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.

Creation of Synthetic Surface Temperature and Precipitation Ensembles Through A Computationally Efficient, Mixed Method Approach

NASA Astrophysics Data System (ADS)

Hartin, C.; Lynch, C.; Kravitz, B.; Link, R. P.; Bond-Lamberty, B. P.

2017-12-01

Typically, uncertainty quantification of internal variability relies on large ensembles of climate model runs under multiple forcing scenarios or perturbations in a parameter space. Computationally efficient, standard pattern scaling techniques only generate one realization and do not capture the complicated dynamics of the climate system (i.e., stochastic variations with a frequency-domain structure). In this study, we generate large ensembles of climate data with spatially and temporally coherent variability across a subselection of Coupled Model Intercomparison Project Phase 5 (CMIP5) models. First, for each CMIP5 model we apply a pattern emulation approach to derive the model response to external forcing. We take all the spatial and temporal variability that isn't explained by the emulator and decompose it into non-physically based structures through use of empirical orthogonal functions (EOFs). Then, we perform a Fourier decomposition of the EOF projection coefficients to capture the input fields' temporal autocorrelation so that our new emulated patterns reproduce the proper timescales of climate response and "memory" in the climate system. Through this 3-step process, we derive computationally efficient climate projections consistent with CMIP5 model trends and modes of variability, which address a number of deficiencies inherent in the ability of pattern scaling to reproduce complex climate model behavior.

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

Response of wheat yield in Spain to large-scale patterns

NASA Astrophysics Data System (ADS)

Hernandez-Barrera, Sara; Rodriguez-Puebla, Concepcion

2016-04-01

Crops are vulnerable to extreme climate conditions as drought, heat stress and frost risk. In previous study we have quantified the influence of these climate conditions for winter wheat in Spain (Hernandez-Barrera et al. 2015). The climate extremes respond to large-scale atmospheric and oceanic patterns. Therefore, a question emerges in our investigation: How large-scale patterns affect wheat yield? Obtaining and understanding these relationships require different approaches. In this study, we first obtained the leading mode of observed wheat yield variability to characterize the common variability over different provinces in Spain. Then, the wheat variability is related to different modes of mean sea level pressure, jet stream and sea surface temperature by using Partial Least-Squares, which captures the relevant climate drivers accounting for variations in wheat yield from sowing to harvesting. We used the ERA-Interim reanalysis data and the Extended Reconstructed Sea Surface Temperature (SST) (ERSST v3b). The derived model provides insight about the teleconnections between wheat yield and atmospheric and oceanic circulations, which is considered to project the wheat yield trend under global warming using outputs of twelve climate models corresponding to the Coupled Models Intercomparison Project phase 5 (CMIP5). Hernandez-Barrera S., C. Rodríguez-Puebla and A.J. Challinor. Effects of diurnal temperature range and drought on wheat yield in Spain. Theoretical and Applied Climatology (submitted)

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.

Climate-driven C4 plant distributions in China: divergence in C4 taxa

PubMed Central

Wang, Renzhong; Ma, Linna

2016-01-01

There have been debates on the driving factors of C4 plant expansion, such as PCO2 decline in the late Micocene and warmer climate and precipitation at large-scale modern ecosystems. These disputes are mainly due to the lack of direct evidence and extensive data analysis. Here we use mass flora data to explore the driving factors of C4 distribution and divergent patterns for different C4 taxa at continental scale in China. The results display that it is mean annual climate variables driving C4 distribution at present-day vegetation. Mean annual temperature is the critical restriction of total C4 plants and the precipitation gradients seem to have much less impact. Grass and sedge C4 plants are largely restricted to mean annual temperature and precipitation respectively, while Chenopod C4 plants are strongly restricted by aridity in China. Separate regression analysis can succeed to detect divergences of climate distribution patterns of C4 taxa at global scale. PMID:27302686

Synoptic circulation and temperature pattern during severe wildland fires

Treesearch

Warren E. Heilman

1996-01-01

Large-scale changes in the atmosphere associated with a globally changed climate and changes in climatic variability may have important regional impacts on the frequency and severity of wildland fires in the future.

The spatiotemporal changes in precipitation extremes over Canada and their connections to large-scale climate patterns

NASA Astrophysics Data System (ADS)

Yang, Y.; Gan, T. Y.; Tan, X.

2017-12-01

In the past few decades, there have been more extreme climate events around the world, and Canada has also suffered from numerous extreme precipitation events. In this paper, trend analysis, change point analysis, probability distribution function, principal component analysis and wavelet analysis were used to investigate the spatial and temporal patterns of extreme precipitation in Canada. Ten extreme precipitation indices were calculated using long-term daily precipitation data from 164 gauging stations. Several large-scale climate patterns such as El Niño-Southern Oscillation (ENSO), Pacific Decadal Oscillation (PDO), Pacific-North American (PNA), and North Atlantic Oscillation (NAO) were selected to analyze the relationships between extreme precipitation and climate indices. Convective Available Potential Energy (CAPE), specific humidity, and surface temperature were employed to investigate the potential causes of the trends.The results show statistically significant positive trends for most indices, which indicate increasing extreme precipitation. The majority of indices display more increasing trends along the southern border of Canada while decreasing trends dominate in the central Canadian Prairies (CP). In addition, strong connections are found between the extreme precipitation and climate indices and the effects of climate pattern differ for each region. The seasonal CAPE, specific humidity, and temperature are found to be closely related to Canadian extreme precipitation.

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.

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

Sensitivity of tree ring growth to local and large-scale climate variability in a region of Southeastern Brazil

NASA Astrophysics Data System (ADS)

Venegas-González, Alejandro; Chagas, Matheus Peres; Anholetto Júnior, Claudio Roberto; Alvares, Clayton Alcarde; Roig, Fidel Alejandro; Tomazello Filho, Mario

2016-01-01

We explored the relationship between tree growth in two tropical species and local and large-scale climate variability in Southeastern Brazil. Tree ring width chronologies of Tectona grandis (teak) and Pinus caribaea (Caribbean pine) trees were compared with local (Water Requirement Satisfaction Index—WRSI, Standardized Precipitation Index—SPI, and Palmer Drought Severity Index—PDSI) and large-scale climate indices that analyze the equatorial pacific sea surface temperature (Trans-Niño Index-TNI and Niño-3.4-N3.4) and atmospheric circulation variations in the Southern Hemisphere (Antarctic Oscillation-AAO). Teak trees showed positive correlation with three indices in the current summer and fall. A significant correlation between WRSI index and Caribbean pine was observed in the dry season preceding tree ring formation. The influence of large-scale climate patterns was observed only for TNI and AAO, where there was a radial growth reduction in months preceding the growing season with positive values of the TNI in teak trees and radial growth increase (decrease) during December (March) to February (May) of the previous (current) growing season with positive phase of the AAO in teak (Caribbean pine) trees. The development of a new dendroclimatological study in Southeastern Brazil sheds light to local and large-scale climate influence on tree growth in recent decades, contributing in future climate change studies.

Cryptic biodiversity loss linked to global climate change

NASA Astrophysics Data System (ADS)

Bálint, M.; Domisch, S.; Engelhardt, C. H. M.; Haase, P.; Lehrian, S.; Sauer, J.; Theissinger, K.; Pauls, S. U.; Nowak, C.

2011-09-01

Global climate change (GCC) significantly affects distributional patterns of organisms, and considerable impacts on biodiversity are predicted for the next decades. Inferred effects include large-scale range shifts towards higher altitudes and latitudes, facilitation of biological invasions and species extinctions. Alterations of biotic patterns caused by GCC have usually been predicted on the scale of taxonomically recognized morphospecies. However, the effects of climate change at the most fundamental level of biodiversity--intraspecific genetic diversity--remain elusive. Here we show that the use of morphospecies-based assessments of GCC effects will result in underestimations of the true scale of biodiversity loss. Species distribution modelling and assessments of mitochondrial DNA variability in nine montane aquatic insect species in Europe indicate that future range contractions will be accompanied by severe losses of cryptic evolutionary lineages and genetic diversity within these lineages. These losses greatly exceed those at the scale of morphospecies. We also document that the extent of range reduction may be a useful proxy when predicting losses of genetic diversity. Our results demonstrate that intraspecific patterns of genetic diversity should be considered when estimating the effects of climate change on biodiversity.

Hydroclimatic Extremes and Cholera Dynamics in the 21st Century

NASA Astrophysics Data System (ADS)

Akanda, A. S.; Jutla, A. S.; Islam, S.

2012-12-01

Cholera, an acute water-borne diarrheal illness, has reemerged as a significant health threat across much of the developing world. Despite major advances in the ecological and the microbiological understanding of the causative agent, V. cholerae, the role of the underlying climatic and environmental processes in propagating transmission is not adequately understood. Recent findings suggest a more prominent role of hydroclimatic extremes - droughts and floods - on the unique dual cholera peaks in the Bengal Delta region of South Asia, the native homeland of cholera. Increasing water scarcity and abundance, and coastal sea-level rise, influenced by changing climate patterns and large-scale climatic phenomena, is likely to adversely impact cholera transmission in South Asia. We focus on understanding how associated changes in macro-scale conditions in this region will impact micro-scale processes related to cholera in coming decades. We use the PRECIS Regional Climate Model over the Ganges-Brahmaputra-Meghna (GBM) basin region to simulate detailed high resolution projections of climate patterns for the 21st century. Precipitation outputs are analyzed for the 1980-2040 period to identify the trends and changes in hydroclimatic extremes and potential impacts on cholera dynamics over the next three decades (2010-2040), in relation to the cholera surveillance operations over the past three decades (1980-2010). We find that an increased number of extreme precipitation events with prolonged dry periods in the Ganges basin region will likely adversely affect dry season cholera outbreaks. Increased monsoon precipitation volumes in the Brahmaputra basin catchments are likely to cause record floods and subsequently trigger large epidemics in downstream areas. Our results provide new insight by identifying the changes in the two distinctly different, pre and post monsoon, cholera transmission mechanisms related to large-scale climatic controls that prevail in the region. A quantitative understanding of the changes in seasonal hydroclimatic controls and underlying dominant processes will form the basis for forecasting future epidemic cholera outbreaks in light of changing climate patterns.

Climatic and weather factors affecting fire occurrence and behavior

Treesearch

Randall P. Benson; John O. Roads; David R. Weise

2009-01-01

Weather and climate have a profound influence on wildland fire ignition potential, fire behavior, and fire severity. Local weather and climate are affected by large-scale patterns of winds over the hemispheres that predispose wildland fuels to fire. The characteristics of wildland fuels, especially the moisture content, ultimately determine fire behavior and the impact...

Large-Scale Ocean Circulation-Cloud Interactions Reduce the Pace of Transient Climate Change

NASA Technical Reports Server (NTRS)

Trossman, D. S.; Palter, J. B.; Merlis, T. M.; Huang, Y.; Xia, Y.

2016-01-01

Changes to the large scale oceanic circulation are thought to slow the pace of transient climate change due, in part, to their influence on radiative feedbacks. Here we evaluate the interactions between CO2-forced perturbations to the large-scale ocean circulation and the radiative cloud feedback in a climate model. Both the change of the ocean circulation and the radiative cloud feedback strongly influence the magnitude and spatial pattern of surface and ocean warming. Changes in the ocean circulation reduce the amount of transient global warming caused by the radiative cloud feedback by helping to maintain low cloud coverage in the face of global warming. The radiative cloud feedback is key in affecting atmospheric meridional heat transport changes and is the dominant radiative feedback mechanism that responds to ocean circulation change. Uncertainty in the simulated ocean circulation changes due to CO2 forcing may contribute a large share of the spread in the radiative cloud feedback among climate models.

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.

Characterizing Temperature Variability and Associated Large Scale Meteorological Patterns Across South America

NASA Astrophysics Data System (ADS)

Detzer, J.; Loikith, P. C.; Mechoso, C. R.; Barkhordarian, A.; Lee, H.

2017-12-01

South America's climate varies considerably owing to its large geographic range and diverse topographical features. Spanning the tropics to the mid-latitudes and from high peaks to tropical rainforest, the continent experiences an array of climate and weather patterns. Due to this considerable spatial extent, assessing temperature variability at the continent scale is particularly challenging. It is well documented in the literature that temperatures have been increasing across portions of South America in recent decades, and while there have been many studies that have focused on precipitation variability and change, temperature has received less scientific attention. Therefore, a more thorough understanding of the drivers of temperature variability is critical for interpreting future change. First, k-means cluster analysis is used to identify four primary modes of temperature variability across the continent, stratified by season. Next, composites of large scale meteorological patterns (LSMPs) are calculated for months assigned to each cluster. Initial results suggest that LSMPs, defined using meteorological variables such as sea level pressure (SLP), geopotential height, and wind, are able to identify synoptic scale mechanisms important for driving temperature variability at the monthly scale. Some LSMPs indicate a relationship with known recurrent modes of climate variability. For example, composites of geopotential height suggest that the Southern Annular Mode is an important, but not necessarily dominant, component of temperature variability over southern South America. This work will be extended to assess the drivers of temperature extremes across South America.

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.

A CONCEPTUAL FRAMEWORK FOR SELECTING AND ANALYZING STRESSOR DATA TO STUDY SPECIES RICHNESS AT LARGE SPATIAL SCALES

EPA Science Inventory

In this paper we develop a conceptual framework for selecting stressor data and anlyzing their relationship to geographic patterns of species richness at large spatial scales. Aspects of climate and topography, which are not stressors per se, have been most strongly linked with g...

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.

Biological communities in San Francisco Bay track large-scale climate forcing over the North Pacific

NASA Astrophysics Data System (ADS)

Cloern, James E.; Hieb, Kathryn A.; Jacobson, Teresa; Sansó, Bruno; Di Lorenzo, Emanuele; Stacey, Mark T.; Largier, John L.; Meiring, Wendy; Peterson, William T.; Powell, Thomas M.; Winder, Monika; Jassby, Alan D.

2010-11-01

Long-term observations show that fish and plankton populations in the ocean fluctuate in synchrony with large-scale climate patterns, but similar evidence is lacking for estuaries because of shorter observational records. Marine fish and invertebrates have been sampled in San Francisco Bay since 1980 and exhibit large, unexplained population changes including record-high abundances of common species after 1999. Our analysis shows that populations of demersal fish, crabs and shrimp covary with the Pacific Decadal Oscillation (PDO) and North Pacific Gyre Oscillation (NPGO), both of which reversed signs in 1999. A time series model forced by the atmospheric driver of NPGO accounts for two-thirds of the variability in the first principal component of species abundances, and generalized linear models forced by PDO and NPGO account for most of the annual variability of individual species. We infer that synchronous shifts in climate patterns and community variability in San Francisco Bay are related to changes in oceanic wind forcing that modify coastal currents, upwelling intensity, surface temperature, and their influence on recruitment of marine species that utilize estuaries as nursery habitat. Ecological forecasts of estuarine responses to climate change must therefore consider how altered patterns of atmospheric forcing across ocean basins influence coastal oceanography as well as watershed hydrology.

How uncertain are climate model projections of water availability indicators across the Middle East?

PubMed

Hemming, Debbie; Buontempo, Carlo; Burke, Eleanor; Collins, Mat; Kaye, Neil

2010-11-28

The projection of robust regional climate changes over the next 50 years presents a considerable challenge for the current generation of climate models. Water cycle changes are particularly difficult to model in this area because major uncertainties exist in the representation of processes such as large-scale and convective rainfall and their feedback with surface conditions. We present climate model projections and uncertainties in water availability indicators (precipitation, run-off and drought index) for the 1961-1990 and 2021-2050 periods. Ensembles from two global climate models (GCMs) and one regional climate model (RCM) are used to examine different elements of uncertainty. Although all three ensembles capture the general distribution of observed annual precipitation across the Middle East, the RCM is consistently wetter than observations, especially over the mountainous areas. All future projections show decreasing precipitation (ensemble median between -5 and -25%) in coastal Turkey and parts of Lebanon, Syria and Israel and consistent run-off and drought index changes. The Intergovernmental Panel on Climate Change (IPCC) Fourth Assessment Report (AR4) GCM ensemble exhibits drying across the north of the region, whereas the Met Office Hadley Centre work Quantifying Uncertainties in Model ProjectionsAtmospheric (QUMP-A) GCM and RCM ensembles show slight drying in the north and significant wetting in the south. RCM projections also show greater sensitivity (both wetter and drier) and a wider uncertainty range than QUMP-A. The nature of these uncertainties suggests that both large-scale circulation patterns, which influence region-wide drying/wetting patterns, and regional-scale processes, which affect localized water availability, are important sources of uncertainty in these projections. To reduce large uncertainties in water availability projections, it is suggested that efforts would be well placed to focus on the understanding and modelling of both large-scale processes and their teleconnections with Middle East climate and localized processes involved in orographic precipitation.

Satellite-based characterization of climatic conditions before large-scale general flowering events in Peninsular Malaysia

PubMed Central

Azmy, Muna Maryam; Hashim, Mazlan; Numata, Shinya; Hosaka, Tetsuro; Noor, Nur Supardi Md.; Fletcher, Christine

2016-01-01

General flowering (GF) is a unique phenomenon wherein, at irregular intervals, taxonomically diverse trees in Southeast Asian dipterocarp forests synchronize their reproduction at the community level. Triggers of GF, including drought and low minimum temperatures a few months previously has been limitedly observed across large regional scales due to lack of meteorological stations. Here, we aim to identify the climatic conditions that trigger large-scale GF in Peninsular Malaysia using satellite sensors, Tropical Rainfall Measuring Mission (TRMM) and Moderate Resolution Imaging Spectroradiometer (MODIS), to evaluate the climatic conditions of focal forests. We observed antecedent drought, low temperature and high photosynthetic radiation conditions before large-scale GF events, suggesting that large-scale GF events could be triggered by these factors. In contrast, we found higher-magnitude GF in forests where lower precipitation preceded large-scale GF events. GF magnitude was also negatively influenced by land surface temperature (LST) for a large-scale GF event. Therefore, we suggest that spatial extent of drought may be related to that of GF forests, and that the spatial pattern of LST may be related to that of GF occurrence. With significant new findings and other results that were consistent with previous research we clarified complicated environmental correlates with the GF phenomenon. PMID:27561887

Satellite-based characterization of climatic conditions before large-scale general flowering events in Peninsular Malaysia.

PubMed

Azmy, Muna Maryam; Hashim, Mazlan; Numata, Shinya; Hosaka, Tetsuro; Noor, Nur Supardi Md; Fletcher, Christine

2016-08-26

General flowering (GF) is a unique phenomenon wherein, at irregular intervals, taxonomically diverse trees in Southeast Asian dipterocarp forests synchronize their reproduction at the community level. Triggers of GF, including drought and low minimum temperatures a few months previously has been limitedly observed across large regional scales due to lack of meteorological stations. Here, we aim to identify the climatic conditions that trigger large-scale GF in Peninsular Malaysia using satellite sensors, Tropical Rainfall Measuring Mission (TRMM) and Moderate Resolution Imaging Spectroradiometer (MODIS), to evaluate the climatic conditions of focal forests. We observed antecedent drought, low temperature and high photosynthetic radiation conditions before large-scale GF events, suggesting that large-scale GF events could be triggered by these factors. In contrast, we found higher-magnitude GF in forests where lower precipitation preceded large-scale GF events. GF magnitude was also negatively influenced by land surface temperature (LST) for a large-scale GF event. Therefore, we suggest that spatial extent of drought may be related to that of GF forests, and that the spatial pattern of LST may be related to that of GF occurrence. With significant new findings and other results that were consistent with previous research we clarified complicated environmental correlates with the GF phenomenon.

Evaluating the fidelity of CMIP5 models in producing large-scale meteorological patterns over the Northwestern United States

NASA Astrophysics Data System (ADS)

Lintner, B. R.; Loikith, P. C.; Pike, M.; Aragon, C.

2017-12-01

Climate change information is increasingly required at impact-relevant scales. However, most state-of-the-art climate models are not of sufficiently high spatial resolution to resolve features explicitly at such scales. This challenge is particularly acute in regions of complex topography, such as the Pacific Northwest of the United States. To address this scale mismatch problem, we consider large-scale meteorological patterns (LSMPs), which can be resolved by climate models and associated with the occurrence of local scale climate and climate extremes. In prior work, using self-organizing maps (SOMs), we computed LSMPs over the northwestern United States (NWUS) from daily reanalysis circulation fields and further related these to the occurrence of observed extreme temperatures and precipitation: SOMs were used to group LSMPs into 12 nodes or clusters spanning the continuum of synoptic variability over the regions. Here this observational foundation is utilized as an evaluation target for a suite of global climate models from the Fifth Phase of the Coupled Model Intercomparison Project (CMIP5). Evaluation is performed in two primary ways. First, daily model circulation fields are assigned to one of the 12 reanalysis nodes based on minimization of the mean square error. From this, a bulk model skill score is computed measuring the similarity between the model and reanalysis nodes. Next, SOMs are applied directly to the model output and compared to the nodes obtained from reanalysis. Results reveal that many of the models have LSMPs analogous to the reanalysis, suggesting that the models reasonably capture observed daily synoptic states.

Spatio-temporal variability of dryness/wetness in the middle and lower reaches of the Yangtze River Basin and correlation with large-scale climatic factors

NASA Astrophysics Data System (ADS)

Chen, Xinchi; Zhang, Liping; Zou, Lei; Shan, Lijie; She, Dunxian

2018-02-01

The middle and lower reaches of the Yangtze River Basin (MLYR) are greatly affected by frequent drought/flooding events and abrupt alternations of these events in China. The purpose of this study is to analyze the spatial and temporal variability of dryness/wetness based on the data obtained from 75 meteorological stations in the MLYR for the period 1960-2015 and investigate the correlations between dryness/wetness and atmospheric circulation factors. The empirical orthogonal function method was applied in this study based on the monthly Standardized Precipitation Index at a 12-month time scale. The first leading pattern captured the same characteristics of dryness/wetness over the entire MLYR area and accounted for 40.87% of the total variance. Both the second and third leading patterns manifested as regional features of variability over the entire MLYR. The cross-wavelet transform method was applied to explore the potential relationship between the three leading patterns and the large-scale climate factors, and finally the relationships between drought/wetness events and climate factors were also analyzed. Our results indicated that the main patterns of dryness/wetness were primarily associated with the Niño 3.4, Indian Ocean Dipole, Southern Oscillation Index and Northern Oscillation Index, with the first pattern exhibiting noticeable periods and remarkable changes in phase with the indices.

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.

Relationships between large-scale circulation patterns and carbon dioxide exchange by a deciduous forest

NASA Astrophysics Data System (ADS)

Zhang, Jingyong; Wu, Lingyun; Huang, Gang; Notaro, Michael

2011-02-01

In this study, we focus on a deciduous forest in central Massachusetts and investigate the relationships between global climate indices and CO2 exchange using eddy-covariance flux measurements from 1992 to 2007. Results suggest that large-scale circulation patterns influence the annual CO2 exchange in the forest through their effects on the local surface climate. Annual gross ecosystem exchange (GEE) in the forest is closely associated with spring El Niño-Southern Oscillation (ENSO) and Pacific Decadal Oscillation (PDO), previous fall Atlantic Multidecadal Oscillation (AMO), and previous winter East Pacific-North Pacific (EP-NP) pattern. Annual net ecosystem exchange (NEE) responds to previous fall AMO and PDO, while annual respiration (R) is impacted by previous fall ENSO and Pacific/North American Oscillation (PNA). Regressions based on these relationships are developed to simulate the annual GEE, NEE, and R. To avoid problems of multicollinearity, we compute a "Composite Index for GEE (CIGEE)" based on a linear combination of spring ENSO and PDO, fall AMO, and winter EP-NP and a "Composite Index for R (CIR)" based on a linear combination of fall ENSO and PNA. CIGEE, CIR, and fall AMO and PDO can explain 41, 27, and 40% of the variance of the annual GEE, R, and NEE, respectively. We further apply the methodology to two other northern midlatitude forests and find that interannual variabilities in NEE of the two forests are largely controlled by large-scale circulation patterns. This study suggests that global climate indices provide the potential for predicting CO2 exchange variability in the northern midlatitude forests.

Impacts of climate variability and future climate change on harmful algal blooms and human health.

PubMed

Moore, Stephanie K; Trainer, Vera L; Mantua, Nathan J; Parker, Micaela S; Laws, Edward A; Backer, Lorraine C; Fleming, Lora E

2008-11-07

Anthropogenically-derived increases in atmospheric greenhouse gas concentrations have been implicated in recent climate change, and are projected to substantially impact the climate on a global scale in the future. For marine and freshwater systems, increasing concentrations of greenhouse gases are expected to increase surface temperatures, lower pH, and cause changes to vertical mixing, upwelling, precipitation, and evaporation patterns. The potential consequences of these changes for harmful algal blooms (HABs) have received relatively little attention and are not well understood. Given the apparent increase in HABs around the world and the potential for greater problems as a result of climate change and ocean acidification, substantial research is needed to evaluate the direct and indirect associations between HABs, climate change, ocean acidification, and human health. This research will require a multidisciplinary approach utilizing expertise in climatology, oceanography, biology, epidemiology, and other disciplines. We review the interactions between selected patterns of large-scale climate variability and climate change, oceanic conditions, and harmful algae.

Impacts of climate variability and future climate change on harmful algal blooms and human health

PubMed Central

Moore, Stephanie K; Trainer, Vera L; Mantua, Nathan J; Parker, Micaela S; Laws, Edward A; Backer, Lorraine C; Fleming, Lora E

2008-01-01

Anthropogenically-derived increases in atmospheric greenhouse gas concentrations have been implicated in recent climate change, and are projected to substantially impact the climate on a global scale in the future. For marine and freshwater systems, increasing concentrations of greenhouse gases are expected to increase surface temperatures, lower pH, and cause changes to vertical mixing, upwelling, precipitation, and evaporation patterns. The potential consequences of these changes for harmful algal blooms (HABs) have received relatively little attention and are not well understood. Given the apparent increase in HABs around the world and the potential for greater problems as a result of climate change and ocean acidification, substantial research is needed to evaluate the direct and indirect associations between HABs, climate change, ocean acidification, and human health. This research will require a multidisciplinary approach utilizing expertise in climatology, oceanography, biology, epidemiology, and other disciplines. We review the interactions between selected patterns of large-scale climate variability and climate change, oceanic conditions, and harmful algae. PMID:19025675

Selectivity by host plants affects the distribution of arbuscular mycorrhizal fungi: evidence from ITS rDNA sequence metadata.

PubMed

Yang, Haishui; Zang, Yanyan; Yuan, Yongge; Tang, Jianjun; Chen, Xin

2012-04-12

Arbuscular mycorrhizal fungi (AMF) can form obligate symbioses with the vast majority of land plants, and AMF distribution patterns have received increasing attention from researchers. At the local scale, the distribution of AMF is well documented. Studies at large scales, however, are limited because intensive sampling is difficult. Here, we used ITS rDNA sequence metadata obtained from public databases to study the distribution of AMF at continental and global scales. We also used these sequence metadata to investigate whether host plant is the main factor that affects the distribution of AMF at large scales. We defined 305 ITS virtual taxa (ITS-VTs) among all sequences of the Glomeromycota by using a comprehensive maximum likelihood phylogenetic analysis. Each host taxonomic order averaged about 53% specific ITS-VTs, and approximately 60% of the ITS-VTs were host specific. Those ITS-VTs with wide host range showed wide geographic distribution. Most ITS-VTs occurred in only one type of host functional group. The distributions of most ITS-VTs were limited across ecosystem, across continent, across biogeographical realm, and across climatic zone. Non-metric multidimensional scaling analysis (NMDS) showed that AMF community composition differed among functional groups of hosts, and among ecosystem, continent, biogeographical realm, and climatic zone. The Mantel test showed that AMF community composition was significantly correlated with plant community composition among ecosystem, among continent, among biogeographical realm, and among climatic zone. The structural equation modeling (SEM) showed that the effects of ecosystem, continent, biogeographical realm, and climatic zone were mainly indirect on AMF distribution, but plant had strongly direct effects on AMF. The distribution of AMF as indicated by ITS rDNA sequences showed a pattern of high endemism at large scales. This pattern indicates high specificity of AMF for host at different scales (plant taxonomic order and functional group) and high selectivity from host plants for AMF. The effects of ecosystemic, biogeographical, continental and climatic factors on AMF distribution might be mediated by host plants.

Dual impacts of climate change: forest migration and turnover through life history.

PubMed

Zhu, Kai; Woodall, Christopher W; Ghosh, Souparno; Gelfand, Alan E; Clark, James S

2014-01-01

Tree species are predicted to track future climate by shifting their geographic distributions, but climate-mediated migrations are not apparent in a recent continental-scale analysis. To better understand the mechanisms of a possible migration lag, we analyzed relative recruitment patterns by comparing juvenile and adult tree abundances in climate space. One would expect relative recruitment to be higher in cold and dry climates as a result of tree migration with juveniles located further poleward than adults. Alternatively, relative recruitment could be higher in warm and wet climates as a result of higher tree population turnover with increased temperature and precipitation. Using the USDA Forest Service's Forest Inventory and Analysis data at regional scales, we jointly modeled juvenile and adult abundance distributions for 65 tree species in climate space of the eastern United States. We directly compared the optimal climate conditions for juveniles and adults, identified the climates where each species has high relative recruitment, and synthesized relative recruitment patterns across species. Results suggest that for 77% and 83% of the tree species, juveniles have higher optimal temperature and optimal precipitation, respectively, than adults. Across species, the relative recruitment pattern is dominated by relatively more abundant juveniles than adults in warm and wet climates. These different abundance-climate responses through life history are consistent with faster population turnover and inconsistent with the geographic trend of large-scale tree migration. Taken together, this juvenile-adult analysis suggests that tree species might respond to climate change by having faster turnover as dynamics accelerate with longer growing seasons and higher temperatures, before there is evidence of poleward migration at biogeographic scales.

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

Spatial Patterns in Water Temperature in Pacific Northwest Rivers: Diversity at Multiple Scales and Potential Influence of Climate Change

NASA Astrophysics Data System (ADS)

Torgersen, C. E.; Fullerton, A.; Lawler, J. J.; Ebersole, J. L.; Leibowitz, S. G.; Steel, E. A.; Beechie, T. J.; Faux, R.

2016-12-01

Understanding spatial patterns in water temperature will be essential for evaluating vulnerability of aquatic biota to future climate and for identifying and protecting diverse thermal habitats. We used high-resolution remotely sensed water temperature data for over 16,000 km of 2nd to 7th-order rivers throughout the Pacific Northwest and California to evaluate spatial patterns of summertime water temperature at multiple spatial scales. We found a diverse and geographically distributed suite of whole-river patterns. About half of rivers warmed asymptotically in a downstream direction, whereas the rest exhibited complex and unique spatial patterns. Patterns were associated with both broad-scale hydroclimatic variables as well as characteristics unique to each basin. Within-river thermal heterogeneity patterns were highly river-specific; across rivers, median size and spacing of cool patches <15 °C were around 250 m. Patches of this size are large enough for juvenile salmon rearing and for resting during migration, and the distance between patches is well within the movement capabilities of both juvenile and adult salmon. We found considerable thermal heterogeneity at fine spatial scales that may be important to fish that would be missed if data were analyzed at coarser scales. We estimated future thermal heterogeneity and concluded that climate change will cause warmer temperatures overall, but that thermal heterogeneity patterns may remain similar in the future for many rivers. We demonstrated considerable spatial complexity in both current and future water temperature, and resolved spatial patterns that could not have been perceived without spatially continuous data.

Application of regional climate models to the Indian winter monsoon over the western Himalayas.

PubMed

Dimri, A P; Yasunari, T; Wiltshire, A; Kumar, P; Mathison, C; Ridley, J; Jacob, D

2013-12-01

The Himalayan region is characterized by pronounced topographic heterogeneity and land use variability from west to east, with a large variation in regional climate patterns. Over the western part of the region, almost one-third of the annual precipitation is received in winter during cyclonic storms embedded in westerlies, known locally as the western disturbance. In the present paper, the regional winter climate over the western Himalayas is analyzed from simulations produced by two regional climate models (RCMs) forced with large-scale fields from ERA-Interim. The analysis was conducted by the composition of contrasting (wet and dry) winter precipitation years. The findings showed that RCMs could simulate the regional climate of the western Himalayas and represent the atmospheric circulation during extreme precipitation years in accordance with observations. The results suggest the important role of topography in moisture fluxes, transport and vertical flows. Dynamical downscaling with RCMs represented regional climates at the mountain or even event scale. However, uncertainties of precipitation scale and liquid-solid precipitation ratios within RCMs are still large for the purposes of hydrological and glaciological studies. Copyright © 2013 Elsevier B.V. All rights reserved.

Climate Dynamics and Hysteresis at Low and High Obliquity

NASA Astrophysics Data System (ADS)

Colose, C.; Del Genio, A. D.; Way, M.

2017-12-01

We explore the large-scale climate dynamics at low and high obliquity for an Earth-like planet using the ROCKE-3D (Resolving Orbital and Climate Keys of Earth and Extraterrestrial Environments with Dynamics) 3-D General Circulation model being developed at NASA GISS as part of the Nexus for Exoplanet System Science (NExSS) initiative. We highlight the role of ocean heat storage and transport in determining the seasonal cycle at high obliquity, and describe the large-scale circulation and resulting regional climate patterns using both aquaplanet and Earth topographical boundary conditions. Finally, we contrast the hysteresis structure to varying CO2 concentration for a low and high obliquity planet near the outer edge of the habitable zone. We discuss the prospects for habitability for a high obliquity planet susceptible to global glaciation.

Exploring precipitation pattern scaling methodologies and robustness among CMIP5 models

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

Kravitz, Ben; Lynch, Cary; Hartin, Corinne

Pattern scaling is a well-established method for approximating modeled spatial distributions of changes in temperature by assuming a time-invariant pattern that scales with changes in global mean temperature. We compare two methods of pattern scaling for annual mean precipitation (regression and epoch difference) and evaluate which method is better in particular circumstances by quantifying their robustness to interpolation/extrapolation in time, inter-model variations, and inter-scenario variations. Both the regression and epoch-difference methods (the two most commonly used methods of pattern scaling) have good absolute performance in reconstructing the climate model output, measured as an area-weighted root mean square error. We decomposemore » the precipitation response in the RCP8.5 scenario into a CO 2 portion and a non-CO 2 portion. Extrapolating RCP8.5 patterns to reconstruct precipitation change in the RCP2.6 scenario results in large errors due to violations of pattern scaling assumptions when this CO 2-/non-CO 2-forcing decomposition is applied. As a result, the methodologies discussed in this paper can help provide precipitation fields to be utilized in other models (including integrated assessment models or impacts assessment models) for a wide variety of scenarios of future climate change.« less

Exploring precipitation pattern scaling methodologies and robustness among CMIP5 models

DOE PAGES

Kravitz, Ben; Lynch, Cary; Hartin, Corinne; ...

2017-05-12

Pattern scaling is a well-established method for approximating modeled spatial distributions of changes in temperature by assuming a time-invariant pattern that scales with changes in global mean temperature. We compare two methods of pattern scaling for annual mean precipitation (regression and epoch difference) and evaluate which method is better in particular circumstances by quantifying their robustness to interpolation/extrapolation in time, inter-model variations, and inter-scenario variations. Both the regression and epoch-difference methods (the two most commonly used methods of pattern scaling) have good absolute performance in reconstructing the climate model output, measured as an area-weighted root mean square error. We decomposemore » the precipitation response in the RCP8.5 scenario into a CO 2 portion and a non-CO 2 portion. Extrapolating RCP8.5 patterns to reconstruct precipitation change in the RCP2.6 scenario results in large errors due to violations of pattern scaling assumptions when this CO 2-/non-CO 2-forcing decomposition is applied. As a result, the methodologies discussed in this paper can help provide precipitation fields to be utilized in other models (including integrated assessment models or impacts assessment models) for a wide variety of scenarios of future climate change.« less

Links between large-scale circulation patterns and streamflow in Central Europe: A review

NASA Astrophysics Data System (ADS)

Steirou, Eva; Gerlitz, Lars; Apel, Heiko; Merz, Bruno

2017-06-01

We disentangle the relationships between streamflow and large-scale atmospheric circulation in Central Europe (CE), an area affected by climatic influences from different origins (Atlantic, Mediterranean and Continental) and characterized by diverse topography and flow regimes. Our literature review examines in detail the links between mean, high and low flows in CE and large-scale circulation patterns, with focus on two closely related phenomena, the North Atlantic Oscillation (NAO) and the Western-zonal circulation (WC). For both patterns, significant relations, consistent between different studies, are found for large parts of CE. The strongest links are found for the winter season, forming a dipole-like pattern with positive relationships with streamflow north of the Alps and the Carpathians for both indices and negative relationships for the NAO in the south. An influence of winter NAO is also detected in the amplitude and timing of snowmelt flows later in the year. Discharge in CE has further been linked to other large-scale climatic modes such as the Scandinavia pattern (SCA), the East Atlantic/West Russian pattern (EA/WR), the El Niño-Southern Oscillation (ENSO) and synoptic weather patterns such as the Vb weather regime. Different mechanisms suggested in the literature to modulate links between streamflow and the NAO are combined with topographical characteristics of the target area in order to explain the divergent NAO/WC influence on streamflow in different parts of CE. In particular, a precipitation mechanism seems to regulate winter flows in North-Western Germany, an area with short duration of snow cover and with rainfall-generated floods. The precipitation mechanism is also likely in Southern CE, where correlations between the NAO and temperature are low. Finally, in the rest of the study area (Northern CE, Alpine region), a joint precipitation-snow mechanism influences floods not only in winter, but also in the spring/snowmelt period, providing some possibilities for flood forecasting.

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.

Seasonal prediction of US summertime ozone using statistical analysis of large scale climate patterns.

PubMed

Shen, Lu; Mickley, Loretta J

2017-03-07

We develop a statistical model to predict June-July-August (JJA) daily maximum 8-h average (MDA8) ozone concentrations in the eastern United States based on large-scale climate patterns during the previous spring. We find that anomalously high JJA ozone in the East is correlated with these springtime patterns: warm tropical Atlantic and cold northeast Pacific sea surface temperatures (SSTs), as well as positive sea level pressure (SLP) anomalies over Hawaii and negative SLP anomalies over the Atlantic and North America. We then develop a linear regression model to predict JJA MDA8 ozone from 1980 to 2013, using the identified SST and SLP patterns from the previous spring. The model explains ∼45% of the variability in JJA MDA8 ozone concentrations and ∼30% variability in the number of JJA ozone episodes (>70 ppbv) when averaged over the eastern United States. This seasonal predictability results from large-scale ocean-atmosphere interactions. Warm tropical Atlantic SSTs can trigger diabatic heating in the atmosphere and influence the extratropical climate through stationary wave propagation, leading to greater subsidence, less precipitation, and higher temperatures in the East, which increases surface ozone concentrations there. Cooler SSTs in the northeast Pacific are also associated with more summertime heatwaves and high ozone in the East. On average, models participating in the Atmospheric Model Intercomparison Project fail to capture the influence of this ocean-atmosphere interaction on temperatures in the eastern United States, implying that such models would have difficulty simulating the interannual variability of surface ozone in this region.

Seasonal prediction of US summertime ozone using statistical analysis of large scale climate patterns

PubMed Central

Mickley, Loretta J.

2017-01-01

We develop a statistical model to predict June–July–August (JJA) daily maximum 8-h average (MDA8) ozone concentrations in the eastern United States based on large-scale climate patterns during the previous spring. We find that anomalously high JJA ozone in the East is correlated with these springtime patterns: warm tropical Atlantic and cold northeast Pacific sea surface temperatures (SSTs), as well as positive sea level pressure (SLP) anomalies over Hawaii and negative SLP anomalies over the Atlantic and North America. We then develop a linear regression model to predict JJA MDA8 ozone from 1980 to 2013, using the identified SST and SLP patterns from the previous spring. The model explains ∼45% of the variability in JJA MDA8 ozone concentrations and ∼30% variability in the number of JJA ozone episodes (>70 ppbv) when averaged over the eastern United States. This seasonal predictability results from large-scale ocean–atmosphere interactions. Warm tropical Atlantic SSTs can trigger diabatic heating in the atmosphere and influence the extratropical climate through stationary wave propagation, leading to greater subsidence, less precipitation, and higher temperatures in the East, which increases surface ozone concentrations there. Cooler SSTs in the northeast Pacific are also associated with more summertime heatwaves and high ozone in the East. On average, models participating in the Atmospheric Model Intercomparison Project fail to capture the influence of this ocean–atmosphere interaction on temperatures in the eastern United States, implying that such models would have difficulty simulating the interannual variability of surface ozone in this region. PMID:28223483

Climate Drivers of Alaska Summer Stream Temperature

NASA Astrophysics Data System (ADS)

Bieniek, P.; Bhatt, U. S.; Plumb, E. W.; Thoman, R.; Trammell, E. J.

2016-12-01

The temperature of the water in lakes, rivers and streams has wide ranging impacts from local water quality and fish habitats to global climate change. Salmon fisheries in Alaska, a critical source of food in many subsistence communities, are sensitive to large-scale climate variability and river and stream temperatures have also been linked with salmon production in Alaska. Given current and projected climate change, understanding the mechanisms that link the large-scale climate and river and stream temperatures is essential to better understand the changes that may occur with aquatic life in Alaska's waterways on which subsistence users depend. An analysis of Alaska stream temperatures in the context of reanalysis, downscaled, station and other climate data is undertaken in this study to fill that need. Preliminary analysis identified eight stream observation sites with sufficiently long (>15 years) data available for climate-scale analysis in Alaska with one station, Terror Creek in Kodiak, having a 30-year record. Cross-correlation of summer (June-August) water temperatures between the stations are generally high even though they are spread over a large geographic region. Correlation analysis of the Terror Creek summer observations with seasonal sea surface temperatures (SSTs) in the North Pacific broadly resembles the SST anomaly fields typically associated with the Pacific Decadal Oscillation (PDO). A similar result was found for the remaining stations and in both cases PDO-like correlation patterns also occurred in the preceding spring. These preliminary results demonstrate that there is potential to diagnose the mechanisms that link the large-scale climate system and Alaska stream temperatures.

Functional and phylogenetic relatedness in temporary wetland invertebrates: current macroecological patterns and implications for future climatic change scenarios.

PubMed

Ruhí, Albert; Boix, Dani; Gascón, Stéphanie; Sala, Jordi; Batzer, Darold P

2013-01-01

In freshwater ecosystems, species compositions are known to be determined hierarchically by large to small‑scale environmental factors, based on the biological traits of the organisms. However, in ephemeral habitats this heuristic framework remains largely untested. Although temporary wetland faunas are constrained by a local filter (i.e., desiccation), we propose its magnitude may still depend on large-scale climate characteristics. If this is true, climate should be related to the degree of functional and taxonomic relatedness of invertebrate communities inhabiting seasonal wetlands. We tested this hypothesis in two ways. First, based on 52 biological traits for invertebrates, we conducted a case study to explore functional trends among temperate seasonal wetlands differing in the harshness (i.e., dryness) of their dry season. After finding evidence of trait filtering, we addressed whether it could be generalized across a broader climatic scale. To this end, a meta-analysis (225 seasonal wetlands spread across broad climatic categories: Arid, Temperate, and Cold) allowed us to identify whether an equivalent climate-dependent pattern of trait richness was consistent between the Nearctic and the Western Palearctic. Functional overlap of invertebrates increased from mild (i.e., Temperate) to harsher climates (i.e., Arid and Cold), and phylogenetic clustering (using taxonomy as a surrogate) was highest in Arid and lowest in Temperate wetlands. We show that, (i) as has been described in streams, higher relatedness than would be expected by chance is generally observed in seasonal wetland invertebrate communities; and (ii) this relatedness is not constant but climate-dependent, with the climate under which a given seasonal wetland is located determining the functional overlap and the phylogenetic clustering of the community. Finally, using a space-for-time substitution approach we suggest our results may anticipate how the invertebrate biodiversity embedded in these vulnerable and often overlooked ecosystems will be affected by long-term climate change.

Functional and Phylogenetic Relatedness in Temporary Wetland Invertebrates: Current Macroecological Patterns and Implications for Future Climatic Change Scenarios

PubMed Central

Ruhí, Albert; Boix, Dani; Gascón, Stéphanie; Sala, Jordi; Batzer, Darold P.

2013-01-01

In freshwater ecosystems, species compositions are known to be determined hierarchically by large to small‑scale environmental factors, based on the biological traits of the organisms. However, in ephemeral habitats this heuristic framework remains largely untested. Although temporary wetland faunas are constrained by a local filter (i.e., desiccation), we propose its magnitude may still depend on large-scale climate characteristics. If this is true, climate should be related to the degree of functional and taxonomic relatedness of invertebrate communities inhabiting seasonal wetlands. We tested this hypothesis in two ways. First, based on 52 biological traits for invertebrates, we conducted a case study to explore functional trends among temperate seasonal wetlands differing in the harshness (i.e., dryness) of their dry season. After finding evidence of trait filtering, we addressed whether it could be generalized across a broader climatic scale. To this end, a meta-analysis (225 seasonal wetlands spread across broad climatic categories: Arid, Temperate, and Cold) allowed us to identify whether an equivalent climate-dependent pattern of trait richness was consistent between the Nearctic and the Western Palearctic. Functional overlap of invertebrates increased from mild (i.e., Temperate) to harsher climates (i.e., Arid and Cold), and phylogenetic clustering (using taxonomy as a surrogate) was highest in Arid and lowest in Temperate wetlands. We show that, (i) as has been described in streams, higher relatedness than would be expected by chance is generally observed in seasonal wetland invertebrate communities; and (ii) this relatedness is not constant but climate-dependent, with the climate under which a given seasonal wetland is located determining the functional overlap and the phylogenetic clustering of the community. Finally, using a space-for-time substitution approach we suggest our results may anticipate how the invertebrate biodiversity embedded in these vulnerable and often overlooked ecosystems will be affected by long-term climate change. PMID:24312347

Climatic and Catchment-Scale Predictors of Chinese Stream Insect Richness Differ between Taxonomic Groups

PubMed Central

Tonkin, Jonathan D.; Shah, Deep Narayan; Kuemmerlen, Mathias; Li, Fengqing; Cai, Qinghua; Haase, Peter; Jähnig, Sonja C.

2015-01-01

Little work has been done on large-scale patterns of stream insect richness in China. We explored the influence of climatic and catchment-scale factors on stream insect (Ephemeroptera, Plecoptera, Trichoptera; EPT) richness across mid-latitude China. We assessed the predictive ability of climatic, catchment land cover and physical structure variables on genus richness of EPT, both individually and combined, in 80 mid-latitude Chinese streams, spanning a 3899-m altitudinal gradient. We performed analyses using boosted regression trees and explored the nature of their influence on richness patterns. The relative importance of climate, land cover, and physical factors on stream insect richness varied considerably between the three orders, and while important for Ephemeroptera and Plecoptera, latitude did not improve model fit for any of the groups. EPT richness was linked with areas comprising high forest cover, elevation and slope, large catchments and low temperatures. Ephemeroptera favoured areas with high forest cover, medium-to-large catchment sizes, high temperature seasonality, and low potential evapotranspiration. Plecoptera richness was linked with low temperature seasonality and annual mean, and high slope, elevation and warm-season rainfall. Finally, Trichoptera favoured high elevation areas, with high forest cover, and low mean annual temperature, seasonality and aridity. Our findings highlight the variable role that catchment land cover, physical properties and climatic influences have on stream insect richness. This is one of the first studies of its kind in Chinese streams, thus we set the scene for more in-depth assessments of stream insect richness across broader spatial scales in China, but stress the importance of improving data availability and consistency through time. PMID:25909190

Patterns of soil community structure differ by scale and ecosystem type along a large-scale precipitation gradient

USDA-ARS?s Scientific Manuscript database

Climate models predict increased variability in precipitation regimes, which will likely increase frequency/duration of drought. Reductions in soil moisture affect physical and chemical characteristics of the soil habitat and can influence soil organisms such as mites and nematodes. These organisms ...

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.

Patterns of variations in large pelagic fish: A comparative approach between the Indian and the Atlantic Oceans

NASA Astrophysics Data System (ADS)

Corbineau, A.; Rouyer, T.; Fromentin, J.-M.; Cazelles, B.; Fonteneau, A.; Ménard, F.

2010-07-01

Catch data of large pelagic fish such as tuna, swordfish and billfish are highly variable ranging from short to long term. Based on fisheries data, these time series are noisy and reflect mixed information on exploitation (targeting, strategy, fishing power), population dynamics (recruitment, growth, mortality, migration, etc.), and environmental forcing (local conditions or dominant climate patterns). In this work, we investigated patterns of variation of large pelagic fish (i.e. yellowfin tuna, bigeye tuna, swordfish and blue marlin) in Japanese longliners catch data from 1960 to 2004. We performed wavelet analyses on the yearly time series of each fish species in each biogeographic province of the tropical Indian and Atlantic Oceans. In addition, we carried out cross-wavelet analyses between these biological time series and a large-scale climatic index, i.e. the Southern Oscillation Index (SOI). Results showed that the biogeographic province was the most important factor structuring the patterns of variability of Japanese catch time series. Relationships between the SOI and the fish catches in the Indian and Atlantic Oceans also pointed out the role of climatic variability for structuring patterns of variation of catch time series. This work finally confirmed that Japanese longline CPUE data poorly reflect the underlying population dynamics of tunas.

Impact of Spatial Soil and Climate Input Data Aggregation on Regional Yield Simulations

PubMed Central

Hoffmann, Holger; Zhao, Gang; Asseng, Senthold; Bindi, Marco; Biernath, Christian; Constantin, Julie; Coucheney, Elsa; Dechow, Rene; Doro, Luca; Eckersten, Henrik; Gaiser, Thomas; Grosz, Balázs; Heinlein, Florian; Kassie, Belay T.; Kersebaum, Kurt-Christian; Klein, Christian; Kuhnert, Matthias; Lewan, Elisabet; Moriondo, Marco; Nendel, Claas; Priesack, Eckart; Raynal, Helene; Roggero, Pier P.; Rötter, Reimund P.; Siebert, Stefan; Specka, Xenia; Tao, Fulu; Teixeira, Edmar; Trombi, Giacomo; Wallach, Daniel; Weihermüller, Lutz; Yeluripati, Jagadeesh; Ewert, Frank

2016-01-01

We show the error in water-limited yields simulated by crop models which is associated with spatially aggregated soil and climate input data. Crop simulations at large scales (regional, national, continental) frequently use input data of low resolution. Therefore, climate and soil data are often generated via averaging and sampling by area majority. This may bias simulated yields at large scales, varying largely across models. Thus, we evaluated the error associated with spatially aggregated soil and climate data for 14 crop models. Yields of winter wheat and silage maize were simulated under water-limited production conditions. We calculated this error from crop yields simulated at spatial resolutions from 1 to 100 km for the state of North Rhine-Westphalia, Germany. Most models showed yields biased by <15% when aggregating only soil data. The relative mean absolute error (rMAE) of most models using aggregated soil data was in the range or larger than the inter-annual or inter-model variability in yields. This error increased further when both climate and soil data were aggregated. Distinct error patterns indicate that the rMAE may be estimated from few soil variables. Illustrating the range of these aggregation effects across models, this study is a first step towards an ex-ante assessment of aggregation errors in large-scale simulations. PMID:27055028

Impact of Spatial Soil and Climate Input Data Aggregation on Regional Yield Simulations.

PubMed

Hoffmann, Holger; Zhao, Gang; Asseng, Senthold; Bindi, Marco; Biernath, Christian; Constantin, Julie; Coucheney, Elsa; Dechow, Rene; Doro, Luca; Eckersten, Henrik; Gaiser, Thomas; Grosz, Balázs; Heinlein, Florian; Kassie, Belay T; Kersebaum, Kurt-Christian; Klein, Christian; Kuhnert, Matthias; Lewan, Elisabet; Moriondo, Marco; Nendel, Claas; Priesack, Eckart; Raynal, Helene; Roggero, Pier P; Rötter, Reimund P; Siebert, Stefan; Specka, Xenia; Tao, Fulu; Teixeira, Edmar; Trombi, Giacomo; Wallach, Daniel; Weihermüller, Lutz; Yeluripati, Jagadeesh; Ewert, Frank

2016-01-01

We show the error in water-limited yields simulated by crop models which is associated with spatially aggregated soil and climate input data. Crop simulations at large scales (regional, national, continental) frequently use input data of low resolution. Therefore, climate and soil data are often generated via averaging and sampling by area majority. This may bias simulated yields at large scales, varying largely across models. Thus, we evaluated the error associated with spatially aggregated soil and climate data for 14 crop models. Yields of winter wheat and silage maize were simulated under water-limited production conditions. We calculated this error from crop yields simulated at spatial resolutions from 1 to 100 km for the state of North Rhine-Westphalia, Germany. Most models showed yields biased by <15% when aggregating only soil data. The relative mean absolute error (rMAE) of most models using aggregated soil data was in the range or larger than the inter-annual or inter-model variability in yields. This error increased further when both climate and soil data were aggregated. Distinct error patterns indicate that the rMAE may be estimated from few soil variables. Illustrating the range of these aggregation effects across models, this study is a first step towards an ex-ante assessment of aggregation errors in large-scale simulations.

Global weather and local butterflies: variable responses to a large-scale climate pattern along an elevational gradient.

PubMed

Pardikes, Nicholas A; Shapiro, Arthur M; Dyer, Lee A; Forister, Matthew L

2015-11-01

Understanding the spatial and temporal scales at which environmental variation affects populations of plants and animals is an important goal for modern population biology, especially in the context of shifting climatic conditions. The El Niño Southern Oscillation (ENSO) generates climatic extremes of interannual variation, and has been shown to have significant effects on the diversity and abundance of a variety of terrestrial taxa. However, studies that have investigated the influence of such large-scale climate phenomena have often been limited in spatial and taxonomic scope. We used 23 years (1988-2010) of a long-term butterfly monitoring data set to explore associations between variation in population abundance of 28 butterfly species and variation in ENSO-derived sea surface temperature anomalies (SSTA) across 10 sites that encompass an elevational range of 2750 m in the Sierra Nevada mountain range of California. Our analysis detected a positive, regional effect of increased SSTA on butterfly abundance (wetter and warmer years predict more butterfly observations), yet the influence of SSTA on butterfly abundances varied along the elevational gradient, and also differed greatly among the 28 species. Migratory species had the strongest relationships with ENSO-derived SSTA, suggesting that large-scale climate indices are particularly valuable for understanding biotic-abiotic relationships of the most mobile species. In general, however, the ecological effects of large-scale climatic factors are context dependent between sites and species. Our results illustrate the power of long-term data sets for revealing pervasive yet subtle climatic effects, but also caution against expectations derived from exemplar species or single locations in the study of biotic-abiotic interactions.

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.

Explaining European fungal fruiting phenology with climate variability.

PubMed

Andrew, Carrie; Heegaard, Einar; Høiland, Klaus; Senn-Irlet, Beatrice; Kuyper, Thomas W; Krisai-Greilhuber, Irmgard; Kirk, Paul M; Heilmann-Clausen, Jacob; Gange, Alan C; Egli, Simon; Bässler, Claus; Büntgen, Ulf; Boddy, Lynne; Kauserud, Håvard

2018-06-01

Here we assess the impact of geographically dependent (latitude, longitude, and altitude) changes in bioclimatic (temperature, precipitation, and primary productivity) variability on fungal fruiting phenology across Europe. Two main nutritional guilds of fungi, saprotrophic and ectomycorrhizal, were further separated into spring and autumn fruiters. We used a path analysis to investigate how biogeographic patterns in fungal fruiting phenology coincided with seasonal changes in climate and primary production. Across central to northern Europe, mean fruiting varied by approximately 25 d, primarily with latitude. Altitude affected fruiting by up to 30 d, with spring delays and autumnal accelerations. Fruiting was as much explained by the effects of bioclimatic variability as by their large-scale spatial patterns. Temperature drove fruiting of autumnal ectomycorrhizal and saprotrophic groups as well as spring saprotrophic groups, while primary production and precipitation were major drivers for spring-fruiting ectomycorrhizal fungi. Species-specific phenology predictors were not stable, instead deviating from the overall mean. There is significant likelihood that further climatic change, especially in temperature, will impact fungal phenology patterns at large spatial scales. The ecological implications are diverse, potentially affecting food webs (asynchrony), nutrient cycling and the timing of nutrient availability in ecosystems. © 2018 by the Ecological Society of America.

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

Biogeographic affinity helps explain productivity-richness relationships at regional and local scales

USGS Publications Warehouse

Harrison, S.; Grace, J.B.

2007-01-01

The unresolved question of what causes the observed positive relationship between large-scale productivity and species richness has long interested ecologists and evolutionists. Here we examine a potential explanation that we call the biogeographic affinity hypothesis, which proposes that the productivity-richness relationship is a function of species' climatic tolerances that in turn are shaped by the earth's climatic history combined with evolutionary niche conservatism. Using botanical data from regions and sites across California, we find support for a key prediction of this hypothesis, namely, that the productivity-species richness relationship differs strongly and predictably among groups of higher taxa on the basis of their biogeographic affinities (i.e., between families or genera primarily associated with north-temperate, semiarid, or desert zones). We also show that a consideration of biogeographic affinity can yield new insights on how productivity-richness patterns at large geographic scales filter down to affect patterns of species richness and composition within local communities. ?? 2007 by The University of Chicago. All rights reserved.

Decoding the spatial signatures of multi-scale climate variability - a climate network perspective

NASA Astrophysics Data System (ADS)

Donner, R. V.; Jajcay, N.; Wiedermann, M.; Ekhtiari, N.; Palus, M.

2017-12-01

During the last years, the application of complex networks as a versatile tool for analyzing complex spatio-temporal data has gained increasing interest. Establishing this approach as a new paradigm in climatology has already provided valuable insights into key spatio-temporal climate variability patterns across scales, including novel perspectives on the dynamics of the El Nino Southern Oscillation or the emergence of extreme precipitation patterns in monsoonal regions. In this work, we report first attempts to employ network analysis for disentangling multi-scale climate variability. Specifically, we introduce the concept of scale-specific climate networks, which comprises a sequence of networks representing the statistical association structure between variations at distinct time scales. For this purpose, we consider global surface air temperature reanalysis data and subject the corresponding time series at each grid point to a complex-valued continuous wavelet transform. From this time-scale decomposition, we obtain three types of signals per grid point and scale - amplitude, phase and reconstructed signal, the statistical similarity of which is then represented by three complex networks associated with each scale. We provide a detailed analysis of the resulting connectivity patterns reflecting the spatial organization of climate variability at each chosen time-scale. Global network characteristics like transitivity or network entropy are shown to provide a new view on the (global average) relevance of different time scales in climate dynamics. Beyond expected trends originating from the increasing smoothness of fluctuations at longer scales, network-based statistics reveal different degrees of fragmentation of spatial co-variability patterns at different scales and zonal shifts among the key players of climate variability from tropically to extra-tropically dominated patterns when moving from inter-annual to decadal scales and beyond. The obtained results demonstrate the potential usefulness of systematically exploiting scale-specific climate networks, whose general patterns are in line with existing climatological knowledge, but provide vast opportunities for further quantifications at local, regional and global scales that are yet to be explored.

Model uncertainties do not affect observed patterns of species richness in the Amazon.

PubMed

Sales, Lilian Patrícia; Neves, Olívia Viana; De Marco, Paulo; Loyola, Rafael

2017-01-01

Climate change is arguably a major threat to biodiversity conservation and there are several methods to assess its impacts on species potential distribution. Yet the extent to which different approaches on species distribution modeling affect species richness patterns at biogeographical scale is however unaddressed in literature. In this paper, we verified if the expected responses to climate change in biogeographical scale-patterns of species richness and species vulnerability to climate change-are affected by the inputs used to model and project species distribution. We modeled the distribution of 288 vertebrate species (amphibians, birds and mammals), all endemic to the Amazon basin, using different combinations of the following inputs known to affect the outcome of species distribution models (SDMs): 1) biological data type, 2) modeling methods, 3) greenhouse gas emission scenarios and 4) climate forecasts. We calculated uncertainty with a hierarchical ANOVA in which those different inputs were considered factors. The greatest source of variation was the modeling method. Model performance interacted with data type and modeling method. Absolute values of variation on suitable climate area were not equal among predictions, but some biological patterns were still consistent. All models predicted losses on the area that is climatically suitable for species, especially for amphibians and primates. All models also indicated a current East-western gradient on endemic species richness, from the Andes foot downstream the Amazon river. Again, all models predicted future movements of species upwards the Andes mountains and overall species richness losses. From a methodological perspective, our work highlights that SDMs are a useful tool for assessing impacts of climate change on biodiversity. Uncertainty exists but biological patterns are still evident at large spatial scales. As modeling methods are the greatest source of variation, choosing the appropriate statistics according to the study objective is also essential for estimating the impacts of climate change on species distribution. Yet from a conservation perspective, we show that Amazon endemic fauna is potentially vulnerable to climate change, due to expected reductions on suitable climate area. Climate-driven faunal movements are predicted towards the Andes mountains, which might work as climate refugia for migrating species.

Final Technical Report for DE-SC0005467

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

Broccoli, Anthony J.

2014-09-14

The objective of this project is to gain a comprehensive understanding of the key atmospheric mechanisms and physical processes associated with temperature extremes in order to better interpret and constrain uncertainty in climate model simulations of future extreme temperatures. To achieve this objective, we first used climate observations and a reanalysis product to identify the key atmospheric circulation patterns associated with extreme temperature days over North America during the late twentieth century. We found that temperature extremes were associated with distinctive signatures in near-surface and mid-tropospheric circulation. The orientations and spatial scales of these circulation anomalies vary with latitude, season,more » and proximity to important geographic features such as mountains and coastlines. We next examined the associations between daily and monthly temperature extremes and large-scale, recurrent modes of climate variability, including the Pacific-North American (PNA) pattern, the northern annular mode (NAM), and the El Niño-Southern Oscillation (ENSO). The strength of the associations are strongest with the PNA and NAM and weaker for ENSO, and also depend upon season, time scale, and location. The associations are stronger in winter than summer, stronger for monthly than daily extremes, and stronger in the vicinity of the centers of action of the PNA and NAM patterns. In the final stage of this project, we compared climate model simulations of the circulation patterns associated with extreme temperature days over North America with those obtained from observations. Using a variety of metrics and self-organizing maps, we found the multi-model ensemble and the majority of individual models from phase 5 of the Coupled Model Intercomparison Project (CMIP5) generally capture the observed patterns well, including their strength and as well as variations with latitude and season. The results from this project indicate that current models are capable of simulating the large-scale meteorological patterns associated with daily temperature extremes and they suggest that such models can be used to evaluate the extent to which changes in atmospheric circulation will influence future changes in temperature extremes.« less

What do the data show? Fostering physical intuition with ClimateBits and NASA Earth Observations

NASA Astrophysics Data System (ADS)

Schollaert Uz, S.; Ward, K.

2017-12-01

Through data visualizations using global satellite imagery available in NASA Earth Observations (NEO), we explain Earth science concepts (e.g. albedo, urban heat island effect, phytoplankton). We also provide examples of ways to explore the satellite data in NEO within a new blog series. This is an ideal tool for scientists and non-scientists alike who want to quickly check satellite imagery for large scale features or patterns. NEO analysis requires no software or plug-ins; only a browser and an internet connection. You can even check imagery and perform simple analyses from your smart phone. NEO can be used to create graphics for presentations and papers or as a first step before acquiring data for more rigorous analysis. NEO has potential application to easily explore large scale environmental and climate patterns that impact operations and infrastructure. This is something we are currently exploring with end user groups.

Hydrometeorological variability on a large french catchment and its relation to large-scale circulation across temporal scales

NASA Astrophysics Data System (ADS)

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

2015-04-01

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 large-scale/local-scale correlation, enmpirical 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 large-scale/local-scale links 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 local hydrometeorological processes (predictand : precipitation and streamflow on the Seine river catchment) based on a large-scale predictor (SLP over the Euro-Atlantic sector) on a monthly time-step. This approach basically consisted in 1- decomposing both signals (SLP field and precipitation or streamflow) using discrete wavelet multiresolution analysis and synthesis, 2- generating one 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 addition, the scale-dependent spatial patterns associated to the model matched quite well those obtained from scale-dependent composite analysis. In particular, the multiresolution ESD model handled very well the significant changes in variance through time observed in either prepciptation or streamflow. For instance, the post-1980 period, which had been characterized by particularly high amplitudes in interannual-to-interdecadal variability associated with flood and extremely low-flow/drought periods (e.g., winter 2001, summer 2003), could not be reconstructed without integrating wavelet multiresolution analysis into the model. Further investigations would be required to address the issue of the stationarity of the large-scale/local-scale relationships and to test the capability of the multiresolution ESD model for interannual-to-interdecadal forecasting. In terms of methodological approach, further investigations may concern a fully comprehensive sensitivity analysis of the modeling to the parameter of the multiresolution approach (different families of scaling and wavelet functions used, number of coefficients/degree of smoothness, etc.).

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.

The climate response of the Indo-Pacific warm pool to glacial sea level

NASA Astrophysics Data System (ADS)

Di Nezio, Pedro N.; Timmermann, Axel; Tierney, Jessica E.; Jin, Fei-Fei; Otto-Bliesner, Bette; Rosenbloom, Nan; Mapes, Brian; Neale, Rich; Ivanovic, Ruza F.; Montenegro, Alvaro

2016-06-01

Growing climate proxy evidence suggests that changes in sea level are important drivers of tropical climate change on glacial-interglacial timescales. These paleodata suggest that rainfall patterns over the Indo-Pacific warm pool (IPWP) are highly sensitive to the landmass configuration of the Maritime Continent and that lowered sea level contributed to large-scale drying during the Last Glacial Maximum (LGM, approximately 21,000 years B.P.). Using the Community Earth System Model Version 1.2 (CESM1), we investigate the mechanisms by which lowered sea level influenced the climate of the IPWP during the LGM. The CESM1 simulations show that, in agreement with previous hypotheses, changes in atmospheric circulation are initiated by the exposure of the Sunda and Sahul shelves. Ocean dynamical processes amplify the changes in atmospheric circulation by increasing the east-west sea surface temperature (SST) gradient along the equatorial Indian Ocean. The coupled mechanism driving this response is akin to the Bjerknes feedback and results in a large-scale climatic reorganization over the Indian Ocean with impacts extending from east Africa to the western tropical Pacific. Unlike exposure of the Sunda shelf, exposure of Sahul shelf and the associated changes in surface albedo play a key role because of the positive feedback. This mechanism could explain the pattern of dry (wet) eastern (western) Indian Ocean identified in climate proxies and LGM simulations. However, this response also requires a strengthened SST gradient along the equatorial Indian Ocean, a pattern that is not evident in marine paleoreconstructions. Strategies to resolve this issue are discussed.

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

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.

Large-Scale Covariability Between Aerosol and Precipitation Over the 7-SEAS Region: Observations and Simulations

NASA Technical Reports Server (NTRS)

Huang, Jingfeng; Hsu, N. Christina; Tsay, Si-Chee; Zhang, Chidong; Jeong, Myeong Jae; Gautam, Ritesh; Bettenhausen, Corey; Sayer, Andrew M.; Hansell, Richard A.; Liu, Xiaohong;

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.

Probabilistic projections of 21st century climate change over Northern Eurasia

NASA Astrophysics Data System (ADS)

Monier, E.; Sokolov, A. P.; Schlosser, C. A.; Scott, J. R.; Gao, X.

2013-12-01

We present probabilistic projections of 21st century climate change over Northern Eurasia using the Massachusetts Institute of Technology (MIT) Integrated Global System Model (IGSM), an integrated assessment model that couples an earth system model of intermediate complexity, with a two-dimensional zonal-mean atmosphere, to a human activity model. Regional climate change is obtained by two downscaling methods: a dynamical downscaling, where the IGSM is linked to a three dimensional atmospheric model; and a statistical downscaling, where a pattern scaling algorithm uses climate-change patterns from 17 climate models. This framework allows for key sources of uncertainty in future projections of regional climate change to be accounted for: emissions projections; climate system parameters (climate sensitivity, strength of aerosol forcing and ocean heat uptake rate); natural variability; and structural uncertainty. Results show that the choice of climate policy and the climate parameters are the largest drivers of uncertainty. We also nd that dierent initial conditions lead to dierences in patterns of change as large as when using different climate models. Finally, this analysis reveals the wide range of possible climate change over Northern Eurasia, emphasizing the need to consider all sources of uncertainty when modeling climate impacts over Northern Eurasia.

Probabilistic projections of 21st century climate change over Northern Eurasia

NASA Astrophysics Data System (ADS)

Monier, Erwan; Sokolov, Andrei; Schlosser, Adam; Scott, Jeffery; Gao, Xiang

2013-12-01

We present probabilistic projections of 21st century climate change over Northern Eurasia using the Massachusetts Institute of Technology (MIT) Integrated Global System Model (IGSM), an integrated assessment model that couples an Earth system model of intermediate complexity with a two-dimensional zonal-mean atmosphere to a human activity model. Regional climate change is obtained by two downscaling methods: a dynamical downscaling, where the IGSM is linked to a three-dimensional atmospheric model, and a statistical downscaling, where a pattern scaling algorithm uses climate change patterns from 17 climate models. This framework allows for four major sources of uncertainty in future projections of regional climate change to be accounted for: emissions projections, climate system parameters (climate sensitivity, strength of aerosol forcing and ocean heat uptake rate), natural variability, and structural uncertainty. The results show that the choice of climate policy and the climate parameters are the largest drivers of uncertainty. We also find that different initial conditions lead to differences in patterns of change as large as when using different climate models. Finally, this analysis reveals the wide range of possible climate change over Northern Eurasia, emphasizing the need to consider these sources of uncertainty when modeling climate impacts over Northern Eurasia.

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.

Evaluating the Large-Scale Environment of Extreme Events Using Reanalyses

NASA Astrophysics Data System (ADS)

Bosilovich, M. G.; Schubert, S. D.; Koster, R. D.; da Silva, A. M., Jr.; Eichmann, A.

2014-12-01

Extreme conditions and events have always been a long standing concern in weather forecasting and national security. While some evidence indicates extreme weather will increase in global change scenarios, extremes are often related to the large scale atmospheric circulation, but also occurring infrequently. Reanalyses assimilate substantial amounts of weather data and a primary strength of reanalysis data is the representation of the large-scale atmospheric environment. In this effort, we link the occurrences of extreme events or climate indicators to the underlying regional and global weather patterns. Now, with greater than 3o years of data, reanalyses can include multiple cases of extreme events, and thereby identify commonality among the weather to better characterize the large-scale to global environment linked to the indicator or extreme event. Since these features are certainly regionally dependent, and also, the indicators of climate are continually being developed, we outline various methods to analyze the reanalysis data and the development of tools to support regional evaluation of the data. Here, we provide some examples of both individual case studies and composite studies of similar events. For example, we will compare the large scale environment for Northeastern US extreme precipitation with that of highest mean precipitation seasons. Likewise, southerly winds can shown to be a major contributor to very warm days in the Northeast winter. While most of our development has involved NASA's MERRA reanalysis, we are also looking forward to MERRA-2 which includes several new features that greatly improve the representation of weather and climate, especially for the regions and sectors involved in the National Climate Assessment.

Separating climate change signals into thermodynamic, lapse-rate and circulation effects: theory and application to the European summer climate

NASA Astrophysics Data System (ADS)

Kröner, Nico; Kotlarski, Sven; Fischer, Erich; Lüthi, Daniel; Zubler, Elias; Schär, Christoph

2017-05-01

Climate models robustly project a strong overall summer warming across Europe showing a characteristic north-south gradient with enhanced warming and drying in southern Europe. However, the processes that are responsible for this pattern are not fully understood. We here employ an extended surrogate or pseudo-warming approach to disentangle the contribution of different mechanisms to this response pattern. The basic idea of the surrogate technique is to use a regional climate model and apply a large-scale warming to the lateral boundary conditions of a present-day reference simulation, while maintaining the relative humidity (and thus implicitly increasing the specific moisture content). In comparison to previous studies, our approach includes two important extensions: first, different vertical warming profiles are applied in order to separate the effects of a mean warming from lapse-rate effects. Second, a twin-design is used, in which the climate change signals are not only added to present-day conditions, but also subtracted from a scenario experiment. We demonstrate that these extensions provide an elegant way to separate the full climate change signal into contributions from large-scale thermodynamic (TD), lapse-rate (LR), and circulation and other remaining effects (CO). The latter in particular include changes in land-ocean contrast and spatial variations of the SST warming patterns. We find that the TD effect yields a large-scale warming across Europe with no distinct latitudinal gradient. The LR effect, which is quantified for the first time in our study, leads to a stronger warming and some drying in southern Europe. It explains about 50 % of the warming amplification over the Iberian Peninsula, thus demonstrating the important role of lapse-rate changes. The effect is linked to an extending Hadley circulation. The CO effect as inherited from the driving GCM is shown to further amplify the north-south temperature change gradient. In terms of mean summer precipitation the TD effect leads to a significant overall increase in precipitation all across Europe, which is compensated and regionally reversed by the LR and CO effects in particular in southern Europe.

Effects of the Pacific Decadal Oscillation and global warming on drought in the US Southwest

NASA Astrophysics Data System (ADS)

Grossmann, I.

2012-12-01

Droughts are among the most expensive weather related disasters in the US. In the semi-arid regions of the US Southwest, where average annual rainfall is already very low, multiyear droughts can have large economic, societal and ecological impacts. The US Southwest relies on annual precipitation maxima during winter and the North American Monsoon (NAM), both of which undergo considerable interannual variability associated with large-scale climate patterns, in particular ENSO, the Pacific Decadal Oscillation (PDO) and the Atlantic Multidecadal Oscillation (AMO). The region is also part of the subtropical belt projected to become more arid in a warming climate. These impacts have not been combined and compared with projections of long-term variations due to natural climate patterns. This study addresses this need by deriving future projections of rainfall departures for Arizona and New Mexico with the PDO and AMO and combining these with projected global warming impacts. Depending on the precipitation dataset used, the impacts for the ongoing negative PDO phase are projected to be between 1-1.6 times as large as the multi-model means projection of precipitation minus evaporation during 2020-2040 in the IPCC A1B Scenario. The projected precipitation impacts of a combined negative PDO and positive AMO phase are between 1-2 times as large as the A1B Scenario projection. The study also advances earlier work by addressing problems in detecting the effect of the PDO on precipitation. Given the different mechanisms with which the PDO affects precipitation during winter and the NAM season, precipitation impacts are here investigated on a monthly scale. The impacts of the PDO also vary with other climate patterns. This can be partly addressed by investigating precipitation departures in dependence on other patterns. It is further found that the long-term effect of the PDO can be more clearly separated from short-term variability by considering return periods of multi-year drought measures rather than return periods of simple drought measures.

Continuous evolutionary change in Plio-Pleistocene mammals of eastern Africa

NASA Astrophysics Data System (ADS)

Bibi, Faysal; Kiessling, Wolfgang

2015-08-01

Much debate has revolved around the question of whether the mode of evolutionary and ecological turnover in the fossil record of African mammals was continuous or pulsed, and the degree to which faunal turnover tracked changes in global climate. Here, we assembled and analyzed large specimen databases of the fossil record of eastern African Bovidae (antelopes) and Turkana Basin large mammals. Our results indicate that speciation and extinction proceeded continuously throughout the Pliocene and Pleistocene, as did increases in the relative abundance of arid-adapted bovids, and in bovid body mass. Species durations were similar among clades with different ecological attributes. Occupancy patterns were unimodal, with long and nearly symmetrical origination and extinction phases. A single origination pulse may be present at 2.0-1.75 Ma, but besides this, there is no evidence that evolutionary or ecological changes in the eastern African record tracked rapid, 100,000-y-scale changes in global climate. Rather, eastern African large mammal evolution tracked global or regional climatic trends at long (million year) time scales, while local, basin-scale changes (e.g., tectonic or hydrographic) and biotic interactions ruled at shorter timescales.

On the design of paleoenvironmental data networks for estimating large-scale patterns of climate

NASA Astrophysics Data System (ADS)

Kutzbach, J. E.; Guetter, P. J.

1980-09-01

Guidelines are determined for the spatial density and location of climatic variables (temperature and precipitation) that are appropriate for estimating the continental- to hemispheric-scale pattern of atmospheric circulation (sea-level pressure). Because instrumental records of temperature and precipitation simulate the climatic information that is contained in certain paleoenvironmental records (tree-ring, pollen, and written-documentary records, for example), these guidelines provide useful sampling strategies for reconstructing the pattern of atmospheric circulation from paleoenvironmental records. The statistical analysis uses a multiple linear regression model. The sampling strategies consist of changes in site density (from 0.5 to 2.5 sites per million square kilometers) and site location (from western North American sites only to sites in Japan, North America, and western Europe) of the climatic data. The results showed that the accuracy of specification of the pattern of sea-level pressure: (1) is improved if sites with climatic records are spread as uniformly as possible over the area of interest; (2) increases with increasing site density-at least up to the maximum site density used in this study; (3) is improved if sites cover an area that extends considerably beyond the limits of the area of interest. The accuracy of specification was lower for independent data than for the data that were used to develop the regression model; some skill was found for almost all sampling strategies.

Regional climate model sensitivity to domain size

NASA Astrophysics Data System (ADS)

Leduc, Martin; Laprise, René

2009-05-01

Regional climate models are increasingly used to add small-scale features that are not present in their lateral boundary conditions (LBC). It is well known that the limited area over which a model is integrated must be large enough to allow the full development of small-scale features. On the other hand, integrations on very large domains have shown important departures from the driving data, unless large scale nudging is applied. The issue of domain size is studied here by using the “perfect model” approach. This method consists first of generating a high-resolution climatic simulation, nicknamed big brother (BB), over a large domain of integration. The next step is to degrade this dataset with a low-pass filter emulating the usual coarse-resolution LBC. The filtered nesting data (FBB) are hence used to drive a set of four simulations (LBs for Little Brothers), with the same model, but on progressively smaller domain sizes. The LB statistics for a climate sample of four winter months are compared with BB over a common region. The time average (stationary) and transient-eddy standard deviation patterns of the LB atmospheric fields generally improve in terms of spatial correlation with the reference (BB) when domain gets smaller. The extraction of the small-scale features by using a spectral filter allows detecting important underestimations of the transient-eddy variability in the vicinity of the inflow boundary, which can penalize the use of small domains (less than 100 × 100 grid points). The permanent “spatial spin-up” corresponds to the characteristic distance that the large-scale flow needs to travel before developing small-scale features. The spin-up distance tends to grow in size at higher levels in the atmosphere.

Projected Future Vegetation Changes for the Northwest United States and Southwest Canada at a Fine Spatial Resolution Using a Dynamic Global Vegetation Model.

