosystem exchange of CO2 (NEE), data-driven analysis and semi-empirical modelling (Lasslop et al. 2010) were performed based on a 13 year NEE record in a temperate deciduous forest (Pilegaard et al 2011, Wu et al. 2012). We found that the sensitivity of carbon fluxes to climatic variability was significantly higher at shorter than at longer time scales and changed seasonally. This implied that the changing distribution of climate anomalies during the vegetation period could have stronger impacts on future ecosystem carbon balances than changes in average climate. At the annual time scale, approximately 80% of the interannual variability in NEE was attributed to the variation in the model parameters, indicating the observed IAV in the carbon dynamics at the investigated site was dominated by changes in ecosystem functioning. In general this study showed the need for understanding the mechanisms of ecosystem functional change. The method can be applied at other sites to explore ecosystem behavior across different plant functional types and climate gradients. Incorporating ecosystem functional change into process based models will reduce the uncertainties in long-term predictions of ecosystem carbon balances in global climate change projections. Acknowledgements. This work was supported by the EU FP7 project CARBO-Extreme, the DTU Climate Centre and the Danish national project ECOCLIM (Danish Council for Strategic Research).

A note on Bjerkne's hypothesis for North Atlantic variability

NASA Astrophysics Data System (ADS)

Bryan, Kirk; Stouffer, Ron

1991-01-01

On decadal time-scales the historical surface temperature record over land in the Northern Hemisphere is dominated by polar amplified variations. These variations are coherent with SST anomalies concentrated in the Northwest Atlantic, but extending with lesser amplitude into the North Pacific as well. Bierknes suggested that multi-year SST anomalies in the subpolar North Atlantic were due to irregular changes in the intensity of the thermohaline circulation. In support of the Bjerknes hypothesis there is evidence that winter overturning in the Labrador Sea was suppressed for a brief period from 1967-1969 by a cap of relative fresh water at the surface. Cause and effect are unclear, but this event was associated with a marked cooling of the entire Northern Hemisphere. The difference in SST averaged over the Northern Hemisphere oceans and SST averaged over the Southern Hemisphere oceans from the equator to 40°S is coherent with Sahel summer rainfall on decadal time scales. Empirical evidence is supported by numerical experiments with the British Meteorological Office atmospheric climate model which simulate augmented monsoonal rainfall in the Sahel region of Africa in response to realistic warm SST anomalies in the Northwest Atlantic. A coupled ocean-atmosphere global model exhibits two equilibrium climate states. One has an active thermohaline circulation in the North Atlantic and the other does not. The two climate states provide an extreme example which illustrates the type of large scale air sea interaction Bjerknes visualized as a mechanism for North Atlantic climate variability on decadal time-scales.

Simulating 2,368 temperate lakes reveals weak coherence in stratification phenology

USGS Publications Warehouse

Read, Jordan S.; Winslow, Luke A.; Hansen, Gretchen J. A.; Van Den Hoek, Jamon; Hanson, Paul C.; Bruce, Louise C; Markfort, Corey D.

2014-01-01

Changes in water temperatures resulting from climate warming can alter the structure and function of aquatic ecosystems. Lake-specific physical characteristics may play a role in mediating individual lake responses to climate. Past mechanistic studies of lake-climate interactions have simulated generic lake classes at large spatial scales or performed detailed analyses of small numbers of real lakes. Understanding the diversity of lake responses to climate change across landscapes requires a hybrid approach that couples site-specific lake characteristics with broad-scale environmental drivers. This study provides a substantial advancement in lake ecosystem modeling by combining open-source tools with freely available continental-scale data to mechanistically model daily temperatures for 2,368 Wisconsin lakes over three decades (1979-2011). The model accurately predicted observed surface layer temperatures (RMSE: 1.74°C) and the presence/absence of stratification (81.1% agreement). Among-lake coherence was strong for surface temperatures and weak for the timing of stratification, suggesting individual lake characteristics mediate some - but not all - ecologically relevant lake responses to climate.

Solar Variability in the Context of Other Climate Forcing Mechanisms

NASA Technical Reports Server (NTRS)

Hansen, James E.

1999-01-01

I compare and contrast climate forcings due to solar variability with climate forcings due to other mechanisms of climate change, interpretation of the role of the sun in climate change depends upon climate sensitivity and upon the net forcing by other climate change mechanisms. Among the potential indirect climate forcings due to solar variability, only that due to solar cycle induced ozone changes has been well quantified. There is evidence that the sun has been a significant player in past climate change on decadal to century time scales, and that it has the potential to contribute to climate change in the 21st century.

Detecting climate-change responses of plants and soil organic matter using isotopomers

NASA Astrophysics Data System (ADS)

Schleucher, Jürgen; Ehlers, Ina; Segura, Javier; Haei, Mahsa; Augusti, Angela; Köhler, Iris; Zuidema, Pieter; Nilsson, Mats; Öquist, Mats

2015-04-01

Responses of vegetation and soils to environmental changes will strongly influence future climate, and responses on century time scales are most important for feedbacks on the carbon cycle, climate models, prediction of crop productivity, and for adaptation to climate change. That plants respond to increasing CO2 on century time scales has been proven by changes in stomatal index, but very little is known beyond this. In soil, the complexity of soil organic matter (SOM) has hampered a sufficient understanding of the temperature sensitivity of SOM turnover. Here we present new stable isotope methodology that allows detecting shifts in metabolism on long time scales, and elucidating SOM turnover on the molecular level. Compound-specific isotope analysis measures isotope ratios of defined metabolites, but as average of the entire molecule. Here we demonstrate how much more detailed information can be obtained from analyses of intramolecular distributions of stable isotopes, so-called isotopomer abundances. As key tool, we use nuclear magnetic resonance (NMR) spectroscopy, which allows detecting isotope abundance with intramolecular resolution and without risk for isotope fractionation during analysis. Enzyme isotope fractionations create non-random isotopomer patterns in biochemical metabolites. At natural isotope abundance, these patterns continuously store metabolic information. We present a strategy how these patterns can be used as to extract signals on plant physiology, climate variables, and their interactions. Applied in retrospective analyses to herbarium samples and tree-ring series, we detect century-time-scale metabolic changes in response to increasing atmospheric CO2, with no evidence for acclimatory reactions by the plants. In trees, the increase in photosynthesis expected from increasing CO2 ("CO2 fertilization) was diminished by increasing temperatures, which resolves the discrepancy between expected increases in photosynthesis and commonly observed lack of biomass increases. Isotopomer patterns are a rich source of metabolic information, which can be retrieved from archives of plant material covering centuries and millennia, the time scales relevant for climate change. Boreal soils contain a huge carbon pool that may be particularly vulnerable to climate change. Biological activity persists in soils under frozen conditions, but it is largely unknown what controls it, and whether it differs from unfrozen conditions. In an incubation experiment, we traced the metabolism of 13C-labeled cellulose by soil microorganisms. NMR analysis revealed that the 13C label was converted both to respired CO2 and to phospholipid fatty acids, indicating that the polymeric substrate cellulose entered both catabolic and anabolic pathways. Both applications demonstrate a fundamental advantage of isotopomer analysis, namely that their abundances directly reflect biochemical processes. This allows obtaining metabolic information on millennial time scales, thus bridging between plant-physiology and paleo sciences. It may also be key to characterizing SOM with sufficient resolution to understand current biogeochemical fluxes involving SOM and to identify molecular components and organisms that are key for SOM turnover.

Hydrological response of karst systems to large-scale climate variability for different catchments of the French karst observatory network INSU/CNRS SNO KARST

NASA Astrophysics Data System (ADS)

Massei, Nicolas; Labat, David; Jourde, Hervé; Lecoq, Nicolas; Mazzilli, Naomi

2017-04-01

The french karst observatory network SNO KARST is a national initiative from the National Institute for Earth Sciences and Astronomy (INSU) of the National Center for Scientific Research (CNRS). It is also part of the new french research infrastructure for the observation of the critical zone OZCAR. SNO KARST is composed by several karst sites distributed over conterminous France which are located in different physiographic and climatic contexts (Mediterranean, Pyrenean, Jura mountain, western and northwestern shore near the Atlantic or the English Channel). This allows the scientific community to develop advanced research and experiments dedicated to improve understanding of the hydrological functioning of karst catchments. Here we used several sites of SNO KARST in order to assess the hydrological response of karst catchments to long-term variation of large-scale atmospheric circulation. Using NCEP reanalysis products and karst discharge, we analyzed the links between large-scale circulation and karst water resources variability. As karst hydrosystems are highly heterogeneous media, they behave differently across different time-scales : we explore the large-scale/local-scale relationships according to time-scales using a wavelet multiresolution approach of both karst hydrological variables and large-scale climate fields such as sea level pressure (SLP). The different wavelet components of karst discharge in response to the corresponding wavelet component of climate fields are either 1) compared to physico-chemical/geochemical responses at karst springs, or 2) interpreted in terms of hydrological functioning by comparing discharge wavelet components to internal components obtained from precipitation/discharge models using the KARSTMOD conceptual modeling platform of SNO KARST.

Unravelling connections between river flow and large-scale climate: experiences from Europe

NASA Astrophysics Data System (ADS)

Hannah, D. M.; Kingston, D. G.; Lavers, D.; Stagge, J. H.; Tallaksen, L. M.

2016-12-01

The United Nations has identified better knowledge of large-scale water cycle processes as essential for socio-economic development and global water-food-energy security. In this context, and given the ever-growing concerns about climate change/ variability and human impacts on hydrology, there is an urgent research need: (a) to quantify space-time variability in regional river flow, and (b) to improve hydroclimatological understanding of climate-flow connections as a basis for identifying current and future water-related issues. In this paper, we draw together studies undertaken at the pan-European scale: (1) to evaluate current methods for assessing space-time dynamics for different streamflow metrics (annual regimes, low flows and high flows) and for linking flow variability to atmospheric drivers (circulation indices, air-masses, gridded climate fields and vapour flux); and (2) to propose a plan for future research connecting streamflow and the atmospheric conditions in Europe and elsewhere. We believe this research makes a useful, unique contribution to the literature through a systematic inter-comparison of different streamflow metrics and atmospheric descriptors. In our findings, we highlight the need to consider appropriate atmospheric descriptors (dependent on the target flow metric and region of interest) and to develop analytical techniques that best characterise connections in the ocean-atmosphere-land surface process chain. We call for the need to consider not only atmospheric interactions, but also the role of the river basin-scale terrestrial hydrological processes in modifying the climate signal response of river flows.

Does climate variability influence the demography of wild primates? Evidence from long-term life-history data in seven species.

PubMed

Campos, Fernando A; Morris, William F; Alberts, Susan C; Altmann, Jeanne; Brockman, Diane K; Cords, Marina; Pusey, Anne; Stoinski, Tara S; Strier, Karen B; Fedigan, Linda M

2017-11-01

Earth's rapidly changing climate creates a growing need to understand how demographic processes in natural populations are affected by climate variability, particularly among organisms threatened by extinction. Long-term, large-scale, and cross-taxon studies of vital rate variation in relation to climate variability can be particularly valuable because they can reveal environmental drivers that affect multiple species over extensive regions. Few such data exist for animals with slow life histories, particularly in the tropics, where climate variation over large-scale space is asynchronous. As our closest relatives, nonhuman primates are especially valuable as a resource to understand the roles of climate variability and climate change in human evolutionary history. Here, we provide the first comprehensive investigation of vital rate variation in relation to climate variability among wild primates. We ask whether primates are sensitive to global changes that are universal (e.g., higher temperature, large-scale climate oscillations) or whether they are more sensitive to global change effects that are local (e.g., more rain in some places), which would complicate predictions of how primates in general will respond to climate change. To address these questions, we use a database of long-term life-history data for natural populations of seven primate species that have been studied for 29-52 years to investigate associations between vital rate variation, local climate variability, and global climate oscillations. Associations between vital rates and climate variability varied among species and depended on the time windows considered, highlighting the importance of temporal scale in detection of such effects. We found strong climate signals in the fertility rates of three species. However, survival, which has a greater impact on population growth, was little affected by climate variability. Thus, we found evidence for demographic buffering of life histories, but also evidence of mechanisms by which climate change could affect the fates of wild primates. © 2017 John Wiley & Sons Ltd.

Cosmogenic radionuclides as a synchronisation tool - present status

NASA Astrophysics Data System (ADS)

Muscheler, Raimund; Adolphi, Florian; Mekhaldi, Florian; Mellström, Anette; Svensson, Anders; Aldahan, Ala; Possnert, Göran

2014-05-01

Changes in the flux of galactic cosmic rays into Earth's atmosphere produce variations in the production rates of cosmogenic radionuclides. The resulting globally synchronous signal in cosmogenic radionuclide records can be used to compare time scales and synchronise climate records. The most prominent example is the 14C wiggle match dating approach where variations in the atmospheric 14C concentration are used to match climate records and the tree-ring based part of the 14C calibration record. This approach can be extended to other cosmogenic radionuclide records such as 10Be time series provided that the different geochemical behaviour of 10Be and 14C is taken into account. Here we will present some recent results that illustrate the potential of using cosmogenic radionuclide records for comparing and synchronising different time scales. The focus will be on the last 50000 years where we will show examples how geomagnetic field, solar activity and unusual short-term cosmic ray changes can be used for comparing ice core, tree ring and sediment time scales. We will discuss some unexpected offsets between Greenland ice core and 14C time scale and we will examine how far back in time solar induced 10Be and 14C variations presently can be used to reliably synchronise ice core and 14C time scales.

A downscaling method for the assessment of local climate change

NASA Astrophysics Data System (ADS)

Bruno, E.; Portoghese, I.; Vurro, M.

2009-04-01

The use of complimentary models is necessary to study the impact of climate change scenarios on the hydrological response at different space-time scales. However, the structure of GCMs is such that their space resolution (hundreds of kilometres) is too coarse and not adequate to describe the variability of extreme events at basin scale (Burlando and Rosso, 2002). To bridge the space-time gap between the climate scenarios and the usual scale of the inputs for hydrological prediction models is a fundamental requisite for the evaluation of climate change impacts on water resources. Since models operate a simplification of a complex reality, their results cannot be expected to fit with climate observations. Identifying local climate scenarios for impact analysis implies the definition of more detailed local scenario by downscaling GCMs or RCMs results. Among the output correction methods we consider the statistical approach by Déqué (2007) reported as a ‘Variable correction method' in which the correction of model outputs is obtained by a function build with the observation dataset and operating a quantile-quantile transformation (Q-Q transform). However, in the case of daily precipitation fields the Q-Q transform is not able to correct the temporal property of the model output concerning the dry-wet lacunarity process. An alternative correction method is proposed based on a stochastic description of the arrival-duration-intensity processes in coherence with the Poissonian Rectangular Pulse scheme (PRP) (Eagleson, 1972). In this proposed approach, the Q-Q transform is applied to the PRP variables derived from the daily rainfall datasets. Consequently the corrected PRP parameters are used for the synthetic generation of statistically homogeneous rainfall time series that mimic the persistency of daily observations for the reference period. Then the PRP parameters are forced through the GCM scenarios to generate local scale rainfall records for the 21st century. The statistical parameters characterizing daily storm occurrence, storm intensity and duration needed to apply the PRP scheme are considered among STARDEX collection of extreme indices.

Are We Telling Decision-makers the Wrong Things - and with Too Much Confidence?

NASA Astrophysics Data System (ADS)

Arnold, J.; Nowak, K. C.; Vano, J. A.; Newman, A. J.; Mizukami, N.; Mendoza, P. A.; Nijssen, B.; Wood, A.; Gutmann, E. D.; Clark, M. P.; Rasmussen, R.

2016-12-01

Water-resource management relies on decision-making over a wide range of space-time scales, nearly none of which maps cleanly onto the scales of current hydroclimatic scenarios of anthropogenic change. Myriad choices are made during vulnerability and impact assessments to quantify the changed-climate sensitivities of models used in that decision-making, including choices of hydrologic models, parameters, and parameterizations; their input forcings determined with various climate downscaling approaches; selected GCMs and output variables to be downscaled; and the forcing emissions scenarios, to name a few. Choosing alternative methods for producing gridded meteorological fields, for examples, can produce very different effects on the projected hydrologic outcomes they drive, with uncertainties across those methods revealed to be as large or larger than the climate change signal itself in some cases. Additionally, many popular climate downscaling methods simply rescale GCM precipitation, producing hydroclimatic projections with too much drizzle, incorrect representations of extreme events, and improper spatial scaling of variables crucial to water-resource vulnerability assessments and, importantly, the decisions they seek to inform. Real-world water-resource vulnerability and impacts assessments can be highly time-sensitive and resource limited, though, so they typically do not confront or even fully represent uncertainties associated with all choices. That deficiency results in assessments built on only partially revealed uncertainties which can misrepresent significant sensitivities and impacts in the final assessments of climate threats and hydrologic vulnerabilities. This talk will describe recent work by the U.S. Army Corps of Engineers, Bureau of Reclamation, University of Washington, and National Center for Atmospheric Research to develop and test methods to characterize more fully the uncertainties in the modeling chain for real-world uses. Examples will illustrate new implementations for communicating that fuller characterization in the ways most useful to inform water-resource management across multiple space-time scales under climate-changed futures.

Global Warming in Geologic Time

ScienceCinema

Archer, David

2018-01-01

The notion is pervasive in the climate science community and in the public at large that the climate impacts of fossil fuel CO2 release will only persist for a few centuries. This conclusion has no basis in theory or models of the atmosphere / ocean carbon cycle, which we review here. The largest fraction of the CO2 recovery will take place on time scales of centuries, as CO2 invades the ocean, but a significant fraction of the fossil fuel CO2, ranging in published models in the literature from 20-60%, remains airborne for a thousand years or longer. Ultimate recovery takes place on time scales of hundreds of thousands of years, a geologic longevity typically associated in public perceptions with nuclear waste. The glacial / interglacial climate cycles demonstrate that ice sheets and sea level respond dramatically to millennial-timescale changes in climate forcing. There are also potential positive feedbacks in the carbon cycle, including methane hydrates in the ocean, and peat frozen in permafrost, that are most sensitive to the long tail of the fossil fuel CO2 in the atmosphere.

Testing the Sun-climate Connection with Paleoclimate Data

NASA Technical Reports Server (NTRS)

Crowley, Thomas J.; Howard, Matthew K.

1990-01-01

If there is a significant sun-climate connection, it should be detectable in high-resolution paleoclimate records. Of particular interest is the last few thousand years, where we have both indices of solar variability (C-14 and Be-10) and climate variations (alpine glaciers, tree rings, ice cores, corals, etc.). Although there are a few exceptions, statistical analyses of solar and climate records generally indicates a flickering relationship between the two -- sometimes it seems to be present, sometimes not. The most repeatable solar climate periods occur at approx. 120 and approx. 56 yrs, although there is also evidence for approx. 420 and approx. 200 yrs. power in some records. However, coherence between solar and climate spectra is usually low, and occurrence of solar spectra in climate records is sometimes dependent on choice of analysis program. These results suggest in general a relatively weak sun-climate link on time scales of decades to centuries. This conclusion is consistent with previous studies and with the observation that inferred climate fluctuations of 1.0 to 1.5 C on this time scale would require solar constant variations of approximately 0.5 to 1.0 percent. This change in forcing is almost an order of magnitude greater than observed changes over the last solar cycle and appears to be on the far-outer limit of acceptable changes for a Maunder Minimum-type event.

Climate change and the past, present, and future of biotic interactions.

PubMed

Blois, Jessica L; Zarnetske, Phoebe L; Fitzpatrick, Matthew C; Finnegan, Seth

2013-08-02

Biotic interactions drive key ecological and evolutionary processes and mediate ecosystem responses to climate change. The direction, frequency, and intensity of biotic interactions can in turn be altered by climate change. Understanding the complex interplay between climate and biotic interactions is thus essential for fully anticipating how ecosystems will respond to the fast rates of current warming, which are unprecedented since the end of the last glacial period. We highlight episodes of climate change that have disrupted ecosystems and trophic interactions over time scales ranging from years to millennia by changing species' relative abundances and geographic ranges, causing extinctions, and creating transient and novel communities dominated by generalist species and interactions. These patterns emerge repeatedly across disparate temporal and spatial scales, suggesting the possibility of similar underlying processes. Based on these findings, we identify knowledge gaps and fruitful areas for research that will further our understanding of the effects of climate change on ecosystems.

Work Environment: A Profile of the Social Climate of Nursing Faculty in an Academic Setting.

ERIC Educational Resources Information Center

Doughty, Jana; May, Barbara; Butell, Sue; Tong, Vivian

2002-01-01

The perceptions of 15 full-time and 7 part-time nursing faculty regarding their work environment at a liberal arts college were gathered using the Moos Work Environment Scale. Scores were congruent in 7 of 10 social climate subscales. Widest discrepancies were in the areas of work pressures, physical comfort, and managerial control. (Contains 42…

The Impact of ARM on Climate Modeling. Chapter 26

NASA Technical Reports Server (NTRS)

Randall, David A.; Del Genio, Anthony D.; Donner, Leo J.; Collins, William D.; Klein, Stephen A.

2016-01-01

Climate models are among humanity's most ambitious and elaborate creations. They are designed to simulate the interactions of the atmosphere, ocean, land surface, and cryosphere on time scales far beyond the limits of deterministic predictability, and including the effects of time-dependent external forcings. The processes involved include radiative transfer, fluid dynamics, microphysics, and some aspects of geochemistry, biology, and ecology. The models explicitly simulate processes on spatial scales ranging from the circumference of the Earth down to one hundred kilometers or smaller, and implicitly include the effects of processes on even smaller scales down to a micron or so. The atmospheric component of a climate model can be called an atmospheric global circulation model (AGCM). In an AGCM, calculations are done on a three-dimensional grid, which in some of today's climate models consists of several million grid cells. For each grid cell, about a dozen variables are time-stepped as the model integrates forward from its initial conditions. These so-called prognostic variables have special importance because they are the only things that a model remembers from one time step to the next; everything else is recreated on each time step by starting from the prognostic variables and the boundary conditions. The prognostic variables typically include information about the mass of dry air, the temperature, the wind components, water vapor, various condensed-water species, and at least a few chemical species such as ozone. A good way to understand how climate models work is to consider the lengthy and complex process used to develop one. Lets imagine that a new AGCM is to be created, starting from a blank piece of paper. The model may be intended for a particular class of applications, e.g., high-resolution simulations on time scales of a few decades. Before a single line of code is written, the conceptual foundation of the model must be designed through a creative envisioning that starts from the intended application and is based on current understanding of how the atmosphere works and the inventory of mathematical methods available.

Reassessing regime shifts in the North Pacific: incremental climate change and commercial fishing are necessary for explaining decadal-scale biological variability.

PubMed

Litzow, Michael A; Mueter, Franz J; Hobday, Alistair J

2014-01-01

In areas of the North Pacific that are largely free of overfishing, climate regime shifts - abrupt changes in modes of low-frequency climate variability - are seen as the dominant drivers of decadal-scale ecological variability. We assessed the ability of leading modes of climate variability [Pacific Decadal Oscillation (PDO), North Pacific Gyre Oscillation (NPGO), Arctic Oscillation (AO), Pacific-North American Pattern (PNA), North Pacific Index (NPI), El Niño-Southern Oscillation (ENSO)] to explain decadal-scale (1965-2008) patterns of climatic and biological variability across two North Pacific ecosystems (Gulf of Alaska and Bering Sea). Our response variables were the first principle component (PC1) of four regional climate parameters [sea surface temperature (SST), sea level pressure (SLP), freshwater input, ice cover], and PCs 1-2 of 36 biological time series [production or abundance for populations of salmon (Oncorhynchus spp.), groundfish, herring (Clupea pallasii), shrimp, and jellyfish]. We found that the climate modes alone could not explain ecological variability in the study region. Both linear models (for climate PC1) and generalized additive models (for biology PC1-2) invoking only the climate modes produced residuals with significant temporal trends, indicating that the models failed to capture coherent patterns of ecological variability. However, when the residual climate trend and a time series of commercial fishery catches were used as additional candidate variables, resulting models of biology PC1-2 satisfied assumptions of independent residuals and out-performed models constructed from the climate modes alone in terms of predictive power. As measured by effect size and Akaike weights, the residual climate trend was the most important variable for explaining biology PC1 variability, and commercial catch the most important variable for biology PC2. Patterns of climate sensitivity and exploitation history for taxa strongly associated with biology PC1-2 suggest plausible mechanistic explanations for these modeling results. Our findings suggest that, even in the absence of overfishing and in areas strongly influenced by internal climate variability, climate regime shift effects can only be understood in the context of other ecosystem perturbations. © 2013 John Wiley & Sons Ltd.

Effects of land-use and climate on Holocene vegetation composition in northern Europe

NASA Astrophysics Data System (ADS)

Marquer, Laurent; Gaillard, Marie-José; Sugita, Shinya; Poska, Anneli; Trondman, Anna-Kari; Mazier, Florence; Nielsen, Anne Birgitte; Fyfe, Ralph; Jönsson, Anna Maria

2016-04-01

Prior to the advent of agriculture, broad-scale vegetation patterns in Europe were controlled primarily by climate. Early agriculture can be detected in palaeovegetation records, but the relative extent to which past regional vegetation was climatically or anthropogenically-forced is of current scientific interest. Using comparisons of transformed pollen data, climate-model data, dynamic vegetation model simulations and anthropogenic land-cover change data, this study aims to estimate the relative impacts of human activities and climate on the Holocene vegetation composition of northern Europe at a subcontinental scale. The REVEALS model was used for pollen-based quantitative reconstruction of vegetation (RV). Climate variables from ECHAM and the extent of human deforestation from KK10 were used as explanatory variables to evaluate their respective impacts on RV. Indices of vegetation-composition changes based on RV and climate-induced vegetation simulated by the LPJ-GUESS model (LPJG) were used to assess the relative importance of climate and anthropogenic impacts. The results show that climate is the major predictor of Holocene vegetation changes until 5000 years ago. The similarity in rate of change and turnover between RV and LPJG decreases after this time. Changes in RV explained by climate and KK10 vary for the last 2000 years; the similarity in rate of change, turnover, and evenness between RV and LPJG decreases to the present. The main conclusions provide important insights on Neolithic forest clearances that affected regional vegetation from 6700 years ago, although climate (temperature and precipitation) still was a major driver of vegetation change (explains 37% of the variation) at the subcontinental scale. Land use became more important around 5000-4000 years ago, while the influence of climate decreased (explains 28% of the variation). Land-use affects all indices of vegetation compositional change during the last 2000 years; the influence of climate on vegetation, although reduced, remains at 16% until modern time while land-use explains 7%, which underlines that North-European vegetation is still climatically sensitive and, therefore, responds strongly to ongoing climate change.

Predicting phenology by integrating ecology, evolution and climate science

USGS Publications Warehouse

Pau, Stephanie; Wolkovich, Elizabeth M.; Cook, Benjamin I.; Davies, T. Jonathan; Kraft, Nathan J.B.; Bolmgren, Kjell; Betancourt, Julio L.; Cleland, Elsa E.

2011-01-01

Forecasting how species and ecosystems will respond to climate change has been a major aim of ecology in recent years. Much of this research has focused on phenology — the timing of life-history events. Phenology has well-demonstrated links to climate, from genetic to landscape scales; yet our ability to explain and predict variation in phenology across species, habitats and time remains poor. Here, we outline how merging approaches from ecology, climate science and evolutionary biology can advance research on phenological responses to climate variability. Using insight into seasonal and interannual climate variability combined with niche theory and community phylogenetics, we develop a predictive approach for species' reponses to changing climate. Our approach predicts that species occupying higher latitudes or the early growing season should be most sensitive to climate and have the most phylogenetically conserved phenologies. We further predict that temperate species will respond to climate change by shifting in time, while tropical species will respond by shifting space, or by evolving. Although we focus here on plant phenology, our approach is broadly applicable to ecological research of plant responses to climate variability.

Variations in evapotranspiration and climate for an Amazonian semi-deciduous forest over seasonal, annual, and El Niño cycles.

PubMed

Vourlitis, George L; de Souza Nogueira, José; de Almeida Lobo, Francisco; Pinto, Osvaldo Borges

2015-02-01

Tropical forests exchange large amounts of water and energy with the atmosphere and are important in controlling regional and global climate; however, climate and evaportranspiration (E) vary significantly across multiple time scales. To better understand temporal patterns in E and climate, we measured the energy balance and meteorology of a semi-deciduous forest in the rainforest-savanna ecotone of northern Mato Grosso, Brazil, over a 7-year period and analyzed regional climate patterns over a 16-year period. Spectral analysis revealed that E and local climate exhibited consistent cycles over annual, seasonal, and weekly time scales. Annual and seasonal cycles were also apparent in the regional monthly rainfall and humidity time series, and a cycle on the order of 3-5.5 years was also apparent in the regional air temperature time series, which is coincident with the average return interval of El Niño. Annual rates of E were significantly affected by the 2002 El Niño. Prior to this event, annual E was on average 1,011 mm/year and accounted for 52% of the annual rainfall, while after, annual E was 931 mm/year and accounted for 42% of the annual rainfall. Our data also suggest that E declined significantly over the 7-year study period while air temperature significantly increased, which was coincident with a long-term, regional warming and drying trend. These results suggest that drought and warming induced by El Niño and/or climate change cause declines in E for semi-deciduous forests of the southeast Amazon Basin.

Variations in evapotranspiration and climate for an Amazonian semi-deciduous forest over seasonal, annual, and El Niño cycles

NASA Astrophysics Data System (ADS)

Vourlitis, George L.; de Souza Nogueira, José; de Almeida Lobo, Francisco; Pinto, Osvaldo Borges

2015-02-01

Tropical forests exchange large amounts of water and energy with the atmosphere and are important in controlling regional and global climate; however, climate and evaportranspiration ( E) vary significantly across multiple time scales. To better understand temporal patterns in E and climate, we measured the energy balance and meteorology of a semi-deciduous forest in the rainforest-savanna ecotone of northern Mato Grosso, Brazil, over a 7-year period and analyzed regional climate patterns over a 16-year period. Spectral analysis revealed that E and local climate exhibited consistent cycles over annual, seasonal, and weekly time scales. Annual and seasonal cycles were also apparent in the regional monthly rainfall and humidity time series, and a cycle on the order of 3-5.5 years was also apparent in the regional air temperature time series, which is coincident with the average return interval of El Niño. Annual rates of E were significantly affected by the 2002 El Niño. Prior to this event, annual E was on average 1,011 mm/year and accounted for 52 % of the annual rainfall, while after, annual E was 931 mm/year and accounted for 42 % of the annual rainfall. Our data also suggest that E declined significantly over the 7-year study period while air temperature significantly increased, which was coincident with a long-term, regional warming and drying trend. These results suggest that drought and warming induced by El Niño and/or climate change cause declines in E for semi-deciduous forests of the southeast Amazon Basin.

A strategy for assessing potential future changes in climate, hydrology, and vegetation in the Western United States

USGS Publications Warehouse

Thompson, Robert Stephen; Hostetler, Steven W.; Bartlein, Patrick J.; Anderson, Katherine H.

1998-01-01

Historical and geological data indicate that significant changes can occur in the Earth's climate on time scales ranging from years to millennia. In addition to natural climatic change, climatic changes may occur in the near future due to increased concentrations of carbon dioxide and other trace gases in the atmosphere that are the result of human activities. International research efforts using atmospheric general circulation models (AGCM's) to assess potential climatic conditions under atmospheric carbon dioxide concentrations of twice the pre-industrial level (a '2 X CO2' atmosphere) conclude that climate would warm on a global basis. However, it is difficult to assess how the projected warmer climatic conditions would be distributed on a regional scale and what the effects of such warming would be on the landscape, especially for temperate mountainous regions such as the Western United States. In this report, we present a strategy to assess the regional sensitivity to global climatic change. The strategy makes use of a hierarchy of models ranging from an AGCM, to a regional climate model, to landscape-scale process models of hydrology and vegetation. A 2 X CO2 global climate simulation conducted with the National Center for Atmospheric Research (NCAR) GENESIS AGCM on a grid of approximately 4.5o of latitude by 7.5o of longitude was used to drive the NCAR regional climate model (RegCM) over the Western United States on a grid of 60 km by 60 km. The output from the RegCM is used directly (for hydrologic models) or interpolated onto a 15-km grid (for vegetation models) to quantify possible future environmental conditions on a spatial scale relevant to policy makers and land managers.

Multiscale complex network analysis: An approach to study spatiotemporal rainfall pattern in south Germany

NASA Astrophysics Data System (ADS)

Agarwal, Ankit; Marwan, Norbert; Rathinasamy, Maheswaran; Oeztuerk, Ugur; Merz, Bruno; Kurths, Jürgen

2017-04-01

Understanding of the climate sytems has been of tremendous importance to different branches such as agriculture, flood, drought and water resources management etc. In this regard, complex networks analysis and time series analysis attracted considerable attention, owing to their potential role in understanding the climate system through characteristic properties. One of the basic requirements in studying climate network dynamics is to identify connections in space or time or space-time, depending upon the purpose. Although a wide variety of approaches have been developed and applied to identify and analyse spatio-temporal relationships by climate networks, there is still further need for improvements in particular when considering precipitation time series or interactions on different scales. In this regard, recent developments in the area of network theory, especially complex networks, offer new avenues, both for their generality about systems and for their holistic perspective about spatio-temporal relationships. The present study has made an attempt to apply the ideas developed in the field of complex networks to examine connections in regional climate networks with particular focus on multiscale spatiotemporal connections. This paper proposes a novel multiscale understanding of regional climate networks using wavelets. The proposed approach is applied to daily precipitation records observed at 543 selected stations from south Germany for a period of 110 years (1901-2010). Further, multiscale community mining is performed on the same study region to shed more light on the underlying processes at different time scales. Various network measure and tools so far employed provide micro-level (individual station) and macro-level (community structure) information of the network. It is interesting to investigate how the result of this study can be useful for future climate predictions and for evaluating climate models on their implementation regarding heavy precipitation. Keywords: Complex network, event synchronization, wavelet, regional climate network, multiscale community mining

Communicating Climate Uncertainties: Challenges and Opportunities Related to Spatial Scales, Extreme Events, and the Warming 'Hiatus'

NASA Astrophysics Data System (ADS)

Casola, J. H.; Huber, D.

2013-12-01

Many media, academic, government, and advocacy organizations have achieved sophistication in developing effective messages based on scientific information, and can quickly translate salient aspects of emerging climate research and evolving observations. However, there are several ways in which valid messages can be misconstrued by decision makers, leading them to inaccurate conclusions about the risks associated with climate impacts. Three cases will be discussed: 1) Issues of spatial scale in interpreting climate observations: Local climate observations may contradict summary statements about the effects of climate change on larger regional or global spatial scales. Effectively addressing these differences often requires communicators to understand local and regional climate drivers, and the distinction between a 'signal' associated with climate change and local climate 'noise.' Hydrological statistics in Missouri and California are shown to illustrate this case. 2) Issues of complexity related to extreme events: Climate change is typically invoked following a wide range of damaging meteorological events (e.g., heat waves, landfalling hurricanes, tornadoes), regardless of the strength of the relationship between anthropogenic climate change and the frequency or severity of that type of event. Examples are drawn from media coverage of several recent events, contrasting useful and potentially confusing word choices and frames. 3) Issues revolving around climate sensitivity: The so-called 'pause' or 'hiatus' in global warming has reverberated strongly through political and business discussions of climate change. Addressing the recent slowdown in warming yields an important opportunity to raise climate literacy in these communities. Attempts to use recent observations as a wedge between climate 'believers' and 'deniers' is likely to be counterproductive. Examples are drawn from Congressional testimony and media stories. All three cases illustrate ways that decision makers can arrive at invalid conclusions from a seemingly valid scientific messages. Honest discussion of uncertainties, and recognition of the spatial and time scales associated with decision making, can work to combat this potential confusion.

Creating Impact Functions to Estimate the Domestic Effects of Global Climate Action

EPA Science Inventory

Quantifying and monetizing the impacts of climate change can be challenging due to the complexity of impacts, availability of data, variability across geographic and temporal time scales, sources of uncertainty, and computational constraints. Recent advancements in using consist...

Climate forcings and feedbacks

NASA Technical Reports Server (NTRS)

Hansen, James

1993-01-01

Global temperature has increased significantly during the past century. Understanding the causes of observed global temperature change is impossible in the absence of adequate monitoring of changes in global climate forcings and radiative feedbacks. Climate forcings are changes imposed on the planet's energy balance, such as change of incoming sunlight or a human-induced change of surface properties due to deforestation. Radiative feedbacks are radiative changes induced by climate change, such as alteration of cloud properties or the extent of sea ice. Monitoring of global climate forcings and feedbacks, if sufficiently precise and long-term, can provide a very strong constraint on interpretation of observed temperature change. Such monitoring is essential to eliminate uncertainties about the relative importance of various climate change mechanisms including tropospheric sulfate aerosols from burning of coal and oil smoke from slash and burn agriculture, changes of solar irradiance changes of several greenhouse gases, and many other mechanisms. The considerable variability of observed temperature, together with evidence that a substantial portion of this variability is unforced indicates that observations of climate forcings and feedbacks must be continued for decades. Since the climate system responds to the time integral of the forcing, a further requirement is that the observations be carried out continuously. However, precise observations of forcings and feedbacks will also be able to provide valuable conclusions on shorter time scales. For example, knowledge of the climate forcing by increasing CFC's relative to the forcing by changing ozone is important to policymakers, as is information on the forcing by CO2 relative to the forcing by sulfate aerosols. It will also be possible to obtain valuable tests of climate models on short time scales, if there is precise monitoring of all forcings and feedbacks during and after events such as a large volcanic eruption or an El Nino.

San Diego Declaration on Climate Change and Fire Management: Ramifications for fuels management

Treesearch

Brian P. Oswald

2007-01-01

Climate plays a central role in shaping fire regimes over long time scales and in generating short-term weather that drives fire events. Recent research suggests that the increasing numbers of large and severe wildfires, lengthened wildfire seasons, and increased area burned are, in part, related to shifts in climate. The historical fire regimes in many ecosystems have...

Detection of the Coupling between Vegetation Leaf Area and Climate in a Multifunctional Watershed, Northwestern China

Treesearch

Lu Hao; Cen Pan; Peilong Liu; Decheng Zhou; Liangxia Zhang; Zhe Xiong; Yongqiang Liu; Ge Sun

2016-01-01

Accurate detection and quantification of vegetation dynamics and drivers of observed climatic and anthropogenic change in space and time is fundamental for our understanding of the atmosphere–biosphere interactions at local and global scales. This case study examined the coupled spatial patterns of vegetation dynamics and climatic variabilities during the past...

Genetic consequences of forest population dynamics influenced by historic climatic variability in the western USA

Treesearch

Robert D. Westfall; Constance I. Millar

2004-01-01

We review recent advances in climate science that show cyclic climatic variation over multiple time scales and give examples of the impacts of this variation on plant populations in the western USA. The paleohistorical reconstructions we review and others indicate that plant specles track these cycles in individualistically complex ways. These dynamic histories suggest...

A Multi-Scale, Integrated Approach to Representing Watershed Systems

NASA Astrophysics Data System (ADS)

Ivanov, Valeriy; Kim, Jongho; Fatichi, Simone; Katopodes, Nikolaos

2014-05-01

Understanding and predicting process dynamics across a range of scales are fundamental challenges for basic hydrologic research and practical applications. This is particularly true when larger-spatial-scale processes, such as surface-subsurface flow and precipitation, need to be translated to fine space-time scale dynamics of processes, such as channel hydraulics and sediment transport, that are often of primary interest. Inferring characteristics of fine-scale processes from uncertain coarse-scale climate projection information poses additional challenges. We have developed an integrated model simulating hydrological processes, flow dynamics, erosion, and sediment transport, tRIBS+VEGGIE-FEaST. The model targets to take the advantage of the current generation of wealth of data representing watershed topography, vegetation, soil, and landuse, as well as to explore the hydrological effects of physical factors and their feedback mechanisms over a range of scales. We illustrate how the modeling system connects precipitation-hydrologic runoff partition process to the dynamics of flow, erosion, and sedimentation, and how the soil's substrate condition can impact the latter processes, resulting in a non-unique response. We further illustrate an approach to using downscaled climate change information with a process-based model to infer the moments of hydrologic variables in future climate conditions and explore the impact of climate information uncertainty.

Climate Engine - Monitoring Drought with Google Earth Engine

NASA Astrophysics Data System (ADS)

Hegewisch, K.; Daudert, B.; Morton, C.; McEvoy, D.; Huntington, J. L.; Abatzoglou, J. T.

2016-12-01

Drought has adverse effects on society through reduced water availability and agricultural production and increased wildfire risk. An abundance of remotely sensed imagery and climate data are being collected in near-real time that can provide place-based monitoring and early warning of drought and related hazards. However, in an era of increasing wealth of earth observations, tools that quickly access, compute, and visualize archives, and provide answers at relevant scales to better inform decision-making are lacking. We have developed ClimateEngine.org, a web application that uses Google's Earth Engine platform to enable users to quickly compute and visualize real-time observations. A suite of drought indices allow us to monitor and track drought from local (30-meters) to regional scales and contextualize current droughts within the historical record. Climate Engine is currently being used by U.S. federal agencies and researchers to develop baseline conditions and impact assessments related to agricultural, ecological, and hydrological drought. Climate Engine is also working with the Famine Early Warning Systems Network (FEWS NET) to expedite monitoring agricultural drought over broad areas at risk of food insecurity globally.

Climatological temperature senstivity of soil carbon turnover: Observations, simple scaling models, and ESMs

NASA Astrophysics Data System (ADS)

Koven, C. D.; Hugelius, G.; Lawrence, D. M.; Wieder, W. R.

2016-12-01

The projected loss of soil carbon to the atmosphere resulting from climate change is a potentially large but highly uncertain feedback to warming. The magnitude of this feedback is poorly constrained by observations and theory, and is disparately represented in Earth system models. To assess the likely long-term response of soils to climate change, spatial gradients in soil carbon turnover times can identify broad-scale and long-term controls on the rate of carbon cycling as a function of climate and other factors. Here we show that the climatological temperature control on carbon turnover in the top meter of global soils is more sensitive in cold climates than in warm ones. We present a simplified model that explains the high cold-climate sensitivity using only the physical scaling of soil freeze-thaw state across climate gradients. Critically, current Earth system models (ESMs) fail to capture this pattern, however it emerges from an ESM that explicitly resolves vertical gradients in soil climate and turnover. The weak tropical temperature sensitivity emerges from a different model that explicitly resolves mineralogical control on decomposition. These results support projections of strong future carbon-climate feedbacks from northern soils and demonstrate a method for ESMs to capture this emergent behavior.

Large-Scale Circulation and Climate Variability. Chapter 5

NASA Technical Reports Server (NTRS)

Perlwitz, J.; Knutson, T.; Kossin, J. P.; LeGrande, A. N.

2017-01-01

The causes of regional climate trends cannot be understood without considering the impact of variations in large-scale atmospheric circulation and an assessment of the role of internally generated climate variability. There are contributions to regional climate trends from changes in large-scale latitudinal circulation, which is generally organized into three cells in each hemisphere-Hadley cell, Ferrell cell and Polar cell-and which determines the location of subtropical dry zones and midlatitude jet streams. These circulation cells are expected to shift poleward during warmer periods, which could result in poleward shifts in precipitation patterns, affecting natural ecosystems, agriculture, and water resources. In addition, regional climate can be strongly affected by non-local responses to recurring patterns (or modes) of variability of the atmospheric circulation or the coupled atmosphere-ocean system. These modes of variability represent preferred spatial patterns and their temporal variation. They account for gross features in variance and for teleconnections which describe climate links between geographically separated regions. Modes of variability are often described as a product of a spatial climate pattern and an associated climate index time series that are identified based on statistical methods like Principal Component Analysis (PC analysis), which is also called Empirical Orthogonal Function Analysis (EOF analysis), and cluster analysis.

The Hydroclimatic Response of the Whitewater River Basin: Influence of Groundwater Time Scales

NASA Astrophysics Data System (ADS)

Beeson, P. C.; Springer, E. P.; Duffy, C. J.

2003-12-01

A near-surface groundwater model was developed to assess the impact of land use and climate variability on the overall water budget of the Whitewater River Basin. The watershed is located in southeastern Kansas within the ARM-SGP as part of the DOE Water Cycle Pilot Study. The Whitewater River Basin has an area of 1,100 square-kilometers, an elevation range of 380 - 470m (amsl), and an average annual precipitation of 858 millimeters. The approach presented here attempts to examine the importance of groundwater in the water budget and hydroclimatic response at the river basin scale. In order to identify the time scales of groundwater in this system, time series and geospatial analyses were used to identify significant spatial structure and dominant temporal modes in the climate, runoff and groundwater response. In this research, we show that the time scales of groundwater baseflow to the river network are proportional to drainage density and position in the hydrologic landscape. The concept of a hydrologic landscape (Winter, JAWRA, April 2001) defines three zones: recharge (upland), translation (intervening steep slopes), and discharge (lowland), and the hydrologic landscape is useful for standardizing the evaluation of physical properties within any watershed. Singular spectrum analysis was used for a 50-year simulation to determine dominant modes and time scales for the hydrologic landscape units in the Whitewater River Basin. We found that the time scale of groundwater baseflow response increases with increasing drainage density. The sensitivity of this response is important to understand and close the water budget for a river basin through observation network design. The effects of climate forcing, both precipitation and evapotranspiration, can be seen through the hydrologic landscapes and channel networks by changes in the baseflow response time. Los Alamos National Laboratory, an affirmative action/equal opportunity employer, is operated by the University of California for the U.S. Department of Energy under contract W-7405-ENG-36.

Palaeoclimate dynamics : a voyage through scales

NASA Astrophysics Data System (ADS)

Crucifix, Michel; Mitsui, Takahito

2015-04-01

Our knowledge of climate dynamics depends on indirect observations of past climate evolution, as well as on what can be inferred from theoretical arguments. At the scale of the Cenozoic, it is common to define a framework of nested time scales, the longest time scale of interest being related to the slow tectonic evolution, then variability associated with or controlled by the astronomical forcing, and finally the fastest dynamics associated with the natural modes of variability of the ocean and the atmosphere. For example, in a model, the astronomical modes of variability may be simulated with deterministic equations under fixed boundary conditions representing the tectonic state, and associated with stochastic parameterisations of the ocean-atmosphere (chaotic) modes of motion. Bifurcations or, more generally, qualitative changes in climate dynamics may be scanned by changing slowly the tectonic state, in order to provide explanations to observed changes in regimes such as the appearance of ice ages and their changes in length or amplitude. The above framework, largely theorized by B. Saltzman, may still be partly justified but is in need of a review. We address here specifically three questions: To what extent astronomical variability interacts with natural modes of ocean - atmosphere variability ? Specifically, how does millennial variability (e.g.: Dansgaard-Oeschger events) fit the Saltzman scheme ? The astronomical forcing is quasi-periodic, and we recently showed that it may produce somewhat counter-intuitive dynamics associated with the emergence of strange non-chaotic attractors. What are the consequences on the spectrum of climate variability ? What are the effects of centennial climate variability on the slow variability of climate ? These three questions are addressed by reference to recently published material, with the objective of emphasising research questions to be explored in the near future.

High Resolution Simulations of Future Climate in West Africa Using a Variable-Resolution Atmospheric Model

NASA Astrophysics Data System (ADS)

Adegoke, J. O.; Engelbrecht, F.; Vezhapparambu, S.

2013-12-01

In previous work demonstrated the application of a var¬iable-resolution global atmospheric model, the conformal-cubic atmospheric model (CCAM), across a wide range of spatial and time scales to investigate the ability of the model to provide realistic simulations of present-day climate and plausible projections of future climate change over sub-Saharan Africa. By applying the model in stretched-grid mode the versatility of the model dynamics, numerical formulation and physical parameterizations to function across a range of length scales over the region of interest, was also explored. We primarily used CCAM to illustrate the capability of the model to function as a flexible downscaling tool at the climate-change time scale. Here we report on additional long term climate projection studies performed by downscaling at much higher resolutions (8 Km) over an area that stretches from just south of Sahara desert to the southern coast of the Niger Delta and into the Gulf of Guinea. To perform these simulations, CCAM was provided with synoptic-scale forcing of atmospheric circulation from 2.5 deg resolution NCEP reanalysis at 6-hourly interval and SSTs from NCEP reanalysis data uses as lower boundary forcing. CCAM 60 Km resolution downscaled to 8 Km (Schmidt factor 24.75) then 8 Km resolution simulation downscaled to 1 Km (Schmidt factor 200) over an area approximately 50 Km x 50 Km in the southern Lake Chad Basin (LCB). Our intent in conducting these high resolution model runs was to obtain a deeper understanding of linkages between the projected future climate and the hydrological processes that control the surface water regime in this part of sub-Saharan Africa.

Flood events across the North Atlantic region - past development and future perspectives

NASA Astrophysics Data System (ADS)

Matti, Bettina; Dieppois, Bastien; Lawler, Damian; Dahlke, Helen E.; Lyon, Steve W.

2016-04-01

Flood events have a large impact on humans, both socially and economically. An increase in winter and spring flooding across much of northern Europe in recent years opened up the question of changing underlying hydro-climatic drivers of flood events. Predicting the manifestation of such changes is difficult due to the natural variability and fluctuations in northern hydrological systems caused by large-scale atmospheric circulations, especially under altered climate conditions. Improving knowledge on the complexity of these hydrological systems and their interactions with climate is essential to be able to determine drivers of flood events and to predict changes in these drivers under altered climate conditions. This is particularly true for the North Atlantic region where both physical catchment properties and large-scale atmospheric circulations have a profound influence on floods. This study explores changes in streamflow across North Atlantic region catchments. An emphasis is placed on high-flow events, namely the timing and magnitude of past flood events, and selected flood percentiles were tested for stationarity by applying a flood frequency analysis. The issue of non-stationarity of flood return periods is important when linking streamflow to large-scale atmospheric circulations. Natural fluctuations in these circulations are found to have a strong influence on the outcome causing natural variability in streamflow records. Long time series and a multi-temporal approach allows for determining drivers of floods and linking streamflow to large-scale atmospheric circulations. Exploring changes in selected hydrological signatures consistency was found across much of the North Atlantic region suggesting a shift in flow regime. The lack of an overall regional pattern suggests that how catchments respond to changes in climatic drivers is strongly influenced by their physical characteristics. A better understanding of hydrological response to climate drivers is essential for example for forecasting purposes.

Grand challenges in understanding the interplay of climate and land changes

USGS Publications Warehouse

Liu, Shuguang; Bond-Lamberty, Ben; Boysen, Lena R.; Ford, James D.; Fox, Andrew; Gallo, Kevin; Hatfield, Jerry L.; Henebry, Geoffrey M.; Huntington, Thomas G.; Liu, Zhihua; Loveland, Thomas R.; Norby, Richard J.; Sohl, Terry L.; Steiner, Allison L.; Yuan, Wenping; Zhang, Zhao; Zhao, Shuqing

2017-01-01

Half of Earth’s land surface has been altered by human activities, creating various consequences on the climate and weather systems at local to global scales, which in turn affect a myriad of land surface processes and the adaptation behaviors. This study reviews the status and major knowledge gaps in the interactions of land and atmospheric changes and present 11 grand challenge areas for the scientific research and adaptation community in the coming decade. These land-cover and land-use change (LCLUC)-related areas include 1) impacts on weather and climate, 2) carbon and other biogeochemical cycles, 3) biospheric emissions, 4) the water cycle, 5) agriculture, 6) urbanization, 7) acclimation of biogeochemical processes to climate change, 8) plant migration, 9) land-use projections, 10) model and data uncertainties, and, finally, 11) adaptation strategies. Numerous studies have demonstrated the effects of LCLUC on local to global climate and weather systems, but these putative effects vary greatly in magnitude and even sign across space, time, and scale and thus remain highly uncertain. At the same time, many challenges exist toward improved understanding of the consequences of atmospheric and climate change on land process dynamics and services. Future effort must improve the understanding of the scale-dependent, multifaceted perturbations and feedbacks between land and climate changes in both reality and models. To this end, one critical cross-disciplinary need is to systematically quantify and better understand measurement and model uncertainties. Finally, LCLUC mitigation and adaptation assessments must be strengthened to identify implementation barriers, evaluate and prioritize opportunities, and examine how decision-making processes work in specific contexts.

ICLEA - The Virtual Institute of Integrated Climate and Landscape Evolution Analyses

NASA Astrophysics Data System (ADS)

Schwab, Markus J.; Brauer, Achim; Błaszkiewicz, Mirosław; Blume, Theresa; Itzerott, Sibylle; Raab, Thomas; Wilmking, Martin; Iclea Team

2016-04-01

In the Virtual Institute ICLEA we view on past changes as natural experiments as a guidebook for better anticipation of future changes and their impacts. Since the natural evolution became increasingly superimposed by human impacts since the Neolithic we include an in-depth discussion of impacts of climate and environment change on societies and vice versa. The partner focusing their research capacities and expertise in ICLEA and offers young researchers an interdisciplinary and structured education and promote their early independence through coaching and mentoring. Training, Research and Analytical workshops between research partners of ICLEA are an important measure to qualify young researchers. Understanding causes and effects of present-day climate change on landscapes and the human habitat faces two main challenges, (I) too short time series of instrumental observation that do not cover the full range of variability since mechanisms of climate change and landscape evolution work on different time scales, which often not susceptible to human perception, and, (II) distinct regional differences due to the location with respect to oceanic/continental climatic influences, the geological underground, and the history and intensity of anthropogenic land-use. Both challenges are central for the ICLEA research strategy and demand a high degree of interdisciplinary. In particular, the need to link observations and measurements of ongoing changes with information from the past taken from natural archives requires joint work of scientists with very different time perspectives. On the one hand, scientists that work at geological time scales of thousands and more years and, on the other hand, those observing and investigating recent processes at short time scales. The long-term mission of the Virtual Institute is to provide a substantiated data basis for sustained environmental maintenance based on a profound process understanding at all relevant time scales. Aim is to explore processes of climate and landscape evolution in an historical cultural landscape extending from northeastern Germany into northwestern Poland. The northern-central European lowlands will be facilitated as a natural laboratory providing an ideal case for utilizing a systematic and holistic approach. Five complementary work packages (WP) are established according to the key research aspects: WP 1 focused on monitoring mainly hydrology and soil moisture as well as meteorological parameters. WP 2 is linking present day and future monitoring data with the most recent past through analyzing satellite images. This WP will further provide larger spatial scales. WP 3-5 are focused on different natural archives to obtain a broad variety of high quality proxy data. Tree rings provide sub-seasonal data for the last centuries up to few millennia, varved lake sediments cover the entire research time interval at seasonal to decadal resolution and palaeosoils and geomorphological features also cover the entire period but not continuously and with lower resolution. Complementary information, like climate, tree ecophysiological and limnological data etc., are provided by cooperation with associated partners. Further information about ICLEA: www.iclea.de

Capital investment requirements for greenhouse gas emissions mitigation in power generation on near term to century time scales and global to regional spatial scales

DOE Office of Scientific and Technical Information (OSTI.GOV)

Chaturvedi, Vaibhav; Clarke, Leon E.; Edmonds, James A.

Electrification plays a crucial role in cost-effective greenhouse gas emissions mitigation strategies. Such strategies in turn carry implications for financial capital markets. This paper explores the implication of climate mitigation policy for capital investment demands by the electric power sector on decade to century time scales. We go further to explore the implications of technology performance and the stringency of climate policy for capital investment demands by the power sector. Finally, we discuss the regional distribution of investment demands. We find that stabilizing GHG emissions will require additional investment in the electricity generation sector over and above investments that wouldmore » be need in the absence of climate policy, in the range of 16 to 29 Trillion US$ (60-110%) depending on the stringency of climate policy during the period 2015 to 2095 under default technology assumptions. This increase reflects the higher capital intensity of power systems that control emissions. Limits on the penetration of nuclear and carbon capture and storage technology could increase costs substantially. Energy efficiency improvements can reduce the investment requirement by 8 to21 Trillion US$ (default technology assumptions), depending on climate policy scenario with higher savings being obtained under the most stringent climate policy. The heaviest investments in power generation were observed in the China, India, SE Asia and Africa regions with the latter three regions dominating in the second half of the 21st century.« less

Sensitivity of peak flow to the change of rainfall temporal pattern due to warmer climate

NASA Astrophysics Data System (ADS)

Fadhel, Sherien; Rico-Ramirez, Miguel Angel; Han, Dawei

2018-05-01

The widely used design storms in urban drainage networks has different drawbacks. One of them is that the shape of the rainfall temporal pattern is fixed regardless of climate change. However, previous studies have shown that the temporal pattern may scale with temperature due to climate change, which consequently affects peak flow. Thus, in addition to the scaling of the rainfall volume, the scaling relationship for the rainfall temporal pattern with temperature needs to be investigated by deriving the scaling values for each fraction within storm events, which is lacking in many parts of the world including the UK. Therefore, this study analysed rainfall data from 28 gauges close to the study area with a 15-min resolution as well as the daily temperature data. It was found that, at warmer temperatures, the rainfall temporal pattern becomes less uniform, with more intensive peak rainfall during higher intensive times and weaker rainfall during less intensive times. This is the case for storms with and without seasonal separations. In addition, the scaling values for both the rainfall volume and the rainfall fractions (i.e. each segment of rainfall temporal pattern) for the summer season were found to be higher than the corresponding results for the winter season. Applying the derived scaling values for the temporal pattern of the summer season in a hydrodynamic sewer network model produced high percentage change of peak flow between the current and future climate. This study on the scaling of rainfall fractions is the first in the UK, and its findings are of importance to modellers and designers of sewer systems because it can provide more robust scenarios for flooding mitigation in urban areas.

Locally Downscaled and Spatially Customizable Climate Data for Historical and Future Periods for North America

PubMed Central

Wang, Tongli; Hamann, Andreas; Spittlehouse, Dave; Carroll, Carlos

2016-01-01

Large volumes of gridded climate data have become available in recent years including interpolated historical data from weather stations and future predictions from general circulation models. These datasets, however, are at various spatial resolutions that need to be converted to scales meaningful for applications such as climate change risk and impact assessments or sample-based ecological research. Extracting climate data for specific locations from large datasets is not a trivial task and typically requires advanced GIS and data management skills. In this study, we developed a software package, ClimateNA, that facilitates this task and provides a user-friendly interface suitable for resource managers and decision makers as well as scientists. The software locally downscales historical and future monthly climate data layers into scale-free point estimates of climate values for the entire North American continent. The software also calculates a large number of biologically relevant climate variables that are usually derived from daily weather data. ClimateNA covers 1) 104 years of historical data (1901–2014) in monthly, annual, decadal and 30-year time steps; 2) three paleoclimatic periods (Last Glacial Maximum, Mid Holocene and Last Millennium); 3) three future periods (2020s, 2050s and 2080s); and 4) annual time-series of model projections for 2011–2100. Multiple general circulation models (GCMs) were included for both paleo and future periods, and two representative concentration pathways (RCP4.5 and 8.5) were chosen for future climate data. PMID:27275583

Locally Downscaled and Spatially Customizable Climate Data for Historical and Future Periods for North America.

