School Climate and Student Absenteeism and Internalizing and Externalizing Behavioral Problems

ERIC Educational Resources Information Center

Hendron, Marisa; Kearney, Christopher A.

2016-01-01

This study examined whether school climate variables were directly and inversely related to absenteeism severity and key symptoms of psychopathology among youths specifically referred for problematic attendance (N = 398). Adolescents in our sample completed the School Climate Survey Revised Edition, which measured sharing of resources, order and…

The Contribution of Vegetation and Landscape Configuration for Predicting Environmental Change Impacts on Iberian Birds

PubMed Central

Triviño, Maria; Thuiller, Wilfried; Cabeza, Mar; Hickler, Thomas; Araújo, Miguel B.

2011-01-01

Although climate is known to be one of the key factors determining animal species distributions amongst others, projections of global change impacts on their distributions often rely on bioclimatic envelope models. Vegetation structure and landscape configuration are also key determinants of distributions, but they are rarely considered in such assessments. We explore the consequences of using simulated vegetation structure and composition as well as its associated landscape configuration in models projecting global change effects on Iberian bird species distributions. Both present-day and future distributions were modelled for 168 bird species using two ensemble forecasting methods: Random Forests (RF) and Boosted Regression Trees (BRT). For each species, several models were created, differing in the predictor variables used (climate, vegetation, and landscape configuration). Discrimination ability of each model in the present-day was then tested with four commonly used evaluation methods (AUC, TSS, specificity and sensitivity). The different sets of predictor variables yielded similar spatial patterns for well-modelled species, but the future projections diverged for poorly-modelled species. Models using all predictor variables were not significantly better than models fitted with climate variables alone for ca. 50% of the cases. Moreover, models fitted with climate data were always better than models fitted with landscape configuration variables, and vegetation variables were found to correlate with bird species distributions in 26–40% of the cases with BRT, and in 1–18% of the cases with RF. We conclude that improvements from including vegetation and its landscape configuration variables in comparison with climate only variables might not always be as great as expected for future projections of Iberian bird species. PMID:22216263

CLARREO Cornerstone of the Earth Observing System: Measuring Decadal Change Through Accurate Emitted Infrared and Reflected Solar Spectra and Radio Occultation

NASA Technical Reports Server (NTRS)

Sandford, Stephen P.

2010-01-01

The Climate Absolute Radiance and Refractivity Observatory (CLARREO) is one of four Tier 1 missions recommended by the recent NRC Decadal Survey report on Earth Science and Applications from Space (NRC, 2007). The CLARREO mission addresses the need to provide accurate, broadly acknowledged climate records that are used to enable validated long-term climate projections that become the foundation for informed decisions on mitigation and adaptation policies that address the effects of climate change on society. The CLARREO mission accomplishes this critical objective through rigorous SI traceable decadal change observations that are sensitive to many of the key uncertainties in climate radiative forcings, responses, and feedbacks that in turn drive uncertainty in current climate model projections. These same uncertainties also lead to uncertainty in attribution of climate change to anthropogenic forcing. For the first time CLARREO will make highly accurate, global, SI-traceable decadal change observations sensitive to the most critical, but least understood, climate forcings, responses, and feedbacks. The CLARREO breakthrough is to achieve the required levels of accuracy and traceability to SI standards for a set of observations sensitive to a wide range of key decadal change variables. The required accuracy levels are determined so that climate trend signals can be detected against a background of naturally occurring variability. Climate system natural variability therefore determines what level of accuracy is overkill, and what level is critical to obtain. In this sense, the CLARREO mission requirements are considered optimal from a science value perspective. The accuracy for decadal change traceability to SI standards includes uncertainties associated with instrument calibration, satellite orbit sampling, and analysis methods. Unlike most space missions, the CLARREO requirements are driven not by the instantaneous accuracy of the measurements, but by accuracy in the large time/space scale averages that are key to understanding decadal changes.

VEMAP phase 2 bioclimatic database. I. Gridded historical (20th century) climate for modeling ecosystem dynamics across the conterminous USA

Treesearch

Timothy G.F. Kittel; Nan. A. Rosenbloom; J.A. Royle; C. Daly; W.P. Gibson; H.H. Fisher; P. Thornton; D.N. Yates; S. Aulenbach; C. Kaufman; R. McKeown; Dominque Bachelet; David S. Schimel

2004-01-01

Analysis and simulation of biospheric responses to historical forcing require surface climate data that capture those aspects of climate that control ecological processes, including key spatial gradients and modes of temporal variability. We developed a multivariate, gridded historical climate dataset for the conterminous USA as a common input database for the...

Climate Change Impact Assessment of Food- and Waterborne Diseases.

PubMed

Semenza, Jan C; Herbst, Susanne; Rechenburg, Andrea; Suk, Jonathan E; Höser, Christoph; Schreiber, Christiane; Kistemann, Thomas

2012-04-01

The PubMed and ScienceDirect bibliographic databases were searched for the period of 1998-2009 to evaluate the impact of climatic and environmental determinants on food- and waterborne diseases. The authors assessed 1,642 short and concise sentences (key facts), which were extracted from 722 relevant articles and stored in a climate change knowledge base. Key facts pertaining to temperature, precipitation, water, and food for 6 selected pathogens were scrutinized, evaluated, and compiled according to exposure pathways. These key facts (corresponding to approximately 50,000 words) were mapped to 275 terminology terms identified in the literature, which generated 6,341 connections. These relationships were plotted on semantic network maps to examine the interconnections between variables. The risk of campylobacteriosis is associated with mean weekly temperatures, although this link is shown more strongly in the literature relating to salmonellosis. Irregular and severe rain events are associated with Cryptosporidium sp. outbreaks, while noncholera Vibrio sp. displays increased growth rates in coastal waters during hot summers. In contrast, for Norovirus and Listeria sp. the association with climatic variables was relatively weak, but much stronger for food determinants. Electronic data mining to assess the impact of climate change on food- and waterborne diseases assured a methodical appraisal of the field. This climate change knowledge base can support national climate change vulnerability, impact, and adaptation assessments and facilitate the management of future threats from infectious diseases. In the light of diminishing resources for public health this approach can help balance different climate change adaptation options.

Climate Change Impact Assessment of Food- and Waterborne Diseases

PubMed Central

Semenza, Jan C.; Herbst, Susanne; Rechenburg, Andrea; Suk, Jonathan E.; Höser, Christoph; Schreiber, Christiane; Kistemann, Thomas

2011-01-01

The PubMed and ScienceDirect bibliographic databases were searched for the period of 1998–2009 to evaluate the impact of climatic and environmental determinants on food- and waterborne diseases. The authors assessed 1,642 short and concise sentences (key facts), which were extracted from 722 relevant articles and stored in a climate change knowledge base. Key facts pertaining to temperature, precipitation, water, and food for 6 selected pathogens were scrutinized, evaluated, and compiled according to exposure pathways. These key facts (corresponding to approximately 50,000 words) were mapped to 275 terminology terms identified in the literature, which generated 6,341 connections. These relationships were plotted on semantic network maps to examine the interconnections between variables. The risk of campylobacteriosis is associated with mean weekly temperatures, although this link is shown more strongly in the literature relating to salmonellosis. Irregular and severe rain events are associated with Cryptosporidium sp. outbreaks, while noncholera Vibrio sp. displays increased growth rates in coastal waters during hot summers. In contrast, for Norovirus and Listeria sp. the association with climatic variables was relatively weak, but much stronger for food determinants. Electronic data mining to assess the impact of climate change on food- and waterborne diseases assured a methodical appraisal of the field. This climate change knowledge base can support national climate change vulnerability, impact, and adaptation assessments and facilitate the management of future threats from infectious diseases. In the light of diminishing resources for public health this approach can help balance different climate change adaptation options. PMID:24808720

Rivers and Floodplains as Key Components of Global Terrestrial Water Storage Variability

NASA Astrophysics Data System (ADS)

Getirana, Augusto; Kumar, Sujay; Girotto, Manuela; Rodell, Matthew

2017-10-01

This study quantifies the contribution of rivers and floodplains to terrestrial water storage (TWS) variability. We use state-of-the-art models to simulate land surface processes and river dynamics and to separate TWS into its main components. Based on a proposed impact index, we show that surface water storage (SWS) contributes 8% of TWS variability globally, but that contribution differs widely among climate zones. Changes in SWS are a principal component of TWS variability in the tropics, where major rivers flow over arid regions and at high latitudes. SWS accounts for 22-27% of TWS variability in both the Amazon and Nile Basins. Changes in SWS are negligible in the Western U.S., Northern Africa, Middle East, and central Asia. Based on comparisons with Gravity Recovery and Climate Experiment-based TWS, we conclude that accounting for SWS improves simulated TWS in most of South America, Africa, and Southern Asia, confirming that SWS is a key component of TWS variability.

Climate, soil or both? Which variables are better predictors of the distributions of Australian shrub species?

PubMed Central

Esperón-Rodríguez, Manuel; Baumgartner, John B.; Beaumont, Linda J.

2017-01-01

Background Shrubs play a key role in biogeochemical cycles, prevent soil and water erosion, provide forage for livestock, and are a source of food, wood and non-wood products. However, despite their ecological and societal importance, the influence of different environmental variables on shrub distributions remains unclear. We evaluated the influence of climate and soil characteristics, and whether including soil variables improved the performance of a species distribution model (SDM), Maxent. Methods This study assessed variation in predictions of environmental suitability for 29 Australian shrub species (representing dominant members of six shrubland classes) due to the use of alternative sets of predictor variables. Models were calibrated with (1) climate variables only, (2) climate and soil variables, and (3) soil variables only. Results The predictive power of SDMs differed substantially across species, but generally models calibrated with both climate and soil data performed better than those calibrated only with climate variables. Models calibrated solely with soil variables were the least accurate. We found regional differences in potential shrub species richness across Australia due to the use of different sets of variables. Conclusions Our study provides evidence that predicted patterns of species richness may be sensitive to the choice of predictor set when multiple, plausible alternatives exist, and demonstrates the importance of considering soil properties when modeling availability of habitat for plants. PMID:28652933

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.

Malaria incidence trends and their association with climatic variables in rural Gwanda, Zimbabwe, 2005-2015.

PubMed

Gunda, Resign; Chimbari, Moses John; Shamu, Shepherd; Sartorius, Benn; Mukaratirwa, Samson

2017-09-30

Malaria is a public health problem in Zimbabwe. Although many studies have indicated that climate change may influence the distribution of malaria, there is paucity of information on its trends and association with climatic variables in Zimbabwe. To address this shortfall, the trends of malaria incidence and its interaction with climatic variables in rural Gwanda, Zimbabwe for the period January 2005 to April 2015 was assessed. Retrospective data analysis of reported cases of malaria in three selected Gwanda district rural wards (Buvuma, Ntalale and Selonga) was carried out. Data on malaria cases was collected from the district health information system and ward clinics while data on precipitation and temperature were obtained from the climate hazards group infrared precipitation with station data (CHIRPS) database and the moderate resolution imaging spectro-radiometer (MODIS) satellite data, respectively. Distributed lag non-linear models (DLNLM) were used to determine the temporal lagged association between monthly malaria incidence and monthly climatic variables. There were 246 confirmed malaria cases in the three wards with a mean incidence of 0.16/1000 population/month. The majority of malaria cases (95%) occurred in the > 5 years age category. The results showed no correlation between trends of clinical malaria (unconfirmed) and confirmed malaria cases in all the three study wards. There was a significant association between malaria incidence and the climatic variables in Buvuma and Selonga wards at specific lag periods. In Ntalale ward, only precipitation (1- and 3-month lag) and mean temperature (1- and 2-month lag) were significantly associated with incidence at specific lag periods (p < 0.05). DLNM results suggest a key risk period in current month, based on key climatic conditions in the 1-4 month period prior. As the period of high malaria risk is associated with precipitation and temperature at 1-4 month prior in a seasonal cycle, intensifying malaria control activities over this period will likely contribute to lowering the seasonal malaria incidence.

Quantitative approaches in climate change ecology

PubMed Central

Brown, Christopher J; Schoeman, David S; Sydeman, William J; Brander, Keith; Buckley, Lauren B; Burrows, Michael; Duarte, Carlos M; Moore, Pippa J; Pandolfi, John M; Poloczanska, Elvira; Venables, William; Richardson, Anthony J

2011-01-01

Contemporary impacts of anthropogenic climate change on ecosystems are increasingly being recognized. Documenting the extent of these impacts requires quantitative tools for analyses of ecological observations to distinguish climate impacts in noisy data and to understand interactions between climate variability and other drivers of change. To assist the development of reliable statistical approaches, we review the marine climate change literature and provide suggestions for quantitative approaches in climate change ecology. We compiled 267 peer-reviewed articles that examined relationships between climate change and marine ecological variables. Of the articles with time series data (n = 186), 75% used statistics to test for a dependency of ecological variables on climate variables. We identified several common weaknesses in statistical approaches, including marginalizing other important non-climate drivers of change, ignoring temporal and spatial autocorrelation, averaging across spatial patterns and not reporting key metrics. We provide a list of issues that need to be addressed to make inferences more defensible, including the consideration of (i) data limitations and the comparability of data sets; (ii) alternative mechanisms for change; (iii) appropriate response variables; (iv) a suitable model for the process under study; (v) temporal autocorrelation; (vi) spatial autocorrelation and patterns; and (vii) the reporting of rates of change. While the focus of our review was marine studies, these suggestions are equally applicable to terrestrial studies. Consideration of these suggestions will help advance global knowledge of climate impacts and understanding of the processes driving ecological change.

Past climate variability and change in the Arctic and at high latitudes

USGS Publications Warehouse

Alley, Richard B.; Brigham-Grette, Julie; Miller, Gifford H.; Polyak, Leonid; ,; ,; ,

2009-01-01

Paleoclimate records play a key role in our understanding of Earth's past and present climate system and in our confidence in predicting future climate changes. Paleoclimate data help to elucidate past and present active mechanisms of climate change by placing the short instrumental record into a longer term context and by permitting models to be tested beyond the limited time that instrumental measurements have been available.

School Climate and Planned Educational Change: A Review and Critique of the Literature. Working Paper 279.

ERIC Educational Resources Information Center

Kasten, Katherine Lewellan

This paper examines the concept of school climate as a key factor in the success of planned change in elementary schools. Beginning with a general review of the literature on organizational climate and using as its basis three major reviews that appeared in the mid-1970s, the paper defines climate, examines variables that have been used as part of…

Temperature variability is a key component in accurately forecasting the effects of climate change on pest phenology.

PubMed

Merrill, Scott C; Peairs, Frank B

2017-02-01

Models describing the effects of climate change on arthropod pest ecology are needed to help mitigate and adapt to forthcoming changes. Challenges arise because climate data are at resolutions that do not readily synchronize with arthropod biology. Here we explain how multiple sources of climate and weather data can be synthesized to quantify the effects of climate change on pest phenology. Predictions of phenological events differ substantially between models that incorporate scale-appropriate temperature variability and models that do not. As an illustrative example, we predicted adult emergence of a pest of sunflower, the sunflower stem weevil Cylindrocopturus adspersus (LeConte). Predictions of the timing of phenological events differed by an average of 11 days between models with different temperature variability inputs. Moreover, as temperature variability increases, developmental rates accelerate. Our work details a phenological modeling approach intended to help develop tools to plan for and mitigate the effects of climate change. Results show that selection of scale-appropriate temperature data is of more importance than selecting a climate change emission scenario. Predictions derived without appropriate temperature variability inputs will likely result in substantial phenological event miscalculations. Additionally, results suggest that increased temperature instability will lead to accelerated pest development. © 2016 Society of Chemical Industry. © 2016 Society of Chemical Industry.

Decadal variability of extreme wave height representing storm severity in the northeast Atlantic and North Sea since the foundation of the Royal Society.

PubMed

Santo, H; Taylor, P H; Gibson, R

2016-09-01

Long-term estimation of extreme wave height remains a key challenge because of the short duration of available wave data, and also because of the possible impact of climate variability on ocean waves. Here, we analyse storm-based statistics to obtain estimates of extreme wave height at locations in the northeast Atlantic and North Sea using the NORA10 wave hindcast (1958-2011), and use a 5 year sliding window to examine temporal variability. The decadal variability is correlated to the North Atlantic oscillation and other atmospheric modes, using a six-term predictor model incorporating the climate indices and their Hilbert transforms. This allows reconstruction of the historic extreme climate back to 1661, using a combination of known and proxy climate indices. Significant decadal variability primarily driven by the North Atlantic oscillation is observed, and this should be considered for the long-term survivability of offshore structures and marine renewable energy devices. The analysis on wave climate reconstruction reveals that the variation of the mean, 99th percentile and extreme wave climates over decadal time scales for locations close to the dominant storm tracks in the open North Atlantic are comparable, whereas the wave climates for the rest of the locations including the North Sea are rather different.

Decadal variability of extreme wave height representing storm severity in the northeast Atlantic and North Sea since the foundation of the Royal Society

NASA Astrophysics Data System (ADS)

Santo, H.; Taylor, P. H.; Gibson, R.

2016-09-01

Long-term estimation of extreme wave height remains a key challenge because of the short duration of available wave data, and also because of the possible impact of climate variability on ocean waves. Here, we analyse storm-based statistics to obtain estimates of extreme wave height at locations in the northeast Atlantic and North Sea using the NORA10 wave hindcast (1958-2011), and use a 5 year sliding window to examine temporal variability. The decadal variability is correlated to the North Atlantic oscillation and other atmospheric modes, using a six-term predictor model incorporating the climate indices and their Hilbert transforms. This allows reconstruction of the historic extreme climate back to 1661, using a combination of known and proxy climate indices. Significant decadal variability primarily driven by the North Atlantic oscillation is observed, and this should be considered for the long-term survivability of offshore structures and marine renewable energy devices. The analysis on wave climate reconstruction reveals that the variation of the mean, 99th percentile and extreme wave climates over decadal time scales for locations close to the dominant storm tracks in the open North Atlantic are comparable, whereas the wave climates for the rest of the locations including the North Sea are rather different.

Thermal barriers constrain microbial elevational range size via climate variability.

PubMed

Wang, Jianjun; Soininen, Janne

2017-08-01

Range size is invariably limited and understanding range size variation is an important objective in ecology. However, microbial range size across geographical gradients remains understudied, especially on mountainsides. Here, the patterns of range size of stream microbes (i.e., bacteria and diatoms) and macroorganisms (i.e., macroinvertebrates) along elevational gradients in Asia and Europe were examined. In bacteria, elevational range size showed non-significant phylogenetic signals. In all taxa, there was a positive relationship between niche breadth and species elevational range size, driven by local environmental and climatic variables. No taxa followed the elevational Rapoport's rule. Climate variability explained the most variation in microbial mean elevational range size, whereas local environmental variables were more important for macroinvertebrates. Seasonal and annual climate variation showed negative effects, while daily climate variation had positive effects on community mean elevational range size for all taxa. The negative correlation between range size and species richness suggests that understanding the drivers of range is key for revealing the processes underlying diversity. The results advance the understanding of microbial species thermal barriers by revealing the importance of seasonal and diurnal climate variation, and highlight that aquatic and terrestrial biota may differ in their response to short- and long-term climate variability. © 2017 Society for Applied Microbiology and John Wiley & Sons Ltd.

Use of a scenario-neutral approach to identify the key hydro-meteorological attributes that impact runoff from a natural catchment

NASA Astrophysics Data System (ADS)

Guo, Danlu; Westra, Seth; Maier, Holger R.

2017-11-01

Scenario-neutral approaches are being used increasingly for assessing the potential impact of climate change on water resource systems, as these approaches allow the performance of these systems to be evaluated independently of climate change projections. However, practical implementations of these approaches are still scarce, with a key limitation being the difficulty of generating a range of plausible future time series of hydro-meteorological data. In this study we apply a recently developed inverse stochastic generation approach to support the scenario-neutral analysis, and thus identify the key hydro-meteorological variables to which the system is most sensitive. The stochastic generator simulates synthetic hydro-meteorological time series that represent plausible future changes in (1) the average, extremes and seasonal patterns of rainfall; and (2) the average values of temperature (Ta), relative humidity (RH) and wind speed (uz) as variables that drive PET. These hydro-meteorological time series are then fed through a conceptual rainfall-runoff model to simulate the potential changes in runoff as a function of changes in the hydro-meteorological variables, and runoff sensitivity is assessed with both correlation and Sobol' sensitivity analyses. The method was applied to a case study catchment in South Australia, and the results showed that the most important hydro-meteorological attributes for runoff were winter rainfall followed by the annual average rainfall, while the PET-related meteorological variables had comparatively little impact. The high importance of winter rainfall can be related to the winter-dominated nature of both the rainfall and runoff regimes in this catchment. The approach illustrated in this study can greatly enhance our understanding of the key hydro-meteorological attributes and processes that are likely to drive catchment runoff under a changing climate, thus enabling the design of tailored climate impact assessments to specific water resource systems.

MISST: The Multi-Sensor Improved Sea Surface Temperature Project

DTIC Science & Technology

2009-06-01

climate change studies, fisheries management, and a wide range of other applications. Measurements are taken by several satellites carrying infrared and...TEMPERATURE PROJECT ABSTRACT. Sea surface temperature (SST) measurements are vital to global weather prediction, climate change studies, fisheries management...important variables related to the global ocean-atmosphere system. It is a key indicator of climate change , is widely applied to studies of upper

EO based Agro-ecosystem approach for climate change adaptation in enhancing the crop production efficiency in the Indo-gangetic plains of India

NASA Astrophysics Data System (ADS)

Pandey, Suraj

This study develops a spatial mapping of agro-ecological zones based on earth observation model using MODIS regional dataset as a tool to guide key areas of cropping system and targeting to climate change strategies. This tool applies to the Indo-gangetic Plains of north India to target the domains of bio-physical characteristics and socio-economics with respect to changing climate in the region. It derive on secondary data for spatially-explicit variables at the state/district level, which serve as indicators of climate variability based on sustainable livelihood approach, natural, social and human. The study details the methodology used and generates the spatial climate risk maps for composite indicators of livelihood and vulnerability index in the region.

Optimization of agricultural field workability predictions for improved risk management

USDA-ARS?s Scientific Manuscript database

Risks introduced by weather variability are key considerations in agricultural production. The sensitivity of agriculture to weather variability is of special concern in the face of climate change. In particular, the availability of workable days is an important consideration in agricultural practic...

Identification of weather variables sensitive to dysentery in disease-affected county of China.

PubMed

Liu, Jianing; Wu, Xiaoxu; Li, Chenlu; Xu, Bing; Hu, Luojia; Chen, Jin; Dai, Shuang

2017-01-01

Climate change mainly refers to long-term change in weather variables, and it has significant impact on sustainability and spread of infectious diseases. Among three leading infectious diseases in China, dysentery is exclusively sensitive to climate change. Previous researches on weather variables and dysentery mainly focus on determining correlation between dysentery incidence and weather variables. However, the contribution of each variable to dysentery incidence has been rarely clarified. Therefore, we chose a typical county in epidemic of dysentery as the study area. Based on data of dysentery incidence, weather variables (monthly mean temperature, precipitation, wind speed, relative humidity, absolute humidity, maximum temperature, and minimum temperature) and lagged analysis, we used principal component analysis (PCA) and classification and regression trees (CART) to examine the relationships between the incidence of dysentery and weather variables. Principal component analysis showed that temperature, precipitation, and humidity played a key role in determining transmission of dysentery. We further selected weather variables including minimum temperature, precipitation, and relative humidity based on results of PCA, and used CART to clarify contributions of these three weather variables to dysentery incidence. We found when minimum temperature was at a high level, the high incidence of dysentery occurred if relative humidity or precipitation was at a high level. We compared our results with other studies on dysentery incidence and meteorological factors in areas both in China and abroad, and good agreement has been achieved. Yet, some differences remain for three reasons: not identifying all key weather variables, climate condition difference caused by local factors, and human factors that also affect dysentery incidence. This study hopes to shed light on potential early warnings for dysentery transmission as climate change occurs, and provide a theoretical basis for the control and prevention of dysentery. Copyright © 2016 Elsevier B.V. All rights reserved.

Water governance: learning by developing adaptive capacity to incorporate climate variability and change.

PubMed

Kashyap, A

2004-01-01

There is increasing evidence that global climate variability and change is affecting the quality and availability of water supplies. Integrated water resources development, use, and management strategies, represent an effective approach to achieve sustainable development of water resources in a changing environment with competing demands. It is also a key to achieving the Millennium Development Goals. It is critical that integrated water management strategies must incorporate the impacts of climate variability and change to reduce vulnerability of the poor, strengthen sustainable livelihoods and support national sustainable development. UNDP's strategy focuses on developing adaptation in the water governance sector as an entry point within the framework of poverty reduction and national sustainable development. This strategy aims to strengthen the capacity of governments and civil society organizations to have access to early warning systems, ability to assess the impact of climate variability and change on integrated water resources management, and developing adaptation intervention through hands-on learning by undertaking pilot activities.

Decadal variability of extreme wave height representing storm severity in the northeast Atlantic and North Sea since the foundation of the Royal Society

PubMed Central

Taylor, P. H.; Gibson, R.

2016-01-01

Long-term estimation of extreme wave height remains a key challenge because of the short duration of available wave data, and also because of the possible impact of climate variability on ocean waves. Here, we analyse storm-based statistics to obtain estimates of extreme wave height at locations in the northeast Atlantic and North Sea using the NORA10 wave hindcast (1958–2011), and use a 5 year sliding window to examine temporal variability. The decadal variability is correlated to the North Atlantic oscillation and other atmospheric modes, using a six-term predictor model incorporating the climate indices and their Hilbert transforms. This allows reconstruction of the historic extreme climate back to 1661, using a combination of known and proxy climate indices. Significant decadal variability primarily driven by the North Atlantic oscillation is observed, and this should be considered for the long-term survivability of offshore structures and marine renewable energy devices. The analysis on wave climate reconstruction reveals that the variation of the mean, 99th percentile and extreme wave climates over decadal time scales for locations close to the dominant storm tracks in the open North Atlantic are comparable, whereas the wave climates for the rest of the locations including the North Sea are rather different. PMID:27713662

The role of the oceans in changes of the Earth's climate system

NASA Astrophysics Data System (ADS)

von Schuckmann, K.

2016-12-01

Any changes to the Earth's climate system affect an imbalance of the Earth's energy budget due to natural or human made climate forcing. The current positive Earth's energy imbalance is mostly caused by human activity, and is driving global warming. Variations in the world's ocean heat storage and its associated volume changes are a key factor to gauge global warming, to assess changes in the Earth's energy budget and to estimate contributions to the global sea level budget. Present-day sea-level rise is one of the major symptoms of the current positive Earth Energy Imbalance. Sea level also responds to natural climate variability that is superimposing and altering the global warming signal. The most prominent signature in the global mean sea level interannual variability is caused by El Niño-Southern Oscillation. It has been also shown that sea level variability in other regions of the Indo-Pacific area significantly alters estimates of the rate of sea level rise, i.e. in the Indonesian archipelago. In summary, improving the accuracy of our estimates of global Earth's climate state and variability is critical for advancing the understanding and prediction of the evolution of our climate, and an overview on recent findings on the role of the global ocean in changes of the Earth's climate system with particular focus on sea level variability in the Indo-Pacific region will be given in this contribution.

Scientific Uncertainties in Climate Change Detection and Attribution Studies

NASA Astrophysics Data System (ADS)

Santer, B. D.

2017-12-01

It has been claimed that the treatment and discussion of key uncertainties in climate science is "confined to hushed sidebar conversations at scientific conferences". This claim is demonstrably incorrect. Climate change detection and attribution studies routinely consider key uncertainties in observational climate data, as well as uncertainties in model-based estimates of natural variability and the "fingerprints" in response to different external forcings. The goal is to determine whether such uncertainties preclude robust identification of a human-caused climate change fingerprint. It is also routine to investigate the impact of applying different fingerprint identification strategies, and to assess how detection and attribution results are impacted by differences in the ability of current models to capture important aspects of present-day climate. The exploration of the uncertainties mentioned above will be illustrated using examples from detection and attribution studies with atmospheric temperature and moisture.

Disentangling Global Warming, Multidecadal Variability, and El Niño in Pacific Temperatures

NASA Astrophysics Data System (ADS)

Wills, Robert C.; Schneider, Tapio; Wallace, John M.; Battisti, David S.; Hartmann, Dennis L.

2018-03-01

A key challenge in climate science is to separate observed temperature changes into components due to internal variability and responses to external forcing. Extended integrations of forced and unforced climate models are often used for this purpose. Here we demonstrate a novel method to separate modes of internal variability from global warming based on differences in time scale and spatial pattern, without relying on climate models. We identify uncorrelated components of Pacific sea surface temperature variability due to global warming, the Pacific Decadal Oscillation (PDO), and the El Niño-Southern Oscillation (ENSO). Our results give statistical representations of PDO and ENSO that are consistent with their being separate processes, operating on different time scales, but are otherwise consistent with canonical definitions. We isolate the multidecadal variability of the PDO and find that it is confined to midlatitudes; tropical sea surface temperatures and their teleconnections mix in higher-frequency variability. This implies that midlatitude PDO anomalies are more persistent than previously thought.

Assessing adaptation to the health risks of climate change: what guidance can existing frameworks provide?

PubMed

Füssel, Hans-Martin

2008-02-01

Climate change adaptation assessments aim at assisting policy-makers in reducing the health risks associated with climate change and variability. This paper identifies key characteristics of the climate-health relationship and of the adaptation decision problem that require consideration in climate change adaptation assessments. It then analyzes whether these characteristics are appropriately considered in existing guidelines for climate impact and adaptation assessment and in pertinent conceptual models from environmental epidemiology. The review finds three assessment guidelines based on a generalized risk management framework to be most useful for guiding adaptation assessments of human health. Since none of them adequately addresses all key challenges of the adaptation decision problem, actual adaptation assessments need to combine elements from different guidelines. Established conceptual models from environmental epidemiology are found to be of limited relevance for assessing and planning adaptation to climate change since the prevailing toxicological model of environmental health is not applicable to many climate-sensitive health risks.

Collaborative Proposal: Improving Decadal Prediction of Arctic Climate Variability and Change Using a Regional Arctic System Model (RASM)

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

Maslowski, Wieslaw

This project aims to develop, apply and evaluate a regional Arctic System model (RASM) for enhanced decadal predictions. Its overarching goal is to advance understanding of the past and present states of arctic climate and to facilitate improvements in seasonal to decadal predictions. In particular, it will focus on variability and long-term change of energy and freshwater flows through the arctic climate system. The project will also address modes of natural climate variability as well as extreme and rapid climate change in a region of the Earth that is: (i) a key indicator of the state of global climate throughmore » polar amplification and (ii) which is undergoing environmental transitions not seen in instrumental records. RASM will readily allow the addition of other earth system components, such as ecosystem or biochemistry models, thus allowing it to facilitate studies of climate impacts (e.g., droughts and fires) and of ecosystem adaptations to these impacts. As such, RASM is expected to become a foundation for more complete Arctic System models and part of a model hierarchy important for improving climate modeling and predictions.« less

Climate variability, social and environmental factors, and ross river virus transmission: research development and future research needs.

PubMed

Tong, Shilu; Dale, Pat; Nicholls, Neville; Mackenzie, John S; Wolff, Rodney; McMichael, Anthony J

2008-12-01

Arbovirus diseases have emerged as a global public health concern. However, the impact of climatic, social, and environmental variability on the transmission of arbovirus diseases remains to be determined. Our goal for this study was to provide an overview of research development and future research directions about the interrelationship between climate variability, social and environmental factors, and the transmission of Ross River virus (RRV), the most common and widespread arbovirus disease in Australia. We conducted a systematic literature search on climatic, social, and environmental factors and RRV disease. Potentially relevant studies were identified from a series of electronic searches. The body of evidence revealed that the transmission cycles of RRV disease appear to be sensitive to climate and tidal variability. Rainfall, temperature, and high tides were among major determinants of the transmission of RRV disease at the macro level. However, the nature and magnitude of the interrelationship between climate variability, mosquito density, and the transmission of RRV disease varied with geographic area and socioenvironmental condition. Projected anthropogenic global climatic change may result in an increase in RRV infections, and the key determinants of RRV transmission we have identified here may be useful in the development of an early warning system. The analysis indicates that there is a complex relationship between climate variability, social and environmental factors, and RRV transmission. Different strategies may be needed for the control and prevention of RRV disease at different levels. These research findings could be used as an additional tool to support decision making in disease control/surveillance and risk management.

Relevance of Regional Hydro-Climatic Projection Data for Hydrodynamics and Water Quality Modelling of the Baltic Sea

NASA Astrophysics Data System (ADS)

Goldenberg, R.; Vigouroux, G.; Chen, Y.; Bring, A.; Kalantari, Z.; Prieto, C.; Destouni, G.

2017-12-01

The Baltic Sea, located in Northern Europe, is one of the world's largest body of brackish water, enclosed and surrounded by nine different countries. The magnitude of climate change may be particularly large in northern regions, and identifying its impacts on vulnerable inland waters and their runoff and nutrient loading to the Baltic Sea is an important and complex task. Exploration of such hydro-climatic impacts is needed to understand potential future changes in physical, ecological and water quality conditions in the regional coastal and marine waters. In this study, we investigate hydro-climatic changes and impacts on the Baltic Sea by synthesizing multi-model climate projection data from the CORDEX regional downscaling initiative (EURO- and Arctic- CORDEX domains, http://www.cordex.org/). We identify key hydro-climatic variable outputs of these models and assess model performance with regard to their projected temporal and spatial change behavior and impacts on different scales and coastal-marine parts, up to the whole Baltic Sea. Model spreading, robustness and impact implications for the Baltic Sea system are investigated for and through further use in simulations of coastal-marine hydrodynamics and water quality based on these key output variables and their change projections. Climate model robustness in this context is assessed by inter-model spreading analysis and observation data comparisons, while projected change implications are assessed by forcing of linked hydrodynamic and water quality modeling of the Baltic Sea based on relevant hydro-climatic outputs for inland water runoff and waterborne nutrient loading to the Baltic sea, as well as for conditions in the sea itself. This focused synthesis and analysis of hydro-climatically relevant output data of regional climate models facilitates assessment of reliability and uncertainty in projections of driver-impact changes of key importance for Baltic Sea physical, water quality and ecological conditions and their future evolution.

Global variation in thermal tolerances and vulnerability of endotherms to climate change

PubMed Central

Khaliq, Imran; Hof, Christian; Prinzinger, Roland; Böhning-Gaese, Katrin; Pfenninger, Markus

2014-01-01

The relationships among species' physiological capacities and the geographical variation of ambient climate are of key importance to understanding the distribution of life on the Earth. Furthermore, predictions of how species will respond to climate change will profit from the explicit consideration of their physiological tolerances. The climatic variability hypothesis, which predicts that climatic tolerances are broader in more variable climates, provides an analytical framework for studying these relationships between physiology and biogeography. However, direct empirical support for the hypothesis is mostly lacking for endotherms, and few studies have tried to integrate physiological data into assessments of species' climatic vulnerability at the global scale. Here, we test the climatic variability hypothesis for endotherms, with a comprehensive dataset on thermal tolerances derived from physiological experiments, and use these data to assess the vulnerability of species to projected climate change. We find the expected relationship between thermal tolerance and ambient climatic variability in birds, but not in mammals—a contrast possibly resulting from different adaptation strategies to ambient climate via behaviour, morphology or physiology. We show that currently most of the species are experiencing ambient temperatures well within their tolerance limits and that in the future many species may be able to tolerate projected temperature increases across significant proportions of their distributions. However, our findings also underline the high vulnerability of tropical regions to changes in temperature and other threats of anthropogenic global changes. Our study demonstrates that a better understanding of the interplay among species' physiology and the geography of climate change will advance assessments of species' vulnerability to climate change. PMID:25009066

Multiple stressors, nonlinear effects and the implications of climate change impacts on marine coastal ecosystems.

PubMed

Hewitt, Judi E; Ellis, Joanne I; Thrush, Simon F

2016-08-01

Global climate change will undoubtedly be a pressure on coastal marine ecosystems, affecting not only species distributions and physiology but also ecosystem functioning. In the coastal zone, the environmental variables that may drive ecological responses to climate change include temperature, wave energy, upwelling events and freshwater inputs, and all act and interact at a variety of spatial and temporal scales. To date, we have a poor understanding of how climate-related environmental changes may affect coastal marine ecosystems or which environmental variables are likely to produce priority effects. Here we use time series data (17 years) of coastal benthic macrofauna to investigate responses to a range of climate-influenced variables including sea-surface temperature, southern oscillation indices (SOI, Z4), wind-wave exposure, freshwater inputs and rainfall. We investigate responses from the abundances of individual species to abundances of functional traits and test whether species that are near the edge of their tolerance to another stressor (in this case sedimentation) may exhibit stronger responses. The responses we observed were all nonlinear and some exhibited thresholds. While temperature was most frequently an important predictor, wave exposure and ENSO-related variables were also frequently important and most ecological variables responded to interactions between environmental variables. There were also indications that species sensitive to another stressor responded more strongly to weaker climate-related environmental change at the stressed site than the unstressed site. The observed interactions between climate variables, effects on key species or functional traits, and synergistic effects of additional anthropogenic stressors have important implications for understanding and predicting the ecological consequences of climate change to coastal ecosystems. © 2015 John Wiley & Sons Ltd.

A design for a sustained assessment of climate forcings and feedbacks on land use land cover change

USGS Publications Warehouse

Loveland, Thomas; Mahmood, Rezaul

2014-01-01

Land use and land cover change (LULCC) significantly influences the climate system. Hence, to prepare the nation for future climate change and variability, a sustained assessment of LULCC and its climatic impacts needs to be undertaken. To address this objective, not only do we need to determine contemporary trends in land use and land cover that affect, or are affected by, weather and climate but also identify sectors and regions that are most affected by weather and climate variability. Moreover, it is critical that we recognize land cover and regions that are most vulnerable to climate change and how end-use practices are adapting to climate change. This paper identifies a series of steps that need to be undertaken to address these key items. In addition, national-scale institutional capabilities are identified and discussed. Included in the discussions are challenges and opportunities for collaboration among these institutions for a sustained assessment.

The Pacific Northwest's Climate Impacts Group: Climate Science in the Public Interest

NASA Astrophysics Data System (ADS)

Mantua, N.; Snover, A.

2006-12-01

Since its inception in 1995, the University of Washington's Climate Impacts Group (CIG) (funded under NOAA's Regional Integrated Science and Assessments (RISA) Program) has become the leader in exploring the impacts of climate variability and climate change on natural and human systems in the U.S. Pacific Northwest (PNW), specifically climate impacts on water, forest, fish and coastal resource systems. The CIG's research provides PNW planners, decision makers, resource managers, local media, and the general public with valuable knowledge of ways in which the region's key natural resources are vulnerable to changes in climate, and how this vulnerability can be reduced. The CIG engages in climate science in the public interest, conducting original research on the causes and consequences of climate variability and change for the PNW and developing forecasts and decision support tools to support the use of this information in federal, state, local, tribal, and private sector resource management decisions. The CIG's focus on the intersection of climate science and public policy has placed the CIG nationally at the forefront of regional climate impacts assessment and integrated analysis.

Implications of multi-scale sea level and climate variability for coastal resources

USGS Publications Warehouse

Karamperidou, Christina; Engel, Victor; Lall, Upmanu; Stabenau, Erik; Smith, Thomas J.

2013-01-01

While secular changes in regional sea levels and their implications for coastal zone management have been studied extensively, less attention is being paid to natural fluctuations in sea levels, whose interaction with a higher mean level could have significant impacts on low-lying areas, such as wetlands. Here, the long record of sea level at Key West, FL is studied in terms of both the secular trend and the multi-scale sea level variations. This analysis is then used to explore implications for the Everglades National Park (ENP), which is recognized internationally for its ecological significance, and is the site of the largest wetland restoration project in the world. Very shallow topographic gradients (3–6 cm per km) make the region susceptible to small changes in sea level. Observations of surface water levels from a monitoring network within ENP exhibit both the long-term trends and the interannual-to-(multi)decadal variability that are observed in the Key West record. Water levels recorded at four long-term monitoring stations within ENP exhibit increasing trends approximately equal to or larger than the long-term trend at Key West. Time- and frequency-domain analyses highlight the potential influence of climate mechanisms, such as the El Niño/Southern Oscillation and the North Atlantic Oscillation (NAO), on Key West sea levels and marsh water levels, and the potential modulation of their influence by the background state of the North Atlantic Sea Surface Temperatures. In particular, the Key West sea levels are found to be positively correlated with the NAO index, while the two series exhibit high spectral power during the transition to a cold Atlantic Multidecadal Oscillation (AMO). The correlation between the Key West sea levels and the NINO3 Index reverses its sign in coincidence with a reversal of the AMO phase. Water levels in ENP are also influenced by precipitation and freshwater releases from the northern boundary of the Park. The analysis of both climate variability and climate change in such wetlands is needed to inform management practices in coastal wetland zones around the world.

Quantitative Assessment of Antarctic Climate Variability and Change

NASA Astrophysics Data System (ADS)

Ordonez, A.; Schneider, D. P.

2013-12-01

The Antarctic climate is both extreme and highly variable, but there are indications it may be changing. As the climate in Antarctica can affect global sea level and ocean circulation, it is important to understand and monitor its behavior. Observational and model data have been used to study climate change in Antarctica and the Southern Ocean, though observational data is sparse and models have difficulty reproducing many observed climate features. For example, a leading hypothesis that ozone depletion has been responsible for sea ice trends is struggling with the inability of ozone-forced models to reproduce the observed sea ice increase. The extent to which this data-model disagreement represents inadequate observations versus model biases is unknown. This research assessed a variety of climate change indicators to present an overview of Antarctic climate that will allow scientists to easily access this data and compare indicators with other observational data and model output. Indicators were obtained from observational and reanalysis data for variables such as temperature, sea ice area, and zonal wind stress. Multiple datasets were used for key variables. Monthly and annual anomaly data from Antarctica and the Southern Ocean as well as tropical indices were plotted as time series on common axes for comparison. Trends and correlations were also computed. Zonal wind, surface temperature, and austral springtime sea ice had strong relationships and were further discussed in terms of how they may relate to climate variability and change in the Antarctic. This analysis will enable hypothesized mechanisms of Antarctic climate change to be critically evaluated.

Climate and Southern Africa's Water-Energy-Food Nexus

NASA Astrophysics Data System (ADS)

Conway, D.; Osborn, T.; Dorling, S.; Ringler, C.; Lankford, B.; Dalin, C.; Thurlow, J.; Zhu, T.; Deryng, D.; Landman, W.; Archer van Garderen, E.; Krueger, T.; Lebek, K.

2014-12-01

Numerous challenges coalesce to make Southern Africa emblematic of the connections between climate and the water-energy-food nexus. Rainfall and river flows in the region show high levels of variability across a range of spatial and temporal scales. Physical and socioeconomic exposure to climate variability and change is high, for example, the contribution of electricity produced from hydroelectric sources is over 30% in Madagascar and Zimbabwe and almost 100% in the DRC, Lesotho, Malawi, and Zambia. The region's economy is closely linked with that of the rest of the African continent and climate-sensitive food products are an important item of trade. Southern Africa's population is concentrated in regions exposed to high levels of hydro-meteorological variability, and will increase rapidly over the next four decades. The capacity to manage the effects of climate variability tends, however, to be low. Moreover, with climate change annual precipitation levels, soil moisture and runoff are likely to decrease and rising temperatures will increase evaporative demand. Despite high levels of hydro-meteorological variability, the sectoral and cross-sectoral water-energy-food linkages with climate in Southern Africa have not been considered in detail. Lack of data and questionable reliability are compounded by complex dynamic relationships. We review the role of climate in Southern Africa's nexus, complemented by empirical analysis of national level data on climate, water resources, crop and energy production, and economic activity. Our aim is to examine the role of climate variability as a driver of production fluctuations in the nexus, and to improve understanding of the magnitude and temporal dimensions of their interactions. We first consider national level exposure of food, water and energy production to climate in aggregate economic terms and then examine the linkages between interannual and multi-year climate variability and economic activity, focusing on food and hydropower production. We then review the potential for connecting areas with robust seasonal climate forecasting skill with key precursors of economic output and conclude by identifying knowledge gaps in our understanding of regional and national economic linkages in the climate and water-energy-food nexus.

Evaluation of probable maximum snow accumulation: Development of a methodology for climate change studies

NASA Astrophysics Data System (ADS)

Klein, Iris M.; Rousseau, Alain N.; Frigon, Anne; Freudiger, Daphné; Gagnon, Patrick

2016-06-01

Probable maximum snow accumulation (PMSA) is one of the key variables used to estimate the spring probable maximum flood (PMF). A robust methodology for evaluating the PMSA is imperative so the ensuing spring PMF is a reasonable estimation. This is of particular importance in times of climate change (CC) since it is known that solid precipitation in Nordic landscapes will in all likelihood change over the next century. In this paper, a PMSA methodology based on simulated data from regional climate models is developed. Moisture maximization represents the core concept of the proposed methodology; precipitable water being the key variable. Results of stationarity tests indicate that CC will affect the monthly maximum precipitable water and, thus, the ensuing ratio to maximize important snowfall events. Therefore, a non-stationary approach is used to describe the monthly maximum precipitable water. Outputs from three simulations produced by the Canadian Regional Climate Model were used to give first estimates of potential PMSA changes for southern Quebec, Canada. A sensitivity analysis of the computed PMSA was performed with respect to the number of time-steps used (so-called snowstorm duration) and the threshold for a snowstorm to be maximized or not. The developed methodology is robust and a powerful tool to estimate the relative change of the PMSA. Absolute results are in the same order of magnitude as those obtained with the traditional method and observed data; but are also found to depend strongly on the climate projection used and show spatial variability.

Coral Records of 20th Century Central Tropical Pacific SST and Salinity: Signatures of Natural and Anthropogenic Climate Change

NASA Astrophysics Data System (ADS)

Nurhati, I. S.; Cobb, K.; Di Lorenzo, E.

2011-12-01

Accurate forecasts of regional climate changes in many regions of the world largely depend on quantifying anthropogenic trends in tropical Pacific climate against its rich background of interannual to decadal-scale climate variability. However, the strong natural climate variability combined with limited instrumental climate datasets have obscured potential anthropogenic climate signals in the region. Here, we present coral-based sea-surface temperature (SST) and salinity proxy records over the 20th century (1898-1998) from the central tropical Pacific - a region sensitive to El Niño-Southern Oscillation (ENSO) whose variability strongly impacts the global climate. The SST and salinity proxy records are reconstructed via coral Sr/Ca and the oxygen isotopic composition of seawater (δ18Osw), respectively. On interannual (2-7yr) timescales, the SST proxy record tracks both eastern- and central-Pacific flavors of ENSO variability (R=0.65 and R=0.67, respectively). Interannual-scale salinity variability in our coral record highlights profound differences in precipitation and ocean advections during the two flavors of ENSO. On decadal (8yr-lowpassed) timescales, the central tropical Pacific SST and salinity proxy records are controlled by different sets of dynamics linked to the leading climate modes of North Pacific climate variability. Decadal-scale central tropical Pacific SST is highly correlated to the recently discovered North Pacific Gyre Oscillation (NPGO; R=-0.85), reflecting strong dynamical links between the central Pacific warming mode and extratropical decadal climate variability. Whereas decadal-scale salinity variations in the central tropical Pacific are significantly correlated with the Pacific Decadal Oscillation (PDO; R=0.54), providing a better understanding on low-frequency salinity variability in the region. Having characterized natural climate variability in this region, the coral record shows a +0.5°C warming trend throughout the last century. However, the most prominent feature of the new coral records is an unprecedented freshening trend since the mid-20th century, in line with global climate models (GCMs) projections of enhanced hydrological patterns (wet areas are getting wetter and vice versa) under greenhouse forcing. Taken together, the coral records provide key constraints on tropical Pacific climate trends that may improve regional climate projections in areas affected by tropical Pacific climate variability.
Central Tropical Pacific SST and Salinity Proxy Records

Implementation of a Time Series Analysis for the Assessment of the Role of Climate Variability in a Post-Disturbance Savanna System

NASA Astrophysics Data System (ADS)

Gibbes, C.; Southworth, J.; Waylen, P. R.

2013-05-01

How do climate variability and climate change influence vegetation cover and vegetation change in savannas? A landscape scale investigation of the effect of changes in precipitation on vegetation is undertaken through the employment of a time series analysis. The multi-national study region is located within the Kavango-Zambezi region, and is delineated by the Okavango, Kwando, and Zambezi watersheds. A mean-variance time-series analysis quantifies vegetation dynamics and characterizes vegetation response to climate. The spatially explicit approach used to quantify the persistence of vegetation productivity permits the extraction of information regarding long term climate-landscape dynamics. Results show a pattern of reduced mean annual precipitation and increased precipitation variability across key social and ecological areas within the study region. Despite decreased mean annual precipitation since the mid to late 1970's vegetation trends predominantly indicate increasing biomass. The limited areas which have diminished vegetative cover relate to specific vegetation types, and are associated with declines in precipitation variability. Results indicate that in addition to short term changes in vegetation cover, long term trends in productive biomass are apparent, relate to spatial differences in precipitation variability, and potentially represent shifts vegetation composition. This work highlights the importance of time-series analyses for examining climate-vegetation linkages in a spatially explicit manner within a highly vulnerable region of the world.

Evaluating climatic and non-climatic stresses for declining surface water quality in Bagmati River of Nepal.

PubMed

Panthi, Jeeban; Li, Fengting; Wang, Hongtao; Aryal, Suman; Dahal, Piyush; Ghimire, Sheila; Kabenge, Martin

2017-06-01

Both climatic and non-climatic factors affect surface water quality. Similar to its effect across various sectors and areas, climate change has potential to affect surface water quality directly and indirectly. On the one hand, the rise in temperature enhances the microbial activity and decomposition of organic matter in the river system and changes in rainfall alter discharge and water flow in the river ultimately affecting pollution dilution level. On the other hand, the disposal of organic waste and channelizing municipal sewage into the rivers seriously worsen water quality. This study attempts to relate hydro-climatology, water quality, and impact of climatic and non-climatic stresses in affecting river water quality in the upper Bagmati basin in Central Nepal. The results showed that the key water quality indicators such as dissolved oxygen and chemical oxygen demand are getting worse in recent years. No significant relationships were found between the key water quality indicators and changes in key climatic variables. However, the water quality indicators correlated with the increase in urban population and per capita waste production in the city. The findings of this study indicate that dealing with non-climatic stressors such as reducing direct disposal of sewerage and other wastes in the river rather than emphasizing on working with the effects from climate change would largely help to improve water quality in the river flowing from highly populated urban areas.

Fishing, fast growth and climate variability increase the risk of collapse

PubMed Central

Pinsky, Malin L.; Byler, David

2015-01-01

Species around the world have suffered collapses, and a key question is why some populations are more vulnerable than others. Traditional conservation biology and evidence from terrestrial species suggest that slow-growing populations are most at risk, but interactions between climate variability and harvest dynamics may alter or even reverse this pattern. Here, we test this hypothesis globally. We use boosted regression trees to analyse the influences of harvesting, species traits and climate variability on the risk of collapse (decline below a fixed threshold) across 154 marine fish populations around the world. The most important factor explaining collapses was the magnitude of overfishing, while the duration of overfishing best explained long-term depletion. However, fast growth was the next most important risk factor. Fast-growing populations and those in variable environments were especially sensitive to overfishing, and the risk of collapse was more than tripled for fast-growing when compared with slow-growing species that experienced overfishing. We found little evidence that, in the absence of overfishing, climate variability or fast growth rates alone drove population collapse over the last six decades. Expanding efforts to rapidly adjust harvest pressure to account for climate-driven lows in productivity could help to avoid future collapses, particularly among fast-growing species. PMID:26246548

Fishing, fast growth and climate variability increase the risk of collapse.

PubMed

Pinsky, Malin L; Byler, David

2015-08-22

Species around the world have suffered collapses, and a key question is why some populations are more vulnerable than others. Traditional conservation biology and evidence from terrestrial species suggest that slow-growing populations are most at risk, but interactions between climate variability and harvest dynamics may alter or even reverse this pattern. Here, we test this hypothesis globally. We use boosted regression trees to analyse the influences of harvesting, species traits and climate variability on the risk of collapse (decline below a fixed threshold) across 154 marine fish populations around the world. The most important factor explaining collapses was the magnitude of overfishing, while the duration of overfishing best explained long-term depletion. However, fast growth was the next most important risk factor. Fast-growing populations and those in variable environments were especially sensitive to overfishing, and the risk of collapse was more than tripled for fast-growing when compared with slow-growing species that experienced overfishing. We found little evidence that, in the absence of overfishing, climate variability or fast growth rates alone drove population collapse over the last six decades. Expanding efforts to rapidly adjust harvest pressure to account for climate-driven lows in productivity could help to avoid future collapses, particularly among fast-growing species. © 2015 The Author(s).

ENSO activity during the last climate cycle using IFA

NASA Astrophysics Data System (ADS)

Leduc, Guillaume; Vidal, Laurence; Thirumalai, Kaustubh

2017-04-01

The El Niño / Southern Oscillation (ENSO) is the principal mode of interannual climate variability and affects key climate parameters such as low-latitude rainfall variability. Anticipating future ENSO variability under anthropogenic forcing is vital due to its profound socioeconomic impact. Fossil corals suggest that 20th century ENSO variance is particularly high as compared to other time periods of the Holocene (Cobb et al., 2013, Science), the Last Glacial Maximum (Ford et al., 2015, Science) and the last glacial period (Tudhope et al., 2001, Science). Yet, recent climate modeling experiments suggest an increase in the frequency of both El Niño (Cai et al., 2014, Nature Climate Change) and La Niña (Cai et al., 2015, Nature Climate Change) events. We have expanded an Individual Foraminifera Analysis (IFA) dataset using the thermocline-dwelling N. dutertrei on a marine core collected in the Panama Basin (Leduc et al., 2009, Paleoceanography), that has proven to be a skillful way to reconstruct the ENSO (Thirumalai et al., 2013, Paleoceanography). Our new IFA dataset comprehensively covers the Holocene, the last deglaciation and Termination II (MIS5/6) time windows. We will also use previously published data from the Marine Isotope Stage 3 (MIS3). Our dataset confirms variable ENSO intensity during the Holocene and weaker activity during LGM than during the Holocene. As a next step, ENSO activity will be discussed with respect to the contrasting climatic background of the analysed time windows (millenial-scale variability, Terminations).

Food Security Under Shifting Economic, Demographic, and Climatic Conditions (Invited)

NASA Astrophysics Data System (ADS)

Naylor, R. L.

2013-12-01

Global demand for food, feed, and fuel will continue to rise in a more populous and affluent world. Meeting this demand in the future will become increasingly challenging with global climate change; when production shocks stemming from climate variability are added to the new mean climate state, food markets could become more volatile. This talk will focus on the interacting market effects of demand and supply for major food commodities, with an eye on climate-related supply trends and shocks. Lessons from historical patterns of climate variability (e.g., ENSO and its global teleconnections) will be used to infer potential food security outcomes in the event of abrupt changes in the mean climate state. Domestic food and trade policy responses to crop output and price volatility in key producing and consuming nations, such as export bans and import tariffs, will be discussed as a potentially major destabilizing force, underscoring the important influence of uncertainty in achieving--or failing to achieve--food security.

Rates of projected climate change dramatically exceed past rates of climatic niche evolution among vertebrate species.

PubMed

Quintero, Ignacio; Wiens, John J

2013-08-01

A key question in predicting responses to anthropogenic climate change is: how quickly can species adapt to different climatic conditions? Here, we take a phylogenetic approach to this question. We use 17 time-calibrated phylogenies representing the major tetrapod clades (amphibians, birds, crocodilians, mammals, squamates, turtles) and climatic data from distributions of > 500 extant species. We estimate rates of change based on differences in climatic variables between sister species and estimated times of their splitting. We compare these rates to predicted rates of climate change from 2000 to 2100. Our results are striking: matching projected changes for 2100 would require rates of niche evolution that are > 10,000 times faster than rates typically observed among species, for most variables and clades. Despite many caveats, our results suggest that adaptation to projected changes in the next 100 years would require rates that are largely unprecedented based on observed rates among vertebrate species. © 2013 John Wiley & Sons Ltd/CNRS.

Climate Variability, Social and Environmental Factors, and Ross River Virus Transmission: Research Development and Future Research Needs

PubMed Central

Tong, Shilu; Dale, Pat; Nicholls, Neville; Mackenzie, John S.; Wolff, Rodney; McMichael, Anthony J.

2008-01-01

Background Arbovirus diseases have emerged as a global public health concern. However, the impact of climatic, social, and environmental variability on the transmission of arbovirus diseases remains to be determined. Objective Our goal for this study was to provide an overview of research development and future research directions about the interrelationship between climate variability, social and environmental factors, and the transmission of Ross River virus (RRV), the most common and widespread arbovirus disease in Australia. Methods We conducted a systematic literature search on climatic, social, and environmental factors and RRV disease. Potentially relevant studies were identified from a series of electronic searches. Results The body of evidence revealed that the transmission cycles of RRV disease appear to be sensitive to climate and tidal variability. Rainfall, temperature, and high tides were among major determinants of the transmission of RRV disease at the macro level. However, the nature and magnitude of the interrelationship between climate variability, mosquito density, and the transmission of RRV disease varied with geographic area and socioenvironmental condition. Projected anthropogenic global climatic change may result in an increase in RRV infections, and the key determinants of RRV transmission we have identified here may be useful in the development of an early warning system. Conclusions The analysis indicates that there is a complex relationship between climate variability, social and environmental factors, and RRV transmission. Different strategies may be needed for the control and prevention of RRV disease at different levels. These research findings could be used as an additional tool to support decision making in disease control/surveillance and risk management. PMID:19079707

Improving preparedness of farmers to Climate Variability: A case study of Vidarbha region of Maharashtra, India

NASA Astrophysics Data System (ADS)

Swami, D.; Parthasarathy, D.; Dave, P.

2016-12-01

A key objective of the ongoing research is to understand the risk and vulnerability of agriculture and farming communities with respect to multiple climate change attributes, particularly monsoon variability and hydrology such as ground water availability. Climate Variability has always been a feature affecting Indian agriculture but the nature and characteristics of this variability is not well understood. Indian monsoon patterns are highly variable and most of the studies focus on larger domain such as Central India or Western coast (Ghosh et al., 2009) but district level analysis is missing i.e. the linkage between agriculture and climate variables at finer scale has not been investigated comprehensively. For example, Eastern Vidarbha region in Maharashtra is considered as one of the most agriculturally sensitive region in India, where every year a large number of farmers commit suicide. The main reasons for large number of suicides are climate related stressors such as droughts, hail storms, and monsoon variability aggravated with poor socio-economic conditions. Present study has tried to explore the areas in Vidarbha region of Maharashtra where famers and crop productivity, specifically cotton, sorghum, is highly vulnerable to monsoon variability, hydrological and socio-economic variables which are further modelled to determine the maximal contributing factor towards crops and farmers' vulnerability. After analysis using primary and secondary data, it will aid in decision making regarding field operations such as time of sowing, harvesting and irrigation requirements by optimizing the cropping pattern with climatic, hydrological and socio-economic variables. It also suggests the adaptation strategies to farmers regarding different types of cropping and water harvesting practices, optimized dates and timings for harvesting, sowing, water and nutrient requirements of particular crops according to the specific region. Primarily along with secondary analysis captured here can be highly beneficial for the farmers and policy makers while formulating agricultural policies related to climate change.

Sensitivity of the reference evapotranspiration to key climatic variables during the growing season in the Ejina oasis northwest China.

PubMed

Hou, Lan-Gong; Zou, Song-Bing; Xiao, Hong-Lang; Yang, Yong-Gang

2013-01-01

The standardized FAO56 Penman-Monteith model, which has been the most reasonable method in both humid and arid climatic conditions, provides reference evapotranspiration (ETo) estimates for planning and efficient use of agricultural water resources. And sensitivity analysis is important in understanding the relative importance of climatic variables to the variation of reference evapotranspiration. In this study, a non-dimensional relative sensitivity coefficient was employed to predict responses of ETo to perturbations of four climatic variables in the Ejina oasis northwest China. A 20-year historical dataset of daily air temperature, wind speed, relative humidity and daily sunshine duration in the Ejina oasis was used in the analysis. Results have shown that daily sensitivity coefficients exhibited large fluctuations during the growing season, and shortwave radiation was the most sensitive variable in general for the Ejina oasis, followed by air temperature, wind speed and relative humidity. According to this study, the response of ETo can be preferably predicted under perturbation of air temperature, wind speed, relative humidity and shortwave radiation by their sensitivity coefficients.