PubMed

Shafer, Sarah L; Bartlein, Patrick J; Gray, Elizabeth M; Pelltier, Richard T

2015-01-01

Future climate change may significantly alter the distributions of many plant taxa. The effects of climate change may be particularly large in mountainous regions where climate can vary significantly with elevation. Understanding potential future vegetation changes in these regions requires methods that can resolve vegetation responses to climate change at fine spatial resolutions. We used LPJ, a dynamic global vegetation model, to assess potential future vegetation changes for a large topographically complex area of the northwest United States and southwest Canada (38.0-58.0°N latitude by 136.6-103.0°W longitude). LPJ is a process-based vegetation model that mechanistically simulates the effect of changing climate and atmospheric CO2 concentrations on vegetation. It was developed and has been mostly applied at spatial resolutions of 10-minutes or coarser. In this study, we used LPJ at a 30-second (~1-km) spatial resolution to simulate potential vegetation changes for 2070-2099. LPJ was run using downscaled future climate simulations from five coupled atmosphere-ocean general circulation models (CCSM3, CGCM3.1(T47), GISS-ER, MIROC3.2(medres), UKMO-HadCM3) produced using the A2 greenhouse gases emissions scenario. Under projected future climate and atmospheric CO2 concentrations, the simulated vegetation changes result in the contraction of alpine, shrub-steppe, and xeric shrub vegetation across the study area and the expansion of woodland and forest vegetation. Large areas of maritime cool forest and cold forest are simulated to persist under projected future conditions. The fine spatial-scale vegetation simulations resolve patterns of vegetation change that are not visible at coarser resolutions and these fine-scale patterns are particularly important for understanding potential future vegetation changes in topographically complex areas.

The Spatial Scaling of Global Rainfall Extremes

NASA Astrophysics Data System (ADS)

Devineni, N.; Xi, C.; Lall, U.; Rahill-Marier, B.

2013-12-01

Floods associated with severe storms are a significant source of risk for property, life and supply chains. These property losses tend to be determined as much by the duration of flooding as by the depth and velocity of inundation. High duration floods are typically induced by persistent rainfall (upto 30 day duration) as seen recently in Thailand, Pakistan, the Ohio and the Mississippi Rivers, France, and Germany. Events related to persistent and recurrent rainfall appear to correspond to the persistence of specific global climate patterns that may be identifiable from global, historical data fields, and also from climate models that project future conditions. A clear understanding of the space-time rainfall patterns for events or for a season will enable in assessing the spatial distribution of areas likely to have a high/low inundation potential for each type of rainfall forcing. In this paper, we investigate the statistical properties of the spatial manifestation of the rainfall exceedances. We also investigate the connection of persistent rainfall events at different latitudinal bands to large-scale climate phenomena such as ENSO. Finally, we present the scaling phenomena of contiguous flooded areas as a result of large scale organization of long duration rainfall events. This can be used for spatially distributed flood risk assessment conditional on a particular rainfall scenario. Statistical models for spatio-temporal loss simulation including model uncertainty to support regional and portfolio analysis can be developed.

A crisis in the making: responses of Amazonian forests to land use and climate change.

PubMed

Laurance, W F

1998-10-01

At least three global-change phenomena are having major impacts on Amazonian forests: (1) accelerating deforestation and logging; (2) rapidly changing patterns of forest loss; and (3) interactions between human land-use and climatic variability. Additional alterations caused by climatic change, rising concentrations of atmospheric carbon dioxide, mining, overhunting and other large-scale phenomena could also have important effects on the Amazon ecosystem. Consequently, decisions regarding Amazon forest use in the next decade are crucial to its future existence.

Unimodal Latitudinal Pattern of Land-Snail Species Richness across Northern Eurasian Lowlands

PubMed Central

Horsák, Michal; Chytrý, Milan

2014-01-01

Large-scale patterns of species richness and their causes are still poorly understood for most terrestrial invertebrates, although invertebrates can add important insights into the mechanisms that generate regional and global biodiversity patterns. Here we explore the general plausibility of the climate-based “water-energy dynamics” hypothesis using the latitudinal pattern of land-snail species richness across extensive topographically homogeneous lowlands of northern Eurasia. We established a 1480-km long latitudinal transect across the Western Siberian Plain (Russia) from the Russia-Kazakhstan border (54.5°N) to the Arctic Ocean (67.5°N), crossing eight latitudinal vegetation zones: steppe, forest-steppe, subtaiga, southern, middle and northern taiga, forest-tundra, and tundra. We sampled snails in forests and open habitats each half-degree of latitude and used generalized linear models to relate snail species richness to climatic variables and soil calcium content measured in situ. Contrary to the classical prediction of latitudinal biodiversity decrease, we found a striking unimodal pattern of snail species richness peaking in the subtaiga and southern-taiga zones between 57 and 59°N. The main south-to-north interchange of the two principal diversity constraints, i.e. drought stress vs. cold stress, explained most of the variance in the latitudinal diversity pattern. Water balance, calculated as annual precipitation minus potential evapotranspiration, was a single variable that could explain 81.7% of the variance in species richness. Our data suggest that the “water-energy dynamics” hypothesis can apply not only at the global scale but also at subcontinental scales of higher latitudes, as water availability was found to be the primary limiting factor also in this extratropical region with summer-warm and dry climate. A narrow zone with a sharp south-to-north switch in the two main diversity constraints seems to constitute the dominant and general pattern of terrestrial diversity across a large part of northern Eurasia, resulting in a subcontinental diversity hotspot of various taxa in this zone. PMID:25090628

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.

Linking Teleconnections and Iowa's Climate

NASA Astrophysics Data System (ADS)

Rowe, S. T.; Villarini, G.; Lavers, D. A.; Scoccimarro, E.

2013-12-01

In recent years Iowa and the U.S. Midwest has experienced both extreme drought and flood periods. With a drought in 2012 bounded by major floods in 2011 and 2013, the rapid progression from one extreme to the next is on the forefront of the public mind. Given that Iowa is a major agricultural state, extreme weather conditions can have severe socioeconomic consequences. In this research we investigate the large-scale climate processes that occurred concurrently and before a range of dry/wet and cold/hot periods to improve process understanding of these events. It is essential to understand the large-scale climate processes, as these can then provide valuable insight toward the development of long-term climate forecasts for Iowa. In this study monthly and seasonal surface temperature and precipitation over 1950-2012 across Iowa are used. Precipitation and surface temperature data are retrieved from the Parameter-elevation Regressions on Independent Slopes Model (PRISM) Climate Group at Oregon State University. The large-scale atmospheric fields are obtained from the National Center for Environmental Prediction (NCEP) / National Center for Atmospheric Research (NCAR) Reanalysis 1 Project. Precipitation is stratified according to wet, normal, and dry conditions, while temperature according to hot, average, and cold periods. Different stratification criteria based on the precipitation and temperature distributions are examined. Mean sea-level pressure and sea-surface temperature composite maps for the northern hemisphere are then produced for the wet/dry conditions, and cold/hot conditions. Further analyses include correlation, anomalies, and assessment of large-scale planetary wave activity, shedding light on the differences and similarities among the opposite weather conditions. The results of this work will highlight regional weather patterns that are related to the climate over Iowa, providing valuable insight into the mechanisms controlling the occurrence of potentially extreme weather conditions over this area.

The effect of aerosols on northern hemisphere wintertime stationary waves

NASA Astrophysics Data System (ADS)

Lewinschal, Anna; Ekman, Annica M. L.

2010-05-01

Aerosol particles have a considerable impact on the energy budget of the atmosphere because of their ability to scatter and absorb incoming solar radiation. Since the beginning of the industrialisation a large increase has been seen mainly in the concentrations of sulphate and black carbon as a result of combustion of fossil fuel and biomass burning. Aerosol particles have a relatively short residence time in the atmosphere why the aerosol concentration shows a large variation spatially as well as in time where high concentrations are found close to emission sources. This leads to a highly varying radiative forcing pattern which modifies temperature gradients which in turn can alter the pressure distribution and lead to changes in the circulation in the atmosphere. In this study, the effect on the wintertime planetary scale waves on the northern hemisphere is specifically considered together with the regional climate impact due to changes in the stationary waves. To investigate the effect of aerosols on the circulation a global general circulation model based on the ECMWF operational forecast model is used (EC-Earth). The aerosol description in EC-Earth consists of prescribed monthly mean mass concentration fields of five different types of aerosols: sulphate, black carbon, organic carbon, dust and sea salt. Only the direct radiative effect is considered and the different aerosol types are treated as external mixtures. Changes in the stationary wave pattern are determined by comparing model simulations using present-day and pre-industrial concentrations of aerosol particles. Since the planetary scale waves largely influence the storm tracks and are an important part of the meridional heat transport, changes in the wave pattern may have substantial impact on the climate globally and locally. By looking at changes in the model simulations globally it can be found that the aerosol radiative forcing has the potential to change the stationary wave pattern. Furthermore, it shows that regional changes in the climate occur also where the radiative forcing from aerosol particles is not particularly strong, which would indicate that the large scale dynamical response to aerosol forcing can induce changes in temperature, precipitation and wind patterns outside the region where the forcing is initially located.

Pacific/North American teleconnection controls on precipitation isotope ratios across the contiguous United States

NASA Astrophysics Data System (ADS)

Liu, Zhongfang; Kennedy, Casey D.; Bowen, Gabriel J.

2011-10-01

Large-scale climate teleconnections such as the Pacific/North American (PNA) pattern strongly influence atmospheric processes and continental climate. Here we show that precipitation δ 18O values in the contiguous United States are correlated with an index of the PNA pattern. The δ 18O/PNA relationship varies across the study region and exhibits two prominent modes, with positive correlation in the western USA and negative correlation in the east. This spatial pattern appears not to reflect variation in local climate variables, but rather primarily reflects differences in atmospheric circulation and moisture sources associated with PNA. Our results suggest that strong antiphase variation in paired paleo-water δ 18O proxy records from regions characterized by the two modes of δ 18O/PNA correlation, especially in the Midwest and southwestern USA, may provide a robust basis for reconstruction of past variation in the PNA pattern.

Characteristics of atmospheric circulation patterns associated with extreme temperatures over North America in observations and climate models

NASA Astrophysics Data System (ADS)

Loikith, Paul C.

Motivated by a desire to understand the physical mechanisms involved in future anthropogenic changes in extreme temperature events, the key atmospheric circulation patterns associated with extreme daily temperatures over North America in the current climate are identified. Several novel metrics are used to systematically identify and describe these patterns for the entire continent. The orientation, physical characteristics, and spatial scale of these circulation patterns vary based on latitude, season, and proximity to important geographic features (i.e., mountains, coastlines). The anomaly patterns associated with extreme cold events tend to be similar to, but opposite in sign of, those associated with extreme warm events, especially within the westerlies, and tend to scale with temperature in the same locations. The influence of the Pacific North American (PNA) pattern, the Northern Annular Mode (NAM), and the El Niño-Southern Oscillation (ENSO) on extreme temperature days and months shows that associations between extreme temperatures and the PNA and NAM are stronger than associations with ENSO. In general, the association with extremes tends to be stronger on monthly than daily time scales. Extreme temperatures are associated with the PNA and NAM in locations typically influenced by these circulation patterns; however many extremes still occur on days when the amplitude and polarity of these patterns do not favor their occurrence. In winter, synoptic-scale, transient weather disturbances are important drivers of extreme temperature days; however these smaller-scale events are often concurrent with amplified PNA or NAM patterns. Associations are weaker in summer when other physical mechanisms affecting the surface energy balance, such as anomalous soil moisture content, are associated with extreme temperatures. Analysis of historical runs from seventeen climate models from the CMIP5 database suggests that most models simulate realistic circulation patterns associated with extreme temperature days in most places. Model-simulated patterns tend to resemble observed patterns better in the winter than the summer and at 500 hPa than at the surface. There is substantial variability among the suite of models analyzed and most models simulate circulation patterns more realistically away from influential features such as large bodies of water and complex topography.

Synchronous multi-decadal climate variability of the whole Pacific areas revealed in tree rings since 1567

NASA Astrophysics Data System (ADS)

Fang, Keyan; Cook, Edward; Guo, Zhengtang; Chen, Deliang; Ou, Tinghai; Zhao, Yan

2018-02-01

Oceanic and atmospheric patterns play a crucial role in modulating climate variability from interannual to multi-decadal timescales by causing large-scale co-varying climate changes. The brevity of the existing instrumental records hinders the ability to recognize climate patterns before the industrial era, which can be alleviated using proxies. Unfortunately, proxy based reconstructions of oceanic and atmospheric modes of the past millennia often have modest agreements with each other before the instrumental period, raising questions about the robustness of the reconstructions. To ensure the stability of climate signals in proxy data through time, we first identified tree-ring datasets from distant regions containing coherent variations in Asia and North America, and then interpreted their climate information. We found that the multi-decadal covarying climate patterns of the middle and high latitudinal regions around the northern Pacific Ocean agreed quite well with the climate reconstructions of the tropical and southern Pacific areas. This indicates a synchronous variability at the multi-decadal timescale of the past 430 years for the entire Pacific Ocean. This pattern is closely linked to the dominant mode of the Pacific sea surface temperature (SST) after removing the warming trend. This Pacific multi-decadal SST variability resembles the Interdecadal Pacific Oscillation.

ASSOCIATIONS BETWEEN NAO VARIBILITY AND U.S. MID-ATLANTIC REGION HYDROCLIMATOLOGY

EPA Science Inventory

Variability in the climate of the US Mid-Atlantic Region is associated with larger scale variability in the El Nino-Southern Oscillation (ENSO), the Pacific North American (PNA) teleconnection pattern, and the North Atlantic Oscillation (NAO). Collectively, these three large-scal...

Co-occurrence patterns of trees along macro-climatic gradients and their potential influence on the present and future distribution of Fagus sylvatica L.

USGS Publications Warehouse

Meier, E.S.; Edwards, T.C.; Kienast, Felix; Dobbertin, M.; Zimmermann, N.E.

2011-01-01

Aim During recent and future climate change, shifts in large-scale species ranges are expected due to the hypothesized major role of climatic factors in regulating species distributions. The stress-gradient hypothesis suggests that biotic interactions may act as major constraints on species distributions under more favourable growing conditions, while climatic constraints may dominate under unfavourable conditions. We tested this hypothesis for one focal tree species having three major competitors using broad-scale environmental data. We evaluated the variation of species co-occurrence patterns in climate space and estimated the influence of these patterns on the distribution of the focal species for current and projected future climates.Location Europe.Methods We used ICP Forest Level 1 data as well as climatic, topographic and edaphic variables. First, correlations between the relative abundance of European beech (Fagus sylvatica) and three major competitor species (Picea abies, Pinus sylvestris and Quercus robur) were analysed in environmental space, and then projected to geographic space. Second, a sensitivity analysis was performed using generalized additive models (GAM) to evaluate where and how much the predicted F. sylvatica distribution varied under current and future climates if potential competitor species were included or excluded. We evaluated if these areas coincide with current species co-occurrence patterns.Results Correlation analyses supported the stress-gradient hypothesis: towards favourable growing conditions of F. sylvatica, its abundance was strongly linked to the abundance of its competitors, while this link weakened towards unfavourable growing conditions, with stronger correlations in the south and at low elevations than in the north and at high elevations. The sensitivity analysis showed a potential spatial segregation of species with changing climate and a pronounced shift of zones where co-occurrence patterns may play a major role.Main conclusions Our results demonstrate the importance of species co-occurrence patterns for calibrating improved species distribution models for use in projections of climate effects. The correlation approach is able to localize European areas where inclusion of biotic predictors is effective. The climate-induced spatial segregation of the major tree species could have ecological and economic consequences. ?? 2010 Blackwell Publishing Ltd.

Declining body size: a third universal response to warming?

PubMed

Gardner, Janet L; Peters, Anne; Kearney, Michael R; Joseph, Leo; Heinsohn, Robert

2011-06-01

A recently documented correlate of anthropogenic climate change involves reductions in body size, the nature and scale of the pattern leading to suggestions of a third universal response to climate warming. Because body size affects thermoregulation and energetics, changing body size has implications for resilience in the face of climate change. A review of recent studies shows heterogeneity in the magnitude and direction of size responses, exposing a need for large-scale phylogenetically controlled comparative analyses of temporal size change. Integrative analyses of museum data combined with new theoretical models of size-dependent thermoregulatory and metabolic responses will increase both understanding of the underlying mechanisms and physiological consequences of size shifts and, therefore, the ability to predict the sensitivities of species to climate change. Copyright © 2011 Elsevier Ltd. All rights reserved.

European land CO2 sink influenced by NAO and East-Atlantic Pattern coupling

PubMed Central

Bastos, Ana; Janssens, Ivan A.; Gouveia, Célia M.; Trigo, Ricardo M.; Ciais, Philippe; Chevallier, Frédéric; Peñuelas, Josep; Rödenbeck, Christian; Piao, Shilong; Friedlingstein, Pierre; Running, Steven W.

2016-01-01

Large-scale climate patterns control variability in the global carbon sink. In Europe, the North-Atlantic Oscillation (NAO) influences vegetation activity, however the East-Atlantic (EA) pattern is known to modulate NAO strength and location. Using observation-driven and modelled data sets, we show that multi-annual variability patterns of European Net Biome Productivity (NBP) are linked to anomalies in heat and water transport controlled by the NAO–EA interplay. Enhanced NBP occurs when NAO and EA are both in negative phase, associated with cool summers with wet soils which enhance photosynthesis. During anti-phase periods, NBP is reduced through distinct impacts of climate anomalies in photosynthesis and respiration. The predominance of anti-phase years in the early 2000s may explain the European-wide reduction of carbon uptake during this period, reported in previous studies. Results show that improving the capability of simulating atmospheric circulation patterns may better constrain regional carbon sink variability in coupled carbon-climate models. PMID:26777730

European land CO2 sink influenced by NAO and East-Atlantic Pattern coupling.

PubMed

Bastos, Ana; Janssens, Ivan A; Gouveia, Célia M; Trigo, Ricardo M; Ciais, Philippe; Chevallier, Frédéric; Peñuelas, Josep; Rödenbeck, Christian; Piao, Shilong; Friedlingstein, Pierre; Running, Steven W

2016-01-18

Large-scale climate patterns control variability in the global carbon sink. In Europe, the North-Atlantic Oscillation (NAO) influences vegetation activity, however the East-Atlantic (EA) pattern is known to modulate NAO strength and location. Using observation-driven and modelled data sets, we show that multi-annual variability patterns of European Net Biome Productivity (NBP) are linked to anomalies in heat and water transport controlled by the NAO-EA interplay. Enhanced NBP occurs when NAO and EA are both in negative phase, associated with cool summers with wet soils which enhance photosynthesis. During anti-phase periods, NBP is reduced through distinct impacts of climate anomalies in photosynthesis and respiration. The predominance of anti-phase years in the early 2000s may explain the European-wide reduction of carbon uptake during this period, reported in previous studies. Results show that improving the capability of simulating atmospheric circulation patterns may better constrain regional carbon sink variability in coupled carbon-climate models.

400 Years of summer hydroclimate from stable isotopes in Iberian trees

NASA Astrophysics Data System (ADS)

Andreu-Hayles, Laia; Ummenhofer, Caroline C.; Barriendos, Mariano; Schleser, Gerhard H.; Helle, Gerhard; Leuenberger, Markus; Gutiérrez, Emilia; Cook, Edward R.

2017-07-01

Tree rings are natural archives that annually record distinct types of past climate variability depending on the parameters measured. Here, we use ring-width and stable isotopes in cellulose of trees from the northwestern Iberian Peninsula (IP) to understand regional summer hydroclimate over the last 400 years and the associated atmospheric patterns. Correlations between tree rings and climate data demonstrate that isotope signatures in the targeted Iberian pine forests are very sensitive to water availability during the summer period, and are mainly controlled by stomatal conductance. Non-linear methods based on extreme events analysis allow for capturing distinct seasonal climatic variability recorded by tree-ring parameters and asymmetric signals of the associated atmospheric features. Moreover, years with extreme high (low) values in the tree-ring records were characterised by coherent large-scale atmospheric circulation patterns with reduced (enhanced) moisture transport onto the northwestern IP. These analyses of extremes revealed that high/low proxy values do not necessarily correspond to mirror images in the atmospheric anomaly patterns, suggesting different drivers of these patterns and the corresponding signature recorded in the proxies. Regional hydroclimate features across the broader IP and western Europe during extreme wet/dry summers detected by the northwestern IP trees compare favourably to independent multicentury sea level pressure and drought reconstructions for Europe. Historical records also validate our findings that attribute non-linear moisture signals recorded by extreme tree-ring values to distinct large-scale atmospheric patterns and allow for 400-year reconstructions of the frequency of occurrence of extreme conditions in late spring and summer hydroclimate.

400 years of summer hydroclimate from stable isotopes in Iberian trees

NASA Astrophysics Data System (ADS)

Andreu-Hayles, Laia; Ummenhofer, Caroline C.; Barriendos, Mariano; Schleser, Gerhard H.; Helle, Gerhard; Leuenberger, Markus; Gutierrez, Emilia; Cook, Edward R.

2017-04-01

Tree rings are natural archives that annually record distinct types of past climate variability depending on the parameters measured. Here, we use ring-width and stable isotopes in cellulose of trees from the northwestern Iberian Peninsula (IP) to understand regional summer hydroclimate over the last 400 years and the associated atmospheric patterns. Correlations between tree rings and climate data demonstrate that isotope signatures in the targeted Iberian pine forests are very sensitive to water availability during the summer period, and are mainly controlled by stomatal conductance. Non-linear methods based on extreme events analysis allow for capturing distinct seasonal climatic variability recorded by tree-ring parameters and asymmetric signals of the associated atmospheric features. Moreover, years with extreme high (low) values in the tree-ring records were characterised by coherent large-scale atmospheric circulation patterns with reduced (enhanced) moisture transport onto the northwestern IP. These analyses of extremes revealed that high/low proxy values do not necessarily correspond to mirror images in the atmospheric anomaly patterns, suggesting different drivers of these patterns and the corresponding signature recorded in the proxies. Regional hydroclimate features across the broader IP and western Europe during extreme wet/dry summers detected by the northwestern IP trees compare favourably to an independent multicentury sea level pressure and drought reconstruction for Europe. Historical records also validate our findings that attribute non-linear moisture signals recorded by extreme tree-ring values to distinct large-scale atmospheric patterns and allow for 400-yr reconstructions of the frequency of occurrence of extreme conditions in summer hydroclimate. We will discuss how the results for Lillo compare with other records.

Multiresolution comparison of precipitation datasets for large-scale models

NASA Astrophysics Data System (ADS)

Chun, K. P.; Sapriza Azuri, G.; Davison, B.; DeBeer, C. M.; Wheater, H. S.

2014-12-01

Gridded precipitation datasets are crucial for driving large-scale models which are related to weather forecast and climate research. However, the quality of precipitation products is usually validated individually. Comparisons between gridded precipitation products along with ground observations provide another avenue for investigating how the precipitation uncertainty would affect the performance of large-scale models. In this study, using data from a set of precipitation gauges over British Columbia and Alberta, we evaluate several widely used North America gridded products including the Canadian Gridded Precipitation Anomalies (CANGRD), the National Center for Environmental Prediction (NCEP) reanalysis, the Water and Global Change (WATCH) project, the thin plate spline smoothing algorithms (ANUSPLIN) and Canadian Precipitation Analysis (CaPA). Based on verification criteria for various temporal and spatial scales, results provide an assessment of possible applications for various precipitation datasets. For long-term climate variation studies (~100 years), CANGRD, NCEP, WATCH and ANUSPLIN have different comparative advantages in terms of their resolution and accuracy. For synoptic and mesoscale precipitation patterns, CaPA provides appealing performance of spatial coherence. In addition to the products comparison, various downscaling methods are also surveyed to explore new verification and bias-reduction methods for improving gridded precipitation outputs for large-scale models.

Wave climate and trends along the eastern Chukchi Arctic Alaska coast

USGS Publications Warehouse

Erikson, L.H.; Storlazzi, C.D.; Jensen, R.E.

2011-01-01

Due in large part to the difficulty of obtaining measurements in the Arctic, little is known about the wave climate along the coast of Arctic Alaska. In this study, numerical model simulations encompassing 40 years of wave hind-casts were used to assess mean and extreme wave conditions. Results indicate that the wave climate was strongly modulated by large-scale atmospheric circulation patterns and that mean and extreme wave heights and periods exhibited increasing trends in both the sea and swell frequency bands over the time-period studied (1954-2004). Model simulations also indicate that the upward trend was not due to a decrease in the minimum icepack extent. ?? 2011 ASCE.

Improved pattern scaling approaches for the use in climate impact studies

NASA Astrophysics Data System (ADS)

Herger, Nadja; Sanderson, Benjamin M.; Knutti, Reto

2015-05-01

Pattern scaling is a simple way to produce climate projections beyond the scenarios run with expensive global climate models (GCMs). The simplest technique has known limitations and assumes that a spatial climate anomaly pattern obtained from a GCM can be scaled by the global mean temperature (GMT) anomaly. We propose alternatives and assess their skills and limitations. One approach which avoids scaling is to consider a period in a different scenario with the same GMT change. It is attractive as it provides patterns of any temporal resolution that are consistent across variables, and it does not distort variability. Second, we extend the traditional approach with a land-sea contrast term, which provides the largest improvements over the traditional technique. When interpolating between known bounding scenarios, the proposed methods significantly improve the accuracy of the pattern scaled scenario with little computational cost. The remaining errors are much smaller than the Coupled Model Intercomparison Project Phase 5 model spread.

Non-stationarity of extreme weather events in a changing climate - an application to long-term droughts in the US Southwest

NASA Astrophysics Data System (ADS)

Grossmann, I.

2013-12-01

Return periods of many extreme weather events are not stationary over time, given increasing risks due to global warming and multidecadal variability resulting from large scale climate patterns. This is problematic as extreme weather events and long-term climate risks such as droughts are typically conceptualized via measures such as return periods that implicitly assume non-stationarity. I briefly review these problems and present an application to the non-stationarity of droughts in the US Southwest. The US Southwest relies on annual precipitation maxima during winter and the North American Monsoon (NAM), both of which vary with large-scale climate patterns, in particular ENSO, the Pacific Decadal Oscillation (PDO) and the Atlantic Multidecadal Oscillation (AMO). The latter two exhibit variability on longer (multi-decadal) time scales in addition to short-term variations. The region is also part of the subtropical belt projected to become more arid in a warming climate. The possible multidecadal impacts of the PDO on precipitation in the study region are analyzed with a focus on Arizona and New Mexico, using GPCC and CRU data since 1900. The projected impacts of the PDO on annual precipitation during the next three decades with GPCC data are similar in scale to the impacts of global warming on precipitation according to the A1B scenario and the CMIP2 multi-model means, while the combined impact of the PDO and AMO is about 19% larger. The effects according to the CRU dataset are about half as large as the projected global warming impacts. Given the magnitude of the projected impacts from both multidecadal variability and global warming, water management needs to explicitly incorporate both of these trends into long-term planning. Multi-decadal variability could be incorporated into the concept of return periods by presenting return periods as time-varying or as conditional on the respective 'phase' of relevant multidecadal patterns and on global warming. Problems in detecting the PDO signal and potential solutions are also discussed. We find that the long-term effect of the PDO can be more clearly separated from short-term variability by considering return periods of multi-year drought measures rather than return periods of simple drought measures that are more affected by short-term variations.

Fine-Scale Microclimatic Variation Can Shape the Responses of Organisms to Global Change in Both Natural and Urban Environments.

PubMed

Pincebourde, Sylvain; Murdock, Courtney C; Vickers, Mathew; Sears, Michael W

2016-07-01

When predicting the response of organisms to global change, models use measures of climate at a coarse resolution from general circulation models or from downscaled regional models. Organisms, however, do not experience climate at such large scales. The climate heterogeneity over a landscape and how much of that landscape an organism can sample will determine ultimately the microclimates experienced by organisms. This past few decades has seen an important increase in the number of studies reporting microclimatic patterns at small scales. This synthesis intends to unify studies reporting microclimatic heterogeneity (mostly temperature) at various spatial scales, to infer any emerging trends, and to discuss the causes and consequences of such heterogeneity for organismal performance and with respect to changing land use patterns and climate. First, we identify the environmental drivers of heterogeneity across the various spatial scales that are pertinent to ectotherms. The thermal heterogeneity at the local and micro-scales is mostly generated by the architecture or the geometrical features of the microhabitat. Then, the thermal heterogeneity experienced by individuals is modulated by behavior. Second, we survey the literature to quantify thermal heterogeneity from the micro-scale up to the scale of a landscape in natural habitats. Despite difficulties in compiling studies that differ much in their design and aims, we found that there is as much thermal heterogeneity across micro-, local and landscape scales, and that the temperature range is large in general (>9 °C on average, and up to 26 °C). Third, we examine the extent to which urban habitats can be used to infer the microclimatic patterns of the future. Urban areas generate globally drier and warmer microclimatic patterns and recent evidence suggest that thermal traits of ectotherms are adapted to them. Fourth, we explore the interplay between microclimate heterogeneity and the behavioral thermoregulatory abilities of ectotherms in setting their overall performance. We used a random walk framework to show that the thermal heterogeneity allows a more precise behavioral thermoregulation and a narrower temperature distribution of the ectotherm compared to less heterogeneous microhabitats. Finally, we discuss the potential impacts of global change on the fine scale mosaics of microclimates. The amplitude of change may differ between spatial scales. In heterogeneous microhabitats, the amplitude of change at micro-scale, caused by atmospheric warming, can be substantial while it can be limited at the local and landscape scales. We suggest that the warming signal will influence species performance and biotic interactions by modulating the mosaic of microclimates. © The Author 2016. Published by Oxford University Press on behalf of the Society for Integrative and Comparative Biology. All rights reserved. For permissions please email: journals.permissions@oup.com.

Modern Climate Analogues of Late-Quaternary Paleoclimates for the Western United States.

NASA Astrophysics Data System (ADS)

Mock, Cary Jeffrey

This study examined spatial variations of modern and late-Quaternary climates for the western United States. Synoptic climatological analyses of the modern record identified the predominate climatic controls that normally produce the principal modes of spatial climatic variability. They also provided a modern standard to assess past climates. Maps of the month-to-month changes in 500 mb heights, sea-level pressure, temperature, and precipitation illustrated how different climatic controls govern the annual cycle of climatic response. The patterns of precipitation ratios, precipitation bar graphs, and the seasonal precipitation maximum provided additional insight into how different climatic controls influence spatial climatic variations. Synoptic-scale patterns from general circulation model (GCM) simulations or from analyses of climatic indices were used as the basis for finding modern climate analogues for 18 ka and 9 ka. Composite anomaly maps of atmospheric circulation, precipitation, and temperature were compared with effective moisture maps compiled from proxy data to infer how the patterns, which were evident from the proxy data, were generated. The analyses of the modern synoptic climatology indicate that smaller-scale climatic controls must be considered along with larger-scale ones in order to explain patterns of spatial climate heterogeneity. Climatic extremes indicate that changes in the spatial patterns of precipitation seasonality are the exception rather than the rule, reflecting the strong influence of smaller-scale controls. Modern climate analogues for both 18 ka and 9 ka clearly depict the dry Northwest/wet Southwest contrast that is suggested by GCM simulations and paleoclimatic evidence. 18 ka analogues also show the importance of smaller-scale climatic controls in explaining spatial climatic variation in the Northwest and northern Great Plains. 9 ka analogues provide climatological explanations for patterns of spatial heterogeneity over several mountainous areas as suggested by paleoclimatic evidence. Modern analogues of past climates supplement modeling approaches by providing information below the resolution of model simulations. Analogues can be used to examine the controls of spatial paleoclimatic variation if sufficient instrumental data and paleoclimatic evidence are available, and if one carefully exercises uniformitarianism when extrapolating modern relationships to the past.

Decadal-Scale Forecasting of Climate Drivers for Marine Applications.

PubMed

Salinger, J; Hobday, A J; Matear, R J; O'Kane, T J; Risbey, J S; Dunstan, P; Eveson, J P; Fulton, E A; Feng, M; Plagányi, É E; Poloczanska, E S; Marshall, A G; Thompson, P A

Climate influences marine ecosystems on a range of time scales, from weather-scale (days) through to climate-scale (hundreds of years). Understanding of interannual to decadal climate variability and impacts on marine industries has received less attention. Predictability up to 10 years ahead may come from large-scale climate modes in the ocean that can persist over these time scales. In Australia the key drivers of climate variability affecting the marine environment are the Southern Annular Mode, the Indian Ocean Dipole, the El Niño/Southern Oscillation, and the Interdecadal Pacific Oscillation, each has phases that are associated with different ocean circulation patterns and regional environmental variables. The roles of these drivers are illustrated with three case studies of extreme events-a marine heatwave in Western Australia, a coral bleaching of the Great Barrier Reef, and flooding in Queensland. Statistical and dynamical approaches are described to generate forecasts of climate drivers that can subsequently be translated to useful information for marine end users making decisions at these time scales. Considerable investment is still needed to support decadal forecasting including improvement of ocean-atmosphere models, enhancement of observing systems on all scales to support initiation of forecasting models, collection of important biological data, and integration of forecasts into decision support tools. Collaboration between forecast developers and marine resource sectors-fisheries, aquaculture, tourism, biodiversity management, infrastructure-is needed to support forecast-based tactical and strategic decisions that reduce environmental risk over annual to decadal time scales. © 2016 Elsevier Ltd. All rights reserved.

Model uncertainties do not affect observed patterns of species richness in the Amazon

PubMed Central

Sales, Lilian Patrícia; Neves, Olívia Viana; De Marco, Paulo

2017-01-01

Background Climate change is arguably a major threat to biodiversity conservation and there are several methods to assess its impacts on species potential distribution. Yet the extent to which different approaches on species distribution modeling affect species richness patterns at biogeographical scale is however unaddressed in literature. In this paper, we verified if the expected responses to climate change in biogeographical scale—patterns of species richness and species vulnerability to climate change—are affected by the inputs used to model and project species distribution. Methods We modeled the distribution of 288 vertebrate species (amphibians, birds and mammals), all endemic to the Amazon basin, using different combinations of the following inputs known to affect the outcome of species distribution models (SDMs): 1) biological data type, 2) modeling methods, 3) greenhouse gas emission scenarios and 4) climate forecasts. We calculated uncertainty with a hierarchical ANOVA in which those different inputs were considered factors. Results The greatest source of variation was the modeling method. Model performance interacted with data type and modeling method. Absolute values of variation on suitable climate area were not equal among predictions, but some biological patterns were still consistent. All models predicted losses on the area that is climatically suitable for species, especially for amphibians and primates. All models also indicated a current East-western gradient on endemic species richness, from the Andes foot downstream the Amazon river. Again, all models predicted future movements of species upwards the Andes mountains and overall species richness losses. Conclusions From a methodological perspective, our work highlights that SDMs are a useful tool for assessing impacts of climate change on biodiversity. Uncertainty exists but biological patterns are still evident at large spatial scales. As modeling methods are the greatest source of variation, choosing the appropriate statistics according to the study objective is also essential for estimating the impacts of climate change on species distribution. Yet from a conservation perspective, we show that Amazon endemic fauna is potentially vulnerable to climate change, due to expected reductions on suitable climate area. Climate-driven faunal movements are predicted towards the Andes mountains, which might work as climate refugia for migrating species. PMID:29023503

Network approach to patterns in stratocumulus clouds

NASA Astrophysics Data System (ADS)

Glassmeier, Franziska; Feingold, Graham

2017-10-01

Stratocumulus clouds (Sc) have a significant impact on the amount of sunlight reflected back to space, with important implications for Earth’s climate. Representing Sc and their radiative impact is one of the largest challenges for global climate models. Sc fields self-organize into cellular patterns and thus lend themselves to analysis and quantification in terms of natural cellular networks. Based on large-eddy simulations of Sc fields, we present a first analysis of the geometric structure and self-organization of Sc patterns from this network perspective. Our network analysis shows that the Sc pattern is scale-invariant as a consequence of entropy maximization that is known as Lewis’s Law (scaling parameter: 0.16) and is largely independent of the Sc regime (cloud-free vs. cloudy cell centers). Cells are, on average, hexagonal with a neighbor number variance of about 2, and larger cells tend to be surrounded by smaller cells, as described by an Aboav-Weaire parameter of 0.9. The network structure is neither completely random nor characteristic of natural convection. Instead, it emerges from Sc-specific versions of cell division and cell merging that are shaped by cell expansion. This is shown with a heuristic model of network dynamics that incorporates our physical understanding of cloud processes.

Network approach to patterns in stratocumulus clouds.

PubMed

Glassmeier, Franziska; Feingold, Graham

2017-10-03

Stratocumulus clouds (Sc) have a significant impact on the amount of sunlight reflected back to space, with important implications for Earth's climate. Representing Sc and their radiative impact is one of the largest challenges for global climate models. Sc fields self-organize into cellular patterns and thus lend themselves to analysis and quantification in terms of natural cellular networks. Based on large-eddy simulations of Sc fields, we present a first analysis of the geometric structure and self-organization of Sc patterns from this network perspective. Our network analysis shows that the Sc pattern is scale-invariant as a consequence of entropy maximization that is known as Lewis's Law (scaling parameter: 0.16) and is largely independent of the Sc regime (cloud-free vs. cloudy cell centers). Cells are, on average, hexagonal with a neighbor number variance of about 2, and larger cells tend to be surrounded by smaller cells, as described by an Aboav-Weaire parameter of 0.9. The network structure is neither completely random nor characteristic of natural convection. Instead, it emerges from Sc-specific versions of cell division and cell merging that are shaped by cell expansion. This is shown with a heuristic model of network dynamics that incorporates our physical understanding of cloud processes.

Network approach to patterns in stratocumulus clouds

PubMed Central

Feingold, Graham

2017-01-01

Stratocumulus clouds (Sc) have a significant impact on the amount of sunlight reflected back to space, with important implications for Earth’s climate. Representing Sc and their radiative impact is one of the largest challenges for global climate models. Sc fields self-organize into cellular patterns and thus lend themselves to analysis and quantification in terms of natural cellular networks. Based on large-eddy simulations of Sc fields, we present a first analysis of the geometric structure and self-organization of Sc patterns from this network perspective. Our network analysis shows that the Sc pattern is scale-invariant as a consequence of entropy maximization that is known as Lewis’s Law (scaling parameter: 0.16) and is largely independent of the Sc regime (cloud-free vs. cloudy cell centers). Cells are, on average, hexagonal with a neighbor number variance of about 2, and larger cells tend to be surrounded by smaller cells, as described by an Aboav–Weaire parameter of 0.9. The network structure is neither completely random nor characteristic of natural convection. Instead, it emerges from Sc-specific versions of cell division and cell merging that are shaped by cell expansion. This is shown with a heuristic model of network dynamics that incorporates our physical understanding of cloud processes. PMID:28904097

Twenty-million-year relationship between mammalian diversity and primary productivity

PubMed Central

Fritz, Susanne A.; Eronen, Jussi T.; Schnitzler, Jan; Hof, Christian; Janis, Christine M.; Mulch, Andreas; Böhning-Gaese, Katrin; Graham, Catherine H.

2016-01-01

At global and regional scales, primary productivity strongly correlates with richness patterns of extant animals across space, suggesting that resource availability and climatic conditions drive patterns of diversity. However, the existence and consistency of such diversity–productivity relationships through geological history is unclear. Here we provide a comprehensive quantitative test of the diversity–productivity relationship for terrestrial large mammals through time across broad temporal and spatial scales. We combine >14,000 occurrences for 690 fossil genera through the Neogene (23–1.8 Mya) with regional estimates of primary productivity from fossil plant communities in North America and Europe. We show a significant positive diversity–productivity relationship through the 20-million-year record, providing evidence on unprecedented spatial and temporal scales that this relationship is a general pattern in the ecology and paleo-ecology of our planet. Further, we discover that genus richness today does not match the fossil relationship, suggesting that a combination of human impacts and Pleistocene climate variability has modified the 20-million-year ecological relationship by strongly reducing primary productivity and driving many mammalian species into decline or to extinction. PMID:27621451

Twenty-million-year relationship between mammalian diversity and primary productivity

NASA Astrophysics Data System (ADS)

Fritz, Susanne A.; Eronen, Jussi T.; Schnitzler, Jan; Hof, Christian; Janis, Christine M.; Mulch, Andreas; Böhning-Gaese, Katrin; Graham, Catherine H.

2016-09-01

At global and regional scales, primary productivity strongly correlates with richness patterns of extant animals across space, suggesting that resource availability and climatic conditions drive patterns of diversity. However, the existence and consistency of such diversity-productivity relationships through geological history is unclear. Here we provide a comprehensive quantitative test of the diversity-productivity relationship for terrestrial large mammals through time across broad temporal and spatial scales. We combine >14,000 occurrences for 690 fossil genera through the Neogene (23-1.8 Mya) with regional estimates of primary productivity from fossil plant communities in North America and Europe. We show a significant positive diversity-productivity relationship through the 20-million-year record, providing evidence on unprecedented spatial and temporal scales that this relationship is a general pattern in the ecology and paleo-ecology of our planet. Further, we discover that genus richness today does not match the fossil relationship, suggesting that a combination of human impacts and Pleistocene climate variability has modified the 20-million-year ecological relationship by strongly reducing primary productivity and driving many mammalian species into decline or to extinction.

North American extreme temperature events and related large scale meteorological patterns: A review of statistical methods, dynamics, modeling, and trends

DOE PAGES

Grotjahn, Richard; Black, Robert; Leung, Ruby; ...

2015-05-22

This paper reviews research approaches and open questions regarding data, statistical analyses, dynamics, modeling efforts, and trends in relation to temperature extremes. Our specific focus is upon extreme events of short duration (roughly less than 5 days) that affect parts of North America. These events are associated with large scale meteorological patterns (LSMPs). Methods used to define extreme events statistics and to identify and connect LSMPs to extreme temperatures are presented. Recent advances in statistical techniques can connect LSMPs to extreme temperatures through appropriately defined covariates that supplements more straightforward analyses. A wide array of LSMPs, ranging from synoptic tomore » planetary scale phenomena, have been implicated as contributors to extreme temperature events. Current knowledge about the physical nature of these contributions and the dynamical mechanisms leading to the implicated LSMPs is incomplete. There is a pressing need for (a) systematic study of the physics of LSMPs life cycles and (b) comprehensive model assessment of LSMP-extreme temperature event linkages and LSMP behavior. Generally, climate models capture the observed heat waves and cold air outbreaks with some fidelity. However they overestimate warm wave frequency and underestimate cold air outbreaks frequency, and underestimate the collective influence of low-frequency modes on temperature extremes. Climate models have been used to investigate past changes and project future trends in extreme temperatures. Overall, modeling studies have identified important mechanisms such as the effects of large-scale circulation anomalies and land-atmosphere interactions on changes in extreme temperatures. However, few studies have examined changes in LSMPs more specifically to understand the role of LSMPs on past and future extreme temperature changes. Even though LSMPs are resolvable by global and regional climate models, they are not necessarily well simulated so more research is needed to understand the limitations of climate models and improve model skill in simulating extreme temperatures and their associated LSMPs. Furthermore, the paper concludes with unresolved issues and research questions.« less

A collaborative characterization of North American grasslands and rangelands: climate, ecohydrology and carbon sink-source dynamics

NASA Astrophysics Data System (ADS)

Petrie, M. D.; Brunsell, N. A.; Vargas, R.; Collins, S. L.

2013-12-01

Grassland and rangeland ecoregions extend across the North American continent and exhibit diversity in climate, ecosystem services, and biophysical processes. In many grasslands and rangelands, the potential for reductions in ecosystem services and for large-scale ecosystem state change may increase under future climate scenarios. Climate change projections for North America vary, however, and the way changing climate will influence specific ecoregions is largely unknown. To better understand the regional effects of climate change on grasslands and rangelands, it is important to better understand the biophysical characteristics of these systems locally, and to identify the sensitivity of these characteristics to observed climate variation. In our study, we propose to use eddy covariance, soil moisture and precipitation data to identify how the grasslands and rangelands of North America differ in their responses to climate variability through time, with specific focus on the active growing season. Our primary goal is to determine the sensitivity of ecosystem Net Primary Productivity [NPP] to variation in temperature and precipitation patterns, and classify North American grasslands and rangelands by these sensitivities in addition to more standard climate and productivity variables. Our preliminary analyses in mesic, semiarid and arid grasslands in Kansas, Colorado and New Mexico show significant (P < 0.05) differences in climate, carbon sink strength and growing season length, and suggest that patterns of seasonal productivity and precipitation sensitivity may elucidate important grassland and rangeland responses to changing climate. Using change in Gross Primary Productivity (GPP) as an indicator of the onset of photosynthesis in spring and of senescense in the fall, grassland and rangeland ecosystems in Kansas (top and bottom left panels) and New Mexico (bottom right panel) display differing patterns of activity throughout the year.

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.

Synoptic moisture pathways associated with mean and extreme precipitation over Canada for winter and spring

NASA Astrophysics Data System (ADS)

Tan, X.; Gan, T. Y. Y.; Chen, Y. D.

2017-12-01

Dominant synoptic moisture pathway patterns of vertically integrated water vapor transport (IVT) in winter and spring over Canada West and East were identified using the self-organizing map method. Large-scale meteorological patterns (LSMPs) were related to the variability in seasonal precipitation totals and occurrences of precipitation extremes. Changes in both occurrences of LSMPs and seasonal precipitation occurred under those LSMPs were evaluated to attribute observed changes in seasonal precipitation totals and occurrences of precipitation extremes. Effects of large-scale climate anomalies on occurrences of LSMPs were also examined. Results show that synoptic moisture pathways and LSMPs exhibit the propagation of jet streams as the location and direction of ridges and troughs, and the strength and center of pressure lows and highs varied considerably between LSMPs. Significant decreases in occurrences of synoptic moisture pathway patterns that are favorable with positive precipitation anomalies and more precipitation extremes in winter over Canada West resulted in decreases in seasonal precipitation and occurrences of precipitation extremes. LSMPs resulting in a hot and dry climate and less (more) frequent precipitation extremes over the Canadian Prairies in winter and northwestern Canada in spring are more likely to occur in years with a negative phase of PNA. Occurrences of LSMPs for a wet climate and frequent occurrences of extreme precipitation events over southeastern Canada are associated with a positive phase of NAO. In El Niño years or negative PDO years, LSMPs associated with a dry climate and less frequent precipitation extremes over western Canada tend to occur.

Rainfall From Resolved Rather Than Parameterized Processes Better Represents the Present-Day and Climate Change Response of Moderate Rates in the Community Atmosphere Model

DOE PAGES

Kooperman, Gabriel J.; Pritchard, Michael S.; O'Brien, Travis A.; ...

2018-04-01

Deficiencies in the parameterizations of convection used in global climate models often lead to a distorted representation of the simulated rainfall intensity distribution (i.e., too much rainfall from weak rain rates). While encouraging improvements in high percentile rainfall intensity have been found as the horizontal resolution of the Community Atmosphere Model is increased to ~25 km, we demonstrate no corresponding improvement in the moderate rain rates that generate the majority of accumulated rainfall. Using a statistical framework designed to emphasize links between precipitation intensity and accumulated rainfall beyond just the frequency distribution, we show that CAM cannot realistically simulate moderatemore » rain rates, and cannot capture their intensification with climate change, even as resolution is increased. However, by separating the parameterized convective and large-scale resolved contributions to total rainfall, we find that the intensity, geographic pattern, and climate change response of CAM's large-scale rain rates are more consistent with observations (TRMM 3B42), superparameterization, and theoretical expectations, despite issues with parameterized convection. Increasing CAM's horizontal resolution does improve the representation of total rainfall intensity, but not due to changes in the intensity of large-scale rain rates, which are surprisingly insensitive to horizontal resolution. Rather, improvements occur through an increase in the relative contribution of the large-scale component to the total amount of accumulated rainfall. Analysis of sensitivities to convective timescale and entrainment rate confirm the importance of these parameters in the possible development of scale-aware parameterizations, but also reveal unrecognized trade-offs from the entanglement of precipitation frequency and total amount.« less

Rainfall From Resolved Rather Than Parameterized Processes Better Represents the Present-Day and Climate Change Response of Moderate Rates in the Community Atmosphere Model

NASA Astrophysics Data System (ADS)

Kooperman, Gabriel J.; Pritchard, Michael S.; O'Brien, Travis A.; Timmermans, Ben W.

2018-04-01

Deficiencies in the parameterizations of convection used in global climate models often lead to a distorted representation of the simulated rainfall intensity distribution (i.e., too much rainfall from weak rain rates). While encouraging improvements in high percentile rainfall intensity have been found as the horizontal resolution of the Community Atmosphere Model is increased to ˜25 km, we demonstrate no corresponding improvement in the moderate rain rates that generate the majority of accumulated rainfall. Using a statistical framework designed to emphasize links between precipitation intensity and accumulated rainfall beyond just the frequency distribution, we show that CAM cannot realistically simulate moderate rain rates, and cannot capture their intensification with climate change, even as resolution is increased. However, by separating the parameterized convective and large-scale resolved contributions to total rainfall, we find that the intensity, geographic pattern, and climate change response of CAM's large-scale rain rates are more consistent with observations (TRMM 3B42), superparameterization, and theoretical expectations, despite issues with parameterized convection. Increasing CAM's horizontal resolution does improve the representation of total rainfall intensity, but not due to changes in the intensity of large-scale rain rates, which are surprisingly insensitive to horizontal resolution. Rather, improvements occur through an increase in the relative contribution of the large-scale component to the total amount of accumulated rainfall. Analysis of sensitivities to convective timescale and entrainment rate confirm the importance of these parameters in the possible development of scale-aware parameterizations, but also reveal unrecognized trade-offs from the entanglement of precipitation frequency and total amount.

Rainfall From Resolved Rather Than Parameterized Processes Better Represents the Present-Day and Climate Change Response of Moderate Rates in the Community Atmosphere Model

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

Kooperman, Gabriel J.; Pritchard, Michael S.; O'Brien, Travis A.

Deficiencies in the parameterizations of convection used in global climate models often lead to a distorted representation of the simulated rainfall intensity distribution (i.e., too much rainfall from weak rain rates). While encouraging improvements in high percentile rainfall intensity have been found as the horizontal resolution of the Community Atmosphere Model is increased to ~25 km, we demonstrate no corresponding improvement in the moderate rain rates that generate the majority of accumulated rainfall. Using a statistical framework designed to emphasize links between precipitation intensity and accumulated rainfall beyond just the frequency distribution, we show that CAM cannot realistically simulate moderatemore » rain rates, and cannot capture their intensification with climate change, even as resolution is increased. However, by separating the parameterized convective and large-scale resolved contributions to total rainfall, we find that the intensity, geographic pattern, and climate change response of CAM's large-scale rain rates are more consistent with observations (TRMM 3B42), superparameterization, and theoretical expectations, despite issues with parameterized convection. Increasing CAM's horizontal resolution does improve the representation of total rainfall intensity, but not due to changes in the intensity of large-scale rain rates, which are surprisingly insensitive to horizontal resolution. Rather, improvements occur through an increase in the relative contribution of the large-scale component to the total amount of accumulated rainfall. Analysis of sensitivities to convective timescale and entrainment rate confirm the importance of these parameters in the possible development of scale-aware parameterizations, but also reveal unrecognized trade-offs from the entanglement of precipitation frequency and total amount.« less

Towards an automatic statistical model for seasonal precipitation prediction and its application to Central and South Asian headwater catchments

NASA Astrophysics Data System (ADS)

Gerlitz, Lars; Gafurov, Abror; Apel, Heiko; Unger-Sayesteh, Katy; Vorogushyn, Sergiy; Merz, Bruno

2016-04-01

Statistical climate forecast applications typically utilize a small set of large scale SST or climate indices, such as ENSO, PDO or AMO as predictor variables. If the predictive skill of these large scale modes is insufficient, specific predictor variables such as customized SST patterns are frequently included. Hence statistically based climate forecast models are either based on a fixed number of climate indices (and thus might not consider important predictor variables) or are highly site specific and barely transferable to other regions. With the aim of developing an operational seasonal forecast model, which is easily transferable to any region in the world, we present a generic data mining approach which automatically selects potential predictors from gridded SST observations and reanalysis derived large scale atmospheric circulation patterns and generates robust statistical relationships with posterior precipitation anomalies for user selected target regions. Potential predictor variables are derived by means of a cellwise correlation analysis of precipitation anomalies with gridded global climate variables under consideration of varying lead times. Significantly correlated grid cells are subsequently aggregated to predictor regions by means of a variability based cluster analysis. Finally for every month and lead time, an individual random forest based forecast model is automatically calibrated and evaluated by means of the preliminary generated predictor variables. The model is exemplarily applied and evaluated for selected headwater catchments in Central and South Asia. Particularly the for winter and spring precipitation (which is associated with westerly disturbances in the entire target domain) the model shows solid results with correlation coefficients up to 0.7, although the variability of precipitation rates is highly underestimated. Likewise for the monsoonal precipitation amounts in the South Asian target areas a certain skill of the model could be detected. The skill of the model for the dry summer season in Central Asia and the transition seasons over South Asia is found to be low. A sensitivity analysis by means on well known climate indices reveals the major large scale controlling mechanisms for the seasonal precipitation climate of each target area. For the Central Asian target areas, both, the El Nino Southern Oscillation and the North Atlantic Oscillation are identified as important controlling factors for precipitation totals during moist spring season. Drought conditions are found to be triggered by a warm ENSO phase in combination with a positive phase of the NAO. For the monsoonal summer precipitation amounts over Southern Asia, the model suggests a distinct negative response to El Nino events.

North Atlantic sub-decadal variability in climate models

NASA Astrophysics Data System (ADS)

Reintges, Annika; Martin, Thomas; Latif, Mojib; Park, Wonsun

2017-04-01

The North Atlantic Oscillation (NAO) is the dominant variability mode for the winter climate of the North Atlantic sector. During a positive (negative) NAO phase, the sea level pressure (SLP) difference between the subtropical Azores high and the subpolar Icelandic low is anomalously strong (weak). This affects, for example, temperature, precipitation, wind, and surface heat flux over the North Atlantic, and over large parts of Europe. In observations we find enhanced sub-decadal variability of the NAO index that goes along with a dipolar sea surface temperature (SST) pattern. The corresponding SLP and SST patterns are reproduced in a control experiment of the Kiel Climate Model (KCM). Large-scale air-sea interaction is suggested to be essential for the North Atlantic sub-decadal variability in the KCM. The Atlantic Meridional Overturning Circulation (AMOC) plays a key role, setting the timescale of the variability by providing a delayed negative feedback to the NAO. The interplay of the NAO and the AMOC on the sub-decadal timescale is further investigated in the CMIP5 model ensemble. For example, the average CMIP5 model AMOC pattern associated with sub-decadal variability is characterized by a deep-reaching dipolar structure, similar to the KCM's sub-decadal AMOC variability pattern. The results suggest that dynamical air-sea interactions are crucial to generate enhanced sub-decadal variability in the North Atlantic climate.

Sandy beaches: state of the art of nematode ecology.

PubMed

Maria, Tatiana F; Vanaverbeke, Jan; Vanreusel, Ann; Esteves, André M

2016-01-01

In this review, we summarize existing knowledge of the ecology of sandy-beach nematodes, in relation to spatial distribution, food webs, pollution and climate change. We attempt to discuss spatial scale patterns (macro-, meso- and microscale) according to their degree of importance in structuring sandy-beach nematode assemblages. This review will provide a substantial background on current knowledge of sandy-beach nematodes, and can be used as a starting point to delineate further investigations in this field. Over decades, sandy beaches have been the scene of studies focusing on community and population ecology, both related to morphodynamic models. The combination of physical factors (e.g. grain size, tidal exposure) and biological interactions (e.g. trophic relationships) is responsible for the spatial distribution of nematodes. In other words, the physical factors are more important in structuring nematodes communities over large scale of distribution while biological interactions are largely important in finer-scale distributions. It has been accepted that biological interactions are assumed to be of minor importance because physical factors overshadow the biological interactions in sandy beach sediments; however, the most recent results from in-situ and ex-situ experimental investigations on behavior and biological factors on a microscale have shown promise for understanding the mechanisms underlying larger-scale patterns and processes. Besides nematodes are very promising organisms used to understand the effects of pollution and climate changes although these subjects are less studied in sandy beaches than distribution patterns.

Studies of regional-scale climate variability and change. Hidden Markov models and coupled ocean-atmosphere modes

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

Ghil, M.; Kravtsov, S.; Robertson, A. W.

2008-10-14

This project was a continuation of previous work under DOE CCPP funding, in which we had developed a twin approach of probabilistic network (PN) models (sometimes called dynamic Bayesian networks) and intermediate-complexity coupled ocean-atmosphere models (ICMs) to identify the predictable modes of climate variability and to investigate their impacts on the regional scale. We had developed a family of PNs (similar to Hidden Markov Models) to simulate historical records of daily rainfall, and used them to downscale GCM seasonal predictions. Using an idealized atmospheric model, we had established a novel mechanism through which ocean-induced sea-surface temperature (SST) anomalies might influencemore » large-scale atmospheric circulation patterns on interannual and longer time scales; we had found similar patterns in a hybrid coupled ocean-atmosphere-sea-ice model. The goal of the this continuation project was to build on these ICM results and PN model development to address prediction of rainfall and temperature statistics at the local scale, associated with global climate variability and change, and to investigate the impact of the latter on coupled ocean-atmosphere modes. Our main results from the grant consist of extensive further development of the hidden Markov models for rainfall simulation and downscaling together with the development of associated software; new intermediate coupled models; a new methodology of inverse modeling for linking ICMs with observations and GCM results; and, observational studies of decadal and multi-decadal natural climate results, informed by ICM results.« less

Exploiting Synoptic-Scale Climate Processes to Develop Nonstationary, Probabilistic Flood Hazard Projections

NASA Astrophysics Data System (ADS)

Spence, C. M.; Brown, C.; Doss-Gollin, J.

2016-12-01

Climate model projections are commonly used for water resources management and planning under nonstationarity, but they do not reliably reproduce intense short-term precipitation and are instead more skilled at broader spatial scales. To provide a credible estimate of flood trend that reflects climate uncertainty, we present a framework that exploits the connections between synoptic-scale oceanic and atmospheric patterns and local-scale flood-producing meteorological events to develop long-term flood hazard projections. We demonstrate the method for the Iowa River, where high flow episodes have been found to correlate with tropical moisture exports that are associated with a pressure dipole across the eastern continental United States We characterize the relationship between flooding on the Iowa River and this pressure dipole through a nonstationary Pareto-Poisson peaks-over-threshold probability distribution estimated based on the historic record. We then combine the results of a trend analysis of dipole index in the historic record with the results of a trend analysis of the dipole index as simulated by General Circulation Models (GCMs) under climate change conditions through a Bayesian framework. The resulting nonstationary posterior distribution of dipole index, combined with the dipole-conditioned peaks-over-threshold flood frequency model, connects local flood hazard to changes in large-scale atmospheric pressure and circulation patterns that are related to flooding in a process-driven framework. The Iowa River example demonstrates that the resulting nonstationary, probabilistic flood hazard projection may be used to inform risk-based flood adaptation decisions.

Monthly mean large-scale analyses of upper-tropospheric humidity and wind field divergence derived from three geostationary satellites

NASA Technical Reports Server (NTRS)

Schmetz, Johannes; Menzel, W. Paul; Velden, Christopher; Wu, Xiangqian; Vandeberg, Leo; Nieman, Steve; Hayden, Christopher; Holmlund, Kenneth; Geijo, Carlos

1995-01-01

This paper describes the results from a collaborative study between the European Space Operations Center, the European Organization for the Exploitation of Meteorological Satellites, the National Oceanic and Atmospheric Administration, and the Cooperative Institute for Meteorological Satellite Studies investigating the relationship between satellite-derived monthly mean fields of wind and humidity in the upper troposphere for March 1994. Three geostationary meteorological satellites GOES-7, Meteosat-3, and Meteosat-5 are used to cover an area from roughly 160 deg W to 50 deg E. The wind fields are derived from tracking features in successive images of upper-tropospheric water vapor (WV) as depicted in the 6.5-micron absorption band. The upper-tropospheric relative humidity (UTH) is inferred from measured water vapor radiances with a physical retrieval scheme based on radiative forward calculations. Quantitative information on large-scale circulation patterns in the upper-troposphere is possible with the dense spatial coverage of the WV wind vectors. The monthly mean wind field is used to estimate the large-scale divergence; values range between about-5 x 10(exp -6) and 5 x 10(exp 6)/s when averaged over a scale length of about 1000-2000 km. The spatial patterns of the UTH field and the divergence of the wind field closely resemble one another, suggesting that UTH patterns are principally determined by the large-scale circulation. Since the upper-tropospheric humidity absorbs upwelling radiation from lower-tropospheric levels and therefore contributes significantly to the atmospheric greenhouse effect, this work implies that studies on the climate relevance of water vapor should include three-dimensional modeling of the atmospheric dynamics. The fields of UTH and WV winds are useful parameters for a climate-monitoring system based on satellite data. The results from this 1-month analysis suggest the desirability of further GOES and Meteosat studies to characterize the changes in the upper-tropospheric moisture sources and sinks over the past decade.

Ocean-atmosphere forcing of centennial hydroclimatic variability in the Pacific Northwest

USGS Publications Warehouse

Steinman, Byron A.; Abbott, Mark B.; Mann, Michael E.; Ortiz, Joseph D.; Feng, Song; Pompeani, David P.; Stansell, Nathan D.; Anderson, Lesleigh; Finney, Bruce P.; Bird, Broxton W.

2014-01-01

Reconstructing centennial timescale hydroclimate variability during the late Holocene is critically important for understanding large-scale patterns of drought and their relationship with climate dynamics. We present sediment oxygen isotope records spanning the last two millennia from 10 lakes, as well as climate model simulations, indicating that the Little Ice Age was dry relative to the Medieval Climate Anomaly in much of the Pacific Northwest of North America. This pattern is consistent with observed associations between the El Niño Southern Oscillation (ENSO), the Northern Annular Mode and drought as well as with proxy-based reconstructions of Pacific ocean-atmosphere variations over the past 1000 years. The large amplitude of centennial variability indicated by the lake data suggests that regional hydroclimate is characterized by longer-term shifts in ENSO-like dynamics, and that an improved understanding of the centennial timescale relationship between external forcing and drought conditions is necessary for projecting future hydroclimatic conditions in western North America.

Large Scale Processes and Extreme Floods in Brazil

NASA Astrophysics Data System (ADS)

Ribeiro Lima, C. H.; AghaKouchak, A.; Lall, U.

2016-12-01

Persistent large scale anomalies in the atmospheric circulation and ocean state have been associated with heavy rainfall and extreme floods in water basins of different sizes across the world. Such studies have emerged in the last years as a new tool to improve the traditional, stationary based approach in flood frequency analysis and flood prediction. Here we seek to advance previous studies by evaluating the dominance of large scale processes (e.g. atmospheric rivers/moisture transport) over local processes (e.g. local convection) in producing floods. We consider flood-prone regions in Brazil as case studies and the role of large scale climate processes in generating extreme floods in such regions is explored by means of observed streamflow, reanalysis data and machine learning methods. The dynamics of the large scale atmospheric circulation in the days prior to the flood events are evaluated based on the vertically integrated moisture flux and its divergence field, which are interpreted in a low-dimensional space as obtained by machine learning techniques, particularly supervised kernel principal component analysis. In such reduced dimensional space, clusters are obtained in order to better understand the role of regional moisture recycling or teleconnected moisture in producing floods of a given magnitude. The convective available potential energy (CAPE) is also used as a measure of local convection activities. We investigate for individual sites the exceedance probability in which large scale atmospheric fluxes dominate the flood process. Finally, we analyze regional patterns of floods and how the scaling law of floods with drainage area responds to changes in the climate forcing mechanisms (e.g. local vs large scale).

Projected future vegetation changes for the northwest United States and southwest Canada at a fine spatial resolution using a dynamic global vegetation model.

USGS Publications Warehouse

Shafer, Sarah; Bartlein, Patrick J.; Gray, Elizabeth M.; Pelltier, Richard T.

2015-01-01

Future climate change may significantly alter the distributions of many plant taxa. The effects of climate change may be particularly large in mountainous regions where climate can vary significantly with elevation. Understanding potential future vegetation changes in these regions requires methods that can resolve vegetation responses to climate change at fine spatial resolutions. We used LPJ, a dynamic global vegetation model, to assess potential future vegetation changes for a large topographically complex area of the northwest United States and southwest Canada (38.0–58.0°N latitude by 136.6–103.0°W longitude). LPJ is a process-based vegetation model that mechanistically simulates the effect of changing climate and atmospheric CO2 concentrations on vegetation. It was developed and has been mostly applied at spatial resolutions of 10-minutes or coarser. In this study, we used LPJ at a 30-second (~1-km) spatial resolution to simulate potential vegetation changes for 2070–2099. LPJ was run using downscaled future climate simulations from five coupled atmosphere-ocean general circulation models (CCSM3, CGCM3.1(T47), GISS-ER, MIROC3.2(medres), UKMO-HadCM3) produced using the A2 greenhouse gases emissions scenario. Under projected future climate and atmospheric CO2 concentrations, the simulated vegetation changes result in the contraction of alpine, shrub-steppe, and xeric shrub vegetation across the study area and the expansion of woodland and forest vegetation. Large areas of maritime cool forest and cold forest are simulated to persist under projected future conditions. The fine spatial-scale vegetation simulations resolve patterns of vegetation change that are not visible at coarser resolutions and these fine-scale patterns are particularly important for understanding potential future vegetation changes in topographically complex areas.

Projected Future Vegetation Changes for the Northwest United States and Southwest Canada at a Fine Spatial Resolution Using a Dynamic Global Vegetation Model

PubMed Central

Shafer, Sarah L.; Bartlein, Patrick J.; Gray, Elizabeth M.; Pelltier, Richard T.

2015-01-01

Future climate change may significantly alter the distributions of many plant taxa. The effects of climate change may be particularly large in mountainous regions where climate can vary significantly with elevation. Understanding potential future vegetation changes in these regions requires methods that can resolve vegetation responses to climate change at fine spatial resolutions. We used LPJ, a dynamic global vegetation model, to assess potential future vegetation changes for a large topographically complex area of the northwest United States and southwest Canada (38.0–58.0°N latitude by 136.6–103.0°W longitude). LPJ is a process-based vegetation model that mechanistically simulates the effect of changing climate and atmospheric CO2 concentrations on vegetation. It was developed and has been mostly applied at spatial resolutions of 10-minutes or coarser. In this study, we used LPJ at a 30-second (~1-km) spatial resolution to simulate potential vegetation changes for 2070–2099. LPJ was run using downscaled future climate simulations from five coupled atmosphere-ocean general circulation models (CCSM3, CGCM3.1(T47), GISS-ER, MIROC3.2(medres), UKMO-HadCM3) produced using the A2 greenhouse gases emissions scenario. Under projected future climate and atmospheric CO2 concentrations, the simulated vegetation changes result in the contraction of alpine, shrub-steppe, and xeric shrub vegetation across the study area and the expansion of woodland and forest vegetation. Large areas of maritime cool forest and cold forest are simulated to persist under projected future conditions. The fine spatial-scale vegetation simulations resolve patterns of vegetation change that are not visible at coarser resolutions and these fine-scale patterns are particularly important for understanding potential future vegetation changes in topographically complex areas. PMID:26488750

The impact of large-scale circulation patterns on summer crop yields in IP

NASA Astrophysics Data System (ADS)

Capa Morocho, Mirian; Rodríguez Fonseca, Belén; Ruiz Ramos, Margarita

2014-05-01

Large-scale circulations patterns (ENSO, NAO) have been shown to have a significant impact on seasonal weather, and therefore on crop yield over many parts of the world(Garnett and Khandekar, 1992; Aasa et al., 2004; Rozas and Garcia-Gonzalez, 2012). In this study, we analyze the influence of large-scale circulation patterns and regional climate on the principal components of maize yield variability in Iberian Peninsula (IP) using reanalysis datasets. Additionally, we investigate the modulation of these relationships by multidecadal patterns. This study is performed analyzing long time series of maize yield, only climate dependent, computed with the crop model CERES-maize (Jones and Kiniry, 1986) included in Decision Support System for Agrotechnology Transfer (DSSAT v.4.5). To simulate yields, reanalysis daily data of radiation, maximum and minimum temperature and precipitation were used. The reanalysis climate data were obtained from National Center for Environmental Prediction (20th Century and NCEP) and European Centre for Medium-Range Weather Forecasts (ECMWF) data server (ERA 40 and ERA Interim). Simulations were run at five locations: Lugo (northwestern), Lerida (NE), Madrid (central), Albacete (southeastern) and Córdoba (S IP) (Gabaldón et al., 2013). From these time series standardized anomalies were calculated. Afterwards, time series were time filtered to focus on the interannual-to-multiannual variability, splitting up in two components: low frequency (LF) and high frequency (HF) time scales. The principal components of HF yield anomalies in IP were compared with a set of documented patterns. These relationships were compared with multidecadal patterns, as Atlanctic Multidecadal Oscillations (AMO) and Interdecadal Pacific Oscillations (IPO). The results of this study have important implications in crop forecasting. In this way, it may have a positive impact on both public (agricultural planning) and private (decision support to farmers, insurance companies) sectors, to take advantage of favorable conditions or reduce the effect of adverse conditions. Acknowledgements Research by M. Capa-Morocho has been partly supported by a PICATA predoctoral fellowship of the Moncloa Campus of International Excellence (UCM-UPM) and MULCLIVAR project (CGL2012-38923-C02-02) References Aasa, A., Jaagus, J., Ahas, R. and Sepp, M. 2004. The influence of atmospheric circulation on plant phenological phases in central and eastern Europe. International Journal of Climatology 24, 1551-1564. Gabaldón, C. et al. 2013. Evaluation of local strategies to climate change of maize crop in Andalusia for the first half of 21st century. European Geosciences Union - General Assembly2013 Vol. 15 (Vienna - Austria, 2013). Garnett, E. R. and Khandekar, M. L. 1992. The impact of large-scale atmospheric circulations and anomalies on Indian monsoon droughts and floods and on world grain yields-a statistical analysis. Agricultural and Forest Meteorology 61, 113-128. Jones, C. and Kiniry, J. 1986. CERES-Maize: A Simulation Model of Maize Growth and Development. Texas A&M University Press, 194. Rozas, V. and Garcia-Gonzalez, I. 2012. Non-stationary influence of El Nino-Southern Oscillation and winter temperature on oak latewood growth in NW Iberian Peninsula. Int J Biometeorol 56, 787-800.

Direct and indirect effects of climate change on projected future fire regimes in the western United States.

PubMed

Liu, Zhihua; Wimberly, Michael C

2016-01-15

We asked two research questions: (1) What are the relative effects of climate change and climate-driven vegetation shifts on different components of future fire regimes? (2) How does incorporating climate-driven vegetation change into future fire regime projections alter the results compared to projections based only on direct climate effects? We used the western United States (US) as study area to answer these questions. Future (2071-2100) fire regimes were projected using statistical models to predict spatial patterns of occurrence, size and spread for large fires (>400 ha) and a simulation experiment was conducted to compare the direct climatic effects and the indirect effects of climate-driven vegetation change on fire regimes. Results showed that vegetation change amplified climate-driven increases in fire frequency and size and had a larger overall effect on future total burned area in the western US than direct climate effects. Vegetation shifts, which were highly sensitive to precipitation pattern changes, were also a strong determinant of the future spatial pattern of burn rates and had different effects on fire in currently forested and grass/shrub areas. Our results showed that climate-driven vegetation change can exert strong localized effects on fire occurrence and size, which in turn drive regional changes in fire regimes. The effects of vegetation change for projections of the geographic patterns of future fire regimes may be at least as important as the direct effects of climate change, emphasizing that accounting for changing vegetation patterns in models of future climate-fire relationships is necessary to provide accurate projections at continental to global scales. Copyright © 2015 Elsevier B.V. All rights reserved.

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.

Global linkages between teleconnection patterns and the terrestrial biosphere

NASA Astrophysics Data System (ADS)

Dahlin, Kyla M.; Ault, Toby R.

2018-07-01

Interannual variability in the global carbon cycle is largely due to variations in carbon uptake by terrestrial ecosystems, yet linkages between climate variability and variability in the terrestrial carbon cycle are not well understood at the global scale. Using a 30-year satellite record of semi-monthly leaf area index (LAI), we show that four modes of climate variability - El Niño/Southern Oscillation, the North Atlantic Oscillation, the Atlantic Meridional Mode, and the Indian Ocean Dipole Mode - strongly impact interannual vegetation growth patterns, with 68% of the land surface impacted by at least one of these teleconnection patterns, yet the spatial distribution of these impacts is heterogeneous. Considering the patterns' impacts by biome, none has an exclusively positive or negative relationship with LAI. Our findings imply that future changes in the frequency and/or magnitude of teleconnection patterns will lead to diverse changes to the terrestrial biosphere and the global carbon cycle.

Responses of the Tropical Atmospheric Circulation to Climate Change and Connection to the Hydrological Cycle

NASA Astrophysics Data System (ADS)

Ma, Jian; Chadwick, Robin; Seo, Kyong-Hwan; Dong, Changming; Huang, Gang; Foltz, Gregory R.; Jiang, Jonathan H.

2018-05-01

This review describes the climate change–induced responses of the tropical atmospheric circulation and their impacts on the hydrological cycle. We depict the theoretically predicted changes and diagnose physical mechanisms for observational and model-projected trends in large-scale and regional climate. The tropical circulation slows down with moisture and stratification changes, connecting to a poleward expansion of the Hadley cells and a shift of the intertropical convergence zone. Redistributions of regional precipitation consist of thermodynamic and dynamical components, including a strong offset between moisture increase and circulation weakening throughout the tropics. This allows other dynamical processes to dominate local circulation changes, such as a surface warming pattern effect over oceans and multiple mechanisms over land. To improve reliability in climate projections, more fundamental understandings of pattern formation, circulation change, and the balance of various processes redistributing land rainfall are suggested to be important.

Evapotranspiration patterns in complex upland forests reveal contrasting topographic thresholds of non-linearity

NASA Astrophysics Data System (ADS)

Metzen, D.; Sheridan, G. J.; Benyon, R. G.; Bolstad, P. V.; Nyman, P.; Lane, P. N. J.

2017-12-01

Large areas of forest are often treated as being homogeneous just because they fall in a single climate category. However, we observe strong vegetation patterns in relation to topography in SE Australian forests and thus hypothesise that ET will vary spatially as well. Spatial heterogeneity evolves over different temporal scales in response to climatic forcing with increasing time lag from soil moisture (sub-yearly), to vegetation (10s -100s of years) to soil properties and topography (>100s of years). Most importantly, these processes and time scales are not independent, creating feedbacks that result in "co-evolved stable states" which yield the current spatial terrain, vegetation and ET patterns. We used up-scaled sap flux and understory ET measurements from water-balance plots, as well as LiDAR derived terrain and vegetation information, to infer links between spatio-temporal energy and water fluxes, topography and vegetation patterns at small catchment scale. Topography caused variations in aridity index between polar and equatorial-facing slopes (1.3 vs 1.8), which in turn manifested in significant differences in sapwood area index (6.9 vs 5.8), overstory LAI (3.0 vs 2.3), understory LAI (0.5 vs 0.4), sub-canopy radiation load (4.6 vs 6.8 MJ m-2 d-1), overstory transpiration (501 vs 347 mm a-1) and understory ET (79 vs 155 mm a-1). Large spatial variation in overstory transpiration (195 to 891 mm a-1) was observed over very short distances (100s m); a range representative of diverse forests such as arid open woodlands and wet mountain ash forests. Contrasting, non-linear overstory and understory ET patterns were unveiled between aspects, and topographic thresholds were lower for overstory than understory ET. While ET partitioning remained stable on polar-facing slopes regardless of slope position, overstory contribution gradually decreased with increasing slope inclination on equatorial aspects. Further, we show that ET patterns and controls underlie strong seasonality and overstory LAI explained 61% of variations in ET partitioning over the entire domain. Strong links between vegetation, topography and energy and water fluxes offer the potential to exploit terrain and vegetation patterns to infer spatio-temporal ET dynamics ultimately helping manage water resources in a changing climate.

2012/13 abnormal cold winter in Japan associated with Large-scale Atmospheric Circulation and Local Sea Surface Temperature over the Sea of Japan

NASA Astrophysics Data System (ADS)

Ando, Y.; Ogi, M.; Tachibana, Y.

2013-12-01

On Japan, wintertime cold wave has social, economic, psychological and political impacts because of the lack of atomic power stations in the era of post Fukushima world. The colder winter is the more electricity is needed. Wintertime weather of Japan and its prediction has come under the world spotlight. The winter of 2012/13 in Japan was abnormally cold, and such a cold winter has persisted for 3 years. Wintertime climate of Japan is governed by some dominant modes of the large-scale atmospheric circulations. Yasunaka and Hanawa (2008) demonstrated that the two dominant modes - Arctic Oscillation (AO) and Western Pacific (WP) pattern - account for about 65% of the interannual variation of the wintertime mean surface air temperature of Japan. A negative AO brings about cold winter in Japan. In addition, a negative WP also brings about cold winter in Japan. Looking back to the winter of 2012/13, both the negative AO and negative WP continued from October through December. If the previous studies were correct, it would have been extremely very cold from October through December. In fact, in December, in accordance with previous studies, it was colder than normal. Contrary to the expectation, in October and November, it was, however, warmer than normal. This discrepancy signifies that an additional hidden circumstance that heats Japan overwhelms these large-scale atmospheric circulations that cool Japan. In this study, we therefore seek an additional cause of wintertime climate of Japan particularly focusing 2012 as well as the AO and WP. We found that anomalously warm oceanic temperature surrounding Japan overwhelmed influences of the AO or WP. Unlike the inland climate, the island climate can be strongly influenced by surrounding ocean temperature, suggesting that large-scale atmospheric patterns alone do not determine the climate of islands. (a) Time series of a 5-day running mean AO index (blue) as defined by Ogi et al., (2004), who called it the SVNAM index. For reference, the conventional AO index is shown by the gray line. (b) a 5-day running mean WP index, (c) area-averaged Surface Air Temperature anomalies in Japan, (d) Air Temperature anomalies, (e) heat flux anomalies, and (f) Sea Surface Temperature anomalies. The boxed area on the Sea of Japan indicates the area in which the (d)-(f) indexes were calculated.

Regional Climate Simulations over North America: Interaction of Local Processes with Improved Large-Scale Flow.

NASA Astrophysics Data System (ADS)

Miguez-Macho, Gonzalo; Stenchikov, Georgiy L.; Robock, Alan

2005-04-01

The reasons for biases in regional climate simulations were investigated in an attempt to discern whether they arise from deficiencies in the model parameterizations or are due to dynamical problems. Using the Regional Atmospheric Modeling System (RAMS) forced by the National Centers for Environmental Prediction-National Center for Atmospheric Research reanalysis, the detailed climate over North America at 50-km resolution for June 2000 was simulated. First, the RAMS equations were modified to make them applicable to a large region, and its turbulence parameterization was corrected. The initial simulations showed large biases in the location of precipitation patterns and surface air temperatures. By implementing higher-resolution soil data, soil moisture and soil temperature initialization, and corrections to the Kain-Fritch convective scheme, the temperature biases and precipitation amount errors could be removed, but the precipitation location errors remained. The precipitation location biases could only be improved by implementing spectral nudging of the large-scale (wavelength of 2500 km) dynamics in RAMS. This corrected for circulation errors produced by interactions and reflection of the internal domain dynamics with the lateral boundaries where the model was forced by the reanalysis.

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.