PubMed

Wang, Tongli; Hamann, Andreas; Spittlehouse, Dave; Carroll, Carlos

2016-01-01

Large volumes of gridded climate data have become available in recent years including interpolated historical data from weather stations and future predictions from general circulation models. These datasets, however, are at various spatial resolutions that need to be converted to scales meaningful for applications such as climate change risk and impact assessments or sample-based ecological research. Extracting climate data for specific locations from large datasets is not a trivial task and typically requires advanced GIS and data management skills. In this study, we developed a software package, ClimateNA, that facilitates this task and provides a user-friendly interface suitable for resource managers and decision makers as well as scientists. The software locally downscales historical and future monthly climate data layers into scale-free point estimates of climate values for the entire North American continent. The software also calculates a large number of biologically relevant climate variables that are usually derived from daily weather data. ClimateNA covers 1) 104 years of historical data (1901-2014) in monthly, annual, decadal and 30-year time steps; 2) three paleoclimatic periods (Last Glacial Maximum, Mid Holocene and Last Millennium); 3) three future periods (2020s, 2050s and 2080s); and 4) annual time-series of model projections for 2011-2100. Multiple general circulation models (GCMs) were included for both paleo and future periods, and two representative concentration pathways (RCP4.5 and 8.5) were chosen for future climate data.

Assessing a Top-Down Modeling Approach for Seasonal Scale Snow Sensitivity

NASA Astrophysics Data System (ADS)

Luce, C. H.; Lute, A.

2017-12-01

Mechanistic snow models are commonly applied to assess changes to snowpacks in a warming climate. Such assessments involve a number of assumptions about details of weather at daily to sub-seasonal time scales. Models of season-scale behavior can provide contrast for evaluating behavior at time scales more in concordance with climate warming projections. Such top-down models, however, involve a degree of empiricism, with attendant caveats about the potential of a changing climate to affect calibrated relationships. We estimated the sensitivity of snowpacks from 497 Snowpack Telemetry (SNOTEL) stations in the western U.S. based on differences in climate between stations (spatial analog). We examined the sensitivity of April 1 snow water equivalent (SWE) and mean snow residence time (SRT) to variations in Nov-Mar precipitation and average Nov-Mar temperature using multivariate local-fit regressions. We tested the modeling approach using a leave-one-out cross-validation as well as targeted two-fold non-random cross-validations contrasting, for example, warm vs. cold years, dry vs. wet years, and north vs. south stations. Nash-Sutcliffe Efficiency (NSE) values for the validations were strong for April 1 SWE, ranging from 0.71 to 0.90, and still reasonable, but weaker, for SRT, in the range of 0.64 to 0.81. From these ranges, we exclude validations where the training data do not represent the range of target data. A likely reason for differences in validation between the two metrics is that the SWE model reflects the influence of conservation of mass while using temperature as an indicator of the season-scale energy balance; in contrast, SRT depends more strongly on the energy balance aspects of the problem. Model forms with lower numbers of parameters generally validated better than more complex model forms, with the caveat that pseudoreplication could encourage selection of more complex models when validation contrasts were weak. Overall, the split sample validations confirm transferability of the relationships in space and time contingent upon full representation of validation conditions in the calibration data set. The ability of the top-down space-for-time models to predict in new time periods and locations lends confidence to their application for assessments and for improving finer time scale models.

Evaluation of Hydrologic and Meteorological Impacts on Dengue Fever Incidences in Southern Taiwan using Time- Frequency Method

NASA Astrophysics Data System (ADS)

Tsai, Christina; Yeh, Ting-Gu

2017-04-01

Extreme weather events are occurring more frequently as a result of climate change. Recently dengue fever has become a serious issue in southern Taiwan. It may have characteristic temporal scales that can be identified. Some researchers have hypothesized that dengue fever incidences are related to climate change. This study applies time-frequency analysis to time series data concerning dengue fever and hydrologic and meteorological variables. Results of three time-frequency analytical methods - the Hilbert Huang transform (HHT), the Wavelet Transform (WT) and the Short Time Fourier Transform (STFT) are compared and discussed. A more effective time-frequency analysis method will be identified to analyze relevant time series data. The most influential time scales of hydrologic and meteorological variables that are associated with dengue fever are determined. Finally, the linkage between hydrologic/meteorological factors and dengue fever incidences can be established.

A review of the South American monsoon history as recorded in stable isotopic proxies over the past two millennia

NASA Astrophysics Data System (ADS)

Vuille, M.; Burns, S. J.; Taylor, B. L.; Cruz, F. W.; Bird, B. W.; Abbott, M. B.; Kanner, L. C.; Cheng, H.; Novello, V. F.

2012-08-01

We review the history of the South American summer monsoon (SASM) over the past ~2000 yr based on high-resolution stable isotope proxies from speleothems, ice cores and lake sediments. Our review is complemented by an analysis of an isotope-enabled atmospheric general circulation model (GCM) for the past 130 yr. Proxy records from the monsoon belt in the tropical Andes and SE Brazil show a very coherent behavior over the past 2 millennia with significant decadal to multidecadal variability superimposed on large excursions during three key periods: the Medieval Climate Anomaly (MCA), the Little Ice Age (LIA) and the current warm period (CWP). We interpret these three periods as times when the SASM's mean state was significantly weakened (MCA and CWP) and strengthened (LIA), respectively. During the LIA each of the proxy archives considered contains the most negative δ18O values recorded during the entire record length. On the other hand, the monsoon strength is currently rather weak in a 2000-yr historical perspective, rivaled only by the low intensity during the MCA. Our climatic interpretation of these archives is consistent with our isotope-based GCM analysis, which suggests that these sites are sensitive recorders of large-scale monsoon variations. We hypothesize that these centennial-scale climate anomalies were at least partially driven by temperature changes in the Northern Hemisphere and in particular over the North Atlantic, leading to a latitudinal displacement of the ITCZ and a change in monsoon intensity (amount of rainfall upstream over the Amazon Basin). This interpretation is supported by several independent records from different proxy archives and modeling studies. Although ENSO is the main forcing for δ18O variability over tropical South America on interannual time scales, our results suggest that its influence may be significantly modulated by North Atlantic climate variability on longer time scales. Finally, our analyses indicate that isotopic proxies, because of their ability to integrate climatic information on large spatial scales, could complement more traditional proxies such as tree rings or documentary evidence. Future climate reconstruction efforts could potentially benefit from including isotopic proxies as large-scale predictors in order to better constrain past changes in the atmospheric circulation.

Semi-arid vegetation response to antecedent climate and water balance windows

USGS Publications Warehouse

Thoma, David P.; Munson, Seth M.; Irvine, Kathryn M.; Witwicki, Dana L.; Bunting, Erin

2016-01-01

Questions Can we improve understanding of vegetation response to water availability on monthly time scales in semi-arid environments using remote sensing methods? What climatic or water balance variables and antecedent windows of time associated with these variables best relate to the condition of vegetation? Can we develop credible near-term forecasts from climate data that can be used to prepare for future climate change effects on vegetation? Location Semi-arid grasslands in Capitol Reef National Park, Utah, USA. Methods We built vegetation response models by relating the normalized difference vegetation index (NDVI) from MODIS imagery in Mar–Nov 2000–2013 to antecedent climate and water balance variables preceding the monthly NDVI observations. We compared how climate and water balance variables explained vegetation greenness and then used a multi-model ensemble of climate and water balance models to forecast monthly NDVI for three holdout years. Results Water balance variables explained vegetation greenness to a greater degree than climate variables for most growing season months. Seasonally important variables included measures of antecedent water input and storage in spring, switching to indicators of drought, input or use in summer, followed by antecedent moisture availability in autumn. In spite of similar climates, there was evidence the grazed grassland showed a response to drying conditions 1 mo sooner than the ungrazed grassland. Lead times were generally short early in the growing season and antecedent window durations increased from 3 mo early in the growing season to 1 yr or more as the growing season progressed. Forecast accuracy for three holdout years using a multi-model ensemble of climate and water balance variables outperformed forecasts made with a naïve NDVI climatology. Conclusions We determined the influence of climate and water balance on vegetation at a fine temporal scale, which presents an opportunity to forecast vegetation response with short lead times. This understanding was obtained through high-frequency vegetation monitoring using remote sensing, which reduces the costs and time necessary for field measurements and can lead to more rapid detection of vegetation changes that could help managers take appropriate actions.

Evolution of the Climate Continuum from the Mid-Miocene Climatic Optimum to the Present

NASA Astrophysics Data System (ADS)

Aswasereelert, W.; Meyers, S. R.; Hinnov, L. A.; Kelly, D.

2011-12-01

The recognition of orbital rhythms in paleoclimate data has led to a rich understanding of climate evolution during the Neogene and Quaternary. In contrast, changes in stochastic variability associated with the transition from unipolar to bipolar glaciation have received less attention, although the stochastic component likely preserves key insights about climate. In this study, we seek to evaluate the dominance and character of stochastic climate energy since the Middle Miocene Climatic Optimum (~17 Ma). These analyses extend a previous study that suggested diagnostic stochastic responses associated with Northern Hemisphere ice sheet development during the Plio-Pleistocene (Meyers and Hinnov, 2010). A critical and challenging step necessary to conduct the work is the conversion of depth data to time data. We investigate climate proxy datasets using multiple time scale hypotheses, including depth-derived time scales, sedimentologic/geochemical "tuning", minimal orbital tuning, and comprehensive orbital tuning. To extract the stochastic component of climate, and also explore potential relationships between the orbital parameters and paleoclimate response, a number of approaches rooted in Thomson's (1982) multi-taper spectral method (MTM) are applied. Importantly, the MTM technique is capable of separating the spectral "continuum" - a measure of stochastic variability - from the deterministic periodic orbital signals (spectral "lines") preserved in proxy data. Time series analysis of the proxy records using different chronologic approaches allows us to evaluate the sensitivity of our conclusion about stochastic and deterministic orbital processes during the Middle Miocene to present. Moreover, comparison of individual records permits examination of the spatial dependence of the identified climate responses. Meyers, S.R., and Hinnov, L.A. (2010), Northern Hemisphere glaciation and the evolution of Plio-Pleistocene climate noise: Paleoceanography, 25, PA3207, doi:10.1029/2009PA001834. Thomson, D.J. (1982), Spectrum estimation and harmonic analysis: IEEE Proceedings, v. 70, p. 1055-1096.

Cross-scale impact of climate temporal variability on ecosystem water and carbon fluxes

DOE PAGES

Paschalis, Athanasios; Fatichi, Simone; Katul, Gabriel G.; ...

2015-08-07

While the importance of ecosystem functioning is undisputed in the context of climate change and Earth system modeling, the role of short-scale temporal variability of hydrometeorological forcing (~1 h) on the related ecosystem processes remains to be fully understood. Additionally, various impacts of meteorological forcing variability on water and carbon fluxes across a range of scales are explored here using numerical simulations. Synthetic meteorological drivers that highlight dynamic features of the short temporal scale in series of precipitation, temperature, and radiation are constructed. These drivers force a mechanistic ecohydrological model that propagates information content into the dynamics of water andmore » carbon fluxes for an ensemble of representative ecosystems. The focus of the analysis is on a cross-scale effect of the short-scale forcing variability on the modeled evapotranspiration and ecosystem carbon assimilation. Interannual variability of water and carbon fluxes is emphasized in the analysis. The main study inferences are summarized as follows: (a) short-scale variability of meteorological input does affect water and carbon fluxes across a wide range of time scales, spanning from the hourly to the annual and longer scales; (b) different ecosystems respond to the various characteristics of the short-scale variability of the climate forcing in various ways, depending on dominant factors limiting system productivity; (c) whenever short-scale variability of meteorological forcing influences primarily fast processes such as photosynthesis, its impact on the slow-scale variability of water and carbon fluxes is small; and (d) whenever short-scale variability of the meteorological forcing impacts slow processes such as movement and storage of water in the soil, the effects of the variability can propagate to annual and longer time scales.« less

Cross-scale impact of climate temporal variability on ecosystem water and carbon fluxes

DOE Office of Scientific and Technical Information (OSTI.GOV)

Paschalis, Athanasios; Fatichi, Simone; Katul, Gabriel G.

While the importance of ecosystem functioning is undisputed in the context of climate change and Earth system modeling, the role of short-scale temporal variability of hydrometeorological forcing (~1 h) on the related ecosystem processes remains to be fully understood. Additionally, various impacts of meteorological forcing variability on water and carbon fluxes across a range of scales are explored here using numerical simulations. Synthetic meteorological drivers that highlight dynamic features of the short temporal scale in series of precipitation, temperature, and radiation are constructed. These drivers force a mechanistic ecohydrological model that propagates information content into the dynamics of water andmore » carbon fluxes for an ensemble of representative ecosystems. The focus of the analysis is on a cross-scale effect of the short-scale forcing variability on the modeled evapotranspiration and ecosystem carbon assimilation. Interannual variability of water and carbon fluxes is emphasized in the analysis. The main study inferences are summarized as follows: (a) short-scale variability of meteorological input does affect water and carbon fluxes across a wide range of time scales, spanning from the hourly to the annual and longer scales; (b) different ecosystems respond to the various characteristics of the short-scale variability of the climate forcing in various ways, depending on dominant factors limiting system productivity; (c) whenever short-scale variability of meteorological forcing influences primarily fast processes such as photosynthesis, its impact on the slow-scale variability of water and carbon fluxes is small; and (d) whenever short-scale variability of the meteorological forcing impacts slow processes such as movement and storage of water in the soil, the effects of the variability can propagate to annual and longer time scales.« less

Agroforestry, climate change, and food security

USDA-ARS?s Scientific Manuscript database

Successfully addressing global climate change effects on agriculture will require a holistic, sustained approach incorporating a suite of strategies at multiple spatial scales and time horizons. In the USA of the 1930’s, bold and innovative leadership at high levels of government was needed to enact...

Hazardous thunderstorm intensification over Lake Victoria

PubMed Central

Thiery, Wim; Davin, Edouard L.; Seneviratne, Sonia I.; Bedka, Kristopher; Lhermitte, Stef; van Lipzig, Nicole P. M.

2016-01-01

Weather extremes have harmful impacts on communities around Lake Victoria, where thousands of fishermen die every year because of intense night-time thunderstorms. Yet how these thunderstorms will evolve in a future warmer climate is still unknown. Here we show that Lake Victoria is projected to be a hotspot of future extreme precipitation intensification by using new satellite-based observations, a high-resolution climate projection for the African Great Lakes and coarser-scale ensemble projections. Land precipitation on the previous day exerts a control on night-time occurrence of extremes on the lake by enhancing atmospheric convergence (74%) and moisture availability (26%). The future increase in extremes over Lake Victoria is about twice as large relative to surrounding land under a high-emission scenario, as only over-lake moisture advection is high enough to sustain Clausius–Clapeyron scaling. Our results highlight a major hazard associated with climate change over East Africa and underline the need for high-resolution projections to assess local climate change. PMID:27658848

Application of Multi-Model CMIP5 Analysis in Future Drought Adaptation Strategies

NASA Astrophysics Data System (ADS)

Casey, M.; Luo, L.; Lang, Y.

2014-12-01

Drought influences the efficacy of numerous natural and artificial systems including species diversity, agriculture, and infrastructure. Global climate change raises concerns that extend well beyond atmospheric and hydrological disciplines - as climate changes with time, the need for system adaptation becomes apparent. Drought, as a natural phenomenon, is typically defined relative to the climate in which it occurs. Typically a 30-year reference time frame (RTF) is used to determine the severity of a drought event. This study investigates the projected future droughts over North America with different RTFs. Confidence in future hydroclimate projection is characterized by the agreement of long term (2005-2100) multi-model precipitation (P) and temperature (T) projections within the Coupled model Intercomparison Project Phase 5 (CMIP5). Drought severity and the propensity of extreme conditions are measured by the multi-scalar, probabilistic, RTF-based Standard Precipitation Index (SPI) and Standard Precipitation Evapotranspiration Index (SPEI). SPI considers only P while SPEI incorporates Evapotranspiration (E) via T; comparing the two reveals the role of temperature change in future hydroclimate change. Future hydroclimate conditions, hydroclimate extremity, and CMIP5 model agreement are assessed for each Representative Concentration Pathway (RCP 2.6, 4.5, 6.0, 8.5) in regions throughout North America for the entire year and for the boreal seasons. In addition, multiple time scales of SPI and SPEI are calculated to characterize drought at time scales ranging from short to long term. The study explores a simple, standardized method for considering adaptation in future drought assessment, which provides a novel perspective to incorporate adaptation with climate change. The result of the analysis is a multi-dimension, probabilistic summary of the hydrological (P, E) environment a natural or artificial system must adapt to over time. Studies similar to this with specified criteria (SPI/SPEI value, time scale, RCP, etc.) can provide professionals in a variety of disciplines with necessary climatic insight to develop adaptation strategies.

Long-range persistence in the global mean surface temperature and the global warming "time bomb"

NASA Astrophysics Data System (ADS)

Rypdal, M.; Rypdal, K.

2012-04-01

Detrended Fluctuation Analysis (DFA) and Maximum Likelihood Estimations (MLE) based on instrumental data over the last 160 years indicate that there is Long-Range Persistence (LRP) in Global Mean Surface Temperature (GMST) on time scales of months to decades. The persistence is much higher in sea surface temperature than in land temperatures. Power spectral analysis of multi-model, multi-ensemble runs of global climate models indicate further that this persistence may extend to centennial and maybe even millennial time-scales. We also support these conclusions by wavelet variogram analysis, DFA, and MLE of Northern hemisphere mean surface temperature reconstructions over the last two millennia. These analyses indicate that the GMST is a strongly persistent noise with Hurst exponent H>0.9 on time scales from decades up to at least 500 years. We show that such LRP can be very important for long-term climate prediction and for the establishment of a "time bomb" in the climate system due to a growing energy imbalance caused by the slow relaxation to radiative equilibrium under rising anthropogenic forcing. We do this by the construction of a multi-parameter dynamic-stochastic model for the GMST response to deterministic and stochastic forcing, where LRP is represented by a power-law response function. Reconstructed data for total forcing and GMST over the last millennium are used with this model to estimate trend coefficients and Hurst exponent for the GMST on multi-century time scale by means of MLE. Ensembles of solutions generated from the stochastic model also allow us to estimate confidence intervals for these estimates.

Study of phase clustering method for analyzing large volumes of meteorological observation data

NASA Astrophysics Data System (ADS)

Volkov, Yu. V.; Krutikov, V. A.; Botygin, I. A.; Sherstnev, V. S.; Sherstneva, A. I.

2017-11-01

The article describes an iterative parallel phase grouping algorithm for temperature field classification. The algorithm is based on modified method of structure forming by using analytic signal. The developed method allows to solve tasks of climate classification as well as climatic zoning for any time or spatial scale. When used to surface temperature measurement series, the developed algorithm allows to find climatic structures with correlated changes of temperature field, to make conclusion on climate uniformity in a given area and to overview climate changes over time by analyzing offset in type groups. The information on climate type groups specific for selected geographical areas is expanded by genetic scheme of class distribution depending on change in mutual correlation level between ground temperature monthly average.

Changes in Concurrent Risk of Warm and Dry Years under Impact of Climate Change

NASA Astrophysics Data System (ADS)

Sarhadi, A.; Wiper, M.; Touma, D. E.; Ausín, M. C.; Diffenbaugh, N. S.

2017-12-01

Anthropogenic global warming has changed the nature and the risk of extreme climate phenomena. The changing concurrence of multiple climatic extremes (warm and dry years) may result in intensification of undesirable consequences for water resources, human and ecosystem health, and environmental equity. The present study assesses how global warming influences the probability that warm and dry years co-occur in a global scale. In the first step of the study a designed multivariate Mann-Kendall trend analysis is used to detect the areas in which the concurrence of warm and dry years has increased in the historical climate records and also climate models in the global scale. The next step investigates the concurrent risk of the extremes under dynamic nonstationary conditions. A fully generalized multivariate risk framework is designed to evolve through time under dynamic nonstationary conditions. In this methodology, Bayesian, dynamic copulas are developed to model the time-varying dependence structure between the two different climate extremes (warm and dry years). The results reveal an increasing trend in the concurrence risk of warm and dry years, which are in agreement with the multivariate trend analysis from historical and climate models. In addition to providing a novel quantification of the changing probability of compound extreme events, the results of this study can help decision makers develop short- and long-term strategies to prepare for climate stresses now and in the future.

Climate proxy data as groundwater tracers in regional flow systems

NASA Astrophysics Data System (ADS)

Clark, J. F.; Morrissey, S. K.; Stute, M.

2008-05-01

The isotopic and chemical signatures of groundwater reflect local climate conditions. By systematically analyzing groundwater and determining their hydrologic setting, records of past climates can be constructed. Because of their chemistries and relatively uncomplicated source functions, dissolved noble gases have yielded reliable records of continental temperatures for the last 30,000 to 50,000 years. Variations in the stable isotope compositions of groundwater due to long term climate changes have also been documented over these time scales. Because glacial - interglacial climate changes are relatively well known, these climate proxies can be used as "stratigraphic" markers within flow systems and used to distinguish groundwaters that have recharged during the Holocene from those recharged during the last glacial period, important time scales for distinguishing regional and local flow systems in many aquifers. In southern Georgia, the climate proxy tracers were able to identify leakage from surface aquifers into the Upper Floridan aquifer in areas previously thought to be confined. In south Florida, the transition between Holocene and glacial signatures in the Upper Floridan aquifer occurs mid-way between the recharge area and Lake Okeechobee. Down gradient of the lake, the proxies are uniform, indicating recharge during the last glacial period. Furthermore, there is no evidence for leakage from the shallow aquifers into the Upper Floridan. In the Lower Floridan, the climate proxies indicate that the saline water entered the aquifer after sea level rose to its present level.

Urban Impact Assessment and Adaptation Strategies to Climate Change in Europe: A Case Study for Antwerp, Berlin and Almada

NASA Astrophysics Data System (ADS)

Stevens, Catherine; Thomas, Bart

2014-05-01

Climate change is driven by global processes such as the global ocean circulation and its variability over time leading to changing weather patterns on regional scales as well as changes in the severity and occurrence of extreme events such as heat waves. For example, the summer 2003 European heat wave caused up to 70.000 excess deaths over four months in Central and Western Europe. As around 75% of Europe's population resides in urban areas, it is of particular relevance to examine the impact of seasonal to decadal-scale climate variability on urban areas and their populations. This study aims at downscaling the spatially coarse resolution CMIP5 climate predictions to the local urban scale and investigating the relation between heat waves and the urban-rural temperature increment (urban heat island effect). The resulting heat stress effect is not only driven by climatic variables but also impacted by urban morphology. Moreover, the exposure varies significantly with the geographical location. All this information is coupled with relevant socio-economic datasets such as population density, age structure, etc. focussing on human health. The analyses are conducted in the framework of the NACLIM FP7 project funded by the European Commission involving local stakeholders such as the cities of Antwerp (BE), Berlin (DE) and Almada (PT) represented by different climate and urban characteristics. The end-user needs have been consolidated in a climate services plan including the production of heat risk exposure maps and the analysis of various scenarios considering e.g. the uncertainty of the global climate predictions, urban expansion over time and the impact of mitigation measures such as green roofs. The results of this study will allow urban planners and policy makers facing the challenges of climate change and develop sound strategies for the design and management of climate resilient cities.

Improving the representation of clouds, radiation, and precipitation using spectral nudging in the Weather Research and Forecasting model

NASA Astrophysics Data System (ADS)

Spero, Tanya L.; Otte, Martin J.; Bowden, Jared H.; Nolte, Christopher G.

2014-10-01

Spectral nudging—a scale-selective interior constraint technique—is commonly used in regional climate models to maintain consistency with large-scale forcing while permitting mesoscale features to develop in the downscaled simulations. Several studies have demonstrated that spectral nudging improves the representation of regional climate in reanalysis-forced simulations compared with not using nudging in the interior of the domain. However, in the Weather Research and Forecasting (WRF) model, spectral nudging tends to produce degraded precipitation simulations when compared to analysis nudging—an interior constraint technique that is scale indiscriminate but also operates on moisture fields which until now could not be altered directly by spectral nudging. Since analysis nudging is less desirable for regional climate modeling because it dampens fine-scale variability, changes are proposed to the spectral nudging methodology to capitalize on differences between the nudging techniques and aim to improve the representation of clouds, radiation, and precipitation without compromising other fields. These changes include adding spectral nudging toward moisture, limiting nudging to below the tropopause, and increasing the nudging time scale for potential temperature, all of which collectively improve the representation of mean and extreme precipitation, 2 m temperature, clouds, and radiation, as demonstrated using a model-simulated 20 year historical period. Such improvements to WRF may increase the fidelity of regional climate data used to assess the potential impacts of climate change on human health and the environment and aid in climate change mitigation and adaptation studies.

Climate and landscape drive the pace and pattern of conifer encroachment into subalpine meadows.

PubMed

Lubetkin, Kaitlin C; Westerling, Anthony LeRoy; Kueppers, Lara M

2017-09-01

Mountain meadows have high biodiversity and help regulate stream water release following the snowmelt pulse. However, many meadows are experiencing woody plant encroachment, threatening these ecosystem services. While there have been field surveys of individual meadows and remote sensing-based landscape-scale studies of encroachment, what is missing is a broad-scale, ground-based study to understand common regional drivers, especially at high elevations, where land management has often played a less direct role. With this study, we ask: What are the climate and landscape conditions conducive to woody plant encroachment at the landscape scale, and how has historical climate variation affected tree recruitment in subalpine meadows over time? We measured density of encroaching trees across 340 subalpine meadows in the central Sierra Nevada, California, USA, and used generalized additive models (GAMs) to determine the relationship between landscape-scale patterns of encroachment and meadow environmental properties. We determined ages of trees in 30 survey meadows, used observed climate and GAMs to model the relationship between timing of recruitment and climate since the early 1900s, and extrapolated recruitment patterns into the future using downscaled climate scenarios. Encroachment was high among meadows with lodgepole pine (Pinus contorta Douglas ex Loudon var. murrayana (Balf.) Engelm.) in the immediate vicinity, at lower elevations, with physical conditions favoring strong soil drying, and with maximum temperatures above or below average. Climatic conditions during the year of germination were unimportant, with tree recruitment instead depending on a 3-yr seed production period prior to germination and a 6-yr seedling establishment period following germination. Recruitment was high when the seed production period had high snowpack, and when the seedling establishment period had warm summer maximum temperatures, high summer precipitation, and high snowpack. Applying our temporal model to downscaled output from four global climate models indicated that the average meadow will shift to forest by the end of the 21st century. Sierra Nevada meadow encroachment by conifers is ubiquitous and associated with climate conditions increasingly favorable for tree recruitment, which will lead to substantial changes in subalpine meadows and the ecosystem services they provide. © 2017 by the Ecological Society of America.

The environmental context for the origins of modern human diversity: a synthesis of regional variability in African climate 150,000-30,000 years ago.

PubMed

Blome, Margaret Whiting; Cohen, Andrew S; Tryon, Christian A; Brooks, Alison S; Russell, Joellen

2012-05-01

We synthesize African paleoclimate from 150 to 30 ka (thousand years ago) using 85 diverse datasets at a regional scale, testing for coherence with North Atlantic glacial/interglacial phases and northern and southern hemisphere insolation cycles. Two major determinants of circum-African climate variability over this time period are supported by principal components analysis: North Atlantic sea surface temperature (SST) variations and local insolation maxima. North Atlantic SSTs correlated with the variability found in most circum-African SST records, whereas the variability of the majority of terrestrial temperature and precipitation records is explained by local insolation maxima, particularly at times when solar radiation was intense and highly variable (e.g., 150-75 ka). We demonstrate that climates varied with latitude, such that periods of relatively increased aridity or humidity were asynchronous across the northern, eastern, tropical and southern portions of Africa. Comparisons of the archaeological, fossil, or genetic records with generalized patterns of environmental change based solely on northern hemisphere glacial/interglacial cycles are therefore imprecise. We compare our refined climatic framework to a database of 64 radiometrically-dated paleoanthropological sites to test hypotheses of demographic response to climatic change among African hominin populations during the 150-30 ka interval. We argue that at a continental scale, population and climate changes were asynchronous and likely occurred under different regimes of climate forcing, creating alternating opportunities for migration into adjacent regions. Our results suggest little relation between large scale demographic and climate change in southern Africa during this time span, but strongly support the hypothesis of hominin occupation of the Sahara during discrete humid intervals ~135-115 ka and 105-75 ka. Hominin populations in equatorial and eastern Africa may have been buffered from the extremes of climate change by locally steep altitudinal and rainfall gradients and the complex and variable effects of increased aridity on human habitat suitability in the tropics. Our data are consistent with hominin migrations out of Africa through varying exit points from ~140-80 ka. Copyright © 2012 Elsevier Ltd. All rights reserved.

A Scaling Model for the Anthropocene Climate Variability with Projections to 2100

NASA Astrophysics Data System (ADS)

Hébert, Raphael; Lovejoy, Shaun

2017-04-01

The determination of the climate sensitivity to radiative forcing is a fundamental climate science problem with important policy implications. We use a scaling model, with a limited set of parameters, which can directly calculate the forced globally-average surface air temperature response to anthropogenic and natural forcings. At timescales larger than an inner scale τ, which we determine as the ocean-atmosphere coupling scale at around 2 years, the global system responds, approximately, linearly, so that the variability may be decomposed into additive forced and internal components. The Ruelle response theory extends the classical linear response theory for small perturbations to systems far from equilibrium. Our model thus relates radiative forcings to a forced temperature response by convolution with a suitable Green's function, or climate response function. Motivated by scaling symmetries which allow for long range dependence, we assume a general scaling form, a scaling climate response function (SCRF) which is able to produce a wide range of responses: a power-law truncated at τ. This allows us to analytically calculate the climate sensitivity at different time scales, yielding a one-to-one relation from the transient climate response to the equilibrium climate sensitivity which are estimated, respectively, as 1.6+0.3-0.2K and 2.4+1.3-0.6K at the 90 % confidence level. The model parameters are estimated within a Bayesian framework, with a fractional Gaussian noise error model as the internal variability, from forcing series, instrumental surface temperature datasets and CMIP5 GCMs Representative Concentration Pathways (RCP) scenario runs. This observation based model is robust and projections for the coming century are made following the RCP scenario 2.6, 4.5 and 8.5, yielding in the year 2100, respectively : 1.5 +0.3)_{-0.2K, 2.3 ± 0.4 K and 4.0 ± 0.6 K at the 90 % confidence level. For comparison, the associated projections from a CMIP5 multi-model ensemble(MME) (32 models) are: 1.7 ± 0.8 K, 2.6 ± 0.8 K and 4.8 ± 1.3 K. Therefore, our projection uncertainty is less than half the structural uncertainty of this CMIP5 MME.

Reducing uncertainty in Climate Response Time Scale by Bayesian Analysis of the 8.2 ka event

NASA Astrophysics Data System (ADS)

Lorenz, A.; Held, H.; Bauer, E.; Schneider von Deimling, T.

2009-04-01

We analyze the possibility of uncertainty reduction in Climate Response Time Scale by utilizing Greenland ice-core data that contain the 8.2 ka event within a Bayesian model-data intercomparison with the Earth system model of intermediate complexity, CLIMBER-2.3. Within a stochastic version of the model it has been possible to mimic the 8.2 ka event within a plausible experimental setting and with relatively good accuracy considering the timing of the event in comparison to other modeling exercises [1]. The simulation of the centennial cold event is effectively determined by the oceanic cooling rate which depends largely on the ocean diffusivity described by diffusion coefficients of relatively wide uncertainty ranges. The idea now is to discriminate between the different values of diffusivities according to their likelihood to rightly represent the duration of the 8.2 ka event and thus to exploit the paleo data to constrain uncertainty in model parameters in analogue to [2]. Implementing this inverse Bayesian Analysis with this model the technical difficulty arises to establish the related likelihood numerically in addition to the uncertain model parameters: While mainstream uncertainty analyses can assume a quasi-Gaussian shape of likelihood, with weather fluctuating around a long term mean, the 8.2 ka event as a highly nonlinear effect precludes such an a priori assumption. As a result of this study [3] the Bayesian Analysis showed a reduction of uncertainty in vertical ocean diffusivity parameters of factor 2 compared to prior knowledge. This learning effect on the model parameters is propagated to other model outputs of interest; e.g. the inverse ocean heat capacity, which is important for the dominant time scale of climate response to anthropogenic forcing which, in combination with climate sensitivity, strongly influences the climate systems reaction for the near- and medium-term future. 1 References [1] E. Bauer, A. Ganopolski, M. Montoya: Simulation of the cold climate event 8200 years ago by meltwater outburst from lake Agassiz. Paleoceanography 19:PA3014, (2004) [2] T. Schneider von Deimling, H. Held, A. Ganopolski, S. Rahmstorf, Climate sensitivity estimated from ensemble simulations of glacial climates, Climate Dynamics 27, 149-163, DOI 10.1007/s00382-006-0126-8 (2006). [3] A. Lorenz, Diploma Thesis, U Potsdam (2007).

When at what scale will trends in European mean and heavy precipitation emerge

NASA Astrophysics Data System (ADS)

Maraun, Douglas

2013-04-01

A multi-model ensemble of regional climate projections for Europe is employed to investigate how the time of emergence (TOE) for seasonal sums and maxima of daily precipitation depends on spatial scale. The TOE is redefined for emergence from internal variability only, the spread of the TOE due to imperfect climate model formulation is used as a measure of uncertainty in the TOE itself. Thereby the TOE becomes a fundamentally limiting time scale and translates into a minimum spatial scale on which robust conclusions can be drawn about precipitation trends. Thus also minimum temporal and spatial scales for adaptation planning are given. In northern Europe, positive winter trends in mean and heavy precipitation, in southwestern and southeastern Europe summer trends in mean precipitation emerge already within the next decades. Yet across wide areas, especially for heavy summer precipitation, the local trend emerges only late in the 21st century or later. For precipitation averaged to larger scales, the trend in general emerges earlier. Douglas Maraun, When at what scale will trends in European mean and heavy precipitation emerge? Env. Res. Lett., in press, 2013.

Millennial-Scale Temperature Change Velocity in the Continental Northern Neotropics

PubMed Central

Correa-Metrio, Alexander; Bush, Mark; Lozano-García, Socorro; Sosa-Nájera, Susana

2013-01-01

Climate has been inherently linked to global diversity patterns, and yet no empirical data are available to put modern climate change into a millennial-scale context. High tropical species diversity has been linked to slow rates of climate change during the Quaternary, an assumption that lacks an empirical foundation. Thus, there is the need for quantifying the velocity at which the bioclimatic space changed during the Quaternary in the tropics. Here we present rates of climate change for the late Pleistocene and Holocene from Mexico and Guatemala. An extensive modern pollen survey and fossil pollen data from two long sedimentary records (30,000 and 86,000 years for highlands and lowlands, respectively) were used to estimate past temperatures. Derived temperature profiles show a parallel long-term trend and a similar cooling during the Last Glacial Maximum in the Guatemalan lowlands and the Mexican highlands. Temperature estimates and digital elevation models were used to calculate the velocity of isotherm displacement (temperature change velocity) for the time period contained in each record. Our analyses showed that temperature change velocities in Mesoamerica during the late Quaternary were at least four times slower than values reported for the last 50 years, but also at least twice as fast as those obtained from recent models. Our data demonstrate that, given extremely high temperature change velocities, species survival must have relied on either microrefugial populations or persistence of suppressed individuals. Contrary to the usual expectation of stable climates being associated with high diversity, our results suggest that Quaternary tropical diversity was probably maintained by centennial-scale oscillatory climatic variability that forestalled competitive exclusion. As humans have simplified modern landscapes, thereby removing potential microrefugia, and climate change is occurring monotonically at a very high velocity, extinction risk for tropical species is higher than at any time in the last 86,000 years. PMID:24312614

Millennial-scale temperature change velocity in the continental northern Neotropics.

PubMed

Correa-Metrio, Alexander; Bush, Mark; Lozano-García, Socorro; Sosa-Nájera, Susana

2013-01-01

Climate has been inherently linked to global diversity patterns, and yet no empirical data are available to put modern climate change into a millennial-scale context. High tropical species diversity has been linked to slow rates of climate change during the Quaternary, an assumption that lacks an empirical foundation. Thus, there is the need for quantifying the velocity at which the bioclimatic space changed during the Quaternary in the tropics. Here we present rates of climate change for the late Pleistocene and Holocene from Mexico and Guatemala. An extensive modern pollen survey and fossil pollen data from two long sedimentary records (30,000 and 86,000 years for highlands and lowlands, respectively) were used to estimate past temperatures. Derived temperature profiles show a parallel long-term trend and a similar cooling during the Last Glacial Maximum in the Guatemalan lowlands and the Mexican highlands. Temperature estimates and digital elevation models were used to calculate the velocity of isotherm displacement (temperature change velocity) for the time period contained in each record. Our analyses showed that temperature change velocities in Mesoamerica during the late Quaternary were at least four times slower than values reported for the last 50 years, but also at least twice as fast as those obtained from recent models. Our data demonstrate that, given extremely high temperature change velocities, species survival must have relied on either microrefugial populations or persistence of suppressed individuals. Contrary to the usual expectation of stable climates being associated with high diversity, our results suggest that Quaternary tropical diversity was probably maintained by centennial-scale oscillatory climatic variability that forestalled competitive exclusion. As humans have simplified modern landscapes, thereby removing potential microrefugia, and climate change is occurring monotonically at a very high velocity, extinction risk for tropical species is higher than at any time in the last 86,000 years.

Species interactions and response time to climate change: ice-cover and terrestrial run-off shaping Arctic char and brown trout competitive asymmetries

NASA Astrophysics Data System (ADS)

Finstad, A. G.; Palm Helland, I.; Jonsson, B.; Forseth, T.; Foldvik, A.; Hessen, D. O.; Hendrichsen, D. K.; Berg, O. K.; Ulvan, E.; Ugedal, O.

2011-12-01

There has been a growing recognition that single species responses to climate change often mainly are driven by interaction with other organisms and single species studies therefore not are sufficient to recognize and project ecological climate change impacts. Here, we study how performance, relative abundance and the distribution of two common Arctic and sub-Arctic freshwater fishes (brown trout and Arctic char) are driven by competitive interactions. The interactions are modified both by direct climatic effects on temperature and ice-cover, and indirectly through climate forcing of terrestrial vegetation pattern and associated carbon and nutrient run-off. We first use laboratory studies to show that Arctic char, which is the world's most northernmost distributed freshwater fish, outperform trout under low light levels and also have comparable higher growth efficiency. Corresponding to this, a combination of time series and time-for-space analyses show that ice-cover duration and carbon and nutrient load mediated by catchment vegetation properties strongly affected the outcome of the competition and likely drive the species distribution pattern through competitive exclusion. In brief, while shorter ice-cover period and decreased carbon load favored brown trout, increased ice-cover period and increased carbon load favored Arctic char. Length of ice-covered period and export of allochthonous material from catchments are major, but contrasting, climatic drivers of competitive interaction between these two freshwater lake top-predators. While projected climate change lead to decreased ice-cover, corresponding increase in forest and shrub cover amplify carbon and nutrient run-off. Although a likely outcome of future Arctic and sub-arctic climate scenarios are retractions of the Arctic char distribution area caused by competitive exclusion, the main drivers will act on different time scales. While ice-cover will change instantaneously with increasing temperature, changes in catchment vegetation, such as forest-line or shrub advancement affecting carbon and nutrient transport into lakes, act on considerably longer time-scales. This study therefore emphasizes the recurring challenge for ecological climate change studies related to species interactions within and across ecosystem compartments and the response time of ecosystems.

A first-order global model of Late Cenozoic climatic change: Orbital forcing as a pacemaker of the ice ages

NASA Technical Reports Server (NTRS)

Saltzman, Barry

1992-01-01

The development of a theory of the evolution of the climate of the earth over millions of years can be subdivided into three fundamental, nested, problems: (1) to establish by equilibrium climate models (e.g., general circulation models) the diagnostic relations, valid at any time, between the fast-response climate variables (i.e., the 'weather statistics') and both the prescribed external radiative forcing and the prescribed distribution of the slow response variables (e.g., the ice sheets and shelves, the deep ocean state, and the atmospheric CO2 concentration); (2) to construct, by an essentially inductive process, a model of the time-dependent evolution of the slow-response climatic variables over time scales longer than the damping times of these variables but shorter than the time scale of tectonic changes in the boundary conditions (e.g., altered geography and elevation of the continents, slow outgassing, and weathering) and ultra-slow astronomical changes such as in the solar radiative output; and (3) to determine the nature of these ultra-slow processes and their effects on the evolution of the equilibrium state of the climatic system about which the above time-dependent variations occur. All three problems are discussed in the context of the theory of the Quaternary climate, which will be incomplete unless it is embedded in a more general theory for the fuller Cenozoic that can accommodate the onset of the ice-age fluctuations. We construct a simple mathematical model for the Late Cenozoic climatic changes based on the hypothesis that forced and free variations of the concentration of atmospheric greenhouse gases (notably CO2), coupled with changes in the deep ocean state and ice mass, under the additional 'pacemaking' influence of earth-orbital forcing, are primary determinants of the climate state over this period. Our goal is to illustrate how a single model governing both very long term variations and higher frequency oscillatory variations in the Pleistocene can be formulated with relatively few adjustable parameters.

Specialization in Plant-Hummingbird Networks Is Associated with Species Richness, Contemporary Precipitation and Quaternary Climate-Change Velocity

PubMed Central

Dalsgaard, Bo; Magård, Else; Fjeldså, Jon; Martín González, Ana M.; Rahbek, Carsten; Olesen, Jens M.; Ollerton, Jeff; Alarcón, Ruben; Cardoso Araujo, Andrea; Cotton, Peter A.; Lara, Carlos; Machado, Caio Graco; Sazima, Ivan; Sazima, Marlies; Timmermann, Allan; Watts, Stella; Sandel, Brody; Sutherland, William J.; Svenning, Jens-Christian

2011-01-01

Large-scale geographical patterns of biotic specialization and the underlying drivers are poorly understood, but it is widely believed that climate plays an important role in determining specialization. As climate-driven range dynamics should diminish local adaptations and favor generalization, one hypothesis is that contemporary biotic specialization is determined by the degree of past climatic instability, primarily Quaternary climate-change velocity. Other prominent hypotheses predict that either contemporary climate or species richness affect biotic specialization. To gain insight into geographical patterns of contemporary biotic specialization and its drivers, we use network analysis to determine the degree of specialization in plant-hummingbird mutualistic networks sampled at 31 localities, spanning a wide range of climate regimes across the Americas. We found greater biotic specialization at lower latitudes, with latitude explaining 20–22% of the spatial variation in plant-hummingbird specialization. Potential drivers of specialization - contemporary climate, Quaternary climate-change velocity, and species richness - had superior explanatory power, together explaining 53–64% of the variation in specialization. Notably, our data provides empirical evidence for the hypothesized roles of species richness, contemporary precipitation and Quaternary climate-change velocity as key predictors of biotic specialization, whereas contemporary temperature and seasonality seem unimportant in determining specialization. These results suggest that both ecological and evolutionary processes at Quaternary time scales can be important in driving large-scale geographical patterns of contemporary biotic specialization, at least for co-evolved systems such as plant-hummingbird networks. PMID:21998716

Macroweather Predictions and Climate Projections using Scaling and Historical Observations

NASA Astrophysics Data System (ADS)

Hébert, R.; Lovejoy, S.; Del Rio Amador, L.

2017-12-01

There are two fundamental time scales that are pertinent to decadal forecasts and multidecadal projections. The first is the lifetime of planetary scale structures, about 10 days (equal to the deterministic predictability limit), and the second is - in the anthropocene - the scale at which the forced anthropogenic variability exceeds the internal variability (around 16 - 18 years). These two time scales define three regimes of variability: weather, macroweather and climate that are respectively characterized by increasing, decreasing and then increasing varibility with scale.We discuss how macroweather temperature variability can be skilfully predicted to its theoretical stochastic predictability limits by exploiting its long-range memory with the Stochastic Seasonal and Interannual Prediction System (StocSIPS). At multi-decadal timescales, the temperature response to forcing is approximately linear and this can be exploited to make projections with a Green's function, or Climate Response Function (CRF). To make the problem tractable, we exploit the temporal scaling symmetry and restrict our attention to global mean forcing and temperature response using a scaling CRF characterized by the scaling exponent H and an inner scale of linearity τ. An aerosol linear scaling factor α and a non-linear volcanic damping exponent ν were introduced to account for the large uncertainty in these forcings. We estimate the model and forcing parameters by Bayesian inference using historical data and these allow us to analytically calculate a median (and likely 66% range) for the transient climate response, and for the equilibrium climate sensitivity: 1.6K ([1.5,1.8]K) and 2.4K ([1.9,3.4]K) respectively. Aerosol forcing typically has large uncertainty and we find a modern (2005) forcing very likely range (90%) of [-1.0, -0.3] Wm-2 with median at -0.7 Wm-2. Projecting to 2100, we find that to keep the warming below 1.5 K, future emissions must undergo cuts similar to Representative Concentration Pathway (RCP) 2.6 for which the probability to remain under 1.5 K is 48%. RCP 4.5 and RCP 8.5-like futures overshoot with very high probability. This underscores that over the next century, the state of the environment will be strongly influenced by past, present and future economical policies.

TerraClimate, a high-resolution global dataset of monthly climate and climatic water balance from 1958-2015.

PubMed

Abatzoglou, John T; Dobrowski, Solomon Z; Parks, Sean A; Hegewisch, Katherine C

2018-01-09

We present TerraClimate, a dataset of high-spatial resolution (1/24°, ~4-km) monthly climate and climatic water balance for global terrestrial surfaces from 1958-2015. TerraClimate uses climatically aided interpolation, combining high-spatial resolution climatological normals from the WorldClim dataset, with coarser resolution time varying (i.e., monthly) data from other sources to produce a monthly dataset of precipitation, maximum and minimum temperature, wind speed, vapor pressure, and solar radiation. TerraClimate additionally produces monthly surface water balance datasets using a water balance model that incorporates reference evapotranspiration, precipitation, temperature, and interpolated plant extractable soil water capacity. These data provide important inputs for ecological and hydrological studies at global scales that require high spatial resolution and time varying climate and climatic water balance data. We validated spatiotemporal aspects of TerraClimate using annual temperature, precipitation, and calculated reference evapotranspiration from station data, as well as annual runoff from streamflow gauges. TerraClimate datasets showed noted improvement in overall mean absolute error and increased spatial realism relative to coarser resolution gridded datasets.

TerraClimate, a high-resolution global dataset of monthly climate and climatic water balance from 1958-2015

NASA Astrophysics Data System (ADS)

Abatzoglou, John T.; Dobrowski, Solomon Z.; Parks, Sean A.; Hegewisch, Katherine C.

2018-01-01

We present TerraClimate, a dataset of high-spatial resolution (1/24°, ~4-km) monthly climate and climatic water balance for global terrestrial surfaces from 1958-2015. TerraClimate uses climatically aided interpolation, combining high-spatial resolution climatological normals from the WorldClim dataset, with coarser resolution time varying (i.e., monthly) data from other sources to produce a monthly dataset of precipitation, maximum and minimum temperature, wind speed, vapor pressure, and solar radiation. TerraClimate additionally produces monthly surface water balance datasets using a water balance model that incorporates reference evapotranspiration, precipitation, temperature, and interpolated plant extractable soil water capacity. These data provide important inputs for ecological and hydrological studies at global scales that require high spatial resolution and time varying climate and climatic water balance data. We validated spatiotemporal aspects of TerraClimate using annual temperature, precipitation, and calculated reference evapotranspiration from station data, as well as annual runoff from streamflow gauges. TerraClimate datasets showed noted improvement in overall mean absolute error and increased spatial realism relative to coarser resolution gridded datasets.

Solar Activity and the Sea-surface Temperature Record-evidence of a Long-period Variation in Solar Total Irradiance

NASA Technical Reports Server (NTRS)

Reid, George C.

1990-01-01

There have been many suggestions over the years of a connection between solar activity and the Earth's climate on time scales long compared to the 11-year sunspot cycle. They have remained little more than suggestions largely because of the major uncertainties in the climate record itself, and the difficulty in trying to compile a global average from an assembly of measurements that are uneven in both quality and distribution. Different climate time response to solar activity, some suggesting a positive correlation, some a negative correlation, and some no correlation at all. The only excuse for making yet another such suggestion is that much effort has been devoted in recent years to compiling climate records for the past century or more that are internally consistent and believable, and that a decadal-scale record of solar total irradiance is emerging from spacecraft measurements, and can be used to set limits on the variation that is likely to have occurred on these time scales. The work described here was originally inspired by the observation that the time series of globally averaged sea-surface temperatures over the past 120 years or so, as compiled by the British Meteorological Office group (Folland and Kates, 1984), bore a resonable similarity to the long-term average sunspot number, which is an indicator of the secular variability of solar activity. The two time series are shown where the sunspot number is shown as the 135-month running mean, and the SST variation is shown as the departure from an arbitrary average value. The simplest explanation of the similarity, if one accepts it as other than coincidental, is that the sun's luminosity may have been varying more or less in step with the level of solar activity, or in other words that there is a close coupling between the sun's magnetic condition and its radiative output on time scales longer than the 11-year cycle. Such an idea is not new, and in fact the time series shown can be regarded as a modern extension of the proposal put forward by Eddy (1977) to explain the covariance between various global climate indicators and solar activity as revealed by the C-14 record over the past millenium.

Local control on precipitation in a fully coupled climate-hydrology model.

PubMed

Larsen, Morten A D; Christensen, Jens H; Drews, Martin; Butts, Michael B; Refsgaard, Jens C

2016-03-10

The ability to simulate regional precipitation realistically by climate models is essential to understand and adapt to climate change. Due to the complexity of associated processes, particularly at unresolved temporal and spatial scales this continues to be a major challenge. As a result, climate simulations of precipitation often exhibit substantial biases that affect the reliability of future projections. Here we demonstrate how a regional climate model (RCM) coupled to a distributed hydrological catchment model that fully integrates water and energy fluxes between the subsurface, land surface, plant cover and the atmosphere, enables a realistic representation of local precipitation. Substantial improvements in simulated precipitation dynamics on seasonal and longer time scales is seen for a simulation period of six years and can be attributed to a more complete treatment of hydrological sub-surface processes including groundwater and moisture feedback. A high degree of local influence on the atmosphere suggests that coupled climate-hydrology models have a potential for improving climate projections and the results further indicate a diminished need for bias correction in climate-hydrology impact studies.

Local control on precipitation in a fully coupled climate-hydrology model

PubMed Central

Larsen, Morten A. D.; Christensen, Jens H.; Drews, Martin; Butts, Michael B.; Refsgaard, Jens C.

2016-01-01

The ability to simulate regional precipitation realistically by climate models is essential to understand and adapt to climate change. Due to the complexity of associated processes, particularly at unresolved temporal and spatial scales this continues to be a major challenge. As a result, climate simulations of precipitation often exhibit substantial biases that affect the reliability of future projections. Here we demonstrate how a regional climate model (RCM) coupled to a distributed hydrological catchment model that fully integrates water and energy fluxes between the subsurface, land surface, plant cover and the atmosphere, enables a realistic representation of local precipitation. Substantial improvements in simulated precipitation dynamics on seasonal and longer time scales is seen for a simulation period of six years and can be attributed to a more complete treatment of hydrological sub-surface processes including groundwater and moisture feedback. A high degree of local influence on the atmosphere suggests that coupled climate-hydrology models have a potential for improving climate projections and the results further indicate a diminished need for bias correction in climate-hydrology impact studies. PMID:26960564

Uncovering the Anthropogenic Sea Level Change using an Improved Sea Level Reconstruction for the Indian Ocean

NASA Astrophysics Data System (ADS)

Kumar, P.; Hamlington, B.; Thompson, P. R.; Han, W.

2016-12-01

Despite having some of the world's most densely populated and vulnerable coastal regions, sea level (SL) variability in the Indian Ocean (IO) has received considerably less attention than the Pacific Ocean. Differentiating the internal variability from the long-term trend in global mean sea level (GMSL) at decadal time-scales is vital for planning and mitigation efforts in the IO region. Understanding the dynamics of internal and anthropogenic SL change is essential for understanding the dynamic pathways that link the IO basin to terrestrial climates world-wide. With a sparse pre-satellite observational record of the IO, the Indo-Pacific internal climate variability is difficult to represent accurately. However, an improved representation of pre-satellite SL variability can be achieved by using a multivariate reconstruction technique. By using cyclostationary empirical orthogonal functions (CSEOFs) that can capture time-varying spatial patterns, gaps in the historical record when observations are sparse are filled using spatial relationships from time periods when the observational network is dense. This reconstruction method combines SL data and sea surface temperature (SST) to create a SL reconstruction that spans a period from 1900 to present, long enough to study climate signals over interannual to decadal time scales. This study aims at estimating the component of SL rise that relates to anthropogenic forcing by identifying and removing the fraction related to internal variability. An improved understanding of how the internal climate variability can affect the IO SL trend and variability, will provide an insight into the future SL changes. It is also important to study links between SL and climate variability in the past to understand how SL will respond to similar climatic events in the future and if this response will be influenced by the changing climate.

Semi-supervised tracking of extreme weather events in global spatio-temporal climate datasets

NASA Astrophysics Data System (ADS)

Kim, S. K.; Prabhat, M.; Williams, D. N.

2017-12-01

Deep neural networks have been successfully applied to solve problem to detect extreme weather events in large scale climate datasets and attend superior performance that overshadows all previous hand-crafted methods. Recent work has shown that multichannel spatiotemporal encoder-decoder CNN architecture is able to localize events in semi-supervised bounding box. Motivated by this work, we propose new learning metric based on Variational Auto-Encoders (VAE) and Long-Short-Term-Memory (LSTM) to track extreme weather events in spatio-temporal dataset. We consider spatio-temporal object tracking problems as learning probabilistic distribution of continuous latent features of auto-encoder using stochastic variational inference. For this, we assume that our datasets are i.i.d and latent features is able to be modeled by Gaussian distribution. In proposed metric, we first train VAE to generate approximate posterior given multichannel climate input with an extreme climate event at fixed time. Then, we predict bounding box, location and class of extreme climate events using convolutional layers given input concatenating three features including embedding, sampled mean and standard deviation. Lastly, we train LSTM with concatenated input to learn timely information of dataset by recurrently feeding output back to next time-step's input of VAE. Our contribution is two-fold. First, we show the first semi-supervised end-to-end architecture based on VAE to track extreme weather events which can apply to massive scaled unlabeled climate datasets. Second, the information of timely movement of events is considered for bounding box prediction using LSTM which can improve accuracy of localization. To our knowledge, this technique has not been explored neither in climate community or in Machine Learning community.

The associations between work-life balance behaviours, teamwork climate and safety climate: cross-sectional survey introducing the work-life climate scale, psychometric properties, benchmarking data and future directions.

PubMed

Sexton, J Bryan; Schwartz, Stephanie P; Chadwick, Whitney A; Rehder, Kyle J; Bae, Jonathan; Bokovoy, Joanna; Doram, Keith; Sotile, Wayne; Adair, Kathryn C; Profit, Jochen

2017-08-01

Improving the resiliency of healthcare workers is a national imperative, driven in part by healthcare workers having minimal exposure to the skills and culture to achieve work-life balance (WLB). Regardless of current policies, healthcare workers feel compelled to work more and take less time to recover from work. Satisfaction with WLB has been measured, as has work-life conflict, but how frequently healthcare workers engage in specific WLB behaviours is rarely assessed. Measurement of behaviours may have advantages over measurement of perceptions; behaviours more accurately reflect WLB and can be targeted by leaders for improvement. 1. To describe a novel survey scale for evaluating work-life climate based on specific behavioural frequencies in healthcare workers.2. To evaluate the scale's psychometric properties and provide benchmarking data from a large healthcare system.3. To investigate associations between work-life climate, teamwork climate and safety climate. Cross-sectional survey study of US healthcare workers within a large healthcare system. 7923 of 9199 eligible healthcare workers across 325 work settings within 16 hospitals completed the survey in 2009 (86% response rate). The overall work-life climate scale internal consistency was Cronbach α=0.790. t-Tests of top versus bottom quartile work settings revealed that positive work-life climate was associated with better teamwork climate, safety climate and increased participation in safety leadership WalkRounds with feedback (p<0.001). Univariate analysis of variance demonstrated differences that varied significantly in WLB between healthcare worker role, hospitals and work setting. The work-life climate scale exhibits strong psychometric properties, elicits results that vary widely by work setting, discriminates between positive and negative workplace norms, and aligns well with other culture constructs that have been found to correlate with clinical outcomes. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://www.bmj.com/company/products-services/rights-and-licensing/.

Developing Flexible, Integrated Hydrologic Modeling Systems for Multiscale Analysis in the Midwest and Great Lakes Region

NASA Astrophysics Data System (ADS)

Hamlet, A. F.; Chiu, C. M.; Sharma, A.; Byun, K.; Hanson, Z.

2016-12-01

Physically based hydrologic modeling of surface and groundwater resources that can be flexibly and efficiently applied to support water resources policy/planning/management decisions at a wide range of spatial and temporal scales are greatly needed in the Midwest, where stakeholder access to such tools is currently a fundamental barrier to basic climate change assessment and adaptation efforts, and also the co-production of useful products to support detailed decision making. Based on earlier pilot studies in the Pacific Northwest Region, we are currently assembling a suite of end-to-end tools and resources to support various kinds of water resources planning and management applications across the region. One of the key aspects of these integrated tools is that the user community can access gridded products at any point along the end-to-end chain of models, looking backwards in time about 100 years (1915-2015), and forwards in time about 85 years using CMIP5 climate model projections. The integrated model is composed of historical and projected future meteorological data based on station observations and statistical and dynamically downscaled climate model output respectively. These gridded meteorological data sets serve as forcing data for the macro-scale VIC hydrologic model implemented over the Midwest at 1/16 degree resolution. High-resolution climate model (4km WRF) output provides inputs for the analyses of urban impacts, hydrologic extremes, agricultural impacts, and impacts to the Great Lakes. Groundwater recharge estimated by the surface water model provides input data for fine-scale and macro-scale groundwater models needed for specific applications. To highlight the multi-scale use of the integrated models in support of co-production of scientific information for decision making, we briefly describe three current case studies addressing different spatial scales of analysis: 1) Effects of climate change on the water balance of the Great Lakes, 2) Future hydropower resources in the St. Joseph River basin, 3) Effects of climate change on carbon cycling in small lakes in the Northern Highland Lakes District.