Knowledge Mapping for Climate Change and Food- and Waterborne Diseases.

PubMed

Semenza, Jan C; Höuser, Christoph; Herbst, Susanne; Rechenburg, Andrea; Suk, Jonathan E; Frechen, Tobias; Kistemann, Thomas

2012-02-01

The authors extracted from the PubMed and ScienceDirect bibliographic databases all articles published between 1998 and 2009 that were relevant to climate change and food- and waterborne diseases. Any material within each article that provided information about a relevant pathogen and its relationship with climate and climate change was summarized as a key fact, entered into a relational knowledge base, and tagged with the terminology (predefined terms) used in the field. These terms were organized, quantified, and mapped according to predefined hierarchical categories. For noncholera Vibrio sp. and Cryptosporidium sp., data on climatic and environmental influences (52% and 49% of the total number of key facts, respectively) pertained to specific weather phenomena (as opposed to climate change phenomena) and environmental determinants, whereas information on the potential effects of food-related determinants that might be related to climate or climate change were virtually absent. This proportion was lower for the other pathogens studied ( Campylobacter sp. 40%, Salmonella sp. 27%, Norovirus 25%, Listeria sp. 8%), but they all displayed a distinct concentration of information on general food-and water-related determinants or effects, albeit with little detail. Almost no information was available concerning the potential effects of changes in climatic variables on the pathogens evaluated, such as changes in air or water temperature, precipitation, humidity, UV radiation, wind, cloud coverage, sunshine hours, or seasonality. Frequency profiles revealed an abundance of data on weather and food-specific determinants, but also exposed extensive data deficiencies, particularly with regard to the potential effects of climate change on the pathogens evaluated. A reprioritization of public health research is warranted to ensure that funding is dedicated to explicitly studying the effects of changes in climate variables on food- and waterborne diseases.

Knowledge Mapping for Climate Change and Food- and Waterborne Diseases

PubMed Central

Semenza, Jan C.; Höuser, Christoph; Herbst, Susanne; Rechenburg, Andrea; Suk, Jonathan E.; Frechen, Tobias; Kistemann, Thomas

2011-01-01

The authors extracted from the PubMed and ScienceDirect bibliographic databases all articles published between 1998 and 2009 that were relevant to climate change and food- and waterborne diseases. Any material within each article that provided information about a relevant pathogen and its relationship with climate and climate change was summarized as a key fact, entered into a relational knowledge base, and tagged with the terminology (predefined terms) used in the field. These terms were organized, quantified, and mapped according to predefined hierarchical categories. For noncholera Vibrio sp. and Cryptosporidium sp., data on climatic and environmental influences (52% and 49% of the total number of key facts, respectively) pertained to specific weather phenomena (as opposed to climate change phenomena) and environmental determinants, whereas information on the potential effects of food-related determinants that might be related to climate or climate change were virtually absent. This proportion was lower for the other pathogens studied (Campylobacter sp. 40%, Salmonella sp. 27%, Norovirus 25%, Listeria sp. 8%), but they all displayed a distinct concentration of information on general food-and water-related determinants or effects, albeit with little detail. Almost no information was available concerning the potential effects of changes in climatic variables on the pathogens evaluated, such as changes in air or water temperature, precipitation, humidity, UV radiation, wind, cloud coverage, sunshine hours, or seasonality. Frequency profiles revealed an abundance of data on weather and food-specific determinants, but also exposed extensive data deficiencies, particularly with regard to the potential effects of climate change on the pathogens evaluated. A reprioritization of public health research is warranted to ensure that funding is dedicated to explicitly studying the effects of changes in climate variables on food- and waterborne diseases. PMID:24771989

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.

North Atlantic variability and its links to European climate over the last 3000 years.

PubMed

Moffa-Sánchez, Paola; Hall, Ian R

2017-11-23

The subpolar North Atlantic is a key location for the Earth's climate system. In the Labrador Sea, intense winter air-sea heat exchange drives the formation of deep waters and the surface circulation of warm waters around the subpolar gyre. This process therefore has the ability to modulate the oceanic northward heat transport. Recent studies reveal decadal variability in the formation of Labrador Sea Water. Yet, crucially, its longer-term history and links with European climate remain limited. Here we present new decadally resolved marine proxy reconstructions, which suggest weakened Labrador Sea Water formation and gyre strength with similar timing to the centennial cold periods recorded in terrestrial climate archives and historical records over the last 3000 years. These new data support that subpolar North Atlantic circulation changes, likely forced by increased southward flow of Arctic waters, contributed to modulating the climate of Europe with important societal impacts as revealed in European history.

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.

Impacts of Irrigation on Daily Extremes in the Coupled Climate System

NASA Technical Reports Server (NTRS)

Puma, Michael J.; Cook, Benjamin I.; Krakauer, Nir; Gentine, Pierre; Nazarenka, Larissa; Kelly, Maxwell; Wada, Yoshihide

2014-01-01

Widespread irrigation alters regional climate through changes to the energy and water budgets of the land surface. Within general circulation models, simulation studies have revealed significant changes in temperature, precipitation, and other climate variables. Here we investigate the feedbacks of irrigation with a focus on daily extremes at the global scale. We simulate global climate for the year 2000 with and without irrigation to understand irrigation-induced changes. Our simulations reveal shifts in key climate-extreme metrics. These findings indicate that land cover and land use change may be an important contributor to climate extremes both locally and in remote regions including the low-latitudes.

Effect of antecedent terrestrial land-use on C and N cycling in created wetlands

NASA Astrophysics Data System (ADS)

McCalley, C. K.; Al Graiti, T.; Williams, T.; Huang, S.; McGowan, M. B.; Eddingsaas, N. C.; Tyler, A. C.

2017-12-01

Land-use legacies and their interaction with both management actions and climate variability has a poorly characterized impact on the development of ecosystem functions and the trajectory of climate-carbon feedbacks. The complex structure-function relationships in wetlands foster delivery of valuable, climate sensitive, ecosystem services (carbon sequestration, nutrient removal, flood control, etc.) but also make them susceptible to colonization by invasive plants and lead to emission of key greenhouse gases. This project uses created wetland ecosystems as a model to understand how heterogeneity in antecedent conditions interacts with management options to create unique structure-function scenarios and a range of climate feedback outcomes. We utilized ongoing experiments in created wetlands that differ in antecedent conditions (crop agriculture, livestock grazing) and investigated how management options (invasive species removal, organic matter addition) interact with legacy impacts to promote key ecosystem functions, including greenhouse gas emissions, carbon sequestration, denitrification and plant biodiversity. The effects of antecedent land-use on soil chemistry, coupled with hydrologic patterns resulted in wetlands with divergent C and N dynamics despite their similar creation history. Additionally, the occurrence of extreme weather events (drought and excessive flooding) during the study period highlighted the overarching role that increased climate variability will play in determining key ecosystem processes in wetlands. Responses to management were linked to hydro-period: while organic matter addition successfully increased soil organic matter to more closely replicate natural systems at all sites, it had the largest impact on C and N cycling when soils were saturated. Overall, environmental conditions that promoted saturated soils, both those shaped by human activities or climate extremes, enhanced primary productivity, nutrient removal and greenhouse gas production as well as decreased soil respiration.

Who, What, Where, When, and Why: Demographic and Ecological Factors Contributing to Hostile School Climate for Lesbian, Gay, Bisexual, and Transgender Youth

ERIC Educational Resources Information Center

Kosciw, Joseph G.; Greytak, Emily A.; Diaz, Elizabeth M.

2009-01-01

This study examines how locational (region and locale), community-level (school district poverty and adult educational attainment), and school district-level (district size and ratios of students to key school personnel) variables are related to indicators of hostile school climate for lesbian, gay, bisexual, and transgender (LGBT) youth.…

Considering Species Tolerance to Climate Change in Conservation Management at Little Cayman's Coral Reefs

NASA Astrophysics Data System (ADS)

Camp, E.; Manfrino, C.; Smith, D.; Suggett, D.

2013-05-01

There is growing evidence demonstrating that climate change, notably increased frequency and intensity of thermal anomalies combined with ocean acidification, will negatively impact the future growth and viability of many reef systems, including those in the Caribbean. One key question that remains unanswered is whether or not there are management options aimed at protecting coral species from these threats. Little Cayman (Cayman Islands) provides a rare opportunity to investigate global climate stressors without the confounding impact of local anthropogenic stressors. Our research has focused on two climate change issues: Firstly, we have identified species-specific coral bleaching susceptibility (and the influence of regulation upon this susceptibility) to thermal anomalies. Species level of vulnerability to thermal anomalies can decrease when grown under variable temperature. Environmental variability may be key in influencing the susceptibility of corals to stress. The second part of our research has therefore addressed the variability in inorganic carbon chemistry that naturally occurs where certain reef building corals exist. We have identified how the inorganic carbon chemistry varies naturally among habitats and thus how corals within these habitats are potentially adapted to future acidification. Spatial, diurnal, lunar and seasonal variability have been identified as important factors with pCO2 values of up to 700-800 μatm and pH values as low as 7.801 for lagoon habitats, showing that some species are already being exposed to typical pCO2 and pH levels expected for the oceans in ~50 years' time. Using an eco-physiological approach, we are exploring how some reef-building corals are able to acclimate to more variable chemistry compared to others and whether this natural capacity installs increased tolerance to future acidification. These eco-physiological studies provide important information that can be utilized in a management framework. The aim of this framework will be to provide options to buffer or decrease the future impacts of global climate change on tropical coral reef systems.

Solar Effects on Global Climate Due to Cosmic Rays and Solar Energetic Particles

NASA Technical Reports Server (NTRS)

Turco, R. P.; Raeder, J.; DAuria, R.

2005-01-01

Although the work reported here does not directly connect solar variability with global climate change, this research establishes a plausible quantitative causative link between observed solar activity and apparently correlated variations in terrestrial climate parameters. Specifically, we have demonstrated that ion-mediated nucleation of atmospheric particles is a likely, and likely widespread, phenomenon that relates solar variability to changes in the microphysical properties of clouds. To investigate this relationship, we have constructed and applied a new model describing the formation and evolution of ionic clusters under a range of atmospheric conditions throughout the lower atmosphere. The activation of large ionic clusters into cloud nuclei is predicted to be favorable in the upper troposphere and mesosphere, and possibly in the lower stratosphere. The model developed under this grant needs to be extended to include additional cluster families, and should be incorporated into microphysical models to further test the cause-and-effect linkages that may ultimately explain key aspects of the connections between solar variability and climate.

Annually resolved North Atlantic marine climate over the last millennium

NASA Astrophysics Data System (ADS)

Reynolds, D. J.; Scourse, J. D.; Halloran, P. R.; Nederbragt, A. J.; Wanamaker, A. D.; Butler, P. G.; Richardson, C. A.; Heinemeier, J.; Eiríksson, J.; Knudsen, K. L.; Hall, I. R.

2016-12-01

Owing to the lack of absolutely dated oceanographic information before the modern instrumental period, there is currently significant debate as to the role played by North Atlantic Ocean dynamics in previous climate transitions (for example, Medieval Climate Anomaly-Little Ice Age, MCA-LIA). Here we present analyses of a millennial-length, annually resolved and absolutely dated marine δ18O archive. We interpret our record of oxygen isotope ratios from the shells of the long-lived marine bivalve Arctica islandica (δ18O-shell), from the North Icelandic shelf, in relation to seawater density variability and demonstrate that solar and volcanic forcing coupled with ocean circulation dynamics are key drivers of climate variability over the last millennium. During the pre-industrial period (AD 1000-1800) variability in the sub-polar North Atlantic leads changes in Northern Hemisphere surface air temperatures at multi-decadal timescales, indicating that North Atlantic Ocean dynamics played an active role in modulating the response of the atmosphere to solar and volcanic forcing.

Climate variability slows evolutionary responses of Colias butterflies to recent climate change.

PubMed

Kingsolver, Joel G; Buckley, Lauren B

2015-03-07

How does recent climate warming and climate variability alter fitness, phenotypic selection and evolution in natural populations? We combine biophysical, demographic and evolutionary models with recent climate data to address this question for the subalpine and alpine butterfly, Colias meadii, in the southern Rocky Mountains. We focus on predicting patterns of selection and evolution for a key thermoregulatory trait, melanin (solar absorptivity) on the posterior ventral hindwings, which affects patterns of body temperature, flight activity, adult and egg survival, and reproductive success in Colias. Both mean annual summer temperatures and thermal variability within summers have increased during the past 60 years at subalpine and alpine sites. At the subalpine site, predicted directional selection on wing absorptivity has shifted from generally positive (favouring increased wing melanin) to generally negative during the past 60 years, but there is substantial variation among years in the predicted magnitude and direction of selection and the optimal absorptivity. The predicted magnitude of directional selection at the alpine site declined during the past 60 years and varies substantially among years, but selection has generally been positive at this site. Predicted evolutionary responses to mean climate warming at the subalpine site since 1980 is small, because of the variability in selection and asymmetry of the fitness function. At both sites, the predicted effects of adaptive evolution on mean population fitness are much smaller than the fluctuations in mean fitness due to climate variability among years. Our analyses suggest that variation in climate within and among years may strongly limit evolutionary responses of ectotherms to mean climate warming in these habitats. © 2015 The Author(s) Published by the Royal Society. All rights reserved.

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.

Spatial patterns of simulated transpiration response to climate variability in a snow dominated mountain ecosystem

USGS Publications Warehouse

Christensen, L.; Tague, C.L.; Baron, Jill S.

2008-01-01

Transpiration is an important component of soil water storage and stream-flow and is linked with ecosystem productivity, species distribution, and ecosystem health. In mountain environments, complex topography creates heterogeneity in key controls on transpiration as well as logistical challenges for collecting representative measurements. In these settings, ecosystem models can be used to account for variation in space and time of the dominant controls on transpiration and provide estimates of transpiration patterns and their sensitivity to climate variability and change. The Regional Hydro-Ecological Simulation System (RHESSys) model was used to assess elevational differences in sensitivity of transpiration rates to the spatiotemporal variability of climate variables across the Upper Merced River watershed, Yosemite Valley, California, USA. At the basin scale, predicted annual transpiration was lowest in driest and wettest years, and greatest in moderate precipitation years (R2 = 0.32 and 0.29, based on polynomial regression of maximum snow depth and annual precipitation, respectively). At finer spatial scales, responsiveness of transpiration rates to climate differed along an elevational gradient. Low elevations (1200-1800 m) showed little interannual variation in transpiration due to topographically controlled high soil moistures along the river corridor. Annual conifer stand transpiration at intermediate elevations (1800-2150 m) responded more strongly to precipitation, resulting in a unimodal relationship between transpiration and precipitation where highest transpiration occurred during moderate precipitation levels, regardless of annual air temperatures. Higher elevations (2150-2600 m) maintained this trend, but air temperature sensitivities were greater. At these elevations, snowfall provides enough moisture for growth, and increased temperatures influenced transpiration. Transpiration at the highest elevations (2600-4000 m) showed strong sensitivity to air temperature, little sensitivity to precipitation. Model results suggest elevational differences in vegetation water use and sensitivity to climate were significant and will likely play a key role in controlling responses and vulnerability of Sierra Nevada ecosystems to climate change. Copyright ?? 2008 John Wiley & Sons, Ltd.

A synthesis of Plio-Pleistocene leaf wax biomarker records of hydrological variation in East Africa and their relationship with hominin evolution

NASA Astrophysics Data System (ADS)

Lupien, R.; Russell, J. M.; Campisano, C. J.; Feibel, C. S.; Deino, A. L.; Kingston, J.; Potts, R.; Cohen, A. S.

2017-12-01

Climate change is thought to play a critical role in human evolution. However, the mechanisms behind this relationship are difficult to test due to a lack of long, high-quality paleoclimate records from hominin fossil locales. We improve the understanding of this relationship by examining Plio-Pleistocene lake sediment cores from East Africa that were drilled by the Hominin Sites and Paleolakes Drilling Project, an international effort to study the environment in which our hominin ancestors evolved and dispersed. We have analyzed organic geochemical signals of climate from drill cores from Ethiopia and Kenya spanning the Pliocene to recent time (from north to south: paleolake Hadar, Lake Turkana, Lake Baringo, and paleolake Koora). Specifically, we analyzed the hydrogen isotopic composition of terrestrial leaf waxes, which records changes in regional atmospheric circulation and hydrology. We reconstructed quantitative records of rainfall amount at each of the study sites, which host sediment spanning different geologic times and regions. By compiling these records, we test hominin evolutionary hypotheses as well as crucial questions about climate trend and variability. We find that there is a gradual or step-wise enrichment in δDwax, signifying a trend from a wet to dry climate, from the Pliocene to the Pleistocene, perhaps implying an influence of global temperature, ice sheet extent, and/or atmospheric greenhouse gas concentrations on East African climate. However, the shift is small relative to the amplitude of orbital-scale isotopic variations. The records indicate a strong influence of eccentricity-modulated orbital precession, and imply that local insolation effects are the likely cause of East African precipitation. Several of the intervals of high isotopic variability coincide with key hominin fossil or technological transitions, suggesting that climate variability plays a key role in hominin evolution.

Spatial and temporal variation in plant hydraulic traits and their relevance for climate change impacts on vegetation.

PubMed

Anderegg, William R L

2015-02-01

Plant hydraulics mediate terrestrial woody plant productivity, influencing global water, carbon, and biogeochemical cycles, as well as ecosystem vulnerability to drought and climate change. While inter-specific differences in hydraulic traits are widely documented, intra-specific hydraulic variability is less well known and is important for predicting climate change impacts. Here, I present a conceptual framework for this intra-specific hydraulic trait variability, reviewing the mechanisms that drive variability and the consequences for vegetation response to climate change. I performed a meta-analysis on published studies (n = 33) of intra-specific variation in a prominent hydraulic trait - water potential at which 50% stem conductivity is lost (P50) - and compared this variation to inter-specific variability within genera and plant functional types used by a dynamic global vegetation model. I found that intra-specific variability is of ecologically relevant magnitudes, equivalent to c. 33% of the inter-specific variability within a genus, and is larger in angiosperms than gymnosperms, although the limited number of studies highlights that more research is greatly needed. Furthermore, plant functional types were poorly situated to capture key differences in hydraulic traits across species, indicating a need to approach prediction of drought impacts from a trait-based, rather than functional type-based perspective.

Socio-economic and climate change impacts on agriculture: an integrated assessment, 1990–2080

PubMed Central

Fischer, Günther; Shah, Mahendra; N. Tubiello, Francesco; van Velhuizen, Harrij

2005-01-01

A comprehensive assessment of the impacts of climate change on agro-ecosystems over this century is developed, up to 2080 and at a global level, albeit with significant regional detail. To this end an integrated ecological–economic modelling framework is employed, encompassing climate scenarios, agro-ecological zoning information, socio-economic drivers, as well as world food trade dynamics. Specifically, global simulations are performed using the FAO/IIASA agro-ecological zone model, in conjunction with IIASAs global food system model, using climate variables from five different general circulation models, under four different socio-economic scenarios from the intergovernmental panel on climate change. First, impacts of different scenarios of climate change on bio-physical soil and crop growth determinants of yield are evaluated on a 5′×5′ latitude/longitude global grid; second, the extent of potential agricultural land and related potential crop production is computed. The detailed bio-physical results are then fed into an economic analysis, to assess how climate impacts may interact with alternative development pathways, and key trends expected over this century for food demand and production, and trade, as well as key composite indices such as risk of hunger and malnutrition, are computed. This modelling approach connects the relevant bio-physical and socio-economic variables within a unified and coherent framework to produce a global assessment of food production and security under climate change. The results from the study suggest that critical impact asymmetries due to both climate and socio-economic structures may deepen current production and consumption gaps between developed and developing world; it is suggested that adaptation of agricultural techniques will be central to limit potential damages under climate change. PMID:16433094

Lakes as sentinels of climate change

PubMed Central

Adrian, Rita; O’Reilly, Catherine M.; Zagarese, Horacio; Baines, Stephen B.; Hessen, Dag O.; Keller, Wendel; Livingstone, David M.; Sommaruga, Ruben; Straile, Dietmar; Van Donk, Ellen; Weyhenmeyer, Gesa A.; Winder, Monika

2010-01-01

While there is a general sense that lakes can act as sentinels of climate change, their efficacy has not been thoroughly analyzed. We identified the key response variables within a lake that act as indicators of the effects of climate change on both the lake and the catchment. These variables reflect a wide range of physical, chemical, and biological responses to climate. However, the efficacy of the different indicators is affected by regional response to climate change, characteristics of the catchment, and lake mixing regimes. Thus, particular indicators or combinations of indicators are more effective for different lake types and geographic regions. The extraction of climate signals can be further complicated by the influence of other environmental changes, such as eutrophication or acidification, and the equivalent reverse phenomena, in addition to other land-use influences. In many cases, however, confounding factors can be addressed through analytical tools such as detrending or filtering. Lakes are effective sentinels for climate change because they are sensitive to climate, respond rapidly to change, and integrate information about changes in the catchment. PMID:20396409

National climate assessment technical report on the impacts of climate and land use and land cover change

USGS Publications Warehouse

Loveland, Thomas; Mahmood, Rezaul; Patel-Weynand, Toral; Karstensen, Krista; Beckendorf, Kari; Bliss, Norman; Carleton, Andrew

2012-01-01

This technical report responds to the recognition by the U.S. Global Change Research Program (USGCRP) and the National Climate Assessment (NCA) of the importance of understanding how land use and land cover (LULC) affects weather and climate variability and change and how that variability and change affects LULC. Current published, peer-reviewed, scientific literature and supporting data from both existing and original sources forms the basis for this report's assessment of the current state of knowledge regarding land change and climate interactions. The synthesis presented herein documents how current and future land change may alter environment processes and in turn, how those conditions may affect both land cover and land use by specifically investigating, * The primary contemporary trends in land use and land cover, * The land-use and land-cover sectors and regions which are most affected by weather and climate variability,* How land-use practices are adapting to climate change, * How land-use and land-cover patterns and conditions are affecting weather and climate, and * The key elements of an ongoing Land Resources assessment. These findings present information that can be used to better assess land change and climate interactions in order to better assess land management and adaptation strategies for future environmental change and to assist in the development of a framework for an ongoing national assessment.

Millennial-scale variability in the local radiocarbon reservoir age of the Florida Keys reef tract during the Holocene

NASA Astrophysics Data System (ADS)

Ashe, E.; Toth, L. T.; Cheng, H.; Edwards, R. L.; Richey, J. N.

2016-12-01

The oceanic passage between the Florida Keys and Cuba, known as the Straits of Florida, provides a critical connection between the tropics and northern Atlantic. Changes in the character of water masses transported through this region may ultimately have important impacts on high-latitude climate variability. Although recent studies have documented significant changes in the density of regional surface waters over millennial timescales, little is known about the contribution of local- to regional-scale changes in circulation to surface-water variability. Local variability in the radiocarbon age, ΔR, of surface waters can be used to trace changes in local water-column mixing and/or changes in regional source water over a variety of spatial and temporal scales. We reconstructed "snapshots" of ΔR variability across the Florida Keys reef tract during the last 10,000 years by dating 68 unaltered corals collected from Holocene reef cores with both U-series and radiocarbon techniques. We combined the snapshots of ΔR into a semi-empirical model to develop a robust statistical reconstruction of millennial-scale variability in ΔR on the Florida Keys reef tract. Our model demonstrates that ΔR varied significantly during the Holocene, with relatively high values during the early Holocene and around 3000 years BP and relatively low values around 7000 years BP and at present. We compare the trends in ΔR to existing paleoceanographic reconstructions to evaluate the relative contribution of local upwelling versus changes in source water to the region as a whole in driving local radiocarbon variability, and discuss the importance of these results to our understanding of regional-scale oceanographic and climatic variability during the Holocene. We also discuss the implications of our results for radiocarbon dating of marine samples from south Florida and present a model of ΔR versus 14C age that can be used to improve the accuracy of radiocarbon calibrations from this region.

Hydrological Impacts of Land Use Change and Climate Variability in the Headwater Region of the Heihe River Basin, Northwest China

PubMed Central

Zhang, Ling; Nan, Zhuotong; Xu, Yi; Li, Shuo

2016-01-01

Land use change and climate variability are two key factors impacting watershed hydrology, which is strongly related to the availability of water resources and the sustainability of local ecosystems. This study assessed separate and combined hydrological impacts of land use change and climate variability in the headwater region of a typical arid inland river basin, known as the Heihe River Basin, northwest China, in the recent past (1995–2014) and near future (2015–2024), by combining two land use models (i.e., Markov chain model and Dyna-CLUE) with a hydrological model (i.e., SWAT). The potential impacts in the near future were explored using projected land use patterns and hypothetical climate scenarios established on the basis of analyzing long-term climatic observations. Land use changes in the recent past are dominated by the expansion of grassland and a decrease in farmland; meanwhile the climate develops with a wetting and warming trend. Land use changes in this period induce slight reductions in surface runoff, groundwater discharge and streamflow whereas climate changes produce pronounced increases in them. The joint hydrological impacts are similar to those solely induced by climate changes. Spatially, both the effects of land use change and climate variability vary with the sub-basin. The influences of land use changes are more identifiable in some sub-basins, compared with the basin-wide impacts. In the near future, climate changes tend to affect the hydrological regimes much more prominently than land use changes, leading to significant increases in all hydrological components. Nevertheless, the role of land use change should not be overlooked, especially if the climate becomes drier in the future, as in this case it may magnify the hydrological responses. PMID:27348224

Hydrological Impacts of Land Use Change and Climate Variability in the Headwater Region of the Heihe River Basin, Northwest China.

PubMed

Zhang, Ling; Nan, Zhuotong; Xu, Yi; Li, Shuo

2016-01-01

Land use change and climate variability are two key factors impacting watershed hydrology, which is strongly related to the availability of water resources and the sustainability of local ecosystems. This study assessed separate and combined hydrological impacts of land use change and climate variability in the headwater region of a typical arid inland river basin, known as the Heihe River Basin, northwest China, in the recent past (1995-2014) and near future (2015-2024), by combining two land use models (i.e., Markov chain model and Dyna-CLUE) with a hydrological model (i.e., SWAT). The potential impacts in the near future were explored using projected land use patterns and hypothetical climate scenarios established on the basis of analyzing long-term climatic observations. Land use changes in the recent past are dominated by the expansion of grassland and a decrease in farmland; meanwhile the climate develops with a wetting and warming trend. Land use changes in this period induce slight reductions in surface runoff, groundwater discharge and streamflow whereas climate changes produce pronounced increases in them. The joint hydrological impacts are similar to those solely induced by climate changes. Spatially, both the effects of land use change and climate variability vary with the sub-basin. The influences of land use changes are more identifiable in some sub-basins, compared with the basin-wide impacts. In the near future, climate changes tend to affect the hydrological regimes much more prominently than land use changes, leading to significant increases in all hydrological components. Nevertheless, the role of land use change should not be overlooked, especially if the climate becomes drier in the future, as in this case it may magnify the hydrological responses.

Climate change and water availability for vulnerable agriculture

NASA Astrophysics Data System (ADS)

Dalezios, Nicolas; Tarquis, Ana Maria

2017-04-01

Climatic projections for the Mediterranean basin indicate that the area will suffer a decrease in water resources due to climate change. The key climatic trends identified for the Mediterranean region are continuous temperature increase, further drying with precipitation decrease and the accentuation of climate extremes, such as droughts, heat waves and/or forest fires, which are expected to have a profound effect on agriculture. Indeed, the impact of climate variability on agricultural production is important at local, regional, national, as well as global scales. Agriculture of any kind is strongly influenced by the availability of water. Climate change will modify rainfall, evaporation, runoff, and soil moisture storage patterns. Changes in total seasonal precipitation or in its pattern of variability are both important. Similarly, with higher temperatures, the water-holding capacity of the atmosphere and evaporation into the atmosphere increase, and this favors increased climate variability, with more intense precipitation and more droughts. As a result, crop yields are affected by variations in climatic factors, such as air temperature and precipitation, and the frequency and severity of the above mentioned extreme events. The aim of this work is to briefly present the main effects of climate change and variability on water resources with respect to water availability for vulnerable agriculture, namely in the Mediterranean region. Results of undertaken studies in Greece on precipitation patterns and drought assessment using historical data records are presented. Based on precipitation frequency analysis, evidence of precipitation reductions is shown. Drought is assessed through an agricultural drought index, namely the Vegetation Health Index (VHI), in Thessaly, a drought-prone region in central Greece. The results justify the importance of water availability for vulnerable agriculture and the need for drought monitoring in the Mediterranean basin as part of an integrated climate adaptation strategy.

Meridional Modes and Increasing Pacific Decadal Variability Under Anthropogenic Forcing

NASA Astrophysics Data System (ADS)

Liguori, Giovanni; Di Lorenzo, Emanuele

2018-01-01

Pacific decadal variability has strong impacts on the statistics of weather, atmosphere extremes, droughts, hurricanes, marine heatwaves, and marine ecosystems. Sea surface temperature (SST) observations show that the variance of the El Niño-like decadal variability has increased by 30% (1920-2015) with a stronger coupling between the major Pacific climate modes. Although we cannot attribute these trends to global climate change, the examination of 30 members of the Community Earth System Model Large Ensemble (LENS) forced with the RCP8.5 radiative forcing scenario (1920-2100) suggests that significant anthropogenic trends in Pacific decadal variance will emerge by 2020 in response to a more energetic North Pacific Meridional Mode (PMM)—a well-known El Niño precursor. The PMM is a key mechanism for energizing and coupling tropical and extratropical decadal variability. In the LENS, the increase in PMM variance is consistent with an intensification of the winds-evaporation-SST thermodynamic feedback that results from a warmer mean climate.

Climate Change and Conservation Planning in California: The San Francisco Bay Area Upland Habitat Goals Approach

NASA Astrophysics Data System (ADS)

Branciforte, R.; Weiss, S. B.; Schaefer, N.

2008-12-01

Climate change threatens California's vast and unique biodiversity. The Bay Area Upland Habitat Goals is a comprehensive regional biodiversity assessment of the 9 counties surrounding San Francisco Bay, and is designing conservation land networks that will serve to protect, manage, and restore that biodiversity. Conservation goals for vegetation, rare plants, mammals, birds, fish, amphibians, reptiles, and invertebrates are set, and those goals are met using the optimization algorithm MARXAN. Climate change issues are being considered in the assessment and network design in several ways. The high spatial variability at mesoclimatic and topoclimatic scales in California creates high local biodiversity, and provides some degree of local resiliency to macroclimatic change. Mesoclimatic variability from 800 m scale PRISM climatic norms is used to assess "mesoclimate spaces" in distinct mountain ranges, so that high mesoclimatic variability, especially local extremes that likely support range limits of species and potential climatic refugia, can be captured in the network. Quantitative measures of network resiliency to climate change include the spatial range of key temperature and precipitation variables within planning units. Topoclimatic variability provides a finer-grained spatial patterning. Downscaling to the topoclimatic scale (10-50 m scale) includes modeling solar radiation across DEMs for predicting maximum temperature differentials, and topographic position indices for modeling minimum temperature differentials. PRISM data are also used to differentiate grasslands into distinct warm and cool types. The overall conservation strategy includes local and regional connectivity so that range shifts can be accommodated.

Assessment of climate change impacts on climate variables using probabilistic ensemble modeling and trend analysis

NASA Astrophysics Data System (ADS)

Safavi, Hamid R.; Sajjadi, Sayed Mahdi; Raghibi, Vahid

2017-10-01

Water resources in snow-dependent regions have undergone significant changes due to climate change. Snow measurements in these regions have revealed alarming declines in snowfall over the past few years. The Zayandeh-Rud River in central Iran chiefly depends on winter falls as snow for supplying water from wet regions in high Zagrous Mountains to the downstream, (semi-)arid, low-lying lands. In this study, the historical records (baseline: 1971-2000) of climate variables (temperature and precipitation) in the wet region were chosen to construct a probabilistic ensemble model using 15 GCMs in order to forecast future trends and changes while the Long Ashton Research Station Weather Generator (LARS-WG) was utilized to project climate variables under two A2 and B1 scenarios to a future period (2015-2044). Since future snow water equivalent (SWE) forecasts by GCMs were not available for the study area, an artificial neural network (ANN) was implemented to build a relationship between climate variables and snow water equivalent for the baseline period to estimate future snowfall amounts. As a last step, homogeneity and trend tests were performed to evaluate the robustness of the data series and changes were examined to detect past and future variations. Results indicate different characteristics of the climate variables at upstream stations. A shift is observed in the type of precipitation from snow to rain as well as in its quantities across the subregions. The key role in these shifts and the subsequent side effects such as water losses is played by temperature.

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.

Modelling climate change and malaria transmission.

PubMed

Parham, Paul E; Michael, Edwin

2010-01-01

The impact of climate change on human health has received increasing attention in recent years, with potential impacts due to vector-borne diseases only now beginning to be understood. As the most severe vector-borne disease, with one million deaths globally in 2006, malaria is thought most likely to be affected by changes in climate variables due to the sensitivity of its transmission dynamics to environmental conditions. While considerable research has been carried out using statistical models to better assess the relationship between changes in environmental variables and malaria incidence, less progress has been made on developing process-based climate-driven mathematical models with greater explanatory power. Here, we develop a simple model of malaria transmission linked to climate which permits useful insights into the sensitivity of disease transmission to changes in rainfall and temperature variables. Both the impact of changes in the mean values of these key external variables and importantly temporal variation in these values are explored. We show that the development and analysis of such dynamic climate-driven transmission models will be crucial to understanding the rate at which P. falciparum and P. vivax may either infect, expand into or go extinct in populations as local environmental conditions change. Malaria becomes endemic in a population when the basic reproduction number R0 is greater than unity and we identify an optimum climate-driven transmission window for the disease, thus providing a useful indicator for determing how transmission risk may change as climate changes. Overall, our results indicate that considerable work is required to better understand ways in which global malaria incidence and distribution may alter with climate change. In particular, we show that the roles of seasonality, stochasticity and variability in environmental variables, as well as ultimately anthropogenic effects, require further study. The work presented here offers a theoretical framework upon which this future research may be developed.

Water management to cope with and adapt to climate variability and change.

NASA Astrophysics Data System (ADS)

Hamdy, A.; Trisorio-Liuzzi, G.

2009-04-01

In many parts of the world, variability in climatic conditions is already resulting in major impacts. These impacts are wide ranging and the link to water management problems is obvious and profound. The know-how and the available information undoubtedly indicate that climate change will lead to an intensification of the global hydrological cycle and can have major impacts on regional water resources, affecting both ground and surface water supply for sectorial water uses and, in particular, the irrigation field imposing notable negative effects on food security and poverty alleviation programs in most arid and semi-arid developing countries. At the United Nations Millennium Summit, in September 2000, world leaders adopted the Millennium Development Declaration. From this declaration, the IWRM was recognised as the key concept the water sector should be using for water related development and measures and, hence, for achieving the water related MDG's. However, the potential impacts of climate change and increasing climate variability are not sufficiently addressed in the IWRM plans. Indeed, only a very limited IWRM national plans have been prepared, coping with climate variability and changes. This is mainly due to the lack of operational instruments to deal with climate change and climate variability issues. This is particularly true in developing countries where the financial, human and ecological impacts are potentially greatest and where water resources may be already highly stressed, but the capacity to cope and adapt is weakest. Climate change has now brought realities including mainly rising temperatures and increasing frequency of floods and droughts that present new challenges to be addressed by the IWRM practice. There are already several regional and international initiatives underway that focus on various aspects of water resources management those to be linked with climate changes and vulnerability issues. This is the way where the water resources management and climate scientist communities are engaged in a process for building confidence and understanding, identifying options and defining the water resources management strategies which to cope with impacts of climate variability and change.

Assessing the Role of Climate Variability on Liver Fluke Risk in the UK Through Mechanistic Hydro-Epidemiological Modelling

NASA Astrophysics Data System (ADS)

Beltrame, L.; Dunne, T.; Rose, H.; Walker, J.; Morgan, E.; Vickerman, P.; Wagener, T.

2016-12-01

Liver fluke is a flatworm parasite infecting grazing animals worldwide. In the UK, it causes considerable production losses to cattle and sheep industries and costs farmers millions of pounds each year due to reduced growth rates and lower milk yields. Large part of the parasite life-cycle takes place outside of the host, with its survival and development strongly controlled by climatic and hydrologic conditions. Evidence of climate-driven changes in the distribution and seasonality of fluke disease already exists, as the infection is increasingly expanding to new areas and becoming a year-round problem. Therefore, it is crucial to assess current and potential future impacts of climate variability on the disease to guide interventions at the farm scale and mitigate risk. Climate-based fluke risk models have been available since the 1950s, however, they are based on empirical relationships derived between historical climate and incidence data, and thus are unlikely to be robust for simulating risk under changing conditions. Moreover, they are not dynamic, but estimate risk over large regions in the UK based on monthly average climate conditions, so they do not allow investigating the effects of climate variability for supporting farmers' decisions. In this study, we introduce a mechanistic model for fluke, which represents habitat suitability for disease development at 25m resolution with a daily time step, explicitly linking the parasite life-cycle to key hydro-climate conditions. The model is used on a case study in the UK and sensitivity analysis is performed to better understand the role of climate variability on the space-time dynamics of the disease, while explicitly accounting for uncertainties. Comparisons are presented with experts' knowledge and a widely used empirical model.

Native Peoples-Native Homelands Climate Change Workshop: Lessons Learned

NASA Technical Reports Server (NTRS)

Maynard, Nancy G.

2003-01-01

The Native Peoples-Native Homelands Climate Change Workshop was held on October 28 through November 01,1998, as part of a series of workshops being held around the U.S. to improve the understanding of the potential consequences of climate variability and change for the Nation. This workshop was specifically designed by Native Peoples to examine the impacts of climate change and extreme weather variability on Native Peoples and Native Homelands from an indigenous cultural and spiritual perspective and to develop recommendations as well as identify potential response actions. The workshop brought together interested Native Peoples, representatives of Tribal governments, traditional elders, Tribal leaders, natural resource managers, Tribal College faculty and students, and climate scientists fiom government agencies and universities. It is clear that Tribal colleges and universities play a unique and critical role in the success of these emerging partnerships for decision-making in addition to the important education function for both Native and non-Native communities such as serving as a culturally-appropriate vehicle for access, analysis, control, and protection of indigenous cultural and intellectual property. During the discussions between scientists and policy-makers from both Native and non-Native communities, a number of important lessons emerged which are key to building more effective partnerships between Native and non-Native communities for collaboration and decision-making for a more sustainable future. This talk summarizes the key issues, recommendations, and lessons learned during this workshop.

Texas: Houston

Atmospheric Science Data Center

2014-05-15

... key variables used to characterize their climatic and environmental influence. The extent of haze across Galveston Bay can be ... as part of the Houston regional air quality study. Airborne pollution particles that contribute to the poor air quality come in part from ...

The amplitude of decadal to multidecadal variability in precipitation simulated by state-of-the-art climate models

NASA Astrophysics Data System (ADS)

Ault, T. R.; Cole, J. E.; St. George, S.

2012-11-01

We assess the magnitude of decadal to multidecadal (D2M) variability in Climate Model Intercomparison Project 5 (CMIP5) simulations that will be used to understand, and plan for, climate change as part of the Intergovernmental Panel on Climate Change's 5th Assessment Report. Model performance on D2M timescales is evaluated using metrics designed to characterize the relative and absolute magnitude of variability at these frequencies. In observational data, we find that between 10% and 35% of the total variance occurs on D2M timescales. Regions characterized by the high end of this range include Africa, Australia, western North America, and the Amazon region of South America. In these areas D2M fluctuations are especially prominent and linked to prolonged drought. D2M fluctuations account for considerably less of the total variance (between 5% and 15%) in the CMIP5 archive of historical (1850-2005) simulations. The discrepancy between observation and model based estimates of D2M prominence reflects two features of the CMIP5 archive. First, interannual components of variability are generally too energetic. Second, decadal components are too weak in several key regions. Our findings imply that projections of the future lack sufficient decadal variability, presenting a limited view of prolonged drought and pluvial risk.

Population viability of Pediocactus bradyi (Cactaceae) in a changing climate.

PubMed

Shryock, Daniel F; Esque, Todd C; Hughes, Lee

2014-11-01

A key question concerns the vulnerability of desert species adapted to harsh, variable climates to future climate change. Evaluating this requires coupling long-term demographic models with information on past and projected future climates. We investigated climatic drivers of population growth using a 22-yr demographic model for Pediocactus bradyi, an endangered cactus in northern Arizona. We used a matrix model to calculate stochastic population growth rates (λs) and the relative influences of life-cycle transitions on population growth. Regression models linked population growth with climatic variability, while stochastic simulations were used to (1) understand how predicted increases in drought frequency and extreme precipitation would affect λs, and (2) quantify variability in λs based on temporal replication of data. Overall λs was below unity (0.961). Population growth was equally influenced by fecundity and survival and significantly correlated with increased annual precipitation and higher winter temperatures. Stochastic simulations increasing the probability of drought and extreme precipitation reduced λs, but less than simulations increasing the probability of drought alone. Simulations varying the temporal replication of data suggested 14 yr were required for accurate λs estimates. Pediocactus bradyi may be vulnerable to increases in the frequency and intensity of extreme climatic events, particularly drought. Biotic interactions resulting in low survival during drought years outweighed increased seedling establishment following heavy precipitation. Climatic extremes beyond historical ranges of variability may threaten rare desert species with low population growth rates and therefore high susceptibility to stochastic events. © 2014 Botanical Society of America, Inc.

Sensitivity analysis of monthly reference crop evapotranspiration trends in Iran: a qualitative approach

NASA Astrophysics Data System (ADS)

Mosaedi, Abolfazl; Ghabaei Sough, Mohammad; Sadeghi, Sayed-Hossein; Mooshakhian, Yousof; Bannayan, Mohammad

2017-05-01

The main objective of this study was to analyze the sensitivity of the monthly reference crop evapotranspiration (ETo) trends to key climatic factors (minimum and maximum air temperature ( T max and T min), relative humidity (RH), sunshine hours ( t sun), and wind speed ( U 2)) in Iran by applying a qualitative detrended method, rather than the historical mathematical approach. Meteorological data for the period of 1963-2007 from five synoptic stations with different climatic characteristics, including Mashhad (mountains), Tabriz (mountains), Tehran (semi-desert), Anzali (coastal wet), and Shiraz (semi-mountains) were used to address this objective. The Mann-Kendall test was employed to assess the trends of ETo and the climatic variables. The results indicated a significant increasing trend of the monthly ETo for Mashhad and Tabriz for most part of the year while the opposite conclusion was drawn for Tehran, Anzali, and Shiraz. Based on the detrended method, RH and U 2 were the two main variables enhancing the negative ETo trends in Tehran and Anzali stations whereas U 2 and temperature were responsible for this observation in Shiraz. On the other hand, the main meteorological variables affecting the significant positive trend of ETo were RH and t sun in Tabriz and T min, RH, and U 2 in Mashhad. Although a relative agreement was observed in terms of identifying one of the first two key climatic variables affecting the ETo trend, the qualitative and the quantitative sensitivity analysis solutions did never coincide. Further research is needed to evaluate this interesting finding for other geographic locations, and also to search for the major causes of this discrepancy.

Global land carbon sink response to temperature and precipitation varies with ENSO phase

DOE PAGES

Fang, Yuanyuan; Michalak, Anna M.; Schwalm, Christopher R.; ...

2017-06-01

Climate variability associated with the El Niño-Southern Oscillation (ENSO) and its consequent impacts on land carbon sink interannual variability have been used as a basis for investigating carbon cycle responses to climate variability more broadly, and to inform the sensitivity of the tropical carbon budget to climate change. Past studies have presented opposing views about whether temperature or precipitation is the primary factor driving the response of the land carbon sink to ENSO. We show that the dominant driver varies with ENSO phase. And whereas tropical temperature explains sink dynamics following El Niño conditions (r TG,P = 0.59, p

Global land carbon sink response to temperature and precipitation varies with ENSO phase

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

Fang, Yuanyuan; Michalak, Anna M.; Schwalm, Christopher R.

Climate variability associated with the El Niño-Southern Oscillation (ENSO) and its consequent impacts on land carbon sink interannual variability have been used as a basis for investigating carbon cycle responses to climate variability more broadly, and to inform the sensitivity of the tropical carbon budget to climate change. Past studies have presented opposing views about whether temperature or precipitation is the primary factor driving the response of the land carbon sink to ENSO. Here, we show that the dominant driver varies with ENSO phase. Whereas tropical temperature explains sink dynamics following El Niño conditions (r TG,P=0.59, p<0.01), the post Lamore » Niña sink is driven largely by tropical precipitation (r PG,T=-0.46, p=0.04). This finding points to an ENSO-phase-dependent interplay between water availability and temperature in controlling the carbon uptake response to climate variations in tropical ecosystems. We further find that none of a suite of ten contemporary terrestrial biosphere models captures these ENSO-phase-dependent responses, highlighting a key uncertainty in modeling climate impacts on the future of the global land carbon sink.« less

Global land carbon sink response to temperature and precipitation varies with ENSO phase

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

Fang, Yuanyuan; Michalak, Anna M.; Schwalm, Christopher R.

Climate variability associated with the El Niño-Southern Oscillation (ENSO) and its consequent impacts on land carbon sink interannual variability have been used as a basis for investigating carbon cycle responses to climate variability more broadly, and to inform the sensitivity of the tropical carbon budget to climate change. Past studies have presented opposing views about whether temperature or precipitation is the primary factor driving the response of the land carbon sink to ENSO. We show that the dominant driver varies with ENSO phase. And whereas tropical temperature explains sink dynamics following El Niño conditions (r TG,P = 0.59, p

Climate induced changes in biome distribution, NPP and hydrology for potential vegetation of the Upper Midwest U.S

NASA Astrophysics Data System (ADS)

Motew, M.; Kucharik, C. J.

2011-12-01

While much attention is focused on future impacts of climate change on ecosystems, much can be learned about the previous interactions of ecosystems with recent climate change. In this study, we investigated the impacts of climate change on potential vegetation distributions (i.e. grasses, trees, and shrubs) and carbon and water cycling across the Upper Midwest USA from 1948-2007 using the Agro-IBIS dynamic vegetation model. We drove the model using a historical, gridded daily climate data set (temperature, precipitation, humidity, solar radiation, and wind speed) at a spatial resolution of 5 min x 5 min. While trends in climate variables exhibited heterogeneous spatial patterns over the study period, the overall impact of climate change on vegetation productivity was positive. We observed total increases in net primary productivity (NPP) ranging from 20-150 g C m-2, based on linear regression analysis. We determined that increased summer relative humidity, increased annual precipitation and decreased mean maximum summer temperatures were key variables contributing to these positive trends, likely through a reduction in soil moisture stress (e.g., increased available water) and heat stress. Model simulations also illustrated an increase in annual drainage throughout the region of 20-140 mm yr-1, driven by substantial increases in annual precipitation. Evapotranspiration had a highly variable spatial trend over the 60-year period, with total change over the study period ranging between -100 and +100 mm yr-1. We also analyzed potential changes in plant functional type (PFT) distributions at the biome level, but hypothesize that the model may be unable to adequately capture competitive interactions among PFTs as well as the dynamics between upper and lower canopies consisting of trees, grasses and shrubs. An analysis of the bioclimatic envelopes for PFTs common to the region revealed no significant change to the boreal conifer tree climatic domain over the study period, yet did reveal a slightly expanded domain for temperate deciduous broadleaf trees. The location of the Tension Zone, a broad ecotone dividing mixed forests in the north and southern hardwood forests and prairies in the south, was not observed to shift using analyses of both meteorological variables and through the results of simulated vegetation distributions. In general, our results supported the idea that climate change is spatially variable in nature, having significant effects on ecosystem structure and function. Our analysis also revealed interesting relationships among the key climatic quantities driving plant productivity and hydrology in the region. Most notably, while the model suggested that potential biome and PFT distributions have not likely shifted significantly in the past 60 years, climate change has contributed to substantial changes in coupled carbon, water, and energy exchange in natural ecosystems of the Upper Midwest US. We conclude that incorporating recent, high-resolution climate records into ecological studies offers valuable insight into the heterogeneous nature of climate change and its impacts on ecosystems at the local level.

Effects of Global Change on U.S. Urban Areas: Vulnerabilities, Impacts, and Adaptation

NASA Technical Reports Server (NTRS)

Quattrochi, Dale A.; Wilbanks, Thomas J.; Kirshen, Paul; Romero-Lnkao, Patricia; Rosenzweig, Cynthia; Ruth, Matthias; Solecki, William; Tarr, Joel

2007-01-01

Human settlements, both large and small, are where the vast majority of people on the Earth live. Expansion of cities both in population and areal extent, is a relentless process that will accelerate in the 21st century. As a consequence of urban growth both in the United States and around the globe, it is important to develop an understanding of how urbanization will affect the local and regional environment. Of equal importance, however, is the assessment of how cities will be impacted by the looming prospects of global climate change and climate variability. The potential impacts of climate change and variability has recently been annunciated by the IPCC's "Climate Change 2007" report. Moreover, the U.S. Climate Change Science Program (CCSP) is preparing a series of "Synthesis and Assessment Products" (SAPs) reports to support informed discussion and decision making regarding climate change and variability by policy matters, resource managers, stakeholders, the media, and the general public. We are authors on a SAP describing the effects of global climate change on human settlements. This paper will present the elements of our SAP report that relate to what vulnerabilities and impacts will occur, what adaptation responses may take place, and what possible effects on settlement patterns and characteristics will potentially arise, on human settlements in the U.S. as a result of climate change and climate variability. We will also present some recommendations about what should be done to further research on how climate change and variability will impact human settlements in the U.S., as well as how to engage government officials, policy and decision makers, and the general public in understanding the implications of climate change and variability on the local and regional levels. Additionally, we wish to explore how technology such as remote sensing data coupled with modeling, can be employed as synthesis tools for deriving insight across a spectrum of impacts (e.g. public health, urban planning for mitigation strategies) on how cities can cope and adapt to climate change and variability. This latter point parallels the concepts and ideas presented in the U.S. National Academy of Sciences, Decadal Survey report on "Earth Science Applications from Space: National Imperatives for the Next Decade and Beyond" wherein the analysis of the impacts of climate change and variability, human health, and land use change are listed as key areas for development of future Earth observing remote sensing systems.

The idiosyncrasies of streams: local variability mitigates vulnerability of trout to changing conditions

Treesearch

Andrea Watts; Brooke Penaluna; Jason Dunham

2016-01-01

Land use and climate change are two key factors with the potential to affect stream conditions and fish habitat. Since the 1950s, Washington and Oregon have required forest practices designed to mitigate the effects of timber harvest on streams and fish. Yet questions remain about the extent to which these practices are effective. Add in the effects of climate change—...

Land Cover Land Use Change and Soil Organic Carbon under Climate Variability in the Semi-Arid West African Sahel (1960-2050)

ERIC Educational Resources Information Center

Dieye, Amadou M.

2016-01-01

Land Cover Land Use (LCLU) change affects land surface processes recognized to influence climate change at local, national and global levels. Soil organic carbon is a key component for the functioning of agro-ecosystems and has a direct effect on the physical, chemical and biological characteristics of the soil. The capacity to model and project…

Improve projections of changes in southern African summer rainfall through comprehensive multi-timescale empirical statistical downscaling

NASA Astrophysics Data System (ADS)

Dieppois, B.; Pohl, B.; Eden, J.; Crétat, J.; Rouault, M.; Keenlyside, N.; New, M. G.

2017-12-01

The water management community has hitherto neglected or underestimated many of the uncertainties in climate impact scenarios, in particular, uncertainties associated with decadal climate variability. Uncertainty in the state-of-the-art global climate models (GCMs) is time-scale-dependant, e.g. stronger at decadal than at interannual timescales, in response to the different parameterizations and to internal climate variability. In addition, non-stationarity in statistical downscaling is widely recognized as a key problem, in which time-scale dependency of predictors plays an important role. As with global climate modelling, therefore, the selection of downscaling methods must proceed with caution to avoid unintended consequences of over-correcting the noise in GCMs (e.g. interpreting internal climate variability as a model bias). GCM outputs from the Coupled Model Intercomparison Project 5 (CMIP5) have therefore first been selected based on their ability to reproduce southern African summer rainfall variability and their teleconnections with Pacific sea-surface temperature across the dominant timescales. In observations, southern African summer rainfall has recently been shown to exhibit significant periodicities at the interannual timescale (2-8 years), quasi-decadal (8-13 years) and inter-decadal (15-28 years) timescales, which can be interpret as the signature of ENSO, the IPO, and the PDO over the region. Most of CMIP5 GCMs underestimate southern African summer rainfall variability and their teleconnections with Pacific SSTs at these three timescales. In addition, according to a more in-depth analysis of historical and pi-control runs, this bias is might result from internal climate variability in some of the CMIP5 GCMs, suggesting potential for bias-corrected prediction based empirical statistical downscaling. A multi-timescale regression based downscaling procedure, which determines the predictors across the different timescales, has thus been used to simulate southern African summer rainfall. This multi-timescale procedure shows much better skills in simulating decadal timescales of variability compared to commonly used statistical downscaling approaches.

The role of ENSO in understanding changes in Colombia's annual malaria burden by region, 1960–2006

PubMed Central

Mantilla, Gilma; Oliveros, Hugo; Barnston, Anthony G

2009-01-01

Background Malaria remains a serious problem in Colombia. The number of malaria cases is governed by multiple climatic and non-climatic factors. Malaria control policies, and climate controls such as rainfall and temperature variations associated with the El Niño/Southern Oscillation (ENSO), have been associated with malaria case numbers. Using historical climate data and annual malaria case number data from 1960 to 2006, statistical models are developed to isolate the effects of climate in each of Colombia's five contrasting geographical regions. Methods Because year to year climate variability associated with ENSO causes interannual variability in malaria case numbers, while changes in population and institutional control policy result in more gradual trends, the chosen predictors in the models are annual indices of the ENSO state (sea surface temperature [SST] in the tropical Pacific Ocean) and time reference indices keyed to two major malaria trends during the study period. Two models were used: a Poisson and a Negative Binomial regression model. Two ENSO indices, two time reference indices, and one dummy variable are chosen as candidate predictors. The analysis was conducted using the five geographical regions to match the similar aggregation used by the National Institute of Health for its official reports. Results The Negative Binomial regression model is found better suited to the malaria cases in Colombia. Both the trend variables and the ENSO measures are significant predictors of malaria case numbers in Colombia as a whole, and in two of the five regions. A one degree Celsius change in SST (indicating a weak to moderate ENSO event) is seen to translate to an approximate 20% increase in malaria cases, holding other variables constant. Conclusion Regional differentiation in the role of ENSO in understanding changes in Colombia's annual malaria burden during 1960–2006 was found, constituting a new approach to use ENSO as a significant predictor of the malaria cases in Colombia. These results naturally point to additional needed work: (1) refining the regional and seasonal dependence of climate on the ENSO state, and of malaria on the climate variables; (2) incorporating ENSO-related climate variability into dynamic malaria models. PMID:19133152

Unveiling climate and ice-sheet history from drilling in high-latitude margins and future perspectives

NASA Astrophysics Data System (ADS)

Escutia Dotti, Carlota

2010-05-01

Polar ice is an important component of the climate system, affecting global sea level, ocean circulation and heat transport, marine productivity, and albedo. During the last decades drilling in the Arctic (IODP ACEX and Bering Expeditions) and in Antarctica (ODP Legs 178, 188, IODP Expedition 318 and ANDRILL) has revealed regional information about sea ice and ice sheets development and evolution. Integration of this data with numerical modeling provide an understanding of the early development of the ice sheets and their variability through the Cenozoic. Much of this work points to atmospheric CO2 and other greenhouse gases concentrations as important triggering mechanism driving the onset of glaciation and subsequent ice volume variability. With current increasing atmospheric greenhouse gases concentrations resulting in rapidly rising global temperatures, studies of polar climates become increasingly prominent on the research agenda. Despite of the relevance of the high-latitudes in the global climate systems, the short- and long-term history of the ice sheets and sea-ice and its relationships with paleoclimatic, paleoceanographic, and sea level changes is still poorly understood. A multinational, multiplatform scientific drilling strategy is being developed to recover key physical evidence from selected high-latitude areas. This strategy is aimed at addressing key knowledge gaps about the role of polar ice in climate change, targeting questions such as timing of events, rates of change, tipping points, regional variations, and northern vs. southern hemispheres (in phase or out-of-phase) variability. This data is critical to provide constrains to sea-ice and ice sheet models, which are the basis for forecasting the future of the cryosphere in a warming world.

Can climate variability information constrain a hydrological model for an ungauged Costa Rican catchment?

NASA Astrophysics Data System (ADS)

Quesada-Montano, Beatriz; Westerberg, Ida K.; Fuentes-Andino, Diana; Hidalgo-Leon, Hugo; Halldin, Sven

2017-04-01

Long-term hydrological data are key to understanding catchment behaviour and for decision making within water management and planning. Given the lack of observed data in many regions worldwide, hydrological models are an alternative for reproducing historical streamflow series. Additional types of information - to locally observed discharge - can be used to constrain model parameter uncertainty for ungauged catchments. Climate variability exerts a strong influence on streamflow variability on long and short time scales, in particular in the Central-American region. We therefore explored the use of climate variability knowledge to constrain the simulated discharge uncertainty of a conceptual hydrological model applied to a Costa Rican catchment, assumed to be ungauged. To reduce model uncertainty we first rejected parameter relationships that disagreed with our understanding of the system. We then assessed how well climate-based constraints applied at long-term, inter-annual and intra-annual time scales could constrain model uncertainty. Finally, we compared the climate-based constraints to a constraint on low-flow statistics based on information obtained from global maps. We evaluated our method in terms of the ability of the model to reproduce the observed hydrograph and the active catchment processes in terms of two efficiency measures, a statistical consistency measure, a spread measure and 17 hydrological signatures. We found that climate variability knowledge was useful for reducing model uncertainty, in particular, unrealistic representation of deep groundwater processes. The constraints based on global maps of low-flow statistics provided more constraining information than those based on climate variability, but the latter rejected slow rainfall-runoff representations that the low flow statistics did not reject. The use of such knowledge, together with information on low-flow statistics and constraints on parameter relationships showed to be useful to constrain model uncertainty for an - assumed to be - ungauged basin. This shows that our method is promising for reconstructing long-term flow data for ungauged catchments on the Pacific side of Central America, and that similar methods can be developed for ungauged basins in other regions where climate variability exerts a strong control on streamflow variability.

Multi-Site and Multi-Variables Statistical Downscaling Technique in the Monsoon Dominated Region of Pakistan

NASA Astrophysics Data System (ADS)

Khan, Firdos; Pilz, Jürgen

2016-04-01

South Asia is under the severe impacts of changing climate and global warming. The last two decades showed that climate change or global warming is happening and the first decade of 21st century is considered as the warmest decade over Pakistan ever in history where temperature reached 53 0C in 2010. Consequently, the spatio-temporal distribution and intensity of precipitation is badly effected and causes floods, cyclones and hurricanes in the region which further have impacts on agriculture, water, health etc. To cope with the situation, it is important to conduct impact assessment studies and take adaptation and mitigation remedies. For impact assessment studies, we need climate variables at higher resolution. Downscaling techniques are used to produce climate variables at higher resolution; these techniques are broadly divided into two types, statistical downscaling and dynamical downscaling. The target location of this study is the monsoon dominated region of Pakistan. One reason for choosing this area is because the contribution of monsoon rains in this area is more than 80 % of the total rainfall. This study evaluates a statistical downscaling technique which can be then used for downscaling climatic variables. Two statistical techniques i.e. quantile regression and copula modeling are combined in order to produce realistic results for climate variables in the area under-study. To reduce the dimension of input data and deal with multicollinearity problems, empirical orthogonal functions will be used. Advantages of this new method are: (1) it is more robust to outliers as compared to ordinary least squares estimates and other estimation methods based on central tendency and dispersion measures; (2) it preserves the dependence among variables and among sites and (3) it can be used to combine different types of distributions. This is important in our case because we are dealing with climatic variables having different distributions over different meteorological stations. The proposed model will be validated by using the (National Centers for Environmental Prediction / National Center for Atmospheric Research) NCEP/NCAR predictors for the period of 1960-1990 and validated for 1990-2000. To investigate the efficiency of the proposed model, it will be compared with the multivariate multiple regression model and with dynamical downscaling climate models by using different climate indices that describe the frequency, intensity and duration of the variables of interest. KEY WORDS: Climate change, Copula, Monsoon, Quantile regression, Spatio-temporal distribution.

Multi-agent modelling of climate outlooks and food security on a community garden scheme in Limpopo, South Africa.