Himalayan glaciers: understanding contrasting patterns of glacier behavior using multi-temporal satellite imagery

NASA Astrophysics Data System (ADS)

Racoviteanu, A.

2014-12-01

High rates of glacier retreat for the last decades are often reported, and believed to be induced by 20th century climate changes. However, regional glacier fluctuations are complex, and depend on a combination of climate and local topography. Furthermore, in ares such as the Hindu-Kush Himalaya, there are concerns about warming, decreasing monsoon precipitation and their impact on local glacier regimes. Currently, the challenge is in understanding the magnitude of feedbacks between large-scale climate forcing and small-scale glacier behavior. Spatio-temporal patterns of glacier distribution are still llimited in some areas of the high Hindu-Kush Himalaya, but multi-temporal satellite imagery has helped fill spatial and temporal gaps in regional glacier parameters in the last decade. Here I present a synopsis of the behavior of glaciers across the Himalaya, following a west to east gradient. In particular, I focus on spatial patterns of glacier parameters in the eastern Himalaya, which I investigate at multi-spatial scales using remote sensing data from declassified Corona, ASTER, Landsat ETM+, Quickbird and Worldview2 sensors. I also present the use of high-resolution imagery, including texture and thermal analysis for mapping glacier features at small scale, which are particularly useful in understanding surface trends of debris-covered glaciers, which are prevalent in the Himalaya. I compare and contrast spatial patterns of glacier area and élévation changes in the monsoon-influenced eastern Himalaya (the Everest region in the Nepal Himalaya and Sikkim in the Indian Himalaya) with other observations from the dry western Indian Himalaya (Ladakh and Lahul-Spiti), both field measurements and remote sensing-based. In the eastern Himalaya, results point to glacier area change of -0.24 % ± 0.08% per year from the 1960's to the 2006's, with a higher rate of retreat in the last decade (-0.43% /yr). Debris-covered glacier tongues show thinning trends of -30.8 m± 39 m on average over the last four decades, similar to other studies in the same climatic area. However, at small scales, the behavior of glaciers is highly heterogenous, with contrasting patterns of thickening glacier termini versus retreating nad thinning glacier tongues.

Continental synchronicity of human influenza virus epidemics despite climatic variation.

PubMed

Geoghegan, Jemma L; Saavedra, Aldo F; Duchêne, Sebastián; Sullivan, Sheena; Barr, Ian; Holmes, Edward C

2018-01-01

The factors that determine the pattern and rate of spread of influenza virus at a continental-scale are uncertain. Although recent work suggests that influenza epidemics in the United States exhibit a strong geographical correlation, the spatiotemporal dynamics of influenza in Australia, a country and continent of approximately similar size and climate complexity but with a far smaller population, are not known. Using a unique combination of large-scale laboratory-confirmed influenza surveillance comprising >450,000 entries and genomic sequence data we determined the local-level spatial diffusion of this important human pathogen nationwide in Australia. We used laboratory-confirmed influenza data to characterize the spread of influenza virus across Australia during 2007-2016. The onset of established epidemics varied across seasons, with highly synchronized epidemics coinciding with the emergence of antigenically distinct viruses, particularly during the 2009 A/H1N1 pandemic. The onset of epidemics was largely synchronized between the most populous cities, even those separated by distances of >3000 km and those that experience vastly diverse climates. In addition, by analyzing global phylogeographic patterns we show that the synchronized dissemination of influenza across Australian cities involved multiple introductions from the global influenza population, coupled with strong domestic connectivity, rather than through the distinct radial patterns of geographic dispersal that are driven by work-flow transmission as observed in the United States. In addition, by comparing the spatial structure of influenza A and B, we found that these viruses tended to occupy different geographic regions, and peak in different seasons, perhaps indicative of moderate cross-protective immunity or viral interference effects. The highly synchronized outbreaks of influenza virus at a continental-scale revealed here highlight the importance of coordinated public health responses in the event of the emergence of a novel, human-to-human transmissible, virus.

Potential climatic impacts and reliability of large-scale offshore wind farms

NASA Astrophysics Data System (ADS)

Wang, Chien; Prinn, Ronald G.

2011-04-01

The vast availability of wind power has fueled substantial interest in this renewable energy source as a potential near-zero greenhouse gas emission technology for meeting future world energy needs while addressing the climate change issue. However, in order to provide even a fraction of the estimated future energy needs, a large-scale deployment of wind turbines (several million) is required. The consequent environmental impacts, and the inherent reliability of such a large-scale usage of intermittent wind power would have to be carefully assessed, in addition to the need to lower the high current unit wind power costs. Our previous study (Wang and Prinn 2010 Atmos. Chem. Phys. 10 2053) using a three-dimensional climate model suggested that a large deployment of wind turbines over land to meet about 10% of predicted world energy needs in 2100 could lead to a significant temperature increase in the lower atmosphere over the installed regions. A global-scale perturbation to the general circulation patterns as well as to the cloud and precipitation distribution was also predicted. In the later study reported here, we conducted a set of six additional model simulations using an improved climate model to further address the potential environmental and intermittency issues of large-scale deployment of offshore wind turbines for differing installation areas and spatial densities. In contrast to the previous land installation results, the offshore wind turbine installations are found to cause a surface cooling over the installed offshore regions. This cooling is due principally to the enhanced latent heat flux from the sea surface to lower atmosphere, driven by an increase in turbulent mixing caused by the wind turbines which was not entirely offset by the concurrent reduction of mean wind kinetic energy. We found that the perturbation of the large-scale deployment of offshore wind turbines to the global climate is relatively small compared to the case of land-based installations. However, the intermittency caused by the significant seasonal wind variations over several major offshore sites is substantial, and demands further options to ensure the reliability of large-scale offshore wind power. The method that we used to simulate the offshore wind turbine effect on the lower atmosphere involved simply increasing the ocean surface drag coefficient. While this method is consistent with several detailed fine-scale simulations of wind turbines, it still needs further study to ensure its validity. New field observations of actual wind turbine arrays are definitely required to provide ultimate validation of the model predictions presented here.

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.

Ground-water recharge in the arid and semiarid southwestern United States - Climatic and geologic framework: Chapter A in Ground-water recharge in the arid and semiarid southwestern United States (Professional Paper 1703)

USGS Publications Warehouse

Stonestrom, David A.; Harrill, James R.; Stonestrom, David A.; Constantz, Jim; Ferré, Ty P.A.; Leake, Stanley A.

2007-01-01

Ground-water recharge in the arid and semiarid southwestern United States results from the complex interplay of climate, geology, and vegetation across widely ranging spatial and temporal scales. Present-day recharge tends to be narrowly focused in time and space. Widespread water-table declines accompanied agricultural development during the twentieth century, demonstrating that sustainable ground-water supplies are not guaranteed when part of the extracted resource represents paleorecharge. Climatic controls on ground-water recharge range from seasonal cycles of summer monsoonal and winter frontal storms to multimillennial cycles of glacial and interglacial periods. Precipitation patterns reflect global-scale interactions among the oceans, atmosphere, and continents. Large-scale climatic influences associated with El Niño and Pacific Decadal Oscillations strongly but irregularly control weather in the study area, so that year-to-year variations in precipitation and ground-water recharge are large and difficult to predict. Proxy data indicate geologically recent periods of multidecadal droughts unlike any in the modern instrumental record. Anthropogenically induced climate change likely will reduce ground-water recharge through diminished snowpack at higher elevations, and perhaps through increased drought. Future changes in El Niño and monsoonal patterns, both crucial to precipitation in the study area, are highly uncertain in current models. Land-use modifications influence ground-water recharge directly through vegetation, irrigation, and impermeable area, and indirectly through climate change. High ranges bounding the study area—the San Bernadino Mountains and Sierra Nevada to the west, and the Wasatch and southern Colorado Rocky Mountains to the east—provide external geologic controls on ground-water recharge. Internal geologic controls stem from tectonic processes that led to numerous, variably connected alluvial-filled basins, exposure of extensive Paleozoic aquifers in mountainous recharge areas, and distinct modes of recharge in the Colorado Plateau and Basin and Range subregions.

The geographical distribution of underweight children in Africa.

PubMed Central

Nubé, Maarten; Sonneveld, Benjamin G. J. S.

2005-01-01

OBJECTIVE: To study geographical patterns of underweight children in Africa by combining information on prevalence with headcounts at a subnational level. METHODS: We used large-scale, nationally representative nutrition surveys, in particular the Demographic and Health Surveys and the Multiple Indicator Cluster Surveys, which have been designed, analysed and presented according to largely similar protocols, and which report at the national and subnational levels. FINDINGS: We found distinct geographical patterns in the occurrence of underweight children, which could be linked to factors such as agronomic and climatic conditions, population density and economic integration. CONCLUSION: Patterns of underweight children cross national borders suggesting that regional characteristics and interactions need to be considered when addressing malnutrition. PMID:16283053

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.

Ability of an ensemble of regional climate models to reproduce weather regimes over Europe-Atlantic during the period 1961-2000

NASA Astrophysics Data System (ADS)

Sanchez-Gomez, Emilia; Somot, S.; Déqué, M.

2009-10-01

One of the main concerns in regional climate modeling is to which extent limited-area regional climate models (RCM) reproduce the large-scale atmospheric conditions of their driving general circulation model (GCM). In this work we investigate the ability of a multi-model ensemble of regional climate simulations to reproduce the large-scale weather regimes of the driving conditions. The ensemble consists of a set of 13 RCMs on a European domain, driven at their lateral boundaries by the ERA40 reanalysis for the time period 1961-2000. Two sets of experiments have been completed with horizontal resolutions of 50 and 25 km, respectively. The spectral nudging technique has been applied to one of the models within the ensemble. The RCMs reproduce the weather regimes behavior in terms of composite pattern, mean frequency of occurrence and persistence reasonably well. The models also simulate well the long-term trends and the inter-annual variability of the frequency of occurrence. However, there is a non-negligible spread among the models which is stronger in summer than in winter. This spread is due to two reasons: (1) we are dealing with different models and (2) each RCM produces an internal variability. As far as the day-to-day weather regime history is concerned, the ensemble shows large discrepancies. At daily time scale, the model spread has also a seasonal dependence, being stronger in summer than in winter. Results also show that the spectral nudging technique improves the model performance in reproducing the large-scale of the driving field. In addition, the impact of increasing the number of grid points has been addressed by comparing the 25 and 50 km experiments. We show that the horizontal resolution does not affect significantly the model performance for large-scale circulation.

Large Scale Eocene Ocean Circulation Transition Could Help Antarctic Glaciation.

NASA Astrophysics Data System (ADS)

Baatsen, M.

2016-12-01

The global climate underwent major changes going from the Eocene into the Oligocene, including the formation of a continental-scale Antarctic ice sheet. In addition to a gradual drawdown of CO2 since the Early Eocene, the changing background geography of the earth may also have played a crucial role in setting the background oceanic circulation pattern favorable to ice growth. On the other hand, the ocean circulation may have changed only after the ice sheet started growing, with a similar climatic imprint. It is, therefore, still under debate what the primary forcing or trigger of this transition was. Using an ocean general circulation model (POP) and two different geography reconstruc-tions for the middle-late Eocene, we find two distinctly different patterns of the oceanic circulation to be possible under the same forcing. The first one features deep-water formation and warmer SSTs in the Southern Pacific while in the second, deep water forms in the North Pacific Ocean and Southern Ocean SSTs are colder. The presence of a double equilibrium shows that the ocean circulation was highly susceptible to large scale transitions during the middle-late Eocene. Additionally, changes in benthic oxygen and Neodymium isotopes depict significant changes during the same period. We suggest that a transition in the global meridional overturing circulation can explain the observed changes and preconditions the global climate for the two-step transition into an Icehouse state at the Eocene-Oligocene boundary.

Canary in the coal mine: Historical oxygen decline in the Gulf of St. Lawrence due to large scale climate changes

NASA Astrophysics Data System (ADS)

Claret, M.; Galbraith, E. D.; Palter, J. B.; Gilbert, D.; Bianchi, D.; Dunne, J. P.

2016-02-01

The regional signature of anthropogenic climate change on the atmosphere and upper ocean is often difficult to discern from observational timeseries, dominated as they are by decadal climate variability. Here we argue that a long-term decline of dissolved oxygen concentrations observed in the Gulf of S. Lawrence (GoSL) is consistent with anthropogenic climate change. Oxygen concentrations in the GoSL have declined markedly since 1930 due primarily to an increase of oxygen-poor North Atlantic Central Waters relative to Labrador Current Waters (Gilbert et al. 2005). We compare these observations to a climate warming simulation using a very high-resolution global coupled ocean-atmospheric climate model. The numerical model (CM2.6), developed by the Geophysical Fluid Dynamics Laboratory, is strongly eddying and includes a biogeochemical module with dissolved oxygen. The warming scenario shows that oxygen in the GoSL decreases and it is associated to changes in western boundary currents and wind patterns in the North Atlantic. We speculate that the large-scale changes behind the simulated decrease in GoSL oxygen have also been at play in the real world over the past century, although they are difficult to resolve in noisy atmospheric data.

Corporate funding and ideological polarization about climate change

PubMed Central

Farrell, Justin

2016-01-01

Drawing on large-scale computational data and methods, this research demonstrates how polarization efforts are influenced by a patterned network of political and financial actors. These dynamics, which have been notoriously difficult to quantify, are illustrated here with a computational analysis of climate change politics in the United States. The comprehensive data include all individual and organizational actors in the climate change countermovement (164 organizations), as well as all written and verbal texts produced by this network between 1993–2013 (40,785 texts, more than 39 million words). Two main findings emerge. First, that organizations with corporate funding were more likely to have written and disseminated texts meant to polarize the climate change issue. Second, and more importantly, that corporate funding influences the actual thematic content of these polarization efforts, and the discursive prevalence of that thematic content over time. These findings provide new, and comprehensive, confirmation of dynamics long thought to be at the root of climate change politics and discourse. Beyond the specifics of climate change, this paper has important implications for understanding ideological polarization more generally, and the increasing role of private funding in determining why certain polarizing themes are created and amplified. Lastly, the paper suggests that future studies build on the novel approach taken here that integrates large-scale textual analysis with social networks. PMID:26598653

Corporate funding and ideological polarization about climate change.

PubMed

Farrell, Justin

2016-01-05

Drawing on large-scale computational data and methods, this research demonstrates how polarization efforts are influenced by a patterned network of political and financial actors. These dynamics, which have been notoriously difficult to quantify, are illustrated here with a computational analysis of climate change politics in the United States. The comprehensive data include all individual and organizational actors in the climate change countermovement (164 organizations), as well as all written and verbal texts produced by this network between 1993-2013 (40,785 texts, more than 39 million words). Two main findings emerge. First, that organizations with corporate funding were more likely to have written and disseminated texts meant to polarize the climate change issue. Second, and more importantly, that corporate funding influences the actual thematic content of these polarization efforts, and the discursive prevalence of that thematic content over time. These findings provide new, and comprehensive, confirmation of dynamics long thought to be at the root of climate change politics and discourse. Beyond the specifics of climate change, this paper has important implications for understanding ideological polarization more generally, and the increasing role of private funding in determining why certain polarizing themes are created and amplified. Lastly, the paper suggests that future studies build on the novel approach taken here that integrates large-scale textual analysis with social networks.

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.

New Insights on Hydro-Climate Feedback Processes over the Tropical Ocean from TRMM

NASA Technical Reports Server (NTRS)

Lau, William K. M.; Wu, H. T.; Li, Xiaofan; Sui, C. H.

2002-01-01

In this paper, we study hydro-climate feedback processes over the tropical oceans, by examining the relationships among large scale circulation and Tropical Rainfall Measuring Mission Microwave Imager-Sea Surface Temperature (TMI-SST), and a range of TRMM rain products including rain rate, cloud liquid water, precipitable water, cloud types and areal coverage, and precipitation efficiency. Results show that for a warm event (1998), the 28C threshold of convective precipitation is quite well defined over the tropical oceans. However, for a cold event (1999), the SST threshold is less well defined, especially over the central and eastern Pacific cold tongue, where stratiform rain occurs at much lower than 28 C. Precipitation rates and cloud liquid water are found to be more closely related to the large scale vertical motion than to the underlying SST. While total columnar water vapor is more strongly dependent on SST. For a large domain, over the eastern Pacific, we find that the areal extent of the cloudy region tends to shrink as the SST increases. Examination of the relationship between cloud liquid water and rain rate suggests that the residence time of cloud liquid water tends to be shorter, associated with higher precipitation efficiency in a warmer climate. It is hypothesized that the reduction in cloudy area may be influenced both by the shift in large scale cloud patterns in response to changes in large scale forcings, and possible increase in the cloud liquid water conversion to rain water in a warmer environment. Results of numerical experiments with the Goddard cloud resolving model to test the hypothesis will be discussed.

Evaluation of large-scale meteorological patterns associated with temperature extremes in the NARCCAP regional climate model simulations

NASA Astrophysics Data System (ADS)

Loikith, Paul C.; Waliser, Duane E.; Lee, Huikyo; Neelin, J. David; Lintner, Benjamin R.; McGinnis, Seth; Mearns, Linda O.; Kim, Jinwon

2015-12-01

Large-scale meteorological patterns (LSMPs) associated with temperature extremes are evaluated in a suite of regional climate model (RCM) simulations contributing to the North American Regional Climate Change Assessment Program. LSMPs are characterized through composites of surface air temperature, sea level pressure, and 500 hPa geopotential height anomalies concurrent with extreme temperature days. Six of the seventeen RCM simulations are driven by boundary conditions from reanalysis while the other eleven are driven by one of four global climate models (GCMs). Four illustrative case studies are analyzed in detail. Model fidelity in LSMP spatial representation is high for cold winter extremes near Chicago. Winter warm extremes are captured by most RCMs in northern California, with some notable exceptions. Model fidelity is lower for cool summer days near Houston and extreme summer heat events in the Ohio Valley. Physical interpretation of these patterns and identification of well-simulated cases, such as for Chicago, boosts confidence in the ability of these models to simulate days in the tails of the temperature distribution. Results appear consistent with the expectation that the ability of an RCM to reproduce a realistically shaped frequency distribution for temperature, especially at the tails, is related to its fidelity in simulating LMSPs. Each ensemble member is ranked for its ability to reproduce LSMPs associated with observed warm and cold extremes, identifying systematically high performing RCMs and the GCMs that provide superior boundary forcing. The methodology developed here provides a framework for identifying regions where further process-based evaluation would improve the understanding of simulation error and help guide future model improvement and downscaling efforts.

Drought Patterns Forecasting using an Auto-Regressive Logistic Model

NASA Astrophysics Data System (ADS)

del Jesus, M.; Sheffield, J.; Méndez Incera, F. J.; Losada, I. J.; Espejo, A.

2014-12-01

Drought is characterized by a water deficit that may manifest across a large range of spatial and temporal scales. Drought may create important socio-economic consequences, many times of catastrophic dimensions. A quantifiable definition of drought is elusive because depending on its impacts, consequences and generation mechanism, different water deficit periods may be identified as a drought by virtue of some definitions but not by others. Droughts are linked to the water cycle and, although a climate change signal may not have emerged yet, they are also intimately linked to climate.In this work we develop an auto-regressive logistic model for drought prediction at different temporal scales that makes use of a spatially explicit framework. Our model allows to include covariates, continuous or categorical, to improve the performance of the auto-regressive component.Our approach makes use of dimensionality reduction (principal component analysis) and classification techniques (K-Means and maximum dissimilarity) to simplify the representation of complex climatic patterns, such as sea surface temperature (SST) and sea level pressure (SLP), while including information on their spatial structure, i.e. considering their spatial patterns. This procedure allows us to include in the analysis multivariate representation of complex climatic phenomena, as the El Niño-Southern Oscillation. We also explore the impact of other climate-related variables such as sun spots. The model allows to quantify the uncertainty of the forecasts and can be easily adapted to make predictions under future climatic scenarios. The framework herein presented may be extended to other applications such as flash flood analysis, or risk assessment of natural hazards.

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.

The influence of large-scale wind power on global climate.

PubMed

Keith, David W; Decarolis, Joseph F; Denkenberger, David C; Lenschow, Donald H; Malyshev, Sergey L; Pacala, Stephen; Rasch, Philip J

2004-11-16

Large-scale use of wind power can alter local and global climate by extracting kinetic energy and altering turbulent transport in the atmospheric boundary layer. We report climate-model simulations that address the possible climatic impacts of wind power at regional to global scales by using two general circulation models and several parameterizations of the interaction of wind turbines with the boundary layer. We find that very large amounts of wind power can produce nonnegligible climatic change at continental scales. Although large-scale effects are observed, wind power has a negligible effect on global-mean surface temperature, and it would deliver enormous global benefits by reducing emissions of CO(2) and air pollutants. Our results may enable a comparison between the climate impacts due to wind power and the reduction in climatic impacts achieved by the substitution of wind for fossil fuels.

Climate, Santa Ana Winds and Autumn Wildfires in Southern California

NASA Astrophysics Data System (ADS)

Westerling, Anthony L.; Cayan, Daniel R.; Brown, Timothy J.; Hall, Beth L.; Riddle, Laurence G.

2004-08-01

Wildfires periodically burn large areas of chaparral and adjacent woodlands in autumn and winter in southern California. These fires often occur in conjunction with Santa Ana weather events, which combine high winds and low humidity, and tend to follow a wet winter rainy season. Because conditions fostering large fall and winter wildfires in California are the result of large-scale patterns in atmospheric circulation, the same dangerous conditions are likely to occur over a wide area at the same time. Furthermore, over a century of watershed reserve management and fire suppression have promoted fuel accumulations, helping to shape one of the most conflagration-prone environments in the world. Combined with a complex topography and a large human population, southern Californian ecology and climate pose a considerable physical and societal challenge to fire management.

Influence of large-scale climate modes on dynamical complexity patterns of Indian Summer Monsoon rainfall

NASA Astrophysics Data System (ADS)

Papadimitriou, Constantinos; Donner, Reik V.; Stolbova, Veronika; Balasis, Georgios; Kurths, Jürgen

2015-04-01

Indian Summer monsoon is one of the most anticipated and important weather events with vast environmental, economical and social effects. Predictability of the Indian Summer Monsoon strength is crucial question for life and prosperity of the Indian population. In this study, we are attempting to uncover the relationship between the spatial complexity of Indian Summer Monsoon rainfall patterns, and the monsoon strength, in an effort to qualitatively determine how spatial organization of the rainfall patterns differs between strong and weak instances of the Indian Summer Monsoon. Here, we use observational satellite data from 1998 to 2012 from the Tropical Rainfall Measuring Mission (TRMM 3B42V7) and reanalysis gridded daily rainfall data for a time period of 57 years (1951-2007) (Asian Precipitation Highly Resolved Observational Data Integration Towards the Evaluation of Water Resources, APHRODITE). In order to capture different aspects of the system's dynamics, first, we convert rainfall time series to binary symbolic sequences, exploring various thresholding criteria. Second, we apply the Shannon entropy formulation (in a block-entropy sense) using different measures of normalization of the resulting entropy values. Finally, we examine the effect of various large-scale climate modes such as El-Niño-Southern Oscillation, North Atlantic Oscillation, and Indian Ocean Dipole, on the emerging complexity patterns, and discuss the possibility for the utilization of such pattern maps in the forecasting of the spatial variability and strength of the Indian Summer Monsoon.

Autogenic and Allogenic: Emergent Coastline Patterns Interact With Forcing Variations

NASA Astrophysics Data System (ADS)

Murray, A. B.; Alvarez Antolinez, J. A.; Mendez, F. J.; Moore, L. J.; Wood, J.; Farley, G.

2017-12-01

A range of coastline shapes can emerge from large-scale morphodynamic interactions. Coastline shape determines local wave influences. Local wave influences (fluxes of alongshore momentum), determine sediment fluxes, and gradients in these sediment fluxes, in turn, alter coastline shape. Modeling studies show that such feedbacks lead to an instability, and to subsequent finite-amplitude interactions, producing self-organized patterns and emergent structures including sandwaves, capes, and spits (e.g. Ashton and Murray, 2006; Ashton et al., 2015); spiral bays on rocky coastlines (e.g. Barkwith et al., 2014); and convex, spit-bounded coastlines (Ells et al., in prep.). Coastline shapes depend sensitively on wave climate, defined as the angular distribution of wave influences on alongshore sediment transport. Therefore, shifts in wave climate arising from shifts in storms (decadal scale fluctuations or longer-term trends) will tend to change coastline shape. Previous efforts have detected changing coastline shape, likely related to changing influence from hurricane-generated waves, as expressed in changes in the location and intensity of coastal erosion zones along the cuspate capes in North Carolina, USA (Moore et al., 2013). These efforts involved the assumption that coastline response to changing forcing occurs in a quasi-equilibrium manner. However, in some cases coastline responses can exhibit long-term memory and path dependence (Thomas et al., 2016). Recently, we have hindcast the wave climate affecting the North Carolina coast since 1870, using a series of statistical analyses to downscale from basin-scale surface pressure fields to regional deep-water wave climate, and then a numerical transformation to local offshore wave climate. We used this wave climate as input for the Coastline Evolution Model (CEM). The results show that the emergent coastline features respond to decadal-scale shifts in wave climate, but with time lags that complicate the relationship between forcing and coastline shape. Comparisons between model predictions and observed shoreline-change patterns support the suggestion that the relationship between emergent coastline behaviours (autogenic processes) and external influences (autogenic forcing) involves such memory effects (Antolinez et al., in revision).

Statistical downscaling of daily precipitation over Llobregat river basin in Catalonia (Spain) using three downscaling methods.

NASA Astrophysics Data System (ADS)

Ballinas, R.; Versini, P.-A.; Sempere, D.; Escaler, I.

2009-09-01

Any long-term change in the patterns of average weather in a global or regional scale is called climate change. It may cause a progressive increase of atmospheric temperature and consequently may change the amount, frequency and intensity of precipitation. All these changes of meteorological parameters may modify the water cycle: run-off, infiltration, aquifer recharge, etc. Recent studies in Catalonia foresee changes in hydrological systems caused by climate change. This will lead to alterations in the hydrological cycle that could impact in land use, in the regimen of water extractions, in the hydrological characteristics of the territory and reduced groundwater recharge. Besides, can expect a loss of flow in rivers. In addition to possible increases in the frequency of extreme rainfall, being necessary to modify the design of infrastructure. Because this, it work focuses on studying the impacts of climate change in one of the most important basins in Catalonia, the Llobregat River Basin. The basin is the hub of the province of Barcelona. It is a highly populated and urbanized catchment, where water resources are used for different purposes, as drinking water production, agricultural irrigation, industry and hydro-electrical energy production. In consequence, many companies and communities depend on these resources. To study the impact of climate change in the Llobregat basin, storms (frequency, intensity) mainly, we will need regional climate change information. A regional climate is determined by interactions at large, regional and local scales. The general circulation models (GCMs) are run at too coarse resolution to permit accurate description of these regional and local interactions. So far, they have been unable to provide consistent estimates of climate change on a local scale. Several regionalization techniques have been developed to bridge the gap between the large-scale information provided by GCMs and fine spatial scales required for regional and environmental impact studies. Downscaling methods to assess the effect of large-scale circulations on local parameters have. Statistical downscaling methods are based on the view that regional climate can be conditioned by two factors: large-scale climatic state and regional/local features. Local climate information is derived by first developing a statistical model which relates large-scale variables or "predictors" for which GCMs are trustable to regional or local surface "predictands" for which models are less skilful. The main advantage of these methods is that they are computationally inexpensive, and can be applied to outputs from different GCM experiments. Three statistical downscaling methods are applied: Analogue method, Delta Change and Direct Forcing. These methods have been used to determine daily precipitation projections at rain gauge location to study the intensity, frequency and variability of storms in a context of climate change in the Llobregat River Basin in Catalonia, Spain. This work is part of the European project "Water Change" (included in the LIFE + Environment Policy and Governance program). It deals with Medium and long term water resources modelling as a tool for planning and global change adaptation. Two stakeholders involved in the project provided the historical time series: Catalan Water Agency (ACA) and the State Meteorological Agency (AEMET).

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.

Large and local-scale influences on physical and chemical characteristics of coastal waters of Western Europe during winter

NASA Astrophysics Data System (ADS)

Tréguer, Paul; Goberville, Eric; Barrier, Nicolas; L'Helguen, Stéphane; Morin, Pascal; Bozec, Yann; Rimmelin-Maury, Peggy; Czamanski, Marie; Grossteffan, Emilie; Cariou, Thierry; Répécaud, Michel; Quéméner, Loic

2014-11-01

There is now a strong scientific consensus that coastal marine systems of Western Europe are highly sensitive to the combined effects of natural climate variability and anthropogenic climate change. However, it still remains challenging to assess the spatial and temporal scales at which climate influence operates. While large-scale hydro-climatic indices, such as the North Atlantic Oscillation (NAO) or the East Atlantic Pattern (EAP) and the weather regimes such as the Atlantic Ridge (AR), are known to be relevant predictors of physical processes, changes in coastal waters can also be related to local hydro-meteorological and geochemical forcing. Here, we study the temporal variability of physical and chemical characteristics of coastal waters located at about 48°N over the period 1998-2013 using (1) sea surface temperature, (2) sea surface salinity and (3) nutrient concentration observations for two coastal sites located at the outlet of the Bay of Brest and off Roscoff, (4) river discharges of the major tributaries close to these two sites and (5) regional and local precipitation data over the region of interest. Focusing on the winter months, we characterize the physical and chemical variability of these coastal waters and document changes in both precipitation and river runoffs. Our study reveals that variability in coastal waters is connected to the large-scale North Atlantic atmospheric circulation but is also partly explained by local river influences. Indeed, while the NAO is strongly related to changes in sea surface temperature at the Brest and Roscoff sites, the EAP and the AR have a major influence on precipitations, which in turn modulate river discharges that impact sea surface salinity at the scale of the two coastal stations.

Simulated Tree Growth across the Northern Hemisphere and the Seasonality of Climate Signals Encoded within Tree-ring Widths

NASA Astrophysics Data System (ADS)

Li, X.; St George, S.

2013-12-01

Both dendrochronological theory and regional and global networks of tree-ring width measurements indicate that trees can respond to climate variations quite differently from one location to another. To explain these geographical differences at hemispheric scale, we used a process-based model of tree-ring formation (the Vaganov-Shashkin model) to simulate tree growth at over 6000 locations across the Northern Hemisphere. We compared the seasonality and strength of climate signals in the simulated tree-ring records against parallel analysis conducted on a hemispheric network of real tree-ring observations, tested the ability of the model to reproduce behaviors that emerge from large networks of tree-ring widths and used the model outputs to explain why the network exhibits these behaviors. The simulated tree-ring records are consistent with observations with respect to the seasonality and relative strength of the encoded climate signals, and time-related changes in these climate signals can be predicted using the modeled relative growth rate due to temperature or soil moisture. The positive imprint of winter (DJF) precipitation is strongest in simulations from the American Southwest and northern Mexico as well as selected locations in the Mediterranean and central Asia. Summer (JJA) precipitation has higher positive correlations with simulations in the mid-latitudes, but some high-latitude coastal sites exhibit a negative association. The influence of summer temperature is mainly positive at high-latitude or high-altitude sites and negative in the mid-latitudes. The absolute magnitude of climate correlations are generally higher in simulations than in observations, but the pattern and geographical differences remain the same, demonstrating that the model has skill in reproducing tree-ring growth response to climate variability in the Northern Hemisphere. Because the model uses only temperature, precipitation and latitude as input and is not adjusted for species or other biological factors, the fact that the climate response of the simulations largely agrees with the observations may imply that climate, rather than biology, is the main factor that influences large-scale patterns of the climate information recorded by tree rings. Our results also suggest that the Vaganov-Shashkin model could be used to estimate the likely climate response of trees in ';frontier' areas that have not been sampled extensively. Seasonal Climate Correlations of Simulated Tree-ring Records

Denudational slope processes and slope response to global climate changes and other disturbances: insights from the Nepal Himalayas.

NASA Astrophysics Data System (ADS)

Fort, Monique

2016-04-01

Hillslope geomorphology results from a large range of denudational processes mainly controlled by relief, structure, lithology, climate, land-cover and land use. In most areas of the world, the "critical zone" concept is a good integrator of denudation that operates on a long-term scale. However, in large and high mountain areas, short-time scale factors often play a significant role in the denudational pattern, accelerating and/or delaying the transfer of denudation products and fluxes, and creating specific, spatially limited disturbances. We focus on the Nepal Himalayas, where the wide altitudinal range of bio-climatic zones and the intense geodynamic activity create a complex mosaic of landforms, as expressed by the present geomorphology of mountain slopes. On the basis of examples selected in the different Himalayan mountain belts (Siwaliks hills, middle mountains, High Himalaya), we illustrate different types of slopes and disturbances induced by active tectonics, climate extremes, and climate warming trends. Special attention is paid to recent events, such as landslide damming, triggered by either intense rainfalls (Kali Gandaki and Sun Kosi valleys) or the last April-May 2015 Gorkha seismic sequence (southern Khumbu). Lastly, references to older, larger events show that despite the highly dynamic environment, landforms caused by large magnitude disturbances may persist in the landscape in the long term.

Forest disturbances under climate change

NASA Astrophysics Data System (ADS)

Seidl, Rupert; Thom, Dominik; Kautz, Markus; Martin-Benito, Dario; Peltoniemi, Mikko; Vacchiano, Giorgio; Wild, Jan; Ascoli, Davide; Petr, Michal; Honkaniemi, Juha; Lexer, Manfred J.; Trotsiuk, Volodymyr; Mairota, Paola; Svoboda, Miroslav; Fabrika, Marek; Nagel, Thomas A.; Reyer, Christopher P. O.

2017-06-01

Forest disturbances are sensitive to climate. However, our understanding of disturbance dynamics in response to climatic changes remains incomplete, particularly regarding large-scale patterns, interaction effects and dampening feedbacks. Here we provide a global synthesis of climate change effects on important abiotic (fire, drought, wind, snow and ice) and biotic (insects and pathogens) disturbance agents. Warmer and drier conditions particularly facilitate fire, drought and insect disturbances, while warmer and wetter conditions increase disturbances from wind and pathogens. Widespread interactions between agents are likely to amplify disturbances, while indirect climate effects such as vegetation changes can dampen long-term disturbance sensitivities to climate. Future changes in disturbance are likely to be most pronounced in coniferous forests and the boreal biome. We conclude that both ecosystems and society should be prepared for an increasingly disturbed future of forests.

Forest disturbances under climate change

PubMed Central

Seidl, Rupert; Thom, Dominik; Kautz, Markus; Martin-Benito, Dario; Peltoniemi, Mikko; Vacchiano, Giorgio; Wild, Jan; Ascoli, Davide; Petr, Michal; Honkaniemi, Juha; Lexer, Manfred J.; Trotsiuk, Volodymyr; Mairota, Paola; Svoboda, Miroslav; Fabrika, Marek; Nagel, Thomas A.; Reyer, Christopher P. O.

2017-01-01

Forest disturbances are sensitive to climate. However, our understanding of disturbance dynamics in response to climatic changes remains incomplete, particularly regarding large-scale patterns, interaction effects and dampening feedbacks. Here we provide a global synthesis of climate change effects on important abiotic (fire, drought, wind, snow and ice) and biotic (insects and pathogens) disturbance agents. Warmer and drier conditions particularly facilitate fire, drought and insect disturbances, while warmer and wetter conditions increase disturbances from wind and pathogens. Widespread interactions between agents are likely to amplify disturbances, while indirect climate effects such as vegetation changes can dampen long-term disturbance sensitivities to climate. Future changes in disturbance are likely to be most pronounced in coniferous forests and the boreal biome. We conclude that both ecosystems and society should be prepared for an increasingly disturbed future of forests. PMID:28861124

Groundwater Variability in a Sandstone Catchment and Linkages with Large-scale Climatic Circulatio

NASA Astrophysics Data System (ADS)

Hannah, D. M.; Lavers, D. A.; Bradley, C.

2015-12-01

Groundwater is a crucial water resource that sustains river ecosystems and provides public water supply. Furthermore, during periods of prolonged high rainfall, groundwater-dominated catchments can be subject to protracted flooding. Climate change and associated projected increases in the frequency and intensity of hydrological extremes have implications for groundwater levels. This study builds on previous research undertaken on a Chalk catchment by investigating groundwater variability in a UK sandstone catchment: the Tern in Shropshire. In contrast to the Chalk, sandstone is characterised by a more lagged response to precipitation inputs; and, as such, it is important to determine the groundwater behaviour and its links with the large-scale climatic circulation to improve process understanding of recharge, groundwater level and river flow responses to hydroclimatological drivers. Precipitation, river discharge and groundwater levels for borehole sites in the Tern basin over 1974-2010 are analysed as the target variables; and we use monthly gridded reanalysis data from the Twentieth Century Reanalysis Project (20CR). First, groundwater variability is evaluated and associations with precipitation / discharge are explored using monthly concurrent and lagged correlation analyses. Second, gridded 20CR reanalysis data are used in composite and correlation analyses to identify the regions of strongest climate-groundwater association. Results show that reasonably strong climate-groundwater connections exist in the Tern basin, with a several months lag. These lags are associated primarily with the time taken for recharge waters to percolate through to the groundwater table. The uncovered patterns improve knowledge of large-scale climate forcing of groundwater variability and may provide a basis to inform seasonal prediction of groundwater levels, which would be useful for strategic water resource planning.

The Signature of Southern Hemisphere Atmospheric Circulation Patterns in Antarctic Precipitation

PubMed Central

Thompson, David W. J.; van den Broeke, Michiel R.

2017-01-01

Abstract We provide the first comprehensive analysis of the relationships between large‐scale patterns of Southern Hemisphere climate variability and the detailed structure of Antarctic precipitation. We examine linkages between the high spatial resolution precipitation from a regional atmospheric model and four patterns of large‐scale Southern Hemisphere climate variability: the southern baroclinic annular mode, the southern annular mode, and the two Pacific‐South American teleconnection patterns. Variations in all four patterns influence the spatial configuration of precipitation over Antarctica, consistent with their signatures in high‐latitude meridional moisture fluxes. They impact not only the mean but also the incidence of extreme precipitation events. Current coupled‐climate models are able to reproduce all four patterns of atmospheric variability but struggle to correctly replicate their regional impacts on Antarctic climate. Thus, linking these patterns directly to Antarctic precipitation variability may allow a better estimate of future changes in precipitation than using model output alone. PMID:29398735

Cholera and shigellosis in Bangladesh: similarities and differences in population dynamics under climate forcing

NASA Astrophysics Data System (ADS)

Pascual, M.; Cash, B.; Reiner, R.; King, A.; Emch, M.; Yunus, M.; Faruque, A. S.

2012-12-01

The influence of climate variability on the population dynamics of infectious diseases is considered a large scale, regional, phenomenon, and as such, has been previously addressed for cholera with temporal models that do not incorporate fine-scale spatial structure. In our previous work, evidence for a role of ENSO (El Niño Southern Oscillation) on cholera in Bangladesh was elucidated, and shown to influence the regional climate through precipitation. With a probabilistic spatial model for cholera dynamics in the megacity of Dhaka, we found that the action of climate variability (ENSO and flooding) is localized: there is a climate-sensitive urban core that acts to propagate risk to the rest of the city. Here, we consider long-term surveillance data for shigellosis, another diarrheal disease that coexists with cholera in Bangladesh. We compare the patterns of association with climate variables for these two diseases in a rural setting, as well as the spatial structure in their spatio-temporal dynamics in an urban one. Evidence for similar patterns is presented, and discussed in the context of the differences in the routes of transmission of the two diseases and the proposed role of an environmental reservoir in cholera. The similarities provide evidence for a more general influence of hydrology and of socio-economic factors underlying human susceptibility and sanitary conditions.

Impact of the hydrological cycle on past climate changes: three illustrations at different time scales

NASA Astrophysics Data System (ADS)

Ramstein, Gilles; Khodri, Myriam; Donnadieu, Yannick; Fluteau, Frédéric; Goddéris, Yves

2005-02-01

We investigate in the paper the impact of the hydrologic cycle on climate at different periods. The aim is to illustrate how the changes in moisture transport, precipitation pattern, and weathering may alter, at regional or global scales, the CO 2 and climate equilibriums. We choose three climate periods to pinpoint intricate relationships between water cycle and climate. The illustrations are the following. ( i) The onset of ice-sheet build-up, 115 kyr BP. We show that the increased thermal meridian gradient of SST allows large moisture advection over the North American continent and provides appropriate conditions for perennial snow on the Canadian Archipelago. ( ii) The onset of Indian Monsoon at the end of the Tertiary. We demonstrate that superimposed to the Tibetan Plateau, the shrinkage of the Tethys, since Oligocene, plays a major role to explain changes in the geographical pattern of the southeastern Asian Monsoon. ( iii) The onset of Global Glaciation (750 Ma). We show that the break-up of Rodinia occurring at low latitudes is an important feature to explain how the important precipitation increase leads to weathering and carbon burial, which contribute to decrease atmospheric CO 2 enough to produce a snows ball Earth. All these periods have been simulated with a hierarchy of models appropriate to quantify the water cycle impact on climate. To cite this article: G. Ramstein et al., C. R. Geoscience 337 (2005).

Climatic Redistribution of Canada's Water Resources (CROCWR): An analysis of spatial and temporal hydrological trends and patterns in western Canada

NASA Astrophysics Data System (ADS)

Bawden, A. J.; Burn, D. H.; Prowse, T. D.

2012-12-01

Climate variability and change can have profound impacts on the hydrologic regime of a watershed. These effects are likely to be especially severe in regions particularly sensitive to changes in climate, such as the Canadian north, or when there are other stresses on the hydrologic regime, such as may occur when there are large withdrawals from, or land-use changes within, a watershed. A recent report of the Intergovernmental Panel on Climate Change (IPCC) stressed that future climate is likely to accelerate the hydrologic cycle and hence may affect water security in certain locations. For some regions, this will mean enhanced access to water resources, but because the effects will not be spatially uniform, other regions will experience reduced access. Understanding these patterns is critical for water managers and government agencies in western Canada - an area of highly contrasting hydroclimatic regimes and overlapping water-use and jurisdictional borders - as adapting to climate change may require reconsideration of inter-regional transfers and revised allocation of water resources to competing industrial sectors, including agriculture, hydroelectric production, and oil and gas. This research involves the detection and examination of spatial and temporal streamflow trends in western Canadian rivers as a response to changing climatic factors, including temperature, precipitation, snowmelt, and the synoptic patterns controlling these drivers. The study area, known as the CROCWR region, extends from the Pacific coast of British Columbia as far east as the Saskatchewan-Manitoba border and from the Canada-United States international border through a large portion of the Northwest Territories. This analysis examines hydrologic trends in monthly and annual streamflow for a collection of 34 hydrometric gauging stations believed to adequately represent the overall effects of climate variability and change on flows in western Canada by means of the Mann-Kendall non-parametric trend test. Large-scale spatial patterns are determined through examination of trends and contrasts between upper and lower reaches of individual sub-basins, as well as via analysis of streamflow redistributions within the CROCWR region as an entirety (i.e. north, south, east and/or west-moving patterns). Results are used to predict future implications of hydroclimatic variability and change on western Canada's water resources and recommend measures to be taken by water managers in response to these changes. This research is part of a larger hydroclimatic study that includes an analysis of the climatic drivers contributing to shifting flow regimes in western Canada as well as a study of the controlling synoptic patterns and teleconnections associated with changes in these driving forces.

Response of Tropical Forests to Intense Climate Variability and Rainfall Anomaly over the Last Decade

NASA Astrophysics Data System (ADS)

Saatchi, S.; Asefi, S.

2012-04-01

During the last decade, strong precipitation anomalies resulted from increased sea surface temperature in the tropical Atlantic, have caused extensive drying trends in rainforests of western Amazonia, exerting water stress, tree mortality, biomass loss, and large-scale fire disturbance. In contrast, there have been no reports on large-scale disturbance in rainforests of west and central Africa, though being exposed to similar intensity of climate variability. Using data from Tropical Rainfall Mapping Mission (TRMM) (1999-2010), and time series of rainfall observations from meteorological stations (1971-2000), we show that both Amazonian and African rainforest experienced strong precipitation anomalies from 2005-2010. We monitored the response of forest to the climate variability by analyzing the canopy water content observed by SeaWinds Ku-band Scatterometer (QSCAT) (1999-2009) and found that more than 70 million ha of forests in western Amazonia experienced a strong water deficit during the dry season of 2005 and a closely corresponding decline in canopy backscatter that persisted until the next major drought in 2010. This decline in backscatter has been attributed to loss of canopy water content and large-scale tree mortality corroborated by ground and airborne observations. However, no strong impacts was observed on tropical forests of Africa, suggesting that the African rainforest may have more resilience to droughts. We tested this hypothesis by examining the seasonal rainfall patterns, maximum water deficit, and the surface temperature variations. Results show that there is a complex pattern of low annual rainfall, moderate seasonality, and lower surface temperature in Central Africa compared to Amazonia, indicating potentially a lower evapotranspiration circumventing strong water deficits

Response of Tropical Forests to Intense Climate Variability and Rainfall Anomaly of Last Decade

NASA Astrophysics Data System (ADS)

Saatchi, S. S.; Asefi Najafabady, S.

2011-12-01

During the last decade, strong precipitation anomalies resulted from increased sea surface temperature in the tropical Atlantic, have caused extensive drying trends in rainforests of western Amazonia, exerting water stress, tree mortality, biomass loss, and large-scale fire disturbance. In contrast, there have been no reports on large-scale disturbance in rainforests of west and central Africa, though being exposed to similar intensity of climate variability. Using data from Tropical Rainfall Mapping Mission (TRMM) (1999-2010), and time series of rainfall observations from meteorological stations (1971-2000), we show that both Amazonian and African rainforest experienced strong precipitation anomalies from 2005-2010. We monitored the response of forest to the climate variability by analyzing the canopy water content observed by SeaWinds Ku-band Scatterometer (QSCAT) (1999-2009) and found that more than 70 million ha of forests in western Amazonia experienced a strong water deficit during the dry season of 2005 and a closely corresponding decline in canopy backscatter that persisted until the next major drought in 2010. This decline in backscatter has been attributed to loss of canopy water content and large-scale tree mortality corroborated by ground and airborne observations. However, no strong impacts was observed on tropical forests of Africa, suggesting that the African rainforest may have more resilience to droughts. We tested this hypothesis by examining the seasonal rainfall patterns, maximum water deficit, and the surface temperature variations. Results show that there is a complex pattern of low annual rainfall, moderate seasonality, and lower surface temperature in Central Africa compared to Amazonia, indicating potentially a lower evapotranspiration circumventing strong water deficits.

Spatial Pattern of Standing Timber Value across the Brazilian Amazon

PubMed Central

Ahmed, Sadia E.; Ewers, Robert M.

2012-01-01

The Amazon is a globally important system, providing a host of ecosystem services from climate regulation to food sources. It is also home to a quarter of all global diversity. Large swathes of forest are removed each year, and many models have attempted to predict the spatial patterns of this forest loss. The spatial patterns of deforestation are determined largely by the patterns of roads that open access to frontier areas and expansion of the road network in the Amazon is largely determined by profit seeking logging activities. Here we present predictions for the spatial distribution of standing value of timber across the Amazon. We show that the patterns of timber value reflect large-scale ecological gradients, determining the spatial distribution of functional traits of trees which are, in turn, correlated with timber values. We expect that understanding the spatial patterns of timber value across the Amazon will aid predictions of logging movements and thus predictions of potential future road developments. These predictions in turn will be of great use in estimating the spatial patterns of deforestation in this globally important biome. PMID:22590520

Genome-environment association study suggests local adaptation to climate at the regional scale in Fagus sylvatica.

PubMed

Pluess, Andrea R; Frank, Aline; Heiri, Caroline; Lalagüe, Hadrien; Vendramin, Giovanni G; Oddou-Muratorio, Sylvie

2016-04-01

The evolutionary potential of long-lived species, such as forest trees, is fundamental for their local persistence under climate change (CC). Genome-environment association (GEA) analyses reveal if species in heterogeneous environments at the regional scale are under differential selection resulting in populations with potential preadaptation to CC within this area. In 79 natural Fagus sylvatica populations, neutral genetic patterns were characterized using 12 simple sequence repeat (SSR) markers, and genomic variation (144 single nucleotide polymorphisms (SNPs) out of 52 candidate genes) was related to 87 environmental predictors in the latent factor mixed model, logistic regressions and isolation by distance/environmental (IBD/IBE) tests. SSR diversity revealed relatedness at up to 150 m intertree distance but an absence of large-scale spatial genetic structure and IBE. In the GEA analyses, 16 SNPs in 10 genes responded to one or several environmental predictors and IBE, corrected for IBD, was confirmed. The GEA often reflected the proposed gene functions, including indications for adaptation to water availability and temperature. Genomic divergence and the lack of large-scale neutral genetic patterns suggest that gene flow allows the spread of advantageous alleles in adaptive genes. Thereby, adaptation processes are likely to take place in species occurring in heterogeneous environments, which might reduce their regional extinction risk under CC. © 2016 The Authors. New Phytologist © 2016 New Phytologist Trust.

A boundary current drives synchronous growth of marine fishes across tropical and temperate latitudes.

PubMed

Ong, Joyce J L; Rountrey, Adam N; Black, Bryan A; Nguyen, Hoang Minh; Coulson, Peter G; Newman, Stephen J; Wakefield, Corey B; Meeuwig, Jessica J; Meekan, Mark G

2018-05-01

Entrainment of growth patterns of multiple species to single climatic drivers can lower ecosystem resilience and increase the risk of species extinction during stressful climatic events. However, predictions of the effects of climate change on the productivity and dynamics of marine fishes are hampered by a lack of historical data on growth patterns. We use otolith biochronologies to show that the strength of a boundary current, modulated by the El Niño-Southern Oscillation, accounted for almost half of the shared variance in annual growth patterns of five of six species of tropical and temperate marine fishes across 23° of latitude (3000 km) in Western Australia. Stronger flow during La Niña years drove increased growth of five species, whereas weaker flow during El Niño years reduced growth. Our work is the first to link the growth patterns of multiple fishes with a single oceanographic/climate phenomenon at large spatial scales and across multiple climate zones, habitat types, trophic levels and depth ranges. Extreme La Niña and El Niño events are predicted to occur more frequently in the future and these are likely to have implications for these vulnerable ecosystems, such as a limited capacity of the marine taxa to recover from stressful climatic events. © 2018 John Wiley & Sons Ltd.

Hydrologic Impacts of Climate Change: Quantification of Uncertainties (Alexander von Humboldt Medal Lecture)

NASA Astrophysics Data System (ADS)

Mujumdar, Pradeep P.

2014-05-01

Climate change results in regional hydrologic change. The three prominent signals of global climate change, viz., increase in global average temperatures, rise in sea levels and change in precipitation patterns convert into signals of regional hydrologic change in terms of modifications in water availability, evaporative water demand, hydrologic extremes of floods and droughts, water quality, salinity intrusion in coastal aquifers, groundwater recharge and other related phenomena. A major research focus in hydrologic sciences in recent years has been assessment of impacts of climate change at regional scales. An important research issue addressed in this context deals with responses of water fluxes on a catchment scale to the global climatic change. A commonly adopted methodology for assessing the regional hydrologic impacts of climate change is to use the climate projections provided by the General Circulation Models (GCMs) for specified emission scenarios in conjunction with the process-based hydrologic models to generate the corresponding hydrologic projections. The scaling problem arising because of the large spatial scales at which the GCMs operate compared to those required in distributed hydrologic models, and their inability to satisfactorily simulate the variables of interest to hydrology are addressed by downscaling the GCM simulations to hydrologic scales. Projections obtained with this procedure are burdened with a large uncertainty introduced by the choice of GCMs and emission scenarios, small samples of historical data against which the models are calibrated, downscaling methods used and other sources. Development of methodologies to quantify and reduce such uncertainties is a current area of research in hydrology. In this presentation, an overview of recent research carried out by the author's group on assessment of hydrologic impacts of climate change addressing scale issues and quantification of uncertainties is provided. Methodologies developed with conditional random fields, Dempster-Shafer theory, possibility theory, imprecise probabilities and non-stationary extreme value theory are discussed. Specific applications on uncertainty quantification in impacts on streamflows, evaporative water demands, river water quality and urban flooding are presented. A brief discussion on detection and attribution of hydrologic change at river basin scales, contribution of landuse change and likely alterations in return levels of hydrologic extremes is also provided.

Cloudy Windows: What GCM Ensembles, Reanalyses and Observations Tell Us About Uncertainty in Greenland's Future Climate and Surface Melting

NASA Astrophysics Data System (ADS)

Reusch, D. B.

2016-12-01

Any analysis that wants to use a GCM-based scenario of future climate benefits from knowing how much uncertainty the GCM's inherent variability adds to the development of climate change predictions. This is extra relevant in the polar regions due to the potential of global impacts (e.g., sea level rise) from local (ice sheet) climate changes such as more frequent/intense surface melting. High-resolution, regional-scale models using GCMs for boundary/initial conditions in future scenarios inherit a measure of GCM-derived externally-driven uncertainty. We investigate these uncertainties for the Greenland ice sheet using the 30-member CESM1.0-CAM5-BGC Large Ensemble (CESMLE) for recent (1981-2000) and future (2081-2100, RCP 8.5) decades. Recent simulations are skill-tested against the ERA-Interim reanalysis and AWS observations with results informing future scenarios. We focus on key variables influencing surface melting through decadal climatologies, nonlinear analysis of variability with self-organizing maps (SOMs), regional-scale modeling (Polar WRF), and simple melt models. Relative to the ensemble average, spatially averaged climatological July temperature anomalies over a Greenland ice-sheet/ocean domain are mostly between +/- 0.2 °C. The spatial average hides larger local anomalies of up to +/- 2 °C. The ensemble average itself is 2 °C cooler than ERA-Interim. SOMs extend our diagnostics by providing a concise, objective summary of model variability as a set of generalized patterns. For CESMLE, the SOM patterns summarize the variability of multiple realizations of climate. Changes in pattern frequency by ensemble member show the influence of initial conditions. For example, basic statistical analysis of pattern frequency yields interquartile ranges of 2-4% for individual patterns across the ensemble. In climate terms, this tells us about climate state variability through the range of the ensemble, a potentially significant source of melt-prediction uncertainty. SOMs can also capture the different trajectories of climate due to intramodel variability over time. Polar WRF provides higher resolution regional modeling with improved, polar-centric model physics. Simple melt models allow us to characterize impacts of the upstream uncertainties on estimates of surface melting.

Mapping spatial patterns of denitrifiers at large scales (Invited)

NASA Astrophysics Data System (ADS)

Philippot, L.; Ramette, A.; Saby, N.; Bru, D.; Dequiedt, S.; Ranjard, L.; Jolivet, C.; Arrouays, D.

2010-12-01

Little information is available regarding the landscape-scale distribution of microbial communities and its environmental determinants. Here we combined molecular approaches and geostatistical modeling to explore spatial patterns of the denitrifying community at large scales. The distribution of denitrifrying community was investigated over 107 sites in Burgundy, a 31 500 km2 region of France, using a 16 X 16 km sampling grid. At each sampling site, the abundances of denitrifiers and 42 soil physico-chemical properties were measured. The relative contributions of land use, spatial distance, climatic conditions, time and soil physico-chemical properties to the denitrifier spatial distribution were analyzed by canonical variation partitioning. Our results indicate that 43% to 85% of the spatial variation in community abundances could be explained by the measured environmental parameters, with soil chemical properties (mostly pH) being the main driver. We found spatial autocorrelation up to 739 km and used geostatistical modelling to generate predictive maps of the distribution of denitrifiers at the landscape scale. Studying the distribution of the denitrifiers at large scale can help closing the artificial gap between the investigation of microbial processes and microbial community ecology, therefore facilitating our understanding of the relationships between the ecology of denitrifiers and N-fluxes by denitrification.

Population signatures of large-scale, long-term disjunction and small-scale, short-term habitat fragmentation in an Afromontane forest bird

PubMed Central

Habel, J C; Mulwa, R K; Gassert, F; Rödder, D; Ulrich, W; Borghesio, L; Husemann, M; Lens, L

2014-01-01

The Eastern Afromontane cloud forests occur as geographically distinct mountain exclaves. The conditions of these forests range from large to small and from fairly intact to strongly degraded. For this study, we sampled individuals of the forest bird species, the Montane White-eye Zosterops poliogaster from 16 sites and four mountain archipelagos. We analysed 12 polymorphic microsatellites and three phenotypic traits, and calculated Species Distribution Models (SDMs) to project past distributions and predict potential future range shifts under a scenario of climate warming. We found well-supported genetic and morphologic clusters corresponding to the mountain ranges where populations were sampled, with 43% of all alleles being restricted to single mountains. Our data suggest that large-scale and long-term geographic isolation on mountain islands caused genetically and morphologically distinct population clusters in Z. poliogaster. However, major genetic and biometric splits were not correlated to the geographic distances among populations. This heterogeneous pattern can be explained by past climatic shifts, as highlighted by our SDM projections. Anthropogenically fragmented populations showed lower genetic diversity and a lower mean body mass, possibly in response to suboptimal habitat conditions. On the basis of these findings and the results from our SDM analysis we predict further loss of genotypic and phenotypic uniqueness in the wake of climate change, due to the contraction of the species' climatic niche and subsequent decline in population size. PMID:24713824

Population signatures of large-scale, long-term disjunction and small-scale, short-term habitat fragmentation in an Afromontane forest bird.

PubMed

Habel, J C; Mulwa, R K; Gassert, F; Rödder, D; Ulrich, W; Borghesio, L; Husemann, M; Lens, L

2014-09-01

The Eastern Afromontane cloud forests occur as geographically distinct mountain exclaves. The conditions of these forests range from large to small and from fairly intact to strongly degraded. For this study, we sampled individuals of the forest bird species, the Montane White-eye Zosterops poliogaster from 16 sites and four mountain archipelagos. We analysed 12 polymorphic microsatellites and three phenotypic traits, and calculated Species Distribution Models (SDMs) to project past distributions and predict potential future range shifts under a scenario of climate warming. We found well-supported genetic and morphologic clusters corresponding to the mountain ranges where populations were sampled, with 43% of all alleles being restricted to single mountains. Our data suggest that large-scale and long-term geographic isolation on mountain islands caused genetically and morphologically distinct population clusters in Z. poliogaster. However, major genetic and biometric splits were not correlated to the geographic distances among populations. This heterogeneous pattern can be explained by past climatic shifts, as highlighted by our SDM projections. Anthropogenically fragmented populations showed lower genetic diversity and a lower mean body mass, possibly in response to suboptimal habitat conditions. On the basis of these findings and the results from our SDM analysis we predict further loss of genotypic and phenotypic uniqueness in the wake of climate change, due to the contraction of the species' climatic niche and subsequent decline in population size.

Prediction of monthly rainfall on homogeneous monsoon regions of India based on large scale circulation patterns using Genetic Programming

NASA Astrophysics Data System (ADS)

Kashid, Satishkumar S.; Maity, Rajib

2012-08-01

SummaryPrediction of Indian Summer Monsoon Rainfall (ISMR) is of vital importance for Indian economy, and it has been remained a great challenge for hydro-meteorologists due to inherent complexities in the climatic systems. The Large-scale atmospheric circulation patterns from tropical Pacific Ocean (ENSO) and those from tropical Indian Ocean (EQUINOO) are established to influence the Indian Summer Monsoon Rainfall. The information of these two large scale atmospheric circulation patterns in terms of their indices is used to model the complex relationship between Indian Summer Monsoon Rainfall and the ENSO as well as EQUINOO indices. However, extracting the signal from such large-scale indices for modeling such complex systems is significantly difficult. Rainfall predictions have been done for 'All India' as one unit, as well as for five 'homogeneous monsoon regions of India', defined by Indian Institute of Tropical Meteorology. Recent 'Artificial Intelligence' tool 'Genetic Programming' (GP) has been employed for modeling such problem. The Genetic Programming approach is found to capture the complex relationship between the monthly Indian Summer Monsoon Rainfall and large scale atmospheric circulation pattern indices - ENSO and EQUINOO. Research findings of this study indicate that GP-derived monthly rainfall forecasting models, that use large-scale atmospheric circulation information are successful in prediction of All India Summer Monsoon Rainfall with correlation coefficient as good as 0.866, which may appears attractive for such a complex system. A separate analysis is carried out for All India Summer Monsoon rainfall for India as one unit, and five homogeneous monsoon regions, based on ENSO and EQUINOO indices of months of March, April and May only, performed at end of month of May. In this case, All India Summer Monsoon Rainfall could be predicted with 0.70 as correlation coefficient with somewhat lesser Correlation Coefficient (C.C.) values for different 'homogeneous monsoon regions'.

Application of hierarchical clustering method to classify of space-time rainfall patterns

NASA Astrophysics Data System (ADS)

Yu, Hwa-Lung; Chang, Tu-Je

2010-05-01

Understanding the local precipitation patterns is essential to the water resources management and flooding mitigation. The precipitation patterns can vary in space and time depending upon the factors from different spatial scales such as local topological changes and macroscopic atmospheric circulation. The spatiotemporal variation of precipitation in Taiwan is significant due to its complex terrain and its location at west pacific and subtropical area, where is the boundary between the pacific ocean and Asia continent with the complex interactions among the climatic processes. This study characterizes local-scale precipitation patterns by classifying the historical space-time precipitation records. We applied the hierarchical ascending clustering method to analyze the precipitation records from 1960 to 2008 at the six rainfall stations located in Lan-yang catchment at the northeast of the island. Our results identify the four primary space-time precipitation types which may result from distinct driving forces from the changes of atmospheric variables and topology at different space-time scales. This study also presents an important application of the statistical downscaling to combine large-scale upper-air circulation with local space-time precipitation patterns.

Climate anomalies generate an exceptional dinoflagellate bloom in San Francisco Bay

USGS Publications Warehouse

Cloern, J.E.; Schraga, T.S.; Lopez, C.B.; Knowles, N.; Grover, Labiosa R.; Dugdale, R.

2005-01-01

We describe a large dinoflagellate bloom, unprecedented in nearly three decades of observation, that developed in San Francisco Bay (SFB) during September 2004. SFB is highly enriched in nutrients but has low summer-autumn algal biomass because wind stress and tidally induced bottom stress produce a well mixed and light-limited pelagic habitat. The bloom coincided with calm winds and record high air temperatures that stratified the water column and suppressed mixing long enough for motile dinoflagellates to grow and accumulate in surface waters. This event-scale climate pattern, produced by an upper-atmosphere high-pressure anomaly off the U.S. west coast, followed a summer of weak coastal upwelling and high dinoflagellate biomass in coastal waters that apparently seeded the SFB bloom. This event suggests that some red tides are responses to changes in local physical dynamics that are driven by large-scale atmospheric processes and operate over both the event scale of biomass growth and the antecedent seasonal scale that shapes the bloom community. Copyright 2005 by the American Geophysical Union.

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

Climate responses to anthropogenic emissions of short-lived climate pollutants

NASA Astrophysics Data System (ADS)

Baker, L. H.; Collins, W. J.; Olivié, D. J. L.; Cherian, R.; Hodnebrog, Ø.; Myhre, G.; Quaas, J.

2015-07-01

Policies to control air quality focus on mitigating emissions of aerosols and their precursors, and other short-lived climate pollutants (SLCPs). On a local scale, these policies will have beneficial impacts on health and crop yields, by reducing particulate matter (PM) and surface ozone concentrations; however, the climate impacts of reducing emissions of SLCPs are less straightforward to predict. In this paper we consider a set of idealized, extreme mitigation strategies, in which the total anthropogenic emissions of individual SLCP emissions species are removed. This provides an upper bound on the potential climate impacts of such air quality strategies. We focus on evaluating the climate responses to changes in anthropogenic emissions of aerosol precursor species: black carbon (BC), organic carbon (OC) and sulphur dioxide (SO2). We perform climate integrations with four fully coupled atmosphere-ocean global climate models (AOGCMs), and examine the effects on global and regional climate of removing the total land-based anthropogenic emissions of each of the three aerosol precursor species. We find that the SO2 emissions reductions lead to the strongest response, with all models showing an increase in surface temperature focussed in the Northern Hemisphere mid and (especially) high latitudes, and showing a corresponding increase in global mean precipitation. Changes in precipitation patterns are driven mostly by a northward shift in the ITCZ (Intertropical Convergence Zone), consistent with the hemispherically asymmetric warming pattern driven by the emissions changes. The BC and OC emissions reductions give a much weaker response, and there is some disagreement between models in the sign of the climate responses to these perturbations. These differences between models are due largely to natural variability in sea-ice extent, circulation patterns and cloud changes. This large natural variability component to the signal when the ocean circulation and sea-ice are free-running means that the BC and OC mitigation measures do not necessarily lead to a discernible climate response.

Climate responses to anthropogenic emissions of short-lived climate pollutants

NASA Astrophysics Data System (ADS)

Baker, L. H.; Collins, W. J.; Olivié, D. J. L.; Cherian, R.; Hodnebrog, Ø.; Myhre, G.; Quaas, J.; Samset, B. H.

2015-02-01

Policies to control air quality focus on mitigating emissions of aerosols and their precursors, and other short-lived climate pollutants (SLCPs). On a local scale, these policies will have beneficial impacts on health and crop yields, by reducing particulate matter (PM) and surface ozone concentrations; however, the climate impacts of reducing emissions of SLCPs are less straightforward to predict. In this paper we consider a set of idealised, extreme mitigation strategies, in which the total anthropogenic emissions of individual SLCP emissions species are removed. This provides an upper bound on the potential climate impacts of such air quality strategies. We focus on evaluating the climate responses to changes in anthropogenic emissions of aerosol precursor species: black carbon (BC), organic carbon (OC) and sulphur dioxide (SO2). We perform climate integrations with four fully coupled atmosphere-ocean global climate models (AOGCMs), and examine the effects on global and regional climate of removing the total land-based anthropogenic emissions of each of the three aerosol precursor species. We find that the SO2 emissions reductions lead to the strongest response, with all three models showing an increase in surface temperature focussed in the northern hemisphere high latitudes, and a corresponding increase in global mean precipitation and run-off. Changes in precipitation and run-off patterns are driven mostly by a northward shift in the ITCZ, consistent with the hemispherically asymmetric warming pattern driven by the emissions changes. The BC and OC emissions reductions give a much weaker forcing signal, and there is some disagreement between models in the sign of the climate responses to these perturbations. These differences between models are due largely to natural variability in sea-ice extent, circulation patterns and cloud changes. This large natural variability component to the signal when the ocean circulation and sea-ice are free-running means that the BC and OC mitigation measures do not necessarily lead to a discernible climate response.

Basin-scale heterogeneity in Antarctic precipitation and its impact on surface mass variability

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

Fyke, Jeremy; Lenaerts, Jan T. M.; Wang, Hailong

Annually averaged precipitation in the form of snow, the dominant term of the Antarctic Ice Sheet surface mass balance, displays large spatial and temporal variability. Here we present an analysis of spatial patterns of regional Antarctic precipitation variability and their impact on integrated Antarctic surface mass balance variability simulated as part of a preindustrial 1800-year global, fully coupled Community Earth System Model simulation. Correlation and composite analyses based on this output allow for a robust exploration of Antarctic precipitation variability. We identify statistically significant relationships between precipitation patterns across Antarctica that are corroborated by climate reanalyses, regional modeling and icemore » core records. These patterns are driven by variability in large-scale atmospheric moisture transport, which itself is characterized by decadal- to centennial-scale oscillations around the long-term mean. We suggest that this heterogeneity in Antarctic precipitation variability has a dampening effect on overall Antarctic surface mass balance variability, with implications for regulation of Antarctic-sourced sea level variability, detection of an emergent anthropogenic signal in Antarctic mass trends and identification of Antarctic mass loss accelerations.« less

Basin-scale heterogeneity in Antarctic precipitation and its impact on surface mass variability

DOE PAGES

Fyke, Jeremy; Lenaerts, Jan T. M.; Wang, Hailong

2017-11-15

Annually averaged precipitation in the form of snow, the dominant term of the Antarctic Ice Sheet surface mass balance, displays large spatial and temporal variability. Here we present an analysis of spatial patterns of regional Antarctic precipitation variability and their impact on integrated Antarctic surface mass balance variability simulated as part of a preindustrial 1800-year global, fully coupled Community Earth System Model simulation. Correlation and composite analyses based on this output allow for a robust exploration of Antarctic precipitation variability. We identify statistically significant relationships between precipitation patterns across Antarctica that are corroborated by climate reanalyses, regional modeling and icemore » core records. These patterns are driven by variability in large-scale atmospheric moisture transport, which itself is characterized by decadal- to centennial-scale oscillations around the long-term mean. We suggest that this heterogeneity in Antarctic precipitation variability has a dampening effect on overall Antarctic surface mass balance variability, with implications for regulation of Antarctic-sourced sea level variability, detection of an emergent anthropogenic signal in Antarctic mass trends and identification of Antarctic mass loss accelerations.« less

Objective Use of Climate Indices to Inform Ensemble Streamflow Forecasts in the Columbia River Basin - An Initial Review

NASA Astrophysics Data System (ADS)

Pytlak, E.; McManamon, A.; Hughes, S. P.; Van Der Zweep, R. A.; Butcher, P.; Karafotias, C.; Beckers, J.; Welles, E.

2016-12-01

Numerous studies have documented the impacts that large scale weather patterns and climate phenomenon like the El Niño Southern Oscillation (ENSO), Pacific-North American (PNA) Pattern, and others can have on seasonal temperature and precipitation in the Columbia River Basin (CRB). While far from perfect in terms of seasonal predictability in specific locations, these intra-annual weather and climate signal do tilt the odds toward different temperature and precipitation outcomes, which in turn can have impacts on seasonal snowpacks, streamflows and water supply in large river basins like the CRB. We hypothesize that intraseasonal climate signals and long wave jet stream patterns can be objectively incorporated into what it is otherwise a climatology-based set of Ensemble Streamflow Forecasts, and can increase the predictive skill and utility of these forecasts used for mid-range hydropower planning. The Bonneville Power Administration (BPA) and Deltares have developed a subsampling-resampling method to incorporate climate mode information into the Ensemble Streamflow Prediction (ESP) forecasts (Beckers, et al., 2016). Since 2015, BPA and Deltares USA have experimented with this method in pre-operational use, using five objective multivariate climate indices that appear to have the greatest predictive value for seasonal temperature and precipitation in the CRB. The indices are used to objectively select historical weather from about twenty analog years in the 66-year (1949-2015) historical ESP set. These twenty scenarios then serve as the starting point to generate monthly synthetic weather and streamflow time series to return to a set of 66 streamflow traces. Our poster will share initial results from the 2015 and 2016 water years, which included large swings in the Quasi-Biennial Oscillation, persistent blocking jet stream patterns, and the development of a strong El Niño event. While the results are very preliminary and for only two seasons, there may be some value in incorporating objectively-identified climate signals into ESP-based streamflow forecasts.Beckers, J. V. L., Weerts, A. H., Tijdeman, E., and Welles, E.: ENSO-Conditioned Weather Resampling Method for Seasonal Ensemble Streamflow Prediction, Hydrol. Earth Syst. Sci. Discuss., doi:10.5194/hess-2016-72, in review, 2016.

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.

Climate and soil texture influence patterns of forb species richness and composition in big sagebrush plant communities across their spatial extent in the western US

USGS Publications Warehouse

Pennington, Victoria E.; Palmquist, Kyle A.; Bradford, John B.; Lauenroth, William K.

2017-01-01

Article for outlet: Plant Ecology. Abstract: Big sagebrush (Artemisia tridentata Nutt.) plant communities are widespread non-forested drylands in western North American and similar to all shrub steppe ecosystems world-wide are composed of a shrub overstory layer and a forb and graminoid understory layer. Forbs account for the majority of plant species diversity in big sagebrush plant communities and are important for ecosystem function. Few studies have explored the geographic patterns of forb species richness and composition and their relationships with environmental variables in these communities. Our objectives were to examine the small and large-scale spatial patterns in forb species richness and composition and the influence of environmental variables. We sampled forb species richness and composition along transects at 15 field sites in Colorado, Idaho, Montana, Nevada, Oregon, Utah, and Wyoming, built species-area relationships to quantify differences in forb species richness at sites, and used Principal Components Analysis and nonmetric multidimensional scaling to identify relationships among environmental variables and forb species richness and composition. We found that species richness was most strongly correlated with soil texture, while species composition was most related to climate. The combination of climate and soil texture influences water availability, with important consequences for forb species richness and composition, which suggests climate-change induced modification of soil water availability may have important implications for plant species diversity in the future. Our paper is the first to our knowledge to examine forb biodiversity patterns in big sagebrush ecosystems in relation to environmental factors across the big sagebrush region.

Ecosystem heterogeneity determines the ecological resilience of the Amazon to climate change

PubMed Central

Longo, Marcos; Baccini, Alessandro; Phillips, Oliver L.; Lewis, Simon L.; Alvarez-Dávila, Esteban; Segalin de Andrade, Ana Cristina; Brienen, Roel J. W.; Erwin, Terry L.; Feldpausch, Ted R.; Monteagudo Mendoza, Abel Lorenzo; Nuñez Vargas, Percy; Prieto, Adriana; Silva-Espejo, Javier Eduardo; Malhi, Yadvinder; Moorcroft, Paul R.

2016-01-01

Amazon forests, which store ∼50% of tropical forest carbon and play a vital role in global water, energy, and carbon cycling, are predicted to experience both longer and more intense dry seasons by the end of the 21st century. However, the climate sensitivity of this ecosystem remains uncertain: several studies have predicted large-scale die-back of the Amazon, whereas several more recent studies predict that the biome will remain largely intact. Combining remote-sensing and ground-based observations with a size- and age-structured terrestrial ecosystem model, we explore the sensitivity and ecological resilience of these forests to changes in climate. We demonstrate that water stress operating at the scale of individual plants, combined with spatial variation in soil texture, explains observed patterns of variation in ecosystem biomass, composition, and dynamics across the region, and strongly influences the ecosystem’s resilience to changes in dry season length. Specifically, our analysis suggests that in contrast to existing predictions of either stability or catastrophic biomass loss, the Amazon forest’s response to a drying regional climate is likely to be an immediate, graded, heterogeneous transition from high-biomass moist forests to transitional dry forests and woody savannah-like states. Fire, logging, and other anthropogenic disturbances may, however, exacerbate these climate change-induced ecosystem transitions. PMID:26711984

Ecosystem heterogeneity determines the ecological resilience of the Amazon to climate change.

PubMed

Levine, Naomi M; Zhang, Ke; Longo, Marcos; Baccini, Alessandro; Phillips, Oliver L; Lewis, Simon L; Alvarez-Dávila, Esteban; Segalin de Andrade, Ana Cristina; Brienen, Roel J W; Erwin, Terry L; Feldpausch, Ted R; Monteagudo Mendoza, Abel Lorenzo; Nuñez Vargas, Percy; Prieto, Adriana; Silva-Espejo, Javier Eduardo; Malhi, Yadvinder; Moorcroft, Paul R

2016-01-19

Amazon forests, which store ∼ 50% of tropical forest carbon and play a vital role in global water, energy, and carbon cycling, are predicted to experience both longer and more intense dry seasons by the end of the 21st century. However, the climate sensitivity of this ecosystem remains uncertain: several studies have predicted large-scale die-back of the Amazon, whereas several more recent studies predict that the biome will remain largely intact. Combining remote-sensing and ground-based observations with a size- and age-structured terrestrial ecosystem model, we explore the sensitivity and ecological resilience of these forests to changes in climate. We demonstrate that water stress operating at the scale of individual plants, combined with spatial variation in soil texture, explains observed patterns of variation in ecosystem biomass, composition, and dynamics across the region, and strongly influences the ecosystem's resilience to changes in dry season length. Specifically, our analysis suggests that in contrast to existing predictions of either stability or catastrophic biomass loss, the Amazon forest's response to a drying regional climate is likely to be an immediate, graded, heterogeneous transition from high-biomass moist forests to transitional dry forests and woody savannah-like states. Fire, logging, and other anthropogenic disturbances may, however, exacerbate these climate change-induced ecosystem transitions.

Historical drought patterns over Canada and their teleconnections with large-scale climate signals

NASA Astrophysics Data System (ADS)

Asong, Zilefac Elvis; Wheater, Howard Simon; Bonsal, Barrie; Razavi, Saman; Kurkute, Sopan

2018-06-01

Drought is a recurring extreme climate event and among the most costly natural disasters in the world. This is particularly true over Canada, where drought is both a frequent and damaging phenomenon with impacts on regional water resources, agriculture, industry, aquatic ecosystems, and health. However, nationwide drought assessments are currently lacking and impacted by limited ground-based observations. This study provides a comprehensive analysis of historical droughts over the whole of Canada, including the role of large-scale teleconnections. Drought events are characterized by the Standardized Precipitation Evapotranspiration Index (SPEI) over various temporal scales (1, 3, 6, and 12 consecutive months, 6 months from April to September, and 12 months from October to September) applied to different gridded monthly data sets for the period 1950-2013. The Mann-Kendall test, rotated empirical orthogonal function, continuous wavelet transform, and wavelet coherence analyses are used, respectively, to investigate the trend, spatio-temporal patterns, periodicity, and teleconnectivity of drought events. Results indicate that southern (northern) parts of the country experienced significant trends towards drier (wetter) conditions although substantial variability exists. Two spatially well-defined regions with different temporal evolution of droughts were identified - the Canadian Prairies and northern central Canada. The analyses also revealed the presence of a dominant periodicity of between 8 and 32 months in the Prairie region and between 8 and 40 months in the northern central region. These cycles of low-frequency variability are found to be associated principally with the Pacific-North American (PNA) and Multivariate El Niño/Southern Oscillation Index (MEI) relative to other considered large-scale climate indices. This study is the first of its kind to identify dominant periodicities in drought variability over the whole of Canada in terms of when the drought events occur, their duration, and how often they occur.

CLIMATE VARIABILITY, LAND OWNERSHIP AND MIGRATION: EVIDENCE FROM THAILAND ABOUT GENDER IMPACTS

PubMed Central

Curran, Sara R.; Meijer-Irons, Jacqueline

2016-01-01

Scholars point to climate change, often in the form of more frequent and severe drought, as a potential driver of migration in the developing world, particularly for places where populations rely on agriculture for their livelihoods. To date, however, there have been few large-scale, longitudinal studies that explore the relationship between climate change and migration. This study significantly extends current scholarship by evaluating distinctive effects of climatic variation and models these effects on men’s and women’s responsiveness to drought and rainfall. Our study also investigates how land ownership moderates these effects. We find small, but significant, increases in migration above existing migratory levels during periods of prolonged climatic stress, and that these patterns differ both by gender and land tenure. PMID:27547492

Global patterns of foliar nitrogen isotopes and their relationships with climate, mycorrhizal fungi, foliar nutrient concentrations, and nitrogen availability

Treesearch

Joseph M. Craine; Andrew J. Elmore; Marcos P. M. Aidar; Mercedes Bustamante; Todd E. Dawson; Erik A. Hobbie; Ansgar Kahmen; Michelle C. Mack; Kendra K. McLauchlan; Anders Michelsen; Gabriela Nardoto; Linda H. Pardo; Josep Penuelas; Peter B. Reich; Edward A.G. Schuur; William D. Stock; Pamela H. Templer; Ross A. Virginia; Jeffrey M. Welker; Ian J. Wright

2009-01-01

Ratios of nitrogen (N) isotopes in leaves could elucidate underlying patterns of N cycling across ecological gradients. To better understand global-scale patterns of N cycling, we compiled data on foliar N isotope ratios, foliar N concentrations, mycorrhizal type and climate for over 11 000 plants worldwide. Global-scale comparisons of other components of the N cycle...