Native American Students' Understanding of Geologic Time Scale: 4th-8th Grade Ojibwe Students' Understanding of Earth's Geologic History

ERIC Educational Resources Information Center

Nam, Younkyeong; Karahan, Engin; Roehrig, Gillian

2016-01-01

Geologic time scale is a very important concept for understanding long-term earth system events such as climate change. This study examines forty-three 4th-8th grade Native American--particularly Ojibwe tribe--students' understanding of relative ordering and absolute time of Earth's significant geological and biological events. This study also…

Land radiative management as contributor to regional-scale climate adaptation and mitigation

NASA Astrophysics Data System (ADS)

Seneviratne, Sonia I.; Phipps, Steven J.; Pitman, Andrew J.; Hirsch, Annette L.; Davin, Edouard L.; Donat, Markus G.; Hirschi, Martin; Lenton, Andrew; Wilhelm, Micah; Kravitz, Ben

2018-02-01

Greenhouse gas emissions urgently need to be reduced. Even with a step up in mitigation, the goal of limiting global temperature rise to well below 2 °C remains challenging. Consequences of missing these goals are substantial, especially on regional scales. Because progress in the reduction of carbon dioxide emissions has been slow, climate engineering schemes are increasingly being discussed. But global schemes remain controversial and have important shortcomings. A reduction of global mean temperature through global-scale management of solar radiation could lead to strong regional disparities and affect rainfall patterns. On the other hand, active management of land radiative effects on a regional scale represents an alternative option of climate engineering that has been little discussed. Regional land radiative management could help to counteract warming, in particular hot extremes in densely populated and important agricultural regions. Regional land radiative management also raises some ethical issues, and its efficacy would be limited in time and space, depending on crop growing periods and constraints on agricultural management. But through its more regional focus and reliance on tested techniques, regional land radiative management avoids some of the main shortcomings associated with global radiation management. We argue that albedo-related climate benefits of land management should be considered more prominently when assessing regional-scale climate adaptation and mitigation as well as ecosystem services.

Consistent response of vegetation dynamics to recent climate change in tropical mountain regions.

PubMed

Krishnaswamy, Jagdish; John, Robert; Joseph, Shijo

2014-01-01

Global climate change has emerged as a major driver of ecosystem change. Here, we present evidence for globally consistent responses in vegetation dynamics to recent climate change in the world's mountain ecosystems located in the pan-tropical belt (30°N-30°S). We analyzed decadal-scale trends and seasonal cycles of vegetation greenness using monthly time series of satellite greenness (Normalized Difference Vegetation Index) and climate data for the period 1982-2006 for 47 mountain protected areas in five biodiversity hotspots. The time series of annual maximum NDVI for each of five continental regions shows mild greening trends followed by reversal to stronger browning trends around the mid-1990s. During the same period we found increasing trends in temperature but only marginal change in precipitation. The amplitude of the annual greenness cycle increased with time, and was strongly associated with the observed increase in temperature amplitude. We applied dynamic models with time-dependent regression parameters to study the time evolution of NDVI-climate relationships. We found that the relationship between vegetation greenness and temperature weakened over time or was negative. Such loss of positive temperature sensitivity has been documented in other regions as a response to temperature-induced moisture stress. We also used dynamic models to extract the trends in vegetation greenness that remain after accounting for the effects of temperature and precipitation. We found residual browning and greening trends in all regions, which indicate that factors other than temperature and precipitation also influence vegetation dynamics. Browning rates became progressively weaker with increase in elevation as indicated by quantile regression models. Tropical mountain vegetation is considered sensitive to climatic changes, so these consistent vegetation responses across widespread regions indicate persistent global-scale effects of climate warming and associated moisture stresses. © 2013 John Wiley & Sons Ltd.

Downscaling large-scale circulation to local winter climate using neural network techniques

NASA Astrophysics Data System (ADS)

Cavazos Perez, Maria Tereza

1998-12-01

The severe impacts of climate variability on society reveal the increasing need for improving regional-scale climate diagnosis. A new downscaling approach for climate diagnosis is developed here. It is based on neural network techniques that derive transfer functions from the large-scale atmospheric controls to the local winter climate in northeastern Mexico and southeastern Texas during the 1985-93 period. A first neural network (NN) model employs time-lagged component scores from a rotated principal component analysis of SLP, 500-hPa heights, and 1000-500 hPa thickness as predictors of daily precipitation. The model is able to reproduce the phase and, to some decree, the amplitude of large rainfall events, reflecting the influence of the large-scale circulation. Large errors are found over the Sierra Madre, over the Gulf of Mexico, and during El Nino events, suggesting an increase in the importance of meso-scale rainfall processes. However, errors are also due to the lack of randomization of the input data and the absence of local atmospheric predictors such as moisture. Thus, a second NN model uses time-lagged specific humidity at the Earth's surface and at the 700 hPa level, SLP tendency, and 700-500 hPa thickness as input to a self-organizing map (SOM) that pre-classifies the atmospheric fields into different patterns. The results from the SOM classification document that negative (positive) anomalies of winter precipitation over the region are associated with: (1) weaker (stronger) Aleutian low; (2) stronger (weaker) North Pacific high; (3) negative (positive) phase of the Pacific North American pattern; and (4) La Nina (El Nino) events. The SOM atmospheric patterns are then used as input to a feed-forward NN that captures over 60% of the daily rainfall variance and 94% of the daily minimum temperature variance over the region. This demonstrates the ability of artificial neural network models to simulate realistic relationships on daily time scales. The results of this research also reveal that the SOM pre-classification of days with similar atmospheric conditions succeeded in emphasizing the differences of the atmospheric variance conducive to extreme events. This resulted in a downscaling NN model that is highly sensitive to local-scale weather anomalies associated with El Nino and extreme cold events.

Low order climate models as a tool for cross-disciplinary collaboration

NASA Astrophysics Data System (ADS)

Newton, R.; Pfirman, S. L.; Tremblay, B.; Schlosser, P.

2014-12-01

Human impacts on climate are pervasive and significant and project future states cannot be projected without taking human influence into account. We recently helped convene a meeting of climatologists, policy analysts, lawyers and social scientists to discuss the dramatic loss in Arctic summer sea ice. A dialogue emerged around distinct time scales in the integrated human/natural climate system. Climate scientists tended to discuss engineering solutions as though they could be implemented immediately, whereas lags of 2 or more decades were estimated by social scientists for societal shifts and similar lags were cited for deployment by the engineers. Social scientists tended to project new climate states virtually overnight, while climatologists described time scales of decades to centuries for the system to respond to changes in forcing functions. For the conversation to develop, the group had to come to grips with an increasingly complex set of transient effect time scales and lags between decisions, changes in forcing, and system outputs. We use several low-order dynamical system models to explore mismatched timescales, ranges of lags, and uncertainty in cost estimates on climate outcomes, focusing on Arctic-specific issues. In addition to lessons regarding what is/isn't feasible from a policy and engineering perspective, these models provide a useful tool to concretize cross-disciplinary thinking. They are fast and easy to iterate through a large region of the problem space, while including surprising complexity in their evolution. Thus they are appropriate for investigating the implications of policy in an efficient, but not unrealistic physical setting. (Earth System Models, by contrast, can be too resource- and time-intensive for iteratively testing "what if" scenarios in cross-disciplinary collaborations.) Our runs indicate, for example, that the combined social, engineering and climate physics lags make it extremely unlikely that an ice-free summer ecology in the Arctic can be avoided. Further, if prospective remediation strategies are successful, a return to perennial ice conditions between one and two centuries from now is entirely likely, with interesting and large impacts on Northern economies.

A Decade-long Continental-Scale Convection-Resolving Climate Simulation on GPUs

NASA Astrophysics Data System (ADS)

Leutwyler, David; Fuhrer, Oliver; Lapillonne, Xavier; Lüthi, Daniel; Schär, Christoph

2016-04-01

The representation of moist convection in climate models represents a major challenge, due to the small scales involved. Convection-resolving models have proven to be very useful tools in numerical weather prediction and in climate research. Using horizontal grid spacings of O(1km), they allow to explicitly resolve deep convection leading to an improved representation of the water cycle. However, due to their extremely demanding computational requirements, they have so far been limited to short simulations and/or small computational domains. Innovations in the supercomputing domain have led to new supercomputer-designs that involve conventional multicore CPUs and accelerators such as graphics processing units (GPUs). One of the first atmospheric models that has been fully ported to GPUs is the Consortium for Small-Scale Modeling weather and climate model COSMO. This new version allows us to expand the size of the simulation domain to areas spanning continents and the time period up to one decade. We present results from a decade-long, convection-resolving climate simulation using the GPU-enabled COSMO version. The simulation is driven by the ERA-interim reanalysis. The results illustrate how the approach allows for the representation of interactions between synoptic-scale and meso-scale atmospheric circulations at scales ranging from 1000 to 10 km. We discuss the performance of the convection-resolving modeling approach on the European scale. Specifically we focus on the annual cycle of convection in Europe, on the organization of convective clouds and on the verification of hourly rainfall with various high resolution datasets.

Bridging long proxy data time series and instrumental observation in the Virtual Institute of Integrated Climate and Landscape Evolution Analyses - ICLEA

NASA Astrophysics Data System (ADS)

Schwab, Markus J.; Brauer, Achim; Błaszkiewicz, Mirosław; Raab, Thomas; Wilmking, Martin

2015-04-01

Understanding causes and effects of present-day climate change on landscapes and the human habitat faces two main challenges, (i) too short time series of instrumental observation that do not cover the full range of variability since mechanisms of climate change and landscape evolution work on different time scales, which often not susceptible to human perception, and, (ii) distinct regional differences due to the location with respect to oceanic/continental climatic influences, the geological underground, and the history and intensity of anthropogenic land-use. Both challenges are central for the ICLEA research strategy and demand a high degree of interdisciplinary. In particular, the need to link observations and measurements of ongoing changes with information from the past taken from natural archives requires joint work of scientists with very different time perspectives. On the one hand, scientists that work at geological time scales of thousands and more years and, on the other hand, those observing and investigating recent processes at short time scales. The GFZ, Greifswald University and the Brandenburg University of Technology together with their partner the Polish Academy of Sciences strive for focusing their research capacities and expertise in ICLEA. ICLEA offers young researchers an interdisciplinary and structured education and promote their early independence through coaching and mentoring. Postdoctoral rotation positions at the ICLEA partner institutions ensure mobility of young researchers and promote dissemination of information and expertise between disciplines. Training, Research and Analytical workshops between research partners of the ICLEA virtual institute are another important measure to qualify young researchers. The long-term mission of the Virtual Institute is to provide a substantiated data basis for sustained environmental maintenance based on a profound process understanding at all relevant time scales. Aim is to explore processes of climate and landscape evolution in an historical cultural landscape extending from northeastern Germany into northwestern Poland. The northern-central European lowlands will be facilitated as a natural laboratory providing an ideal case for utilizing a systematic and holistic approach. In ICLEA five complementary work packages (WP) are established according to the key research aspects. WP 1 focused on monitoring mainly hydrology and soil moisture as well as meteorological parameters. WP 2 is linking present day and future monitoring data with the most recent past through analyzing satellite images. This WP will further provide larger spatial scales. WP 3-5 focus on different natural archives to obtain a broad variety of high quality proxy data. Tree rings provide sub-seasonal data for the last centuries up to few millennia, varved lake sediments cover the entire research time interval at seasonal to decadal resolution and palaeosoils and geomorphological features also cover the entire period but not continuously and with lower resolution. Complementary information, like climate, tree ecophysiological and limnological data etc., are provided by cooperation with associated partners. Further information about ICLEA: www.iclea.de

On the wrong inference of long-range correlations in climate data; the case of the solar and volcanic forcing over the Tropical Pacific

NASA Astrophysics Data System (ADS)

Varotsos, Costas A.; Efstathiou, Maria N.

2017-05-01

A substantial weakness of several climate studies on long-range dependence is the conclusion of long-term memory of the climate conditions, without considering it necessary to establish the power-law scaling and to reject a simple exponential decay of the autocorrelation function. We herewith show one paradigmatic case, where a strong long-range dependence could be wrongly inferred from incomplete data analysis. We firstly apply the DFA method on the solar and volcanic forcing time series over the tropical Pacific, during the past 1000 years and the results obtained show that a statistically significant straight line fit to the fluctuation function in a log-log representation is revealed with slope higher than 0.5, which wrongly may be assumed as an indication of persistent long-range correlations in the time series. We argue that the long-range dependence cannot be concluded just from this straight line fit, but it requires the fulfilment of the two additional prerequisites i.e. reject the exponential decay of the autocorrelation function and establish the power-law scaling. In fact, the investigation of the validity of these prerequisites showed that the DFA exponent higher than 0.5 does not justify the existence of persistent long-range correlations in the temporal evolution of the solar and volcanic forcing during last millennium. In other words, we show that empirical analyses, based on these two prerequisites must not be considered as panacea for a direct proof of scaling, but only as evidence that the scaling hypothesis is plausible. We also discuss the scaling behaviour of solar and volcanic forcing data based on the Haar tool, which recently proved its ability to reliably detect the existence of the scaling effect in climate series.

CIM-EARTH: Community Integrated Model of Economic and Resource Trajectories for Humankind

NASA Astrophysics Data System (ADS)

Foster, I.; Elliott, J.; Munson, T.; Judd, K.; Moyer, E. J.; Sanstad, A. H.

2010-12-01

We report here on the development of an open source software framework termed CIM-EARTH that is intended to aid decision-making in climate and energy policy. Numerical modeling in support of evaluating policies to address climate change is difficult not only because of inherent uncertainties but because of the differences in scale and modeling approach required for various subcomponents of the system. Economic and climate models are structured quite differently, and while climate forcing can be assumed to be roughly global, climate impacts and the human response to them occur on small spatial scales. Mitigation policies likewise can be applied on scales ranging from the better part of a continent (e.g. a carbon cap-and-trade program for the entire U.S.) to a few hundred km (e.g. statewide renewable portfolio standards and local gasoline taxes). Both spatial and time resolution requirements can be challenging for global economic models. CIM-EARTH is a modular framework based around dynamic general equilibrium models. It is designed as a community tool that will enable study of the environmental benefits, transition costs, capitalization effects, and other consequences of both mitigation policies and unchecked climate change. Modularity enables both integration of highly resolved component sub-models for energy and other key systems and also user-directed choice of tradeoffs between e.g. spatial, sectoral, and time resolution. This poster describes the framework architecture, the current realized version, and plans for future releases. As with other open-source models familiar to the climate community (e.g. CCSM), deliverables will be made publicly available on a regular schedule, and community input is solicited for development of new features and modules.

Global climate shocks to agriculture from 1950 - 2015

NASA Astrophysics Data System (ADS)

Jackson, N. D.; Konar, M.; Debaere, P.; Sheffield, J.

2016-12-01

Climate shocks represent a major disruption to crop yields and agricultural production, yet a consistent and comprehensive database of agriculturally relevant climate shocks does not exist. To this end, we conduct a spatially and temporally disaggregated analysis of climate shocks to agriculture from 1950-2015 using a new gridded dataset. We quantify the occurrence and magnitude of climate shocks for all global agricultural areas during the growing season using a 0.25-degree spatial grid and daily time scale. We include all major crops and both temperature and precipitation extremes in our analysis. Critically, we evaluate climate shocks to all potential agricultural areas to improve projections within our time series. To do this, we use Global Agro-Ecological Zones maps from the Food and Agricultural Organization, the Princeton Global Meteorological Forcing dataset, and crop calendars from Sacks et al. (2010). We trace the dynamic evolution of climate shocks to agriculture, evaluate the spatial heterogeneity in agriculturally relevant climate shocks, and identify the crops and regions that are most prone to climate shocks.

Assessing fit, interplay, and scale: Aligning governance and information for improved water management in a changing climate

NASA Astrophysics Data System (ADS)

Kirchhoff, C.; Dilling, L.

2011-12-01

Water managers have long experienced the challenges of managing water resources in a variable climate. However, climate change has the potential to reshape the experiential landscape by, for example, increasing the intensity and duration of droughts, shifting precipitation timing and amounts, and changing sea levels. Given the uncertainty in evaluating potential climate risks as well as future water availability and water demands, scholars suggest water managers employ more flexible and adaptive science-based management to manage uncertainty (NRC 2009). While such an approach is appropriate, for adaptive science-based management to be effective both governance and information must be concordant across three measures: fit, interplay and scale (Young 2002)(Note 1). Our research relies on interviews of state water managers and related experts (n=50) and documentary analysis in five U.S. states to understand the drivers and constraints to improving water resource planning and decision-making in a changing climate using an assessment of fit, interplay and scale as an evaluative framework. We apply this framework to assess and compare how water managers plan and respond to current or anticipated water resource challenges within each state. We hypothesize that better alignment between the data and management framework and the water resource problem improves water managers' facility to understand (via available, relevant, timely information) and respond appropriately (through institutional response mechanisms). In addition, better alignment between governance mechanisms (between the scope of the problem and identified appropriate responses) improves water management. Moreover, because many of the management challenges analyzed in this study concern present day issues with scarcity brought on by a combination of growth and drought, better alignment of fit, interplay, and scale today will enable and prepare water managers to be more successful in adapting to climate change impacts in the long-term. Note 1: For the purposes of this research, the problem of fit deals with the level of concordance between the natural and human systems while interplay involves how institutional arrangements interact both horizontally and vertically. Lastly, scale considers both spatial and temporal alignment of the physical systems and management structure. For example, to manage water resources effectively in a changing climate suggests having information that informs short-term and long-term changes and having institutional arrangements that seek understanding across temporal scales and facilitate responses based on information available (Young 2002).

Statistical Downscaling in Multi-dimensional Wave Climate Forecast

NASA Astrophysics Data System (ADS)

Camus, P.; Méndez, F. J.; Medina, R.; Losada, I. J.; Cofiño, A. S.; Gutiérrez, J. M.

2009-04-01

Wave climate at a particular site is defined by the statistical distribution of sea state parameters, such as significant wave height, mean wave period, mean wave direction, wind velocity, wind direction and storm surge. Nowadays, long-term time series of these parameters are available from reanalysis databases obtained by numerical models. The Self-Organizing Map (SOM) technique is applied to characterize multi-dimensional wave climate, obtaining the relevant "wave types" spanning the historical variability. This technique summarizes multi-dimension of wave climate in terms of a set of clusters projected in low-dimensional lattice with a spatial organization, providing Probability Density Functions (PDFs) on the lattice. On the other hand, wind and storm surge depend on instantaneous local large-scale sea level pressure (SLP) fields while waves depend on the recent history of these fields (say, 1 to 5 days). Thus, these variables are associated with large-scale atmospheric circulation patterns. In this work, a nearest-neighbors analog method is used to predict monthly multi-dimensional wave climate. This method establishes relationships between the large-scale atmospheric circulation patterns from numerical models (SLP fields as predictors) with local wave databases of observations (monthly wave climate SOM PDFs as predictand) to set up statistical models. A wave reanalysis database, developed by Puertos del Estado (Ministerio de Fomento), is considered as historical time series of local variables. The simultaneous SLP fields calculated by NCEP atmospheric reanalysis are used as predictors. Several applications with different size of sea level pressure grid and with different temporal domain resolution are compared to obtain the optimal statistical model that better represents the monthly wave climate at a particular site. In this work we examine the potential skill of this downscaling approach considering perfect-model conditions, but we will also analyze the suitability of this methodology to be used for seasonal forecast and for long-term climate change scenario projection of wave climate.

Sensitivity of Regulated Flow Regimes to Climate Change in the Western United States

DOE Office of Scientific and Technical Information (OSTI.GOV)

Zhou, Tian; Voisin, Nathalie; Leng, Guoyong

Water management activities or flow regulations modify water fluxes at the land surface and affect water resources in space and time. We hypothesize that flow regulations change the sensitivity of river flow to climate change with respect to unmanaged water resources. Quantifying these changes in sensitivity could help elucidate the impacts of water management at different spatiotemporal scales and inform climate adaptation decisions. In this study, we compared the emergence of significant changes in natural and regulated river flow regimes across the Western United States from simulations driven by multiple climate models and scenarios. We find that significant climate change-inducedmore » alterations in natural flow do not cascade linearly through water management activities. At the annual time scale, 50% of the Hydrologic Unit Code 4 (HUC4) sub-basins over the Western U.S. regions tend to have regulated flow regime more sensitive to the climate change than natural flow regime. Seasonality analyses show that the sensitivity varies remarkably across the seasons. We also find that the sensitivity is related to the level of water management. For 35% of the HUC4 sub-basins with the highest level of water management, the summer and winter flows tend to show a heightened sensitivity to climate change due to the complexity of joint reservoir operations. We further demonstrate that the impacts of considering water management in models are comparable to those that arises from uncertainties across climate models and emission scenarios. This prompts further climate adaptation studies research about nonlinearity effects of climate change through water management activities.« less

GISS GCMAM Modeled Climate Responses to Total and Spectral Solar Forcing on Decadal and Centennial Time Scales

NASA Astrophysics Data System (ADS)

Wen, Guoyong; Cahalan, Robert; Rind, David; Jonas, Jeffrey; Pilewskie, Peter; Harder, Jerry

2014-05-01

We examine the influence of the SORCE (Solar Radiation and Climate Experiment) SIM (Spectral Irradiance Monitor) observed spectral solar irradiance (SSI) variations on Earth's climate. We apply two reconstructed spectral solar forcing scenarios, one SIM based, the other based on the SATIRE (Spectral And Total Irradiance REconstruction) model, as inputs to the GISS (Goddard Institute for Space Studies) GCMAM (Global Climate Middle Atmosphere Model) to examine the climate responses on decadal and centennial time scales. We show that the atmosphere has different temperature, ozone, and dynamic responses to the two solar spectral forcing scenarios, even when the variations in TSI (Total Solar Irradiance) are the same. We find that solar variations under either scenario contribute a small fraction of the observed temperature increase since the industrial revolution. The trend of global averaged surface air temperature response to the SIM-based solar forcing is 0.02 °C/century, about half of the temperature trend to the SATIRE-based SSI. However the temporal variation of the surface air temperature for the SIM-based solar forcing scenario is much larger compared to its SATIRE counterpart. Further research is required to examine TSI and SSI variations in the ascending phase of solar cycle 24, to assess their implications for the solar influence on climate.

GISS GCMAM Modeled Climate Responses to Total and Spectral Solar Forcing on Decadal and Centennial Time Scales

NASA Astrophysics Data System (ADS)

Wen, G.; Cahalan, R. F.; Rind, D. H.; Jonas, J.; Pilewskie, P.; Harder, J. W.; Krivova, N.

2014-12-01

We examine the influence of the SORCE (Solar Radiation and Climate Experiment) SIM (Spectral Irradiance Monitor) observed spectral solar irradiance (SSI) variations on Earth's climate. We apply two reconstructed spectral solar forcing scenarios, one SIM based, the other based on the SATIRE (Spectral And Total Irradiance REconstruction) model, as inputs to the GISS (Goddard Institute for Space Studies) GCMAM (Global Climate Middle Atmosphere Model) to examine the climate responses on decadal and centennial time scales. We show that the atmosphere has different temperature, ozone, and dynamic responses to the two solar spectral forcing scenarios, even when the variations in TSI (Total Solar Irradiance) are the same. We find that solar variations under either scenario contribute a small fraction of the observed temperature increase since the industrial revolution. The trend of global averaged surface air temperature response to the SIM-based solar forcing is 0.02 °C/century, about half of the temperature trend to the SATIRE-based SSI. However the temporal variation of the surface air temperature for the SIM-based solar forcing scenario is much larger compared to its SATIRE counterpart. Further research is required to examine TSI and SSI variations in the ascending phase of solar cycle 24, to assess their implications for the solar influence on climate.

Climate model biases in jet streams, blocking and storm tracks resulting from missing orographic drag

NASA Astrophysics Data System (ADS)

Pithan, Felix; Shepherd, Theodore G.; Zappa, Giuseppe; Sandu, Irina

2016-07-01

State-of-the art climate models generally struggle to represent important features of the large-scale circulation. Common model deficiencies include an equatorward bias in the location of the midlatitude westerlies and an overly zonal orientation of the North Atlantic storm track. Orography is known to strongly affect the atmospheric circulation and is notoriously difficult to represent in coarse-resolution climate models. Yet how the representation of orography affects circulation biases in current climate models is not understood. Here we show that the effects of switching off the parameterization of drag from low-level orographic blocking in one climate model resemble the biases of the Coupled Model Intercomparison Project Phase 5 ensemble: An overly zonal wintertime North Atlantic storm track and less European blocking events, and an equatorward shift in the Southern Hemispheric jet and increase in the Southern Annular Mode time scale. This suggests that typical circulation biases in coarse-resolution climate models may be alleviated by improved parameterizations of low-level drag.

Large-scale climatic phenomena drive fluctuations in macroinvertebrate assemblages in lowland tropical streams, Costa Rica: The importance of ENSO events in determining long-term (15y) patterns

PubMed Central

Ramírez, Alonso; Pringle, Catherine M.

2018-01-01

Understanding how environmental variables influence the distribution and density of organisms over relatively long temporal scales is a central question in ecology given increased climatic variability (e.g., precipitation, ENSO events). The primary goal of our study was to evaluate long-term (15y time span) patterns of climate, as well as environmental parameters in two Neotropical streams in lowland Costa Rica, to assess potential effects on aquatic macroinvertebrates. We also examined the relative effects of an 8y whole-stream P-enrichment experiment on macroinvertebrate assemblages against the backdrop of this long-term study. Climate, environmental variables and macroinvertebrate samples were measured monthly for 7y and then quarterly for an additional 8y in each stream. Temporal patterns in climatic and environmental variables showed high variability over time, without clear inter-annual or intra-annual patterns. Macroinvertebrate richness and abundance decreased with increasing discharge and was positively related to the number of days since the last high discharge event. Findings show that fluctuations in stream physicochemistry and macroinvertebrate assemblage structure are ultimately the result of large-scale climatic phenomena, such as ENSO events, while the 8y P-enrichment did not appear to affect macroinvertebrates. Our study demonstrates that Neotropical lowland streams are highly dynamic and not as stable as is commonly presumed, with high intra- and inter-annual variability in environmental parameters that change the structure and composition of freshwater macroinvertebrate assemblages. PMID:29420548

Coherence among climate signals, precipitation, and groundwater.

PubMed

Ghanbari, Reza Namdar; Bravo, Hector R

2011-01-01

Climate signals may affect groundwater level at different time scales in different geographical regions, and those patterns or time scales can be estimated using coherence analysis. This study shows that the synthesis effort required to search for patterns at the physical geography scale is possible, and this approach should be applicable in other regions of the world. The relations between climate signals, Southern Oscillation Index, Pacific Decadal Oscillation, North Atlantic Oscillation, North Pacific Pattern (SOI, PDO, NAO, and NP), precipitation, and groundwater level in three geographical areas of Wisconsin are examined using a three-tiered coherence analysis. In the high frequency band (<4(-1) cycles/year), there is a significant coherence between four climate signals and groundwater level in all three areas. In the low frequency band (>8(-1) to ≤23(-1) cycles/year), we found significant coherence between the SOI and NP signals and groundwater level in the forested area, characterized by shallow wells constructed in sand and gravel aquifers. In the high frequency band, there is significant coherence between the four climate signals and precipitation in all three areas. In the low frequency band, the four climate signals have effect on precipitation in the agricultural area, and SOI and NP have effect on precipitation in the forested and driftless areas. Precipitation affects groundwater level in all three areas, and in high, low and intermediate frequency bands. In the agricultural area, deeper aquifers and a more complex hydrostratigraphy and land use dilute the effect of precipitation on groundwater level for interdecadal frequencies. Copyright © 2010 The Author(s). Journal compilation © 2010 National Ground Water Association.

High regional climate sensitivity over continental China constrained by glacial-recent changes in temperature and the hydrological cycle.

PubMed

Eagle, Robert A; Risi, Camille; Mitchell, Jonathan L; Eiler, John M; Seibt, Ulrike; Neelin, J David; Li, Gaojun; Tripati, Aradhna K

2013-05-28

The East Asian monsoon is one of Earth's most significant climatic phenomena, and numerous paleoclimate archives have revealed that it exhibits variations on orbital and suborbital time scales. Quantitative constraints on the climate changes associated with these past variations are limited, yet are needed to constrain sensitivity of the region to changes in greenhouse gas levels. Here, we show central China is a region that experienced a much larger temperature change since the Last Glacial Maximum than typically simulated by climate models. We applied clumped isotope thermometry to carbonates from the central Chinese Loess Plateau to reconstruct temperature and water isotope shifts from the Last Glacial Maximum to present. We find a summertime temperature change of 6-7 °C that is reproduced by climate model simulations presented here. Proxy data reveal evidence for a shift to lighter isotopic composition of meteoric waters in glacial times, which is also captured by our model. Analysis of model outputs suggests that glacial cooling over continental China is significantly amplified by the influence of stationary waves, which, in turn, are enhanced by continental ice sheets. These results not only support high regional climate sensitivity in Central China but highlight the fundamental role of planetary-scale atmospheric dynamics in the sensitivity of regional climates to continental glaciation, changing greenhouse gas levels, and insolation.

Terrestrial carbon cycle responses to drought and climate stress: New insights using atmospheric observations of CO2 and delta13C

NASA Astrophysics Data System (ADS)

Alden, Caroline B.

Atmospheric concentrations of carbon dioxide (CO2) continue to rise well into the second decade of the new millennium, in spite of broad-scale human understanding of the impacts of fossil fuel emissions on the earth's climate. Natural sinks for CO2 that are relevant on human time scales---the world's oceans and land biosphere---appear to have kept pace with emissions. The continuously increasing strength of the land biosphere sink for CO2 is surpassing expectations given our understanding of the CO2 fertilization and warming effects on the balance between photosynthesis and respiration, especially in the face of ongoing forest degradation. The climate and carbon cycle links between the atmosphere and land biosphere are not well understood, especially at regional (100 km to 10,000 km) scales. The climate modulating effects of changing plant stomatal conductance in response to temperature and water availability is a key area of uncertainty. Further, the differential response to climate change of C3 and C4 plant functional types is not well known at regional scales. This work outlines the development of a novel application of atmospheric observations of delta13C of CO2 to investigate the links between climate and water and carbon cycling and the integrated responses of C3 and C4 ecosystems to climate variables. A two-step Bayesian batch inversion for 3-hourly, 1x1º CO2 fluxes (step one), and for 3-hourly 1x1º delta13C of recently assimilated carbon (step two) is created here for the first time, and is used to investigate links between regional climate indicators and changes in delta13C of the biosphere. Results show that predictable responses of regional-scale, integrated plant discrimination to temperature, precipitation and relative humidity anomalies can be recovered from atmospheric signals. Model development, synthetic data simulations to test sensitivity, and results for the year 2010 are presented here. This dissertation also includes two other applications of atmospheric observations of CO2 and delta13C: 1) a state of the art atmospheric CO2 budgeting exercise to show that global net sinks for CO2 have steadily increased over the last 50 years, and 2) a global investigation of the mechanistic drivers of interannual variability in biosphere discrimination against delta13C.

Improving seasonal forecasts of hydroclimatic variables through the state of multiple large-scale climate signals

NASA Astrophysics Data System (ADS)

Castelletti, A.; Giuliani, M.; Block, P. J.

2017-12-01

Increasingly uncertain hydrologic regimes combined with more frequent and intense extreme events are challenging water systems management worldwide, emphasizing the need of accurate medium- to long-term predictions to timely prompt anticipatory operations. Despite modern forecasts are skillful over short lead time (from hours to days), predictability generally tends to decrease on longer lead times. Global climate teleconnection, such as El Niño Southern Oscillation (ENSO), may contribute in extending forecast lead times. However, ENSO teleconnection is well defined in some locations, such as Western USA and Australia, while there is no consensus on how it can be detected and used in other regions, particularly in Europe, Africa, and Asia. In this work, we generalize the Niño Index Phase Analysis (NIPA) framework by contributing the Multi Variate Niño Index Phase Analysis (MV-NIPA), which allows capturing the state of multiple large-scale climate signals (i.e. ENSO, North Atlantic Oscillation, Pacific Decadal Oscillation, Atlantic Multi-decadal Oscillation, Indian Ocean Dipole) to forecast hydroclimatic variables on a seasonal time scale. Specifically, our approach distinguishes the different phases of the considered climate signals and, for each phase, identifies relevant anomalies in Sea Surface Temperature (SST) that influence the local hydrologic conditions. The potential of the MV-NIPA framework is demonstrated through an application to the Lake Como system, a regulated lake in northern Italy which is mainly operated for flood control and irrigation supply. Numerical results show high correlations between seasonal SST values and one season-ahead precipitation in the Lake Como basin. The skill of the resulting MV-NIPA forecast outperforms the one of ECMWF products. This information represents a valuable contribution to partially anticipate the summer water availability, especially during drought events, ultimately supporting the improvement of the Lake Como operations.

Net ecosystem carbon dioxide exchange in tropical rainforests - sensitivity to environmental drivers and flux measurement methodology

NASA Astrophysics Data System (ADS)

Fu, Z.; Stoy, P. C.

2017-12-01

Tropical rainforests play a central role in the Earth system services of carbon metabolism, climate regulation, biodiversity maintenance, and more. They are under threat by direct anthropogenic effects including deforestation and indirect anthropogenic effects including climate change. A synthesis of the factors that determine the net ecosystem exchange of carbon dioxide (NEE) across multiple time scales in different tropical rainforests has not been undertaken to date. Here, we study NEE and its components, gross primary productivity (GPP) and ecosystem respiration (RE), across thirteen tropical rainforest research sites with 63 total site-years of eddy covariance data. Results reveal that the five ecosystems that have greater carbon uptakes (with the magnitude of GPP greater than 3000 g C m-2 y-1) sequester less carbon - or even lose it - on an annual basis at the ecosystem scale. This counterintuitive result is because high GPP is compensated by similar magnitudes of RE. Sites that provided subcanopy CO2 storage observations had higher average magnitudes of GPP and RE and consequently lower NEE, highlighting the importance of measurement methodology for understanding carbon dynamics in tropical rainforests. Vapor pressure deficit (VPD) constrained GPP at all sites, but to differing degrees. Many environmental variables are significantly related to NEE at time scales greater than one year, and NEE at a rainforest in Malaysia is significantly related to soil moisture variability at seasonal time scales. Climate projections from 13 general circulation models (CMIP5) under representative concentration pathway (RCP) 8.5 suggest that many current tropical rainforest sites on the cooler end of the current temperature range are likely to reach a climate space similar to present-day warmer sites by the year 2050, and warmer sites will reach a climate space not currently experienced. Results demonstrate the need to quantify if mature tropical trees acclimate to heat and VPD, and to further develop flux-partitioning and gap-filling algorithms for defensible estimates of carbon exchange in tropical rainforests.

An empirical perspective for understanding climate change impacts in Switzerland

USGS Publications Warehouse

Henne, Paul; Bigalke, Moritz; Büntgen, Ulf; Colombaroli, Daniele; Conedera, Marco; Feller, Urs; Frank, David; Fuhrer, Jürg; Grosjean, Martin; Heiri, Oliver; Luterbacher, Jürg; Mestrot, Adrien; Rigling, Andreas; Rössler, Ole; Rohr, Christian; Rutishauser, This; Schwikowski, Margit; Stampfli, Andreas; Szidat, Sönke; Theurillat, Jean-Paul; Weingartner, Rolf; Wilcke, Wolfgan; Tinner, Willy

2018-01-01

Planning for the future requires a detailed understanding of how climate change affects a wide range of systems at spatial scales that are relevant to humans. Understanding of climate change impacts can be gained from observational and reconstruction approaches and from numerical models that apply existing knowledge to climate change scenarios. Although modeling approaches are prominent in climate change assessments, observations and reconstructions provide insights that cannot be derived from simulations alone, especially at local to regional scales where climate adaptation policies are implemented. Here, we review the wealth of understanding that emerged from observations and reconstructions of ongoing and past climate change impacts in Switzerland, with wider applicability in Europe. We draw examples from hydrological, alpine, forest, and agricultural systems, which are of paramount societal importance, and are projected to undergo important changes by the end of this century. For each system, we review existing model-based projections, present what is known from observations, and discuss how empirical evidence may help improve future projections. A particular focus is given to better understanding thresholds, tipping points and feedbacks that may operate on different time scales. Observational approaches provide the grounding in evidence that is needed to develop local to regional climate adaptation strategies. Our review demonstrates that observational approaches should ideally have a synergistic relationship with modeling in identifying inconsistencies in projections as well as avenues for improvement. They are critical for uncovering unexpected relationships between climate and agricultural, natural, and hydrological systems that will be important to society in the future.

Probabilistic Evaluation of Competing Climate Models

NASA Astrophysics Data System (ADS)

Braverman, A. J.; Chatterjee, S.; Heyman, M.; Cressie, N.

2017-12-01

A standard paradigm for assessing the quality of climate model simulations is to compare what these models produce for past and present time periods, to observations of the past and present. Many of these comparisons are based on simple summary statistics called metrics. Here, we propose an alternative: evaluation of competing climate models through probabilities derived from tests of the hypothesis that climate-model-simulated and observed time sequences share common climate-scale signals. The probabilities are based on the behavior of summary statistics of climate model output and observational data, over ensembles of pseudo-realizations. These are obtained by partitioning the original time sequences into signal and noise components, and using a parametric bootstrap to create pseudo-realizations of the noise sequences. The statistics we choose come from working in the space of decorrelated and dimension-reduced wavelet coefficients. We compare monthly sequences of CMIP5 model output of average global near-surface temperature anomalies to similar sequences obtained from the well-known HadCRUT4 data set, as an illustration.

From the Last Interglacial to the Anthropocene: Modelling a Complete Glacial Cycle (PalMod)

NASA Astrophysics Data System (ADS)

Brücher, Tim; Latif, Mojib

2017-04-01

We will give a short overview and update on the current status of the national climate modelling initiative PalMod (Paleo Modelling, www.palmod.de). PalMod focuses on the understanding of the climate system dynamics and its variability during the last glacial cycle. The initiative is funded by the German Federal Ministry of Education and Research (BMBF) and its specific topics are: (i) to identify and quantify the relative contributions of the fundamental processes which determined the Earth's climate trajectory and variability during the last glacial cycle, (ii) to simulate with comprehensive Earth System Models (ESMs) the climate from the peak of the last interglacial - the Eemian warm period - up to the present, including the changes in the spectrum of variability, and (iii) to assess possible future climate trajectories beyond this century during the next millennia with sophisticated ESMs tested in such a way. The research is intended to be conducted over a period of 10 years, but with shorter funding cycles. PalMod kicked off in February 2016. The first phase focuses on the last deglaciation (app. the last 23.000 years). From the ESM perspective PalMod pushes forward model development by coupling ESM with dynamical ice sheet models. Computer scientists work on speeding up climate models using different concepts (like parallelisation in time) and one working group is dedicated to perform a comprehensive data synthesis to validate model performance. The envisioned approach is innovative in three respects. First, the consortium aims at simulating a full glacial cycle in transient mode and with comprehensive ESMs which allow full interactions between the physical and biogeochemical components of the Earth system, including ice sheets. Second, we shall address climate variability during the last glacial cycle on a large range of time scales, from interannual to multi-millennial, and attempt to quantify the relative contributions of external forcing and processes internal to the Earth system to climate variability at different time scales. Third, in order to achieve a higher level of understanding of natural climate variability at time scales of millennia, its governing processes and implications for the future climate, we bring together three different research communities: the Earth system modeling community, the proxy data community and the computational science community. The consortium consists of 18 partners including all major modelling centers within Germany. The funding comprises approximately 65 PostDoc positions and more than 120 scientists are involved. PalMod is coordinated at the Helmholtz Centre for Ocean Research Kiel (GEOMAR).

ICLEA - The Virtual Institute of Integrated Climate and Landscape Evolution Analyses

NASA Astrophysics Data System (ADS)

Schwab, Markus; Brauer, Achim; Błaszkiewicz, Mirosław; Blume, Theresa; Raab, Thomas; Wilmking, Martin

2017-04-01

Since 2012, the partner of the virtual institute ICLEA from Germany and Poland view on past changes as natural experiments as a guidebook for better anticipation of future changes and their impacts. Since the natural evolution became increasingly superimposed by human impacts since the Neolithic we include an in-depth discussion of impacts of climate and environment change on societies and vice versa. Understanding causes and effects of present-day climate change on landscapes and the human habitat faces two main challenges, (I) too short time series of instrumental observation that do not cover the full range of variability since mechanisms of climate change and landscape evolution work on different time scales, which often not susceptible to human perception, and, (II) distinct regional differences due to the location with respect to oceanic/continental climatic influences, the geological underground, and the history and intensity of anthropogenic land-use. Both challenges are central for the ICLEA research strategy and demand a high degree of interdisciplinary. In particular, the need to link observations and measurements of ongoing changes with information from the past taken from natural archives requires joint work of scientists with very different time perspectives. On the one hand, scientists that work at geological time scales of thousands and more years and, on the other hand, those observing and investigating recent processes at short time scales. Five complementary work packages (WP) are established according to the key research aspects: WP 1 focused on monitoring mainly hydrology and soil moisture as well as meteorological parameters. WP 2 is linking present day and future monitoring data with the most recent past through analyzing satellite images. This WP will further provide larger spatial scales. WP 3-5 are focused on different natural archives to obtain a broad variety of high quality proxy data. Tree rings provide sub-seasonal data for the last centuries up to few millennia, varved lake sediments cover the entire research time interval at seasonal to decadal resolution and palaeosoils and geomorphological features also cover the entire period but not continuously and with lower resolution. Complementary information, like climate, tree ecophysiological and limnological data etc., are provided by cooperation with associated partners. In these five WP the partner focusing their research capacities and expertise in ICLEA. We offers young researchers an interdisciplinary and structured education and promote their early independence through coaching and mentoring. Postdoctoral rotation positions promote dissemination of information and expertise between disciplines. ICLEA results are published in about 80 peer reviewed scientific articles and available for the scientific community. The long-term mission of the Virtual Institute is to provide a substantiated data basis for sustained environmental maintenance based on a profound process understanding at all relevant time scales. Aim is to explore processes of climate and landscape evolution in an historical cultural landscape extending from northeastern Germany into northwestern Poland. The northern-central European lowlands is facilitated as a natural laboratory providing an ideal case for utilizing a systematic and holistic approach. Further information about ICLEA: www.iclea.de

Inter-model variability in hydrological extremes projections for Amazonian sub-basins

NASA Astrophysics Data System (ADS)

Andres Rodriguez, Daniel; Garofolo, Lucas; Lázaro de Siqueira Júnior, José; Samprogna Mohor, Guilherme; Tomasella, Javier

2014-05-01

Irreducible uncertainties due to knowledge's limitations, chaotic nature of climate system and human decision-making process drive uncertainties in Climate Change projections. Such uncertainties affect the impact studies, mainly when associated to extreme events, and difficult the decision-making process aimed at mitigation and adaptation. However, these uncertainties allow the possibility to develop exploratory analyses on system's vulnerability to different sceneries. The use of different climate model's projections allows to aboard uncertainties issues allowing the use of multiple runs to explore a wide range of potential impacts and its implications for potential vulnerabilities. Statistical approaches for analyses of extreme values are usually based on stationarity assumptions. However, nonstationarity is relevant at the time scales considered for extreme value analyses and could have great implications in dynamic complex systems, mainly under climate change transformations. Because this, it is required to consider the nonstationarity in the statistical distribution parameters. We carried out a study of the dispersion in hydrological extremes projections using climate change projections from several climate models to feed the Distributed Hydrological Model of the National Institute for Spatial Research, MHD-INPE, applied in Amazonian sub-basins. This model is a large-scale hydrological model that uses a TopModel approach to solve runoff generation processes at the grid-cell scale. MHD-INPE model was calibrated for 1970-1990 using observed meteorological data and comparing observed and simulated discharges by using several performance coeficients. Hydrological Model integrations were performed for present historical time (1970-1990) and for future period (2010-2100). Because climate models simulate the variability of the climate system in statistical terms rather than reproduce the historical behavior of climate variables, the performances of the model's runs during the historical period, when feed with climate model data, were tested using descriptors of the Flow Duration Curves. The analyses of projected extreme values were carried out considering the nonstationarity of the GEV distribution parameters and compared with extremes events in present time. Results show inter-model variability in a broad dispersion on projected extreme's values. Such dispersion implies different degrees of socio-economic impacts associated to extreme hydrological events. Despite the no existence of one optimum result, this variability allows the analyses of adaptation strategies and its potential vulnerabilities.

Rapid coupling between ice volume and polar temperature over the past 150,000 years.

PubMed

Grant, K M; Rohling, E J; Bar-Matthews, M; Ayalon, A; Medina-Elizalde, M; Ramsey, C Bronk; Satow, C; Roberts, A P

2012-11-29

Current global warming necessitates a detailed understanding of the relationships between climate and global ice volume. Highly resolved and continuous sea-level records are essential for quantifying ice-volume changes. However, an unbiased study of the timing of past ice-volume changes, relative to polar climate change, has so far been impossible because available sea-level records either were dated by using orbital tuning or ice-core timescales, or were discontinuous in time. Here we present an independent dating of a continuous, high-resolution sea-level record in millennial-scale detail throughout the past 150,000 years. We find that the timing of ice-volume fluctuations agrees well with that of variations in Antarctic climate and especially Greenland climate. Amplitudes of ice-volume fluctuations more closely match Antarctic (rather than Greenland) climate changes. Polar climate and ice-volume changes, and their rates of change, are found to covary within centennial response times. Finally, rates of sea-level rise reached at least 1.2 m per century during all major episodes of ice-volume reduction.

Improving seasonal forecast through the state of large-scale climate signals

NASA Astrophysics Data System (ADS)

Samale, Chiara; Zimmerman, Brian; Giuliani, Matteo; Castelletti, Andrea; Block, Paul

2017-04-01

Increasingly uncertain hydrologic regimes are challenging water systems management worldwide, emphasizing the need of accurate medium- to long-term predictions to timely prompt anticipatory operations. In fact, forecasts are usually skillful over short lead time (from hours to days), but predictability tends to decrease on longer lead times. The forecast lead time might be extended by using climate teleconnection, such as El Nino Southern Oscillation (ENSO). Despite the ENSO teleconnection is well defined in some locations such as Western USA and Australia, there is no consensus on how it can be detected and used in other river basins, particularly in Europe, Africa, and Asia. In this work, we propose the use of the Nino Index Phase Analysis for capturing the state of multiple large-scale climate signals (i.e., ENSO, North Atlantic Oscillation, Pacific Decadal Oscillation, Atlantic Multidecadal Oscillation, Dipole Mode Index). This climate state information is used for distinguishing the different phases of the climate signals and for identifying relevant teleconnections between the observations of Sea Surface Temperature (SST) that mostly influence the local hydrologic conditions. The framework is applied to the Lake Como system, a regulated lake in northern Italy which is mainly operated for flood control and irrigation supply. Preliminary results show high correlations between SST and three to six months ahead precipitation in the Lake Como basin. This forecast represents a valuable information to partially anticipate the summer water availability, ultimately supporting the improvement of the Lake Como operations.

Wintertime East Asian Jet Stream and its Association with the Asian-Pacific-American Climate

NASA Technical Reports Server (NTRS)

Yang, Song; Lau, K.-M.; Kim, K.-M.

1999-01-01

The wintertime upper-tropospheric westerly jet stream over subtropical East Asia and western Pacific, often referred to as East Asian Jet (EAJ), is an important atmospheric circulation system in the Asian-Pacific-American (APA) region. It is characterized by variabilities on a wide range of time scales and exerts a strong impact on the weather and climate of the region. On the synoptic scale, the jet is closely linked to many phenomena such as cyclogenesis, frontogenesis, blocking, storm track activity, and the development of other atmospheric disturbances. On the seasonal time scale, the variation of the EAJ determines many characteristics of the seasonal transition of the atmospheric circulation over Asia. The variabilities of the jet on these time scales have been relatively well documented (e.g., Yeh et al. 1959, Palmen and Newton 1969; Zeng 1979). It has also been understood that the inter-annual variability of the EAJ is associated with many climate signals in the APA region. These signals include the persistent anomalies of the East Asian winter monsoon and the changes in diabatic heating and in the Hadley circulation (Bjerknes 1966; Chang and Lau 1980; Huang and Gambo 1982; Kang and Held 1986; Tao and Chen 1987; Lau et al. 1988; Yang and Webster 1990; Ding 1992; Webster and Yang 1992; Dong et al. 1999). However, many questions remain for the year-to-year variabilities of the jet and their relation to the APA climate. For example, what is the relationship between the EAJ and El Nino/Southern Oscillation (ENSO)? Will the jet and ENSO play different roles in modulating the APA climate? How is the jet linked to North Pacific sea surface temperature (SST) and the Pacific/North American (PNA) teleconnection pattern? In this study, we address several issues related to the wintertime EAJ with a focus on interannual time scales. We will examine the association between the jet core and ENSO, which has always been overshadowed by the relationship between ENSO and the upper-tropospheric winds over northern extratropics of the central Pacific. We will investigate the linkage of the jet to variabilities of the Asian winter monsoon, tropical convection, and upper tropospheric wave patterns. We will also explore the relationship between the jet core and extratropical S ST with an aim at providing helpful information for improving our understanding of the connection of the EAJ to surface boundary conditions. The analysis is expected to provide information that is helpful for improving regional climate predictions.

Climate Model Evaluation using New Datasets from the Clouds and the Earth's Radiant Energy System (CERES)

NASA Technical Reports Server (NTRS)

Loeb, Norman G.; Wielicki, Bruce A.; Doelling, David R.

2008-01-01

There are some in the science community who believe that the response of the climate system to anthropogenic radiative forcing is unpredictable and we should therefore call off the quest . The key limitation in climate predictability is associated with cloud feedback. Narrowing the uncertainty in cloud feedback (and therefore climate sensitivity) requires optimal use of the best available observations to evaluate and improve climate model processes and constrain climate model simulations over longer time scales. The Clouds and the Earth s Radiant Energy System (CERES) is a satellite-based program that provides global cloud, aerosol and radiative flux observations for improving our understanding of cloud-aerosol-radiation feedbacks in the Earth s climate system. CERES is the successor to the Earth Radiation Budget Experiment (ERBE), which has widely been used to evaluate climate models both at short time scales (e.g., process studies) and at decadal time scales. A CERES instrument flew on the TRMM satellite and captured the dramatic 1998 El Nino, and four other CERES instruments are currently flying aboard the Terra and Aqua platforms. Plans are underway to fly the remaining copy of CERES on the upcoming NPP spacecraft (mid-2010 launch date). Every aspect of CERES represents a significant improvement over ERBE. While both CERES and ERBE measure broadband radiation, CERES calibration is a factor of 2 better than ERBE. In order to improve the characterization of clouds and aerosols within a CERES footprint, we use coincident higher-resolution imager observations (VIRS, MODIS or VIIRS) to provide a consistent cloud-aerosol-radiation dataset at climate accuracy. Improved radiative fluxes are obtained by using new CERES-derived Angular Distribution Models (ADMs) for converting measured radiances to fluxes. CERES radiative fluxes are a factor of 2 more accurate than ERBE overall, but the improvement by cloud type and at high latitudes can be as high as a factor of 5. Diurnal cycles are explicitly resolved by merging geostationary satellite observations with CERES and MODIS. Atmospheric state data are provided from a frozen version of the Global Modeling and Assimilation Office- Data Assimilation System at the NASA Goddard Space Flight Center. In addition to improving the accuracy of top-of-atmosphere (TOA) radiative fluxes, CERES also produces radiative fluxes at the surface and at several levels in the atmosphere using radiative transfer modeling, constrained at the TOA by CERES (ERBE was limited to the TOA). In all, CERES uses 11 instruments on 7 spacecraft all integrated to obtain climate accuracy in TOA to surface fluxes. This presentation will provide an overview of several new CERES datasets of interest to the climate community (including a new adjusted TOA flux dataset constrained by estimates of heat storage in the Earth system), show direct comparisons between CERES ad ERBE, and provide a detailed error analysis of CERES fluxes at various time and space scales. We discuss how observations can be used to reduce uncertainties in cloud feedback and climate sensitivity and strongly argue why we should NOT "call off the quest".

Application of global weather and climate model output to the design and operation of wind-energy systems

DOE Office of Scientific and Technical Information (OSTI.GOV)

Curry, Judith

This project addressed the challenge of providing weather and climate information to support the operation, management and planning for wind-energy systems. The need for forecast information is extending to longer projection windows with increasing penetration of wind power into the grid and also with diminishing reserve margins to meet peak loads during significant weather events. Maintenance planning and natural gas trading is being influenced increasingly by anticipation of wind generation on timescales of weeks to months. Future scenarios on decadal time scales are needed to support assessment of wind farm siting, government planning, long-term wind purchase agreements and the regulatorymore » environment. The challenge of making wind forecasts on these longer time scales is associated with a wide range of uncertainties in general circulation and regional climate models that make them unsuitable for direct use in the design and planning of wind-energy systems. To address this challenge, CFAN has developed a hybrid statistical/dynamical forecasting scheme for delivering probabilistic forecasts on time scales from one day to seven months using what is arguably the best forecasting system in the world (European Centre for Medium Range Weather Forecasting, ECMWF). The project also provided a framework to assess future wind power through developing scenarios of interannual to decadal climate variability and change. The Phase II research has successfully developed an operational wind power forecasting system for the U.S., which is being extended to Europe and possibly Asia.« less

Effects of lateral boundary condition resolution and update frequency on regional climate model predictions

NASA Astrophysics Data System (ADS)

Pankatz, Klaus; Kerkweg, Astrid

2015-04-01

The work presented is part of the joint project "DecReg" ("Regional decadal predictability") which is in turn part of the project "MiKlip" ("Decadal predictions"), an effort funded by the German Federal Ministry of Education and Research to improve decadal predictions on a global and regional scale. In MiKlip, one big question is if regional climate modeling shows "added value", i.e. to evaluate, if regional climate models (RCM) produce better results than the driving models. However, the scope of this study is to look more closely at the setup specific details of regional climate modeling. As regional models only simulate a small domain, they have to inherit information about the state of the atmosphere at their lateral boundaries from external data sets. There are many unresolved questions concerning the setup of lateral boundary conditions (LBC). External data sets come from global models or from global reanalysis data-sets. A temporal resolution of six hours is common for this kind of data. This is mainly due to the fact, that storage space is a limiting factor, especially for climate simulations. However, theoretically, the coupling frequency could be as high as the time step of the driving model. Meanwhile, it is unclear if a more frequent update of the LBCs has a significant effect on the climate in the domain of the RCM. The first study examines how the RCM reacts to a higher update frequency. The study is based on a 30 year time slice experiment for three update frequencies of the LBC, namely six hours, one hour and six minutes. The evaluation of means, standard deviations and statistics of the climate in the regional domain shows only small deviations, some statistically significant though, of 2m temperature, sea level pressure and precipitation. The second part of the first study assesses parameters linked to cyclone activity, which is affected by the LBC update frequency. Differences in track density and strength are found when comparing the simulations. Theoretically, regional down-scaling should act like a magnifying glass. It should reveal details on small scales which a global model cannot resolve, but it should not affect the large scale flow. As the development of the small scale features takes some time, it is important that the air stays long enough within the regional domain. The spin-up time of the small scale features is, of course, dependent on the resolution of the LBC and the resolution of the RCM. The second study examines the quality of decadal hind-casts over Europe of the decade 2001-2010 when the horizontal resolution of the driving model, namely 2.8°, 1.8°, 1.4°, 1.1°, from which the LBC are calculated, is altered. The study shows, that a smaller resolution gap between LBC resolution and RCM resolution might be beneficial.

A hydrogeologic framework for characterizing summer streamflow sensitivity to climate warming in the Pacific Northwest, USA

NASA Astrophysics Data System (ADS)

Safeeq, M.; Grant, G. E.; Lewis, S. L.; Kramer, M. G.; Staab, B.

2014-09-01

Summer streamflows in the Pacific Northwest are largely derived from melting snow and groundwater discharge. As the climate warms, diminishing snowpack and earlier snowmelt will cause reductions in summer streamflow. Most regional-scale assessments of climate change impacts on streamflow use downscaled temperature and precipitation projections from general circulation models (GCMs) coupled with large-scale hydrologic models. Here we develop and apply an analytical hydrogeologic framework for characterizing summer streamflow sensitivity to a change in the timing and magnitude of recharge in a spatially explicit fashion. In particular, we incorporate the role of deep groundwater, which large-scale hydrologic models generally fail to capture, into streamflow sensitivity assessments. We validate our analytical streamflow sensitivities against two empirical measures of sensitivity derived using historical observations of temperature, precipitation, and streamflow from 217 watersheds. In general, empirically and analytically derived streamflow sensitivity values correspond. Although the selected watersheds cover a range of hydrologic regimes (e.g., rain-dominated, mixture of rain and snow, and snow-dominated), sensitivity validation was primarily driven by the snow-dominated watersheds, which are subjected to a wider range of change in recharge timing and magnitude as a result of increased temperature. Overall, two patterns emerge from this analysis: first, areas with high streamflow sensitivity also have higher summer streamflows as compared to low-sensitivity areas. Second, the level of sensitivity and spatial extent of highly sensitive areas diminishes over time as the summer progresses. Results of this analysis point to a robust, practical, and scalable approach that can help assess risk at the landscape scale, complement the downscaling approach, be applied to any climate scenario of interest, and provide a framework to assist land and water managers in adapting to an uncertain and potentially challenging future.

A dataset of future daily weather data for crop modelling over Europe derived from climate change scenarios

NASA Astrophysics Data System (ADS)

Duveiller, G.; Donatelli, M.; Fumagalli, D.; Zucchini, A.; Nelson, R.; Baruth, B.

2017-02-01

Coupled atmosphere-ocean general circulation models (GCMs) simulate different realizations of possible future climates at global scale under contrasting scenarios of land-use and greenhouse gas emissions. Such data require several additional processing steps before it can be used to drive impact models. Spatial downscaling, typically by regional climate models (RCM), and bias-correction are two such steps that have already been addressed for Europe. Yet, the errors in resulting daily meteorological variables may be too large for specific model applications. Crop simulation models are particularly sensitive to these inconsistencies and thus require further processing of GCM-RCM outputs. Moreover, crop models are often run in a stochastic manner by using various plausible weather time series (often generated using stochastic weather generators) to represent climate time scale for a period of interest (e.g. 2000 ± 15 years), while GCM simulations typically provide a single time series for a given emission scenario. To inform agricultural policy-making, data on near- and medium-term decadal time scale is mostly requested, e.g. 2020 or 2030. Taking a sample of multiple years from these unique time series to represent time horizons in the near future is particularly problematic because selecting overlapping years may lead to spurious trends, creating artefacts in the results of the impact model simulations. This paper presents a database of consolidated and coherent future daily weather data for Europe that addresses these problems. Input data consist of daily temperature and precipitation from three dynamically downscaled and bias-corrected regional climate simulations of the IPCC A1B emission scenario created within the ENSEMBLES project. Solar radiation is estimated from temperature based on an auto-calibration procedure. Wind speed and relative air humidity are collected from historical series. From these variables, reference evapotranspiration and vapour pressure deficit are estimated ensuring consistency within daily records. The weather generator ClimGen is then used to create 30 synthetic years of all variables to characterize the time horizons of 2000, 2020 and 2030, which can readily be used for crop modelling studies.