PubMed

Bharwani, Sukaina; Bithell, Mike; Downing, Thomas E; New, Mark; Washington, Richard; Ziervogel, Gina

2005-11-29

Seasonal climate outlooks provide one tool to help decision-makers allocate resources in anticipation of poor, fair or good seasons. The aim of the 'Climate Outlooks and Agent-Based Simulation of Adaptation in South Africa' project has been to investigate whether individuals, who adapt gradually to annual climate variability, are better equipped to respond to longer-term climate variability and change in a sustainable manner. Seasonal climate outlooks provide information on expected annual rainfall and thus can be used to adjust seasonal agricultural strategies to respond to expected climate conditions. A case study of smallholder farmers in a village in Vhembe district, Limpopo Province, South Africa has been used to examine how such climate outlooks might influence agricultural strategies and how this climate information can be improved to be more useful to farmers. Empirical field data has been collected using surveys, participatory approaches and computer-based knowledge elicitation tools to investigate the drivers of decision-making with a focus on the role of climate, market and livelihood needs. This data is used in an agent-based social simulation which incorporates household agents with varying adaptation options which result in differing impacts on crop yields and thus food security, as a result of using or ignoring the seasonal outlook. Key variables are the skill of the forecast, the social communication of the forecast and the range of available household and community-based risk coping strategies. This research provides a novel approach for exploring adaptation within the context of climate change.

Effects of Global Change on U.S. Urban Areas: Vulnerabilities, Impacts, and Adaptation

NASA Technical Reports Server (NTRS)

Quattrochi, Dale A.; Wilbanks, Thomas J.; Kirshen, Paul; Romero-Lankao, Patricia; Rosenzweig, Cynthia; Ruth, Mattias; Solecki, William; Tarr, Joel

2008-01-01

This slide presentation reviews some of the effects that global change has on urban areas in the United States and how the growth of urban areas will affect the environment. It presents the elements of our Synthesis and Assessment Report (SAP) report that relate to what vulnerabilities and impacts will occur, what adaptation responses may take place, and what possible effects on settlement patterns and characteristics will potentially arise, on human settlements in the U.S. as a result of climate change and climate variability. We will also present some recommendations about what should be done to further research on how climate change and variability will impact human settlements in the U.S., as well as how to engage government officials, policy and decision makers, and the general public in understanding the implications of climate change and variability on the local and regional levels. Additionally, we wish to explore how technology such as remote sensing data coupled with modeling, can be employed as synthesis tools for deriving insight across a spectrum of impacts (e.g. public health, urban planning for mitigation strategies) on how cities can cope and adapt to climate change and variability. This latter point parallels the concepts and ideas presented in the U.S. National Academy of Sciences, Decadal Survey report on "Earth Science Applications from Space: National Imperatives for the Next Decade and Beyond" wherein the analysis of the impacts of climate change and variability, human health, and land use change are listed as key areas for development of future Earth observing remote sensing systems.

The Use of Climate Projections in the Modelling of Bud Burst

NASA Astrophysics Data System (ADS)

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

2010-05-01

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

Impact of Hydrologic Variability on Ecosystem Dynamics and the Sustainable Use of Soil and Water Resources

NASA Astrophysics Data System (ADS)

Porporato, A. M.

2013-05-01

We discuss the key processes by which hydrologic variability affects the probabilistic structure of soil moisture dynamics in water-controlled ecosystems. These in turn impact biogeochemical cycling and ecosystem structure through plant productivity and biodiversity as well as nitrogen availability and soil conditions. Once the long-term probabilistic structure of these processes is quantified, the results become useful to understand the impact of climatic changes and human activities on ecosystem services, and can be used to find optimal strategies of water and soil resources management under unpredictable hydro-climatic fluctuations. Particular applications regard soil salinization, phytoremediation and optimal stochastic irrigation.

Forest management as possible driver in mitigating climate change impacts at northern latitudes

NASA Astrophysics Data System (ADS)

Collalti, Alessio; Trotta, Carlo; Santini, Monia; Matteucci, Giorgio

2017-04-01

Climate change is likely to impact the dynamics of carbon and water cycles in forests over the next century. To date, it is still debated how forests will react. Some key variables may help in understanding the extent at which terrestrial ecosystems will be affected. Carbon Use Efficiency (CUE) and Water Use Efficiency (WUE) represent some of these key aspects. CUE represents the capacity of the forests to transfer carbon from the atmosphere to the terrestrial biomass, WUE the carbon gained for the water lost via canopy transpiration. Hence, both are key variables since they intimately represent the effects of several coupled ecophysiological processes affected by climate change. Here, we analyzed how within the 3D-CMCC-CNR FEM, forced by five general circulation model data and the four representative concentration pathways, the modeled CUE and WUE are affected by, from seasonal to over medium- and long-time period, warming, rising atmospheric [CO2] and management, assessing at which extent each component influences model results in an existing boreal forest in Finland. The 3D-CMCC-CNR FEM model results reveal that CUE tends to decrease with warmer scenarios, and management may greatly dampen the effects but only in the short- to medium-time period. WUE can increase consistently owing to the increasing of the CO2 fertilization if coupled with management. These results confirm also, at stand spatial scale resolution, what found globally in other recent studies and suggesting to consider for long-term period alternative forest management practices to enhance these effects in mitigating climate change.

Using Time Series of Landsat Data to Improve Understanding of Short- and Long-Term Changes to Vegetation Phenology in Response to Climate Change

NASA Astrophysics Data System (ADS)

Friedl, M. A.; Melaas, E. K.; Sulla-menashe, D. J.; Gray, J. M.

2014-12-01

Phenology, the seasonal progression of organisms through stages of dormancy, active growth, and senescence is a key regulator of ecosystem processes and is widely used as an indicator of vegetation responses to climate change. This is especially true in temperate forests, where seasonal dynamics in canopy development and senescence are tightly coupled to the climate system. Despite this, understanding of climate-phenology interactions is incomplete. A key impediment to improving this understanding is that available datasets are geographically sparse, and in most cases include relatively short time series. Remote sensing has been widely promoted as a useful tool for studies of large-scale phenology, but long-term studies from remote sensing have been limited to AVHRR data, which suffers from limitations related to its coarse spatial resolution and uncertainties in atmospheric corrections and radiometric adjustments that are used to create AVHRR time series. In this study, we used 30 years of Landsat data to quantify the nature and magnitude of long-term trends and short-term variability in the timing of spring leaf emergence and fall senescence. Our analysis focuses on temperate forest locations in the Northeastern United States that are co-located with surface meteorological observations, where we have estimated the timing of leaf emergence and leaf senescence at annual time steps using atmospherically corrected surface reflectances from Landsat TM and ETM+ imagery. Comparison of results from Landsat against ground observations demonstrates that phenological events can be reliably estimated from Landsat time series. More importantly, results from this analysis suggest two main conclusions related to the nature of climate change impacts on temperate forest phenology. First, there is clear evidence of trends towards longer growing seasons in the Landsat record. Second, interannual variability is large, with average year-to-year variability exceeding the magnitude of total changes to the growing season that have occurred over the last three decades. Based on these results we suggest that year-to-year variability in phenology, rather than long-term trends, provides the best basis for predicting future changes in temperate forest phenology in response to climate change.

Climate controls on streamflow variability in the Missouri River Basin

NASA Astrophysics Data System (ADS)

Wise, E.; Woodhouse, C. A.; McCabe, G. J., Jr.; Pederson, G. T.; St-Jacques, J. M.

2017-12-01

The Missouri River's hydroclimatic variability presents a challenge for water managers, who must balance many competing demands on the system. Water resources in the Missouri River Basin (MRB) have increasingly been challenged by the droughts and floods that have occurred over the past several decades and the potential future exacerbation of these extremes by climate change. Here, we use observed and modeled hydroclimatic data and estimated natural flow records to describe the climatic controls on streamflow in the upper and lower portions of the MRB, examine atmospheric and oceanic patterns associated with high- and low-flow years, and investigate trends in climate and streamflow over the instrumental period. Results indicate that the two main source regions for total outflow, in the uppermost and lowermost parts of the basin, are under the influence of very different sets of climatic controls. Winter precipitation, impacted by changes in zonal versus meridional flow from the Pacific Ocean, as well as spring precipitation and temperature, play a key role in surface water supply variability in the upper basin. Lower basin flow is significantly correlated with precipitation in late spring and early summer, indicative of Atlantic-influenced circulation variability affecting the flow of moisture from the Gulf of Mexico. The upper basin, with decreasing snowpack and streamflow and warming spring temperatures, will be less likely to provide important flow supplements to the lower basin in the future.

Predicting Trophic Interactions and Habitat Utilization in the California Current Ecosystem

DTIC Science & Technology

2015-09-30

spatial and temporal distribution of key marine organisms over multiple trophic levels, and (2) natural and anthropogenic variability in ecosystem...areas of climate modeling in upwelling regions (E. Curchitser), physical-biological modeling in the CCLME (J. Fiechter and C. Edwards), data...optimal growth conditions). By comparing interannual changes in fat depot against EOF modes for environmental variability (i.e., SST) and prey

Shifts in tree functional composition amplify the response of forest biomass to climate

NASA Astrophysics Data System (ADS)

Zhang, Tao; Niinemets, Ülo; Sheffield, Justin; Lichstein, Jeremy W.

2018-04-01

Forests have a key role in global ecosystems, hosting much of the world’s terrestrial biodiversity and acting as a net sink for atmospheric carbon. These and other ecosystem services that are provided by forests may be sensitive to climate change as well as climate variability on shorter time scales (for example, annual to decadal). Previous studies have documented responses of forest ecosystems to climate change and climate variability, including drought-induced increases in tree mortality rates. However, relationships between forest biomass, tree species composition and climate variability have not been quantified across a large region using systematically sampled data. Here we use systematic forest inventories from the 1980s and 2000s across the eastern USA to show that forest biomass responds to decadal-scale changes in water deficit, and that this biomass response is amplified by concurrent changes in community-mean drought tolerance, a functionally important aspect of tree species composition. The amplification of the direct effects of water stress on biomass occurs because water stress tends to induce a shift in tree species composition towards species that are more tolerant to drought but are slower growing. These results demonstrate concurrent changes in forest species composition and biomass carbon storage across a large, systematically sampled region, and highlight the potential for climate-induced changes in forest ecosystems across the world, resulting from both direct effects of climate on forest biomass and indirect effects mediated by shifts in species composition.

Shifts in tree functional composition amplify the response of forest biomass to climate.

PubMed

Zhang, Tao; Niinemets, Ülo; Sheffield, Justin; Lichstein, Jeremy W

2018-04-05

Forests have a key role in global ecosystems, hosting much of the world's terrestrial biodiversity and acting as a net sink for atmospheric carbon. These and other ecosystem services that are provided by forests may be sensitive to climate change as well as climate variability on shorter time scales (for example, annual to decadal). Previous studies have documented responses of forest ecosystems to climate change and climate variability, including drought-induced increases in tree mortality rates. However, relationships between forest biomass, tree species composition and climate variability have not been quantified across a large region using systematically sampled data. Here we use systematic forest inventories from the 1980s and 2000s across the eastern USA to show that forest biomass responds to decadal-scale changes in water deficit, and that this biomass response is amplified by concurrent changes in community-mean drought tolerance, a functionally important aspect of tree species composition. The amplification of the direct effects of water stress on biomass occurs because water stress tends to induce a shift in tree species composition towards species that are more tolerant to drought but are slower growing. These results demonstrate concurrent changes in forest species composition and biomass carbon storage across a large, systematically sampled region, and highlight the potential for climate-induced changes in forest ecosystems across the world, resulting from both direct effects of climate on forest biomass and indirect effects mediated by shifts in species composition.

1,500 Year Periodicity in Central Texas Moisture Source Variability Reconstructed from Speleothems

NASA Astrophysics Data System (ADS)

Wong, C. I.; James, E. W.; Silver, M. M.; Banner, J. L.; Musgrove, M.

2014-12-01

Delineating the climate processes governing precipitation variability in drought-prone Texas is critical for predicting and mitigating climate change effects, and requires the reconstruction of past climate beyond the instrumental record. Presently, there are few high-resolution Holocene climate records for this region, which limits the assessment of precipitation variability during a relatively stable climatic interval that comprises the closest analogue to the modern climate state. To address this, we present speleothem growth rate and δ18O records from two central Texas caves that span the mid to late Holocene, and assess hypotheses about the climate processes that can account for similarity in the timing and periodicity of variability with other regional and global records. A key finding is the independent variation of speleothem growth rate and δ18O values, suggesting the decoupling of moisture amount and source. This decoupling likely occurs because i) the often direct relation between speleothem growth rate and moisture availability is complicated by changes in the overlying ecosystem that affect subsurface CO2 production, and ii) speleothem δ18O variations reflect changes in moisture source (i.e., proportion of Pacific- vs. Gulf of Mexico-derived moisture) that appear not to be linked to moisture amount. Furthermore, we document a 1,500-year periodicity in δ18O values that is consistent with variability in the percent of hematite-stained grains in North Atlantic sediments, North Pacific SSTs, and El Nino events preserved in an Ecuadorian lake. Previous modeling experiments and analysis of observational data delineate the coupled atmospheric-ocean processes that can account for the coincidence of such variability in climate archives across the northern hemisphere. Reduction of the thermohaline circulation results in North Atlantic cooling, which translates to cooler North Pacific SSTs. The resulting reduction of the meridional SST gradient in the Pacific weakens the air-sea coupling that modulates ENSO activity, resulting in faster growth of interannual anomalies and larger mature El Niño relative to La Niña events. The asymmetrically enhanced ENSO variability can account for a greater portion of Pacific-derived moisture reflected by speleothem δ18O values.

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.

Decreasing spatial variability in precipitation extremes in southwestern China and the local/large-scale influencing factors

NASA Astrophysics Data System (ADS)

Liu, Meixian; Xu, Xianli; Sun, Alex

2015-07-01

Climate extremes can cause devastating damage to human society and ecosystems. Recent studies have drawn many conclusions about trends in climate extremes, but few have focused on quantitative analysis of their spatial variability and underlying mechanisms. By using the techniques of overlapping moving windows, the Mann-Kendall trend test, correlation, and stepwise regression, this study examined the spatial-temporal variation of precipitation extremes and investigated the potential key factors influencing this variation in southwestern (SW) China, a globally important biodiversity hot spot and climate-sensitive region. Results showed that the changing trends of precipitation extremes were not spatially uniform, but the spatial variability of these precipitation extremes decreased from 1959 to 2012. Further analysis found that atmospheric circulations rather than local factors (land cover, topographic conditions, etc.) were the main cause of such precipitation extremes. This study suggests that droughts or floods may become more homogenously widespread throughout SW China. Hence, region-wide assessments and coordination are needed to help mitigate the economic and ecological impacts.

Comparative Analysis of Upper Ocean Heat Content Variability from Ensemble Operational Ocean Analyses

NASA Technical Reports Server (NTRS)

Xue, Yan; Balmaseda, Magdalena A.; Boyer, Tim; Ferry, Nicolas; Good, Simon; Ishikawa, Ichiro; Rienecker, Michele; Rosati, Tony; Yin, Yonghong; Kumar, Arun

2012-01-01

Upper ocean heat content (HC) is one of the key indicators of climate variability on many time-scales extending from seasonal to interannual to long-term climate trends. For example, HC in the tropical Pacific provides information on thermocline anomalies that is critical for the longlead forecast skill of ENSO. Since HC variability is also associated with SST variability, a better understanding and monitoring of HC variability can help us understand and forecast SST variability associated with ENSO and other modes such as Indian Ocean Dipole (IOD), Pacific Decadal Oscillation (PDO), Tropical Atlantic Variability (TAV) and Atlantic Multidecadal Oscillation (AMO). An accurate ocean initialization of HC anomalies in coupled climate models could also contribute to skill in decadal climate prediction. Errors, and/or uncertainties, in the estimation of HC variability can be affected by many factors including uncertainties in surface forcings, ocean model biases, and deficiencies in data assimilation schemes. Changes in observing systems can also leave an imprint on the estimated variability. The availability of multiple operational ocean analyses (ORA) that are routinely produced by operational and research centers around the world provides an opportunity to assess uncertainties in HC analyses, to help identify gaps in observing systems as they impact the quality of ORAs and therefore climate model forecasts. A comparison of ORAs also gives an opportunity to identify deficiencies in data assimilation schemes, and can be used as a basis for development of real-time multi-model ensemble HC monitoring products. The OceanObs09 Conference called for an intercomparison of ORAs and use of ORAs for global ocean monitoring. As a follow up, we intercompared HC variations from ten ORAs -- two objective analyses based on in-situ data only and eight model analyses based on ocean data assimilation systems. The mean, annual cycle, interannual variability and longterm trend of HC have been analyzed

The Effects of Solar Variability on Earth's Climate: A Workshop Report

NASA Technical Reports Server (NTRS)

2012-01-01

Solar irradiance, the flux of the Sun s output directed toward Earth, is Earth s main energy source.1 The Sun itself varies on several timescales over billions of years its luminosity increases as it evolves on the main sequence toward becoming a red giant; about every 11 years its sunspot activity cycles; and within just minutes flares can erupt and release massive amounts of energy. Most of the fluctuations from tens to thousands of years are associated with changes in the solar magnetic field. The focus of the National Research Council's September 2011 workshop on solar variability and Earth's climate, and of this summary report, is mainly magnetically driven variability and its possible connection with Earth's climate variations in the past 10,000 years. Even small variations in the amount or distribution of energy received at Earth can have a major influence on Earth's climate when they persist for decades. However, no satellite measurements have indicated that solar output and variability have contributed in a significant way to the increase in global mean temperature in the last 50 years. Locally, however, correlations between solar activity and variations in average weather may stand out beyond the global trend; such has been argued to be the case for the El Nino-Southern Oscillation, even in the present day. A key area of inquiry deals with establishing a unified record of the solar output and solar-modified particles that extends from the present to the prescientific past. The workshop focused attention on the need for a better understanding of the links between indices of solar activity such as cosmogenic isotopes and solar irradiance. A number of presentations focused on the timescale of the solar cycle and of the satellite record, and on the problem of extending this record back in time. Highlights included a report of progress on pyroheliometer calibration, leading to greater confidence in the time history and future stability of total solar irradiance (TSI), and surprising results on changes in spectral irradiance over the last solar cycle, which elicited spirited discussion. New perspectives on connections between features of the quiet and active areas of the photosphere and variations in TSI were also presented, emphasizing the importance of developing better understanding in order to extrapolate back in time using activity indices. Workshop participants reviews highlighted difficulties as well as causes for optimism in current understanding of the cosmogenic isotope record and the use of observed variability in Sun-like stars in reconstructing variations in TSI occurring on lower frequencies than the sunspot cycle. The workshop succeeded in bringing together informed, focused presentations on major drivers of the Sun-climate connection. The importance of the solar cycle as a unique quasi-periodic probe of climate responses on a timescale between the seasonal and Milankovitch cycles was recognized in several presentations. The signal need only be detectable, not dominant, for it to play this role of a useful probe. Some workshop participants also found encouraging progress in the top-down perspective, according to which solar variability affects surface climate by first perturbing the stratosphere, which then forces the troposphere and surface. This work is now informing and being informed by research on tropospheric responses to the Antarctic ozone hole and volcanic aerosols. In contrast to the top-down perspective is the bottom-up view that the interaction of solar energy with the ocean and surface leads to changes in dynamics and temperature. During the discussion of how dynamical air-sea coupling in the tropical Pacific and solar variability interact from a bottom-up perspective, several participants remarked on the wealth of open research questions in the dynamics of the climatic response to TSI and spectral variability. The discussion of the paleoclimate record emphasized that the link between solar varbility and Earth s climate is multifaceted and that some components are understood better than others. According to two presenters on paleoclimate, there is a need to study the idiosyncrasies of each key proxy record. Yet they also emphasized that there may be an emerging pattern of paleoclimate change coincident with periods of solar activity and inactivity, but only on long timescales of multiple decades to millennia. Several speakers discussed the effects of particle events and cosmic-ray variability. These are all areas of exciting fundamental research; however, they have not yet led to conclusive evidence for significant related climate effects. The key problem of attribution of climate variability on the timescales of the Little Ice Age and the Maunder Minimum were directly addressed in several presentations. Several workshop participants remarked that the combination of solar, paleoclimatic, and climate modeling research has the potential to dramatically improve the credibility of these attribution studies.

Dengue: recent past and future threats

PubMed Central

Rogers, David J.

2015-01-01

This article explores four key questions about statistical models developed to describe the recent past and future of vector-borne diseases, with special emphasis on dengue: (1) How many variables should be used to make predictions about the future of vector-borne diseases?(2) Is the spatial resolution of a climate dataset an important determinant of model accuracy?(3) Does inclusion of the future distributions of vectors affect predictions of the futures of the diseases they transmit?(4) Which are the key predictor variables involved in determining the distributions of vector-borne diseases in the present and future?Examples are given of dengue models using one, five or 10 meteorological variables and at spatial resolutions of from one-sixth to two degrees. Model accuracy is improved with a greater number of descriptor variables, but is surprisingly unaffected by the spatial resolution of the data. Dengue models with a reduced set of climate variables derived from the HadCM3 global circulation model predictions for the 1980s are improved when risk maps for dengue's two main vectors (Aedes aegypti and Aedes albopictus) are also included as predictor variables; disease and vector models are projected into the future using the global circulation model predictions for the 2020s, 2040s and 2080s. The Garthwaite–Koch corr-max transformation is presented as a novel way of showing the relative contribution of each of the input predictor variables to the map predictions. PMID:25688021

Ecosystem response to climatic variables - air temperature and precipitation: How can these variables alter plant productions in C4-grass dominant ecosystem?

NASA Astrophysics Data System (ADS)

Jung, C. G.; Jiang, L.; Luo, Y.

2017-12-01

Understanding net primary production (NPP) response to the key climatic variables, temperature and precipitation, is essential since the response could be represented by one of future consequences from ecosystem responses. Under future climatic warming, fluctuating precipitation is expected. In addition, NPP solely could not explain whole ecosystem response; therefore, not only NPP, but also above- and below-ground NPP (ANPP and BNPP, respectively) need to be examined. This examination needs to include how the plant productions response along temperature and precipitation gradients. Several studies have examined the response of NPP against each of single climatic variable, but understanding the response of ANPP and BNPP to the multiple variables is notably poor. In this study, we used the plant productions data (NPP, ANPP, and BNPP) with climatic variables, i.e., air temperature and precipitation, from 1999 to 2015 under warming and clipping treatments (mimicking hay-harvesting) in C4-grass dominant ecosystem located in central Oklahoma, United States. Firstly, we examined the nonlinear relationships with the climatic variables for NPP, ANPP and BNPP; and then predicted possible responses in the temperature - precipitation space by using a linear mixed effect model. Nonlinearities of NPP, ANPP and BNPP to the climatic variables have been found to show unimodal curves, and nonlinear models have better goodness of fit as shown lower Akaike information criterion (AIC) than linear models. Optimum condition for NPP is represented at high temperature and precipitation level whereas BNPP is maximized at moderate precipitation levels while ANPP has same range of NPP's optimum condition. Clipping significantly reduced ANPP while there was no clipping effect on NPP and BNPP. Furthermore, inclining NPP and ANPP have shown in a range from moderate to high precipitation level with increasing temperature while inclining pattern for BNPP was observed in moderate precipitation level. Overall, the C4-grass dominant ecosystem has a potential for considerable increases in NPP in hotter and wetter conditions as shown a range from moderate to high temperature and precipitation levels; ANPP has peaked at the high temperature and precipitation level, but maximum BNPP needs moderate precipitation level and high temperature.

Adaptation to Climatic Hazards in the Savannah Ecosystem: Improving Adaptation Policy and Action

NASA Astrophysics Data System (ADS)

Yiran, Gerald A. B.; Stringer, Lindsay C.

2017-10-01

People in Ghana's savannah ecosystem have historically experienced a range of climatic hazards that have affected their livelihoods. In view of current climate variability and change, and projected increases in extreme events, adaptation to climate risks is vital. Policies have been put in place to enhance adaptation across sub-Saharan Africa in accordance with international agreements. At the same time, local people, through experience, have learned to adapt. This paper examines current policy actions and their implementation alongside an assessment of barriers to local adaptation. In doing so it links adaptation policy and practice. Policy documents were analysed that covered key livelihood sectors, which were identified as climate sensitive. These included agriculture, water, housing and health policies, as well as the National Climate Change Policy. In-depth interviews and focus group discussions were also held with key stakeholders in the Upper East Region of Ghana. Analyses were carried using thematic content analysis. Although policies and actions complement each other, their integration is weak. Financial, institutional, social, and technological barriers hinder successful local implementation of some policy actions, while lack of local involvement in policy formulation also hinders adaptation practice. Integration of local perspectives into policy needs to be strengthened in order to enhance adaptation. Coupled with this is a need to consider adaptation to climate change in development policies and to pursue efforts to reduce or remove the key barriers to implementation at the local level.

The impacts of climate change in coastal marine systems.

PubMed

Harley, Christopher D G; Randall Hughes, A; Hultgren, Kristin M; Miner, Benjamin G; Sorte, Cascade J B; Thornber, Carol S; Rodriguez, Laura F; Tomanek, Lars; Williams, Susan L

2006-02-01

Anthropogenically induced global climate change has profound implications for marine ecosystems and the economic and social systems that depend upon them. The relationship between temperature and individual performance is reasonably well understood, and much climate-related research has focused on potential shifts in distribution and abundance driven directly by temperature. However, recent work has revealed that both abiotic changes and biological responses in the ocean will be substantially more complex. For example, changes in ocean chemistry may be more important than changes in temperature for the performance and survival of many organisms. Ocean circulation, which drives larval transport, will also change, with important consequences for population dynamics. Furthermore, climatic impacts on one or a few 'leverage species' may result in sweeping community-level changes. Finally, synergistic effects between climate and other anthropogenic variables, particularly fishing pressure, will likely exacerbate climate-induced changes. Efforts to manage and conserve living marine systems in the face of climate change will require improvements to the existing predictive framework. Key directions for future research include identifying key demographic transitions that influence population dynamics, predicting changes in the community-level impacts of ecologically dominant species, incorporating populations' ability to evolve (adapt), and understanding the scales over which climate will change and living systems will respond.

Developing Health-Related Indicators of Climate Change: Australian Stakeholder Perspectives.

PubMed

Navi, Maryam; Hansen, Alana; Nitschke, Monika; Hanson-Easey, Scott; Pisaniello, Dino

2017-05-22

Climate-related health indicators are potentially useful for tracking and predicting the adverse public health effects of climate change, identifying vulnerable populations, and monitoring interventions. However, there is a need to understand stakeholders' perspectives on the identification, development, and utility of such indicators. A qualitative approach was used, comprising semi-structured interviews with key informants and service providers from government and non-government stakeholder organizations in South Australia. Stakeholders saw a need for indicators that could enable the monitoring of health impacts and time trends, vulnerability to climate change, and those which could also be used as communication tools. Four key criteria for utility were identified, namely robust and credible indicators, specificity, data availability, and being able to be spatially represented. The variability of risk factors in different regions, lack of resources, and data and methodological issues were identified as the main barriers to indicator development. This study demonstrates a high level of stakeholder awareness of the health impacts of climate change, and the need for indicators that can inform policy makers regarding interventions.

Climate Benchmark Missions: CLARREO

NASA Technical Reports Server (NTRS)

Wielicki, Bruce A.; Young, David F.

2010-01-01

CLARREO (Climate Absolute Radiance and Refractivity Observatory) is one of the four Tier 1 missions recommended by the recent NRC decadal survey report on Earth Science and Applications from Space (NRC, 2007). The CLARREO mission addresses the need to rigorously observe climate change on decade time scales and to use decadal change observations as the most critical method to determine the accuracy of climate change projections such as those used in the Fourth Assessment Report of the Intergovernmental Panel on Climate Change (IPCC AR4). A rigorously known accuracy of both decadal change observations as well as climate projections is critical in order to enable sound policy decisions. The CLARREO mission accomplishes this critical objective through highly accurate and SI traceable decadal change observations sensitive to many of the key uncertainties in climate radiative forcings, responses, and feedbacks that in turn drive uncertainty in current climate model projections. The same uncertainties also lead to uncertainty in attribution of climate change to anthropogenic forcing. The CLARREO breakthrough in decadal climate change observations is to achieve the required levels of accuracy and traceability to SI standards for a set of observations sensitive to a wide range of key decadal change variables. These accuracy levels are determined both by the projected decadal changes as well as by the background natural variability that such signals must be detected against. The accuracy for decadal change traceability to SI standards includes uncertainties of calibration, sampling, and analysis methods. Unlike most other missions, all of the CLARREO requirements are judged not by instantaneous accuracy, but instead by accuracy in large time/space scale average decadal changes. Given the focus on decadal climate change, the NRC Decadal Survey concluded that the single most critical issue for decadal change observations was their lack of accuracy and low confidence in observing the small but critical climate change signals. CLARREO is the recommended attack on this challenge, and builds on the last decade of climate observation advances in the Earth Observing System as well as metrological advances at NIST (National Institute of Standards and Technology) and other standards laboratories.

Refractory periods and climate forcing in cholera dynamics.

PubMed

Koelle, Katia; Rodó, Xavier; Pascual, Mercedes; Yunus, Md; Mostafa, Golam

2005-08-04

Outbreaks of many infectious diseases, including cholera, malaria and dengue, vary over characteristic periods longer than 1 year. Evidence that climate variability drives these interannual cycles has been highly controversial, chiefly because it is difficult to isolate the contribution of environmental forcing while taking into account nonlinear epidemiological dynamics generated by mechanisms such as host immunity. Here we show that a critical interplay of environmental forcing, specifically climate variability, and temporary immunity explains the interannual disease cycles present in a four-decade cholera time series from Matlab, Bangladesh. We reconstruct the transmission rate, the key epidemiological parameter affected by extrinsic forcing, over time for the predominant strain (El Tor) with a nonlinear population model that permits a contributing effect of intrinsic immunity. Transmission shows clear interannual variability with a strong correspondence to climate patterns at long periods (over 7 years, for monsoon rains and Brahmaputra river discharge) and at shorter periods (under 7 years, for flood extent in Bangladesh, sea surface temperatures in the Bay of Bengal and the El Niño-Southern Oscillation). The importance of the interplay between extrinsic and intrinsic factors in determining disease dynamics is illustrated during refractory periods, when population susceptibility levels are low as the result of immunity and the size of cholera outbreaks only weakly reflects climate forcing.

Challenges of coordinating global climate observations - Role of satellites in climate monitoring

NASA Astrophysics Data System (ADS)

Richter, C.

2017-12-01

Global observation of the Earth's atmosphere, ocean and land is essential for identifying climate variability and change, and for understanding their causes. Observation also provides data that are fundamental for evaluating, refining and initializing the models that predict how the climate system will vary over the months and seasons ahead, and that project how climate will change in the longer term under different assumptions concerning greenhouse gas emissions and other human influences. Long-term observational records have enabled the Intergovernmental Panel on Climate Change to deliver the message that warming of the global climate system is unequivocal. As the Earth's climate enters a new era, in which it is forced by human activities, as well as natural processes, it is critically important to sustain an observing system capable of detecting and documenting global climate variability and change over long periods of time. High-quality climate observations are required to assess the present state of the ocean, cryosphere, atmosphere and land and place them in context with the past. The global observing system for climate is not a single, centrally managed observing system. Rather, it is a composite "system of systems" comprising a set of climate-relevant observing, data-management, product-generation and data-distribution systems. Data from satellites underpin many of the Essential Climate Variables(ECVs), and their historic and contemporary archives are a key part of the global climate observing system. In general, the ECVs will be provided in the form of climate data records that are created by processing and archiving time series of satellite and in situ measurements. Early satellite data records are very valuable because they provide unique observations in many regions which were not otherwise observed during the 1970s and which can be assimilated in atmospheric reanalyses and so extend the satellite climate data records back in time.

The impact of climate change on the characteristics of the frost-free season over the contiguous USA as projected by the NARCCAP model ensembles

Treesearch

Shiyuan Zhong; Lejiang Yu; Julie A. Winkler; Ying Tang; Warren E. Heilman; Xiandi. Bian

2017-01-01

Understanding the impacts of climate change on frost-free seasons is key to designing effective adaptation strategies for ecosystem management and agricultural production. This study examines the potential changes in the frost-free season length between historical (1971−2000) and future (2041−2070) periods over the contiguous USA with a focus on spatial variability and...

Classification and Feature Selection Algorithms for Modeling Ice Storm Climatology

NASA Astrophysics Data System (ADS)

Swaminathan, R.; Sridharan, M.; Hayhoe, K.; Dobbie, G.

2015-12-01

Ice storms account for billions of dollars of winter storm loss across the continental US and Canada. In the future, increasing concentration of human populations in areas vulnerable to ice storms such as the northeastern US will only exacerbate the impacts of these extreme events on infrastructure and society. Quantifying the potential impacts of global climate change on ice storm prevalence and frequency is challenging, as ice storm climatology is driven by complex and incompletely defined atmospheric processes, processes that are in turn influenced by a changing climate. This makes the underlying atmospheric and computational modeling of ice storm climatology a formidable task. We propose a novel computational framework that uses sophisticated stochastic classification and feature selection algorithms to model ice storm climatology and quantify storm occurrences from both reanalysis and global climate model outputs. The framework is based on an objective identification of ice storm events by key variables derived from vertical profiles of temperature, humidity and geopotential height. Historical ice storm records are used to identify days with synoptic-scale upper air and surface conditions associated with ice storms. Evaluation using NARR reanalysis and historical ice storm records corresponding to the northeastern US demonstrates that an objective computational model with standard performance measures, with a relatively high degree of accuracy, identify ice storm events based on upper-air circulation patterns and provide insights into the relationships between key climate variables associated with ice storms.

The GCOS Reference Upper-Air Network (GRUAN)

NASA Astrophysics Data System (ADS)

Vömel, H.; Berger, F. H.; Immler, F. J.; Seidel, D.; Thorne, P.

2009-04-01

While the global upper-air observing network has provided useful observations for operational weather forecasting for decades, its measurements lack the accuracy and long-term continuity needed for understanding climate change. Consequently, the scientific community faces uncertainty on such key issues as the trends of temperature in the upper troposphere and stratosphere or the variability and trends of stratospheric water vapour. To address these shortcomings, and to ensure that future climate records will be more useful than the records to date, the Global Climate Observing System (GCOS) program initiated the GCOS Reference Upper Air Network (GRUAN). GRUAN will be a network of about 30-40 observatories with a representative sampling of geographic regions and surface types. These stations will provide upper-air reference observations of the essential climate variables, i.e. temperature, geopotential, humidity, wind, radiation and cloud properties using specialized radiosondes and complementary remote sensing profiling instrumentation. Long-term stability, quality assurance / quality control, and a detailed assessment of measurement uncertainties will be the key aspects of GRUAN observations. The network will not be globally complete but will serve to constrain and adjust data from more spatially comprehensive global observing systems including satellites and the current radiosonde networks. This paper outlines the scientific rationale for GRUAN, its role in the Global Earth Observation System of Systems, network requirements and likely instrumentation, management structure, current status and future plans.

Projected 2050 Model Simulations for the Chesapeake Bay Program

EPA Science Inventory

The Chesapeake Bay Program as has been tasked with assessing how changes in climate systems are expected to alter key variables and processes within the Watershed in concurrence with land use changes. EPA’s Office of Research and Development will be conducting historic and...

Solving the Global Climate Monitoring Problem in the Atmosphere: Towards SI-tied Climate Records with Integrated Uncertainty Propagation

NASA Astrophysics Data System (ADS)

Kirchengast, G.; Schwaerz, M.; Fritzer, J.; Schwarz, J.; Scherllin-Pirscher, B.; Steiner, A. K.

2013-12-01

Monitoring the atmosphere to gain accurate and long-term stable records of essential climate variables (ECVs) such as temperature and greenhouse gases is the backbone of contemporary atmospheric and climate science. Earth observation from space is the key to obtain such data globally in the atmosphere. Currently, however, not any existing satellite-based atmospheric ECV record can serve as authoritative benchmark over months to decades so that climate variability and change in the atmosphere are not yet reliably monitored. Radio occultation (RO) using Global Navigation Satellite System (GNSS) signals provides a unique opportunity to solve this problem in the free atmosphere (from ~1-2 km altitude upwards) for core ECVs: the thermodynamic variables temperature and pressure, and to some degree water vapor, which are key parameters for tracking climate change. On top of RO we have recently conceived next-generation methods, microwave and infrared-laser occultation and nadir-looking infrared-laser reflectometry. These can monitor a full set of thermo-dynamic ECVs (incl. wind) as well as the greenhouse gases such as carbon dioxide and methane as main drivers of climate change; for the latter we also target the boundary layer for tracking carbon sources and sinks. We briefly introduce to why the atmospheric climate monitoring challenge is unsolved so far and why just the above methods have the capabilities to break through. We then focus on RO, which already provided more than a decade of observations. RO accurately measures time delays from refraction of GNSS signals during atmospheric occultation events. This enables to tie RO-derived ECVs and their uncertainty to fundamental time standards, effectively the SI second, and to their unique long-term stability and narrow uncertainty. However, despite impressive advances since the pioneering RO mission GPS/Met in the mid-1990ties no rigorous trace from fundamental time to the ECVs (duly accounting also for relevant side influences) exists so far. Establishing such a trace first-time in form of the Reference Occultation Processing System rOPS, providing reference RO data for climate science and applications, is therefore a current cornerstone endeavor at the Wegener Center over 2011 to 2015, supported also by colleagues from other key groups at EUMETSAT Darmstadt, UCAR Boulder, DMI Copenhagen, ECMWF Reading, IAP Moscow, AIUB Berne, and RMIT Melbourne. With the rOPS we undertake to process the full chain from the SI-tied raw data to the atmospheric ECVs with integrated uncertainty propagation. We summarize where we currently stand in quantifying RO accuracy and long-term stability and then discuss the concept, development status and initial results from the rOPS, with emphasis on its novel capability to provide SI-tied reference data with integrated uncertainty estimation. We comment how these data can provide ground-breaking support to challenges such as climate model evaluation, anthropogenic change detection and attribution, and calibration of complementary climate observing systems.

A Fiji multi-coral δ18O composite approach to obtaining a more accurate reconstruction of the last two-centuries of the ocean-climate variability in the South Pacific Convergence Zone region

NASA Astrophysics Data System (ADS)

Dassié, Emilie P.; Linsley, Braddock K.; Corrège, Thierry; Wu, Henry C.; Lemley, Gavin M.; Howe, Steve; Cabioch, Guy

2014-12-01

The limited availability of oceanographic data in the tropical Pacific Ocean prior to the satellite era makes coral-based climate reconstructions a key tool for extending the instrumental record back in time, thereby providing a much needed test for climate models and projections. We have generated a unique regional network consisting of five Porites coral δ18O time series from different locations in the Fijian archipelago. Our results indicate that using a minimum of three Porites coral δ18O records from Fiji is statistically sufficient to obtain a reliable signal for climate reconstruction, and that application of an approach used in tree ring studies is a suitable tool to determine this number. The coral δ18O composite indicates that while sea surface temperature (SST) variability is the primary driver of seasonal δ18O variability in these Fiji corals, annual average coral δ18O is more closely correlated to sea surface salinity (SSS) as previously reported. Our results highlight the importance of water mass advection in controlling Fiji coral δ18O and salinity variability at interannual and decadal time scales despite being located in the heavy rainfall region of the South Pacific Convergence Zone (SPCZ). The Fiji δ18O composite presents a secular freshening and warming trend since the 1850s coupled with changes in both interannual (IA) and decadal/interdecadal (D/I) variance. The changes in IA and D/I variance suggest a re-organization of climatic variability in the SPCZ region beginning in the late 1800s to period of a more dominant interannual variability, which could correspond to a southeast expansion of the SPCZ.

Modelling interactions between mitigation, adaptation and sustainable development

NASA Astrophysics Data System (ADS)

Reusser, D. E.; Siabatto, F. A. P.; Garcia Cantu Ros, A.; Pape, C.; Lissner, T.; Kropp, J. P.

2012-04-01

Managing the interdependence of climate mitigation, adaptation and sustainable development requires a good understanding of the dominant socioecological processes that have determined the pathways in the past. Key variables include water and food availability which depend on climate and overall ecosystem services, as well as energy supply and social, political and economic conditions. We present our initial steps to build a system dynamic model of nations that represents a minimal set of relevant variables of the socio- ecological development. The ultimate goal of the modelling exercise is to derive possible future scenarios and test those for their compatibility with sustainability boundaries. Where dynamics go beyond sustainability boundaries intervention points in the dynamics can be searched.

Linking the climatic and geochemical controls on global soil carbon cycling

NASA Astrophysics Data System (ADS)

Doetterl, Sebastian; Stevens, Antoine; Six, Johan; Merckx, Roel; Van Oost, Kristof; Casanova Pinto, Manuel; Casanova-Katny, Angélica; Muñoz, Cristina; Boudin, Mathieu; Zagal Venegas, Erick; Boeckx, Pascal

2015-04-01

Climatic and geochemical parameters are regarded as the primary controls for soil organic carbon (SOC) storage and turnover. However, due to the difference in scale between climate and geochemical-related soil research, the interaction of these key factors for SOC dynamics have rarely been assessed. Across a large geochemical and climatic transect in similar biomes in Chile and the Antarctic Peninsula we show how abiotic geochemical soil features describing soil mineralogy and weathering pose a direct control on SOC stocks, concentration and turnover and are central to explaining soil C dynamics at larger scales. Precipitation and temperature had an only indirect control by regulating geochemistry. Soils with high SOC content have low specific potential CO2 respiration rates, but a large fraction of SOC that is stabilized via organo-mineral interactions. The opposite was observed for soils with low SOC content. The observed differences for topsoil SOC stocks along this transect of similar biomes but differing geo-climatic site conditions are of the same magnitude as differences observed for topsoil SOC stocks across all major global biomes. Using precipitation and a set of abiotic geochemical parameters describing soil mineralogy and weathering status led to predictions of high accuracy (R2 0.53-0.94) for different C response variables. Partial correlation analyses revealed that the strength of the correlation between climatic predictors and SOC response variables decreased by 51 - 83% when controlling for geochemical predictors. In contrast, controlling for climatic variables did not result in a strong decrease in the strength of the correlations of between most geochemical variables and SOC response variables. In summary, geochemical parameters describing soil mineralogy and weathering were found to be essential for accurate predictions of SOC stocks and potential CO2 respiration, while climatic factors were of minor importance as a direct control, but are important through governing soil weathering and geochemistry. In conclusion, we pledge for a stronger implementation of geochemical soil properties to predict SOC stocks on a global scale. Understanding the effects of climate (temperature and precipitation) change on SOC dynamics also requires good understanding of the relationship between climate and soil geochemistry.

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.

Relating adaptive genetic traits to climate for Sandberg bluegrass from the intermountain western United States.

PubMed

Johnson, Richard C; Horning, Matthew E; Espeland, Erin K; Vance-Borland, Ken

2015-02-01

Genetic variation for potentially adaptive traits of the key restoration species Sandberg bluegrass (Poa secunda J. Presl) was assessed over the intermountain western United States in relation to source population climate. Common gardens were established at two intermountain west sites with progeny from two maternal parents from each of 130 wild populations. Data were collected over 2 years at each site on fifteen plant traits associated with production, phenology, and morphology. Analyses of variance revealed strong population differences for all plant traits (P < 0.0001), indicating genetic variation. Both the canonical correlation and linear correlation established associations between source populations and climate variability. Populations from warmer, more arid climates had generally lower dry weight, earlier phenology, and smaller, narrower leaves than those from cooler, moister climates. The first three canonical variates were regressed with climate variables resulting in significant models (P < 0.0001) used to map 12 seed zones. Of the 700 981 km(2) mapped, four seed zones represented 92% of the area in typically semi-arid and arid regions. The association of genetic variation with source climates in the intermountain west suggested climate driven natural selection and evolution. We recommend seed transfer zones and population movement guidelines to enhance adaptation and diversity for large-scale restoration projects.

Measurement and structural relations of an authoritative school climate model: A multi-level latent variable investigation.

PubMed

Konold, Timothy R; Cornell, Dewey

2015-12-01

This study tested a conceptual model of school climate in which two key elements of an authoritative school, structure and support variables, are associated with student engagement in school and lower levels of peer aggression. Multilevel multivariate structural modeling was conducted in a statewide sample of 48,027 students in 323 public high schools who completed the Authoritative School Climate Survey. As hypothesized, two measures of structure (Disciplinary Structure and Academic Expectations) and two measures of support (Respect for Students and Willingness to Seek Help) were associated with higher student engagement (Affective Engagement and Cognitive Engagement) and lower peer aggression (Prevalence of Teasing and Bullying) on both student and school levels of analysis, controlling for the effects of school demographics (school size, percentage of minority students, and percentage of low income students). These results support the extension of authoritative school climate model to high school and guide further research on the conditions for a positive school climate. Copyright © 2015 Society for the Study of School Psychology. Published by Elsevier Ltd. All rights reserved.

Analyses of historical and projected climates to support climate adaptation in the northern Rocky Mountains: Chapter 4

USGS Publications Warehouse

Gross, John E.; Tercek, Michael; Guay, Kevin; Chang, Tony; Talbert, Marian; Rodman, Ann; Thoma, David; Jantz, Patrick; Morisette, Jeffrey T.

2016-01-01

Most of the western United States is experiencing the effects of rapid and directional climate change (Garfin et al. 2013). These effects, along with forecasts of profound changes in the future, provide strong motivation for resource managers to learn about and prepare for future changes. Climate adaptation plans are based on an understanding of historic climate variation and their effects on ecosystems and on forecasts of future climate trends. Frameworks for climate adaptation thus universally identify the importance of a summary of historical, current, and projected climates (Glick, Stein, and Edelson 2011; Cross et al. 2013; Stein et al. 2014). Trends in physical climate variables are usually the basis for evaluating the exposure component in vulnerability assessments. Thus, this chapter focuses on step 2 of the Climate-Smart Conservation framework (chap. 2): vulnerability assessment. We present analyses of historical and current observations of temperature, precipitation, and other key climate measurements to provide context and a baseline for interpreting the ecological impacts of projected climate changes.

Lessons Learned on Health Adaptation to Climate Variability and Change: Experiences Across Low- and Middle-Income Countries

PubMed Central

Otmani del Barrio, Mariam

2017-01-01

Background: There is limited published evidence of the effectiveness of adaptation in managing the health risks of climate variability and change in low- and middle-income countries. Objectives: To document lessons learned and good practice examples from health adaptation pilot projects in low- and middle-income countries to facilitate assessing and overcoming barriers to implementation and to scaling up. Methods: We evaluated project reports and related materials from the first five years of implementation (2008–2013) of multinational health adaptation projects in Albania, Barbados, Bhutan, China, Fiji, Jordan, Kazakhstan, Kenya, Kyrgyzstan, Philippines, Russian Federation, Tajikistan, and Uzbekistan. We also collected qualitative data through a focus group consultation and 19 key informant interviews. Results: Our recommendations include that national health plans, policies, and budget processes need to explicitly incorporate the risks of current and projected climate variability and change. Increasing resilience is likely to be achieved through longer-term, multifaceted, and collaborative approaches, with supporting activities (and funding) for capacity building, communication, and institutionalized monitoring and evaluation. Projects should be encouraged to focus not just on shorter-term outputs to address climate variability, but also on establishing processes to address longer-term climate change challenges. Opportunities for capacity development should be created, identified, and reinforced. Conclusions: Our analyses highlight that, irrespective of resource constraints, ministries of health and other institutions working on climate-related health issues in low- and middle-income countries need to continue to prepare themselves to prevent additional health burdens in the context of a changing climate and socioeconomic development patterns. https://doi.org/10.1289/EHP405 PMID:28632491

The U.S. Geological Survey Monthly Water Balance Model Futures Portal

USGS Publications Warehouse

Bock, Andy

2017-03-16

Simulations of future climate suggest profiles of temperature and precipitation may differ significantly from those in the past. These changes in climate will likely lead to changes in the hydrologic cycle. As such, natural resource managers are in need of tools that can provide estimates of key components of the hydrologic cycle, uncertainty associated with the estimates, and limitations associated with the climate forcing data used to estimate these components. To help address this need, the U.S. Geological Survey Monthly Water Balance Model Futures Portal (https://my.usgs.gov/mows/) provides a user friendly interface to deliver hydrologic and meteorological variables for monthly historic and potential future climatic conditions across the continental United States.

VEMAP Phase 2 bioclimatic database. I. Gridded historical (20th century) climate for modeling ecosystem dynamics across the conterminous USA

USGS Publications Warehouse

Kittel, T.G.F.; Rosenbloom, N.A.; Royle, J. Andrew; Daly, Christopher; Gibson, W.P.; Fisher, H.H.; Thornton, P.; Yates, D.N.; Aulenbach, S.; Kaufman, C.; McKeown, R.; Bachelet, D.; Schimel, D.S.; Neilson, R.; Lenihan, J.; Drapek, R.; Ojima, D.S.; Parton, W.J.; Melillo, J.M.; Kicklighter, D.W.; Tian, H.; McGuire, A.D.; Sykes, M.T.; Smith, B.; Cowling, S.; Hickler, T.; Prentice, I.C.; Running, S.; Hibbard, K.A.; Post, W.M.; King, A.W.; Smith, T.; Rizzo, B.; Woodward, F.I.

2004-01-01

Analysis and simulation of biospheric responses to historical forcing require surface climate data that capture those aspects of climate that control ecological processes, including key spatial gradients and modes of temporal variability. We developed a multivariate, gridded historical climate dataset for the conterminous USA as a common input database for the Vegetation/Ecosystem Modeling and Analysis Project (VEMAP), a biogeochemical and dynamic vegetation model intercomparison. The dataset covers the period 1895-1993 on a 0.5?? latitude/longitude grid. Climate is represented at both monthly and daily timesteps. Variables are: precipitation, mininimum and maximum temperature, total incident solar radiation, daylight-period irradiance, vapor pressure, and daylight-period relative humidity. The dataset was derived from US Historical Climate Network (HCN), cooperative network, and snowpack telemetry (SNOTEL) monthly precipitation and mean minimum and maximum temperature station data. We employed techniques that rely on geostatistical and physical relationships to create the temporally and spatially complete dataset. We developed a local kriging prediction model to infill discontinuous and limited-length station records based on spatial autocorrelation structure of climate anomalies. A spatial interpolation model (PRISM) that accounts for physiographic controls was used to grid the infilled monthly station data. We implemented a stochastic weather generator (modified WGEN) to disaggregate the gridded monthly series to dailies. Radiation and humidity variables were estimated from the dailies using a physically-based empirical surface climate model (MTCLIM3). Derived datasets include a 100 yr model spin-up climate and a historical Palmer Drought Severity Index (PDSI) dataset. The VEMAP dataset exhibits statistically significant trends in temperature, precipitation, solar radiation, vapor pressure, and PDSI for US National Assessment regions. The historical climate and companion datasets are available online at data archive centers. ?? Inter-Research 2004.

Detection and Attribution of Anthropogenic Climate Change Impacts

NASA Technical Reports Server (NTRS)

Rosenzweig, Cynthia; Neofotis, Peter

2013-01-01

Human-influenced climate change is an observed phenomenon affecting physical and biological systems across the globe. The majority of observed impacts are related to temperature changes and are located in the northern high- and midlatitudes. However, new evidence is emerging that demonstrates that impacts are related to precipitation changes as well as temperature, and that climate change is impacting systems and sectors beyond the Northern Hemisphere. In this paper, we highlight some of this new evidence-focusing on regions and sectors that the Intergovernmental Panel on Climate Change Fourth Assessment Report (IPCC AR4) noted as under-represented-in the context of observed climate change impacts, direct and indirect drivers of change (including carbon dioxide itself), and methods of detection. We also present methods and studies attributing observed impacts to anthropogenic forcing. We argue that the expansion of methods of detection (in terms of a broader array of climate variables and data sources, inclusion of the major modes of climate variability, and incorporation of other drivers of change) is key to discerning the climate sensitivities of sectors and systems in regions where the impacts of climate change currently remain elusive. Attributing such changes to human forcing of the climate system, where possible, is important for development of effective mitigation and adaptation. Current challenges in documenting adaptation and the role of indigenous knowledge in detection and attribution are described.

Interannual variation of carbon fluxes from three contrasting evergreen forests: the role of forest dynamics and climate.

PubMed

Sierra, Carlos A; Loescher, Henry W; Harmon, Mark E; Richardson, Andrew D; Hollinger, David Y; Perakis, Steven S

2009-10-01

Interannual variation of carbon fluxes can be attributed to a number of biotic and abiotic controls that operate at different spatial and temporal scales. Type and frequency of disturbance, forest dynamics, and climate regimes are important sources of variability. Assessing the variability of carbon fluxes from these specific sources can enhance the interpretation of past and current observations. Being able to separate the variability caused by forest dynamics from that induced by climate will also give us the ability to determine if the current observed carbon fluxes are within an expected range or whether the ecosystem is undergoing unexpected change. Sources of interannual variation in ecosystem carbon fluxes from three evergreen ecosystems, a tropical, a temperate coniferous, and a boreal forest, were explored using the simulation model STANDCARB. We identified key processes that introduced variation in annual fluxes, but their relative importance differed among the ecosystems studied. In the tropical site, intrinsic forest dynamics contributed approximately 30% of the total variation in annual carbon fluxes. In the temperate and boreal sites, where many forest processes occur over longer temporal scales than those at the tropical site, climate controlled more of the variation among annual fluxes. These results suggest that climate-related variability affects the rates of carbon exchange differently among sites. Simulations in which temperature, precipitation, and radiation varied from year to year (based on historical records of climate variation) had less net carbon stores than simulations in which these variables were held constant (based on historical records of monthly average climate), a result caused by the functional relationship between temperature and respiration. This suggests that, under a more variable temperature regime, large respiratory pulses may become more frequent and high enough to cause a reduction in ecosystem carbon stores. Our results also show that the variation of annual carbon fluxes poses an important challenge in our ability to determine whether an ecosystem is a source, a sink, or is neutral in regard to CO2 at longer timescales. In simulations where climate change negatively affected ecosystem carbon stores, there was a 20% chance of committing Type II error, even with 20 years of sequential data.

Investigating annually-resovled natural climate variability during MIS 11 using lacustrine records

NASA Astrophysics Data System (ADS)

Tye, G. J.; Palmer, A. P.; Candy, I.; Coxon, P.; Hardiman, M.

2012-04-01

Marine isotope stage 11 (MIS 11, ca 410,000 yrs BP) is considered to be one of the best analogues for current and future climate change due to the similarity of orbital forcing patterns during these two interglacials. Marine and ice-core records suggest that MIS 11 was a particularly long interglacial, characterised by stable climates. The investigation of high-resolution climate records from MIS 11 can, therefore, allow us to understand how the climate of a Holocene-like interglacial might evolve in the absence of anthropogenic modification. MIS 11 sediments preserved in the palaeolake basin at Marks Tey, eastern England, offer the potential for such a study as they are considered to be annually-laminated (varved) throughout a large part of the interglacial (Turner, 1970, 1975). The lamination sets appear to be comprised, primarily, of three regularly occurring laminae types; 1) authigenic carbonate, 2) diatom blooms, and 3) organic detritus, although there appears to be some variability in the microfacies of these laminations. The carbonate laminations are the key to the study of climate variability during MIS 11, as they represent authigenic carbonate precipitation, consistent with temperature/biologically driven changes in lake chemistry during the summer months. Oxygen isotopic analysis of the carbonate therefore gives a proxy for summer temperature. A period of key interest in the MIS 11 sequence at Marks Tey occurs during the early part of the interglacial, where there is a short-lived increase in grass pollen relative to tree pollen, termed the Non-Arboreal Pollen Zone (NAPZ). The cause of this shift in pollen has been subject to debate, with natural wildfire (Turner, 1970) or climatic deterioration (e.g. Kelly, 1964) being suggested as possible forcing mechanisms. In this study, as well as discussing the main characteristics of the MIS 11 sequence at Marks Tey, we will focus on the sedimentary, micromorphological and geochemical record of the NAPZ. In particular we discuss the potential role of abrupt, sub-Milankovitch, climate cooling in its genesis, whilst highlighting the complexity of ecological and landscape response that such a climatic event may generate. The study concludes by discussing the potential occurrence of 8.2ka-like events in pre-Holocene interglacials.

Response of groundwater level and surface-water/groundwater interaction to climate variability: Clarence-Moreton Basin, Australia

NASA Astrophysics Data System (ADS)

Cui, Tao; Raiber, Matthias; Pagendam, Dan; Gilfedder, Mat; Rassam, David

2018-03-01

Understanding the response of groundwater levels in alluvial and sedimentary basin aquifers to climatic variability and human water-resource developments is a key step in many hydrogeological investigations. This study presents an analysis of groundwater response to climate variability from 2000 to 2012 in the Queensland part of the sedimentary Clarence-Moreton Basin, Australia. It contributes to the baseline hydrogeological understanding by identifying the primary groundwater flow pattern, water-level response to climate extremes, and the resulting dynamics of surface-water/groundwater interaction. Groundwater-level measurements from thousands of bores over several decades were analysed using Kriging and nonparametric trend analysis, together with a newly developed three-dimensional geological model. Groundwater-level contours suggest that groundwater flow in the shallow aquifers shows local variations in the close vicinity of streams, notwithstanding general conformance with topographic relief. The trend analysis reveals that climate variability can be quickly reflected in the shallow aquifers of the Clarence-Moreton Basin although the alluvial aquifers have a quicker rainfall response than the sedimentary bedrock formations. The Lockyer Valley alluvium represents the most sensitively responding alluvium in the area, with the highest declining (-0.7 m/year) and ascending (2.1 m/year) Sen's slope rates during and after the drought period, respectively. Different surface-water/groundwater interaction characteristics were observed in different catchments by studying groundwater-level fluctuations along hydrogeologic cross-sections. The findings of this study lay a foundation for future water-resource management in the study area.

Error characterization of microwave satellite soil moisture data sets using fourier analysis

USDA-ARS?s Scientific Manuscript database

Soil moisture is a key geophysical variable in hydrological and meteorological processes. Accurate and current observations of soil moisture over meso to global scales used as inputs to hydrological, weather and climate modelling will benefit the predictability and understanding of these processes. ...

Error characterization of microwave satellite soil moisture data sets using fourier analysis

USDA-ARS?s Scientific Manuscript database

Abstract: Soil moisture is a key geophysical variable in hydrological and meteorological processes. Accurate and current observations of soil moisture over mesoscale to global scales as inputs to hydrological, weather and climate modelling will benefit the predictability and understanding of these p...

Multi-proxy palaeoclimate reconstructions from peatlands in southern South America

NASA Astrophysics Data System (ADS)

Roland, Thomas; Hughes, Paul; Mauquoy, Dmitri; van Bellen, Simon; Daley, Tim; Loader, Neil; Street-Perrott, Alayne

2014-05-01

There is a relative paucity of palaeoclimatic archives in South America relative to many other regions of the world. This paucity must be addressed in order to validate climate models and improve our understanding of the global climate system. The southern westerlies represent an important component of climatic variability in the region and, in turn, their migration and changes in their intensity can play a key role in determining whether the Southern Ocean functions as a sink or source of atmospheric carbon dioxide. Increased ventilation of deep waters with elevated concentrations of dissolved inorganic carbon, driven by enhanced Ekman transport, leads to increased outgassing of carbon dioxide. However, as instrumental records are limited to the latter half of the twentieth century, little is known about the long-term variability of the southern Westerlies and their subsequent effects. The Peninsula Brunswick and Isla Grande de Tierra del Fuego are directly situated in the core path of the southern westerlies during the Austral summer and they are ideally suited for studies of past variability in westerly intensity and position. The region's abundant peatlands are capable of recording these long-term changes, as wind intensity and westerly position affects precipitation and temperature, two key drivers (i.e. P-E) of water-table dynamics in ombrotrophic peatlands. Currently, the peatlands of southern Patagonia represent a relatively unexploited resource in terms of palaeoclimate reconstruction. As a result, we have developed a new regional network of multi-proxy (testate amoebae, plant macrofossils, stable isotopes) archives, supported by high-resolution radiocarbon chronologies, to develop quantitative climate reconstructions for southern South America spanning the last ~2000 years using Sphagnum magellanicum-dominated peat deposits.

"Intelligent Ensemble" Projections of Precipitation and Surface Radiation in Support of Agricultural Climate Change Adaptation

NASA Technical Reports Server (NTRS)

Taylor, Patrick C.; Baker, Noel C.