Evaluating sub-seasonal skill in probabilistic forecasts of Atmospheric Rivers and associated extreme events

NASA Astrophysics Data System (ADS)

Subramanian, A. C.; Lavers, D.; Matsueda, M.; Shukla, S.; Cayan, D. R.; Ralph, M.

2017-12-01

Atmospheric rivers (ARs) - elongated plumes of intense moisture transport - are a primary source of hydrological extremes, water resources and impactful weather along the West Coast of North America and Europe. There is strong demand in the water management, societal infrastructure and humanitarian sectors for reliable sub-seasonal forecasts, particularly of extreme events, such as floods and droughts so that actions to mitigate disastrous impacts can be taken with sufficient lead-time. Many recent studies have shown that ARs in the Pacific and the Atlantic are modulated by large-scale modes of climate variability. Leveraging the improved understanding of how these large-scale climate modes modulate the ARs in these two basins, we use the state-of-the-art multi-model forecast systems such as the North American Multi-Model Ensemble (NMME) and the Subseasonal-to-Seasonal (S2S) database to help inform and assess the probabilistic prediction of ARs and related extreme weather events over the North American and European West Coasts. We will present results from evaluating probabilistic forecasts of extreme precipitation and AR activity at the sub-seasonal scale. In particular, results from the comparison of two winters (2015-16 and 2016-17) will be shown, winters which defied canonical El Niño teleconnection patterns over North America and Europe. We further extend this study to analyze probabilistic forecast skill of AR events in these two basins and the variability in forecast skill during certain regimes of large-scale climate modes.

Climate change alters diffusion of forest pest: A model study

NASA Astrophysics Data System (ADS)

Jo, Woo Seong; Kim, Hwang-Yong; Kim, Beom Jun

2017-01-01

Population dynamics with spatial information is applied to understand the spread of pests. We introduce a model describing how pests spread in discrete space. The number of pest descendants at each site is controlled by local information such as temperature, precipitation, and the density of pine trees. Our simulation leads to a pest spreading pattern comparable to the real data for pine needle gall midge in the past. We also simulate the model in two different climate conditions based on two different representative concentration pathways scenarios for the future. We observe that after an initial stage of a slow spread of pests, a sudden change in the spreading speed occurs, which is soon followed by a large-scale outbreak. We found that a future climate change causes the outbreak point to occur earlier and that the detailed spatio-temporal pattern of the spread depends on the source position from which the initial pest infection starts.

Large-Scale Patterns of Forest Fire Occurrence in the Conterminous United States and Alaska, 2010

Treesearch

Kevin M. Potter

2013-01-01

Free-burning fire has been a constant ecological presence on the American landscape, the expression of which has changed as new climates, peoples and land uses have become predominant (Pyne 2010). It is an important ecological mechanism that shapes the distributions of species, maintains the structure and function of fire-prone communities, and is a significant...

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.

Hurricane Activity and the Large-Scale Pattern of Spread of an Invasive Plant Species

PubMed Central

Bhattarai, Ganesh P.; Cronin, James T.

2014-01-01

Disturbances are a primary facilitator of the growth and spread of invasive species. However, the effects of large-scale disturbances, such as hurricanes and tropical storms, on the broad geographic patterns of invasive species growth and spread have not been investigated. We used historical aerial imagery to determine the growth rate of invasive Phragmites australis patches in wetlands along the Atlantic and Gulf Coasts of the United States. These were relatively undisturbed wetlands where P. australis had room for unrestricted growth. Over the past several decades, invasive P. australis stands expanded in size by 6–35% per year. Based on tropical storm and hurricane activity over that same time period, we found that the frequency of hurricane-force winds explained 81% of the variation in P. australis growth over this broad geographic range. The expansion of P. australis stands was strongly and positively correlated with hurricane frequency. In light of the many climatic models that predict an increase in the frequency and intensity of hurricanes over the next century, these results suggest a strong link between climate change and species invasion and a challenging future ahead for the management of invasive species. PMID:24878928

North Atlantic climate variability: The role of the North Atlantic Oscillation

NASA Astrophysics Data System (ADS)

Hurrell, James W.; Deser, Clara

2009-08-01

Marine ecosystems are undergoing rapid change at local and global scales. To understand these changes, including the relative roles of natural variability and anthropogenic effects, and to predict the future state of marine ecosystems requires quantitative understanding of the physics, biogeochemistry and ecology of oceanic systems at mechanistic levels. Central to this understanding is the role played by dominant patterns or "modes" of atmospheric and oceanic variability, which orchestrate coherent variations in climate over large regions with profound impacts on ecosystems. We review the spatial structure of extratropical climate variability over the Northern Hemisphere and, specifically, focus on modes of climate variability over the extratropical North Atlantic. A leading pattern of weather and climate variability over the Northern Hemisphere is the North Atlantic Oscillation (NAO). The NAO refers to a redistribution of atmospheric mass between the Arctic and the subtropical Atlantic, and swings from one phase to another producing large changes in surface air temperature, winds, storminess and precipitation over the Atlantic as well as the adjacent continents. The NAO also affects the ocean through changes in heat content, gyre circulations, mixed layer depth, salinity, high latitude deep water formation and sea ice cover. Thus, indices of the NAO have become widely used to document and understand how this mode of variability alters the structure and functioning of marine ecosystems. There is no unique way, however, to define the NAO. Several approaches are discussed including both linear (e.g., principal component analysis) and nonlinear (e.g., cluster analysis) techniques. The former, which have been most widely used, assume preferred atmospheric circulation states come in pairs, in which anomalies of opposite polarity have the same spatial structure. In contrast, nonlinear techniques search for recurrent patterns of a specific amplitude and sign. They reveal, for instance, spatial asymmetries between different phases of the NAO that are likely important for ecological studies. It also follows that there is no universally accepted index to describe the temporal evolution of the NAO. Several of the most common measures are presented and compared. All reveal that there is no preferred time scale of variability for the NAO: large changes occur from one winter to the next and from one decade to the next. There is also a large amount of within-season variability in the patterns of atmospheric circulation of the North Atlantic, so that most winters cannot be characterized solely by a canonical NAO structure. A better understanding of how the NAO responds to external forcing, including sea surface temperature changes in the tropics, stratospheric influences, and increasing greenhouse gas concentrations, is crucial to the current debate on climate variability and change.

North Atlantic climate variability: The role of the North Atlantic Oscillation

NASA Astrophysics Data System (ADS)

Hurrell, James W.; Deser, Clara

2010-02-01

Marine ecosystems are undergoing rapid change at local and global scales. To understand these changes, including the relative roles of natural variability and anthropogenic effects, and to predict the future state of marine ecosystems requires quantitative understanding of the physics, biogeochemistry and ecology of oceanic systems at mechanistic levels. Central to this understanding is the role played by dominant patterns or "modes" of atmospheric and oceanic variability, which orchestrate coherent variations in climate over large regions with profound impacts on ecosystems. We review the spatial structure of extratropical climate variability over the Northern Hemisphere and, specifically, focus on modes of climate variability over the extratropical North Atlantic. A leading pattern of weather and climate variability over the Northern Hemisphere is the North Atlantic Oscillation (NAO). The NAO refers to a redistribution of atmospheric mass between the Arctic and the subtropical Atlantic, and swings from one phase to another producing large changes in surface air temperature, winds, storminess and precipitation over the Atlantic as well as the adjacent continents. The NAO also affects the ocean through changes in heat content, gyre circulations, mixed layer depth, salinity, high latitude deep water formation and sea ice cover. Thus, indices of the NAO have become widely used to document and understand how this mode of variability alters the structure and functioning of marine ecosystems. There is no unique way, however, to define the NAO. Several approaches are discussed including both linear (e.g., principal component analysis) and nonlinear (e.g., cluster analysis) techniques. The former, which have been most widely used, assume preferred atmospheric circulation states come in pairs, in which anomalies of opposite polarity have the same spatial structure. In contrast, nonlinear techniques search for recurrent patterns of a specific amplitude and sign. They reveal, for instance, spatial asymmetries between different phases of the NAO that are likely important for ecological studies. It also follows that there is no universally accepted index to describe the temporal evolution of the NAO. Several of the most common measures are presented and compared. All reveal that there is no preferred time scale of variability for the NAO: large changes occur from one winter to the next and from one decade to the next. There is also a large amount of within-season variability in the patterns of atmospheric circulation of the North Atlantic, so that most winters cannot be characterized solely by a canonical NAO structure. A better understanding of how the NAO responds to external forcing, including sea surface temperature changes in the tropics, stratospheric influences, and increasing greenhouse gas concentrations, is crucial to the current debate on climate variability and change.

Climate forcing for dynamics of dissolved inorganic nutrients at Palmer Station, Antarctica: An interdecadal (1993-2013) analysis

NASA Astrophysics Data System (ADS)

Kim, Hyewon; Doney, Scott C.; Iannuzzi, Richard A.; Meredith, Michael P.; Martinson, Douglas G.; Ducklow, Hugh W.

2016-09-01

We analyzed 20 years (1993-2013) of observations of dissolved inorganic macronutrients (nitrate, N; phosphate, P; and silicate, Si) and chlorophyll a (Chl) at Palmer Station, Antarctica (64.8°S, 64.1°W) to elucidate how large-scale climate and local physical forcing affect the interannual variability in the seasonal phytoplankton bloom and associated drawdown of nutrients. The leading modes of nutrients (N, P, and Si empirical orthogonal functions 1, EOF1) represent overall negative anomalies throughout growing seasons, showing a mixed signal of variability in the initial levels and drawdown thereafter (low-frequency dynamics). The second most common seasonal patterns of nitrate and phosphate (N and P EOF2) capture prolonged drawdown events during December-March, which are correlated to Chl EOF1. Si EOF2 captures a drawdown event during November-December, which is correlated to Chl EOF2. These different drawdown patterns are shaped by different sets of physical and climate forcing mechanisms. N and P drawdown events during December-March are influenced by the winter and spring Southern Annular Mode (SAM) phase, where nutrient utilization is enhanced in a stabilized upper water column as a consequence of SAM-driven winter sea ice and spring wind dynamics. Si drawdown during November-December is influenced by early sea ice retreat, where ice breakup may induce abrupt water column stratification and a subsequent diatom bloom or release of diatom cells from within the sea ice. Our findings underscore that seasonal nutrient dynamics in the coastal WAP are coupled to large-scale climate forcing and related physics, understanding of which may enable improved projections of biogeochemical responses to climate change.

High-Resolution Subtropical Summer Precipitation Derived from Dynamical Downscaling of the NCEP-DOE Reanalysis: How Much Small-Scale Information Is Added by a Regional Model?

NASA Technical Reports Server (NTRS)

Lim, Young-Kwon; Stefanova, Lydia B.; Chan, Steven C.; Schubert, Siegfried D.; OBrien, James J.

2010-01-01

This study assesses the regional-scale summer precipitation produced by the dynamical downscaling of analyzed large-scale fields. The main goal of this study is to investigate how much the regional model adds smaller scale precipitation information that the large-scale fields do not resolve. The modeling region for this study covers the southeastern United States (Florida, Georgia, Alabama, South Carolina, and North Carolina) where the summer climate is subtropical in nature, with a heavy influence of regional-scale convection. The coarse resolution (2.5deg latitude/longitude) large-scale atmospheric variables from the National Center for Environmental Prediction (NCEP)/DOE reanalysis (R2) are downscaled using the NCEP Environmental Climate Prediction Center regional spectral model (RSM) to produce precipitation at 20 km resolution for 16 summer seasons (19902005). The RSM produces realistic details in the regional summer precipitation at 20 km resolution. Compared to R2, the RSM-produced monthly precipitation shows better agreement with observations. There is a reduced wet bias and a more realistic spatial pattern of the precipitation climatology compared with the interpolated R2 values. The root mean square errors of the monthly R2 precipitation are reduced over 93 (1,697) of all the grid points in the five states (1,821). The temporal correlation also improves over 92 (1,675) of all grid points such that the domain-averaged correlation increases from 0.38 (R2) to 0.55 (RSM). The RSM accurately reproduces the first two observed eigenmodes, compared with the R2 product for which the second mode is not properly reproduced. The spatial patterns for wet versus dry summer years are also successfully simulated in RSM. For shorter time scales, the RSM resolves heavy rainfall events and their frequency better than R2. Correlation and categorical classification (above/near/below average) for the monthly frequency of heavy precipitation days is also significantly improved by the RSM.

Dominant forest tree species are potentially vulnerable to climate change over large portions of their range even at high latitudes

PubMed Central

de Blois, Sylvie

2016-01-01

Projecting suitable conditions for a species as a function of future climate provides a reasonable, although admittedly imperfect, spatially explicit estimate of species vulnerability associated with climate change. Projections emphasizing range shifts at continental scale, however, can mask contrasting patterns at local or regional scale where management and policy decisions are made. Moreover, models usually show potential for areas to become climatically unsuitable, remain suitable, or become suitable for a particular species with climate change, but each of these outcomes raises markedly different ecological and management issues. Managing forest decline at sites where climatic stress is projected to increase is likely to be the most immediate challenge resulting from climate change. Here we assess habitat suitability with climate change for five dominant tree species of eastern North American forests, focusing on areas of greatest vulnerability (loss of suitability in the baseline range) in Quebec (Canada) rather than opportunities (increase in suitability). Results show that these species are at risk of maladaptation over a remarkably large proportion of their baseline range. Depending on species, 5–21% of currently climatically suitable habitats are projected to be at risk of becoming unsuitable. This suggests that species that have traditionally defined whole regional vegetation assemblages could become less adapted to these regions, with significant impact on ecosystems and forest economy. In spite of their well-recognised limitations and the uncertainty that remains, regionally-explicit risk assessment approaches remain one of the best options to convey that message and the need for climate policies and forest management adaptation strategies. PMID:27478706

Dominant forest tree species are potentially vulnerable to climate change over large portions of their range even at high latitudes.

PubMed

Périé, Catherine; de Blois, Sylvie

2016-01-01

Projecting suitable conditions for a species as a function of future climate provides a reasonable, although admittedly imperfect, spatially explicit estimate of species vulnerability associated with climate change. Projections emphasizing range shifts at continental scale, however, can mask contrasting patterns at local or regional scale where management and policy decisions are made. Moreover, models usually show potential for areas to become climatically unsuitable, remain suitable, or become suitable for a particular species with climate change, but each of these outcomes raises markedly different ecological and management issues. Managing forest decline at sites where climatic stress is projected to increase is likely to be the most immediate challenge resulting from climate change. Here we assess habitat suitability with climate change for five dominant tree species of eastern North American forests, focusing on areas of greatest vulnerability (loss of suitability in the baseline range) in Quebec (Canada) rather than opportunities (increase in suitability). Results show that these species are at risk of maladaptation over a remarkably large proportion of their baseline range. Depending on species, 5-21% of currently climatically suitable habitats are projected to be at risk of becoming unsuitable. This suggests that species that have traditionally defined whole regional vegetation assemblages could become less adapted to these regions, with significant impact on ecosystems and forest economy. In spite of their well-recognised limitations and the uncertainty that remains, regionally-explicit risk assessment approaches remain one of the best options to convey that message and the need for climate policies and forest management adaptation strategies.

Regression tree modeling of forest NPP using site conditions and climate variables across eastern USA

NASA Astrophysics Data System (ADS)

Kwon, Y.

2013-12-01

As evidence of global warming continue to increase, being able to predict forest response to climate changes, such as expected rise of temperature and precipitation, will be vital for maintaining the sustainability and productivity of forests. To map forest species redistribution by climate change scenario has been successful, however, most species redistribution maps lack mechanistic understanding to explain why trees grow under the novel conditions of chaining climate. Distributional map is only capable of predicting under the equilibrium assumption that the communities would exist following a prolonged period under the new climate. In this context, forest NPP as a surrogate for growth rate, the most important facet that determines stand dynamics, can lead to valid prediction on the transition stage to new vegetation-climate equilibrium as it represents changes in structure of forest reflecting site conditions and climate factors. The objective of this study is to develop forest growth map using regression tree analysis by extracting large-scale non-linear structures from both field-based FIA and remotely sensed MODIS data set. The major issue addressed in this approach is non-linear spatial patterns of forest attributes. Forest inventory data showed complex spatial patterns that reflect environmental states and processes that originate at different spatial scales. At broad scales, non-linear spatial trends in forest attributes and mixture of continuous and discrete types of environmental variables make traditional statistical (multivariate regression) and geostatistical (kriging) models inefficient. It calls into question some traditional underlying assumptions of spatial trends that uncritically accepted in forest data. To solve the controversy surrounding the suitability of forest data, regression tree analysis are performed using Software See5 and Cubist. Four publicly available data sets were obtained: First, field-based Forest Inventory and Analysis (USDA, Forest Service) data set for the 31 eastern most United States. Second, 8-day composite of MODIS Land Cover, FPAR, LAI and GPP/NPP data were obtained from Jan 2001 to Dec 2004 (total 182 composite) and each product were filtered by pixel-level quality assurance data to select best quality pixels. Third, 30-year averaged climate data were collected from National Oceanic and Atmospheric Administration (NOAA) and five climatic variables were obtained: Monthly temperature, precipitation, annual heating and cooling days, and annual frost-free days. Forth, topographic data were obtained from digital elevation model (1km by 1km). This research will provide a better understanding of large-scale forest responses to environmental factors that will be beneficial for the development of important forest management applications.

Climatic and Landscape Influences on Fire Regimes from 1984 to 2010 in the Western United States

PubMed Central

Liu, Zhihua; Wimberly, Michael C.

2015-01-01

An improved understanding of the relative influences of climatic and landscape controls on multiple fire regime components is needed to enhance our understanding of modern fire regimes and how they will respond to future environmental change. To address this need, we analyzed the spatio-temporal patterns of fire occurrence, size, and severity of large fires (> 405 ha) in the western United States from 1984–2010. We assessed the associations of these fire regime components with environmental variables, including short-term climate anomalies, vegetation type, topography, and human influences, using boosted regression tree analysis. Results showed that large fire occurrence, size, and severity each exhibited distinctive spatial and spatio-temporal patterns, which were controlled by different sets of climate and landscape factors. Antecedent climate anomalies had the strongest influences on fire occurrence, resulting in the highest spatial synchrony. In contrast, climatic variability had weaker influences on fire size and severity and vegetation types were the most important environmental determinants of these fire regime components. Topography had moderately strong effects on both fire occurrence and severity, and human influence variables were most strongly associated with fire size. These results suggest a potential for the emergence of novel fire regimes due to the responses of fire regime components to multiple drivers at different spatial and temporal scales. Next-generation approaches for projecting future fire regimes should incorporate indirect climate effects on vegetation type changes as well as other landscape effects on multiple components of fire regimes. PMID:26465959

Investigating added value of regional climate modeling in North American winter storm track simulations

NASA Astrophysics Data System (ADS)

Poan, E. D.; Gachon, P.; Laprise, R.; Aider, R.; Dueymes, G.

2018-03-01

Extratropical Cyclone (EC) characteristics depend on a combination of large-scale factors and regional processes. However, the latter are considered to be poorly represented in global climate models (GCMs), partly because their resolution is too coarse. This paper describes a framework using possibilities given by regional climate models (RCMs) to gain insight into storm activity during winter over North America (NA). Recent past climate period (1981-2005) is considered to assess EC activity over NA using the NCEP regional reanalysis (NARR) as a reference, along with the European reanalysis ERA-Interim (ERAI) and two CMIP5 GCMs used to drive the Canadian Regional Climate Model—version 5 (CRCM5) and the corresponding regional-scale simulations. While ERAI and GCM simulations show basic agreement with NARR in terms of climatological storm track patterns, detailed bias analyses show that, on the one hand, ERAI presents statistically significant positive biases in terms of EC genesis and therefore occurrence while capturing their intensity fairly well. On the other hand, GCMs present large negative intensity biases in the overall NA domain and particularly over NA eastern coast. In addition, storm occurrence over the northwestern topographic regions is highly overestimated. When the CRCM5 is driven by ERAI, no significant skill deterioration arises and, more importantly, all storm characteristics near areas with marked relief and over regions with large water masses are significantly improved with respect to ERAI. Conversely, in GCM-driven simulations, the added value contributed by CRCM5 is less prominent and systematic, except over western NA areas with high topography and over the Western Atlantic coastlines where the most frequent and intense ECs are located. Despite this significant added-value on seasonal-mean characteristics, a caveat is raised on the RCM ability to handle storm temporal `seriality', as a measure of their temporal variability at a given location. In fact, the driving models induce some significant footprints on the RCM skill to reproduce the intra-seasonal pattern of storm activity.

Evaluating the potential of Iberian lakes as sensors of climate circulation patterns

NASA Astrophysics Data System (ADS)

Hernández, Armand; Trigo, Ricardo M.; Jerez, Sonia; Rico-Herrero, Maria T.; Vega, José C.; Jambrina-Enríquez, Margarita; Valero-Garcés, Blas L.; Giralt, Santiago

2013-04-01

Lakes are one of the best continental sensors for reconstructing past environmental and climatic changes. Recent lacustrine systems may be used for reconstructing with high-temporal resolution past climate parameters (e.g. precipitation, temperature, wind), land management changes and limnological conditions such as pH, salinity, or nutrients concentrations using a large set of techniques and proxies. Paleoenvironmental reconstructions can be improved by validating them with instrumental data, and the availability of monitoring data greatly enhances the potential of lakes to evaluate the link between the measured physical-chemical-biological parameters and the indicators from lake sediments. The Iberian Peninsula (IP) is an excellent site to conduct quantitative climate reconstructions owing to its location between the Eurosiberian and Mediterranean regions. Due to its geographic position, a large fraction of the IP climate is dominated by the most important large scale pattern of the Northern Hemisphere, i.e. the North Atlantic Oscillation (NAO). However, a number of recent works has put into evidence that besides the NAO mode there are other relevant atmospheric circulation patterns over the North Atlantic and European sector that play an important role in terms of Western Mediterranean climate. Among these we have evaluated particularly the so-called Scandinavian (SCAND) and eastern Atlantic (EA) which have commonly been overlooked. Monthly limnological monitoring in Lake Sanabria (42°07'N, 06°43'W) and Lake Las Madres (40°18'N, 3°31'W) since 1986 and 1991, respectively, provided a unique opportunity to test the spatio-temporal relationships between meteorological data and climate modes, hydrology, lake dynamics and, in the Lake Sanabria case, how the climate signal is transferred to the lake sediments. For this purpose, we have used five complementary datasets: (1) meteorological (air temperature, total precipitation and wind intensity), (2) climate modes index (NAO, EA, SCAND), (3) limnological (Secchi disk, water temperature, conductivity, pH, dissolved oxygen, nitrate, total phosphorus and chlorophyll) in both lake systems; and in Lake Sanabria (4) hydrological (Tera River water input and output) and (5) XRF core scanner measurements carried out in short cores. The preliminary results based on linear models and Principal Component Analyses between the different dataset variables show how the climate signal is transferred from the atmosphere to the lake, and ultimately to the sediments. Establishment of such links allowed us to infer quantitatively the pattern of precipitation and its temporal and spatial relationship with the main climate over the last decades using the limnological and sediment data in these two IP lakes. These results highlight that besides NAO, the SCAND and EA patterns must be taken into account on any analysis of climate variability in the IP.

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.

Global change impacts on large-scale biogeographic patterns of marine organisms on Atlantic oceanic islands.

PubMed

Ávila, Sérgio P; Cordeiro, Ricardo; Madeira, Patrícia; Silva, Luís; Medeiros, António; Rebelo, Ana C; Melo, Carlos; Neto, Ana I; Haroun, Ricardo; Monteiro, António; Rijsdijk, Kenneth; Johnson, Markes E

2018-01-01

Past climate changes provide important clues for advancement of studies on current global change biology. We have tested large-scale biogeographic patterns through four marine groups from twelve Atlantic Ocean archipelagos and searched for patterns between species richness/endemism and littoral area, age, isolation, latitude and mean annual sea-surface temperatures. Species richness is strongly correlated with littoral area. Two reinforcing effects take place during glacial episodes: i) species richness is expected to decrease (in comparison with interglacial periods) due to the local disappearance of sandy/muddy-associated species; ii) because littoral area is minimal during glacial episodes, area per se induces a decrease on species richness (by extirpation/extinction of marine species) as well as affecting speciation rates. Maximum speciation rates are expected to occur during the interglacial periods, whereas immigration rates are expected to be higher at the LGM. Finally, sea-level changes are a paramount factor influencing marine biodiversity of animals and plants living on oceanic islands. Copyright © 2017 Elsevier Ltd. All rights reserved.

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.

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.

Complex seasonal patterns of primary producers at the land-sea interface

USGS Publications Warehouse

Cloern, J.E.; Jassby, A.D.

2008-01-01

Seasonal fluctuations of plant biomass and photosynthesis are key features of the Earth system because they drive variability of atmospheric CO 2, water and nutrient cycling, and food supply to consumers. There is no inventory of phytoplankton seasonal cycles in nearshore coastal ecosystems where forcings from ocean, land and atmosphere intersect. We compiled time series of phytoplankton biomass (chlorophyll a) from 114 estuaries, lagoons, inland seas, bays and shallow coastal waters around the world, and searched for seasonal patterns as common timing and amplitude of monthly variability. The data revealed a broad continuum of seasonal patterns, with large variability across and within ecosystems. This contrasts with annual cycles of terrestrial and oceanic primary producers for which seasonal fluctuations are recurrent and synchronous over large geographic regions. This finding bears on two fundamental ecological questions: (1) how do estuarine and coastal consumers adapt to an irregular and unpredictable food supply, and (2) how can we extract signals of climate change from phytoplankton observations in coastal ecosystems where local-scale processes can mask responses to changing climate? ?? 2008 Blackwell Publishing Ltd/CNRS.

Distant Influence of Kuroshio Eddies on North Pacific Weather Patterns?

PubMed

Ma, Xiaohui; Chang, Ping; Saravanan, R; Montuoro, Raffaele; Hsieh, Jen-Shan; Wu, Dexing; Lin, Xiaopei; Wu, Lixin; Jing, Zhao

2015-12-04

High-resolution satellite measurements of surface winds and sea-surface temperature (SST) reveal strong coupling between meso-scale ocean eddies and near-surface atmospheric flow over eddy-rich oceanic regions, such as the Kuroshio and Gulf Stream, highlighting the importance of meso-scale oceanic features in forcing the atmospheric planetary boundary layer (PBL). Here, we present high-resolution regional climate modeling results, supported by observational analyses, demonstrating that meso-scale SST variability, largely confined in the Kuroshio-Oyashio confluence region (KOCR), can further exert a significant distant influence on winter rainfall variability along the U.S. Northern Pacific coast. The presence of meso-scale SST anomalies enhances the diabatic conversion of latent heat energy to transient eddy energy, intensifying winter cyclogenesis via moist baroclinic instability, which in turn leads to an equivalent barotropic downstream anticyclone anomaly with reduced rainfall. The finding points to the potential of improving forecasts of extratropical winter cyclones and storm systems and projections of their response to future climate change, which are known to have major social and economic impacts, by improving the representation of ocean eddy-atmosphere interaction in forecast and climate models.

Teleconnection Linking Asian/Pacific Monsoon Variability and Summertime Droughts and Floods Over the United States

NASA Technical Reports Server (NTRS)

Lau, K. M.; Weng, Hengyi

2000-01-01

Major droughts and floods over the U.S. continent may be related to a far field energy source in the Asian Pacific. This is illustrated by two climate patterns associated with summertime rainfall over the U.S. and large-scale circulation on interannual timescale. The first shows an opposite variation between the drought/flood over the Midwest and that over eastern and southeastern U.S., coupled to a coherent wave pattern spanning the entire East Asia-North Pacific-North America region related to the East Asian jetstream. The second shows a continental-scale drought/flood in the central U.S., coupled to a wavetrain linking Asian/Pacific monsoon region to North America.

Patterns of species diversity and phylogenetic structure of vascular plants on the Qinghai-Tibetan Plateau.

PubMed

Yan, Yujing; Yang, Xian; Tang, Zhiyao

2013-11-01

Large-scale patterns of species richness and the underlying mechanisms regulating these patterns have long been the central issues in biogeography and macroecology. Phylogenetic community structure is a result of combined effects of contemporary ecological interactions, environmental filtering, and evolutionary history, and it links community ecology with biogeography and trait evolution. The Qinghai-Tibetan Plateau provides a good opportunity to test the influence of contemporary climate on shaping species richness because of its unique geological history, cold climate, and high biodiversity. In this study, based on high-resolution distributions of ˜9000 vascular plant species, we explored how species richness and phylogenetic structure of vascular plants correlate with climates on the highest (and species rich) plateau on the Earth. The results showed that most of the vascular plants were distributed on the eastern part of the plateau; there was a strong association between species richness and climate, even after the effects of habitat heterogeneity were controlled. However, the responses of richness to climate remarkably depended on life-forms. Richness of woody plants showed stronger climatic associations than that of herbaceous plants; energy and water availability together regulated richness pattern of woody plants; whereas water availability predominantly regulated richness pattern of herbaceous plants. The phylogenetic structure of vascular species clustered in most areas of the plateau, suggesting that rapid speciation and environment filtering dominated the assembly of communities on the plateau. We further propose that biodiversity conservation in this area should better take into account ecological features for different life-forms and phylogenetic lineages.

Patterns of species diversity and phylogenetic structure of vascular plants on the Qinghai-Tibetan Plateau

PubMed Central

Yan, Yujing; Yang, Xian; Tang, Zhiyao

2013-01-01

Large-scale patterns of species richness and the underlying mechanisms regulating these patterns have long been the central issues in biogeography and macroecology. Phylogenetic community structure is a result of combined effects of contemporary ecological interactions, environmental filtering, and evolutionary history, and it links community ecology with biogeography and trait evolution. The Qinghai-Tibetan Plateau provides a good opportunity to test the influence of contemporary climate on shaping species richness because of its unique geological history, cold climate, and high biodiversity. In this study, based on high-resolution distributions of ˜9000 vascular plant species, we explored how species richness and phylogenetic structure of vascular plants correlate with climates on the highest (and species rich) plateau on the Earth. The results showed that most of the vascular plants were distributed on the eastern part of the plateau; there was a strong association between species richness and climate, even after the effects of habitat heterogeneity were controlled. However, the responses of richness to climate remarkably depended on life-forms. Richness of woody plants showed stronger climatic associations than that of herbaceous plants; energy and water availability together regulated richness pattern of woody plants; whereas water availability predominantly regulated richness pattern of herbaceous plants. The phylogenetic structure of vascular species clustered in most areas of the plateau, suggesting that rapid speciation and environment filtering dominated the assembly of communities on the plateau. We further propose that biodiversity conservation in this area should better take into account ecological features for different life-forms and phylogenetic lineages. PMID:24340197

Long Term Population, City Size and Climate Trends in the Fertile Crescent: A First Approximation.

PubMed

Lawrence, Dan; Philip, Graham; Hunt, Hannah; Snape-Kennedy, Lisa; Wilkinson, T J

2016-01-01

Over the last 8000 years the Fertile Crescent of the Near East has seen the emergence of urban agglomerations, small scale polities and large territorial empires, all of which had profound effects on settlement patterns. Computational approaches, including the use of remote sensing data, allow us to analyse these changes at unprecedented geographical and temporal scales. Here we employ these techniques to examine and compare long term trends in urbanisation, population and climate records. Maximum city size is used as a proxy for the intensity of urbanisation, whilst population trends are modelled from settlement densities in nine archaeological surveys conducted over the last 30 years across the region. These two measures are then compared with atmospheric moisture levels derived from multiple proxy analyses from two locations close to the study area, Soreq Cave in Israel and Lake Van in south-eastern Turkey, as well as wider literature. The earliest urban sites emerged during a period of relatively high atmospheric moisture levels and conform to a series of size thresholds. However, after the Early Bronze Age maximum urban size and population levels increase rapidly whilst atmospheric moisture declines. We argue that although the initial phase of urbanization may have been linked to climate conditions, we can see a definitive decoupling of climate and settlement patterns after 2000 BC. We relate this phenomenon to changes in socio-economic organisation and integration in large territorial empires. The complex relationships sustaining urban growth during this later period resulted in an increase in system fragility and ultimately impacted on the sustainability of cities in the long term.

Long Term Population, City Size and Climate Trends in the Fertile Crescent: A First Approximation

PubMed Central

Lawrence, Dan; Philip, Graham; Hunt, Hannah; Snape-Kennedy, Lisa; Wilkinson, T. J.

2016-01-01

Over the last 8000 years the Fertile Crescent of the Near East has seen the emergence of urban agglomerations, small scale polities and large territorial empires, all of which had profound effects on settlement patterns. Computational approaches, including the use of remote sensing data, allow us to analyse these changes at unprecedented geographical and temporal scales. Here we employ these techniques to examine and compare long term trends in urbanisation, population and climate records. Maximum city size is used as a proxy for the intensity of urbanisation, whilst population trends are modelled from settlement densities in nine archaeological surveys conducted over the last 30 years across the region. These two measures are then compared with atmospheric moisture levels derived from multiple proxy analyses from two locations close to the study area, Soreq Cave in Israel and Lake Van in south-eastern Turkey, as well as wider literature. The earliest urban sites emerged during a period of relatively high atmospheric moisture levels and conform to a series of size thresholds. However, after the Early Bronze Age maximum urban size and population levels increase rapidly whilst atmospheric moisture declines. We argue that although the initial phase of urbanization may have been linked to climate conditions, we can see a definitive decoupling of climate and settlement patterns after 2000 BC. We relate this phenomenon to changes in socio-economic organisation and integration in large territorial empires. The complex relationships sustaining urban growth during this later period resulted in an increase in system fragility and ultimately impacted on the sustainability of cities in the long term. PMID:27018998

New Reasons to Preserve the Amazon Rainforest

NASA Astrophysics Data System (ADS)

Costa, M. H.

2014-12-01

Historically, preservation of the rainforest was justified in terms of conservation of biodiversity, protection of indigenous people habitats and maintenance of carbon stocks. Most of these arguments are based on the direct effect of rainforest removal, and ignore second order effects of the presence of the rainforest, such as modulation of regional climate patterns. The rainforest helps define the regional climate of the region, in particular the regional temperature and precipitation patterns. Of course, any activity that depends on the local climate may be affected by changes in the rainforest. Recent evidence in the literature presented enough arguments to believe that the widespread removal of the rainforest will have economic consequences at least in agriculture output and hydroelectric power generation. Economic impacts may affect not only the agriculture and energy sectors, but also several other economic activities that are related to climate. As a country, we are counting with the climate of Amazonia as fixed, but if the present climate needs the presence of the rainforest, we need to quantify the economic value of the climate regulation service provided by the rainforest. Important questions to be answered: How much of the rainforest is needed to conserve the present climate? Where it should stand for best climate regulation? Answer to these questions may affect Brazil´s large-scale policy on land use.

Assessing the Effects of Climate on Global Fluvial Discharge Variability

NASA Astrophysics Data System (ADS)

Hansford, M. R.; Plink-Bjorklund, P.

2017-12-01

Plink-Bjorklund (2015) established the link between precipitation seasonality and river discharge variability in the monsoon domain and subtropical rivers (see also Leier et al, 2005; Fielding et al., 2009), resulting in distinct morphodynamic processes and a sedimentary record distinct from perennial precipitation zone in tropical rainforest zone and mid latitudes. This study further develops our understanding of discharge variability using a modern global river database created with data from the Global Runoff Data Centre (GRDC). The database consists of daily discharge for 595 river stations and examines them using a series of discharge variability indexes (DVI) on different temporal scales to examine how discharge variability occurs in river systems around the globe. These indexes examine discharge of individual days and monthly averages that allows for comparison of river systems against each other, regardless of size of the river. Comparing river discharge patterns in seven climate zones (arid, cold, humid subtropics, monsoonal, polar, rainforest, and temperate) based off the Koppen-Geiger climate classifications reveals a first order climatic control on discharge patterns and correspondingly sediment transport. Four groupings of discharge patterns emerge when coming climate zones and DVI: persistent, moderate, seasonal, and erratic. This dataset has incredible predictive power about the nature of discharge in fluvial systems around the world. These seasonal effects on surface water supply affects river morphodynamics and sedimentation on a wide timeframe, ranging from large single events to an inter-annual or even decadal timeframe. The resulting sedimentary deposits lead to differences in fluvial architecture on a range of depositional scales from sedimentary structures and bedforms to channel complex systems. These differences are important to accurately model for several reasons, ranging from stratigraphic and paleoenviromental reconstructions to more economic reasons, such as predicting reservoir presence, distribution, and connectivity in continental basins. The ultimate objective of this research is to develop differentiated fluvial facies and architecture based on the observed discharge patterns in the different climate zones.

Large-scale drivers of local precipitation extremes in convection-permitting climate simulations

NASA Astrophysics Data System (ADS)

Chan, Steven C.; Kendon, Elizabeth J.; Roberts, Nigel M.; Fowler, Hayley J.; Blenkinsop, Stephen

2016-04-01

The Met Office 1.5-km UKV convective-permitting models (CPM) is used to downscale present-climate and RCP8.5 60-km HadGEM3 GCM simulations. Extreme UK hourly precipitation intensities increase with local near-surface temperatures and humidity; for temperature, the simulated increase rate for the present-climate simulation is about 6.5% K**-1, which is consistent with observations and theoretical expectations. While extreme intensities are higher in the RCP8.5 simulation as higher temperatures are sampled, there is a decline at the highest temperatures due to circulation and relative humidity changes. Extending the analysis to the broader synoptic scale, it is found that circulation patterns, as diagnosed by MSLP or circulation type, play an increased role in the probability of extreme precipitation in the RCP8.5 simulation. Nevertheless for both CPM simulations, vertical instability is the principal driver for extreme precipitation.

Santa Ana Winds of Southern California: Their climatology, extremes, and behavior spanning six and a half decades

NASA Astrophysics Data System (ADS)

Guzman-Morales, Janin; Gershunov, Alexander; Theiss, Jurgen; Li, Haiqin; Cayan, Daniel

2016-03-01

Santa Ana Winds (SAWs) are an integral feature of the regional climate of Southern California/Northern Baja California region, but their climate-scale behavior is poorly understood. In the present work, we identify SAWs in mesoscale dynamical downscaling of a global reanalysis from 1948 to 2012. Model winds are validated with anemometer observations. SAWs exhibit an organized pattern with strongest easterly winds on westward facing downwind slopes and muted magnitudes at sea and over desert lowlands. We construct hourly local and regional SAW indices and analyze elements of their behavior on daily, annual, and multidecadal timescales. SAWs occurrences peak in winter, but some of the strongest winds have occurred in fall. Finally, we observe that SAW intensity is influenced by prominent large-scale low-frequency modes of climate variability rooted in the tropical and north Pacific ocean-atmosphere system.

Catastrophic flooding origin of shelf valley systems in the English Channel.

PubMed

Gupta, Sanjeev; Collier, Jenny S; Palmer-Felgate, Andy; Potter, Graeme

2007-07-19

Megaflood events involving sudden discharges of exceptionally large volumes of water are rare, but can significantly affect landscape evolution, continental-scale drainage patterns and climate change. It has been proposed that a significant flood event eroded a network of large ancient valleys on the floor of the English Channel-the narrow seaway between England and France. This hypothesis has remained untested through lack of direct evidence, and alternative non-catastrophist ideas have been entertained for valley formation. Here we analyse a new regional bathymetric map of part of the English Channel derived from high-resolution sonar data, which shows the morphology of the valley in unprecedented detail. We observe a large bedrock-floored valley that contains a distinct assemblage of landforms, including streamlined islands and longitudinal erosional grooves, which are indicative of large-scale subaerial erosion by high-magnitude water discharges. Our observations support the megaflood model, in which breaching of a rock dam at the Dover Strait instigated catastrophic drainage of a large pro-glacial lake in the southern North Sea basin. We suggest that megaflooding provides an explanation for the permanent isolation of Britain from mainland Europe during interglacial high-sea-level stands, and consequently for patterns of early human colonisation of Britain together with the large-scale reorganization of palaeodrainage in northwest Europe.

Large-scale phytogeographical patterns in East Asia in relation to latitudinal and climatic gradients

USGS Publications Warehouse

Qian, H.; Song, J.-S.; Krestov, P.; Guo, Q.; Wu, Z.; Shen, X.; Guo, X.

2003-01-01

Aim: This paper aims at determining how different floristic elements (e.g. cosmopolitan, tropical, and temperate) change with latitude and major climate factors, and how latitude affects the floristic relationships between East Asia and the other parts of the world. Location: East Asia from the Arctic to tropical regions, an area crossing over 50?? of latitudes and covering the eastern part of China, Korea, Japan and the eastern part of Russia. Methods: East Asia is divided into forty-five geographical regions. Based on the similarity of their world-wide distributional patterns, a total of 2808 indigenous genera of seed plants found in East Asia were grouped into fourteen geographical elements, belonging to three major categories (cosmopolitan, tropical and temperate). The 50??-long latitudinal gradient of East Asia was divided into five latitudinal zones, each of c. 10??. Phytogeographical relationships of East Asia to latitude and climatic variables were examined based on the forty-five regional floras. Results: Among all geographical and climatic variables considered, latitude showed the strongest relationship to phytogeographical composition. Tropical genera (with pantropical, amphi-Pacific tropical, palaeotropical, tropical Asia-tropical Australia, tropical Asia-tropical Africa and tropical Asia geographical elements combined) accounted for c. 80% of the total genera at latitude 20??N and for c. 0% at latitude 55-60??N. In contrast, temperate genera (including holarctic, eastern Asia-North America, temperate Eurasia, temperate Asia, Mediterranean, western Asia to central Asia, central Asia and eastern Asia geographical elements) accounted for 15.5% in the southernmost latitude and for 80% at 55-60??N, from where northward the percentage tended to level off. The proportion of cosmopolitan genera increased gradually with latitude from 5% at the southernmost latitude to 21% at 55-60??N, where it levelled off northward. In general, the genera present in a more northerly flora are a subset of the genera present in a more southerly flora. Main conclusions: The large-scale patterns of phytogeography in East Asia are strongly related to latitude, which covaries with several climatic variables such as temperature. Evolutionary processes such as the adaptation of plants to cold climates and current and past land connections are likely responsible for the observed latitudinal patterns.

Diversity of herbaceous plants and bacterial communities regulates soil resistome across forest biomes.

PubMed

Hu, Hang-Wei; Wang, Jun-Tao; Singh, Brajesh K; Liu, Yu-Rong; Chen, Yong-Liang; Zhang, Yu-Jing; He, Ji-Zheng

2018-04-24

Antibiotic resistance is ancient and prevalent in natural ecosystems and evolved long before the utilization of synthetic antibiotics started, but factors influencing the large-scale distribution patterns of natural antibiotic resistance genes (ARGs) remain largely unknown. Here, a large-scale investigation over 4000 km was performed to profile soil ARGs, plant communities and bacterial communities from 300 quadrats across five forest biomes with minimal human impact. We detected diverse and abundant ARGs in forests, including over 160 genes conferring resistance to eight major categories of antibiotics. The diversity of ARGs was strongly and positively correlated with the diversity of bacteria, herbaceous plants and mobile genetic elements (MGEs). The ARG composition was strongly correlated with the taxonomic structure of bacteria and herbs. Consistent with this strong correlation, structural equation modelling demonstrated that the positive effects of bacterial and herb communities on ARG patterns were maintained even when simultaneously accounting for multiple drivers (climate, spatial predictors and edaphic factors). These findings suggest a paradigm that the interactions between aboveground and belowground communities shape the large-scale distribution of soil resistomes, providing new knowledge for tackling the emerging environmental antibiotic resistance. © 2018 Society for Applied Microbiology and John Wiley & Sons Ltd.

Winter precipitation forecast in the European and Mediterranean regions using cluster analysis

NASA Astrophysics Data System (ADS)

Molnos, S.

2017-12-01

The European and Mediterranean climates are sensitive to large-scale circulation of the atmosphere andocean making it difficult to forecast precipitation or temperature on seasonal time-scales. In addition, theMediterranean region has been identified as a hotspot for climate change and already today a drying in theMediterranean region is observed.Thus, it is critically important to predict seasonal droughts as early as possible such that water managersand stakeholders can mitigate impacts.We developed a novel cluster-based forecast method to empirically predict winter's precipitationanomalies in European and Mediterranean regions using precursors in autumn. This approach does notonly utilizes the amplitude but also the pattern of the precursors in generating the forecast.Using a toy model we show that it achieves a better forecast skill than more traditional regression models. Furthermore, we compare our algorithm with dynamic forecast models demonstrating that our prediction method performs better in terms of time and pattern correlation in the Mediterranean and European regions.

Satellite measurements reveal strong anisotropy in spatial coherence of climate variations over the Tibet Plateau.

PubMed

Chen, Deliang; Tian, Yudong; Yao, Tandong; Ou, Tinghai

2016-08-24

This study uses high-resolution, long-term satellite observations to evaluate the spatial scales of the climate variations across the Tibet Plateau (TP). Both land surface temperature and precipitation observations of more than 10 years were analysed with a special attention to eight existing ice-core sites in the TP. The temporal correlation for the monthly or annual anomalies between any two points decreases exponentially with their spatial distance, and we used the e-folding decay constant to quantify the spatial scales. We found that the spatial scales are strongly direction-dependent, with distinctive patterns in the west-east and south-north orientations, for example. Meanwhile, in the same directions the scales are largely symmetric backward and forward. Focusing on the west-east and south-north directions, we found the spatial coherence in the first is generally stronger than in the second. The annual surface temperature had typical spatial scales of 302-480 km, while the annual precipitation showed smaller scales of 111-182 km. The majority of the eight ice-core sites exhibit scales much smaller than the typical scales over the TP as a whole. These results provide important observational basis for the selection of appropriate downscaling strategies, deployment of climate-data collection networks, and interpreting paleoclimate reconstructions.

Satellite measurements reveal strong anisotropy in spatial coherence of climate variations over the Tibet Plateau

NASA Astrophysics Data System (ADS)

Chen, Deliang; Tian, Yudong; Yao, Tandong; Ou, Tinghai

2016-08-01

This study uses high-resolution, long-term satellite observations to evaluate the spatial scales of the climate variations across the Tibet Plateau (TP). Both land surface temperature and precipitation observations of more than 10 years were analysed with a special attention to eight existing ice-core sites in the TP. The temporal correlation for the monthly or annual anomalies between any two points decreases exponentially with their spatial distance, and we used the e-folding decay constant to quantify the spatial scales. We found that the spatial scales are strongly direction-dependent, with distinctive patterns in the west-east and south-north orientations, for example. Meanwhile, in the same directions the scales are largely symmetric backward and forward. Focusing on the west-east and south-north directions, we found the spatial coherence in the first is generally stronger than in the second. The annual surface temperature had typical spatial scales of 302-480 km, while the annual precipitation showed smaller scales of 111-182 km. The majority of the eight ice-core sites exhibit scales much smaller than the typical scales over the TP as a whole. These results provide important observational basis for the selection of appropriate downscaling strategies, deployment of climate-data collection networks, and interpreting paleoclimate reconstructions.

Satellite measurements reveal strong anisotropy in spatial coherence of climate variations over the Tibet Plateau

PubMed Central

Chen, Deliang; Tian, Yudong; Yao, Tandong; Ou, Tinghai

2016-01-01

This study uses high-resolution, long-term satellite observations to evaluate the spatial scales of the climate variations across the Tibet Plateau (TP). Both land surface temperature and precipitation observations of more than 10 years were analysed with a special attention to eight existing ice-core sites in the TP. The temporal correlation for the monthly or annual anomalies between any two points decreases exponentially with their spatial distance, and we used the e-folding decay constant to quantify the spatial scales. We found that the spatial scales are strongly direction-dependent, with distinctive patterns in the west-east and south-north orientations, for example. Meanwhile, in the same directions the scales are largely symmetric backward and forward. Focusing on the west-east and south-north directions, we found the spatial coherence in the first is generally stronger than in the second. The annual surface temperature had typical spatial scales of 302–480 km, while the annual precipitation showed smaller scales of 111–182 km. The majority of the eight ice-core sites exhibit scales much smaller than the typical scales over the TP as a whole. These results provide important observational basis for the selection of appropriate downscaling strategies, deployment of climate-data collection networks, and interpreting paleoclimate reconstructions. PMID:27553388

Quantifying the scale- and process- dependent reorganization of landscape under climatic change: inferences from an experimental landscape

NASA Astrophysics Data System (ADS)

Singh, A.; Tejedor, A.; Grimaud, J. L.; Zaliapin, I. V.; Foufoula-Georgiou, E.

2016-12-01

Knowledge of the dynamics of evolving landscapes in terms of their geomorphic and topologic re-organization in response to changing climatic or tectonic forcing is of scientific and practical interest. Although several studies have addressed the large-scale response (e.g., change in mean relief), studies on the smaller-scale drainage pattern re-organization and quantification of landscape vulnerability to the timing, magnitude, and frequency of changing forcing are lacking. The reason is the absence of data for such an analysis. To that goal, a series of controlled laboratory experiments were conducted at the St. Anthony Falls laboratory of the University of Minnesota to study the effect of changing precipitation patterns on landscape evolution at the short and long-time scales. High resolution digital elevation (DEM) both in space and time were measured for a range of rainfall patterns and uplift rates. Results from our study show a distinct signature of the precipitation increase on the probabilistic and geometrical structure of landscape features, evident in widening and deepening of channels and valleys, change in drainage patterns within sub-basins and change in the space-time structure of erosional and depositional events. A spatially explicit analysis of the locus of these erosional and depositional events suggests a regime shift, during the onset of the transient state, from supply-limited to transport-limited fluvial channels. We document a characteristic scale-dependent signature of erosion at steady state (which we term the "E50-area curve") and show that during reorganization, its evolving shape reflects process and scales of geomorphic change. Finally, we document changes in the longitudinal river profiles, in response to increased precipitation rate, with the formation of abrupt gradient (knickpoints) that migrate upstream as time proceeds.

Sensitivity analysis of key components in large-scale hydroeconomic models

NASA Astrophysics Data System (ADS)

Medellin-Azuara, J.; Connell, C. R.; Lund, J. R.; Howitt, R. E.

2008-12-01

This paper explores the likely impact of different estimation methods in key components of hydro-economic models such as hydrology and economic costs or benefits, using the CALVIN hydro-economic optimization for water supply in California. In perform our analysis using two climate scenarios: historical and warm-dry. The components compared were perturbed hydrology using six versus eighteen basins, highly-elastic urban water demands, and different valuation of agricultural water scarcity. Results indicate that large scale hydroeconomic hydro-economic models are often rather robust to a variety of estimation methods of ancillary models and components. Increasing the level of detail in the hydrologic representation of this system might not greatly affect overall estimates of climate and its effects and adaptations for California's water supply. More price responsive urban water demands will have a limited role in allocating water optimally among competing uses. Different estimation methods for the economic value of water and scarcity in agriculture may influence economically optimal water allocation; however land conversion patterns may have a stronger influence in this allocation. Overall optimization results of large-scale hydro-economic models remain useful for a wide range of assumptions in eliciting promising water management alternatives.

Assessing Weather-Yield Relationships in Rice at Local Scale Using Data Mining Approaches

PubMed Central

Delerce, Sylvain; Dorado, Hugo; Grillon, Alexandre; Rebolledo, Maria Camila; Prager, Steven D.; Patiño, Victor Hugo; Garcés Varón, Gabriel; Jiménez, Daniel

2016-01-01

Seasonal and inter-annual climate variability have become important issues for farmers, and climate change has been shown to increase them. Simultaneously farmers and agricultural organizations are increasingly collecting observational data about in situ crop performance. Agriculture thus needs new tools to cope with changing environmental conditions and to take advantage of these data. Data mining techniques make it possible to extract embedded knowledge associated with farmer experiences from these large observational datasets in order to identify best practices for adapting to climate variability. We introduce new approaches through a case study on irrigated and rainfed rice in Colombia. Preexisting observational datasets of commercial harvest records were combined with in situ daily weather series. Using Conditional Inference Forest and clustering techniques, we assessed the relationships between climatic factors and crop yield variability at the local scale for specific cultivars and growth stages. The analysis showed clear relationships in the various location-cultivar combinations, with climatic factors explaining 6 to 46% of spatiotemporal variability in yield, and with crop responses to weather being non-linear and cultivar-specific. Climatic factors affected cultivars differently during each stage of development. For instance, one cultivar was affected by high nighttime temperatures in the reproductive stage but responded positively to accumulated solar radiation during the ripening stage. Another was affected by high nighttime temperatures during both the vegetative and reproductive stages. Clustering of the weather patterns corresponding to individual cropping events revealed different groups of weather patterns for irrigated and rainfed systems with contrasting yield levels. Best-suited cultivars were identified for some weather patterns, making weather-site-specific recommendations possible. This study illustrates the potential of data mining for adding value to existing observational data in agriculture by allowing embedded knowledge to be quickly leveraged. It generates site-specific information on cultivar response to climatic factors and supports on-farm management decisions for adaptation to climate variability. PMID:27560980

Assessing Weather-Yield Relationships in Rice at Local Scale Using Data Mining Approaches.

PubMed

Delerce, Sylvain; Dorado, Hugo; Grillon, Alexandre; Rebolledo, Maria Camila; Prager, Steven D; Patiño, Victor Hugo; Garcés Varón, Gabriel; Jiménez, Daniel

2016-01-01

Seasonal and inter-annual climate variability have become important issues for farmers, and climate change has been shown to increase them. Simultaneously farmers and agricultural organizations are increasingly collecting observational data about in situ crop performance. Agriculture thus needs new tools to cope with changing environmental conditions and to take advantage of these data. Data mining techniques make it possible to extract embedded knowledge associated with farmer experiences from these large observational datasets in order to identify best practices for adapting to climate variability. We introduce new approaches through a case study on irrigated and rainfed rice in Colombia. Preexisting observational datasets of commercial harvest records were combined with in situ daily weather series. Using Conditional Inference Forest and clustering techniques, we assessed the relationships between climatic factors and crop yield variability at the local scale for specific cultivars and growth stages. The analysis showed clear relationships in the various location-cultivar combinations, with climatic factors explaining 6 to 46% of spatiotemporal variability in yield, and with crop responses to weather being non-linear and cultivar-specific. Climatic factors affected cultivars differently during each stage of development. For instance, one cultivar was affected by high nighttime temperatures in the reproductive stage but responded positively to accumulated solar radiation during the ripening stage. Another was affected by high nighttime temperatures during both the vegetative and reproductive stages. Clustering of the weather patterns corresponding to individual cropping events revealed different groups of weather patterns for irrigated and rainfed systems with contrasting yield levels. Best-suited cultivars were identified for some weather patterns, making weather-site-specific recommendations possible. This study illustrates the potential of data mining for adding value to existing observational data in agriculture by allowing embedded knowledge to be quickly leveraged. It generates site-specific information on cultivar response to climatic factors and supports on-farm management decisions for adaptation to climate variability.

Assessment of climate change impacts on runoff in China using climate elasticity and multiple CMIP5 GCMs

NASA Astrophysics Data System (ADS)

Wu, C.; Hu, B. X.; Wang, P.; Xu, K.

2017-12-01

The occurrence of climate warming is unequivocal and is expected to alter the temporal-spatial patterns of regional water resources. Based on the long-term (1960-2012) water budget data and climate projections from 28 Global Climate Models (GCMs) of the Coupled Model Intercomparison Project Phase 5 (CMIP5), this study investigated the responses of runoff (R) to future climate variability in China at both grid and catchment scales using the Budyko-based elasticity method. Results indicate a large spatial variation in precipitation (P) elasticity (from 1.2 to 3.3) and potential evaporation (PET) elasticity (from -2.3 to -0.2) across China. The P elasticity is larger in northeast and western China than in southern China, while the opposite occurs for PET elasticity. Climate projections suggest that there is large uncertainty involved among the GCM simulations, but most project a consistent change in P (or PET) over China at the mean annual scale. During the future period of 2071-2100, the mean annual P will likely increase in most parts of China particularly the western regions, while the mean annual PET will likely increase in the whole China especially the southern regions due to future increases in temperature. Moreover, larger increases are projected for higher emission scenarios. Compared with the baseline 1971-2000, the arid regions and humid regions of China will likely become wetter and drier in the period 2071-2100, respectively.

Physical and human dimensions of deforestation in Amazonia

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

Skole, D.L.; Chomentowski, W.H.; Salas W.A.

1994-05-01

In the Brazilian Amazon, regional trends are influenced by large scale external forces but mediated by local conditions. Tropical deforestation has a large influence on global hydrology, climate and biogeochemical cycles, but understanding is inadequate because of a lack of accurate measurements of rate, geographic extent and spatial patterns and lack of insight into its causes including interrelated social, economic and environmental factors. This article proposes an interdisciplinary approach for analyzing tropical deforestation in the Brazilian Amazon. The first part shows how deforestation can be measured from satellite remote sensing and sociodemographic and economic data. The second part proposes anmore » explanatory model, considering the relationship among deforestation and large scale social, economic, and institutional factors. 43 refs., 8 figs.« less

From GCM grid cell to agricultural plot: scale issues affecting modelling of climate impact

PubMed Central

Baron, Christian; Sultan, Benjamin; Balme, Maud; Sarr, Benoit; Traore, Seydou; Lebel, Thierry; Janicot, Serge; Dingkuhn, Michael

2005-01-01

General circulation models (GCM) are increasingly capable of making relevant predictions of seasonal and long-term climate variability, thus improving prospects of predicting impact on crop yields. This is particularly important for semi-arid West Africa where climate variability and drought threaten food security. Translating GCM outputs into attainable crop yields is difficult because GCM grid boxes are of larger scale than the processes governing yield, involving partitioning of rain among runoff, evaporation, transpiration, drainage and storage at plot scale. This study analyses the bias introduced to crop simulation when climatic data is aggregated spatially or in time, resulting in loss of relevant variation. A detailed case study was conducted using historical weather data for Senegal, applied to the crop model SARRA-H (version for millet). The study was then extended to a 10°N–17° N climatic gradient and a 31 year climate sequence to evaluate yield sensitivity to the variability of solar radiation and rainfall. Finally, a down-scaling model called LGO (Lebel–Guillot–Onibon), generating local rain patterns from grid cell means, was used to restore the variability lost by aggregation. Results indicate that forcing the crop model with spatially aggregated rainfall causes yield overestimations of 10–50% in dry latitudes, but nearly none in humid zones, due to a biased fraction of rainfall available for crop transpiration. Aggregation of solar radiation data caused significant bias in wetter zones where radiation was limiting yield. Where climatic gradients are steep, these two situations can occur within the same GCM grid cell. Disaggregation of grid cell means into a pattern of virtual synoptic stations having high-resolution rainfall distribution removed much of the bias caused by aggregation and gave realistic simulations of yield. It is concluded that coupling of GCM outputs with plot level crop models can cause large systematic errors due to scale incompatibility. These errors can be avoided by transforming GCM outputs, especially rainfall, to simulate the variability found at plot level. PMID:16433096

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.

Identifying Meteorological Controls on Open and Closed Mesoscale Cellular Convection as Associated with Marine Cold Air Outbreaks

NASA Astrophysics Data System (ADS)

McCoy, Isabel; Wood, Robert; Fletcher, Jennifer

Marine low clouds are key influencers of the climate and contribute significantly to uncertainty in model climate sensitivity due to their small scale and complex processes. Many low clouds occur in large-scale cellular patterns, known as open and closed mesoscale cellular convection (MCC), which have significantly different radiative and microphysical properties. Investigating MCC development and meteorological controls will improve our understanding of their impacts on the climate. We conducted an examination of time-varying meteorological conditions associated with satellite-determined open and closed MCC. The spatial and temporal patterns of MCC clouds were compared with key meteorological control variables calculated from ERA-Interim Reanalysis to highlight dependencies and major differences. This illustrated the influence of environmental stability and surface forcing as well as the role of marine cold air outbreaks (MCAO, the movement of cold air from polar-regions across warmer waters) in MCC cloud formation. Such outbreaks are important to open MCC development and may also influence the transition from open to closed MCC. Our results may lead to improvements in the parameterization of cloudiness and advance the simulation of marine low clouds. National Science Foundation Graduate Research Fellowship Grant (DGE-1256082).

Anelastic and Compressible Simulation of Moist Dynamics at Planetary Scales

NASA Astrophysics Data System (ADS)

Kurowski, M.; Smolarkiewicz, P. K.; Grabowski, W.

2015-12-01

Moist anelastic and compressible numerical solutions to the planetary baroclinic instability and climate benchmarks are compared. The solutions are obtained applying a consistent numerical framework for dis- crete integrations of the various nonhydrostatic flow equations. Moist extension of the baroclinic instability benchmark is formulated as an analog of the dry case. Flow patterns, surface vertical vorticity and pressure, total kinetic energy, power spectra, and total amount of condensed water are analyzed. The climate bench- mark extends the baroclinic instability study by addressing long-term statistics of an idealized planetary equilibrium and associated meridional transports. Short-term deterministic anelastic and compressible so- lutions differ significantly. In particular, anelastic baroclinic eddies propagate faster and develop slower owing to, respectively, modified dispersion relation and abbreviated baroclinic vorticity production. These eddies also carry less kinetic energy, and the onset of their rapid growth occurs later than for the compressible solutions. The observed differences between the two solutions are sensitive to initial conditions as they di- minish for large-amplitude excitations of the instability. In particular, on the climatic time scales, the anelastic and compressible solutions evince similar zonally averaged flow patterns with the matching meridional transports of entropy, momentum, and moisture.

Structural overshoot of tree growth with climate variability and the global spectrum of drought-induced forest dieback.

PubMed

Jump, Alistair S; Ruiz-Benito, Paloma; Greenwood, Sarah; Allen, Craig D; Kitzberger, Thomas; Fensham, Rod; Martínez-Vilalta, Jordi; Lloret, Francisco

2017-09-01

Ongoing climate change poses significant threats to plant function and distribution. Increased temperatures and altered precipitation regimes amplify drought frequency and intensity, elevating plant stress and mortality. Large-scale forest mortality events will have far-reaching impacts on carbon and hydrological cycling, biodiversity, and ecosystem services. However, biogeographical theory and global vegetation models poorly represent recent forest die-off patterns. Furthermore, as trees are sessile and long-lived, their responses to climate extremes are substantially dependent on historical factors. We show that periods of favourable climatic and management conditions that facilitate abundant tree growth can lead to structural overshoot of aboveground tree biomass due to a subsequent temporal mismatch between water demand and availability. When environmental favourability declines, increases in water and temperature stress that are protracted, rapid, or both, drive a gradient of tree structural responses that can modify forest self-thinning relationships. Responses ranging from premature leaf senescence and partial canopy dieback to whole-tree mortality reduce canopy leaf area during the stress period and for a lagged recovery window thereafter. Such temporal mismatches of water requirements from availability can occur at local to regional scales throughout a species geographical range. As climate change projections predict large future fluctuations in both wet and dry conditions, we expect forests to become increasingly structurally mismatched to water availability and thus overbuilt during more stressful episodes. By accounting for the historical context of biomass development, our approach can explain previously problematic aspects of large-scale forest mortality, such as why it can occur throughout the range of a species and yet still be locally highly variable, and why some events seem readily attributable to an ongoing drought while others do not. This refined understanding can facilitate better projections of structural overshoot responses, enabling improved prediction of changes in forest distribution and function from regional to global scales. © 2017 John Wiley & Sons Ltd.

Structural overshoot of tree growth with climate variability and the global spectrum of drought-induced forest dieback

USGS Publications Warehouse

Jump, Alistair S.; Ruiz-Benito, Paloma; Greenwood, Sarah; Allen, Craig D.; Kitzberger, Thomas; Fensham, Rod; Martínez-Vilalta, Jordi; Lloret, Francisco

2017-01-01

Ongoing climate change poses significant threats to plant function and distribution. Increased temperatures and altered precipitation regimes amplify drought frequency and intensity, elevating plant stress and mortality. Large-scale forest mortality events will have far-reaching impacts on carbon and hydrological cycling, biodiversity, and ecosystem services. However, biogeographical theory and global vegetation models poorly represent recent forest die-off patterns. Furthermore, as trees are sessile and long-lived, their responses to climate extremes are substantially dependent on historical factors. We show that periods of favourable climatic and management conditions that facilitate abundant tree growth can lead to structural overshoot of aboveground tree biomass due to a subsequent temporal mismatch between water demand and availability. When environmental favourability declines, increases in water and temperature stress that are protracted, rapid, or both, drive a gradient of tree structural responses that can modify forest self-thinning relationships. Responses ranging from premature leaf senescence and partial canopy dieback to whole-tree mortality reduce canopy leaf area during the stress period and for a lagged recovery window thereafter. Such temporal mismatches of water requirements from availability can occur at local to regional scales throughout a species geographical range. As climate change projections predict large future fluctuations in both wet and dry conditions, we expect forests to become increasingly structurally mismatched to water availability and thus overbuilt during more stressful episodes. By accounting for the historical context of biomass development, our approach can explain previously problematic aspects of large-scale forest mortality, such as why it can occur throughout the range of a species and yet still be locally highly variable, and why some events seem readily attributable to an ongoing drought while others do not. This refined understanding can facilitate better projections of structural overshoot responses, enabling improved prediction of changes in forest distribution and function from regional to global scales.

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.

Climate and Human Pressure Constraints Co-Explain Regional Plant Invasion at Different Spatial Scales

PubMed Central

García-Baquero, Gonzalo; Caño, Lidia; Biurrun, Idoia; García-Mijangos, Itziar; Loidi, Javier; Herrera, Mercedes

2016-01-01

Alien species invasion represents a global threat to biodiversity and ecosystems. Explaining invasion patterns in terms of environmental constraints will help us to assess invasion risks and plan control strategies. We aim to identify plant invasion patterns in the Basque Country (Spain), and to determine the effects of climate and human pressure on that pattern. We modeled the regional distribution of 89 invasive plant species using two approaches. First, distance-based Moran’s eigenvector maps were used to partition variation in the invasive species richness, S, into spatial components at broad and fine scales; redundancy analysis was then used to explain those components on the basis of climate and human pressure descriptors. Second, we used generalized additive mixed modeling to fit species-specific responses to the same descriptors. Climate and human pressure descriptors have different effects on S at different spatial scales. Broad-scale spatially structured temperature and precipitation, and fine-scale spatially structured human population density and percentage of natural and semi-natural areas, explained altogether 38.7% of the total variance. The distribution of 84% of the individually tested species was related to either temperature, precipitation or both, and 68% was related to either population density or natural and semi-natural areas, displaying similar responses. The spatial pattern of the invasive species richness is strongly environmentally forced, mainly by climate factors. Since individual species responses were proved to be both similarly constrained in shape and explained variance by the same environmental factors, we conclude that the pattern of invasive species richness results from individual species’ environmental preferences. PMID:27741276

A fresh look at the Last Glacial Maximum using Paleoclimate Data Assimilation

NASA Astrophysics Data System (ADS)

Malevich, S. B.; Tierney, J. E.; Hakim, G. J.; Tardif, R.

2017-12-01

Quantifying climate conditions during the Last Glacial Maximum ( 21ka) can help us to understand climate responses to forcing and climate states that are poorly represented in the instrumental record. Paleoclimate proxies may be used to estimate these climate conditions, but proxies are sparsely distributed and possess uncertainties from environmental and biogeochemical processes. Alternatively, climate model simulations provide a full-field view, but may predict unrealistic climate states or states not faithful to proxy records. Here, we use data assimilation - combining climate proxy records with a theoretical understanding from climate models - to produce field reconstructions of the LGM that leverage the information from both data and models. To date, data assimilation has mainly been used to produce reconstructions of climate fields through the last millennium. We expand this approach in order to produce a climate fields for the Last Glacial Maximum using an ensemble Kalman filter assimilation. Ensemble samples were formed from output from multiple models including CCSM3, CESM2.1, and HadCM3. These model simulations are combined with marine sediment proxies for upper ocean temperature (TEX86, UK'37, Mg/Ca and δ18O of foraminifera), utilizing forward models based on a newly developed suite of Bayesian proxy system models. We also incorporate age model and radiocarbon reservoir uncertainty into our reconstructions using Bayesian age modeling software. The resulting fields show familiar patterns based on comparison with previous proxy-based reconstructions, but additionally reveal novel patterns of large-scale shifts in ocean-atmosphere dynamics, as the surface temperature data inform upon atmospheric circulation and precipitation patterns.

Chapter 3 - Large-scale patterns of forest fire occurrence in the conterminous United States and Alaska, 2011.

Treesearch

Kevin M. Potter

2014-01-01

Free-burning fire has been a constant ecological presence on the American landscape, the expression of which has changed as new climates, peoples, and land uses have become predominant (Pyne 2010). It is an important ecological mechanism that shapes the distributions of species, maintains the structure and function of fire-prone communities, and is a significant...

Storm-tracks interannual variability and large-scale climate modes

NASA Astrophysics Data System (ADS)

Liberato, Margarida L. R.; Trigo, Isabel F.; Trigo, Ricardo M.

2013-04-01

In this study we focus on the interannual variability and observed changes in northern hemisphere mid-latitude storm-tracks and relate them to large scale atmospheric circulation variability modes. Extratropical storminess, cyclones dominant paths, frequency and intensity have long been the object of climatological studies. The analysis of storm characteristics and historical trends presented here is based on the cyclone detecting and tracking algorithm first developed for the Mediterranean region (Trigo et al. 1999) and recently extended to a larger Euro-Atlantic region (Trigo 2006). The objective methodology, which identifies and follows individual lows as minima in SLP fields, fulfilling a set of conditions regarding the central pressure and the pressure gradient, is applied to the northern hemisphere 6-hourly geopotential data at 1000 hPa from the 20th Century Reanalyses (20CRv2) project and from reanalyses datasets provided by the European Centre for Medium-Range Weather Forecasts (ECMWF): ERA-40 and ERA Interim reanalyses. First, we assess the interannual variability and cyclone frequency trends for each of the datasets, for the 20th century and for the period between 1958 and 2002 using the highest spatial resolution available (1.125° x 1.125°) from the ERA-40 data. Results show that winter variability of storm paths, cyclone frequency and travel times is in agreement with the reported variability in a number of large-scale climate patterns (including the North Atlantic Oscillation, the East Atlantic Pattern and the Scandinavian Pattern). In addition, three storm-track databases are built spanning the common available extended winter seasons from October 1979 to March 2002. Although relatively short, this common period allows a comparison of systems represented in reanalyses datasets with distinct horizontal resolutions. This exercise is mostly focused on the key areas of cyclogenesis and cyclolysis and main cyclone characteristics over the northern hemisphere. Trigo IF., TD Davies, GR Bigg (1999) Objective climatology of cyclones in the Mediterranean region. J. Climate 12: 1685-1696. Trigo IF (2006) Climatology and interannual variability of storm-tracks in the Euro-Atlantic sector: a comparison between ERA-40 and NCEP/NCAR reanalyses. Clim. Dyn. 26: 127-143.

Climate Change: Vulnerability Assessment for Water Resources Management in South Florida

NASA Astrophysics Data System (ADS)

Obeysekera, J.

2008-12-01

South Florida is home to over 7 million people and its population is projected to increase to over 10 million people by 2025 and possibly 12-15 million by 2050. Through Federal/State/Local partnerships, the Greater Everglades is being restored under numerous water resources management projects requiring large investments of time and money. Recent climate change projections as published in the most recent report of the Intergovernmental Panel on Climate Change (IPCC) have the potential to cause significant impacts on flood control and water supply functions of water resources management, and on existing and future ecosystem restoration projects in south Florida. More recent estimates of sea level rise for south Florida are much higher than those in the IPCC report and if such projections become a reality, consequences may be disastrous. It is extremely important to understand the extent of global projections for various emission scenarios, their ability to represent the climatology of local regions, and the potential vulnerabilities of both climate change and sea level rise on water resources management. Implications of natural variability of the climate and teleconnections in South Florida are understood with a reasonable degree of certainty. Recent emphasis on climate change due to human-induced impacts have generated new questions on the sustainability of coastal environments with a heightened concern for the success of large-scale environmental projects throughout South Florida. An assessment of the precipitation projections of the General Circulation Models (GCMs) shows that their ability to represent the landscape of Florida and predict historical climate patterns may be limited. In order to understand the vulnerability of the water management system in south Florida under changing precipitation and evapotranspiration patterns, a sensitivity analysis using a regional-scale, hydrologic simulation model was conducted. The results show the vulnerability of projected climate change on water supply for all water sectors including the environment, and the potential impact of sea level rise on coastal regions. Questions on the potential impacts of climate change including sea level rise need to be investigated along with the uncertainties of projections to provide critical information for decision making on the planned infrastructure and operational changes in south Florida.

Changes in the Winter-Time Storminess over the North Atlantic, Associated with the 1.5°C and 2°C Levels of Global Warming.

NASA Astrophysics Data System (ADS)

Barcikowska, M. J.; Weaver, S. J.; Feser, F.; Schenk, F.

2017-12-01

This study investigates the changes in extreme winter-time weather conditions over the NH midlatitudes. These conditions are to a large degree caused by extratropical storms, often associated with very intense and hazardous precipitation and wind. Although the skill of CMIP5 models in capturing these extremes is improved when compared to the previous generations, the spatial and temporal resolution of the models still remains a primary reason for the deficiencies. Therefore, many features of the storms projected for the future remain inconsistent. Here we are using the high-res horizontal (0.25° lat x lon) and temporal (3hr) output of the HAPPI experiment. This output facilitates not only an implicit extraction of storm tracks but also an analysis of the storm intensity, in terms of their maximum wind and rainfall, at subdaily time-scales. The analysis of simulated present climate shows an improved spatial pattern of large-scale circulation over North America and Europe, as compared to the CMIP5-generation models, and consequently a reduced zonal bias in storm tracks pattern. The information provided at subdaily time scale provides much more realistic representation of the magnitude of the extremes. These advances significantly contribute to our understanding of differential climate impacts between 1.5°C and 2°C levels of global warming. The spatial pattern of the north-eastward shift of storm tracks, derived from the recent CMIP5 future projections, is remarkably refined here. For example, increasing storminess expands towards Scandinavia, and not towards the north-central Europe. Derived spatial features of the storm intensity, e.g. increase in wind and precipitation on the west coasts of both the British Isles and Scandinavia underlines the relevancy of the results for the local communities and potential climate change adaptation initiatives.

HISTORICAL CHANGES IN GLOBAL SCALE CIRCULATION PATTERNS, MID-ATLANTIC CLIMATE STREAM FLOW AND NUTRIENT FLUXES TO THE CHESAPEAKE BAY

EPA Science Inventory

The rate of change in Northern Hemisphere temperature in the past century strongly suggests that we are now in a period of rapid global climate change. Also, the climate in the mid-Atlantic is quite sensitive to larger scale climate variation, which affects the frequency and seve...

Observations of Local Positive Low Cloud Feedback Patterns and Their Role in Internal Variability and Climate Sensitivity

NASA Astrophysics Data System (ADS)

Yuan, Tianle; Oreopoulos, Lazaros; Platnick, Steven E.; Meyer, Kerry

2018-05-01

Modeling studies have shown that cloud feedbacks are sensitive to the spatial pattern of sea surface temperature (SST) anomalies, while cloud feedbacks themselves strongly influence the magnitude of SST anomalies. Observational counterparts to such patterned interactions are still needed. Here we show that distinct large-scale patterns of SST and low-cloud cover (LCC) emerge naturally from objective analyses of observations and demonstrate their close coupling in a positive local SST-LCC feedback loop that may be important for both internal variability and climate change. The two patterns that explain the maximum amount of covariance between SST and LCC correspond to the Interdecadal Pacific Oscillation and the Atlantic Multidecadal Oscillation, leading modes of multidecadal internal variability. Spatial patterns and time series of SST and LCC anomalies associated with both modes point to a strong positive local SST-LCC feedback. In many current climate models, our analyses suggest that SST-LCC feedback strength is too weak compared to observations. Modeled local SST-LCC feedback strength affects simulated internal variability so that stronger feedback produces more intense and more realistic patterns of internal variability. To the extent that the physics of the local positive SST-LCC feedback inferred from observed climate variability applies to future greenhouse warming, we anticipate significant amount of delayed warming because of SST-LCC feedback when anthropogenic SST warming eventually overwhelm the effects of internal variability that may mute anthropogenic warming over parts of the ocean. We postulate that many climate models may be underestimating both future warming and the magnitude of modeled internal variability because of their weak SST-LCC feedback.

Continental-level population differentiation and environmental adaptation in the mushroom Suillus brevipes

PubMed Central

Branco, Sara; Bi, Ke; Liao, Hui-Ling; Gladieux, Pierre; Badouin, Hélène; Ellison, Christopher E.; Nguyen, Nhu H.; Vilgalys, Rytas; Peay, Kabir G.; Taylor, John W.; Bruns, Thomas D.

2016-01-01

Recent advancements in sequencing technology allowed researchers to better address the patterns and mechanisms involved in microbial environmental adaptation at large spatial scales. Here we investigated the genomic basis of adaptation to climate at the continental scale in Suillus brevipes, an ectomycorrhizal fungus symbiotically associated with the roots of pine trees. We used genomic data from 55 individuals in seven locations across North America to perform genome scans to detect signatures of positive selection and assess whether temperature and precipitation were associated with genetic differentiation. We found that S. brevipes exhibited overall strong population differentiation, with potential admixture in Canadian populations. This species also displayed genomic signatures of positive selection as well as genomic sites significantly associated with distinct climatic regimes and abiotic environmental parameters. These genomic regions included genes involved in transmembrane transport of substances and helicase activity potentially involved in cold stress response. Our study sheds light on large-scale environmental adaptation in fungi by identifying putative adaptive genes and providing a framework to further investigate the genetic basis of fungal adaptation. PMID:27761941

North American Extreme Temperature Events and Related Large Scale Meteorological Patterns: A Review of Statistical Methods, Dynamics, Modeling, and Trends

NASA Technical Reports Server (NTRS)

Grotjahn, Richard; Black, Robert; Leung, Ruby; Wehner, Michael F.; Barlow, Mathew; Bosilovich, Michael G.; Gershunov, Alexander; Gutowski, William J., Jr.; Gyakum, John R.; Katz, Richard W.;

Progressive Mid-latitude Afforestation: Local and Remote Climate Impacts in the Framework of Two Coupled Earth System Models

NASA Astrophysics Data System (ADS)

Lague, Marysa

Vegetation influences the atmosphere in complex and non-linear ways, such that large-scale changes in vegetation cover can drive changes in climate on both local and global scales. Large-scale land surface changes have been shown to introduce excess energy to one hemisphere, causing a shift in atmospheric circulation on a global scale. However, past work has not quantified how the climate response scales with the area of vegetation. Here, we systematically evaluate the response of climate to linearly increasing the area of forest cover over the northern mid-latitudes. We show that the magnitude of afforestation of the northern mid-latitudes determines the climate response in a non-linear fashion, and identify a threshold in vegetation-induced cloud feedbacks - a concept not previously addressed by large-scale vegetation manipulation experiments. Small increases in tree cover drive compensating cloud feedbacks, while latent heat fluxes reach a threshold after sufficiently large increases in tree cover, causing the troposphere to warm and dry, subsequently reducing cloud cover. Increased absorption of solar radiation at the surface is driven by both surface albedo changes and cloud feedbacks. We identify how vegetation-induced changes in cloud cover further feedback on changes in the global energy balance. We also show how atmospheric cross-equatorial energy transport changes as the area of afforestation is incrementally increased (a relationship which has not previously been demonstrated). This work demonstrates that while some climate effects (such as energy transport) of large scale mid-latitude afforestation scale roughly linearly across a wide range of afforestation areas, others (such as the local partitioning of the surface energy budget) are non-linear, and sensitive to the particular magnitude of mid-latitude forcing. Our results highlight the importance of considering both local and remote climate responses to large-scale vegetation change, and explore the scaling relationship between changes in vegetation cover and the resulting climate impacts.