Herbarium specimens can reveal impacts of climate change on plant phenology; a review of methods and applications.

PubMed

Jones, Casey A; Daehler, Curtis C

2018-01-01

Studies in plant phenology have provided some of the best evidence for large-scale responses to recent climate change. Over the last decade, more than thirty studies have used herbarium specimens to analyze changes in flowering phenology over time, although studies from tropical environments are thus far generally lacking. In this review, we summarize the approaches and applications used to date. Reproductive plant phenology has primarily been analyzed using two summary statistics, the mean flowering day of year and first-flowering day of year, but mean flowering day has proven to be a more robust statistic. Two types of regression models have been applied to test for associations between flowering, temperature and time: flowering day regressed on year and flowering day regressed on temperature. Most studies analyzed the effect of temperature by averaging temperatures from three months prior to the date of flowering. On average, published studies have used 55 herbarium specimens per species to characterize changes in phenology over time, but in many cases fewer specimens were used. Geospatial grid data are increasingly being used for determining average temperatures at herbarium specimen collection locations, allowing testing for finer scale correspondence between phenology and climate. Multiple studies have shown that inferences from herbarium specimen data are comparable to findings from systematically collected field observations. Understanding phenological responses to climate change is a crucial step towards recognizing implications for higher trophic levels and large-scale ecosystem processes. As herbaria are increasingly being digitized worldwide, more data are becoming available for future studies. As temperatures continue to rise globally, herbarium specimens are expected to become an increasingly important resource for analyzing plant responses to climate change.

Forecasting the forest and the trees: consequences of drought in competitive forests

NASA Astrophysics Data System (ADS)

Clark, J. S.

2015-12-01

Models that translate individual tree responses to distribution and abundance of competing populations are needed to understand forest vulnerability to drought. Currently, biodiversity predictions rely on one scale or the other, but do not combine them. Synthesis is accomplished here by modeling data together, each with their respective scale-dependent connections to the scale needed for prediction—landscape to regional biodiversity. The approach we summarize integrates three scales, i) individual growth, reproduction, and survival, ii) size-species structure of stands, and iii) regional forest biomass. Data include 24,347 USDA Forest Inventory and Analysis (FIA) plots and 135 Long-term Forest Demography plots. Climate, soil moisture, and competitive interactions are predictors. We infer and predict the four-dimensional size/species/space/time (SSST) structure of forests, where all demographic rates respond to winter temperature, growing season length, moisture deficits, local moisture status, and competition. Responses to soil moisture are highly non-linear and not strongly related to responses to climatic moisture deficits over time. In the Southeast the species that are most sensitive to drought on dry sites are not the same as those that are most sensitive on moist sites. Those that respond most to spatial moisture gradients are not the same as those that respond most to regional moisture deficits. There is little evidence of simple tradeoffs in responses. Direct responses to climate constrain the ranges of few tree species, north or south; there is little evidence that range limits are defined by fecundity or survival responses to climate. By contrast, recruitment and the interactions between competition and drought that affect growth and survival are predicted to limit ranges of many species. Taken together, results suggest a rich interaction involving demographic responses at all size classes to neighbors, landscape variation in moisture, and regional climate change.

Developing a Process for Sustained Climate Assessment in the US Southwest Region

NASA Astrophysics Data System (ADS)

Duncan, B.; Rick, U. K.; McNie, E. C.

2017-12-01

Climate information needs often vary across states, regions, and sectors. While a national assessment provides foundational guidance about the science and impacts of climate change, there is also value in an ongoing climate assessment process with a more targeted regional geographic scale and sectoral focus. Such a process could provide timely and relevant climate information that is sometimes more detailed than what can be included in a national assessment, while also providing a foundation of knowledge and relationships that can be drawn on in larger-scale assessment processes. In the Sustained Climate Assessment in the Southwest project, researchers are investigating opportunities for sustained assessment in the US Southwest National Climate Assessment (NCA) region - an area that consists of Arizona, California, Colorado, Nevada, New Mexico, and Utah. This work is focused on identifying key elements of an ongoing climate assessment process for the region in collaboration with climate service providers and users, with the goal of connecting providers and users to increase access to information and understanding of climate impacts in decision-making contexts. It is focused on four key sectors that represent a range of existing capacity in the region: water, oceans and coasts, agriculture, and transportation. Recommendations for an ongoing assessment process may vary by sector - a reflection of the capacity and opportunity associated with each. In this presentation, we will share case studies of particularly useful or successful existing assessment activities and identify common characteristics across the case studies. We will also share preliminary recommendations for a regional sustained climate assessment process that draws on the broad existing capacity for climate assessment in the region and complements national-scale assessment processes.

Linkages between terrestrial ecosystems and the atmosphere

NASA Technical Reports Server (NTRS)

Bretherton, Francis; Dickinson, Robert E.; Fung, Inez; Moore, Berrien, III; Prather, Michael; Running, Steven W.; Tiessen, Holm

1992-01-01

The primary research issue in understanding the role of terrestrial ecosystems in global change is analyzing the coupling between processes with vastly differing rates of change, from photosynthesis to community change. Representing this coupling in models is the central challenge to modeling the terrestrial biosphere as part of the earth system. Terrestrial ecosystems participate in climate and in the biogeochemical cycles on several temporal scales. Some of the carbon fixed by photosynthesis is incorporated into plant tissue and is delayed from returning to the atmosphere until it is oxidized by decomposition or fire. This slower (i.e., days to months) carbon loop through the terrestrial component of the carbon cycle, which is matched by cycles of nutrients required by plants and decomposers, affects the increasing trend in atmospheric CO2 concentration and imposes a seasonal cycle on that trend. Moreover, this cycle includes key controls over biogenic trace gas production. The structure of terrestrial ecosystems, which responds on even longer time scales (annual to century), is the integrated response to the biogeochemical and environmental constraints that develop over the intermediate time scale. The loop is closed back to the climate system since it is the structure of ecosystems, including species composition, that sets the terrestrial boundary condition in the climate system through modification of surface roughness, albedo, and, to a great extent, latent heat exchange. These separate temporal scales contain explicit feedback loops which may modify ecosystem dynamics and linkages between ecosystems and the atmosphere. The long-term change in climate, resulting from increased atmospheric concentrations of greenhouse gases (e.g., CO2, CH4, and nitrous oxide (N2O)) will further modify the global environment and potentially induce further ecosystem change. Modeling these interactions requires coupling successional models to biogeochemical models to physiological models that describe the exchange of water, energy, and biogenic trace gases between the vegetation and the atmosphere at fine time scales. There does not appear to be any obvious way to allow direct reciprocal coupling of atmospheric general circulation models (GCM's), which inherently run with fine time steps, to ecosystem or successional models, which have coarse temporal resolution, without the interposition of physiological canopy models. This is equally true for biogeochemical models of the exchange of carbon dioxide and trace gases. This coupling across time scales is nontrivial and sets the focus for the modeling strategy.

The Kain-Fritsch Scheme: Science Updates & Revisiting Gray-Scale Issues from the NWP & Regional Climatae Perspectives

EPA Science Inventory

It’s just a matter of time before we see global climate models increasing their spatial resolution to that now typical of regional models. This encroachment brings in an urgent need for making regional NWP and climate models applicable at certain finer resolutions. One of the hin...

Diversification of land plants: insights from a family-level phylogenetic analysis.

PubMed

Fiz-Palacios, Omar; Schneider, Harald; Heinrichs, Jochen; Savolainen, Vincent

2011-11-21

Some of the evolutionary history of land plants has been documented based on the fossil record and a few broad-scale phylogenetic analyses, especially focusing on angiosperms and ferns. Here, we reconstructed phylogenetic relationships among all 706 families of land plants using molecular data. We dated the phylogeny using multiple fossils and a molecular clock technique. Applying various tests of diversification that take into account topology, branch length, numbers of extant species as well as extinction, we evaluated diversification rates through time. We also compared these diversification profiles against the distribution of the climate modes of the Phanerozoic. We found evidence for the radiations of ferns and mosses in the shadow of angiosperms coinciding with the rather warm Cretaceous global climate. In contrast, gymnosperms and liverworts show a signature of declining diversification rates during geological time periods of cool global climate. This broad-scale phylogenetic analysis helps to reveal the successive waves of diversification that made up the diversity of land plants we see today. Both warm temperatures and wet climate may have been necessary for the rise of the diversity under a successive lineage replacement scenario.

Cross-biome transplants of plant litter show decomposition models extend to a broader climatic range but lose predictability at the decadal time scale

Treesearch

William S. Currie; Mark E. Harmon; Ingrid C. Burke; Stephen C. Hart; William J. Parton; Whendee L. Silver

2009-01-01

We analyzed results from 10-year long field incubations of foliar and fine root litter from the Long-term lntersite Decomposition Experiment Team (LIDET) study. We tested whether a variety of climate and litter quality variables could be used to develop regression models of decomposition parameters across wide ranges in litter quality and climate and whether these...

Climatic drivers of vegetation based on wavelet analysis

NASA Astrophysics Data System (ADS)

Claessen, Jeroen; Martens, Brecht; Verhoest, Niko E. C.; Molini, Annalisa; Miralles, Diego

2017-04-01

Vegetation dynamics are driven by climate, and at the same time they play a key role in forcing the different bio-geochemical cycles. As climate change leads to an increase in frequency and intensity of hydro-meteorological extremes, vegetation is expected to respond to these changes, and subsequently feed back on their occurrence. This response can be analysed using time series of different vegetation diagnostics observed from space, in the optical (e.g. Normalised Difference Vegetation Index (NDVI), Solar Induced Fluorescence (SIF)) and microwave (Vegetation Optical Depth (VOD)) domains. In this contribution, we compare the climatic drivers of different vegetation diagnostics, based on a monthly global data-cube of 24 years at a 0.25° resolution. To do so, we calculate the wavelet coherence between each vegetation-related observation and observations of air temperature, precipitation and incoming radiation. The use of wavelet coherence allows unveiling the scale-by-scale response and sensitivity of the diverse vegetation indices to their climatic drivers. Our preliminary results show that the wavelet-based statistics prove to be a suitable tool for extracting information from different vegetation indices. Going beyond traditional methods based on linear correlations, the application of wavelet coherence provides information about: (a) the specific periods at which the correspondence between climate and vegetation dynamics is larger, (b) the frequencies at which this correspondence occurs (e.g. monthly or seasonal scales), and (c) the time lag in the response of vegetation to their climate drivers, and vice versa. As expected, areas of high rainfall volumes are characterised by a strong control of radiation and temperature over vegetation. Furthermore, precipitation is the most important driver of vegetation variability over short terms in most regions of the world - which can be explained by the rapid response of leaf development towards available water content - while at seasonal scales the vegetative response is dominated by solar radiation in most regions. At the higher latitudes, the trends in all vegetation diagnostics agree with the hypothesis of a greening pattern explained by the increase in temperature. At the same time, substantial differences can be observed between the responses of the different vegetation indices as well. As an example, the VOD - thought to be a close proxy for vegetation water content - shows a larger sensitivity to precipitation than traditional optical indices like the NDVI. Our findings help to further understand the physical attributes of vegetation that each remotely-sensed vegetation index is responding to in order to optimize their use in global bio-geoscience research.

High-resolution downscaling for hydrological management

NASA Astrophysics Data System (ADS)

Ulbrich, Uwe; Rust, Henning; Meredith, Edmund; Kpogo-Nuwoklo, Komlan; Vagenas, Christos

2017-04-01

Hydrological modellers and water managers require high-resolution climate data to model regional hydrologies and how these may respond to future changes in the large-scale climate. The ability to successfully model such changes and, by extension, critical infrastructure planning is often impeded by a lack of suitable climate data. This typically takes the form of too-coarse data from climate models, which are not sufficiently detailed in either space or time to be able to support water management decisions and hydrological research. BINGO (Bringing INnovation in onGOing water management; ) aims to bridge the gap between the needs of hydrological modellers and planners, and the currently available range of climate data, with the overarching aim of providing adaptation strategies for climate change-related challenges. Producing the kilometre- and sub-daily-scale climate data needed by hydrologists through continuous simulations is generally computationally infeasible. To circumvent this hurdle, we adopt a two-pronged approach involving (1) selective dynamical downscaling and (2) conditional stochastic weather generators, with the former presented here. We take an event-based approach to downscaling in order to achieve the kilometre-scale input needed by hydrological modellers. Computational expenses are minimized by identifying extremal weather patterns for each BINGO research site in lower-resolution simulations and then only downscaling to the kilometre-scale (convection permitting) those events during which such patterns occur. Here we (1) outline the methodology behind the selection of the events, and (2) compare the modelled precipitation distribution and variability (preconditioned on the extremal weather patterns) with that found in observations.

A Decade-Long European-Scale Convection-Resolving Climate Simulation on GPUs

NASA Astrophysics Data System (ADS)

Leutwyler, D.; Fuhrer, O.; Ban, N.; Lapillonne, X.; Lüthi, D.; Schar, C.

2016-12-01

Convection-resolving models have proven to be very useful tools in numerical weather prediction and in climate research. However, due to their extremely demanding computational requirements, they have so far been limited to short simulations and/or small computational domains. Innovations in the supercomputing domain have led to new supercomputer designs that involve conventional multi-core CPUs and accelerators such as graphics processing units (GPUs). One of the first atmospheric models that has been fully ported to GPUs is the Consortium for Small-Scale Modeling weather and climate model COSMO. This new version allows us to expand the size of the simulation domain to areas spanning continents and the time period up to one decade. We present results from a decade-long, convection-resolving climate simulation over Europe using the GPU-enabled COSMO version on a computational domain with 1536x1536x60 gridpoints. The simulation is driven by the ERA-interim reanalysis. The results illustrate how the approach allows for the representation of interactions between synoptic-scale and meso-scale atmospheric circulations at scales ranging from 1000 to 10 km. We discuss some of the advantages and prospects from using GPUs, and focus on the performance of the convection-resolving modeling approach on the European scale. Specifically we investigate the organization of convective clouds and on validate hourly rainfall distributions with various high-resolution data sets.

On the climate impacts from the volcanic and solar forcings

NASA Astrophysics Data System (ADS)

Varotsos, Costas A.; Lovejoy, Shaun

2016-04-01

The observed and the modelled estimations show that the main forcings on the atmosphere are of volcanic and solar origins, which act however in an opposite way. The former can be very strong and decrease at short time scales, whereas, the latter increase with time scale. On the contrary, the observed fluctuations in temperatures increase at long scales (e.g. centennial and millennial), and the solar forcings do increase with scale. The common practice is to reduce forcings to radiative equivalents assuming that their combination is linear. In order to clarify the validity of the linearity assumption and determine its range of validity, we systematically compare the statistical properties of solar only, volcanic only and combined solar and volcanic forcings over the range of time scales from one to 1000 years. Additionally, we attempt to investigate plausible reasons for the discrepancies observed between the measured and modeled anomalies of tropospheric temperatures in the tropics. For this purpose, we analyse tropospheric temperature anomalies for both the measured and modeled time series. The results obtained show that the measured temperature fluctuations reveal white noise behavior, while the modeled ones exhibit long-range power law correlations. We suggest that the persistent signal, should be removed from the modeled values in order to achieve better agreement with observations. Keywords: Scaling, Nonlinear variability, Climate system, Solar radiation

Holocene forest dynamics in central and western Mediterranean: periodicity, spatio-temporal patterns and climate influence.

PubMed

Di Rita, Federico; Fletcher, William J; Aranbarri, Josu; Margaritelli, Giulia; Lirer, Fabrizio; Magri, Donatella

2018-06-12

It is well-known that the Holocene exhibits a millennial-scale climate variability. However, its periodicity, spatio-temporal patterns and underlying processes are not fully deciphered yet. Here we focus on the central and western Mediterranean. We show that recurrent forest declines from the Gulf of Gaeta (central Tyrrhenian Sea) reveal a 1860-yr periodicity, consistent with a ca. 1800-yr climate fluctuation induced by large-scale changes in climate modes, linked to solar activity and/or AMOC intensity. We show that recurrent forest declines and dry events are also recorded in several pollen and palaeohydrological proxy-records in the south-central Mediterranean. We found coeval events also in several palaeohydrological records from the south-western Mediterranean, which however show generally wet climate conditions, indicating a spatio-temporal hydrological pattern opposite to the south-central Mediterranean and suggesting that different expressions of climate modes occurred in the two regions at the same time. We propose that these opposite hydroclimate regimes point to a complex interplay of the prevailing or predominant phases of NAO-like circulation, East Atlantic pattern, and extension and location of the North African anticyclone. At a larger geographical scale, displacements of the ITCZ, modulated by solar activity and/or AMOC intensity, may have also indirectly influenced the observed pattern.

Late Pleistocene climate drivers of early human migration.

PubMed

Timmermann, Axel; Friedrich, Tobias

2016-10-06

On the basis of fossil and archaeological data it has been hypothesized that the exodus of Homo sapiens out of Africa and into Eurasia between ~50-120 thousand years ago occurred in several orbitally paced migration episodes. Crossing vegetated pluvial corridors from northeastern Africa into the Arabian Peninsula and the Levant and expanding further into Eurasia, Australia and the Americas, early H. sapiens experienced massive time-varying climate and sea level conditions on a variety of timescales. Hitherto it has remained difficult to quantify the effect of glacial- and millennial-scale climate variability on early human dispersal and evolution. Here we present results from a numerical human dispersal model, which is forced by spatiotemporal estimates of climate and sea level changes over the past 125 thousand years. The model simulates the overall dispersal of H. sapiens in close agreement with archaeological and fossil data and features prominent glacial migration waves across the Arabian Peninsula and the Levant region around 106-94, 89-73, 59-47 and 45-29 thousand years ago. The findings document that orbital-scale global climate swings played a key role in shaping Late Pleistocene global population distributions, whereas millennial-scale abrupt climate changes, associated with Dansgaard-Oeschger events, had a more limited regional effect.

Late Pleistocene climate drivers of early human migration

NASA Astrophysics Data System (ADS)

Timmermann, Axel; Friedrich, Tobias

2016-10-01

On the basis of fossil and archaeological data it has been hypothesized that the exodus of Homo sapiens out of Africa and into Eurasia between ~50-120 thousand years ago occurred in several orbitally paced migration episodes. Crossing vegetated pluvial corridors from northeastern Africa into the Arabian Peninsula and the Levant and expanding further into Eurasia, Australia and the Americas, early H. sapiens experienced massive time-varying climate and sea level conditions on a variety of timescales. Hitherto it has remained difficult to quantify the effect of glacial- and millennial-scale climate variability on early human dispersal and evolution. Here we present results from a numerical human dispersal model, which is forced by spatiotemporal estimates of climate and sea level changes over the past 125 thousand years. The model simulates the overall dispersal of H. sapiens in close agreement with archaeological and fossil data and features prominent glacial migration waves across the Arabian Peninsula and the Levant region around 106-94, 89-73, 59-47 and 45-29 thousand years ago. The findings document that orbital-scale global climate swings played a key role in shaping Late Pleistocene global population distributions, whereas millennial-scale abrupt climate changes, associated with Dansgaard-Oeschger events, had a more limited regional effect.

Extracting climate memory using Fractional Integrated Statistical Model: A new perspective on climate prediction

PubMed Central

Yuan, Naiming; Fu, Zuntao; Liu, Shida

2014-01-01

Long term memory (LTM) in climate variability is studied by means of fractional integral techniques. By using a recently developed model, Fractional Integral Statistical Model (FISM), we in this report proposed a new method, with which one can estimate the long-lasting influences of historical climate states on the present time quantitatively, and further extract the influence as climate memory signals. To show the usability of this method, two examples, the Northern Hemisphere monthly Temperature Anomalies (NHTA) and the Pacific Decadal Oscillation index (PDO), are analyzed in this study. We find the climate memory signals indeed can be extracted and the whole variations can be further decomposed into two parts: the cumulative climate memory (CCM) and the weather-scale excitation (WSE). The stronger LTM is, the larger proportion the climate memory signals will account for in the whole variations. With the climate memory signals extracted, one can at least determine on what basis the considered time series will continue to change. Therefore, this report provides a new perspective on climate prediction. PMID:25300777

Spatial patterns and temporal dynamics of global scale climate-groundwater interactions

NASA Astrophysics Data System (ADS)

Cuthbert, M. O.; Gleeson, T. P.; Moosdorf, N.; Schneider, A. C.; Hartmann, J.; Befus, K. M.; Lehner, B.

2017-12-01

The interactions between groundwater and climate are important to resolve in both space and time as they influence mass and energy transfers at Earth's land surface. Despite the significance of these processes, little is known about the spatio-temporal distribution of such interactions globally, and many large-scale climate, hydrological and land surface models oversimplify groundwater or exclude it completely. In this study we bring together diverse global geomatic data sets to map spatial patterns in the sensitivity and degree of connectedness between the water table and the land surface, and use the output from a global groundwater model to assess the locations where the lateral import or export of groundwater is significant. We also quantify the groundwater response time, the characteristic time for groundwater systems to respond to a change in boundary conditions, and map its distribution globally to assess the likely dynamics of groundwater's interaction with climate. We find that more than half of the global land surface significantly exports or imports groundwater laterally. Nearly 40% of Earth's landmass has water tables that are strongly coupled to topography with water tables shallow enough to enable a bi-directional exchange of moisture with the climate system. However, only a small proportion (around 12%) of such regions have groundwater response times of 100 years or less and have groundwater fluxes that would significantly respond to rapid environmental changes over this timescale. We last explore fundamental relationships between aridity, groundwater response times and groundwater turnover times. Our results have wide ranging implications for understanding and modelling changes in Earth's water and energy balance and for informing robust future water management and security decisions.

Nudging and predictability in regional climate modelling: investigation in a nested quasi-geostrophic model

NASA Astrophysics Data System (ADS)

Omrani, Hiba; Drobinski, Philippe; Dubos, Thomas

2010-05-01

In this work, we consider the effect of indiscriminate and spectral nudging on the large and small scales of an idealized model simulation. The model is a two layer quasi-geostrophic model on the beta-plane driven at its boundaries by the « global » version with periodic boundary condition. This setup mimics the configuration used for regional climate modelling. The effect of large-scale nudging is studied by using the "perfect model" approach. Two sets of experiments are performed: (1) the effect of nudging is investigated with a « global » high resolution two layer quasi-geostrophic model driven by a low resolution two layer quasi-geostrophic model. (2) similar simulations are conducted with the two layer quasi-geostrophic Limited Area Model (LAM) where the size of the LAM domain comes into play in addition to the first set of simulations. The study shows that the indiscriminate nudging time that minimizes the error at both the large and small scales is reached for a nudging time close to the predictability time, for spectral nudging, the optimum nudging time should tend to zero since the best large scale dynamics is supposed to be given by the driving large-scale fields are generally given at much lower frequency than the model time step(e,g, 6-hourly analysis) with a basic interpolation between the fields, the optimum nudging time differs from zero, however remaining smaller than the predictability time.

Regional climate engineering by radiation management: Prerequisites and prospects

NASA Astrophysics Data System (ADS)

Quaas, Johannes; Quaas, Martin F.; Boucher, Olivier; Rickels, Wilfried

2016-12-01

Radiation management (RM), as an option to engineer the climate, is highly controversial and suffers from a number of ethical and regulatory concerns, usually studied in the context of the objective to mitigate the global mean temperature. In this article, we discuss the idea that RM can be differentiated and scaled in several dimensions with potential objectives being to influence a certain climate parameter in a specific region. Some short-lived climate forcers (e.g., tropospheric aerosols) exhibit strong geographical and temporal variability, potentially leading to limited-area climate responses. Marine cloud brightening and thinning or dissolution of cirrus clouds could be operated at a rather local scale. It is therefore conceivable that such schemes could be applied with the objective to influence the climate at a regional scale. From a governance perspective, it is desirable to avoid any substantial climate effects of regional RM outside the target region. This, however, could prove impossible for a sustained, long-term RM. In turn, regional RM during limited time periods could prove more feasible without effects beyond the target area. It may be attractive as it potentially provides the opportunity to target the suppression of some extreme events such as heat waves. Research is needed on the traceability of regional RM, for example, using detection and attribution methods. Incentives and implications of regional RM need to be examined, and new governance options have to be conceived.

Multi-time-scale hydroclimate dynamics of a regional watershed and links to large-scale atmospheric circulation: Application to the Seine river catchment, France

NASA Astrophysics Data System (ADS)

Massei, N.; Dieppois, B.; Hannah, D. M.; Lavers, D. A.; Fossa, M.; Laignel, B.; Debret, M.

2017-03-01

In the present context of global changes, considerable efforts have been deployed by the hydrological scientific community to improve our understanding of the impacts of climate fluctuations on water resources. Both observational and modeling studies have been extensively employed to characterize hydrological changes and trends, assess the impact of climate variability or provide future scenarios of water resources. In the aim of a better understanding of hydrological changes, it is of crucial importance to determine how and to what extent trends and long-term oscillations detectable in hydrological variables are linked to global climate oscillations. In this work, we develop an approach associating correlation between large and local scales, empirical statistical downscaling and wavelet multiresolution decomposition of monthly precipitation and streamflow over the Seine river watershed, and the North Atlantic sea level pressure (SLP) in order to gain additional insights on the atmospheric patterns associated with the regional hydrology. We hypothesized that: (i) atmospheric patterns may change according to the different temporal wavelengths defining the variability of the signals; and (ii) definition of those hydrological/circulation relationships for each temporal wavelength may improve the determination of large-scale predictors of local variations. The results showed that the links between large and local scales were not necessarily constant according to time-scale (i.e. for the different frequencies characterizing the signals), resulting in changing spatial patterns across scales. This was then taken into account by developing an empirical statistical downscaling (ESD) modeling approach, which integrated discrete wavelet multiresolution analysis for reconstructing monthly regional hydrometeorological processes (predictand: precipitation and streamflow on the Seine river catchment) based on a large-scale predictor (SLP over the Euro-Atlantic sector). This approach basically consisted in three steps: 1 - decomposing large-scale climate and hydrological signals (SLP field, precipitation or streamflow) using discrete wavelet multiresolution analysis, 2 - generating a statistical downscaling model per time-scale, 3 - summing up all scale-dependent models in order to obtain a final reconstruction of the predictand. The results obtained revealed a significant improvement of the reconstructions for both precipitation and streamflow when using the multiresolution ESD model instead of basic ESD. In particular, the multiresolution ESD model handled very well the significant changes in variance through time observed in either precipitation or streamflow. For instance, the post-1980 period, which had been characterized by particularly high amplitudes in interannual-to-interdecadal variability associated with alternating flood and extremely low-flow/drought periods (e.g., winter/spring 2001, summer 2003), could not be reconstructed without integrating wavelet multiresolution analysis into the model. In accordance with previous studies, the wavelet components detected in SLP, precipitation and streamflow on interannual to interdecadal time-scales could be interpreted in terms of influence of the Gulf-Stream oceanic front on atmospheric circulation.

Distinguishing globally-driven changes from regional- and local-scale impacts: The case for long-term and broad-scale studies of recovery from pollution.

PubMed

Hawkins, S J; Evans, A J; Mieszkowska, N; Adams, L C; Bray, S; Burrows, M T; Firth, L B; Genner, M J; Leung, K M Y; Moore, P J; Pack, K; Schuster, H; Sims, D W; Whittington, M; Southward, E C

2017-11-30

Marine ecosystems are subject to anthropogenic change at global, regional and local scales. Global drivers interact with regional- and local-scale impacts of both a chronic and acute nature. Natural fluctuations and those driven by climate change need to be understood to diagnose local- and regional-scale impacts, and to inform assessments of recovery. Three case studies are used to illustrate the need for long-term studies: (i) separation of the influence of fishing pressure from climate change on bottom fish in the English Channel; (ii) recovery of rocky shore assemblages from the Torrey Canyon oil spill in the southwest of England; (iii) interaction of climate change and chronic Tributyltin pollution affecting recovery of rocky shore populations following the Torrey Canyon oil spill. We emphasize that "baselines" or "reference states" are better viewed as envelopes that are dependent on the time window of observation. Recommendations are made for adaptive management in a rapidly changing world. Copyright © 2017. Published by Elsevier Ltd.

Coupling carbon isotopes with astrochronology and correlation techniques for Late Cretaceous chronostratigraphic refinement and paleoclimate reconstruction

NASA Astrophysics Data System (ADS)

Jones, M. M.; Sageman, B. B.; Meyers, S. R.

2016-12-01

Late Cretaceous carbon isotope ratios (δ13C) recorded in organic matter and marine carbonates preserve an archive of the global carbon cycle in a greenhouse climate state. Due to excellent connectivity among surface carbon reservoirs and the low residence time of carbon in them, excursions in the δ13C that record changes in fluxes serve as widely correlative chronostratigraphic markers. In this study, floating astronomical time scales (ATS) from an organic carbon-rich marine Turonian succession at Demerara Rise (tropical N. Atlantic) are combined with high-resolution δ13C chemostratigraphy to estimate CIE timing and duration for refinement of the geologic time scale. In addition, a Gaussian kernel smoothing technique for objective correlation of astronomically tuned δ13C records is developed. Correlation with three coeval Turonian sections (Western Interior Basin, Texas, & Europe) shows consistency in astronomical and radioisotopic time scale ages for CIEs. In particular, a mid-Turonian sea level fall is demonstrated to be synchronous within 100 ka uncertainty. Spectral analyses of δ13Corg, %TOC, %Carbonate, and C/N time series provide insights into astronomical forcings influencing paleoclimate and paleoceanographic conditions in the tropical proto-North Atlantic upwelling zone. The stable long eccentricity cycle ( 405 ka) is robustly recorded in all geochemical data, and has the highest amplitude in %TOC, %Carbonate, and C/N time series. However, δ13C from Demerara Rise is dominated by a 1 Myr cycle resembling long obliquity, suggesting a dynamic organic carbon reservoir and/or climate feedback originating in high-latitudes was prominent during the Turonian greenhouse carbon cycle. This investigation emphasizes δ13C chemostratigraphy and astrochronology are useful chronostratigraphic methods for importing high-resolution time control into disparate basins to answer questions regarding sea level records, paleoclimate, and mass extinction on a global scale, and at the same time for deciphering the response of the global carbon cycle to astronomical climate forcing.

Towards Cloud-Resolving European-Scale Climate Simulations using a fully GPU-enabled Prototype of the COSMO Regional Model

NASA Astrophysics Data System (ADS)

Leutwyler, David; Fuhrer, Oliver; Cumming, Benjamin; Lapillonne, Xavier; Gysi, Tobias; Lüthi, Daniel; Osuna, Carlos; Schär, Christoph

2014-05-01

The representation of moist convection is a major shortcoming of current global and regional climate models. State-of-the-art global models usually operate at grid spacings of 10-300 km, and therefore cannot fully resolve the relevant upscale and downscale energy cascades. Therefore parametrization of the relevant sub-grid scale processes is required. Several studies have shown that this approach entails major uncertainties for precipitation processes, which raises concerns about the model's ability to represent precipitation statistics and associated feedback processes, as well as their sensitivities to large-scale conditions. Further refining the model resolution to the kilometer scale allows representing these processes much closer to first principles and thus should yield an improved representation of the water cycle including the drivers of extreme events. Although cloud-resolving simulations are very useful tools for climate simulations and numerical weather prediction, their high horizontal resolution and consequently the small time steps needed, challenge current supercomputers to model large domains and long time scales. The recent innovations in the domain of hybrid supercomputers have led to mixed node designs with a conventional CPU and an accelerator such as a graphics processing unit (GPU). GPUs relax the necessity for cache coherency and complex memory hierarchies, but have a larger system memory-bandwidth. This is highly beneficial for low compute intensity codes such as atmospheric stencil-based models. However, to efficiently exploit these hybrid architectures, climate models need to be ported and/or redesigned. Within the framework of the Swiss High Performance High Productivity Computing initiative (HP2C) a project to port the COSMO model to hybrid architectures has recently come to and end. The product of these efforts is a version of COSMO with an improved performance on traditional x86-based clusters as well as hybrid architectures with GPUs. We present our redesign and porting approach as well as our experience and lessons learned. Furthermore, we discuss relevant performance benchmarks obtained on the new hybrid Cray XC30 system "Piz Daint" installed at the Swiss National Supercomputing Centre (CSCS), both in terms of time-to-solution as well as energy consumption. We will demonstrate a first set of short cloud-resolving climate simulations at the European-scale using the GPU-enabled COSMO prototype and elaborate our future plans on how to exploit this new model capability.

Empirical Investigation of Critical Transitions in Paleoclimate

NASA Astrophysics Data System (ADS)

Loskutov, E. M.; Mukhin, D.; Gavrilov, A.; Feigin, A.

2016-12-01

In this work we apply a new empirical method for the analysis of complex spatially distributed systems to the analysis of paleoclimate data. The method consists of two general parts: (i) revealing the optimal phase-space variables and (ii) construction the empirical prognostic model by observed time series. The method of phase space variables construction based on the data decomposition into nonlinear dynamical modes which was successfully applied to global SST field and allowed clearly separate time scales and reveal climate shift in the observed data interval [1]. The second part, the Bayesian approach to optimal evolution operator reconstruction by time series is based on representation of evolution operator in the form of nonlinear stochastic function represented by artificial neural networks [2,3]. In this work we are focused on the investigation of critical transitions - the abrupt changes in climate dynamics - in match longer time scale process. It is well known that there were number of critical transitions on different time scales in the past. In this work, we demonstrate the first results of applying our empirical methods to analysis of paleoclimate variability. In particular, we discuss the possibility of detecting, identifying and prediction such critical transitions by means of nonlinear empirical modeling using the paleoclimate record time series. The study is supported by Government of Russian Federation (agreement #14.Z50.31.0033 with the Institute of Applied Physics of RAS). 1. Mukhin, D., Gavrilov, A., Feigin, A., Loskutov, E., & Kurths, J. (2015). Principal nonlinear dynamical modes of climate variability. Scientific Reports, 5, 15510. http://doi.org/10.1038/srep155102. Ya. I. Molkov, D. N. Mukhin, E. M. Loskutov, A.M. Feigin, (2012) : Random dynamical models from time series. Phys. Rev. E, Vol. 85, n.3.3. Mukhin, D., Kondrashov, D., Loskutov, E., Gavrilov, A., Feigin, A., & Ghil, M. (2015). Predicting Critical Transitions in ENSO models. Part II: Spatially Dependent Models. Journal of Climate, 28(5), 1962-1976. http://doi.org/10.1175/JCLI-D-14-00240.1

Uncertainties in Past and Future Global Water Availability

NASA Astrophysics Data System (ADS)

Sheffield, J.; Kam, J.

2014-12-01

Understanding how water availability changes on inter-annual to decadal time scales and how it may change in the future under climate change are a key part of understanding future stresses on water and food security. Historic evaluations of water availability on regional to global scales are generally based on large-scale model simulations with their associated uncertainties, in particular for long-term changes. Uncertainties are due to model errors and missing processes, parameter uncertainty, and errors in meteorological forcing data. Recent multi-model inter-comparisons and impact studies have highlighted large differences for past reconstructions, due to different simplifying assumptions in the models or the inclusion of physical processes such as CO2 fertilization. Modeling of direct anthropogenic factors such as water and land management also carry large uncertainties in their physical representation and from lack of socio-economic data. Furthermore, there is little understanding of the impact of uncertainties in the meteorological forcings that underpin these historic simulations. Similarly, future changes in water availability are highly uncertain due to climate model diversity, natural variability and scenario uncertainty, each of which dominates at different time scales. In particular, natural climate variability is expected to dominate any externally forced signal over the next several decades. We present results from multi-land surface model simulations of the historic global availability of water in the context of natural variability (droughts) and long-term changes (drying). The simulations take into account the impact of uncertainties in the meteorological forcings and the incorporation of water management in the form of reservoirs and irrigation. The results indicate that model uncertainty is important for short-term drought events, and forcing uncertainty is particularly important for long-term changes, especially uncertainty in precipitation due to reduced gauge density in recent years. We also discuss uncertainties in future projections from these models as driven by bias-corrected and downscaled CMIP5 climate projections, in the context of the balance between climate model robustness and climate model diversity.

Synchronous centennial-scale variability in abundance of remote sardine populations in the Pacific

NASA Astrophysics Data System (ADS)

Kuwae, M.; Takashige, S.; Yamamoto, M.; Sagawa, T.; Takeoka, H.

2012-12-01

A number of studies have identified evidence for connections between Pacific climate decadal variability and variations in Pacific marine ecosystems which are typically shown in abundance of remote sardine and anchovy species off Japan, California, Peru, and Chile as well as Alaska salmon species. The variations in climate indices and abundance of sardine and anchovy species most likely have 50-70 year cycles and therefore these natural perturbations in climates and Pacific ecosystems should be considered for developing predictive models of fisheries productions and the managements. Despite the importance of natural perturbations for long-term predictions, one issue, whether synchronous centennial-variations in remote Pacific fisheries productions in response to climate variability exists in the past, has not been questioned, because there has never been long-term reconstructed time series in the western North Pacific. Here we present well preserved, fossil fish scale-based abundance record of Japanese sardine over the last 1100 years reconstructed from a seasonal anoxic basin in the western Seto Inland Sea near their spawning areas in the western North Pacific. A comparison of our record with other previous records clearly showed centennial-scale variations in abundance of sardine species off Japan, California, and Chile, characterized by centennial-scale alternations between low abundance regimes and high abundance regimes in which multidecadal fluctuations with large amplitudes occurred once or several times. High abundance regimes from 1450 to 1650 AD and after 1800 AD and a low abundance regime from 1650 to 1800 AD corresponded to low frequency patterns of PDO index reconstructed from tree-ring records in North America. This indicates that connections between Pacific climate variability and variations in Pacific marine ecosystems exist not only on multidecadal timescales but on centennial timescales. Three to four hundred-yr periodicity of the Pacific climate-ecosystem dynamics suggests possibility of a change into a century-long, low sardine abundance regime in the next 100 years.

Centennial-scale fluctuations and regional complexity characterize Pacific salmon population dynamics over the past five centuries.

PubMed

Rogers, Lauren A; Schindler, Daniel E; Lisi, Peter J; Holtgrieve, Gordon W; Leavitt, Peter R; Bunting, Lynda; Finney, Bruce P; Selbie, Daniel T; Chen, Guangjie; Gregory-Eaves, Irene; Lisac, Mark J; Walsh, Patrick B

2013-01-29

Observational data from the past century have highlighted the importance of interdecadal modes of variability in fish population dynamics, but how these patterns of variation fit into a broader temporal and spatial context remains largely unknown. We analyzed time series of stable nitrogen isotopes from the sediments of 20 sockeye salmon nursery lakes across western Alaska to characterize temporal and spatial patterns in salmon abundance over the past ∼500 y. Although some stocks varied on interdecadal time scales (30- to 80-y cycles), centennial-scale variation, undetectable in modern-day catch records and survey data, has dominated salmon population dynamics over the past 500 y. Before 1900, variation in abundance was clearly not synchronous among stocks, and the only temporal signal common to lake sediment records from this region was the onset of commercial fishing in the late 1800s. Thus, historical changes in climate did not synchronize stock dynamics over centennial time scales, emphasizing that ecosystem complexity can produce a diversity of ecological responses to regional climate forcing. Our results show that marine fish populations may alternate between naturally driven periods of high and low abundance over time scales of decades to centuries and suggest that management models that assume time-invariant productivity or carrying capacity parameters may be poor representations of the biological reality in these systems.

Assessments of Drought Impacts on Vegetation in China with the Optimal Time Scales of the Climatic Drought Index.

PubMed

Li, Zheng; Zhou, Tao; Zhao, Xiang; Huang, Kaicheng; Gao, Shan; Wu, Hao; Luo, Hui

2015-07-08

Drought is expected to increase in frequency and severity due to global warming, and its impacts on vegetation are typically extensively evaluated with climatic drought indices, such as multi-scalar Standardized Precipitation Evapotranspiration Index (SPEI). We analyzed the covariation between the SPEIs of various time scales and the anomalies of the normalized difference vegetation index (NDVI), from which the vegetation type-related optimal time scales were retrieved. The results indicated that the optimal time scales of needle-leaved forest, broadleaf forest and shrubland were between 10 and 12 months, which were considerably longer than the grassland, meadow and cultivated vegetation ones (2 to 4 months). When the optimal vegetation type-related time scales were used, the SPEI could better reflect the vegetation's responses to water conditions, with the correlation coefficients between SPEIs and NDVI anomalies increased by 5.88% to 28.4%. We investigated the spatio-temporal characteristics of drought and quantified the different responses of vegetation growth to drought during the growing season (April-October). The results revealed that the frequency of drought has increased in the 21st century with the drying trend occurring in most of China. These results are useful for ecological assessments and adapting management steps to mitigate the impact of drought on vegetation. They are helpful to employ water resources more efficiently and reduce potential damage to human health caused by water shortages.

Centennial-scale fluctuations and regional complexity characterize Pacific salmon population dynamics over the past five centuries

PubMed Central

Rogers, Lauren A.; Schindler, Daniel E.; Lisi, Peter J.; Holtgrieve, Gordon W.; Leavitt, Peter R.; Bunting, Lynda; Finney, Bruce P.; Selbie, Daniel T.; Chen, Guangjie; Gregory-Eaves, Irene; Lisac, Mark J.; Walsh, Patrick B.

2013-01-01

Observational data from the past century have highlighted the importance of interdecadal modes of variability in fish population dynamics, but how these patterns of variation fit into a broader temporal and spatial context remains largely unknown. We analyzed time series of stable nitrogen isotopes from the sediments of 20 sockeye salmon nursery lakes across western Alaska to characterize temporal and spatial patterns in salmon abundance over the past ∼500 y. Although some stocks varied on interdecadal time scales (30- to 80-y cycles), centennial-scale variation, undetectable in modern-day catch records and survey data, has dominated salmon population dynamics over the past 500 y. Before 1900, variation in abundance was clearly not synchronous among stocks, and the only temporal signal common to lake sediment records from this region was the onset of commercial fishing in the late 1800s. Thus, historical changes in climate did not synchronize stock dynamics over centennial time scales, emphasizing that ecosystem complexity can produce a diversity of ecological responses to regional climate forcing. Our results show that marine fish populations may alternate between naturally driven periods of high and low abundance over time scales of decades to centuries and suggest that management models that assume time-invariant productivity or carrying capacity parameters may be poor representations of the biological reality in these systems. PMID:23322737

High-resolution RCMs as pioneers for future GCMs

NASA Astrophysics Data System (ADS)

Schar, C.; Ban, N.; Arteaga, A.; Charpilloz, C.; Di Girolamo, S.; Fuhrer, O.; Hoefler, T.; Leutwyler, D.; Lüthi, D.; Piaget, N.; Ruedisuehli, S.; Schlemmer, L.; Schulthess, T. C.; Wernli, H.

2017-12-01

Currently large efforts are underway to refine the horizontal resolution of global and regional climate models to O(1 km), with the intent to represent convective clouds explicitly rather than using semi-empirical parameterizations. This refinement will move the governing equations closer to first principles and is expected to reduce the uncertainties of climate models. High resolution is particularly attractive in order to better represent critical cloud feedback processes (e.g. related to global climate sensitivity and extratropical summer convection) and extreme events (such as heavy precipitation events, floods, and hurricanes). The presentation will be illustrated using decade-long simulations at 2 km horizontal grid spacing, some of these covering the European continent on a computational mesh with 1536x1536x60 grid points. To accomplish such simulations, use is made of emerging heterogeneous supercomputing architectures, using a version of the COSMO limited-area weather and climate model that is able to run entirely on GPUs. Results show that kilometer-scale resolution dramatically improves the simulation of precipitation in terms of the diurnal cycle and short-term extremes. The modeling framework is used to address changes of precipitation scaling with climate change. It is argued that already today, modern supercomputers would in principle enable global atmospheric convection-resolving climate simulations, provided appropriately refactored codes were available, and provided solutions were found to cope with the rapidly growing output volume. A discussion will be provided of key challenges affecting the design of future high-resolution climate models. It is suggested that km-scale RCMs should be exploited to pioneer this terrain, at a time when GCMs are not yet available at such resolutions. Areas of interest include the development of new parameterization schemes adequate for km-scale resolution, the exploration of new validation methodologies and data sets, the assessment of regional-scale climate feedback processes, and the development of alternative output analysis methodologies.

Representation of Precipitation in a Decade-long Continental-Scale Convection-Resolving Climate Simulation

NASA Astrophysics Data System (ADS)

Leutwyler, D.; Fuhrer, O.; Ban, N.; Lapillonne, X.; Lüthi, D.; Schar, C.

2017-12-01

The representation of moist convection in climate models represents a major challenge, due to the small scales involved. Regional climate simulations using horizontal resolutions of O(1km) allow to explicitly resolve deep convection leading to an improved representation of the water cycle. However, due to their extremely demanding computational requirements, they have so far been limited to short simulations and/or small computational domains. A new version of the Consortium for Small-Scale Modeling weather and climate model (COSMO) is capable of exploiting new supercomputer architectures employing GPU accelerators, and allows convection-resolving climate simulations on computational domains spanning continents and time periods up to one decade. We present results from a decade-long, convection-resolving climate simulation on a European-scale computational domain. The simulation has a grid spacing of 2.2 km, 1536x1536x60 grid points, covers the period 1999-2008, and is driven by the ERA-Interim reanalysis. Specifically we present an evaluation of hourly rainfall using a wide range of data sets, including several rain-gauge networks and a remotely-sensed lightning data set. Substantial improvements are found in terms of the diurnal cycles of precipitation amount, wet-hour frequency and all-hour 99th percentile. However the results also reveal substantial differences between regions with and without strong orographic forcing. Furthermore we present an index for deep-convective activity based on the statistics of vertical motion. Comparison of the index with lightning data shows that the convection-resolving climate simulations are able to reproduce important features of the annual cycle of deep convection in Europe. Leutwyler D., D. Lüthi, N. Ban, O. Fuhrer, and C. Schär (2017): Evaluation of the Convection-Resolving Climate Modeling Approach on Continental Scales , J. Geophys. Res. Atmos., 122, doi:10.1002/2016JD026013.

Evaluation and projected changes of precipitation statistics in convection-permitting WRF climate simulations over Central Europe

NASA Astrophysics Data System (ADS)

Knist, Sebastian; Goergen, Klaus; Simmer, Clemens

2018-02-01

We perform simulations with the WRF regional climate model at 12 and 3 km grid resolution for the current and future climates over Central Europe and evaluate their added value with a focus on the daily cycle and frequency distribution of rainfall and the relation between extreme precipitation and air temperature. First, a 9 year period of ERA-Interim driven simulations is evaluated against observations; then global climate model runs (MPI-ESM-LR RCP4.5 scenario) are downscaled and analyzed for three 12-year periods: a control, a mid-of-century and an end-of-century projection. The higher resolution simulations reproduce both the diurnal cycle and the hourly intensity distribution of precipitation more realistically compared to the 12 km simulation. Moreover, the observed increase of the temperature-extreme precipitation scaling from the Clausius-Clapeyron (C-C) scaling rate of 7% K-1 to a super-adiabatic scaling rate for temperatures above 11 °C is reproduced only by the 3 km simulation. The drop of the scaling rates at high temperatures under moisture limited conditions differs between sub-regions. For both future scenario time spans both simulations suggest a slight decrease in mean summer precipitation and an increase in hourly heavy and extreme precipitation. This increase is stronger in the 3 km runs. Temperature-extreme precipitation scaling curves in the future climate are projected to shift along the 7% K-1 trajectory to higher peak extreme precipitation values at higher temperatures. The curves keep their typical shape of C-C scaling followed by super-adiabatic scaling and a drop-off at higher temperatures due to moisture limitation.

Interannual Variations in Global Vegetation Phenology Derived from a Long Term AVHRR and MODIS Data Record

NASA Astrophysics Data System (ADS)

Zhang, X.; Friedl, M. A.; Yu, Y.

2013-12-01

Land surface phenology metrics are widely retrieved from satellite observations at regional and global scales, and have been shown to be valuable for monitoring terrestrial ecosystem dynamics in response to extreme climate events and predicting biological responses to future climate scenarios. While the response of spring vegetation greenup to climate warming at mid-to-high latitudes is well-documented, understanding of diverse phenological responses to climate change over entire growing cycles and at broad geographic scales is incomplete. Many studies assume that the timing of individual phenological indicators in responses to climate forcing is independent of phenological events that occur at other times during the growing season. In this paper we use a different strategy. Specifically, we hypothesize that integrating sequences of key phenological indicators across growing seasons provides a more effective way to capture long-term variation in phenology in response to climate change. To explore this hypothesis we use global land surface phenology metrics derived from the Version 3 Long Term Vegetation Index Products from Multiple Satellite Data Records data set to examine interannual variations and trends in global land surface phenology from 1982-2010. Using daily enhanced vegetation index (EVI) data at a spatial resolution of 0.05 degrees, we model the phenological trajectory for each individual pixel using piecewise logistic models. The modeled trajectories were then used to detect phenological indicators including the onset of greenness increase, the onset of greenness maximum, the onset of greenness decrease, the onset of greenness minimum, and the growing season length, among others at global scale. The quality of land surface phenology detection for individual pixels was calculated based on metrics that characterize the EVI quality and model fits in annual time series at each pixel. Phenological indicators characterized as having good quality were then used to detect interannual variation and long-term trends using linear and nonlinear trend analysis techniques.

Spatially distributed potential evapotranspiration modeling and climate projections.

PubMed

Gharbia, Salem S; Smullen, Trevor; Gill, Laurence; Johnston, Paul; Pilla, Francesco

2018-08-15

Evapotranspiration integrates energy and mass transfer between the Earth's surface and atmosphere and is the most active mechanism linking the atmosphere, hydrosphsophere, lithosphere and biosphere. This study focuses on the fine resolution modeling and projection of spatially distributed potential evapotranspiration on the large catchment scale as response to climate change. Six potential evapotranspiration designed algorithms, systematically selected based on a structured criteria and data availability, have been applied and then validated to long-term mean monthly data for the Shannon River catchment with a 50m 2 cell size. The best validated algorithm was therefore applied to evaluate the possible effect of future climate change on potential evapotranspiration rates. Spatially distributed potential evapotranspiration projections have been modeled based on climate change projections from multi-GCM ensembles for three future time intervals (2020, 2050 and 2080) using a range of different Representative Concentration Pathways producing four scenarios for each time interval. Finally, seasonal results have been compared to baseline results to evaluate the impact of climate change on the potential evapotranspiration and therefor on the catchment dynamical water balance. The results present evidence that the modeled climate change scenarios would have a significant impact on the future potential evapotranspiration rates. All the simulated scenarios predicted an increase in potential evapotranspiration for each modeled future time interval, which would significantly affect the dynamical catchment water balance. This study addresses the gap in the literature of using GIS-based algorithms to model fine-scale spatially distributed potential evapotranspiration on the large catchment systems based on climatological observations and simulations in different climatological zones. Providing fine-scale potential evapotranspiration data is very crucial to assess the dynamical catchment water balance to setup management scenarios for the water abstractions. This study illustrates a transferable systematic method to design GIS-based algorithms to simulate spatially distributed potential evapotranspiration on the large catchment systems. Copyright © 2018 Elsevier B.V. All rights reserved.

Was millennial scale climate change during the Last Glacial triggered by explosive volcanism?

PubMed Central

Baldini, James U.L.; Brown, Richard J.; McElwaine, Jim N.

2015-01-01

The mechanisms responsible for millennial scale climate change within glacial time intervals are equivocal. Here we show that all eight known radiometrically-dated Tambora-sized or larger NH eruptions over the interval 30 to 80 ka BP are associated with abrupt Greenland cooling (>95% confidence). Additionally, previous research reported a strong statistical correlation between the timing of Southern Hemisphere volcanism and Dansgaard-Oeschger (DO) events (>99% confidence), but did not identify a causative mechanism. Volcanic aerosol-induced asymmetrical hemispheric cooling over the last few hundred years restructured atmospheric circulation in a similar fashion as that associated with Last Glacial millennial-scale shifts (albeit on a smaller scale). We hypothesise that following both recent and Last Glacial NH eruptions, volcanogenic sulphate injections into the stratosphere cooled the NH preferentially, inducing a hemispheric temperature asymmetry that shifted atmospheric circulation cells southward. This resulted in Greenland cooling, Antarctic warming, and a southward shifted ITCZ. However, during the Last Glacial, the initial eruption-induced climate response was prolonged by NH glacier and sea ice expansion, increased NH albedo, AMOC weakening, more NH cooling, and a consequent positive feedback. Conversely, preferential SH cooling following large SH eruptions shifted atmospheric circulation to the north, resulting in the characteristic features of DO events. PMID:26616338

Was millennial scale climate change during the Last Glacial triggered by explosive volcanism?

PubMed

Baldini, James U L; Brown, Richard J; McElwaine, Jim N

2015-11-30

The mechanisms responsible for millennial scale climate change within glacial time intervals are equivocal. Here we show that all eight known radiometrically-dated Tambora-sized or larger NH eruptions over the interval 30 to 80 ka BP are associated with abrupt Greenland cooling (>95% confidence). Additionally, previous research reported a strong statistical correlation between the timing of Southern Hemisphere volcanism and Dansgaard-Oeschger (DO) events (>99% confidence), but did not identify a causative mechanism. Volcanic aerosol-induced asymmetrical hemispheric cooling over the last few hundred years restructured atmospheric circulation in a similar fashion as that associated with Last Glacial millennial-scale shifts (albeit on a smaller scale). We hypothesise that following both recent and Last Glacial NH eruptions, volcanogenic sulphate injections into the stratosphere cooled the NH preferentially, inducing a hemispheric temperature asymmetry that shifted atmospheric circulation cells southward. This resulted in Greenland cooling, Antarctic warming, and a southward shifted ITCZ. However, during the Last Glacial, the initial eruption-induced climate response was prolonged by NH glacier and sea ice expansion, increased NH albedo, AMOC weakening, more NH cooling, and a consequent positive feedback. Conversely, preferential SH cooling following large SH eruptions shifted atmospheric circulation to the north, resulting in the characteristic features of DO events.

Large-scale disturbance legacies and the climate sensitivity of primary Picea abies forests.

PubMed

Schurman, Jonathan S; Trotsiuk, Volodymyr; Bače, Radek; Čada, Vojtěch; Fraver, Shawn; Janda, Pavel; Kulakowski, Dominik; Labusova, Jana; Mikoláš, Martin; Nagel, Thomas A; Seidl, Rupert; Synek, Michal; Svobodová, Kristýna; Chaskovskyy, Oleh; Teodosiu, Marius; Svoboda, Miroslav

2018-05-01

Determining the drivers of shifting forest disturbance rates remains a pressing global change issue. Large-scale forest dynamics are commonly assumed to be climate driven, but appropriately scaled disturbance histories are rarely available to assess how disturbance legacies alter subsequent disturbance rates and the climate sensitivity of disturbance. We compiled multiple tree ring-based disturbance histories from primary Picea abies forest fragments distributed throughout five European landscapes spanning the Bohemian Forest and the Carpathian Mountains. The regional chronology includes 11,595 tree cores, with ring dates spanning the years 1750-2000, collected from 560 inventory plots in 37 stands distributed across a 1,000 km geographic gradient, amounting to the largest disturbance chronology yet constructed in Europe. Decadal disturbance rates varied significantly through time and declined after 1920, resulting in widespread increases in canopy tree age. Approximately 75% of current canopy area recruited prior to 1900. Long-term disturbance patterns were compared to an historical drought reconstruction, and further linked to spatial variation in stand structure and contemporary disturbance patterns derived from LANDSAT imagery. Historically, decadal Palmer drought severity index minima corresponded to higher rates of canopy removal. The severity of contemporary disturbances increased with each stand's estimated time since last major disturbance, increased with mean diameter, and declined with increasing within-stand structural variability. Reconstructed spatial patterns suggest that high small-scale structural variability has historically acted to reduce large-scale susceptibility and climate sensitivity of disturbance. Reduced disturbance rates since 1920, a potential legacy of high 19th century disturbance rates, have contributed to a recent region-wide increase in disturbance susceptibility. Increasingly common high-severity disturbances throughout primary Picea forests of Central Europe should be reinterpreted in light of both legacy effects (resulting in increased susceptibility) and climate change (resulting in increased exposure to extreme events). © 2018 John Wiley & Sons Ltd.

Population synchrony of a native fish across three Laurentian Great Lakes: Evaluating the effects of dispersal and climate

USGS Publications Warehouse

Bunnell, D.B.; Adams, J.V.; Gorman, O.T.; Madenjian, C.P.; Riley, S.C.; Roseman, E.F.; Schaeffer, J.S.

2010-01-01

Climate and dispersal are the two most commonly cited mechanisms to explain spatial synchrony among time series of animal populations, and climate is typically most important for fishes. Using data from 1978-2006, we quantified the spatial synchrony in recruitment and population catch-per-unit-effort (CPUE) for bloater (Coregonus hoyi) populations across lakes Superior, Michigan, and Huron. In this natural field experiment, climate was highly synchronous across lakes but the likelihood of dispersal between lakes differed. When data from all lakes were pooled, modified correlograms revealed spatial synchrony to occur up to 800 km for long-term (data not detrended) trends and up to 600 km for short-term (data detrended by the annual rate of change) trends. This large spatial synchrony more than doubles the scale previously observed in freshwater fish populations, and exceeds the scale found in most marine or estuarine populations. When analyzing the data separately for within- and between-lake pairs, spatial synchrony was always observed within lakes, up to 400 or 600 km. Conversely, between-lake synchrony did not occur among short-term trends, and for long-term trends, the scale of synchrony was highly variable. For recruit CPUE, synchrony occurred up to 600 km between both lakes Michigan and Huron (where dispersal was most likely) and lakes Michigan and Superior (where dispersal was least likely), but failed to occur between lakes Huron and Superior (where dispersal likelihood was intermediate). When considering the scale of putative bloater dispersal and genetic information from previous studies, we concluded that dispersal was likely underlying within-lake synchrony but climate was more likely underlying between-lake synchrony. The broad scale of synchrony in Great Lakes bloater populations increases their probability of extirpation, a timely message for fishery managers given current low levels of bloater abundance. ?? Springer-Verlag 2009.

Synchronization and Causality Across Time-scales: Complex Dynamics and Extremes in El Niño/Southern Oscillation

NASA Astrophysics Data System (ADS)

Jajcay, N.; Kravtsov, S.; Tsonis, A.; Palus, M.