2015-01-01

Earth's climate is changing and will continue to change into the foreseeable future. Expected changes in the climatological distribution of precipitation, surface temperature, and surface solar radiation will significantly impact agriculture. Adaptation strategies are, therefore, required to reduce the agricultural impacts of climate change. Climate change projections of precipitation, surface temperature, and surface solar radiation distributions are necessary input for adaption planning studies. These projections are conventionally constructed from an ensemble of climate model simulations (e.g., the Coupled Model Intercomparison Project 5 (CMIP5)) as an equal weighted average, one model one vote. Each climate model, however, represents the array of climate-relevant physical processes with varying degrees of fidelity influencing the projection of individual climate variables differently. Presented here is a new approach, termed the "Intelligent Ensemble, that constructs climate variable projections by weighting each model according to its ability to represent key physical processes, e.g., precipitation probability distribution. This approach provides added value over the equal weighted average method. Physical process metrics applied in the "Intelligent Ensemble" method are created using a combination of NASA and NOAA satellite and surface-based cloud, radiation, temperature, and precipitation data sets. The "Intelligent Ensemble" method is applied to the RCP4.5 and RCP8.5 anthropogenic climate forcing simulations within the CMIP5 archive to develop a set of climate change scenarios for precipitation, temperature, and surface solar radiation in each USDA Farm Resource Region for use in climate change adaptation studies.

Limits on determining the skill of North Atlantic Ocean decadal predictions.

PubMed

Menary, Matthew B; Hermanson, Leon

2018-04-27

The northern North Atlantic is important globally both through its impact on the Atlantic Meridional Overturning Circulation (AMOC) and through widespread atmospheric teleconnections. The region has been shown to be potentially predictable a decade ahead with the skill of decadal predictions assessed against reanalyses of the ocean state. Here, we show that the prediction skill in this region is strongly dependent on the choice of reanalysis used for validation, and describe the causes. Multiannual skill in key metrics such as Labrador Sea density and the AMOC depends on more than simply the choice of the prediction model. Instead, this skill is related to the similarity between the nature of interannual density variability in the underlying climate model and the chosen reanalysis. The climate models used in these decadal predictions are also used in climate projections, which raises questions about the sensitivity of these projections to the models' innate North Atlantic density variability.

Collaborative Research: Process-resolving Decomposition of the Global Temperature Response to Modes of Low Frequency Variability in a Changing Climate

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

Cai, Ming; Deng, Yi

2015-02-06

El Niño-Southern Oscillation (ENSO) and Annular Modes (AMs) represent respectively the most important modes of low frequency variability in the tropical and extratropical circulations. The future projection of the ENSO and AM variability, however, remains highly uncertain with the state-of-the-art coupled general circulation models. A comprehensive understanding of the factors responsible for the inter-model discrepancies in projecting future changes in the ENSO and AM variability, in terms of multiple feedback processes involved, has yet to be achieved. The proposed research aims to identify sources of such uncertainty and establish a set of process-resolving quantitative evaluations of the existing predictions ofmore » the future ENSO and AM variability. The proposed process-resolving evaluations are based on a feedback analysis method formulated in Lu and Cai (2009), which is capable of partitioning 3D temperature anomalies/perturbations into components linked to 1) radiation-related thermodynamic processes such as cloud and water vapor feedbacks, 2) local dynamical processes including convection and turbulent/diffusive energy transfer and 3) non-local dynamical processes such as the horizontal energy transport in the oceans and atmosphere. Taking advantage of the high-resolution, multi-model ensemble products from the Coupled Model Intercomparison Project Phase 5 (CMIP5) soon to be available at the Lawrence Livermore National Lab, we will conduct a process-resolving decomposition of the global three-dimensional (3D) temperature (including SST) response to the ENSO and AM variability in the preindustrial, historical and future climate simulated by these models. Specific research tasks include 1) identifying the model-observation discrepancies in the global temperature response to ENSO and AM variability and attributing such discrepancies to specific feedback processes, 2) delineating the influence of anthropogenic radiative forcing on the key feedback processes operating on ENSO and AM variability and quantifying their relative contributions to the changes in the temperature anomalies associated with different phases of ENSO and AMs, and 3) investigating the linkages between model feedback processes that lead to inter-model differences in time-mean temperature projection and model feedback processes that cause inter-model differences in the simulated ENSO and AM temperature response. Through a thorough model-observation and inter-model comparison of the multiple energetic processes associated with ENSO and AM variability, the proposed research serves to identify key uncertainties in model representation of ENSO and AM variability, and investigate how the model uncertainty in predicting time-mean response is related to the uncertainty in predicting response of the low-frequency modes. The proposal is thus a direct response to the first topical area of the solicitation: Interaction of Climate Change and Low Frequency Modes of Natural Climate Variability. It ultimately supports the accomplishment of the BER climate science activity Long Term Measure (LTM): "Deliver improved scientific data and models about the potential response of the Earth's climate and terrestrial biosphere to increased greenhouse gas levels for policy makers to determine safe levels of greenhouse gases in the atmosphere."« less

Species-specific responses to climate change and community composition determine future calcification rates of Florida Keys reefs.

PubMed

Okazaki, Remy R; Towle, Erica K; van Hooidonk, Ruben; Mor, Carolina; Winter, Rivah N; Piggot, Alan M; Cunning, Ross; Baker, Andrew C; Klaus, James S; Swart, Peter K; Langdon, Chris

2017-03-01

Anthropogenic climate change compromises reef growth as a result of increasing temperatures and ocean acidification. Scleractinian corals vary in their sensitivity to these variables, suggesting species composition will influence how reef communities respond to future climate change. Because data are lacking for many species, most studies that model future reef growth rely on uniform scleractinian calcification sensitivities to temperature and ocean acidification. To address this knowledge gap, calcification of twelve common and understudied Caribbean coral species was measured for two months under crossed temperatures (27, 30.3 °C) and CO 2 partial pressures (pCO 2 ) (400, 900, 1300 μatm). Mixed-effects models of calcification for each species were then used to project community-level scleractinian calcification using Florida Keys reef composition data and IPCC AR5 ensemble climate model data. Three of the four most abundant species, Orbicella faveolata, Montastraea cavernosa, and Porites astreoides, had negative calcification responses to both elevated temperature and pCO 2 . In the business-as-usual CO 2 emissions scenario, reefs with high abundances of these species had projected end-of-century declines in scleractinian calcification of >50% relative to present-day rates. Siderastrea siderea, the other most common species, was insensitive to both temperature and pCO 2 within the levels tested here. Reefs dominated by this species had the most stable end-of-century growth. Under more optimistic scenarios of reduced CO 2 emissions, calcification rates throughout the Florida Keys declined <20% by 2100. Under the most extreme emissions scenario, projected declines were highly variable among reefs, ranging 10-100%. Without considering bleaching, reef growth will likely decline on most reefs, especially where resistant species like S. siderea are not already dominant. This study demonstrates how species composition influences reef community responses to climate change and how reduced CO 2 emissions can limit future declines in reef calcification. © 2016 John Wiley & Sons Ltd.

Simulating and Predicting Cereal Crop Yields in Ethiopia: Model Calibration and Verification

NASA Astrophysics Data System (ADS)

Yang, M.; Wang, G.; Ahmed, K. F.; Eggen, M.; Adugna, B.; Anagnostou, E. N.

2017-12-01

Agriculture in developing countries are extremely vulnerable to climate variability and changes. In East Africa, most people live in the rural areas with outdated agriculture techniques and infrastructure. Smallholder agriculture continues to play a key role in this area, and the rate of irrigation is among the lowest of the world. As a result, seasonal and inter-annual weather patterns play an important role in the spatiotemporal variability of crop yields. This study investigates how various climate variables (e.g., temperature, precipitation, sunshine) and agricultural practice (e.g., fertilization, irrigation, planting date) influence cereal crop yields using a process-based model (DSSAT) and statistical analysis, and focuses on the Blue Nile Basin of Ethiopia. The DSSAT model is driven with meteorological forcing from the ECMWF's latest reanalysis product that cover the past 35 years; the statistical model will be developed by linking the same meteorological reanalysis data with harvest data at the woreda level from the Ethiopian national dataset. Results from this study will set the stage for the development of a seasonal prediction system for weather and crop yields in Ethiopia, which will serve multiple sectors in coping with the agricultural impact of climate variability.

Global Climate Change: Valuable Insights from Concordant and Discordant Ice Core Histories

NASA Astrophysics Data System (ADS)

Mosley-Thompson, E.; Thompson, L. G.; Porter, S. E.; Goodwin, B. P.; Wilson, A. B.

2014-12-01

Earth's ice cover is responding to the ongoing large-scale warming driven in part by anthropogenic forces. The highest tropical and subtropical ice fields are dramatically shrinking and/or thinning and unique climate histories archived therein are now threatened, compromised or lost. Many ice fields in higher latitudes are also experiencing and recording climate system changes although these are often manifested in less evident and spectacular ways. The Antarctic Peninsula (AP) has experienced a rapid, widespread and dramatic warming over the last 60 years. Carefully selected ice fields in the AP allow reconstruction of long histories of key climatic variables. As more proxy climate records are recovered it is clear they reflect a combination of expected and unexpected responses to seemingly similar climate forcings. Recently acquired temperature and precipitation histories from the Bruce Plateau are examined within the context provided by other cores recently collected in the AP. Understanding the differences and similarities among these records provides a better understanding of the forces driving climate variability in the AP over the last century. The Arctic is also rapidly warming. The δ18O records from the Bona-Churchill and Mount Logan ice cores from southeast Alaska and southwest Yukon Territory, respectively, do not record this strong warming. The Aleutian Low strongly influences moisture transport to this geographically complex region, yet its interannual variability is preserved differently in these cores located just 110 km apart. Mount Logan is very sensitive to multi-decadal to multi-centennial climate shifts in the tropical Pacific while low frequency variability on Bona-Churchill is more strongly connected to Western Arctic sea ice extent. There is a natural tendency to focus more strongly on commonalities among records, particularly on regional scales. However, it is also important to investigate seemingly poorly correlated records, particularly those from geographically complex settings that appear to be dominated by similar large-scale climatological processes. Better understanding of the spatially and temporally diverse responses in such regions will expand our understanding of the mechanisms forcing climate variability in meteorologically complex environments.

Watershed Adaptation Measures to Climate Change Impacts: A case of Kiha Watershed in Albertine Graben

NASA Astrophysics Data System (ADS)

Zizinga, A.

2017-12-01

Watershed Adaptation Measures to Climate Change Impacts: A case of Kiha Watershed in Albertine GrabenAlex Zizinga1, Moses Tenywa2, Majaliwa Jackson Gilbert1, 1Makerere University, Department of Environmental Sciences, O Box 7062, Kampala, Uganda 1Makerere University, Department of Agricultural Production, P.O Box 7062, Kampala, Uganda Corresponding author: azizinga@caes.mak.ac.ug AbstractThe most pressing issues local communities in Uganda are facing result from land-use and land cover changes exacerbated by climate change impacts. A key issue is the documentation of land-cover changes visible with the ongoing clearance of remaining forests, bush-lands and wetlands for expanding farmland for sugarcane production, producing charcoal and collecting firewood for local distilleries using imported molasses. Decision-makers, resource managers, farmers and practitioners must build their capacity for adaptive measures. Here we present the potential impacts of climate change on watershed hydrological processes in the River Kiha Watershed, located in Western Uganda, Lake Albert Water Management Zone, by using social learning techniques incorporating water users, local stakeholders and researchers. The research team examined different farming and economic activities within the watershed to assess their impacts on catchment water resources, namely on water quality and discharge of river Kiha. We present the impacts of locally induced climate change, which are already manifested in increasing seasonal variability of rainfall. The study aims at answering questions posed by local communities and stakeholders about climate change and its effects on livelihood and key resources, specifically water and soils within the Kiha watershed. Key words: Climate change impacts, Social Learning and Watershed Management

Projecting the Hydrologic Impacts of Climate Change on Montane Wetlands.

PubMed

Lee, Se-Yeun; Ryan, Maureen E; Hamlet, Alan F; Palen, Wendy J; Lawler, Joshua J; Halabisky, Meghan

2015-01-01

Wetlands are globally important ecosystems that provide critical services for natural communities and human society. Montane wetland ecosystems are expected to be among the most sensitive to changing climate, as their persistence depends on factors directly influenced by climate (e.g. precipitation, snowpack, evaporation). Despite their importance and climate sensitivity, wetlands tend to be understudied due to a lack of tools and data relative to what is available for other ecosystem types. Here, we develop and demonstrate a new method for projecting climate-induced hydrologic changes in montane wetlands. Using observed wetland water levels and soil moisture simulated by the physically based Variable Infiltration Capacity (VIC) hydrologic model, we developed site-specific regression models relating soil moisture to observed wetland water levels to simulate the hydrologic behavior of four types of montane wetlands (ephemeral, intermediate, perennial, permanent wetlands) in the U. S. Pacific Northwest. The hybrid models captured observed wetland dynamics in many cases, though were less robust in others. We then used these models to a) hindcast historical wetland behavior in response to observed climate variability (1916-2010 or later) and classify wetland types, and b) project the impacts of climate change on montane wetlands using global climate model scenarios for the 2040s and 2080s (A1B emissions scenario). These future projections show that climate-induced changes to key driving variables (reduced snowpack, higher evapotranspiration, extended summer drought) will result in earlier and faster drawdown in Pacific Northwest montane wetlands, leading to systematic reductions in water levels, shortened wetland hydroperiods, and increased probability of drying. Intermediate hydroperiod wetlands are projected to experience the greatest changes. For the 2080s scenario, widespread conversion of intermediate wetlands to fast-drying ephemeral wetlands will likely reduce wetland habitat availability for many species.

An analytical approach to separate climate and human contributions to basin streamflow variability

NASA Astrophysics Data System (ADS)

Li, Changbin; Wang, Liuming; Wanrui, Wang; Qi, Jiaguo; Linshan, Yang; Zhang, Yuan; Lei, Wu; Cui, Xia; Wang, Peng

2018-04-01

Climate variability and anthropogenic regulations are two interwoven factors in the ecohydrologic system across large basins. Understanding the roles that these two factors play under various hydrologic conditions is of great significance for basin hydrology and sustainable water utilization. In this study, we present an analytical approach based on coupling water balance method and Budyko hypothesis to derive effectiveness coefficients (ECs) of climate change, as a way to disentangle contributions of it and human activities to the variability of river discharges under different hydro-transitional situations. The climate dominated streamflow change (ΔQc) by EC approach was compared with those deduced by the elasticity method and sensitivity index. The results suggest that the EC approach is valid and applicable for hydrologic study at large basin scale. Analyses of various scenarios revealed that contributions of climate change and human activities to river discharge variation differed among the regions of the study area. Over the past several decades, climate change dominated hydro-transitions from dry to wet, while human activities played key roles in the reduction of streamflow during wet to dry periods. Remarkable decline of discharge in upstream was mainly due to human interventions, although climate contributed more to runoff increasing during dry periods in the semi-arid downstream. Induced effectiveness on streamflow changes indicated a contribution ratio of 49% for climate and 51% for human activities at the basin scale from 1956 to 2015. The mathematic derivation based simple approach, together with the case example of temporal segmentation and spatial zoning, could help people understand variation of river discharge with more details at a large basin scale under the background of climate change and human regulations.

Projecting the Hydrologic Impacts of Climate Change on Montane Wetlands

PubMed Central

Hamlet, Alan F.; Palen, Wendy J.; Lawler, Joshua J.; Halabisky, Meghan

2015-01-01

Wetlands are globally important ecosystems that provide critical services for natural communities and human society. Montane wetland ecosystems are expected to be among the most sensitive to changing climate, as their persistence depends on factors directly influenced by climate (e.g. precipitation, snowpack, evaporation). Despite their importance and climate sensitivity, wetlands tend to be understudied due to a lack of tools and data relative to what is available for other ecosystem types. Here, we develop and demonstrate a new method for projecting climate-induced hydrologic changes in montane wetlands. Using observed wetland water levels and soil moisture simulated by the physically based Variable Infiltration Capacity (VIC) hydrologic model, we developed site-specific regression models relating soil moisture to observed wetland water levels to simulate the hydrologic behavior of four types of montane wetlands (ephemeral, intermediate, perennial, permanent wetlands) in the U. S. Pacific Northwest. The hybrid models captured observed wetland dynamics in many cases, though were less robust in others. We then used these models to a) hindcast historical wetland behavior in response to observed climate variability (1916–2010 or later) and classify wetland types, and b) project the impacts of climate change on montane wetlands using global climate model scenarios for the 2040s and 2080s (A1B emissions scenario). These future projections show that climate-induced changes to key driving variables (reduced snowpack, higher evapotranspiration, extended summer drought) will result in earlier and faster drawdown in Pacific Northwest montane wetlands, leading to systematic reductions in water levels, shortened wetland hydroperiods, and increased probability of drying. Intermediate hydroperiod wetlands are projected to experience the greatest changes. For the 2080s scenario, widespread conversion of intermediate wetlands to fast-drying ephemeral wetlands will likely reduce wetland habitat availability for many species. PMID:26331850

Ice_Sheets_CCI: Essential Climate Variables for the Greenland Ice Sheet

NASA Astrophysics Data System (ADS)

Forsberg, R.; Sørensen, L. S.; Khan, A.; Aas, C.; Evansberget, D.; Adalsteinsdottir, G.; Mottram, R.; Andersen, S. B.; Ahlstrøm, A.; Dall, J.; Kusk, A.; Merryman, J.; Hvidberg, C.; Khvorostovsky, K.; Nagler, T.; Rott, H.; Scharrer, M.; Shepard, A.; Ticconi, F.; Engdahl, M.

2012-04-01

As part of the ESA Climate Change Initiative (www.esa-cci.org) a long-term project "ice_sheets_cci" started January 1, 2012, in addition to the existing 11 projects already generating Essential Climate Variables (ECV) for the Global Climate Observing System (GCOS). The "ice_sheets_cci" goal is to generate a consistent, long-term and timely set of key climate parameters for the Greenland ice sheet, to maximize the impact of European satellite data on climate research, from missions such as ERS, Envisat and the future Sentinel satellites. The climate parameters to be provided, at first in a research context, and in the longer perspective by a routine production system, would be grids of Greenland ice sheet elevation changes from radar altimetry, ice velocity from repeat-pass SAR data, as well as time series of marine-terminating glacier calving front locations and grounding lines for floating-front glaciers. The ice_sheets_cci project will involve a broad interaction of the relevant cryosphere and climate communities, first through user consultations and specifications, and later in 2012 optional participation in "best" algorithm selection activities, where prototype climate parameter variables for selected regions and time frames will be produced and validated using an objective set of criteria ("Round-Robin intercomparison"). This comparative algorithm selection activity will be completely open, and we invite all interested scientific groups with relevant experience to participate. The results of the "Round Robin" exercise will form the algorithmic basis for the future ECV production system. First prototype results will be generated and validated by early 2014. The poster will show the planned outline of the project and some early prototype results.

Are GRACE-era terrestrial water trends driven by anthropogenic climate change?

DOE PAGES

Fasullo, J. T.; Lawrence, D. M.; Swenson, S. C.

2016-01-01

To provide context for observed trends in terrestrial water storage (TWS) during GRACE (2003–2014), trends and variability in the CESM1-CAM5 Large Ensemble (LE) are examined. Motivated in part by the anomalous nature of climate variability during GRACE, the characteristics of both forced change and internal modes are quantified and their influences on observations are estimated. Trends during the GRACE era in the LE are dominated by internal variability rather than by the forced response, with TWS anomalies in much of the Americas, eastern Australia, Africa, and southwestern Eurasia largely attributable to the negative phases of the Pacific Decadal Oscillation (PDO)more » and Atlantic Multidecadal Oscillation (AMO). While similarities between observed trends and the model-inferred forced response also exist, it is inappropriate to attribute such trends mainly to anthropogenic forcing. For several key river basins, trends in the mean state and interannual variability and the time at which the forced response exceeds background variability are also estimated while aspects of global mean TWS, including changes in its annual amplitude and decadal trends, are quantified. Lastly, the findings highlight the challenge of detecting anthropogenic climate change in temporally finite satellite datasets and underscore the benefit of utilizing models in the interpretation of the observed record.« less

Are GRACE-era terrestrial water trends driven by anthropogenic climate change?

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

Fasullo, J. T.; Lawrence, D. M.; Swenson, S. C.

To provide context for observed trends in terrestrial water storage (TWS) during GRACE (2003–2014), trends and variability in the CESM1-CAM5 Large Ensemble (LE) are examined. Motivated in part by the anomalous nature of climate variability during GRACE, the characteristics of both forced change and internal modes are quantified and their influences on observations are estimated. Trends during the GRACE era in the LE are dominated by internal variability rather than by the forced response, with TWS anomalies in much of the Americas, eastern Australia, Africa, and southwestern Eurasia largely attributable to the negative phases of the Pacific Decadal Oscillation (PDO)more » and Atlantic Multidecadal Oscillation (AMO). While similarities between observed trends and the model-inferred forced response also exist, it is inappropriate to attribute such trends mainly to anthropogenic forcing. For several key river basins, trends in the mean state and interannual variability and the time at which the forced response exceeds background variability are also estimated while aspects of global mean TWS, including changes in its annual amplitude and decadal trends, are quantified. Lastly, the findings highlight the challenge of detecting anthropogenic climate change in temporally finite satellite datasets and underscore the benefit of utilizing models in the interpretation of the observed record.« less

Global Warming: Discussion for EOS Science Writers Workshop

NASA Technical Reports Server (NTRS)

Hansen, James E

1999-01-01

The existence of global warming this century is no longer an issue of scientific debate. But there are many important questions about the nature and causes of long-term climate change, th roles of nature and human-made climate forcings and unforced (chaotic) climate variability, the practical impacts of climate change, and what, if anything, should be done to reduce global warming, Global warming is not a uniform increase of temperature, but rather involves at complex geographically varying climate change. Understanding of global warming will require improved observations of climate change itself and the forcing factors that can lead to climate change. The NASA Terra mission and other NASA Earth Science missions will provide key measurement of climate change and climate forcings. The strategy to develop an understanding of the causes and predictability of long-term climate change must be based on combination of observations with models and analysis. The upcoming NASA missions will make important contributions to the required observations.

Simulating malaria transmission in the current and future climate of West Africa

NASA Astrophysics Data System (ADS)

Yamana, T. K.; Bomblies, A.; Eltahir, E. A. B.

2015-12-01

Malaria transmission in West Africa is closely tied to climate, as rain fed water pools provide breeding habitat for the anopheles mosquito vector, and temperature affects the mosquito's ability to spread disease. We present results of a highly detailed, spatially explicit mechanistic modelling study exploring the relationships between the environment and malaria in the current and future climate of West Africa. A mechanistic model of human immunity was incorporated into an existing agent-based model of malaria transmission, allowing us to move beyond entomological measures such as mosquito density and vectorial capacity to analyzing the prevalence of the malaria parasite within human populations. The result is a novel modelling tool that mechanistically simulates all of the key processes linking environment to malaria transmission. Simulations were conducted across climate zones in West Africa, linking temperature and rainfall to entomological and epidemiological variables with a focus on nonlinearities due to threshold effects and interannual variability. Comparisons to observations from the region confirmed that the model provides a reasonable representation of the entomological and epidemiological conditions in this region. We used the predictions of future climate from the most credible CMIP5 climate models to predict the change in frequency and severity of malaria epidemics in West Africa as a result of climate change.

The I.A.G. / A.I.G. SEDIBUD Book Project: Source-to-Sink Fluxes in Undisturbed Cold Environments

NASA Astrophysics Data System (ADS)

Beylich, Achim A.; Dixon, John C.; Zwolinski, Zbigniew

2015-04-01

The currently prepared SEDIBUD Book on "Source-to-Sink Fluxes in Undisturbed Cold Environments" (edited by Achim A. Beylich, John C. Dixon and Zbigniew Zwolinski and published by Cambridge University Press) is summarizing and synthesizing the achievements of the International Association of Geomorphologists` (I.A.G./A.I.G.) Working Group SEDIBUD (Sediment Budgets in Cold Environments), which has been active since 2005 (http://www.geomorph.org/wg/wgsb.html). Amplified climate change and ecological sensitivity of largely undisturbed polar and high-altitude cold climate environments have been highlighted as key global environmental issues. The effects of projected climate change will change surface environments in cold regions and will alter the fluxes of sediments, nutrients and solutes, but the absence of quantitative data and coordinated geomorphic process monitoring and analysis to understand the sensitivity of the Earth surface environment in these largely undisturbed environments is acute. Our book addresses this existing key knowledge gap. The applied approach of integrating comparable and longer-term field datasets on contemporary solute and sedimentary fluxes from a number of different defined cold climate catchment geosystems for better understanding (i) the environmental drivers and rates of contemporary denudational surface processes and (ii) possible effects of projected climate change in cold regions is unique in the field of geomorphology. Largely undisturbed cold climate environments can provide baseline data for modeling the effects of environmental change. The book synthesizes work carried out by numerous SEDIBUD Members over the last decade in numerous cold climate catchment geosystems worldwide. For reaching a global cover of different cold climate environments the book is - after providing an introduction part and a basic part on climate change in cold environments and general implications for solute and sedimentary fluxes - dealing in different defined parts with Sub-Arctic and Arctic Environments, Sub-Antarctic and Antarctic Environments, and Alpine / Mountain Environments. The book includes a synthesis key chapter where comparable datasets on contemporary solute and sedimentary fluxes generated during the conducted coordinated research efforts in different cold climate catchment geosystems are integrated with the key goals to (i) identify the main environmental drivers and rates of contemporary solute and sedimentary fluxes, and (ii) model possible effects of projected climate change on solute and sedimentary fluxes in cold climate environments. The SEDIBUD Book provides new key findings on environmental drivers and rates of contemporary solute and sedimentary fluxes, and on spatial variability within global cold climate environments. The book will go in production in July 2015.

Professional Learning: A Fuzzy Logic-Based Modelling Approach

ERIC Educational Resources Information Center

Gravani, M. N.; Hadjileontiadou, S. J.; Nikolaidou, G. N.; Hadjileontiadis, L. J.

2007-01-01

Studies have suggested that professional learning is influenced by two key parameters, i.e., climate and planning, and their associated variables (mutual respect, collaboration, mutual trust, supportiveness, openness). In this paper, we applied analysis of the relationships between the proposed quantitative, fuzzy logic-based model and a series of…

Increasing importance of precipitation variability on global livestock grazing lands

NASA Astrophysics Data System (ADS)

Sloat, Lindsey L.; Gerber, James S.; Samberg, Leah H.; Smith, William K.; Herrero, Mario; Ferreira, Laerte G.; Godde, Cécile M.; West, Paul C.

2018-03-01

Pastures and rangelands underpin global meat and milk production and are a critical resource for millions of people dependent on livestock for food security1,2. Forage growth, which is highly climate dependent3,4, is potentially vulnerable to climate change, although precisely where and to what extent remains relatively unexplored. In this study, we assess climate-based threats to global pastures, with a specific focus on changes in within- and between-year precipitation variability (precipitation concentration index (PCI) and coefficient of variation of precipitation (CVP), respectively). Relating global satellite measures of vegetation greenness (such as the Normalized Difference Vegetation Index; NDVI) to key climatic factors reveals that CVP is a significant, yet often overlooked, constraint on vegetation productivity across global pastures. Using independent stocking data, we found that areas with high CVP support lower livestock densities than less-variable regions. Globally, pastures experience about a 25% greater year-to-year precipitation variation (CVP = 0.27) than the average global land surface area (0.21). Over the past century, CVP has generally increased across pasture areas, although both positive (49% of pasture area) and negative (31% of pasture area) trends exist. We identify regions in which livestock grazing is important for local food access and economies, and discuss the potential for pasture intensification in the context of long-term regional trends in precipitation variability.

Composition and structure of Pinus koraiensis mixed forest respond to spatial climatic changes.

PubMed

Zhang, Jingli; Zhou, Yong; Zhou, Guangsheng; Xiao, Chunwang

2014-01-01

Although some studies have indicated that climate changes can affect Pinus koraiensis mixed forest, the responses of composition and structure of Pinus koraiensis mixed forests to climatic changes are unknown and the key climatic factors controlling the composition and structure of Pinus koraiensis mixed forest are uncertain. Field survey was conducted in the natural Pinus koraiensis mixed forests along a latitudinal gradient and an elevational gradient in Northeast China. In order to build the mathematical models for simulating the relationships of compositional and structural attributes of the Pinus koraiensis mixed forest with climatic and non-climatic factors, stepwise linear regression analyses were performed, incorporating 14 dependent variables and the linear and quadratic components of 9 factors. All the selected new models were computed under the +2°C and +10% precipitation and +4°C and +10% precipitation scenarios. The Max Temperature of Warmest Month, Mean Temperature of Warmest Quarter and Precipitation of Wettest Month were observed to be key climatic factors controlling the stand densities and total basal areas of Pinus koraiensis mixed forest. Increased summer temperatures and precipitations strongly enhanced the stand densities and total basal areas of broadleaf trees but had little effect on Pinus koraiensis under the +2°C and +10% precipitation scenario and +4°C and +10% precipitation scenario. These results show that the Max Temperature of Warmest Month, Mean Temperature of Warmest Quarter and Precipitation of Wettest Month are key climatic factors which shape the composition and structure of Pinus koraiensis mixed forest. Although the Pinus koraiensis would persist, the current forests dominated by Pinus koraiensis in the region would all shift and become broadleaf-dominated forests due to the dramatic increase of broadleaf trees under the future global warming and increased precipitation.

ENSO activity during the last climate cycle using Individual Foraminifera Analysis

NASA Astrophysics Data System (ADS)

Leduc, G.; Vidal, L.; Thirumalai, K.

2017-12-01

The El Niño / Southern Oscillation (ENSO) is the principal mode of interannual climate variability and affects key climate parameters such as low-latitude rainfall variability. Recent climate modeling experiments tend to suggest an increase in the frequency of both El Niño and La Niña events in the future, but these results remain model-dependent and require to be validated by paleodata-model comparisons. Fossil corals indicate that the ENSO variance during the 20th century is particularly high as compared to other time periods of the Holocene. Beyond the Holocene, however, little is known on past ENSO changes, which makes difficult to test paleoclimate model simulations that are used to study the ENSO sensitivity to various types of forcings. We have expanded an Individual Foraminifera Analysis (IFA) dataset using the thermocline-dwelling N. dutertrei on a marine core collected in the Panama Basin (Leduc et al., 2009), that has proven to be a skillful way to reconstruct the ENSO (Thirumalai et al., 2013). Our new IFA dataset comprehensively covers the Holocene, allowing to verify how the IFA method compares with ENSO reconstructions using corals. The dataset then extends back in time to Marine Isotope Stage 6 (MIS), with a special focus the last deglaciation and Termination II (MIS5/6) time windows, as well as key time periods to tests the sensitivity of ENSO to ice volume and orbital parameters. The new dataset confirms variable ENSO activity during the Holocene and weaker activity during LGM than during the Holocene, as a recent isotope-enabled climate model simulations of the LGM suggests (Zhu et al., 2017). Such pattern is reproduced for the Termination II. Leduc, G., L. Vidal, O. Cartapanis, and E. Bard (2009), Modes of eastern equatorial Pacific thermocline variability: Implications for ENSO dynamics over the last glacial period, Paleoceanography, 24, PA3202, doi:10.1029/2008PA001701. Thirumalai, K., J. W. Partin, C. S. Jackson, and T. M. Quinn (2013), Statistical constraints on El Niño Southern Oscillation reconstructions using individual foraminifera: A sensitivity analysis, Paleoceanography, 28, 401-412, doi:10.1002/palo.20037. Zhu, J., et al. (2017), Reduced ENSO variability at the LGM revealed by an isotope-enabled Earth system model, Geophys. Res. Lett., 44, 6984-6992, doi:10.1002/2017GL073406.

Estimating Ecosystem Carbon Stock Change in the Conterminous United States from 1971 to 2010

NASA Astrophysics Data System (ADS)

Liu, J.; Sleeter, B. M.; Zhu, Z.; Loveland, T. R.; Sohl, T.; Howard, S. M.; Hawbaker, T. J.; Liu, S.; Heath, L. S.; Cochrane, M. A.; Key, C. H.; Jiang, H.; Price, D. T.; Chen, J. M.

2015-12-01

There is significant geographic variability in U.S. ecosystem carbon sequestration due to natural and human environmental conditions. Climate change, natural disturbance and human land use are the major driving forces that can alter local and regional carbon sequestration rates. In this study, a comprehensive environmental input dataset (1-km resolution) was developed and used in the process-based Integrated Biosphere Simulator (IBIS) to quantify the U.S. carbon stock changes from 1971-2010, which potentially forms a baseline for future U.S. carbon scenarios. The key environmental data sources include land cover change information from more than 2,600 sample blocks across U.S. (10-km by 10-km in size, 60-m resolution, 1973-2000), wildland fire scar and burn severity information (30-m resolution, 1984-2010), vegetation canopy percentage and live biomass level (30-m resolution, ~2000), spatially heterogeneous atmospheric carbon dioxide and nitrogen deposition (~50-km resolution, 2003-2009), and newly available climate (4-km resolution, 1895-2010) and soil variables (1-km resolution, ~2000). The IBIS simulated the effects of atmospheric CO2 fertilization, nitrogen deposition, climate change, fire, logging, and deforestation/devegetation on ecosystem carbon changes. Multiple comparable simulations were implemented to quantify the contributions of key environmental drivers.

An overview of new insights from satellite salinity missions on oceanography

NASA Astrophysics Data System (ADS)

Reul, Nicolas

2015-04-01

The Soil Moisture and Ocean Salinity (SMOS) mission, launched on 2 November 2009, is the European Space Agency's (ESA) second Earth Explorer Opportunity mission. The scientific objectives of the SMOS mission directly respond to the need for global observations of soil moisture and ocean salinity, two key variables describing the Earth's water cycle and having been identified as Essential Climate Variables (ECVs) by the Global Climate Observing System (GCOS). After five years of satellite Sea Surface Salinity (SSS) monitoring from SMOS data, we will present an overview of the scientific highlights these data have brougtht to the oceanographic communities. In particular, we shall review the impact of SMOS SSS and brightness tempeaerture data for the monitoring of: -Mesoscale variability of SSS (and density) in frontal structures, eddies, -Ocean propagative SSS signals (e.g. TIW, planetary waves), -Freshwater flux Monitoring (Evaportaion minus precipitation, river run off), -Large scale SSS anomalies related to climate fluctuations (e.g. ENSO, IOD), -Air-Sea interactions (equatorial upwellings, Tropical cyclone wakes) -Temperature-Salinity dependencies, -Sea Ice thickness, -Tropical Storm and high wind monitoring, -Ocean surface bio-geo chemistry.

Role of multidecadal climate variability in a range extension of pinyon pine

USGS Publications Warehouse

Gray, Stephen T.; Betancourt, Julio L.; Jackson, Stephen T.; Eddy, Robert G.

2006-01-01

Evidence from woodrat middens and tree rings at Dutch John Mountain (DJM) in northeastern Utah reveal spatiotemporal patterns of pinyon pine (Pinus edulis Engelm.) colonization and expansion in the past millennium. The DJM population, a northern outpost of pinyon, was established by long-distance dispersal (~40 km). Growth of this isolate was markedly episodic and tracked multidecadal variability in precipitation. Initial colonization occurred by AD 1246, but expansion was forestalled by catastrophic drought (1250–1288), which we speculate produced extensive mortality of Utah Juniper (Juniperus osteosperma (Torr.) Little), the dominant tree at DJM for the previous ~8700 years. Pinyon then quickly replaced juniper across DJM during a few wet decades (1330–1339 and 1368–1377). Such alternating decadal-scale droughts and pluvial events play a key role in structuring plant communities at the landscape to regional level. These decadal-length precipitation anomalies tend to be regionally coherent and can synchronize physical and biological processes across large areas. Vegetation forecast models must incorporate these temporal and geographic aspects of climate variability to accurately predict the effects of future climate change.

Separating decadal global water cycle variability from sea level rise.

PubMed

Hamlington, B D; Reager, J T; Lo, M-H; Karnauskas, K B; Leben, R R

2017-04-20

Under a warming climate, amplification of the water cycle and changes in precipitation patterns over land are expected to occur, subsequently impacting the terrestrial water balance. On global scales, such changes in terrestrial water storage (TWS) will be reflected in the water contained in the ocean and can manifest as global sea level variations. Naturally occurring climate-driven TWS variability can temporarily obscure the long-term trend in sea level rise, in addition to modulating the impacts of sea level rise through natural periodic undulation in regional and global sea level. The internal variability of the global water cycle, therefore, confounds both the detection and attribution of sea level rise. Here, we use a suite of observations to quantify and map the contribution of TWS variability to sea level variability on decadal timescales. In particular, we find that decadal sea level variability centered in the Pacific Ocean is closely tied to low frequency variability of TWS in key areas across the globe. The unambiguous identification and clean separation of this component of variability is the missing step in uncovering the anthropogenic trend in sea level and understanding the potential for low-frequency modulation of future TWS impacts including flooding and drought.

The predicted CLARREO sampling error of the inter-annual SW variability

NASA Astrophysics Data System (ADS)

Doelling, D. R.; Keyes, D. F.; Nguyen, C.; Macdonnell, D.; Young, D. F.

2009-12-01

The NRC Decadal Survey has called for SI traceability of long-term hyper-spectral flux measurements in order to monitor climate variability. This mission is called the Climate Absolute Radiance and Refractivity Observatory (CLARREO) and is currently defining its mission requirements. The requirements are focused on the ability to measure decadal change of key climate variables at very high accuracy. The accuracy goals are set using anticipated climate change magnitudes, but the accuracy achieved for any given climate variable must take into account the temporal and spatial sampling errors based on satellite orbits and calibration accuracy. The time period to detect a significant trend in the CLARREO record depends on the magnitude of the sampling calibration errors relative to the current inter-annual variability. The largest uncertainty in climate feedbacks remains the effect of changing clouds on planetary energy balance. Some regions on earth have strong diurnal cycles, such as maritime stratus and afternoon land convection; other regions have strong seasonal cycles, such as the monsoon. However, when monitoring inter-annual variability these cycles are only important if the strength of these cycles vary on decadal time scales. This study will attempt to determine the best satellite constellations to reduce sampling error and to compare the error with the current inter-annual variability signal to ensure the viability of the mission. The study will incorporate Clouds and the Earth's Radiant Energy System (CERES) (Monthly TOA/Surface Averages) SRBAVG product TOA LW and SW climate quality fluxes. The fluxes are derived by combining Terra (10:30 local equator crossing time) CERES fluxes with 3-hourly 5-geostationary satellite estimated broadband fluxes, which are normalized using the CERES fluxes, to complete the diurnal cycle. These fluxes were saved hourly during processing and considered the truth dataset. 90°, 83° and 74° inclination precessionary orbits as well as sun-synchronous orbits will be evaluated. This study will focus on the SW radiance, since these low earth orbits are only in daylight for half the orbit. The precessionary orbits were designed to cycle through all solar zenith angles over the course of a year. The inter-annual variability sampling error will be stratified globally/zonally and annually/seasonally and compared with the corresponding truth anomalies.

Advances in Understanding Decadal Climate Variability

NASA Technical Reports Server (NTRS)

Busalaacchi, Antonio J.

1998-01-01

Recently, a joint Brazil-France-U.S. program, known as PIRATA (Pilot Research moored Array in the Tropical Atlantic), was proposed to begin the deployment of moored measurement platforms in the tropical Atlantic in order to enhance the existing observational data base and subsequent understanding of the processes by which the ocean and atmosphere couple in key regions of the tropical Atlantic Ocean. Empirical studies have suggested that there are strong relationships between tropical Atlantic upper ocean variability, SST, ocean-atmosphere coupling and regional climate variability. During the early 1980's a coordinated set of surface wind, subsurface thermal structure, and subsurface current observations were obtained as part of the U.S.-France SEQUAL- FOCAL process experiment designed to observe the seasonal response of the tropical Atlantic Ocean to surface forcing. Since that time, however, the observational data base for the tropical Atlantic Ocean has disintegrated to a few shiptracks measuring ocean temperatures and a small collection of tide gauge stations measuring sea level. A more comprehensive set of observations, modeling and empirical studies is now in order to make progress on understanding the regional climate variability. The proposed PIRATA program will use mooring platforms similar to the tropical Pacific Ocean TAO array to measure surface fluxes of momentum and heat and the corresponding changes in the upper ocean thermal structure. It is anticipated that the oceanic data from this monitoring array will also be used in a predictive mode for initialization studies of regional coupled climate models. Of particular interest are zonal and meridional modes of ocean-atmosphere variability within the tropical Atlantic basin that have significant impacts on the regional climate of the bordering continents.

Advances in Understanding Decadal Climate Variability

NASA Technical Reports Server (NTRS)

Busalacchi, Antonio J.

1999-01-01

Recently, a joint Brazil-France-U.S. program, known as PIRATA (Pilot Research moored Array in the Tropical Atlantic), was proposed to begin the deployment of moored measurement platforms in the tropical Atlantic in order to enhance the existing observational data base and subsequent understanding of the processes by which the ocean and atmosphere couple in key regions of the tropical Atlantic Ocean. Empirical studies have suggested that there are strong relationships between tropical Atlantic upper ocean variability, SST, ocean-atmosphere coupling and regional climate variability. During the early 1980's a coordinated set of surface wind, subsurface thermal structure, and subsurface current observations were obtained as part of the U.S.-France SEQUAL-FOCAL process experiment designed to observe the seasonal response of the tropical Atlantic Ocean to surface forcing. Since that time, however, the observational data base for the tropical Atlantic Ocean has disintegrated to a few ship-tracks measuring ocean temperatures and a small collection of tide gauge stations measuring sea level. A more comprehensive set of observations, modeling and empirical studies is now in order to make progress on understanding the regional climate variability. The proposed PIRATA program will use mooring platforms similar to the tropical Pacific Ocean TAO array to measure surface fluxes of momentum and heat and the corresponding changes in the upper ocean thermal structure. It is anticipated that the oceanic data from this monitoring array will also be used in a predictive mode for initialization studies of regional coupled climate models. Of particular interest are zonal and meridional modes of ocean-atmosphere variability within the tropical Atlantic basin that have significant impacts on the regional climate of the bordering continents.

A Bayesian model for quantifying the change in mortality associated with future ozone exposures under climate change.

PubMed

Alexeeff, Stacey E; Pfister, Gabriele G; Nychka, Doug

2016-03-01

Climate change is expected to have many impacts on the environment, including changes in ozone concentrations at the surface level. A key public health concern is the potential increase in ozone-related summertime mortality if surface ozone concentrations rise in response to climate change. Although ozone formation depends partly on summertime weather, which exhibits considerable inter-annual variability, previous health impact studies have not incorporated the variability of ozone into their prediction models. A major source of uncertainty in the health impacts is the variability of the modeled ozone concentrations. We propose a Bayesian model and Monte Carlo estimation method for quantifying health effects of future ozone. An advantage of this approach is that we include the uncertainty in both the health effect association and the modeled ozone concentrations. Using our proposed approach, we quantify the expected change in ozone-related summertime mortality in the contiguous United States between 2000 and 2050 under a changing climate. The mortality estimates show regional patterns in the expected degree of impact. We also illustrate the results when using a common technique in previous work that averages ozone to reduce the size of the data, and contrast these findings with our own. Our analysis yields more realistic inferences, providing clearer interpretation for decision making regarding the impacts of climate change. © 2015, The International Biometric Society.

Future changes in peak river flows across northern Eurasia as inferred from an ensemble of regional climate projections under the IPCC RCP8.5 scenario

NASA Astrophysics Data System (ADS)

Shkolnik, Igor; Pavlova, Tatiana; Efimov, Sergey; Zhuravlev, Sergey

2018-01-01

Climate change simulation based on 30-member ensemble of Voeikov Main Geophysical Observatory RCM (resolution 25 km) for northern Eurasia is used to drive hydrological model CaMa-Flood. Using this modeling framework, we evaluate the uncertainties in the future projection of the peak river discharge and flood hazard by 2050-2059 relative to 1990-1999 under IPCC RCP8.5 scenario. Large ensemble size, along with reasonably high modeling resolution, allows one to efficiently sample natural climate variability and increase our ability to predict future changes in the hydrological extremes. It has been shown that the annual maximum river discharge can almost double by the mid-XXI century in the outlets of major Siberian rivers. In the western regions, there is a weak signal in the river discharge and flood hazard, hardly discernible above climate variability. Annual maximum flood area is projected to increase across Siberia mostly by 2-5% relative to the baseline period. A contribution of natural climate variability at different temporal scales to the uncertainty of ensemble prediction is discussed. The analysis shows that there expected considerable changes in the extreme river discharge probability at locations of the key hydropower facilities. This suggests that the extensive impact studies are required to develop recommendations for maintaining regional energy security.

Phenology at the crossroads?

NASA Astrophysics Data System (ADS)

Menzel, Annette

2014-05-01

Phenology is the study of the timing of natural events such as plant growth or animal migration. Currently nearly 500 papers are published annually that include 'phenolog*' in their title; many are related to anthropogenic change. Since seasonal events are triggered predominantly by climate, phenology has emerged as a key asset in identifying fingerprints of climate change in natural systems, especially since recent warming has been mirrored by significantly advancing spring events. Phenological changes have been reported across continents, habitats and taxa, predominantly as mean temporal changes ('trends') or as relationships to temperature and other drivers ('responses'), and have been summarised in various meta-analyses. However, a considerable variability in observed trends and responses is reported along with mixed messages of the footprint of climate change in nature. Phenology has made considerable advances but is a crossroads of understanding this variability. At the same time a change of emphasis in explanation, prediction and adaptation is emerging, which needs a full acknowledgement of this variability; likely yielding to more plasticity and resilience. In this review, I summarize current knowledge and recent insights into the role of • different observation methods, their accuracy and their target phenophases • observed events, species, traits, ontogenetic effects • species-specific safeguarding strategies, e.g. chilling, photoperiod • additional drivers other than climate, e.g. nutrients, GHG, biotic effects, anthropogenic / agricultural management • seasonal as well as spatio-temporal variation, effects of regional climate changes and analogous climates. This review clearly demonstrated that, comparable to weather and climate ensembles, only a full consideration of variation in responses allows a complete understanding of ecological, cultural and socioeconomic consequences of these phenological changes.

An evaluation of the variable-resolution CESM for modeling California's climate: Evaluation of VR-CESM for Modeling California's Climate

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

Huang, Xingying; Rhoades, Alan M.; Ullrich, Paul A.

In this paper, the recently developed variable-resolution option within the Community Earth System Model (VR-CESM) is assessed for long-term regional climate modeling of California at 0.25° (~ 28 km) and 0.125° (~ 14 km) horizontal resolutions. The mean climatology of near-surface temperature and precipitation is analyzed and contrasted with reanalysis, gridded observational data sets, and a traditional regional climate model (RCM)—the Weather Research and Forecasting (WRF) model. Statistical metrics for model evaluation and tests for differential significance have been extensively applied. VR-CESM tended to produce a warmer summer (by about 1–3°C) and overestimated overall winter precipitation (about 25%–35%) compared tomore » reference data sets when sea surface temperatures were prescribed. Increasing resolution from 0.25° to 0.125° did not produce a statistically significant improvement in the model results. By comparison, the analogous WRF climatology (constrained laterally and at the sea surface by ERA-Interim reanalysis) was ~1–3°C colder than the reference data sets, underestimated precipitation by ~20%–30% at 27 km resolution, and overestimated precipitation by ~ 65–85% at 9 km. Overall, VR-CESM produced comparable statistical biases to WRF in key climatological quantities. Moreover, this assessment highlights the value of variable-resolution global climate models (VRGCMs) in capturing fine-scale atmospheric processes, projecting future regional climate, and addressing the computational expense of uniform-resolution global climate models.« less

An evaluation of the variable-resolution CESM for modeling California's climate: Evaluation of VR-CESM for Modeling California's Climate

DOE PAGES

Huang, Xingying; Rhoades, Alan M.; Ullrich, Paul A.; ...

2016-03-01

In this paper, the recently developed variable-resolution option within the Community Earth System Model (VR-CESM) is assessed for long-term regional climate modeling of California at 0.25° (~ 28 km) and 0.125° (~ 14 km) horizontal resolutions. The mean climatology of near-surface temperature and precipitation is analyzed and contrasted with reanalysis, gridded observational data sets, and a traditional regional climate model (RCM)—the Weather Research and Forecasting (WRF) model. Statistical metrics for model evaluation and tests for differential significance have been extensively applied. VR-CESM tended to produce a warmer summer (by about 1–3°C) and overestimated overall winter precipitation (about 25%–35%) compared tomore » reference data sets when sea surface temperatures were prescribed. Increasing resolution from 0.25° to 0.125° did not produce a statistically significant improvement in the model results. By comparison, the analogous WRF climatology (constrained laterally and at the sea surface by ERA-Interim reanalysis) was ~1–3°C colder than the reference data sets, underestimated precipitation by ~20%–30% at 27 km resolution, and overestimated precipitation by ~ 65–85% at 9 km. Overall, VR-CESM produced comparable statistical biases to WRF in key climatological quantities. Moreover, this assessment highlights the value of variable-resolution global climate models (VRGCMs) in capturing fine-scale atmospheric processes, projecting future regional climate, and addressing the computational expense of uniform-resolution global climate models.« less

The Agricultural Model Intercomparison and Improvement Project: Phase I Activities by a Global Community of Science. Chapter 1

NASA Technical Reports Server (NTRS)

Rosenzweig, Cynthia E.; Jones, James W.; Hatfield, Jerry L.; Antle, John M.; Ruane, Alexander C.; Mutter, Carolyn Z.

2015-01-01

The Agricultural Model Intercomparison and Improvement Project (AgMIP) was founded in 2010. Its mission is to improve substantially the characterization of world food security as affected by climate variability and change, and to enhance adaptation capacity in both developing and developed countries. The objectives of AgMIP are to: Incorporate state-of-the-art climate, crop/livestock, and agricultural economic model improvements into coordinated multi-model regional and global assessments of future climate impacts and adaptation and other key aspects of the food system. Utilize multiple models, scenarios, locations, crops/livestock, and participants to explore uncertainty and the impact of data and methodological choices. Collaborate with regional experts in agronomy, animal sciences, economics, and climate to build a strong basis for model applications, addressing key climate related questions and sustainable intensification farming systems. Improve scientific and adaptive capacity in modeling for major agricultural regions in the developing and developed world, with a focus on vulnerable regions. Improve agricultural data and enhance data-sharing based on their intercomparison and evaluation using best scientific practices. Develop modeling frameworks to identify and evaluate promising adaptation technologies and policies and to prioritize strategies.

Continuation of the NVAP Global Water Vapor Data Sets for Pathfinder Science Analysis

NASA Technical Reports Server (NTRS)

VonderHaar, Thomas H.; Engelen, Richard J.; Forsythe, John M.; Randel, David L.; Ruston, Benjamin C.; Woo, Shannon; Dodge, James (Technical Monitor)

2001-01-01

This annual report covers August 2000 - August 2001 under NASA contract NASW-0032, entitled "Continuation of the NVAP (NASA's Water Vapor Project) Global Water Vapor Data Sets for Pathfinder Science Analysis". NASA has created a list of Earth Science Research Questions which are outlined by Asrar, et al. Particularly relevant to NVAP are the following questions: (a) How are global precipitation, evaporation, and the cycling of water changing? (b) What trends in atmospheric constituents and solar radiation are driving global climate? (c) How well can long-term climatic trends be assessed or predicted? Water vapor is a key greenhouse gas, and an understanding of its behavior is essential in global climate studies. Therefore, NVAP plays a key role in addressing the above climate questions by creating a long-term global water vapor dataset and by updating the dataset with recent advances in satellite instrumentation. The NVAP dataset produced from 1988-1998 has found wide use in the scientific community. Studies of interannual variability are particularly important. A recent paper by Simpson, et al. that examined the NVAP dataset in detail has shown that its relative accuracy is sufficient for the variability studies that contribute toward meeting NASA's goals. In the past year, we have made steady progress towards continuing production of this high-quality dataset as well as performing our own investigations of the data. This report summarizes the past year's work on production of the NVAP dataset and presents results of analyses we have performed in the past year.

Effects of Global Change on U.S. Urban Areas: Vulnerabilities, Impacts, and Adaptation

NASA Astrophysics Data System (ADS)

Quattrochi, D. A.; Wilbanks, T. J.; Kirshen, P. H.; Romero-Lankao, P.; Rosenzweig, C. E.; Ruth, M.; Solecki, W.; Tarr, J. A.

2007-05-01

Human settlements, both large and small, are where the vast majority of people on the Earth live. Expansion of cities both in population and areal extent, is a relentless process that will accelerate in the 21st century. As a consequence of urban growth both in the United States and around the globe, it is important to develop an understanding of how urbanization will affect the local and regional environment. Of equal importance, however, is the assessment of how cities will be impacted by the looming prospects of global climate change and climate variability. The potential impacts of climate change and variability has recently been enunciated by the IPCC's "Climate Change 2007" report. Moreover, the U.S. Climate Change Science Program (CCSP) is preparing a series of "Synthesis and Assessment Products" (SAP) reports to support informed discussion and decision making regarding climate change and variability by policy makers, resource managers, stakeholders, the media, and the general public. We are working on a chapter of SAP 4.6 ("Analysis of the Effects of Global Chance on Human Health and Welfare and Human Systems") wherein we wish to describe the effects of global climate change on human settlements. This paper will present the thoughts and ideas that are being formulated for our SAP report that relate to what vulnerabilities and impacts will occur, what adaptation responses may take place, and what possible effects on settlement patterns and characteristics will potentially arise, on human settlements in the U.S. as a result of climate change and climate variability. We wish to present these ideas and concepts as a "work in progress" that are subject to several rounds of review, and we invite comments from listeners at this session on the rationale and veracity of our thoughts. Additionally, we wish to explore how technology such as remote sensing data coupled with modeling, can be employed as synthesis tools for deriving insight across a spectrum of impacts (e.g. public health, urban planning for mitigation strategies) on how cities can cope and adapt to climate change and variability. This latter point parallels the concepts and ideas presented in the U.S. National Academy of Sciences, Decadal Survey report on "Earth Science Applications from Space: National Imperatives for the Next Decade and Beyond" wherein the analysis of the impacts of climate change and variability, human health, and land use change are listed as key areas for development of future Earth observing remote sensing systems.

Adapting to climate variability and change: experiences from cereal-based farming in the central rift and Kobo Valleys, Ethiopia.

PubMed

Kassie, Belay Tseganeh; Hengsdijk, Huib; Rötter, Reimund; Kahiluoto, Helena; Asseng, Senthold; Van Ittersum, Martin

2013-11-01

Small-holder farmers in Ethiopia are facing several climate related hazards, in particular highly variable rainfall with severe droughts which can have devastating effects on their livelihoods. Projected changes in climate are expected to aggravate the existing challenges. This study examines farmer perceptions on current climate variability and long-term changes, current adaptive strategies, and potential barriers for successful further adaptation in two case study regions-the Central Rift Valley (CRV) and Kobo Valley. The study was based on a household questionnaire, interviews with key stakeholders, and focus group discussions. The result revealed that about 99 % of the respondents at the CRV and 96 % at the Kobo Valley perceived an increase in temperature and 94 % at CRV and 91 % at the Kobo Valley perceived a decrease in rainfall over the last 20-30 years. Inter-annual and intraseasonal rainfall variability also has increased according to the farmers. The observed climate data (1977-2009) also showed an increasing trend in temperature and high inter-annual and intra-seasonal rainfall variability. In contrast to farmers' perceptions of a decrease in rainfall totals, observed rainfall data showed no statistically significant decline. The interaction among various bio-physical and socio-economic factors, changes in rainfall intensity and reduced water available to crops due to increased hot spells, may have influenced the perception of farmers with respect to rainfall trends. In recent decades, farmers in both the CRV and Kobo have changed farming practices to adapt to perceived climate change and variability, for example, through crop and variety choice, adjustment of cropping calendar, and in situ moisture conservation. These relatively low-cost changes in farm practices were within the limited adaptation capacity of farmers, which may be insufficient to deal with the impacts of future climate change. Anticipated climate change is expected to impose new risks outside the range of current experiences. To enable farmers to adapt to these impacts critical technological, institutional, and market-access constraints need to be removed. Inconsistencies between farmers' perceptions and observed climate trends (e.g., decrease in annual rainfall) could lead to sub-optimal or counterproductive adaptations, and therefore must be removed by better communication and capacity building, for example through Climate Field Schools. Enabling strategies, which are among others targeted at agricultural inputs, credit supply, market access, and strengthening of local knowledge and information services need to become integral part of government policies to assist farmers to adapt to the impacts of current and future climate change.

Adapting to Climate Variability and Change: Experiences from Cereal-Based Farming in the Central Rift and Kobo Valleys, Ethiopia

NASA Astrophysics Data System (ADS)

Kassie, Belay Tseganeh; Hengsdijk, Huib; Rötter, Reimund; Kahiluoto, Helena; Asseng, Senthold; Van Ittersum, Martin

2013-11-01

Small-holder farmers in Ethiopia are facing several climate related hazards, in particular highly variable rainfall with severe droughts which can have devastating effects on their livelihoods. Projected changes in climate are expected to aggravate the existing challenges. This study examines farmer perceptions on current climate variability and long-term changes, current adaptive strategies, and potential barriers for successful further adaptation in two case study regions—the Central Rift Valley (CRV) and Kobo Valley. The study was based on a household questionnaire, interviews with key stakeholders, and focus group discussions. The result revealed that about 99 % of the respondents at the CRV and 96 % at the Kobo Valley perceived an increase in temperature and 94 % at CRV and 91 % at the Kobo Valley perceived a decrease in rainfall over the last 20-30 years. Inter-annual and intraseasonal rainfall variability also has increased according to the farmers. The observed climate data (1977-2009) also showed an increasing trend in temperature and high inter-annual and intra-seasonal rainfall variability. In contrast to farmers’ perceptions of a decrease in rainfall totals, observed rainfall data showed no statistically significant decline. The interaction among various bio-physical and socio-economic factors, changes in rainfall intensity and reduced water available to crops due to increased hot spells, may have influenced the perception of farmers with respect to rainfall trends. In recent decades, farmers in both the CRV and Kobo have changed farming practices to adapt to perceived climate change and variability, for example, through crop and variety choice, adjustment of cropping calendar, and in situ moisture conservation. These relatively low-cost changes in farm practices were within the limited adaptation capacity of farmers, which may be insufficient to deal with the impacts of future climate change. Anticipated climate change is expected to impose new risks outside the range of current experiences. To enable farmers to adapt to these impacts critical technological, institutional, and market-access constraints need to be removed. Inconsistencies between farmers’ perceptions and observed climate trends (e.g., decrease in annual rainfall) could lead to sub-optimal or counterproductive adaptations, and therefore must be removed by better communication and capacity building, for example through Climate Field Schools. Enabling strategies, which are among others targeted at agricultural inputs, credit supply, market access, and strengthening of local knowledge and information services need to become integral part of government policies to assist farmers to adapt to the impacts of current and future climate change.