New Statistical Model for Variability of Aerosol Optical Thickness: Theory and Application to MODIS Data over Ocean

NASA Technical Reports Server (NTRS)

Alexandrov, Mikhail Dmitrievic; Geogdzhayev, Igor V.; Tsigaridis, Konstantinos; Marshak, Alexander; Levy, Robert; Cairns, Brian

2016-01-01

A novel model for the variability in aerosol optical thickness (AOT) is presented. This model is based on the consideration of AOT fields as realizations of a stochastic process, that is the exponent of an underlying Gaussian process with a specific autocorrelation function. In this approach AOT fields have lognormal PDFs and structure functions having the correct asymptotic behavior at large scales. The latter is an advantage compared with fractal (scale-invariant) approaches. The simple analytical form of the structure function in the proposed model facilitates its use for the parameterization of AOT statistics derived from remote sensing data. The new approach is illustrated using a month-long global MODIS AOT dataset (over ocean) with 10 km resolution. It was used to compute AOT statistics for sample cells forming a grid with 5deg spacing. The observed shapes of the structure functions indicated that in a large number of cases the AOT variability is split into two regimes that exhibit different patterns of behavior: small-scale stationary processes and trends reflecting variations at larger scales. The small-scale patterns are suggested to be generated by local aerosols within the marine boundary layer, while the large-scale trends are indicative of elevated aerosols transported from remote continental sources. This assumption is evaluated by comparison of the geographical distributions of these patterns derived from MODIS data with those obtained from the GISS GCM. This study shows considerable potential to enhance comparisons between remote sensing datasets and climate models beyond regional mean AOTs.

On the limitations of General Circulation Climate Models

NASA Technical Reports Server (NTRS)

Stone, Peter H.; Risbey, James S.

1990-01-01

General Circulation Models (GCMs) by definition calculate large-scale dynamical and thermodynamical processes and their associated feedbacks from first principles. This aspect of GCMs is widely believed to give them an advantage in simulating global scale climate changes as compared to simpler models which do not calculate the large-scale processes from first principles. However, it is pointed out that the meridional transports of heat simulated GCMs used in climate change experiments differ from observational analyses and from other GCMs by as much as a factor of two. It is also demonstrated that GCM simulations of the large scale transports of heat are sensitive to the (uncertain) subgrid scale parameterizations. This leads to the question whether current GCMs are in fact superior to simpler models for simulating temperature changes associated with global scale climate change.

Dying like rabbits: general determinants of spatio-temporal variability in survival.

PubMed

Tablado, Zulima; Revilla, Eloy; Palomares, Francisco

2012-01-01

1. Identifying general patterns of how and why survival rates vary across space and time is necessary to truly understand population dynamics of a species. However, this is not an easy task given the complexity and interactions of processes involved, and the interpopulation differences in main survival determinants. 2. Here, using European rabbits (Oryctolagus cuniculus) as a model and information from local studies, we investigated whether we could make inferences about trends and drivers of survival of a species that are generalizable to large spatio-temporal scales. To do this, we first focused on overall survival and then examined cause-specific mortalities, mainly predation and diseases, which may lead to those patterns. 3. Our results show that within the large-scale variability in rabbit survival, there exist general patterns that are explained by the integration of factors previously known to be important at the local level (i.e. age, climate, diseases, predation or density dependence). We found that both inter- and intrastudy survival rates increased in magnitude and decreased in variability as rabbits grow old, although this tendency was less pronounced in populations with epidemic diseases. Some causes leading to these higher mortalities in young rabbits could be the stronger effect of rainfall at those ages, as well as, other death sources like malnutrition or infanticide. 4. Predation is also greater for newborns and juveniles, especially in population without diseases. Apart from the effect of diseases, predation patterns also depended on factors, such as, density, season, and type and density of predators. Finally, we observed that infectious diseases also showed general relationships with climate, breeding (i.e. new susceptible rabbits) and age, although the association type varied between myxomatosis and rabbit haemorrhagic disease. 5. In conclusion, large-scale patterns of spatio-temporal variability in rabbit survival emerge from the combination of different factors that interrelate both directly and through density dependence. This highlights the importance of performing more comprehensive studies to reveal combined effects and complex relationships that help us to better understand the mechanisms underlying population dynamics. © 2011 The Authors. Journal of Animal Ecology © 2011 British Ecological Society.

Broad-Scale Patterns of Late Jurassic Dinosaur Paleoecology

PubMed Central

Noto, Christopher R.; Grossman, Ari

2010-01-01

Background There have been numerous studies on dinosaur biogeographic distribution patterns. However, these distribution data have not yet been applied to ecological questions. Ecological studies of dinosaurs have tended to focus on reconstructing individual taxa, usually through comparisons to modern analogs. Fewer studies have sought to determine if the ecological structure of fossil assemblages is preserved and, if so, how dinosaur communities varied. Climate is a major component driving differences between communities. If the ecological structure of a fossil locality is preserved, we expect that dinosaur assemblages from similar environments will share a similar ecological structure. Methodology/Principal Findings This study applies Ecological Structure Analysis (ESA) to a dataset of 100+ dinosaur taxa arranged into twelve composite fossil assemblages from around the world. Each assemblage was assigned a climate zone (biome) based on its location. Dinosaur taxa were placed into ecomorphological categories. The proportion of each category creates an ecological profile for the assemblage, which were compared using cluster and principal components analyses. Assemblages grouped according to biome, with most coming from arid or semi-arid/seasonal climates. Differences between assemblages are tied to the proportion of large high-browsing vs. small ground-foraging herbivores, which separates arid from semi-arid and moister environments, respectively. However, the effects of historical, taphonomic, and other environmental factors are still evident. Conclusions/Significance This study is the first to show that the general ecological structure of Late Jurassic dinosaur assemblages is preserved at large scales and can be assessed quantitatively. Despite a broad similarity of climatic conditions, a degree of ecological variation is observed between assemblages, from arid to moist. Taxonomic differences between Asia and the other regions demonstrate at least one case of ecosystem convergence. The proportion of different ecomorphs, which reflects the prevailing climatic and environmental conditions present during fossil deposition, may therefore be used to differentiate Late Jurassic dinosaur fossil assemblages. This method is broadly applicable to different taxa and times, allowing one to address questions of evolutionary, biogeographic, and climatic importance. PMID:20838442

Broad-scale patterns of late jurassic dinosaur paleoecology.

PubMed

Noto, Christopher R; Grossman, Ari

2010-09-03

There have been numerous studies on dinosaur biogeographic distribution patterns. However, these distribution data have not yet been applied to ecological questions. Ecological studies of dinosaurs have tended to focus on reconstructing individual taxa, usually through comparisons to modern analogs. Fewer studies have sought to determine if the ecological structure of fossil assemblages is preserved and, if so, how dinosaur communities varied. Climate is a major component driving differences between communities. If the ecological structure of a fossil locality is preserved, we expect that dinosaur assemblages from similar environments will share a similar ecological structure. This study applies Ecological Structure Analysis (ESA) to a dataset of 100+ dinosaur taxa arranged into twelve composite fossil assemblages from around the world. Each assemblage was assigned a climate zone (biome) based on its location. Dinosaur taxa were placed into ecomorphological categories. The proportion of each category creates an ecological profile for the assemblage, which were compared using cluster and principal components analyses. Assemblages grouped according to biome, with most coming from arid or semi-arid/seasonal climates. Differences between assemblages are tied to the proportion of large high-browsing vs. small ground-foraging herbivores, which separates arid from semi-arid and moister environments, respectively. However, the effects of historical, taphonomic, and other environmental factors are still evident. This study is the first to show that the general ecological structure of Late Jurassic dinosaur assemblages is preserved at large scales and can be assessed quantitatively. Despite a broad similarity of climatic conditions, a degree of ecological variation is observed between assemblages, from arid to moist. Taxonomic differences between Asia and the other regions demonstrate at least one case of ecosystem convergence. The proportion of different ecomorphs, which reflects the prevailing climatic and environmental conditions present during fossil deposition, may therefore be used to differentiate Late Jurassic dinosaur fossil assemblages. This method is broadly applicable to different taxa and times, allowing one to address questions of evolutionary, biogeographic, and climatic importance.

Global Climate Models Intercomparison of Anthropogenic Aerosols Effects on Regional Climate over North Pacific

NASA Astrophysics Data System (ADS)

Hu, J.; Zhang, R.; Wang, Y.; Ming, Y.; Lin, Y.; Pan, B.

2015-12-01

Aerosols can alter atmospheric radiation and cloud physics, which further exert impacts on weather and global climate. With the development and industrialization of the developing Asian countries, anthropogenic aerosols have received considerable attentions and remain to be the largest uncertainty in the climate projection. Here we assess the performance of two stat-of-art global climate models (National Center for Atmospheric Research-Community Atmosphere Model 5 (CAM5) and Geophysical Fluid Dynamics Laboratory Atmosphere Model 3 (AM3)) in simulating the impacts of anthropogenic aerosols on North Pacific storm track region. By contrasting two aerosol scenarios, i.e. present day (PD) and pre-industrial (PI), both models show aerosol optical depth (AOD) enhanced by about 22%, with CAM5 AOD 40% lower in magnitude due to the long range transport of anthropogenic aerosols. Aerosol effects on the ice water path (IWP), stratiform precipitation, convergence and convection strengths in the two models are distinctive in patterns and magnitudes. AM3 shows qualitatively good agreement with long-term satellite observations, while CAM5 overestimates convection and liquid water path resulting in an underestimation of large-scale precipitation and IWP. Due to coarse resolution and parameterization in convection schemes, both models' performance on convection needs to be improved. Aerosols performance on large-scale circulation and radiative budget are also examined in this study.

Climate Induced Changes in Global-Scale Litter Decomposition and Long-term Relationships with Net Primary Productivity

NASA Astrophysics Data System (ADS)

Silver, W. L.; Smith, W. K.; Parton, W. J.; Wieder, W. R.; DelGrosso, S.

2016-12-01

Surface litter decomposition represents the largest annual carbon (C) flux to the atmosphere from terrestrial ecosystems (Esser et al. 1982). Using broad-scale long-term datasets we show that litter decomposition rates are largely predicted by a climate-decomposition index (CDI) at a global scale, and use CDI to estimate patterns in litter decomposition over the 110 years from 1901-2011. There were rapid changes in CDI over the last 30 y of the record amounting to a 4.3% increase globally. Boreal forests (+13.9%), tundra (+12.2%), savannas (+5.3%), and temperate (+2.4%) and tropical (+2.1%) forests all experienced accelerated decomposition. During the same period, most biomes experienced corresponding increases in a primary production index (PPI) estimated from an ensemble of long-term, observation-based productivity indices. The percent increase in PPI was only half that of decomposition globally. Tropical forests and savannas showed no increase in PPI to offset greater decomposition rates. Temperature-limited ecosystems (i.e., tundra, boreal, and temperate forests) showed the greatest differences between CDI and PPI, highlighting potentially large decoupling of C fluxes in these biomes. Precipitation and actual evapotranspiration were the best climate predictors of CDI at a global scale, while PPI varied consistently with actual evapotranspiration. As expected, temperature was the best predictor of PPI across temperature limited ecosystems. Our results show that climate change could be leading to a decoupling of C uptake and losses, potentially resulting in lower C storage in northern latitudes, temperate and tropical forests, and savannas.

Putting Beta-Diversity on the Map: Broad-Scale Congruence and Coincidence in the Extremes

PubMed Central

McKnight, Meghan W; White, Peter S; McDonald, Robert I; Lamoreux, John F; Sechrest, Wes; Ridgely, Robert S; Stuart, Simon N

2007-01-01

Beta-diversity, the change in species composition between places, is a critical but poorly understood component of biological diversity. Patterns of beta-diversity provide information central to many ecological and evolutionary questions, as well as to conservation planning. Yet beta-diversity is rarely studied across large extents, and the degree of similarity of patterns among taxa at such scales remains untested. To our knowledge, this is the first broad-scale analysis of cross-taxon congruence in beta-diversity, and introduces a new method to map beta-diversity continuously across regions. Congruence between amphibian, bird, and mammal beta-diversity in the Western Hemisphere varies with both geographic location and spatial extent. We demonstrate that areas of high beta-diversity for the three taxa largely coincide, but areas of low beta-diversity exhibit little overlap. These findings suggest that similar processes lead to high levels of differentiation in amphibian, bird, and mammal assemblages, while the ecological and biogeographic factors influencing homogeneity in vertebrate assemblages vary. Knowledge of beta-diversity congruence can help formulate hypotheses about the mechanisms governing regional diversity patterns and should inform conservation, especially as threat from global climate change increases. PMID:17927449

Weak hydrological sensitivity to temperature change over land, independent of climate forcing

NASA Astrophysics Data System (ADS)

Samset, Bjorn H.

2017-04-01

As the global surface temperature changes, so will patterns and rates of precipitation. Theoretically, these changes can be understood in terms of changes to the energy balance of the atmosphere, caused by introducing drivers of climate change such as greenhouse gases, aerosols and altered insolation. Climate models, however, disagree strongly in their prediction of precipitation changes, both for historical and future emission pathways, and per degree of surface warming in idealized experiments. The latter value, often termed the apparent hydrological sensitivity, has also been found to differ substantially between climate drivers. Here, we present the global and regional hydrological sensitivity (HS) to surface temperature changes, for perturbations to CO2, CH4, sulfate and black carbon concentrations, and solar irradiance. Based on results from 10 climate models participating in the Precipitation Driver and Response Model Intercomparison Project (PDRMIP), we show how modeled global mean precipitation increases by 2-3 % per kelvin of global mean surface warming, independent of driver, when the effects of rapid adjustments are removed. Previously reported differences in response between drivers are therefore mainly ascribable to rapid atmospheric adjustment processes. All models show a sharp contrast in behavior over land and over ocean, with a strong surface temperature driven (slow) ocean HS of 3-5 %/K, while the slow land HS is only 0-2 %/K. Separating the response into convective and large-scale cloud processes, we find larger inter-model differences, in particular over land regions. Large-scale precipitation changes are most relevant at high latitudes, while the equatorial HS is dominated by convective precipitation changes. Black carbon stands out as the driver with the largest inter-model slow HS variability, and also the strongest contrast between a weak land and strong sea response. Convective precipitation in the Arctic and large scale precipitation around the Equator are found to be topics where further model investigations and observational constraints may provide rapid improvements to modelling of the precipitation response to future, CO2 dominated climate change.

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.

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.

Large-scale climatic anomalies affect marine predator foraging behaviour and demography.

PubMed

Bost, Charles A; Cotté, Cedric; Terray, Pascal; Barbraud, Christophe; Bon, Cécile; Delord, Karine; Gimenez, Olivier; Handrich, Yves; Naito, Yasuhiko; Guinet, Christophe; Weimerskirch, Henri

2015-10-27

Determining the links between the behavioural and population responses of wild species to environmental variations is critical for understanding the impact of climate variability on ecosystems. Using long-term data sets, we show how large-scale climatic anomalies in the Southern Hemisphere affect the foraging behaviour and population dynamics of a key marine predator, the king penguin. When large-scale subtropical dipole events occur simultaneously in both subtropical Southern Indian and Atlantic Oceans, they generate tropical anomalies that shift the foraging zone southward. Consequently the distances that penguins foraged from the colony and their feeding depths increased and the population size decreased. This represents an example of a robust and fast impact of large-scale climatic anomalies affecting a marine predator through changes in its at-sea behaviour and demography, despite lack of information on prey availability. Our results highlight a possible behavioural mechanism through which climate variability may affect population processes.

Large-scale climatic anomalies affect marine predator foraging behaviour and demography

NASA Astrophysics Data System (ADS)

Bost, Charles A.; Cotté, Cedric; Terray, Pascal; Barbraud, Christophe; Bon, Cécile; Delord, Karine; Gimenez, Olivier; Handrich, Yves; Naito, Yasuhiko; Guinet, Christophe; Weimerskirch, Henri

2015-10-01

Determining the links between the behavioural and population responses of wild species to environmental variations is critical for understanding the impact of climate variability on ecosystems. Using long-term data sets, we show how large-scale climatic anomalies in the Southern Hemisphere affect the foraging behaviour and population dynamics of a key marine predator, the king penguin. When large-scale subtropical dipole events occur simultaneously in both subtropical Southern Indian and Atlantic Oceans, they generate tropical anomalies that shift the foraging zone southward. Consequently the distances that penguins foraged from the colony and their feeding depths increased and the population size decreased. This represents an example of a robust and fast impact of large-scale climatic anomalies affecting a marine predator through changes in its at-sea behaviour and demography, despite lack of information on prey availability. Our results highlight a possible behavioural mechanism through which climate variability may affect population processes.

Interannual variations in fire weather, fire extent, and synoptic-scale circulation patterns in northern California and Oregon

Treesearch

Valerie Trouet; Alan H. Taylor; Andrew M. Carleton; Carl N. Skinner

2009-01-01

The Mediterranean climate region on the west coast of the United States is characterized by wet winters and dry summers, and by high fire activity. The importance of synoptic-scale circulation patterns (ENSO, PDO, PNA) on fire-climate interactions is evident in contemporary fire data sets and in pre-Euroamerican tree-ring-based fire records. We investigated how...

Investigating links between climate and orography in the central Andes: Coupling erosion and precipitation using a physical-statistical model

NASA Astrophysics Data System (ADS)

Lowman, Lauren E. L.; Barros, Ana P.

2014-06-01

Prior studies evaluated the interplay between climate and orography by investigating the sensitivity of relief to precipitation using the stream power erosion law (SPEL) for specified erosion rates. Here we address the inverse problem, inferring realistic spatial distributions of erosion rates for present-day topography and contemporaneous climate forcing. In the central Andes, similarities in the altitudinal distribution and density of first-order stream outlets and precipitation suggest a direct link between climate and fluvial erosion. Erosion rates are estimated with a Bayesian physical-statistical model based on the SPEL applied at spatial scales that capture joint hydrogeomorphic and hydrometeorological patterns within five river basins and one intermontane basin in Peru and Bolivia. Topographic slope and area data were generated from a high-resolution (˜90 m) digital elevation map, and mean annual precipitation was derived from 14 years of Tropical Rainfall Measuring Mission 3B42v.7 product and adjusted with rain gauge data. Estimated decadal-scale erosion rates vary between 0.68 and 11.59 mm/yr, with basin averages of 2.1-8.5 mm/yr. Even accounting for uncertainty in precipitation and simplifying assumptions, these values are 1-2 orders of magnitude larger than most millennial and million year timescale estimates in the central Andes, using various geological dating techniques (e.g., thermochronology and cosmogenic nuclides), but they are consistent with other decadal-scale estimates using landslide mapping and sediment flux observations. The results also reveal a pattern of spatially dependent erosion consistent with basin hypsometry. The modeling framework provides a means of remotely estimating erosion rates and associated uncertainties under current climate conditions over large regions. 2014. American Geophysical Union. All Rights Reserved.

Predicting Plant Diversity Patterns in Madagascar: Understanding the Effects of Climate and Land Cover Change in a Biodiversity Hotspot

PubMed Central

Brown, Kerry A.; Parks, Katherine E.; Bethell, Colin A.; Johnson, Steig E.; Mulligan, Mark

2015-01-01

Climate and land cover change are driving a major reorganization of terrestrial biotic communities in tropical ecosystems. In an effort to understand how biodiversity patterns in the tropics will respond to individual and combined effects of these two drivers of environmental change, we use species distribution models (SDMs) calibrated for recent climate and land cover variables and projected to future scenarios to predict changes in diversity patterns in Madagascar. We collected occurrence records for 828 plant genera and 2186 plant species. We developed three scenarios, (i.e., climate only, land cover only and combined climate-land cover) based on recent and future climate and land cover variables. We used this modelling framework to investigate how the impacts of changes to climate and land cover influenced biodiversity across ecoregions and elevation bands. There were large-scale climate- and land cover-driven changes in plant biodiversity across Madagascar, including both losses and gains in diversity. The sharpest declines in biodiversity were projected for the eastern escarpment and high elevation ecosystems. Sharp declines in diversity were driven by the combined climate-land cover scenarios; however, there were subtle, region-specific differences in model outputs for each scenario, where certain regions experienced relatively higher species loss under climate or land cover only models. We strongly caution that predicted future gains in plant diversity will depend on the development and maintenance of dispersal pathways that connect current and future suitable habitats. The forecast for Madagascar’s plant diversity in the face of future environmental change is worrying: regional diversity will continue to decrease in response to the combined effects of climate and land cover change, with habitats such as ericoid thickets and eastern lowland and sub-humid forests particularly vulnerable into the future. PMID:25856241

Predicting plant diversity patterns in Madagascar: understanding the effects of climate and land cover change in a biodiversity hotspot.

PubMed

Brown, Kerry A; Parks, Katherine E; Bethell, Colin A; Johnson, Steig E; Mulligan, Mark

2015-01-01

Climate and land cover change are driving a major reorganization of terrestrial biotic communities in tropical ecosystems. In an effort to understand how biodiversity patterns in the tropics will respond to individual and combined effects of these two drivers of environmental change, we use species distribution models (SDMs) calibrated for recent climate and land cover variables and projected to future scenarios to predict changes in diversity patterns in Madagascar. We collected occurrence records for 828 plant genera and 2186 plant species. We developed three scenarios, (i.e., climate only, land cover only and combined climate-land cover) based on recent and future climate and land cover variables. We used this modelling framework to investigate how the impacts of changes to climate and land cover influenced biodiversity across ecoregions and elevation bands. There were large-scale climate- and land cover-driven changes in plant biodiversity across Madagascar, including both losses and gains in diversity. The sharpest declines in biodiversity were projected for the eastern escarpment and high elevation ecosystems. Sharp declines in diversity were driven by the combined climate-land cover scenarios; however, there were subtle, region-specific differences in model outputs for each scenario, where certain regions experienced relatively higher species loss under climate or land cover only models. We strongly caution that predicted future gains in plant diversity will depend on the development and maintenance of dispersal pathways that connect current and future suitable habitats. The forecast for Madagascar's plant diversity in the face of future environmental change is worrying: regional diversity will continue to decrease in response to the combined effects of climate and land cover change, with habitats such as ericoid thickets and eastern lowland and sub-humid forests particularly vulnerable into the future.

Trees tell of past climates: but are they speaking less clearly today?

PubMed Central

Briffa, K. R.

1998-01-01

The annual growth of trees, as represented by a variety of ring-width, densitometric, or chemical parameters, represents a combined record of different environmental forcings, one of which is climate. Along with climate, relatively large-scale positive growth influences such as hypothesized 'fertilization' due to increased levels of atmospheric carbon dioxide or various nitrogenous compounds, or possibly deleterious effects of 'acid rain' or increased ultra-violet radiation, might all be expected to exert some influence on recent tree growth rates. Inferring the details of past climate variability from tree-ring data remains a largely empirical exercise, but one that goes hand-in-hand with the development of techniques that seek to identify and isolate the confounding influence of local and larger-scale non-climatic factors. By judicious sampling, and the use of rigorous statistical procedures, dendroclimatology has provided unique insight into the nature of past climate variability, but most significantly at interannual, decadal, and centennial timescales. Here, examples are shown that illustrate the reconstruction of annually resolved patterns of past summer temperature around the Northern Hemisphere, as well as some more localized reconstructions, but ones which span 1000 years or more. These data provide the means of exploring the possible role of different climate forcings; for example, they provide evidence of the large-scale effects of explosive volcanic eruptions on regional and hemispheric temperatures during the last 400 years. However, a dramatic change in the sensitivity of hemispheric tree-growth to temperature forcing has become apparent during recent decades, and there is additional evidence of major tree-growth (and hence, probably, ecosystem biomass) increases in the northern boreal forests, most clearly over the last century. These possibly anthropogenically related changes in the ecology of tree growth have important implications for modelling future atmospheric CO2 concentrations. Also, where dendroclimatology is concerned to reconstruct longer (increasingly above centennial) temperature histories, such alterations of 'normal' (pre-industrial) tree-growth rates and climate-growth relationships must be accounted for in our attempts to translate the evidence of past tree growth changes.

The Use of Principal Components in Long-Range Forecasting

NASA Astrophysics Data System (ADS)

Chern, Jonq-Gong

Large-scale modes of the global sea surface temperatures and the Northern Hemisphere tropospheric circulation are described by principal component analysis. The first and the second SST components well describe the El Nino episodes, and the El Nino index (ENI), suggested in this study, is consistent with the winter Southern Oscillation index (SOI), where this ENI is a composite component of the weighted first and second SST components. The large-scale interactive modes of the coupling ocean-atmosphere system are identified by cross-correlation analysis The result shows that the first SST component is strongly correlated with the first component of geopotential height in lead time of 6 months. In the El Nino-Southern Oscillation (ENSO) evolution, the El Nino mode strongly influences the winter tropospheric circulation in the mid -latitudes for up to three leading seasons. The regional long-range variation of climate is investigated with these major components of the SST and the tropospheric circulation. In the mid-latitude, the climate of the central United States shows a weak linkage with these large-scale circulations, and the climate of the western United States appears to be consistently associated with the ENSO modes. These El Nino modes also show a dominant influence on Eastern Asia as evidenced in Taiwan Mei-Yu patterns. Possible regional long-range forecasting schemes, utilizing the complementary characteristics of the winter El Nino mode and SST anomalies, are examined with the Taiwan Mei-Yu.

Updated Global Patterns of Drought and Heat-Induced Forest Die-off, and Ecohydrological Feedbacks

NASA Astrophysics Data System (ADS)

Allen, C. D.

2011-12-01

Ongoing climate changes - particularly increases in mean temperatures as well as frequencies, durations, and severities of extreme drought and heat - can amplify tree physiological stress and thereby drive increases in both background tree mortality rates and episodes of rapid, broad-scale forest die-off. Updates are presented to a recent global synthesis of documented tree mortality episodes attributed to drought and/or heat, further expanding the documented spatial distribution and demonstrating the vulnerability of all major forest types from tropical moist forests and savannas to temperate and boreal forests. Given that anthropogenic climate change is projected to drive substantial increases in both mean temperatures and the frequency/duration/severity of extreme drought and heat in many regions, recent episodes of broad-scale drought-induced forest mortality may reflect increasing global risks of forest die-off, even in environments not normally considered water-limited. Since vegetation cover patterns are closely and interactively linked with ecosystem water fluxes, episodes of massive forest die-off can be expected to significantly affect ecohydrological patterns and processes, ranging from runoff and erosion to evaporation and transpiration, often with nonlinear threshold responses expected. Diverse examples of such feedbacks between climate-induced forest mortality and ecohydrology are presented, ranging from detailed observations of linked changes in vegetation, runoff, and erosion in response to forest mortality in the southwestern US to Western Australia and Amazonian rainforest water cycling. Current research efforts to address the large knowledge gaps that at present hinder our ability to predict climate-induced forest mortality and associated ecohydrological responses are discussed.

Recent changes in county-level corn yield variability in the United States from observations and crop models

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

Leng, Guoyong

The United States is responsible for 35% and 60% of global corn supply and exports. Enhanced supply stability through a reduction in the year-to-year variability of US corn yield would greatly benefit global food security. Important in this regard is to understand how corn yield variability has evolved geographically in the history and how it relates to climatic and non-climatic factors. Results showed that year-to-year variation of US corn yield has decreased significantly during 1980-2010, mainly in Midwest Corn Belt, Nebraska and western arid regions. Despite the country-scale decreasing variability, corn yield variability exhibited an increasing trend in South Dakota,more » Texas and Southeast growing regions, indicating the importance of considering spatial scales in estimating yield variability. The observed pattern is partly reproduced by process-based crop models, simulating larger areas experiencing increasing variability and underestimating the magnitude of decreasing variability. And 3 out of 11 models even produced a differing sign of change from observations. Hence, statistical model which produces closer agreement with observations is used to explore the contribution of climatic and non-climatic factors to the changes in yield variability. It is found that climate variability dominate the change trends of corn yield variability in the Midwest Corn Belt, while the ability of climate variability in controlling yield variability is low in southeastern and western arid regions. Irrigation has largely reduced the corn yield variability in regions (e.g. Nebraska) where separate estimates of irrigated and rain-fed corn yield exist, demonstrating the importance of non-climatic factors in governing the changes in corn yield variability. The results highlight the distinct spatial patterns of corn yield variability change as well as its influencing factors at the county scale. I also caution the use of process-based crop models, which have substantially underestimated the change trend of corn yield variability, in projecting its future changes.« less

Climate and litter quality differently modulate the effects of soil fauna on litter decomposition across biomes

PubMed Central

García-Palacios, Pablo; Maestre, Fernando T.; Kattge, Jens; Wall, Diana H.

2015-01-01

Climate and litter quality have been identified as major drivers of litter decomposition at large spatial scales. However, the role played by soil fauna remains largely unknown, despite its importance for litter fragmentation and microbial activity. We synthesized litterbag studies to quantify the effect sizes of soil fauna on litter decomposition rates at the global and biome scales, and to assess how climate, litter quality and soil fauna interact to determine such rates. Soil fauna consistently enhanced litter decomposition at both global and biome scales (average increment ~27%). However, climate and litter quality differently modulated the effects of soil fauna on decomposition rates between biomes, from climate-driven biomes to those where climate effects were mediated by changes in litter quality. Our results advocate for the inclusion of biome-specific soil fauna effects on litter decomposition as a mean to reduce the unexplained variation in large-scale decomposition models. PMID:23763716

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

Climate variability drives recent tree mortality in Europe.

PubMed

Neumann, Mathias; Mues, Volker; Moreno, Adam; Hasenauer, Hubert; Seidl, Rupert

2017-11-01

Tree mortality is an important process in forest ecosystems, frequently hypothesized to be highly climate sensitive. Yet, tree death remains one of the least understood processes of forest dynamics. Recently, changes in tree mortality have been observed in forests around the globe, which could profoundly affect ecosystem functioning and services provisioning to society. We describe continental-scale patterns of recent tree mortality from the only consistent pan-European forest monitoring network, identifying recent mortality hotspots in southern and northern Europe. Analyzing 925,462 annual observations of 235,895 trees between 2000 and 2012, we determine the influence of climate variability and tree age on interannual variation in tree mortality using Cox proportional hazard models. Warm summers as well as high seasonal variability in precipitation increased the likelihood of tree death. However, our data also suggest that reduced cold-induced mortality could compensate increased mortality related to peak temperatures in a warming climate. Besides climate variability, age was an important driver of tree mortality, with individual mortality probability decreasing with age over the first century of a trees life. A considerable portion of the observed variation in tree mortality could be explained by satellite-derived net primary productivity, suggesting that widely available remote sensing products can be used as an early warning indicator of widespread tree mortality. Our findings advance the understanding of patterns of large-scale tree mortality by demonstrating the influence of seasonal and diurnal climate variation, and highlight the potential of state-of-the-art remote sensing to anticipate an increased likelihood of tree mortality in space and time. © 2017 John Wiley & Sons Ltd.

An observational and modeling study of the regional impacts of climate variability

NASA Astrophysics Data System (ADS)

Horton, Radley M.

Climate variability has large impacts on humans and their agricultural systems. Farmers are at the center of this agricultural network, but it is often agricultural planners---regional planners, extension agents, commodity groups and cooperatives---that translate climate information for users. Global climate models (GCMs) are a leading tool for understanding and predicting climate and climate change. Armed with climate projections and forecasts, agricultural planners adapt their decision-making to optimize outcomes. This thesis explores what GCMs can, and cannot, tell us about climate variability and change at regional scales. The question is important, since high-quality regional climate projections could assist farmers and regional planners in key management decisions, contributing to better agricultural outcomes. To answer these questions, climate variability and its regional impacts are explored in observations and models for the current and future climate. The goals are to identify impacts of observed variability, assess model simulation of variability, and explore how climate variability and its impacts may change under enhanced greenhouse warming. Chapter One explores how well Goddard Institute for Space Studies (GISS) atmospheric models, forced by historical sea surface temperatures (SST), simulate climatology and large-scale features during the exceptionally strong 1997--1999 El Nino Southern Oscillation (ENSO) cycle. Reasonable performance in this 'proof of concept' test is considered a minimum requirement for further study of variability in models. All model versions produce appropriate local changes with ENSO, indicating that with correct ocean temperatures these versions are capable of simulating the large-scale effects of ENSO around the globe. A high vertical resolution model (VHR) provides the best simulation. Evidence is also presented that SST anomalies outside the tropical Pacific may play a key role in generating remote teleconnections even during El Nino events. Based on the results from Chapter One, the analysis is expanded in several ways in Chapter Two. To gain a more complete and statistically meaningful understanding of ENSO, a 25 year time period is used instead of a single event. To gain a fuller understanding of climate variability, additional patterns are analyzed. Finally analysis is conducted at the regional scales that are of interest to farmers and agricultural planners. Key findings are that GISS ModelE can reproduce: (1) the spatial pattern associated with two additional related modes, the Arctic Oscillation (AO) and the North Atlantic Oscillation (NAO); (2) rainfall patterns in Indonesia; and (3) dynamical features such as sea level pressure (SLP) gradients and wind in the study regions. When run in coupled mode, the same model reproduces similar modes spatially but with reduced variance and weak teleconnections. Since Chapter Two identified Western Indonesia as the region where GCMs hold the most promise for agricultural applications, in Chapter Three a finer spatial and temporal scale analysis of ENSO's effects is presented. Agricultural decision-making is also linked to ENSO's climate effects. Early rainy season precipitation and circulation, and same-season planting and harvesting dates, are shown to be sensitive to ENSO. The locus of ENSO convergence and rainfall anomalies is shown to be near the axis of rainy season establishment, defined as the 6--8 mm/day isohyet, an approximate threshold for irrigated rice cultivation. As the axis tracks south and east between October and January, so do ENSO anomalies. Circulation anomalies associated with ENSO are shown to be similar to those associated with rainfall anomalies, suggesting that long lead-time ENSO forecasts may allow more adaptation than 'wait and see' methods, with little loss of forecast skill. Additional findings include: (1) rice and corn yields are lower (higher) during dry (wet) trimesters and El Nino (La Nina) years; and (2) a statistically significant negative relationship exists between malaria cases and ENSO. The final chapter adds climate change to the climate variability story. Under high CO2, the model able to capture ENSO dynamics---an atmospheric model coupled to the Cane-Zebiak ocean model ('C4' here)---generates more El Nino-like mean conditions in the tropical Pacific. These changes produce a 4x larger increase in maximum precipitation with warming in C4 than an atmospheric model with a slab ocean (Q4), dramatically enhancing the Pacific Hadley and Walker circulations, and through positive feedbacks, increasing the global temperature. Near Nordeste warming alone (Q4) produces added rainfall, which in C4 is partially cancelled out by El Nino-like changes in the Walker Cell. Both Q4 and C4 produce small changes in Indonesia, although C4 generates large circulation and precipitation anomalies over the Western Indian Ocean. C4 changes in the midlatitudes produce a very strong Pacific North American pattern (PNA) response that dominates a small positive AO change associated with Q4. These PNA changes produce increased rainfall over the Southeastern United States (SEUS) in C4. AO and NAO-like variability are also found to increase with enhanced CO2. This thesis highlights how climate variability influences regional climate variability, with an emphasis on four regions: Nordeste, Brazil, Western Indonesia, the Southeastern United States (SEUS), and the Mediterranean. It links El Nino-driven delay in the onset of rainy season drivers in Western Indonesia to decision-making about when to plant the year's largest crop. In a coupled configuration, the GISS GCM produces strong El Nino-like changes with global warming. This result suggests that the impacts---climatological and agricultural---of climate change may ultimately exceed the impacts of current variability. Somewhat paradoxically, these results indicate that one of the central manifestations of climate change is likely to be changes in patterns of climate variability and their regional impacts.

Combining super-ensembles and statistical emulation to improve a regional climate and vegetation model

NASA Astrophysics Data System (ADS)

Hawkins, L. R.; Rupp, D. E.; Li, S.; Sarah, S.; McNeall, D. J.; Mote, P.; Betts, R. A.; Wallom, D.

2017-12-01

Changing regional patterns of surface temperature, precipitation, and humidity may cause ecosystem-scale changes in vegetation, altering the distribution of trees, shrubs, and grasses. A changing vegetation distribution, in turn, alters the albedo, latent heat flux, and carbon exchanged with the atmosphere with resulting feedbacks onto the regional climate. However, a wide range of earth-system processes that affect the carbon, energy, and hydrologic cycles occur at sub grid scales in climate models and must be parameterized. The appropriate parameter values in such parameterizations are often poorly constrained, leading to uncertainty in predictions of how the ecosystem will respond to changes in forcing. To better understand the sensitivity of regional climate to parameter selection and to improve regional climate and vegetation simulations, we used a large perturbed physics ensemble and a suite of statistical emulators. We dynamically downscaled a super-ensemble (multiple parameter sets and multiple initial conditions) of global climate simulations using a 25-km resolution regional climate model HadRM3p with the land-surface scheme MOSES2 and dynamic vegetation module TRIFFID. We simultaneously perturbed land surface parameters relating to the exchange of carbon, water, and energy between the land surface and atmosphere in a large super-ensemble of regional climate simulations over the western US. Statistical emulation was used as a computationally cost-effective tool to explore uncertainties in interactions. Regions of parameter space that did not satisfy observational constraints were eliminated and an ensemble of parameter sets that reduce regional biases and span a range of plausible interactions among earth system processes were selected. This study demonstrated that by combining super-ensemble simulations with statistical emulation, simulations of regional climate could be improved while simultaneously accounting for a range of plausible land-atmosphere feedback strengths.

The role of the NAO on the North Atlantic hydrological conditions and its interplay with the EA and SCAND atmospheric patterns

NASA Astrophysics Data System (ADS)

Hernandez, A.; Rubio-Ingles, M. J.; Shanahan, T. M.; Sáez, A.; Raposeiro, P. M.; Vázquez-Loureiro, D.; Sánchez-López, G.; Gonçalves, V. M.; Bao, R.; Trigo, R.; Giralt, S.

2016-12-01

The NAO is the main atmospheric circulation mode controlling the largest fraction of the North Atlantic climate variability. It is defined by the normalized air pressure difference between the Azores High and the Iceland Low as the southern and northern centers of action of the dipole respectively. The NAO pattern has large influence over the precipitation regime in the North Atlantic and the western facade of Europe. Thus, the Lake Azul (São Miguel island, Azores archipelago), with a strategic location in the middle of the north Atlantic Ocean, is influenced by variations on intensity and position of the southern NAO center of action. The reconstruction of the past hydrological conditions in lake location for the last 700 years was obtained by means of high resolution δD plant leaf wax analyses, a proxy for the Precipitation/Evaporation ratio. The 700 years of climatic history included the end of the Medieval Climate Anomaly (MCA), the Little Ice Age (LIA) and the modern Global Warming (GW). The hydrological results showed multidecadal variations with no particular conditions at any climatic period. Overall, the MCA (1285 - 1350 AD) displayed mostly dry conditions, the LIA (1350 - 1820 AD) was mainly wet and, the last 200 years of record showed highly variable conditions. The lake Azul hydrological variations have been compared with a wide range of additional proxy datasets, including: documentary, ice, tree rings, speleothem, lacustrine and oceanic records from the North Atlantic. This comparison has allowed us to understand the decadal and centennial imprints of the NAO as well as to infer its interaction with other relevant large-scale circulation patterns over this sector, such as the Eastern Atlantic (EA) and the Scandinavian (SCAND) climate modes.

Fragmented patterns of flood change across the United States

USGS Publications Warehouse

Archfield, Stacey A.; Hirsch, Robert M.; Viglione, A.; Blöschl, G.

2016-01-01

Trends in the peak magnitude, frequency, duration, and volume of frequent floods (floods occurring at an average of two events per year relative to a base period) across the United States show large changes; however, few trends are found to be statistically significant. The multidimensional behavior of flood change across the United States can be described by four distinct groups, with streamgages experiencing (1) minimal change, (2) increasing frequency, (3) decreasing frequency, or (4) increases in all flood properties. Yet group membership shows only weak geographic cohesion. Lack of geographic cohesion is further demonstrated by weak correlations between the temporal patterns of flood change and large-scale climate indices. These findings reveal a complex, fragmented pattern of flood change that, therefore, clouds the ability to make meaningful generalizations about flood change across the United States.

Estimation of Fractional Plant Lifeform Cover Using Landsat and Airborne LiDAR/hyperspectral Data

NASA Astrophysics Data System (ADS)

Parra, A. S.; Xu, Q.; Dilts, T.; Weisberg, P.; Greenberg, J. A.

2017-12-01

Land-cover change has generally been understood as the result of local, landscape or regional-scale processes with most studies focusing on case-study landscapes or smaller regions. However, as we observe similar types of land-cover change occurring across different biomes worldwide, it becomes clear that global-scale processes such as climate change and CO2 fertilization, in interaction with local influences, are underlying drivers in land-cover change patterns. Prior studies on global land-cover change may not have had a suitable spatial, temporal and thematic resolution for allowing the identification of such patterns. Furthermore, the lack of globally consistent spatial data products also constitutes a limiting factor in evaluating both proximate and ultimate causes of land-cover change. In this study, we derived a global model for broadleaf tree, needleleaf tree, shrub, herbaceous, and "other" fractional cover using Landsat imagery. Combined LiDAR/hyperspectral data sets were used for calibration and validation of the Landsat-derived products. Spatially explicit uncertainties were also created as part of the data products. Our results highlight the potential for large-scale studies that model local and global influences on land-cover transition types and rates at fine thematic, spatial, and temporal resolutions. These spatial data products are relevant for identifying patterns in land-cover change due to underlying global-scale processes and can provide valuable insights into climatic and land-use factors determining vegetation distributions.

North-South precipitation patterns in western North America on interannual-to-decadal timescales

USGS Publications Warehouse

Dettinger, M.D.; Cayan, D.R.; Diaz, Henry F.; Meko, D.M.

1998-01-01

The overall amount of precipitation deposited along the West Coast and western cordillera of North America from 25??to 55??N varies from year to year, and superimposed on this domain-average variability are varying north-south contrasts on timescales from at least interannual to interdecadal. In order to better understand the north-south precipitation contrasts, their interannual and decadal variations are studied in terms of how much they affect overall precipitation amounts and how they are related to large-scale climatic patterns. Spatial empirical orthogonal functions (EOFs) and spatial moments (domain average, central latitude, and latitudinal spread) of zonally averaged precipitation anomalies along the westernmost parts of North America are analyzed, and each is correlated with global sea level pressure (SLP) and sea surface temperature series, on interannual (defined here as 3-7 yr) and decadal (>7 yr) timescales. The interannual band considered here corresponds to timescales that are particularly strong in tropical climate variations and thus is expected to contain much precipitation variability that is related to El Nino-Southern Oscillation; the decadal scale is defined so as to capture the whole range of long-term climatic variations affecting western North America. Zonal EOFs of the interannual and decadal filtered versions of the zonal-precipitation series are remarkably similar. At both timescales, two leading EOFs describe 1) a north-south seesaw of precipitation pivoting near 40??N and 2) variations in precipitation near 40??N, respectively. The amount of overall precipitation variability is only about 10% of the mean and is largely determined by precipitation variations around 40??-45??N and most consistently influenced by nearby circulation patterns; in this sense, domain-average precipitation is closely related to the second EOF. The central latitude and latitudinal spread of precipitation distributions are strongly influenced by precipitation variations in the southern parts of western North America and are closely related to the first EOF. Central latitude of precipitation moves south (north) with tropical warming (cooling) in association with midlatitude western Pacific SLP variations, on both interannual and decadal timescales. Regional patterns and zonal averages of precipitation-sensitive tree-ring series are used to corroborate these patterns and to extend them into the past and appear to share much long- and short-term information with the instrumentally based zonal precipitation EOFs and moments.The overall amount of precipitation deposited along the West Coast and western cordillera of North America from 25?? to 55 ??N varies from year to year, and superimposed on this domain-average variability are varying north-south contrasts on timescales from at least interannual to interdecadal. In order to better understand the north-south precipitation contrasts, their interannual and decadal variations are studied in terms of how much they affect overall precipitation amounts and how they are related to large-scale climatic patterns. Spatial empirical orthogonal functions (EOFs) and spatial moments (domain average, central latitude, and latitudinal spread) of zonally averaged precipitation anomalies along the westernmost parts of North America are analyzed, and each is correlated with global sea level pressure (SLP) and sea surface temperature series, on interannual (defined here as 3-7 yr) and decadal (>7 yr) timescales. The interannual band considered here corresponds to timescales that are particularly strong in tropical climate variations and thus is expected to contain much precipitation variability that is related to El Nino-Southern Oscillation; the decadal scale is defined so as to capture the whole range of long-term climatic variations affecting western North America. Zonal EOFs of the interannual and decadal filtered versions of the zonal-precipitation series are remarkably similar. At both tim

Global climate forcing from albedo change caused by large-scale deforestation and reforestation: quantification and attribution of geographic variation

USDA-ARS?s Scientific Manuscript database

Large-scale deforestation and reforestation have contributed substantially to historical and contemporary global climate change in part through albedo-induced radiative forcing, with meaningful implications for forest management aiming to mitigate climate change. Associated warming or cooling varies...

Phylogeographic Patterns in Africa and High Resolution Delineation of Genetic Clades in the Lion (Panthera leo)

NASA Astrophysics Data System (ADS)

Bertola, L. D.; Jongbloed, H.; van der Gaag, K. J.; de Knijff, P.; Yamaguchi, N.; Hooghiemstra, H.; Bauer, H.; Henschel, P.; White, P. A.; Driscoll, C. A.; Tende, T.; Ottosson, U.; Saidu, Y.; Vrieling, K.; de Iongh, H. H.

2016-08-01

Comparative phylogeography of African savannah mammals shows a congruent pattern in which populations in West/Central Africa are distinct from populations in East/Southern Africa. However, for the lion, all African populations are currently classified as a single subspecies (Panthera leo leo), while the only remaining population in Asia is considered to be distinct (Panthera leo persica). This distinction is disputed both by morphological and genetic data. In this study we introduce the lion as a model for African phylogeography. Analyses of mtDNA sequences reveal six supported clades and a strongly supported ancestral dichotomy with northern populations (West Africa, Central Africa, North Africa/Asia) on one branch, and southern populations (North East Africa, East/Southern Africa and South West Africa) on the other. We review taxonomies and phylogenies of other large savannah mammals, illustrating that similar clades are found in other species. The described phylogeographic pattern is considered in relation to large scale environmental changes in Africa over the past 300,000 years, attributable to climate. Refugial areas, predicted by climate envelope models, further confirm the observed pattern. We support the revision of current lion taxonomy, as recognition of a northern and a southern subspecies is more parsimonious with the evolutionary history of the lion.

Phylogeographic Patterns in Africa and High Resolution Delineation of Genetic Clades in the Lion (Panthera leo).

PubMed

Bertola, L D; Jongbloed, H; van der Gaag, K J; de Knijff, P; Yamaguchi, N; Hooghiemstra, H; Bauer, H; Henschel, P; White, P A; Driscoll, C A; Tende, T; Ottosson, U; Saidu, Y; Vrieling, K; de Iongh, H H

2016-08-04

Comparative phylogeography of African savannah mammals shows a congruent pattern in which populations in West/Central Africa are distinct from populations in East/Southern Africa. However, for the lion, all African populations are currently classified as a single subspecies (Panthera leo leo), while the only remaining population in Asia is considered to be distinct (Panthera leo persica). This distinction is disputed both by morphological and genetic data. In this study we introduce the lion as a model for African phylogeography. Analyses of mtDNA sequences reveal six supported clades and a strongly supported ancestral dichotomy with northern populations (West Africa, Central Africa, North Africa/Asia) on one branch, and southern populations (North East Africa, East/Southern Africa and South West Africa) on the other. We review taxonomies and phylogenies of other large savannah mammals, illustrating that similar clades are found in other species. The described phylogeographic pattern is considered in relation to large scale environmental changes in Africa over the past 300,000 years, attributable to climate. Refugial areas, predicted by climate envelope models, further confirm the observed pattern. We support the revision of current lion taxonomy, as recognition of a northern and a southern subspecies is more parsimonious with the evolutionary history of the lion.

Phylogeographic Patterns in Africa and High Resolution Delineation of Genetic Clades in the Lion (Panthera leo)

PubMed Central

Bertola, L. D.; Jongbloed, H.; van der Gaag, K. J.; de Knijff, P.; Yamaguchi, N.; Hooghiemstra, H.; Bauer, H.; Henschel, P.; White, P. A.; Driscoll, C. A.; Tende, T.; Ottosson, U.; Saidu, Y.; Vrieling, K.; de Iongh, H. H.

2016-01-01

Comparative phylogeography of African savannah mammals shows a congruent pattern in which populations in West/Central Africa are distinct from populations in East/Southern Africa. However, for the lion, all African populations are currently classified as a single subspecies (Panthera leo leo), while the only remaining population in Asia is considered to be distinct (Panthera leo persica). This distinction is disputed both by morphological and genetic data. In this study we introduce the lion as a model for African phylogeography. Analyses of mtDNA sequences reveal six supported clades and a strongly supported ancestral dichotomy with northern populations (West Africa, Central Africa, North Africa/Asia) on one branch, and southern populations (North East Africa, East/Southern Africa and South West Africa) on the other. We review taxonomies and phylogenies of other large savannah mammals, illustrating that similar clades are found in other species. The described phylogeographic pattern is considered in relation to large scale environmental changes in Africa over the past 300,000 years, attributable to climate. Refugial areas, predicted by climate envelope models, further confirm the observed pattern. We support the revision of current lion taxonomy, as recognition of a northern and a southern subspecies is more parsimonious with the evolutionary history of the lion. PMID:27488946

Evidence for climate change in the satellite cloud record.

PubMed

Norris, Joel R; Allen, Robert J; Evan, Amato T; Zelinka, Mark D; O'Dell, Christopher W; Klein, Stephen A

2016-08-04

Clouds substantially affect Earth's energy budget by reflecting solar radiation back to space and by restricting emission of thermal radiation to space. They are perhaps the largest uncertainty in our understanding of climate change, owing to disagreement among climate models and observational datasets over what cloud changes have occurred during recent decades and will occur in response to global warming. This is because observational systems originally designed for monitoring weather have lacked sufficient stability to detect cloud changes reliably over decades unless they have been corrected to remove artefacts. Here we show that several independent, empirically corrected satellite records exhibit large-scale patterns of cloud change between the 1980s and the 2000s that are similar to those produced by model simulations of climate with recent historical external radiative forcing. Observed and simulated cloud change patterns are consistent with poleward retreat of mid-latitude storm tracks, expansion of subtropical dry zones, and increasing height of the highest cloud tops at all latitudes. The primary drivers of these cloud changes appear to be increasing greenhouse gas concentrations and a recovery from volcanic radiative cooling. These results indicate that the cloud changes most consistently predicted by global climate models are currently occurring in nature.

Evidence for climate change in the satellite cloud record

NASA Astrophysics Data System (ADS)

Norris, Joel R.; Allen, Robert J.; Evan, Amato T.; Zelinka, Mark D.; O'Dell, Christopher W.; Klein, Stephen A.

2016-08-01

Clouds substantially affect Earth’s energy budget by reflecting solar radiation back to space and by restricting emission of thermal radiation to space. They are perhaps the largest uncertainty in our understanding of climate change, owing to disagreement among climate models and observational datasets over what cloud changes have occurred during recent decades and will occur in response to global warming. This is because observational systems originally designed for monitoring weather have lacked sufficient stability to detect cloud changes reliably over decades unless they have been corrected to remove artefacts. Here we show that several independent, empirically corrected satellite records exhibit large-scale patterns of cloud change between the 1980s and the 2000s that are similar to those produced by model simulations of climate with recent historical external radiative forcing. Observed and simulated cloud change patterns are consistent with poleward retreat of mid-latitude storm tracks, expansion of subtropical dry zones, and increasing height of the highest cloud tops at all latitudes. The primary drivers of these cloud changes appear to be increasing greenhouse gas concentrations and a recovery from volcanic radiative cooling. These results indicate that the cloud changes most consistently predicted by global climate models are currently occurring in nature.

Climate and landscape influence on indicators of lake carbon cycling through spatial patterns in dissolved organic carbon.

PubMed

Lapierre, Jean-Francois; Seekell, David A; Del Giorgio, Paul A

2015-12-01

Freshwater ecosystems are strongly influenced by both climate and the surrounding landscape, yet the specific pathways connecting climatic and landscape drivers to the functioning of lake ecosystems are poorly understood. Here, we hypothesize that the links that exist between spatial patterns in climate and landscape properties and the spatial variation in lake carbon (C) cycling at regional scales are at least partly mediated by the movement of terrestrial dissolved organic carbon (DOC) in the aquatic component of the landscape. We assembled a set of indicators of lake C cycling (bacterial respiration and production, chlorophyll a, production to respiration ratio, and partial pressure of CO2 ), DOC concentration and composition, and landscape and climate characteristics for 239 temperate and boreal lakes spanning large environmental and geographic gradients across seven regions. There were various degrees of spatial structure in climate and landscape features that were coherent with the regionally structured patterns observed in lake DOC and indicators of C cycling. These different regions aligned well, albeit nonlinearly along a mean annual temperature gradient; whereas there was a considerable statistical effect of climate and landscape properties on lake C cycling, the direct effect was small and the overall effect was almost entirely overlapping with that of DOC concentration and composition. Our results suggest that key climatic and landscape signals are conveyed to lakes in part via the movement of terrestrial DOC to lakes and that DOC acts both as a driver of lake C cycling and as a proxy for other external signals. © 2015 John Wiley & Sons Ltd.

Distant Influence of Kuroshio Eddies on North Pacific Weather Patterns?

PubMed Central

Ma, Xiaohui; Chang, Ping; Saravanan, R.; Montuoro, Raffaele; Hsieh, Jen-Shan; Wu, Dexing; Lin, Xiaopei; Wu, Lixin; Jing, Zhao

2015-01-01

High-resolution satellite measurements of surface winds and sea-surface temperature (SST) reveal strong coupling between meso-scale ocean eddies and near-surface atmospheric flow over eddy-rich oceanic regions, such as the Kuroshio and Gulf Stream, highlighting the importance of meso-scale oceanic features in forcing the atmospheric planetary boundary layer (PBL). Here, we present high-resolution regional climate modeling results, supported by observational analyses, demonstrating that meso-scale SST variability, largely confined in the Kuroshio-Oyashio confluence region (KOCR), can further exert a significant distant influence on winter rainfall variability along the U.S. Northern Pacific coast. The presence of meso-scale SST anomalies enhances the diabatic conversion of latent heat energy to transient eddy energy, intensifying winter cyclogenesis via moist baroclinic instability, which in turn leads to an equivalent barotropic downstream anticyclone anomaly with reduced rainfall. The finding points to the potential of improving forecasts of extratropical winter cyclones and storm systems and projections of their response to future climate change, which are known to have major social and economic impacts, by improving the representation of ocean eddy–atmosphere interaction in forecast and climate models. PMID:26635077

Vulnerability of the global terrestrial ecosystems to climate change.

PubMed

Li, Delong; Wu, Shuyao; Liu, Laibao; Zhang, Yatong; Li, Shuangcheng

2018-05-27

Climate change has far-reaching impacts on ecosystems. Recent attempts to quantify such impacts focus on measuring exposure to climate change but largely ignore ecosystem resistance and resilience, which may also affect the vulnerability outcomes. In this study, the relative vulnerability of global terrestrial ecosystems to short-term climate variability was assessed by simultaneously integrating exposure, sensitivity, and resilience at a high spatial resolution (0.05°). The results show that vulnerable areas are currently distributed primarily in plains. Responses to climate change vary among ecosystems and deserts and xeric shrublands are the most vulnerable biomes. Global vulnerability patterns are determined largely by exposure, while ecosystem sensitivity and resilience may exacerbate or alleviate external climate pressures at local scales; there is a highly significant negative correlation between exposure and sensitivity. Globally, 61.31% of the terrestrial vegetated area is capable of mitigating climate change impacts and those areas are concentrated in polar regions, boreal forests, tropical rainforests, and intact forests. Under current sensitivity and resilience conditions, vulnerable areas are projected to develop in high Northern Hemisphere latitudes in the future. The results suggest that integrating all three aspects of vulnerability (exposure, sensitivity, and resilience) may offer more comprehensive and spatially explicit adaptation strategies to reduce the impacts of climate change on terrestrial ecosystems. © 2018 John Wiley & Sons Ltd.

Natural habitats matter: Determinants of spatial pattern in the composition of animal assemblages of the Czech Republic

NASA Astrophysics Data System (ADS)

Divíšek, Jan; Zelený, David; Culek, Martin; Št'astný, Karel

2014-08-01

Studies that explore species-environment relationships at a broad scale are usually limited by the availability of sufficient habitat description, which is often too coarse to differentiate natural habitat patches. Therefore, it is not well understood how the distribution of natural habitats affects broad-scale patterns in the distribution of animal species. In this study, we evaluate the role of field-mapped natural habitats, land-cover types derived from remote sensing and climate on the composition of assemblages of five distinct animal groups, namely non-volant mammals, birds, reptiles, amphibians and butterflies native to the Czech Republic. First, we used variation partitioning based on redundancy analysis to evaluate the extent to which the environmental variables and their spatial structure might underlie the observed spatial patterns in the composition of animal assemblages. Second, we partitioned variations explained by climate, natural habitats and land-cover to compare their relative importance. Finally, we tested the independent effects of each variable in order to evaluate the significance of their contributions to the environmental model. Our results showed that spatial patterns in the composition of assemblages of almost all the considered animal groups may be ascribed mostly to variations in the environment. Although the shared effects of climatic variables, natural habitats and land-cover types explained the largest proportion of variation in each animal group, the variation explained purely by natural habitats was always higher than the variation explained purely by climate or land-cover. We conclude that most spatial variation in the composition of assemblages of almost all animal groups probably arises from biological processes operating within a spatially structured environment and suggest that natural habitats are important to explain observed patterns because they often perform better than habitat descriptions based on remote sensing. This underlines the value of using appropriate habitat data, for which high-resolution and large-area field-mapping projects are necessary.

Influence of land use and climate on wetland breeding birds in the Prairie Pothole region of Canada

USGS Publications Warehouse

Forcey, G.M.; Linz, G.M.; Thogmartin, W.E.; Bleier, W.J.

2007-01-01

Bird populations are influenced by a variety of factors at both small and large scales that range from the presence of suitable nesting habitat, predators, and food supplies to climate conditions and land-use patterns. We evaluated the influences of regional climate and land-use variables on wetland breeding birds in the Canada section of Bird Conservation Region 11 (CA-BCR11), the Prairie Potholes. We used bird abundance data from the North American Breeding Bird Survey, land-use data from the Prairie Farm Rehabilitation Administration, and weather data from the National Climatic Data and Information Archive to model effects of regional environmental variables on bird abundance. Models were constructed a priori using information from published habitat associations in the literature, and fitting was performed with WinBUGS using Markov chain Monte Carlo techniques. Both land-use and climate variables contributed to predicting bird abundance in CA-BCR11, although climate predictors contributed the most to improving model fit. Examination of regional effects of climate and land use on wetland birds in CA-BCR11 revealed relationships with environmental covariates that are often overlooked by small-scale habitat studies. Results from these studies can be used to improve conservation and management planning for regional populations of avifauna. ?? 2007 NRC.

Objective spatiotemporal proxy-model comparisons of the Asian monsoon for the last millennium

NASA Astrophysics Data System (ADS)

Anchukaitis, K. J.; Cook, E. R.; Ammann, C. M.; Buckley, B. M.; D'Arrigo, R. D.; Jacoby, G.; Wright, W. E.; Davi, N.; Li, J.

2008-12-01

The Asian monsoon system can be studied using a complementary proxy/simulation approach which evaluates climate models using estimates of past precipitation and temperature, and which subsequently applies the best understanding of the physics of the climate system as captured in general circulation models to evaluate the broad-scale dynamics behind regional paleoclimate reconstructions. Here, we use a millennial-length climate field reconstruction of monsoon season summer (JJA) drought, developed from tree- ring proxies, with coupled climate simulations from NCAR CSM1.4 and CCSM3 to evaluate the cause of large- scale persistent droughts over the last one thousand years. Direct comparisons are made between the external forced response within the climate model and the spatiotemporal field reconstruction. In order to identify patterns of drought associated with internal variability in the climate system, we use a model/proxy analog technique which objectively selects epochs in the model that most closely reproduce those observed in the reconstructions. The concomitant ocean-atmosphere dynamics are then interpreted in order to identify and understand the internal climate system forcing of low frequency monsoon variability. We examine specific periods of extensive or intensive regional drought in the 15th, 17th, and 18th centuries, many of which are coincident with major cultural changes in the region.

Simulating phenological shifts in French temperate forests under two climatic change scenarios and four driving global circulation models

NASA Astrophysics Data System (ADS)

Lebourgeois, François; Pierrat, Jean-Claude; Perez, Vincent; Piedallu, Christian; Cecchini, Sébastien; Ulrich, Erwin

2010-09-01

After modeling the large-scale climate response patterns of leaf unfolding, leaf coloring and growing season length of evergreen and deciduous French temperate trees, we predicted the effects of eight future climate scenarios on phenological events. We used the ground observations from 103 temperate forests (10 species and 3,708 trees) from the French Renecofor Network and for the period 1997-2006. We applied RandomForest algorithms to predict phenological events from climatic and ecological variables. With the resulting models, we drew maps of phenological events throughout France under present climate and under two climatic change scenarios (A2, B2) and four global circulation models (HadCM3, CGCM2, CSIRO2 and PCM). We compared current observations and predicted values for the periods 2041-2070 and 2071-2100. On average, spring development of oaks precedes that of beech, which precedes that of conifers. Annual cycles in budburst and leaf coloring are highly correlated with January, March-April and October-November weather conditions through temperature, global solar radiation or potential evapotranspiration depending on species. At the end of the twenty-first century, each model predicts earlier budburst (mean: 7 days) and later leaf coloring (mean: 13 days) leading to an average increase in the growing season of about 20 days (for oaks and beech stands). The A2-HadCM3 hypothesis leads to an increase of up to 30 days in many areas. As a consequence of higher predicted warming during autumn than during winter or spring, shifts in leaf coloring dates appear greater than trends in leaf unfolding. At a regional scale, highly differing climatic response patterns were observed.

Simulating phenological shifts in French temperate forests under two climatic change scenarios and four driving global circulation models.

PubMed

Lebourgeois, François; Pierrat, Jean-Claude; Perez, Vincent; Piedallu, Christian; Cecchini, Sébastien; Ulrich, Erwin

2010-09-01

After modeling the large-scale climate response patterns of leaf unfolding, leaf coloring and growing season length of evergreen and deciduous French temperate trees, we predicted the effects of eight future climate scenarios on phenological events. We used the ground observations from 103 temperate forests (10 species and 3,708 trees) from the French Renecofor Network and for the period 1997-2006. We applied RandomForest algorithms to predict phenological events from climatic and ecological variables. With the resulting models, we drew maps of phenological events throughout France under present climate and under two climatic change scenarios (A2, B2) and four global circulation models (HadCM3, CGCM2, CSIRO2 and PCM). We compared current observations and predicted values for the periods 2041-2070 and 2071-2100. On average, spring development of oaks precedes that of beech, which precedes that of conifers. Annual cycles in budburst and leaf coloring are highly correlated with January, March-April and October-November weather conditions through temperature, global solar radiation or potential evapotranspiration depending on species. At the end of the twenty-first century, each model predicts earlier budburst (mean: 7 days) and later leaf coloring (mean: 13 days) leading to an average increase in the growing season of about 20 days (for oaks and beech stands). The A2-HadCM3 hypothesis leads to an increase of up to 30 days in many areas. As a consequence of higher predicted warming during autumn than during winter or spring, shifts in leaf coloring dates appear greater than trends in leaf unfolding. At a regional scale, highly differing climatic response patterns were observed.

Characterization of extreme precipitation within atmospheric river events over California

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

Jeon, S.; Prabhat,; Byna, S.

Atmospheric rivers (ARs) are large, spatially coherent weather systems with high concentrations of elevated water vapor. These systems often cause severe downpours and flooding over the western coastal United States – and with the availability of more atmospheric moisture in the future under global warming we expect ARs to play an important role as potential causes of extreme precipitation changes. Therefore, we aim to investigate changes in extreme precipitation properties correlated with AR events in a warmer climate, which are large-scale meteorological patterns affecting the weather and climate of California. We have recently developed the TECA (Toolkit for Extreme Climatemore » Analysis) software for automatically identifying and tracking features in climate data sets. Specifically, we can now identify ARs that make landfall on the western coast of North America. Based on this detection procedure, we can investigate the impact of ARs by exploring the spatial extent of AR precipitation using climate model (CMIP5) simulations and characterize spatial patterns of dependence for future projections between AR precipitation extremes under climate change within the statistical framework. Our results show that AR events in the future RCP (Representative Concentration Pathway)8.5 scenario (2076–2100) tend to produce heavier rainfall with higher frequency and longer days than events from the historical run (1981–2005). We also find that the dependence between extreme precipitation events has a shorter spatial range, within localized areas in California, under the high future emissions scenario than under the historical run.« less

Characterization of extreme precipitation within atmospheric river events over California

DOE PAGES

Jeon, S.; Prabhat,; Byna, S.; ...

2015-11-17

Atmospheric rivers (ARs) are large, spatially coherent weather systems with high concentrations of elevated water vapor. These systems often cause severe downpours and flooding over the western coastal United States – and with the availability of more atmospheric moisture in the future under global warming we expect ARs to play an important role as potential causes of extreme precipitation changes. Therefore, we aim to investigate changes in extreme precipitation properties correlated with AR events in a warmer climate, which are large-scale meteorological patterns affecting the weather and climate of California. We have recently developed the TECA (Toolkit for Extreme Climatemore » Analysis) software for automatically identifying and tracking features in climate data sets. Specifically, we can now identify ARs that make landfall on the western coast of North America. Based on this detection procedure, we can investigate the impact of ARs by exploring the spatial extent of AR precipitation using climate model (CMIP5) simulations and characterize spatial patterns of dependence for future projections between AR precipitation extremes under climate change within the statistical framework. Our results show that AR events in the future RCP (Representative Concentration Pathway)8.5 scenario (2076–2100) tend to produce heavier rainfall with higher frequency and longer days than events from the historical run (1981–2005). We also find that the dependence between extreme precipitation events has a shorter spatial range, within localized areas in California, under the high future emissions scenario than under the historical run.« less

Biogeography and Change among Regional Coral Communities across the Western Indian Ocean

PubMed Central

McClanahan, Timothy R.; Ateweberhan, Mebrahtu; Darling, Emily S.; Graham, Nicholas A. J.; Muthiga, Nyawira A.

2014-01-01

Coral reefs are biodiverse ecosystems structured by abiotic and biotic factors operating across many spatial scales. Regional-scale interactions between climate change, biogeography and fisheries management remain poorly understood. Here, we evaluated large-scale patterns of coral communities in the western Indian Ocean after a major coral bleaching event in 1998. We surveyed 291 coral reef sites in 11 countries and over 30° of latitude between 2004 and 2011 to evaluate variations in coral communities post 1998 across gradients in latitude, mainland-island geography and fisheries management. We used linear mixed-effect hierarchical models to assess total coral cover, the abundance of four major coral families (acroporids, faviids, pocilloporids and poritiids), coral genus richness and diversity, and the bleaching susceptibility of the coral communities. We found strong latitudinal and geographic gradients in coral community structure and composition that supports the presence of a high coral cover and diversity area that harbours temperature-sensitive taxa in the northern Mozambique Channel between Tanzania, northern Mozambique and northern Madagascar. Coral communities in the more northern latitudes of Kenya, Seychelles and the Maldives were generally composed of fewer bleaching-tolerant coral taxa and with reduced richness and diversity. There was also evidence for continued declines in the abundance of temperature-sensitive taxa and community change after 2004. While there are limitations of our regional dataset in terms of spatial and temporal replication, these patterns suggest that large-scale interactions between biogeographic factors and strong temperature anomalies influence coral communities while smaller-scale factors, such as the effect of fisheries closures, were weak. The northern Mozambique Channel, while not immune to temperature disturbances, shows continued signs of resistance to climate disturbances and remains a priority for future regional conservation and management actions. PMID:24718371

Biogeography and change among regional coral communities across the Western Indian Ocean.

PubMed

McClanahan, Timothy R; Ateweberhan, Mebrahtu; Darling, Emily S; Graham, Nicholas A J; Muthiga, Nyawira A

2014-01-01

Coral reefs are biodiverse ecosystems structured by abiotic and biotic factors operating across many spatial scales. Regional-scale interactions between climate change, biogeography and fisheries management remain poorly understood. Here, we evaluated large-scale patterns of coral communities in the western Indian Ocean after a major coral bleaching event in 1998. We surveyed 291 coral reef sites in 11 countries and over 30° of latitude between 2004 and 2011 to evaluate variations in coral communities post 1998 across gradients in latitude, mainland-island geography and fisheries management. We used linear mixed-effect hierarchical models to assess total coral cover, the abundance of four major coral families (acroporids, faviids, pocilloporids and poritiids), coral genus richness and diversity, and the bleaching susceptibility of the coral communities. We found strong latitudinal and geographic gradients in coral community structure and composition that supports the presence of a high coral cover and diversity area that harbours temperature-sensitive taxa in the northern Mozambique Channel between Tanzania, northern Mozambique and northern Madagascar. Coral communities in the more northern latitudes of Kenya, Seychelles and the Maldives were generally composed of fewer bleaching-tolerant coral taxa and with reduced richness and diversity. There was also evidence for continued declines in the abundance of temperature-sensitive taxa and community change after 2004. While there are limitations of our regional dataset in terms of spatial and temporal replication, these patterns suggest that large-scale interactions between biogeographic factors and strong temperature anomalies influence coral communities while smaller-scale factors, such as the effect of fisheries closures, were weak. The northern Mozambique Channel, while not immune to temperature disturbances, shows continued signs of resistance to climate disturbances and remains a priority for future regional conservation and management actions.

Classification of mechanisms, climatic context, areal scaling, and synchronization of floods: the hydroclimatology of floods in the Upper Paraná River basin, Brazil

NASA Astrophysics Data System (ADS)

Lima, Carlos H. R.; AghaKouchak, Amir; Lall, Upmanu

2017-12-01

Floods are the main natural disaster in Brazil, causing substantial economic damage and loss of life. Studies suggest that some extreme floods result from a causal climate chain. Exceptional rain and floods are determined by large-scale anomalies and persistent patterns in the atmospheric and oceanic circulations, which influence the magnitude, extent, and duration of these extremes. Moreover, floods can result from different generating mechanisms. These factors contradict the assumptions of homogeneity, and often stationarity, in flood frequency analysis. Here we outline a methodological framework based on clustering using self-organizing maps (SOMs) that allows the linkage of large-scale processes to local-scale observations. The methodology is applied to flood data from several sites in the flood-prone Upper Paraná River basin (UPRB) in southern Brazil. The SOM clustering approach is employed to classify the 6-day rainfall field over the UPRB into four categories, which are then used to classify floods into four types based on the spatiotemporal dynamics of the rainfall field prior to the observed flood events. An analysis of the vertically integrated moisture fluxes, vorticity, and high-level atmospheric circulation revealed that these four clusters are related to known tropical and extratropical processes, including the South American low-level jet (SALLJ); extratropical cyclones; and the South Atlantic Convergence Zone (SACZ). Persistent anomalies in the sea surface temperature fields in the Pacific and Atlantic oceans are also found to be associated with these processes. Floods associated with each cluster present different patterns in terms of frequency, magnitude, spatial variability, scaling, and synchronization of events across the sites and subbasins. These insights suggest new directions for flood risk assessment, forecasting, and management.

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.

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

Large rainfall changes consistently projected over substantial areas of tropical land

NASA Astrophysics Data System (ADS)

Chadwick, Robin; Good, Peter; Martin, Gill; Rowell, David P.

2016-02-01

Many tropical countries are exceptionally vulnerable to changes in rainfall patterns, with floods or droughts often severely affecting human life and health, food and water supplies, ecosystems and infrastructure. There is widespread disagreement among climate model projections of how and where rainfall will change over tropical land at the regional scales relevant to impacts, with different models predicting the position of current tropical wet and dry regions to shift in different ways. Here we show that despite uncertainty in the location of future rainfall shifts, climate models consistently project that large rainfall changes will occur for a considerable proportion of tropical land over the twenty-first century. The area of semi-arid land affected by large changes under a higher emissions scenario is likely to be greater than during even the most extreme regional wet or dry periods of the twentieth century, such as the Sahel drought of the late 1960s to 1990s. Substantial changes are projected to occur by mid-century--earlier than previously expected--and to intensify in line with global temperature rise. Therefore, current climate projections contain quantitative, decision-relevant information on future regional rainfall changes, particularly with regard to climate change mitigation policy.

The Plant Phenology Ontology: A New Informatics Resource for Large-Scale Integration of Plant Phenology Data.

PubMed

Stucky, Brian J; Guralnick, Rob; Deck, John; Denny, Ellen G; Bolmgren, Kjell; Walls, Ramona

2018-01-01

Plant phenology - the timing of plant life-cycle events, such as flowering or leafing out - plays a fundamental role in the functioning of terrestrial ecosystems, including human agricultural systems. Because plant phenology is often linked with climatic variables, there is widespread interest in developing a deeper understanding of global plant phenology patterns and trends. Although phenology data from around the world are currently available, truly global analyses of plant phenology have so far been difficult because the organizations producing large-scale phenology data are using non-standardized terminologies and metrics during data collection and data processing. To address this problem, we have developed the Plant Phenology Ontology (PPO). The PPO provides the standardized vocabulary and semantic framework that is needed for large-scale integration of heterogeneous plant phenology data. Here, we describe the PPO, and we also report preliminary results of using the PPO and a new data processing pipeline to build a large dataset of phenology information from North America and Europe.

Simulating the impact of the large-scale circulation on the 2-m temperature and precipitation climatology

NASA Astrophysics Data System (ADS)

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

2013-04-01

The impact of the simulated large-scale atmospheric circulation on the regional climate is examined using the Weather Research and Forecasting (WRF) model as a regional climate model. The purpose is to understand the potential need for interior grid nudging for dynamical downscaling of global climate model (GCM) output for air quality applications under a changing climate. In this study we downscale the NCEP-Department of Energy Atmospheric Model Intercomparison Project (AMIP-II) Reanalysis using three continuous 20-year WRF simulations: one simulation without interior grid nudging and two using different interior grid nudging methods. The biases in 2-m temperature and precipitation for the simulation without interior grid nudging are unreasonably large with respect to the North American Regional Reanalysis (NARR) over the eastern half of the contiguous United States (CONUS) during the summer when air quality concerns are most relevant. This study examines how these differences arise from errors in predicting the large-scale atmospheric circulation. It is demonstrated that the Bermuda high, which strongly influences the regional climate for much of the eastern half of the CONUS during the summer, is poorly simulated without interior grid nudging. In particular, two summers when the Bermuda high was west (1993) and east (2003) of its climatological position are chosen to illustrate problems in the large-scale atmospheric circulation anomalies. For both summers, WRF without interior grid nudging fails to simulate the placement of the upper-level anticyclonic (1993) and cyclonic (2003) circulation anomalies. The displacement of the large-scale circulation impacts the lower atmosphere moisture transport and precipitable water, affecting the convective environment and precipitation. Using interior grid nudging improves the large-scale circulation aloft and moisture transport/precipitable water anomalies, thereby improving the simulated 2-m temperature and precipitation. The results demonstrate that constraining the RCM to the large-scale features in the driving fields improves the overall accuracy of the simulated regional climate, and suggest that in the absence of such a constraint, the RCM will likely misrepresent important large-scale shifts in the atmospheric circulation under a future climate.

Climate-soil Interactions: Global Change, Local Properties, and Ecological Sites

USDA-ARS?s Scientific Manuscript database

Global climate change is predicted to alter historic patterns of precipitation and temperature in rangelands globally. Vegetation community response to altered weather patterns will be mediated at the site level by local-scale properties that govern ecological potential, including geology, topograph...

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.

Simulation of seasonal US precipitation and temperature by the nested CWRF-ECHAM system

NASA Astrophysics Data System (ADS)

Chen, Ligang; Liang, Xin-Zhong; DeWitt, David; Samel, Arthur N.; Wang, Julian X. L.

2016-02-01

This study investigates the refined simulation skill that results when the regional Climate extension of the Weather Research and Forecasting (CWRF) model is nested in the ECMWF Hamburg version 4.5 (ECHAM) atmospheric general circulation model over the United States during 1980-2009, where observed sea surface temperatures are used in both models. Over the contiguous US, for each of the four seasons from winter to fall, CWRF reduces the root mean square error of the ECHAM seasonal mean surface air temperature simulation by 0.19, 0.82, 2.02 and 1.85 °C, and increases the equitable threat score of seasonal mean precipitation by 0.18, 0.11, 0.09 and 0.12. CWRF also simulates much more realistically daily precipitation frequency and heavy precipitation events, typically over the Central Great Plains, Cascade Mountains and Gulf Coast States. These CWRF skill enhancements are attributed to the increased spatial resolution and physics refinements in representing orographic, terrestrial hydrology, convection, and cloud-aerosol-radiation effects and their interactions. Empirical orthogonal function analysis of seasonal mean precipitation and surface air temperature interannual variability shows that, in general, CWRF substantially improves the spatial distribution of both quantities, while temporal evolution (i.e. interannual variability) of the first 3 primary patterns is highly correlated with that of the driving ECHAM (except for summer precipitation), and they both have low temporal correlations against observations. During winter, when large-scale forcing dominates, both models also have similar responses to strong ENSO signals where they successfully capture observed precipitation composite anomalies but substantially fail to reproduce surface air temperature anomalies. When driven by the ECMWF Reanalysis Interim, CWRF produces a very realistic interannual evolution of large-scale precipitation and surface air temperature patterns where the temporal correlations with observations are significant. These results indicate that CWRF can greatly improve mesoscale regional climate structures but it cannot change interannual variations of the large-scale patterns, which are determined by the driving lateral boundary conditions.

Evidence for climate-driven synchrony of marine and terrestrial ecosystems in northwest Australia.