2017-12-01

A better understanding of dynamics in complex systems, such as the Earth's climate is one of the key challenges for contemporary science and society. A large amount of experimental data requires new mathematical and computational approaches. Natural complex systems vary on many temporal and spatial scales, often exhibiting recurring patterns and quasi-oscillatory phenomena. The statistical inference of causal interactions and synchronization between dynamical phenomena evolving on different temporal scales is of vital importance for better understanding of underlying mechanisms and a key for modeling and prediction of such systems. This study introduces and applies information theory diagnostics to phase and amplitude time series of different wavelet components of the observed data that characterizes El Niño. A suite of significant interactions between processes operating on different time scales was detected, and intermittent synchronization among different time scales has been associated with the extreme El Niño events. The mechanisms of these nonlinear interactions were further studied in conceptual low-order and state-of-the-art dynamical, as well as statistical climate models. Observed and simulated interactions exhibit substantial discrepancies, whose understanding may be the key to an improved prediction. Moreover, the statistical framework which we apply here is suitable for direct usage of inferring cross-scale interactions in nonlinear time series from complex systems such as the terrestrial magnetosphere, solar-terrestrial interactions, seismic activity or even human brain dynamics.

Climate change and species interactions: ways forward.

PubMed

Angert, Amy L; LaDeau, Shannon L; Ostfeld, Richard S

2013-09-01

With ongoing and rapid climate change, ecologists are being challenged to predict how individual species will change in abundance and distribution, how biotic communities will change in structure and function, and the consequences of these climate-induced changes for ecosystem functioning. It is now well documented that indirect effects of climate change on species abundances and distributions, via climatic effects on interspecific interactions, can outweigh and even reverse the direct effects of climate. However, a clear framework for incorporating species interactions into projections of biological change remains elusive. To move forward, we suggest three priorities for the research community: (1) utilize tractable study systems as case studies to illustrate possible outcomes, test processes highlighted by theory, and feed back into modeling efforts; (2) develop a robust analytical framework that allows for better cross-scale linkages; and (3) determine over what time scales and for which systems prediction of biological responses to climate change is a useful and feasible goal. We end with a list of research questions that can guide future research to help understand, and hopefully mitigate, the negative effects of climate change on biota and the ecosystem services they provide. © 2013 New York Academy of Sciences.

Circumpolar spatio-temporal patterns and contributing climatic factors of wildfire activity in the Arctic tundra from 2001-2015

NASA Astrophysics Data System (ADS)

Masrur, Arif; Petrov, Andrey N.; DeGroote, John

2018-01-01

Recent years have seen an increased frequency of wildfire events in different parts of Arctic tundra ecosystems. Contemporary studies have largely attributed these wildfire events to the Arctic’s rapidly changing climate and increased atmospheric disturbances (i.e. thunderstorms). However, existing research has primarily examined the wildfire-climate dynamics of individual large wildfire events. No studies have investigated wildfire activity, including climatic drivers, for the entire tundra biome across multiple years, i.e. at the planetary scale. To address this limitation, this paper provides a planetary/circumpolar scale analyses of space-time patterns of tundra wildfire occurrence and climatic association in the Arctic over a 15 year period (2001-2015). In doing so, we have leveraged and analyzed NASA Terra’s MODIS active fire and MERRA climate reanalysis products at multiple temporal scales (decadal, seasonal and monthly). Our exploratory spatial data analysis found that tundra wildfire occurrence was spatially clustered and fire intensity was spatially autocorrelated across the Arctic regions. Most of the wildfire events occurred in the peak summer months (June-August). Our multi-temporal (decadal, seasonal and monthly) scale analyses provide further support to the link between climate variability and wildfire activity. Specifically, we found that warm and dry conditions in the late spring to mid-summer influenced tundra wildfire occurrence, spatio-temporal distribution, and fire intensity. Additionally, reduced average surface precipitation and soil moisture levels in the winter-spring period were associated with increased fire intensity in the following summer. These findings enrich contemporary knowledge on tundra wildfire’s spatial and seasonal patterns, and shed new light on tundra wildfire-climate relationships in the circumpolar context. Furthermore, this first pan-Arctic analysis provides a strong incentive and direction for future studies which integrate multiple datasets (i.e. climate, fuels, topography, and ignition sources) to accurately estimate carbon emission from tundra burning and its global climate feedbacks in coming decades.

Groundwater level responses to precipitation variability in Mediterranean insular aquifers

NASA Astrophysics Data System (ADS)

Lorenzo-Lacruz, Jorge; Garcia, Celso; Morán-Tejeda, Enrique

2017-09-01

Groundwater is one of the largest and most important sources of fresh water on many regions under Mediterranean climate conditions, which are exposed to large precipitation variability that includes frequent meteorological drought episodes, and present high evapotranspiration rates and water demand during the dry season. The dependence on groundwater increases in those areas with predominant permeable lithologies, contributing to aquifer recharge and the abundance of ephemeral streams. The increasing pressure of tourism on water resources in many Mediterranean coastal areas, and uncertainty related to future precipitation and water availability, make it urgent to understand the spatio-temporal response of groundwater bodies to precipitation variability, if sustainable use of the resource is to be achieved. We present an assessment of the response of aquifers to precipitation variability based on correlations between the Standardized Precipitation Index (SPI) at various time scales and the Standardized Groundwater Index (SGI) across a Mediterranean island. We detected three main responses of aquifers to accumulated precipitation anomalies: (i) at short time scales of the SPI (<6 months); (ii) at medium time scales (6-24 months); and at long time scales (>24 months). The differing responses were mainly explained by differences in lithology and the percentage of highly permeable rock strata in the aquifer recharge areas. We also identified differences in the months and seasons when aquifer storages are more dependent on precipitation; these were related to climate seasonality and the degree of aquifer exploitation or underground water extraction. The recharge of some aquifers, especially in mountainous areas, is related to precipitation variability within a limited spatial extent, whereas for aquifers located in the plains, precipitation variability influence much larger areas; the topography and geological structure of the island explain these differences. Results indicate large spatial variability in the response of aquifers to precipitation in a very small area, highlighting the importance of having high spatial resolution hydro-climatic databases available to enable full understanding of the effects of climate variability on scarce water resources.

Realizing the electric-vehicle revolution

NASA Astrophysics Data System (ADS)

Tran, Martino; Banister, David; Bishop, Justin D. K.; McCulloch, Malcolm D.

2012-05-01

Full battery electric vehicles (BEVs) have become an important policy option to mitigate climate change, but there are major uncertainties in the scale and timing of market diffusion. Although there has been substantial work showing the potential energy and climate benefits of BEVs, demand-side factors, such as consumer behaviour, are less recognized in the debate. We show the importance of assessing BEV diffusion from an integrated perspective, focusing on key interactions between technology and behaviour across different scales, including power-system demand, charging infrastructure, vehicle performance, driving patterns and individual adoption behaviour.

Climate Warming Can Increase Soil Carbon Fluxes Without Decreasing Soil Carbon Stocks in Boreal Forests

NASA Astrophysics Data System (ADS)

Ziegler, S. E.; Benner, R. H.; Billings, S. A.; Edwards, K. A.; Philben, M. J.; Zhu, X.; Laganiere, J.

2016-12-01

Ecosystem C fluxes respond positively to climate warming, however, the net impact of changing C fluxes on soil organic carbon (SOC) stocks over decadal scales remains unclear. Manipulative studies and global-scale observations have informed much of the existing knowledge of SOC responses to climate, providing insights on relatively short (e.g. days to years) and long (centuries to millennia) time scales, respectively. Natural climate gradient studies capture integrated ecosystem responses to climate on decadal time scales. Here we report the soil C reservoirs, fluxes into and out of those reservoirs, and the chemical composition of inputs and soil organic matter pools along a mesic boreal forest climate transect. The sites studied consist of similar forest composition, successional stage, and soil moisture but differ by 5.2°C mean annual temperature. Carbon fluxes through these boreal forest soils were greatest in the lowest latitude regions and indicate that enhanced C inputs can offset soil C losses with warming in these forests. Respiration rates increased by 55% and the flux of dissolved organic carbon from the organic to mineral soil horizons tripled across this climate gradient. The 2-fold increase in litterfall inputs to these soils coincided with a significant increase in the organic horizon C stock with warming, however, no significant difference in the surface mineral soil C stocks was observed. The younger mean age of the mineral soil C ( 70 versus 330 YBP) provided further evidence for the greater turnover of SOC in the warmer climate soils. In spite of these differences in mean radiocarbon age, mineral SOC exhibited chemical characteristics of highly decomposed material across all regions. In contrast with depth trends in soil OM diagenetic indices, diagenetic shifts with latitude were limited to increases in C:N and alkyl to O-alkyl ratios in the overlying organic horizons in the warmer relative to the colder regions. These data indicate that the lowest latitude forests experience accelerated C fluxes that maintain relatively young but highly decomposed material. Collectively, these observations of within-biome soil C responses to climate demonstrate that the enhanced rates of SOC loss that typically occur with warming can be balanced by enhanced rates of C inputs.

Can Regional Climate Models Improve Warm Season Forecasts in the North American Monsoon Region?

NASA Astrophysics Data System (ADS)

Dominguez, F.; Castro, C. L.

2009-12-01

The goal of this work is to improve warm season forecasts in the North American Monsoon Region. To do this, we are dynamically downscaling warm season CFS (Climate Forecast System) reforecasts from 1982-2005 for the contiguous U.S. using the Weather Research and Forecasting (WRF) regional climate model. CFS is the global coupled ocean-atmosphere model used by the Climate Prediction Center (CPC), a branch of the National Center for Environmental Prediction (NCEP), to provide official U.S. seasonal climate forecasts. Recently, NCEP has produced a comprehensive long-term retrospective ensemble CFS reforecasts for the years 1980-2005. These reforecasts show that CFS model 1) has an ability to forecast tropical Pacific SSTs and large-scale teleconnection patterns, at least as evaluated for the winter season; 2) has greater skill in forecasting winter than summer climate; and 3) demonstrates an increase in skill when a greater number of ensembles members are used. The decrease in CFS skill during the warm season is due to the fact that the physical mechanisms of rainfall at this time are more related to mesoscale processes, such as the diurnal cycle of convection, low-level moisture transport, propagation and organization of convection, and surface moisture recycling. In general, these are poorly represented in global atmospheric models. Preliminary simulations for years with extreme summer climate conditions in the western and central U.S. (specifically 1988 and 1993) show that CFS-WRF simulations can provide a more realistic representation of convective rainfall processes. Thus a RCM can potentially add significant value in climate forecasting of the warm season provided the downscaling methodology incorporates the following: 1) spectral nudging to preserve the variability in the large scale circulation while still permitting the development of smaller-scale variability in the RCM; and 2) use of realistic soil moisture initial condition, in this case provided by the North American Regional Reanalysis. With these conditions, downscaled CFS-WRF reforecast simulations can produce realistic continental-scale patterns of warm season precipitation. This includes a reasonable representation of the North American monsoon in the southwest U.S. and northwest Mexico, which is notoriously difficult to represent in a global atmospheric model. We anticipate that this research will help lead the way toward substantially improved real time operational forecasts of North American summer climate with a RCM.

Climate variability and human impact on the environment in South America during the last 2000 years: synthesis and perspectives

NASA Astrophysics Data System (ADS)

Flantua, S. G. A.; Hooghiemstra, H.; Vuille, M.; Behling, H.; Carson, J. F.; Gosling, W. D.; Hoyos, I.; Ledru, M. P.; Montoya, E.; Mayle, F.; Maldonado, A.; Rull, V.; Tonello, M. S.; Whitney, B. S.; González-Arango, C.

2015-07-01

An improved understanding of present-day climate variability and change relies on high-quality data sets from the past two millennia. Global efforts to reconstruct regional climate modes are in the process of validating and integrating paleo-proxies. For South America, however, the full potential of vegetation records for evaluating and improving climate models has hitherto not been sufficiently acknowledged due to its unknown spatial and temporal coverage. This paper therefore serves as a guide to high-quality pollen records that capture environmental variability during the last two millennia. We identify the pollen records with the required temporal characteristics for PAGES-2 ka climate modelling and we discuss their sensitivity to the spatial signature of climate modes throughout the continent. Diverse patterns of vegetation response to climate change are observed, with more similar patterns of change in the lowlands and varying intensity and direction of responses in the highlands. Pollen records display local scale responses to climate modes, thus it is necessary to understand how vegetation-climate interactions might diverge under variable settings. Additionally, pollen is an excellent indicator of human impact through time. Evidence for human land use in pollen records is useful for archaeological hypothesis testing and important in distinguishing natural from anthropogenically driven vegetation change. We stress the need for the palynological community to be more familiar with climate variability patterns to correctly attribute the potential causes of observed vegetation dynamics. The LOTRED-SA-2 k initiative provides the ideal framework for the integration of the various paleoclimatic sub-disciplines and paleo-science, thereby jumpstarting and fostering multi-disciplinary research into environmental change on centennial and millennial time scales.

High Resolution Global Climate Modeling with GEOS-5: Intense Precipitation, Convection and Tropical Cyclones on Seasonal Time-Scales.

NASA Technical Reports Server (NTRS)

Putnam, WilliamM.

2011-01-01

In 2008 the World Modeling Summit for Climate Prediction concluded that "climate modeling will need-and is ready-to move to fundamentally new high-resolution approaches to capitalize on the seamlessness of the weather-climate continuum." Following from this, experimentation with very high-resolution global climate modeling has gained enhanced priority within many modeling groups and agencies. The NASA Goddard Earth Observing System model (GEOS-5) has been enhanced to provide a capability for the execution at the finest horizontal resolutions POS,SIOle with a global climate model today. Using this high-resolution, non-hydrostatic version of GEOS-5, we have developed a unique capability to explore the intersection of weather and climate within a seamless prediction system. Week-long weather experiments, to mUltiyear climate simulations at global resolutions ranging from 3.5- to 14-km have demonstrated the predictability of extreme events including severe storms along frontal systems, extra-tropical storms, and tropical cyclones. The primary benefits of high resolution global models will likely be in the tropics, with better predictions of the genesis stages of tropical cyclones and of the internal structure of their mature stages. Using satellite data we assess the accuracy of GEOS-5 in representing extreme weather phenomena, and their interaction within the global climate on seasonal time-scales. The impacts of convective parameterization and the frequency of coupling between the moist physics and dynamics are explored in terms of precipitation intensity and the representation of deep convection. We will also describe the seasonal variability of global tropical cyclone activity within a global climate model capable of representing the most intense category 5 hurricanes.

Global vegetation productivity response to climatic oscillations during the satellite era.

PubMed

Gonsamo, Alemu; Chen, Jing M; Lombardozzi, Danica

2016-10-01

Climate control on global vegetation productivity patterns has intensified in response to recent global warming. Yet, the contributions of the leading internal climatic variations to global vegetation productivity are poorly understood. Here, we use 30 years of global satellite observations to study climatic variations controls on continental and global vegetation productivity patterns. El Niño-Southern Oscillation (ENSO) phases (La Niña, neutral, and El Niño years) appear to be a weaker control on global-scale vegetation productivity than previously thought, although continental-scale responses are substantial. There is also clear evidence that other non-ENSO climatic variations have a strong control on spatial patterns of vegetation productivity mainly through their influence on temperature. Among the eight leading internal climatic variations, the East Atlantic/West Russia Pattern extensively controls the ensuing year vegetation productivity of the most productive tropical and temperate forest ecosystems of the Earth's vegetated surface through directionally consistent influence on vegetation greenness. The Community Climate System Model (CCSM4) simulations do not capture the observed patterns of vegetation productivity responses to internal climatic variations. Our analyses show the ubiquitous control of climatic variations on vegetation productivity and can further guide CCSM and other Earth system models developments to represent vegetation response patterns to unforced variability. Several winter time internal climatic variation indices show strong potentials on predicting growing season vegetation productivity two to six seasons ahead which enables national governments and farmers forecast crop yield to ensure supplies of affordable food, famine early warning, and plan management options to minimize yield losses ahead of time. © 2016 John Wiley & Sons Ltd.

Climatic and socio-economic fire drivers in the Mediterranean basin at a century scale: Analysis and modelling based on historical fire statistics and dynamic global vegetation models (DGVMs)

NASA Astrophysics Data System (ADS)

Mouillot, F.; Koutsias, N.; Conedera, M.; Pezzatti, B.; Madoui, A.; Belhadj Kheder, C.

2017-12-01

Wildfire is the main disturbance affecting Mediterranean ecosystems, with implications on biogeochemical cycles, biosphere/atmosphere interactions, air quality, biodiversity, and socio-ecosystems sustainability. The fire/climate relationship is time-scale dependent and may additionally vary according to concurrent changes climatic, environmental (e.g. land use), and fire management processes (e.g. fire prevention and control strategies). To date, however, most studies focus on a decadal scale only, being fire statistics ore remote sensing data usually available for a few decades only. Long-term fire data may allow for a better caption of the slow-varying human and climate constrains and for testing the consistency of the fire/climate relationship on the mid-time to better apprehend global change effects on fire risks. Dynamic Global Vegetation Models (DGVMs) associated with process-based fire models have been recently developed to capture both the direct role of climate on fire hazard and the indirect role of changes in vegetation and human population, to simulate biosphere/atmosphere interactions including fire emissions. Their ability to accurately reproduce observed fire patterns is still under investigation regarding seasonality, extreme events or temporal trend to identify potential misrepresentations of processes. We used a unique long-term fire reconstruction (from 1880 to 2016) of yearly burned area along a North/South and East/West environmental gradient across the Mediterranean Basin (southern Switzerland, Greece, Algeria, Tunisia) to capture the climatic and socio economic drivers of extreme fire years by linking yearly burned area with selected climate indices derived from historical climate databases and socio-economic variables. We additionally compared the actual historical reconstructed fire history with the yearly burned area simulated by a panel of DGVMS (FIREMIP initiative) driven by daily CRU climate data at 0.5° resolution across the Mediterranean basin. We will present and discuss the key processes driving interannual fire hazard along the 20th century, and analysed how DGVMs capture this interannual variability.

Bayesian Non-Stationary Flood Frequency Estimation at Ungauged Basins Using Climate Information and a Scaling Model

NASA Astrophysics Data System (ADS)

Lima, C. H.; Lall, U.

2010-12-01

Flood frequency statistical analysis most often relies on stationary assumptions, where distribution moments (e.g. mean, standard deviation) and associated flood quantiles do not change over time. In this sense, one expects that flood magnitudes and their frequency of occurrence will remain constant as observed in the historical information. However, evidence of inter-annual and decadal climate variability and anthropogenic change as well as an apparent increase in the number and magnitude of flood events across the globe have made the stationary assumption questionable. Here, we show how to estimate flood quantiles (e.g. 100-year flood) at ungauged basins without needing to consider stationarity. A statistical model based on the well known flow-area scaling law is proposed to estimate flood flows at ungauged basins. The slope and intercept scaling law coefficients are assumed time varying and a hierarchical Bayesian model is used to include climate information and reduce parameter uncertainties. Cross-validated results from 34 streamflow gauges located in a nested Basin in Brazil show that the proposed model is able to estimate flood quantiles at ungauged basins with remarkable skills compared with data based estimates using the full record. The model as developed in this work is also able to simulate sequences of flood flows considering global climate changes provided an appropriate climate index developed from the General Circulation Model is used as a predictor. The time varying flood frequency estimates can be used for pricing insurance models, and in a forecast mode for preparations for flooding, and finally, for timing infrastructure investments and location. Non-stationary 95% interval estimation for the 100-year Flood (shaded gray region) and 95% interval for the 100-year flood estimated from data (horizontal dashed and solid lines). The average distribution of the 100-year flood is shown in green in the right side.

Inferring changes in water cycle dynamics of intensively managed landscapes via the theory of time-variant travel time distributions

NASA Astrophysics Data System (ADS)

Danesh-Yazdi, Mohammad; Foufoula-Georgiou, Efi; Karwan, Diana L.; Botter, Gianluca

2016-10-01

Climatic trends and anthropogenic changes in land cover and land use are impacting the hydrology and water quality of streams at the field, watershed, and regional scales in complex ways. In poorly drained agricultural landscapes, subsurface drainage systems have been successful in increasing crop productivity by removing excess soil moisture. However, their hydroecological consequences are still debated in view of the observed increased concentrations of nitrate, phosphorus, and pesticides in many streams, as well as altered runoff volumes and timing. In this study, we employ the recently developed theory of time-variant travel time distributions within the StorAge Selection function framework to quantify changes in water cycle dynamics resulting from the combined climate and land use changes. Our results from analysis of a subbasin in the Minnesota River Basin indicate a significant decrease in the mean travel time of water in the shallow subsurface layer during the growing season under current conditions compared to the pre-1970s conditions. We also find highly damped year-to-year fluctuations in the mean travel time, which we attribute to the "homogenization" of the hydrologic response due to artificial drainage. The dependence of the mean travel time on the spatial heterogeneity of some soil characteristics as well as on the basin scale is further explored via numerical experiments. Simulations indicate that the mean travel time is independent of scale for spatial scales larger than approximately 200 km2, suggesting that hydrologic data from larger basins may be used to infer the average of smaller-scale-driven changes in water cycle dynamics.

The weather and climate: emergent laws and multifractal cascades

NASA Astrophysics Data System (ADS)

Lovejoy, Shaun; Schertzer, Daniel

2013-04-01

Science in general and physics and geophysics in particular are hierarchies of interlocking theories and models with low level, fundamental laws such as quantum mechanics and statistical mechanics providing the underpinnings for the emergence of the qualitatively new, higher level laws of thermodynamics and continuum mechanics that provide the current bases for modelling the weather and climate. Yest it was the belief of generations of turbulence pioneers (notably Richardson, Kolmogorov, Obhukhov, Corrsin, Bolgiano) that at sufficiently high levels of nonlinearity (quantified by the Reynold's number, of the order 10**12 in the atmosphere) that new even higher level laws would emerge describing "fully developed turbulence". However for atmospheric applications, the pioneers' eponymous laws suffered from two basic restrictions - isotropy and homogeneity - that prevented them from being valid over wide ranges of scale. Over the last thirty years both of these restrictions have been overcome - the former with the generalization from isotropic to strongly anisotropic notions of scale (to account notably for stratification), and from homogeneity to strong heterogeneity (intermittency) via multifractal cascades. In this presentation we give an overview of recent developments and analyses covering huge ranges of space-time scales (including weather, macroweather and climate time scales). We show how the combination of strong anisotropy and strong intermittency commonly leads to the "phenomenological fallacy" in which morphology is confounded with mechanism. With the help of stochastic models, we show how processes with vastly different large and small scale morphologies can arise from a unique multifractal dynamical mechanisms [Lovejoy and Schertzer, 2013]. References: Lovejoy, S., and D. Schertzer (2013), The Weather and Climate: Emergent Laws and Multifractal Cascades, 480 pp., Cambridge University Press, Cambridge.

Efficacy of Radiative Transfer Model Across Space, Time and Hydro-climates

NASA Astrophysics Data System (ADS)

Mohanty, B.; Neelam, M.

2017-12-01

The efficiency of radiative transfer model for better soil moisture retrievals is not yet clearly understood over natural systems with great variability and heterogeneity with respect to soil, land cover, topography, precipitation etc. However, this knowledge is important to direct and strategize future research direction and field campaigns. In this work, we present global sensitivity analysis (GSA) technique to study the influence of heterogeneity and uncertainties on radiative transfer model (RTM) and to quantify climate-soil-vegetation interactions. A framework is proposed to understand soil moisture mechanisms underlying these interactions, and influence of these interactions on soil moisture retrieval accuracy. Soil moisture dynamics is observed to play a key role in variability of these interactions, i.e., it enhances both mean and variance of soil-vegetation coupling. The analysis is conducted for different support scales (Point Scale, 800 m, 1.6 km, 3.2 km, 6.4 km, 12.8 km, and 36 km), seasonality (time), hydro-climates, aggregation (scaling) methods and across Level I and Level II ecoregions of contiguous USA (CONUS). For undisturbed natural environments such as SGP'97 (Oklahoma, USA) and SMEX04 (Arizona, USA), the sensitivity of TB to land surface variables remain nearly uniform and are not influenced by extent, support scales or averaging method. On the contrary, for anthropogenically-manipulated environments such as SMEX02 (Iowa, USA) and SMAPVEX12 (Winnipeg, Canada), the sensitivity to variables are highly influenced by the distribution of land surface heterogeneity and upscaling methods. The climate-soil-vegetation interactions analyzed across all ecoregions are presented through a probability distribution function (PDF). The intensity of these interactions are categorized accordingly to yield "hotspots", where the RTM model fails to retrieve soil moisture. A ecoregion specific scaling function is proposed for these hotspots to rectify RTM for retrieving soil moisture.

Population-level consequences of herbivory, changing climate, and source-sink dynamics on a long-lived invasive shrub.

PubMed

van Klinken, R D; Pichancourt, J B

2015-12-01

Long-lived plant species are highly valued environmentally, economically, and socially, but can also cause substantial harm as invaders. Realistic demographic predictions can guide management decisions, and are particularly valuable for long-lived species where population response times can be long. Long-lived species are also challenging, given population dynamics can be affected by factors as diverse as herbivory, climate, and dispersal. We developed a matrix model to evaluate the effects of herbivory by a leaf-feeding biological control agent released in Australia against a long-lived invasive shrub (mesquite, Leguminoseae: Prosopis spp.). The stage-structured, density-dependent model used an annual time step and 10 climatically diverse years of field data. Mesquite population demography is sensitive to source-sink dynamics as most seeds are consumed and redistributed spatially by livestock. In addition, individual mesquite plants, because they are long lived, experience natural climate variation that cycles over decadal scales, as well as anthropogenic climate change. The model therefore explicitly considered the effects of both net dispersal and climate variation. Herbivory strongly regulated mesquite populations through reduced growth and fertility, but additional mortality of older plants will be required to reach management goals within a reasonable time frame. Growth and survival of seeds and seedlings were correlated with daily soil moisture. As a result, population dynamics were sensitive to rainfall scenario, but population response times were typically slow (20-800 years to reach equilibrium or extinction) due to adult longevity. Equilibrium population densities were expected to remain 5% higher, and be more dynamic, if historical multi-decadal climate patterns persist, the effect being dampened by herbivory suppressing seed production irrespective of preceding rainfall. Dense infestations were unlikely to form under a drier climate, and required net dispersal under the current climate. Seed input wasn't required to form dense infestations under a wetter climate. Each factor we considered (ongoing herbivory, changing climate, and source-sink dynamics) has a strong bearing on how this invasive species should be managed, highlighting the need for considering both ecological context (in this case, source-sink dynamics) and the effect of climate variability at relevant temporal scales (daily, multi-decadal, and anthropogenic) when deriving management recommendations for long-lived species.

Using Four Downscaling Techniques to Characterize Uncertainty in Updating Intensity-Duration-Frequency Curves Under Climate Change

NASA Astrophysics Data System (ADS)

Cook, L. M.; Samaras, C.; McGinnis, S. A.

2017-12-01

Intensity-duration-frequency (IDF) curves are a common input to urban drainage design, and are used to represent extreme rainfall in a region. As rainfall patterns shift into a non-stationary regime as a result of climate change, these curves will need to be updated with future projections of extreme precipitation. Many regions have begun to update these curves to reflect the trends from downscaled climate models; however, few studies have compared the methods for doing so, as well as the uncertainty that results from the selection of the native grid scale and temporal resolution of the climate model. This study examines the variability in updated IDF curves for Pittsburgh using four different methods for adjusting gridded regional climate model (RCM) outputs into station scale precipitation extremes: (1) a simple change factor applied to observed return levels, (2) a naïve adjustment of stationary and non-stationary Generalized Extreme Value (GEV) distribution parameters, (3) a transfer function of the GEV parameters from the annual maximum series, and (4) kernel density distribution mapping bias correction of the RCM time series. Return level estimates (rainfall intensities) and confidence intervals from these methods for the 1-hour to 48-hour duration are tested for sensitivity to the underlying spatial and temporal resolution of the climate ensemble from the NA-CORDEX project, as well as, the future time period for updating. The first goal is to determine if uncertainty is highest for: (i) the downscaling method, (ii) the climate model resolution, (iii) the climate model simulation, (iv) the GEV parameters, or (v) the future time period examined. Initial results of the 6-hour, 10-year return level adjusted with the simple change factor method using four climate model simulations of two different spatial resolutions show that uncertainty is highest in the estimation of the GEV parameters. The second goal is to determine if complex downscaling methods and high-resolution climate models are necessary for updating, or if simpler methods and lower resolution climate models will suffice. The final results can be used to inform the most appropriate method and climate model resolutions to use for updating IDF curves for urban drainage design.

An expert system-based approach to prediction of year-to-year climatic variations in the North Atlantic region

NASA Astrophysics Data System (ADS)

Rodionov, S. N.; Martin, J. H.

1999-07-01

A novel approach to climate forecasting on an interannual time scale is described. The approach is based on concepts and techniques from artificial intelligence and expert systems. The suitability of this approach to climate diagnostics and forecasting problems and its advantages compared with conventional forecasting techniques are discussed. The article highlights some practical aspects of the development of climatic expert systems (CESs) and describes an implementation of such a system for the North Atlantic (CESNA). Particular attention is paid to the content of CESNA's knowledge base and those conditions that make climatic forecasts one to several years in advance possible. A detailed evaluation of the quality of the experimental real-time forecasts made by CESNA for the winters of 1995-1996, 1996-1997 and 1997-1998 are presented.

Monitoring and Assessment of US Drylands

NASA Astrophysics Data System (ADS)

Washington-Allen, R. A.; Johnson, J. S.; van Riper, C.; Modala, N. R.; Barnes, M.; Brademan, C.; Bruton, R.; Delgado, A.; Kim, J.; March, R.; Saenz, N.; Srinivasan, S.; Reeves, M. C.

2012-12-01

Monitoring of drylands requires time scales of 15 years or more in order to replicate twice the major climatic phenomena such as El Niño that have both proximal and ultimate consequences in this ecosystems. Spatially, federal agencies such as the USFS must comply with laws that request they report the condition and trend of US drylands at the national spatial scale. The MODIS sensor on both TERRA and AQUA platforms has been collecting data operational data since 2000 that include value added products such as the enhanced vegetation index (EVI), leaf area index (LAI), Land Cover, Burn Area, and net primary productivity (NPP) that can provide multiple indicators of Dryland condition and trend for now 13-years. Consequently, this sensor meets the space and time criteria necessary to begin monitoring US drylands. Additionally, the USDA National Agricultural Statistics Service has been collecting data on the spatial distribution and numbers of livestock including sheep, goats, and cattle, since the 1890's and contemporary and reconstructed climatic records at national scales go back even further in time. Time series data on climatic and land management drivers provides a basis for assessment of the causes of possible land degradation. We provide here an assessment of US Dryland condition and trend in regards to multiple indicators including land cover change in patch dynamics, NPP, and land surface temperature. For instance we show that from 2000 to 2011 US Drylands exhibit a net carbon gain that is reflected in increased connectivity of US grasslands, but conversely a decrease in surface temperatures that are indicative of increased woody encroachment. We also show that both climate, particularly drought, and livestock grazing are drivers of these dynamics.

Cosmo-geo-anthropo-logical history and political and deep future events in climate and life evolution conveyed by a physical/virtual installation at a scale of 1 mm per 100 years across Denmark during the COP15 climate summit meeting.

NASA Astrophysics Data System (ADS)

Holm Jacobsen, Bo

2010-05-01

During the COP15 climate summit meeting a physical and virtual installation of time was performed at a linear scale of 1 mm per 100 years. The "track of time" was carefully anchored geographically so that highlights in time history coincided with landmarks of historical and cultural significance to both tourists and the local Danish population; with Big Bang at the site of early royal settlements from the Viking age (13.7 billion years ~ 137 km from now), Earth origin at Kronborg in Elsinore (4.6 bil. Years ~ 46 km), and fish go on land at The Little Mermaid (390 mil. Years ~ 3900 m). The venue of the COP15 meeting coincided with the position of severe global warming, driven by the steady solar constant increase, to be expected 600 million years into the future. Nested in this grand track of time were the Quaternary ice-ages (2.6 mil. years ~ 26 m), human origin as species (100,000 years ~ 1 m), human history (< 10,000 years ~ 100 mm), personal life and the scope of political consequences of voting action (100 years ~ 1 mm). This installation of time involved several media. Highlights in time history and future were installed as a kml-file so that the convenient user interface of Google Earth could be utilized to provide both overview of time and understanding of details and proportions events antropo-geo-cosmo-history. Each Google Earth marker-balloon gave short explanations and linked to "on location" video-narratives. A classical printed text-folder was prepared as a tour guide for those who wanted to actually walk the Phanerozoic (~5 km). Credit-card-shaped graphs of temperature, CO2 and sealevel development and scenarios were prepared to scale for the period 4000 BP to 1000 years into the future. Along the time line from "Fish on land" to the present 3900 chalk marks were placed on the street surface, one for every metre = time span of Man as a species so far. A "NowGate" marking the present was implemented physically as a door frame, where citizens could meet and discuss time and political and technological milestones in climate/biodiversity remediation and energy system developments. Meanwhile, children and young of mind tested who could take the longest jump into the future. This case study in teaching of scientific time confirmed that 1 mm per 100 years is an adequate linear scale when conveying a joint comprehension of even the longest scientific time scales together with time scales of personal/ethical/political choice. Virtual media of the installation are available for download at www.1mmper100y.dk.

Hiatus-like decades in the absence of equatorial Pacific cooling and accelerated global ocean heat uptake

NASA Astrophysics Data System (ADS)

von Känel, Lukas; Frölicher, Thomas L.; Gruber, Nicolas

2017-08-01

A surface cooling pattern in the equatorial Pacific associated with a negative phase of the Interdecadal Pacific Oscillation is the leading hypothesis to explain the smaller rate of global warming during 1998-2012, with these cooler than normal conditions thought to have accelerated the oceanic heat uptake. Here using a 30-member ensemble simulation of a global Earth system model, we show that in 10% of all simulated decades with a global cooling trend, the eastern equatorial Pacific actually warms. This implies that there is a 1 in 10 chance that decadal hiatus periods may occur without the equatorial Pacific being the dominant pacemaker. In addition, the global ocean heat uptake tends to slow down during hiatus decades implying a fundamentally different global climate feedback factor on decadal time scales than on centennial time scales and calling for caution inferring climate sensitivity from decadal-scale variability.

A global cyclostratigraphic framework constrains the timing and pacing of environmental changes over the Late Devonian (Frasnian - Famennian) mass extinction

NASA Astrophysics Data System (ADS)

De Vleeschouwer, David; Da Silva, Anne-Christine; Day, James E.; Whalen, Michael; Claeys, Philippe

2016-04-01

Milankovitch cycles (obliquity, eccentricity and precession) result in changes in the distribution of solar energy over seasons, as well as over latitudes, on time scales of ten thousands of years to millions of years. These changing patterns in insolation have induced significant variations in Earth's past climate over the last 4.5 billion years. Cyclostratigraphy and astrochronology utilize the geologic imprint of such quasi-cyclic climatic variations to measure geologic time. In recent years, major improvements of the Geologic Time Scale have been proposed through the application of cyclostratigraphy, mostly for the Mesozoic and Cenozoic (Gradstein et al., 2012). However, the field of Paleozoic cyclostratigraphy and astrochronology is still in its infancy and the application of cyclostratigraphic techniques in the Paleozoic allows for a whole new range of research questions. For example, unraveling the timing and pacing of environmental changes over the Late Devonian mass extinction on a 105-year time-scale concerns such a novel research question. Here, we present a global cyclostratigraphic framework for late Frasnian to early Famennian climatic and environmental change, through the integration of globally distributed sections. The backbone of this relative time scale consists of previously published cyclostratigraphies for western Canada and Poland (De Vleeschouwer et al., 2012; De Vleeschouwer et al., 2013). We elaborate this Euramerican base by integrating new proxy data -interpreted in terms of astronomical climate forcing- from the Iowa basin (USA, magnetic susceptibility and carbon isotope data) and Belgium (XRF and carbon isotope data). Next, we expand this well-established cyclostratigraphic framework towards the Paleo-Tethys Ocean, using magnetic susceptibility and carbon isotope records from the Fuhe section in South China (Whalen et al., 2015). The resulting global cyclostratigraphic framework implies an important refinement of the late Frasnian to early Famennian stratigraphy, but also allows for an evaluation of the role of astronomical forcing in perturbing the global carbon cycle and pacing anoxic conditions throughout the Late Devonian mass extinction event. The late Frasnian anoxic Kellwasser events, for example, each represent only a portion of a 405-kyr eccentricity cycle, with the onset of both events separated by 500-600 kyr. References: De Vleeschouwer, D., Whalen, M. T., Day, J. E., and Claeys, P., 2012, Cyclostratigraphic calibration of the Frasnian (Late Devonian) time scale (western Alberta, Canada): Geological Society of America Bulletin, v. 124, no. 5-6, p. 928-942. De Vleeschouwer, D., Rakociński, M., Racki, G., Bond, D. P., Sobień, K., and Claeys, P., 2013, The astronomical rhythm of Late-Devonian climate change (Kowala section, Holy Cross Mountains, Poland): Earth and Planetary Science Letters, v. 365, p. 25-37. Gradstein, F. M., Ogg, J. G., Schmitz, M., and Ogg, G., 2012, The Geologic Time Scale 2012 2-Volume Set, Elsevier. Whalen, M. T., Śliwiński, M. G., Payne, J. H., Day, J. E., Chen, D., and da Silva, A.-C., 2015, Chemostratigraphy and magnetic susceptibility of the Late Devonian Frasnian-Famennian transition in western Canada and southern China: implications for carbon and nutrient cycling and mass extinction: Geological Society, London, Special Publications, v. 414.

Atlas of climatic controls of wildfire in the western United States

USGS Publications Warehouse

Hostetler, S.W.; Bartlein, P.J.; Holman, J.O.

2006-01-01

Wildfire behavior depends on several factors including ecologic characteristics, near-term and antecedent climatic conditions,fuel availability and moisture level, weather, and sources of ignition (lightning or human). The variability and interplay of these factors over many spatial and temporal scales present an ongoing challenge to our ability to forecast a given wildfire season. Here we focus on one aspect of wildfire in the western US through a retrospective analysis of wildfire (starts and area burned) and climate over monthly time scales. We consider prefire conditions up to a year preceding fire outbreaks. For our analysis, we used daily and monthly wildfire records and a combination of observed and model-simulated atmospheric and surface climate data. The focus of this report is on monthly wildfire and climate for the period 1980-2000. Although a longer fire record is desirable, the 21-year record is the longest currently available and it is sufficient for the purpose of a first-order regional analysis. We present the main results in the form of a wildfire-climate atlas for 8 subregions of the West that can be used by resource managers to assess current wildfire conditions relative to high, normal, and low fire years in the historical record. Our results clearly demonstrate the link between wildfire conditions and a small set of climatic variables, and our methodology is a framework for providing near-real-time assessments of current wildfire conditions in the West.

Separation of spatial-temporal patterns ('climatic modes') by combined analysis of really measured and generated numerically vector time series

NASA Astrophysics Data System (ADS)

Feigin, A. M.; Mukhin, D.; Volodin, E. M.; Gavrilov, A.; Loskutov, E. M.

2013-12-01

The new method of decomposition of the Earth's climate system into well separated spatial-temporal patterns ('climatic modes') is discussed. The method is based on: (i) generalization of the MSSA (Multichannel Singular Spectral Analysis) [1] for expanding vector (space-distributed) time series in basis of spatial-temporal empirical orthogonal functions (STEOF), which makes allowance delayed correlations of the processes recorded in spatially separated points; (ii) expanding both real SST data, and longer by several times SST data generated numerically, in STEOF basis; (iii) use of the numerically produced STEOF basis for exclusion of 'too slow' (and thus not represented correctly) processes from real data. The application of the method allows by means of vector time series generated numerically by the INM RAS Coupled Climate Model [2] to separate from real SST anomalies data [3] two climatic modes possessing by noticeably different time scales: 3-5 and 9-11 years. Relations of separated modes to ENSO and PDO are investigated. Possible applications of spatial-temporal climatic patterns concept to prognosis of climate system evolution is discussed. 1. Ghil, M., R. M. Allen, M. D. Dettinger, K. Ide, D. Kondrashov, et al. (2002) "Advanced spectral methods for climatic time series", Rev. Geophys. 40(1), 3.1-3.41. 2. http://83.149.207.89/GCM_DATA_PLOTTING/GCM_INM_DATA_XY_en.htm 3. http://iridl.ldeo.columbia.edu/SOURCES/.KAPLAN/.EXTENDED/.v2/.ssta/

Assessing Impacts of Climate Change on Food Security Worldwide

NASA Technical Reports Server (NTRS)

Rosenzweig, Cynthia E.; Antle, John; Elliott, Joshua

2015-01-01

The combination of a warming Earth and an increasing population will likely strain the world's food systems in the coming decades. Experts involved with the Agricultural Model Intercomparison and Improvement Project (AgMIP) focus on quantifying the changes through time. AgMIP, a program begun in 2010, involves about 800 climate scientists, economists, nutritionists, information technology specialists, and crop and livestock experts. In mid-September 2015, the Aspen Global Change Institute convened an AgMIP workshop to draft plans and protocols for assessing global- and regional-scale modeling of crops, livestock, economics, and nutrition across major agricultural regions worldwide. The goal of this Coordinated Global and Regional Integrated Assessments (CGRA) project is to characterize climate effects on large- and small-scale farming systems.

Targeting, out-scaling and prioritising climate-smart interventions in agricultural systems: Lessons from applying a generic framework to the livestock sector in sub-Saharan Africa.

PubMed

Notenbaert, An; Pfeifer, Catherine; Silvestri, Silvia; Herrero, Mario

2017-02-01

As a result of population growth, urbanization and climate change, agricultural systems around the world face enormous pressure on the use of resources. There is a pressing need for wide-scale innovation leading to development that improves the livelihoods and food security of the world's population while at the same time addressing climate change adaptation and mitigation. A variety of promising climate-smart interventions have been identified. However, what remains is the prioritization of interventions for investment and broad dissemination. The suitability and adoption of interventions depends on a variety of bio-physical and socio-economic factors. Also their impacts, when adopted and out-scaled, are likely to be highly heterogeneous. This heterogeneity expresses itself not only spatially and temporally but also in terms of the stakeholders affected, some might win and some might lose. A mechanism that can facilitate a systematic, holistic assessment of the likely spread and consequential impact of potential interventions is one way of improving the selection and targeting of such options. In this paper we provide climate smart agriculture (CSA) planners and implementers at all levels with a generic framework for evaluating and prioritising potential interventions. This entails an iterative process of mapping out recommendation domains, assessing adoption potential and estimating impacts. Through examples, related to livestock production in sub-Saharan Africa, we demonstrate each of the steps and how they are interlinked. The framework is applicable in many different forms, scales and settings. It has a wide applicability beyond the examples presented and we hope to stimulate readers to integrate the concepts in the planning process for climate-smart agriculture, which invariably involves multi-stakeholder, multi-scale and multi-objective decision-making.

Reactivity continuum modeling of leaf, root, and wood decomposition across biomes

NASA Astrophysics Data System (ADS)

Koehler, Birgit; Tranvik, Lars J.

2015-07-01

Large carbon dioxide amounts are released to the atmosphere during organic matter decomposition. Yet the large-scale and long-term regulation of this critical process in global carbon cycling by litter chemistry and climate remains poorly understood. We used reactivity continuum (RC) modeling to analyze the decadal data set of the "Long-term Intersite Decomposition Experiment," in which fine litter and wood decomposition was studied in eight biome types (224 time series). In 32 and 46% of all sites the litter content of the acid-unhydrolyzable residue (AUR, formerly referred to as lignin) and the AUR/nitrogen ratio, respectively, retarded initial decomposition rates. This initial rate-retarding effect generally disappeared within the first year of decomposition, and rate-stimulating effects of nutrients and a rate-retarding effect of the carbon/nitrogen ratio became more prevalent. For needles and leaves/grasses, the influence of climate on decomposition decreased over time. For fine roots, the climatic influence was initially smaller but increased toward later-stage decomposition. The climate decomposition index was the strongest climatic predictor of decomposition. The similar variability in initial decomposition rates across litter categories as across biome types suggested that future changes in decomposition may be dominated by warming-induced changes in plant community composition. In general, the RC model parameters successfully predicted independent decomposition data for the different litter-biome combinations (196 time series). We argue that parameterization of large-scale decomposition models with RC model parameters, as opposed to the currently common discrete multiexponential models, could significantly improve their mechanistic foundation and predictive accuracy across climate zones and litter categories.

Short-term stream water temperature observations permit rapid assessment of potential climate change impacts

Treesearch

Peter Caldwell; Catalina Segura; Shelby Gull Laird; Ge Sun; Steven G. McNulty; Maria Sandercock; Johnny Boggs; James M. Vose

2015-01-01

Assessment of potential climate change impacts on stream water temperature (Ts) across large scales remains challenging for resource managers because energy exchange processes between the atmosphere and the stream environment are complex and uncertain, and few long-term datasets are available to evaluate changes over time. In this study, we...

Climate, weather, socio-economic and electricity usage data for the residential and commercial sectors in FL, U.S.

PubMed

Mukhopadhyay, Sayanti; Nateghi, Roshanak

2017-08-01

This paper presents the data that is used in the article entitled "Climate sensitivity of end-use electricity consumption in the built environment: An application to the state of Florida, United States" (Mukhopadhyay and Nateghi, 2017) [1]. The data described in this paper pertains to the state of Florida (during the period of January 1990 to November 2015). It can be classified into four categories of (i) state-level electricity consumption data; (ii) climate data; (iii) weather data; and (iv) socio-economic data. While, electricity consumption data and climate data are obtained at monthly scale directly from the source, the weather data was initially obtained at daily-level, and then aggregated to monthly level for the purpose of analysis. The time scale of socio-economic data varies from monthly-level to yearly-level. This dataset can be used to analyze the influence of climate and weather on the electricity demand as described in Mukhopadhyay and Nateghi (2017) [1].

The frequency response of a coupled ice sheet-ice shelf-ocean system to climate forcing variability

NASA Astrophysics Data System (ADS)

Goldberg, D.; Snow, K.; Jordan, J. R.; Holland, P.; Arthern, R. J.

2017-12-01

Changes at the West Antarctic ice-ocean boundary in recent decades has triggered significant increases in the regions contribution to global sea-level rise, coincident with large scale, and in some cases potentially unstable, grounding line retreat. Much of the induced change is thought to be driven by fluctuations in the oceanic heat available at the ice-ocean boundary, transported on-shelf via warm Circumpolar Deep Water (CDW). However, the processes in which ocean heat drives ice-sheet loss remains poorly understood, with observational studies routinely hindered by the extreme environment notorious to the Antarctic region. In this study we apply a novel synchronous coupled ice-ocean model, developed within the MITgcm, and are thus able to provide detailed insight into the impacts of short time scale (interannual to decadal) climate variability and feedbacks within the ice-ocean system. Feedbacks and response are assessed in an idealised ice-sheet/ocean-cavity configuration in which the far field ocean condition is adjusted to emulate periodic climate variability patterns. We reveal a non-linear response of the ice-sheet to periodic variations in thermocline depth. These non-linearities illustrate the heightened sensitivity of fast flowing ice-shelves to periodic perturbations in heat fluxes occurring at interannual and decadal time scales. The results thus highlight how small perturbations in variable climate forcing, like that of ENSO, may trigger large changes in ice-sheet response.

The Aerosol-Monsoon Climate System of Asia

NASA Technical Reports Server (NTRS)

Lau, William K. M.; Kyu-Myong, Kim

2012-01-01

In Asian monsoon countries such as China and India, human health and safety problems caused by air-pollution are worsening due to the increased loading of atmospheric pollutants stemming from rising energy demand associated with the rapid pace of industrialization and modernization. Meanwhile, uneven distribution of monsoon rain associated with flash flood or prolonged drought, has caused major loss of human lives, and damages in crop and properties with devastating societal impacts on Asian countries. Historically, air-pollution and monsoon research are treated as separate problems. However a growing number of recent studies have suggested that the two problems may be intrinsically intertwined and need to be studied jointly. Because of complexity of the dynamics of the monsoon systems, aerosol impacts on monsoons and vice versa must be studied and understood in the context of aerosol forcing in relationship to changes in fundamental driving forces of the monsoon climate system (e.g. sea surface temperature, land-sea contrast etc.) on time scales from intraseasonal variability (weeks) to climate change ( multi-decades). Indeed, because of the large contributions of aerosols to the global and regional energy balance of the atmosphere and earth surface, and possible effects of the microphysics of clouds and precipitation, a better understanding of the response to climate change in Asian monsoon regions requires that aerosols be considered as an integral component of a fully coupled aerosol-monsoon system on all time scales. In this paper, using observations and results from climate modeling, we will discuss the coherent variability of the coupled aerosol-monsoon climate system in South Asia and East Asia, including aerosol distribution and types, with respect to rainfall, moisture, winds, land-sea thermal contrast, heat sources and sink distributions in the atmosphere in seasonal, interannual to climate change time scales. We will show examples of how elevated absorbing aerosols (dust and black carbon) may interact with monsoon dynamics to produce feedback effects on the atmospheric water cycle, leading to in accelerated melting of snowpacks over the Himalayas and Tibetan Plateau, and subsequent changes in evolution of the pre-monsoon and peak monsoon rainfall, moisture and wind distributions in South Asia and East Asia.

Climate and weather influences on spatial temporal patterns of mountain pine beetle populations in Washington and Oregon.

PubMed

Preisler, Haiganoush K; Hicke, Jeffrey A; Ager, Alan A; Hayes, Jane L

2012-11-01

Widespread outbreaks of mountain pine beetle in North America have drawn the attention of scientists, forest managers, and the public. There is strong evidence that climate change has contributed to the extent and severity of recent outbreaks. Scientists are interested in quantifying relationships between bark beetle population dynamics and trends in climate. Process models that simulate climate suitability for mountain pine beetle outbreaks have advanced our understanding of beetle population dynamics; however, there are few studies that have assessed their accuracy across multiple outbreaks or at larger spatial scales. This study used the observed number of trees killed by mountain pine beetles per square kilometer in Oregon and Washington, USA, over the past three decades to quantify and assess the influence of climate and weather variables on beetle activity over longer time periods and larger scales than previously studied. Influences of temperature and precipitation in addition to process model output variables were assessed at annual and climatological time scales. The statistical analysis showed that new attacks are more likely to occur at locations with climatological mean August temperatures >15 degrees C. After controlling for beetle pressure, the variables with the largest effect on the odds of an outbreak exceeding a certain size were minimum winter temperature (positive relationship) and drought conditions in current and previous years. Precipitation levels in the year prior to the outbreak had a positive effect, possibly an indication of the influence of this driver on brood size. Two-year cumulative precipitation had a negative effect, a possible indication of the influence of drought on tree stress. Among the process model variables, cold tolerance was the strongest indicator of an outbreak increasing to epidemic size. A weather suitability index developed from the regression analysis indicated a 2.5x increase in the odds of outbreak at locations with highly suitable weather vs. locations with low suitability. The models were useful for estimating expected amounts of damage (total area with outbreaks) and for quantifying the contribution of climate to total damage. Overall, the results confirm the importance of climate and weather on the spatial expansion of bark beetle outbreaks over time.

Scientific Overview of Temporal Experiment for Storms and Tropical Systems (TEMPEST) Program

NASA Astrophysics Data System (ADS)

Chandra, C. V.; Reising, S. C.; Kummerow, C. D.; van den Heever, S. C.; Todd, G.; Padmanabhan, S.; Brown, S. T.; Lim, B.; Haddad, Z. S.; Koch, T.; Berg, G.; L'Ecuyer, T.; Munchak, S. J.; Luo, Z. J.; Boukabara, S. A.; Ruf, C. S.

2014-12-01

Over the past decade and a half, we have gained a better understanding of the role of clouds and precipitation on Earth's water cycle, energy budget and climate, from focused Earth science observational satellite missions. However, these missions provide only a snapshot at one point in time of the cloud's development. Processes that govern cloud system development occur primarily on time scales of the order of 5-30 minutes that are generally not observable from low Earth orbiting satellites. Geostationary satellites, in contrast, have higher temporal resolution but at present are limited to visible and infrared wavelengths that observe only the tops of clouds. This observing gap was noted by the National Research Council's Earth Science Decadal Survey in 2007. Uncertainties in global climate models are significantly affected by processes that govern the formation and dissipation of clouds that largely control the global water and energy budgets. Current uncertainties in cloud parameterization within climate models lead to drastically different climate outcomes. With all evidence suggesting that the precipitation onset may be governed by factors such atmospheric stability, it becomes critical to have at least first-order observations globally in diverse climate regimes. Similar arguments are valid for ice processes where more efficient ice formation and precipitation have a tendency to leave fewer ice clouds behind that have different but equally important impacts on the Earth's energy budget and resulting temperature trends. TEMPEST is a unique program that will provide a small constellation of inexpensive CubeSats with millimeter-wave radiometers to address key science needs related to cloud and precipitation processes. Because these processes are most critical in the development of climate models that will soon run at scales that explicitly resolve clouds, the TEMPEST program will directly focus on examining, validating and improving the parameterizations currently used in cloud scale models. The time evolution of cloud and precipitation microphysics is dependent upon parameterized process rates. The outcome of TEMPEST will provide a first-order understanding of how individual assumptions in current cloud model parameterizations behave in diverse climate regimes.

More reliable forecasts with less precise computations: a fast-track route to cloud-resolved weather and climate simulators?

PubMed Central

Palmer, T. N.

2014-01-01

This paper sets out a new methodological approach to solving the equations for simulating and predicting weather and climate. In this approach, the conventionally hard boundary between the dynamical core and the sub-grid parametrizations is blurred. This approach is motivated by the relatively shallow power-law spectrum for atmospheric energy on scales of hundreds of kilometres and less. It is first argued that, because of this, the closure schemes for weather and climate simulators should be based on stochastic–dynamic systems rather than deterministic formulae. Second, as high-wavenumber elements of the dynamical core will necessarily inherit this stochasticity during time integration, it is argued that the dynamical core will be significantly over-engineered if all computations, regardless of scale, are performed completely deterministically and if all variables are represented with maximum numerical precision (in practice using double-precision floating-point numbers). As the era of exascale computing is approached, an energy- and computationally efficient approach to cloud-resolved weather and climate simulation is described where determinism and numerical precision are focused on the largest scales only. PMID:24842038

More reliable forecasts with less precise computations: a fast-track route to cloud-resolved weather and climate simulators?

PubMed

Palmer, T N

2014-06-28

This paper sets out a new methodological approach to solving the equations for simulating and predicting weather and climate. In this approach, the conventionally hard boundary between the dynamical core and the sub-grid parametrizations is blurred. This approach is motivated by the relatively shallow power-law spectrum for atmospheric energy on scales of hundreds of kilometres and less. It is first argued that, because of this, the closure schemes for weather and climate simulators should be based on stochastic-dynamic systems rather than deterministic formulae. Second, as high-wavenumber elements of the dynamical core will necessarily inherit this stochasticity during time integration, it is argued that the dynamical core will be significantly over-engineered if all computations, regardless of scale, are performed completely deterministically and if all variables are represented with maximum numerical precision (in practice using double-precision floating-point numbers). As the era of exascale computing is approached, an energy- and computationally efficient approach to cloud-resolved weather and climate simulation is described where determinism and numerical precision are focused on the largest scales only.

Climate: Into the 21st Century

NASA Astrophysics Data System (ADS)

Burroughs, William

2003-08-01

Toward the end of the twentieth century, it became evident to professionals working within the meterological arena that the world's climate system was showing signs of change that could not be adequately explained in terms of natural variation. Since that time there has been an increasing recognition that the climate system is changing as a result of human industries and lifestyles, and that the outcomes may prove catastrophic to the world's escalating population. Compiled by an international team formed under the auspices of the World Meteorological Organization (WMO), Climate: Into the 21st Century features an unrivalled collection of essays by the world's leading meteorological experts. These fully integrated contributions provide a perspective of the global climate system across the twentieth century, and describe some of the most arresting and extreme climatic events and their effects that have occurred during that time. In addition, the book traces the development of our capabilities to observe and monitor the climate system, and outlines our understanding of the predictability of climate on time-scales of months and longer. It concludes with a summary of the prospects for applying the twentieth century climate experience in order to benefit society in the twenty-first century. Lavishly illustrated in color, Climate is an accessible acccount of the challenges that climate poses at the start of the twenty-first century. Filled with fascinating facts and diagrams, it is written for a wide audience and will captivate the general reader interested in climate issues, and will be a valuable teaching resource. William Burroughs is a successful science author of books on climate, including Weather (Time Life, 2000), and Climate Change: A Multidisciplinary Approach (2001), Does the Weather Really Matter? (1997) and The Climate Revealed (1999), all published by Cambridge University Press.

Extended-Range Forecasts at Climate Prediction Center: Current Status and Future Plans

NASA Astrophysics Data System (ADS)

Kumar, A.

2016-12-01

Motivated by a user need to provide forecast information on extended-range time-scales (i.e., weeks 2-4), in recent years Climate Prediction Center (CPC) has made considerable efforts towards developing and testing the feasibility for developing the required forecasts. The forecasts targeting this particular time-scale face a unique challenge in that while the forecast skill due to atmospheric initial conditions is small (because of rapid decay in the memory associated with the atmospheric initial conditions), short time averages for which forecasts are made do not benefit from skill associated with anomalous boundary conditions either. Despite these challenges, CPC has embarked on providing an experimental outlook for weeks 3-4 average. The talk will summarize the current status of CPC's current suite of extended-range forecast products, and further, will discuss some future plans.

A Multi-Scale Energy Food Systems Modeling Framework For Climate Adaptation

NASA Astrophysics Data System (ADS)

Siddiqui, S.; Bakker, C.; Zaitchik, B. F.; Hobbs, B. F.; Broaddus, E.; Neff, R.; Haskett, J.; Parker, C.

2016-12-01

Our goal is to understand coupled system dynamics across scales in a manner that allows us to quantify the sensitivity of critical human outcomes (nutritional satisfaction, household economic well-being) to development strategies and to climate or market induced shocks in sub-Saharan Africa. We adopt both bottom-up and top-down multi-scale modeling approaches focusing our efforts on food, energy, water (FEW) dynamics to define, parameterize, and evaluate modeled processes nationally as well as across climate zones and communities. Our framework comprises three complementary modeling techniques spanning local, sub-national and national scales to capture interdependencies between sectors, across time scales, and on multiple levels of geographic aggregation. At the center is a multi-player micro-economic (MME) partial equilibrium model for the production, consumption, storage, and transportation of food, energy, and fuels, which is the focus of this presentation. We show why such models can be very useful for linking and integrating across time and spatial scales, as well as a wide variety of models including an agent-based model applied to rural villages and larger population centers, an optimization-based electricity infrastructure model at a regional scale, and a computable general equilibrium model, which is applied to understand FEW resources and economic patterns at national scale. The MME is based on aggregating individual optimization problems for relevant players in an energy, electricity, or food market and captures important food supply chain components of trade and food distribution accounting for infrastructure and geography. Second, our model considers food access and utilization by modeling food waste and disaggregating consumption by income and age. Third, the model is set up to evaluate the effects of seasonality and system shocks on supply, demand, infrastructure, and transportation in both energy and food.