Climate Information Needs for Financial Decision Making

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

Higgins, Paul

Climate Information Needs for Financial Decision Making (Final Report) This Department of Energy workshop award (grant #DE-SC0008480) provided primary support for the American Meteorological Society’s study on climate information needs for financial decision making. The goal of this study was to help advance societal decision making by examining the implications of climate variability and change on near-term financial investments. We explored four key topics: 1) the conditions and criteria that influence returns on investment of major financial decisions, 2) the climate sensitivity of financial decisions, 3) climate information needs of financial decision makers, and 4) potential new mechanisms to promotemore » collaboration between scientists and financial decision makers. Better understanding of these four topics will help scientists provide the most useful information and enable financial decision makers to use scientific information most effectively. As a result, this study will enable leaders in business and government to make well-informed choices that help maximize long-term economic success and social wellbeing in the United States The outcomes of the study include a workshop, which brought together leaders from the scientific and financial decision making communities, a publication of the study report, and a public briefing of the results to the policy community. In addition, we will present the results to the scientific community at the AMS Annual Meeting in February, 2014. The study results were covered well by the media including Bloomberg News and E&E News. Upon request, we also briefed the Office of Science Technology Policy (OSTP) and the Council on Environmental Quality (CEQ) on the outcomes. We presented the results to the policy community through a public briefing in December on Capitol Hill. The full report is publicly available at www.ametsoc.org/cin. Summary of Key Findings The United States invests roughly $1.5 trillion U.S. dollars (USD) in capital assets each year across the public and private sectors (Orszag 2008; United States Census Bureau 2013). Extreme weather events create and exacerbate risks to these financial investments by contributing to: • Direct physical impacts on the investments themselves • Degradation of critical supporting infrastructure • Changes in the availability of key natural resources • Changes to workforce availability or capacity • Changes in the customer base • Supply chain disruptions • Legal liability • Shifts in the regulatory environment • Reductions in credit ratings Even small changes in weather can impact operations in critical economic sectors. As a result, maximizing returns on financial investments depends on accurately understanding and effectively accounting for these risks. Climate variability and change can either exacerbate existing risks or cause new sources of risk to emerge. Managing these risks most effectively will depend on scientific advances and increases in the capacity of financial decision makers to use the scientific knowledge that results. Barriers to using climate information must also be overcome. This study proposes three predefined levels of certainty for communicating about weather and climate risks: 1) possible (i.e., unknown likelihood or less than 50% chance of occurrence), 2) probable (greater than 50% chance of occurrence), and 3) effectively certain (at least 95% chance of occurrence). For example, it is effectively certain that a change in climate will alter weather patterns. It is probable that climate warming will cause increases in the intensity of some extreme events. It is possible that climate change will cause major and widespread disruptions to key planetary life-support services. Key recommendations of this study: 1) Identify climate-related risks and opportunities for financial decision making. 2) Create a framework to translate scientific information in clear and actionable terms for financial decision makers. 3) Analyze existing climate assessments and translate projected impacts into possible, probable, and effectively certain impacts. 4) Improve climate projections with respect to precipitation (timing, amount, and intensity), extreme events, and tails of probability distributions (i.e., low-probability but high-consequence events). 5) Increase spatial resolution of climate projections in order to provide climate information at the scale most relevant to financial investments. 6) Improve projections of the societal consequences of climate impacts through integrated assessments of physical, natural, and social sciences. 7) Create a user-friendly information repository and portal that provides easy access to information relevant to financial decision making. 8) Create and maintain opportunities to bring together financial decision makers, scientists, and service providers. Near-term financial decisions have long-term implications for the United States’ social and economic well-being that depend, in part, on climate variability and change. Investments will be most successful, and will advance the interests of society most effectively, if they are grounded in the best available knowledge & understanding.« less

Analysis on flood generation processes by means of a continuous simulation model

NASA Astrophysics Data System (ADS)

Fiorentino, M.; Gioia, A.; Iacobellis, V.; Manfreda, S.

2006-03-01

In the present research, we exploited a continuous hydrological simulation to investigate on key variables responsible of flood peak formation. With this purpose, a distributed hydrological model (DREAM) is used in cascade with a rainfall generator (IRP-Iterated Random Pulse) to simulate a large number of extreme events providing insight into the main controls of flood generation mechanisms. Investigated variables are those used in theoretically derived probability distribution of floods based on the concept of partial contributing area (e.g. Iacobellis and Fiorentino, 2000). The continuous simulation model is used to investigate on the hydrological losses occurring during extreme events, the variability of the source area contributing to the flood peak and its lag-time. Results suggest interesting simplification for the theoretical probability distribution of floods according to the different climatic and geomorfologic environments. The study is applied to two basins located in Southern Italy with different climatic characteristics.

Climate change impacts and adaptive strategies: lessons from the grapevine.

PubMed

Mosedale, Jonathan R; Abernethy, Kirsten E; Smart, Richard E; Wilson, Robert J; Maclean, Ilya M D

2016-11-01

The cultivation of grapevines for winemaking, known as viticulture, is widely cited as a climate-sensitive agricultural system that has been used as an indicator of both historic and contemporary climate change. Numerous studies have questioned the viability of major viticulture regions under future climate projections. We review the methods used to study the impacts of climate change on viticulture in the light of what is known about the effects of climate and weather on the yields and quality of vineyard harvests. Many potential impacts of climate change on viticulture, particularly those associated with a change in climate variability or seasonal weather patterns, are rarely captured. Key biophysical characteristics of viticulture are often unaccounted for, including the variability of grapevine phenology and the exploitation of microclimatic niches that permit successful cultivation under suboptimal macroclimatic conditions. We consider how these same biophysical characteristics permit a variety of strategies by which viticulture can adapt to changing climatic conditions. The ability to realize these strategies, however, is affected by uneven exposure to risks across the winemaking sector, and the evolving capacity for decision-making within and across organizational boundaries. The role grape provenance plays in shaping perceptions of wine value and quality illustrates how conflicts of interest influence decisions about adaptive strategies within the industry. We conclude by considering what lessons can be taken from viticulture for studies of climate change impacts and the capacity for adaptation in other agricultural and natural systems. © 2016 John Wiley & Sons Ltd.

Comparative study of air-conditioning energy use of four office buildings in China and USA

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

Zhou, Xin; Yan, Da; An, Jingjing

Energy use in buildings has great variability. In order to design and operate low energy buildings as well as to establish building energy codes and standards and effective energy policy, it is crucial to understand and quantify key factors influencing building energy performance. Here, this study investigates air-conditioning (AC) energy use of four office buildings in four locations: Beijing, Taiwan, Hong Kong, and Berkeley. Building simulation was employed to quantify the influences of key factors, including climate, building envelope and occupant behavior. Through simulation of various combinations of the three influencing elements, it is found that climate can lead tomore » AC cooling consumption differences by almost two times, while occupant behavior resulted in the greatest differences (of up to three times) in AC cooling consumption. The influence of occupant behavior on AC energy consumption is not homogeneous. Under similar climates, when the occupant behavior in the building differed, the optimized building envelope design also differed. In conclusion, the optimal building envelope should be determined according to the climate as well as the occupants who use the building.« less

Comparative study of air-conditioning energy use of four office buildings in China and USA

DOE PAGES

Zhou, Xin; Yan, Da; An, Jingjing; ...

2018-04-05

Energy use in buildings has great variability. In order to design and operate low energy buildings as well as to establish building energy codes and standards and effective energy policy, it is crucial to understand and quantify key factors influencing building energy performance. Here, this study investigates air-conditioning (AC) energy use of four office buildings in four locations: Beijing, Taiwan, Hong Kong, and Berkeley. Building simulation was employed to quantify the influences of key factors, including climate, building envelope and occupant behavior. Through simulation of various combinations of the three influencing elements, it is found that climate can lead tomore » AC cooling consumption differences by almost two times, while occupant behavior resulted in the greatest differences (of up to three times) in AC cooling consumption. The influence of occupant behavior on AC energy consumption is not homogeneous. Under similar climates, when the occupant behavior in the building differed, the optimized building envelope design also differed. In conclusion, the optimal building envelope should be determined according to the climate as well as the occupants who use the building.« less

On the key role of droughts in the dynamics of summer fires in Mediterranean Europe.

PubMed

Turco, Marco; von Hardenberg, Jost; AghaKouchak, Amir; Llasat, Maria Carmen; Provenzale, Antonello; Trigo, Ricardo M

2017-03-06

Summer fires frequently rage across Mediterranean Europe, often intensified by high temperatures and droughts. According to the state-of-the-art regional fire risk projections, in forthcoming decades climate effects are expected to become stronger and possibly overcome fire prevention efforts. However, significant uncertainties exist and the direct effect of climate change in regulating fuel moisture (e.g. warmer conditions increasing fuel dryness) could be counterbalanced by the indirect effects on fuel structure (e.g. warmer conditions limiting fuel amount), affecting the transition between climate-driven and fuel-limited fire regimes as temperatures increase. Here we analyse and model the impact of coincident drought and antecedent wet conditions (proxy for the climatic factor influencing total fuel and fine fuel structure) on the summer Burned Area (BA) across all eco-regions in Mediterranean Europe. This approach allows BA to be linked to the key drivers of fire in the region. We show a statistically significant relationship between fire and same-summer droughts in most regions, while antecedent climate conditions play a relatively minor role, except in few specific eco-regions. The presented models for individual eco-regions provide insights on the impacts of climate variability on BA, and appear to be promising for developing a seasonal forecast system supporting fire management strategies.

Linear and non-linear responses of vegetation and soils to glacial-interglacial climate change in a Mediterranean refuge.

PubMed

Holtvoeth, Jens; Vogel, Hendrik; Valsecchi, Verushka; Lindhorst, Katja; Schouten, Stefan; Wagner, Bernd; Wolff, George A

2017-08-14

The impact of past global climate change on local terrestrial ecosystems and their vegetation and soil organic matter (OM) pools is often non-linear and poorly constrained. To address this, we investigated the response of a temperate habitat influenced by global climate change in a key glacial refuge, Lake Ohrid (Albania, Macedonia). We applied independent geochemical and palynological proxies to a sedimentary archive from the lake over the penultimate glacial-interglacial transition (MIS 6-5) and the following interglacial (MIS 5e-c), targeting lake surface temperature as an indicator of regional climatic development and the supply of pollen and biomarkers from the vegetation and soil OM pools to determine local habitat response. Climate fluctuations strongly influenced the ecosystem, however, lake level controls the extent of terrace surfaces between the shoreline and mountain slopes and hence local vegetation, soil development and OM export to the lake sediments. There were two phases of transgressional soil erosion from terrace surfaces during lake-level rise in the MIS 6-5 transition that led to habitat loss for the locally dominant pine vegetation as the terraces drowned. Our observations confirm that catchment morphology plays a key role in providing refuges with low groundwater depth and stable soils during variable climate.

Teleconnections in the Presence of Climate Change: A Case Study of the Annular Modes

NASA Astrophysics Data System (ADS)

Gerber, Edwin; Baldwin, Mark

2010-05-01

Long model integrations of future and past climates present a problem for defining teleconnection patterns through Empirical Orthogonal Function (EOF) or correlation analysis when trends in the underlying climate begin to dominate the covariance structure. Similar issues may soon appear in observations as the record becomes longer, especially if climate trends accelerate. The Northern and Southern Annular Modes provide a prime example, because the poleward shift of the jet streams strongly projects onto these patterns, particularly in the Southern Hemisphere. Climate forecasts of the 21st century by chemistry climate models provide a case study. Computation of the annular modes in these long data sets with secular trends requires refinement of the standard definition of the annular mode, and a more robust procedure that allows for slowly varying trends is established and verified. The new procedure involves two key changes. First, the global mean geopotential height is removed at each time step before computing anomalies. This is particularly important high in the atmosphere, where seasonal variations in geopotential height become significant, and filters out trends due to changes in the temperature structure of the atmosphere. Pattern definition can be very sensitive near the tropopause, as regions of the atmosphere that used to be more of stratospheric character begin to take on tropospheric characteristics as the tropopause rises. The second change is to define anomalies relative to a slowly evolving seasonal climatology, so that the covariance structure reflects internal variability. Once these changes are accounted for, it is found that the zonal mean variability of the atmosphere stays remarkably constant, despite significant changes in the baseline climate forecast for the rest of the century. This stability of the internal variability makes it possible to relate trends in climate to teleconnections.

Application of scenario-neutral methods to quantify impacts of climate change on water resources in East Africa

NASA Astrophysics Data System (ADS)

Ascott, M.; Macdonald, D.; Lapworth, D.; Tindimugaya, C.

2017-12-01

Quantification of the impact of climate change on water resources is essential for future resource planning. Unfortunately, climate change impact studies in African regions are often hindered by the extent in variability in future rainfall predictions, which also diverge from current drying trends. To overcome this limitation, "scenario-neutral" methods have been developed which stress a hydrological system using a wide range of climate futures to build a "climate response surface". We developed a hydrological model and scenario-neutral framework to quantify climate change impacts on river flows in the Katonga catchment, Uganda. Using the lumped catchment model GR4J, an acceptable calibration to historic daily flows (1966 - 2010, NSE = 0.69) was achieved. Using a delta change approach, we then systematically changed rainfall and PET inputs to develop response surfaces for key metrics, developed with Ugandan water resources planners (e.g. Q5, Q95). Scenarios from the CMIP5 models for 2030s and 2050s were then overlain on the response surface. The CMIP5 scenarios show consistent increases in temperature but large variability in rainfall increases, which results in substantial variability in increases in river flows. The developed response surface covers a wide range of climate futures beyond the CMIP5 projections, and can help water resources planners understand the sensitivity of water resource systems to future changes. When future climate scenarios are available, these can be directly overlain on the response surface without the need to re-run the hydrological model. Further work will consider using scenario-neutral approaches in more complex, semi-distributed models (e.g. SWAT), and will consider land use and socioeconomic change.

An Evaluation of Antarctica as a Calibration Target for Passive Microwave Satellite Missions with Climate Data Record Applications

NASA Technical Reports Server (NTRS)

Kim, Edward

2011-01-01

Passive microwave remote sensing at L-band (1.4 GHz) is sensitive to soil moisture and sea surface salinity, both important climate variables. Science studies involving these variables can now take advantage of new satellite L-band observations. The first mission with regular global passive microwave observations at L-band is the European Space Agency's Soil Moisture and Ocean Salinity (SMOS), launched November, 2009. A second mission, NASA's Aquarius, was launched June, 201 I. A third mission, NASA's Soil Moisture Active Passive (SMAP) is scheduled to launch in 2014. Together, these three missions may provide a decade-long data record-provided that they are intercalibrated. The intercalibration is best performed at the radiance (brightness temperature) level, and Antarctica is proving to be a key calibration target. However, Antarctica has thus far not been fully characterized as a potential target. This paper will present evaluations of Antarctica as a microwave calibration target for the above satellite missions. Preliminary analyses have identified likely target areas, such as the vicinity of Dome-C and larger areas within East Antarctica. Physical sources of temporal and spatial variability of polar firn are key to assessing calibration uncertainty. These sources include spatial variability of accumulation rate, compaction, surface characteristics (dunes, micro-topography), wind patterns, and vertical profiles of density and temperature. Using primarily SMOS data, variability is being empirically characterized and attempts are being made to attribute observed variability to physical sources. One expected outcome of these studies is the potential discovery of techniques for remotely sensing--over all of Antarctica-parameters such as surface temperature.

Impacts of Austrian Climate Variability on Honey Bee Mortality

NASA Astrophysics Data System (ADS)

Switanek, Matt; Brodschneider, Robert; Crailsheim, Karl; Truhetz, Heimo

2015-04-01

Global food production, as it is today, is not possible without pollinators such as the honey bee. It is therefore alarming that honey bee populations across the world have seen increased mortality rates in the last few decades. The challenges facing the honey bee calls into question the future of our food supply. Beside various infectious diseases, Varroa destructor is one of the main culprits leading to increased rates of honey bee mortality. Varroa destructor is a parasitic mite which strongly depends on honey bee brood for reproduction and can wipe out entire colonies. However, climate variability may also importantly influence honey bee breeding cycles and bee mortality rates. Persistent weather events affects vegetation and hence foraging possibilities for honey bees. This study first defines critical statistical relationships between key climate indicators (e.g., precipitation and temperature) and bee mortality rates across Austria, using 6 consecutive years of data. Next, these leading indicators, as they vary in space and time, are used to build a statistical model to predict bee mortality rates and the respective number of colonies affected. Using leave-one-out cross validation, the model reduces the Root Mean Square Error (RMSE) by 21% with respect to predictions made with the mean mortality rate and the number of colonies. Furthermore, a Monte Carlo test is used to establish that the model's predictions are statistically significant at the 99.9% confidence level. These results highlight the influence of climate variables on honey bee populations, although variability in climate, by itself, cannot fully explain colony losses. This study was funded by the Austrian project 'Zukunft Biene'.

Atmospheric Parameter Climatologies from AIRS: Monitoring Short-, and Longer-Term Climate Variabilities and 'Trends'

NASA Technical Reports Server (NTRS)

Molnar, Gyula; Susskind, Joel

2008-01-01

The AIRS instrument is currently the best space-based tool to simultaneously monitor the vertical distribution of key climatically important atmospheric parameters as well as surface properties, and has provided high quality data for more than 5 years. AIRS analysis results produced at the GODDARD/DAAC, based on Versions 4 & 5 of the AIRS retrieval algorithm, are currently available for public use. Here, first we present an assessment of interrelationships of anomalies (proxies of climate variability based on 5 full years, since Sept. 2002) of various climate parameters at different spatial scales. We also present AIRS-retrievals-based global, regional and 1x1 degree grid-scale "trend"-analyses of important atmospheric parameters for this 5-year period. Note that here "trend" simply means the linear fit to the anomaly (relative the mean seasonal cycle) time series of various parameters at the above-mentioned spatial scales, and we present these to illustrate the usefulness of continuing AIRS-based climate observations. Preliminary validation efforts, in terms of intercomparisons of interannual variabilities with other available satellite data analysis results, will also be addressed. For example, we show that the outgoing longwave radiation (OLR) interannual spatial variabilities from the available state-of-the-art CERES measurements and from the AIRS computations are in remarkably good agreement. Version 6 of the AIRS retrieval scheme (currently under development) promises to further improve bias agreements for the absolute values by implementing a more accurate radiative transfer model for the OLR computations and by improving surface emissivity retrievals.

What Can Plasticity Contribute to Insect Responses to Climate Change?

PubMed

Sgrò, Carla M; Terblanche, John S; Hoffmann, Ary A

2016-01-01

Plastic responses figure prominently in discussions on insect adaptation to climate change. Here we review the different types of plastic responses and whether they contribute much to adaptation. Under climate change, plastic responses involving diapause are often critical for population persistence, but key diapause responses under dry and hot conditions remain poorly understood. Climate variability can impose large fitness costs on insects showing diapause and other life cycle responses, threatening population persistence. In response to stressful climatic conditions, insects also undergo ontogenetic changes including hardening and acclimation. Environmental conditions experienced across developmental stages or by prior generations can influence hardening and acclimation, although evidence for the latter remains weak. Costs and constraints influence patterns of plasticity across insect clades, but they are poorly understood within field contexts. Plastic responses and their evolution should be considered when predicting vulnerability to climate change-but meaningful empirical data lag behind theory.

Climate variability and change in high elevation regions: Past, present & future

USGS Publications Warehouse

Diaz, Henry F.; Grosjean, Martin; Graumlich, Lisa J.

2003-01-01

This special issue of Climatic Change contains a series of research and review articles, arising from papers that were presented and discussed at a workshop held in Davos, Switzerland on 25–28 June 2001. The workshop was titled ‘Climate Change at High Elevation Sites: Emerging Impacts’, and was convened to reprise an earlier conference on the same subject that was held in Wengen, Switzerland in 1995 (Diaz et al., 1997). The Davos meeting had as its main goals, a discussion of the following key issues: (1) reviewing recent climatic trends in high elevation regions of the world, (2) assessing the reliability of various biological indicators as indicators of climatic change, and (3) assessing whether physical impacts of climatic change in high elevation areas are becoming evident, and to discuss a range of monitoring strategies needed to observe and to understand the nature of any changes.

Cross-continent comparisons reveal differing environmental drivers of growth of the coral reef fish, Lutjanus bohar

NASA Astrophysics Data System (ADS)

Ong, Joyce J. L.; Rountrey, Adam N.; Marriott, Ross J.; Newman, Stephen J.; Meeuwig, Jessica J.; Meekan, Mark G.

2017-03-01

Biochronologies provide important insights into the growth responses of fishes to past variability in physical and biological environments and, in so doing, allow modelling of likely responses to climate change in the future. We examined spatial variability in the key drivers of inter-annual growth patterns of a widespread, tropical snapper, Lutjanus bohar, at similar tropical latitudes on the north-western and north-eastern coasts of the continent of Australia. For this study, we developed biochronologies from otoliths that provided proxies of somatic growth and these were analysed using mixed-effects models to examine the historical drivers of growth. Our analyses demonstrated that growth patterns of fish were driven by different climatic and biological factors in each region, including Pacific Ocean climate indices, regional sea level and the size structure of the fish community. Our results showed that the local oceanographic and biological context of reef systems strongly influenced the growth of L. bohar and that a single age-related growth trend cannot be assumed for separate populations of this species that are likely to experience different environmental conditions. Generalised predictions about the growth response of fishes to climate change will thus require adequate characterisation of the spatial variability in growth determinants likely to be found throughout the range of species that have cosmopolitan distributions.

The interplay between knowledge, perceived efficacy, and concern about global warming and climate change: a one-year longitudinal study.

PubMed

Milfont, Taciano L

2012-06-01

If the long-term goal of limiting warming to less than 2°C is to be achieved, rapid and sustained reductions of greenhouse gas emissions are required. These reductions will demand political leadership and widespread public support for action on global warming and climate change. Public knowledge, level of concern, and perceived personal efficacy, in positively affecting these issues are key variables in understanding public support for mitigation action. Previous research has documented some contradictory associations between knowledge, personal efficacy, and concern about global warming and climate change, but these cross-sectional findings limit inferences about temporal stability and direction of influence. This study examines the relationships between these three variables over a one-year period and three waves with national data from New Zealand. Results showed a positive association between the variables, and the pattern of findings was stable and consistent across the three data points. More importantly, results indicate that concern mediates the influence of knowledge on personal efficacy. Knowing more about global warming and climate change increases overall concern about the risks of these issues, and this increased concern leads to greater perceived efficacy and responsibility to help solving them. Implications for risk communication are discussed. © 2012 Society for Risk Analysis.

Selecting climate change scenarios for regional hydrologic impact studies based on climate extremes indices

NASA Astrophysics Data System (ADS)

Seo, Seung Beom; Kim, Young-Oh; Kim, Youngil; Eum, Hyung-Il

2018-04-01

When selecting a subset of climate change scenarios (GCM models), the priority is to ensure that the subset reflects the comprehensive range of possible model results for all variables concerned. Though many studies have attempted to improve the scenario selection, there is a lack of studies that discuss methods to ensure that the results from a subset of climate models contain the same range of uncertainty in hydrologic variables as when all models are considered. We applied the Katsavounidis-Kuo-Zhang (KKZ) algorithm to select a subset of climate change scenarios and demonstrated its ability to reduce the number of GCM models in an ensemble, while the ranges of multiple climate extremes indices were preserved. First, we analyzed the role of 27 ETCCDI climate extremes indices for scenario selection and selected the representative climate extreme indices. Before the selection of a subset, we excluded a few deficient GCM models that could not represent the observed climate regime. Subsequently, we discovered that a subset of GCM models selected by the KKZ algorithm with the representative climate extreme indices could not capture the full potential range of changes in hydrologic extremes (e.g., 3-day peak flow and 7-day low flow) in some regional case studies. However, the application of the KKZ algorithm with a different set of climate indices, which are correlated to the hydrologic extremes, enabled the overcoming of this limitation. Key climate indices, dependent on the hydrologic extremes to be projected, must therefore be determined prior to the selection of a subset of GCM models.

Land Cover Land Use change and soil organic carbon under climate variability in the semi-arid West African Sahel (1960-2050)

NASA Astrophysics Data System (ADS)

Dieye, Amadou M.

Land Cover Land Use (LCLU) change affects land surface processes recognized to influence climate change at local, national and global levels. Soil organic carbon is a key component for the functioning of agro-ecosystems and has a direct effect on the physical, chemical and biological characteristics of the soil. The capacity to model and project LCLU change is of considerable interest for mitigation and adaptation measures in response to climate change. A combination of remote sensing analyses, qualitative social survey techniques, and biogeochemical modeling was used to study the relationships between climate change, LCLU change and soil organic carbon in the semi-arid rural zone of Senegal between 1960 and 2050. For this purpose, four research hypotheses were addressed. This research aims to contribute to an understanding of future land cover land use change in the semi-arid West African Sahel with respect to climate variability and human activities. Its findings may provide insights to enable policy makers at local to national levels to formulate environmentally and economically adapted policy decisions. This dissertation research has to date resulted in two published and one submitted paper.

VALUE - Validating and Integrating Downscaling Methods for Climate Change Research

NASA Astrophysics Data System (ADS)

Maraun, Douglas; Widmann, Martin; Benestad, Rasmus; Kotlarski, Sven; Huth, Radan; Hertig, Elke; Wibig, Joanna; Gutierrez, Jose

2013-04-01

Our understanding of global climate change is mainly based on General Circulation Models (GCMs) with a relatively coarse resolution. Since climate change impacts are mainly experienced on regional scales, high-resolution climate change scenarios need to be derived from GCM simulations by downscaling. Several projects have been carried out over the last years to validate the performance of statistical and dynamical downscaling, yet several aspects have not been systematically addressed: variability on sub-daily, decadal and longer time-scales, extreme events, spatial variability and inter-variable relationships. Different downscaling approaches such as dynamical downscaling, statistical downscaling and bias correction approaches have not been systematically compared. Furthermore, collaboration between different communities, in particular regional climate modellers, statistical downscalers and statisticians has been limited. To address these gaps, the EU Cooperation in Science and Technology (COST) action VALUE (www.value-cost.eu) has been brought into life. VALUE is a research network with participants from currently 23 European countries running from 2012 to 2015. Its main aim is to systematically validate and develop downscaling methods for climate change research in order to improve regional climate change scenarios for use in climate impact studies. Inspired by the co-design idea of the international research initiative "future earth", stakeholders of climate change information have been involved in the definition of research questions to be addressed and are actively participating in the network. The key idea of VALUE is to identify the relevant weather and climate characteristics required as input for a wide range of impact models and to define an open framework to systematically validate these characteristics. Based on a range of benchmark data sets, in principle every downscaling method can be validated and compared with competing methods. The results of this exercise will directly provide end users with important information about the uncertainty of regional climate scenarios, and will furthermore provide the basis for further developing downscaling methods. This presentation will provide background information on VALUE and discuss the identified characteristics and the validation framework.

Improving plot- and regional-scale crop models for simulating impacts of climate variability and extremes

NASA Astrophysics Data System (ADS)

Tao, F.; Rötter, R.

2013-12-01

Many studies on global climate report that climate variability is increasing with more frequent and intense extreme events1. There are quite large uncertainties from both the plot- and regional-scale models in simulating impacts of climate variability and extremes on crop development, growth and productivity2,3. One key to reducing the uncertainties is better exploitation of experimental data to eliminate crop model deficiencies and develop better algorithms that more adequately capture the impacts of extreme events, such as high temperature and drought, on crop performance4,5. In the present study, in a first step, the inter-annual variability in wheat yield and climate from 1971 to 2012 in Finland was investigated. Using statistical approaches the impacts of climate variability and extremes on wheat growth and productivity were quantified. In a second step, a plot-scale model, WOFOST6, and a regional-scale crop model, MCWLA7, were calibrated and validated, and applied to simulate wheat growth and yield variability from 1971-2012. Next, the estimated impacts of high temperature stress, cold damage, and drought stress on crop growth and productivity based on the statistical approaches, and on crop simulation models WOFOST and MCWLA were compared. Then, the impact mechanisms of climate extremes on crop growth and productivity in the WOFOST model and MCWLA model were identified, and subsequently, the various algorithm and impact functions were fitted against the long-term crop trial data. Finally, the impact mechanisms, algorithms and functions in WOFOST model and MCWLA model were improved to better simulate the impacts of climate variability and extremes, particularly high temperature stress, cold damage and drought stress for location-specific and large area climate impact assessments. Our studies provide a good example of how to improve, in parallel, the plot- and regional-scale models for simulating impacts of climate variability and extremes, as needed for better informed decision-making on adaptation strategies. References 1. Coumou, D. & Rahmstorf, S. A decade of extremes. Nature Clim. Change, 2, 491-496 (2012). 2. Rötter, R. P., Carter, T. R., Olesen, J. E. & Porter, J. R. Crop-climate models need an overhaul. Nature Clim. Change, 1, 175-177 (2011). 3. Asseng, S. et al., Uncertainty in simulating wheat yields under climate change. Nature Clim. Change. 10.1038/nclimate1916. (2013). 4. Porter, J.R., & Semenov, M., Crop responses to climatic variation . Trans. R. Soc. B., 360, 2021-2035 (2005). 5. Porter, J.R. & Christensen, S. Deconstructing crop processes and models via identities. Plant, Cell and Environment . doi: 10.1111/pce.12107 (2013). 6. Boogaard, H.L., van Diepen C.A., Rötter R.P., Cabrera J.M. & van Laar H.H. User's guide for the WOFOST 7.1 crop growth simulation model and Control Center 1.5, Alterra, Wageningen, The Netherlands. (1998) 7. Tao, F. & Zhang, Z. Climate change, wheat productivity and water use in the North China Plain: a new super-ensemble-based probabilistic projection. Agric. Forest Meteorol., 170, 146-165. (2013).

Final Technical Report for "Collaborative Research: Regional climate-change projections through next-generation empirical and dynamical models"

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

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

2011-04-08

This project was a continuation of previous work under DOE CCPP funding in which we developed a twin approach of non-homogeneous hidden Markov models (NHMMs) and coupled ocean-atmosphere (O-A) intermediate-complexity models (ICMs) to identify the potentially predictable modes of climate variability, and to investigate their impacts on the regional-scale. We have developed a family of latent-variable NHMMs to simulate historical records of daily rainfall, and used them to downscale seasonal predictions. We have also developed empirical mode reduction (EMR) models for gaining insight into the underlying dynamics in observational data and general circulation model (GCM) simulations. Using coupled O-A ICMs,more » we have identified a new mechanism of interdecadal climate variability, involving the midlatitude oceans mesoscale eddy field and nonlinear, persistent atmospheric response to the oceanic anomalies. A related decadal mode is also identified, associated with the oceans thermohaline circulation. The goal of the continuation was to build on these ICM results and NHMM/EMR model developments and software to strengthen two key pillars of support for the development and application of climate models for climate change projections on time scales of decades to centuries, namely: (a) dynamical and theoretical understanding of decadal-to-interdecadal oscillations and their predictability; and (b) an interface from climate models to applications, in order to inform societal adaptation strategies to climate change at the regional scale, including model calibration, correction, downscaling and, most importantly, assessment and interpretation of spread and uncertainties in multi-model ensembles. Our main results from the grant consist of extensive further development of the hidden Markov models for rainfall simulation and downscaling specifically within the non-stationary climate change context together with the development of parallelized software; application of NHMMs to downscaling of rainfall projections over India; identification and analysis of decadal climate signals in data and models; and, studies of climate variability in terms of the dynamics of atmospheric flow regimes. Each of these project components is elaborated on below, followed by a list of publications resulting from the grant.« less

Final Technical Report for "Collaborative Research. Regional climate-change projections through next-generation empirical and dynamical models"

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

Kravtsov, S.; Robertson, Andrew W.; Ghil, Michael

2011-04-08

This project was a continuation of previous work under DOE CCPP funding in which we developed a twin approach of non-homogeneous hidden Markov models (NHMMs) and coupled ocean-atmosphere (O-A) intermediate-complexity models (ICMs) to identify the potentially predictable modes of climate variability, and to investigate their impacts on the regional-scale. We have developed a family of latent-variable NHMMs to simulate historical records of daily rainfall, and used them to downscale seasonal predictions. We have also developed empirical mode reduction (EMR) models for gaining insight into the underlying dynamics in observational data and general circulation model (GCM) simulations. Using coupled O-A ICMs,more » we have identified a new mechanism of interdecadal climate variability, involving the midlatitude oceans mesoscale eddy field and nonlinear, persistent atmospheric response to the oceanic anomalies. A related decadal mode is also identified, associated with the oceans thermohaline circulation. The goal of the continuation was to build on these ICM results and NHMM/EMR model developments and software to strengthen two key pillars of support for the development and application of climate models for climate change projections on time scales of decades to centuries, namely: (a) dynamical and theoretical understanding of decadal-to-interdecadal oscillations and their predictability; and (b) an interface from climate models to applications, in order to inform societal adaptation strategies to climate change at the regional scale, including model calibration, correction, downscaling and, most importantly, assessment and interpretation of spread and uncertainties in multi-model ensembles. Our main results from the grant consist of extensive further development of the hidden Markov models for rainfall simulation and downscaling specifically within the non-stationary climate change context together with the development of parallelized software; application of NHMMs to downscaling of rainfall projections over India; identification and analysis of decadal climate signals in data and models; and, studies of climate variability in terms of the dynamics of atmospheric flow regimes. Each of these project components is elaborated on below, followed by a list of publications resulting from the grant.« less

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

USGS Publications Warehouse

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

2013-01-01

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

Evaluating the performance of infectious disease forecasts: A comparison of climate-driven and seasonal dengue forecasts for Mexico.

PubMed

Johansson, Michael A; Reich, Nicholas G; Hota, Aditi; Brownstein, John S; Santillana, Mauricio

2016-09-26

Dengue viruses, which infect millions of people per year worldwide, cause large epidemics that strain healthcare systems. Despite diverse efforts to develop forecasting tools including autoregressive time series, climate-driven statistical, and mechanistic biological models, little work has been done to understand the contribution of different components to improved prediction. We developed a framework to assess and compare dengue forecasts produced from different types of models and evaluated the performance of seasonal autoregressive models with and without climate variables for forecasting dengue incidence in Mexico. Climate data did not significantly improve the predictive power of seasonal autoregressive models. Short-term and seasonal autocorrelation were key to improving short-term and long-term forecasts, respectively. Seasonal autoregressive models captured a substantial amount of dengue variability, but better models are needed to improve dengue forecasting. This framework contributes to the sparse literature of infectious disease prediction model evaluation, using state-of-the-art validation techniques such as out-of-sample testing and comparison to an appropriate reference model.

Evaluating the performance of infectious disease forecasts: A comparison of climate-driven and seasonal dengue forecasts for Mexico

PubMed Central

Johansson, Michael A.; Reich, Nicholas G.; Hota, Aditi; Brownstein, John S.; Santillana, Mauricio

2016-01-01

Dengue viruses, which infect millions of people per year worldwide, cause large epidemics that strain healthcare systems. Despite diverse efforts to develop forecasting tools including autoregressive time series, climate-driven statistical, and mechanistic biological models, little work has been done to understand the contribution of different components to improved prediction. We developed a framework to assess and compare dengue forecasts produced from different types of models and evaluated the performance of seasonal autoregressive models with and without climate variables for forecasting dengue incidence in Mexico. Climate data did not significantly improve the predictive power of seasonal autoregressive models. Short-term and seasonal autocorrelation were key to improving short-term and long-term forecasts, respectively. Seasonal autoregressive models captured a substantial amount of dengue variability, but better models are needed to improve dengue forecasting. This framework contributes to the sparse literature of infectious disease prediction model evaluation, using state-of-the-art validation techniques such as out-of-sample testing and comparison to an appropriate reference model. PMID:27665707

An Investigation of the Knowledge Claims Supporting Goal Based Planning and Organizational Culture as Keys to Excellence in Educational Organizations.

ERIC Educational Resources Information Center

Hossler, Don; And Others

Two independent bodies of organizational theory and research are developing around separate concepts associated with organizational effectiveness: goal-based behavior (intention) and organizational climate (distinction). Although both variables have been found to influence organizational effectiveness, findings have been inconsistent. The term…

Development of the Long-Term Agro-ecosystem Research (LTAR) Network: Current status and future trends

USDA-ARS?s Scientific Manuscript database

Long-term research conducted at multiple scales is critical to assessing the effects of key long term drivers (e.g., global population growth; land-use change; increased competition for natural resources; climate variability and change) on our ability to sustain or enhance agricultural production to...

Students Perspectives toward Key Personal Finance Variables

ERIC Educational Resources Information Center

Miller, Donald; Hite, Nancy Groneman; Slocombe, Tom; Railsback, Barbara

2010-01-01

Purpose: In the current economic climate, young people's attitudes and habits related to money management seem to be of great interest. The primary purpose of this study is to advance the knowledge base in the area of personal finance education. Methodology: This survey was administered by English teachers to a convenience sample population of 326…

Statistical methods for the analysis of climate extremes

NASA Astrophysics Data System (ADS)

Naveau, Philippe; Nogaj, Marta; Ammann, Caspar; Yiou, Pascal; Cooley, Daniel; Jomelli, Vincent

2005-08-01

Currently there is an increasing research activity in the area of climate extremes because they represent a key manifestation of non-linear systems and an enormous impact on economic and social human activities. Our understanding of the mean behavior of climate and its 'normal' variability has been improving significantly during the last decades. In comparison, climate extreme events have been hard to study and even harder to predict because they are, by definition, rare and obey different statistical laws than averages. In this context, the motivation for this paper is twofold. Firstly, we recall the basic principles of Extreme Value Theory that is used on a regular basis in finance and hydrology, but it still does not have the same success in climate studies. More precisely, the theoretical distributions of maxima and large peaks are recalled. The parameters of such distributions are estimated with the maximum likelihood estimation procedure that offers the flexibility to take into account explanatory variables in our analysis. Secondly, we detail three case-studies to show that this theory can provide a solid statistical foundation, specially when assessing the uncertainty associated with extreme events in a wide range of applications linked to the study of our climate. To cite this article: P. Naveau et al., C. R. Geoscience 337 (2005).

Assessing Soil Organic C Stability at the Continental Scale: An Analysis of Soil C and Radiocarbon Profiles Across the NEON Sites

NASA Astrophysics Data System (ADS)

Heckman, K. A.; Gallo, A.; Hatten, J. A.; Swanston, C.; McKnight, D. M.; Strahm, B. D.; Sanclements, M.

2017-12-01

Soil carbon stocks have become recognized as increasingly important in the context of climate change and global C cycle modeling. As modelers seek to identify key parameters affecting the size and stability of belowground C stocks, attention has been drawn to the mineral matrix and the soil physiochemical factors influenced by it. Though clay content has often been utilized as a convenient and key explanatory variable for soil C dynamics, its utility has recently come under scrutiny as new paradigms of soil organic matter stabilization have been developed. We utilized soil cores from a range of National Ecological Observatory Network (NEON) experimental plots to examine the influence of physicochemical parameters on soil C stocks and turnover, and their relative importance in comparison to climatic variables. Soils were cored at NEON sites, sampled by genetic horizon, and density separated into light fractions (particulate organics neither occluded within aggregates nor associated with mineral surfaces), occluded fractions (particulate organics occluded within aggregates), and heavy fractions (organics associated with mineral surfaces). Bulk soils and density fractions were measured for % C and radiocarbon abundance (as a measure of C stability). Carbon and radiocarbon abundances were examined among fractions and in the context of climatic variables (temperature, precipitation, elevation) and soil physiochemical variables (% clay and pH). No direct relationships between temperature and soil C or radiocarbon abundances were found. As a whole, soil radiocarbon abundance in density fractions decreased in the order of light>heavy>occluded, highlighting the importance of both surface sorption and aggregation to the preservation of organics. Radiocarbon abundance was correlated with pH, with variance also grouping by dominate vegetation type. Soil order was also identified as an important proxy variable for C and radiocarbon abundance. Preliminary results suggest that both integrative proxies as well as physicochemical properties may be needed to account for variation in soil C abundance and stability at the continental scale.

Climate change hampers endangered species through intensified moisture-related plant stresses (Invited)

NASA Astrophysics Data System (ADS)

Bartholomeus, R.; Witte, J.; van Bodegom, P.; Dam, J. V.; Aerts, R.

2010-12-01

With recent climate change, extremes in meteorological conditions are forecast and observed to increase globally, and to affect vegetation composition. More prolonged dry periods will alternate with more intensive rainfall events, both within and between years, which will change soil moisture dynamics. In temperate climates, soil moisture, in concert with nutrient availability and soil acidity, is the most important environmental filter in determining local plant species composition, as it determines the availability of both oxygen and water to plant roots. These resources are indispensable for meeting the physiological demands of plants. The consequences of climate change for our natural environment are among the most pressing issues of our time. The international research community is beginning to realise that climate extremes may be more powerful drivers of vegetation change and species extinctions than slow-and-steady climatic changes, but the causal mechanisms of such changes are presently unknown. The roles of amplitudes in water availability as drivers of vegetation change have been particularly elusive owing to the lack of integration of the key variables involved. Here we show that the combined effect of increased rainfall variability, temperature and atmospheric CO2-concentration will lead to an increased variability in both wet and dry extremes in stresses faced by plants (oxygen and water stress, respectively). We simulated these plant stresses with a novel, process-based approach, incorporating in detail the interacting processes in the soil-plant-atmosphere interface. In order to quantify oxygen and water stress with causal measures, we focused on interacting meteorological, soil physical, microbial, and plant physiological processes in the soil-plant-atmosphere system. As both the supply and demand of oxygen and water depend strongly on the prevailing meteorological conditions, both oxygen and water stress were calculated dynamically in time to capture climate change effects. We demonstrate that increased rainfall variability in interaction with predicted changes in temperature and CO2, affects soil moisture conditions and plant oxygen and water demands such, that both oxygen stress and water stress will intensify due to climate change. Moreover, these stresses will increasingly coincide, causing variable stress conditions. These variable stress conditions were found to decrease future habitat suitability, especially for plant species that are presently endangered. The future existence of such species is thus at risk by climate change, which has direct implications for policies to maintain endangered species, as applied by international nature management organisations (e.g. IUCN). Our integrated mechanistic analysis of two stresses combined, which has never been done so far, reveals large impacts of climate change on species extinctions and thereby on biodiversity.

Interannual variation of carbon fluxes from three contrasting evergreen forests: The role of forest dynamics and climate

USGS Publications Warehouse

Sierra, C.A.; Loescher, H.W.; Harmon, M.E.; Richardson, A.D.; Hollinger, D.Y.; Perakis, S.S.

2009-01-01

Interannual variation of carbon fluxes can be attributed to a number of biotic and abiotic controls that operate at different spatial and temporal scales. Type and frequency of disturbance, forest dynamics, and climate regimes are important sources of variability. Assessing the variability of carbon fluxes from these specific sources can enhance the interpretation of past and current observations. Being able to separate the variability caused by forest dynamics from that induced by climate will also give us the ability to determine if the current observed carbon fluxes are within an expected range or whether the ecosystem is undergoing unexpected change. Sources of interannual variation in ecosystem carbon fluxes from three evergreen ecosystems, a tropical, a temperate coniferous, and a boreal forest, were explored using the simulation model STANDCARB. We identified key processes that introduced variation in annual fluxes, but their relative importance differed among the ecosystems studied. In the tropical site, intrinsic forest dynamics contributed ?? 30% of the total variation in annual carbon fluxes. In the temperate and boreal sites, where many forest processes occur over longer temporal scales than those at the tropical site, climate controlled more of the variation among annual fluxes. These results suggest that climate-related variability affects the rates of carbon exchange differently among sites. Simulations in which temperature, precipitation, and radiation varied from year to year (based on historical records of climate variation) had less net carbon stores than simulations in which these variables were held constant (based on historical records of monthly average climate), a result caused by the functional relationship between temperature and respiration. This suggests that, under a more variable temperature regime, large respiratory pulses may become more frequent and high enough to cause a reduction in ecosystem carbon stores. Our results also show that the variation of annual carbon fluxes poses an important challenge in our ability to determine whether an ecosystem is a source, a sink, or is neutral in regard to CO2 at longer timescales. In simulations where climate change negatively affected ecosystem carbon stores, there was a 20% chance of committing Type II error, even with 20 years of sequential data. ?? 2009 by the Ecological Society of America.

Advancing a Model-Validated Statistical Method for Decomposing the Key Oceanic Drivers of Regional Climate: Focus on Northern and Tropical African Climate Variability in the Community Earth System Model (CESM)

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

Wang, Fuyao; Yu, Yan; Notaro, Michael

This study advances the practicality and stability of the traditional multivariate statistical method, generalized equilibrium feedback assessment (GEFA), for decomposing the key oceanic drivers of regional atmospheric variability, especially when available data records are short. An advanced stepwise GEFA methodology is introduced, in which unimportant forcings within the forcing matrix are eliminated through stepwise selection. Method validation of stepwise GEFA is performed using the CESM, with a focused application to northern and tropical Africa (NTA). First, a statistical assessment of the atmospheric response to each primary oceanic forcing is carried out by applying stepwise GEFA to a fully coupled controlmore » run. Then, a dynamical assessment of the atmospheric response to individual oceanic forcings is performed through ensemble experiments by imposing sea surface temperature anomalies over focal ocean basins. Finally, to quantify the reliability of stepwise GEFA, the statistical assessment is evaluated against the dynamical assessment in terms of four metrics: the percentage of grid cells with consistent response sign, the spatial correlation of atmospheric response patterns, the area-averaged seasonal cycle of response magnitude, and consistency in associated mechanisms between assessments. In CESM, tropical modes, namely El Niño–Southern Oscillation and the tropical Indian Ocean Basin, tropical Indian Ocean dipole, and tropical Atlantic Niño modes, are the dominant oceanic controls of NTA climate. In complementary studies, stepwise GEFA is validated in terms of isolating terrestrial forcings on the atmosphere, and observed oceanic and terrestrial drivers of NTA climate are extracted to establish an observational benchmark for subsequent coupled model evaluation and development of process-based weights for regional climate projections.« less

Advancing a Model-Validated Statistical Method for Decomposing the Key Oceanic Drivers of Regional Climate: Focus on Northern and Tropical African Climate Variability in the Community Earth System Model (CESM)

DOE PAGES

Wang, Fuyao; Yu, Yan; Notaro, Michael; ...

2017-09-27

This study advances the practicality and stability of the traditional multivariate statistical method, generalized equilibrium feedback assessment (GEFA), for decomposing the key oceanic drivers of regional atmospheric variability, especially when available data records are short. An advanced stepwise GEFA methodology is introduced, in which unimportant forcings within the forcing matrix are eliminated through stepwise selection. Method validation of stepwise GEFA is performed using the CESM, with a focused application to northern and tropical Africa (NTA). First, a statistical assessment of the atmospheric response to each primary oceanic forcing is carried out by applying stepwise GEFA to a fully coupled controlmore » run. Then, a dynamical assessment of the atmospheric response to individual oceanic forcings is performed through ensemble experiments by imposing sea surface temperature anomalies over focal ocean basins. Finally, to quantify the reliability of stepwise GEFA, the statistical assessment is evaluated against the dynamical assessment in terms of four metrics: the percentage of grid cells with consistent response sign, the spatial correlation of atmospheric response patterns, the area-averaged seasonal cycle of response magnitude, and consistency in associated mechanisms between assessments. In CESM, tropical modes, namely El Niño–Southern Oscillation and the tropical Indian Ocean Basin, tropical Indian Ocean dipole, and tropical Atlantic Niño modes, are the dominant oceanic controls of NTA climate. In complementary studies, stepwise GEFA is validated in terms of isolating terrestrial forcings on the atmosphere, and observed oceanic and terrestrial drivers of NTA climate are extracted to establish an observational benchmark for subsequent coupled model evaluation and development of process-based weights for regional climate projections.« less

An integrated risk and vulnerability assessment framework for climate change and malaria transmission in East Africa.

PubMed

Onyango, Esther Achieng; Sahin, Oz; Awiti, Alex; Chu, Cordia; Mackey, Brendan

2016-11-11

Malaria is one of the key research concerns in climate change-health relationships. Numerous risk assessments and modelling studies provide evidence that the transmission range of malaria will expand with rising temperatures, adversely impacting on vulnerable communities in the East African highlands. While there exist multiple lines of evidence for the influence of climate change on malaria transmission, there is insufficient understanding of the complex and interdependent factors that determine the risk and vulnerability of human populations at the community level. Moreover, existing studies have had limited focus on the nature of the impacts on vulnerable communities or how well they are prepared to cope. In order to address these gaps, a systems approach was used to present an integrated risk and vulnerability assessment framework for studies of community level risk and vulnerability to malaria due to climate change. Drawing upon published literature on existing frameworks, a systems approach was applied to characterize the factors influencing the interactions between climate change and malaria transmission. This involved structural analysis to determine influential, relay, dependent and autonomous variables in order to construct a detailed causal loop conceptual model that illustrates the relationships among key variables. An integrated assessment framework that considers indicators of both biophysical and social vulnerability was proposed based on the conceptual model. A major conclusion was that this integrated assessment framework can be implemented using Bayesian Belief Networks, and applied at a community level using both quantitative and qualitative methods with stakeholder engagement. The approach enables a robust assessment of community level risk and vulnerability to malaria, along with contextually relevant and targeted adaptation strategies for dealing with malaria transmission that incorporate both scientific and community perspectives.

Climate variability and change in the United States: potential impacts on water- and foodborne diseases caused by microbiologic agents.

PubMed Central

Rose, J B; Epstein, P R; Lipp, E K; Sherman, B H; Bernard, S M; Patz, J A

2001-01-01

Exposure to waterborne and foodborne pathogens can occur via drinking water (associated with fecal contamination), seafood (due to natural microbial hazards, toxins, or wastewater disposal) or fresh produce (irrigated or processed with contaminated water). Weather influences the transport and dissemination of these microbial agents via rainfall and runoff and the survival and/or growth through such factors as temperature. Federal and state laws and regulatory programs protect much of the U.S. population from waterborne disease; however, if climate variability increases, current and future deficiencies in areas such as watershed protection, infrastructure, and storm drainage systems will probably increase the risk of contamination events. Knowledge about transport processes and the fate of microbial pollutants associated with rainfall and snowmelt is key to predicting risks from a change in weather variability. Although recent studies identified links between climate variability and occurrence of microbial agents in water, the relationships need further quantification in the context of other stresses. In the marine environment as well, there are few studies that adequately address the potential health effects of climate variability in combination with other stresses such as overfishing, introduced species, and rise in sea level. Advances in monitoring are necessary to enhance early-warning and prevention capabilities. Application of existing technologies, such as molecular fingerprinting to track contaminant sources or satellite remote sensing to detect coastal algal blooms, could be expanded. This assessment recommends incorporating a range of future scenarios of improvement plans for current deficiencies in the public health infrastructure to achieve more realistic risk assessments. PMID:11359688

Climate variability and change in the United States: potential impacts on water- and foodborne diseases caused by microbiologic agents.

PubMed

Rose, J B; Epstein, P R; Lipp, E K; Sherman, B H; Bernard, S M; Patz, J A

2001-05-01

Exposure to waterborne and foodborne pathogens can occur via drinking water (associated with fecal contamination), seafood (due to natural microbial hazards, toxins, or wastewater disposal) or fresh produce (irrigated or processed with contaminated water). Weather influences the transport and dissemination of these microbial agents via rainfall and runoff and the survival and/or growth through such factors as temperature. Federal and state laws and regulatory programs protect much of the U.S. population from waterborne disease; however, if climate variability increases, current and future deficiencies in areas such as watershed protection, infrastructure, and storm drainage systems will probably increase the risk of contamination events. Knowledge about transport processes and the fate of microbial pollutants associated with rainfall and snowmelt is key to predicting risks from a change in weather variability. Although recent studies identified links between climate variability and occurrence of microbial agents in water, the relationships need further quantification in the context of other stresses. In the marine environment as well, there are few studies that adequately address the potential health effects of climate variability in combination with other stresses such as overfishing, introduced species, and rise in sea level. Advances in monitoring are necessary to enhance early-warning and prevention capabilities. Application of existing technologies, such as molecular fingerprinting to track contaminant sources or satellite remote sensing to detect coastal algal blooms, could be expanded. This assessment recommends incorporating a range of future scenarios of improvement plans for current deficiencies in the public health infrastructure to achieve more realistic risk assessments.

Collaborative Research: Quantifying the Uncertainties of Aerosol Indirect Effects and Impacts on Decadal-Scale Climate Variability in NCAR CAM5 and CESM1

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

Nenes, Athanasios

The goal of this proposed project is to assess the climatic importance and sensitivity of aerosol indirect effect (AIE) to cloud and aerosol processes and feedbacks, which include organic aerosol hygroscopicity, cloud condensation nuclei (CCN) activation kinetics, Giant CCN, cloud-scale entrainment, ice nucleation in mixed-phase and cirrus clouds, and treatment of subgrid variability of vertical velocity. A key objective was to link aerosol, cloud microphysics and dynamics feedbacks in CAM5 with a suite of internally consistent and integrated parameterizations that provide the appropriate degrees of freedom to capture the various aspects of the aerosol indirect effect. The proposal integrated newmore » parameterization elements into the cloud microphysics, moist turbulence and aerosol modules used by the NCAR Community Atmospheric Model version 5 (CAM5). The CAM5 model was then used to systematically quantify the uncertainties of aerosol indirect effects through a series of sensitivity tests with present-day and preindustrial aerosol emissions. New parameterization elements were developed as a result of these efforts, and new diagnostic tools & methodologies were also developed to quantify the impacts of aerosols on clouds and climate within fully coupled models. Observations were used to constrain key uncertainties in the aerosol-cloud links. Advanced sensitivity tools were developed and implements to probe the drivers of cloud microphysical variability with unprecedented temporal and spatial scale. All these results have been published in top and high impact journals (or are in the final stages of publication). This proposal has also supported a number of outstanding graduate students.« less

Adaptation of mammalian host-pathogen interactions in a changing arctic environment

PubMed Central

2011-01-01

Many arctic mammals are adapted to live year-round in extreme environments with low winter temperatures and great seasonal variations in key variables (e.g. sunlight, food, temperature, moisture). The interaction between hosts and pathogens in high northern latitudes is not very well understood with respect to intra-annual cycles (seasons). The annual cycles of interacting pathogen and host biology is regulated in part by highly synchronized temperature and photoperiod changes during seasonal transitions (e.g., freezeup and breakup). With a warming climate, only one of these key biological cues will undergo drastic changes, while the other will remain fixed. This uncoupling can theoretically have drastic consequences on host-pathogen interactions. These poorly understood cues together with a changing climate by itself will challenge host populations that are adapted to pathogens under the historic and current climate regime. We will review adaptations of both host and pathogens to the extreme conditions at high latitudes and explore some potential consequences of rapid changes in the Arctic. PMID:21392401

Adaptation of mammalian host-pathogen interactions in a changing arctic environment.

PubMed

Hueffer, Karsten; O'Hara, Todd M; Follmann, Erich H

2011-03-11

Many arctic mammals are adapted to live year-round in extreme environments with low winter temperatures and great seasonal variations in key variables (e.g. sunlight, food, temperature, moisture). The interaction between hosts and pathogens in high northern latitudes is not very well understood with respect to intra-annual cycles (seasons). The annual cycles of interacting pathogen and host biology is regulated in part by highly synchronized temperature and photoperiod changes during seasonal transitions (e.g., freezeup and breakup). With a warming climate, only one of these key biological cues will undergo drastic changes, while the other will remain fixed. This uncoupling can theoretically have drastic consequences on host-pathogen interactions. These poorly understood cues together with a changing climate by itself will challenge host populations that are adapted to pathogens under the historic and current climate regime. We will review adaptations of both host and pathogens to the extreme conditions at high latitudes and explore some potential consequences of rapid changes in the Arctic.

Millennial Climatic Fluctuations Are Key to the Structure of Last Glacial Ecosystems

PubMed Central

Huntley, Brian; Allen, Judy R. M.; Collingham, Yvonne C.; Hickler, Thomas; Lister, Adrian M.; Singarayer, Joy; Stuart, Anthony J.; Sykes, Martin T.; Valdes, Paul J.

2013-01-01

Whereas fossil evidence indicates extensive treeless vegetation and diverse grazing megafauna in Europe and northern Asia during the last glacial, experiments combining vegetation models and climate models have to-date simulated widespread persistence of trees. Resolving this conflict is key to understanding both last glacial ecosystems and extinction of most of the mega-herbivores. Using a dynamic vegetation model (DVM) we explored the implications of the differing climatic conditions generated by a general circulation model (GCM) in “normal” and “hosing” experiments. Whilst the former approximate interstadial conditions, the latter, designed to mimic Heinrich Events, approximate stadial conditions. The “hosing” experiments gave simulated European vegetation much closer in composition to that inferred from fossil evidence than did the “normal” experiments. Given the short duration of interstadials, and the rate at which forest cover expanded during the late-glacial and early Holocene, our results demonstrate the importance of millennial variability in determining the character of last glacial ecosystems. PMID:23613985

Millennial climatic fluctuations are key to the structure of last glacial ecosystems.

PubMed

Huntley, Brian; Allen, Judy R M; Collingham, Yvonne C; Hickler, Thomas; Lister, Adrian M; Singarayer, Joy; Stuart, Anthony J; Sykes, Martin T; Valdes, Paul J

2013-01-01

Whereas fossil evidence indicates extensive treeless vegetation and diverse grazing megafauna in Europe and northern Asia during the last glacial, experiments combining vegetation models and climate models have to-date simulated widespread persistence of trees. Resolving this conflict is key to understanding both last glacial ecosystems and extinction of most of the mega-herbivores. Using a dynamic vegetation model (DVM) we explored the implications of the differing climatic conditions generated by a general circulation model (GCM) in "normal" and "hosing" experiments. Whilst the former approximate interstadial conditions, the latter, designed to mimic Heinrich Events, approximate stadial conditions. The "hosing" experiments gave simulated European vegetation much closer in composition to that inferred from fossil evidence than did the "normal" experiments. Given the short duration of interstadials, and the rate at which forest cover expanded during the late-glacial and early Holocene, our results demonstrate the importance of millennial variability in determining the character of last glacial ecosystems.

Study of gravity waves propagation in the thermosphere of Mars based on MAVEN/NGIMS density measurements

NASA Astrophysics Data System (ADS)

Vals, M.

2017-09-01

We use MAVEN/NGIMS CO2 density measurements to analyse gravity waves in the thermosphere of Mars. In particular the seasonal/latitudinal variability of their amplitude is studied and interpreted. Key background parameters controlling the activity of gravity waves are analysed with the help of the Mars Climate Database (MCD). Gravity waves activity presents a good anti-correlation to the temperature variability retrieved from the MCD. An analysis at pressure levels is ongoing.

Collaborative Research: Improving Decadal Prediction of Arctic Climate Variability and Change Using a Regional Arctic

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

Gutowski, William J.

This project developed and applied a regional Arctic System model for enhanced decadal predictions. It built on successful research by four of the current PIs with support from the DOE Climate Change Prediction Program, which has resulted in the development of a fully coupled Regional Arctic Climate Model (RACM) consisting of atmosphere, land-hydrology, ocean and sea ice components. An expanded RACM, a Regional Arctic System Model (RASM), has been set up to include ice sheets, ice caps, mountain glaciers, and dynamic vegetation to allow investigation of coupled physical processes responsible for decadal-scale climate change and variability in the Arctic. RASMmore » can have high spatial resolution (~4-20 times higher than currently practical in global models) to advance modeling of critical processes and determine the need for their explicit representation in Global Earth System Models (GESMs). The pan-Arctic region is a key indicator of the state of global climate through polar amplification. However, a system-level understanding of critical arctic processes and feedbacks needs further development. Rapid climate change has occurred in a number of Arctic System components during the past few decades, including retreat of the perennial sea ice cover, increased surface melting of the Greenland ice sheet, acceleration and thinning of outlet glaciers, reduced snow cover, thawing permafrost, and shifts in vegetation. Such changes could have significant ramifications for global sea level, the ocean thermohaline circulation and heat budget, ecosystems, native communities, natural resource exploration, and commercial transportation. The overarching goal of the RASM project has been to advance understanding of past and present states of arctic climate and to improve seasonal to decadal predictions. To do this the project has focused on variability and long-term change of energy and freshwater flows through the arctic climate system. The three foci of this research are: - Changes in the freshwater flux between arctic climate system components resulting from decadal changes in land and sea ice, seasonal snow, vegetation, and ocean circulation. - Changing energetics due to decadal changes in ice mass, vegetation, and air-sea interactions. - The role of small-scale atmospheric and oceanic processes that influence decadal variability. This research has been addressing modes of natural climate variability as well as extreme and rapid climate change. RASM can facilitate studies of climate impacts (e.g., droughts and fires) and of ecosystem adaptations to these impacts.« less

Evaluation of Stochastic Rainfall Models in Capturing Climate Variability for Future Drought and Flood Risk Assessment

NASA Astrophysics Data System (ADS)

Chowdhury, A. F. M. K.; Lockart, N.; Willgoose, G. R.; Kuczera, G. A.; Kiem, A.; Nadeeka, P. M.

2016-12-01

One of the key objectives of stochastic rainfall modelling is to capture the full variability of climate system for future drought and flood risk assessment. However, it is not clear how well these models can capture the future climate variability when they are calibrated to Global/Regional Climate Model data (GCM/RCM) as these datasets are usually available for very short future period/s (e.g. 20 years). This study has assessed the ability of two stochastic daily rainfall models to capture climate variability by calibrating them to a dynamically downscaled RCM dataset in an east Australian catchment for 1990-2010, 2020-2040, and 2060-2080 epochs. The two stochastic models are: (1) a hierarchical Markov Chain (MC) model, which we developed in a previous study and (2) a semi-parametric MC model developed by Mehrotra and Sharma (2007). Our hierarchical model uses stochastic parameters of MC and Gamma distribution, while the semi-parametric model uses a modified MC process with memory of past periods and kernel density estimation. This study has generated multiple realizations of rainfall series by using parameters of each model calibrated to the RCM dataset for each epoch. The generated rainfall series are used to generate synthetic streamflow by using a SimHyd hydrology model. Assessing the synthetic rainfall and streamflow series, this study has found that both stochastic models can incorporate a range of variability in rainfall as well as streamflow generation for both current and future periods. However, the hierarchical model tends to overestimate the multiyear variability of wet spell lengths (therefore, is less likely to simulate long periods of drought and flood), while the semi-parametric model tends to overestimate the mean annual rainfall depths and streamflow volumes (hence, simulated droughts are likely to be less severe). Sensitivity of these limitations of both stochastic models in terms of future drought and flood risk assessment will be discussed.