PubMed

Ong, Joyce J L; Rountrey, Adam N; Zinke, Jens; Meeuwig, Jessica J; Grierson, Pauline F; O'Donnell, Alison J; Newman, Stephen J; Lough, Janice M; Trougan, Mélissa; Meekan, Mark G

2016-08-01

The effects of climate change are difficult to predict for many marine species because little is known of their response to climate variations in the past. However, long-term chronologies of growth, a variable that integrates multiple physical and biological factors, are now available for several marine taxa. These allow us to search for climate-driven synchrony in growth across multiple taxa and ecosystems, identifying the key processes driving biological responses at very large spatial scales. We hypothesized that in northwest (NW) Australia, a region that is predicted to be strongly influenced by climate change, the El Niño Southern Oscillation (ENSO) phenomenon would be an important factor influencing the growth patterns of organisms in both marine and terrestrial environments. To test this idea, we analyzed existing growth chronologies of the marine fish Lutjanus argentimaculatus, the coral Porites spp. and the tree Callitris columellaris and developed a new chronology for another marine fish, Lethrinus nebulosus. Principal components analysis and linear model selection showed evidence of ENSO-driven synchrony in growth among all four taxa at interannual time scales, the first such result for the Southern Hemisphere. Rainfall, sea surface temperatures, and sea surface salinities, which are linked to the ENSO system, influenced the annual growth of fishes, trees, and corals. All four taxa had negative relationships with the Niño-4 index (a measure of ENSO status), with positive growth patterns occurring during strong La Niña years. This finding implies that future changes in the strength and frequency of ENSO events are likely to have major consequences for both marine and terrestrial taxa. Strong similarities in the growth patterns of fish and trees offer the possibility of using tree-ring chronologies, which span longer time periods than those of fish, to aid understanding of both historical and future responses of fish populations to climate variation. © 2016 John Wiley & Sons Ltd.

Comparison of Grid Nudging and Spectral Nudging Techniques for Dynamical Climate Downscaling within the WRF Model

NASA Astrophysics Data System (ADS)

Fan, X.; Chen, L.; Ma, Z.

2010-12-01

Climate downscaling has been an active research and application area in the past several decades focusing on regional climate studies. Dynamical downscaling, in addition to statistical methods, has been widely used in downscaling as the advanced modern numerical weather and regional climate models emerge. The utilization of numerical models enables that a full set of climate variables are generated in the process of downscaling, which are dynamically consistent due to the constraints of physical laws. While we are generating high resolution regional climate, the large scale climate patterns should be retained. To serve this purpose, nudging techniques, including grid analysis nudging and spectral nudging, have been used in different models. There are studies demonstrating the benefit and advantages of each nudging technique; however, the results are sensitive to many factors such as nudging coefficients and the amount of information to nudge to, and thus the conclusions are controversy. While in a companion work of developing approaches for quantitative assessment of the downscaled climate, in this study, the two nudging techniques are under extensive experiments in the Weather Research and Forecasting (WRF) model. Using the same model provides fair comparability. Applying the quantitative assessments provides objectiveness of comparison. Three types of downscaling experiments were performed for one month of choice. The first type is serving as a base whereas the large scale information is communicated through lateral boundary conditions only; the second is using the grid analysis nudging; and the third is using spectral nudging. Emphases are given to the experiments of different nudging coefficients and nudging to different variables in the grid analysis nudging; while in spectral nudging, we focus on testing the nudging coefficients, different wave numbers on different model levels to nudge.

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.

Large Scale EOF Analysis of Climate Data

NASA Astrophysics Data System (ADS)

Prabhat, M.; Gittens, A.; Kashinath, K.; Cavanaugh, N. R.; Mahoney, M.

2016-12-01

We present a distributed approach towards extracting EOFs from 3D climate data. We implement the method in Apache Spark, and process multi-TB sized datasets on O(1000-10,000) cores. We apply this method to latitude-weighted ocean temperature data from CSFR, a 2.2 terabyte-sized data set comprising ocean and subsurface reanalysis measurements collected at 41 levels in the ocean, at 6 hour intervals over 31 years. We extract the first 100 EOFs of this full data set and compare to the EOFs computed simply on the surface temperature field. Our analyses provide evidence of Kelvin and Rossy waves and components of large-scale modes of oscillation including the ENSO and PDO that are not visible in the usual SST EOFs. Further, they provide information on the the most influential parts of the ocean, such as the thermocline, that exist below the surface. Work is ongoing to understand the factors determining the depth-varying spatial patterns observed in the EOFs. We will experiment with weighting schemes to appropriately account for the differing depths of the observations. We also plan to apply the same distributed approach to analysis of analysis of 3D atmospheric climatic data sets, including multiple variables. Because the atmosphere changes on a quicker time-scale than the ocean, we expect that the results will demonstrate an even greater advantage to computing 3D EOFs in lieu of 2D EOFs.

Influence of climate on alpine stream chemistry and water sources

USGS Publications Warehouse

Foks, Sydney; Stets, Edward; Singha, Kamini; Clow, David W.

2018-01-01

The resilience of alpine/subalpine watersheds may be viewed as the resistance of streamflow or stream chemistry to change under varying climatic conditions, which is governed by the relative size (volume) and transit time of surface and subsurface water sources. Here, we use end‐member mixing analysis in Andrews Creek, an alpine stream in Rocky Mountain National Park, Colorado, from water year 1994 to 2015, to explore how the partitioning of water sources and associated hydrologic resilience change in response to climate. Our results indicate that four water sources are significant contributors to Andrews Creek, including snow, rain, soil water, and talus groundwater. Seasonal patterns in source‐water contributions reflected the seasonal hydrologic cycle, which is driven by the accumulation and melting of seasonal snowpack. Flushing of soil water had a large effect on stream chemistry during spring snowmelt, despite making only a small contribution to streamflow volume. Snow had a large influence on stream chemistry as well, contributing large amounts of water with low concentrations of weathering products. Interannual patterns in end‐member contributions reflected responses to drought and wet periods. Moderate and significant correlations exist between annual end‐member contributions and regional‐scale climate indices (the Palmer Drought Severity Index, the Palmer Hydrologic Drought Index, and the Modified Palmer Drought Severity Index). From water year 1994 to 2015, the percent contribution from the talus‐groundwater end member to Andrews Creek increased an average of 0.5% per year (p < 0.0001), whereas the percent contributions from snow plus rain decreased by a similar amount (p = 0.001). Our results show how water and solute sources in alpine environments shift in response to climate variability and highlight the role of talus groundwater and soil water in providing hydrologic resilience to the system.

Holocene vegetation and climate dynamics of NE China based on the pollen record from Sihailongwan Maar Lake

NASA Astrophysics Data System (ADS)

Stebich, Martina; Rehfeld, Kira; Schlütz, Frank; Tarasov, Pavel E.; Liu, Jiaqi; Mingram, Jens

2015-09-01

High-resolution palynological analysis on annually laminated sediments of Sihailongwan Maar Lake (SHL) provides new insights into the Holocene vegetation and climate dynamics of NE China. The robust chronology of the presented record is based on varve counting and AMS radiocarbon dates from terrestrial plant macro-remains. In addition to the qualitative interpretation of the pollen data, we provide quantitative reconstructions of vegetation and climate based on the method of biomization and weighted averaging partial least squares regression (WA-PLS) technique, respectively. Power spectra were computed to investigate the frequency domain distribution of proxy signals and potential natural periodicities. Pollen assemblages, pollen-derived biome scores and climate variables as well as the cyclicity pattern indicate that NE China experienced significant changes in temperature and moisture conditions during the Holocene. Within the earliest phase of the Holocene, a large-scale reorganization of vegetation occurred, reflecting the reconstructed shift towards higher temperatures and precipitation values and the initial Holocene strengthening and northward expansion of the East Asian summer monsoon (EASM). Afterwards, summer temperatures remain at a high level, whereas the reconstructed precipitation shows an increasing trend until approximately 4000 cal. yr BP. Since 3500 cal. yr BP, temperature and precipitation values decline, indicating moderate cooling and weakening of the EASM. A distinct periodicity of 550-600 years and evidence of a Mid-Holocene transition from a temperature-triggered to a predominantly moisture-triggered climate regime are derived from the power spectra analysis. The results obtained from SHL are largely consistent with other palaeoenvironmental records from NE China, substantiating the regional nature of the reconstructed vegetation and climate patterns. However, the reconstructed climate changes contrast with the moisture evolution recorded in S China and the mid-latitude (semi-)arid regions of N China. Whereas a clear insolation-related trend of monsoon intensity over the Holocene is lacking from the SHL record, variations in the coupled atmosphere-Pacific Ocean system can largely explain the reconstructed changes in NE China.

Statistical Emulation of Climate Model Projections Based on Precomputed GCM Runs*

DOE PAGES

Castruccio, Stefano; McInerney, David J.; Stein, Michael L.; ...

2014-02-24

The authors describe a new approach for emulating the output of a fully coupled climate model under arbitrary forcing scenarios that is based on a small set of precomputed runs from the model. Temperature and precipitation are expressed as simple functions of the past trajectory of atmospheric CO 2 concentrations, and a statistical model is fit using a limited set of training runs. The approach is demonstrated to be a useful and computationally efficient alternative to pattern scaling and captures the nonlinear evolution of spatial patterns of climate anomalies inherent in transient climates. The approach does as well as patternmore » scaling in all circumstances and substantially better in many; it is not computationally demanding; and, once the statistical model is fit, it produces emulated climate output effectively instantaneously. In conclusion, it may therefore find wide application in climate impacts assessments and other policy analyses requiring rapid climate projections.« less

Observational Evidence for Desert Amplification Using Multiple Satellite Datasets.

PubMed

Wei, Nan; Zhou, Liming; Dai, Yongjiu; Xia, Geng; Hua, Wenjian

2017-05-17

Desert amplification identified in recent studies has large uncertainties due to data paucity over remote deserts. Here we present observational evidence using multiple satellite-derived datasets that desert amplification is a real large-scale pattern of warming mode in near surface and low-tropospheric temperatures. Trend analyses of three long-term temperature products consistently confirm that near-surface warming is generally strongest over the driest climate regions and this spatial pattern of warming maximizes near the surface, gradually decays with height, and disappears in the upper troposphere. Short-term anomaly analyses show a strong spatial and temporal coupling of changes in temperatures, water vapor and downward longwave radiation (DLR), indicating that the large increase in DLR drives primarily near surface warming and is tightly associated with increasing water vapor over deserts. Atmospheric soundings of temperature and water vapor anomalies support the results of the long-term temperature trend analysis and suggest that desert amplification is due to comparable warming and moistening effects of the troposphere. Likely, desert amplification results from the strongest water vapor feedbacks near the surface over the driest deserts, where the air is very sensitive to changes in water vapor and thus efficient in enhancing the longwave greenhouse effect in a warming climate.

20th century trends of drought conditions in the Mediterranean: the influence of large-scale circulation patterns.

NASA Astrophysics Data System (ADS)

Sousa, Pedro; Trigo, Ricardo; Garcia-Herrera, Ricardo

2010-05-01

Here we have used the Self Calibrated PDSI (scPDSI) proposed by Wells et al (2004) as a more appropriate approach to characterize drought conditions in the Mediterranean area. The scPDSI has been shown to perform better (than the original PDSI) when evaluating spatial and temporal drought characteristics for regions outside the USA (Schrier et al, 2005). Seasonal and annual trends for the 1901-2000, 1901-1950 and 1951-2000 periods were computed using the standard Mann-Kendall test for trend significance evaluation. However, statistical significance obtained with this test can be highly misleading because it does not take into account the low variability nature that dominates the seasonal evolution of scPDSI fields. We have now improved these results by employing a modified Mann-Kendall test for auto-correlated series (Hamed and Ramachandra, 1997), such as the scPDSI case. This development allowed for a better definition of the Mediterranean areas characterized by significant changes in the scPDSI, namely the largely negative trends that dominate the Mediterranean basin, with the exceptions of parts of eastern Turkey and northwestern Iberia, since initially these areas were overestimated. The spatio-temporal variability of these indices was evaluated with an EOF analysis, in order to reduce the large dimensionality of the fields under analysis. Spatial representation of the first EOF patterns shows that EOF 1 covers the entire Mediterranean basin (16.4% of EV), while EOF2 is dominated by a W-E dipole (10% EV). The following EOF patterns present smaller scale features, and explain smaller amounts of variance. The EOF patterns have also facilitated the definition of four sub-regions with large socio-economic relevance: 1) Iberia, 2) Italian Peninsula, 3) Balkans and 4) Turkey. Afterwards we perform a comprehensive analysis on the links between the scPDSI and the large-scale atmospheric circulation indices that affect the Mediterranean basin, namely; NAO, EA, and SCAND (Trigo et al., 2006) and where we have also taken into account once again the effect of autocorrelation. Some of these links were obtained with 3 or 6 months lagged relationships, while others were achieved with instantaneous (no lag) links. This analysis was performed for the entire Mediterranean region as a whole, but also for each considered sub-domain. Finally, a stepwise regression model was developed to reproduce summer scPDSI series during the 1951-2002 period, using these large scale indices as predictors in the model. This procedure results in positive Skill Score values against the persistence model. Hamed K.H., Ramachandra A. (1997) "A modified Mann-Kendall trend test for autocorrelated data", Journal of Hidrology, 204, 182-196. Schrier G, Briffa KR, Jones PD, Osborn TJ. (2005). Summer moisture variability across Europe. Journal of Climate 19: 2818-2834. Trigo, R. and 21 authors (2006) Relations between variability in the Mediterranean region and mid-latitude variability. In: P. Lionello, P. Malanotte-Rizzoli & R. Boscolo (Eds), Mediterranean Climate Variability, Amsterdam: Elsevier, pp. 179-226. Wells N, Goddard S and Hayes MJ (2004) A self-calibrating Palmer Drought Severity Index. Journal of Climate 17, 2335-2351.

Elevation-dependent temperature trends in the Rocky Mountain Front Range: changes over a 56- and 20-year record.

PubMed

McGuire, Chris R; Nufio, César R; Bowers, M Deane; Guralnick, Robert P

2012-01-01

Determining the magnitude of climate change patterns across elevational gradients is essential for an improved understanding of broader climate change patterns and for predicting hydrologic and ecosystem changes. We present temperature trends from five long-term weather stations along a 2077-meter elevational transect in the Rocky Mountain Front Range of Colorado, USA. These trends were measured over two time periods: a full 56-year record (1953-2008) and a shorter 20-year (1989-2008) record representing a period of widely reported accelerating change. The rate of change of biological indicators, season length and accumulated growing-degree days, were also measured over the 56 and 20-year records. Finally, we compared how well interpolated Parameter-elevation Regression on Independent Slopes Model (PRISM) datasets match the quality controlled and weather data from each station. Our results show that warming signals were strongest at mid-elevations over both temporal scales. Over the 56-year record, most sites show warming occurring largely through increases in maximum temperatures, while the 20-year record documents warming associated with increases in maximum temperatures at lower elevations and increases in minimum temperatures at higher elevations. Recent decades have also shown a shift from warming during springtime to warming in July and November. Warming along the gradient has contributed to increases in growing-degree days, although to differing degrees, over both temporal scales. However, the length of the growing season has remained unchanged. Finally, the actual and the PRISM interpolated yearly rates rarely showed strong correlations and suggest different warming and cooling trends at most sites. Interpretation of climate trends and their seasonal biases in the Rocky Mountain Front Range are dependent on both elevation and the temporal scale of analysis. Given mismatches between interpolated data and the directly measured station data, we caution against an over-reliance on interpolation methods for documenting local patterns of climatic change.

Elevation-Dependent Temperature Trends in the Rocky Mountain Front Range: Changes over a 56- and 20-Year Record

PubMed Central

McGuire, Chris R.; Nufio, César R.; Bowers, M. Deane; Guralnick, Robert P.

2012-01-01

Determining the magnitude of climate change patterns across elevational gradients is essential for an improved understanding of broader climate change patterns and for predicting hydrologic and ecosystem changes. We present temperature trends from five long-term weather stations along a 2077-meter elevational transect in the Rocky Mountain Front Range of Colorado, USA. These trends were measured over two time periods: a full 56-year record (1953–2008) and a shorter 20-year (1989–2008) record representing a period of widely reported accelerating change. The rate of change of biological indicators, season length and accumulated growing-degree days, were also measured over the 56 and 20-year records. Finally, we compared how well interpolated Parameter-elevation Regression on Independent Slopes Model (PRISM) datasets match the quality controlled and weather data from each station. Our results show that warming signals were strongest at mid-elevations over both temporal scales. Over the 56-year record, most sites show warming occurring largely through increases in maximum temperatures, while the 20-year record documents warming associated with increases in maximum temperatures at lower elevations and increases in minimum temperatures at higher elevations. Recent decades have also shown a shift from warming during springtime to warming in July and November. Warming along the gradient has contributed to increases in growing-degree days, although to differing degrees, over both temporal scales. However, the length of the growing season has remained unchanged. Finally, the actual and the PRISM interpolated yearly rates rarely showed strong correlations and suggest different warming and cooling trends at most sites. Interpretation of climate trends and their seasonal biases in the Rocky Mountain Front Range are dependent on both elevation and the temporal scale of analysis. Given mismatches between interpolated data and the directly measured station data, we caution against an over-reliance on interpolation methods for documenting local patterns of climatic change. PMID:22970205

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.

The influence of land cover change in the Asian monsoon region on present-day and mid-Holocene climate

NASA Astrophysics Data System (ADS)

Dallmeyer, A.; Claussen, M.

2011-02-01

Using the general circulation model ECHAM5/JSBACH, we investigate the biogeophysical effect of large-scale afforestation and deforestation in the Asian monsoon domain on present-day and mid-Holocene climate. We demonstrate that the applied land cover change does not only modify the local climate but also change the climate in North Africa and the Middle East via teleconnections. Deforestation in the Asian monsoon domain enhances the rainfall in North Africa. In parts of the Sahara summer precipitation is more than doubled. In contrast, afforestation strongly decreases summer rainfall in the Middle East and even leads to the cessation of the rainfall-activity in some parts of this region. Regarding the local climate, deforestation results in a reduction of precipitation and a cooler climate as grass mostly has a higher albedo than forests. However, in the core region of the Asian monsoon the decrease of evaporative cooling in the monsoon season overcompensates this signal and results in a net warming. Afforestation has mainly the opposite effect, although the pattern of change is less clear. It leads to more precipitation in most parts of the Asian monsoon domain and a warmer climate except for the southern regions where a stronger evaporation decreases near-surface temperatures in the monsoon season. When prescribing mid-Holocene insolation, the pattern of local precipitation change differs. Afforestation particularly increases monsoon rainfall in the region along the Yellow River which was the settlement area of major prehistoric cultures. In this region, the effect of land cover change on precipitation is half as large as the orbitally-induced precipitation change. Thus, our model results reveal that mid- to late-Holocene land cover change could strongly have contributed to the decreasing Asian monsoon precipitation during the Holocene known from reconstructions.

The influence of land cover change in the Asian monsoon region on present-day and mid-Holocene climate

NASA Astrophysics Data System (ADS)

Dallmeyer, A.; Claussen, M.

2011-06-01

Using the general circulation model ECHAM5/JSBACH, we investigate the biogeophysical effect of large-scale afforestation and deforestation in the Asian monsoon domain on present-day and mid-Holocene climate. We demonstrate that the applied land cover change does not only modify the local climate but also change the climate in North Africa and the Middle East via teleconnections. Deforestation in the Asian monsoon domain enhances the rainfall in North Africa. In parts of the Sahara summer precipitation is more than doubled. In contrast, afforestation strongly decreases summer rainfall in the Middle East and even leads to the cessation of the rainfall-activity in some parts of this region. Regarding the local climate, deforestation results in a reduction of precipitation and a cooler climate as grass mostly has a higher albedo than forests. However, in the core region of the Asian monsoon the decrease in evaporative cooling in the monsoon season overcompensates this signal and results in a net warming. Afforestation has mainly the opposite effect, although the pattern of change is less clear. It leads to more precipitation in most parts of the Asian monsoon domain and a warmer climate except for the southern regions where a stronger evaporation decreases near-surface temperatures in the monsoon season. When prescribing mid-Holocene insolation, the pattern of local precipitation change differs. Afforestation particularly increases monsoon rainfall in the region along the Yellow River which was the settlement area of major prehistoric cultures. In this region, the effect of land cover change on precipitation is half as large as the orbitally-induced precipitation change. Thus, our model results reveal that mid- to late-Holocene land cover change could strongly have contributed to the decreasing Asian monsoon precipitation during the Holocene known from reconstructions.

Wildfires, mountain pine beetle and large-scale climate in Northern North America.

NASA Astrophysics Data System (ADS)

Macias Fauria, M.; Johnson, E. A.

2009-05-01

Research on the interactions between biosphere and atmosphere and ocean/atmosphere dynamics, concretely on the coupling between ecological processes and large-scale climate, is presented in two studies in Northern North America: the occurrence of large lightning wildfires and the forest area affected by mountain pine beetle (Dendroctonus ponderosae, MPB). In both cases, large-scale climatic patterns such as the Pacific Decadal Oscillation (PDO) and the Arctic Oscillation (AO) operate as low and low and high frequency frameworks, respectively, that control the occurrence, duration and spatial correlation over large areas of key local weather variables which affect specific ecological processes. Warm PDO phases tend to produce persistent (more than 10 days long) positive mid-troposphere anomalies (blocking highs) over western Canada and Alaska. Likewise, positive (negative) AO configurations increase the frequency of blocking highs at mid (high) latitudes of the Northern Hemisphere. Under these conditions, lack of precipitation and prevailing warm air meridional flow rapidly dry fuel over large areas and increase fire hazard. The spatiotemporal patterns of occurrence of large lightning wildfire in Canada and Alaska for 1959-1999 were largely explained by the action and possible interaction of AO and PDO, the AO being more influential over Eastern Canada, the PDO over Western Canada and Alaska. Changes in the dynamics of the PDO are linked to the occurrence of cold winter temperatures in British Columbia (BC), Western Canada. Reduced frequency of cold events during warm PDO winters is consistent with a northward-displaced polar jet stream inhibiting the outflow of cold Arctic air over BC. Likewise, the AO influences the occurrence of winter cold spells in the area. PDO, and to a lesser degree AO, were strongly related to MPB synchrony in BC during 1959-2002, operating through the control of the frequency of extreme cold winter temperatures that affect MPB larvae survival. The onset of a warm PDO phase in 1976 1) increased (decreased) the area burnt by wildfire in the Canadian Boreal Forest (BC) by increasing (decreasing) the frequency of blocking highs in the area, and 2) favored MPB outbreaks in BC by reducing the occurrence of extremely low winter temperatures. Likewise, the exceptionally high and persistent AO values of the late 1980s and 1990s increased area burned in Eastern Canada and MPB activity in the southern and northern parts of BC. A possible recent PDO phase shift may largely reverse these trends.

Climate and litter quality differently modulate the effects of soil fauna on litter decomposition across biomes.

PubMed

García-Palacios, Pablo; Maestre, Fernando T; Kattge, Jens; Wall, Diana H

2013-08-01

Climate and litter quality have been identified as major drivers of litter decomposition at large spatial scales. However, the role played by soil fauna remains largely unknown, despite its importance for litter fragmentation and microbial activity. We synthesised litterbag studies to quantify the effect sizes of soil fauna on litter decomposition rates at the global and biome scales, and to assess how climate, litter quality and soil fauna interact to determine such rates. Soil fauna consistently enhanced litter decomposition at both global and biome scales (average increment ~ 37%). [corrected]. However, climate and litter quality differently modulated the effects of soil fauna on decomposition rates between biomes, from climate-driven biomes to those where climate effects were mediated by changes in litter quality. Our results advocate for the inclusion of biome-specific soil fauna effects on litter decomposition as a mean to reduce the unexplained variation in large-scale decomposition models. © 2013 John Wiley & Sons Ltd/CNRS.

Accounting for sampling patterns reverses the relative importance of trade and climate for the global sharing of exotic plants

USGS Publications Warehouse

Sofaer, Helen R.; Jarnevich, Catherine S.

2017-01-01

AimThe distributions of exotic species reflect patterns of human-mediated dispersal, species climatic tolerances and a suite of other biotic and abiotic factors. The relative importance of each of these factors will shape how the spread of exotic species is affected by ongoing economic globalization and climate change. However, patterns of trade may be correlated with variation in scientific sampling effort globally, potentially confounding studies that do not account for sampling patterns.LocationGlobal.Time periodMuseum records, generally from the 1800s up to 2015.Major taxa studiedPlant species exotic to the United States.MethodsWe used data from the Global Biodiversity Information Facility (GBIF) to summarize the number of plant species with exotic occurrences in the United States that also occur in each other country world-wide. We assessed the relative importance of trade and climatic similarity for explaining variation in the number of shared species while evaluating several methods to account for variation in sampling effort among countries.ResultsAccounting for variation in sampling effort reversed the relative importance of trade and climate for explaining numbers of shared species. Trade was strongly correlated with numbers of shared U.S. exotic plants between the United States and other countries before, but not after, accounting for sampling variation among countries. Conversely, accounting for sampling effort strengthened the relationship between climatic similarity and species sharing. Using the number of records as a measure of sampling effort provided a straightforward approach for the analysis of occurrence data, whereas species richness estimators and rarefaction were less effective at removing sampling bias.Main conclusionsOur work provides support for broad-scale climatic limitation on the distributions of exotic species, illustrates the need to account for variation in sampling effort in large biodiversity databases, and highlights the difficulty in inferring causal links between the economic drivers of invasion and global patterns of exotic species occurrence.

Simulating topographic controls on the abundance of larch forest in eastern Siberia, and its consequences under changing climate

NASA Astrophysics Data System (ADS)

Sato, H.; Kobayashi, H.

2017-12-01

In eastern Siberia, larches (Larix spp.) often exist in pure stands, constructing the world's largest coniferous forest, of which changes can significantly affect the earth's albedo and the global carbon balance. Our previous studies tried to reconstruct this vegetation, aiming to forecast its structures and functions under changing climate (1, 2). In previous studies of simulating vegetation at large geographical scales, the examining area is divided into coarse grid cells such as 0.5 × 0.5 degree resolution, and topographical heterogeneities within each grid cell are just ignored. However, in Siberian larch area, which is located on the environmental edge of existence of forest ecosystem, abundance of larch trees largely depends on topographic condition at the scale of tens to hundreds meters. In our preliminary analysis, we found a quantitative pattern that topographic properties controls the abundance of larch forest via both drought and flooding stresses in eastern Siberia. We, therefore, refined the hydrological sub-model of our dynamic vegetation model SEIB-DGVM, and validated whether the modified model can reconstruct the pattern, examined its impact on the estimation of biomass and vegetation productivity under the current and forecasted future climatic conditions. -- References --1. Sato, H., et al. (2010). "Simulation study of the vegetation structure and function in eastern Siberian larch forests using the individual-based vegetation model SEIB-DGVM." Forest Ecology and Management 259(3): 301-311. 2. Sato, H., et al. (2016). "Endurance of larch forest ecosystems in eastern Siberia under warming trends." Ecology and Evolution

Seasonal climate change patterns due to cumulative CO2 emissions

NASA Astrophysics Data System (ADS)

Partanen, Antti-Ilari; Leduc, Martin; Damon Matthews, H.

2017-07-01

Cumulative CO2 emissions are near linearly related to both global and regional changes in annual-mean surface temperature. These relationships are known as the transient climate response to cumulative CO2 emissions (TCRE) and the regional TCRE (RTCRE), and have been shown to remain approximately constant over a wide range of cumulative emissions. Here, we assessed how well this relationship holds for seasonal patterns of temperature change, as well as for annual-mean and seasonal precipitation patterns. We analyzed an idealized scenario with CO2 concentration growing at an annual rate of 1% using data from 12 Earth system models from the Coupled Model Intercomparison Project Phase 5 (CMIP5). Seasonal RTCRE values for temperature varied considerably, with the highest seasonal variation evident in the Arctic, where RTCRE was about 5.5 °C per Tt C for boreal winter and about 2.0 °C per Tt C for boreal summer. Also the precipitation response in the Arctic during boreal winter was stronger than during other seasons. We found that emission-normalized seasonal patterns of temperature change were relatively robust with respect to time, though they were sub-linear with respect to emissions particularly near the Arctic. Moreover, RTCRE patterns for precipitation could not be quantified robustly due to the large internal variability of precipitation. Our results suggest that cumulative CO2 emissions are a useful metric to predict regional and seasonal changes in precipitation and temperature. This extension of the TCRE framework to seasonal and regional climate change is helpful for communicating the link between emissions and climate change to policy-makers and the general public, and is well-suited for impact studies that could make use of estimated regional-scale climate changes that are consistent with the carbon budgets associated with global temperature targets.

Model Sensitivity to North Atlantic Freshwater Forcing at 8.2 Ka

NASA Technical Reports Server (NTRS)

Morrill, Carrie; Legrande, Allegra Nicole; Renssen, H.; Bakker, P.; Otto-Bliesner, B. L.

2013-01-01

We compared four simulations of the 8.2 ka event to assess climate model sensitivity and skill in responding to North Atlantic freshwater perturbations. All of the simulations used the same freshwater forcing, 2.5 Sv for one year, applied to either the Hudson Bay (northeastern Canada) or Labrador Sea (between Canada's Labrador coast and Greenland). This freshwater pulse induced a decadal-mean slowdown of 10-25%in the Atlantic Meridional Overturning Circulation (AMOC) of the models and caused a large-scale pattern of climate anomalies that matched proxy evidence for cooling in the Northern Hemisphere and a southward shift of the Intertropical Convergence Zone. The multi-model ensemble generated temperature anomalies that were just half as large as those from quantitative proxy reconstructions, however. Also, the duration of AMOC and climate anomalies in three of the simulations was only several decades, significantly shorter than the duration of approx.150 yr in the paleoclimate record. Possible reasons for these discrepancies include incorrect representation of the early Holocene climate and ocean state in the North Atlantic and uncertainties in the freshwater forcing estimates.

Long-term variability of the thunderstorm and hail potential in Europe

NASA Astrophysics Data System (ADS)

Mohr, Susanna; Kunz, Michael; Speidel, Johannes; Piper, David

2016-04-01

Severe thunderstorms and associated hazardous weather events such as hail frequently cause considerable damage to buildings, crops, and automobiles, resulting in large monetary costs in many parts of Europe and the world. To relate single extreme hail events to the historic context and to estimate their return periods and possible trends related to climate change, long-term statistics of hail events are required. Due to the local-scale nature of hail and a lack of suitable observation systems, however, hailstorms are not captured reliably and comprehensively for a long period of time. In view of this fact, different proxies (indirect climate data) obtained from sounding stations and regional climate models can be used to infer the probability and intensity of thunderstorms or hailstorms. In contrast to direct observational data, such proxies are available homogeneously over a long time period. The aim of the study is to investigate the potential for severe thunderstorms and their changes over past decades. Statistical analyses of sounding data show that the convective potential over the past 20 - 30 years has significantly increased over large parts of Central Europe, making severe thunderstorms more likely. A similar picture results from analyses of weather types that are most likely associated with damaging hailstorms. These weather patterns have increased, even if only slightly but nevertheless statistically significantly, in the time period from 1971 to 2000. To improve the diagnostics of hail events in regional climate models, a logistic hail model has been developed by means of a multivariate analysis method. The model is based on a combination of appropriate hail-relevant meteorological parameters. The output of the model is a new index that estimates the potential of the atmosphere for hailstorm development, referred to as potential hail index (PHI). Applied to a high-resolved reanalysis run for Europe driven by NCEP/NCAR1, long-term changes of the PHI for 60 years (1951-2010) show large annual and multiannual variability. The trends are mostly positive in the western parts and negative to the east. However, due to the large temporal variability, the trends are not significant at most of the grid points. Furthermore, it becomes clear that the environmental conditions that favor the formation of hailstorms prevail in larger areas. This finding suggests that, despite the local-scale nature of convective storms, the ambient conditions favoring these events are mainly controlled by large-scale circulation patterns and mechanisms. This result is important to estimate the convective potential of the atmosphere in case of single events.

Anthropogenic and Climatic Influence on Vegetation Fires in Peatland of Insular Southeast Asia

NASA Astrophysics Data System (ADS)

Liew, S.; Miettinen, J.; Salinas Cortijo, S. V.

2011-12-01

Fire is traditionally used as a tool in land clearing by farmers and shifting cultivators in Southeast Asia. However, the small scale clearing of land is increasingly being replaced by modern large-scale conversion of forests into plantations/agricultural land, usually also by fires. Fires get out of control in periods of extreme drought, especially during the El Nino periods, resulting in severe episodes of transboundary air pollution in the form of smoke haze. We use the MODIS active fires product (hotspots) to establish correlations between the temporal and spatial patterns of vegetation fires with climatic variables, land cover change and soil type (peat or non-peat) in the western part of Insular Southeast Asia for a decade from 2001 to 2010. Fire occurrence exhibits a negative correlation with rainfall, and is more severe overall during the El-Nino periods. However, not all regions are equally affected by El-Nino. In Southern Sumatra and Southern Borneo the correlation with El-Nino is high. However, fires in some regions such as the peatland in Riau, Jambi and Sarawak do not appear to be influenced by El-Nino. These regions are also experiencing rapid conversion of forest to large scale plantations.

Large-scale climate variation modifies the winter grouping behavior of endangered Indiana bats

USGS Publications Warehouse

Thogmartin, Wayne E.; McKann, Patrick C.

2014-01-01

Power laws describe the functional relationship between 2 quantities, such as the frequency of a group as the multiplicative power of group size. We examined whether the annual size of well-surveyed wintering populations of endangered Indiana bats (Myotis sodalis) followed a power law, and then leveraged this relationship to predict whether the aggregation of Indiana bats in winter was influenced by global climate processes. We determined that Indiana bat wintering populations were distributed according to a power law (mean scaling coefficient α = −0.44 [95% confidence interval {95% CI} = −0.61, −0.28). The antilog of these annual scaling coefficients ranged between 0.67 and 0.81, coincident with the three-fourths power found in many other biological phenomena. We associated temporal patterns in the annual (1983–2011) scaling coefficient with the North Atlantic Oscillation (NAO) index in August (βNAOAugust = −0.017 [90% CI = −0.032, −0.002]), when Indiana bats are deciding when and where to hibernate. After accounting for the strong effect of philopatry to habitual wintering locations, Indiana bats aggregated in larger wintering populations during periods of severe winter and in smaller populations in milder winters. The association with August values of the NAO indicates that bats anticipate future winter weather conditions when deciding where to roost, a heretofore unrecognized role for prehibernation swarming behavior. Future research is needed to understand whether the three-fourths–scaling patterns we observed are related to scaling in metabolism.

Constraining Centennial-Scale Ecosystem-Climate Interactions with a Pre-colonial Forest Reconstruction across the Upper Midwest and Northeastern United States

NASA Astrophysics Data System (ADS)

Matthes, J. H.; Dietze, M.; Fox, A. M.; Goring, S. J.; McLachlan, J. S.; Moore, D. J.; Poulter, B.; Quaife, T. L.; Schaefer, K. M.; Steinkamp, J.; Williams, J. W.

2014-12-01

Interactions between ecological systems and the atmosphere are the result of dynamic processes with system memories that persist from seconds to centuries. Adequately capturing long-term biosphere-atmosphere exchange within earth system models (ESMs) requires an accurate representation of changes in plant functional types (PFTs) through time and space, particularly at timescales associated with ecological succession. However, most model parameterization and development has occurred using datasets than span less than a decade. We tested the ability of ESMs to capture the ecological dynamics observed in paleoecological and historical data spanning the last millennium. Focusing on an area from the Upper Midwest to New England, we examined differences in the magnitude and spatial pattern of PFT distributions and ecotones between historic datasets and the CMIP5 inter-comparison project's large-scale ESMs. We then conducted a 1000-year model inter-comparison using six state-of-the-art biosphere models at sites that bridged regional temperature and precipitation gradients. The distribution of ecosystem characteristics in modeled climate space reveals widely disparate relationships between modeled climate and vegetation that led to large differences in long-term biosphere-atmosphere fluxes for this region. Model simulations revealed that both the interaction between climate and vegetation and the representation of ecosystem dynamics within models were important controls on biosphere-atmosphere exchange.

Biodiversity promotes primary productivity and growing season lengthening at the landscape scale

PubMed Central

Niklaus, Pascal A.

2017-01-01

Experiments have shown positive biodiversity-ecosystem functioning (BEF) relationships in small plots with model communities established from species pools typically comprising few dozen species. Whether patterns found can be extrapolated to complex, nonexperimental, real-world landscapes that provide ecosystem services to humans remains unclear. Here, we combine species inventories from a large-scale network of 447 1-km2 plots with remotely sensed indices of primary productivity (years 2000–2015). We show that landscape-scale productivity and its temporal stability increase with the diversity of plants and other taxa. Effects of biodiversity indicators on productivity were comparable in size to effects of other important drivers related to climate, topography, and land cover. These effects occurred in plots that integrated different ecosystem types (i.e., metaecosystems) and were consistent over vast environmental and altitudinal gradients. The BEF relations we report are as strong or even exceed the ones found in small-scale experiments, despite different community assembly processes and a species pool comprising nearly 2,000 vascular plant species. Growing season length increased progressively over the observation period, and this shift was accelerated in more diverse plots, suggesting that a large species pool is important for adaption to climate change. Our study further implies that abiotic global-change drivers may mediate ecosystem functioning through biodiversity changes. PMID:28874547

Towards a Multi-scale Montecarlo Climate Emulator for Coastal Flooding and Long-Term Coastal Change Modeling: The Beautiful Problem

NASA Astrophysics Data System (ADS)

Rueda, A.; Alvarez Antolinez, J. A.; Hegermiller, C.; Serafin, K.; Anderson, D. L.; Ruggiero, P.; Barnard, P.; Erikson, L. H.; Vitousek, S.; Camus, P.; Tomas, A.; Gonzalez, M.; Mendez, F. J.

2016-02-01

Long-term coastal evolution and coastal flooding hazards are the result of the non-linear interaction of multiple oceanographic, hydrological, geological and meteorological forcings (e.g., astronomical tide, monthly mean sea level, large-scale storm surge, dynamic wave set-up, shoreline evolution, backshore erosion). Additionally, interannual variability and trends in storminess and sea level rise are climate drivers that must be considered. Moreover, the chronology of the hydraulic boundary conditions plays an important role since a collection of consecutive minor storm events can have more impact than the 100-yr return level event. Therefore, proper modeling of shoreline erosion, beach recovery and coastal flooding should consider the sequence of storms, the multivariate nature of the hydrodynamic forcings, and the different time scales of interest (seasonality, interannual and decadal variability). To address this `beautiful problem', we propose a hybrid approach that combines: (a) numerical hydrodynamic and morphodynamic models (SWAN for wave transformation, a shoreline change model, X-Beach for modeling infragravity waves and erosion of the backshore during extreme events and RFSM-EDA (Jamieson et al, 2012) for high resolution flooding of the coastal hinterland); (b) long-term data bases (observational and hindcast) of sea state parameters, astronomical tides and non-tidal residuals; and (c) statistical downscaling techniques, non-linear data mining, and extreme value models. The statistical downscaling approaches for multivariate variables are based on circulation patterns (Espejo et al., 2014), the chronology of the circulation patterns (Guanche et al, 2013) and the event hydrographs of multivariate extremes, resulting in a time-dependent climate emulator of hydraulic boundary conditions for coupled simulations of the coastal change and flooding models. ReferencesEspejo et al (2014) Spectral ocean wave climate variability based on circulation patterns, J Phys Oc, doi: 10.1175/JPO-D-13-0276.1 Guanche et al (2013) Autoregressive logistic regression applied to atmospheric circulation patterns, Clim Dyn, doi: 10.1007/s00382-013-1690-3 Jamieson et al (2012) A highly efficient 2D flood model with sub-element topography, Proc. Of the Inst Civil Eng., 165(10), 581-595

The role of climate on inter-annual variation in stream nitrate fluxes and concentrations.

PubMed

Gascuel-Odoux, Chantal; Aurousseau, Pierre; Durand, Patrick; Ruiz, Laurent; Molenat, Jérôme

2010-11-01

In recent decades, temporal variations in nitrate fluxes and concentrations in temperate rivers have resulted from the interaction of anthropogenic and climatic factors. The effect of climatic drivers remains unclear, while the relative importance of the drivers seems to be highly site dependent. This paper focuses on 2-6 year variations called meso-scale variations, and analyses the climatic drivers of these variations in a study site characterized by high N inputs from intensive animal farming systems and shallow aquifers with impervious bedrock in a temperate climate. Three approaches are developed: 1) an analysis of long-term records of nitrate fluxes and nitrate concentrations in 30 coastal rivers of Western France, which were well-marked by meso-scale cycles in the fluxes and concentration with a slight hysteresis; 2) a test of the climatic control using a lumped two-box model, which demonstrates that hydrological assumptions are sufficient to explain these meso-scale cycles; and 3) a model of nitrate fluxes and concentrations in two contrasted catchments subjected to recent mitigation measures, which analyses nitrate fluxes and concentrations in relation to N stored in groundwater. In coastal rivers, hydrological drivers (i.e., effective rainfall), and particularly the dynamics of the water table and rather stable nitrate concentration, explain the meso-scale cyclic patterns. In the headwater catchment, agricultural and hydrological drivers can interact according to their settings. The requirements to better distinguish the effect of climate and human changes in integrated water management are addressed: long-term monitoring, coupling the analysis and the modelling of large sets of catchments incorporating different sizes, land uses and environmental factors. Copyright © 2009 Elsevier B.V. All rights reserved.

Climatic controls on hurricane patterns: a 1200-y near-annual record from Lighthouse Reef, Belize

NASA Astrophysics Data System (ADS)

Denommee, K. C.; Bentley, S. J.; Droxler, A. W.

2014-01-01

Tropical cyclones (TCs) are powerful agents of destruction, and understanding climatic controls on TC patterns is of great importance. Over timescales of seasons to several decades, relationships among TC track, frequency, intensity and basin-scale climate changes are well documented by instrumental records. Over centuries to millennia, climate-shift influence on TC regimes remains poorly constrained. To better understand these relationships, records from multiple locations of TC strikes spanning millennia with high temporal resolution are required, but such records are rare. Here we report on a highly detailed sedimentary proxy record of paleo-TC strikes from the Blue Hole of Lighthouse Reef, Belize. Our findings provide an important addition to other high-resolution records, which collectively demonstrate that shifts between active and inactive TC regimes have occurred contemporaneously with shifts hemispheric-scale oceanic and atmospheric circulation patterns such as MDR SSTs and NAO mode, rather than with changes in local climate phenomena as has previously been suggested.

Assessing the climate-scale variability of atmospheric rivers affecting western North America

NASA Astrophysics Data System (ADS)

Gershunov, Alexander; Shulgina, Tamara; Ralph, F. Martin; Lavers, David A.; Rutz, Jonathan J.

2017-08-01

A new method for automatic detection of atmospheric rivers (ARs) is developed and applied to an atmospheric reanalysis, yielding an extensive catalog of ARs land-falling along the west coast of North America during 1948-2017. This catalog provides a large array of variables that can be used to examine AR cases and their climate-scale variability in exceptional detail. The new record of AR activity, as presented, validated and examined here, provides a perspective on the seasonal cycle and the interannual-interdecadal variability of AR activity affecting the hydroclimate of western North America. Importantly, AR intensity does not exactly follow the climatological pattern of AR frequency. Strong links to hydroclimate are demonstrated using a high-resolution precipitation data set. We describe the seasonal progression of AR activity and diagnose linkages with climate variability expressed in Pacific sea surface temperatures, revealing links to Pacific decadal variability, recent regional anomalies, as well as a generally rising trend in land-falling AR activity. The latter trend is consistent with a long-term increase in vapor transport from the warming North Pacific onto the North American continent. The new catalog provides unprecedented opportunities to study the climate-scale behavior and predictability of ARs affecting western North America.

What We Talk About When We Talk About Drought: Tree-ring Perspectives on Model-Data Comparisons in Hydroclimate Research

NASA Astrophysics Data System (ADS)

Cook, B.; Anchukaitis, K. J.

2017-12-01

Comparative analyses of paleoclimate reconstructions and climate model simulations can provide valuable insights into past and future climate events. Conducting meaningful and quantitative comparisons, however, can be difficult for a variety of reasons. Here, we use tree-ring based hydroclimate reconstructions to discuss some best practices for paleoclimate-model comparisons, highlighting recent studies that have successfully used this approach. These analyses have improved our understanding of the Medieval-era megadroughts, ocean forcing of large scale drought patterns, and even climate change contributions to future drought risk. Additional work is needed, however, to better reconcile and formalize uncertainties across observed, modeled, and reconstructed variables. In this regard, process based forward models of proxy-systems will likely be a critical tool moving forward.

First look at changes in flood hazard in the Inter-Sectoral Impact Model Intercomparison Project ensemble

PubMed Central

Dankers, Rutger; Arnell, Nigel W.; Clark, Douglas B.; Falloon, Pete D.; Fekete, Balázs M.; Gosling, Simon N.; Heinke, Jens; Kim, Hyungjun; Masaki, Yoshimitsu; Satoh, Yusuke; Stacke, Tobias; Wada, Yoshihide; Wisser, Dominik

2014-01-01

Climate change due to anthropogenic greenhouse gas emissions is expected to increase the frequency and intensity of precipitation events, which is likely to affect the probability of flooding into the future. In this paper we use river flow simulations from nine global hydrology and land surface models to explore uncertainties in the potential impacts of climate change on flood hazard at global scale. As an indicator of flood hazard we looked at changes in the 30-y return level of 5-d average peak flows under representative concentration pathway RCP8.5 at the end of this century. Not everywhere does climate change result in an increase in flood hazard: decreases in the magnitude and frequency of the 30-y return level of river flow occur at roughly one-third (20–45%) of the global land grid points, particularly in areas where the hydrograph is dominated by the snowmelt flood peak in spring. In most model experiments, however, an increase in flooding frequency was found in more than half of the grid points. The current 30-y flood peak is projected to occur in more than 1 in 5 y across 5–30% of land grid points. The large-scale patterns of change are remarkably consistent among impact models and even the driving climate models, but at local scale and in individual river basins there can be disagreement even on the sign of change, indicating large modeling uncertainty which needs to be taken into account in local adaptation studies. PMID:24344290

Relation between climatic factors, diet and reproductive parameters of Little Terns over a decade

NASA Astrophysics Data System (ADS)

Ramos, Jaime A.; Pedro, Patrícia; Matos, Antonio; Paiva, Vitor H.

2013-11-01

We used 10 years of data on clutch size, egg size and diet, and 8 years of data on timing of laying on Little Terns (Sternula albifrons) breeding in Ria Formosa lagoon system, Algarve, Portugal to assess whether diet acts as an important intermediary between climatic conditions and breeding parameters. We used Generalized Linear Models to relate (1) the relative occurrence and size of the main prey species, sand smelts (Atherina spp.), with environmental variables, a large-scale climate variable, the North Atlantic Oscillation (NAO) index, and a local scale variable, the sea-surface temperature (SST), and (2) the respective effects of sand smelts relative occurrence, NAO index and SST on Little Tern breeding parameters. The diet of Little Terns was dominated by sand smelts, with a frequency occurrence of over 60% in all years. The winter SST (February) was negatively associated with the relative occurrence of sand smelts in the diet of Little Terns during the breeding season which, in turn, was positively associated with Little Tern clutch size. Our results suggest that negative NAO conditions in the Atlantic Ocean, often associated with rougher sea conditions (greater vertical mixing, stronger winds and lower SST) were related with earlier breeding, and lower SST in the surroundings of the colony during winter-spring favour the abundance of prey fish for Little Terns as well as their reproductive parameters. Climate patterns at both large and local scales are likely to change in the future, which may have important implications for estuarine seabirds in Southern Europe.

Life-History Patterns of Lizards of the World.

PubMed

Mesquita, Daniel O; Costa, Gabriel C; Colli, Guarino R; Costa, Taís B; Shepard, Donald B; Vitt, Laurie J; Pianka, Eric R

2016-06-01

Identification of mechanisms that promote variation in life-history traits is critical to understand the evolution of divergent reproductive strategies. Here we compiled a large life-history data set (674 lizard populations, representing 297 species from 263 sites globally) to test a number of hypotheses regarding the evolution of life-history traits in lizards. We found significant phylogenetic signal in most life-history traits, although phylogenetic signal was not particularly high. Climatic variables influenced the evolution of many traits, with clutch frequency being positively related to precipitation and clutches of tropical lizards being smaller than those of temperate species. This result supports the hypothesis that in tropical and less seasonal climates, many lizards tend to reproduce repeatedly throughout the season, producing smaller clutches during each reproductive episode. Our analysis also supported the hypothesis that viviparity has evolved in lizards as a response to cooler climates. Finally, we also found that variation in trait values explained by clade membership is unevenly distributed among lizard clades, with basal clades and a few younger clades showing the most variation. Our global analyses are largely consistent with life-history theory and previous results based on smaller and scattered data sets, suggesting that these patterns are remarkably consistent across geographic and taxonomic scales.

The asymmetric impact of global warming on US drought types and distributions in a large ensemble of 97 hydro-climatic simulations.

PubMed

Huang, Shengzhi; Leng, Guoyong; Huang, Qiang; Xie, Yangyang; Liu, Saiyan; Meng, Erhao; Li, Pei

2017-07-19

Projection of future drought is often involved large uncertainties from climate models, emission scenarios as well as drought definitions. In this study, we investigate changes in future droughts in the conterminous United States based on 97 1/8 degree hydro-climate model projections. Instead of focusing on a specific drought type, we investigate changes in meteorological, agricultural, and hydrological drought as well as the concurrences. Agricultural and hydrological droughts are projected to become more frequent with increase in global mean temperature, while less meteorological drought is expected. Changes in drought intensity scale linearly with global temperature rises under RCP8.5 scenario, indicating the potential feasibility to derive future drought severity given certain global warming amount under this scenario. Changing pattern of concurrent droughts generally follows that of agricultural and hydrological droughts. Under the 1.5 °C warming target as advocated in recent Paris agreement, several hot spot regions experiencing highest droughts are identified. Extreme droughts show similar patterns but with much larger magnitude than the climatology. This study highlights the distinct response of droughts of various types to global warming and the asymmetric impact of global warming on drought distribution resulting in a much stronger influence on extreme drought than on mean drought.

Evaluation of a Mesoscale Convective System in Variable-Resolution CESM

NASA Astrophysics Data System (ADS)

Payne, A. E.; Jablonowski, C.

2017-12-01

Warm season precipitation over the Southern Great Plains (SGP) follows a well observed diurnal pattern of variability, peaking at night-time, due to the eastward propagation of mesoscale convection systems that develop over the eastern slopes of the Rockies in the late afternoon. While most climate models are unable to adequately capture the organization of convection and characteristic pattern of precipitation over this region, models with high enough resolution to explicitly resolve convection show improvement. However, high resolution simulations are computationally expensive and, in the case of regional climate models, are subject to boundary conditions. Newly developed variable resolution global climate models strike a balance between the benefits of high-resolution regional climate models and the large-scale dynamics of global climate models and low computational cost. Recently developed parameterizations that are insensitive to the model grid scale provide a way to improve model performance. Here, we present an evaluation of the newly available Cloud Layers Unified by Binormals (CLUBB) parameterization scheme in a suite of variable-resolution CESM simulations with resolutions ranging from 110 km to 7 km within a regionally refined region centered over the SGP Atmospheric Radiation Measurement (ARM) site. Simulations utilize the hindcast approach developed by the Department of Energy's Cloud-Associated Parameterizations Testbed (CAPT) for the assessment of climate models. We limit our evaluation to a single mesoscale convective system that passed over the region on May 24, 2008. The effects of grid-resolution on the timing and intensity of precipitation, as well as, on the transition from shallow to deep convection are assessed against ground-based observations from the SGP ARM site, satellite observations and ERA-Interim reanalysis.

Connecting medieval megadroughts and surface climate in the Last Millennium Reanalysis

NASA Astrophysics Data System (ADS)

Erb, M. P.; Emile-Geay, J.; Anderson, D. M.; Hakim, G. J.; Horlick, K. A.; Noone, D.; Perkins, W. A.; Steig, E. J.; Tardif, R.

2016-12-01

The North American Drought Atlas shows severe, long-lasting droughts during the Medieval Climate Anomaly. Because drought frequency and severity over the coming century is an area of vital interest, better understanding the causes of these historic droughts is crucial. A variety of research has suggested that a La Niña state was important for producing medieval megadroughts [1], and other work has indicated the potential roles of the Atlantic Multidecadal Oscillation [2] and internal atmospheric variability [3]. Correlations between drought and large-scale climate patterns also exist in the instrumental record [4], but understanding these relationships is far from complete. To investigate these relationships further, a data assimilation approach is employed. Proxy records - including tree rings, corals, and ice cores - are used to constrain climate states over the Common Era. By using general circulation model (GCM) output to quantify the covariances in the climate system, climate can be constrained not just at proxy sites but for all covarying locations and climate fields. Multiple GCMs will be employed to offset the limitations of imperfect model physics. This "Last Millennium Reanalysis" will be used to quantify relationships between North American medieval megadroughts and sea surface temperature patterns in the Atlantic and Pacific. 1. Cook, E. R., et al., Earth-Sci. Rev. 81, 93 (2007). 2. Oglesby, R., et al., Global Planet. Change 84-85, 56 (2012). 3. Stevenson, S., et al., J. Climate 28, 1865 (2015). 4. Cook, B. I., et al., J. Climate 27, 383 (2014).

Adaptation of Land-Use Demands to the Impact of Climate Change on the Hydrological Processes of an Urbanized Watershed

PubMed Central

Lin, Yu-Pin; Hong, Nien-Ming; Chiang, Li-Chi; Liu, Yen-Lan; Chu, Hone-Jay

2012-01-01

The adaptation of land-use patterns is an essential aspect of minimizing the inevitable impact of climate change at regional and local scales; for example, adapting watershed land-use patterns to mitigate the impact of climate change on a region’s hydrology. The objective of this study is to simulate and assess a region’s ability to adapt to hydrological changes by modifying land-use patterns in the Wu-Du watershed in northern Taiwan. A hydrological GWLF (Generalized Watershed Loading Functions) model is used to simulate three hydrological components, namely, runoff, groundwater and streamflow, based on various land-use scenarios under six global climate models. The land-use allocations are simulated by the CLUE-s model for the various development scenarios. The simulation results show that runoff and streamflow are strongly related to the precipitation levels predicted by different global climate models for the wet and dry seasons, but groundwater cycles are more related to land-use. The effects of climate change on groundwater and runoff can be mitigated by modifying current land-use patterns; and slowing the rate of urbanization would also reduce the impact of climate change on hydrological components. Thus, land-use adaptation on a local/regional scale provides an alternative way to reduce the impacts of global climate change on local hydrology. PMID:23202833

The Legacy of Episodic Climatic Events in Shaping Temperate, Broadleaf Forests

NASA Technical Reports Server (NTRS)

Pederson, Neil; Dyer, James M.; McEwan, Ryan W.; Hessl, Amy E.; Mock, Cary J.; Orwig, David A.; Rieder, Harald E.; Cook, Benjamin I.

2015-01-01

In humid, broadleaf-dominated forests where gap dynamics and partial canopy mortality appears to dominate the disturbance regime at local scales, paleoecological evidence shows alteration at regional-scales associated with climatic change. Yet, little evidence of these broad-scale events exists in extant forests. To evaluate the potential for the occurrence of large-scale disturbance, we used 76 tree-ring collections spanning approx. 840 000 sq km and 5327 tree recruitment dates spanning approx. 1.4 million sq km across the humid eastern United States. Rotated principal component analysis indicated a common growth pattern of a simultaneous reduction in competition in 22 populations across 61 000 km2. Growth-release analysis of these populations reveals an intense and coherent canopy disturbance from 1775 to 1780, peaking in 1776. The resulting time series of canopy disturbance is so poorly described by a Gaussian distribution that it can be described as ''heavy tailed,'' with most of the years from 1775 to 1780 comprising the heavy-tail portion of the distribution. Historical documents provide no evidence that hurricanes or ice storms triggered the 1775-1780 event. Instead, we identify a significant relationship between prior drought and years with elevated rates of disturbance with an intense drought occurring from 1772 to 1775. We further find that years with high rates of canopy disturbance have a propensity to create larger canopy gaps indicating repeated opportunities for rapid change in species composition beyond the landscape scale. Evidence of elevated, regional-scale disturbance reveals how rare events can potentially alter system trajectory: a substantial portion of old-growth forests examined here originated or were substantially altered more than two centuries ago following events lasting just a few years. Our recruitment data, comprised of at least 21 species and several shade-intolerant species, document a pulse of tree recruitment at the subcontinental scale during the late-1600s suggesting that this event was severe enough to open large canopy gaps. These disturbances and their climatic drivers support the hypothesis that punctuated, episodic, climatic events impart a legacy in broadleaf-dominated forests centuries after their occurrence. Given projections of future drought, these results also reveal the potential for abrupt, meso- to large-scale forest change in broadleaf-dominated forests over future decades.

Development of National Future Extreme Heat Scenario to Enable the Assessment of Climate Impacts on Public Health

NASA Technical Reports Server (NTRS)

Quattrochi, Dale A.; Cresson, William L.; Al-Hamdan, Mohammad Z.; Estes, Maurice G.

2013-01-01

The project's emphasis is on providing assessments of the magnitude, frequency and geographic distribution of EHEs to facilitate public health studies. We focus on the daily to weekly time scales on which EHEs occur, not on decadal-scale climate changes. There is, however, a very strong connection between air temperature patterns at the two time scales and long-term climatic changes will certainly alter the frequency of EHEs.

Impacts of large-scale atmospheric circulation changes in winter on black carbon transport and deposition to the Arctic

NASA Astrophysics Data System (ADS)

Pozzoli, Luca; Dobricic, Srdan; Russo, Simone; Vignati, Elisabetta

2017-10-01

Winter warming and sea-ice retreat observed in the Arctic in the last decades may be related to changes of large-scale atmospheric circulation pattern, which may impact the transport of black carbon (BC) to the Arctic and its deposition on the sea ice, with possible feedbacks on the regional and global climate forcing. In this study we developed and applied a statistical algorithm, based on the maximum likelihood estimate approach, to determine how the changes of three large-scale weather patterns associated with increasing temperatures in winter and sea-ice retreat in the Arctic impact the transport of BC to the Arctic and its deposition. We found that two atmospheric patterns together determine a decreasing winter deposition trend of BC between 1980 and 2015 in the eastern Arctic while they increase BC deposition in the western Arctic. The increasing BC trend is mainly due to a pattern characterized by a high-pressure anomaly near Scandinavia favouring the transport in the lower troposphere of BC from Europe and North Atlantic directly into to the Arctic. Another pattern with a high-pressure anomaly over the Arctic and low-pressure anomaly over the North Atlantic Ocean has a smaller impact on BC deposition but determines an increasing BC atmospheric load over the entire Arctic Ocean with increasing BC concentrations in the upper troposphere. The results show that changes in atmospheric circulation due to polar atmospheric warming and reduced winter sea ice significantly impacted BC transport and deposition. The anthropogenic emission reductions applied in the last decades were, therefore, crucial to counterbalance the most likely trend of increasing BC pollution in the Arctic.

Accounting for observational uncertainties in the evaluation of low latitude turbulent air-sea fluxes simulated in a suite of IPSL model versions

NASA Astrophysics Data System (ADS)

Servonnat, Jerome; Braconnot, Pascale; Gainusa-Bogdan, Alina

2015-04-01

Turbulent momentum and heat (sensible and latent) fluxes at the air-sea interface are key components of the whole energetic of the Earth's climate and their good representation in climate models is of prime importance. In this work, we use the methodology developed by Braconnot & Frankignoul (1993) to perform a Hotelling T2 test on spatio-temporal fields (annual cycles). This statistic provides a quantitative measure accounting for an estimate of the observational uncertainty for the evaluation of low-latitude turbulent air-sea fluxes in a suite of IPSL model versions. The spread within the observational ensemble of turbulent flux data products assembled by Gainusa-Bogdan et al (submitted) is used as an estimate of the observational uncertainty for the different turbulent fluxes. The methodology holds on a selection of a small number of dominating variability patterns (EOFs) that are common to both the model and the observations for the comparison. Consequently it focuses on the large-scale variability patterns and avoids the possibly noisy smaller scales. The results show that different versions of the IPSL couple model share common large scale model biases, but also that there the skill on sea surface temperature is not necessarily directly related to the skill in the representation of the different turbulent fluxes. Despite the large error bars on the observations the test clearly distinguish the different merits of the different model version. The analyses of the common EOF patterns and related time series provide guidance on the major differences with the observations. This work is a first attempt to use such statistic on the evaluation of the spatio-temporal variability of the turbulent fluxes, accounting for an observational uncertainty, and represents an efficient tool for systematic evaluation of simulated air-seafluxes, considering both the fluxes and the related atmospheric variables. References Braconnot, P., and C. Frankignoul (1993), Testing Model Simulations of the Thermocline Depth Variability in the Tropical Atlantic from 1982 through 1984, J. Phys. Oceanogr., 23(4), 626-647 Gainusa-Bogdan A., Braconnot P. and Servonnat J. (submitted), Using an ensemble data set of turbulent air-sea fluxes to evaluate the IPSL climate model in tropical regions, Journal of Geophysical Research Atmosphere, 2014JD022985

Analysis of the ability of large-scale reanalysis data to define Siberian fire danger in preparation for future fire prediction

NASA Astrophysics Data System (ADS)

Soja, Amber; Westberg, David; Stackhouse, Paul, Jr.; McRae, Douglas; Jin, Ji-Zhong; Sukhinin, Anatoly

2010-05-01

Fire is the dominant disturbance that precipitates ecosystem change in boreal regions, and fire is largely under the control of weather and climate. Fire frequency, fire severity, area burned and fire season length are predicted to increase in boreal regions under current climate change scenarios. Therefore, changes in fire regimes have the potential to compel ecological change, moving ecosystems more quickly towards equilibrium with a new climate. The ultimate goal of this research is to assess the viability of large-scale (1°) data to be used to define fire weather danger and fire regimes, so that large-scale data can be confidently used to predict future fire regimes using large-scale fire weather data, like that available from current Intergovernmental Panel on Climate Change (IPCC) climate change scenarios. In this talk, we intent to: (1) evaluate Fire Weather Indices (FWI) derived using reanalysis and interpolated station data; (2) discuss the advantages and disadvantages of using these distinct data sources; and (3) highlight established relationships between large-scale fire weather data, area burned, active fires and ecosystems burned. Specifically, the Canadian Forestry Service (CFS) Fire Weather Index (FWI) will be derived using: (1) NASA Goddard Earth Observing System version 4 (GEOS-4) large-scale reanalysis and NASA Global Precipitation Climatology Project (GPCP) data; and National Climatic Data Center (NCDC) surface station-interpolated data. Requirements of the FWI are local noon surface-level air temperature, relative humidity, wind speed, and daily (noon-noon) rainfall. GEOS-4 reanalysis and NCDC station-interpolated fire weather indices are generally consistent spatially, temporally and quantitatively. Additionally, increased fire activity coincides with increased FWI ratings in both data products. Relationships have been established between large-scale FWI to area burned, fire frequency, ecosystem types, and these can be use to estimate historic and future fire regimes.

Scale and modeling issues in water resources planning

USGS Publications Warehouse

Lins, H.F.; Wolock, D.M.; McCabe, G.J.

1997-01-01

Resource planners and managers interested in utilizing climate model output as part of their operational activities immediately confront the dilemma of scale discordance. Their functional responsibilities cover relatively small geographical areas and necessarily require data of relatively high spatial resolution. Climate models cover a large geographical, i.e. global, domain and produce data at comparatively low spatial resolution. Although the scale differences between model output and planning input are large, several techniques have been developed for disaggregating climate model output to a scale appropriate for use in water resource planning and management applications. With techniques in hand to reduce the limitations imposed by scale discordance, water resource professionals must now confront a more fundamental constraint on the use of climate models-the inability to produce accurate representations and forecasts of regional climate. Given the current capabilities of climate models, and the likelihood that the uncertainty associated with long-term climate model forecasts will remain high for some years to come, the water resources planning community may find it impractical to utilize such forecasts operationally.

Developing and applying uncertain global climate change projections for regional water management planning

NASA Astrophysics Data System (ADS)

Groves, David G.; Yates, David; Tebaldi, Claudia

2008-12-01

Climate change may impact water resources management conditions in difficult-to-predict ways. A key challenge for water managers is how to incorporate highly uncertain information about potential climate change from global models into local- and regional-scale water management models and tools to support local planning. This paper presents a new method for developing large ensembles of local daily weather that reflect a wide range of plausible future climate change scenarios while preserving many statistical properties of local historical weather patterns. This method is demonstrated by evaluating the possible impact of climate change on the Inland Empire Utilities Agency service area in southern California. The analysis shows that climate change could impact the region, increasing outdoor water demand by up to 10% by 2040, decreasing local water supply by up to 40% by 2040, and decreasing sustainable groundwater yields by up to 15% by 2040. The range of plausible climate projections suggests the need for the region to augment its long-range water management plans to reduce its vulnerability to climate change.

Permafrost Meta-Omics and Climate Change

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

Mackelprang, Rachel; Saleska, Scott R.; Jacobsen, Carsten Suhr

2016-06-29

Permafrost (i.e., soil that has been frozen for at least 2 consecutive years) represents a habitat for microbial life at subzero temperatures (Gilichinsky et al. 2008). Approximately one quarter of the Earth’s surface is underlain by permafrost, which contains 25-50% of the total global soil carbon pool (Schuur et al. 2008, Tarnocai et al. 2009). This carbon is largely protected from microbial decomposition by reduced microbial activity in frozen conditions, but climate change is threatening to induce large-scale permafrost thaw thus exposing it to degradation. The resulting emissions of greenhouse gasses (GHGs) can produce a positive feedback loop and significantlymore » amplify the effects of global warming. Increasing temperatures at high latitudes, changes in precipitation patterns, and frequent fire events have already initiated a widespread degradation of permafrost (Schuur et al. 2015).« less

Controls of multi-modal wave conditions in a complex coastal setting

USGS Publications Warehouse

Hegermiller, Christie; Rueda, Ana C.; Erikson, Li H.; Barnard, Patrick L.; Antolinez, J.A.A.; Mendez, Fernando J.

2017-01-01

Coastal hazards emerge from the combined effect of wave conditions and sea level anomalies associated with storms or low-frequency atmosphere-ocean oscillations. Rigorous characterization of wave climate is limited by the availability of spectral wave observations, the computational cost of dynamical simulations, and the ability to link wave-generating atmospheric patterns with coastal conditions. We present a hybrid statistical-dynamical approach to simulating nearshore wave climate in complex coastal settings, demonstrated in the Southern California Bight, where waves arriving from distant, disparate locations are refracted over complex bathymetry and shadowed by offshore islands. Contributions of wave families and large-scale atmospheric drivers to nearshore wave energy flux are analyzed. Results highlight the variability of influences controlling wave conditions along neighboring coastlines. The universal method demonstrated here can be applied to complex coastal settings worldwide, facilitating analysis of the effects of climate change on nearshore wave climate.

Controls of Multimodal Wave Conditions in a Complex Coastal Setting

NASA Astrophysics Data System (ADS)

Hegermiller, C. A.; Rueda, A.; Erikson, L. H.; Barnard, P. L.; Antolinez, J. A. A.; Mendez, F. J.

2017-12-01

Coastal hazards emerge from the combined effect of wave conditions and sea level anomalies associated with storms or low-frequency atmosphere-ocean oscillations. Rigorous characterization of wave climate is limited by the availability of spectral wave observations, the computational cost of dynamical simulations, and the ability to link wave-generating atmospheric patterns with coastal conditions. We present a hybrid statistical-dynamical approach to simulating nearshore wave climate in complex coastal settings, demonstrated in the Southern California Bight, where waves arriving from distant, disparate locations are refracted over complex bathymetry and shadowed by offshore islands. Contributions of wave families and large-scale atmospheric drivers to nearshore wave energy flux are analyzed. Results highlight the variability of influences controlling wave conditions along neighboring coastlines. The universal method demonstrated here can be applied to complex coastal settings worldwide, facilitating analysis of the effects of climate change on nearshore wave climate.

Towards a Better Understanding of Biomas Burning and Large Scale Climate Dynamics on the West African Monsoon

NASA Astrophysics Data System (ADS)

Ajoku, O.; Norris, J. R.; Miller, A. J.

2017-12-01

Seasonal biomass burning and resulting black carbon (BC) emissions have been well documented to effect regional weather patterns, especially including low level convection. These effects can be due to the hydrophilic and radiative qualities of the aerosols emitted from such burning. This project focuses on utilizing observation and reanalysis data in order to understand the effects of BC advected from the Southern hemisphere impact the dynamics of the West African Monsoon. Our results show that, of all monsoon months, BC advection has a direct impact on precipitation in July. Early analysis indicates that biomass burning occuring near Angola/Congo advects over the Gulf of Guinea, towards the Intertropical Convergence Zone at around 850mb and stabalizes the atmosphere. For a broader impact, this region is home to more than 200 million people and thus understanding these climate patterns may carry great importance.

How Will Climate Change Impact Cholera Outbreaks?

NASA Astrophysics Data System (ADS)

Nasr Azadani, F.; Jutla, A.; Rahimikolu, J.; Akanda, A. S.; Huq, A.; Colwell, R. R.

2014-12-01

Environmental parameters associated with cholera are well documented. However, cholera continues to be a global public health threat. Uncertainty in defining environmental processes affecting growth and multiplication of the cholera bacteria can be affected significantly by changing climate at different temporal and spatial scales, either through amplification of the hydroclimatic cycle or by enhanced variability of large scale geophysical processes. Endemic cholera in the Bengal Delta region of South Asia has a unique pattern of two seasonal peaks and there are associated with asymmetric and episodic variability in river discharge. The first cholera outbreak in spring is related with intrusion of bacteria laden coastal seawater during low river discharge. Cholera occurring during the fall season is hypothesized to be associated with high river discharge related to a cross-contamination of water resources and, therefore, a second wave of disease, a phenomenon characteristic primarily in the inland regions. Because of difficulties in establishing linkage between coarse resolutions of the Global Climate Model (GCM) output and localized disease outbreaks, the impact of climate change on diarrheal disease has not been explored. Here using the downscaling method of Support Vector Machines from HADCM3 and ECHAM models, we show how cholera outbreak patterns are changing in the Bengal Delta. Our preliminary results indicate statistically significant changes in both seasonality and magnitude in the occurrence of cholera over the next century. Endemic cholera is likely to transform into epidemic forms and new geographical areas will be at risk for cholera outbreaks.

Do radiative feedbacks depend on the structure and type of climate forcing, or only on the spatial pattern of surface temperature change?

NASA Astrophysics Data System (ADS)

Haugstad, A.; Battisti, D. S.; Armour, K.

2016-12-01

Earth's climate sensitivity depends critically on the strength of radiative feedbacks linking surface warming to changes in top-of-atmosphere (TOA) radiation. Many studies use a simplistic idea of radiative feedbacks, either by treating them as global mean quantities, or by assuming they can be defined uniquely by geographic location and thus that TOA radiative response depends only on local surface warming. For example, a uniform increase in sea-surface temperature has been widely used as a surrogate for global warming (e.g., Cess et al 1990 and the CMIP 'aqua4k' simulations), with the assumption that this produces the same radiative feedbacks as those arising from a doubling of carbon dioxide - even though the spatial patterns of warming differ. However, evidence suggests that these assumptions are not valid, and local feedbacks may be integrally dependent on the structure of warming or type of climate forcing applied (Rose et al 2014). This study thus investigates the following questions: to what extent do local feedbacks depend on the structure and type of forcing applied? And, to what extent do they depend on the pattern of surface temperature change induced by that forcing? Using an idealized framework of an aquaplanet atmosphere-only model, we show that radiative feedbacks are indeed dependent on the large scale structure of warming and type of forcing applied. For example, the climate responds very differently to two forcings of equal global magnitude but applied in different global regions; the pattern of local feedbacks arising from uniform warming are not the same as that arising from polar amplified warming; and the same local feedbacks can be induced by distinct forcing patterns, provided that they produce the same pattern of surface temperature change. These findings suggest that the so-called `efficacies' of climate forcings can be understood simply in terms of how local feedbacks depend on the temperature patterns they induce.

Nursing organizational climates in public and private hospitals.

PubMed

García, I García; Castillo, R F; Santa-Bárbara, E S

2014-06-01

Researchers study climate to gain an understanding of the psychological environment of organizations, especially in healthcare institutions. Climate is considered to be the set of recurring patterns of individual and group behaviour in an organization. There is evidence confirming a relationship between ethical climate within organizations and job satisfaction. The aim of this study is to describe organizational climate for nursing personnel in public and private hospitals and to confirm the relationships among the climate variables of such hospitals. A correlational study was carried out to measure the organizational climate of one public hospital and two private hospitals in Granada. The Work Environment Scale was used for data collection. The Work Environment Scale includes 10 scales, ranging from 0 to 9, which were used to evaluate social, demographic and organizational climate variables. In this study, 386 subjects were surveyed in three hospitals. A total of 87% of the participants were female and 16% were male. Most participants were nurses (65.6%), followed by nursing aides (20%), and technicians (14.4%). The results obtained reflected different patterns of organizational climate formation, based on hospital type (i.e. public or private) within the Spanish context. Most of the dimensions were below the midpoint of the scale. In conclusion, in public hospitals, there is a greater specialization and the organizational climate is more salient than in the private hospitals. In addition, in the public hospitals, the characteristics of the human resources and their management can have a significant impact on the perception of the climate, which gives greater importance to the organizational climate as decisive of the ethical climate. © The Author(s) 2013.

Modifying a dynamic global vegetation model for simulating large spatial scale land surface water balance

NASA Astrophysics Data System (ADS)

Tang, G.; Bartlein, P. J.

2012-01-01

Water balance models of simple structure are easier to grasp and more clearly connect cause and effect than models of complex structure. Such models are essential for studying large spatial scale land surface water balance in the context of climate and land cover change, both natural and anthropogenic. This study aims to (i) develop a large spatial scale water balance model by modifying a dynamic global vegetation model (DGVM), and (ii) test the model's performance in simulating actual evapotranspiration (ET), soil moisture and surface runoff for the coterminous United States (US). Toward these ends, we first introduced development of the "LPJ-Hydrology" (LH) model by incorporating satellite-based land covers into the Lund-Potsdam-Jena (LPJ) DGVM instead of dynamically simulating them. We then ran LH using historical (1982-2006) climate data and satellite-based land covers at 2.5 arc-min grid cells. The simulated ET, soil moisture and surface runoff were compared to existing sets of observed or simulated data for the US. The results indicated that LH captures well the variation of monthly actual ET (R2 = 0.61, p < 0.01) in the Everglades of Florida over the years 1996-2001. The modeled monthly soil moisture for Illinois of the US agrees well (R2 = 0.79, p < 0.01) with the observed over the years 1984-2001. The modeled monthly stream flow for most 12 major rivers in the US is consistent R2 > 0.46, p < 0.01; Nash-Sutcliffe Coefficients >0.52) with observed values over the years 1982-2006, respectively. The modeled spatial patterns of annual ET and surface runoff are in accordance with previously published data. Compared to its predecessor, LH simulates better monthly stream flow in winter and early spring by incorporating effects of solar radiation on snowmelt. Overall, this study proves the feasibility of incorporating satellite-based land-covers into a DGVM for simulating large spatial scale land surface water balance. LH developed in this study should be a useful tool for studying effects of climate and land cover change on land surface hydrology at large spatial scales.

Development of incremental dynamical downscaling and analysis system for regional scale climate change projections

NASA Astrophysics Data System (ADS)

Wakazuki, Yasutaka; Hara, Masayuki; Fujita, Mikiko; Ma, Xieyao; Kimura, Fujio

2013-04-01

Regional scale climate change projections play an important role in assessments of influences of global warming and include statistical (SD) and dynamical downscaling (DD) approaches. One of DD methods is developed basing on the pseudo-global-warming (PGW) method developed by Kimura and Kitoh (2007) in this study. In general, DD uses regional climate model (RCM) with lateral boundary data. In PGW method, the climatological mean difference estimated by GCMs are added to the objective analysis data (ANAL), and the data are used as the lateral boundary data in the future climate simulations. The ANAL is also used as the lateral boundary conditions of the present climate simulation. One of merits of the PGW method is that influences of biases of GCMs in RCM simulations are reduced. However, the PGW method does not treat climate changes in relative humidity, year-to-year variation, and short-term disturbances. The developing new downscaling method is named as the incremental dynamical downscaling and analysis system (InDDAS). The InDDAS treat climate changes in relative humidity and year-to-year variations. On the other hand, uncertainties of climate change projections estimated by many GCMs are large and are not negligible. Thus, stochastic regional scale climate change projections are expected for assessments of influences of global warming. Many RCM runs must be performed to make stochastic information. However, the computational costs are huge because grid size of RCM runs should be small to resolve heavy rainfall phenomena. Therefore, the number of runs to make stochastic information must be reduced. In InDDAS, climatological differences added to ANAL become statistically pre-analyzed information. The climatological differences of many GCMs are divided into mean climatological difference (MD) and departures from MD. The departures are analyzed by principal component analysis, and positive and negative perturbations (positive and negative standard deviations multiplied by departure patterns (eigenvectors)) with multi modes are added to MD. Consequently, the most likely future states are calculated with climatological difference of MD. For example, future states in cases that temperature increase is large and small are calculated with MD plus positive and negative perturbations of the first mode.

Permafrost thaw in a nested groundwater-flow system

USGS Publications Warehouse

McKenzie, Jeffery M.; Voss, Clifford I.

2013-01-01

Groundwater flow in cold regions containing permafrost accelerates climate-warming-driven thaw and changes thaw patterns. Simulation analyses of groundwater flow and heat transport with freeze/thaw in typical cold-regions terrain with nested flow indicate that early thaw rate is particularly enhanced by flow, the time when adverse environmental impacts of climate-warming-induced permafrost loss may be severest. For the slowest climate-warming rate predicted by the Intergovernmental Panel on Climate Change (IPCC), once significant groundwater flow begins, thick permafrost layers can vanish in several hundred years, but survive over 1,000 years where flow is minimal. Large-scale thaw depends mostly on the balance of heat advection and conduction in the supra-permafrost zone. Surface-water bodies underlain by open taliks allow slow sub-permafrost flow, with lesser influence on regional thaw. Advection dominance over conduction depends on permeability and topography. Groundwater flow around permafrost and flow through permafrost impact thaw differently; the latter enhances early thaw rate. Air-temperature seasonality also increases early thaw. Hydrogeologic heterogeneity and topography strongly affect thaw rates/patterns. Permafrost controls the groundwater/surface-water-geomorphology system; hence, prediction and mitigation of impacts of thaw on ecology, chemical exports and infrastructure require improved hydrogeology/permafrost characterization and understanding

A south equatorial African precipitation dipole and the associated atmospheric circulation

NASA Astrophysics Data System (ADS)

Dezfuli, A. K.; Zaitchik, B.; Gnanadesikan, A.