HIST-EU - a dataset of European relevance, a database to enable long-term climate variability studies on regional scale

NASA Astrophysics Data System (ADS)

Auer, I.; Böhm, R.; Ganekind, M.; Schöner, W.; Nemec, J.; Chimani, B.

2010-09-01

Instrumental time series of different climate elements are an important requisite for climate and climate impact studies. Long-term time series can improve our understanding of climate change during the instrumental period. During recent decades a number of national and international initiatives in European countries have significantly increased the number of existing long-term instrumental series; however a publically available data base covering Europe has not been created so far. For the "Greater Alpine Region" (4-19 deg E, 43-49 deg N, 0-3500m asl) the HISTALP data base has been established consisting of monthly homogenised temperature, pressure, precipitation, sunshine and cloudiness records. The data set may be described as follows: Long-term (fully exploiting the potential of systematically measured data). dense (network density adequate in respect to the spatial coherence of the given climate element) quality improved (outliers removed, gaps filled) homogenised (earlier sections adjusted to the recent state of the measuring site) multiple (covering more than one climate element) user friendly (well described and kept in different modes for different applications) HIST-EU is inteded to be a data set of European relevance allowing studying climate variability on regional scale. It focuses on data collection, data recovery and rescue, and homogenizing. HIST-EU will use the infrastructure of HISTALP (www.zamg.ac.at/histalp) and will allow free or restricted data access due to the regulations of data providers. HIST-EU will be carried out under the umbrella of ECSN/EUMETNET.

Relative importance of thermal versus carbon dioxide induced warming from fossil-fuel combustion

NASA Astrophysics Data System (ADS)

Zhang, X.; Caldeira, K.

2015-12-01

The Earth is heated both when reduced carbon is oxidized to carbon dioxide and when outgoing longwave radiation is trapped by carbon dioxide in the atmosphere (CO2 greenhouse effect). The purpose of this study is to improve our understanding of time scales and relative magnitudes of climate forcing increase over time from pulse, continuous, and historical CO2 and thermal emissions. To estimate the amount of global warming that would be produced by thermal and CO2 emissions from fossil fuel combustion, we calculate thermal emissions with thermal contents of fossil fuels and estimate CO2 emissions with emission factors from Intergovernmental Panel on Climate Change (IPCC) AR5. We then use a schematic climate model mimicking Coupled Model Intercomparison Project Phase 5 to investigate the climate forcing and the time-integrated climate forcing. We show that, considered globally, direct thermal forcing from fossil fuel combustion is about 1.71% the radiative forcing from CO2 that has accumulated in the atmosphere from past fossil fuel combustion. When a new power plant comes on line, the radiative forcing from the accumulation of released CO2 exceeds the thermal emissions from the power plant in less than half a year (and about 3 months for coal plants). Due to the long lifetime of CO2 in the atmosphere, CO2 radiative forcing greatly overwhelms direct thermal forcing on longer time scales. Ultimately, the cumulative radiative forcing from the CO2 exceeds the direct thermal forcing by a factor of ~100,000.

Integrated approaches to climate-crop modelling: needs and challenges.

PubMed

Betts, Richard A

2005-11-29

This paper discusses the need for a more integrated approach to modelling changes in climate and crops, and some of the challenges posed by this. While changes in atmospheric composition are expected to exert an increasing radiative forcing of climate change leading to further warming of global mean temperatures and shifts in precipitation patterns, these are not the only climatic processes which may influence crop production. Changes in the physical characteristics of the land cover may also affect climate; these may arise directly from land use activities and may also result from the large-scale responses of crops to seasonal, interannual and decadal changes in the atmospheric state. Climate models used to drive crop models may, therefore, need to consider changes in the land surface, either as imposed boundary conditions or as feedbacks from an interactive climate-vegetation model. Crops may also respond directly to changes in atmospheric composition, such as the concentrations of carbon dioxide (CO2), ozone (03) and compounds of sulphur and nitrogen, so crop models should consider these processes as well as climate change. Changes in these, and the responses of the crops, may be intimately linked with meteorological processes so crop and climate models should consider synergies between climate and atmospheric chemistry. Some crop responses may occur at scales too small to significantly influence meteorology, so may not need to be included as feedbacks within climate models. However, the volume of data required to drive the appropriate crop models may be very large, especially if short-time-scale variability is important. Implementation of crop models within climate models would minimize the need to transfer large quantities of data between separate modelling systems. It should also be noted that crop responses to climate change may interact with other impacts of climate change, such as hydrological changes. For example, the availability of water for irrigation may be affected by changes in runoff as a direct consequence of climate change, and may also be affected by climate-related changes in demand for water for other uses. It is, therefore, necessary to consider the interactions between the responses of several impacts sectors to climate change. Overall, there is a strong case for a much closer coupling between models of climate, crops and hydrology, but this in itself poses challenges arising from issues of scale and errors in the models. A strategy is proposed whereby the pursuit of a fully coupled climate-chemistry-crop-hydrology model is paralleled by continued use of separate climate and land surface models but with a focus on consistency between the models.

Climate Change Impact on Air Quality in High Resolution Simulation for Central Europe

NASA Astrophysics Data System (ADS)

Halenka, T.; Huszar, P.; Belda, M.

2009-04-01

Recently the effects of climate change on air-quality and vice-versa are studied quite extensively. In fact, even at regional and local scale especially the impact of climate change on the atmospheric composition and photochemical smog formation conditions can be significant when expecting e.g. more frequent appearance of heat waves etc. For the purpose of qualifying and quantifying the magnitude of such effects and to study the potential of climate forcing due to atmospheric chemistry/aerosols on regional scale, chemistry-transport model was coupled to RegCM on the Department of Meteorology and Environmental Protection, Faculty of Mathematics and Physics, Charles University in Prague, for the simulations in framework of the EC FP6 Project CECILIA. Off-line one way coupling enables the simulation of distribution of pollutants over 1991-2001 in very high resolution of 10 km is compared to the EMEP observations for the area of Central Europe. Simulations driven by climate change boundary conditions for time slices 1991-2000, 2041-2050 and 2091-2100 are presented to show the effect of climate change on the air quality in the region.

Social Environmental Conceptions of Male Homosexual Behavior: A University Climate Analysis.

ERIC Educational Resources Information Center

Reynolds, Arthur J.

1989-01-01

Assessed university climate of 32 male homosexual and 32 male heterosexual undergraduates. Subjects completed the University Climate Scale, Alienation Scale, Bem Sex-Role Inventory, Rosenberg Self-Esteem Scale, and the University Homophobia Scale. Results revealed that homosexual subjects perceived measures of university climate as significantly…

Maximum rates of climate change are systematically underestimated in the geological record.

PubMed

Kemp, David B; Eichenseer, Kilian; Kiessling, Wolfgang

2015-11-10

Recently observed rates of environmental change are typically much higher than those inferred for the geological past. At the same time, the magnitudes of ancient changes were often substantially greater than those established in recent history. The most pertinent disparity, however, between recent and geological rates is the timespan over which the rates are measured, which typically differ by several orders of magnitude. Here we show that rates of marked temperature changes inferred from proxy data in Earth history scale with measurement timespan as an approximate power law across nearly six orders of magnitude (10(2) to >10(7) years). This scaling reveals how climate signals measured in the geological record alias transient variability, even during the most pronounced climatic perturbations of the Phanerozoic. Our findings indicate that the true attainable pace of climate change on timescales of greatest societal relevance is underestimated in geological archives.

A 2,000-year reconstruction of the rain-fed maize agricultural niche in the US Southwest.

PubMed

Bocinsky, R Kyle; Kohler, Timothy A

2014-12-04

Humans experience, adapt to and influence climate at local scales. Paleoclimate research, however, tends to focus on continental, hemispheric or global scales, making it difficult for archaeologists and paleoecologists to study local effects. Here we introduce a method for high-frequency, local climate-field reconstruction from tree-rings. We reconstruct the rain-fed maize agricultural niche in two regions of the southwestern United States with dense populations of prehispanic farmers. Niche size and stability are highly variable within and between the regions. Prehispanic rain-fed maize farmers tended to live in agricultural refugia--areas most reliably in the niche. The timing and trajectory of the famous thirteenth century Pueblo migration can be understood in terms of relative niche size and stability. Local reconstructions like these illuminate the spectrum of strategies past humans used to adapt to climate change by recasting climate into the distributions of resources on which they depended.

Multiscale characterization and prediction of monsoon rainfall in India using Hilbert-Huang transform and time-dependent intrinsic correlation analysis

NASA Astrophysics Data System (ADS)

Adarsh, S.; Reddy, M. Janga

2017-07-01

In this paper, the Hilbert-Huang transform (HHT) approach is used for the multiscale characterization of All India Summer Monsoon Rainfall (AISMR) time series and monsoon rainfall time series from five homogeneous regions in India. The study employs the Complete Ensemble Empirical Mode Decomposition with Adaptive Noise (CEEMDAN) for multiscale decomposition of monsoon rainfall in India and uses the Normalized Hilbert Transform and Direct Quadrature (NHT-DQ) scheme for the time-frequency characterization. The cross-correlation analysis between orthogonal modes of All India monthly monsoon rainfall time series and that of five climate indices such as Quasi Biennial Oscillation (QBO), El Niño Southern Oscillation (ENSO), Sunspot Number (SN), Atlantic Multi Decadal Oscillation (AMO), and Equatorial Indian Ocean Oscillation (EQUINOO) in the time domain showed that the links of different climate indices with monsoon rainfall are expressed well only for few low-frequency modes and for the trend component. Furthermore, this paper investigated the hydro-climatic teleconnection of ISMR in multiple time scales using the HHT-based running correlation analysis technique called time-dependent intrinsic correlation (TDIC). The results showed that both the strength and nature of association between different climate indices and ISMR vary with time scale. Stemming from this finding, a methodology employing Multivariate extension of EMD and Stepwise Linear Regression (MEMD-SLR) is proposed for prediction of monsoon rainfall in India. The proposed MEMD-SLR method clearly exhibited superior performance over the IMD operational forecast, M5 Model Tree (MT), and multiple linear regression methods in ISMR predictions and displayed excellent predictive skill during 1989-2012 including the four extreme events that have occurred during this period.

Decomposition of the complex system into nonlinear spatio-temporal modes: algorithm and application to climate data mining

NASA Astrophysics Data System (ADS)

Feigin, Alexander; Gavrilov, Andrey; Loskutov, Evgeny; Mukhin, Dmitry

2015-04-01

Proper decomposition of the complex system into well separated "modes" is a way to reveal and understand the mechanisms governing the system behaviour as well as discover essential feedbacks and nonlinearities. The decomposition is also natural procedure that provides to construct adequate and concurrently simplest models of both corresponding sub-systems, and of the system in whole. In recent works two new methods of decomposition of the Earth's climate system into well separated modes were discussed. The first method [1-3] is based on the MSSA (Multichannel Singular Spectral Analysis) [4] for linear expanding vector (space-distributed) time series and makes allowance delayed correlations of the processes recorded in spatially separated points. The second one [5-7] allows to construct nonlinear dynamic modes, but neglects delay of correlations. It was demonstrated [1-3] that first method provides effective separation of different time scales, but prevent from correct reduction of data dimension: slope of variance spectrum of spatio-temporal empirical orthogonal functions that are "structural material" for linear spatio-temporal modes, is too flat. The second method overcomes this problem: variance spectrum of nonlinear modes falls essentially sharply [5-7]. However neglecting time-lag correlations brings error of mode selection that is uncontrolled and increases with growth of mode time scale. In the report we combine these two methods in such a way that the developed algorithm allows constructing nonlinear spatio-temporal modes. The algorithm is applied for decomposition of (i) multi hundreds years globally distributed data generated by the INM RAS Coupled Climate Model [8], and (ii) 156 years time series of SST anomalies distributed over the globe [9]. We compare efficiency of different methods of decomposition and discuss the abilities of nonlinear spatio-temporal modes for construction of adequate and concurrently simplest ("optimal") models of climate systems. 1. Feigin A.M., Mukhin D., Gavrilov A., Volodin E.M., and Loskutov E.M. (2013) "Separation of spatial-temporal patterns ("climatic modes") by combined analysis of really measured and generated numerically vector time series", AGU 2013 Fall Meeting, Abstract NG33A-1574. 2. Alexander Feigin, Dmitry Mukhin, Andrey Gavrilov, Evgeny Volodin, and Evgeny Loskutov (2014) "Approach to analysis of multiscale space-distributed time series: separation of spatio-temporal modes with essentially different time scales", Geophysical Research Abstracts, Vol. 16, EGU2014-6877. 3. Dmitry Mukhin, Dmitri Kondrashov, Evgeny Loskutov, Andrey Gavrilov, Alexander Feigin, and Michael Ghil (2014) "Predicting critical transitions in ENSO models, Part II: Spatially dependent models", Journal of Climate (accepted, doi: 10.1175/JCLI-D-14-00240.1). 4. Ghil, M., R. M. Allen, M. D. Dettinger, K. Ide, D. Kondrashov, et al. (2002) "Advanced spectral methods for climatic time series", Rev. Geophys. 40(1), 3.1-3.41. 5. Dmitry Mukhin, Andrey Gavrilov, Evgeny M Loskutov and Alexander M Feigin (2014) "Nonlinear Decomposition of Climate Data: a New Method for Reconstruction of Dynamical Modes", AGU 2014 Fall Meeting, Abstract NG43A-3752. 6. Andrey Gavrilov, Dmitry Mukhin, Evgeny Loskutov, and Alexander Feigin (2015) "Empirical decomposition of climate data into nonlinear dynamic modes", Geophysical Research Abstracts, Vol. 17, EGU2015-627. 7. Dmitry Mukhin, Andrey Gavrilov, Evgeny Loskutov, Alexander Feigin, and Juergen Kurths (2015) "Reconstruction of principal dynamical modes from climatic variability: nonlinear approach", Geophysical Research Abstracts, Vol. 17, EGU2015-5729. 8. http://83.149.207.89/GCM_DATA_PLOTTING/GCM_INM_DATA_XY_en.htm. 9. http://iridl.ldeo.columbia.edu/SOURCES/.KAPLAN/.EXTENDED/.v2/.ssta/.

Addressing Spatial Dependence Bias in Climate Model Simulations—An Independent Component Analysis Approach

NASA Astrophysics Data System (ADS)

Nahar, Jannatun; Johnson, Fiona; Sharma, Ashish

2018-02-01

Conventional bias correction is usually applied on a grid-by-grid basis, meaning that the resulting corrections cannot address biases in the spatial distribution of climate variables. To solve this problem, a two-step bias correction method is proposed here to correct time series at multiple locations conjointly. The first step transforms the data to a set of statistically independent univariate time series, using a technique known as independent component analysis (ICA). The mutually independent signals can then be bias corrected as univariate time series and back-transformed to improve the representation of spatial dependence in the data. The spatially corrected data are then bias corrected at the grid scale in the second step. The method has been applied to two CMIP5 General Circulation Model simulations for six different climate regions of Australia for two climate variables—temperature and precipitation. The results demonstrate that the ICA-based technique leads to considerable improvements in temperature simulations with more modest improvements in precipitation. Overall, the method results in current climate simulations that have greater equivalency in space and time with observational data.

Different growth sensitivity to climate of the conifer Juniperus thurifera on both sides of the Mediterranean Sea

NASA Astrophysics Data System (ADS)

DeSoto, Lucía; Varino, Filipa; Andrade, José P.; Gouveia, Celia M.; Campelo, Filipe; Trigo, Ricardo M.; Nabais, Cristina

2014-12-01

Mediterranean plants cope with cold wet winters and dry hot summers, with a drought gradient from northwest to southeast. Limiting climatic conditions have become more pronounced in the last decades due to the warming trend and rainfall decrease. Juniperus thurifera L., a long-lived conifer tree endemic to the western Mediterranean region, has a disjunct distribution in Europe and Africa, making it a suitable species to study sensitivity to climate in both sides of the Mediterranean Basin. Tree-ring width chronologies were built for three J. thurifera stands at Spain (Europe) and three in Morocco (Africa) and correlated with monthly temperature and precipitation. The temporal stability of climate-growth relationships was assessed using moving correlations; the drought effect on growth was calculated using the monthly standardized precipitation-evapotranspiration index (SPEI) at different temporal scales. In the wettest stands, increasing spring temperature and summer precipitation enhanced growth, while in the driest stands, growth was enhanced by higher spring precipitation and lower summer temperature. The climate-growth correlations shifted during the twentieth century, especially since the 1970s. Particularly noticeable is the recent negative correlation with previous autumn and winter precipitation in the wettest stands of J. thurifera, probably related with an effect of cloud cover or flooding on carbon storage depletion for next year growth. The driest stands were affected by drought at long time scales, while the wettest stands respond to drought at short time scales. This reveals a different strategy to cope with drought conditions, with populations from drier sites able to cope with short periods of water deficit.

Using Minimax Regret Optimization to Search for Multi-Stakeholder Solutions to Deeply Uncertain Flood Hazards under Climate Change

NASA Astrophysics Data System (ADS)

Kirshen, P. H.; Hecht, J. S.; Vogel, R. M.

2015-12-01

Prescribing long-term urban floodplain management plans under the deep uncertainty of climate change is a challenging endeavor. To address this, we have implemented and tested with stakeholders a parsimonious multi-stage mixed integer programming (MIP) model that identifies the optimal time period(s) for implementing publicly and privately financed adaptation measures. Publicly funded measures include reach-scale flood barriers, flood insurance, and buyout programs to encourage property owners in flood-prone areas to retreat from the floodplain. Measures privately funded by property owners consist of property-scale floodproofing options, such as raising building foundations, as well as investments in flood insurance or retreat from flood-prone areas. The objective function to minimize the sum of flood control and damage costs in all planning stages for different property types during floods of different severities. There are constraints over time for flow mass balances, construction of flood management alternatives and their cumulative implementation, budget allocations, and binary decisions. Damages are adjusted for flood control investments. In recognition of the deep uncertainty of GCM-derived climate change scenarios, we employ the minimax regret criterion to identify adaptation portfolios robust to different climate change trajectories. As an example, we identify publicly and privately funded adaptation measures for a stylized community based on the estuarine community of Exeter, New Hampshire, USA. We explore the sensitivity of recommended portfolios to different ranges of climate changes, and costs associated with economies of scale and flexible infrastructure design as well as different municipal budget constraints.

Beyond scenario planning: projecting the future using models at Wind Cave National Park (USA)

NASA Astrophysics Data System (ADS)

King, D. A.; Bachelet, D. M.; Symstad, A. J.

2011-12-01

Scenario planning has been used by the National Park Service as a tool for natural resource management planning in the face of climate change. Sets of plausible but divergent future scenarios are constructed from available information and expert opinion and serve as starting point to derive climate-smart management strategies. However, qualitative hypotheses about how systems would react to a particular set of conditions assumed from coarse scale climate projections may lack the scientific rigor expected from a federal agency. In an effort to better assess the range of likely futures at Wind Cave National Park, a project was conceived to 1) generate high resolution historic and future climate time series to identify local weather patterns that may or may not persist, 2) simulate the hydrological cycle in this geologically varied landscape and its response to future climate, 3) project vegetation dynamics and ensuing changes in the biogeochemical cycles given grazing and fire disturbances under new climate conditions, and 4) synthesize and compare results with those from the scenario planning exercise. In this framework, we tested a dynamic global vegetation model against local information on vegetation cover, disturbance history and stream flow to better understand the potential resilience of these ecosystems to climate change. We discuss the tradeoffs between a coarse scale application of the model showing regional trends with limited ability to project the fine scale mosaic of vegetation at Wind Cave, and a finer scale approach that can account for local slope effects on water balance and better assess the vulnerability of landscape facets, but requires more intensive data acquisition. We elaborate on the potential for sharing information between models to mitigate the often-limited treatment of biological feedbacks in the physical representations of soil and atmospheric processes.

Development and nationwide scale-up of Climate Matters, a localized climate change education program delivered by TV weathercasters.

NASA Astrophysics Data System (ADS)

Cullen, H. M.; Maibach, E.

2016-12-01

Most Americans view climate change as a threat that is distant in space (i.e., not here), time (i.e., not now), and species (i.e., not us). TV weathercasters are ideally positioned to educate Americans about the current and projected impacts of climate change in their community: they have tremendous reach, are trusted sources of climate information, and are highly skilled science communicators. In 2009, we learned that many weathercasters were potentially interested in reporting on climate change, but few actually were, citing significant barriers including a lack of time to prepare and air stories, and lack of access to high quality content. To test the premise that TV weathercasters can be effective climate educators - if supported with high quality localized climate communication content - in 2010 George Mason University, Climate Central and WLTX-TV (Columbia, SC) developed and pilot-tested Climate Matters, a series of short on-air (and online) segments about the local impacts of climate change, delivered by the station's chief meteorologist. During the first year, more than a dozen stories aired. To formally evaluate Climate Matters, we conducted pre- and post-test surveys of local TV news viewers in Columbia. After one year, WLTX viewers had developed a more science-based understanding of climate change than viewers of other local news stations, confirming our premise that when TV weathercasters report on the local implications of climate change, their viewers learn. Through a series of expansions, including the addition of important new partners - AMS, NASA, NOAA & Yale University - Climate Matters has become a comprehensive nationwide climate communication resource program for American TV weathercasters. As of March 2016, a network of 313 local weathercasters nationwide (at 202 stations in 111 media markets) are participating in the program, receiving new content on a weekly basis. This presentation will review the theoretical basis of the program, detail its development and national scale-up, and conclude with insights for how to develop climate communication initiatives for other professional communities of practice in the U.S. and other countries.

Accelerating Time Integration for the Shallow Water Equations on the Sphere Using GPUs

DOE PAGES

Archibald, R.; Evans, K. J.; Salinger, A.

2015-06-01

The push towards larger and larger computational platforms has made it possible for climate simulations to resolve climate dynamics across multiple spatial and temporal scales. This direction in climate simulation has created a strong need to develop scalable timestepping methods capable of accelerating throughput on high performance computing. This study details the recent advances in the implementation of implicit time stepping of the spectral element dynamical core within the United States Department of Energy (DOE) Accelerated Climate Model for Energy (ACME) on graphical processing units (GPU) based machines. We demonstrate how solvers in the Trilinos project are interfaced with ACMEmore » and GPU kernels to increase computational speed of the residual calculations in the implicit time stepping method for the atmosphere dynamics. We demonstrate the optimization gains and data structure reorganization that facilitates the performance improvements.« less

Spatiotemporal variation of the association between climate dynamics and HFRS outbreaks in Eastern China during 2005-2016 and its geographic determinants

PubMed Central

Wu, Jiaping; Cazelles, Bernard; Qian, Quan; Mu, Di; Wang, Yong; Yin, Wenwu; Zhang, Wenyi

2018-01-01

Background Hemorrhagic fever with renal syndrome (HFRS) is a rodent-associated zoonosis caused by hantavirus. The HFRS was initially detected in northeast China in 1931, and since 1955 it has been detected in many regions of the country. Global climate dynamics influences HFRS spread in a complex nonlinear way. The quantitative assessment of the spatiotemporal variation of the “HFRS infections-global climate dynamics” association at a large geographical scale and during a long time period is still lacking. Methods and findings This work is the first study of a recently completed dataset of monthly HFRS cases in Eastern China during the period 2005–2016. A methodological synthesis that involves a time-frequency technique, a composite space-time model, hotspot analysis, and machine learning is implemented in the study of (a) the association between HFRS incidence spread and climate dynamics and (b) the geographic factors impacting this association over Eastern China during the period 2005–2016. The results showed that by assimilating core and city-specific knowledge bases the synthesis was able to depict quantitatively the space-time variation of periodic climate-HFRS associations at a large geographic scale and to assess numerically the strength of this association in the area and period of interest. It was found that the HFRS infections in Eastern China has a strong association with global climate dynamics, in particular, the 12, 18 and 36 mos periods were detected as the three main synchronous periods of climate dynamics and HFRS distribution. For the 36 mos period (which is the period with the strongest association), the space-time correlation pattern of the association strength indicated strong temporal but rather weak spatial dependencies. The generated space-time maps of association strength and association hotspots provided a clear picture of the geographic variation of the association strength that often-exhibited cluster characteristics (e.g., the south part of the study area displays a strong climate-HFRS association with non-point effects, whereas the middle-north part displays a weak climate-HFRS association). Another finding of this work is the upward climate-HFRS coherency trend for the past few years (2013–2015) indicating that the climate impacts on HFRS were becoming increasingly sensitive with time. Lastly, another finding of this work is that geographic factors affect the climate-HFRS association in an interrelated manner through local climate or by means of HFRS infections. In particular, location (latitude, distance to coastline and longitude), grassland and woodland are the geographic factors exerting the most noticeable effects on the climate-HFRS association (e.g., low latitude has a strong effect, whereas distance to coastline has a wave-like effect). Conclusions The proposed synthetic quantitative approach revealed important aspects of the spatiotemporal variation of the climate-HFRS association in Eastern China during a long time period, and identified the geographic factors having a major impact on this association. Both findings could improve public health policy in an HFRS-torn country like China. Furthermore, the synthetic approach developed in this work can be used to map the space-time variation of different climate-disease associations in other parts of China and the World. PMID:29874263

On climate prediction: how much can we expect from climate memory?

NASA Astrophysics Data System (ADS)

Yuan, Naiming; Huang, Yan; Duan, Jianping; Zhu, Congwen; Xoplaki, Elena; Luterbacher, Jürg

2018-03-01

Slowing variability in climate system is an important source of climate predictability. However, it is still challenging for current dynamical models to fully capture the variability as well as its impacts on future climate. In this study, instead of simulating the internal multi-scale oscillations in dynamical models, we discussed the effects of internal variability in terms of climate memory. By decomposing climate state x(t) at a certain time point t into memory part M(t) and non-memory part ɛ (t) , climate memory effects from the past 30 years on climate prediction are quantified. For variables with strong climate memory, high variance (over 20% ) in x(t) is explained by the memory part M(t), and the effects of climate memory are non-negligible for most climate variables, but the precipitation. Regarding of multi-steps climate prediction, a power law decay of the explained variance was found, indicating long-lasting climate memory effects. The explained variances by climate memory can remain to be higher than 10% for more than 10 time steps. Accordingly, past climate conditions can affect both short (monthly) and long-term (interannual, decadal, or even multidecadal) climate predictions. With the memory part M(t) precisely calculated from Fractional Integral Statistical Model, one only needs to focus on the non-memory part ɛ (t) , which is an important quantity that determines climate predictive skills.

Disentangling Global Warming, Multidecadal Variability, and El Niño in Pacific Temperatures

NASA Astrophysics Data System (ADS)

Wills, Robert C.; Schneider, Tapio; Wallace, John M.; Battisti, David S.; Hartmann, Dennis L.

2018-03-01

A key challenge in climate science is to separate observed temperature changes into components due to internal variability and responses to external forcing. Extended integrations of forced and unforced climate models are often used for this purpose. Here we demonstrate a novel method to separate modes of internal variability from global warming based on differences in time scale and spatial pattern, without relying on climate models. We identify uncorrelated components of Pacific sea surface temperature variability due to global warming, the Pacific Decadal Oscillation (PDO), and the El Niño-Southern Oscillation (ENSO). Our results give statistical representations of PDO and ENSO that are consistent with their being separate processes, operating on different time scales, but are otherwise consistent with canonical definitions. We isolate the multidecadal variability of the PDO and find that it is confined to midlatitudes; tropical sea surface temperatures and their teleconnections mix in higher-frequency variability. This implies that midlatitude PDO anomalies are more persistent than previously thought.

Transport of ice into the stratosphere and the humidification of the stratosphere over the 21st century.

PubMed

Dessler, A E; Ye, H; Wang, T; Schoeberl, M R; Oman, L D; Douglass, A R; Butler, A H; Rosenlof, K H; Davis, S M; Portmann, R W

2016-03-16

Climate models predict that tropical lower-stratospheric humidity will increase as the climate warms. We examine this trend in two state-of-the-art chemistry-climate models. Under high greenhouse gas emissions scenarios, the stratospheric entry value of water vapor increases by ~1 part per million by volume (ppmv) over this century in both models. We show with trajectory runs driven by model meteorological fields that the warming tropical tropopause layer (TTL) explains 50-80% of this increase. The remainder is a consequence of trends in evaporation of ice convectively lofted into the TTL and lower stratosphere. Our results further show that, within the models we examined, ice lofting is primarily important on long time scales - on interannual time scales, TTL temperature variations explain most of the variations in lower stratospheric humidity. Assessing the ability of models to realistically represent ice-lofting processes should be a high priority in the modeling community.

Transport of ice into the stratosphere and the humidification of the stratosphere over the 21st century

PubMed Central

Dessler, A.E.; Ye, H.; Wang, T.; Schoeberl, M.R.; Oman, L.D.; Douglass, A.R.; Butler, A.H.; Rosenlof, K.H.; Davis, S.M.; Portmann, R.W.

2018-01-01

Climate models predict that tropical lower-stratospheric humidity will increase as the climate warms. We examine this trend in two state-of-the-art chemistry-climate models. Under high greenhouse gas emissions scenarios, the stratospheric entry value of water vapor increases by ~1 part per million by volume (ppmv) over this century in both models. We show with trajectory runs driven by model meteorological fields that the warming tropical tropopause layer (TTL) explains 50–80% of this increase. The remainder is a consequence of trends in evaporation of ice convectively lofted into the TTL and lower stratosphere. Our results further show that, within the models we examined, ice lofting is primarily important on long time scales — on interannual time scales, TTL temperature variations explain most of the variations in lower stratospheric humidity. Assessing the ability of models to realistically represent ice-lofting processes should be a high priority in the modeling community. PMID:29551841

Transport of Ice into the Stratosphere and the Humidification of the Stratosphere over the 21st Century

NASA Technical Reports Server (NTRS)

Dessler, A. E.; Ye, H.; Wang, T.; Schoeberl, M. R.; Oman, L. D.; Douglass, A. R.; Butler, A. H.; Rosenlof, K. H.; Davis, S. M.; Portmann, R. W.

2016-01-01

Climate models predict that tropical lower-stratospheric humidity will increase as the climate warms. We examine this trend in two state-of-the-art chemistry-climate models. Under high greenhouse gas emissions scenarios, the stratospheric entry value of water vapor increases by approx. 1 part per million by volume (ppmv) over this century in both models. We show with trajectory runs driven by model meteorological fields that the warming tropical tropopause layer (TTL) explains 50-80% of this increase. The remainder is a consequence of trends in evaporation of ice convectively lofted into the TTL and lower stratosphere. Our results further show that, within the models we examined, ice lofting is primarily important on long time scales - on interannual time scales, TTL temperature variations explain most of the variations in lower stratospheric humidity. Assessing the ability of models to realistically represent ice-lofting processes should be a high priority in the modeling community.

Airborne Particles: What We Have Learned About Their Role in Climate from Remote Sensing, and Prospects for Future Advances

NASA Technical Reports Server (NTRS)

Kahn, Ralph A.

2013-01-01

Desert dust, wildfire smoke, volcanic ash, biogenic and urban pollution particles, all affect the regional-scale climate of Earth in places and at times; some have global-scale impacts on the column radiation balance, cloud properties, atmospheric stability structure, and circulation patterns. Remote sensing has played a central role in identifying the sources and transports of airborne particles, mapping their three-dimensional distribution and variability, quantifying their amount, and constraining aerosol air mass type. The measurements obtained from remote sensing have strengths and limitations, and their value for characterizing Earths environment is enhanced immensely when they are combined with direct, in situ observations, and used to constrain aerosol transport and climate models. A similar approach has been taken to study the role particles play in determining the climate of Mars, though based on far fewer observations. This presentation will focus what we have learned from remote sensing about the impacts aerosol have on Earths climate; a few points about how aerosols affect the climate of Mars will also be introduced, in the context of how we might assess aerosol-climate impacts more generally on other worlds.

AIRS Observations Based Evaluation of Relative Climate Feedback Strengths on a GCM Grid-Scale

NASA Astrophysics Data System (ADS)

Molnar, G. I.; Susskind, J.

2012-12-01

Climate feedback strengths, especially those associated with moist processes, still have a rather wide range in GCMs, the primary tools to predict future climate changes associated with man's ever increasing influences on our planet. Here, we make use of the first 10 years of AIRS observations to evaluate interrelationships/correlations of atmospheric moist parameter anomalies computed from AIRS Version 5 Level-3 products, and demonstrate their usefulness to assess relative feedback strengths. Although one may argue about the possible usability of shorter-term, observed climate parameter anomalies for estimating the strength of various (mostly moist processes related) feedbacks, recent works, in particular analyses by Dessler [2008, 2010], have demonstrated their usefulness in assessing global water vapor and cloud feedbacks. First, we create AIRS-observed monthly anomaly time-series (ATs) of outgoing longwave radiation, water vapor, clouds and temperature profile over a 10-year long (Sept. 2002 through Aug. 2012) period using 1x1 degree resolution (a common GCM grid-scale). Next, we evaluate the interrelationships of ATs of the above parameters with the corresponding 1x1 degree, as well as global surface temperature ATs. The latter provides insight comparable with more traditional climate feedback definitions (e. g., Zelinka and Hartmann, 2012) whilst the former is related to a new definition of "local (in surface temperature too) feedback strengths" on a GCM grid-scale. Comparing the correlation maps generated provides valuable new information on the spatial distribution of relative climate feedback strengths. We argue that for GCMs to be trusted for predicting longer-term climate variability, they should be able to reproduce these observed relationships/metrics as closely as possible. For this time period the main climate "forcing" was associated with the El Niño/La Niña variability (e. g., Dessler, 2010), so these assessments may not be descriptive of longer-term climate feedbacks due to global warming, for example. Nevertheless, one should take more confidence of greenhouse warming predictions of those GCMs that reproduce the (high quality observations-based) shorter-term feedback-relationships the best.

Sensitivity of Water Scarcity Events to ENSO-Driven Climate Variability at the Global Scale

NASA Technical Reports Server (NTRS)

Veldkamp, T. I. E.; Eisner, S.; Wada, Y.; Aerts, J. C. J. H.; Ward, P. J.

2015-01-01

Globally, freshwater shortage is one of the most dangerous risks for society. Changing hydro-climatic and socioeconomic conditions have aggravated water scarcity over the past decades. A wide range of studies show that water scarcity will intensify in the future, as a result of both increased consumptive water use and, in some regions, climate change. Although it is well-known that El Niño- Southern Oscillation (ENSO) affects patterns of precipitation and drought at global and regional scales, little attention has yet been paid to the impacts of climate variability on water scarcity conditions, despite its importance for adaptation planning. Therefore, we present the first global-scale sensitivity assessment of water scarcity to ENSO, the most dominant signal of climate variability. We show that over the time period 1961-2010, both water availability and water scarcity conditions are significantly correlated with ENSO-driven climate variability over a large proportion of the global land area (> 28.1 %); an area inhabited by more than 31.4% of the global population. We also found, however, that climate variability alone is often not enough to trigger the actual incidence of water scarcity events. The sensitivity of a region to water scarcity events, expressed in terms of land area or population exposed, is determined by both hydro-climatic and socioeconomic conditions. Currently, the population actually impacted by water scarcity events consists of 39.6% (CTA: consumption-to-availability ratio) and 41.1% (WCI: water crowding index) of the global population, whilst only 11.4% (CTA) and 15.9% (WCI) of the global population is at the same time living in areas sensitive to ENSO-driven climate variability. These results are contrasted, however, by differences in growth rates found under changing socioeconomic conditions, which are relatively high in regions exposed to water scarcity events. Given the correlations found between ENSO and water availability and scarcity conditions, and the relative developments of water scarcity impacts under changing socioeconomic conditions, we suggest that there is potential for ENSO-based adaptation and risk reduction that could be facilitated by more research on this emerging topic.

Forecasting climate change impacts on plant populations over large spatial extents

DOE PAGES

Tredennick, Andrew T.; Hooten, Mevin B.; Aldridge, Cameron L.; ...

2016-10-24

Plant population models are powerful tools for predicting climate change impacts in one location, but are difficult to apply at landscape scales. Here, we overcome this limitation by taking advantage of two recent advances: remotely sensed, species-specific estimates of plant cover and statistical models developed for spatiotemporal dynamics of animal populations. Using computationally efficient model reparameterizations, we fit a spatiotemporal population model to a 28-year time series of sagebrush (Artemisia spp.) percent cover over a 2.5 × 5 km landscape in southwestern Wyoming while formally accounting for spatial autocorrelation. We include interannual variation in precipitation and temperature as covariates inmore » the model to investigate how climate affects the cover of sagebrush. We then use the model to forecast the future abundance of sagebrush at the landscape scale under projected climate change, generating spatially explicit estimates of sagebrush population trajectories that have, until now, been impossible to produce at this scale. Our broadscale and long-term predictions are rooted in small-scale and short-term population dynamics and provide an alternative to predictions offered by species distribution models that do not include population dynamics. Finally, our approach, which combines several existing techniques in a novel way, demonstrates the use of remote sensing data to model population responses to environmental change that play out at spatial scales far greater than the traditional field study plot.« less

Forecasting climate change impacts on plant populations over large spatial extents

DOE Office of Scientific and Technical Information (OSTI.GOV)

Tredennick, Andrew T.; Hooten, Mevin B.; Aldridge, Cameron L.

Plant population models are powerful tools for predicting climate change impacts in one location, but are difficult to apply at landscape scales. Here, we overcome this limitation by taking advantage of two recent advances: remotely sensed, species-specific estimates of plant cover and statistical models developed for spatiotemporal dynamics of animal populations. Using computationally efficient model reparameterizations, we fit a spatiotemporal population model to a 28-year time series of sagebrush (Artemisia spp.) percent cover over a 2.5 × 5 km landscape in southwestern Wyoming while formally accounting for spatial autocorrelation. We include interannual variation in precipitation and temperature as covariates inmore » the model to investigate how climate affects the cover of sagebrush. We then use the model to forecast the future abundance of sagebrush at the landscape scale under projected climate change, generating spatially explicit estimates of sagebrush population trajectories that have, until now, been impossible to produce at this scale. Our broadscale and long-term predictions are rooted in small-scale and short-term population dynamics and provide an alternative to predictions offered by species distribution models that do not include population dynamics. Finally, our approach, which combines several existing techniques in a novel way, demonstrates the use of remote sensing data to model population responses to environmental change that play out at spatial scales far greater than the traditional field study plot.« less

Forecasting climate change impacts on plant populations over large spatial extents

USGS Publications Warehouse

Tredennick, Andrew T.; Hooten, Mevin B.; Aldridge, Cameron L.; Homer, Collin G.; Kleinhesselink, Andrew R.; Adler, Peter B.

2016-01-01

Plant population models are powerful tools for predicting climate change impacts in one location, but are difficult to apply at landscape scales. We overcome this limitation by taking advantage of two recent advances: remotely sensed, species-specific estimates of plant cover and statistical models developed for spatiotemporal dynamics of animal populations. Using computationally efficient model reparameterizations, we fit a spatiotemporal population model to a 28-year time series of sagebrush (Artemisia spp.) percent cover over a 2.5 × 5 km landscape in southwestern Wyoming while formally accounting for spatial autocorrelation. We include interannual variation in precipitation and temperature as covariates in the model to investigate how climate affects the cover of sagebrush. We then use the model to forecast the future abundance of sagebrush at the landscape scale under projected climate change, generating spatially explicit estimates of sagebrush population trajectories that have, until now, been impossible to produce at this scale. Our broadscale and long-term predictions are rooted in small-scale and short-term population dynamics and provide an alternative to predictions offered by species distribution models that do not include population dynamics. Our approach, which combines several existing techniques in a novel way, demonstrates the use of remote sensing data to model population responses to environmental change that play out at spatial scales far greater than the traditional field study plot.

National database for calculating fuel available to wildfires

Treesearch

Donald McKenzie; Nancy H.F. French; Roger D. Ottmar

2012-01-01

Wildfires are increasingly emerging as an important component of Earth system models, particularly those that involve emissions from fires and their effects on climate. Currently, there are few resources available for estimating emissions from wildfires in real time, at subcontinental scales, in a spatially consistent manner. Developing subcontinental-scale databases...

A New Look at Big History

ERIC Educational Resources Information Center

Hawkey, Kate

2014-01-01

The article sets out a "big history" which resonates with the priorities of our own time. A globalizing world calls for new spacial scales to underpin what the history curriculum addresses, "big history" calls for new temporal scales, while concern over climate change calls for a new look at subject boundaries. The article…

Influences of large- and regional-scale climate on fish recruitment in the Skagerrak-Kattegat over the last century

NASA Astrophysics Data System (ADS)

Linderholm, Hans W.; Cardinale, Massimiliano; Bartolino, Valerio; Chen, Deliang; Ou, Tinghai; Svedäng, Henrik

2014-06-01

Dynamics of commercial fish stocks are generally associated with fishing pressure and climate variability. Due to short time series, past studies of the relationships between fish stock dynamics and climate have mainly been restricted to the last few decades. Here we analyzed a century-long time series of plaice, cod and haddock from the Skagerrak-Kattegat, to assess the long-term influence of climate on recruitment. Recruitment success (RS) was compared against sea-surface temperature (SST) and atmospheric circulation indices on large (North Atlantic) and regional (Skagerrak-Kattegat) scales. Our results show that the influence of climate on RS was more pronounced on longer, than on shorter timescales. Over the century-long period, a shift from low to high climate sensitivity was seen from the early to the late part for plaice and cod, while the opposite was found for haddock. This shift suggests that the increasing fishing pressure and the climate change in the Skagerrak-Kattegat have resulted in an increased sensitivity of RS to climate for plaice and cod. The diminishing of climate sensitivity in haddock RS, on the other hand, may be linked to the early twentieth century collapse of the stock in the region. While no long-term relationship between RS and the Atlantic Multidecadal Oscillation (AMO) could be found, large RS fluctuations during the positive phase of the AMO (1935-1960), relative to the cold phases, suggests a changed pattern in recruitment during warm periods. On the other hand, this could be due to the increased fishing pressure in the area. Thus, reported correlations between climate and fish may be caused by strong trends in climate in the late-twentieth century, and coincident reduction in fish stocks caused by intense fishing, rather than a stable relationship between climate and fish recruitment per se.

Synchrony between reanalysis-driven RCM simulations and observations: variation with time scale

NASA Astrophysics Data System (ADS)

de Elía, Ramón; Laprise, René; Biner, Sébastien; Merleau, James

2017-04-01

Unlike coupled global climate models (CGCMs) that run in a stand-alone mode, nested regional climate models (RCMs) are driven by either a CGCM or a reanalysis dataset. This feature makes high correlations between the RCM simulation and its driver possible. When the driving dataset is a reanalysis, time correlations between RCM output and observations are also common and to be expected. In certain situations time correlation between driver and driven RCM is of particular interest and techniques have been developed to increase it (e.g. large-scale spectral nudging). For such cases, a question that remains open is whether aggregating in time increases the correlation between RCM output and observations. That is, although the RCM may be unable to reproduce a given daily event, whether it will still be able to satisfactorily simulate an anomaly on a monthly or annual basis. This is a preconception that the authors of this work and others in the community have held, perhaps as a natural extension of the properties of upscaling or aggregating other statistics such as the mean squared error. Here we explore analytically four particular cases that help us partially answer this question. In addition, we use observations datasets and RCM-simulated data to illustrate our findings. Results indicate that time upscaling does not necessarily increase time correlations, and that those interested in achieving high monthly or annual time correlations between RCM output and observations may have to do so by increasing correlation as much as possible at the shortest time scale. This may indicate that even when only concerned with time correlations at large temporal scale, large-scale spectral nudging acting at the time-step level may have to be used.

The scaling law of climate change and its relevance to assessing (palaeo)biological responses

NASA Astrophysics Data System (ADS)

Kiessling, Wolfgang; Eichenseer, Kilian

2014-05-01

It is often argued that current rates of climate change are unprecedented in the geological past. At the same time, the magnitudes of change were often much greater in deep time than they are in history. The most severe global warming in the Phanerozoic, with dramatic consequences for life, probably occurred across the Permian-Triassic (P-T) boundary when an increase of tropical water temperatures of 15° C has been observed to occur over a timespan 0.8 myr (Sun et al. 2012), whereas global ocean warming over the last 50 years was 0.35° C (Burrows et al. 2011). When transforming these data into rates of change the P-T rate was roughly 370 times smaller than the current rate. We argue that the smaller rates of change inferred from geological proxy records are due to a scaling effect, that is, rates of climate change generally decrease with timespan of observation. We compiled from the published literature data on measured or inferred temperature changes and the timespans over which these changes were assessed. Our compilation currently comprises 120 values and covers timespans from 20 to 107 years. A log-log plot of timespan versus rate of temperature change depicts a highly significant correlation (r2 = 0.95) of a power-law relationship with an exponent of -0.87. Warming trends show a slightly lower exponent (-0.84) than cooling trends (-0.89) but the explained variance is better for the scaling of warming trends. Importantly, the scaled warming trend across the P-T boundary is higher than the current rates of warming. Similar scaling effects are well explored for sediment accumulation rates (Sadler 1981) and evolutionary rates (Gingerich 1993). These have been interpreted as being due to breaks in sedimentation and periods of stasis or transient reversals, respectively. In case of climate change, transient reversals in general trends are the most likely explanation for the scaling relationship. Even relatively rapid intervals of warming, such as the Pleistocene interglacials, are not monotonic, but punctuated by short-term cooling intervals. The fossil record tells us that biodiversity responded dramatically to ancient intervals of climate warming. We can now see that the apparently slower rates of change in some mass extinctions (Permian-Triassic, Triassic-Jurassic) were greater than today when the scaling law is considered. This reassures us that studying deep time patterns of organismic response to climate change is a worthwhile endeavor that is relevant for predicting the future. References Burrows, M. T., Schoeman, D. S., Buckley, L. B., Moore, P., Poloczanska, E. S., Brander, K. M., Brown, C., Bruno, J. F., Duarte, C. M., Halpern, B. S., Holding, J., Kappel, C. V., Kiessling, W., O'Connor, M. I., Pandolfi, J. M., Parmesan, C., Schwing, F. B., Sydeman, W. J., and Richardson, A. J.: The pace of shifting climate in marine and terrestrial ecosystems, Science, 334, 652-655, 2011. Gingerich, P. D.: Quantification and comparison of evolutionary rates, American Journal of Science, 293A, 453-478, 1993. Sadler, P. M.: Sediment accumulation rates and the completeness of stratigraphic sections, Journal of Geology, 89, 569-584, 1981. Sun, Y., Joachimski, M. M., Wignall, P. B., Yan, C., Chen, Y., Jiang, H., Wang, L., and Lai, X.: Lethally hot temperatures during the Early Triassic greenhouse, Science, 338, 366-370, 2012.

Climate, Water, and Human Health: Large Scale Hydroclimatic Controls in Forecasting Cholera Epidemics

NASA Astrophysics Data System (ADS)

Akanda, A. S.; Jutla, A. S.; Islam, S.

2009-12-01

Despite ravaging the continents through seven global pandemics in past centuries, the seasonal and interannual variability of cholera outbreaks remain a mystery. Previous studies have focused on the role of various environmental and climatic factors, but provided little or no predictive capability. Recent findings suggest a more prominent role of large scale hydroclimatic extremes - droughts and floods - and attempt to explain the seasonality and the unique dual cholera peaks in the Bengal Delta region of South Asia. We investigate the seasonal and interannual nature of cholera epidemiology in three geographically distinct locations within the region to identify the larger scale hydroclimatic controls that can set the ecological and environmental ‘stage’ for outbreaks and have significant memory on a seasonal scale. Here we show that two distinctly different, pre and post monsoon, cholera transmission mechanisms related to large scale climatic controls prevail in the region. An implication of our findings is that extreme climatic events such as prolonged droughts, record floods, and major cyclones may cause major disruption in the ecosystem and trigger large epidemics. We postulate that a quantitative understanding of the large-scale hydroclimatic controls and dominant processes with significant system memory will form the basis for forecasting such epidemic outbreaks. A multivariate regression method using these predictor variables to develop probabilistic forecasts of cholera outbreaks will be explored. Forecasts from such a system with a seasonal lead-time are likely to have measurable impact on early cholera detection and prevention efforts in endemic regions.

Climate information for the wind energy industry in the Mediterranean Region

NASA Astrophysics Data System (ADS)

Calmanti, Sandro; Davis, Melanie; Schmidt, Peter; Dell'Aquila, Alessandro

2013-04-01

According to the World Wind Energy Association the total wind generation capacity worldwide has come close to cover 3% of the world's electricity demand in 2011. Thanks to the enormous resource potential and the relatively low costs of construction and maintenance of wind power plants, the wind energy sector will remain one of the most attractive renewable energy investment options. Studies reveal that climate variability and change pose a new challenge to the entire renewable energy sector, and in particular for wind energy. Stakeholders in the wind energy sector mainly use, if available, site-specific historical climate information to assess wind resources at a given project site. So far, this is the only source of information that investors (e.g., banks) are keen to accept for decisions concerning the financing of wind energy projects. However, one possible wind energy risk at the seasonal scale is the volatility of earnings from year to year investment. The most significant risk is therefore that not enough units of energy (or megawatt hours) can be generated from the project to capture energy sales to pay down debt in any given quarter or year. On the longer time scale the risk is that a project's energy yields fall short of their estimated levels, resulting in revenues that consistently come in below their projection, over the life of the project. The nature of the risk exposure determines considerable interest in wind scenarios, as a potential component of both the planning and operational phase of a renewable energy project. Fundamentally, by using climate projections, the assumption of stationary wind regimes can be compared to other scenarios where large scale changes in atmospheric circulation patterns may affect local wind regimes. In the framework of CLIM-RUN EU FP7 project, climate experts are exploring the potential of seasonal to decadal climate forecast techniques (time-frame 2012-2040) and regional climate scenarios (time horizon 2040+) over the Mediterranean Region as a tool for assessing the impact of changes in climate patterns on the energy output of wind power plants. Subsequently, we will give here a brief overview of these techniques as well as first results related to wind projections for different sites across the Mediterranean Region. We will highlight that regional climate models have a large potential for enhancing the quality of climate projections in the presence of complex orography and in the proximity of coastal areas.

Water and carbon fluxes in rain fed agricultural sites under a changing climate: The role of stomata

NASA Astrophysics Data System (ADS)

Hosseini, A.; Gayler, S.; Streck, T.; Katul, G. G.

2014-12-01

Vegetation models are needed to assess how crop productivity may be altered due to variations in climatic conditions. Stomatal conductance controls both diffusion of CO2 from the atmosphere into the leaf and water losses from the soil-plant system to the atmosphere through transpiration (E). Despite its significance, stomatal conductance and its links to climatic variables remains empirically specified in current crop models thereby challenging their application to future climatic conditions. It has long been conjectured that stomata has evolved so as to allow terrestrial plants to assimilate CO2 in a desiccating atmosphere while minimizing water losses. Hence, the hypothesis that stomata adapt optimally to their environment so as to maximize assimilation (A) for a given amount of water loss has received significant attention over the past 4 decades. Here, a new approach to implement optimization theory of stomatal conductance into a dynamic canopy gas exchange model is introduced. A key variable in this theory is the so-called marginal water use efficiency (MWUE), which is assumed to be constant on time scales commensurate with fluctuations in stomatal aperture. However, on time scales relevant to crop productivity (daily to seasonal), the boundary conditions on the optimization problem evolve in time prompting the question of how to assign MWUE on such time scales. To address this question, MWUE was formulated as a function of time-integrated leaf-water potential and atmospheric CO2. Next, leaf water potential was linked to root and soil pressure using a soil water balance model based on a modified Richards' equation that considers vertical distribution of root water uptake. The adequacy of the new approach was tested by comparing predicted diurnal cycles of A and E as well as variability of soil moisture with long-term observations at a winter wheat (Triticum aestivum cv.Cubus) field in southwest Germany (see Figure), where transpiration and assimilation rates were derived from eddy-covariance measurements of latent heat flux and net ecosystem exchange. To place those results in the broader context of climate change and food security issues, a sensitivity analyses on water and carbon fluxes with respect to climatic variables, soil texture, and root-density distribution is also presented.

Climate Risk and Vulnerability in the Caribbean and Gulf of Mexico Region: Interactions with Spatial Population and Land Cover Change

NASA Astrophysics Data System (ADS)

Chen, R. S.; Levy, M.; Baptista, S.; Adamo, S.

2010-12-01

Vulnerability to climate variability and change will depend on dynamic interactions between different aspects of climate, land-use change, and socioeconomic trends. Measurements and projections of these changes are difficult at the local scale but necessary for effective planning. New data sources and methods make it possible to assess land-use and socioeconomic changes that may affect future patterns of climate vulnerability. In this paper we report on new time series data sets that reveal trends in the spatial patterns of climate vulnerability in the Caribbean/Gulf of Mexico Region. Specifically, we examine spatial time series data for human population over the period 1990-2000, time series data on land use and land cover over 2000-2009, and infant mortality rates as a proxy for poverty for 2000-2008. We compare the spatial trends for these measures to the distribution of climate-related natural disaster risk hotspots (cyclones, floods, landslides, and droughts) in terms of frequency, mortality, and economic losses. We use these data to identify areas where climate vulnerability appears to be increasing and where it may be decreasing. Regions where trends and patterns are especially worrisome include coastal areas of Guatemala and Honduras.

Multi-time scale Climate Informed Stochastic Hybrid Simulation-Optimization Model (McISH model) for Multi-Purpose Reservoir System

NASA Astrophysics Data System (ADS)

Lu, M.; Lall, U.

2013-12-01

In order to mitigate the impacts of climate change, proactive management strategies to operate reservoirs and dams are needed. A multi-time scale climate informed stochastic model is developed to optimize the operations for a multi-purpose single reservoir by simulating decadal, interannual, seasonal and sub-seasonal variability. We apply the model to a setting motivated by the largest multi-purpose dam in N. India, the Bhakhra reservoir on the Sutlej River, a tributary of the Indus. This leads to a focus on timing and amplitude of the flows for the monsoon and snowmelt periods. The flow simulations are constrained by multiple sources of historical data and GCM future projections, that are being developed through a NSF funded project titled 'Decadal Prediction and Stochastic Simulation of Hydroclimate Over Monsoon Asia'. The model presented is a multilevel, nonlinear programming model that aims to optimize the reservoir operating policy on a decadal horizon and the operation strategy on an updated annual basis. The model is hierarchical, in terms of having a structure that two optimization models designated for different time scales are nested as a matryoshka doll. The two optimization models have similar mathematical formulations with some modifications to meet the constraints within that time frame. The first level of the model is designated to provide optimization solution for policy makers to determine contracted annual releases to different uses with a prescribed reliability; the second level is a within-the-period (e.g., year) operation optimization scheme that allocates the contracted annual releases on a subperiod (e.g. monthly) basis, with additional benefit for extra release and penalty for failure. The model maximizes the net benefit of irrigation, hydropower generation and flood control in each of the periods. The model design thus facilitates the consistent application of weather and climate forecasts to improve operations of reservoir systems. The decadal flow simulations are re-initialized every year with updated climate projections to improve the reliability of the operation rules for the next year, within which the seasonal operation strategies are nested. The multi-level structure can be repeated for monthly operation with weekly subperiods to take advantage of evolving weather forecasts and seasonal climate forecasts. As a result of the hierarchical structure, sub-seasonal even weather time scale updates and adjustment can be achieved. Given an ensemble of these scenarios, the McISH reservoir simulation-optimization model is able to derive the desired reservoir storage levels, including minimum and maximum, as a function of calendar date, and the associated release patterns. The multi-time scale approach allows adaptive management of water supplies acknowledging the changing risks, meeting both the objectives over the decade in expected value and controlling the near term and planning period risk through probabilistic reliability constraints. For the applications presented, the target season is the monsoon season from June to September. The model also includes a monthly flood volume forecast model, based on a Copula density fit to the monthly flow and the flood volume flow. This is used to guide dynamic allocation of the flood control volume given the forecasts.

Spatial climate patterns explain negligible variation in strength of compensatory density feedbacks in birds and mammals.

PubMed

Herrando-Pérez, Salvador; Delean, Steven; Brook, Barry W; Cassey, Phillip; Bradshaw, Corey J A

2014-01-01

The use of long-term population data to separate the demographic role of climate from density-modified demographic processes has become a major topic of ecological investigation over the last two decades. Although the ecological and evolutionary mechanisms that determine the strength of density feedbacks are now well understood, the degree to which climate gradients shape those processes across taxa and broad spatial scales remains unclear. Intuitively, harsh or highly variable environmental conditions should weaken compensatory density feedbacks because populations are hypothetically unable to achieve or maintain densities at which social and trophic interactions (e.g., competition, parasitism, predation, disease) might systematically reduce population growth. Here we investigate variation in the strength of compensatory density feedback, from long-term time series of abundance over 146 species of birds and mammals, in response to spatial gradients of broad-scale temperature precipitation variables covering 97 localities in 28 countries. We use information-theoretic metrics to rank phylogenetic generalized least-squares regression models that control for sample size (time-series length) and phylogenetic non-independence. Climatic factors explained < 1% of the remaining variation in density-feedback strength across species, with the highest non-control, model-averaged effect sizes related to extreme precipitation variables. We could not link our results directly to other published studies, because ecologists use contrasting responses, predictors and statistical approaches to correlate density feedback and climate--at the expense of comparability in a macroecological context. Censuses of multiple populations within a given species, and a priori knowledge of the spatial scales at which density feedbacks interact with climate, seem to be necessary to determine cross-taxa variation in this phenomenon. Despite the availability of robust modelling tools, the appropriate data have not yet been gathered for most species, meaning that we cannot yet make any robust generalisations about how demographic feedbacks interact with climate.

Spatial Climate Patterns Explain Negligible Variation in Strength of Compensatory Density Feedbacks in Birds and Mammals

PubMed Central

Herrando-Pérez, Salvador; Delean, Steven; Brook, Barry W.; Cassey, Phillip; Bradshaw, Corey J. A.

2014-01-01

The use of long-term population data to separate the demographic role of climate from density-modified demographic processes has become a major topic of ecological investigation over the last two decades. Although the ecological and evolutionary mechanisms that determine the strength of density feedbacks are now well understood, the degree to which climate gradients shape those processes across taxa and broad spatial scales remains unclear. Intuitively, harsh or highly variable environmental conditions should weaken compensatory density feedbacks because populations are hypothetically unable to achieve or maintain densities at which social and trophic interactions (e.g., competition, parasitism, predation, disease) might systematically reduce population growth. Here we investigate variation in the strength of compensatory density feedback, from long-term time series of abundance over 146 species of birds and mammals, in response to spatial gradients of broad-scale temperature precipitation variables covering 97 localities in 28 countries. We use information-theoretic metrics to rank phylogenetic generalized least-squares regression models that control for sample size (time-series length) and phylogenetic non-independence. Climatic factors explained < 1% of the remaining variation in density-feedback strength across species, with the highest non-control, model-averaged effect sizes related to extreme precipitation variables. We could not link our results directly to other published studies, because ecologists use contrasting responses, predictors and statistical approaches to correlate density feedback and climate – at the expense of comparability in a macroecological context. Censuses of multiple populations within a given species, and a priori knowledge of the spatial scales at which density feedbacks interact with climate, seem to be necessary to determine cross-taxa variation in this phenomenon. Despite the availability of robust modelling tools, the appropriate data have not yet been gathered for most species, meaning that we cannot yet make any robust generalisations about how demographic feedbacks interact with climate. PMID:24618822

A framework to assess the impacts of climate change on stream health indicators in Michigan watersheds

NASA Astrophysics Data System (ADS)

Woznicki, S. A.; Nejadhashemi, A. P.; Tang, Y.; Wang, L.