An advanced stochastic weather generator for simulating 2-D high-resolution climate variables

NASA Astrophysics Data System (ADS)

Peleg, Nadav; Fatichi, Simone; Paschalis, Athanasios; Molnar, Peter; Burlando, Paolo

2017-07-01

A new stochastic weather generator, Advanced WEather GENerator for a two-dimensional grid (AWE-GEN-2d) is presented. The model combines physical and stochastic approaches to simulate key meteorological variables at high spatial and temporal resolution: 2 km × 2 km and 5 min for precipitation and cloud cover and 100 m × 100 m and 1 h for near-surface air temperature, solar radiation, vapor pressure, atmospheric pressure, and near-surface wind. The model requires spatially distributed data for the calibration process, which can nowadays be obtained by remote sensing devices (weather radar and satellites), reanalysis data sets and ground stations. AWE-GEN-2d is parsimonious in terms of computational demand and therefore is particularly suitable for studies where exploring internal climatic variability at multiple spatial and temporal scales is fundamental. Applications of the model include models of environmental systems, such as hydrological and geomorphological models, where high-resolution spatial and temporal meteorological forcing is crucial. The weather generator was calibrated and validated for the Engelberg region, an area with complex topography in the Swiss Alps. Model test shows that the climate variables are generated by AWE-GEN-2d with a level of accuracy that is sufficient for many practical applications.

Stoichiometry of hydrological C, N, and P losses across climate and geology: An environmental matrix approach across New Zealand primary forests

NASA Astrophysics Data System (ADS)

McGroddy, M. E.; Baisden, W. T.; Hedin, L. O.

2008-03-01

Hydrologic losses can play a key role in regulating ecosystem nutrient balances, particularly in regions where baseline nutrient cycles are not augmented by industrial deposition. We used first-order streams to integrate hydrologic losses at the watershed scale across unpolluted old-growth forests in New Zealand. We employed a matrix approach to resolve how stream water concentrations of dissolved organic carbon (DOC), organic and inorganic nitrogen (DON and DIN), and organic and inorganic phosphorus (DOP and DIP) varied as a function of landscape differences in climate and geology. We found stream water total dissolved nitrogen (TDN) to be dominated by organic forms (medians for DON, 81.3%, nitrate-N, 12.6%, and ammonium-N, 3.9%). The median stream water DOC:TDN:TDP molar ratio of 1050:21:1 favored C slightly over N and P when compared to typical temperate forest foliage ratios. Using the full set of variables in a multiple regression approach explained approximately half of the variability in DON, DOC, and TDP concentrations. Building on this approach we combined a simplified set of variables with a simple water balance model in a regression designed to predict DON export at larger spatial scales. Incorporating the effects of climate and geologic variables on nutrient exports will greatly aid the development of integrated Earth-climate biogeochemical models which are able to take into account multiple element dynamics and complex natural landscapes.

Observations, inferences, and mechanisms of the Atlantic Meridional Overturning Circulation: A review

NASA Astrophysics Data System (ADS)

Buckley, Martha W.; Marshall, John

2016-03-01

This is a review about the Atlantic Meridional Overturning Circulation (AMOC), its mean structure, temporal variability, controlling mechanisms, and role in the coupled climate system. The AMOC plays a central role in climate through its heat and freshwater transports. Northward ocean heat transport achieved by the AMOC is responsible for the relative warmth of the Northern Hemisphere compared to the Southern Hemisphere and is thought to play a role in setting the mean position of the Intertropical Convergence Zone north of the equator. The AMOC is a key means by which heat anomalies are sequestered into the ocean's interior and thus modulates the trajectory of climate change. Fluctuations in the AMOC have been linked to low-frequency variability of Atlantic sea surface temperatures with a host of implications for climate variability over surrounding landmasses. On intra-annual timescales, variability in AMOC is large and primarily reflects the response to local wind forcing; meridional coherence of anomalies is limited to that of the wind field. On interannual to decadal timescales, AMOC changes are primarily geostrophic and related to buoyancy anomalies on the western boundary. A pacemaker region for decadal AMOC changes is located in a western "transition zone" along the boundary between the subtropical and subpolar gyres. Decadal AMOC anomalies are communicated meridionally from this region. AMOC observations, as well as the expanded ocean observational network provided by the Argo array and satellite altimetry, are inspiring efforts to develop decadal predictability systems using coupled atmosphere-ocean models initialized by ocean data.

Agricultural biotechnology for crop improvement in a variable climate: hope or hype?

PubMed

Varshney, Rajeev K; Bansal, Kailash C; Aggarwal, Pramod K; Datta, Swapan K; Craufurd, Peter Q

2011-07-01

Developing crops that are better adapted to abiotic stresses is important for food production in many parts of the world today. Anticipated changes in climate and its variability, particularly extreme temperatures and changes in rainfall, are expected to make crop improvement even more crucial for food production. Here, we review two key biotechnology approaches, molecular breeding and genetic engineering, and their integration with conventional breeding to develop crops that are more tolerant of abiotic stresses. In addition to a multidisciplinary approach, we also examine some constraints that need to be overcome to realize the full potential of agricultural biotechnology for sustainable crop production to meet the demands of a projected world population of nine billion in 2050. Copyright © 2011 Elsevier Ltd. All rights reserved.

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.

Statistical Analysis of Large Simulated Yield Datasets for Studying Climate Effects

NASA Technical Reports Server (NTRS)

Makowski, David; Asseng, Senthold; Ewert, Frank; Bassu, Simona; Durand, Jean-Louis; Martre, Pierre; Adam, Myriam; Aggarwal, Pramod K.; Angulo, Carlos; Baron, Chritian;

Can the biomass-ratio hypothesis predict mixed-species litter decomposition along a climatic gradient?

PubMed Central

Tardif, Antoine; Shipley, Bill; Bloor, Juliette M. G.; Soussana, Jean-François

2014-01-01

Background and Aims The biomass-ratio hypothesis states that ecosystem properties are driven by the characteristics of dominant species in the community. In this study, the hypothesis was operationalized as community-weighted means (CWMs) of monoculture values and tested for predicting the decomposition of multispecies litter mixtures along an abiotic gradient in the field. Methods Decomposition rates (mg g−1 d−1) of litter from four herb species were measured using litter-bed experiments with the same soil at three sites in central France along a correlated climatic gradient of temperature and precipitation. All possible combinations from one to four species mixtures were tested over 28 weeks of incubation. Observed mixture decomposition rates were compared with those predicted by the biomass-ratio hypothesis. Variability of the prediction errors was compared with the species richness of the mixtures, across sites, and within sites over time. Key Results Both positive and negative prediction errors occurred. Despite this, the biomass-ratio hypothesis was true as an average claim for all sites (r = 0·91) and for each site separately, except for the climatically intermediate site, which showed mainly synergistic deviations. Variability decreased with increasing species richness and in less favourable climatic conditions for decomposition. Conclusions Community-weighted mean values provided good predictions of mixed-species litter decomposition, converging to the predicted values with increasing species richness and in climates less favourable to decomposition. Under a context of climate change, abiotic variability would be important to take into account when predicting ecosystem processes. PMID:24482152

Decadal climate prediction with a refined anomaly initialisation approach

NASA Astrophysics Data System (ADS)

Volpi, Danila; Guemas, Virginie; Doblas-Reyes, Francisco J.; Hawkins, Ed; Nichols, Nancy K.

2017-03-01

In decadal prediction, the objective is to exploit both the sources of predictability from the external radiative forcings and from the internal variability to provide the best possible climate information for the next decade. Predicting the climate system internal variability relies on initialising the climate model from observational estimates. We present a refined method of anomaly initialisation (AI) applied to the ocean and sea ice components of the global climate forecast model EC-Earth, with the following key innovations: (1) the use of a weight applied to the observed anomalies, in order to avoid the risk of introducing anomalies recorded in the observed climate, whose amplitude does not fit in the range of the internal variability generated by the model; (2) the AI of the ocean density, instead of calculating it from the anomaly initialised state of temperature and salinity. An experiment initialised with this refined AI method has been compared with a full field and standard AI experiment. Results show that the use of such refinements enhances the surface temperature skill over part of the North and South Atlantic, part of the South Pacific and the Mediterranean Sea for the first forecast year. However, part of such improvement is lost in the following forecast years. For the tropical Pacific surface temperature, the full field initialised experiment performs the best. The prediction of the Arctic sea-ice volume is improved by the refined AI method for the first three forecast years and the skill of the Atlantic multidecadal oscillation is significantly increased compared to a non-initialised forecast, along the whole forecast time.

Differential Response to Soil Salinity in Endangered Key Tree Cactus: Implications for Survival in a Changing Climate

PubMed Central

Goodman, Joie; Maschinski, Joyce; Hughes, Phillip; McAuliffe, Joe; Roncal, Julissa; Powell, Devon; Sternberg, Leonel O'reilly

2012-01-01

Understanding reasons for biodiversity loss is essential for developing conservation and management strategies and is becoming increasingly urgent with climate change. Growing at elevations <1.4 m in the Florida Keys, USA, the endangered Key tree cactus (Pilosocereus robinii) experienced 84 percent loss of total stems from 1994 to 2007. The most severe losses of 99 and 88 percent stems occurred in the largest populations in the Lower Keys, where nine storms with high wind velocities and storm surges, occurred during this period. In contrast, three populations had substantial stem proliferation. To evaluate possible mortality factors related to changes in climate or forest structure, we examined habitat variables: soil salinity, elevation, canopy cover, and habitat structure near 16 dying or dead and 18 living plants growing in the Lower Keys. Soil salinity and elevation were the preliminary factors that discriminated live and dead plants. Soil salinity was 1.5 times greater, but elevation was 12 cm higher near dead plants than near live plants. However, distribution-wide stem loss was not significantly related to salinity or elevation. Controlled salinity trials indicated that salt tolerance to levels above 40 mM NaCl was related to maternal origin. Salt sensitive plants from the Lower Keys had less stem growth, lower root:shoot ratios, lower potassium: sodium ratios and lower recovery rate, but higher δ 13C than a salt tolerant lineage of unknown origin. Unraveling the genetic structure of salt tolerant and salt sensitive lineages in the Florida Keys will require further genetic tests. Worldwide rare species restricted to fragmented, low-elevation island habitats, with little or no connection to higher ground will face challenges from climate change-related factors. These great conservation challenges will require traditional conservation actions and possibly managed relocation that must be informed by studies such as these. PMID:22403670

Differential response to soil salinity in endangered key tree cactus: implications for survival in a changing climate.

PubMed

Goodman, Joie; Maschinski, Joyce; Hughes, Phillip; McAuliffe, Joe; Roncal, Julissa; Powell, Devon; Sternberg, Leonel O'reilly

2012-01-01

Understanding reasons for biodiversity loss is essential for developing conservation and management strategies and is becoming increasingly urgent with climate change. Growing at elevations <1.4 m in the Florida Keys, USA, the endangered Key tree cactus (Pilosocereus robinii) experienced 84 percent loss of total stems from 1994 to 2007. The most severe losses of 99 and 88 percent stems occurred in the largest populations in the Lower Keys, where nine storms with high wind velocities and storm surges, occurred during this period. In contrast, three populations had substantial stem proliferation. To evaluate possible mortality factors related to changes in climate or forest structure, we examined habitat variables: soil salinity, elevation, canopy cover, and habitat structure near 16 dying or dead and 18 living plants growing in the Lower Keys. Soil salinity and elevation were the preliminary factors that discriminated live and dead plants. Soil salinity was 1.5 times greater, but elevation was 12 cm higher near dead plants than near live plants. However, distribution-wide stem loss was not significantly related to salinity or elevation. Controlled salinity trials indicated that salt tolerance to levels above 40 mM NaCl was related to maternal origin. Salt sensitive plants from the Lower Keys had less stem growth, lower root:shoot ratios, lower potassium: sodium ratios and lower recovery rate, but higher δ (13)C than a salt tolerant lineage of unknown origin. Unraveling the genetic structure of salt tolerant and salt sensitive lineages in the Florida Keys will require further genetic tests. Worldwide rare species restricted to fragmented, low-elevation island habitats, with little or no connection to higher ground will face challenges from climate change-related factors. These great conservation challenges will require traditional conservation actions and possibly managed relocation that must be informed by studies such as these.

Paleodust variability since the Last Glacial Maximum and implications for iron inputs to the ocean

NASA Astrophysics Data System (ADS)

Albani, S.; Mahowald, N. M.; Murphy, L. N.; Raiswell, R.; Moore, J. K.; Anderson, R. F.; McGee, D.; Bradtmiller, L. I.; Delmonte, B.; Hesse, P. P.; Mayewski, P. A.

2016-04-01

Changing climate conditions affect dust emissions and the global dust cycle, which in turn affects climate and biogeochemistry. In this study we use observationally constrained model reconstructions of the global dust cycle since the Last Glacial Maximum, combined with different simplified assumptions of atmospheric and sea ice processing of dust-borne iron, to provide estimates of soluble iron deposition to the oceans. For different climate conditions, we discuss uncertainties in model-based estimates of atmospheric processing and dust deposition to key oceanic regions, highlighting the large degree of uncertainty of this important variable for ocean biogeochemistry and the global carbon cycle. We also show the role of sea ice acting as a time buffer and processing agent, which results in a delayed and pulse-like soluble iron release into the ocean during the melting season, with monthly peaks up to ~17 Gg/month released into the Southern Oceans during the Last Glacial Maximum (LGM).

Overall uncertainty study of the hydrological impacts of climate change for a Canadian watershed

NASA Astrophysics Data System (ADS)

Chen, Jie; Brissette, FrançOis P.; Poulin, Annie; Leconte, Robert

2011-12-01

General circulation models (GCMs) and greenhouse gas emissions scenarios (GGES) are generally considered to be the two major sources of uncertainty in quantifying the climate change impacts on hydrology. Other sources of uncertainty have been given less attention. This study considers overall uncertainty by combining results from an ensemble of two GGES, six GCMs, five GCM initial conditions, four downscaling techniques, three hydrological model structures, and 10 sets of hydrological model parameters. Each climate projection is equally weighted to predict the hydrology on a Canadian watershed for the 2081-2100 horizon. The results show that the choice of GCM is consistently a major contributor to uncertainty. However, other sources of uncertainty, such as the choice of a downscaling method and the GCM initial conditions, also have a comparable or even larger uncertainty for some hydrological variables. Uncertainties linked to GGES and the hydrological model structure are somewhat less than those related to GCMs and downscaling techniques. Uncertainty due to the hydrological model parameter selection has the least important contribution among all the variables considered. Overall, this research underlines the importance of adequately covering all sources of uncertainty. A failure to do so may result in moderately to severely biased climate change impact studies. Results further indicate that the major contributors to uncertainty vary depending on the hydrological variables selected, and that the methodology presented in this paper is successful at identifying the key sources of uncertainty to consider for a climate change impact study.

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.

Comment on: "Synchronizing biological cycles as key to survival under a scenario of global change: The Common quail (Coturnix coturnix) strategy" by Nadal, J., Ponz, C., Margalida, A.

PubMed

Rodríguez-Teijeiro, José Domingo; García-Galea, Eduardo; Sardà-Palomera, Francesc; Jiménez-Blasco, Irene; Puigcerver, Manel

2018-04-03

Nadal et al. (2018) recently reported on changes in the phenology of the Common quail (Coturnix coturnix) in seven cloudy regions of Spain in relation to climate change. The authors used a long-term ringing database (1961-2014) and calculated the mean date for three biological stages: arrival at the breeding areas, stay and autumn departure. They observed that some of these phenological variables were associated with the climate variables of temperature and rainfall (Figs. 4 and 6 of their article). They also analysed the yearly variation in temperature and rainfall over the last 86years, reporting an increase in temperature and a decrease in rainfall (Figs. 3 and 5 of their article). Based on these results, the authors suggested that the Common quail phenology has varied as a response to climate change in Spain, thus concluding that "quail movements and breeding attempts are eco-synchronized sequentially in cloudy regions. Our results suggest that quails attempt to overcome the negative impacts of climate change and agricultural intensification by searching for alternative high-quality habitats". We disagree with two methodological aspects of the article by Nadal et al. (2018): (1) the estimation of the mean date of arrival, stay and departure in the different regions studied; and (2) the analyses carried out to correlate the phenology of the species with the changes in climate variables. Copyright © 2018 Elsevier B.V. All rights reserved.

Reconstructing medieval climate in the tropical North Atlantic with corals from Anegada, British Virgin Islands

NASA Astrophysics Data System (ADS)

Kilbourne, K. H.; Xu, Y. Y.

2014-12-01

Resolving the patterns of climate variability during the Medieval Climate Anomaly (MCA) is key for exploring forced versus unforced variability during the last 1000 years. Tropical Atlantic climate is currently not well resolved during the MCA despite it being an important source of heat and moisture to the climate system today. To fill this data gap, we collected cores from Diploria strigosa corals brought onto the low-lying island of Anegada, British Virgin Islands (18.7˚N, 64.3˚S) during an overwash event and use paired analysis of Sr/Ca and δ18O in the skeletal aragonite to explore climate in the tropical Atlantic at the end of the MCA. The three sub-fossil corals used in this analysis overlap temporally and together span the years 1256-1372 C.E. An assessment of three modern corals from the study site indicates that the most robust features of climate reconstructions using Sr/Ca and δ18O in this species are the seasonal cycle and inter-annual variability. The modern seasonal temperature range is 2.8 degrees Celsius and the similarity between the modern and sub-fossil coral Sr/Ca indicates a similar range during the MCA. Today seasonal salinity changes locally are driven in large part by the migration of a regional salinity front. The modern corals capture the related large seasonal seawater δ18O change, but the sub-fossil corals indicate stable seawater δ18O throughout the year, supporting the idea that this site remained on one side of the salinity front continuously throughout the year. Inter-annual variability in the region is influenced by the cross-equatorial SST gradient, the North Atlantic Oscillation and ENSO. Gridded instrumental SST from the area surrounding Anegada and coral geochemical records from nearby Puerto Rico demonstrate concentrations of variance in specific frequency bands associated with these phenomena. The sub-fossil coral shows no concentration of variance in the modern ENSO frequency band, consistent with reduced ENSO variability found in central Pacific corals growing at the same time.

Evidence of genomic adaptation to climate in Eucalyptus microcarpa: Implications for adaptive potential to projected climate change.

PubMed

Jordan, Rebecca; Hoffmann, Ary A; Dillon, Shannon K; Prober, Suzanne M

2017-11-01

Understanding whether populations can adapt in situ or whether interventions are required is of key importance for biodiversity management under climate change. Landscape genomics is becoming an increasingly important and powerful tool for rapid assessments of climate adaptation, especially in long-lived species such as trees. We investigated climate adaptation in Eucalyptus microcarpa using the DArTseq genomic approach. A combination of F ST outlier and environmental association analyses were performed using >4200 genomewide single nucleotide polymorphisms (SNPs) from 26 populations spanning climate gradients in southeastern Australia. Eighty-one SNPs were identified as putatively adaptive, based on significance in F ST outlier tests and significant associations with one or more climate variables related to temperature (70/81), aridity (37/81) or precipitation (35/81). Adaptive SNPs were located on all 11 chromosomes, with no particular region associated with individual climate variables. Climate adaptation appeared to be characterized by subtle shifts in allele frequencies, with no consistent fixed differences identified. Based on these associations, we predict adaptation under projected changes in climate will include a suite of shifts in allele frequencies. Whether this can occur sufficiently rapidly through natural selection within populations, or would benefit from assisted gene migration, requires further evaluation. In some populations, the absence or predicted increases to near fixation of particular adaptive alleles hint at potential limits to adaptive capacity. Together, these results reinforce the importance of standing genetic variation at the geographic level for maintaining species' evolutionary potential. © 2017 John Wiley & Sons Ltd.

Evaluation of GCMs in the context of regional predictive climate impact studies.

NASA Astrophysics Data System (ADS)

Kokorev, Vasily; Anisimov, Oleg

2016-04-01

Significant improvements in the structure, complexity, and general performance of earth system models (ESMs) have been made in the recent decade. Despite these efforts, the range of uncertainty in predicting regional climate impacts remains large. The problem is two-fold. Firstly, there is an intrinsic conflict between the local and regional scales of climate impacts and adaptation strategies, on one hand, and larger scales, at which ESMs demonstrate better performance, on the other. Secondly, there is a growing understanding that majority of the impacts involve thresholds, and are thus driven by extreme climate events, whereas accent in climate projections is conventionally made on gradual changes in means. In this study we assess the uncertainty in projecting extreme climatic events within a region-specific and process-oriented context by examining the skills and ranking of ESMs. We developed a synthetic regionalization of Northern Eurasia that accounts for the spatial features of modern climatic changes and major environmental and socio-economical impacts. Elements of such fragmentation could be considered as natural focus regions that bridge the gap between the spatial scales adopted in climate-impacts studies and patterns of climate change simulated by ESMs. In each focus region we selected several target meteorological variables that govern the key regional impacts, and examined the ability of the models to replicate their seasonal and annual means and trends by testing them against observations. We performed a similar evaluation with regard to extremes and statistics of the target variables. And lastly, we used the results of these analyses to select sets of models that demonstrate the best performance at selected focus regions with regard to selected sets of target meteorological parameters. Ultimately, we ranked the models according to their skills, identified top-end models that "better than average" reproduce the behavior of climatic parameters, and eliminated the outliers. Since the criteria of selecting the "best" models are somewhat loose, we constructed several regional ensembles consisting of different number of high-ranked models and compared results from these optimized ensembles with observations and with the ensemble of all models. We tested our approach in specific regional application of the terrestrial Russian Arctic, considering permafrost and Artic biomes as key regional climate-dependent systems, and temperature and precipitation characteristics governing their state as target meteorological parameters. Results of this case study are deposited on the web portal www.permafrost.su/gcms

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.

Slow science: the value of long ocean biogeochemistry records.

PubMed

Henson, Stephanie A

2014-09-28

Sustained observations (SOs) have provided invaluable information on the ocean's biology and biogeochemistry for over 50 years. They continue to play a vital role in elucidating the functioning of the marine ecosystem, particularly in the light of ongoing climate change. Repeated, consistent observations have provided the opportunity to resolve temporal and/or spatial variability in ocean biogeochemistry, which has driven exploration of the factors controlling biological parameters and processes. Here, I highlight some of the key breakthroughs in biological oceanography that have been enabled by SOs, which include areas such as trophic dynamics, understanding variability, improved biogeochemical models and the role of ocean biology in the global carbon cycle. In the near future, SOs are poised to make progress on several fronts, including detecting climate change effects on ocean biogeochemistry, high-resolution observations of physical-biological interactions and greater observational capability in both the mesopelagic zone and harsh environments, such as the Arctic. We are now entering a new era for biological SOs, one in which our motivations have evolved from the need to acquire basic understanding of the ocean's state and variability, to a need to understand ocean biogeochemistry in the context of increasing pressure in the form of climate change, overfishing and eutrophication.

Modeling the role of environmental variables on the population dynamics of the malaria vector Anopheles gambiae sensu stricto

PubMed Central

2012-01-01

Background The impact of weather and climate on malaria transmission has attracted considerable attention in recent years, yet uncertainties around future disease trends under climate change remain. Mathematical models provide powerful tools for addressing such questions and understanding the implications for interventions and eradication strategies, but these require realistic modeling of the vector population dynamics and its response to environmental variables. Methods Published and unpublished field and experimental data are used to develop new formulations for modeling the relationships between key aspects of vector ecology and environmental variables. These relationships are integrated within a validated deterministic model of Anopheles gambiae s.s. population dynamics to provide a valuable tool for understanding vector response to biotic and abiotic variables. Results A novel, parsimonious framework for assessing the effects of rainfall, cloudiness, wind speed, desiccation, temperature, relative humidity and density-dependence on vector abundance is developed, allowing ease of construction, analysis, and integration into malaria transmission models. Model validation shows good agreement with longitudinal vector abundance data from Tanzania, suggesting that recent malaria reductions in certain areas of Africa could be due to changing environmental conditions affecting vector populations. Conclusions Mathematical models provide a powerful, explanatory means of understanding the role of environmental variables on mosquito populations and hence for predicting future malaria transmission under global change. The framework developed provides a valuable advance in this respect, but also highlights key research gaps that need to be resolved if we are to better understand future malaria risk in vulnerable communities. PMID:22877154

Key ecological responses to nitrogen are altered by climate ...

EPA Pesticide Factsheets

Here we review the effects of nitrogen and climate (e.g. temperature and precipitation) on four aspects of ecosystem structure and function including hydrologic-coupled nitrogen cycling, carbon cycling, acidification and biodiversity. Ecosystems are simultaneously exposed to multiple stressors; two dominant drivers threatening ecosystems are anthropogenic nitrogen loading and climate change. Evaluating the cumulative effects of these stressors provides a holistic view of ecosystem vulnerability, which would better inform policy decisions aimed to protect the sustainability of ecosystems. Our current knowledge of the cumulative effects of these stressors is growing, but limited. The goal of this paper is to synthesize the state of scientific knowledge on how ecosystems are affected by the interactions of meteorlogic/climatic factors (e.g., temperature and precipitation) and nitrogen addition. Understanding the interactions of meteorlogic/climatic factors and nitrogen will help to inform how current and projected variability may affect ecosystem response.

Identification of reliable gridded reference data for statistical downscaling methods in Alberta

NASA Astrophysics Data System (ADS)

Eum, H. I.; Gupta, A.

2017-12-01

Climate models provide essential information to assess impacts of climate change at regional and global scales. However, statistical downscaling methods have been applied to prepare climate model data for various applications such as hydrologic and ecologic modelling at a watershed scale. As the reliability and (spatial and temporal) resolution of statistically downscaled climate data mainly depend on a reference data, identifying the most reliable reference data is crucial for statistical downscaling. A growing number of gridded climate products are available for key climate variables which are main input data to regional modelling systems. However, inconsistencies in these climate products, for example, different combinations of climate variables, varying data domains and data lengths and data accuracy varying with physiographic characteristics of the landscape, have caused significant challenges in selecting the most suitable reference climate data for various environmental studies and modelling. Employing various observation-based daily gridded climate products available in public domain, i.e. thin plate spline regression products (ANUSPLIN and TPS), inverse distance method (Alberta Townships), and numerical climate model (North American Regional Reanalysis) and an optimum interpolation technique (Canadian Precipitation Analysis), this study evaluates the accuracy of the climate products at each grid point by comparing with the Adjusted and Homogenized Canadian Climate Data (AHCCD) observations for precipitation, minimum and maximum temperature over the province of Alberta. Based on the performance of climate products at AHCCD stations, we ranked the reliability of these publically available climate products corresponding to the elevations of stations discretized into several classes. According to the rank of climate products for each elevation class, we identified the most reliable climate products based on the elevation of target points. A web-based system was developed to allow users to easily select the most reliable reference climate data at each target point based on the elevation of grid cell. By constructing the best combination of reference data for the study domain, the accurate and reliable statistically downscaled climate projections could be significantly improved.

The Copernicus Climate Change Service (C3S): A European Answer to Climate Change

NASA Astrophysics Data System (ADS)

Thepaut, Jean-Noel

2016-04-01

Copernicus is the European Commission's flagship Earth observation programme that delivers freely accessible operational data and information services. ECMWF has been entrusted to operate two key parts of the Copernicus programme, which will bring a consistent standard to the measurement, forecasting and prediction of atmospheric conditions and climate change: • The Copernicus Atmosphere Monitoring Service, CAMS, provides daily forecasts detailing the makeup composition of the atmosphere from the ground up to the stratosphere. • The Copernicus Climate Change Service (C3S) (in development) will routinely monitor and analyse more than 20 essential climate variables to build a global picture of our climate, from the past to the future, as well as developing customisable climate indicators for relevant economic sectors, such as energy, water management, agriculture, insurance, health…. C3S has now taken off and a number of proof-of-concept sectoral climate services have been initiated. This paper will focus on the description and expected outcome of these proof-of-concept activities as well as the definition of a roadmap towards a fully operational European Climate Change Service.

Constraints on Variability of Brightness and Surface Magnetism on Time Scales of Decades to Centuries in the Sun and Sun-Like Stars: A Source of Potential Terrestrial Climate Variability

NASA Technical Reports Server (NTRS)

Baliunas, Sallie L.; Sharber, James (Technical Monitor)

2001-01-01

These four points summarize our work to date. (1) Conciliation of solar and stellar photometric variability. Previous research by us and colleagues suggested that the Sun might at present be showing unusually low photometric variability compared to other sun-like stars. Those early results would question the suitability of the technique of using sun-like stars as proxies for solar irradiance change on time scales of decades to centuries. However, our results indicate the contrary: the Sun's observed short-term (seasonal) and longterm (year-to-year) brightness variations closely agree with observed brightness variations in stars of similar mass and age. (2) We have demonstrated an inverse correlation between the global temperature of the terrestrial lower troposphere, inferred from the NASA Microwave Sounding Unit (MSU) radiometers, and the total area of the Sun covered by coronal holes from January 1979 to present (up to May 2000). Variable fluxes of either solar charged particles or cosmic rays, or both, may influence the terrestrial tropospheric temperature. The geographical pattern of the correlation is consistent with our interpretation of an extra-terrestrial charged particle forcing. (3) Possible climate mechanism amplifying the impact of solar ultraviolet irradiance variations. The key points of our proposed climate hypersensitivity mechanism are: (a) The Sun is more variable in the UV (ultraviolet) than in the visible. However, the increased UV irradiance is mainly absorbed in the lower stratosphere/upper troposphere rather than at the surface. (b) Absorption in the stratosphere raises the temperature moderately around the vicinity of the tropopause, and tends to stabilize the atmosphere against vertical convective/diffusive transport, thus decreasing the flux of heat and moisture carried upward from surface. (c) The decrease in the upward convection of heat and moisture tends to raise the surface temperature because a drier upper atmosphere becomes less cloudy, which in turn allows more solar radiation to reach the Earth's surface. (4) Natural variability in an ocean-atmosphere climate model. We use a 14-region, 6-layer, global thermo-hydrodynamic ocean-atmosphere model to study natural climate variability. All the numerical experiments were performed with no change in the prescribed external boundary conditions (except for the seasonal cycle of the Sun's tilt angle). Therefore, the observed inter-annual variability is of an internal kind. The model results are helpful toward the understanding of the role of nonlinearity in climate change. We have demonstrated a range of possible climate behaviors using our newly developed ocean-atmosphere model. These include climate configurations with no interannual variability, with multi-year periodicities, with continuous chaos, or with chaotically occuring transitions between two discrete substrates. These possible modes of climate behavior are all possible for the real climate, as well as the model. We have shown that small temporary climate influences can trigger shifts both in the mean climate, and among these different types of behavior. Such shifts are not only theoretically plausible, as shown here and elsewhere; they are omnipresent in the climate record on time scales from several years to the age of the Earth. This has two apparently opposite implications for the possibility of anthropogenic global warming. First, any warming which might occur as a result of human influence would be only a fraction of the small-to-large unpredictable natural changes and changes which result from other external causes. On the other hand, small temporary influences such as human influence do have the potential of causing large permanent shifts in mean climate and interannual variability.

Different parts, different stories: climate sensitivity of growth is stronger in root collars vs. stems in tundra shrubs.

PubMed

Ropars, Pascale; Angers-Blondin, Sandra; Gagnon, Marianne; Myers-Smith, Isla H; Lévesque, Esther; Boudreau, Stéphane

2017-08-01

Shrub densification has been widely reported across the circumpolar arctic and subarctic biomes in recent years. Long-term analyses based on dendrochronological techniques applied to shrubs have linked this phenomenon to climate change. However, the multi-stemmed structure of shrubs makes them difficult to sample and therefore leads to non-uniform sampling protocols among shrub ecologists, who will favor either root collars or stems to conduct dendrochronological analyses. Through a comparative study of the use of root collars and stems of Betula glandulosa, a common North American shrub species, we evaluated the relative sensitivity of each plant part to climate variables and assessed whether this sensitivity is consistent across three different types of environments in northwestern Québec, Canada (terrace, hilltop and snowbed). We found that root collars had greater sensitivity to climate than stems and that these differences were maintained across the three types of environments. Growth at the root collar was best explained by spring precipitation and summer temperature, whereas stem growth showed weak and inconsistent responses to climate variables. Moreover, sensitivity to climate was not consistent among plant parts, as individuals having climate-sensitive root collars did not tend to have climate-sensitive stems. These differences in sensitivity of shrub parts to climate highlight the complexity of resource allocation in multi-stemmed plants. Whereas stem initiation and growth are driven by microenvironmental variables such as light availability and competition, root collars integrate the growth of all plant parts instead, rendering them less affected by mechanisms such as competition and more responsive to signals of global change. Although further investigations are required to determine the degree to which these findings are generalizable across the tundra biome, our results indicate that consistency and caution in the choice of plant parts are a key consideration for the success of future dendroclimatological studies on shrubs. © 2017 John Wiley & Sons Ltd.

Climate change is advancing spring onset across the U.S. national park system

USGS Publications Warehouse

Monahan, William B.; Rosemartin, Alyssa; Gerst, Katharine L.; Fisichelli, Nicholas A.; Ault, Toby R.; Schwartz, Mark D.; Gross, John E.; Weltzin, Jake F.

2016-01-01

Many U.S. national parks are already at the extreme warm end of their historical temperature distributions. With rapidly warming conditions, park resource management will be enhanced by information on seasonality of climate that supports adjustments in the timing of activities such as treating invasive species, operating visitor facilities, and scheduling climate-related events (e.g., flower festivals and fall leaf-viewing). Seasonal changes in vegetation, such as pollen, seed, and fruit production, are important drivers of ecological processes in parks, and phenology has thus been identified as a key indicator for park monitoring. Phenology is also one of the most proximate biological responses to climate change. Here, we use estimates of start of spring based on climatically modeled dates of first leaf and first bloom derived from indicator plant species to evaluate the recent timing of spring onset (past 10–30 yr) in each U.S. natural resource park relative to its historical range of variability across the past 112 yr (1901–2012). Of the 276 high latitude to subtropical parks examined, spring is advancing in approximately three-quarters of parks (76%), and 53% of parks are experiencing “extreme” early springs that exceed 95% of historical conditions. Our results demonstrate how changes in climate seasonality are important for understanding ecological responses to climate change, and further how spatial variability in effects of climate change necessitates different approaches to management. We discuss how our results inform climate change adaptation challenges and opportunities facing parks, with implications for other protected areas, by exploring consequences for resource management and planning.

Impact of climate change and human activity on soil landscapes over the past 12,300 years.

PubMed

Rothacker, Leo; Dosseto, Anthony; Francke, Alexander; Chivas, Allan R; Vigier, Nathalie; Kotarba-Morley, Anna M; Menozzi, Davide

2018-01-10

Soils are key to ecosystems and human societies, and their critical importance requires a better understanding of how they evolve through time. However, identifying the role of natural climate change versus human activity (e.g. agriculture) on soil evolution is difficult. Here we show that for most of the past 12,300 years soil erosion and development were impacted differently by natural climate variability, as recorded by sediments deposited in Lake Dojran (Macedonia/Greece): short-lived ( < 1,000 years) climatic shifts had no effect on soil development but impacted soil erosion. This decoupling disappeared between 3,500 and 3,100 years ago, when the sedimentary record suggests an unprecedented erosion event associated with the development of agriculture in the region. Our results show unambiguously how differently soils evolved under natural climate variability (between 12,300 and 3,500 years ago) and later in response to intensifying human impact. The transition from natural to anthropogenic landscape started just before, or at, the onset of the Greek 'Dark Ages' (~3,200 cal yr BP). This could represent the earliest recorded sign of a negative feedback between civilization and environmental impact, where the development of agriculture impacted soil resources, which in turn resulted in a slowdown of civilization expansion.

Climate change risk to forests in China associated with warming.

PubMed

Yin, Yunhe; Ma, Danyang; Wu, Shaohong

2018-01-11

Variations in forest net primary productivity (NPP) reflects the combined effects of key climate variables on ecosystem structure and function, especially on the carbon cycle. We performed risk analysis indicated by the magnitude of future negative anomalies in NPP in comparison with the natural interannual variability to investigate the impact of future climatic projections on forests in China. Results from the multi-model ensemble showed that climate change risk of decreases in forest NPP would be more significant in higher emission scenario in China. Under relatively low emission scenarios, the total area of risk was predicted to decline, while for RCP8.5, it was predicted to first decrease and then increase after the middle of 21st century. The rapid temperature increases predicted under the RCP8.5 scenario would be probably unfavorable for forest vegetation growth in the long term. High-level risk area was likely to increase except RCP2.6. The percentage area at high risk was predicted to increase from 5.39% (2021-2050) to 27.62% (2071-2099) under RCP8.5. Climate change risk to forests was mostly concentrated in southern subtropical and tropical regions, generally significant under high emission scenario of RCP8.5, which was mainly attributed to the intensified dryness in south China.

Upgrades to the REA method for producing probabilistic climate change projections

NASA Astrophysics Data System (ADS)

Xu, Ying; Gao, Xuejie; Giorgi, Filippo

2010-05-01

We present an augmented version of the Reliability Ensemble Averaging (REA) method designed to generate probabilistic climate change information from ensembles of climate model simulations. Compared to the original version, the augmented one includes consideration of multiple variables and statistics in the calculation of the performance-based weights. In addition, the model convergence criterion previously employed is removed. The method is applied to the calculation of changes in mean and variability for temperature and precipitation over different sub-regions of East Asia based on the recently completed CMIP3 multi-model ensemble. Comparison of the new and old REA methods, along with the simple averaging procedure, and the use of different combinations of performance metrics shows that at fine sub-regional scales the choice of weighting is relevant. This is mostly because the models show a substantial spread in performance for the simulation of precipitation statistics, a result that supports the use of model weighting as a useful option to account for wide ranges of quality of models. The REA method, and in particular the upgraded one, provides a simple and flexible framework for assessing the uncertainty related to the aggregation of results from ensembles of models in order to produce climate change information at the regional scale. KEY WORDS: REA method, Climate change, CMIP3

Strong coupling of Asian Monsoon and Antarctic climates on sub-orbital timescales

PubMed Central

Chen, Shitao; Wang, Yongjin; Cheng, Hai; Edwards, R. Lawrence; Wang, Xianfeng; Kong, Xinggong; Liu, Dianbing

2016-01-01

There is increasing evidence that millennial-scale climate variability played an active role on orbital-scale climate changes, but the mechanism for this remains unclear. A 230Th-dated stalagmite δ18O record between 88 and 22 thousand years (ka) ago from Yongxing Cave in central China characterizes changes in Asian monsoon (AM) strength. After removing the 65°N insolation signal from our record, the δ18O residue is strongly anti-phased with Antarctic temperature variability on sub-orbital timescales during the Marine Isotope Stage (MIS) 3. Furthermore, once the ice volume signal from Antarctic ice core records were removed and extrapolated back to the last two glacial-interglacial cycles, we observe a linear relationship for both short- and long-duration events between Asian and Antarctic climate changes. This provides the robust evidence of a link between northern and southern hemisphere climates that operates through changes in atmospheric circulation. We find that the weakest monsoon closely associated with the warmest Antarctic event always occurred during the Terminations. This finding, along with similar shifts in the opal flux record, suggests that millennial-scale events play a key role in driving the deglaciation through positive feedbacks associated with enhanced upwelling and increasing CO2. PMID:27605015

Analysis of Terrestrial Water Storage Changes from GRACE and GLDAS

NASA Technical Reports Server (NTRS)

Syed, Tajdarul H.; Famiglietti, James S.; Rodell, Matthew; Chen, Jianli; Wilson, Clark R.

2008-01-01

Since March 2002, the Gravity Recovery and Climate Experiment (GRACE) has provided first estimates of land water storage variations by monitoring the time-variable component of Earth's gravity field. Here we characterize spatial-temporal variations in terrestrial water storage changes (TWSC) from GRACE and compare them to those simulated with the Global Land Data Assimilation System (GLDAS). Additionally, we use GLDAS simulations to infer how TWSC is partitioned into snow, canopy water and soil water components, and to understand how variations in the hydrologic fluxes act to enhance or dissipate the stores. Results quantify the range of GRACE-derived storage changes during the studied period and place them in the context of seasonal variations in global climate and hydrologic extremes including drought and flood, by impacting land memory processes. The role of the largest continental river basins as major locations for freshwater redistribution is highlighted. GRACE-based storage changes are in good agreement with those obtained from GLDAS simulations. Analysis of GLDAS-simulated TWSC illustrates several key characteristics of spatial and temporal land water storage variations. Global averages of TWSC were partitioned nearly equally between soil moisture and snow water equivalent, while zonal averages of TWSC revealed the importance of soil moisture storage at low latitudes and snow storage at high latitudes. Evapotranspiration plays a key role in dissipating globally averaged terrestrial water storage. Latitudinal averages showed how precipitation dominates TWSC variations in the tropics, evapotranspiration is most effective in the midlatitudes, and snowmelt runoff is a key dissipating flux at high latitudes. Results have implications for monitoring water storage response to climate variability and change, and for constraining land model hydrology simulations.

Alleviating tropical Atlantic sector biases in the Kiel climate model by enhancing horizontal and vertical atmosphere model resolution: climatology and interannual variability

NASA Astrophysics Data System (ADS)

Harlaß, Jan; Latif, Mojib; Park, Wonsun

2018-04-01

We investigate the quality of simulating tropical Atlantic (TA) sector climatology and interannual variability in integrations of the Kiel climate model (KCM) with varying atmosphere model resolution. The ocean model resolution is kept fixed. A reasonable simulation of TA sector annual-mean climate, seasonal cycle and interannual variability can only be achieved at sufficiently high horizontal and vertical atmospheric resolution. Two major reasons for the improvements are identified. First, the western equatorial Atlantic westerly surface wind bias in spring can be largely eliminated, which is explained by a better representation of meridional and especially vertical zonal momentum transport. The enhanced atmospheric circulation along the equator in turn greatly improves the thermal structure of the upper equatorial Atlantic with much reduced warm sea surface temperature (SST) biases. Second, the coastline in the southeastern TA and steep orography are better resolved at high resolution, which improves wind structure and in turn reduces warm SST biases in the Benguela upwelling region. The strongly diminished wind and SST biases at high atmosphere model resolution allow for a more realistic latitudinal position of the intertropical convergence zone. Resulting stronger cross-equatorial winds, in conjunction with a shallower thermocline, enable a rapid cold tongue development in the eastern TA in boreal spring. This enables simulation of realistic interannual SST variability and its seasonal phase locking in the KCM, which primarily is the result of a stronger thermocline feedback. Our findings suggest that enhanced atmospheric resolution, both vertical and horizontal, could be a key to achieving more realistic simulation of TA climatology and interannual variability in climate models.

Modeling biogeochemical responses of vegetation to ENSO: comparison and analysis on subgrid PFT patches

NASA Astrophysics Data System (ADS)

Xu, M.; Hoffman, F. M.

2016-12-01

The El Niño Southern Oscillation (ENSO) is an important interannual climate variability and has significant consequences and impacts on the global biosphere. The responses of vegetation to ENSO are highly heterogeneous and generally depend on the biophysical and biochemical characteristics associated with model plant functional types (PFTs). The modeled biogeochemical variables from Earth System Models (ESMs) are generally grid averages consisting of several PFTs within a gridcell, which will lead to difficulties in directly comparing them with site observations and large uncertainties in studying their responses to large scale climate variability. In this study, we conducted a transient ENSO simulation for the previoustwo decades from 1995 to 2020 using the DOE ACME v0.3 model. It has a comprehensive terrestrial biogeochemistry model that is fully coupled with a sophisticated atmospheric model with an advanced spectral element dynamical core. The model was driven by the NOAA optimum interpolation sea surface temperature (SST) for contemporary years and CFS v2 nine-month seasonal predicted and reconstructed SST for future years till to 2020. We saved the key biogeochemical variables in the subgrid PFT patches and compared them with site observations directly. Furthermore, we studied the biogeochemical responses of terrestrial vegetation to two largest ENSO events (1997-1998 and 2015-2016) for different PFTs. Our results show that it is useful and meaningful to compare and analyze model simulations in subgrid patches. The comparison and analysis not only gave us the details of responses of terrestrial ecosystem to global climate variability under changing climate, but also the insightful view on the model performance on the PFT level.

Weather-centric rangeland revegetation planning

USGS Publications Warehouse

Hardegree, Stuart P.; Abatzoglou, John T.; Brunson, Mark W.; Germino, Matthew; Hegewisch, Katherine C.; Moffet, Corey A.; Pilliod, David S.; Roundy, Bruce A.; Boehm, Alex R.; Meredith, Gwendwr R.

2018-01-01

Invasive annual weeds negatively impact ecosystem services and pose a major conservation threat on semiarid rangelands throughout the western United States. Rehabilitation of these rangelands is challenging due to interannual climate and subseasonal weather variability that impacts seed germination, seedling survival and establishment, annual weed dynamics, wildfire frequency, and soil stability. Rehabilitation and restoration outcomes could be improved by adopting a weather-centric approach that uses the full spectrum of available site-specific weather information from historical observations, seasonal climate forecasts, and climate-change projections. Climate data can be used retrospectively to interpret success or failure of past seedings by describing seasonal and longer-term patterns of environmental variability subsequent to planting. A more detailed evaluation of weather impacts on site conditions may yield more flexible adaptive-management strategies for rangeland restoration and rehabilitation, as well as provide estimates of transition probabilities between desirable and undesirable vegetation states. Skillful seasonal climate forecasts could greatly improve the cost efficiency of management treatments by limiting revegetation activities to time periods where forecasts suggest higher probabilities of successful seedling establishment. Climate-change projections are key to the application of current environmental models for development of mitigation and adaptation strategies and for management practices that require a multidecadal planning horizon. Adoption of new weather technology will require collaboration between land managers and revegetation specialists and modifications to the way we currently plan and conduct rangeland rehabilitation and restoration in the Intermountain West.

Impacts of weather on long-term patterns of plant richness and diversity vary with location and management

USGS Publications Warehouse

Jonas, Jayne L.; Buhl, Deborah A.; Symstad, Amy J.

2015-01-01

Better understanding the influence of precipitation and temperature on plant assemblages is needed to predict the effects of climate change. Many studies have examined the relationship between plant productivity and weather (primarily precipitation), but few have directly assessed the relationship between plant richness or diversity and weather despite their increased use as metrics of ecosystem condition. We focus on the grasslands of central North America, which are characterized by high temporal climatic variability. Over the next 100 years, these grasslands are predicted to experience further increased variability in growing season precipitation, as well as increased temperatures, due to global climate change. We assess 1) the portion of interannual variability of richness and diversity explained by weather, 2) how relationships between these metrics and weather vary among plant assemblages, and 3) which aspects of weather best explain temporal variability. We used an information-theoretic approach to assess relationships between long-term plant richness and diversity patterns and a priori weather covariates using six datasets from four grasslands. Weather explained up to 49% and 63% of interannual variability in total plant species richness and diversity, respectively. However, richness and diversity responses to specific weather variables varied both among sites and among experimental treatments within sites. In general, we found many instances in which temperature was of equal or greater importance as precipitation, as well as evidence of the importance of lagged effects and precipitation or temperature variability. Although precipitation has been shown to be a key driver of productivity in grasslands, our results indicate that increasing temperatures alone, without substantial changes in precipitation patterns, could have measurable effects on Great Plains grassland plant assemblages and biodiversity metrics. Our results also suggest that richness and diversity will respond in unique ways to changing climate and management can affect these responses; additional research and monitoring will be essential for further understanding of these complex relationships.Read More: http://www.esajournals.org/doi/abs/10.1890/14-1989.1

Impacts of weather on long-term patterns of plant richness and diversity vary with location and management.

PubMed

Jonas, Jayne L; Buhl, Deborah A; Symstad, Amy J

2015-09-01

Better understanding the influence of precipitation and temperature on plant assemblages is needed to predict the effects of climate change. Many studies have examined the relationship between plant productivity and weather (primarily precipitation), but few have directly assessed the relationship between plant richness or diversity and weather despite their increased use as metrics of ecosystem condition. We focus on the grasslands of central North America, which are characterized by high temporal climatic variability. Over the next 100 years, these grasslands are predicted to experience further increased variability in growing season precipitation, as well as increased temperatures, due to global climate change. We assess the portion of interannual variability of richness and diversity explained by weather, how relationships between these metrics and weather vary among plant assemblages, and which aspects of weather best explain temporal variability. We used an information-theoretic approach to assess relationships between long-term plant richness and diversity patterns and a priori weather covariates using six data sets from four grasslands. Weather explained up to 49% and 63% of interannual variability in total plant species richness and diversity, respectively. However, richness and diversity responses to specific weather variables varied both among sites and among experimental treatments within sites. In general, we found many instances in which temperature was of equal or greater importance as precipitation, as well as evidence of the importance of lagged effects and precipitation or temperature variability. Although precipitation has been shown to be a key driver of productivity in grasslands, our results indicate that increasing temperatures alone, without substantial changes in precipitation patterns, could have measurable effects on Great Plains grassland plant assemblages and biodiversity metrics. Our results also suggest that richness and diversity will respond in unique ways to changing climate and management can affect these responses; additional research and monitoring will be essential for further understanding of these complex relationships.

Stochastic ice stream dynamics

PubMed Central

Bertagni, Matteo Bernard; Ridolfi, Luca

2016-01-01

Ice streams are narrow corridors of fast-flowing ice that constitute the arterial drainage network of ice sheets. Therefore, changes in ice stream flow are key to understanding paleoclimate, sea level changes, and rapid disintegration of ice sheets during deglaciation. The dynamics of ice flow are tightly coupled to the climate system through atmospheric temperature and snow recharge, which are known exhibit stochastic variability. Here we focus on the interplay between stochastic climate forcing and ice stream temporal dynamics. Our work demonstrates that realistic climate fluctuations are able to (i) induce the coexistence of dynamic behaviors that would be incompatible in a purely deterministic system and (ii) drive ice stream flow away from the regime expected in a steady climate. We conclude that environmental noise appears to be crucial to interpreting the past behavior of ice sheets, as well as to predicting their future evolution. PMID:27457960

Interannual variability of human plague occurrence in the Western United States explained by tropical and North Pacific Ocean climate variability.

PubMed

Ari, Tamara Ben; Gershunov, Alexander; Tristan, Rouyer; Cazelles, Bernard; Gage, Kenneth; Stenseth, Nils C

2010-09-01

Plague is a vector-borne, highly virulent zoonotic disease caused by the bacterium Yersinia pestis. It persists in nature through transmission between its hosts (wild rodents) and vectors (fleas). During epizootics, the disease expands and spills over to other host species such as humans living in or close to affected areas. Here, we investigate the effect of large-scale climate variability on the dynamics of human plague in the western United States using a 56-year time series of plague reports (1950-2005). We found that El Niño Southern Oscillation and Pacific Decadal Oscillation in combination affect the dynamics of human plague over the western United States. The underlying mechanism could involve changes in precipitation and temperatures that impact both hosts and vectors. It is suggested that snow also may play a key role, possibly through its effects on summer soil moisture, which is known to be instrumental for flea survival and development and sustained growth of vegetation for rodents.

Preliminary review of adaptation options for climate-sensitive ecosystems and resources. A report by the U.S. Climate Change Science Program and the Subcommittee on Global Change Research

USGS Publications Warehouse

Baron, Jill S.; Griffith, Brad; Joyce, Linda A.; Kareiva, Peter; Keller, Brian D.; Palmer, Margaret A.; Peterson, Charles H.; Scott, J. Michael; Julius, Susan Herrod; West, Jordan M.

2008-01-01

Climate variables are key determinants of geographic distributions and biophysical characteristics of ecosystems, communities, and species. Climate change is therefore affecting many species attributes, ecological interactions, and ecosystem processes. Because changes in the climate system will continue into the future regardless of emissions mitigation, strategies for protecting climate-sensitive ecosystems through management will be increasingly important. While there will always be uncertainties associated with the future path of climate change, the response of ecosystems to climate impacts, and the effects of management, it is both possible and essential for adaptation to proceed using the best available science. This report provides a preliminary review of adaptation options for climate-sensitive ecosystems and resources in the United States. The term “adaptation” in this document refers to adjustments in human social systems (e.g., management) in response to climate stimuli and their effects. Since management always occurs in the context of desired ecosystem conditions or natural resource management goals, it is instructive to examine particular goals and processes used by different organizations to fulfill their objectives. Such an examination allows for discussion of specific adaptation options as well as potential barriers and opportunities for implementation. Using this approach, this report presents a series of chapters on the following selected management systems: National Forests, National Parks, National Wildlife Refuges, Wild and Scenic Rivers, National Estuaries, and Marine Protected Areas. For these chapters, the authors draw on the literature, their own expert opinion, and expert workshops composed of resource management scientists and representatives of managing agencies. The information drawn from across these chapters is then analyzed to develop the key synthetic messages presented below.

Factors influencing smallholder farmers' behavioural intention towards adaptation to climate change in transitional climatic zones: A case study of Hwedza District in Zimbabwe.

PubMed

Zamasiya, Byron; Nyikahadzoi, Kefasi; Mukamuri, Billy Billiard

2017-08-01

This paper examines factors influencing behavioural change among smallholder farmers towards adaptation to climate change in transitional climatic zones of Africa, specifically, Hwedza District in Zimbabwe. Data for this study were collected from 400 randomly-selected smallholder farmers, using a structured questionnaire, focus group discussions and key informant interviews. The study used an ordered logit model to examine the factors that influence smallholder farmers' behavioural intention towards adaptation to climate change. Results from the study show that the gender of the household head, access to extension services on crop and livestock production, access to climate information, membership to social groups and experiencing a drought have a positive influence on farmers' attitude towards adaptation to climate change and variability. The study concluded that although the majority of smallholder farmers perceive that the climate is changing, they continue to habour negative attitudes towards prescribed climate change adaptation techniques. This study recommends more education on climate change, as well as adaptation strategies for both agricultural extension workers and farmers. This can be complemented by disseminating timely climate information through extension officers and farmers' groups. Copyright © 2017 Elsevier Ltd. All rights reserved.

Reconstructing coastal environmental condition in the eastern Norwegian Sea by means of Arctica islandica sclerochronological records

NASA Astrophysics Data System (ADS)

Trofimova, Tamara; Andersson, Carin

2015-04-01

Paleo archives are fundament in improving our knowledge of the natural climate variability. Established marine proxy records for the ocean, especially for high latitudes, are both sparsely distributed and are poorly resolved in time. The identification and development of new archives and proxies for studying key ocean processes at annual to sub-annual resolution that can extend the marine instrumental record is therefore a clear priority for marine climate science. The bivalve species Arctica islandica is a unique paleoclimatic archive with an exceptional longevity combined with high temporal resolution, due to accretion of annual growth increments. The aim of this study is to use sclerochronological records of A. islandica to extend instrumental hydrographic records and increase our understanding of a variability of a Norwegian Coastal Current (NCC). The NCC transports warm, low-salinity water northwards, which eventually plays role for the Arctic halocline. Moreover, previous investigations showed the connection of properties and variability of the NCC with catches of commercially valuable fishes. The knowledge of the variability of the NCC is also essential for possible future prediction climate conditions and fish stock variability in the region. In this study we use shells of Arctica islandica collected off the coast of Eggum (Lofoten, Norway). The material was obtained from the depth 5-10 m by dredging along the seabed and by means of scuba divers. We examine the growth patterns of living and subfossil shells. Ongoing work mainly focuses on the construction of a composite growth chronology based on increment-width time series. The results we will compare with existing time series of the environment and climatic parameters to determine the controlling factors and test the applicability of growth chronology in a climate reconstruction. Furthermore, we will perform geochemical analyses of the stable isotope composition (δ18O and δ13C) in shell carbonate to identify seasonal signals and reconstruct the surface water temperature on a sub-annual time-scale.

On the role of ozone feedback in the ENSO amplitude response under global warming.

PubMed

Nowack, Peer J; Braesicke, Peter; Luke Abraham, N; Pyle, John A

2017-04-28

The El Niño-Southern Oscillation (ENSO) in the tropical Pacific Ocean is of key importance to global climate and weather. However, state-of-the-art climate models still disagree on the ENSO's response under climate change. The potential role of atmospheric ozone changes in this context has not been explored before. Here we show that differences between typical model representations of ozone can have a first-order impact on ENSO amplitude projections in climate sensitivity simulations. The vertical temperature gradient of the tropical middle-to-upper troposphere adjusts to ozone changes in the upper troposphere and lower stratosphere, modifying the Walker circulation and consequently tropical Pacific surface temperature gradients. We show that neglecting ozone changes thus results in a significant increase in the number of extreme ENSO events in our model. Climate modeling studies of the ENSO often neglect changes in ozone. We therefore highlight the need to understand better the coupling between ozone, the tropospheric circulation, and climate variability.

Non-linear responses of glaciated prairie wetlands to climate warming

USGS Publications Warehouse

Johnson, W. Carter; Werner, Brett; Guntenspergen, Glenn R.

2016-01-01

The response of ecosystems to climate warming is likely to include threshold events when small changes in key environmental drivers produce large changes in an ecosystem. Wetlands of the Prairie Pothole Region (PPR) are especially sensitive to climate variability, yet the possibility that functional changes may occur more rapidly with warming than expected has not been examined or modeled. The productivity and biodiversity of these wetlands are strongly controlled by the speed and completeness of a vegetation cover cycle driven by the wet and dry extremes of climate. Two thresholds involving duration and depth of standing water must be exceeded every few decades or so to complete the cycle and to produce highly functional wetlands. Model experiments at 19 weather stations employing incremental warming scenarios determined that wetland function across most of the PPR would be diminished beyond a climate warming of about 1.5–2.0 °C, a critical temperature threshold range identified in other climate change studies.

Climate Analytics as a Service

NASA Technical Reports Server (NTRS)

Schnase, John L.; Duffy, Daniel Q.; McInerney, Mark A.; Webster, W. Phillip; Lee, Tsengdar J.

2014-01-01

Climate science is a big data domain that is experiencing unprecedented growth. In our efforts to address the big data challenges of climate science, we are moving toward a notion of Climate Analytics-as-a-Service (CAaaS). CAaaS combines high-performance computing and data-proximal analytics with scalable data management, cloud computing virtualization, the notion of adaptive analytics, and a domain-harmonized API to improve the accessibility and usability of large collections of climate data. MERRA Analytic Services (MERRA/AS) provides an example of CAaaS. MERRA/AS enables MapReduce analytics over NASA's Modern-Era Retrospective Analysis for Research and Applications (MERRA) data collection. The MERRA reanalysis integrates observational data with numerical models to produce a global temporally and spatially consistent synthesis of key climate variables. The effectiveness of MERRA/AS has been demonstrated in several applications. In our experience, CAaaS is providing the agility required to meet our customers' increasing and changing data management and data analysis needs.

On the data-driven inference of modulatory networks in climate science: an application to West African rainfall

NASA Astrophysics Data System (ADS)

González, D. L., II; Angus, M. P.; Tetteh, I. K.; Bello, G. A.; Padmanabhan, K.; Pendse, S. V.; Srinivas, S.; Yu, J.; Semazzi, F.; Kumar, V.; Samatova, N. F.

2014-04-01

Decades of hypothesis-driven and/or first-principles research have been applied towards the discovery and explanation of the mechanisms that drive climate phenomena, such as western African Sahel summer rainfall variability. Although connections between various climate factors have been theorized, not all of the key relationships are fully understood. We propose a data-driven approach to identify candidate players in this climate system, which can help explain underlying mechanisms and/or even suggest new relationships, to facilitate building a more comprehensive and predictive model of the modulatory relationships influencing a climate phenomenon of interest. We applied coupled heterogeneous association rule mining (CHARM), Lasso multivariate regression, and Dynamic Bayesian networks to find relationships within a complex system, and explored means with which to obtain a consensus result from the application of such varied methodologies. Using this fusion of approaches, we identified relationships among climate factors that modulate Sahel rainfall, including well-known associations from prior climate knowledge, as well as promising discoveries that invite further research by the climate science community.

Current Climate Variability & Change

NASA Astrophysics Data System (ADS)

Diem, J.; Criswell, B.; Elliott, W. C.