2013-12-01

South Equatorial Africa (SEA) is a climatically diverse region that includes a dramatic topographic and vegetation contrast between the lowland, humid Congo basin to the west and the East African Plateau to the east. Due to lack of conventional weather data and a tendency for researchers to treat East and western Africa as separate regions, dynamics of the atmospheric water cycle across SEA have received relatively little attention, particularly at subseasonal timescales. Both western and eastern sectors of SEA are affected by large-scale drivers of the water cycle associated with Atlantic variability (western sector), Indian Ocean variability (eastern sector) and Pacific variability (both sectors). However, a specific characteristic of SEA is strong heterogeneity in interannual rainfall variability that cannot be explained by large-scale climatic phenomena. For this reason, this study examines regional climate dynamics on daily time-scale with a focus on the role that the abrupt topographic contrast between the lowland Congo and the East African highlands plays in driving rainfall behavior on short timescales. Analysis of daily precipitation data during November-March reveals a zonally-oriented dipole mode over SEA that explains the leading pattern of weather-scale precipitation variability in the region. The separating longitude of the two poles is coincident with the zonal variation of topography. An anomalous counter-clockwise atmospheric circulation associated with the dipole mode appears over the entire SEA. The circulation is triggered by its low-level westerly component, which is in turn generated by an interhemispheric pressure gradient. These enhanced westerlies hit the East African highlands and produce topographically-driven low-level convergence and convection that further intensifies the circulation. Recent studies have shown that under climate change the position and intensity of subtropical highs in both hemispheres and the intensity of precipitation over equatorial Africa are projected to change. Both of these trends have implications for the manner in which large-scale dynamics will interact with regional topography, affecting the intensity and frequency of the dipole mode characterized in this study and the occurrence of extreme wet and dry spells in the region.

Mushroom biomass and diversity are driven by different spatio-temporal scales along Mediterranean elevation gradients

NASA Astrophysics Data System (ADS)

Alday, Josu G.; Martínez de Aragón, Juan; de-Miguel, Sergio; Bonet, José Antonio

2017-04-01

Mushrooms are important non-wood-forest-products in many Mediterranean ecosystems, being highly vulnerable to climate change. However, the ecological scales of variation of mushroom productivity and diversity, and climate dependence has been usually overlooked due to a lack of available data. We determined the spatio-temporal variability of epigeous sporocarps and the climatic factors driving their fruiting to plan future sustainable management of wild mushrooms production. We collected fruiting bodies in Pinus sylvestris stands along an elevation gradient for 8 consecutive years. Overall, sporocarp biomass was mainly dependent on inter-annual variations, whereas richness was more spatial-scale dependent. Elevation was not significant, but there were clear elevational differences in biomass and richness patterns between ectomycorrhizal and saprotrophic guilds. The main driver of variation was late-summer-early-autumn precipitation. Thus, different scale processes (inter-annual vs. spatial-scale) drive sporocarp biomass and diversity patterns; temporal effects for biomass and ectomycorrhizal fungi vs. spatial scale for diversity and saprotrophic fungi. The significant role of precipitation across fungal guilds and spatio-temporal scales indicates that it is a limiting resource controlling sporocarp production and diversity in Mediterranean regions. The high spatial and temporal variability of mushrooms emphasize the need for long-term datasets of multiple spatial points to effectively characterize fungal fruiting patterns.

Evidence for climate change in the satellite cloud record

DOE PAGES

Norris, Joel R.; Allen, Robert J.; Evan, Amato T.; ...

2016-07-11

Clouds substantially affect Earth’s energy budget by reflecting solar radiation back to space and by restricting emission of thermal radiation to space 1. They are perhaps the largest uncertainty in our understanding of climate change, owing to disagreement among climate models and observational datasets over what cloud changes have occurred during recent decades and will occur in response to global warming 2, 3. This is because observational systems originally designed for monitoring weather have lacked sufficient stability to detect cloud changes reliably over decades unless they have been corrected to remove artefacts 4, 5. Here we show that several independent,more » empirically corrected satellite records exhibit large-scale patterns of cloud change between the 1980s and the 2000s that are similar to those produced by model simulations of climate with recent historical external radiative forcing. Observed and simulated cloud change patterns are consistent with poleward retreat of mid-latitude storm tracks, expansion of subtropical dry zones, and increasing height of the highest cloud tops at all latitudes. The primary drivers of these cloud changes appear to be increasing greenhouse gas concentrations and a recovery from volcanic radiative cooling. Here, these results indicate that the cloud changes most consistently predicted by global climate models are currently occurring in nature.« less

Evidence for climate change in the satellite cloud record

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

Norris, Joel R.; Allen, Robert J.; Evan, Amato T.

Clouds substantially affect Earth’s energy budget by reflecting solar radiation back to space and by restricting emission of thermal radiation to space 1. They are perhaps the largest uncertainty in our understanding of climate change, owing to disagreement among climate models and observational datasets over what cloud changes have occurred during recent decades and will occur in response to global warming 2, 3. This is because observational systems originally designed for monitoring weather have lacked sufficient stability to detect cloud changes reliably over decades unless they have been corrected to remove artefacts 4, 5. Here we show that several independent,more » empirically corrected satellite records exhibit large-scale patterns of cloud change between the 1980s and the 2000s that are similar to those produced by model simulations of climate with recent historical external radiative forcing. Observed and simulated cloud change patterns are consistent with poleward retreat of mid-latitude storm tracks, expansion of subtropical dry zones, and increasing height of the highest cloud tops at all latitudes. The primary drivers of these cloud changes appear to be increasing greenhouse gas concentrations and a recovery from volcanic radiative cooling. Here, these results indicate that the cloud changes most consistently predicted by global climate models are currently occurring in nature.« less

Range-wide parallel climate-associated genomic clines in Atlantic salmon

PubMed Central

Stanley, Ryan R. E.; Wringe, Brendan F.; Guijarro-Sabaniel, Javier; Bourret, Vincent; Bernatchez, Louis; Bentzen, Paul; Beiko, Robert G.; Gilbey, John; Clément, Marie; Bradbury, Ian R.

2017-01-01

Clinal variation across replicated environmental gradients can reveal evidence of local adaptation, providing insight into the demographic and evolutionary processes that shape intraspecific diversity. Using 1773 genome-wide single nucleotide polymorphisms we evaluated latitudinal variation in allele frequency for 134 populations of North American and European Atlantic salmon (Salmo salar). We detected 84 (4.74%) and 195 (11%) loci showing clinal patterns in North America and Europe, respectively, with 12 clinal loci in common between continents. Clinal single nucleotide polymorphisms were evenly distributed across the salmon genome and logistic regression revealed significant associations with latitude and seasonal temperatures, particularly average spring temperature in both continents. Loci displaying parallel clines were associated with several metabolic and immune functions, suggesting a potential basis for climate-associated adaptive differentiation. These climate-based clines collectively suggest evidence of large-scale environmental associated differences on either side of the North Atlantic. Our results support patterns of parallel evolution on both sides of the North Atlantic, with evidence of both similar and divergent underlying genetic architecture. The identification of climate-associated genomic clines illuminates the role of selection and demographic processes on intraspecific diversity in this species and provides a context in which to evaluate the impacts of climate change. PMID:29291123

Climate change impact assessment on food security in Indonesia

NASA Astrophysics Data System (ADS)

Ettema, Janneke; Aldrian, Edvin; de Bie, Kees; Jetten, Victor; Mannaerts, Chris

2013-04-01

As Indonesia is the world's fourth most populous country, food security is a persistent challenge. The potential impact of future climate change on the agricultural sector needs to be addressed in order to allow early implementation of mitigation strategies. The complex island topography and local sea-land-air interactions cannot adequately be represented in large scale General Climate Models (GCMs) nor visualized by TRMM. Downscaling is needed. Using meteorological observations and a simple statistical downscaling tool, local future projections are derived from state-of-the-art, large-scale GCM scenarios, provided by the CMIP5 project. To support the agriculture sector, providing information on especially rainfall and temperature variability is essential. Agricultural production forecast is influenced by several rain and temperature factors, such as rainy and dry season onset, offset and length, but also by daily and monthly minimum and maximum temperatures and its rainfall amount. A simple and advanced crop model will be used to address the sensitivity of different crops to temperature and rainfall variability, present-day and future. As case study area, Java Island is chosen as it is fourth largest island in Indonesia but contains more than half of the nation's population and dominates it politically and economically. The objective is to identify regions at agricultural risk due to changing patterns in precipitation and temperature.

Cod Gadus morhua and climate change: processes, productivity and prediction.

PubMed

Brander, K M

2010-11-01

Environmental factors act on individual fishes directly and indirectly. The direct effects on rates and behaviour can be studied experimentally and in the field, particularly with the advent of ever smarter tags for tracking fishes and their environment. Indirect effects due to changes in food, predators, parasites and diseases are much more difficult to estimate and predict. Climate can affect all life-history stages through direct and indirect processes and although the consequences in terms of growth, survival and reproductive output can be monitored, it is often difficult to determine the causes. Investigation of cod Gadus morhua populations across the whole North Atlantic Ocean has shown large-scale patterns of change in productivity due to lower individual growth and condition, caused by large-scale climate forcing. If a population is being heavily exploited then a drop in productivity can push it into decline unless the level of fishing is reduced: the idea of a stable carrying capacity is a dangerous myth. Overexploitation can be avoided by keeping fishing mortality low and by monitoring and responding rapidly to changes in productivity. There are signs that this lesson has been learned and that G. morhua will continue to be a mainstay of the human diet. © 2010 The Author. Journal of Fish Biology © 2010 The Fisheries Society of the British Isles.

Ecosystem resilience despite large-scale altered hydro climatic conditions

USDA-ARS?s Scientific Manuscript database

Climate change is predicted to increase both drought frequency and duration, and when coupled with substantial warming, will establish a new hydroclimatological paradigm for many regions. Large-scale, warm droughts have recently impacted North America, Africa, Europe, Amazonia, and Australia result...

A multimodel approach to interannual and seasonal prediction of Danube discharge anomalies

NASA Astrophysics Data System (ADS)

Rimbu, Norel; Ionita, Monica; Patrut, Simona; Dima, Mihai

2010-05-01

Interannual and seasonal predictability of Danube river discharge is investigated using three model types: 1) time series models 2) linear regression models of discharge with large-scale climate mode indices and 3) models based on stable teleconnections. All models are calibrated using discharge and climatic data for the period 1901-1977 and validated for the period 1978-2008 . Various time series models, like autoregressive (AR), moving average (MA), autoregressive and moving average (ARMA) or singular spectrum analysis and autoregressive moving average (SSA+ARMA) models have been calibrated and their skills evaluated. The best results were obtained using SSA+ARMA models. SSA+ARMA models proved to have the highest forecast skill also for other European rivers (Gamiz-Fortis et al. 2008). Multiple linear regression models using large-scale climatic mode indices as predictors have a higher forecast skill than the time series models. The best predictors for Danube discharge are the North Atlantic Oscillation (NAO) and the East Atlantic/Western Russia patterns during winter and spring. Other patterns, like Polar/Eurasian or Tropical Northern Hemisphere (TNH) are good predictors for summer and autumn discharge. Based on stable teleconnection approach (Ionita et al. 2008) we construct prediction models through a combination of sea surface temperature (SST), temperature (T) and precipitation (PP) from the regions where discharge and SST, T and PP variations are stable correlated. Forecast skills of these models are higher than forecast skills of the time series and multiple regression models. The models calibrated and validated in our study can be used for operational prediction of interannual and seasonal Danube discharge anomalies. References Gamiz-Fortis, S., D. Pozo-Vazquez, R.M. Trigo, and Y. Castro-Diez, Quantifying the predictability of winter river flow in Iberia. Part I: intearannual predictability. J. Climate, 2484-2501, 2008. Gamiz-Fortis, S., D. Pozo-Vazquez, R.M. Trigo, and Y. Castro-Diez, Quantifying the predictability of winter river flow in Iberia. Part II: seasonal predictability. J. Climate, 2503-2518, 2008. Ionita, M., G. Lohmann, and N. Rimbu, Prediction of spring Elbe river discharge based on stable teleconnections with global temperature and precipitation. J. Climate. 6215-6226, 2008.

Volcanic influence on centennial to millennial Holocene Greenland temperature change.

PubMed

Kobashi, Takuro; Menviel, Laurie; Jeltsch-Thömmes, Aurich; Vinther, Bo M; Box, Jason E; Muscheler, Raimund; Nakaegawa, Toshiyuki; Pfister, Patrik L; Döring, Michael; Leuenberger, Markus; Wanner, Heinz; Ohmura, Atsumu

2017-05-03

Solar variability has been hypothesized to be a major driver of North Atlantic millennial-scale climate variations through the Holocene along with orbitally induced insolation change. However, another important climate driver, volcanic forcing has generally been underestimated prior to the past 2,500 years partly owing to the lack of proper proxy temperature records. Here, we reconstruct seasonally unbiased and physically constrained Greenland Summit temperatures over the Holocene using argon and nitrogen isotopes within trapped air in a Greenland ice core (GISP2). We show that a series of volcanic eruptions through the Holocene played an important role in driving centennial to millennial-scale temperature changes in Greenland. The reconstructed Greenland temperature exhibits significant millennial correlations with K + and Na + ions in the GISP2 ice core (proxies for atmospheric circulation patterns), and δ 18 O of Oman and Chinese Dongge cave stalagmites (proxies for monsoon activity), indicating that the reconstructed temperature contains hemispheric signals. Climate model simulations forced with the volcanic forcing further suggest that a series of large volcanic eruptions induced hemispheric-wide centennial to millennial-scale variability through ocean/sea-ice feedbacks. Therefore, we conclude that volcanic activity played a critical role in driving centennial to millennial-scale Holocene temperature variability in Greenland and likely beyond.

Spatial heterogeneity in ecologically important climate variables at coarse and fine scales in a high-snow mountain landscape.

PubMed

Ford, Kevin R; Ettinger, Ailene K; Lundquist, Jessica D; Raleigh, Mark S; Hille Ris Lambers, Janneke

2013-01-01

Climate plays an important role in determining the geographic ranges of species. With rapid climate change expected in the coming decades, ecologists have predicted that species ranges will shift large distances in elevation and latitude. However, most range shift assessments are based on coarse-scale climate models that ignore fine-scale heterogeneity and could fail to capture important range shift dynamics. Moreover, if climate varies dramatically over short distances, some populations of certain species may only need to migrate tens of meters between microhabitats to track their climate as opposed to hundreds of meters upward or hundreds of kilometers poleward. To address these issues, we measured climate variables that are likely important determinants of plant species distributions and abundances (snow disappearance date and soil temperature) at coarse and fine scales at Mount Rainier National Park in Washington State, USA. Coarse-scale differences across the landscape such as large changes in elevation had expected effects on climatic variables, with later snow disappearance dates and lower temperatures at higher elevations. However, locations separated by small distances (∼20 m), but differing by vegetation structure or topographic position, often experienced differences in snow disappearance date and soil temperature as great as locations separated by large distances (>1 km). Tree canopy gaps and topographic depressions experienced later snow disappearance dates than corresponding locations under intact canopy and on ridges. Additionally, locations under vegetation and on topographic ridges experienced lower maximum and higher minimum soil temperatures. The large differences in climate we observed over small distances will likely lead to complex range shift dynamics and could buffer species from the negative effects of climate change.

Spatial Heterogeneity in Ecologically Important Climate Variables at Coarse and Fine Scales in a High-Snow Mountain Landscape

PubMed Central

Ford, Kevin R.; Ettinger, Ailene K.; Lundquist, Jessica D.; Raleigh, Mark S.; Hille Ris Lambers, Janneke

2013-01-01

Climate plays an important role in determining the geographic ranges of species. With rapid climate change expected in the coming decades, ecologists have predicted that species ranges will shift large distances in elevation and latitude. However, most range shift assessments are based on coarse-scale climate models that ignore fine-scale heterogeneity and could fail to capture important range shift dynamics. Moreover, if climate varies dramatically over short distances, some populations of certain species may only need to migrate tens of meters between microhabitats to track their climate as opposed to hundreds of meters upward or hundreds of kilometers poleward. To address these issues, we measured climate variables that are likely important determinants of plant species distributions and abundances (snow disappearance date and soil temperature) at coarse and fine scales at Mount Rainier National Park in Washington State, USA. Coarse-scale differences across the landscape such as large changes in elevation had expected effects on climatic variables, with later snow disappearance dates and lower temperatures at higher elevations. However, locations separated by small distances (∼20 m), but differing by vegetation structure or topographic position, often experienced differences in snow disappearance date and soil temperature as great as locations separated by large distances (>1 km). Tree canopy gaps and topographic depressions experienced later snow disappearance dates than corresponding locations under intact canopy and on ridges. Additionally, locations under vegetation and on topographic ridges experienced lower maximum and higher minimum soil temperatures. The large differences in climate we observed over small distances will likely lead to complex range shift dynamics and could buffer species from the negative effects of climate change. PMID:23762277

Cloud/climate sensitivity experiments

NASA Technical Reports Server (NTRS)

Roads, J. O.; Vallis, G. K.; Remer, L.

1982-01-01

A study of the relationships between large-scale cloud fields and large scale circulation patterns is presented. The basic tool is a multi-level numerical model comprising conservation equations for temperature, water vapor and cloud water and appropriate parameterizations for evaporation, condensation, precipitation and radiative feedbacks. Incorporating an equation for cloud water in a large-scale model is somewhat novel and allows the formation and advection of clouds to be treated explicitly. The model is run on a two-dimensional, vertical-horizontal grid with constant winds. It is shown that cloud cover increases with decreased eddy vertical velocity, decreased horizontal advection, decreased atmospheric temperature, increased surface temperature, and decreased precipitation efficiency. The cloud field is found to be well correlated with the relative humidity field except at the highest levels. When radiative feedbacks are incorporated and the temperature increased by increasing CO2 content, cloud amounts decrease at upper-levels or equivalently cloud top height falls. This reduces the temperature response, especially at upper levels, compared with an experiment in which cloud cover is fixed.

Modelling the Effects of Sea-level, Climate Change, Geology, and Tectonism on the Morphology of the Amazon River Valley and its Floodplain

NASA Astrophysics Data System (ADS)

Aalto, R. E.; Cremon, E.; Dunne, T.

2017-12-01

How continental-scale rivers respond to climate, geology, and sea level change is not well represented in morphodynamic models. Large rivers respond to influences less apparent in the form and deposits of smaller streams, as the huge scales require long time periods for changes in form and behavior. Tectonic deformation and excavation of resistant deposits can affect low gradient continental-scale rivers, thereby changing flow pathways, channel slope and sinuosity, along-stream patterns of sediment transport capacity, channel patterns, floodplain construction, and valley topography. Nowhere are such scales of morphodynamic response grander than the Amazon River, as described in papers by L.A.K. Mertes. Field-based understanding has improved over the intervening decades, but mechanistic models are needed to simulate and synthesize key morphodynamic components relevant to the construction of large river valleys, with a focus on the Amazon. The Landscape-Linked Environmental Model (LLEM) utilizes novel massively parallel computer architectures to simulate multiple-direction flow, sediment transport, deposition, and incision for exceptionally large (30-80 million nodes per compute unit) lowland dispersal systems. LLEM represents key fluvial processes such as bed and bar deposition, lateral and vertical erosion/incision, levee and floodplain construction, floodplain hydrology, `badlands dissection' of weak sedimentary deposits during falling sea level, tectonic and glacial-isostatic deformation, and provides a 3D record of created stratigraphy and underlying bedrock. We used LLEM to simulate the development of the main valley of the Amazon over the last million years, exploring the propagation of incision waves and system dissection during glacial lowstands, followed by rapid valley filling and extreme lateral mobility of channels during interglacials. We present metrics, videos, and 3D fly-throughs characterizing how system development responds to key assumptions, comparing highly detailed model outcomes against field-documented reality.

Atmospheric circulation patterns and spatial climatic variations in Beringia

NASA Astrophysics Data System (ADS)

Mock, Cary J.; Bartlein, Patrick J.; Anderson, Patricia M.

1998-08-01

Analyses of more than 40 years of climatic data reveal intriguing spatial variations in climatic patterns for Beringia (North-eastern Siberia and Alaska), aiding the understanding of the hierarchy of climatic controls that operate at different spatial scales within the Arctic. A synoptic climatology, using a subjective classification methodology on January and July sea level pressure, and July 500 hPa height anomaly patterns, identified 13 major atmospheric circulation patterns (26 pairs consisting of 13 synoptic/temperature and 13 synoptic/precipitation comparisons) that occur over Beringia. Composite anomaly maps of circulation, temperature, and precipitation described the spatial variability of surface climatic responses to circulation. Results indicate that nine synoptic pairs yield homogeneous surface climatic anomaly patterns throughout most of Beringia. However, many of the surface climatic responses illustrate heterogeneous anomaly patterns as a result of variations in circulation controls, such as troughing over East Asia and the Pacific subtropical high superimposed over topography, with small shifts in atmospheric circulation dramatically altering spatial variations of anomaly patterns. Distinctive contrasts in climatic responses, as suggested from ten synoptic pairs, are clearly evident for Western Beringia versus Eastern Beringia. These results offer important implications for scholars interested in assessing late Quaternary climatic change in the region from interannual to millennial timescales.

Impact of volcanic eruptions on the climate of the 1st millennium AD in a comprehensive climate simulation

NASA Astrophysics Data System (ADS)

Wagner, Sebastian; Zorita, Eduardo

2015-04-01

The climate of the 1st millennium AD shows some remarkable differences compared to the last millennium concerning variation in external forcings. Together with an orbitally induced increased solar insolation during the northern hemisphere summer season and a general lack of strong solar minima, the frequency and intensity of large tropical and extratropical eruptions is decreased. Here we present results of a new climate simulation carried out with the comprehensive Earth System Model MPI-ESM-P forced with variations in orbital, solar, volcanic and greenhouse gas variations and land use changes for the last 2,100 years. The atmospheric model has a horizontal resolution of T63 (approx. 125x125 km) and therefore also allows investigations of regional-to-continental scale climatic phenomena. The volcanic forcing was reconstructed based on a publication by Sigl et al. (2013) using the sulfate records of the NEEM and WAIS ice cores. To obtain information on the aerosol optical depth (AOD) these sulfate records were scaled to an established reconstruction from Crowley and Unterman (2010), which is also a standard forcing in the framework of CMIP5/PMIP3. A comparison between the newly created data set with the Crowley and Unterman dataset reveals that the new reconstruction shows in general weaker intensities, especially of the large tropical outbreaks and fewer northern hemispheric small-to-medium scale eruptions. However, the general pattern in the overlapping period is similar. A hypothesis that can be tested with the simulation is whether the reduced volcanic intensity of the 1st millennium AD contributed to the elevated temperature levels over Europe, evident within a new proxy-based reconstruction. On the other hand, the few but large volcanic eruptions, e.g. the 528 AD event, also induced negative decadal-scale temperature anomalies. Another interesting result of the simulation relates to the 79 AD eruption of the Vesuvius, which caused the collapse of the city of Pompeii and its surroundings. Despite its severe local effects the eruption does not show a clear-cut hemispheric or global cooling. Therefore the simulation allows investigations on the effect of individual and clustered eruptions on the climate in the 1st millennium AD and its potential influence to human induced migration periods and decay of cultures in different regions.

Habitat availability and gene flow influence diverging local population trajectories under scenarios of climate change: a place-based approach.

PubMed

Schwalm, Donelle; Epps, Clinton W; Rodhouse, Thomas J; Monahan, William B; Castillo, Jessica A; Ray, Chris; Jeffress, Mackenzie R

2016-04-01

Ecological niche theory holds that species distributions are shaped by a large and complex suite of interacting factors. Species distribution models (SDMs) are increasingly used to describe species' niches and predict the effects of future environmental change, including climate change. Currently, SDMs often fail to capture the complexity of species' niches, resulting in predictions that are generally limited to climate-occupancy interactions. Here, we explore the potential impact of climate change on the American pika using a replicated place-based approach that incorporates climate, gene flow, habitat configuration, and microhabitat complexity into SDMs. Using contemporary presence-absence data from occupancy surveys, genetic data to infer connectivity between habitat patches, and 21 environmental niche variables, we built separate SDMs for pika populations inhabiting eight US National Park Service units representing the habitat and climatic breadth of the species across the western United States. We then predicted occurrence probability under current (1981-2010) and three future time periods (out to 2100). Occurrence probabilities and the relative importance of predictor variables varied widely among study areas, revealing important local-scale differences in the realized niche of the American pika. This variation resulted in diverse and - in some cases - highly divergent future potential occupancy patterns for pikas, ranging from complete extirpation in some study areas to stable occupancy patterns in others. Habitat composition and connectivity, which are rarely incorporated in SDM projections, were influential in predicting pika occupancy in all study areas and frequently outranked climate variables. Our findings illustrate the importance of a place-based approach to species distribution modeling that includes fine-scale factors when assessing current and future climate impacts on species' distributions, especially when predictions are intended to manage and conserve species of concern within individual protected areas. © 2015 John Wiley & Sons Ltd.

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.

Carbon Cycle Model Linkage Project (CCMLP): Evaluating Biogeochemical Process Models with Atmospheric Measurements and Field Experiments

NASA Astrophysics Data System (ADS)

Heimann, M.; Prentice, I. C.; Foley, J.; Hickler, T.; Kicklighter, D. W.; McGuire, A. D.; Melillo, J. M.; Ramankutty, N.; Sitch, S.

2001-12-01

Models of biophysical and biogeochemical proceses are being used -either offline or in coupled climate-carbon cycle (C4) models-to assess climate- and CO2-induced feedbacks on atmospheric CO2. Observations of atmospheric CO2 concentration, and supplementary tracers including O2 concentrations and isotopes, offer unique opportunities to evaluate the large-scale behaviour of models. Global patterns, temporal trends, and interannual variability of the atmospheric CO2 concentration and its seasonal cycle provide crucial benchmarks for simulations of regionally-integrated net ecosystem exchange; flux measurements by eddy correlation allow a far more demanding model test at the ecosystem scale than conventional indicators, such as measurements of annual net primary production; and large-scale manipulations, such as the Duke Forest Free Air Carbon Enrichment (FACE) experiment, give a standard to evaluate modelled phenomena such as ecosystem-level CO2 fertilization. Model runs including historical changes of CO2, climate and land use allow comparison with regional-scale monthly CO2 balances as inferred from atmospheric measurements. Such comparisons are providing grounds for some confidence in current models, while pointing to processes that may still be inadequately treated. Current plans focus on (1) continued benchmarking of land process models against flux measurements across ecosystems and experimental findings on the ecosystem-level effects of enhanced CO2, reactive N inputs and temperature; (2) improved representation of land use, forest management and crop metabolism in models; and (3) a strategy for the evaluation of C4 models in a historical observational context.

Invasive plants in Arizona's forests and woodlands

Treesearch

Alix Rogstad; Tom DeGomez; Carol Hull Sieg

2007-01-01

Climate is critically linked to vegetation dynamics at many different spatial and temporal scales across the desert Southwest. Small-scale, short duration monsoon season thunderstorms can bring much needed precipitation to small patches of vegetation or can initiate widespread flooding. Long-term variations in climate related to ocean circulation patterns can create...

Where do the treeless tundra areas of northern highlands fit in the global biome system: toward an ecologically natural subdivision of the tundra biome.

PubMed

Virtanen, Risto; Oksanen, Lauri; Oksanen, Tarja; Cohen, Juval; Forbes, Bruce C; Johansen, Bernt; Käyhkö, Jukka; Olofsson, Johan; Pulliainen, Jouni; Tømmervik, Hans

2016-01-01

According to some treatises, arctic and alpine sub-biomes are ecologically similar, whereas others find them highly dissimilar. Most peculiarly, large areas of northern tundra highlands fall outside of the two recent subdivisions of the tundra biome. We seek an ecologically natural resolution to this long-standing and far-reaching problem. We studied broad-scale patterns in climate and vegetation along the gradient from Siberian tundra via northernmost Fennoscandia to the alpine habitats of European middle-latitude mountains, as well as explored those patterns within Fennoscandian tundra based on climate-vegetation patterns obtained from a fine-scale vegetation map. Our analyses reveal that ecologically meaningful January-February snow and thermal conditions differ between different types of tundra. High precipitation and mild winter temperatures prevail on middle-latitude mountains, low precipitation and usually cold winters prevail on high-latitude tundra, and Scandinavian mountains show intermediate conditions. Similarly, heath-like plant communities differ clearly between middle latitude mountains (alpine) and high-latitude tundra vegetation, including its altitudinal extension on Scandinavian mountains. Conversely, high abundance of snowbeds and large differences in the composition of dwarf shrub heaths distinguish the Scandinavian mountain tundra from its counterparts in Russia and the north Fennoscandian inland. The European tundra areas fall into three ecologically rather homogeneous categories: the arctic tundra, the oroarctic tundra of northern heights and mountains, and the genuinely alpine tundra of middle-latitude mountains. Attempts to divide the tundra into two sub-biomes have resulted in major discrepancies and confusions, as the oroarctic areas are included in the arctic tundra in some biogeographic maps and in the alpine tundra in others. Our analyses based on climate and vegetation criteria thus seem to resolve the long-standing biome delimitation problem, help in consistent characterization of research sites, and create a basis for further biogeographic and ecological research in global tundra environments.

Examining the Influence of Teleconnection Patterns on CO2 Fluxes at an Old-Growth Forest Scaling from Stand to Region Using MODIS

NASA Astrophysics Data System (ADS)

Wharton, S.; Chasmer, L.; Falk, M.; Paw U, K.

2007-12-01

In this study, year-to-year variability in three of the major Pacific teleconnection patterns were examined to determine if CO2 and H2O fluxes at an old-growth forest in the Pacific Northwest were affected by climatic changes associated with these patterns. The three cycles examined are the Pacific Decadal Oscillation, Pacific/North American Oscillation and El Niño-Southern Oscillation. We centered our study on the Wind River Canopy Crane, an AmeriFlux tower located in a 500 year old conifer forest in southern Washington State. CO2 and H2O fluxes have been measured continuously for six years using the eddy covariance method. The objectives of this study are to: 1. determine to what extent teleconnection patterns influence measured CO2 and H2O fluxes through mechanistic anomalies; 2. ascertain if climatic shifts affect annual vegetation canopy characteristics; and 3. make comparisons at the local and regional scales using MODIS. The ecosystem was a significant sink of carbon (-207 gC m-2 year-1) in 1999 but turned into a large carbon source (+ 100 gC m-2 year-1) in 2003. NEE significantly (above the 95th CI) lags the PNA, ENSO and PDO indicating that these patterns affect the forest carbon budget across overlapping time scales. To ascertain the influence of atmospheric patterns on fluxes, we categorized the flux measurement years based on in-phase climate events (1999 = La Niña/cool PDO, 2003 = El Niño/warm PDO, 2000-2002, 2004 = neutral ENSO years). The results of this analysis indicate that the Pacific Ocean/atmospheric oscillation anomalies explain much of variance in annual NEE (R2 = 0.78 between NEE and the PDO, R2 = 0.87 for the PNA, and R2 = 0.56 for ENSO). Teleconnection patterns are found to be associated mostly with air temperature, precipitation, and incoming light radiation (cloudy vs. sunny conditions). Important meteorological driving mechanisms of fluxes include: water- use efficiency (WUE), light-use efficiency (LUE) and canopy structure parameters (e.g., fPAR). Tower-based fPAR was strongly related to NEE (R2 = 0.78) and climatic patterns (R2 = 0.84 with ENSO and R2 = 0.76 with PDO). Variability in fluxes may be a result of changes in the canopy structural characteristics; for example higher, fPAR (e.g., 2003) correlated well with increased respiration fluxes. MODIS data (200 km X 200 km area) were obtained to determine if anomalies in vegetation indices and canopy structure could be linked to teleconnection patterns at the site level and across the region. The MODIS-derived Enhanced Vegetation Index (EVI) correlated well with yearly cumulative NEE at the tower and regional EVI anomalies were strongly negatively correlated with the annual PDO index (R2 = 0.9). MODIS-derived fPAR product correlated with yearly variability in the PDO (R2 = 0.34) at the site level. Therefore, there is reasonable expectation that structural changes, as a result of climate variability during strongly positive or negative teleconnection patterns, will be observed in other parts of the Pacific Northwest. MODIS data is useful for identifying the effects of teleconnections across a regional scale.

Challenges in global modeling of wetland extent and wetland methane dynamics

NASA Astrophysics Data System (ADS)

Spahni, R.; Melton, J. R.; Wania, R.; Stocker, B. D.; Zürcher, S.; Joos, F.

2012-12-01

Global wetlands are known to be climate sensitive, and are the largest natural emitters of methane (CH4). Increased wetland CH4 emissions could act as a positive feedback to future warming. Modelling of global wetland extent and wetland CH4 dynamics remains a challenge. Here we present results from the Wetland and Wetland CH4 Inter-comparison of Models Project (WETCHIMP) that investigated our present ability to simulate large scale wetland characteristics (e.g. wetland type, water table, carbon cycling, gas transport, etc.) and corresponding CH4 emissions. Ten models participated, covering the spectrum from simple to relatively complex, including models tailored either for regional or global simulations. The WETCHIMP experiments showed that while models disagree in spatial and temporal patterns of simulated CH4 emissions and wetland areal extent, they all do agree on a strong positive response to increased carbon dioxide concentrations. WETCHIMP made clear that we currently lack observation data sets that are adequate to evaluate model CH4 soil-atmosphere fluxes at a spatial scale comparable to model grid cells. Thus there are substantial parameter and structural uncertainties in large-scale CH4 emission models. As an illustration of the implications of CH4 emissions on climate we show results of the LPX-Bern model, as one of the models participating in WETCHIMP. LPX-Bern is forced with observed 20th century climate and climate output from an ensemble of five comprehensive climate models for a low and a high emission scenario till 2100 AD. In the high emission scenario increased substrate availability for methanogenesis due to a strong stimulation of net primary productivity, and faster soil turnover leads to an amplification of CH4 emissions with the sharpest increase in peatlands (+180% compared to present). Combined with prescribed anthropogenic CH4 emissions, simulated atmospheric CH4 concentration reaches ~4500 ppbv by 2100 AD, about 800 ppbv more than in standard IPCC scenarios. This represents a significant contribution to radiative forcing of global climate.

Time-lag effects of global vegetation responses to climate change.

PubMed

Wu, Donghai; Zhao, Xiang; Liang, Shunlin; Zhou, Tao; Huang, Kaicheng; Tang, Bijian; Zhao, Wenqian

2015-09-01

Climate conditions significantly affect vegetation growth in terrestrial ecosystems. Due to the spatial heterogeneity of ecosystems, the vegetation responses to climate vary considerably with the diverse spatial patterns and the time-lag effects, which are the most important mechanism of climate-vegetation interactive effects. Extensive studies focused on large-scale vegetation-climate interactions use the simultaneous meteorological and vegetation indicators to develop models; however, the time-lag effects are less considered, which tends to increase uncertainty. In this study, we aim to quantitatively determine the time-lag effects of global vegetation responses to different climatic factors using the GIMMS3g NDVI time series and the CRU temperature, precipitation, and solar radiation datasets. First, this study analyzed the time-lag effects of global vegetation responses to different climatic factors. Then, a multiple linear regression model and partial correlation model were established to statistically analyze the roles of different climatic factors on vegetation responses, from which the primary climate-driving factors for different vegetation types were determined. The results showed that (i) both the time-lag effects of the vegetation responses and the major climate-driving factors that significantly affect vegetation growth varied significantly at the global scale, which was related to the diverse vegetation and climate characteristics; (ii) regarding the time-lag effects, the climatic factors explained 64% variation of the global vegetation growth, which was 11% relatively higher than the model ignoring the time-lag effects; (iii) for the area with a significant change trend (for the period 1982-2008) in the global GIMMS3g NDVI (P < 0.05), the primary driving factor was temperature; and (iv) at the regional scale, the variation in vegetation growth was also related to human activities and natural disturbances. Considering the time-lag effects is quite important for better predicting and evaluating the vegetation dynamics under the background of global climate change. © 2015 John Wiley & Sons Ltd.

Large-scale circulation classification and its links to observed precipitation in the eastern and central Tibetan Plateau

NASA Astrophysics Data System (ADS)

Liu, Wenbin; Wang, Lei; Chen, Deliang; Tu, Kai; Ruan, Chengqing; Hu, Zengyun

2016-06-01

The relationship between the large-scale circulation dynamics and regional precipitation regime in the Tibetan Plateau (TP) has so far not been well understood. In this study, we classify the circulation types using the self-organizing maps based on the daily field of 500 hPa geopotential height and link them to the precipitation climatology in the eastern and central TP. By virtue of an objective determining method, 18 circulation types are quantified. The results show that the large amount of precipitation in summer is closely related to the circulation types in which the enhanced and northward shifted subtropical high (SH) over the northwest Pacific and the obvious cyclconic circulation anomaly over the Bay of Bengal are helpful for the Indian summer monsoon and East Asian summer monsoon to take abundant low-latitude moisture to the eastern and southern TP. On the contrary, the dry winter in the central and eastern Tibet corresponds to the circulation types with divergence over the central and eastern TP and the water vapor transportations of East Asian winter monsoon and mid-latitude westerly are very weak. Some circulation types are associated with some well-known circulation patterns/monsoons influencing the TP (e.g. East Atlantic Pattern, El Niño Southern Oscillation, Indian Summer Monsoon and the mid-latitude westerly), and exhibit an overall good potential for explaining the variability of regional seasonal precipitation. Moreover, the climate shift signals in the late 1970s over the eastern Pacific/North Pacific Oceans could also be reflected by both the variability of some circulation types and their correspondingly composite precipitations. This study extends our understandings for the large-scale atmospheric dynamics and their linkages with regional precipitation and is beneficial for the climate change projection and related adaptation activities in the highest and largest plateau in the world.

Influence of Wave Energetics on Nearshore Storms and Adjacent Shoreline Morphology

NASA Astrophysics Data System (ADS)

Wadman, H. M.; McNinch, J. E.; Hanson, J.

2008-12-01

Large-scale climatic forcings (such as NAO and ENSO) are known to induce fluctuations in regional storm frequency and intensity. Morphology-based studies have traditionally focused on individual storms and their influence on the nearshore coastal wave regime and shoreline response. Few studies have attempted to link long-term observed changes in shoreline position, beach, and nearshore morphology with large-scale climatic forcings that influence regional storm patterns. In order to predict the response of coastlines to future sea level rise and climate change, we need to understand how changes in the frequency of storms affecting nearshore regions (nearshore storms) may influence trends in shoreline position and nearshore morphology. Nearly 30 years of wave data (deep and shallow) collected off of Duck, NC are examined for trends in storm frequency and/or intensity. Changes in shoreline position and shoreface elevation, as observed from monthly beach transects over the same period, are also investigated in light of the observed trends in hydrodynamic forcings. Our preliminary analysis was unable to identify any consistent linear trends (increases or decreases) in frequency or intensity over the ~30-year time period in either the offshore wave heights or the nearshore storm record. These data might suggest that previous observations of recent increases in storm intensity and frequency, speculated to be due to climate change, might be spatially limited. Future analyses will partition the contributions from individual wind sea and swell events in order to better identify long-term trends in wave energetics from the various wave generation regions in the Atlantic. At this location, offshore wave height and the nearshore storm record are dominated by seasonal fluctuations and a strong interdecadal- to decadal periodicity. Previous research in Duck, NC has suggested that changes in shoreline position and shoreface elevations are related both to seasonal trends as well as "storm groupiness". Our analyses support these findings, but also identify interdecadal- to decadal trends in the nearshore morphology. Despite these fluctuations, the overall position of the shoreline and elevation of the shoreface shows little net change over the 30 years investigated. We hypothesize that the interdecadal- to decadal periodicity in the morphology is driven largely by the influences of large-scale climatic forcings on the nearshore wave regime as reflected in the storm record. We also explore the relationship between morphological periodicity, storm and wave height periodicity, and climatic fluctuations.

Human and biophysical influences on fire occurrence in the United States

USGS Publications Warehouse

Hawbaker, Todd J.; Radeloff, Volker C.; Stewart, Susan I.; Hammer, Roger B.; Keuler, Nicholas S.; Clayton, Murray K.

2013-01-01

National-scale analyses of fire occurrence are needed to prioritize fire policy and management activities across the United States. However, the drivers of national-scale patterns of fire occurrence are not well understood, and how the relative importance of human or biophysical factors varies across the country is unclear. Our research goal was to model the drivers of fire occurrence within ecoregions across the conterminous United States. We used generalized linear models to compare the relative influence of human, vegetation, climate, and topographic variables on fire occurrence in the United States, as measured by MODIS active fire detections collected between 2000 and 2006. We constructed models for all fires and for large fires only and generated predictive maps to quantify fire occurrence probabilities. Areas with high fire occurrence probabilities were widespread in the Southeast, and localized in the Mountain West, particularly in southern California, Arizona, and New Mexico. Probabilities for large-fire occurrence were generally lower, but hot spots existed in the western and south-central United States The probability of fire occurrence is a critical component of fire risk assessments, in addition to vegetation type, fire behavior, and the values at risk. Many of the hot spots we identified have extensive development in the wildland–urban interface and are near large metropolitan areas. Our results demonstrated that human variables were important predictors of both all fires and large fires and frequently exhibited nonlinear relationships. However, vegetation, climate, and topography were also significant variables in most ecoregions. If recent housing growth trends and fire occurrence patterns continue, these areas will continue to challenge policies and management efforts seeking to balance the risks generated by wildfires with the ecological benefits of fire.

Paleobiology, community ecology, and scales of ecological pattern.

PubMed

Jablonski, D; Sepkoski, J J

1996-07-01

The fossil record provides a wealth of data on the role of regional processes and historical events in shaping biological communities over a variety of time scales. The Quaternary record with its evidence of repeated climatic change shows that both terrestrial and marine species shifted independently rather than as cohesive assemblages over scales of thousands of years. Larger scale patterns also show a strong individualistic component to taxon dynamics; assemblage stability, when it occurs, is difficult to separate from shared responses to low rates of environmental change. Nevertheless, the fossil record does suggest that some biotic interactions influence large-scale ecological and evolutionary patterns, albeit in more diffuse and protracted fashions than those generally studied by community ecologists. These include: (1) the resistance by incumbents to the establishment of new or invading taxa, with episodes of explosive diversification often appearing contingent on the removal of incumbents at extinction events; (2) steady states of within-habitat and global diversity at longer time scales (10(7)-l0(8) yr), despite enormous turnover of taxa; and (3) morphological and biogeographic responses to increased intensities of predation and substratum disturbance over similarly long time scales. The behavior of species and communities over the array of temporal and spatial scales in the fossil record takes on additional significance for framing conservation strategies, and for understanding recovery of species, lineages, and communities from environmental changes.

Paleobiology, community ecology, and scales of ecological pattern

NASA Technical Reports Server (NTRS)

Jablonski, D.; Sepkoski, J. J. Jr; Sepkoski JJ, J. r. (Principal Investigator)

1996-01-01

The fossil record provides a wealth of data on the role of regional processes and historical events in shaping biological communities over a variety of time scales. The Quaternary record with its evidence of repeated climatic change shows that both terrestrial and marine species shifted independently rather than as cohesive assemblages over scales of thousands of years. Larger scale patterns also show a strong individualistic component to taxon dynamics; assemblage stability, when it occurs, is difficult to separate from shared responses to low rates of environmental change. Nevertheless, the fossil record does suggest that some biotic interactions influence large-scale ecological and evolutionary patterns, albeit in more diffuse and protracted fashions than those generally studied by community ecologists. These include: (1) the resistance by incumbents to the establishment of new or invading taxa, with episodes of explosive diversification often appearing contingent on the removal of incumbents at extinction events; (2) steady states of within-habitat and global diversity at longer time scales (10(7)-l0(8) yr), despite enormous turnover of taxa; and (3) morphological and biogeographic responses to increased intensities of predation and substratum disturbance over similarly long time scales. The behavior of species and communities over the array of temporal and spatial scales in the fossil record takes on additional significance for framing conservation strategies, and for understanding recovery of species, lineages, and communities from environmental changes.

Characterization of the Fire Regime and Drivers of Fires in the West African Tropical Forest

NASA Astrophysics Data System (ADS)

Dwomoh, F. K.; Wimberly, M. C.

2016-12-01

The Upper Guinean forest (UGF), encompassing the tropical regions of West Africa, is a globally significant biodiversity hotspot and a critically important socio-economic and ecological resource for the region. However, the UGF is one of the most human-disturbed tropical forest ecosystems with the only remaining large patches of original forests distributed in protected areas, which are embedded in a hotspot of climate stress & land use pressures, increasing their vulnerability to fire. We hypothesized that human impacts and climate interact to drive spatial and temporal variability in fire, with fire exhibiting distinctive seasonality and sensitivity to drought in areas characterized by different population densities, agricultural practices, vegetation types, and levels of forest degradation. We used the MODIS active fire product to identify and characterize fire activity in the major ecoregions of the UGF. We used TRMM rainfall data to measure climatic variability and derived indicators of human land use from a variety of geospatial datasets. We employed time series modeling to identify the influences of drought indices and other antecedent climatic indicators on temporal patterns of active fire occurrence. We used a variety of modeling approaches to assess the influences of human activities and land cover variables on the spatial pattern of fire activity. Our results showed that temporal patterns of fire activity in the UGF were related to precipitation, but these relationships were spatially heterogeneous. The pattern of fire seasonality varied geographically, reflecting both climatological patterns and agricultural practices. The spatial pattern of fire activity was strongly associated with vegetation gradients and anthropogenic activities occurring at fine spatial scales. The Guinean forest-savanna mosaic ecoregion had the most fires. This study contributes to our understanding of UGF fire regime and the spatio-temporal dynamics of tropical forest fires in response to intense human and climatic drivers.

Geomorphology Drives Amphibian Beta Diversity in Atlantic Forest Lowlands of Southeastern Brazil

PubMed Central

Luiz, Amom Mendes; Leão-Pires, Thiago Augusto; Sawaya, Ricardo J.

2016-01-01

Beta diversity patterns are the outcome of multiple processes operating at different scales. Amphibian assemblages seem to be affected by contemporary climate and dispersal-based processes. However, historical processes involved in present patterns of beta diversity remain poorly understood. We assess and disentangle geomorphological, climatic and spatial drivers of amphibian beta diversity in coastal lowlands of the Atlantic Forest, southeastern Brazil. We tested the hypothesis that geomorphological factors are more important in structuring anuran beta diversity than climatic and spatial factors. We obtained species composition via field survey (N = 766 individuals), museum specimens (N = 9,730) and literature records (N = 4,763). Sampling area was divided in four spatially explicit geomorphological units, representing historical predictors. Climatic descriptors were represented by the first two axis of a Principal Component Analysis. Spatial predictors in different spatial scales were described by Moran Eigenvector Maps. Redundancy Analysis was implemented to partition the explained variation of species composition by geomorphological, climatic and spatial predictors. Moreover, spatial autocorrelation analyses were used to test neutral theory predictions. Beta diversity was spatially structured in broader scales. Shared fraction between climatic and geomorphological variables was an important predictor of species composition (13%), as well as broad scale spatial predictors (13%). However, geomorphological variables alone were the most important predictor of beta diversity (42%). Historical factors related to geomorphology must have played a crucial role in structuring amphibian beta diversity. The complex relationships between geomorphological history and climatic gradients generated by the Serra do Mar Precambrian basements were also important. We highlight the importance of combining spatially explicit historical and contemporary predictors for understanding and disentangling major drivers of beta diversity patterns. PMID:27171522

Geomorphology Drives Amphibian Beta Diversity in Atlantic Forest Lowlands of Southeastern Brazil.

PubMed

Luiz, Amom Mendes; Leão-Pires, Thiago Augusto; Sawaya, Ricardo J

2016-01-01

Beta diversity patterns are the outcome of multiple processes operating at different scales. Amphibian assemblages seem to be affected by contemporary climate and dispersal-based processes. However, historical processes involved in present patterns of beta diversity remain poorly understood. We assess and disentangle geomorphological, climatic and spatial drivers of amphibian beta diversity in coastal lowlands of the Atlantic Forest, southeastern Brazil. We tested the hypothesis that geomorphological factors are more important in structuring anuran beta diversity than climatic and spatial factors. We obtained species composition via field survey (N = 766 individuals), museum specimens (N = 9,730) and literature records (N = 4,763). Sampling area was divided in four spatially explicit geomorphological units, representing historical predictors. Climatic descriptors were represented by the first two axis of a Principal Component Analysis. Spatial predictors in different spatial scales were described by Moran Eigenvector Maps. Redundancy Analysis was implemented to partition the explained variation of species composition by geomorphological, climatic and spatial predictors. Moreover, spatial autocorrelation analyses were used to test neutral theory predictions. Beta diversity was spatially structured in broader scales. Shared fraction between climatic and geomorphological variables was an important predictor of species composition (13%), as well as broad scale spatial predictors (13%). However, geomorphological variables alone were the most important predictor of beta diversity (42%). Historical factors related to geomorphology must have played a crucial role in structuring amphibian beta diversity. The complex relationships between geomorphological history and climatic gradients generated by the Serra do Mar Precambrian basements were also important. We highlight the importance of combining spatially explicit historical and contemporary predictors for understanding and disentangling major drivers of beta diversity patterns.

Nonstationarity RC Workshop Report: Nonstationary Weather Patterns and Extreme Events Informing Design and Planning for Long-Lived Infrastructure

DTIC Science & Technology

2017-11-01

magnitude, intensity, and seasonality of climate. For infrastructure projects, relevant design life often exceeds 30 years—a period of time of...uncertainty about future statistical properties of climate at time and spatial scales required for planning and design purposes. Information...about future statistical properties of climate at time and spatial scales required for planning and design , and for assessing future operational

Mediterranean Thermohaline Response to Large-Scale Winter Atmospheric Forcing in a High-Resolution Ocean Model Simulation

NASA Astrophysics Data System (ADS)

Cusinato, Eleonora; Zanchettin, Davide; Sannino, Gianmaria; Rubino, Angelo

2018-04-01

Large-scale circulation anomalies over the North Atlantic and Euro-Mediterranean regions described by dominant climate modes, such as the North Atlantic Oscillation (NAO), the East Atlantic pattern (EA), the East Atlantic/Western Russian (EAWR) and the Mediterranean Oscillation Index (MOI), significantly affect interannual-to-decadal climatic and hydroclimatic variability in the Euro-Mediterranean region. However, whereas previous studies assessed the impact of such climate modes on air-sea heat and freshwater fluxes in the Mediterranean Sea, the propagation of these atmospheric forcing signals from the surface toward the interior and the abyss of the Mediterranean Sea remains unexplored. Here, we use a high-resolution ocean model simulation covering the 1979-2013 period to investigate spatial patterns and time scales of the Mediterranean thermohaline response to winter forcing from NAO, EA, EAWR and MOI. We find that these modes significantly imprint on the thermohaline properties in key areas of the Mediterranean Sea through a variety of mechanisms. Typically, density anomalies induced by all modes remain confined in the upper 600 m depth and remain significant for up to 18-24 months. One of the clearest propagation signals refers to the EA in the Adriatic and northern Ionian seas: There, negative EA anomalies are associated to an extensive positive density response, with anomalies that sink to the bottom of the South Adriatic Pit within a 2-year time. Other strong responses are the thermally driven responses to the EA in the Gulf of Lions and to the EAWR in the Aegean Sea. MOI and EAWR forcing of thermohaline properties in the Eastern Mediterranean sub-basins seems to be determined by reinforcement processes linked to the persistency of these modes in multiannual anomalous states. Our study also suggests that NAO, EA, EAWR and MOI could critically interfere with internal, deep and abyssal ocean dynamics and variability in the Mediterranean Sea.

Spatial and topographic trends in forest expansion and biomass change, from regional to local scales.

PubMed

Buma, Brian; Barrett, Tara M

2015-09-01

Natural forest growth and expansion are important carbon sequestration processes globally. Climate change is likely to increase forest growth in some regions via CO2 fertilization, increased temperatures, and altered precipitation; however, altered disturbance regimes and climate stress (e.g. drought) will act to reduce carbon stocks in forests as well. Observations of asynchrony in forest change is useful in determining current trends in forest carbon stocks, both in terms of forest density (e.g. Mg ha(-1) ) and spatially (extent and location). Monitoring change in natural (unmanaged) areas is particularly useful, as while afforestation and recovery from historic land use are currently large carbon sinks, the long-term viability of those sinks depends on climate change and disturbance dynamics at their particular location. We utilize a large, unmanaged biome (>135 000 km(2) ) which spans a broad latitudinal gradient to explore how variation in location affects forest density and spatial patterning: the forests of the North American temperate rainforests in Alaska, which store >2.8 Pg C in biomass and soil, equivalent to >8% of the C in contiguous US forests. We demonstrate that the regional biome is shifting; gains exceed losses and are located in different spatio-topographic contexts. Forest gains are concentrated on northerly aspects, lower elevations, and higher latitudes, especially in sheltered areas, whereas loss is skewed toward southerly aspects and lower latitudes. Repeat plot-scale biomass data (n = 759) indicate that within-forest biomass gains outpace losses (live trees >12.7 cm diameter, 986 Gg yr(-1) ) on gentler slopes and in higher latitudes. This work demonstrates that while temperate rainforest dynamics occur at fine spatial scales (<1000 m(2) ), the net result of thousands of individual events is regionally patterned change. Correlations between the disturbance/establishment imbalance and biomass accumulation suggest the potential for relatively rapid biome shifts and biomass changes. © 2015 John Wiley & Sons Ltd.

Glacial Refugia in Pathogens: European Genetic Structure of Anther Smut Pathogens on Silene latifolia and Silene dioica

PubMed Central

Vercken, Elodie; Fontaine, Michael C.; Gladieux, Pierre; Hood, Michael E.; Jonot, Odile; Giraud, Tatiana

2010-01-01

Climate warming is predicted to increase the frequency of invasions by pathogens and to cause the large-scale redistribution of native host species, with dramatic consequences on the health of domesticated and wild populations of plants and animals. The study of historic range shifts in response to climate change, such as during interglacial cycles, can help in the prediction of the routes and dynamics of infectious diseases during the impending ecosystem changes. Here we studied the population structure in Europe of two Microbotryum species causing anther smut disease on the plants Silene latifolia and Silene dioica. Clustering analyses revealed the existence of genetically distinct groups for the pathogen on S. latifolia, providing a clear-cut example of European phylogeography reflecting recolonization from southern refugia after glaciation. The pathogen genetic structure was congruent with the genetic structure of its host species S. latifolia, suggesting dependence of the migration pathway of the anther smut fungus on its host. The fungus, however, appeared to have persisted in more numerous and smaller refugia than its host and to have experienced fewer events of large-scale dispersal. The anther smut pathogen on S. dioica also showed a strong phylogeographic structure that might be related to more northern glacial refugia. Differences in host ecology probably played a role in these differences in the pathogen population structure. Very high selfing rates were inferred in both fungal species, explaining the low levels of admixture between the genetic clusters. The systems studied here indicate that migration patterns caused by climate change can be expected to include pathogen invasions that follow the redistribution of their host species at continental scales, but also that the recolonization by pathogens is not simply a mirror of their hosts, even for obligate biotrophs, and that the ecology of hosts and pathogen mating systems likely affects recolonization patterns. PMID:21187901

Paleoclimatic change, disaster history and the urbanscape transitions in Athens

NASA Astrophysics Data System (ADS)

Yang, Liang

2017-04-01

Past abrupt climate changes on millennium time scales have received wide attention among natural and social scientists, also because of today's rapid climate changes and their extensive impacts on our society. In the eastern Mediterranean area, coherent patterns and synchronous events in history suggest obvious links between urban development and climate forcing. The city of Athens as the origin of ancient Greek civilization experienced many periods of prosperity and decay. Though the transitions were mostly dominated by wars and power changes between empires, severe climate events and natural disasters may also considerably have shaped the process of Athens' development. Among natural disasters, earthquake, tsunami, flood and wildfire were the main forces that stressed the development of Athens. To recover from and respond to these disaster impacts, the city was thereafter developed in ways that either changed the ever existed city patterns or guided sensitive areas to specific directions, which could have transformed the urbanscape gradually. However, the possibility that these transitions may have been responses/resilience strategies triggered by abrupt climate events has so far hardly been explored. With extensive literature review, existing archaeological records and paleoclimate reconstruction modelling results, this study analyzes the large scale climate variations, related environment changes in mesoscale, aiming at setting into context the local natural disasters in Athens and its surrounding areas during the Holocene period. The study treats a number of important climate events in the area and urban transitions of the city, of which the integration of all these elements and insights from recent analysis throw some new light on understanding the forcing-transition process. Preliminary results indicate unclear link of climate forcing and urban transition over the whole city, but a few signs of possible linkages were recognized at specific blocks of Athens. Along with the population growth and land sprawl, more areas and more sections of the city were becoming susceptible to climate events and increased consideration of disasters in their development. The findings have significance for our in-depth understanding of the ancient city construction and development, as well as for the future urban development in facing of global climate change. Keywords: Climate change, natural disasters, urban transition, Holocene, Athens

Stability of ENSO and Its Tropical Pacific Teleconnections over the Last Millennium

NASA Technical Reports Server (NTRS)

Lewis, Sophie; Legrande, A. N.

2015-01-01

Determining past changes in the amplitude, frequency and teleconnections of the El Nio Southern Oscillation (ENSO) is important for understanding its potential sensitivity to future anthropogenic climate change. Palaeo-reconstructions from proxy records provide long-term information of ENSO interactions with the background climatic state through time. However, it remains unclear how ENSO characteristics have changed through time, and precisely which signals proxies record. Proxy interpretations are underpinned by the assumption of stationarity in relationships between local and remote climates, and often utilise archives from single locations located in the Pacific Ocean to reconstruct ENSO histories. Here, we investigate the stationarity of ENSO teleconnections using the Last Millennium experiment of CMIP5 (Coupled Model Intercomparison Project phase 5) (Taylor et al., 2012). We show that modelled ENSO characteristics vary on decadal- to centennial-scales, resulting from internal variability and external forcings, such as tropical volcanic eruptions. Furthermore, the relationship between ENSO conditions and local climates across the Pacific basin varies throughout the Last Millennium. Results show the stability of teleconnections is regionally dependent and proxies may reveal complex changes in teleconnected patterns, rather than large-scale changes in base ENSO characteristics. As such, proxy insights into ENSO likely require evidence to be synthesised over large spatial areas in order to deconvolve changes occurring in the NINO3.4 region from those pertaining to proxy-relevant local climatic variables. To obtain robust histories of the ENSO and its remote impacts, we recommend interpretations of proxy records should be considered in conjunction with palaeo-reconstructions from within the Central Pacific

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.

Colorado River Vegetation, and Climate: Five Decades of Spatio-Temporal Dynamics in the Grand Canyon in Response to River Regulation

NASA Astrophysics Data System (ADS)

Ralston, B. E.; Sankey, J. B.

2013-12-01

Recent analysis of remotely sensed imagery of 400 km of the Colorado River confirms a net increase in vegetated area has occurred since the completion of Glen Canyon Dam in 1963. The rates and magnitude of vegetation change appear to be river stage-dependent. Riparian vegetation expansion on geomorphic surfaces at lower elevations relative to the river was greater for decades with lower peak and average discharges. Vegetation change at higher elevation relative to the river indicate that increases and decreases in vegetated area reflect regional precipitation patterns, and respectively coincide with regionally significant wet and dry periods that include the current early 21st century drought. The objective of this work was to examine the temporal persistence, and changes, in the spatial distribution of riparian vegetation relative to geomorphic characteristics of the Colorado River in Grand Canyon, dam and reservoir management, and regional climate over the 5-decade period from the mid-1960s to present. We employed archived riparian vegetation classifications that used aerial imagery from 1965, 1973, 1984, 1992, 2002, and 2009 coupled with flow regime data that is primarily related to operations of Glen Canyon Dam, field-measured rating relations, predictions of rating relations based on 1-D modeling, and detailed, geomorphic field mapping. Documentation of the effects of river regulation on riparian habitats in the SW USA has traditionally been limited to either small segments of river channels (e.g., 0.1-10km), or focused on specific plant species. The smaller geographic scale approach evaluates local hydrology, river channel changes, and serial recruitment events of riparian plants. The species-specific plant response informs larger scale patterns of riparian plant distributions across the landscape, but is less sensitive to differences of climate and hydrology among rivers. Our study is unique in that it employs datasets that allow both large-scale change detection and local-scale analysis to address questions about transferability of local-scale plant response to the larger river system. Furthermore, we assess the independent and interacting effects of river regulation and regional climate on plant response. Our results show promise for improved understanding of the interplay of river regulation and climate effects for riparian vegetation at a local and river-wide scale in this highly modified river system.

Climatic variation and the distribution of an amphibian polyploid complex

USGS Publications Warehouse

Otto, C.R.V.; Snodgrass, J.W.; Forester, D.C.; Mitchell, J.C.; Miller, R.W.

2007-01-01

1. The establishment of polyploid populations involves the persistence and growth of the polyploid in the presence of the progenitor species. Although there have been a number of animal polyploid species documented, relatively few inquiries have been made into the large-scale mechanisms of polyploid establishment in animal groups. Herein we investigate the influence of regional climatic conditions on the distributional patterns of a diploid-tetraploid species pair of gray treefrogs, Hyla chrysoscelis and H. versicolor (Anura: Hylidae) in the mid-Atlantic region of eastern North America. 2. Calling surveys at breeding sites were used to document the distribution of each species. Twelve climatic models and one elevation model were generated to predict climatic and elevation values for gray treefrog breeding sites. A canonical analysis of discriminants was used to describe relationships between climatic variables, elevation and the distribution of H. chrysoscelis and H. versicolor. 3. There was a strong correlation between several climatic variables, elevation and the distribution of the gray treefrog complex. Specifically, the tetraploid species almost exclusively occupied areas of higher elevation, where climatic conditions were relatively severe (colder, drier, greater annual variation). In contrast, the diploid species was restricted to lower elevations, where climatic conditions were warmer, wetter and exhibited less annual variation. 4. Clusters of syntopic sites were associated with areas of high variation in annual temperature and precipitation during the breeding season. 5. Our data suggest that large-scale climatic conditions have played a role in the establishment of the polyploid H. versicolor in at least some portions of its range. The occurrence of the polyploid and absence of the progenitor in colder, drier and more varied environments suggests the polyploid may posses a tolerance of severe environmental conditions that is not possessed by the diploid progenitor. 6. Our findings support the hypothesis that increased tolerance to severe environmental conditions is a plausible mechanism of polyploid establishment.

Climate mitigation and the future of tropical landscapes

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

Thomson, Allison M.; Calvin, Katherine V.; Chini, Louise Parsons

2010-11-16

Land use change to meet 21st Century demands for food, fuel, and fiber will occur in the context of both a changing climate as well as societal efforts to mitigate climate change. This changing natural and human environment will have large consequences for forest resources, terrestrial carbon storage and emissions, and food and energy crop production over the next century. Any climate change mitigation policies enacted will change the environment under which land-use decisions are made and alter global land use change patterns. Here we use the GCAM integrated assessment model to explore how climate mitigation policies that achieve amore » climate stabilization at 4.5 W m-2 radiative forcing in 2100 and value carbon in terrestrial ecosystems interact with future agricultural productivity and food and energy demands to influence land use in the tropics. The regional land use results are downscaled from GCAM regions to produce gridded maps of tropical land use change. We find that tropical forests are preserved only in cases where a climate mitigation policy that values terrestrial carbon is in place, and crop productivity growth continues throughout the century. Crop productivity growth is also necessary to avoid large scale deforestation globally and enable the production of bioenergy crops. The terrestrial carbon pricing assumptions in GCAM are effective at avoiding deforestation even when cropland must expand to meet future food demand.« less

Influences of climate, fire, and topography on contemporary age structure patterns of Douglas-fir at 205 old forest sites in western Oregon

Treesearch

Nathan J. Poage; Peter J. Weisberg; Peter C. Impara; John C. Tappeiner; Thomas S. Sensenig

2009-01-01

Knowledge of forest development is basic to understanding the ecology, dynamics, and management of forest ecosystems. We hypothesized that the age structure patterns of Douglas-fir at 205 old forest sites in western Oregon are extremely variable with long and (or) multiple establishment periods common, and that these patterns reflect variation in regional-scale climate...

Between-Site Differences in the Scale of Dispersal and Gene Flow in Red Oak

PubMed Central

Moran, Emily V.; Clark, James S.

2012-01-01

Background Nut-bearing trees, including oaks (Quercus spp.), are considered to be highly dispersal limited, leading to concerns about their ability to colonize new sites or migrate in response to climate change. However, estimating seed dispersal is challenging in species that are secondarily dispersed by animals, and differences in disperser abundance or behavior could lead to large spatio-temporal variation in dispersal ability. Parentage and dispersal analyses combining genetic and ecological data provide accurate estimates of current dispersal, while spatial genetic structure (SGS) can shed light on past patterns of dispersal and establishment. Methodology and Principal Findings In this study, we estimate seed and pollen dispersal and parentage for two mixed-species red oak populations using a hierarchical Bayesian approach. We compare these results to those of a genetic ML parentage model. We also test whether observed patterns of SGS in three size cohorts are consistent with known site history and current dispersal patterns. We find that, while pollen dispersal is extensive at both sites, the scale of seed dispersal differs substantially. Parentage results differ between models due to additional data included in Bayesian model and differing genotyping error assumptions, but both indicate between-site dispersal differences. Patterns of SGS in large adults, small adults, and seedlings are consistent with known site history (farmed vs. selectively harvested), and with long-term differences in seed dispersal. This difference is consistent with predator/disperser satiation due to higher acorn production at the low-dispersal site. While this site-to-site variation results in substantial differences in asymptotic spread rates, dispersal for both sites is substantially lower than required to track latitudinal temperature shifts. Conclusions Animal-dispersed trees can exhibit considerable spatial variation in seed dispersal, although patterns may be surprisingly constant over time. However, even under favorable conditions, migration in heavy-seeded species is likely to lag contemporary climate change. PMID:22563504

Impact of climate change on European weather extremes

NASA Astrophysics Data System (ADS)

Duchez, Aurelie; Forryan, Alex; Hirschi, Joel; Sinha, Bablu; New, Adrian; Freychet, Nicolas; Scaife, Adam; Graham, Tim

2015-04-01

An emerging science consensus is that global climate change will result in more extreme weather events with concomitant increasing financial losses. Key questions that arise are: Can an upward trend in natural extreme events be recognised and predicted at the European scale? What are the key drivers within the climate system that are changing and making extreme weather events more frequent, more intense, or both? Using state-of-the-art coupled climate simulations from the UK Met Office (HadGEM3-GC2, historical and future scenario runs) as well as reanalysis data, we highlight the potential of the currently most advanced forecasting systems to progress understanding of the causative drivers of European weather extremes, and assess future frequency and intensity of extreme weather under various climate change scenarios. We characterize European extremes in these simulations using a subset of the 27 core indices for temperature and precipitation from The Expert Team on Climate Change Detection and Indices (Tank et al., 2009). We focus on temperature and precipitation extremes (e.g. extremes in daily and monthly precipitation and temperatures) and relate them to the atmospheric modes of variability over Europe in order to establish the large-scale atmospheric circulation patterns that are conducive to the occurrence of extreme precipitation and temperature events. Klein Tank, Albert M.G., and Francis W. Zwiers. Guidelines on Analysis of Extremes in a Changing Climate in Support of Informed Decisions for Adaptation. WMO-TD No. 1500. Climate Data and Monitoring. World Meteorological Organization, 2009.

A Novel, Unbiased Analysis Approach for Investigating Population Dynamics: A Case Study on Calanus finmarchicus and Its Decline in the North Sea

PubMed Central

Papworth, Danny J.; Marini, Simone; Conversi, Alessandra

2016-01-01

Marine populations are controlled by a series of drivers, pertaining to both the physical environment and the biological environment (trophic predator-prey interactions). There is heated debate over drivers, especially when trying to understand the causes of major ecosystem events termed regime shifts. In this work, we have researched and developed a novel methodology based on Genetic Programming (GP) for distinguishing which drivers can influence species abundance. This methodology benefits of having no a priori assumptions either on the ecological parameters used or on the underlying mathematical relationships among them. We have validated this methodology applying it to the North Sea pelagic ecosystem. We use the target species Calanus finmarchicus, a key copepod in temperate and subarctic ecosystems, along with 86 biological, hydrographical and climatic time series, ranging from local water nutrients and fish predation, to large scale climate pressure patterns. The chosen study area is the central North Sea, from 1972 to 2011, during which period there was an ecological regime shift. The GP based analysis identified 3 likely drivers of C. finmarchicus abundance, which highlights the importance of considering both physical and trophic drivers: temperature, North Sea circulation (net flow into the North Atlantic), and predation (herring). No large scale climate patterns were selected, suggesting that when there is availability of both data types, local drivers are more important. The results produced by the GP based procedure are consistent with the literature published to date, and validate the use of GP for interpreting species dynamics. We propose that this methodology holds promises for the highly non-linear field of ecology. PMID:27366910

Diagnosing Possible Anthropogenic Contributions to Heavy Colorado Rainfall in September 2013

NASA Astrophysics Data System (ADS)

Pall, Pardeep; Patricola, Christina; Wehner, Michael; Stone, Dáithí; Paciorek, Christopher; Collins, William

2015-04-01

Unusually heavy rainfall occurred over the Colorado Front Range during early September 2013, with record or near-record totals recorded in several locations. It was associated predominantly with a stationary large-scale weather pattern (akin to the North American Monsoon, which occurs earlier in the year) that drove a strong plume of deep moisture inland from the Gulf of Mexico against the Front Range foothills. The resulting floods across the South Platte River basin impacted several thousands of people and many homes, roads, and businesses. To diagnose possible anthropogenic contributions to the odds of such heavy rainfall, we adapt an existing event attribution paradigm of modelling an 'event that was' for September 2013 and comparing it to a modelled 'event that might have been' for that same time but for the absence of historical anthropogenic drivers of climate. Specifically, we first perform 'event that was' simulations with the regional Weather Research and Forecasting (WRF) model at 12 km resolution over North America, driven by NCEP2 re-analysis. We then re-simulate, having adjusted the re-analysis to 'event that might have been conditions' by modifying atmospheric greenhouse gas and other pollutant concentrations, temperature, humidity, and winds, as well as sea ice coverage, and sea-surface temperatures - all according to estimates from global climate model simulations. Thus our findings are highly conditional on the driving re-analysis and adjustments therein, but the setup allows us to elucidate possible mechanisms responsible for heavy Colorado rainfall in September 2013. Our model results suggests that, given an insignificant change in the pattern of large-scale driving weather, there is an increase in atmospheric water vapour under anthropogenic climate warming leading to a substantial increase in the probability of heavy rainfall occurring over the South Platte River basin in September 2013.

Diagnosing Possible Anthropogenic Contributions to Heavy Colorado Rainfall in September 2013

NASA Astrophysics Data System (ADS)

Pall, P.; Patricola, C. M.; Wehner, M. F.; Stone, D. A.; Paciorek, C. J.; Collins, W.

2014-12-01

Unusually heavy rainfall occurred over the Colorado Front Range during early September 2013, with record or near-record totals recorded in several locations. It was associated predominantly with a stationary large-scale weather pattern (akin to the North American Monsoon, which occurs earlier in the year) that drove a strong plume of deep moisture inland from the Gulf of Mexico against the Front Range foothills. The resulting floods impacted several thousands of people and many homes, roads, and businesses. To diagnose possible anthropogenic contributions to the odds of such heavy rainfall, we adapt an existing event attribution paradigm of modelling a 'world that was' for September 2013 and comparing it to a modelled 'world that might have been' for that same time but for the absence of historical anthropogenic drivers of climate. Specifically, we first perform 'world that was' simulations with the regional WRF model at 12 km resolution over North America, driven by NCEP2 re-analysis. We then re-simulate, having adjusted the re-analysis to 'world that might have been conditions' by modifying atmospheric greenhouse gas and other pollutant concentrations, temperature, humidity, and winds, as well as sea ice coverage, and sea-surface temperatures - all according to estimates from global climate model simulations. Thus our findings are highly conditional on the driving re-analysis and adjustments therein, but the setup allows us to elucidate possible mechanisms responsible for heavy Colorado rainfall in September 2013. For example, preliminary analysis suggests that, given no change in the pattern of large-scale driving weather, there is an increase in atmospheric water vapour under anthropogenic climate warming leading to a substantial increase in the odds of heavy rainfall over the Front Range.

Global warming and climate forcing by recent albedo changes on Mars

USGS Publications Warehouse

Fenton, L.K.; Geissler, P.E.; Haberle, R.M.

2007-01-01

For hundreds of years, scientists have tracked the changing appearance of Mars, first by hand drawings and later by photographs. Because of this historical record, many classical albedo patterns have long been known to shift in appearance over time. Decadal variations of the martian surface albedo are generally attributed to removal and deposition of small amounts of relatively bright dust on the surface. Large swaths of the surface (up to 56 million km2) have been observed to darken or brighten by 10 per cent or more. It is unknown, however, how these albedo changes affect wind circulation, dust transport and the feedback between these processes and the martian climate. Here we present predictions from a Mars general circulation model, indicating that the observed interannual albedo alterations strongly influence the martian environment. Results indicate enhanced wind stress in recently darkened areas and decreased wind stress in brightened areas, producing a positive feedback system in which the albedo changes strengthen the winds that generate the changes. The simulations also predict a net annual global warming of surface air temperatures by ???0.65 K, enhancing dust lifting by increasing the likelihood of dust devil generation. The increase in global dust lifting by both wind stress and dust devils may affect the mechanisms that trigger large dust storm initiation, a poorly understood phenomenon, unique to Mars. In addition, predicted increases in summertime air temperatures at high southern latitudes would contribute to the rapid and steady scarp retreat that has been observed in the south polar residual ice for the past four Mars years. Our results suggest that documented albedo changes affect recent climate change and large-scale weather patterns on Mars, and thus albedo variations are a necessary component of future atmospheric and climate studies. ??2007 Nature Publishing Group.

Global warming and climate forcing by recent albedo changes on Mars.

PubMed

Fenton, Lori K; Geissler, Paul E; Haberle, Robert M

2007-04-05

For hundreds of years, scientists have tracked the changing appearance of Mars, first by hand drawings and later by photographs. Because of this historical record, many classical albedo patterns have long been known to shift in appearance over time. Decadal variations of the martian surface albedo are generally attributed to removal and deposition of small amounts of relatively bright dust on the surface. Large swaths of the surface (up to 56 million km2) have been observed to darken or brighten by 10 per cent or more. It is unknown, however, how these albedo changes affect wind circulation, dust transport and the feedback between these processes and the martian climate. Here we present predictions from a Mars general circulation model, indicating that the observed interannual albedo alterations strongly influence the martian environment. Results indicate enhanced wind stress in recently darkened areas and decreased wind stress in brightened areas, producing a positive feedback system in which the albedo changes strengthen the winds that generate the changes. The simulations also predict a net annual global warming of surface air temperatures by approximately 0.65 K, enhancing dust lifting by increasing the likelihood of dust devil generation. The increase in global dust lifting by both wind stress and dust devils may affect the mechanisms that trigger large dust storm initiation, a poorly understood phenomenon, unique to Mars. In addition, predicted increases in summertime air temperatures at high southern latitudes would contribute to the rapid and steady scarp retreat that has been observed in the south polar residual ice for the past four Mars years. Our results suggest that documented albedo changes affect recent climate change and large-scale weather patterns on Mars, and thus albedo variations are a necessary component of future atmospheric and climate studies.

Analysis of terrestrial conditions and dynamics

NASA Technical Reports Server (NTRS)

Goward, S. N. (Principal Investigator)

1984-01-01

Land spectral reflectance properties for selected locations, including the Goddard Space Flight Center, the Wallops Flight Facility, a MLA test site in Cambridge, Maryland, and an acid test site in Burlington, Vermont, were measured. Methods to simulate the bidirectional reflectance properties of vegetated landscapes and a data base for spatial resolution were developed. North American vegetation patterns observed with the Advanced Very High Resolution Radiometer were assessed. Data and methods needed to model large-scale vegetation activity with remotely sensed observations and climate data were compiled.

Recent Regional Climate State and Change - Derived through Downscaling Homogeneous Large-scale Components of Re-analyses

NASA Astrophysics Data System (ADS)

Von Storch, H.; Klehmet, K.; Geyer, B.; Li, D.; Schubert-Frisius, M.; Tim, N.; Zorita, E.

2015-12-01

Global re-analyses suffer from inhomogeneities, as they process data from networks under development. However, the large-scale component of such re-analyses is mostly homogeneous; additional observational data add in most cases to a better description of regional details and less so on large-scale states. Therefore, the concept of downscaling may be applied to homogeneously complementing the large-scale state of the re-analyses with regional detail - wherever the condition of homogeneity of the large-scales is fulfilled. Technically this can be done by using a regional climate model, or a global climate model, which is constrained on the large scale by spectral nudging. This approach has been developed and tested for the region of Europe, and a skillful representation of regional risks - in particular marine risks - was identified. While the data density in Europe is considerably better than in most other regions of the world, even here insufficient spatial and temporal coverage is limiting risk assessments. Therefore, downscaled data-sets are frequently used by off-shore industries. We have run this system also in regions with reduced or absent data coverage, such as the Lena catchment in Siberia, in the Yellow Sea/Bo Hai region in East Asia, in Namibia and the adjacent Atlantic Ocean. Also a global (large scale constrained) simulation has been. It turns out that spatially detailed reconstruction of the state and change of climate in the three to six decades is doable for any region of the world.The different data sets are archived and may freely by used for scientific purposes. Of course, before application, a careful analysis of the quality for the intended application is needed, as sometimes unexpected changes in the quality of the description of large-scale driving states prevail.

Montane ecosystem productivity responds more to global circulation patterns than climatic trends.

PubMed

Desai, A R; Wohlfahrt, G; Zeeman, M J; Katata, G; Eugster, W; Montagnani, L; Gianelle, D; Mauder, M; Schmid, H-P

2016-02-01

Regional ecosystem productivity is highly sensitive to inter-annual climate variability, both within and outside the primary carbon uptake period. However, Earth system models lack sufficient spatial scales and ecosystem processes to resolve how these processes may change in a warming climate. Here, we show, how for the European Alps, mid-latitude Atlantic ocean winter circulation anomalies drive high-altitude summer forest and grassland productivity, through feedbacks among orographic wind circulation patterns, snowfall, winter and spring temperatures, and vegetation activity. Therefore, to understand future global climate change influence to regional ecosystem productivity, Earth systems models need to focus on improvements towards topographic downscaling of changes in regional atmospheric circulation patterns and to lagged responses in vegetation dynamics to non-growing season climate anomalies.

Montane ecosystem productivity responds more to global circulation patterns than climatic trends

NASA Astrophysics Data System (ADS)

Desai, A. R.; Wohlfahrt, G.; Zeeman, M. J.; Katata, G.; Eugster, W.; Montagnani, L.; Gianelle, D.; Mauder, M.; Schmid, H.-P.