2016-12-01

Climate change is projected to alter watershed hydrology and potentially amplify nonpoint source pollution transport. These changes have implications for fish and macroinvertebrates, which are often used as measures of aquatic ecosystem health. By quantifying the risk of adverse impacts to aquatic ecosystem health at the reach-scale, watershed climate change adaptation strategies can be developed and prioritized. The objective of this research was to quantify the impacts of climate change on stream health in seven Michigan watersheds. A process-based watershed model, the Soil and Water Assessment Tool (SWAT), was linked to adaptive neuro-fuzzy inferenced (ANFIS) stream health models. SWAT models were used to simulate reach-scale flow regime (magnitude, frequency, timing, duration, and rate of change) and water quality variables. The ANFIS models were developed based on relationships between the in-stream variables and sampling points of four stream health indicators: the fish index of biotic integrity (IBI), macroinvertebrate family index of biotic integrity (FIBI), Hilsenhoff biotic index (HBI), and number of Ephemeroptera, Plecoptera, and Trichoptera (EPT) taxa. The combined SWAT-ANFIS models extended stream health predictions to all watershed reaches. A climate model ensemble from the Coupled Model Intercomparison Project Phase 5 (CMIP5) was used to develop projections of changes to flow regime (using SWAT) and stream health indicators (using ANFIS) from a baseline of 1980-2000 to 2020-2040. Flow regime variables representing variability, duration of extreme events, and timing of low and high flow events were sensitive to changes in climate. The stream health indicators were relatively insensitive to changing climate at the watershed scale. However, there were many instances of individual reaches that were projected to experience declines in stream health. Using the probability of stream health decline coupled with the magnitude of the decline, maps of vulnerable stream ecosystems were developed, which can be used in the watershed management decision-making process.

A new climate modeling framework for convection-resolving simulation at continental scale

NASA Astrophysics Data System (ADS)

Charpilloz, Christophe; di Girolamo, Salvatore; Arteaga, Andrea; Fuhrer, Oliver; Hoefler, Torsten; Schulthess, Thomas; Schär, Christoph

2017-04-01

Major uncertainties remain in our understanding of the processes that govern the water cycle in a changing climate and their representation in weather and climate models. Of particular concern are heavy precipitation events of convective origin (thunderstorms and rain showers). The aim of the crCLIM project [1] is to propose a new climate modeling framework that alleviates the I/O-bottleneck in large-scale, convection-resolving climate simulations and thus to enable new analysis techniques for climate scientists. Due to the large computational costs, convection-resolving simulations are currently restricted to small computational domains or very short time scales, unless the largest available supercomputers system such as hybrid CPU-GPU architectures are used [3]. Hence, the COSMO model has been adapted to run on these architectures for research and production purposes [2]. However, the amount of generated data also increases and storing this data becomes infeasible making the analysis of simulations results impractical. To circumvent this problem and enable high-resolution models in climate we propose a data-virtualization layer (DVL) that re-runs simulations on demand and transparently manages the data for the analysis, that means we trade off computational effort (time) for storage (space). This approach also requires a bit-reproducible version of the COSMO model that produces identical results on different architectures (CPUs and GPUs) [4] that will be coupled with a performance model in order enable optimal re-runs depending on requirements of the re-run and available resources. In this contribution, we discuss the strategy to develop the DVL, a first performance model, the challenge of bit-reproducibility and the first results of the crCLIM project. [1] http://www.c2sm.ethz.ch/research/crCLIM.html [2] O. Fuhrer, C. Osuna, X. Lapillonne, T. Gysi, M. Bianco, and T. Schulthess. "Towards gpu-accelerated operational weather forecasting." In The GPU Technology Conference, GTC. 2013. [3] D. Leutwyler, O. Fuhrer, X. Lapillonne, D. Lüthi, and C. Schär. "Towards European-scale convection-resolving climate simulations with GPUs: a study with COSMO 4.19." Geoscientific Model Development 9, no. 9 (2016): 3393. [4] A. Arteaga, O. Fuhrer, and T. Hoefler. "Designing bit-reproducible portable high-performance applications." In Parallel and Distributed Processing Symposium, 2014 IEEE 28th International, pp. 1235-1244. IEEE, 2014.

Climate change impacts on risks of groundwater pollution by herbicides: a regional scale assessment

NASA Astrophysics Data System (ADS)

Steffens, Karin; Moeys, Julien; Lindström, Bodil; Kreuger, Jenny; Lewan, Elisabet; Jarvis, Nick

2014-05-01

Groundwater contributes nearly half of the Swedish drinking water supply, which therefore needs to be protected both under present and future climate conditions. Pesticides are sometimes found in Swedish groundwater in concentrations exceeding the EU-drinking water limit and thus constitute a threat. The aim of this study was to assess the present and future risks of groundwater pollution at the regional scale by currently approved herbicides. We identified representative combinations of major crop types and their specific herbicide usage (product, dose and application timing) based on long-term monitoring data from two agricultural catchments in the South-West of Sweden. All these combinations were simulated with the regional version of the pesticide fate model MACRO (called MACRO-SE) for the periods 1970-1999 and 2070-2099 for a major crop production region in South West Sweden. To represent the uncertainty in future climate data, we applied a five-member ensemble based on different climate model projections downscaled with the RCA3-model (Swedish Meteorological and Hydrological Institute). In addition to the direct impacts of changes in the climate, the risks of herbicide leaching in the future will also be affected by likely changes in weed pressure and land use and management practices (e.g. changes in crop rotations and application timings). To assess the relative importance of such factors we performed a preliminary sensitivity analysis which provided us with a hierarchical structure for constructing future herbicide use scenarios for the regional scale model runs. The regional scale analysis gave average concentrations of herbicides leaching to groundwater for a large number of combinations of soils, crops and compounds. The results showed that future scenarios for herbicide use (more autumn-sown crops, more frequent multiple applications on one crop, and a shift from grassland to arable crops such as maize) imply significantly greater risks of herbicide leaching to groundwater in a changing climate, and that these indirect effects outweigh the direct effects of changes in climate driving variables. Due to the large uncertainties in climate change impact assessments, drawing firm conclusions is not possible, but this type of analysis provides indications of likely future concerns and can be used as an early-warning tool to inform the general public, responsible public authorities and decision makers.

Instructional climates in preschool children who are at-risk. Part II: perceived physical competence.

PubMed

Robinson, Leah E; Rudisill, Mary E; Goodway, Jacqueline D

2009-09-01

In Part II of this study, we examined the effect of two 9-week instructional climates (low-autonomy [LA] and mastery motivational climate [MMC]) on perceived physical competence (PPC) in preschoolers (N = 117). Participants were randomly assigned to an LA, MMC, or comparison group. PPC was assessed by a pretest, posttest, and retention test with the Pictorial Scale of Perceived Competence and Social Acceptance. A significant Treatment x Time interaction (p < .001) was present, supporting that MMC participants reported significantly higher PPC scores over time, while no positive changes were present in LA and comparison participants. The results show that an MMC leads to psychological benefits related to achievement motivation. These findings should encourage early childhood educators to consider the effect of instructional climates on children's self-perception.

From climate to global change: Following the footprint of Prof. Duzheng YE's research

NASA Astrophysics Data System (ADS)

Fu, Congbin

2017-10-01

To commemorate 100 years since the birth of Professor Duzheng YE, this paper reviews the contribution of Ye and his research team to the development from climate to global change science in the past 30 or so years, including: (1) the role of climate change in global change; (2) the critical time scales and predictability of global change; (3) the sensitive regions of global change—transitional zones of climate and ecosystems; and (4) orderly human activities and adaptation to global change, with a focus on the development of a proactive strategy for adaptation to such change.

Active Climate Stabilization: Practical Physics-Based Approaches to Prevention of Climate Change

DOE R&D Accomplishments Database

Teller, E.; Hyde, T.; Wood, L.

2002-04-18

We offer a case for active technical management of the radiative forcing of the temperatures of the Earth's fluid envelopes, rather than administrative management of atmospheric greenhouse gas inputs, in order to stabilize both the global- and time-averaged climate and its mesoscale features. We suggest that active management of radiative forcing entails negligible--indeed, likely strongly negative--economic costs and environmental impacts, and thus best complies with the pertinent mandate of the UN Framework Convention on Climate Change. We propose that such approaches be swiftly evaluated in sub-scale in the course of an intensive international program.

Patterns of precipitation: Fine-scale rain dynamics in the South of England

NASA Astrophysics Data System (ADS)

Callaghan, Sarah

2010-05-01

The consensus in the climate change community is that one of the (many) effects of climate change will be that the nature of rain events will change, and in all likelihood, they will become more extreme. Currently, most long-term rain rate data sets are hourly (or longer) rain accumulations, so investigating the rain events that occur for less than 0.01% (52.5 minutes) of a year is not possible. Rain datasets do exist with smaller temporal resolution, but these are either not continuous, or simply have not been in operation long enough to investigate any trends in climate change. The Chilbolton Observatory in the south of England is one of the world's most advanced meteorological radar experimental facilities, and is home to the world's largest fully steerable meteorological radar, the Chilbolton Advanced Meteorological Radar (CAMRa). It also hosts a wide range of meteorological and atmospheric sensing instruments, including cameras, lidars, radiometers and a wide selection of different types of rain gauges. The UK atmospheric science, hydrology and Earth Observation communities use the instruments located at Chilbolton to conduct research in weather, flooding and climate. This often involves observations of meteorological phenomena operating below the current resolution of (forecasting and climate) models and work on their effective parameterisation. The Chilbolton datasets contain a continuous drop counting rain gauge time series at 10 seconds integration time, spanning from January 2001 to the present. Though the length of the time series is not sufficient to confidently identify any effects of climate change, the time resolution is sufficient to investigate the differences in the extreme values of rain events over the nine years of the dataset, characterising the inter-annual and seasonal variability. Changes in the occurrence of different rain events have also been investigated by looking at event and inter-event durations to determine if there is any change in the relative number of stratiform and convective events over the time period. Knowledge of the fine scale variability of rain (both in the spatial and temporal domains) is important for the development of accurate models for small-scale forecasting, as well as models for the implementation and operation of rain affected systems, such as microwave radio communications and flood mitigation. As the rain gauge measurements made at Chilbolton will continue for the foreseeable future, these datasets will become increasingly valuable, as they provide a "ground-truth" that can be compared with the results of climate and other models.

Assessments of Drought Impacts on Vegetation in China with the Optimal Time Scales of the Climatic Drought Index

PubMed Central

Li, Zheng; Zhou, Tao; Zhao, Xiang; Huang, Kaicheng; Gao, Shan; Wu, Hao; Luo, Hui

2015-01-01

Drought is expected to increase in frequency and severity due to global warming, and its impacts on vegetation are typically extensively evaluated with climatic drought indices, such as multi-scalar Standardized Precipitation Evapotranspiration Index (SPEI). We analyzed the covariation between the SPEIs of various time scales and the anomalies of the normalized difference vegetation index (NDVI), from which the vegetation type-related optimal time scales were retrieved. The results indicated that the optimal time scales of needle-leaved forest, broadleaf forest and shrubland were between 10 and 12 months, which were considerably longer than the grassland, meadow and cultivated vegetation ones (2 to 4 months). When the optimal vegetation type-related time scales were used, the SPEI could better reflect the vegetation’s responses to water conditions, with the correlation coefficients between SPEIs and NDVI anomalies increased by 5.88% to 28.4%. We investigated the spatio-temporal characteristics of drought and quantified the different responses of vegetation growth to drought during the growing season (April–October). The results revealed that the frequency of drought has increased in the 21st century with the drying trend occurring in most of China. These results are useful for ecological assessments and adapting management steps to mitigate the impact of drought on vegetation. They are helpful to employ water resources more efficiently and reduce potential damage to human health caused by water shortages. PMID:26184243

The AgMIP GRIDded Crop Modeling Initiative (AgGRID) and the Global Gridded Crop Model Intercomparison (GGCMI)

NASA Technical Reports Server (NTRS)

Elliott, Joshua; Muller, Christoff

2015-01-01

Climate change is a significant risk for agricultural production. Even under optimistic scenarios for climate mitigation action, present-day agricultural areas are likely to face significant increases in temperatures in the coming decades, in addition to changes in precipitation, cloud cover, and the frequency and duration of extreme heat, drought, and flood events (IPCC, 2013). These factors will affect the agricultural system at the global scale by impacting cultivation regimes, prices, trade, and food security (Nelson et al., 2014a). Global-scale evaluation of crop productivity is a major challenge for climate impact and adaptation assessment. Rigorous global assessments that are able to inform planning and policy will benefit from consistent use of models, input data, and assumptions across regions and time that use mutually agreed protocols designed by the modeling community. To ensure this consistency, large-scale assessments are typically performed on uniform spatial grids, with spatial resolution of typically 10 to 50 km, over specified time-periods. Many distinct crop models and model types have been applied on the global scale to assess productivity and climate impacts, often with very different results (Rosenzweig et al., 2014). These models are based to a large extent on field-scale crop process or ecosystems models and they typically require resolved data on weather, environmental, and farm management conditions that are lacking in many regions (Bondeau et al., 2007; Drewniak et al., 2013; Elliott et al., 2014b; Gueneau et al., 2012; Jones et al., 2003; Liu et al., 2007; M¨uller and Robertson, 2014; Van den Hoof et al., 2011;Waha et al., 2012; Xiong et al., 2014). Due to data limitations, the requirements of consistency, and the computational and practical limitations of running models on a large scale, a variety of simplifying assumptions must generally be made regarding prevailing management strategies on the grid scale in both the baseline and future periods. Implementation differences in these and other modeling choices contribute to significant variation among global-scale crop model assessments in addition to differences in crop model implementations that also cause large differences in site-specific crop modeling (Asseng et al., 2013; Bassu et al., 2014).

High resolution fossil fuel combustion CO2 emission fluxes for the United States.

PubMed

Gurney, Kevin R; Mendoza, Daniel L; Zhou, Yuyu; Fischer, Marc L; Miller, Chris C; Geethakumar, Sarath; de la Rue du Can, Stephane

2009-07-15

Quantification of fossil fuel CO2 emissions at fine space and time resolution is emerging as a critical need in carbon cycle and climate change research. As atmospheric CO2 measurements expand with the advent of a dedicated remote sensing platform and denser in situ measurements, the ability to close the carbon budget at spatial scales of approximately 100 km2 and daily time scales requires fossil fuel CO2 inventories at commensurate resolution. Additionally, the growing interest in U.S. climate change policy measures are best served by emissions that are tied to the driving processes in space and time. Here we introduce a high resolution data product (the "Vulcan" inventory: www.purdue.edu/eas/carbon/vulcan/) that has quantified fossil fuel CO2 emissions for the contiguous U.S. at spatial scales less than 100 km2 and temporal scales as small as hours. This data product completed for the year 2002, includes detail on combustion technology and 48 fuel types through all sectors of the U.S. economy. The Vulcan inventory is built from the decades of local/regional air pollution monitoring and complements these data with census, traffic, and digital road data sets. The Vulcan inventory shows excellent agreement with national-level Department of Energy inventories, despite the different approach taken by the DOE to quantify U.S. fossil fuel CO2 emissions. Comparison to the global 1degree x 1 degree fossil fuel CO2 inventory, used widely by the carbon cycle and climate change community prior to the construction of the Vulcan inventory, highlights the space/time biases inherent in the population-based approach.

Exotic ecosystems: where root disease is not a beneficial component of temperate conifer forests

Treesearch

William J. Otrosina

2003-01-01

Forest tree species and ecosystems ahve evolved under climatic, geological, and biological forces over eons of time. The present flora represents the sum of these selective forces that have acted upon ancestral and modern species. Adaptations to climatic factors, soils, insects, diseases, and a host of disturbance events, operating at a variety of scales, ahve forged...

Projected changes in diverse ecosystems from climate warming and biophysical drivers in northwest Alaska

Treesearch

Mark Torre Jorgenson; Bruce G. Marcot; David K. Swanson; Janet C. Jorgenson; Anthony R. DeGange

2015-01-01

Climate warming affects arctic and boreal ecosystems by interacting with numerous biophysical factors across heterogeneous landscapes. To assess potential effects of warming on diverse local-scale ecosystems (ecotypes) across northwest Alaska, we compiled data on historical areal changes over the last 25–50 years. Based on historical rates of change relative to time...

Diversification of land plants: insights from a family-level phylogenetic analysis

PubMed Central

2011-01-01

Background Some of the evolutionary history of land plants has been documented based on the fossil record and a few broad-scale phylogenetic analyses, especially focusing on angiosperms and ferns. Here, we reconstructed phylogenetic relationships among all 706 families of land plants using molecular data. We dated the phylogeny using multiple fossils and a molecular clock technique. Applying various tests of diversification that take into account topology, branch length, numbers of extant species as well as extinction, we evaluated diversification rates through time. We also compared these diversification profiles against the distribution of the climate modes of the Phanerozoic. Results We found evidence for the radiations of ferns and mosses in the shadow of angiosperms coinciding with the rather warm Cretaceous global climate. In contrast, gymnosperms and liverworts show a signature of declining diversification rates during geological time periods of cool global climate. Conclusions This broad-scale phylogenetic analysis helps to reveal the successive waves of diversification that made up the diversity of land plants we see today. Both warm temperatures and wet climate may have been necessary for the rise of the diversity under a successive lineage replacement scenario. PMID:22103931

Role of aerosols on the Indian Summer Monsoon variability, as simulated by state-of-the-art global climate models

NASA Astrophysics Data System (ADS)

Cagnazzo, Chiara; Biondi, Riccardo; D'Errico, Miriam; Cherchi, Annalisa; Fierli, Federico; Lau, William K. M.

2016-04-01

Recent observational and modeling analyses have explored the interaction between aerosols and the Indian summer monsoon precipitation on seasonal-to-interannual time scales. By using global scale climate model simulations, we show that when increased aerosol loading is found on the Himalayas slopes in the premonsoon period (April-May), intensification of early monsoon rainfall over India and increased low-level westerly flow follow, in agreement with the elevated-heat-pump (EHP) mechanism. The increase in rainfall during the early monsoon season has a cooling effect on the land surface that may also be amplified through solar dimming (SD) by more cloudiness and aerosol loading with subsequent reduction in monsoon rainfall over India. We extend this analyses to a subset of CMIP5 climate model simulations. Our results suggest that 1) absorbing aerosols, by influencing the seasonal variability of the Indian summer monsoon with the discussed time-lag, may act as a source of predictability for the Indian Summer Monsoon and 2) if the EHP and SD effects are operating also in a number of state-of-the-art climate models, their inclusion could potentially improve seasonal forecasts.

Topics in geophysical fluid dynamics: Atmospheric dynamics, dynamo theory, and climate dynamics

DOE Office of Scientific and Technical Information (OSTI.GOV)

Ghil, M.; Childress, S.

1987-01-01

This text is the first study to apply systematically the successive bifurcations approach to complex time-dependent processes in large scale atmospheric dynamics, geomagnetism, and theoretical climate dynamics. The presentation of recent results on planetary-scale phenomena in the earth's atmosphere, ocean, cryosphere, mantle and core provides an integral account of mathematical theory and methods together with physical phenomena and processes. The authors address a number of problems in rapidly developing areas of geophysics, bringing into closer contact the modern tools of nonlinear mathematics and the novel problems of global change in the environment.

Learning, climate and the evolution of cultural capacity.

PubMed

Whitehead, Hal

2007-03-21

Patterns of environmental variation influence the utility, and thus evolution, of different learning strategies. I use stochastic, individual-based evolutionary models to assess the relative advantages of 15 different learning strategies (genetic determination, individual learning, vertical social learning, horizontal/oblique social learning, and contingent combinations of these) when competing in variable environments described by 1/f noise. When environmental variation has little effect on fitness, then genetic determinism persists. When environmental variation is large and equal over all time-scales ("white noise") then individual learning is adaptive. Social learning is advantageous in "red noise" environments when variation over long time-scales is large. Climatic variability increases with time-scale, so that short-lived organisms should be able to rely largely on genetic determination. Thermal climates usually are insufficiently red for social learning to be advantageous for species whose fitness is very determined by temperature. In contrast, population trajectories of many species, especially large mammals and aquatic carnivores, are sufficiently red to promote social learning in their predators. The ocean environment is generally redder than that on land. Thus, while individual learning should be adaptive for many longer-lived organisms, social learning will often be found in those dependent on the populations of other species, especially if they are marine. This provides a potential explanation for the evolution of a prevalence of social learning, and culture, in humans and cetaceans.

Spring onset variations and long-term trends from new hemispheric-scale products and remote sensing

NASA Astrophysics Data System (ADS)

Dye, D. G.; Li, X.; Ault, T.; Zurita-Milla, R.; Schwartz, M. D.

2015-12-01

Spring onset is commonly characterized by plant phenophase changes among a variety of biophysical transitions and has important implications for natural and man-managed ecosystems. Here, we present a new integrated analysis of variability in gridded Northern Hemisphere spring onset metrics. We developed a set of hemispheric temperature-based spring indices spanning 1920-2013. As these were derived solely from meteorological data, they are used as a benchmark for isolating the climate system's role in modulating spring "green up" estimated from the annual cycle of normalized difference vegetation index (NDVI). Spatial patterns of interannual variations, teleconnections, and long-term trends were also analyzed in all metrics. At mid-to-high latitudes, all indices exhibit larger variability at interannual to decadal time scales than at spatial scales of a few kilometers. Trends of spring onset vary across space and time. However, compared to long-term trend, interannual to decadal variability generally accounts for a larger portion of the total variance in spring onset timing. Therefore, spring onset trends identified from short existing records may be aliased by decadal climate variations due to their limited temporal depth, even when these records span the entire satellite era. Based on our findings, we also demonstrated that our indices have skill in representing ecosystem-level spring phenology and may have important implications in understanding relationships between phenology, atmosphere dynamics and climate variability.

Large-Scale and Global Hydrology. Chapter 92

NASA Technical Reports Server (NTRS)

Rodell, Matthew; Beaudoing, Hiroko Kato; Koster, Randal; Peters-Lidard, Christa D.; Famiglietti, James S.; Lakshmi, Venkat

2016-01-01

Powered by the sun, water moves continuously between and through Earths oceanic, atmospheric, and terrestrial reservoirs. It enables life, shapes Earths surface, and responds to and influences climate change. Scientists measure various features of the water cycle using a combination of ground, airborne, and space-based observations, and seek to characterize it at multiple scales with the aid of numerical models. Over time our understanding of the water cycle and ability to quantify it have improved, owing to advances in observational capabilities, the extension of the data record, and increases in computing power and storage. Here we present some of the most recent estimates of global and continental ocean basin scale water cycle stocks and fluxes and provide examples of modern numerical modeling systems and reanalyses.Further, we discuss prospects for predicting water cycle variability at seasonal and longer scales, which is complicated by a changing climate and direct human impacts related to water management and agriculture. Changes to the water cycle will be among the most obvious and important facets of climate change, thus it is crucial that we continue to invest in our ability to monitor it.

Toward Robust Climate Baselining: Objective Assessment of Climate Change Using Widely Distributed Miniaturized Sensors for Accurate World-Wide Geophysical Measurements

DOE Office of Scientific and Technical Information (OSTI.GOV)

Teller, E; Leith, C; Canavan, G

A gap-free, world-wide, ocean-, atmosphere-, and land surface-spanning geophysical data-set of three decades time-duration containing the full set of geophysical parameters characterizing global weather is the scientific perquisite for defining the climate; the generally-accepted definition in the meteorological community is that climate is the 30-year running-average of weather. Until such a tridecadal climate base line exists, climate change discussions inevitably will have a semi-speculative, vs. a purely scientific, character, as the baseline against which changes are referenced will be at least somewhat uncertain. The contemporary technology base provides ways-and-means for commencing the development of such a meteorological measurement-intensive climate baseline, moreover with a program budget far less than the {approx}more » $2.5 B/year which the US. currently spends on ''global change'' studies. In particular, the recent advent of satellite-based global telephony enables real-time control of, and data-return from, instrument packages of very modest scale, and Silicon Revolution-based sensor, data-processing and -storage advances permit 'intelligent' data-gathering payloads to be created with 10 gram-scale mass budgets. A geophysical measurement system implemented in such modern technology is a populous constellation 03 long-lived, highly-miniaturized robotic weather stations deployed throughout the weather-generating portions of the Earths atmosphere, throughout its oceans and across its land surfaces. Leveraging the technological advances of the OS, the filly-developed atmospheric weather station of this system has a projected weight of the order of 1 ounce, and contains a satellite telephone, a GPS receiver, a full set of atmospheric sensing instruments and a control computer - and has an operational life of the order of 1 year and a mass-production cost of the order of $$20. Such stations are effectively ''intra-atmospheric satellites'' but likely have serial-production unit costs only about twenty-billionths that of a contemporary NASA global change satellite, whose entirely-remote sensing capabilities they complement with entirely-local sensing. It's thus feasible to deploy millions of them, and thereby to intensively monitor all aspects of the Earths weather. Analogs of these atmospheric weather stations will be employed to provide comparable-quality reporting of oceanic and land-surface geophysical parameters affecting weather. This definitive climate baselining system could be in initial-prototype operation on a one-year time-scale, and in intermediate-scale, proof-of-principle operation within three years, at a total cost of {approx}$$95M. Steady-state operating costs are estimated to be {approx} $$75M/year, or {approx}3% of the current US. ''global change'' program-cost. Its data-return would be of great value very quickly as simply the best weather information, and within a few years as the definitive climatic variability-reporting system. It would become the generator of a definitive climate baseline at a total present-value cost of {approx}$$0.9 B.« less

A seamless global hydrological monitoring and forecasting system for water resources assessment and hydrological hazard early warning

NASA Astrophysics Data System (ADS)

Sheffield, Justin; He, Xiaogang; Wood, Eric; Pan, Ming; Wanders, Niko; Zhan, Wang; Peng, Liqing

2017-04-01

Sustainable management of water resources and mitigation of the impacts of hydrological hazards are becoming ever more important at large scales because of inter-basin, inter-country and inter-continental connections in water dependent sectors. These include water resources management, food production, and energy production, whose needs must be weighed against the water needs of ecosystems and preservation of water resources for future generations. The strains on these connections are likely to increase with climate change and increasing demand from burgeoning populations and rapid development, with potential for conflict over water. At the same time, network connections may provide opportunities to alleviate pressures on water availability through more efficient use of resources such as trade in water dependent goods. A key constraint on understanding, monitoring and identifying solutions to increasing competition for water resources and hazard risk is the availability of hydrological data for monitoring and forecasting water resources and hazards. We present a global online system that provides continuous and consistent water products across time scales, from the historic instrumental period, to real-time monitoring, short-term and seasonal forecasts, and climate change projections. The system is intended to provide data and tools for analysis of historic hydrological variability and trends, water resources assessment, monitoring of evolving hazards and forecasts for early warning, and climate change scale projections of changes in water availability and extreme events. The system is particular useful for scientists and stakeholders interested in regions with less available in-situ data, and where forecasts have the potential to help decision making. The system is built on a database of high-resolution climate data from 1950 to present that merges available observational records with bias-corrected reanalysis and satellite data, which then drives a coupled land surface model-flood inundation model to produce hydrological variables and indices at daily, 0.25-degree resolution, globally. The system is updated in near real-time (< 2 days) using satellite precipitation and weather model data, and produces forecasts at short-term (out to 7 days) based on the Global Forecast System (GFS) and seasonal (up to 6 months) based on U.S. National Multi-Model Ensemble (NMME) seasonal forecasts. Climate change projections are based on bias-corrected and downscaled CMIP5 climate data that is used to force the hydrological model. Example products from the system include real-time and forecast drought indices for precipitation, soil moisture, and streamflow, and flood magnitude and extent indices. The model outputs are complemented by satellite based products and indices based on satellite data for vegetation health (MODIS NDVI) and soil moisture (SMAP). We show examples of the validation of the system at regional scales, including how local information can significantly improve predictions, and examples of how the system can be used to understand large-scale water resource issues, and in real-world contexts for early warning, decision making and planning.

Evidence for the timing of sea-level events during MIS 3

NASA Astrophysics Data System (ADS)

Siddall, M.

2005-12-01

Four large sea-level peaks of millennial-scale duration occur during MIS 3. In addition smaller peaks may exist close to the sensitivity of existing methods to derive sea level during these periods. Millennial-scale changes in temperature during MIS 3 are well documented across much of the planet and are linked in some unknown, yet fundamental way to changes in ice volume / sea level. It is therefore highly likely that the timing of the sea level events during MIS 3 will prove to be a `Rosetta Stone' for understanding millennial scale climate variability. I will review observational and mechanistic arguments for the variation of sea level on Antarctic, Greenland and absolute time scales.

Mesoscale to Synoptic Scale Cloud Variability

NASA Technical Reports Server (NTRS)

Rossow, William B.

1998-01-01

The atmospheric circulation and its interaction with the oceanic circulation involve non-linear and non-local exchanges of energy and water over a very large range of space and time scales. These exchanges are revealed, in part, by the related variations of clouds, which occur on a similar range of scales as the atmospheric motions that produce them. Collection of comprehensive measurements of the properties of the atmosphere, clouds and surface allows for diagnosis of some of these exchanges. The use of a multi-satellite-network approach by the International Satellite Cloud Climatology Project (ISCCP) comes closest to providing complete coverage of the relevant range space and time scales over which the clouds, atmosphere and ocean vary. A nearly 15-yr dataset is now available that covers the range from 3 hr and 30 km to decade and planetary. This paper considers three topics: (1) cloud variations at the smallest scales and how they may influence radiation-cloud interactions, and (2) cloud variations at "moderate" scales and how they may cause natural climate variability, and (3) cloud variations at the largest scales and how they affect the climate. The emphasis in this discussion is on the more mature subject of cloud-radiation interactions. There is now a need to begin similar detailed diagnostic studies of water exchange processes.

Consistent response of bird populations to climate change on two continents

USGS Publications Warehouse

Stephens, Philip A.; Mason, Lucy R.; Green, Rhys E.; Gregory, Richard D.; Sauer, John R.; Alison, Jamie; Aunins, Ainars; Brotons, Lluís; Butchart, Stuart H.M.; Campedelli, Tommaso; Chodkiewicz, Tomasz; Chylarecki, Przemyslaw; Crowe, Olivia; Elts, Jaanus; Escandell, Virginia; Foppen, Ruud P.B.; Heldbjerg, Henning; Herrando, Sergi; Husby, Magne; Jiguet, Frédéric; Lehikoinen, Aleksi; Lindström, Åke; Noble, David G.; Paquet, Jean-Yves; Reif, Jiri; Sattler, Thomas; Szép, Tibor; Teufelbauer, Norbert; Trautmann, Sven; Van Strien, Arco; van Turnhout, Chris A.M.; Vorisek, Petr; Willis, Stephen G.

2016-01-01

Global climate change is a major threat to biodiversity. Large-scale analyses have generally focused on the impacts of climate change on the geographic ranges of species and on phenology, the timing of ecological phenomena. We used long-term monitoring of the abundance of breeding birds across Europe and the United States to produce, for both regions, composite population indices for two groups of species: those for which climate suitability has been either improving or declining since 1980. The ratio of these composite indices, the climate impact indicator (CII), reflects the divergent fates of species favored or disadvantaged by climate change. The trend in CII is positive and similar in the two regions. On both continents, interspecific and spatial variation in population abundance trends are well predicted by climate suitability trends.

Estimates of the long-term U.S. economic impacts of global climate change-induced drought.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Ehlen, Mark Andrew; Loose, Verne W.; Warren, Drake E.

2010-01-01

While climate-change models have done a reasonable job of forecasting changes in global climate conditions over the past decades, recent data indicate that actual climate change may be much more severe. To better understand some of the potential economic impacts of these severe climate changes, Sandia economists estimated the impacts to the U.S. economy of climate change-induced impacts to U.S. precipitation over the 2010 to 2050 time period. The economists developed an impact methodology that converts changes in precipitation and water availability to changes in economic activity, and conducted simulations of economic impacts using a large-scale macroeconomic model of themore » U.S. economy.« less

Integrated approaches to climate–crop modelling: needs and challenges

PubMed Central

A. Betts, Richard

2005-01-01

This paper discusses the need for a more integrated approach to modelling changes in climate and crops, and some of the challenges posed by this. While changes in atmospheric composition are expected to exert an increasing radiative forcing of climate change leading to further warming of global mean temperatures and shifts in precipitation patterns, these are not the only climatic processes which may influence crop production. Changes in the physical characteristics of the land cover may also affect climate; these may arise directly from land use activities and may also result from the large-scale responses of crops to seasonal, interannual and decadal changes in the atmospheric state. Climate models used to drive crop models may, therefore, need to consider changes in the land surface, either as imposed boundary conditions or as feedbacks from an interactive climate–vegetation model. Crops may also respond directly to changes in atmospheric composition, such as the concentrations of carbon dioxide (CO2), ozone (O3) and compounds of sulphur and nitrogen, so crop models should consider these processes as well as climate change. Changes in these, and the responses of the crops, may be intimately linked with meteorological processes so crop and climate models should consider synergies between climate and atmospheric chemistry. Some crop responses may occur at scales too small to significantly influence meteorology, so may not need to be included as feedbacks within climate models. However, the volume of data required to drive the appropriate crop models may be very large, especially if short-time-scale variability is important. Implementation of crop models within climate models would minimize the need to transfer large quantities of data between separate modelling systems. It should also be noted that crop responses to climate change may interact with other impacts of climate change, such as hydrological changes. For example, the availability of water for irrigation may be affected by changes in runoff as a direct consequence of climate change, and may also be affected by climate-related changes in demand for water for other uses. It is, therefore, necessary to consider the interactions between the responses of several impacts sectors to climate change. Overall, there is a strong case for a much closer coupling between models of climate, crops and hydrology, but this in itself poses challenges arising from issues of scale and errors in the models. A strategy is proposed whereby the pursuit of a fully coupled climate–chemistry–crop–hydrology model is paralleled by continued use of separate climate and land surface models but with a focus on consistency between the models. PMID:16433093

Modeling climate change impacts on groundwater resources using transient stochastic climatic scenarios

NASA Astrophysics Data System (ADS)

Goderniaux, Pascal; BrouyèRe, Serge; Blenkinsop, Stephen; Burton, Aidan; Fowler, Hayley J.; Orban, Philippe; Dassargues, Alain

2011-12-01

Several studies have highlighted the potential negative impact of climate change on groundwater reserves, but additional work is required to help water managers plan for future changes. In particular, existing studies provide projections for a stationary climate representative of the end of the century, although information is demanded for the near future. Such time-slice experiments fail to account for the transient nature of climatic changes over the century. Moreover, uncertainty linked to natural climate variability is not explicitly considered in previous studies. In this study we substantially improve upon the state-of-the-art by using a sophisticated transient weather generator in combination with an integrated surface-subsurface hydrological model (Geer basin, Belgium) developed with the finite element modeling software "HydroGeoSphere." This version of the weather generator enables the stochastic generation of large numbers of equiprobable climatic time series, representing transient climate change, and used to assess impacts in a probabilistic way. For the Geer basin, 30 equiprobable climate change scenarios from 2010 to 2085 have been generated for each of six different regional climate models (RCMs). Results show that although the 95% confidence intervals calculated around projected groundwater levels remain large, the climate change signal becomes stronger than that of natural climate variability by 2085. Additionally, the weather generator's ability to simulate transient climate change enabled the assessment of the likely time scale and associated uncertainty of a specific impact, providing managers with additional information when planning further investment. This methodology constitutes a real improvement in the field of groundwater projections under climate change conditions.

The Response of Ice Sheets to Climate Variability

NASA Astrophysics Data System (ADS)

Snow, K.; Goldberg, D. N.; Holland, P. R.; Jordan, J. R.; Arthern, R. J.; Jenkins, A.

2017-12-01

West Antarctic Ice Sheet loss is a significant contributor to sea level rise. While the ice loss is thought to be triggered by fluctuations in oceanic heat at the ice shelf bases, ice sheet response to ocean variability remains poorly understood. Using a synchronously coupled ice-ocean model permitting grounding line migration, this study evaluates the response of an ice sheet to periodic variations in ocean forcing. Resulting oscillations in grounded ice volume amplitude is shown to grow as a nonlinear function of ocean forcing period. This implies that slower oscillations in climatic forcing are disproportionately important to ice sheets. The ice shelf residence time offers a critical time scale, above which the ice response amplitude is a linear function of ocean forcing period and below which it is quadratic. These results highlight the sensitivity of West Antarctic ice streams to perturbations in heat fluxes occurring at decadal time scales.

Landscape controls on the timing of spring, autumn, and growing season length in mid-Atlantic forests

USGS Publications Warehouse

Elmore, A.J.; Guinn, S.M.; Minsley, B.J.; Richardson, A.D.

2012-01-01

The timing of spring leaf development, trajectories of summer leaf area, and the timing of autumn senescence have profound impacts to the water, carbon, and energy balance of ecosystems, and are likely influenced by global climate change. Limited field-based and remote-sensing observations have suggested complex spatial patterns related to geographic features that influence climate. However, much of this variability occurs at spatial scales that inhibit a detailed understanding of even the dominant drivers. Recognizing these limitations, we used nonlinear inverse modeling of medium-resolution remote sensing data, organized by day of year, to explore the influence of climate-related landscape factors on the timing of spring and autumn leaf-area trajectories in mid-Atlantic, USA forests. We also examined the extent to which declining summer greenness (greendown) degrades the precision and accuracy of observations of autumn offset of greenness. Of the dominant drivers of landscape phenology, elevation was the strongest, explaining up to 70% of the spatial variation in the onset of greenness. Urban land cover was second in importance, influencing spring onset and autumn offset to a distance of 32 km from large cities. Distance to tidal water also influenced phenological timing, but only within ~5 km of shorelines. Additionally, we observed that (i) growing season length unexpectedly increases with increasing elevation at elevations below 275 m; (ii) along gradients in urban land cover, timing of autumn offset has a stronger effect on growing season length than does timing of spring onset; and (iii) summer greendown introduces bias and uncertainty into observations of the autumn offset of greenness. These results demonstrate the power of medium grain analyses of landscape-scale phenology for understanding environmental controls on growing season length, and predicting how these might be affected by climate change.

10Be in late deglacial climate simulated by ECHAM5-HAM - Part 2: Isolating the solar signal from 10Be deposition

NASA Astrophysics Data System (ADS)

Heikkilä, U.; Shi, X.; Phipps, S. J.; Smith, A. M.

2013-10-01

This study investigates the effect of deglacial climate on the deposition of the solar proxy 10Be globally, and at two specific locations, the GRIP site at Summit, Central Greenland, and the Law Dome site in coastal Antarctica. The deglacial climate is represented by three 30 yr time slice simulations of 10 000 BP (years before present = 1950 CE), 11 000 BP and 12 000 BP, compared with a preindustrial control simulation. The model used is the ECHAM5-HAM atmospheric aerosol-climate model, driven with sea surface temperatures and sea ice cover simulated using the CSIRO Mk3L coupled climate system model. The focus is on isolating the 10Be production signal, driven by solar variability, from the weather or climate driven noise in the 10Be deposition flux during different stages of climate. The production signal varies on lower frequencies, dominated by the 11yr solar cycle within the 30 yr time scale of these experiments. The climatic noise is of higher frequencies. We first apply empirical orthogonal functions (EOF) analysis to global 10Be deposition on the annual scale and find that the first principal component, consisting of the spatial pattern of mean 10Be deposition and the temporally varying solar signal, explains 64% of the variability. The following principal components are closely related to those of precipitation. Then, we apply ensemble empirical decomposition (EEMD) analysis on the time series of 10Be deposition at GRIP and at Law Dome, which is an effective method for adaptively decomposing the time series into different frequency components. The low frequency components and the long term trend represent production and have reduced noise compared to the entire frequency spectrum of the deposition. The high frequency components represent climate driven noise related to the seasonal cycle of e.g. precipitation and are closely connected to high frequencies of precipitation. These results firstly show that the 10Be atmospheric production signal is preserved in the deposition flux to surface even during climates very different from today's both in global data and at two specific locations. Secondly, noise can be effectively reduced from 10Be deposition data by simply applying the EOF analysis in the case of a reasonably large number of available data sets, or by decomposing the individual data sets to filter out high-frequency fluctuations.

Regime Behavior in Paleo-Reconstructed Streamflow: Attributions to Atmospheric Dynamics, Synoptic Circulation and Large-Scale Climate Teleconnection Patterns

NASA Astrophysics Data System (ADS)

Ravindranath, A.; Devineni, N.

2017-12-01

Studies have shown that streamflow behavior and dynamics have a significant link with climate and climate variability. Patterns of persistent regime behavior from extended streamflow records in many watersheds justify investigating large-scale climate mechanisms as potential drivers of hydrologic regime behavior and streamflow variability. Understanding such streamflow-climate relationships is crucial to forecasting/simulation systems and the planning and management of water resources. In this study, hidden Markov models are used with reconstructed streamflow to detect regime-like behaviors - the hidden states - and state transition phenomena. Individual extreme events and their spatial variability across the basin are then verified with the identified states. Wavelet analysis is performed to examine the signals over time in the streamflow records. Joint analyses of the climatic data in the 20th century and the identified states are undertaken to better understand the hydroclimatic connections within the basin as well as important teleconnections that influence water supply. Compositing techniques are used to identify atmospheric circulation patterns associated with identified states of streamflow. The grouping of such synoptic patterns and their frequency are then examined. Sliding time-window correlation analysis and cross-wavelet spectral analysis are performed to establish the synchronicity of basin flows to the identified synoptic and teleconnection patterns. The Missouri River Basin (MRB) is examined in this study, both as a means of better understanding the synoptic climate controls in this important watershed and as a case study for the techniques developed here. Initial wavelet analyses of reconstructed streamflow at major gauges in the MRB show multidecadal cycles in regime behavior.

Climate Local Information over the Mediterranean to Respond User Needs

NASA Astrophysics Data System (ADS)

Ruti, P.

2012-12-01

CLIM-RUN aims at developing a protocol for applying new methodologies and improved modeling and downscaling tools for the provision of adequate climate information at regional to local scale that is relevant to and usable by different sectors of society (policymakers, industry, cities, etc.). Differently from current approaches, CLIM-RUN will develop a bottom-up protocol directly involving stakeholders early in the process with the aim of identifying well defined needs at the regional to local scale. The improved modeling and downscaling tools will then be used to optimally respond to these specific needs. The protocol is assessed by application to relevant case studies involving interdependent sectors, primarily tourism and energy, and natural hazards (wild fires) for representative target areas (mountainous regions, coastal areas, islands). The region of interest for the project is the Greater Mediterranean area, which is particularly important for two reasons. First, the Mediterranean is a recognized climate change hot-spot, i.e. a region particularly sensitive and vulnerable to global warming. Second, while a number of countries in Central and Northern Europe have already in place well developed climate service networks (e.g. the United Kingdom and Germany), no such network is available in the Mediterranean. CLIM-RUN is thus also intended to provide the seed for the formation of a Mediterranean basin-side climate service network which would eventually converge into a pan-European network. The general time horizon of interest for the project is the future period 2010-2050, a time horizon that encompasses the contributions of both inter-decadal variability and greenhouse-forced climate change. In particular, this time horizon places CLIM-RUN within the context of a new emerging area of research, that of decadal prediction, which will provide a strong potential for novel research.

Accuracy requirements. [for monitoring of climate changes

NASA Technical Reports Server (NTRS)

Delgenio, Anthony

1993-01-01

Satellite and surface measurements, if they are to serve as a climate monitoring system, must be accurate enough to permit detection of changes of climate parameters on decadal time scales. The accuracy requirements are difficult to define a priori since they depend on unknown future changes of climate forcings and feedbacks. As a framework for evaluation of candidate Climsat instruments and orbits, we estimate the accuracies that would be needed to measure changes expected over two decades based on theoretical considerations including GCM simulations and on observational evidence in cases where data are available for rates of change. One major climate forcing known with reasonable accuracy is that caused by the anthropogenic homogeneously mixed greenhouse gases (CO2, CFC's, CH4 and N2O). Their net forcing since the industrial revolution began is about 2 W/sq m and it is presently increasing at a rate of about 1 W/sq m per 20 years. Thus for a competing forcing or feedback to be important, it needs to be of the order of 0.25 W/sq m or larger on this time scale. The significance of most climate feedbacks depends on their sensitivity to temperature change. Therefore we begin with an estimate of decadal temperature change. Presented are the transient temperature trends simulated by the GISS GCM when subjected to various scenarios of trace gas concentration increases. Scenario B, which represents the most plausible near-term emission rates and includes intermittent forcing by volcanic aerosols, yields a global mean surface air temperature increase Delta Ts = 0.7 degrees C over the time period 1995-2015. This is consistent with the IPCC projection of about 0.3 degrees C/decade global warming (IPCC, 1990). Several of our estimates below are based on this assumed rate of warming.

Comment on “Can slow variations in solar luminosity provide missing link between the Sun and climate?”

NASA Astrophysics Data System (ADS)

Douglass, David H.

Peter Foukal (Eos, 3 June 2003) has written an interesting and informative article on solar luminosity and climate. He mentions recent evidence correlating solar activity to climate changes during the last millennium and the last Ice Age and discusses possible mechanisms. He also presents the case for the importance of determining the correlation between solar variation and climate.Foukal's discussion is mainly about “slow variations,” which appears to mean centennial-to-millennial time scales. However, in the “Future Direction” section, he discusses the desirability of the determination of the “climate sensitivity to the small irradiance changes so far observed [1979 to present].”

Changing Climate Drives Lagging and Accelerating Glacier Responses and Accelerating Adjustments of the Hazard Regime

NASA Astrophysics Data System (ADS)

Kargel, Jeffrey

2013-04-01

It is virtually universally recognized among climate and cryospheric scientists that climate and greenhouse gas abundances are closely correlated. Disagreements mainly pertain to the fundamental triggers for large fluctuations in climate and greenhouse gases during the pre-industrial era, and exactly how coupling is achieved amongst the dynamic solid Earth, the Sun, orbital and rotational dynamics, greenhouse gas abundances, and climate. Also unsettled is the climate sensitivity defined as the absolute linkage between the magnitude of climate warming/cooling and greenhouse gas increase/decrease. Important questions concern lagging responses (either greenhouse gases lagging climate fluctuations, or vice versa) and the causes of the lags. In terms of glacier and ice sheet responses to climate change, there also exist several processes causing lagging responses to climate change inputs. The simplest parameterization giving a glacier's lagging response time, τ, is that given by Jóhanneson et al. (1989), modified slightly here as τ = b/h, where b is a measure of ablation rate and h is a measure of glacier thickness. The exact definitions of τ, b, and h are subject to some interpretive license, but for a back-of-the-envelope approximation, we may take b as the magnitude of the mean ablation rate over the whole ablation area, and h as the mean glacier thickness in the glacier ablation zone. τ remains a bit ambiguous but may be considered as an exponential time scale for a decreasing response of b to a climatic step change. For some climate changes, b and h can be taken as the values prior to the climate change, but for large climatic shifts, this parameterization must be iterated. The actual response of a glacier at any time is the sum of exponentially decreasing responses from past changes. (Several aspects of glacier dynamics cause various glacier responses to differ from this idealized glacier-response theory.) Some important details relating to the retreat (or advances) of glaciers due to historic and future anthropogenic and longer term climate change relate to a changing glacier hazard regime. Climate change is connected to changes in the geographic distribution and magnitudes of potentially hazardous glacier lakes, large rock and ice avalanches, ice-dammed rivers, and surges. I shall consider these changes in hazard environment in relation to response-time theory and dynamical divergences from idealized response-time theory. Case histories of certain hazard-prone regions, including developments in fast-response-type glaciers and slow-response glaciers and ice sheets will also be discussed. In short, there will be a strong tendency of the hazard regimes of glacierized regions to shift far more rapidly in the 21st century than they did in the 20th century. The magnitude of the shifts will be more dramatic than any simple linear scaling to climate warming would suggest; this is largely because, due to lagging responses, glaciers are still trying to catch up to a new equilibrium for 20th century climate, while climate change remains a moving target that will drive accelerating glacier responses (including responses in hazard environments) in most glacierized regions.

Reconstructions of solar irradiance on centennial time scales

NASA Astrophysics Data System (ADS)

Krivova, Natalie; Solanki, Sami K.; Dasi Espuig, Maria; Kok Leng, Yeo

Solar irradiance is the main external source of energy to Earth's climate system. The record of direct measurements covering less than 40 years is too short to study solar influence on Earth's climate, which calls for reconstructions of solar irradiance into the past with the help of appropriate models. An obvious requirement to a competitive model is its ability to reproduce observed irradiance changes, and a successful example of such a model is presented by the SATIRE family of models. As most state-of-the-art models, SATIRE assumes that irradiance changes on time scales longer than approximately a day are caused by the evolving distribution of dark and bright magnetic features on the solar surface. The surface coverage by such features as a function of time is derived from solar observations. The choice of these depends on the time scale in question. Most accurate is the version of the model that employs full-disc spatially-resolved solar magnetograms and reproduces over 90% of the measured irradiance variation, including the overall decreasing trend in the total solar irradiance over the last four cycles. Since such magnetograms are only available for about four decades, reconstructions on time scales of centuries have to rely on disc-integrated proxies of solar magnetic activity, such as sunspot areas and numbers. Employing a surface flux transport model and sunspot observations as input, we have being able to produce synthetic magnetograms since 1700. This improves the temporal resolution of the irradiance reconstructions on centennial time scales. The most critical aspect of such reconstructions remains the uncertainty in the magnitude of the secular change.

Novel Flood Detection and Analysis Method Using Recurrence Property

NASA Astrophysics Data System (ADS)

Wendi, Dadiyorto; Merz, Bruno; Marwan, Norbert

2016-04-01

Temporal changes in flood hazard are known to be difficult to detect and attribute due to multiple drivers that include processes that are non-stationary and highly variable. These drivers, such as human-induced climate change, natural climate variability, implementation of flood defence, river training, or land use change, could impact variably on space-time scales and influence or mask each other. Flood time series may show complex behavior that vary at a range of time scales and may cluster in time. This study focuses on the application of recurrence based data analysis techniques (recurrence plot) for understanding and quantifying spatio-temporal changes in flood hazard in Germany. The recurrence plot is known as an effective tool to visualize the dynamics of phase space trajectories i.e. constructed from a time series by using an embedding dimension and a time delay, and it is known to be effective in analyzing non-stationary and non-linear time series. The emphasis will be on the identification of characteristic recurrence properties that could associate typical dynamic behavior to certain flood situations.

Gray Wolves as Climate Change Buffers in Yellowstone

PubMed Central

Getz, Wayne M

2005-01-01

Understanding the mechanisms by which climate and predation patterns by top predators co-vary to affect community structure accrues added importance as humans exert growing influence over both climate and regional predator assemblages. In Yellowstone National Park, winter conditions and reintroduced gray wolves (Canis lupus) together determine the availability of winter carrion on which numerous scavenger species depend for survival and reproduction. As climate changes in Yellowstone, therefore, scavenger species may experience a dramatic reshuffling of food resources. As such, we analyzed 55 y of weather data from Yellowstone in order to determine trends in winter conditions. We found that winters are getting shorter, as measured by the number of days with snow on the ground, due to decreased snowfall and increased number of days with temperatures above freezing. To investigate synergistic effects of human and climatic alterations of species interactions, we used an empirically derived model to show that in the absence of wolves, early snow thaw leads to a substantial reduction in late-winter carrion, causing potential food bottlenecks for scavengers. In addition, by narrowing the window of time over which carrion is available and thereby creating a resource pulse, climate change likely favors scavengers that can quickly track food sources over great distances. Wolves, however, largely mitigate late-winter reduction in carrion due to earlier snow thaws. By buffering the effects of climate change on carrion availability, wolves allow scavengers to adapt to a changing environment over a longer time scale more commensurate with natural processes. This study illustrates the importance of restoring and maintaining intact food chains in the face of large-scale environmental perturbations such as climate change. PMID:15757363

Gray wolves as climate change buffers in Yellowstone.

PubMed

Wilmers, Christopher C; Getz, Wayne M

2005-04-01

Understanding the mechanisms by which climate and predation patterns by top predators co-vary to affect community structure accrues added importance as humans exert growing influence over both climate and regional predator assemblages. In Yellowstone National Park, winter conditions and reintroduced gray wolves (Canis lupus) together determine the availability of winter carrion on which numerous scavenger species depend for survival and reproduction. As climate changes in Yellowstone, therefore, scavenger species may experience a dramatic reshuffling of food resources. As such, we analyzed 55 y of weather data from Yellowstone in order to determine trends in winter conditions. We found that winters are getting shorter, as measured by the number of days with snow on the ground, due to decreased snowfall and increased number of days with temperatures above freezing. To investigate synergistic effects of human and climatic alterations of species interactions, we used an empirically derived model to show that in the absence of wolves, early snow thaw leads to a substantial reduction in late-winter carrion, causing potential food bottlenecks for scavengers. In addition, by narrowing the window of time over which carrion is available and thereby creating a resource pulse, climate change likely favors scavengers that can quickly track food sources over great distances. Wolves, however, largely mitigate late-winter reduction in carrion due to earlier snow thaws. By buffering the effects of climate change on carrion availability, wolves allow scavengers to adapt to a changing environment over a longer time scale more commensurate with natural processes. This study illustrates the importance of restoring and maintaining intact food chains in the face of large-scale environmental perturbations such as climate change.

The susceptibility of large river basins to orogenic and climatic drivers

NASA Astrophysics Data System (ADS)

Haedke, Hanna; Wittmann, Hella; von Blanckenburg, Friedhelm

2017-04-01

Large rivers are known to buffer pulses in sediment production driven by changes in climate as sediment is transported through lowlands. Our new dataset of in situ cosmogenic nuclide concentration and chemical composition of 62 sandy bedload samples from the world largest rivers integrates over 25% of Earth's terrestrial surface, distributed over a variety of climatic zones across all continents, and represents the millennial-scale denudation rate of the sediment's source area. We can show that these denudation rates do not respond to climatic forcing, but faithfully record orogenic forcing, when analyzed with respective variables representing orogeny (strain rate, relief, bouguer anomaly, free-air anomaly), and climate (runoff, temperature, precipitation) and basin properties (floodplain response time, drainage area). In contrast to this orogenic forcing of denudation rates, elemental bedload chemistry from the fine-grained portion of the same samples correlates with climate-related variables (precipitation, runoff) and floodplain response times. It is also well-known from previous compilations of river-gauged sediment loads that the short-term basin-integrated sediment export is also climatically controlled. The chemical composition of detrital sediment shows a climate control that can originate in the rivers source area, but this signal is likely overprinted during transfer through the lowlands because we also find correlation with floodplain response times. At the same time, cosmogenic nuclides robustly preserve the orogenic forcing of the source area denudation signal through of the floodplain buffer. Conversely, previous global compilations of cosmogenic nuclides in small river basins show the preservation of climate drivers in their analysis, but these are buffered in large lowland rivers. Hence, we can confirm the assumption that cosmogenic nuclides in large rivers are poorly susceptible to climate changes, but are at the same time highly suited to detect changes in orogenic forcing in their paleo sedimentary records.

Changes toward earlier streamflow timing across western North America

USGS Publications Warehouse

Stewart, I.T.; Cayan, D.R.; Dettinger, M.D.

2005-01-01

The highly variable timing of streamflow in snowmelt-dominated basins across western North America is an important consequence, and indicator, of climate fluctuations. Changes in the timing of snowmelt-derived streamflow from 1948 to 2002 were investigated in a network of 302 western North America gauges by examining the center of mass for flow, spring pulse onset dates, and seasonal fractional flows through trend and principal component analyses. Statistical analysis of the streamflow timing measures with Pacific climate indicators identified local and key large-scale processes that govern the regionally coherent parts of the changes and their relative importance. Widespread and regionally coherent trends toward earlier onsets of springtime snowmelt and streamflow have taken place across most of western North America, affecting an area that is much larger than previously recognized. These timing changes have resulted in increasing fractions of annual flow occurring earlier in the water year by 1-4 weeks. The immediate (or proximal) forcings for the spatially coherent parts of the year-to-year fluctuations and longer-term trends of streamflow timing have been higher winter and spring temperatures. Although these temperature changes are partly controlled by the decadal-scale Pacific climate mode [Pacific decadal oscillation (PDO)], a separate and significant part of the variance is associated with a springtime warming trend that spans the PDO phases. ?? 2005 American Meteorological Society.

Characterization of the Dynamics of Climate Systems and Identification of Missing Mechanisms Impacting the Long Term Predictive Capabilities of Global Climate Models Utilizing Dynamical Systems Approaches to the Analysis of Observed and Modeled Climate

DOE Office of Scientific and Technical Information (OSTI.GOV)

Bhatt, Uma S.; Wackerbauer, Renate; Polyakov, Igor V.

The goal of this research was to apply fractional and non-linear analysis techniques in order to develop a more complete characterization of climate change and variability for the oceanic, sea ice and atmospheric components of the Earth System. This research applied two measures of dynamical characteristics of time series, the R/S method of calculating the Hurst exponent and Renyi entropy, to observational and modeled climate data in order to evaluate how well climate models capture the long-term dynamics evident in observations. Fractional diffusion analysis was applied to ARGO ocean buoy data to quantify ocean transport. Self organized maps were appliedmore » to North Pacific sea level pressure and analyzed in ways to improve seasonal predictability for Alaska fire weather. This body of research shows that these methods can be used to evaluate climate models and shed light on climate mechanisms (i.e., understanding why something happens). With further research, these methods show promise for improving seasonal to longer time scale forecasts of climate.« less

Broad-scale climate influences on spring-spawning herring (Clupea harengus, L.) recruitment in the Western Baltic Sea.