2013-12-01

Current Climate Variability & Change is the ninth among a suite of ten interconnected, sequential labs that address all 39 climate-literacy concepts in the U.S. Global Change Research Program's Climate Literacy: The Essential Principles of Climate Sciences. The labs are as follows: Solar Radiation & Seasons, Stratospheric Ozone, The Troposphere, The Carbon Cycle, Global Surface Temperature, Glacial-Interglacial Cycles, Temperature Changes over the Past Millennium, Climates & Ecosystems, Current Climate Variability & Change, and Future Climate Change. All are inquiry-based, on-line products designed in a way that enables students to construct their own knowledge of a topic. Questions representative of various levels of Webb's depth of knowledge are embedded in each lab. In addition to the embedded questions, each lab has three or four essential questions related to the driving questions for the lab suite. These essential questions are presented as statements at the beginning of the material to represent the lab objectives, and then are asked at the end as questions to function as a summative assessment. For example, the Current Climate Variability & Change is built around these essential questions: (1) What has happened to the global temperature at the Earth's surface, in the middle troposphere, and in the lower stratosphere over the past several decades?; (2) What is the most likely cause of the changes in global temperature over the past several decades and what evidence is there that this is the cause?; and (3) What have been some of the clearly defined effects of the change in global temperature on the atmosphere and other spheres of the Earth system? An introductory Prezi allows the instructor to assess students' prior knowledge in relation to these questions, while also providing 'hooks' to pique their interest related to the topic. The lab begins by presenting examples of and key differences between climate variability (e.g., Mt. Pinatubo eruption) and climate change. The next section guides students through the exploration of temporal changes in global temperature from the surface to the lower stratosphere. Students discover that there has been global warming over the past several decades, and the subsequent section allows them to consider solar radiation and greenhouse gases as possible causes of this warming. Students then zoom in on different latitudinal zones to examine changes in temperature for each zone and hypothesize about why one zone may have warmed more than others. The final section, prior to the answering of the essential questions, is an examination of the following effects of the current change in temperatures: loss of sea ice; rise of sea level; loss of permafrost loss; and moistening of the atmosphere. The lab addresses 14 climate-literacy concepts and all seven climate-literacy principles through data and images that are mainly NASA products. It focuses on the satellite era of climate data; therefore, 1979 is the typical starting year for most datasets used by students. Additionally, all time-series analysis end with the latest year with full-year data availability; thus, the climate variability and trends truly are 'current.'

Extreme rainfall, vulnerability and risk: a continental-scale assessment for South America.

PubMed

Vörösmarty, Charles J; Bravo de Guenni, Lelys; Wollheim, Wilfred M; Pellerin, Brian; Bjerklie, David; Cardoso, Manoel; D'Almeida, Cassiano; Green, Pamela; Colon, Lilybeth

2013-11-13

Extreme weather continues to preoccupy society as a formidable public safety concern bearing huge economic costs. While attention has focused on global climate change and how it could intensify key elements of the water cycle such as precipitation and river discharge, it is the conjunction of geophysical and socioeconomic forces that shapes human sensitivity and risks to weather extremes. We demonstrate here the use of high-resolution geophysical and population datasets together with documentary reports of rainfall-induced damage across South America over a multi-decadal, retrospective time domain (1960-2000). We define and map extreme precipitation hazard, exposure, affectedpopulations, vulnerability and risk, and use these variables to analyse the impact of floods as a water security issue. Geospatial experiments uncover major sources of risk from natural climate variability and population growth, with change in climate extremes bearing a minor role. While rural populations display greatest relative sensitivity to extreme rainfall, urban settings show the highest rates of increasing risk. In the coming decades, rapid urbanization will make South American cities the focal point of future climate threats but also an opportunity for reducing vulnerability, protecting lives and sustaining economic development through both traditional and ecosystem-based disaster risk management systems.

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

NASA Astrophysics Data System (ADS)

Burbank, D. W.

2016-12-01

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

NASA Contributions to Improve Understanding of Extreme Events in the Global Energy and Water Cycle

NASA Technical Reports Server (NTRS)

Lapenta, William M.

2008-01-01

The U.S. Climate Change Science Program (CCSP) has established the water cycle goals of the Nation's climate change program. Accomplishing these goals will require, in part, an accurate accounting of the key reservoirs and fluxes associated with the global water and energy cycle, including their spatial and temporal variability. through integration of all necessary observations and research tools, To this end, in conjunction with NASA's Earth science research strategy, the overarching long-term NASA Energy and Water Cycle Study (NEWS) grand challenge can he summarized as documenting and enabling improved, observationally based, predictions of water and energy cycle consequences of Earth system variability and change. This challenge requires documenting and predicting trends in the rate of the Earth's water and energy cycling that corresponds to climate change and changes in the frequency and intensity of naturally occurring related meteorological and hydrologic events, which may vary as climate may vary in the future. The cycling of water and energy has obvious and significant implications for the health and prosperity of our society. The importance of documenting and predicting water and energy cycle variations and extremes is necessary to accomplish this benefit to society.

Engaging Indigenous Communities and Research Scientists to Manage Climate Risk

NASA Astrophysics Data System (ADS)

Jasko, S. A.; Pandya, R.; Wildcat, D.; Moench, M.; Leshin, L. A.; Jasko, S. A.; Pulwarty, R. S.; Kluck, D. R.; Collins, G.; Lazrus, H.

2014-12-01

For the past five years a strategy has been employed to reach out to tribes and tribal colleges to build awareness and potentially transfer information that would strengthen tribal resilience to climate variability and changes. Finding an effective approach to first engaging tribal communities and risk management issues from their perspective has been the key. Climate information that is place based and temporally relevant provides the greatest value. By engaging in a social process of risk communication instead of traditional sender- receiver model are taking place and continuing across the U.S. 4-Corners, Pacific Northwest and Missouri Basin. For this presentation we will focus primarily on the lessons from those engagements on water resources in the Missouri Basin where twenty-eight tribes reside.

ENSO elicits opposing responses of semi-arid vegetation between Hemispheres

NASA Astrophysics Data System (ADS)

Zhang, Anzhi; Jia, Gensuo; Epstein, Howard E.; Xia, Jiangjiang

2017-02-01

Semi-arid ecosystems are key contributors to the global carbon cycle and may even dominate the inter-annual variability (IAV) and trends of the land carbon sink, driven largely by the El Niño-Southern Oscillation (ENSO). The linkages between dynamics of semi-arid ecosystems and climate at the hemispheric scale however are not well known. Here, we use satellite data and climate observations from 2000 to 2014 to explore the impacts of ENSO on variability of semi-arid ecosystems, using the Ensemble Empirical Mode Decomposition method. We show that the responses of semi-arid vegetation to ENSO occur in opposite directions, resulting from opposing controls of ENSO on precipitation between the Northern Hemisphere (positively correlated to ENSO) and the Southern Hemisphere (negatively correlated to ENSO). Also, the Southern Hemisphere, with a robust negative coupling of temperature and precipitation anomalies, exhibits stronger and faster responses of semi-arid ecosystems to ENSO than the Northern Hemisphere. Our findings suggest that natural coherent variability in semi-arid ecosystem productivity responded to ENSO in opposite ways between two hemispheres, which may imply potential prediction of global semi-arid ecosystem variability, particularly based on variability in tropical Pacific Sea Surface Temperatures.

Sources of global climate data and visualization portals

USGS Publications Warehouse

Douglas, David C.

2014-01-01

Climate is integral to the geophysical foundation upon which ecosystems are structured. Knowledge about mechanistic linkages between the geophysical and biological environments is essential for understanding how global warming may reshape contemporary ecosystems and ecosystem services. Numerous global data sources spanning several decades are available that document key geophysical metrics such as temperature and precipitation, and metrics of primary biological production such as vegetation phenology and ocean phytoplankton. This paper provides an internet directory to portals for visualizing or servers for downloading many of the more commonly used global datasets, as well as a description of how to write simple computer code to efficiently retrieve these data. The data are broadly useful for quantifying relationships between climate, habitat availability, and lower-trophic-level habitat quality - especially in Arctic regions where strong seasonality is accompanied by intrinsically high year-to-year variability. If defensible linkages between the geophysical (climate) and the biological environment can be established, general circulation model (GCM) projections of future climate conditions can be used to infer future biological responses. Robustness of this approach is, however, complicated by the number of direct, indirect, or interacting linkages involved. For example, response of a predator species to climate change will be influenced by the responses of its prey and competitors, and so forth throughout a trophic web. The complexities of ecological systems warrant sensible and parsimonious approaches for assessing and establishing the role of natural climate variability in order to substantiate inferences about the potential effects of global warming.

Large-scale Meteorological Patterns Associated with Extreme Precipitation Events over Portland, OR

NASA Astrophysics Data System (ADS)

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

2017-12-01

Extreme precipitation events can have profound impacts on human life and infrastructure, with broad implications across a range of stakeholders. Changes to extreme precipitation events are a projected outcome of climate change that warrants further study, especially at regional- to local-scales. While global climate models are generally capable of simulating mean climate at global-to-regional scales with reasonable skill, resiliency and adaptation decisions are made at local-scales where most state-of-the-art climate models are limited by coarse resolution. Characterization of large-scale meteorological patterns associated with extreme precipitation events at local-scales can provide climatic information without this scale limitation, thus facilitating stakeholder decision-making. This research will use synoptic climatology as a tool by which to characterize the key large-scale meteorological patterns associated with extreme precipitation events in the Portland, Oregon metro region. Composite analysis of meteorological patterns associated with extreme precipitation days, and associated watershed-specific flooding, is employed to enhance understanding of the climatic drivers behind such events. The self-organizing maps approach is then used to characterize the within-composite variability of the large-scale meteorological patterns associated with extreme precipitation events, allowing us to better understand the different types of meteorological conditions that lead to high-impact precipitation events and associated hydrologic impacts. A more comprehensive understanding of the meteorological drivers of extremes will aid in evaluation of the ability of climate models to capture key patterns associated with extreme precipitation over Portland and to better interpret projections of future climate at impact-relevant scales.

Evaluation of terrestrial carbon cycle models with atmospheric CO2 measurements: Results from transient simulations considering increasing CO2, climate, and land-use effects

USGS Publications Warehouse

Dargaville, R.J.; Heimann, Martin; McGuire, A.D.; Prentice, I.C.; Kicklighter, D.W.; Joos, F.; Clein, Joy S.; Esser, G.; Foley, J.; Kaplan, J.; Meier, R.A.; Melillo, J.M.; Moore, B.; Ramankutty, N.; Reichenau, T.; Schloss, A.; Sitch, S.; Tian, H.; Williams, L.J.; Wittenberg, U.

2002-01-01

An atmospheric transport model and observations of atmospheric CO2 are used to evaluate the performance of four Terrestrial Carbon Models (TCMs) in simulating the seasonal dynamics and interannual variability of atmospheric CO2 between 1980 and 1991. The TCMs were forced with time varying atmospheric CO2 concentrations, climate, and land use to simulate the net exchange of carbon between the terrestrial biosphere and the atmosphere. The monthly surface CO2 fluxes from the TCMs were used to drive the Model of Atmospheric Transport and Chemistry and the simulated seasonal cycles and concentration anomalies are compared with observations from several stations in the CMDL network. The TCMs underestimate the amplitude of the seasonal cycle and tend to simulate too early an uptake of CO2 during the spring by approximately one to two months. The model fluxes show an increase in amplitude as a result of land-use change, but that pattern is not so evident in the simulated atmospheric amplitudes, and the different models suggest different causes for the amplitude increase (i.e., CO2 fertilization, climate variability or land use change). The comparison of the modeled concentration anomalies with the observed anomalies indicates that either the TCMs underestimate interannual variability in the exchange of CO2 between the terrestrial biosphere and the atmosphere, or that either the variability in the ocean fluxes or the atmospheric transport may be key factors in the atmospheric interannual variability.

Untangling Trends and Drivers of Changing River Discharge Along Florida's Gulf Coast

NASA Astrophysics Data System (ADS)

Glodzik, K.; Kaplan, D. A.; Klarenberg, G.

2017-12-01

Along the relatively undeveloped Big Bend coastline of Florida, discharge in many rivers and springs is decreasing. The causes are unclear, though they likely include a combination of groundwater extraction for water supply, climate variability, and altered land use. Saltwater intrusion from altered freshwater influence and sea level rise is causing transformative ecosystem impacts along this flat coastline, including coastal forest die-off and oyster reef collapse. A key uncertainty for understanding river discharge change is predicting discharge from rainfall, since Florida's karstic bedrock stores large amounts of groundwater, which has a long residence time. This study uses Dynamic Factor Analysis (DFA), a multivariate data reduction technique for time series, to find common trends in flow and reveal hydrologic variables affecting flow in eight Big Bend rivers since 1965. The DFA uses annual river flows as response time series, and climate data (annual rainfall and evapotranspiration by watershed) and climatic indices (El Niño Southern Oscillation [ENSO] Index and North Atlantic Oscillation [NAO] Index) as candidate explanatory variables. Significant explanatory variables (one evapotranspiration and three rainfall time series) explained roughly 50% of discharge variation across rivers. Significant trends (representing unexplained variation) were shared among rivers, with geographical grouping of five northern rivers and three southern rivers, along with a strong downward trend affecting six out of eight systems. ENSO and NAO had no significant impact. Advancing knowledge of these dynamics is necessary for forecasting how altered rainfall and temperatures from climate change may impact flows. Improved forecasting is especially important given Florida's reliance on groundwater extraction to support its growing population.

Implications of land use change in tropical West Africa under global warming

NASA Astrophysics Data System (ADS)

Brücher, Tim; Claussen, Martin

2015-04-01

Northern Africa, and the Sahel in particular, are highly vulnerable to climate change, due to strong exposure to increasing temperature, precipitation variability, and population growth. A major link between climate and humans in this region is land use and associated land cover change, mainly where subsistence farming prevails. But how strongly does climate change affect land use and how strongly does land use feeds back into climate change? To which extent may climate-induced water, food and wood shortages exacerbate conflict potential and lead changes in land use and to migration? Estimates of possible changes in African climate vary among the Earth System Models participating in the recent Coupled Model Intercomparison (CMIP5) exercise, except for the region adjacent to the Mediterranean Sea, where a significant decrease of precipitation emerges. While all models agree in a strong temperature increase, rainfall uncertainties for most parts of the Sahara, Sahel, and Sudan are higher. Here we present results of complementary experiments based on extreme and idealized land use change scenarios within a future climate.. We use the MPI-ESM forced with a strong green house gas scenario (RCP8.5) and apply an additional land use forcing by varying largely the intensity and kind of agricultural practice. By these transient experiments (until 2100) we elaborate the additional impact on climate due to strong land use forcing. However, the differences are mostly insignificant. The greenhouse gas caused temperature increase and the high variability in the West African Monsoon rainfall superposes the minor changes in climate due to land use. While simulated climate key variables like precipitation and temperature are not distinguishable from the CMIP5 RCP8.5 results, an additional greening is simulated, when crops are demanded. Crops have lower water usage than pastureland has. This benefits available soil water, which is taken up by the natural vegetation and makes it more productive. Given the limitations of an ESM, the findings of our study show that changes in the kind and intensity of land use have minor effects on the climate. Consequently, implications of extreme land use on e.g. human security, conflict or migration can be investigated in offline simulations.

[Application of regression tree in analyzing the effects of climate factors on NDVI in loess hilly area of Shaanxi Province].

PubMed

Liu, Yang; Lü, Yi-he; Zheng, Hai-feng; Chen, Li-ding

2010-05-01

Based on the 10-day SPOT VEGETATION NDVI data and the daily meteorological data from 1998 to 2007 in Yan' an City, the main meteorological variables affecting the annual and interannual variations of NDVI were determined by using regression tree. It was found that the effects of test meteorological variables on the variability of NDVI differed with seasons and time lags. Temperature and precipitation were the most important meteorological variables affecting the annual variation of NDVI, and the average highest temperature was the most important meteorological variable affecting the inter-annual variation of NDVI. Regression tree was very powerful in determining the key meteorological variables affecting NDVI variation, but could not build quantitative relations between NDVI and meteorological variables, which limited its further and wider application.

Strong spatial variability in trace gas dynamics following experimental drought in a humid tropical forest

Treesearch

Tana Wood; W. L. Silver

2012-01-01

[1] Soil moisture is a key driver of biogeochemical processes in terrestrial ecosystems, strongly affecting carbon (C) and nutrient availability as well as trace gas production and consumption in soils. Models predict increasing drought frequency in tropical forest ecosystems, which could feed back on future climate change directly via effects on trace gasdynamics and...

ForestCrowns: a software tool for analyzing ground-based digital photographs of forest canopies

Treesearch

Matthew F. Winn; Sang-Mook Lee; Phillip A. Araman

2013-01-01

Canopy coverage is a key variable used to characterize forest structure. In addition, the light transmitted through the canopy is an important ecological indicator of plant and animal habitat and understory climate conditions. A common ground-based method used to document canopy coverage is to take digital photographs from below the canopy. To assist with analyzing...

Comparison of elevation and remote sensing derived products as auxiliary data for climate surface interpolation

USGS Publications Warehouse

Alvarez, Otto; Guo, Qinghua; Klinger, Robert C.; Li, Wenkai; Doherty, Paul

2013-01-01

Climate models may be limited in their inferential use if they cannot be locally validated or do not account for spatial uncertainty. Much of the focus has gone into determining which interpolation method is best suited for creating gridded climate surfaces, which often a covariate such as elevation (Digital Elevation Model, DEM) is used to improve the interpolation accuracy. One key area where little research has addressed is in determining which covariate best improves the accuracy in the interpolation. In this study, a comprehensive evaluation was carried out in determining which covariates were most suitable for interpolating climatic variables (e.g. precipitation, mean temperature, minimum temperature, and maximum temperature). We compiled data for each climate variable from 1950 to 1999 from approximately 500 weather stations across the Western United States (32° to 49° latitude and −124.7° to −112.9° longitude). In addition, we examined the uncertainty of the interpolated climate surface. Specifically, Thin Plate Spline (TPS) was used as the interpolation method since it is one of the most popular interpolation techniques to generate climate surfaces. We considered several covariates, including DEM, slope, distance to coast (Euclidean distance), aspect, solar potential, radar, and two Normalized Difference Vegetation Index (NDVI) products derived from Advanced Very High Resolution Radiometer (AVHRR) and Moderate Resolution Imaging Spectroradiometer (MODIS). A tenfold cross-validation was applied to determine the uncertainty of the interpolation based on each covariate. In general, the leading covariate for precipitation was radar, while DEM was the leading covariate for maximum, mean, and minimum temperatures. A comparison to other products such as PRISM and WorldClim showed strong agreement across large geographic areas but climate surfaces generated in this study (ClimSurf) had greater variability at high elevation regions, such as in the Sierra Nevada Mountains.

Spatial patterns of recent Antarctic surface temperature trends and the importance of natural variability: lessons from multiple reconstructions and the CMIP5 models

NASA Astrophysics Data System (ADS)

Smith, Karen L.; Polvani, Lorenzo M.

2017-04-01

The recent annually averaged warming of the Antarctic Peninsula, and of West Antarctica, stands in stark contrast to very small trends over East Antarctica. This asymmetry arises primarily from a highly significant warming of West Antarctica in austral spring and a cooling of East Antarctica in austral autumn. Here we examine whether this East-West asymmetry is a response to anthropogenic climate forcings or a manifestation of natural climate variability. We compare the observed Antarctic surface air temperature trends over two distinct time periods (1960-2005 and 1979-2005), and with those simulated by 40 models participating in Phase 5 of the Coupled Model Intercomparison Project (CMIP5). We find that the observed East-West asymmetry differs substantially between the two periods and, furthermore, that it is completely absent from the forced response seen in the CMIP5 multi-model mean, from which all natural variability is eliminated by the averaging. We also examine the relationship between the Southern Annular mode (SAM) and Antarctic temperature trends, in both models and reanalyses, and again conclude that there is little evidence of anthropogenic SAM-induced driving of the recent temperature trends. These results offer new, compelling evidence pointing to natural climate variability as a key contributor to the recent warming of West Antarctica and of the Peninsula.

Climate Change and Crop Exposure to Adverse Weather: Changes to Frost Risk and Grapevine Flowering Conditions.

PubMed

Mosedale, Jonathan R; Wilson, Robert J; Maclean, Ilya M D

2015-01-01

The cultivation of grapevines in the UK and many other cool climate regions is expected to benefit from the higher growing season temperatures predicted under future climate scenarios. Yet the effects of climate change on the risk of adverse weather conditions or events at key stages of crop development are not always captured by aggregated measures of seasonal or yearly climates, or by downscaling techniques that assume climate variability will remain unchanged under future scenarios. Using fine resolution projections of future climate scenarios for south-west England and grapevine phenology models we explore how risks to cool-climate vineyard harvests vary under future climate conditions. Results indicate that the risk of adverse conditions during flowering declines under all future climate scenarios. In contrast, the risk of late spring frosts increases under many future climate projections due to advancement in the timing of budbreak. Estimates of frost risk, however, were highly sensitive to the choice of phenology model, and future frost exposure declined when budbreak was calculated using models that included a winter chill requirement for dormancy break. The lack of robust phenological models is a major source of uncertainty concerning the impacts of future climate change on the development of cool-climate viticulture in historically marginal climatic regions.

Climate Change and Crop Exposure to Adverse Weather: Changes to Frost Risk and Grapevine Flowering Conditions

PubMed Central

Mosedale, Jonathan R.; Wilson, Robert J.; Maclean, Ilya M. D.

2015-01-01

The cultivation of grapevines in the UK and many other cool climate regions is expected to benefit from the higher growing season temperatures predicted under future climate scenarios. Yet the effects of climate change on the risk of adverse weather conditions or events at key stages of crop development are not always captured by aggregated measures of seasonal or yearly climates, or by downscaling techniques that assume climate variability will remain unchanged under future scenarios. Using fine resolution projections of future climate scenarios for south-west England and grapevine phenology models we explore how risks to cool-climate vineyard harvests vary under future climate conditions. Results indicate that the risk of adverse conditions during flowering declines under all future climate scenarios. In contrast, the risk of late spring frosts increases under many future climate projections due to advancement in the timing of budbreak. Estimates of frost risk, however, were highly sensitive to the choice of phenology model, and future frost exposure declined when budbreak was calculated using models that included a winter chill requirement for dormancy break. The lack of robust phenological models is a major source of uncertainty concerning the impacts of future climate change on the development of cool-climate viticulture in historically marginal climatic regions. PMID:26496127

Revealing, Reducing, and Representing Uncertainties in New Hydrologic Projections for Climate-changed Futures

NASA Astrophysics Data System (ADS)

Arnold, Jeffrey; Clark, Martyn; Gutmann, Ethan; Wood, Andy; Nijssen, Bart; Rasmussen, Roy

2016-04-01

The United States Army Corps of Engineers (USACE) has had primary responsibility for multi-purpose water resource operations on most of the major river systems in the U.S. for more than 200 years. In that time, the USACE projects and programs making up those operations have proved mostly robust against the range of natural climate variability encountered over their operating life spans. However, in some watersheds and for some variables, climate change now is known to be shifting the hydroclimatic baseline around which that natural variability occurs and changing the range of that variability as well. This makes historical stationarity an inappropriate basis for assessing continued project operations under climate-changed futures. That means new hydroclimatic projections are required at multiple scales to inform decisions about specific threats and impacts, and for possible adaptation responses to limit water-resource vulnerabilities and enhance operational resilience. However, projections of possible future hydroclimatologies have myriad complex uncertainties that require explicit guidance for interpreting and using them to inform those decisions about climate vulnerabilities and resilience. Moreover, many of these uncertainties overlap and interact. Recent work, for example, has shown the importance of assessing the uncertainties from multiple sources including: global model structure [Meehl et al., 2005; Knutti and Sedlacek, 2013]; internal climate variability [Deser et al., 2012; Kay et al., 2014]; climate downscaling methods [Gutmann et al., 2012; Mearns et al., 2013]; and hydrologic models [Addor et al., 2014; Vano et al., 2014; Mendoza et al., 2015]. Revealing, reducing, and representing these uncertainties is essential for defining the plausible quantitative climate change narratives required to inform water-resource decision-making. And to be useful, such quantitative narratives, or storylines, of climate change threats and hydrologic impacts must sample from the full range of uncertainties associated with all parts of the simulation chain, from global climate models with simulations of natural climate variability, through regional climate downscaling, and on to modeling of affected hydrologic processes and downstream water resources impacts. This talk will present part of the work underway now both to reveal and reduce some important uncertainties and to develop explicit guidance for future generation of quantitative hydroclimatic storylines. Topics will include: 1- model structural and parameter-set limitations of some methods widely used to quantify climate impacts to hydrologic processes [Gutmann et al., 2014; Newman et al., 2015]; 2- development and evaluation of new, spatially consistent, U.S. national-scale climate downscaling and hydrologic simulation capabilities directly relevant at the multiple scales of water-resource decision-making [Newman et al., 2015; Mizukami et al., 2015; Gutmann et al., 2016]; and 3- development and evaluation of advanced streamflow forecasting methods to reduce and represent integrated uncertainties in a tractable way [Wood et al., 2014; Wood et al., 2015]. A key focus will be areas where climatologic and hydrologic science is currently under-developed to inform decisions - or is perhaps wrongly scaled or misapplied in practice - indicating the need for additional fundamental science and interpretation.

Harmonising and semantically linking key variables from in-situ observing networks of an Integrated Atlantic Ocean Observing System, AtlantOS

NASA Astrophysics Data System (ADS)

Darroch, Louise; Buck, Justin

2017-04-01

Atlantic Ocean observation is currently undertaken through loosely-coordinated, in-situ observing networks, satellite observations and data management arrangements at regional, national and international scales. The EU Horizon 2020 AtlantOS project aims to deliver an advanced framework for the development of an Integrated Atlantic Ocean Observing System that strengthens the Global Ocean Observing System (GOOS) and contributes to the aims of the Galway Statement on Atlantic Ocean Cooperation. One goal is to ensure that data from different and diverse in-situ observing networks are readily accessible and useable to a wider community, including the international ocean science community and other stakeholders in this field. To help achieve this goal, the British Oceanographic Data Centre (BODC) produced a parameter matrix to harmonise data exchange, data flow and data integration for the key variables acquired by multiple in-situ AtlantOS observing networks such as ARGO, Seafloor Mapping and OceanSITES. Our solution used semantic linking of controlled vocabularies and metadata for parameters that were "mappable" to existing EU and international standard vocabularies. An AtlantOS Essential Variables list of terms (aggregated level) based on Global Climate Observing System (GCOS) Essential Climate Variables (ECV), GOOS Essential Ocean Variables (EOV) and other key network variables was defined and published on the Natural Environment Research Council (NERC) Vocabulary Server (version 2.0) as collection A05 (http://vocab.nerc.ac.uk/collection/A05/current/). This new vocabulary was semantically linked to standardised metadata for observed properties and units that had been validated by the AtlantOS community: SeaDataNet parameters (P01), Climate and Forecast (CF) Standard Names (P07) and SeaDataNet units (P06). Observed properties were mapped to biological entities from the internationally assured AphiaID from the WOrld Register of Marine Species (WoRMS), http://www.marinespecies.org/aphia.php?p=webservice. The AtlantOS parameter matrix offers a way to harmonise the globally important variables (such as ECVs and EOVs) from in-situ observing networks that use different flavours of exchange formats based on SeaDataNet and CF parameter metadata. It also offers a way to standardise data in the wider Integrated Ocean Observing System. It uses sustainable and trusted standardised vocabularies that are governed by internationally renowned and long-standing organisations and is interoperable through the use of persistent resource identifiers, such as URNs and PURLs. It is the first step to integrating and serving data in a variety of international exchange formats using Application programming interfaces (API) improving both data discoverability and utility for users.

Evaluation of Limiting Climatic Factors and Simulation of a Climatically Suitable Habitat for Chinese Sea Buckthorn

PubMed Central

Li, Guoqing; Du, Sheng; Guo, Ke

2015-01-01

Chinese sea buckthorn (Hippophae rhamnoides subsp. sinensis) has considerable economic potential and plays an important role in reclamation and soil and water conservation. For scientific cultivation of this species across China, we identified the key climatic factors and explored climatically suitable habitat in order to maximize survival of Chinese sea buckthorn using MaxEnt and GIS tools, based on 98 occurrence records from herbarium and publications and 13 climatic factors from Bioclim, Holdridge life zone and Kria' index variables. Our simulation showed that the MaxEnt model performance was significantly better than random, with an average test AUC value of 0.93 with 10-fold cross validation. A jackknife test and the regularized gain change, which were applied to the training algorithm, showed that precipitation of the driest month (PDM), annual precipitation (AP), coldness index (CI) and annual range of temperature (ART) were the most influential climatic factors in limiting the distribution of Chinese sea buckthorn, which explained 70.1% of the variation. The predicted map showed that the core of climatically suitable habitat was distributed from the southwest to northwest of Gansu, Ningxia, Shaanxi and Shanxi provinces, where the most influential climate variables were PDM of 1.0–7.0 mm, AP of 344.0–1089.0 mm, CI of -47.7–0.0°C, and ART of 26.1–45.0°C. We conclude that the distribution patterns of Chinese sea buckthorn are related to the northwest winter monsoon, the southwest summer monsoon and the southeast summer monsoon systems in China. PMID:26177033

Evaluation of Limiting Climatic Factors and Simulation of a Climatically Suitable Habitat for Chinese Sea Buckthorn.

PubMed

Li, Guoqing; Du, Sheng; Guo, Ke

2015-01-01

Chinese sea buckthorn (Hippophae rhamnoides subsp. sinensis) has considerable economic potential and plays an important role in reclamation and soil and water conservation. For scientific cultivation of this species across China, we identified the key climatic factors and explored climatically suitable habitat in order to maximize survival of Chinese sea buckthorn using MaxEnt and GIS tools, based on 98 occurrence records from herbarium and publications and 13 climatic factors from Bioclim, Holdridge life zone and Kria' index variables. Our simulation showed that the MaxEnt model performance was significantly better than random, with an average test AUC value of 0.93 with 10-fold cross validation. A jackknife test and the regularized gain change, which were applied to the training algorithm, showed that precipitation of the driest month (PDM), annual precipitation (AP), coldness index (CI) and annual range of temperature (ART) were the most influential climatic factors in limiting the distribution of Chinese sea buckthorn, which explained 70.1% of the variation. The predicted map showed that the core of climatically suitable habitat was distributed from the southwest to northwest of Gansu, Ningxia, Shaanxi and Shanxi provinces, where the most influential climate variables were PDM of 1.0-7.0 mm, AP of 344.0-1089.0 mm, CI of -47.7-0.0°C, and ART of 26.1-45.0°C. We conclude that the distribution patterns of Chinese sea buckthorn are related to the northwest winter monsoon, the southwest summer monsoon and the southeast summer monsoon systems in China.

Stress testing hydrologic models using bottom-up climate change assessment

NASA Astrophysics Data System (ADS)

Stephens, C.; Johnson, F.; Marshall, L. A.

2017-12-01

Bottom-up climate change assessment is a promising approach for understanding the vulnerability of a system to potential future changes. The technique has been utilised successfully in risk-based assessments of future flood severity and infrastructure vulnerability. We find that it is also an ideal tool for assessing hydrologic model performance in a changing climate. In this study, we applied bottom-up climate change to compare the performance of two different hydrologic models (an event-based and a continuous model) under increasingly severe climate change scenarios. This allowed us to diagnose likely sources of future prediction error in the two models. The climate change scenarios were based on projections for southern Australia, which indicate drier average conditions with increased extreme rainfall intensities. We found that the key weakness in using the event-based model to simulate drier future scenarios was the model's inability to dynamically account for changing antecedent conditions. This led to increased variability in model performance relative to the continuous model, which automatically accounts for the wetness of a catchment through dynamic simulation of water storages. When considering more intense future rainfall events, representation of antecedent conditions became less important than assumptions around (non)linearity in catchment response. The linear continuous model we applied may underestimate flood risk in a future climate with greater extreme rainfall intensity. In contrast with the recommendations of previous studies, this indicates that continuous simulation is not necessarily the key to robust flood modelling under climate change. By applying bottom-up climate change assessment, we were able to understand systematic changes in relative model performance under changing conditions and deduce likely sources of prediction error in the two models.

Modelling ecological flow regime: an example from the Tennessee and Cumberland River basins

USGS Publications Warehouse

Knight, Rodney R.; Gain, W. Scott; Wolfe, William J.

2012-01-01

Predictive equations were developed for 19 ecologically relevant streamflow characteristics within five major groups of flow variables (magnitude, ratio, frequency, variability, and date) for use in the Tennessee and Cumberland River basins using stepbackward regression. Basin characteristics explain 50% or more of the variation for 12 of the 19 equations. Independent variables identified through stepbackward regression were statistically significant in 78 of 304 cases (α > 0.0001) and represent four major groups: climate, physical landscape features, regional indicators, and land use. Of these groups, the regional and climate variables were the most influential for determining hydrologic response. Daily temperature range, geologic factor, and rock depth were major factors explaining the variability in 17, 15, and 13 equations, respectively. The equations and independent datasets were used to explore the broad relation between basin properties and streamflow and the implication of streamflow to the study of ecological flow requirements. Key results include a high degree of hydrologic variability among least disturbed Blue Ridge streams, similar hydrologic behaviour for watersheds with widely varying degrees of forest cover, and distinct hydrologic profiles for streams in different geographic regions. Published in 2011. This article is a US Government work and is in the public domain in the USA.

Forced vs unforced drivers of Atlantic SST variability - linking forced role to magnitude of aerosol forcing

NASA Astrophysics Data System (ADS)

Booth, B.; Dunstone, N.; Halloran, P. R.; Andrews, T.; Bellouin, N.; Martin, E. R.

2014-12-01

Historical variations in North Atlantic SSTs have been a key driver of regional climate change - linked to drought frequency in the Sahel, Amazon and American Mid-West, rainfall and heat waves in Europe and frequency of Atlantic tropical storms. Traditionally these SST variations were deemed to arise from internally generated ocean variability. We present results from recent studies (Booth et al, 2012, Dunstone, 2013) that identify a mechanism via which volcanic and industrial aerosols could explain a large fraction of observed Atlantic variability, and its associated climate impacts. This work has prompted a lot of subsequent discussion about the relative contribution of ocean generated and external forced variability in the Atlantic. Here we present new results, that extend this earlier work, by looking at forced variability in the CMIP5 modelling context. This provides new insights into the potential externally forced role aerosols may play in the real world. CMIP5 models that represent aerosol-cloud interactions tend to have stronger correlations to observed variations in SSTs, but disagree on the magnitude of forced variability that they explain. We can link this contribution to the magnitude of aerosol forcing in each of these models - a factor that is both dependent on the aerosol parameterisation and the representation of boundary layer cloud in this region. This suggests that whether aerosols have played a larger or smaller role in historical Atlantic variability is tied to whether aerosols have a larger or smaller aerosol forcing (particularly indirect) in the real world. This in turn suggests that benefits of reducing current aerosol uncertainty are likely to extend beyond better estimates of global forcing, to providing a clearer picture of the past aerosol driven role in historical regional climate change.

Quantitative assessment of glacial fluctuations in the level of Lake Lisan, Dead Sea rift

NASA Astrophysics Data System (ADS)

Rohling, Eelco J.

2013-06-01

A quantitative understanding of climatic variations in the Levant during the last glacial cycle is needed to support archaeologists in assessing the drivers behind hominin migrations and cultural developments in this key region at the intersection between Africa and Europe. It will also foster a better understanding of the region's natural variability as context to projections of modern climate change. Detailed documentation of variations in the level of Lake Lisan - the lake that occupied the Dead Sea rift during the last glacial cycle - provides crucial climatic information for this region. Existing reconstructions suggest that Lake Lisan highstands during cold intervals of the last glacial cycle represent relatively humid conditions in the region, but these interpretations have remained predominantly qualitative. Here, I evaluate realistic ranges of the key climatological parameters that controlled lake level, based on the observed timing and amplitudes of lake-level variability. I infer that a mean precipitation rate over the wider catchment area of about 500 mm y-1, as proposed in the literature, would be consistent with observed lake levels if there was a concomitant 15-50% increase in wind speed during cold glacial stadials. This lends quantitative support to previous inferences of a notable increase in the intensity of Mediterranean (winter) storms during glacial periods, which tracked eastward into the Levant. In contrast to highstands during ‘regular’ stadials, lake level dropped during Heinrich Events. I demonstrate that this likely indicates a further intensification of the winds during those times.

Wood phenology: from organ-scale processes to terrestrial ecosystem models

NASA Astrophysics Data System (ADS)

Delpierre, Nicolas; Guillemot, Joannès

2016-04-01

In temperate and boreal trees, a dormancy period prevents organ development during adverse climatic conditions. Whereas the phenology of leaves and flowers has received considerable attention, to date, little is known regarding the phenology of other tree organs such as wood, fine roots, fruits and reserve compounds. In this presentation, we review both the role of environmental drivers in determining the phenology of wood and the models used to predict its phenology in temperate and boreal forest trees. Temperature is a key driver of the resumption of wood activity in spring. There is no such clear dominant environmental cue involved in the cessation of wood formation in autumn, but temperature and water stress appear as prominent factors. We show that wood phenology is a key driver of the interannual variability of wood growth in temperate tree species. Incorporating representations of wood phenology in a terrestrial ecosystem model substantially improved the simulation of wood growth under current climate.

Achieving the NOAA Arctic Action Plan: The Missing Permafrost Element - Permafrost Forecasting Listening Session Results

NASA Astrophysics Data System (ADS)

Buxbaum, T. M.; Thoman, R.; Romanovsky, V. E.

2015-12-01

Permafrost is ground at or below freezing for at least two consecutive years. It currently occupies 80% of Alaska. Permafrost temperature and active layer thickness (ALT) are key climatic variables for monitoring permafrost conditions. Active layer thickness is the depth that the top layer of ground above the permafrost thaws each summer season and permafrost temperature is the temperature of the frozen permafrost under this active layer. Knowing permafrost conditions is key for those individuals working and living in Alaska and the Arctic. The results of climate models predict vast changes and potential permafrost degradation across Alaska and the Arctic. NOAA is working to implement its 2014 Arctic Action Plan and permafrost forecasting is a missing piece of this plan. The Alaska Center for Climate Assessment and Policy (ACCAP), using our webinar software and our diverse network of statewide stakeholder contacts, hosted a listening session to bring together a select group of key stakeholders. During this listening session the National Weather Service (NWS) and key permafrost researchers explained what is possible in the realm of permafrost forecasting and participants had the opportunity to discuss and share with the group (NWS, researchers, other stakeholders) what is needed for usable permafrost forecasting. This listening session aimed to answer the questions: Is permafrost forecasting needed? If so, what spatial scale is needed by stakeholders? What temporal scales do stakeholders need/want? Are there key times (winter, fall freeze-up, etc.) or locations (North Slope, key oil development areas, etc.) where forecasting would be most applicable and useful? Are there other considerations or priority needs we haven't thought of regarding permafrost forecasting? This presentation will present the results of that listening session.

Precipitation variability on global pasturelands may affect food security in livestock-dependent regions

NASA Astrophysics Data System (ADS)

Sloat, L.; Gerber, J. S.; Samberg, L. H.; Smith, W. K.; West, P. C.; Herrero, M.; Brendan, P.; Cecile, G.; Katharina, W.; Smith, W. K.

2016-12-01

The need to feed an increasing number of people while maintaining biodiversity and ecosystem services is one of the key challenges currently facing humanity. Livestock systems are likely to be a crucial piece of this puzzle, as urbanization and changing diets in much of the world lead to increases in global meat consumption. This predicted increase in global demand for livestock products will challenge the ability of pastures and rangelands to maintain or increase their productivity. The majority of people that depend on animal production for food security do so through grazing and herding on natural rangelands, and these systems make a significant contribution to global production of meat and milk. The vegetation dynamics of natural forage are highly dependent on climate, and subject to disruption with changes in climate and climate variability. Precipitation heterogeneity has been linked to the ecosystem dynamics of grazing lands through impacts on livestock carrying capacity and grassland degradation potential. Additionally, changes in precipitation variability are linked to the increased incidence of extreme events (e.g. droughts, floods) that negatively impact food production and food security. Here, we use the inter-annual coefficient of variation (CV) of precipitation as a metric to assess climate risk on global pastures. Comparisons of global satellite measures of vegetation greenness to climate reveal that the CV of precipitation is negatively related to mean annual NDVI, such that areas with low year-to-year precipitation variability have the highest measures of vegetation greenness, and vice versa. Furthermore, areas with high CV of precipitation support lower livestock densities and produce less meat. A sliding window analysis of changes in CV of precipitation over the last century shows that, overall, precipitation variability is increasing in global pasture areas, although global maps reveal a patchwork of both positive and negative changes. We use this information to identify regions in which changes in the variability of precipitation may already be affecting the ability of grazing systems to support intensified livestock production, and assess the potential impacts of those changes on pasture productivity.

Determining diatom ecotones and their relationship to terrestrial ecoregion designations in the central Canadian Arctic Islands.

PubMed

Antoniades, Dermot; Douglas, Marianne S V; Michelutti, Neal; Smol, John P

2014-08-01

Ecotones are key areas for the detection of global change because many are predicted to move with shifts in climate. Prince of Wales Island, in the Canadian Arctic Archipelago, spans the transition between mid- to high-Arctic ecoregions. We analyzed limnological variables and recent diatom assemblages from its lakes and ponds to determine if assemblages reflected this ecotone. Limnological gradients were short, and water chemistry explained 20.0% of diatom variance in a redundancy analysis (RDA), driven primarily by dissolved organic carbon, Ca and SO4 . Most taxa were small, benthic forms; key taxa such as planktonic Cyclotella species were restricted to the warmer, southern portion of the study area, while benthic Staurosirella were associated with larger, ice-dominated lakes. Nonetheless, there were no significant changes in diatom assemblages across the mid- to high-Arctic ecoregion boundary. We combined our data set with one from nearby Cornwallis Island to expand the study area and lengthen its environmental gradients. Within this expanded data set, 40.6% of the diatom variance was explained by a combination of water chemistry and geographic variables, and significant relationships were revealed between diatom distributions and key limnological variables, including pH, specific conductivity, and chl-a. Using principal coordinates analysis, we estimated community turnover with latitude and applied piecewise linear regression to determine diatom ecotone positions. A pronounced transition was present between Prince of Wales Island and the colder, more northerly Cornwallis Island. These data will be important in detecting any future northward ecotone movement in response to predicted Arctic climate warming in this highly sensitive region. © 2014 Phycological Society of America.

Farmers' Perceptions of Climate Variability and Factors Influencing Adaptation: Evidence from Anhui and Jiangsu, China

NASA Astrophysics Data System (ADS)

Kibue, Grace Wanjiru; Liu, Xiaoyu; Zheng, Jufeng; zhang, Xuhui; Pan, Genxing; Li, Lianqing; Han, Xiaojun

2016-05-01

Impacts of climate variability and climate change are on the rise in China posing great threat to agriculture and rural livelihoods. Consequently, China is undertaking research to find solutions of confronting climate change and variability. However, most studies of climate change and variability in China largely fail to address farmers' perceptions of climate variability and adaptation. Yet, without an understanding of farmers' perceptions, strategies are unlikely to be effective. We conducted questionnaire surveys of farmers in two farming regions, Yifeng, Jiangsu and Qinxi, Anhui achieving 280 and 293 responses, respectively. Additionally, we used climatological data to corroborate the farmers' perceptions of climate variability. We found that farmers' were aware of climate variability such that were consistent with climate records. However, perceived impacts of climate variability differed between the two regions and were influenced by farmers' characteristics. In addition, the vast majorities of farmers were yet to make adjustments in their farming practices as a result of numerous challenges. These challenges included socioeconomic and socio-cultural barriers. Results of logit modeling showed that farmers are more likely to adapt to climate variability if contact with extension services, frequency of seeking information, household heads' education, and climate variability perceptions are improved. These results suggest the need for policy makers to understand farmers' perceptions of climate variability and change in order to formulate policies that foster adaptation, and ultimately protect China's agricultural assets.

Farmers' Perceptions of Climate Variability and Factors Influencing Adaptation: Evidence from Anhui and Jiangsu, China.

PubMed

Kibue, Grace Wanjiru; Liu, Xiaoyu; Zheng, Jufeng; Zhang, Xuhui; Pan, Genxing; Li, Lianqing; Han, Xiaojun

2016-05-01

Impacts of climate variability and climate change are on the rise in China posing great threat to agriculture and rural livelihoods. Consequently, China is undertaking research to find solutions of confronting climate change and variability. However, most studies of climate change and variability in China largely fail to address farmers' perceptions of climate variability and adaptation. Yet, without an understanding of farmers' perceptions, strategies are unlikely to be effective. We conducted questionnaire surveys of farmers in two farming regions, Yifeng, Jiangsu and Qinxi, Anhui achieving 280 and 293 responses, respectively. Additionally, we used climatological data to corroborate the farmers' perceptions of climate variability. We found that farmers' were aware of climate variability such that were consistent with climate records. However, perceived impacts of climate variability differed between the two regions and were influenced by farmers' characteristics. In addition, the vast majorities of farmers were yet to make adjustments in their farming practices as a result of numerous challenges. These challenges included socioeconomic and socio-cultural barriers. Results of logit modeling showed that farmers are more likely to adapt to climate variability if contact with extension services, frequency of seeking information, household heads' education, and climate variability perceptions are improved. These results suggest the need for policy makers to understand farmers' perceptions of climate variability and change in order to formulate policies that foster adaptation, and ultimately protect China's agricultural assets.

Drought is a recurring challenge in the Middle East.

PubMed

Kaniewski, David; Van Campo, Elise; Weiss, Harvey

2012-03-06

Climate change and water availability in the Middle East are important in understanding human adaptive capacities in the face of long-term environmental changes. The key role of water availability for sedentary and nomad populations in these arid to semiarid landscapes is understood, but the millennium-scale influence of hydrologic instability on vegetation dynamics, human occupation, and historic land use are unknown, which has led to a stochastic view of population responses and adaptive capacities to precipitation anomalies. Within the time-frame of the last two global climate events, the Medieval Climate Anomaly and the Little Ice Age, we report hydrologic instability reconstructed from pollen-derived climate proxies recovered near Tell Leilan, at the Wadi Jarrah in the Khabur Plains of northeastern Syria, at the heart of ancient northern Mesopotamia. By coupling climate proxies with archaeological-historical data and a pollen-based record of agriculture, this integrative study suggests that variability in precipitation is a key factor on crop yields, productivity, and economic systems. It may also have been one of the main parameters controlling human settlement and population migrations at the century to millennial timescales in the arid to semiarid areas of the Middle East. An abrupt shift to drier conditions at ca. AD 1400 is contemporaneous with a change from sedentary village life to regional desertion and nomadization (sheep/camel pastoralists) during the preindustrial era in formerly Ottoman realms, and thereby adds climate change to the multiple causes for Ottoman Empire "decline."

Drought is a recurring challenge in the Middle East

PubMed Central

Kaniewski, David; Van Campo, Elise; Weiss, Harvey

2012-01-01

Climate change and water availability in the Middle East are important in understanding human adaptive capacities in the face of long-term environmental changes. The key role of water availability for sedentary and nomad populations in these arid to semiarid landscapes is understood, but the millennium-scale influence of hydrologic instability on vegetation dynamics, human occupation, and historic land use are unknown, which has led to a stochastic view of population responses and adaptive capacities to precipitation anomalies. Within the time-frame of the last two global climate events, the Medieval Climate Anomaly and the Little Ice Age, we report hydrologic instability reconstructed from pollen-derived climate proxies recovered near Tell Leilan, at the Wadi Jarrah in the Khabur Plains of northeastern Syria, at the heart of ancient northern Mesopotamia. By coupling climate proxies with archaeological-historical data and a pollen-based record of agriculture, this integrative study suggests that variability in precipitation is a key factor on crop yields, productivity, and economic systems. It may also have been one of the main parameters controlling human settlement and population migrations at the century to millennial timescales in the arid to semiarid areas of the Middle East. An abrupt shift to drier conditions at ca. AD 1400 is contemporaneous with a change from sedentary village life to regional desertion and nomadization (sheep/camel pastoralists) during the preindustrial era in formerly Ottoman realms, and thereby adds climate change to the multiple causes for Ottoman Empire “decline.” PMID:22355126

Unraveling climate influences on the distribution of the parapatric newts Lissotriton vulgaris meridionalis and L. italicus.

PubMed

Iannella, Mattia; Cerasoli, Francesco; Biondi, Maurizio

2017-01-01

Climate is often considered as a key ecological factor limiting the capability of expansion of most species and the extent of suitable habitats. In this contribution, we implement Species Distribution Models (SDMs) to study two parapatric amphibians, Lissotriton vulgaris meridionalis and L. italicus , investigating if and how climate has influenced their present and past (Last Glacial Maximum and Holocene) distributions. A database of 901 GPS presence records was generated for the two newts. SDMs were built through Boosted Regression Trees and Maxent, using the Worldclim bioclimatic variables as predictors. Precipitation-linked variables and the temperature annual range strongly influence the current occurrence patterns of the two Lissotriton species analyzed. The two newts show opposite responses to the most contributing variables, such as BIO7 (temperature annual range), BIO12 (annual precipitation), BIO17 (precipitation of the driest quarter) and BIO19 (precipitation of the coldest quarter). The hypothesis of climate influencing the distributions of these species is also supported by the fact that the co-occurrences within the sympatric area fall in localities characterized by intermediate values of these predictors. Projections to the Last Glacial Maximum and Holocene scenarios provided a coherent representation of climate influences on the past distributions of the target species. Computation of pairwise variables interactions and the discriminant analysis allowed a deeper interpretation of SDMs' outputs. Further, we propose a multivariate environmental dissimilarity index (MEDI), derived through a transformation of the multivariate environmental similarity surface (MESS), to deal with extrapolation-linked uncertainties in model projections to past climate. Finally, the niche equivalency and niche similarity tests confirmed the link between SDMs outputs and actual differences in the ecological niches of the two species. The different responses of the two species to climatic factors have significantly contributed to shape their current distribution, through contractions, expansions and shifts over time, allowing to maintain two wide allopatric areas with an area of sympatry in Central Italy. Moreover, our SDMs hindcasting shows many concordances with previous phylogeographic studies carried out on the same species, thus corroborating the scenarios of potential distribution during the Last Glacial Maximum and the Holocene emerging from the models obtained.

Overview of the Special Issue: A Multi-Model Framework to ...

EPA Pesticide Factsheets

The Climate Change Impacts and Risk Analysis (CIRA) project establishes a new multi-model framework to systematically assess the impacts, economic damages, and risks from climate change in the United States. The primary goal of this framework to estimate how climate change impacts and damages in the United States are avoided or reduced due to global greenhouse gas (GHG) emissions mitigation scenarios. Scenarios are designed to explore key uncertainties around the measurement of these changes. The modeling exercise presented in this Special Issue includes two integrated assessment models and 15 sectoral models encompassing six broad impacts sectors - water resources, electric power, infrastructure, human health, ecosystems, and forests. Three consistent emissions scenarios are used to analyze the benefits of global GHG mitigation targets: a reference and two policy scenarios, with total radiative forcing in 2100 of 10.0W/m2, 4.5W/m2, and 3.7W/m2. A range of climate sensitivities, climate models, natural variability measures, and structural uncertainties of sectoral models are examined to explore the implications of key uncertainties. This overview paper describes the motivations, goals, design, and academic contribution of the CIRA modeling exercise and briefly summarizes the subsequent papers in this Special Issue. A summary of results across impact sectors is provided showing that: GHG mitigation provides benefits to the United States that increase over

Visualizing the uncertainty in the relationship between seasonal average climate and malaria risk.

PubMed

MacLeod, D A; Morse, A P

2014-12-02

Around $1.6 billion per year is spent financing anti-malaria initiatives, and though malaria morbidity is falling, the impact of annual epidemics remains significant. Whilst malaria risk may increase with climate change, projections are highly uncertain and to sidestep this intractable uncertainty, adaptation efforts should improve societal ability to anticipate and mitigate individual events. Anticipation of climate-related events is made possible by seasonal climate forecasting, from which warnings of anomalous seasonal average temperature and rainfall, months in advance are possible. Seasonal climate hindcasts have been used to drive climate-based models for malaria, showing significant skill for observed malaria incidence. However, the relationship between seasonal average climate and malaria risk remains unquantified. Here we explore this relationship, using a dynamic weather-driven malaria model. We also quantify key uncertainty in the malaria model, by introducing variability in one of the first order uncertainties in model formulation. Results are visualized as location-specific impact surfaces: easily integrated with ensemble seasonal climate forecasts, and intuitively communicating quantified uncertainty. Methods are demonstrated for two epidemic regions, and are not limited to malaria modeling; the visualization method could be applied to any climate impact.

Visualizing the uncertainty in the relationship between seasonal average climate and malaria risk

NASA Astrophysics Data System (ADS)

MacLeod, D. A.; Morse, A. P.

2014-12-01

Around $1.6 billion per year is spent financing anti-malaria initiatives, and though malaria morbidity is falling, the impact of annual epidemics remains significant. Whilst malaria risk may increase with climate change, projections are highly uncertain and to sidestep this intractable uncertainty, adaptation efforts should improve societal ability to anticipate and mitigate individual events. Anticipation of climate-related events is made possible by seasonal climate forecasting, from which warnings of anomalous seasonal average temperature and rainfall, months in advance are possible. Seasonal climate hindcasts have been used to drive climate-based models for malaria, showing significant skill for observed malaria incidence. However, the relationship between seasonal average climate and malaria risk remains unquantified. Here we explore this relationship, using a dynamic weather-driven malaria model. We also quantify key uncertainty in the malaria model, by introducing variability in one of the first order uncertainties in model formulation. Results are visualized as location-specific impact surfaces: easily integrated with ensemble seasonal climate forecasts, and intuitively communicating quantified uncertainty. Methods are demonstrated for two epidemic regions, and are not limited to malaria modeling; the visualization method could be applied to any climate impact.

Climate variability, food production shocks, and violent conflict in Sub-Saharan Africa

NASA Astrophysics Data System (ADS)

Buhaug, Halvard; Benjaminsen, Tor A.; Sjaastad, Espen; Magnus Theisen, Ole

2015-12-01

Earlier research that reports a correlational pattern between climate anomalies and violent conflict routinely refers to drought-induced agricultural shocks and adverse economic spillover effects as a key causal mechanism linking the two phenomena. Comparing half a century of statistics on climate variability, food production, and political violence across Sub-Saharan Africa, this study offers the most precise and theoretically consistent empirical assessment to date of the purported indirect relationship. The analysis reveals a robust link between weather patterns and food production where more rainfall generally is associated with higher yields. However, the second step in the causal model is not supported; agricultural output and violent conflict are only weakly and inconsistently connected, even in the specific contexts where production shocks are believed to have particularly devastating social consequences. Although this null result could, in theory, be fully compatible with recent reports of food price-related riots, it suggests that the wider socioeconomic and political context is much more important than drought and crop failures in explaining violent conflict in contemporary Africa.

Glacial-Interglacial Variability of Nd isotopes in the South Atlantic and Southern Ocean

NASA Astrophysics Data System (ADS)

Knudson, K. P.; Goldstein, S. L.; Pena, L.; Seguí, M. J.; Kim, J.; Yehudai, M.; Fahey, T.

2017-12-01

Understanding the relationship between meridional overturning circulation and climate is key to understanding the processes and feedbacks underlying future climate changes. North Atlantic Deep Water (NADW) represents a major water mass that participates in global oceanic circulation and undergoes substantial reorganization with climate changes on millennial and orbital timescales. Nd isotopes are semi-quantitative water mass tracers that reflect the mixing of end-member water masses, and their values in the Southern Ocean offer the ability to characterize NADW variability over time. Here, we present paleo-circulation records of Nd isotopes measured on fish debris and Fe-Mn encrusted foraminifera from ODP Sites 1090 (42° 54.82'S, 3702 m), and 1094 (53° 10.81'S, 2807 m). Site 1090 is located in the Cape Basin, SE Atlantic, near the lower boundary between NADW and Circumpolar Deep Water (CDW), while 1094 is in the Circumpolar Current. They are ideal locations to monitor changes in the export of NADW to the Southern Ocean. These new results build on previous work (Pena and Goldstein, 2014) to document meridional overturning changes in the Southern Ocean.

Interannual Variation in Phytoplankton Concentration and Community in the Pacific Ocean

NASA Technical Reports Server (NTRS)

Rousseaux, C. S.; Gregg, W. W.

2011-01-01

Climate events such as El Nino have been shown to have an effect on the biology of our ocean. Because of the lack of data, we still have very little knowledge about the spatial and temporal effect these climate events may have on biological marine systems. In this study, we used the NASA Ocean Biogeochemical Model (NOBM) to assess the interannual variability in phytoplankton community in the Pacific Ocean between 1998 and 2005. In the North Central and Equatorial Pacific Ocean, changes in the Multivariate El Nino Index were associated with changes in phytoplankton composition. The model identified an increase in diatoms of approx.33 % in the equatorial Pacific in 1999 during a La Nina event. This increase in diatoms coincided with a decrease of approx.11 % in cyanobacteria concentration. The inverse relationship between cyanobacteria and diatoms concentration was significant (p<0.05) throughout the period of study. The use of a numerical model allows us to assess the impact climate variability has on key phytoplankton groups known to lead to contrasting food chain at a spatial and temporal resolution unachievable when relying solely on in-situ observations.

Recent slowing of Atlantic overturning circulation as a recovery from earlier strengthening

NASA Astrophysics Data System (ADS)

Jackson, Laura C.; Peterson, K. Andrew; Roberts, Chris D.; Wood, Richard A.

2016-07-01

The Atlantic meridional overturning circulation (AMOC) has weakened substantially over the past decade. Some weakening may already have occurred over the past century, and global climate models project further weakening in response to anthropogenic climate change. Such a weakening could have significant impacts on the surface climate. However, ocean model simulations based on historical conditions have often found an increase in overturning up to the mid-1990s, followed by a decrease. It is therefore not clear whether the observed weakening over the past decade is part of decadal variability or a persistent weakening. Here we examine a state-of-the-art global-ocean reanalysis product, GloSea5, which covers the years 1989 to 2015 and closely matches observations of the AMOC at 26.5° N, capturing the interannual variability and decadal trend with unprecedented accuracy. The reanalysis data place the ten years of observations--April 2004 to February 2014--into a longer-term context and suggest that the observed decrease in the overturning circulation is consistent with a recovery following a previous increase. We find that density anomalies that propagate southwards from the Labrador Sea are the most likely cause of these variations. We conclude that decadal variability probably played a key role in the decline of the AMOC observed over the past decade.

Slow science: the value of long ocean biogeochemistry records

PubMed Central

Henson, Stephanie A.

2014-01-01

Sustained observations (SOs) have provided invaluable information on the ocean's biology and biogeochemistry for over 50 years. They continue to play a vital role in elucidating the functioning of the marine ecosystem, particularly in the light of ongoing climate change. Repeated, consistent observations have provided the opportunity to resolve temporal and/or spatial variability in ocean biogeochemistry, which has driven exploration of the factors controlling biological parameters and processes. Here, I highlight some of the key breakthroughs in biological oceanography that have been enabled by SOs, which include areas such as trophic dynamics, understanding variability, improved biogeochemical models and the role of ocean biology in the global carbon cycle. In the near future, SOs are poised to make progress on several fronts, including detecting climate change effects on ocean biogeochemistry, high-resolution observations of physical–biological interactions and greater observational capability in both the mesopelagic zone and harsh environments, such as the Arctic. We are now entering a new era for biological SOs, one in which our motivations have evolved from the need to acquire basic understanding of the ocean's state and variability, to a need to understand ocean biogeochemistry in the context of increasing pressure in the form of climate change, overfishing and eutrophication. PMID:25157192

Model tropical Atlantic biases underpin diminished Pacific decadal variability

NASA Astrophysics Data System (ADS)

McGregor, Shayne; Stuecker, Malte F.; Kajtar, Jules B.; England, Matthew H.; Collins, Mat

2018-06-01

Pacific trade winds have displayed unprecedented strengthening in recent decades1. This strengthening has been associated with east Pacific sea surface cooling2 and the early twenty-first-century slowdown in global surface warming2,3, amongst a host of other substantial impacts4-9. Although some climate models produce the timing of these recently observed trends10, they all fail to produce the trend magnitude2,11,12. This may in part be related to the apparent model underrepresentation of low-frequency Pacific Ocean variability and decadal wind trends2,11-13 or be due to a misrepresentation of a forced response1,14-16 or a combination of both. An increasingly prominent connection between the Pacific and Atlantic basins has been identified as a key driver of this strengthening of the Pacific trade winds12,17-20. Here we use targeted climate model experiments to show that combining the recent Atlantic warming trend with the typical climate model bias leads to a substantially underestimated response for the Pacific Ocean wind and surface temperature. The underestimation largely stems from a reduction and eastward shift of the atmospheric heating response to the tropical Atlantic warming trend. This result suggests that the recent Pacific trends and model decadal variability may be better captured by models with improved mean-state climatologies.