2016-02-01

Regional ecosystem productivity is highly sensitive to inter-annual climate variability, both within and outside the primary carbon uptake period. However, Earth system models lack sufficient spatial scales and ecosystem processes to resolve how these processes may change in a warming climate. Here, we show, how for the European Alps, mid-latitude Atlantic ocean winter circulation anomalies drive high-altitude summer forest and grassland productivity, through feedbacks among orographic wind circulation patterns, snowfall, winter and spring temperatures, and vegetation activity. Therefore, to understand future global climate change influence to regional ecosystem productivity, Earth systems models need to focus on improvements towards topographic downscaling of changes in regional atmospheric circulation patterns and to lagged responses in vegetation dynamics to non-growing season climate anomalies.

High-Resolution Climate Data Visualization through GIS- and Web-based Data Portals

NASA Astrophysics Data System (ADS)

WANG, X.; Huang, G.

2017-12-01

Sound decisions on climate change adaptation rely on an in-depth assessment of potential climate change impacts at regional and local scales, which usually requires finer resolution climate projections at both spatial and temporal scales. However, effective downscaling of global climate projections is practically difficult due to the lack of computational resources and/or long-term reference data. Although a large volume of downscaled climate data has been make available to the public, how to understand and interpret the large-volume climate data and how to make use of the data to drive impact assessment and adaptation studies are still challenging for both impact researchers and decision makers. Such difficulties have become major barriers preventing informed climate change adaptation planning at regional scales. Therefore, this research will explore new GIS- and web-based technologies to help visualize the large-volume regional climate data with high spatiotemporal resolutions. A user-friendly public data portal, named Climate Change Data Portal (CCDP, http://ccdp.network), will be established to allow intuitive and open access to high-resolution regional climate projections at local scales. The CCDP offers functions of visual representation through geospatial maps and data downloading for a variety of climate variables (e.g., temperature, precipitation, relative humidity, solar radiation, and wind) at multiple spatial resolutions (i.e., 25 - 50 km) and temporal resolutions (i.e., annual, seasonal, monthly, daily, and hourly). The vast amount of information the CCDP encompasses can provide a crucial basis for assessing impacts of climate change on local communities and ecosystems and for supporting better decision making under a changing climate.

Interannual Variability in the Position and Strength of the East Asian Jet Stream and Its Relation to Large - scale Circulation

NASA Astrophysics Data System (ADS)

Chan, Duo; Zhang, Yang; Wu, Qigang

2013-04-01

East Asian Jet Stream (EASJ) is charactered by obvious interannual variability in strength and position (latitude), with wide impacts on East Asian climate in all seasons. In this study, two indices are established to measure the interannual variability in intensity and position of EAJS. Possible causing factors, including both local signals and non-local large-scale circulation, are examined using NCAP-NCAR reanalysis data to investigate their relations with jet variation. Our analysis shows that the relationship between the interannual variations of EASJ and these factors depends on seasons. In the summer, both the intensity and position of EASJ are closely related to the meridional gradient of local surface temperature, but display no apparent relationship with the larg-scale circulation. In cold seasons (autumn, winter and spring), both the local factor and the large-scale circulation, i.e. the Pacific/North American teleconnection pattern (PNA), play important roles in the interannual variability of the jet intensity. The variability in the jet position, however, is more correlated to the Arctic Oscillation (AO), especially in winter. Diagnostic analysis indicates that transient eddy activity plays an important role in connecting the interannual variability of EASJ position with AO.

Uncertainties in data-model comparisons: Spatio-temporal scales for past climates

NASA Astrophysics Data System (ADS)

Lohmann, G.

2016-12-01

Data-model comparisons are hindered by uncertainties like varying reservoir ages or potential seasonality bias of the recorder systems, but also due to the models' difficulty to represent the spatio-temporal variability patterns. For the Holocene we detect a sensitivity to horizontal resolution in the atmosphere, the representation of atmospheric dynamics, as well as the dynamics of the western boundary currents in the ocean. These features can create strong spatial heterogeneity in the North Atlantic and Pacific Oceans over long timescales (unlike a diffusive spatio-temporal scale separation). Futhermore, it is shown that such non-linear mechanisms could create a non-trivial response to seasonal insolation forcing via an atmospheric bridge inducing non-uniform temperature anomalies over the northern continents on multi-millennial time scales. Through the fluctuation-dissipation-theorem, climate variability and sensitivity are ultimately coupled. It is argued that some obvious biases between models and data may be linked to the missing key persistent component of the atmospheric dynamics, the North Atlantic blocking activity. It is shown that blocking is also linked to Atlantic multidecadal ocean variability and to extreme events. Interestingly, several proxies provide a measure of the frequency of extreme events, and a proper representation is a true challenge for climate models. Finally, case studies from deep paleo are presented in which changes in land-sea distribution or subscale parameterizations can cause relatively large effects on surface temperature. Such experiments can explore the phase space of solutions, but show the limitation of past climates to constrain climate sensitivity.

Anthropogenic aerosols and the distribution of past large-scale precipitation change

DOE PAGES

Wang, Chien

2015-12-28

In this paper, the climate response of precipitation to the effects of anthropogenic aerosols is a critical while not yet fully understood aspect in climate science. Results of selected models that participated the Coupled Model Intercomparison Project Phase 5 and the data from the Twentieth Century Reanalysis Project suggest that, throughout the tropics and also in the extratropical Northern Hemisphere, aerosols have largely dominated the distribution of precipitation changes in reference to the preindustrial era in the second half of the last century. Aerosol-induced cooling has offset some of the warming caused by the greenhouse gases from the tropics tomore » the Arctic and thus formed the gradients of surface temperature anomaly that enable the revealed precipitation change patterns to occur. Improved representation of aerosol-cloud interaction has been demonstrated as the key factor for models to reproduce consistent distributions of past precipitation change with the reanalysis data.« less

Seasonal change of topology and resilience of ecological networks in wetlandscapes

NASA Astrophysics Data System (ADS)

Bin, Kim; Park, Jeryang

2017-04-01

Wetlands distributed in a landscape provide various ecosystem services including habitat for flora and fauna, hydrologic controls, and biogeochemical processes. Hydrologic regime of each wetland at a given landscape varies by hydro-climatic and geological conditions as well as the bathymetry, forming a certain pattern in the wetland area distribution and spatial organization. However, its large-scale pattern also changes over time as this wetland complex is subject to stochastic hydro-climatic forcing in various temporal scales. Consequently, temporal variation in the spatial structure of wetlands inevitably affects the dispersal ability of species depending on those wetlands as habitat. Here, we numerically show (1) the spatiotemporal variation of wetlandscapes by forcing seasonally changing stochastic rainfall and (2) the corresponding ecological networks which either deterministically or stochastically forming the dispersal ranges. We selected four vernal pool regions with distinct climate conditions in California. The results indicate that the spatial structure of wetlands in a landscape by measuring the wetland area frequency distribution changes by seasonal hydro-climatic condition but eventually recovers to the initial state. However, the corresponding ecological networks, which the structure and function change by the change of distances between wetlands, and measured by degree distribution and network efficiency, may not recover to the initial state especially in the regions with high seasonal dryness index. Moreover, we observed that the changes in both the spatial structure of wetlands in a landscape and the corresponding ecological networks exhibit hysteresis over seasons. Our analysis indicates that the hydrologic and ecological resilience of a wetlandcape may be low in a dry region with seasonal hydro-climatic forcing. Implications of these results for modelling ecological networks depending on hydrologic systems especially for conservation purposes are discussed.

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.

Enhanced mesoscale climate projections in TAR and AR5 IPCC scenarios: a case study in a Mediterranean climate (Araucanía Region, south central Chile).

PubMed

Orrego, R; Abarca-Del-Río, R; Ávila, A; Morales, L

2016-01-01

Climate change scenarios are computed on a large scale, not accounting for local variations presented in historical data and related to human scale. Based on historical records, we validate a baseline (1962-1990) and correct the bias of A2 and B2 regional projections for the end of twenty-first century (2070-2100) issued from a high resolution dynamical downscaled (using PRECIS mesoscale model, hereinafter DGF-PRECIS) of Hadley GCM from the IPCC 3rd Assessment Report (TAR). This is performed for the Araucanía Region (Chile; 37°-40°S and 71°-74°W) using two different bias correction methodologies. Next, we study high-resolution precipitations to find monthly patterns such as seasonal variations, rainfall months, and the geographical effect on these two scenarios. Finally, we compare the TAR projections with those from the recent Assessment Report 5 (AR5) to find regional precipitation patterns and update the Chilean `projection. To show the effects of climate change projections, we compute the rainfall climatology for the Araucanía Region, including the impact of ENSO cycles (El Niño and La Niña events). The corrected climate projection from the high-resolution dynamical downscaled model of the TAR database (DGF-PRECIS) show annual precipitation decreases: B2 (-19.19 %, -287 ± 42 mm) and A2 (-43.38 %, -655 ± 27.4 mm per year. Furthermore, both projections increase the probability of lower rainfall months (lower than 100 mm per month) to 64.2 and 72.5 % for B2 and A2, respectively.

Enhanced mesoscale climate projections in TAR and AR5 IPCC scenarios: a case study in a Mediterranean climate (Araucanía Region, south central Chile)

DOE PAGES

Orrego, R.; Abarca-del-Rio, R.; Avila, A.; ...

2016-09-28

Here, climate change scenarios are computed on a large scale, not accounting for local variations presented in historical data and related to human scale. Based on historical records, we validate a baseline (1962–1990) and correct the bias of A2 and B2 regional projections for the end of twenty-first century (2070–2100) issued from a high resolution dynamical downscaled (using PRECIS mesoscale model, hereinafter DGF-PRECIS) of Hadley GCM from the IPCC 3rd Assessment Report (TAR). This is performed for the Araucanía Region (Chile; 37°–40°S and 71°–74°W) using two different bias correction methodologies. Next, we study high-resolution precipitations to find monthly patterns suchmore » as seasonal variations, rainfall months, and the geographical effect on these two scenarios. Finally, we compare the TAR projections with those from the recent Assessment Report 5 (AR5) to find regional precipitation patterns and update the Chilean `projection. To show the effects of climate change projections, we compute the rainfall climatology for the Araucanía Region, including the impact of ENSO cycles (El Niño and La Niña events). The corrected climate projection from the high-resolution dynamical downscaled model of the TAR database (DGF-PRECIS) show annual precipitation decreases: B2 (-19.19 %, -287 ± 42 mm) and A2 (-43.38 %, -655 ± 27.4 mm per year. Furthermore, both projections increase the probability of lower rainfall months (lower than 100 mm per month) to 64.2 and 72.5 % for B2 and A2, respectively.« less

Enhanced mesoscale climate projections in TAR and AR5 IPCC scenarios: a case study in a Mediterranean climate (Araucanía Region, south central Chile)

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

Orrego, R.; Abarca-del-Rio, R.; Avila, A.

Here, climate change scenarios are computed on a large scale, not accounting for local variations presented in historical data and related to human scale. Based on historical records, we validate a baseline (1962–1990) and correct the bias of A2 and B2 regional projections for the end of twenty-first century (2070–2100) issued from a high resolution dynamical downscaled (using PRECIS mesoscale model, hereinafter DGF-PRECIS) of Hadley GCM from the IPCC 3rd Assessment Report (TAR). This is performed for the Araucanía Region (Chile; 37°–40°S and 71°–74°W) using two different bias correction methodologies. Next, we study high-resolution precipitations to find monthly patterns suchmore » as seasonal variations, rainfall months, and the geographical effect on these two scenarios. Finally, we compare the TAR projections with those from the recent Assessment Report 5 (AR5) to find regional precipitation patterns and update the Chilean `projection. To show the effects of climate change projections, we compute the rainfall climatology for the Araucanía Region, including the impact of ENSO cycles (El Niño and La Niña events). The corrected climate projection from the high-resolution dynamical downscaled model of the TAR database (DGF-PRECIS) show annual precipitation decreases: B2 (-19.19 %, -287 ± 42 mm) and A2 (-43.38 %, -655 ± 27.4 mm per year. Furthermore, both projections increase the probability of lower rainfall months (lower than 100 mm per month) to 64.2 and 72.5 % for B2 and A2, respectively.« less

A terrestrial record of water isotopes reveals the Eocene-Oligoene transition in southern Argentina

NASA Astrophysics Data System (ADS)

Auerbach, D. J.; Hren, M. T.; Pacini, A.; Breen, P.

2015-12-01

The Eocene-Oligocene transition (EOT) from a greenhouse to icehouse climate state and the onset of large-scale Antarctic glaciation has been widely documented geochemically in both the marine realm (e.g., Zachos et al., 2001) and the terrestrial realm (e.g., Zanazzi et al., 2007). However, existing terrestrial records from Patagonia show negligible change in the water isotope record (Kohn et al., 2010; Kohn et al., 2015), despite the proximity of South America to Antarctica. Analyses of volcanic glasses from the Vera Member of the Sarmiento Formation in the well-dated (Dunn et al., 2013) sedimentary section at Gran Barranca allow us to reconstruct water isotope record in central Patagonia during the EOT. These data show a drop in precipitation δD of ~20‰ over ~100-200 kyr followed by a recovery of ~15‰ over the next 0.5-1.0 Myr. This pattern of a rapid shift and a more gradual recovery fits the shape and time scale of the marine record, although the magnitude of the isotopic excursion is different. Such a record could potentially be explained by large changes in source (seawater) δD, temperature, paleolatitude, or orographic effect. As the latter two possibilities are geologically improbable, these data suggest large, rapid climatic changes accompanying the EOT in Patagonia. If corroborated by other data, this would suggest that the evolution of hypsodonty in grazers in Patagonia was not driven by or sensitive to the global climate.

Towards a Unified Framework in Hydroclimate Extremes Prediction in Changing Climate

NASA Astrophysics Data System (ADS)

Moradkhani, H.; Yan, H.; Zarekarizi, M.; Bracken, C.

2016-12-01

Spatio-temporal analysis and prediction of hydroclimate extremes are of paramount importance in disaster mitigation and emergency management. The IPCC special report on managing the risks of extreme events and disasters emphasizes that the global warming would change the frequency, severity, and spatial pattern of extremes. In addition to climate change, land use and land cover changes also influence the extreme characteristics at regional scale. Therefore, natural variability and anthropogenic changes to the hydroclimate system result in nonstationarity in hydroclimate variables. In this presentation recent advancements in developing and using Bayesian approaches to account for non-stationarity in hydroclimate extremes are discussed. Also, implications of these approaches in flood frequency analysis, treatment of spatial dependence, the impact of large-scale climate variability, the selection of cause-effect covariates, with quantification of model errors in extreme prediction is explained. Within this framework, the applicability and usefulness of the ensemble data assimilation for extreme flood predictions is also introduced. Finally, a practical and easy to use approach for better communication with decision-makers and emergency managers is presented.

An integrated framework to assess adaptation options to climate change impacts in an irrigated basin in Central North Chile

NASA Astrophysics Data System (ADS)

Vicuna, S.; Melo, O.; Meza, F. J.; Alvarez, P.; Maureira, F.; Sanchez, A.; Tapia, A.; Cortes, M.; Dale, L. L.

2013-12-01

Future climate conditions could potentially affect water supply and demand on water basins throughout the world but especially on snowmelt-driven agriculture oriented basins that can be found throughout central Chile. Increasing temperature and reducing precipitation will affect both the magnitude and timing of water supply this part of the world. Different adaptation strategies could be implemented to reduce the impacts of such scenarios. Some could be incorporated as planned policies decided at the basin or Water Use Organization levels. Examples include changing large scale irrigation infrastructure (reservoirs and main channels) either physically or its operation. Complementing these strategies it is reasonable to think that at a disaggregated level, farmers would also react (adapt) to these new conditions using a mix of options to either modify their patterns of consumption (irrigation efficiency, crop mix, crop area reduction), increase their ability to access new sources of water (groundwater, water markets) or finally compensate their expected losses (insurance). We present a modeling framework developed to represent these issues using as a case study the Limarí basin located in Central Chile. This basin is a renowned example of how the development of reservoirs and irrigation infrastructure can reduce climate vulnerabilities allowing the economic development of a basin. Farmers in this basin tackle climate variability by adopting different strategies that depend first on the reservoir water volume allocation rule, on the type and size of investment they have at their farms and finally their potential access to water markets and other water supplies options. The framework developed can be used to study these strategies under current and future climate scenarios. The cornerstone of the framework is an hydrology and water resources model developed on the WEAP platform. This model is able to reproduce the large scale hydrologic features of the basin such as snowmelt hydrology, reservoir operation and groundwater dynamics. Crop yield under different water irrigation patterns have been inferred using a calibrated Cropsyst model. These crop yields together with user association irrigation constraints are used in a GAMS optimization model embedded dynamically in WEAP in order to obtain every year decisions on crop mix (including fallow land), irrigation patterns and participation in the spot water market. The GAMS optimization model has been calibrated using annual crop mix time series derived using a combination of sources of information ranging from different type of census plus satellite images. The resulting modeling platform is able to simulate under historic and future climate scenarios water availability in different locations of the basin with associated crop yield and economic consequences. The platform also allows the implementation of autonomous and planned adaptation strategies that could reduce the impacts of climate variability and climate change.

Stable isotopic constraints on global soil organic carbon turnover

NASA Astrophysics Data System (ADS)

Wang, Chao; Houlton, Benjamin Z.; Liu, Dongwei; Hou, Jianfeng; Cheng, Weixin; Bai, Edith

2018-02-01

Carbon dioxide release during soil organic carbon (SOC) turnover is a pivotal component of atmospheric CO2 concentrations and global climate change. However, reliably measuring SOC turnover rates on large spatial and temporal scales remains challenging. Here we use a natural carbon isotope approach, defined as beta (β), which was quantified from the δ13C of vegetation and soil reported in the literature (176 separate soil profiles), to examine large-scale controls of climate, soil physical properties and nutrients over patterns of SOC turnover across terrestrial biomes worldwide. We report a significant relationship between β and calculated soil C turnover rates (k), which were estimated by dividing soil heterotrophic respiration rates by SOC pools. ln( - β) exhibits a significant linear relationship with mean annual temperature, but a more complex polynomial relationship with mean annual precipitation, implying strong-feedbacks of SOC turnover to climate changes. Soil nitrogen (N) and clay content correlate strongly and positively with ln( - β), revealing the additional influence of nutrients and physical soil properties on SOC decomposition rates. Furthermore, a strong (R2 = 0.76; p < 0.001) linear relationship between ln( - β) and estimates of litter and root decomposition rates suggests similar controls over rates of organic matter decay among the generalized soil C stocks. Overall, these findings demonstrate the utility of soil δ13C for independently benchmarking global models of soil C turnover and thereby improving predictions of multiple global change influences over terrestrial C-climate feedback.

Simulating the impact of the large-scale circulation on the 2-m temperature and precipitation climatology

EPA Science Inventory

The impact of the simulated large-scale atmospheric circulation on the regional climate is examined using the Weather Research and Forecasting (WRF) model as a regional climate model. The purpose is to understand the potential need for interior grid nudging for dynamical downscal...

Milankovitch Modulation of the Ecosystem Dynamics of Fossil Great Lakes

NASA Astrophysics Data System (ADS)

Whiteside, J. H.; Olsen, P. E.; Eglinton, T. I.; Cornet, B.; Huber, P.; McDonald, N. G.

2008-12-01

Triassic and Early Jurassic lacustrine deposits of eastern North American rift basins preserve a spectacular record of precession-related Milankovitch forcing in the Pangean tropics. The abundant and well-preserved fossil fish assemblages from these great lakes demonstrate a sequence of cyclical changes that track the permeating hierarchy of climatic cycles. To detail ecosystem processes correlating with succession of fish communities, we measured bulk δ13Corg through a 100 ky series of Early Jurassic climatic precession-forced lake level cycles in the lower Shuttle Meadow Formation of the Hartford rift basin, CT. The deep-water phase of one of these cycles, the Bluff Head bed, has produced thousands of articulated fish. We observe fluctuations in the bulk δ13Corg of the cyclical strata that reflect differing degrees of lake water stratification, nutrient levels, and relative proportion of algal vs. plant derived organic matter that trace fish community changes. We can exclude extrinsic changes in the global exchangeable reservoirs as an origin of this variability because molecule-level δ13C of n-alkanes of plant leaf waxes from the same strata show no such variability. While at higher taxonomic levels the fish communities responded largely by sorting of taxa by environmental forcing, at the species level the holostean genus Semionotus responded by in situ evolution, and ultimately extinction, of a species flock. Fluctuations at the higher frequency, climatic precessional scale are mirrored at lower frequency, eccentricity modulated, scales, all following the lake-level hierarchical pattern. Thus, lacustrine isotopic ratios amplify the Milankovitch climate signal that was already intensified by sequelae of the end-Triassic extinctions. The degree to which the ecological structure of modern lakes responds to similar environmental cyclicity is largely unknown, but we suspect similar patterns and processes within the Neogene history of the East African great lakes, which may be modified in the future by anthropogenic CO2-driven intensification of the hydrological cycle.

Controls on late Holocene drift-sand dynamics: the role of people and climate on inland aeolian activity in the Netherlands

NASA Astrophysics Data System (ADS)

Pierik, Harm Jan; Van Lanen, Rowin; Gouw-Bouman, Marjolein; Groenewoudt, Bert; Wallinga, Jakob; Hoek, Wim

2017-04-01

Holocene drift-sand activity is commonly linked directly to either population pressure (via agricultural activity) or to climate change (e.g. storminess). In the Pleistocene sand areas of the Netherlands small-scale Holocene aeolian activity occurred since the Neolithic, whereas large scale drift-sand activity started during the Middle Ages (especially after AD 1000. This last phase coincides with the intensification of farming and demographic pressure, but is also commonly associated with a colder climate and enhanced storminess. This raises the question to what extent drift-sand activity can be attributed to human activities or to natural forcing factors. In this study we compare the spatial and chronological patterns of drift-sand occurrence for four characteristic Pleistocene sand regions in the Netherlands. For this, we compiled a new supra-regional overview of dates related to drift-sand activity (14C, OSL, archaeological and historical), that we compared with existing national soil maps, historical-route networks, and vegetation and climate reconstructions. Results show a steady occurrence of aeolian activity between 1000 BC and AD 1000, interrupted by remarkable dip in aeolian activity around 2000 BP, probably caused by changing land-use practices or by lower storminess. It is evident that human pressure on the landscape was most influential on initiating sand drifting: this is supported by more frequent occurrence close to routes and the uninterrupted increase in drift-sand activity after ca AD 1000 during periods of high population density and large-scale deforestation. Once triggered by human activities, the drift-sand development was probably further enhanced several centuries later during the cold and more stormy Little Ice Age (AD 1570-1900).

Computational data sciences for assessment and prediction of climate extremes

NASA Astrophysics Data System (ADS)

Ganguly, A. R.

2011-12-01

Climate extremes may be defined inclusively as severe weather events or large shifts in global or regional weather patterns which may be caused or exacerbated by natural climate variability or climate change. This area of research arguably represents one of the largest knowledge-gaps in climate science which is relevant for informing resource managers and policy makers. While physics-based climate models are essential in view of non-stationary and nonlinear dynamical processes, their current pace of uncertainty reduction may not be adequate for urgent stakeholder needs. The structure of the models may in some cases preclude reduction of uncertainty for critical processes at scales or for the extremes of interest. On the other hand, methods based on complex networks, extreme value statistics, machine learning, and space-time data mining, have demonstrated significant promise to improve scientific understanding and generate enhanced predictions. When combined with conceptual process understanding at multiple spatiotemporal scales and designed to handle massive data, interdisciplinary data science methods and algorithms may complement or supplement physics-based models. Specific examples from the prior literature and our ongoing work suggests how data-guided improvements may be possible, for example, in the context of ocean meteorology, climate oscillators, teleconnections, and atmospheric process understanding, which in turn can improve projections of regional climate, precipitation extremes and tropical cyclones in an useful and interpretable fashion. A community-wide effort is motivated to develop and adapt computational data science tools for translating climate model simulations to information relevant for adaptation and policy, as well as for improving our scientific understanding of climate extremes from both observed and model-simulated data.

Shaping climate change in the North Atlantic sector: The role of the atmospheric response to local SST changes vs. large-scale changes

NASA Astrophysics Data System (ADS)

Hand, Ralf; Keenlyside, Noel; Omrani, Nour-Eddine; Greatbatch, Richard; Bader, Jürgen

2017-04-01

Climate change simulations robustly show a warming hole in the sub-polar North Atlantic that results from slowing of the AMOC countering the global warming signal. Here we investigate how the distinct SST spatial structures, which include a sharpening of the Gulf Stream SST gradients, influence climate change in the NA sector in winter. For this we analyse the RCP8.5 scenario simulation of the MPI Earth System Model. Additional sensitivity experiments with the atmospheric model component, ECHAM5, are performed to deconstruct the effect of the local spatial structure of the SST change from those arising from large-scale warming of the ocean, remote SST pattern changes and changed radiative forcings. The MPI model simulation shows a signifcant decrease in precipitation to the south of the GS extension region in the future, despite a strong increase in underlying SST. While directly to the north there is a significant increase in precipitation. These distinct features in the precipitation response over the North Atlantic result from the local SST. Over the Gulf Stream, the differential structure of the precipitation changes reflects the changes of the local SST gradients there. Over the subpolar gyre the increase in precipitation is partly suppressed. In this region the Subpolar Gyre the weakened AMOC causes a SST warming, that is much weaker than the warming other regions of the ocean show at the same latitude. The large-scale response, which includes the overall increase in precipitation over the NA is due to the overall warming, remote SSTs and/or directly connected to the radiative forcing.

A method to encapsulate model structural uncertainty in ensemble projections of future climate: EPIC v1.0

NASA Astrophysics Data System (ADS)

Lewis, Jared; Bodeker, Greg E.; Kremser, Stefanie; Tait, Andrew

2017-12-01

A method, based on climate pattern scaling, has been developed to expand a small number of projections of fields of a selected climate variable (X) into an ensemble that encapsulates a wide range of indicative model structural uncertainties. The method described in this paper is referred to as the Ensemble Projections Incorporating Climate model uncertainty (EPIC) method. Each ensemble member is constructed by adding contributions from (1) a climatology derived from observations that represents the time-invariant part of the signal; (2) a contribution from forced changes in X, where those changes can be statistically related to changes in global mean surface temperature (Tglobal); and (3) a contribution from unforced variability that is generated by a stochastic weather generator. The patterns of unforced variability are also allowed to respond to changes in Tglobal. The statistical relationships between changes in X (and its patterns of variability) and Tglobal are obtained in a training phase. Then, in an implementation phase, 190 simulations of Tglobal are generated using a simple climate model tuned to emulate 19 different global climate models (GCMs) and 10 different carbon cycle models. Using the generated Tglobal time series and the correlation between the forced changes in X and Tglobal, obtained in the training phase, the forced change in the X field can be generated many times using Monte Carlo analysis. A stochastic weather generator is used to generate realistic representations of weather which include spatial coherence. Because GCMs and regional climate models (RCMs) are less likely to correctly represent unforced variability compared to observations, the stochastic weather generator takes as input measures of variability derived from observations, but also responds to forced changes in climate in a way that is consistent with the RCM projections. This approach to generating a large ensemble of projections is many orders of magnitude more computationally efficient than running multiple GCM or RCM simulations. Such a large ensemble of projections permits a description of a probability density function (PDF) of future climate states rather than a small number of individual story lines within that PDF, which may not be representative of the PDF as a whole; the EPIC method largely corrects for such potential sampling biases. The method is useful for providing projections of changes in climate to users wishing to investigate the impacts and implications of climate change in a probabilistic way. A web-based tool, using the EPIC method to provide probabilistic projections of changes in daily maximum and minimum temperatures for New Zealand, has been developed and is described in this paper.

Climate Drivers of Spatiotemporal Variability of Precipitation in the Source Region of Yangtze River

NASA Astrophysics Data System (ADS)

Du, Y.; Berndtsson, R.; An, D.; Yuan, F.

2017-12-01

Variability of precipitation regime has significant influence on the environment sustainability in the source region of Yangtze River, especially when the vegetation degradation and biodiversity reduction have already occurred. Understanding the linkage between variability of local precipitation and global teleconnection patterns is essential for water resources management. Based on physical reasoning, indices of the climate drivers can provide a practical way of predicting precipitation. Due to high seasonal variability of precipitation, climate drivers of the seasonal precipitation also varies. However, few reports have gone through the teleconnections between large scale patterns with seasonal precipitation in the source region of Yangtze River. The objectives of this study are therefore (1) assessment of temporal trend and spatial variability of precipitation in the source region of Yangtze River; (2) identification of climate indices with strong influence on seasonal precipitation anomalies; (3) prediction of seasonal precipitation based on revealed climate indices. Principal component analysis and Spearman rank correlation were used to detect significant relationships. A feed-forward artificial neural network(ANN) was developed to predict seasonal precipitation using significant correlated climate indices. Different influencing climate indices were revealed for precipitation in each season, with significant level and lag times. Significant influencing factors were selected to be the predictors for ANN model. With correlation coefficients between observed and simulated precipitation over 0.5, the results were eligible to predict the precipitation of spring, summer and winter using teleconnections, which can improve integrated water resources management in the source region of Yangtze River.

How does the terrestrial carbon exchange respond to inter-annual climatic variations? A quantification based on atmospheric CO2 data

NASA Astrophysics Data System (ADS)

Rödenbeck, Christian; Zaehle, Sönke; Keeling, Ralph; Heimann, Martin

2018-04-01

The response of the terrestrial net ecosystem exchange (NEE) of CO2 to climate variations and trends may crucially determine the future climate trajectory. Here we directly quantify this response on inter-annual timescales by building a linear regression of inter-annual NEE anomalies against observed air temperature anomalies into an atmospheric inverse calculation based on long-term atmospheric CO2 observations. This allows us to estimate the sensitivity of NEE to inter-annual variations in temperature (seen as a climate proxy) resolved in space and with season. As this sensitivity comprises both direct temperature effects and the effects of other climate variables co-varying with temperature, we interpret it as inter-annual climate sensitivity. We find distinct seasonal patterns of this sensitivity in the northern extratropics that are consistent with the expected seasonal responses of photosynthesis, respiration, and fire. Within uncertainties, these sensitivity patterns are consistent with independent inferences from eddy covariance data. On large spatial scales, northern extratropical and tropical inter-annual NEE variations inferred from the NEE-T regression are very similar to the estimates of an atmospheric inversion with explicit inter-annual degrees of freedom. The results of this study offer a way to benchmark ecosystem process models in more detail than existing effective global climate sensitivities. The results can also be used to gap-fill or extrapolate observational records or to separate inter-annual variations from longer-term trends.

Global patterns of drought recovery.

PubMed

Schwalm, Christopher R; Anderegg, William R L; Michalak, Anna M; Fisher, Joshua B; Biondi, Franco; Koch, George; Litvak, Marcy; Ogle, Kiona; Shaw, John D; Wolf, Adam; Huntzinger, Deborah N; Schaefer, Kevin; Cook, Robert; Wei, Yaxing; Fang, Yuanyuan; Hayes, Daniel; Huang, Maoyi; Jain, Atul; Tian, Hanqin

2017-08-09

Drought, a recurring phenomenon with major impacts on both human and natural systems, is the most widespread climatic extreme that negatively affects the land carbon sink. Although twentieth-century trends in drought regimes are ambiguous, across many regions more frequent and severe droughts are expected in the twenty-first century. Recovery time-how long an ecosystem requires to revert to its pre-drought functional state-is a critical metric of drought impact. Yet the factors influencing drought recovery and its spatiotemporal patterns at the global scale are largely unknown. Here we analyse three independent datasets of gross primary productivity and show that, across diverse ecosystems, drought recovery times are strongly associated with climate and carbon cycle dynamics, with biodiversity and CO 2 fertilization as secondary factors. Our analysis also provides two key insights into the spatiotemporal patterns of drought recovery time: first, that recovery is longest in the tropics and high northern latitudes (both vulnerable areas of Earth's climate system) and second, that drought impacts (assessed using the area of ecosystems actively recovering and time to recovery) have increased over the twentieth century. If droughts become more frequent, as expected, the time between droughts may become shorter than drought recovery time, leading to permanently damaged ecosystems and widespread degradation of the land carbon sink.

Global patterns of drought recovery

NASA Astrophysics Data System (ADS)

Schwalm, Christopher R.; Anderegg, William R. L.; Michalak, Anna M.; Fisher, Joshua B.; Biondi, Franco; Koch, George; Litvak, Marcy; Ogle, Kiona; Shaw, John D.; Wolf, Adam; Huntzinger, Deborah N.; Schaefer, Kevin; Cook, Robert; Wei, Yaxing; Fang, Yuanyuan; Hayes, Daniel; Huang, Maoyi; Jain, Atul; Tian, Hanqin

2017-08-01

Drought, a recurring phenomenon with major impacts on both human and natural systems, is the most widespread climatic extreme that negatively affects the land carbon sink. Although twentieth-century trends in drought regimes are ambiguous, across many regions more frequent and severe droughts are expected in the twenty-first century. Recovery time—how long an ecosystem requires to revert to its pre-drought functional state—is a critical metric of drought impact. Yet the factors influencing drought recovery and its spatiotemporal patterns at the global scale are largely unknown. Here we analyse three independent datasets of gross primary productivity and show that, across diverse ecosystems, drought recovery times are strongly associated with climate and carbon cycle dynamics, with biodiversity and CO2 fertilization as secondary factors. Our analysis also provides two key insights into the spatiotemporal patterns of drought recovery time: first, that recovery is longest in the tropics and high northern latitudes (both vulnerable areas of Earth’s climate system) and second, that drought impacts (assessed using the area of ecosystems actively recovering and time to recovery) have increased over the twentieth century. If droughts become more frequent, as expected, the time between droughts may become shorter than drought recovery time, leading to permanently damaged ecosystems and widespread degradation of the land carbon sink.

Environmental and Historical Determinants of Patterns of Genetic Differentiation in Wild Soybean (Glycine soja Sieb. et Zucc)

PubMed Central

He, Shui-Lian; Wang, Yun-Sheng; Li, De-Zhu; Yi, Ting-Shuang

2016-01-01

Wild soybean, the direct progenitor of cultivated soybean, inhabits a wide distribution range across the mainland of East Asia and the Japanese archipelago. A multidisciplinary approach combining analyses of population genetics based on 20 nuclear microsatellites and one plastid locus were applied to reveal the genetic variation of wild soybean, and the contributions of geographical, environmental factors and historic climatic change on its patterns of genetic differentiation. High genetic diversity and significant genetic differentiation were revealed in wild soybean. Wild soybean was inferred to be limited to southern and central China during the Last Glacial Maximum (LGM) and experienced large-scale post-LGM range expansion into northern East Asia. A substantial northward range shift has been predicted to occur by the 2080s. A stronger effect of isolation by environment (IBE) versus isolation by geographical distance (IBD) was found for genetic differentiation in wild soybean, which suggested that environmental factors were responsible for the adaptive eco-geographical differentiation. This study indicated that IBE and historical climatic change together shaped patterns of genetic variation and differentiation of wild soybean. Different conservation measures should be implemented on different populations according to their adaptive potential to future changes in climate and human-induced environmental changes. PMID:26952904

Regional impacts of Atlantic Forest deforestation on climate and vegetation dynamics

NASA Astrophysics Data System (ADS)

Holm, J. A.; Chambers, J. Q.

2012-12-01

The Brazilian Atlantic Forest was a large and important forest due to its high biodiversity, endemism, range in climate, and complex geography. The original Atlantic Forest was estimated to cover 150 million hectares, spanning large latitudinal, longitudinal, and elevation gradients. This unique environment helped contribute to a diverse assemblage of plants, mammals, birds, and reptiles. Unfortunately, due to land conversion into agriculture, pasture, urban areas, and increased forest fragmentation, only ~8-10% of the original Atlantic Forest remains. Tropical deforestation in the Americas can have considerable effects on local to global climates, and surrounding vegetation growth and survival. This study uses a fully coupled, global climate model (Community Earth System Model, CESM v.1.0.1) to simulate the full removal of the historical Atlantic Forest, and evaluate the regional climatic and vegetation responses due to deforestation. We used the fully coupled atmosphere and land surface components in CESM, and a partially interacting ocean component. The vegetated grid cell portion of the land surface component, the Community Landscape Model (CLM), is divided into 4 of 16 plant functional types (PFTs) with vertical layers of canopy, leaf area index, soil physical properties, and interacting hydrological features all tracking energy, water, and carbon state and flux variables, making CLM highly capable in predicting the complex nature and outcomes of large-scale deforestation. The Atlantic Forest removal (i.e. deforestation) was conducted my converting all woody stem PFTs to grasses in CLM, creating a land-use change from forest to pasture. By comparing the simulated historical Atlantic Forest (pre human alteration) to a deforested Atlantic Forest (close to current conditions) in CLM and CESM we found that live stem carbon, NPP (gC m-2 yr-1), and other vegetation dynamics inside and outside the Atlantic Forest region were largely altered. In addition to vegetation effects, regional surface air temperature (C°), precipitation (mm day-1), and emitted longwave radiation (W m-2) were highly affected in the location of the removed forest, and throughout surrounding areas of South America. For example climate patterns of increased temperature and decreased precipitation were affected as far as the Amazon Forest region. The use of fully coupled global climate and terrestrial models to study the effects of large-scale forest removal have been rarely applied. This study successfully showed the valuation of an important tropical forest, and the consequences of large deforestation through the reporting of complex earth-atmosphere interactions between vegetation dynamics and climate.

Effects of Ensemble Configuration on Estimates of Regional Climate Uncertainties

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

Goldenson, N.; Mauger, G.; Leung, L. R.

Internal variability in the climate system can contribute substantial uncertainty in climate projections, particularly at regional scales. Internal variability can be quantified using large ensembles of simulations that are identical but for perturbed initial conditions. Here we compare methods for quantifying internal variability. Our study region spans the west coast of North America, which is strongly influenced by El Niño and other large-scale dynamics through their contribution to large-scale internal variability. Using a statistical framework to simultaneously account for multiple sources of uncertainty, we find that internal variability can be quantified consistently using a large ensemble or an ensemble ofmore » opportunity that includes small ensembles from multiple models and climate scenarios. The latter also produce estimates of uncertainty due to model differences. We conclude that projection uncertainties are best assessed using small single-model ensembles from as many model-scenario pairings as computationally feasible, which has implications for ensemble design in large modeling efforts.« less

Simulations of the future precipitation climate of the Central Andes using a coupled regional climate model

NASA Astrophysics Data System (ADS)

Nicholls, S.; Mohr, K. I.

2014-12-01

The meridional extent and complex orography of the South American continent contributes to a wide diversity of climate regimes ranging from hyper-arid deserts to tropical rainforests to sub-polar highland regions. Global climate models, although capable of resolving synoptic-scale South American climate features, are inadequate for fully-resolving the strong gradients between climate regimes and the complex orography which define the Tropical Andes given their low spatial and temporal resolution. Recent computational advances now make practical regional climate modeling with prognostic mesoscale atmosphere-ocean coupled models, such as the Coupled Ocean-Atmosphere-Wave-Sediment Transport (COAWST) modeling system, to climate research. Previous work has shown COAWST to reasonably simulate the both the entire 2003-2004 wet season (Dec-Feb) as validated against both satellite and model analysis data. More recently, COAWST simulations have also been shown to sensibly reproduce the entire annual cycle of rainfall (Oct 2003 - Oct 2004) with historical climate model input. Using future global climate model input for COAWST, the present work involves year-long cycle spanning October to October for the years 2031, 2059, and 2087 assuming the most likely regional climate pathway (RCP): RCP 6.0. COAWST output is used to investigate how global climate change impacts the spatial distribution, precipitation rates, and diurnal cycle of precipitation patterns in the Central Andes vary in these yearly "snapshots". Initial results show little change to precipitation coverage or its diurnal cycle, however precipitation amounts did tend drier over the Brazilian Plateau and wetter over the Western Amazon and Central Andes. These results suggest potential adjustments to large-scale climate features (such as the Bolivian High).

Large-Scale Atmospheric Teleconnection Patterns Associated with the Interannual Variability of Heatwaves in East Asia and Its Decadal Changes

NASA Astrophysics Data System (ADS)

Choi, N.; Lee, M. I.; Lim, Y. K.; Kim, K. M.

2017-12-01

Heatwave is an extreme hot weather event which accompanies fatal damage to human health. The heatwave has a strong relationship with the large-scale atmospheric teleconnection patterns. In this study, we examine the spatial pattern of heatwave in East Asia by using the EOF analysis and the relationship between heatwave frequency and large-scale atmospheric teleconnection patterns. We also separate the time scale of heatwave frequency as the time scale longer than a decade and the interannual time scale. The long-term variation of heatwave frequency in East Asia shows a linkage with the sea surface temperature (SST) variability over the North Atlantic with a decadal time scale (a.k.a. the Atlantic Multidecadal Oscillation; AMO). On the other hands, the interannual variation of heatwave frequency is linked with the two dominant spatial patterns associated with the large-scale teleconnection patterns mimicking the Scandinavian teleconnection (SCAND-like) pattern and the circumglobal teleconnection (CGT-like) pattern, respectively. It is highlighted that the interannual variation of heatwave frequency in East Asia shows a remarkable change after mid-1990s. While the heatwave frequency was mainly associated with the CGT-like pattern before mid-1990s, the SCAND-like pattern becomes the most dominant one after mid-1990s, making the CGT-like pattern as the second. This study implies that the large-scale atmospheric teleconnection patterns play a key role in developing heatwave events in East Asia. This study further discusses possible mechanisms for the decadal change in the linkage between heatwave frequency and the large-scale teleconnection patterns in East Asia such as early melting of snow cover and/or weakening of East Asian jet stream due to global warming.

Antarctic climate and ice sheet changes and their relationship to global scale climate change over the last 2000 years

NASA Astrophysics Data System (ADS)

Steig, E. J.

2012-12-01

It is well known that the Antarctic ice sheet is changing rapidly and is probably now out of balance; at least in West Antarctica, it is now contributing significantly to sea level rise. Yet Antarctica is often thought of as being immune to the influence of anthropogenic climate trends affecting the rest of the planet. This view is based largely on the record of instrumental observations, which is both very short and largely exclusive of regions in West Antarctica that are undergoing rapid change (1). Data from ice cores (2) and boreholes (3) from across the West Antarctic Ice Sheet and the Antarctic Peninsula (4), coupled with new instrumental reconstructions (5, 6) paint a very different picture. The two newest long records from Antarctica --- at WAIS Divide (2) and at James Ross Island on the Antarctic Peninsula (4) -- show that over the last 2000 years, the temporal pattern of temperature change is similar to that for the Arctic: slow decline attributable to Milankovitch orbital forcing, interrupted by recent warming. The century-scale warming trend began early in the 20th century, coincident with strong warming trends across the Southern Hemisphere, and well before the advent of the ozone hole, to which Antarctic climate trends are frequently attributed (e.g. 7). Decadal temperature variability in Antarctica also follows averaged Southern Hemisphere variations: all the major decadal anomalies in the ~150-year instrumental climate record of the Southern Hemisphere appear in West Antarctica. Similar to the rest of the planet, the warmest period since at least 1850 C.E. in the Antarctic was the most recent two decades (1990s and 2000s), and the most recent warming in West Antarctica (including but not limited to the Peninsula) has been as rapid as anywhere else on Earth. The decadal to century-scale variations in West Antarctic temperature reflect by the strong dynamical link between the tropical Pacific and the southern high latitudes described by the Pacific South America (PSA) pattern, analogous to the better-known PNA of the Northern Hemisphere8. The atmospheric circulation anomalies associated with the PSA account not only for the temperature variability, but also for the recent observed changes in sea ice, and the ocean-driven melting of the margins of the large outlet glaciers that drain West Antarctica. Recent Antarctic ice losses are thus directly connected to global scale climate change, and cannot be attributed simply to local decadal variability or stochastic variations in glacier dynamics. 1. E. J. Steig et al., Nature 457, 459 (2009). 2. E. J. Steig et al., Nat. Geosci. in review, (2012). 3. A. J. Orsi, B. D. Cornuelle, J. P. Severinghaus, Geophys. Res. Lett. 39, L09710 (2012). 4. R. Mulvaney et al., Nature in press, (2012). 5. M. Küttel, E. J. Steig, Q. Ding, D. S. Battisti, A. J. Monaghan, Clim. Dyn. in press, (2012). 6. D. Bromwich, pers. comm., 2012. 7. D. W. J. Thompson et al., Nat. Geosci. 4, 741 (2011). 8. Y. Okumura, D. P. Schneider, C. Deser, R. Wilson. J. Climate in press, (2012).

Timing of seasonal migration in mule deer: effects of climate, plant phenology, and life-history characteristics

USGS Publications Warehouse

Monteith, Kevin L.; Bleich, Vernon C.; Stephenson, Thomas R.; Pierce, Beck M.; Conner, Mary M.; Klaver, Robert W.; Bowyer, R. Terry

2011-01-01

Phenological events of plants and animals are sensitive to climatic processes. Migration is a life-history event exhibited by most large herbivores living in seasonal environments, and is thought to occur in response to dynamics of forage and weather. Decisions regarding when to migrate, however, may be affected by differences in life-history characteristics of individuals. Long-term and intensive study of a population of mule deer (Odocoileus hemionus) in the Sierra Nevada, California, USA, allowed us to document patterns of migration during 11 years that encompassed a wide array of environmental conditions. We used two new techniques to properly account for interval-censored data and disentangle effects of broad-scale climate, local weather patterns, and plant phenology on seasonal patterns of migration, while incorporating effects of individual life-history characteristics. Timing of autumn migration varied substantially among individual deer, but was associated with the severity of winter weather, and in particular, snow depth and cold temperatures. Migratory responses to winter weather, however, were affected by age, nutritional condition, and summer residency of individual females. Old females and those in good nutritional condition risked encountering severe weather by delaying autumn migration, and were thus risk-prone with respect to the potential loss of foraging opportunities in deep snow compared with young females and those in poor nutritional condition. Females that summered on the west side of the crest of the Sierra Nevada delayed autumn migration relative to east-side females, which supports the influence of the local environment on timing of migration. In contrast, timing of spring migration was unrelated to individual life-history characteristics, was nearly twice as synchronous as autumn migration, differed among years, was related to the southern oscillation index, and was influenced by absolute snow depth and advancing phenology of plants. Plasticity in timing of migration in response to climatic conditions and plant phenology may be an adaptive behavioral strategy, which should reduce the detrimental effects of trophic mismatches between resources and other life-history events of large herbivores. Failure to consider effects of nutrition and other life-history traits may cloud interpretation of phenological patterns of mammals and conceal relationships associated with climate change.

The structure and large-scale organization of extreme cold waves over the conterminous United States

NASA Astrophysics Data System (ADS)

Xie, Zuowei; Black, Robert X.; Deng, Yi

2017-12-01

Extreme cold waves (ECWs) occurring over the conterminous United States (US) are studied through a systematic identification and documentation of their local synoptic structures, associated large-scale meteorological patterns (LMPs), and forcing mechanisms external to the US. Focusing on the boreal cool season (November-March) for 1950‒2005, a hierarchical cluster analysis identifies three ECW patterns, respectively characterized by cold surface air temperature anomalies over the upper midwest (UM), northwestern (NW), and southeastern (SE) US. Locally, ECWs are synoptically organized by anomalous high pressure and northerly flow. At larger scales, the UM LMP features a zonal dipole in the mid-tropospheric height field over North America, while the NW and SE LMPs each include a zonal wave train extending from the North Pacific across North America into the North Atlantic. The Community Climate System Model version 4 (CCSM4) in general simulates the three ECW patterns quite well and successfully reproduces the observed enhancements in the frequency of their associated LMPs. La Niña and the cool phase of the Pacific Decadal Oscillation (PDO) favor the occurrence of NW ECWs, while the warm PDO phase, low Arctic sea ice extent and high Eurasian snow cover extent (SCE) are associated with elevated SE-ECW frequency. Additionally, high Eurasian SCE is linked to increases in the occurrence likelihood of UM ECWs.

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.

Patterns and multi-scale drivers of phytoplankton species richness in temperate peri-urban lakes.

PubMed

Catherine, Arnaud; Selma, Maloufi; Mouillot, David; Troussellier, Marc; Bernard, Cécile

2016-07-15

Local species richness (SR) is a key characteristic affecting ecosystem functioning. Yet, the mechanisms regulating phytoplankton diversity in freshwater ecosystems are not fully understood, especially in peri-urban environments where anthropogenic pressures strongly impact the quality of aquatic ecosystems. To address this issue, we sampled the phytoplankton communities of 50 lakes in the Paris area (France) characterized by a large gradient of physico-chemical and catchment-scale characteristics. We used large phytoplankton datasets to describe phytoplankton diversity patterns and applied a machine-learning algorithm to test the degree to which species richness patterns are potentially controlled by environmental factors. Selected environmental factors were studied at two scales: the lake-scale (e.g. nutrients concentrations, water temperature, lake depth) and the catchment-scale (e.g. catchment, landscape and climate variables). Then, we used a variance partitioning approach to evaluate the interaction between lake-scale and catchment-scale variables in explaining local species richness. Finally, we analysed the residuals of predictive models to identify potential vectors of improvement of phytoplankton species richness predictive models. Lake-scale and catchment-scale drivers provided similar predictive accuracy of local species richness (R(2)=0.458 and 0.424, respectively). Both models suggested that seasonal temperature variations and nutrient supply strongly modulate local species richness. Integrating lake- and catchment-scale predictors in a single predictive model did not provide increased predictive accuracy; therefore suggesting that the catchment-scale model probably explains observed species richness variations through the impact of catchment-scale variables on in-lake water quality characteristics. Models based on catchment characteristics, which include simple and easy to obtain variables, provide a meaningful way of predicting phytoplankton species richness in temperate lakes. This approach may prove useful and cost-effective for the management and conservation of aquatic ecosystems. Copyright © 2016 Elsevier B.V. All rights reserved.

Validating Large Scale Networks Using Temporary Local Scale Networks

USDA-ARS?s Scientific Manuscript database

The USDA NRCS Soil Climate Analysis Network and NOAA Climate Reference Networks are nationwide meteorological and land surface data networks with soil moisture measurements in the top layers of soil. There is considerable interest in scaling these point measurements to larger scales for validating ...

Rapid climate fluctuations over the past millennium: evidence from a lacustrine record of Basomtso Lake, southeastern Tibetan Plateau

PubMed Central

Li, Kai; Liu, Xingqi; Herzschuh, Ulrike; Wang, Yongbo

2016-01-01

Abrupt climate changes and fluctuations over short time scales are superimposed on long-term climate changes. Understanding rapid climate fluctuations at the decadal time scale over the past millennium will enhance our understanding of patterns of climate variability and aid in forecasting climate changes in the future. In this study, climate changes on the southeastern Tibetan Plateau over the past millennium were determined from a 4.82-m-long sediment core from Basomtso Lake. At the centennial time scale, the Medieval Climate Anomaly (MCA), Little Ice Age (LIA) and Current Warm Period (CWP) are distinct in the Basomtso region. Rapid climate fluctuations inferred from five episodes with higher sediment input and likely warmer conditions, as well as seven episodes with lower sediment input and likely colder conditions, were well preserved in our record. These episodes with higher and lower sediment input are characterized by abrupt climate changes and short time durations. Spectral analysis indicates that the climate variations at the centennial scale on the southeastern Tibetan Plateau are influenced by solar activity during the past millennium. PMID:27091591

The asymmetric impact of global warming on US drought types and distributions in a large ensemble of 97 hydro-climatic simulations

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

Huang, Shengzhi; Leng, Guoyong; Huang, Qiang

Projection of future drought is often involved large uncertainties from climate models, emission scenarios as well as drought definitions. In this study, we investigate changes in future droughts in the conterminous United States based on 97 1/8 degree hydro-climate model projections. Instead of focusing on a specific drought type, we investigate changes in meteorological, agricultural, and hydrological drought as well as the concurrences. Agricultural and hydrological droughts are projected to become more frequent with increase in global mean temperature, while less meteorological drought is expected. Changes in drought intensity scale linearly with global temperature rises under RCP8.5 scenario, indicating themore » potential feasibility to derive future drought severity given certain global warming amount under this scenario. Changing pattern of concurrent droughts generally follows that of agricultural and hydrological droughts. Under the 1.5 °C warming target as advocated in recent Paris agreement, several hot spot regions experiencing highest droughts are identified. Extreme droughts show similar patterns but with much larger magnitude than the climatology. In conclusion, this study highlights the distinct response of droughts of various types to global warming and the asymmetric impact of global warming on drought distribution resulting in a much stronger influence on extreme drought than on mean drought.« less

The asymmetric impact of global warming on US drought types and distributions in a large ensemble of 97 hydro-climatic simulations

DOE PAGES

Huang, Shengzhi; Leng, Guoyong; Huang, Qiang; ...

2017-07-19

Projection of future drought is often involved large uncertainties from climate models, emission scenarios as well as drought definitions. In this study, we investigate changes in future droughts in the conterminous United States based on 97 1/8 degree hydro-climate model projections. Instead of focusing on a specific drought type, we investigate changes in meteorological, agricultural, and hydrological drought as well as the concurrences. Agricultural and hydrological droughts are projected to become more frequent with increase in global mean temperature, while less meteorological drought is expected. Changes in drought intensity scale linearly with global temperature rises under RCP8.5 scenario, indicating themore » potential feasibility to derive future drought severity given certain global warming amount under this scenario. Changing pattern of concurrent droughts generally follows that of agricultural and hydrological droughts. Under the 1.5 °C warming target as advocated in recent Paris agreement, several hot spot regions experiencing highest droughts are identified. Extreme droughts show similar patterns but with much larger magnitude than the climatology. In conclusion, this study highlights the distinct response of droughts of various types to global warming and the asymmetric impact of global warming on drought distribution resulting in a much stronger influence on extreme drought than on mean drought.« less

Beach Nourishment Dynamics in a Coupled Large-Scale Coastal Change and Economic Optimization Model

NASA Astrophysics Data System (ADS)

McNamara, D. E.; Murray, B.; Smith, M.

2008-12-01

Global climate change is predicted to have significant consequences for shoreline evolution from both sea level rise and changing wave climates. Because many coastal communities actively defend against erosion, changing environmental conditions will influence rates of nourishment. Over large coastal regions, including many towns, the anticipated future rate of nourishment is assumed to be proportional to the expected evolution of the shoreline in the region. This view neglects the possibility of strong coupling between the spatial patterns of nourishment and the distribution of property values within the region. To explore the impact of this coupling, we present a numerical model that incorporates the physical forces of alongshore sediment transport and erosion due to sea level rise as well as the economic forces that drive beach replenishment including the economic benefits of enhanced or maintained beach width and the costs of replenishing. Results are presented for a Carolina-like coastline and show how natural shoreline change rates are altered as the wave climate changes (because of changing storm behaviors). Results also show that the nourishment rate is conserved for varying property value distributions when the nourishment cost is unrelated to past nourishment and, in contrast, increasing nourishment cost as available sand for nourishment is depleted causes strong coupling between the property value distribution and erosion patterns. This strong coupling significantly alters the rate of nourishment and hence the depletion of available sand for nourishing.

Climates Past, Present, and Yet-to-Come Shape Climate Change Vulnerabilities.

PubMed

Nadeau, Christopher P; Urban, Mark C; Bridle, Jon R

2017-10-01

Climate change is altering life at multiple scales, from genes to ecosystems. Predicting the vulnerability of populations to climate change is crucial to mitigate negative impacts. We suggest that regional patterns of spatial and temporal climatic variation scaled to the traits of an organism can predict where and why populations are most vulnerable to climate change. Specifically, historical climatic variation affects the sensitivity and response capacity of populations to climate change by shaping traits and the genetic variation in those traits. Present and future climatic variation can affect both climate change exposure and population responses. We provide seven predictions for how climatic variation might affect the vulnerability of populations to climate change and suggest key directions for future research. Copyright © 2017 Elsevier Ltd. All rights reserved.

Substantial impacts of landscape changes on summer climate with major regional differences: The case of China.

PubMed

Cao, Qian; Yu, Deyong; Georgescu, Matei; Wu, Jianguo

2018-06-01

China's rapid socioeconomic development during the past few decades has resulted in large-scale landscape changes across the country. However, the impacts of these land surface modifications on climate are yet to be adequately understood. Using a coupled process-based land-atmospheric model, therefore, we quantified the climatic effects of land cover and land management changes over mainland China from 2001 to 2010, via incorporation of real-time and high-quality satellite-derived landscape representation (i.e., vegetation fraction, leaf area index, and albedo) into numerical modeling. Our results show that differences in landscape patterns due to changes in land cover and land management have exerted a strong influence on summer climate in China. During 2001 and 2010, extensive cooling of up to 1.5°C was found in the Loess Plateau and 1.0°C in northeastern China. In contrast, regional-scale warming was detected in the Tibetan Plateau (0.3°C), Yunnan province (0.4°C), and rapidly expanding urban centers across China (as high as 2°C). Summer precipitation decreased in the northeastern region, with patchy reduction generally <1.8mm/day, but increased in the Loess Plateau, with local spikes up to 2.4mm/day. Our study highlights that human alterations of landscapes have had substantial impacts on summer climate over the entire mainland China, but these impacts varied greatly on the regional scale, including changes in opposite directions. Therefore, effective national-level policies and regional land management strategies for climate change mitigation and adaptation should take explicit account of the spatial heterogeneity of landscape-climate interactions. Copyright © 2017 Elsevier B.V. All rights reserved.

Uncertainties in Future Regional Sea Level Trends: How to Deal with the Internal Climate Variability?

NASA Astrophysics Data System (ADS)

Becker, M.; Karpytchev, M.; Hu, A.; Deser, C.; Lennartz-Sassinek, S.

2017-12-01

Today, the Climate models (CM) are the main tools for forecasting sea level rise (SLR) at global and regional scales. The CM forecasts are accompanied by inherent uncertainties. Understanding and reducing these uncertainties is becoming a matter of increasing urgency in order to provide robust estimates of SLR impact on coastal societies, which need sustainable choices of climate adaptation strategy. These CM uncertainties are linked to structural model formulation, initial conditions, emission scenario and internal variability. The internal variability is due to complex non-linear interactions within the Earth Climate System and can induce diverse quasi-periodic oscillatory modes and long-term persistences. To quantify the effects of internal variability, most studies used multi-model ensembles or sea level projections from a single model ran with perturbed initial conditions. However, large ensembles are not generally available, or too small, and computationally expensive. In this study, we use a power-law scaling of sea level fluctuations, as observed in many other geophysical signals and natural systems, which can be used to characterize the internal climate variability. From this specific statistical framework, we (1) use the pre-industrial control run of the National Center for Atmospheric Research Community Climate System Model (NCAR-CCSM) to test the robustness of the power-law scaling hypothesis; (2) employ the power-law statistics as a tool for assessing the spread of regional sea level projections due to the internal climate variability for the 21st century NCAR-CCSM; (3) compare the uncertainties in predicted sea level changes obtained from a NCAR-CCSM multi-member ensemble simulations with estimates derived for power-law processes, and (4) explore the sensitivity of spatial patterns of the internal variability and its effects on regional sea level projections.

The Dynamics of a Semi-Arid Region in Response to Climate and Water - Use Policy

NASA Technical Reports Server (NTRS)

Mustard, John F.; Hamburg, Steve; Grant, John A.; Manning, Sara J.; Steinwand, Aaron; Howard, Chris

2000-01-01

The objectives of this project were to determine the response of semi-arid ecosystems to the combined forcings of climate variability and anthropogenic stress. Arid and semi-arid systems encompass close to 40% of the worlds land surface. The ecology of these regions are principally limited by water, and as the water resources wax and wane, so should the health and vigor of the ecosystems. Water, however, is a necessary and critical resource for humans living in these same regions. Thus for many and and semi-arid regions the natural systems and human systems are in direct competition for a limited resource. Increasing competition through development of and and semi-arid regions, export of water resources, as well as potential persistent changes in weather patterns are likely to lead to fundamental changes in carrying capacity, resilience, and ecology of these regions. A detailed understanding of these systems respond to forcing on a regional and local scale is required in order to better prepare for and manage future changes in the availability of water. In the Owens Valley CA, decadal changes in rainfall and increased use of groundwater resources by Los Angles (which derives 60-70% of its water from this region) have resulted in a large-scale experiment on the impacts of these changes in semi-arid ecosystems. This project works directly with the Inyo County Water Department (local water authority) and the Los Angles Department of Water and Power (regional demand on water resources) to understand changes, their causes, and impacts. Very detailed records have been kept for a number of selected sites in the valley which provide essential ground truth. These results are then scaled up through remote sensed data to regions scale to assess large scale patterns and link them to the fundamental decisions regarding the water resources of this region. A fundamental goal is to understand how resilient the native ecosystems are to large changes in water resources. Are they are on a spring (remove and return resources, do the systems return to the original state) or a vector (when water returns have the systems fundamentally changed).

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

Earth System Modeling and Field Experiments in the Arctic-Boreal Zone - Report from a NASA Workshop

NASA Technical Reports Server (NTRS)

Sellers, Piers; Rienecker Michele; Randall, David; Frolking, Steve

2012-01-01

Early climate modeling studies predicted that the Arctic Ocean and surrounding circumpolar land masses would heat up earlier and faster than other parts of the planet as a result of greenhouse gas-induced climate change, augmented by the sea-ice albedo feedback effect. These predictions have been largely borne out by observations over the last thirty years. However, despite constant improvement, global climate models have greater difficulty in reproducing the current climate in the Arctic than elsewhere and the scatter between projections from different climate models is much larger in the Arctic than for other regions. Biogeochemical cycle (BGC) models indicate that the warming in the Arctic-Boreal Zone (ABZ) could lead to widespread thawing of the permafrost, along with massive releases of CO2 and CH4, and large-scale changes in the vegetation cover in the ABZ. However, the uncertainties associated with these BGC model predictions are even larger than those associated with the physical climate system models used to describe climate change. These deficiencies in climate and BGC models reflect, at least in part, an incomplete understanding of the Arctic climate system and can be related to inadequate observational data or analyses of existing data. A workshop was held at NASA/GSFC, May 22-24 2012, to assess the predictive capability of the models, prioritize the critical science questions; and make recommendations regarding new field experiments needed to improve model subcomponents. This presentation will summarize the findings and recommendations of the workshop, including the need for aircraft and flux tower measurements and extension of existing in-situ measurements to improve process modeling of both the physical climate and biogeochemical cycle systems. Studies should be directly linked to remote sensing investigations with a view to scaling up the improved process models to the Earth System Model scale. Data assimilation and observing system simulation studies should be used to guide the deployment pattern and schedule for inversion studies as well. Synthesis and integration of previously funded Arctic-Boreal projects (e.g., ABLE, BOREAS, ICESCAPE, ICEBRIDGE, ARCTAS) should also be undertaken. Such an effort would include the integration of multiple remotely sensed products from the EOS satellites and other resources.

A multi-model ensemble view of winter heat flux dynamics and the dipole mode in the Mediterranean Sea

NASA Astrophysics Data System (ADS)

Liguori, Giovanni; Di Lorenzo, Emanuele; Cabos, William

2017-02-01

Changes in surface heat fluxes affect several climate processes controlling the Mediterranean climate. These include the winter formation of deep waters, which is the primary driver of the Mediterranean Sea overturning circulation. Previous studies that characterize the spatial and temporal variability of surface heat flux anomalies over the basin reveal the existence of two statistically dominant patterns of variability: a monopole of uniform sign and an east-west dipole of opposite signs. In this work, we use the 12 regional climate model ensemble from the EU-FP6 ENSEMBLES project to diagnose the large-scale atmospheric processes that control the variability of heat fluxes over the Mediterranean Sea from interannual to decadal timescales (here defined as timescales > 6 year). Our findings suggest that while the monopole structure captures variability in the winter-to-winter domain-average net heat flux, the dipole pattern tracks changes in the Mediterranean climate that are connected to the East Atlantic/Western Russia (EA/WR) atmospheric teleconnection pattern. Furthermore, while the monopole exhibits significant differences in the spatial structure across the multi-model ensemble, the dipole pattern is very robust and more clearly identifiable in the anomaly maps of individual years. A heat budget analysis of the dipole pattern reveals that changes in winds associated with the EA/WR pattern exert dominant control through both a direct effect on the latent heat flux (i.e., wind speed) and an indirect effect through specific humidity (e.g., wind advection). A simple reconstruction of the heat flux variability over the deep-water formation regions of the Gulf of Lion and the Aegean Sea reveals that the combination of the monopole and dipole time series explains over 90 % of the heat flux variance in these regions. Given the important role that surface heat flux anomalies play in deep-water formation and the regional climate, improving our knowledge on the dynamics controlling the leading modes of heat flux variability may enhance our predictability of the climate of the Mediterranean area.

Volcanic Eruptions and Climate: Outstanding Research Issues

NASA Astrophysics Data System (ADS)

Robock, Alan

2016-04-01

Large volcanic eruptions inject sulfur gases into the stratosphere, which convert to sulfate aerosols with an e-folding residence time of about one year. The radiative and chemical effects of this aerosol cloud produce responses in the climate system. Based on observations after major eruptions of the past and experiments with numerical models of the climate system, we understand much about their climatic impact, but there are also a number of unanswered questions. Volcanic eruptions produce global cooling, and are an important natural cause of interannual, interdecadal, and even centennial-scale climate change. One of the most interesting volcanic effects is the "winter warming" of Northern Hemisphere continents following major tropical eruptions. During the winter in the Northern Hemisphere following every large tropical eruption of the past century, surface air temperatures over North America, Europe, and East Asia were warmer than normal, while they were colder over Greenland and the Middle East. This pattern and the coincident atmospheric circulation correspond to the positive phase of the Arctic Oscillation. While this response is observed after recent major eruptions, most state-of-the-art climate models have trouble simulating winter warming. Why? High latitude eruptions in the Northern Hemisphere, while also producing global cooling, do not have the same impact on atmospheric dynamics. Both tropical and high latitude eruptions can weaken the Indian and African summer monsoon, and the effects can be seen in past records of flow in the Nile and Niger Rivers. Since the Mt. Pinatubo eruption in the Philippines in 1991, there have been no large eruptions that affected climate, but the cumulative effects of small eruptions over the past decade have had a small effect on global temperature trends. Some important outstanding research questions include: How much seasonal, annual, and decadal predictability is possible following a large volcanic eruption? Do volcanic eruptions change the probability of El Niño or La Niña in the years following the eruption? Are there decadal-scale oceanic responses that can provide long-term predictability? What was the contribution of volcanic eruptions to initiation and maintenance of the Little Ice Age? What are the observational needs for future volcanic eruptions that will help to improve forecasts, observe responses following volcanic eruptions, and better understand nucleation and growth of sulfate aerosols, which is important for evaluating suggestions for considering anthropogenic stratospheric clouds for climate engineering?

Expanded spatial extent of the Medieval Climate Anomaly revealed in lake-sediment records across the boreal region in northwest Ontario.

PubMed

Laird, Kathleen R; Haig, Heather A; Ma, Susan; Kingsbury, Melanie V; Brown, Thomas A; Lewis, C F Michael; Oglesby, Robert J; Cumming, Brian F

2012-09-01

Multi-decadal to centennial-scale shifts in effective moisture over the past two millennia are inferred from sedimentary records from six lakes spanning a ~250 km region in northwest Ontario. This is the first regional application of a technique developed to reconstruct drought from drainage lakes (open lakes with surface outlets). This regional network of proxy drought records is based on individual within-lake calibration models developed using diatom assemblages collected from surface sediments across a water-depth gradient. Analysis of diatom assemblages from sediment cores collected close to the near-shore ecological boundary between benthic and planktonic diatom taxa indicated this boundary shifted over time in all lakes. These shifts are largely dependent on climate-driven influences, and can provide a sensitive record of past drought. Our lake-sediment records indicate two periods of synchronous signals, suggesting a common large-scale climate forcing. The first is a period of prolonged aridity during the Medieval Climate Anomaly (MCA, c. 900-1400 CE). Documentation of aridity across this region expands the known spatial extent of the MCA megadrought into a region that historically has not experienced extreme droughts such as those in central and western north America. The second synchronous period is the recent signal of the past ~100 years, which indicates a change to higher effective moisture that may be related to anthropogenic forcing on climate. This approach has the potential to fill regional gaps, where many previous paleo-lake depth methods (based on deeper centrally located cores) were relatively insensitive. By filling regional gaps, a better understanding of past spatial patterns in drought can be used to assess the sensitivity and realism of climate model projections of future climate change. This type of data is especially important for validating high spatial resolution, regional climate models. © 2012 Blackwell Publishing Ltd.

Responses of runoff to historical and future climate variability over China

NASA Astrophysics Data System (ADS)

Wu, Chuanhao; Hu, Bill X.; Huang, Guoru; Wang, Peng; Xu, Kai

2018-03-01

China has suffered some of the effects of global warming, and one of the potential implications of climate warming is the alteration of the temporal-spatial patterns of water resources. Based on the long-term (1960-2008) water budget data and climate projections from 28 global climate models (GCMs) of the Coupled Model Intercomparison Project Phase 5 (CMIP5), this study investigated the responses of runoff (R) to historical and future climate variability in China at both grid and catchment scales using the Budyko-based elasticity method. Results show that there is a large spatial variation in precipitation (P) elasticity (from 1.1 to 3.2) and potential evaporation (PET) elasticity (from -2.2 to -0.1) across China. The P elasticity is larger in north-eastern and western China than in southern China, while the opposite occurs for PET elasticity. The catchment properties' elasticity of R appears to have a strong non-linear relationship with the mean annual aridity index and tends to be more significant in more arid regions. For the period 1960-2008, the climate contribution to R ranges from -2.4 to 3.6 % yr-1 across China, with the negative contribution in north-eastern China and the positive contribution in western China and some parts of the south-west. The results of climate projections indicate that although there is large uncertainty involved in the 28 GCMs, most project a consistent change in P (or PET) in China at the annual scale. For the period 2071-2100, the mean annual P is projected to increase in most parts of China, especially the western regions, while the mean annual PET is projected to increase in all of China, particularly the southern regions. Furthermore, greater increases are projected for higher emission scenarios. Overall, due to climate change, the arid regions and humid regions of China are projected to become wetter and drier in the period 2071-2100, respectively (relative to the baseline 1971-2000).

Long-term Records of Pacific Salmon Abundance From Sediment Core Analysis: Relationships to Past Climatic Change, and Implications for the Future

NASA Astrophysics Data System (ADS)

Finney, B.

2002-12-01

The response of Pacific salmon to future climatic change is uncertain, but will have large impacts on the economy, culture and ecology of the North Pacific Rim. Relationships between sockeye salmon populations and climatic change can be determined by analyzing sediment cores from lakes where sockeye return to spawn. Sockeye salmon return to their natal lake system to spawn and subsequently die following 2 - 3 years of feeding in the North Pacific Ocean. Sockeye salmon abundance can be reconstructed from stable nitrogen isotope analysis of lake sediment cores as returning sockeye transport significant quantities of N, relatively enriched in N-15, from the ocean to freshwater systems. Temporal changes in the input of salmon-derived N, and hence salmon abundance, can be quantified through downcore analysis of N isotopes. Reconstructions of sockeye salmon abundance from lakes in several regions of Alaska show similar temporal patterns, with variability occurring on decadal to millennial timescales. Over the past 2000 years, shifts in sockeye salmon abundance far exceed the historical decadal-scale variability. A decline occurred from about 100 BC - 800 AD, but salmon were consistently more abundant 1200 - 1900 AD. Declines since 1900 AD coincide with the period of extensive commercial fishing. Correspondence between these records and paleoclimatic data suggest that changes in salmon abundance are related to large scale climatic changes over the North Pacific. For example, the increase in salmon abundance c.a. 1200 AD corresponds to a period of glacial advance in southern Alaska, and a shift to drier conditions in western North America. Although the regionally coherent patterns in reconstructed salmon abundance are consistent with the hypothesis that climate is an important driver, the relationships do not always follow patterns observed in the 20th century. A main feature of recorded climate variability in this region is the alternation between multi-decade periods of above and below average strength of the Aleutian Low pressure system. During periods of stronger low pressure, sea surface temperature anomalies are warm in the northeast Pacific and cool in the central and northwest Pacific, a condition referred to as the positive phase of the Pacific Interdecadal Oscillation (PDO). Historically, during positive phases of the PDO Alaska salmon abundance is generally high. Consistent with this pattern, records of reconstructed sockeye salmon generally show higher abundance during warm periods over the past 300 years. However, the long-term trend suggests generally higher abundance during the cooler Little Ice Age, which southern Alaska glacial records suggest occurred between about 1200 - 1900 AD. The apparent complexity of salmon-climate relationships may be due to several factors. Long-term paleoclimate records from this region suggest additional modes of North Pacific climate variability, relative to the PDO. In addition, data on primary and secondary production in the Northeast Pacific Ocean indicates that climatic forcing has a direct impact on lower trophic levels, which subsequently affects salmon production. Thus records of ocean productivity, which are currently unavailable, may provide a mechanistic linkage between climate change and salmon abundance. The long-term perspective provided by the paleodata suggest that historical observations provide a limited understanding of how Pacific salmon respond to climatic change, and point to important areas of research necessary to better predict future responses.

Continental synchronicity of human influenza virus epidemics despite climactic variation

PubMed Central

Sullivan, Sheena; Barr, Ian

2018-01-01

The factors that determine the pattern and rate of spread of influenza virus at a continental-scale are uncertain. Although recent work suggests that influenza epidemics in the United States exhibit a strong geographical correlation, the spatiotemporal dynamics of influenza in Australia, a country and continent of approximately similar size and climate complexity but with a far smaller population, are not known. Using a unique combination of large-scale laboratory-confirmed influenza surveillance comprising >450,000 entries and genomic sequence data we determined the local-level spatial diffusion of this important human pathogen nationwide in Australia. We used laboratory-confirmed influenza data to characterize the spread of influenza virus across Australia during 2007–2016. The onset of established epidemics varied across seasons, with highly synchronized epidemics coinciding with the emergence of antigenically distinct viruses, particularly during the 2009 A/H1N1 pandemic. The onset of epidemics was largely synchronized between the most populous cities, even those separated by distances of >3000 km and those that experience vastly diverse climates. In addition, by analyzing global phylogeographic patterns we show that the synchronized dissemination of influenza across Australian cities involved multiple introductions from the global influenza population, coupled with strong domestic connectivity, rather than through the distinct radial patterns of geographic dispersal that are driven by work-flow transmission as observed in the United States. In addition, by comparing the spatial structure of influenza A and B, we found that these viruses tended to occupy different geographic regions, and peak in different seasons, perhaps indicative of moderate cross-protective immunity or viral interference effects. The highly synchronized outbreaks of influenza virus at a continental-scale revealed here highlight the importance of coordinated public health responses in the event of the emergence of a novel, human-to-human transmissible, virus. PMID:29324895

Bridging a possible gap of GRACE observations in the Arctic Ocean using existing GRACE data and in situ bottom pressure sensors

NASA Astrophysics Data System (ADS)

Peralta Ferriz, C.; Morison, J.

2014-12-01

Since 2003, the Gravity Recovery and Climate Experiment (GRACE) satellite system has provided the means of investigating month-to-month to inter-annual variability of, among many other things, Arctic Ocean circulation over the entire Arctic Basin. Such a comprehensive picture could not have been achieved with the limited in situ pressure observations available. Results from the first 10 years of ocean bottom pressure measurements from GRACE in the Arctic Ocean reveal distinct patterns of ocean variability that are strongly associated with changes in large-scale atmospheric circulation (Peralta-Ferriz et al., 2014): the leading mode of variability being a wintertime basin-coherent mass change driven by winds in the Nordic Seas; the second mode of variability corresponding to a mass signal coherent along the Siberian shelves, and driven by the Arctic Oscillation; and the third mode being a see-saw between western and eastern Arctic shelves, also driven by the large-scale wind patterns. In order to understand Arctic Ocean changes, it is fundamental to continue to track ocean bottom pressure. Our concern is what to do if the present GRACE system, which is already well beyond its design lifetime, should fail before its follow-on is launched, currently estimated to be in 2017. In this work, we regress time series of pressure from the existing and potential Arctic Ocean bottom pressure recorder locations against the fundamental modes of bottom pressure variation. Our aim is to determine the optimum combination of in situ measurements to represent the broader scale variability now observed by GRACE. With this understanding, we can be better prepared to use in situ observations to at least partially cover a possible gap in GRACE coverage. Reference:Peralta-Ferriz, Cecilia, James H. Morison, John M. Wallace, Jennifer A. Bonin, Jinlun Zhang, 2014: Arctic Ocean Circulation Patterns Revealed by GRACE. J. Climate, 27, 1445-1468. doi: http://dx.doi.org/10.1175/JCLI-D-13-00013.1

Northern Plains Blizzards in Past and Future Climates

NASA Astrophysics Data System (ADS)

Trellinger, A.; Kennedy, A. D.

2017-12-01

High-latitude regions of the globe including the northern tier of the United States are subject to adverse conditions during the winter such as snowstorms. When snowfall combines with strong winds, blizzards can result and these events have significant personal, societal, and economic impacts for the Northern Plains. Although the climatology of wintertime extremes such as blizzards is reasonably understood, it is not known how the frequency and intensity of these events may change in a warming climate. Complicating factors include competing trends that suggest winter will have more snow over this region, but over a shorter seasonal duration. Identifying blizzards in climate models is difficult due to the horizontal and vertical grid spacing used. Additionally, blowing snow is not considered in these models, so it cannot be directly diagnosed. Instead, alternative ways must be developed to identify these events. The presented work will use a competitive neural network known as the Self-Organizing Map (SOM) to identify meteorological patterns associated with blizzard events over the Northern Plains from 1979-2016. Once these large-scale patterns are identified from observations, they will be identified in Community Climate System Model (CESM) 4.0 20th Century forcing climate simulations run in support for the Coupled Model Intercomparison Project Phase 5 (CMIP-5). In specific, the methodology will rely on the `Mother of All Runs' (MOAR) ensemble member. Because this member provides subdaily output for many variables, specific meteorological patterns can be identified. Blizzard events will be identified during historical time periods to determine biases, and then under future emissions scenarios.

Climate change and the impact of increased rainfall variability on sediment transport and catchment scale water quality

NASA Astrophysics Data System (ADS)

Hancock, G. R.; Willgoose, G. R.; Cohen, S.

2009-12-01

Recently there has been recognition that changing climate will affect rainfall and storm patterns with research directed to examine how the global hydrological cycle will respond to climate change. This study investigates the effect of different rainfall patterns on erosion and resultant water quality for a well studied tropical monsoonal catchment that is undisturbed by Europeans in the Northern Territory, Australia. Water quality has a large affect on a range of aquatic flora and fauna and a significant change in sediment could have impacts on the aquatic ecosystems. There have been several studies of the effect of climate change on rainfall patterns in the study area with projections indicating a significant increase in storm activity. Therefore it is important that the impact of this variability be assessed in terms of catchment hydrology, sediment transport and water quality. Here a numerical model of erosion and hydrology (CAESAR) is used to assess several different rainfall scenarios over a 1000 year modelled period. The results show that that increased rainfall amount and intensity increases sediment transport rates but predicted water quality was variable and non-linear but within the range of measured field data for the catchment and region. Therefore an assessment of sediment transport and water quality is a significant and complex issue that requires further understandings of the role of biophysical feedbacks such as vegetation as well as the role of humans in managing landscapes (i.e. controlled and uncontrolled fire). The study provides a robust methodology for assessing the impact of enhanced climate variability on sediment transport and water quality.

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.