PubMed

Gröger, Joachim P; Hinrichsen, Hans-Harald; Polte, Patrick

2014-01-01

Climate forcing in complex ecosystems can have profound implications for ecosystem sustainability and may thus challenge a precautionary ecosystem management. Climatic influences documented to affect various ecological functions on a global scale, may themselves be observed on quantitative or qualitative scales including regime shifts in complex marine ecosystems. This study investigates the potential climatic impact on the reproduction success of spring-spawning herring (Clupea harengus) in the Western Baltic Sea (WBSS herring). To test for climate effects on reproduction success, the regionally determined and scientifically well-documented spawning grounds of WBSS herring represent an ideal model system. Climate effects on herring reproduction were investigated using two global indices of atmospheric variability and sea surface temperature, represented by the North Atlantic Oscillation (NAO) and the Atlantic Multi-decadal Oscillation (AMO), respectively, and the Baltic Sea Index (BSI) which is a regional-scale atmospheric index for the Baltic Sea. Moreover, we combined a traditional approach with modern time series analysis based on a recruitment model connecting parental population components with reproduction success. Generalized transfer functions (ARIMAX models) allowed evaluating the dynamic nature of exogenous climate processes interacting with the endogenous recruitment process. Using different model selection criteria our results reveal that in contrast to NAO and AMO, the BSI shows a significant positive but delayed signal on the annual dynamics of herring recruitment. The westward influence of the Siberian high is considered strongly suppressing the influence of the NAO in this area leading to a higher explanatory power of the BSI reflecting the atmospheric pressure regime on a North-South transect between Oslo, Norway and Szczecin, Poland. We suggest incorporating climate-induced effects into stock and risk assessments and management strategies as part of the EU ecosystem approach to support sustainable herring fisheries in the Western Baltic Sea.

Broad-Scale Climate Influences on Spring-Spawning Herring (Clupea harengus, L.) Recruitment in the Western Baltic Sea

PubMed Central

Gröger, Joachim P.; Hinrichsen, Hans-Harald; Polte, Patrick

2014-01-01

Climate forcing in complex ecosystems can have profound implications for ecosystem sustainability and may thus challenge a precautionary ecosystem management. Climatic influences documented to affect various ecological functions on a global scale, may themselves be observed on quantitative or qualitative scales including regime shifts in complex marine ecosystems. This study investigates the potential climatic impact on the reproduction success of spring-spawning herring (Clupea harengus) in the Western Baltic Sea (WBSS herring). To test for climate effects on reproduction success, the regionally determined and scientifically well-documented spawning grounds of WBSS herring represent an ideal model system. Climate effects on herring reproduction were investigated using two global indices of atmospheric variability and sea surface temperature, represented by the North Atlantic Oscillation (NAO) and the Atlantic Multi-decadal Oscillation (AMO), respectively, and the Baltic Sea Index (BSI) which is a regional-scale atmospheric index for the Baltic Sea. Moreover, we combined a traditional approach with modern time series analysis based on a recruitment model connecting parental population components with reproduction success. Generalized transfer functions (ARIMAX models) allowed evaluating the dynamic nature of exogenous climate processes interacting with the endogenous recruitment process. Using different model selection criteria our results reveal that in contrast to NAO and AMO, the BSI shows a significant positive but delayed signal on the annual dynamics of herring recruitment. The westward influence of the Siberian high is considered strongly suppressing the influence of the NAO in this area leading to a higher explanatory power of the BSI reflecting the atmospheric pressure regime on a North-South transect between Oslo, Norway and Szczecin, Poland. We suggest incorporating climate-induced effects into stock and risk assessments and management strategies as part of the EU ecosystem approach to support sustainable herring fisheries in the Western Baltic Sea. PMID:24586279

Relevant climate response tests for stratospheric aerosol injection: A combined ethical and scientific analysis

NASA Astrophysics Data System (ADS)

Lenferna, Georges Alexandre; Russotto, Rick D.; Tan, Amanda; Gardiner, Stephen M.; Ackerman, Thomas P.

2017-06-01

In this paper, we focus on stratospheric sulfate injection as a geoengineering scheme, and provide a combined scientific and ethical analysis of climate response tests, which are a subset of outdoor tests that would seek to impose detectable and attributable changes to climate variables on global or regional scales. We assess the current state of scientific understanding on the plausibility and scalability of climate response tests. Then, we delineate a minimal baseline against which to consider whether certain climate response tests would be relevant for a deployment scenario. Our analysis shows that some climate response tests, such as those attempting to detect changes in regional climate impacts, may not be deployable in time periods relevant to realistic geoengineering scenarios. This might pose significant challenges for justifying stratospheric sulfate aerosol injection deployment overall. We then survey some of the major ethical challenges that proposed climate response tests face. We consider what levels of confidence would be required to ethically justify approving a proposed test; whether the consequences of tests are subject to similar questions of justice, compensation, and informed consent as full-scale deployment; and whether questions of intent and hubris are morally relevant for climate response tests. We suggest further research into laboratory-based work and modeling may help to narrow the scientific uncertainties related to climate response tests, and help inform future ethical debate. However, even if such work is pursued, the ethical issues raised by proposed climate response tests are significant and manifold.

Insights into soil carbon dynamics across climatic and geologic gradients from time-series and fraction-specific radiocarbon analysis

NASA Astrophysics Data System (ADS)

van der Voort, Tessa Sophia; Hagedorn, Frank; Zell, Claudia; McIntyre, Cameron; Eglinton, Tim

2016-04-01

Understanding the interaction between soil organic matter (SOM) and climatic, geologic and ecological factors is essential for the understanding of potential susceptibility and vulnerability to climate and land use change. Radiocarbon constitutes a powerful tool for unraveling SOM dynamics and is increasingly used in studies of carbon turnover. The complex and inherently heterogeneous nature of SOM renders it challenging to assess the processes that govern SOM stability by solely looking at the bulk signature on a plot-scale level. This project combines bulk radiocarbon measurements on a regional-scale spanning wide climatic and geologic gradients with a more in-depth approach for a subset of locations. For this subset, time-series and carbon pool-specific radiocarbon data has been acquired for both topsoil and deeper soils. These well-studied sites are part of the Long-Term Forest Ecosystem Research (LWF) program of the Swiss Federal Institute for Forest, Snow and Landscape research (WSL). Statistical analysis was performed to examine relationships of radiocarbon signatures with variables such as temperature, precipitation and elevation. Bomb-curve modeling was applied determine carbon turnover using time-series data. Results indicate that (1) there is no significant correlation between Δ14C signature and environmental conditions except a weak positive correlation with mean annual temperature, (2) vertical gradients in Δ14C signatures in surface and deeper soils are highly similar despite covering disparate soil-types and climatic systems, and (3) radiocarbon signatures vary significantly between time-series samples and carbon pools. Overall, this study provides a uniquely comprehensive dataset that allows for a better understanding of links between carbon dynamics and environmental settings, as well as for pool-specific and long-term trends in carbon (de)stabilization.

Long-Term and Seasonal Dynamics of Dengue in Iquitos, Peru

PubMed Central

Stoddard, Steven T.; Wearing, Helen J.; Reiner, Robert C.; Morrison, Amy C.; Astete, Helvio; Vilcarromero, Stalin; Alvarez, Carlos; Ramal-Asayag, Cesar; Sihuincha, Moises; Rocha, Claudio; Halsey, Eric S.; Scott, Thomas W.; Kochel, Tadeusz J.; Forshey, Brett M.

2014-01-01

Introduction Long-term disease surveillance data provide a basis for studying drivers of pathogen transmission dynamics. Dengue is a mosquito-borne disease caused by four distinct, but related, viruses (DENV-1-4) that potentially affect over half the world's population. Dengue incidence varies seasonally and on longer time scales, presumably driven by the interaction of climate and host susceptibility. Precise understanding of dengue dynamics is constrained, however, by the relative paucity of laboratory-confirmed longitudinal data. Methods We studied 10 years (2000–2010) of laboratory-confirmed, clinic-based surveillance data collected in Iquitos, Peru. We characterized inter and intra-annual patterns of dengue dynamics on a weekly time scale using wavelet analysis. We explored the relationships of case counts to climatic variables with cross-correlation maps on annual and trimester bases. Findings Transmission was dominated by single serotypes, first DENV-3 (2001–2007) then DENV-4 (2008–2010). After 2003, incidence fluctuated inter-annually with outbreaks usually occurring between October and April. We detected a strong positive autocorrelation in case counts at a lag of ∼70 weeks, indicating a shift in the timing of peak incidence year-to-year. All climatic variables showed modest seasonality and correlated weakly with the number of reported dengue cases across a range of time lags. Cases were reduced after citywide insecticide fumigation if conducted early in the transmission season. Conclusions Dengue case counts peaked seasonally despite limited intra-annual variation in climate conditions. Contrary to expectations for this mosquito-borne disease, no climatic variable considered exhibited a strong relationship with transmission. Vector control operations did, however, appear to have a significant impact on transmission some years. Our results indicate that a complicated interplay of factors underlie DENV transmission in contexts such as Iquitos. PMID:25033412

Time Scale Optimization and the Hunt for Astronomical Cycles in Deep Time Strata

NASA Astrophysics Data System (ADS)

Meyers, Stephen R.

2016-04-01

A valuable attribute of astrochronology is the direct link between chronometer and climate change, providing a remarkable opportunity to constrain the evolution of the surficial Earth System. Consequently, the hunt for astronomical cycles in strata has spurred the development of a rich conceptual framework for climatic/oceanographic change, and has allowed exploration of the geologic record with unprecedented temporal resolution. Accompanying these successes, however, has been a persistent skepticism about appropriate astrochronologic testing and circular reasoning: how does one reliably test for astronomical cycles in stratigraphic data, especially when time is poorly constrained? From this perspective, it would seem that the merits and promise of astrochronology (e.g., a geologic time scale measured in ≤400 kyr increments) also serves as its Achilles heel, if the confirmation of such short rhythms defies rigorous statistical testing. To address these statistical challenges in astrochronologic testing, a new approach has been developed that (1) explicitly evaluates time scale uncertainty, (2) is resilient to common problems associated with spectrum confidence level assessment and 'multiple testing', and (3) achieves high statistical power under a wide range of conditions (it can identify astronomical cycles when present in data). Designated TimeOpt (for "time scale optimization"; Meyers 2015), the method employs a probabilistic linear regression model framework to investigate amplitude modulation and frequency ratios (bundling) in stratigraphic data, while simultaneously determining the optimal time scale. This presentation will review the TimeOpt method, and demonstrate how the flexible statistical framework can be further extended to evaluate (and optimize upon) complex sedimentation rate models, enhancing the statistical power of the approach, and addressing the challenge of unsteady sedimentation. Meyers, S. R. (2015), The evaluation of eccentricity-related amplitude modulation and bundling in paleoclimate data: An inverse approach for astrochronologic testing and time scale optimization, Paleoceanography, 30, doi:10.1002/ 2015PA002850.

Cultural and climatic changes shape the evolutionary history of the Uralic languages.

PubMed

Honkola, T; Vesakoski, O; Korhonen, K; Lehtinen, J; Syrjänen, K; Wahlberg, N

2013-06-01

Quantitative phylogenetic methods have been used to study the evolutionary relationships and divergence times of biological species, and recently, these have also been applied to linguistic data to elucidate the evolutionary history of language families. In biology, the factors driving macroevolutionary processes are assumed to be either mainly biotic (the Red Queen model) or mainly abiotic (the Court Jester model) or a combination of both. The applicability of these models is assumed to depend on the temporal and spatial scale observed as biotic factors act on species divergence faster and in smaller spatial scale than the abiotic factors. Here, we used the Uralic language family to investigate whether both 'biotic' interactions (i.e. cultural interactions) and abiotic changes (i.e. climatic fluctuations) are also connected to language diversification. We estimated the times of divergence using Bayesian phylogenetics with a relaxed-clock method and related our results to climatic, historical and archaeological information. Our timing results paralleled the previous linguistic studies but suggested a later divergence of Finno-Ugric, Finnic and Saami languages. Some of the divergences co-occurred with climatic fluctuation and some with cultural interaction and migrations of populations. Thus, we suggest that both 'biotic' and abiotic factors contribute either directly or indirectly to the diversification of languages and that both models can be applied when studying language evolution. © 2013 The Authors. Journal of Evolutionary Biology © 2013 European Society For Evolutionary Biology.

Polar synchronization and the synchronized climatic history of Greenland and Antarctica

NASA Astrophysics Data System (ADS)

Oh, Jeseung; Reischmann, Elizabeth; Rial, José A.

2014-01-01

Stable isotope proxies from ice cores show subtle differences in the climatic fluctuations of the Arctic and Antarctic, and recent analyses have revealed evidence of polar synchronization at the millennial time scale. At this scale, we analogize the polar climates of the last ice ages to two coupled nonlinear oscillators, which adjust their natural rhythms until they synchronize at a common frequency and constant phase shift. Heat and mass transfers across the intervening ocean and atmosphere make the coupling possible. Here we statistically demonstrate the existence of this phenomenon in polar proxy records with methane-matched age models, and quantify their phase relationship. We show that the time series of representative proxy records of the last glaciation recorded in Greenland (GRIP, NGRIP) and Antarctica (Byrd, Dome C) satisfy phase synchronization conditions, independently of age, for periods ranging 1-6 ky, and can be transformed into one another by a π/2 phase shift, with Antarctica temperature variations leading Greenland's. Based on these results, we use the polar synchronization paradigm to replicate the 800 ky-long, Antarctic, EPICA time series from a theoretical model that extends Greenland's 100 ky-long GRIP record to 800 ky. Statistical analysis of the simulated and actual Antarctic records shows that the procedure is stable to change in adjustable parameters, and requires the coupling between the polar climates to be proportional mainly to the difference in heat storage between the two regions.

Climate variations in northern North America (6000 BP to present) reconstructed from pollen and tree-ring data

DOE Office of Scientific and Technical Information (OSTI.GOV)

Diaz, H.F.; Andrews, J.T.; Short, S.K.

The characteristic anomaly patterns of modern surface temperature and precipitation are compared to tree-ring indices (0-300 yr) and fossil pollen (0-6000 yr) variations in northern North America. The data base consists of 245 climate stations, 55 tree-ring chronologies, 153 modern pollen collections, and 39 fossil pollen sites. A few areas exhibit relatively high climatic sensitivity, displaying generally consistent patterns during alternate warm and cold periods, regardless of time scales. The surface changes are related to the redistribution (i.e., changes in the mean position and strength) of the planetary-scale waves and to north-south shifts in the mean boundary of the Arcticmore » Front. The zone where the largest changes occur is typically located along the mean present-day boundary between Arctic and Pacific airstreams. Establishing plausible relationships between vegetation responses and concomitant changes in atmospheric circulation patterns increases our confidence that the paleoclimatic signals are indeed related to large-scale circulation changes.« less

The role of school organizational climate in occupational stress among secondary school teachers in Tehran.

PubMed

Ahghar, Ghodsy

2008-01-01

This paper aims at studying the influence of the organizational climate of a school on the occupational stress of the teachers. The study population were all secondary schools teachers in Tehran in 2007. Using a multi-stage random sampling method, a sample volume of 220 people was determined using the Cochran formula. Two main instruments were used to measure the study variables: a 27-item questionnaire on organizational climate (four scales: open, engaged, disengaged and closed organizational climate, and a 53-item occupational stress questionnaire by Vingerhoets, employing 11 scales: Skill Discretion, Decision Authority, Task Control, Work and Time Pressure, Role Ambiguity, Physical Exertion, Hazardous Exposure, Job Insecurity, Lack of Meaningfulness, Social Support from Supervisor and Social Support from Coworkers. The frequency, percentage, and mean values were calculated and a stepwise regression analysis was performed to evaluate the statistical significance of the findings. The study results revealed that: (a) 40.02% of secondary school teachers experience occupational stress at a moderate or higher level; (b) the rate of occupational stress among teachers can be predicted. using the scores on the school organizational climate; this predictability is highest for the open climate and gradually decreases through the engaged, and disengaged to the closed climate; (c) among the teachers working in the disengaged and closed climate, the rate of occupational stress significantly exceeds that recorded among the teachers working in the open climate.

Santa Ana Winds of Southern California: Their Climatology and Variability Spanning 6.5 Decades from Regional Dynamical Modelling

NASA Astrophysics Data System (ADS)

Guzman-Morales, J.; Gershunov, A.

2015-12-01

Santa Ana Winds (SAWs) are an integral feature of the regional climate of Southern California/Northern Baja California region. In spite of their tremendous episodic impacts on the health, economy and mood of the region, climate-scale behavior of SAW is poorly understood. In the present work, we identify SAWs in mesoscale dynamical downscaling of a global reanalysis product and construct an hourly SAW catalogue spanning 65 years. We describe the long-term SAW climatology at relevant time-space resolutions, i.e, we developed local and regional SAW indices and analyse their variability on hourly, daily, annual, and multi-decadal timescales. Local and regional SAW indices are validated with available anemometer observations. Characteristic behaviors are revealed, e.g. the SAW intensity-duration relationship. At interdecadal time scales, we find that seasonal SAW activity is sensitive to prominent large-scale low-frequency modes of climate variability rooted in the tropical and north Pacific ocean-atmosphere system that are also known to affect the hydroclimate of this region. Lastly, we do not find any long-term trend in SAW frequency and intensity as previously reported. Instead, we identify a significant long-term trend in SAW behavior whereby contribution of extreme SAW events to total seasonal SAW activity has been increasing at the expense of moderate events. These findings motivate further investigation on SAW evolution in future climate and its impact on wildfires.

Modes and emergent time scales of embayed beach dynamics

NASA Astrophysics Data System (ADS)

Ratliff, Katherine M.; Murray, A. Brad

2014-10-01

In this study, we use a simple numerical model (the Coastline Evolution Model) to explore alongshore transport-driven shoreline dynamics within generalized embayed beaches (neglecting cross-shore effects). Using principal component analysis (PCA), we identify two primary orthogonal modes of shoreline behavior that describe shoreline variation about its unchanging mean position: the rotation mode, which has been previously identified and describes changes in the mean shoreline orientation, and a newly identified breathing mode, which represents changes in shoreline curvature. Wavelet analysis of the PCA mode time series reveals characteristic time scales of these modes (typically years to decades) that emerge within even a statistically constant white-noise wave climate (without changes in external forcing), suggesting that these time scales can arise from internal system dynamics. The time scales of both modes increase linearly with shoreface depth, suggesting that the embayed beach sediment transport dynamics exhibit a diffusive scaling.

Impact of climate variations on Managed Aquifer Recharge infiltration basins.

NASA Astrophysics Data System (ADS)

Barquero, Felix; Stefan, Catalin

2017-04-01

KEYWORDS: Managed Aquifer Recharge, field scale infiltration unit, climatic conditions, numerical model Managed Aquifer Recharge (MAR) is a technique that is gaining more attention as a sustainable alternative for areas where water scarcity is increasing. Main concept relies on facilitating the vertical infiltration of a source of fresh water (river water, rainwater, reclaimed water, etc). The groundwater acts as storage of water for further use in the future, for example in times of water scarcity. In some MAR types the soil itself can be used even as a filter for the removal of specific organic and inorganic compounds. In order to promote the benefits of MAR in different zones of the globe with variable climate conditions, including the effects of climate change, a numerical model (HYDRUS 2D/3D) is being set up. Coupled with the model a field-scale rapid infiltration unit (4m x 5m x 1.5m) was constructed with the capacity to log different MAR key parameters in the soil (tension, water content, temperature and electrical conductivity) in space and time. These data will feed the model for its calibration using specific hydrogeological characteristics of the packing material and hydraulic characteristics of the infiltrated fluid. The unit is located in the city of Pirna (German), 200 m north from the Elbe River where the groundwater level varies seasonally between 6 and 9 m below the ground surface. Together with the field scale rapid infiltration unit, a set of multi-parametric sensors (measuring in time: water stage, electrical conductivity, dissolved oxygen and temperature) in six monitoring wells, located on the basin surroundings, were installed. The purpose of these sensors is to estimate, via tracer experiments, the time that the infiltrated water needed to reach the groundwater and the flow speed in which it travelled once it reached the saturated zone. Once calibrated, the model will be able to estimate the flow behaviour under variable climate conditions (temperature, precipitation and evaporation), representative for different climatic zones in the globe. The simulation results of the different climate models reported by the IPCC will also be considered for critical zones where fresh water availability will decrease considerably. In the field, the first results confirmed the arrival, after 14 days of travel time, of the infiltrated river water front to the monitoring wells located next to the infiltration unit. Further tracer experiments have to be performed in order to catch a stronger breakthrough curve in more than one observation point. Interesting open questions arise from the data stored in the trench sensors. How the change of the travel velocity depends on different external parameters like time of operation, cyclic wetting and drying regime and temperature, will be analysed together with the results of the ongoing experiments.

What’s Needed from Climate Modeling to Advance Actionable Science for Water Utilities?

NASA Astrophysics Data System (ADS)

Barsugli, J. J.; Anderson, C. J.; Smith, J. B.; Vogel, J. M.

2009-12-01

“…perfect information on climate change is neither available today nor likely to be available in the future, but … over time, as the threats climate change poses to our systems grow more real, predicting those effects with greater certainty is non-discretionary. We’re not yet at a level at which climate change projections can drive climate change adaptation.” (Testimony of WUCA Staff Chair David Behar to the House Committee on Science and Technology, May 5, 2009) To respond to this challenge, the Water Utility Climate Alliance (WUCA) has sponsored a white paper titled “Options for Improving Climate Modeling to Assist Water Utility Planning for Climate Change. ” This report concerns how investments in the science of climate change, and in particular climate modeling and downscaling, can best be directed to help make climate projections more actionable. The meaning of “model improvement” can be very different depending on whether one is talking to a climate model developer or to a water manager trying to incorporate climate projections in to planning. We first surveyed the WUCA members on present and potential uses of climate model projections and on climate inputs to their various system models. Based on those surveys and on subsequent discussions, we identified four dimensions along which improvement in modeling would make the science more “actionable”: improved model agreement on change in key parameters; narrowing the range of model projections; providing projections at spatial and temporal scales that match water utilities system models; providing projections that water utility planning horizons. With these goals in mind we developed four options for improving global-scale climate modeling and three options for improving downscaling that will be discussed. However, there does not seem to be a single investment - the proverbial “magic bullet” -- which will substantially reduce the range of model projections at the scales at which utility planning is conducted. In the near term we feel strongly that water utilities and climate scientists should work together to leverage the upcoming Coupled Model Intercomparison Project, Phase 5 (CMIP5; a coordinated set climate model experiments that will be used to support the upcoming IPCC Fifth Assessment) to better benefit water utilities. In the longer term, even with model and downscaling improvements, it is very likely that substantial uncertainty about future climate change at the desired spatial and temporal scales will remain. Nonetheless, there is no doubt the climate is changing, and the challenge is to work with what we have, or what we can reasonably expect to have in the coming years to make the best decisions we can.

Holocene variability in the intensity of wind-gap upwelling in the tropical eastern Pacific

USGS Publications Warehouse

Toth, Lauren T.; Aronson, Richard B.; Cheng, Hai; Edwards, R. Lawrence

2015-01-01

Wind-driven upwelling in Pacific Panamá is a significant source of oceanographic variability in the tropical eastern Pacific. This upwelling system provides a critical teleconnection between the Atlantic and tropical Pacific that may impact climate variability on a global scale. Despite its importance to oceanographic circulation, ecology, and climate, little is known about the long-term stability of the Panamanian upwelling system or its interaction with climatic forcing on millennial time scales. Using a combination of radiocarbon and U-series dating of fossil corals collected in cores from five sites across Pacific Panamá, we reconstructed the local radiocarbon reservoir correction, ΔR, from ~6750 cal B.P. to present. Because the ΔR of shallow-water environments is elevated by upwelling, our data set represents a millennial-scale record of spatial and temporal variability of the Panamanian upwelling system. The general oceanographic gradient from relatively strong upwelling in the Gulf of Panamá to weak-to-absent upwelling in the Gulf of Chiriquí was present throughout our record; however, the intensity of upwelling in the Gulf of Panamá varied significantly through time. Our reconstructions suggest that upwelling in the Gulf of Panamá is weak at present; however, the middle Holocene was characterized by periods of enhanced upwelling, with the most intense upwelling occurring just after of a regional shutdown in the development of reefs at ~4100 cal B.P. Comparisons with regional climate proxies suggest that, whereas the Intertropical Convergence Zone is the primary control on modern upwelling in Pacific Panamá, the El Niño–Southern Oscillation drove the millennial-scale variability of upwelling during the Holocene.

Multi-Decadal to Millennial Scale Holocene Hydrologic Variation in the Southern Hemisphere Tropics of South America

NASA Astrophysics Data System (ADS)

Ekdahl, E. J.; Fritz, S. C.; Baker, P. A.; Burns, S. J.; Coley, K.; Rigsby, C. A.

2005-12-01

Numerous sites in the Northern Hemisphere show multi-decadal to millennial scale climate variation during the Holocene, many of which have been correlated with changes in atmospheric radiocarbon production or with changes in North Atlantic oceanic circulation. The manifestation of such climate variability in the hydrology of the Southern Hemisphere tropics of South America is unclear, because of the limited number of records at suitably high resolution. In the Lake Titicaca drainage basin of Bolivia and Peru, high-resolution lacustrine records reveal the overall pattern of Holocene lake-level change, the influence of precessional forcing of the South American Summer Monsoon, and the effects of high-frequency climate variability in records of lake productivity and lake ecology. Precessional forcing of regional precipitation is evident in the Lake Titicaca basin as a massive (ca. 85 m) mid-Holocene decline in lake level beginning about 7800 cal yr BP and a subsequent rise in lake level after 4000 cal yr BP. Here we show that multi-decadal to millennial-scale climate variability, superimposed upon the envelope of change at orbital time scales, is similar in timing and pattern to the ice-rafted debris record of Holocene Bond events in the North Atlantic. A high-resolution carbon isotopic record from Lake Titicaca that spans the entire Holocene suggests that cold intervals of Holocene Bond events are periods of increased precipitation, thus indicating an anti-phasing of precipitation variation on the Altiplano relative to the Northern Hemisphere tropics. A similar pattern of variation is also evident in high-resolution (2-30 yr spacing) diatom and geochemical records that span the last 7000 yr from two smaller lakes, Lagos Umayo and Lagunillas, in the Lake Titicaca drainage basin.

Satellite remote sensing assessment of climate impact on forest vegetation dynamics

NASA Astrophysics Data System (ADS)

Zoran, M.

2009-04-01

Forest vegetation phenology constitutes an efficient bio-indicator of impacts of climate and anthropogenic changes and a key parameter for understanding and modelling vegetation-climate interactions. Climate variability represents the ensemble of net radiation, precipitation, wind and temperature characteristic for a region in a certain time scale (e.g.monthly, seasonal annual). The temporal and/or spatial sensitivity of forest vegetation dynamics to climate variability is used to characterize the quantitative relationship between these two quantities in temporal and/or spatial scales. So, climate variability has a great impact on the forest vegetation dynamics. Satellite remote sensing is a very useful tool to assess the main phenological events based on tracking significant changes on temporal trajectories of Normalized Difference Vegetation Index (NDVIs), which requires NDVI time-series with good time resolution, over homogeneous area, cloud-free and not affected by atmospheric and geometric effects and variations in sensor characteristics (calibration, spectral responses). Spatio-temporal vegetation dynamics have been quantified as the total amount of vegetation (mean NDVI) and the seasonal difference (annual NDVI amplitude) by a time series analysis of NDVI satellite images with the Harmonic ANalysis of Time Series algorithm. A climate indicator (CI) was created from meteorological data (precipitation over net radiation). The relationships between the vegetation dynamics and the CI have been determined spatially and temporally. The driest test regions prove to be the most sensitive to climate impact. The spatial and temporal patterns of the mean NDVI are the same, while they are partially different for the seasonal difference. The aim of this paper was to quantify this impact over a forest ecosystem placed in the North-Eastern part of Bucharest town, Romania, with Normalized Difference Vegetation Index (NDVI) parameter extracted from IKONOS and LANDSAT TM and ETM satellite images and meteorological data over l995-2007 period. For investigated test area, considerable NDVI decline was observed between 1995 and 2007 due to the drought events during 2003 and 2007 years. Under stress conditions, it is evident that environmental factors such as soil type, parent material, and topography are not correlated with NDVI dynamics. Specific aim of this paper was to assess, forecast, and mitigate the risks of climatic changes on forest systems and its biodiversity as well as on adjacent environment areas and to provide early warning strategies on the basis of spectral information derived from satellite data regarding atmospheric effects of forest biome degradation . The paper aims to describe observed trends and potential impacts based on scenarios from simulations with regional climate models and other downscaling procedures.

The North American Regional Climate Change Assessment Program (NARCCAP): Status and results

NASA Astrophysics Data System (ADS)

Gutowski, W. J.

2009-12-01

NARCCAP is a multi-institutional program that is investigating systematically the uncertainties in regional scale simulations of contemporary climate and projections of future climate. NARCCAP is supported by multiple federal agencies. NARCCAP is producing an ensemble of high-resolution climate-change scenarios by nesting multiple RCMs in reanalyses and multiple atmosphere-ocean GCM simulations of contemporary and future-scenario climates. The RCM domains cover the contiguous U.S., northern Mexico, and most of Canada. The simulation suite also includes time-slice, high resolution GCMs that use sea-surface temperatures from parent atmosphere-ocean GCMs. The baseline resolution of the RCMs and time-slice GCMs is 50 km. Simulations use three sources of boundary conditions: National Centers for Environmental Prediction (NCEP)/Department of Energy (DOE) AMIP-II Reanalysis, GCMs simulating contemporary climate and GCMs using the A2 SRES emission scenario for the twenty-first century. Simulations cover 1979-2004 and 2038-2060, with the first 3 years discarded for spin-up. The resulting RCM and time-slice simulations offer opportunity for extensive analysis of RCM simulations as well as a basis for multiple high-resolution climate scenarios for climate change impacts assessments. Geophysical statisticians are developing measures of uncertainty from the ensemble. To enable very high-resolution simulations of specific regions, both RCM and high-resolution time-slice simulations are saving output needed for further downscaling. All output is publically available to the climate analysis and the climate impacts assessment community, through an archiving and data-distribution plan. Some initial results show that the models closely reproduce ENSO-related precipitation variations in coastal California, where the correlation between the simulated and observed monthly time series exceeds 0.94 for all models. The strong El Nino events of 1982-83 and 1997-98 are well reproduced for the Pacific coastal region of the U.S. in all models. ENSO signals are less well reproduced in other regions. The models also produce well extreme monthly precipitation in coastal California and the Upper Midwest. Model performance tends to deteriorate from west to east across the domain, or roughly from the inflow boundary toward the outflow boundary. This deterioration with distance from the inflow boundary is ameliorated to some extent in models formulated such that large-scale information is included in the model solution, whether implemented by spectral nudging or by use of a perturbation form of the governing equations.

Sensitivity of the carbon cycle in the Arctic to climate change

Treesearch

A.D. McGuire; L.G. Anderson; T.R. Christensen; S. Dallimore; L. Guo; D.J. Hayes; M. Heimann; T.D. Lorenson; R.W. Macdonald; N. Roulet

2009-01-01

The recent warming in the Arctic is affecting a broad spectrum of physical, ecological, and human/cultural systems that may be irreversible on century time scales and have the potential to cause rapid changes in the earth system. The response of the carbon cycle of the Arctic to changes in climate is a major issue of global concern, yet there has not been a...

Detecting mortality induced structural and functional changes in a pinon-juniper woodland using Landsat and RapidEye time series

Treesearch

Dan J. Krofcheck; Jan U. H. Eitel; Lee A. Vierling; Urs Schulthess; Timothy M. Hilton; Eva Dettweiler-Robinson; Rosemary Pendleton; Marcy E. Litvak

2014-01-01

Pinon-juniper (PJ) woodlands have recently undergone dramatic drought-induced mortality, triggering broad scale structural changes in this extensive Southwestern US biome. Given that climate projections for the region suggest widespread conifer mortality is likely to continue into the next century, it is critical to better understand how this climate-induced change in...

Farmer response to climatic and agricultural market drivers: characteristic time scales and sensitivities

NASA Astrophysics Data System (ADS)

Wurster, P. M.; Maneta, M. P.; Vicente-Serrano, S. M.; Beguería, S.; Silverman, N. L.; Holden, Z.

2017-12-01

Agriculture in the intermountain western United States is dominated by extensive farming and ranching, mostly reliant on rainfed crops and therefore very exposed to precipitation shortfalls. It is also poorly diversified, dominated by five or six major grain crops, which makes it vulnerable to changes in agricultural markets. The economy of the region is very reliant on this type of agriculture, making the entire economy vulnerable to climatic and market fluctuations. Western agriculture is also of significant importance for national food security. Resource managers in the region are increasingly concerned with the impacts that more frequent and severe droughts, or the collapse of crop prices, may have on producers and food production. Effective resource management requires an understanding not only of the regional impact of adverse climatic and market events, but also of which geographic areas are most vulnerable, and why. Unfortunately, few studies exist that look into how farmers in different geographic areas respond to climate and market drivers. In this study we analyze the influence of precipitation and crop price anomalies on crop production, and map the characteristic time scale of these anomalies that correlate best with production anomalies for the 56 counties of Montana, U.S.A. We conduct this analysis using the standardized precipitation index (SPI), and defining a standardized crop value index (SCVI) and a standardized crop production index (SCPI). We use 38 years of data to calculate precipitation anomalies at monthly time scales and annual data to calculate crop price and production anomalies. The standardization of the indices allows for straightforward comparison of the relative influence of climatic and market fluctuations on production anomalies. We apply our methodology to winter wheat, spring durum wheat, barley, alfalfa, and beets which are the most valuable crops produced in the state. Results from this study show that precipitation anomalies accumulated between 3 and 8 months in spring are most explanatory of production anomalies, but that crop price anomalies interact with climatic factors. This study will provide agricultural producers and water managers with valuable information regarding the resiliency of key crops in the state and of Montana's rural economy.

Toward a Continental-Scale Mesonet: USDA National Resources Conservation Service SCAN and SNOTEL System

NASA Astrophysics Data System (ADS)

Schaffer, G.; Marks, D.

2004-12-01

Since 1978 snow deposition and SWE in the inter-mountain western US have been monitored by the NRCS SNOTEL (SNOwpack TELemetry) system. This revolutionary network utilizes Meteorburst technology to telemeter data back to a central location in near real-time. With a pilot program starting in 1991, NRCS introduced SCAN (Soil Climate and Analysis Network) adding a focus on soil moisture and climate in regions outside the intermountain west. In the mid-1990's SNOTEL sites began to be augmented to match the full climate instrumentation (air temperature, humidity, solar radiation, wind, and soil moisture and temperature in addition to precipitation, snow depth and SWE) of the SCAN system. At present there are nearly 700 SNOTEL sites in 12 states in the western US and Alaska, and over 100 SCAN sites in 40 states, Puerto Rico, and several foreign countries. Though SNOTEL was originally a western snow-monitoring network, differences between SCAN and SNOTEL have largely disappeared. The combined SNOTEL/SCAN system provides a continental-scale mesonet to support river basin to continental scale hydro-climatic analysis. The system is flexible and based on off-the-shelf data recording technology, allowing instrumentation, sampling and averaging intervals to be specified by site conditions, issues, or scientific questions. Because of the NRCS data management structure, all sites have active telemetery and provide near real-time access to data through the internet. An ongoing research program is directed to improved instrumentation for measuring precipitation, snow depth and SWE, and soil moisture and temperature. Future directions include expansion of the network to be more comprehensive, and to develop focused monitoring efforts to more effectively observe elevational and regional gradients, and to capture high intensity hydro-climatic events such as potential flooding from convective storms and rain-on-snow.

Space-time analysis of snow cover change in the Romanian Carpathians (2001-2016)

NASA Astrophysics Data System (ADS)

Micu, Dana; Cosmin Sandric, Ionut

2017-04-01

Snow cover is recognized as an essential climate variable, highly sensitive to the ongoing climate warming, which plays an important role in regulating mountain ecosystems. Evidence from the existing weather stations located above 800 m over the last 50 years points out that the climate of the Romanian Carpathians is visibly changing, showing an ongoing and consistent warming process. Quantifying and attributing the changes in snow cover on various spatial and temporal scales have a great environmental and socio-economic importance for this mountain region. The study is revealing the inter-seasonal changes in the timing and distribution of snow cover across the Romanian Carpathians, by combining gridded snow data (CARPATCLIM dataset, 1961-2010) and remote sensing data (2001-2016) in specific space-time assessment at regional scale. The geostatistical approach applied in this study, based on a GIS hotspot analysis, takes advantage of all the dimensions in the datasets, in order to understand the space-time trends in this climate variable at monthly time-scale. The MODIS AQUA and TERRA images available from 2001 to 2016 have been processed using ArcGIS for Desktop and Python programming language. All the images were masked out with the Carpathians boundary. Only the pixels with snow have been retained for analysis. The regional trends in snow cover distribution and timing have been analysed using Space-Time cube with ArcGIS for Desktop, according with Esri documentation using the Mann-Kendall trend test on every location with data as an independent bin time-series test. The study aimed also to assess the location of emerging hotspots of snow cover change in Carpathians. These hotspots have been calculated using Getis-Ord Gi* statistic for each bin using Hot Spot Analysis implemented in ArcGIS for Desktop. On regional scale, snow cover appear highly sensitive to the decreasing trends in air temperatures and land surface temperatures, combined with the decrease in seasonal precipitation, especially at lower elevations in all the three divisions of the Romanian Carpathians (generally below 1,700-1,800 m). The space-time patterns of snow cover change are dominated by a significant decreasing trend of snow days and earlier spring snow melt. The key findings of this study provides robust indication of a decreasing snow trends across the Carpathian Mountain region and could provide valuable spatial and temporal snow information for other related research fields as well as for an effective environmental monitoring in the mountain ecosystems of the Carpathian region

Shift of large-scale atmospheric systems over Europe during late MIS 3 and implications for Modern Human dispersal.

PubMed

Obreht, Igor; Hambach, Ulrich; Veres, Daniel; Zeeden, Christian; Bösken, Janina; Stevens, Thomas; Marković, Slobodan B; Klasen, Nicole; Brill, Dominik; Burow, Christoph; Lehmkuhl, Frank

2017-07-19

Understanding the past dynamics of large-scale atmospheric systems is crucial for our knowledge of the palaeoclimate conditions in Europe. Southeastern Europe currently lies at the border between Atlantic, Mediterranean, and continental climate zones. Past changes in the relative influence of associated atmospheric systems must have been recorded in the region's palaeoarchives. By comparing high-resolution grain-size, environmental magnetic and geochemical data from two loess-palaeosol sequences in the Lower Danube Basin with other Eurasian palaeorecords, we reconstructed past climatic patterns over Southeastern Europe and the related interaction of the prevailing large-scale circulation modes over Europe, especially during late Marine Isotope Stage 3 (40,000-27,000 years ago). We demonstrate that during this time interval, the intensification of the Siberian High had a crucial influence on European climate causing the more continental conditions over major parts of Europe, and a southwards shift of the Westerlies. Such a climatic and environmental change, combined with the Campanian Ignimbrite/Y-5 volcanic eruption, may have driven the Anatomically Modern Human dispersal towards Central and Western Europe, pointing to a corridor over the Eastern European Plain as an important pathway in their dispersal.

Geomorphologic Mapping of a Last Glacial Maximum Moraine Sequence in the Far Eastern Tibetan Plateau

NASA Astrophysics Data System (ADS)

Lindsay, B. J.; Putnam, A. E.; Strand, P.; Radue, M. J.; Dong, G.; Kong, X.; Li, M.; Sheriff, M.; Stevens, J.

2017-12-01

The abrupt millennial-scale climate events of the last glacial cycle constitute an important component of the ice-age puzzle. A complete explanation of glacial cycles, and their rapid terminations, must account for these millennial climatic `flickers'. Here we present a glacial geomorphologic map of a moraine system in a formerly glaciated valley within the mountains of Litang County in the eastern Tibetan Plateau of China. Geomorphologic mapping was conducted by interpreting satellite imagery, structure-from-motion imagery and digital elevation models, and field observations. This map provides context for a parallel ongoing 10Be exposure-dating effort, the preliminary results of which may be available by the time of this 2017 AGU Fall Meeting. We interpret the mapped moraines to document the millennial-scale pulsebeat of glacier advances in this region during the peak of the last ice age. Because changes in mountain glacier extent in this region are driven by atmospheric temperature, these moraines record past millennial climate changes. Altogether this mapping and exposure-dating approach will provide insight into the mechanisms for millennial-scale glacier and climate fluctuations in the interior of Asia.

Climate change collaboration among natural resource management agencies: lessons learned from two US regions

USGS Publications Warehouse

Lemieux, Christopher J.; Thompson, Jessica; Slocombe, D. Scott; Schuster, Rudy

2015-01-01

It has been argued that regional collaboration can facilitate adaptation to climate change impacts through integrated planning and management. In an attempt to understand the underlying institutional factors that either support or contest this assumption, this paper explores the institutional factors influencing adaptation to climate change at the regional scale, where multiple public land and natural resource management jurisdictions are involved. Insights from two mid-western US case studies reveal that several challenges to collaboration persist and prevent fully integrative multi-jurisdictional adaptation planning at a regional scale. We propose that some of these challenges, such as lack of adequate time, funding and communication channels, be reframed as opportunities to build interdependence, identify issue-linkages and collaboratively explore the nature and extent of organisational trade-offs with respect to regional climate change adaptation efforts. Such a reframing can better facilitate multi-jurisdictional adaptation planning and management of shared biophysical resources generally while simultaneously enhancing organisational capacity to mitigate negative effects and take advantage of potentially favourable future conditions in an era characterised by rapid climate change.

Aerosol-Radiation-Cloud Interactions in the South-East Atlantic: Model-Relevant Observations and the Beneficiary Modeling Efforts in the Realm of the EVS-2 Project ORACLES

NASA Technical Reports Server (NTRS)

Redemann, Jens

2018-01-01

Globally, aerosols remain a major contributor to uncertainties in assessments of anthropogenically-induced changes to the Earth climate system, despite concerted efforts using satellite and suborbital observations and increasingly sophisticated models. The quantification of direct and indirect aerosol radiative effects, as well as cloud adjustments thereto, even at regional scales, continues to elude our capabilities. Some of our limitations are due to insufficient sampling and accuracy of the relevant observables, under an appropriate range of conditions to provide useful constraints for modeling efforts at various climate scales. In this talk, I will describe (1) the efforts of our group at NASA Ames to develop new airborne instrumentation to address some of the data insufficiencies mentioned above; (2) the efforts by the EVS-2 ORACLES project to address aerosol-cloud-climate interactions in the SE Atlantic and (3) time permitting, recent results from a synergistic use of A-Train aerosol data to test climate model simulations of present-day direct radiative effects in some of the AEROCOM phase II global climate models.

Time-cumulated visible and infrared radiance histograms used as descriptors of surface and cloud variations

NASA Technical Reports Server (NTRS)

Seze, Genevieve; Rossow, William B.

1991-01-01

The spatial and temporal stability of the distributions of satellite-measured visible and infrared radiances, caused by variations in clouds and surfaces, are investigated using bidimensional and monodimensional histograms and time-composite images. Similar analysis of the histograms of the original and time-composite images provides separation of the contributions of the space and time variations to the total variations. The variability of both the surfaces and clouds is found to be larger at scales much larger than the minimum resolved by satellite imagery. This study shows that the shapes of these histograms are distinctive characteristics of the different climate regimes and that particular attributes of these histograms can be related to several general, though not universal, properties of clouds and surface variations at regional and synoptic scales. There are also significant exceptions to these relationships in particular climate regimes. The characteristics of these radiance histograms provide a stable well defined descriptor of the cloud and surface properties.

GTSnext: towards a next generation of the geological time scale over the last 100 millions years. (Invited)

NASA Astrophysics Data System (ADS)

Kuiper, K.; Condon, D.; Hilgen, F.; Laskar, J.; Mezger, K.; Pälike, H.; Quidelleur, X.; Schaltegger, U.; Sprovieri, M.; Storey, M.; Wijbrans, J. R.

2009-12-01

The principal scientific objective of the Marie Curie Initial Trainings Network GTSnext is to establish the next generation standard Geological Time Scale with unprecedented accuracy, precision and resolution through integration and intercalibration of state-of-the-art numerical dating techniques. Such time scales underlie all fields in the Earth Sciences and their application will significantly contribute to a much enhanced understanding of Earth System evolution. During the last decade deep marine successions were successfully employed to establish an astronomical tuning for the entire Neogene, as incorporated in the standard Geological Time Scale (ATNTS2004). In GTSnext we aim to fine-tune this Neogene time scale, before it can reliably be used to accurately determine phase relations between astronomical forcing and climate response in the Neogene and possibly also the Oligocene. Radio-isotopic dating of late Neogene ash layers offers excellent opportunities for gaining insight into isotope systematics via their independent dating by astronomical tuning. An example of this synergy is the development of astronomically calibrated standards for 40Ar/39Ar geochronology. The cross-calibration between the different methods might also yield information on the fundamental problem of potential residence times in U/Pb dating. Extension of the astronomical time scale into the Paleogene seems limited to ~40 Ma due to the accuracy of the current astronomical solution. However, the 405 kyr eccentricity component is very stable permitting its use in time scale calibrations back to 250 Ma using only this frequency. This cycle is strong and well developed in Oligocene and even Eocene records. Phase relations between cyclic paleo-climate records and the 405 kyr eccentricity cycle are typically straightforward and unambiguous. Therefore, a first-order tuning to ~405 kyr eccentricity can only be revised by shifting the tuning with (multiples of) ~405 kyr. Isotopic age constraints of both U/Pb and 40Ar/39Ar will be used to anchor floating astronomical tunings, but absolute uncertainties in isotopic ages should be less than ± 200 kyr. The Cretaceous is famous for its remarkable cyclic successions of marine pelagic sediments which bear the unmistakable imprint of astronomical climate forcing. As a consequence floating astrochronologies which are based on number of cycles have been developed for significant portions of the Cretaceous, covering a number of geological stages. Unfortunately, such floating time scales provide us only with the duration of stages but not with their age. However, due to significant improvements in numerical astronomical solutions for the Solar System and in the accuracy of radio-isotopic dating we will try to establish a tuned time scale for the Late Cretaceous. Classical cyclic sections in Europe (e.g. Sopelana, Spain) will be used for the tuning, but lack ash beds. Therefore, radio-isotopic age constraints necessary for the tuning will come from ash beds in the Western Interior Basin in North America. Here we will present the first results of the GTSnext project.

Evaluating cloud processes in large-scale models: Of idealized case studies, parameterization testbeds and single-column modelling on climate time-scales

NASA Astrophysics Data System (ADS)

Neggers, Roel

2016-04-01

Boundary-layer schemes have always formed an integral part of General Circulation Models (GCMs) used for numerical weather and climate prediction. The spatial and temporal scales associated with boundary-layer processes and clouds are typically much smaller than those at which GCMs are discretized, which makes their representation through parameterization a necessity. The need for generally applicable boundary-layer parameterizations has motivated many scientific studies, which in effect has created its own active research field in the atmospheric sciences. Of particular interest has been the evaluation of boundary-layer schemes at "process-level". This means that parameterized physics are studied in isolated mode from the larger-scale circulation, using prescribed forcings and excluding any upscale interaction. Although feedbacks are thus prevented, the benefit is an enhanced model transparency, which might aid an investigator in identifying model errors and understanding model behavior. The popularity and success of the process-level approach is demonstrated by the many past and ongoing model inter-comparison studies that have been organized by initiatives such as GCSS/GASS. A red line in the results of these studies is that although most schemes somehow manage to capture first-order aspects of boundary layer cloud fields, there certainly remains room for improvement in many areas. Only too often are boundary layer parameterizations still found to be at the heart of problems in large-scale models, negatively affecting forecast skills of NWP models or causing uncertainty in numerical predictions of future climate. How to break this parameterization "deadlock" remains an open problem. This presentation attempts to give an overview of the various existing methods for the process-level evaluation of boundary-layer physics in large-scale models. This includes i) idealized case studies, ii) longer-term evaluation at permanent meteorological sites (the testbed approach), and iii) process-level evaluation at climate time-scales. The advantages and disadvantages of each approach will be identified and discussed, and some thoughts about possible future developments will be given.

Late Noachian Climate Of Mars: Constraints From Valley Network System Formation Times And The Intermittencies (Episodic/Periodic And Punctuated).

NASA Astrophysics Data System (ADS)

Head, James

2017-04-01

Formation of Late Noachian-Early Hesperian (LN-EH) valley network systems (VNS) signaled the presence of warm/wet conditions generating several hypotheses for climates permissive of these conditions. To constrain options for the ambient Noachian climate, we examine estimates for time required to carve channels/deltas and total duration implied by plausible intermittencies. Formation Times for VN, OBL, Deltas, Fans: A synthesis of required timescales show that even with the longest estimated continuous duration of VN formation/intermittencies, total time to carve the VN does not exceed 106 years, <˜0.25% of the total Noachian. Intermittency/episodicity assumptions are climate-model dependent (e.g., most workers use Earth-like fluvial activity and intermittency). Noachian-Early Hesperian Climate Models: 1) Warm and wet/semiarid/arid climate: Sustained background MAT >273 K, hydrological system vertically integrated, and rainfall occurs to recharge the aquifer. Two subtypes: a) "Rainfall/Fluvial Erosion-Dominated Warm and Wet Model": "Rainfall and surface runoff" persist throughout Noachian to explain crater degradation, and a LN-EH short rapidly ending terminal epoch. b) "Recharge Evaporation/Evaporite Dominated Warm and Wet Model": Sustained period of equatorial/mid-latitude precipitation and a vertically integrated hydrological system driven by evaporative upwelling and fluctuating shallow water table playa environments account for sulfate evaporate environments at Meridiani Planum. Sustained temperatures >273 K are required for extended periods (107-108 years). 2) Cold and icy climate: Sustained background temperatures extremely low (MAT ˜225 K), cryosphere is globally continuous, hydrological system is horizontally stratified, separating groundwater system from surface; no combination of spin-axis/orbital perturbations can raise MAT to 273 K. Adiabatic cooling effects transfer water to high altitudes, leading to "Late Noachian Icy Highlands Model". VNS cannot form in this nominal climate environment without special circumstances (e.g., impacts or volcanic eruptions elevate of temperatures by >˜50 K to induce melting and fluvial/lacustrine activity). 3) Cold and Icy climate warmed by greenhouse gases: The climate is sustained cold/icy model, but greenhouse gases of unspecified nature/amount/duration elevate MAT by several tens of Kelvins (say 25 K, to MAT 250 K), bringing annual temperature range into the realm where peak seasonal temperatures (PST) exceed 273 K. In this climate environment, analogous to the Antarctic Dry Valleys, seasonal summer temperatures above 273 K are sufficient to melt snow/ice and form fluvial and lacustrine features, but MAT is well below 273 K (253 K). Fluvial systems driven by episodic/periodic intermittency typically involve short intermittency time-scales (10-106 years) but require a warm climate (MAT >273 K) to be sustained for >0.4 x 109 years. Fluvial systems driven by punctuated intermittency typically involve short duration time-scales (10-105 years) but only require a warm climate (MAT >273 K) for the very short duration of the climatic impact of the punctuated event (102-105 years). We conclude that a cold and icy background climate with punctuated intermittency of warming and melting events is consistent with: 1) the estimated durations of continuous VN formation (<105 years) and 2) VN system estimated recurrence rates (106-107 years).

Development and validation of a measure of workplace climate for healthy weight maintenance.

PubMed

Sliter, Katherine A

2013-07-01

Due to the obesity epidemic, an increasing amount of research is being conducted to better understand the antecedents and consequences of excess employee weight. One construct often of interest to researchers in this area is organizational climate. Unfortunately, a viable measure of climate, as related to employee weight, does not exist. The purpose of this study was to remedy this by developing and validating a concise, psychometrically sound measure of climate for healthy weight. An item pool was developed based on surveys of full-time employees, and a sorting task was used to eliminate ambiguous items. Items were pilot tested by a sample of 338 full-time employees, and the item pool was reduced through item response theory (IRT) and reliability analyses. Finally, the retained 14 items, comprising 3 subscales, were completed by a sample of 360 full-time employees, representing 26 different organizations from across the United States. Multilevel modeling indicated that sufficient variance was explained by group membership to support aggregation, and confirmatory factor analysis (CFA) supported the hypothesized model of 3 subscale factors and an overall climate factor. Nine hypotheses specific to construct validation were tested. Scores on the new scale correlated significantly with individual-level reports of psychological constructs (e.g., health motivation, general leadership support for health) and physiological phenomena (e.g., body mass index [BMI], physical health problems) to which they should theoretically relate, supporting construct validity. Implications for the use of this scale in both applied and research settings are discussed. PsycINFO Database Record (c) 2013 APA, all rights reserved.

The Quasi-Biennial Oscillation and Ross River virus incidence in Queensland, Australia.

PubMed

Done, Sinead J; Holbrook, Neil J; Beggs, Paul J

2002-09-01

Ross River virus (RRV) is the most important vector-borne disease in Australia. The National Notifiable Diseases Surveillance System has confirmed that its incidence is often greatest in the state of Queensland, where there is a clear seasonal pattern as well as interannual variability. Previous studies have examined relationships between large-scale climate fluctuations (such as El Niño Southern Oscillation) and vector-borne disease. No previous study has examined such relationships with the Quasi-Biennial Oscillation (QBO), another large-scale climate fluctuation. We employ time-series analysis techniques to investigate cycles inherent in monthly RRV incidence in Queensland, Australia, from January 1991 to December 1997 inclusive. The presence of a quasi-biennial cycle in the RRV time series that is out of phase with the climatic QBO is described. Quantitative analyses using correlograms and periodograms demonstrate that the quasi-biennial cycle in the RRV time series is statistically significant, at the 95% level, above the noise. Together with the seasonal cycle, the quasi-biennial cycle accounts for 77% of the variance in Queensland RRV cases. Regression analysis of QBO and summer rainfall in three climatic zones of Queensland indicates a significant association between QBO and rainfall in the subtropical southeastern part of the state. These results suggest an indirect influence of the QBO on RRV incidence in Queensland, via its influence on climate in this region. Our findings indicate that the QBO may be a useful predictor of RRV at several months lead, and might be used by public health authorities in the management and prevention of this disease.

Delayed detection of climate mitigation benefits due to climate inertia and variability.

PubMed

Tebaldi, Claudia; Friedlingstein, Pierre

2013-10-22

Climate change mitigation acts by reducing greenhouse gas emissions, and thus curbing, or even reversing, the increase in their atmospheric concentration. This reduces the associated anthropogenic radiative forcing, and hence the size of the warming. Because of the inertia and internal variability affecting the climate system and the global carbon cycle, it is unlikely that a reduction in warming would be immediately discernible. Here we use 21st century simulations from the latest ensemble of Earth System Model experiments to investigate and quantify when mitigation becomes clearly discernible. We use one of the scenarios as a reference for a strong mitigation strategy, Representative Concentration Pathway (RCP) 2.6 and compare its outcome with either RCP4.5 or RCP8.5, both of which are less severe mitigation pathways. We analyze global mean atmospheric CO2, and changes in annually and seasonally averaged surface temperature at global and regional scales. For global mean surface temperature, the median detection time of mitigation is about 25-30 y after RCP2.6 emissions depart from the higher emission trajectories. This translates into detection of a mitigation signal by 2035 or 2045, depending on whether the comparison is with RCP8.5 or RCP4.5, respectively. The detection of climate benefits of emission mitigation occurs later at regional scales, with a median detection time between 30 and 45 y after emission paths separate. Requiring a 95% confidence level induces a delay of several decades, bringing detection time toward the end of the 21st century.

Characterizing sources of uncertainty from global climate models and downscaling techniques

USGS Publications Warehouse

Wootten, Adrienne; Terando, Adam; Reich, Brian J.; Boyles, Ryan; Semazzi, Fred

2017-01-01

In recent years climate model experiments have been increasingly oriented towards providing information that can support local and regional adaptation to the expected impacts of anthropogenic climate change. This shift has magnified the importance of downscaling as a means to translate coarse-scale global climate model (GCM) output to a finer scale that more closely matches the scale of interest. Applying this technique, however, introduces a new source of uncertainty into any resulting climate model ensemble. Here we present a method, based on a previously established variance decomposition method, to partition and quantify the uncertainty in climate model ensembles that is attributable to downscaling. We apply the method to the Southeast U.S. using five downscaled datasets that represent both statistical and dynamical downscaling techniques. The combined ensemble is highly fragmented, in that only a small portion of the complete set of downscaled GCMs and emission scenarios are typically available. The results indicate that the uncertainty attributable to downscaling approaches ~20% for large areas of the Southeast U.S. for precipitation and ~30% for extreme heat days (> 35°C) in the Appalachian Mountains. However, attributable quantities are significantly lower for time periods when the full ensemble is considered but only a sub-sample of all models are available, suggesting that overconfidence could be a serious problem in studies that employ a single set of downscaled GCMs. We conclude with recommendations to advance the design of climate model experiments so that the uncertainty that accrues when downscaling is employed is more fully and systematically considered.

ESiWACE: A Center of Excellence for HPC applications to support cloud resolving earth system modelling

NASA Astrophysics Data System (ADS)

Biercamp, Joachim; Adamidis, Panagiotis; Neumann, Philipp

2017-04-01

With the exa-scale era approaching, length and time scales used for climate research on one hand and numerical weather prediction on the other hand blend into each other. The Centre of Excellence in Simulation of Weather and Climate in Europe (ESiWACE) represents a European consortium comprising partners from climate, weather and HPC in their effort to address key scientific challenges that both communities have in common. A particular challenge is to reach global models with spatial resolutions that allow simulating convective clouds and small-scale ocean eddies. These simulations would produce better predictions of trends and provide much more fidelity in the representation of high-impact regional events. However, running such models in operational mode, i.e with sufficient throughput in ensemble mode clearly will require exa-scale computing and data handling capability. We will discuss the ESiWACE initiative and relate it to work-in-progress on high-resolution simulations in Europe. We present recent strong scalability measurements from ESiWACE to demonstrate current computability in weather and climate simulation. A special focus in this particular talk is on the Icosahedal Nonhydrostatic (ICON) model used for a comparison of high resolution regional and global simulations with high quality observation data. We demonstrate that close-to-optimal parallel efficiency can be achieved in strong scaling global resolution experiments on Mistral/DKRZ, e.g. 94% for 5km resolution simulations using 36k cores on Mistral/DKRZ. Based on our scalability and high-resolution experiments, we deduce and extrapolate future capabilities for ICON that are expected for weather and climate research at exascale.

Examination of Daily Weather in the NCAR CCM

NASA Astrophysics Data System (ADS)

Cocke, S. D.

2006-05-01

The NCAR CCM is one of the most extensively studied climate models in the scientific community. However, most studies focus primarily on the long term mean behavior, typically monthly or longer time scales. In this study we examine the daily weather in the GCM by performing a series of daily or weekly 10 day forecasts for one year at moderate (T63) and high (T126) resolution. The model is initialized with operational "AVN" and ECMWF analyses, and model performance is compared to that of major operational centers, using conventional skill scores used by the major centers. Such a detailed look at the CCM at shorter time scales may lead to improvements in physical parameterizations, which may in turn lead to improved climate simulations. One finding from this study is that the CCM has a significant drying tendency in the lower troposphere compared to the operational analyses. Another is that the large scale predictability of the GCM is competitive with most of the operational models, particularly in the southern hemisphere.