Termites promote resistance of decomposition to spatiotemporal variability in rainfall.

PubMed

Veldhuis, Michiel P; Laso, Francisco J; Olff, Han; Berg, Matty P

2017-02-01

The ecological impact of rapid environmental change will depend on the resistance of key ecosystems processes, which may be promoted by species that exert strong control over local environmental conditions. Recent theoretical work suggests that macrodetritivores increase the resistance of African savanna ecosystems to changing climatic conditions, but experimental evidence is lacking. We examined the effect of large fungus-growing termites and other non-fungus-growing macrodetritivores on decomposition rates empirically with strong spatiotemporal variability in rainfall and temperature. Non-fungus-growing larger macrodetritivores (earthworms, woodlice, millipedes) promoted decomposition rates relative to microbes and small soil fauna (+34%) but both groups reduced their activities with decreasing rainfall. However, fungus-growing termites increased decomposition rates strongest (+123%) under the most water-limited conditions, making overall decomposition rates mostly independent from rainfall. We conclude that fungus-growing termites are of special importance in decoupling decomposition rates from spatiotemporal variability in rainfall due to the buffered environment they create within their extended phenotype (mounds), that allows decomposition to continue when abiotic conditions outside are less favorable. This points at a wider class of possibly important ecological processes, where soil-plant-animal interactions decouple ecosystem processes from large-scale climatic gradients. This may strongly alter predictions from current climate change models. © 2016 by the Ecological Society of America.

Climate change: effects on animal disease systems and implications for surveillance and control.

PubMed

de La Rocque, S; Rioux, J A; Slingenbergh, J

2008-08-01

Climate driven and other changes in landscape structure and texture, plus more general factors, may create favourable ecological niches for emerging diseases. Abiotic factors impact on vectors, reservoirs and pathogen bionomics and their ability to establish in new ecosystems. Changes in climatic patterns and in seasonal conditions may affect disease behaviour in terms of spread pattern, diffusion range, amplification and persistence in novel habitats. Pathogen invasion may result in the emergence of novel disease complexes, presenting major challenges for the sustainability of future animal agriculture at the global level. In this paper, some of the ecological mechanisms underlying the impact of climatic change on disease transmission and disease spread are further described. Potential effects of different climatic variables on pathogens and host population dynamics and distribution are complex to assess, and different approaches are used to describe the underlying epidemiological processes and the availability of ecological niches for pathogens and vectors. The invasion process can disrupt the long-term co-evolution of species. Pathogens adhering to an r-type strategy (e.g. RNA viruses) may be more inclined to encroach on a novel niche resulting from climate change. However, even when linkage between disease dynamics and climate change are relatively strong, there are other factors changing disease behaviour, and these should be accounted for as well. Overall vulnerability of a given ecosystem is a key variable in this regard. The impact of climate-driven changes varies in different parts of the world and in the different agro-climatic zones. Perhaps priority should go to those geographical areas where the integrity of the ecosystem is most severely affected and the adaptability, in terms of robustness and sustainability of response, relatively low.

Sensitivity of bud burst in key tree species in the UK to recent climate variability and change

NASA Astrophysics Data System (ADS)

Abernethy, Rachel; Cook, Sally; Hemming, Deborah; McCarthy, Mark

2017-04-01

Analysing the relationship between the changing climate of the UK and the spatial and temporal distribution of spring bud burst plays an important role in understanding ecosystem functionality and predicting future phenological trends. The location and timing of bud burst of eleven species of trees alongside climatic factors such as, temperature, precipitation and hours of sunshine (photoperiod) were used to investigate: i. which species' bud burst timing experiences the greatest impact from a changing climate, ii. which climatic factor has the greatest influence on the timing of bud burst, and iii. whether the location of bud burst is influenced by climate variability. Winter heatwave duration was also analysed as part of an investigation into the relationship between temperature trends of a specific winter period and the following spring events. Geographic Information Systems (GIS) and statistical analysis tools were used to visualise spatial patterns and to analyse the phenological and climate data through regression and analysis of variance (ANOVA) tests. Where there were areas that showed a strong positive or negative relationship between phenology and climate, satellite imagery was used to calculate a Normalised Difference Vegetation Index (NDVI) and a Leaf Area Index (LAI) to further investigate the relationships found. It was expected that in the north of the UK, where bud burst tends to occur later in the year than in the south, that the bud bursts would begin to occur earlier due to increasing temperatures and increased hours of sunshine. However, initial results show that for some species, the bud burst timing tends to remain or become later in the year. Interesting results will be found when investigating the statistical significance between the changing location of the bud bursts and each climatic factor.

RECONSTRUCTING THE ORIGINS OF HIGH-ALPINE NICHES AND CUSHION LIFE FORM IN THE GENUS ANDROSACE S.L. (PRIMULACEAE)

PubMed Central

Boucher, Florian C.; Thuiller, Wilfried; Roquet, Cristina; Douzet, Rolland; Aubert, Serge; Alvarez, Nadir; Lavergne, Sébastien

2014-01-01

Relatively, few species have been able to colonize extremely cold alpine environments. We investigate the role played by the cushion life form in the evolution of climatic niches in the plant genus Androsace s.l., which spreads across the mountain ranges of the Northern Hemisphere. Using robust methods that account for phylogenetic uncertainty, intraspecific variability of climatic requirements and different life-history evolution scenarios, we show that climatic niches of Androsace s.l. exhibit low phylogenetic signal and that they evolved relatively recently and punctually. Models of niche evolution fitted onto phylogenies show that the cushion life form has been a key innovation providing the opportunity to occupy extremely cold environments, thus contributing to rapid climatic niche diversification in the genus Androsace s.l. We then propose a plausible scenario for the adaptation of plants to alpine habitats. PMID:22486702

Congo Basin rainfall climatology: can we believe the climate models?

PubMed

Washington, Richard; James, Rachel; Pearce, Helen; Pokam, Wilfried M; Moufouma-Okia, Wilfran

2013-01-01

The Congo Basin is one of three key convective regions on the planet which, during the transition seasons, dominates global tropical rainfall. There is little agreement as to the distribution and quantity of rainfall across the basin with datasets differing by an order of magnitude in some seasons. The location of maximum rainfall is in the far eastern sector of the basin in some datasets but the far western edge of the basin in others during March to May. There is no consistent pattern to this rainfall distribution in satellite or model datasets. Resolving these differences is difficult without ground-based data. Moisture flux nevertheless emerges as a useful variable with which to study these differences. Climate models with weak (strong) or even divergent moisture flux over the basin are dry (wet). The paper suggests an approach, via a targeted field campaign, for generating useful climate information with which to confront rainfall products and climate models.

The key role of dry days in changing regional climate and precipitation regimes

USGS Publications Warehouse

Polade, Suraj; Pierce, David W.; Cayan, Daniel R.; Gershunov, Alexander; Dettinger, Michael D.

2014-01-01

Future changes in the number of dry days per year can either reinforce or counteract projected increases in daily precipitation intensity as the climate warms. We analyze climate model projected changes in the number of dry days using 28 coupled global climate models from the Coupled Model Intercomparison Project, version 5 (CMIP5). We find that the Mediterranean Sea region, parts of Central and South America, and western Indonesia could experience up to 30 more dry days per year by the end of this century. We illustrate how changes in the number of dry days and the precipitation intensity on precipitating days combine to produce changes in annual precipitation, and show that over much of the subtropics the change in number of dry days dominates the annual changes in precipitation and accounts for a large part of the change in interannual precipitation variability.

The Dependencies of Ecosystem Pattern, Structure, and Dynamics on Climate, Climate Variability, and Climate Change

NASA Astrophysics Data System (ADS)

Flanagan, S.; Hurtt, G. C.; Fisk, J. P.; Rourke, O.

2012-12-01

A robust understanding of the sensitivity of the pattern, structure, and dynamics of ecosystems to climate, climate variability, and climate change is needed to predict ecosystem responses to current and projected climate change. We present results of a study designed to first quantify the sensitivity of ecosystems to climate through the use of climate and ecosystem data, and then use the results to test the sensitivity of the climate data in a state-of the art ecosystem model. A database of available ecosystem characteristics such as mean canopy height, above ground biomass, and basal area was constructed from sources like the National Biomass and Carbon Dataset (NBCD). The ecosystem characteristics were then paired by latitude and longitude with the corresponding climate characteristics temperature, precipitation, photosynthetically active radiation (PAR) and dew point that were retrieved from the North American Regional Reanalysis (NARR). The average yearly and seasonal means of the climate data, and their associated maximum and minimum values, over the 1979-2010 time frame provided by NARR were constructed and paired with the ecosystem data. The compiled results provide natural patterns of vegetation structure and distribution with regard to climate data. An advanced ecosystem model, the Ecosystem Demography model (ED), was then modified to allow yearly alterations to its mechanistic climate lookup table and used to predict the sensitivities of ecosystem pattern, structure, and dynamics to climate data. The combined ecosystem structure and climate data results were compared to ED's output to check the validity of the model. After verification, climate change scenarios such as those used in the last IPCC were run and future forest structure changes due to climate sensitivities were identified. The results of this study can be used to both quantify and test key relationships for next generation models. The sensitivity of ecosystem characteristics to climate data shown in the database construction and by the model reinforces the need for high-resolution datasets and stresses the importance of understanding and incorporating climate change scenarios into earth system models.

The Sahel Region of West Africa: Examples of Climate Analyses Motivated By Drought Management Needs

NASA Astrophysics Data System (ADS)

Ndiaye, O.; Ward, M. N.; Siebert, A. B.

2011-12-01

The Sahel is one of the most drought-prone regions in the world. This paper focuses on climate sources of drought, and some new analyses mostly driven by users needing climate information to help in drought management strategies. The Sahel region of West Africa is a transition zone between equatorial climate and vegetation to the south, and desert to the north. The climatology of the region is dominated by dry conditions for most of the year, with a single peak in rainfall during boreal summer. The seasonal rainfall total contains both interannual variability and substantial decadal to multidecadal variability (MDV). This brings climate analysis and drought management challenges across this range of timescales. The decline in rainfall from the wet decades of the 1950s and 60s to the dry decades of the 1970s and 80s has been well documented. In recent years, a moderate recovery has emerged, with seasonal totals in the period 1994-2010 significantly higher than the average rainfall 1970-1993. These MDV rainfall fluctuations have expression in large-scale sea-surface temperature fluctuations in all ocean basins, placing the changes in drought frequency within broader ocean-atmosphere climate fluctuation. We have evaluated the changing character of low seasonal rainfall total event frequencies in the Sahel region 1950-2010, highlighting the role of changes in the mean, variance and distribution shape of seasonal rainfall totals as the climate has shifted through the three observed phases. We also consider the extent to which updating climate normals in real-time can damp the bias in expected event frequency, an important issue for the feasibility of index insurance as a drought management tool in the presence of a changing climate. On the interannual timescale, a key factor long discussed for agriculture is the character of rainfall onset. An extended dry spell often occurs early in the rainy season before the crop is fully established, and this often leads to crop failure. This can be viewed as a special case of agricultural drought. Therefore, improving climate information around the time of planting can play a key role in agricultural risk management. Rainfall onset indices have been calculated for stations across Senegal. The problem is climatically challenging because the physical processes that impact rainfall onset appear to span aspects normally studied separately: weather system character, propagating intraseasonal features, and large-scale sea-surface temperature influence. We present aspects of all these, and ideas on how to combine them into seamless information to support agriculture.

Optimization of Water Resources and Agricultural Activities for Economic Benefit in Colorado

NASA Astrophysics Data System (ADS)

LIM, J.; Lall, U.

2017-12-01

The limited water resources available for irrigation are a key constraint for the important agricultural sector of Colorado's economy. As climate change and groundwater depletion reshape these resources, it is essential to understand the economic potential of water resources under different agricultural production practices. This study uses a linear programming optimization at the county spatial scale and annual temporal scales to study the optimal allocation of water withdrawal and crop choices. The model, AWASH, reflects streamflow constraints between different extraction points, six field crops, and a distinct irrigation decision for maize and wheat. The optimized decision variables, under different environmental, social, economic, and physical constraints, provide long-term solutions for ground and surface water distribution and for land use decisions so that the state can generate the maximum net revenue. Colorado, one of the largest agricultural producers, is tested as a case study and the sensitivity on water price and on climate variability is explored.

Long-term variability in the water budget and its controls in an oak-dominated temperate forest

Treesearch

Jing Xie; Ge Sun; Hou-Sen Chu; Junguo Liu; Steven G. McNulty; Asko Noormets; Ranjeet John; Zutao Ouyang; Tianshan Zha; Haitao Li; Wenbin Guan; Jiquan Chen

2014-01-01

Water availability is one of the key environmental factors that control ecosystem functions in temperate forests. Changing climate is likely to alter the ecohydrology and other ecosystem processes, which affect forest structures and functions. We constructed a multi-year water budget (2004–2010) and quantified environmental controls on an evapotranspiration (ET) in a...

Chapter 10 - Wildfire and fire severity effects on post-fire carbon and nitrogen cycling in forest soil (Project NC-EM-F-14-1)

Treesearch

Jessica R. Miesel; Randy Kolka; Phil Townsend

2018-01-01

Fire is a key ecological driver in determining vegetation composition, biomass, and ecosystem dynamics in coniferous forests of the Laurentian Mixed Forest in the Great Lakes region (Cleland and others 2004, Frelich 1995). Regional projections of future climate conditions indicate warmer temperatures, more variable precipitation patterns, and greater moisture stress (...

Land - Ocean Climate Linkages and the Human Evolution - New ICDP and IODP Drilling Initiatives in the East African Rift Valley and SW Indian Ocean

NASA Astrophysics Data System (ADS)

Zahn, R.; Feibel, C.; Co-Pis, Icdp/Iodp

2009-04-01

The past 5 Ma were marked by systematic shifts towards colder climates and concomitant reorganizations in ocean circulation and marine heat transports. Some of the changes involved plate-tectonic shifts such as the closure of the Panamanian Isthmus and restructuring of the Indonesian archipelago that affected inter-ocean communications and altered the world ocean circulation. These changes induced ocean-atmosphere feedbacks with consequences for climates globally and locally. Two new ICDP and IODP drilling initiatives target these developments from the perspectives of marine and terrestrial palaeoclimatology and the human evolution. The ICDP drilling initiative HSPDP ("Hominid Sites and Paleolakes Drilling Project"; ICDP ref. no. 10/07) targets lacustrine depocentres in Ethiopia (Hadar) and Kenya (West Turkana, Olorgesailie, Magadi) to retrieve sedimentary sequences close to the places and times where various species of hominins lived over currently available outcrop records. The records will provide a spatially resolved record of the East African environmental history in conjunction with climate variability at orbital (Milankovitch) and sub-orbital (ENSO decadal) time scales. HSPDP specifically aims at (1) compiling master chronologies for outcrops around each of the depocentres; (2) assessing which aspects of the paleoenvironmental records are a function of local origin (hydrology, hydrogeology) and which are linked with regional or larger-scale signals; (3) correlating broad-scale patterns of hominin phylogeny with the global beat of climate variability and (4) correlating regional shifts in the hominin fossil and archaeological record with more local patterns of paleoenvironmental change. Ultimately the aim is to test hypotheses that link physical and cultural adaptations in the course of the hominin evolution to local environmental change and variability. The IODP initiative SAFARI ("Southern African Climates, Agulhas Warm Water Transports and Retroflection, and Interocean Exchanges"; IODP ref. no. 702-full) aims at deciphering the late Neogene ocean history of the SW Indian Ocean. SAFARI specifically targets the Agulhas Current in the SW Indian Ocean that constitutes the strongest western boundary current in the southern hemisphere oceans. The Current transports warm and saline surface waters from the tropical Indian Ocean to the southern tip of Africa. Exchanges with the atmosphere influence eastern and southern African climates including individual weather systems such as extra-tropical cyclone formation in the region and rainfall patterns. Ocean models further suggest the "leakage" of Agulhas water around South Africa into the Atlantic potentially modulates the Atlantic meridional overturning circulation (MOC) with consequences for climate globally. The SAFARI drilling initiative aims to retrieve a suite of long drill cores along the southeast African margin and in the Indian-Atlantic ocean gateway. SAFARI will shed light on the history of Agulhas Current warm water transports along the southeast African margin during the late Neogene and its linking with ocean-climate developments. Specific objectives of SAFARI are to test (1) the sensitivity of the Agulhas Current to changing climates of the Plio/Pleistocene, including upstream forcing linked with equatorial Indian Ocean changes and Indonesian Throughflow; (2) the Current's influence on eastern and southern Africa climates, including rain fall patterns and vegetation changes; (3) buoyancy transfer to the Atlantic by Agulhas leakage around southern Africa, and (4) the contribution of variable Agulhas Leakage to shifts of the Atlantic MOC during episodes of major ocean and climate reorganizations of the past 5 Ma. These studies will provide insight into the Current's influence on eastern and southern African terrestrial climates, including its possible impact on the late Neogene evolution of large mammals including hominids. The ICDP and IODP drilling campaigns will enable us to establish the linkages between the ocean climatology of the SW Indian and terrestrial climates of Eastern Africa during key periods of global climate change. Combining the ICDP records of East African terrestrial climate at key hominin sites with IODP records of marine climate variability at the SE African continental margin will help to test if pulses of hominin evolutionary innovation were linked with periods of enhanced variability of local terrestrial environments and marine climatology of the Indian Ocean. * co-PIs of the ICDP initiative HSPDP are A.S. Cohen, R. Arrowsmith, A.K. Behrensmeyer, C. Feibel, R. Johnson, Z. Kubsa, D. Olago, R. Potts, R. Renaut * co-PIs of the IODP initiative SAFARI are R. Zahn, I. Hall, R. Schneider, M. Á. Bárcena, S. Barker, A. Biastoch, Chr. Charles, J. Compton, R. Cowling, P. Diz, L. Dupont, J.-A. Flores, S. Goldstein, S. Hemming, K. Holmgren, J. Lee-Thorp, G. Knorr, C. Lear, A. Mazaud, G. Mortyn, F. Peeters, B. Preu, R. Rickaby, J. Rogers, A. Rosell-Mele, Chr. Reason, V. Spiess, M. Trauth, G. Uenzelmann-Neben, S. Weldeab, P. Ziveri

Biophysical constraints to sustainable agricultural intensification in West African drylands: an example of the WASCAL Research Action Plan (WRAP 2.0) Flagship Strategy

NASA Astrophysics Data System (ADS)

Tondoh, E. J.; Forkuor, G.; Adegoke, J. O.

2017-12-01

The West African Science Service Centre on Climate Change and Adapted Land Use (WASCAL) is an intergovernmental research organization established in 2012 as result of multilateral collaborations between the Republic of Germany and Governments of 10 West African countries. Its new research program termed WASCAL Research Action Plan (WRAP 2.0) aims to deploy first-class, demand-driven, and impact-oriented research to achieve development outcomes and deliver key science-based climate and environmental services. It's therefore structured around key flagships, including "Sustainable Agriculture and Food Security" with a focus on enhancing the adaptive capacity of socio-ecological landscapes through increased agricultural productivity. However, as land degradation is one of the major obstacles to sustainable agricultural production and food security in sub Saharan African, it's imperative to mitigate this complex multifaceted process which is particularly acute in West African drylands. This case study aims to diagnose the main constraints to sustainable agricultural intensification at landscape scale and derive best bet soil management practices. The methodological approach is built around biophysical survey at sites of 100 km2 organized around 16 clusters each composed of 10 georeferenced sampling plots in three semi-arid agro-ecological landscapes located in upper-west region of Ghana (Lambussie), southwestern Burkina Faso (Bondigui) and southwestern Mali (Finkolo). Soil samples were collected in both the topsoil (0-20cm) and subsoil (20-50) and key soil physical constraints were measured at each sampling point. Remote Sensing (RS) variables representing biomass, climate and topography were correlated with soil organic carbon (SOC) to determine the influence of these variables on soil health. Results revealed within and between site variations in SOC concentration, soil pH, soil fertility index (SFI), erosion prevalence and root depth restriction. Different RS variables were found to be positively correlated with SOC levels in the three study sites. These findings emphasize the need to prioritize fine scale and trade-off approaches when setting up recommended land management practices to overcome land degradation and sustainably increase agricultural production.

On the persistence and coherence of subpolar sea surface temperature and salinity anomalies associated with the Atlantic multidecadal variability

NASA Astrophysics Data System (ADS)

Zhang, Rong

2017-08-01

This study identifies key features associated with the Atlantic multidecadal variability (AMV) in both observations and a fully coupled climate model, e.g., decadal persistence of monthly mean subpolar North Atlantic (NA) sea surface temperature (SST) and salinity (SSS) anomalies, and high coherence at low frequency among subpolar NA SST/SSS, upper ocean heat/salt content, and the Atlantic Meridional Overturning Circulation (AMOC) fingerprint. These key AMV features, which can be used to distinguish the AMV mechanism, cannot be explained by the slab ocean model results or the red noise process but are consistent with the ocean dynamics mechanism. This study also shows that at low frequency, the correlation and regression between net surface heat flux and SST anomalies are key indicators of the relative roles of oceanic versus atmospheric forcing in SST anomalies. The oceanic forcing plays a dominant role in the subpolar NA SST anomalies associated with the AMV.

Assessing Climate Change Risks Using a Multi-Model Approach

NASA Astrophysics Data System (ADS)

Knorr, W.; Scholze, M.; Prentice, C.

2007-12-01

We quantify the risks of climate-induced changes in key ecosystem processes during the 21st century by forcing a dynamic global vegetation model with multiple scenarios from the IPCC AR4 data archive using 16 climate models and mapping the proportions of model runs showing exceedance of natural variability in wildfire frequency and freshwater supply or shifts in vegetation cover. Our analysis does not assign probabilities to scenarios. Instead, we consider the distribution of outcomes within three sets of model runs grouped according to the amount of global warming they simulate: < 2 degree C (including committed climate change simulations), 2-3 degree C, and >3 degree C. Here, we are contrasting two different methods for calculating the risks: first we use an equal weighting approach giving every model within one of the three sets the same weight, and second, we weight the models according to their ability to model ENSO. The differences are underpinning the need for the development of more robust performance metrics for global climate models.

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

PubMed

Foreman, Brady Z; Straub, Kyle M

2017-09-01

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

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

PubMed Central

Foreman, Brady Z.; Straub, Kyle M.

2017-01-01

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

A plant’s perspective of extremes: Terrestrial plant responses to changing climatic variability

PubMed Central

Reyer, C.; Leuzinger, S.; Rammig, A.; Wolf, A.; Bartholomeus, R. P.; Bonfante, A.; de Lorenzi, F.; Dury, M.; Gloning, P.; Abou Jaoudé, R.; Klein, T.; Kuster, T. M.; Martins, M.; Niedrist, G.; Riccardi, M.; Wohlfahrt, G.; de Angelis, P.; de Dato, G.; François, L.; Menzel, A.; Pereira, M.

2013-01-01

We review observational, experimental and model results on how plants respond to extreme climatic conditions induced by changing climatic variability. Distinguishing between impacts of changing mean climatic conditions and changing climatic variability on terrestrial ecosystems is generally underrated in current studies. The goals of our review are thus (1) to identify plant processes that are vulnerable to changes in the variability of climatic variables rather than to changes in their mean, and (2) to depict/evaluate available study designs to quantify responses of plants to changing climatic variability. We find that phenology is largely affected by changing mean climate but also that impacts of climatic variability are much less studied but potentially damaging. We note that plant water relations seem to be very vulnerable to extremes driven by changes in temperature and precipitation and that heatwaves and flooding have stronger impacts on physiological processes than changing mean climate. Moreover, interacting phenological and physiological processes are likely to further complicate plant responses to changing climatic variability. Phenological and physiological processes and their interactions culminate in even more sophisticated responses to changing mean climate and climatic variability at the species and community level. Generally, observational studies are well suited to study plant responses to changing mean climate, but less suitable to gain a mechanistic understanding of plant responses to climatic variability. Experiments seem best suited to simulate extreme events. In models, temporal resolution and model structure are crucial to capture plant responses to changing climatic variability. We highlight that a combination of experimental, observational and /or modeling studies have the potential to overcome important caveats of the respective individual approaches. PMID:23504722

Organics in the atmosphere: From air pollution to biogeochemical cycles and climate (Vilhelm Bjerknes Medal)

NASA Astrophysics Data System (ADS)

Kanakidou, Maria

2016-04-01

Organics are key players in the biosphere-atmosphere-climate interactions. They have also a significant anthropogenic component due to primary emissions or interactions with pollution. The organic pool in the atmosphere is a complex mixture of compounds of variable reactivity and properties, variable content in C, H, O, N and other elements depending on their origin and their history in the atmosphere. Multiphase atmospheric chemistry is known to produce organic acids with high oxygen content, like oxalic acid. This water soluble organic bi-acid is used as indicator for cloud processing and can form complexes with atmospheric Iron, affecting Iron solubility. Organics are also carriers of other nutrients like nitrogen and phosphorus. They also interact with solar radiation and with atmospheric water impacting on climate. In line with this vision for the role of organics in the atmosphere, we present results from a global 3-dimensional chemistry-transport model on the role of gaseous and particulate organics in atmospheric chemistry, accounting for multiphase chemistry and aerosol ageing in the atmosphere as well as nutrients emissions, atmospheric transport and deposition. Historical simulations and projections highlight the human impact on air quality and atmospheric deposition to the oceans. The results are put in the context of climate change. Uncertainties and implications of our findings for biogeochemical and climate modeling are discussed.

Ecosystem resilience to abrupt late Quaternary change in continental southern Siberia

NASA Astrophysics Data System (ADS)

Harding, Poppy; Mackay, Anson; Bezrukova, Elena; Shchetnikov, Alexander

2017-04-01

Quaternary climate variability is dominated by long term orbital forcing along with abrupt sub-Milankovitch events on the scales of millennia to centuries, driven by internal feedback mechanisms, volcanic forcing and fluctuating solar activity. Although these are well documented in the North Atlantic region, their expression is poorly understood in Siberia, particularly in relation to abrupt climatic events. Siberia has the world's highest level of continentality offering an opportunity to study changes remote from oceanic influences and improving understanding of interactions between the Siberian High and other atmospheric systems including the Aleutian Low, Arctic oscillation and Icelandic Low1 and ENSO2. Understanding of palaeoenvironmental change in Siberia is essential due to the region's high sensitivity to climatic change, with warming rates considerably higher than the global average over the past 50 years3, triggering significant environmental changes, including permafrost degradation, shifts in the forest-steppe biome, increases in forest fires and warming of seasonally ice-covered lakes. Additionally, the region provides essential palaeoenvironmental context for early hominins, for example at globally important sites such as Denisova cave4, and megafauna extinctions5. This presentation outlines ongoing work at Lake Baunt, SE Siberia including: key quaternary climate forcings, the site and its regional context, the key methods and preliminary results. These include a dated record back to ˜30ka BP (based on multiple 14C dates and Bayesian age modelling), multiproxy indicators of palaeoproductivity (e.g. biogenic silica and diatom analyses) and lake mixing regimes (inferred from diatom analyses). Together these highlight several key Quaternary fluctuations potentially correlated to events recorded in Greenland Ice Cores (GS2, GS2.1, GI1, GS1), and these are considered against key Quaternary records including those from nearby Lake Baikal and Hulu Cave in east China. Our analyses suggest that teleconnections between the Siberian High and the East Asian monsoon are also significant for this study, with Lake Baunt showing a relationship between productivity and variability in strength of the Siberian High. References: 1. Tubi, A. & Dayan, U. (2013). Int. J. Climatol. 33, 1357-1366. 2. Park, T.-W. et al. (2014). Clim. Dyn. 45, 1207-1217. 3. Tingley, M. P. & Huybers, P. (2013). Nature 496, 201-5. 4. Krause, J. et al.. (2010). Nature 464, 894-7. 5. Stuart, A. J. et al. (2004). Nature 431, 684-9.

Ecologically-Relevant Maps of Landforms and Physiographic Diversity for Climate Adaptation Planning

PubMed Central

Theobald, David M.; Harrison-Atlas, Dylan; Monahan, William B.; Albano, Christine M.

2015-01-01

Key to understanding the implications of climate and land use change on biodiversity and natural resources is to incorporate the physiographic platform on which changes in ecological systems unfold. Here, we advance a detailed classification and high-resolution map of physiography, built by combining landforms and lithology (soil parent material) at multiple spatial scales. We used only relatively static abiotic variables (i.e., excluded climatic and biotic factors) to prevent confounding current ecological patterns and processes with enduring landscape features, and to make the physiographic classification more interpretable for climate adaptation planning. We generated novel spatial databases for 15 landform and 269 physiographic types across the conterminous United States of America. We examined their potential use by natural resource managers by placing them within a contemporary climate change adaptation framework, and found our physiographic databases could play key roles in four of seven general adaptation strategies. We also calculated correlations with common empirical measures of biodiversity to examine the degree to which the physiographic setting explains various aspects of current biodiversity patterns. Additionally, we evaluated the relationship between landform diversity and measures of climate change to explore how changes may unfold across a geophysical template. We found landform types are particularly sensitive to spatial scale, and so we recommend using high-resolution datasets when possible, as well as generating metrics using multiple neighborhood sizes to both minimize and characterize potential unknown biases. We illustrate how our work can inform current strategies for climate change adaptation. The analytical framework and classification of landforms and parent material are easily extendable to other geographies and may be used to promote climate change adaptation in other settings. PMID:26641818

The historical impact of climate extremes on global agricultural production and trade

NASA Astrophysics Data System (ADS)

Troy, T. J.; Pal, I.; Block, P. J.; Lall, U.

2011-12-01

How does climate variability at interannual time scales impact the volume and prices of key agricultural products on the global market? Do concurrent climate shocks in major breadbaskets of the world have serious impacts on global stocks and food prices? To what extent may irrigated agriculture or food storage buffer such impacts? Is there evidence of such impacts and/or buffering in the publicly available historical data? This talk explores these questions through empirical data analysis. During the past two years, we have seen drought in China, Europe, and Russia and floods in the United States and Australia. In this study, we examine the relationship between climate and crop yields, focusing on three main grain staples: wheat, rice, and maize. To do this, we use global production, trade, and stock data from the Food and Agricultural Organization and the United States Department of Agriculture for agriculture information and gridded observations of temperature and precipitation from 1960 through 2008. We focus on the impact of climate shocks (extreme temperatures, drought, and floods) on the agricultural production for the top exporting countries and quantify how these shocks propagate through the country's exports, imports, and grain stocks in order to understand the effect climate variability and extremes have on global food security. The ability to forecast these climate shocks at seasonal to longer lead times would significantly improve our ability to cope with perturbations in the global food supply, and we evaluate the ability of current models to produce skillful seasonal forecasts over the major grain producing regions.

Underestimated AMOC Variability and Implications for AMV and Predictability in CMIP Models

NASA Astrophysics Data System (ADS)

Yan, Xiaoqin; Zhang, Rong; Knutson, Thomas R.

2018-05-01

The Atlantic Meridional Overturning Circulation (AMOC) has profound impacts on various climate phenomena. Using both observations and simulations from the Coupled Model Intercomparison Project Phase 3 and 5, here we show that most models underestimate the amplitude of low-frequency AMOC variability. We further show that stronger low-frequency AMOC variability leads to stronger linkages between the AMOC and key variables associated with the Atlantic multidecadal variability (AMV), and between the subpolar AMV signal and northern hemisphere surface air temperature. Low-frequency extratropical northern hemisphere surface air temperature variability might increase with the amplitude of low-frequency AMOC variability. Atlantic decadal predictability is much higher in models with stronger low-frequency AMOC variability and much lower in models with weaker or without AMOC variability. Our results suggest that simulating realistic low-frequency AMOC variability is very important, both for simulating realistic linkages between AMOC and AMV-related variables and for achieving substantially higher Atlantic decadal predictability.

A probabilistic approach to quantifying spatial patterns of flow regimes and network-scale connectivity

NASA Astrophysics Data System (ADS)

Garbin, Silvia; Alessi Celegon, Elisa; Fanton, Pietro; Botter, Gianluca

2017-04-01

The temporal variability of river flow regime is a key feature structuring and controlling fluvial ecological communities and ecosystem processes. In particular, streamflow variability induced by climate/landscape heterogeneities or other anthropogenic factors significantly affects the connectivity between streams with notable implication for river fragmentation. Hydrologic connectivity is a fundamental property that guarantees species persistence and ecosystem integrity in riverine systems. In riverine landscapes, most ecological transitions are flow-dependent and the structure of flow regimes may affect ecological functions of endemic biota (i.e., fish spawning or grazing of invertebrate species). Therefore, minimum flow thresholds must be guaranteed to support specific ecosystem services, like fish migration, aquatic biodiversity and habitat suitability. In this contribution, we present a probabilistic approach aiming at a spatially-explicit, quantitative assessment of hydrologic connectivity at the network-scale as derived from river flow variability. Dynamics of daily streamflows are estimated based on catchment-scale climatic and morphological features, integrating a stochastic, physically based approach that accounts for the stochasticity of rainfall with a water balance model and a geomorphic recession flow model. The non-exceedance probability of ecologically meaningful flow thresholds is used to evaluate the fragmentation of individual stream reaches, and the ensuing network-scale connectivity metrics. A multi-dimensional Poisson Process for the stochastic generation of rainfall is used to evaluate the impact of climate signature on reach-scale and catchment-scale connectivity. The analysis shows that streamflow patterns and network-scale connectivity are influenced by the topology of the river network and the spatial variability of climatic properties (rainfall, evapotranspiration). The framework offers a robust basis for the prediction of the impact of land-use/land-cover changes and river regulation on network-scale connectivity.

Variability in understory evapotranspiration with overstory density in Siberian larch forests

NASA Astrophysics Data System (ADS)

Tobio, A.; Loranty, M. M.; Kropp, H.; Pena, H., III; Alexander, H. D.; Natali, S.; Kholodov, A. L.

2016-12-01

Arctic ecosystems are changing rapidly in response to amplified rates of climate change. Increased vegetation productivity, altered ecosystem carbon and hydrologic cycling, and increased wildfire severity are among the key responses to changing permafrost and climate conditions. Boreal larch forests in northeastern Siberia are a critical but understudied ecosystem affected by these modifications. Understory vegetation in these ecosystems, which typically have low canopy cover, may account for half of all water fluxes. Despite the potential importance of the understory for ecosystem water exchange, there has been relatively little research examining variability in understory evapotranspiration in boreal larch forests. In particular, the water balance of understory shrubs and mosses is largely undefined and could provide insight on how understory vegetation and our changing climate interact. This is especially important because both observed increases in vegetation productivity and wildfire severity could lead to increases in forests density, altering the proportional contributions of over- and understory vegetation to whole ecosystem evapotranspiration. In order to better understand variability in understory evapotranspiration we measured in larch forests with differing overstory density and permafrost conditions that likely vary as a consequence of fire severity. We used the static chamber technique to measure fluxes across a range of understory vegetation types and environmental conditions. In general, we found that the understory vegetation in low density stands transpires more than that in high density stands. This tends to be correlated with a larger amount of aboveground biomass in the low density stands, and an increase in solar radiation, due to less shading by overstory trees. These results will help us to better understand water balances, evapotranspiration variability, and productivity changes associated with climate on understory vegetation. Additionally, our results will help understand how fire regime shifts may alter understory contributions to ecosystem evapotranspiration in Siberian larch forests.

Efficacy of Radiative Transfer Model Across Space, Time and Hydro-climates

NASA Astrophysics Data System (ADS)

Mohanty, B.; Neelam, M.

2017-12-01

The efficiency of radiative transfer model for better soil moisture retrievals is not yet clearly understood over natural systems with great variability and heterogeneity with respect to soil, land cover, topography, precipitation etc. However, this knowledge is important to direct and strategize future research direction and field campaigns. In this work, we present global sensitivity analysis (GSA) technique to study the influence of heterogeneity and uncertainties on radiative transfer model (RTM) and to quantify climate-soil-vegetation interactions. A framework is proposed to understand soil moisture mechanisms underlying these interactions, and influence of these interactions on soil moisture retrieval accuracy. Soil moisture dynamics is observed to play a key role in variability of these interactions, i.e., it enhances both mean and variance of soil-vegetation coupling. The analysis is conducted for different support scales (Point Scale, 800 m, 1.6 km, 3.2 km, 6.4 km, 12.8 km, and 36 km), seasonality (time), hydro-climates, aggregation (scaling) methods and across Level I and Level II ecoregions of contiguous USA (CONUS). For undisturbed natural environments such as SGP'97 (Oklahoma, USA) and SMEX04 (Arizona, USA), the sensitivity of TB to land surface variables remain nearly uniform and are not influenced by extent, support scales or averaging method. On the contrary, for anthropogenically-manipulated environments such as SMEX02 (Iowa, USA) and SMAPVEX12 (Winnipeg, Canada), the sensitivity to variables are highly influenced by the distribution of land surface heterogeneity and upscaling methods. The climate-soil-vegetation interactions analyzed across all ecoregions are presented through a probability distribution function (PDF). The intensity of these interactions are categorized accordingly to yield "hotspots", where the RTM model fails to retrieve soil moisture. A ecoregion specific scaling function is proposed for these hotspots to rectify RTM for retrieving soil moisture.

Long-term forecasting of meteorological time series using Nonlinear Canonical Correlation Analysis (NLCCA)

NASA Astrophysics Data System (ADS)

Woldesellasse, H. T.; Marpu, P. R.; Ouarda, T.

2016-12-01

Wind is one of the crucial renewable energy sources which is expected to bring solutions to the challenges of clean energy and the global issue of climate change. A number of linear and nonlinear multivariate techniques has been used to predict the stochastic character of wind speed. A wind forecast with good accuracy has a positive impact on the reduction of electricity system cost and is essential for the effective grid management. Over the past years, few studies have been done on the assessment of teleconnections and its possible effects on the long-term wind speed variability in the UAE region. In this study Nonlinear Canonical Correlation Analysis (NLCCA) method is applied to study the relationship between global climate oscillation indices and meteorological variables, with a major emphasis on wind speed and wind direction, of Abu Dhabi, UAE. The wind dataset was obtained from six ground stations. The first mode of NLCCA is capable of capturing the nonlinear mode of the climate indices at different seasons, showing the symmetry between the warm states and the cool states. The strength of the nonlinear canonical correlation between the two sets of variables varies with the lead/lag time. The performance of the models is assessed by calculating error indices such as the root mean square error (RMSE) and Mean absolute error (MAE). The results indicated that NLCCA models provide more accurate information about the nonlinear intrinsic behaviour of the dataset of variables than linear CCA model in terms of the correlation and root mean square error. Key words: Nonlinear Canonical Correlation Analysis (NLCCA), Canonical Correlation Analysis, Neural Network, Climate Indices, wind speed, wind direction

The Portuguese Climate Portal

NASA Astrophysics Data System (ADS)

Gomes, Sandra; Deus, Ricardo; Nogueira, Miguel; Viterbo, Pedro; Miranda, Miguel; Antunes, Sílvia; Silva, Alvaro; Miranda, Pedro

2016-04-01

The Portuguese Local Warming Website (http://portaldoclima.pt) has been developed in order to support the society in Portugal in preparing for the adaptation to the ongoing and future effects of climate change. The climate portal provides systematic and easy access to authoritative scientific data ready to be used by a vast and diverse user community from different public and private sectors, key players and decision makers, but also to high school students, contributing to the increase in knowledge and awareness on climate change topics. A comprehensive set of regional climate variables and indicators are computed, explained and graphically presented. Variables and indicators were built in agreement with identified needs after consultation of the relevant social partners from different sectors, including agriculture, water resources, health, environment and energy and also in direct cooperation with the Portuguese National Strategy for Climate Change Adaptation (ENAAC) group. The visual interface allows the user to dynamically interact, explore, quickly analyze and compare, but also to download and import the data and graphics. The climate variables and indicators are computed from state-of-the-art regional climate model (RCM) simulations (e.g., CORDEX project), at high space-temporal detail, allowing to push the limits of the projections down to local administrative regions (NUTS3) and monthly or seasonal periods, promoting local adaptation strategies. The portal provides both historical data (observed and modelled for the 1971-2000 period) and future climate projections for different scenarios (modelled for the 2011-2100 period). A large effort was undertaken in order to quantify the impacts of the risk of extreme events, such as heavy rain and flooding, droughts, heat and cold waves, and fires. Furthermore the different climate scenarios and the ensemble of RCM models, with high temporal (daily) and spatial (~11km) detail, is taken advantage in order to quantify a plausible evolution of climate impacts and its uncertainties. Clear information on the data value and limitations is also provided. The portal is expected to become a reference tool for evaluation of impacts and vulnerabilities due to climate change, increased awareness and promotion of local adaptation and sustainable development in Portugal. The Portuguese Local Warming Website is part of the ADAPT programme, and is co-funded by the EEA financial mechanism and the Portuguese Carbon Fund.

Decadal-timescale changes of the Atlantic overturning circulation and climate in a coupled climate model with a hybrid-coordinate ocean component

NASA Astrophysics Data System (ADS)

Persechino, A.; Marsh, R.; Sinha, B.; Megann, A. P.; Blaker, A. T.; New, A. L.

2012-08-01

A wide range of statistical tools is used to investigate the decadal variability of the Atlantic Meridional Overturning Circulation (AMOC) and associated key variables in a climate model (CHIME, Coupled Hadley-Isopycnic Model Experiment), which features a novel ocean component. CHIME is as similar as possible to the 3rd Hadley Centre Coupled Model (HadCM3) with the important exception that its ocean component is based on a hybrid vertical coordinate. Power spectral analysis reveals enhanced AMOC variability for periods in the range 15-30 years. Strong AMOC conditions are associated with: (1) a Sea Surface Temperature (SST) anomaly pattern reminiscent of the Atlantic Multi-decadal Oscillation (AMO) response, but associated with variations in a northern tropical-subtropical gradient; (2) a Surface Air Temperature anomaly pattern closely linked to SST; (3) a positive North Atlantic Oscillation (NAO)-like pattern; (4) a northward shift of the Intertropical Convergence Zone. The primary mode of AMOC variability is associated with decadal changes in the Labrador Sea and the Greenland Iceland Norwegian (GIN) Seas, in both cases linked to the tropical activity about 15 years earlier. These decadal changes are controlled by the low-frequency NAO that may be associated with a rapid atmospheric teleconnection from the tropics to the extratropics. Poleward advection of salinity anomalies in the mixed layer also leads to AMOC changes that are linked to processes in the Labrador Sea. A secondary mode of AMOC variability is associated with interannual changes in the Labrador and GIN Seas, through the impact of the NAO on local surface density.

Comparative Synthesis of Current and Future Urban Stormwater Runoff Scenarios in Tampa Bay Basin under a Changing Climate

NASA Astrophysics Data System (ADS)

Khan, M.; Abdul-Aziz, O. I.

2016-12-01

Changes in climatic regimes and basin characteristics such as imperviousness, roughness and land use types would lead to potential changes in stormwater budget. In this study we quantified reference sensitivities of stormwater runoff to the potential climatic and land use/cover changes by developing a large-scale, mechanistic rainfall-runoff model for the Tampa Bay Basin of Florida using the US EPA Storm Water Management Model (SWMM 5.1). Key processes of urban hydrology, its dynamic interactions with groundwater and sea level, hydro-climatic variables and land use/cover characteristics were incorporated within the model. The model was calibrated and validated with historical streamflow data. We then computed the historical (1970-2000) and potential 2050s stormwater budgets for the Tampa Bay Basin. Climatic scenario projected by the global climate models (GCMs) and the regional climate models (RCMs), along with sea level and land use/cover projections, were utilized to anticipate the future stormwater budget. The comparative assessment of current and future stormwater scenario will aid a proactive management of stormwater runoff under a changing climate in the Tampa Bay Basin and similar urban basins around the world.

The Soft Underbelly of System Change: The Role of Leadership and Organizational Climate in Turnover during Statewide Behavioral Health Reform.

PubMed

Aarons, Gregory A; Sommerfeld, David H; Willging, Cathleen E

2011-01-01

This study examined leadership, organizational climate, staff turnover intentions, and voluntary turnover during a large-scale statewide behavioral health system reform. The initial data collection occurred nine months after initiation of the reform with a follow-up round of data collected 18 months later. A self-administered structured assessment was completed by 190 participants (administrators, support staff, providers) employed by 14 agencies. Key variables included leadership, organizational climate, turnover intentions, turnover, and reform-related financial stress ("low" versus "high") experienced by the agencies. Analyses revealed that positive leadership was related to a stronger empowering climate in both high and low stress agencies. However, the association between more positive leadership and lower demoralizing climate was evident only in high stress agencies. For both types of agencies empowering climate was negatively associated with turnover intentions, and demoralizing climate was associated with stronger turnover intentions. Turnover intentions were positively associated with voluntary turnover. Results suggest that strong leadership is particularly important in times of system and organizational change and may reduce poor climate associated with turnover intentions and turnover. Leadership and organizational context should be addressed to retain staff during these periods of systemic change.

Hospital safety climate surveys: measurement issues.

PubMed

Jackson, Jeanette; Sarac, Cakil; Flin, Rhona

2010-12-01

Organizational safety culture relates to behavioural norms in the workplace and is usually assessed by safety climate surveys. These can be a diagnostic indicator on the state of safety in a hospital. This review examines recent studies using staff surveys of hospital safety climate, focussing on measurement issues. Four questionnaires (hospital survey on patient safety culture, safety attitudes questionnaire, patient safety climate in healthcare organizations, hospital safety climate scale), with acceptable psychometric properties, are now applied across countries and clinical settings. Comparisons for benchmarking must be made with caution in case of questionnaire modifications. Increasing attention is being paid to the unit and hospital level wherein distinct cultures may be located, as well as to associated measurement and study design issues. Predictive validity of safety climate is tested against safety behaviours/outcomes, with some relationships reported, although effects may be specific to professional groups/units. Few studies test the role of intervening variables that could influence the effect of climate on outcomes. Hospital climate studies are becoming a key component of healthcare safety management systems. Large datasets have established more reliable instruments that allow a more focussed investigation of the role of culture in the improvement and maintenance of staff's safety perceptions within units, as well as within hospitals.

Efficient design based on perturbed parameter ensembles to identify plausible and diverse variants of a model for climate change projections

NASA Astrophysics Data System (ADS)

Karmalkar, A.; Sexton, D.; Murphy, J.

2017-12-01

We present exploratory work towards developing an efficient strategy to select variants of a state-of-the-art but expensive climate model suitable for climate projection studies. The strategy combines information from a set of idealized perturbed parameter ensemble (PPE) and CMIP5 multi-model ensemble (MME) experiments, and uses two criteria as basis to select model variants for a PPE suitable for future projections: a) acceptable model performance at two different timescales, and b) maintaining diversity in model response to climate change. We demonstrate that there is a strong relationship between model errors at weather and climate timescales for a variety of key variables. This relationship is used to filter out parts of parameter space that do not give credible simulations of historical climate, while minimizing the impact on ranges in forcings and feedbacks that drive model responses to climate change. We use statistical emulation to explore the parameter space thoroughly, and demonstrate that about 90% can be filtered out without affecting diversity in global-scale climate change responses. This leads to identification of plausible parts of parameter space from which model variants can be selected for projection studies.

Water-the Nation's Fundamental Climate Issue A White Paper on the U.S. Geological Survey Role and Capabilities

USGS Publications Warehouse

Lins, Harry F.; Hirsch, Robert M.; Kiang, Julie

2010-01-01

Of all the potential threats posed by climatic variability and change, those associated with water resources are arguably the most consequential for both society and the environment (Waggoner, 1990). Climatic effects on agriculture, aquatic ecosystems, energy, and industry are strongly influenced by climatic effects on water. Thus, understanding changes in the distribution, quantity and quality of, and demand for water in response to climate variability and change is essential to planning for and adapting to future climatic conditions. A central role of the U.S. Geological Survey (USGS) with respect to climate is to document environmental changes currently underway and to develop improved capabilities to predict future changes. Indeed, a centerpiece of the USGS role is a new Climate Effects Network of monitoring sites. Measuring the climatic effects on water is an essential component of such a network (along with corresponding effects on terrestrial ecosystems). The USGS needs to be unambiguous in communicating with its customers and stakeholders, and with officials at the Department of the Interior, that although modeling future impacts of climate change is important, there is no more critical role for the USGS in climate change science than that of measuring and describing the changes that are currently underway. One of the best statements of that mission comes from a short paper by Ralph Keeling (2008) that describes the inspiration and the challenges faced by David Keeling in operating the all-important Mauna Loa Observatory over a period of more than four decades. Ralph Keeling stated: 'The only way to figure out what is happening to our planet is to measure it, and this means tracking changes decade after decade and poring over the records.' There are three key ideas that are important to the USGS in the above-mentioned sentence. First, to understand what is happening requires measurement. While models are a tool for learning and testing our understanding, they are not a substitute for observations. The second key idea is that measurement needs to be done over a period of many decades. When viewing hydrologic records over time scales of a few years to a few decades, trends commonly appear. However, when viewed in the context of many decades to centuries, these short-term trends are recognized as being part of much longer term oscillations. Thus, while we might want to initiate monitoring of important aspects of our natural resources, the data that will prove to be most useful in the next few years are those records that already have long-term continuity. USGS streamflow and groundwater level data are excellent examples of such long-term records. These measured data span many decades, follow standard protocols for collection and quality assurance, and are stored in a database that provides access to the full period of record. The third point from the Keeling quote relates to the notion of ?poring over the records.? Important trends will not generally jump off the computer screen at us. Thoughtful analyses are required to get past a number of important but confounding influences in the record, such as the role of seasonal variation, changes in water management, or influences of quasi-periodic phenomena, such as El Ni?o-Southern Oscillation (ENSO) or the Pacific Decadal Oscillation (PDO). No organization is better situated to pore over the records than the USGS because USGS scientists know the data, quality-assure the data, understand the factors that influence the data, and have the ancillary information on the watersheds within which the data are collected. To fulfill the USGS role in understanding climatic variability and change, we need to continually improve and strengthen two of our key capabilities: (1) preserving continuity of long-term water data collection and (2) analyzing and interpreting water data to determine how the Nation's water resources are changing. Understanding change in water resources

Understanding north-western Mediterranean climate variability: a multi-proxy and multi-sequence approach based on wavelet analysis.

NASA Astrophysics Data System (ADS)

Azuara, Julien; Lebreton, Vincent; Jalali, Bassem; Sicre, Marie-Alexandrine; Sabatier, Pierre; Dezileau, Laurent; Peyron, Odile; Frigola, Jaime; Combourieu-Nebout, Nathalie

2017-04-01

Forcings and physical mechanisms underlying Holocene climate variability still remain poorly understood. Comparison of different paleoclimatic reconstructions using spectral analysis allows to investigate their common periodicities and helps to understand the causes of past climate changes. Wavelet analysis applied on several proxy time series from the Atlantic domain already revealed the first key-issues on the origin of Holocene climate variability. However the differences in duration, resolution and variance between the time-series are important issues for comparing paleoclimatic sequences in the frequency domain. This work compiles 7 paleoclimatic proxy records from 4 time-series from the north-western Mediterranean all ranging from 7000 to 1000 yrs cal BP: -pollen and clay mineral contents from the lagoonal sediment core PB06 recovered in southern France, -Sea Surface Temperatures (SST) derived from alkenones, concentration of terrestrial alkanes and their average chain length (ACL) from core KSGC-31_GolHo-1B recovered in the Gulf of Lion inner-shelf, - δ18O record from speleothems recovered in the Asiul Cave in north-western Spain, -grain size record from the deep basin sediment drift core MD99-2343 north of Minorca island. A comparison of their frequency content is proposed using wavelet analysis and cluster analysis of wavelet power spectra. Common cyclicities are assessed using cross-wavelet analysis. In addition, a new algorithm is used in order to propagate the age model errors within wavelet power spectra. Results are consistents with a non-stationnary Holocene climate variability. The Halstatt cycles (2000-2500 years) depicted in many proxies (ACL, errestrial alkanes and SSTs) demonstrate solar activity influence in the north-western Mediterranean climate. Cluster analysis shows that pollen and ACL proxies, both indicating changes in aridity, are clearly distinct from other proxies and share significant common periodicities around 1000 and 600 years, since the mid-Holocene. The 1000 years period is also evidenced in terrestrial alkanes and Minorca sediment drift grain size, which respectively indicate changes in the Rhône hydrology and changes in the north-western Mediterranean deep water formation. These findings suggests that an original climate driver influences the Gulf of Lion area. Finally, both clay mineral content from PB06, indicative of past storminess and δ18O record from the north western Iberia, related to precipitations, record the well known 1500 years period since the middle Holocene. The presence of this period, widely encountered in the Atlantic, highlights the link between the north-western Mediterranean and the Atlantic climate variability.

Understanding climate impacts on vegetation using a spatiotemporal non-linear Granger causality framework

NASA Astrophysics Data System (ADS)

Papagiannopoulou, Christina; Decubber, Stijn; Miralles, Diego; Demuzere, Matthias; Dorigo, Wouter; Verhoest, Niko; Waegeman, Willem

2017-04-01

Satellite data provide an abundance of information about crucial climatic and environmental variables. These data - consisting of global records, spanning up to 35 years and having the form of multivariate time series with different spatial and temporal resolutions - enable the study of key climate-vegetation interactions. Although methods which are based on correlations and linear models are typically used for this purpose, their assumptions for linearity about the climate-vegetation relationships are too simplistic. Therefore, we adopt a recently proposed non-linear Granger causality analysis [1], in which we incorporate spatial information, concatenating data from neighboring pixels and training a joint model on the combined data. Experimental results based on global data sets show that considering non-linear relationships leads to a higher explained variance of past vegetation dynamics, compared to simple linear models. Our approach consists of several steps. First, we compile an extensive database [1], which includes multiple data sets for land surface temperature, near-surface air temperature, surface radiation, precipitation, snow water equivalents and surface soil moisture. Based on this database, high-level features are constructed and considered as predictors in our machine-learning framework. These high-level features include (de-trended) seasonal anomalies, lagged variables, past cumulative variables, and extreme indices, all calculated based on the raw climatic data. Second, we apply a spatiotemporal non-linear Granger causality framework - in which the linear predictive model is substituted for a non-linear machine learning algorithm - in order to assess which of these predictor variables Granger-cause vegetation dynamics at each 1° pixel. We use the de-trended anomalies of Normalized Difference Vegetation Index (NDVI) to characterize vegetation, being the target variable of our framework. Experimental results indicate that climate strongly (Granger-)causes vegetation dynamics in most regions globally. More specifically, water availability is the most dominant vegetation driver, being the dominant vegetation driver in 54% of the vegetated surface. Furthermore, our results show that precipitation and soil moisture have prolonged impacts on vegetation in semiarid regions, with up to 10% of additional explained variance on the vegetation dynamics occurring three months later. Finally, hydro-climatic extremes seem to have a remarkable impact on vegetation, since they also explain up to 10% of additional variance of vegetation in certain regions despite their infrequent occurrence. References [1] Papagiannopoulou, C., Miralles, D. G., Verhoest, N. E. C., Dorigo, W. A., and Waegeman, W.: A non-linear Granger causality framework to investigate climate-vegetation dynamics, Geosci. Model Dev. Discuss., doi:10.5194/gmd-2016-266, in review, 2016.

Uncertainty in the response of terrestrial carbon sink to environmental drivers undermines carbon-climate feedback predictions

DOE PAGES

Huntzinger, D. N.; Michalak, A. M.; Schwalm, C.; ...

2017-07-06

Terrestrial ecosystems play a vital role in regulating the accumulation of carbon (C) in the atmosphere. Understanding the factors controlling land C uptake is critical for reducing uncertainties in projections of future climate. The relative importance of changing climate, rising atmospheric CO 2, and other factors, however, remains unclear despite decades of research. Here, we use an ensemble of land models to show that models disagree on the primary driver of cumulative C uptake for 85% of vegetated land area. Disagreement is largest in model sensitivity to rising atmospheric CO 2 which shows almost twice the variability in cumulative landmore » uptake since 1901 (1 s.d. of 212.8 PgC vs. 138.5 PgC, respectively). We find that variability in CO 2 and temperature sensitivity is attributable, in part, to their compensatory effects on C uptake, whereby comparable estimates of C uptake can arise by invoking different sensitivities to key environmental conditions. Conversely, divergent estimates of C uptake can occur despite being based on the same environmental sensitivities. Together, these findings imply an important limitation to the predictability of C cycling and climate under unprecedented environmental conditions. We suggest that the carbon modeling community prioritize a probabilistic multi-model approach to generate more robust C cycle projections.« less

Uncertainty in the response of terrestrial carbon sink to environmental drivers undermines carbon-climate feedback predictions

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

Huntzinger, D. N.; Michalak, A. M.; Schwalm, C.

2017-07-06

Terrestrial ecosystems play a vital role in regulating the accumulation of carbon (C) in the atmosphere. Understanding the factors controlling land C uptake is critical for reducing uncertainties in projections of future climate. The relative importance of changing climate, rising atmospheric CO2, and other factors, however, remains unclear despite decades of research. Here, we use an ensemble of land models to show that models disagree on the primary driver of cumulative C uptake for 85% of vegetated land area. Disagreement is largest in model sensitivity to rising atmospheric CO2 which shows almost twice the variability in cumulative land uptake sincemore » 1901 (1 s.d. of 212.8 PgC vs. 138.5 PgC, respectively). We find that variability in CO2 and temperature sensitivity is attributable, in part, to their compensatory effects on C uptake, whereby comparable estimates of C uptake can arise by invoking different sensitivities to key environmental conditions. Conversely, divergent estimates of C uptake can occur despite being based on the same environmental sensitivities. Together, these findings imply an important limitation to the predictability of C cycling and climate under unprecedented environmental conditions. We suggest that the carbon modeling community prioritize a probabilistic multi-model approach to generate more robust C cycle projections.« less

Uncertainty in the response of terrestrial carbon sink to environmental drivers undermines carbon-climate feedback predictions

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

Huntzinger, D. N.; Michalak, A. M.; Schwalm, C.

Terrestrial ecosystems play a vital role in regulating the accumulation of carbon (C) in the atmosphere. Understanding the factors controlling land C uptake is critical for reducing uncertainties in projections of future climate. The relative importance of changing climate, rising atmospheric CO 2, and other factors, however, remains unclear despite decades of research. Here, we use an ensemble of land models to show that models disagree on the primary driver of cumulative C uptake for 85% of vegetated land area. Disagreement is largest in model sensitivity to rising atmospheric CO 2 which shows almost twice the variability in cumulative landmore » uptake since 1901 (1 s.d. of 212.8 PgC vs. 138.5 PgC, respectively). We find that variability in CO 2 and temperature sensitivity is attributable, in part, to their compensatory effects on C uptake, whereby comparable estimates of C uptake can arise by invoking different sensitivities to key environmental conditions. Conversely, divergent estimates of C uptake can occur despite being based on the same environmental sensitivities. Together, these findings imply an important limitation to the predictability of C cycling and climate under unprecedented environmental conditions. We suggest that the carbon modeling community prioritize a probabilistic multi-model approach to generate more robust C cycle projections.« less

Quantifying the role of ocean initial conditions in decadal prediction

NASA Astrophysics Data System (ADS)

Matei, D.; Pohlmann, H.; Müller, W.; Haak, H.; Jungclaus, J.; Marotzke, J.

2009-04-01

The forecast skill of decadal climate predictions is investigated using two different initialization strategies. First we apply an assimilation of ocean synthesis data provided by the GECCO project (Köhl and Stammer 2008) as initial conditions for the coupled model ECHAM5/MPI-OM. The results show promising skill up to decadal time scales particularly over the North Atlantic (see also Pohlmann et al. 2009). However, mismatches between the ocean climates of GECCO and the MPI-OM model may lead to inconsistencies in the representation of water masses. Therefore, we pursue an alternative approach to the representation of the observed North Atlantic climate for the period 1948-2007. Using the same MPI-OM ocean model as in the coupled system, we perform an ensemble of four NCEP integrations. The ensemble mean temperature and salinity anomalies are then nudged into the coupled model, followed by hindcast/forecast experiments. The model gives dynamically consistent three-dimensional temperature and salinity fields, thereby avoiding the problems of model drift that were encountered when the assimilation experiment was only driven by reconstructed SSTs (Keenlyside et al. 2008, Pohlmann et al. 2009). Differences between the two assimilation approaches are discussed by comparing them with the observational data in key regions and processes, such as North Atlantic and Tropical Pacific climate, MOC variability, Subpolar Gyre variability.

Extreme rainfall, vulnerability and risk: a continental-scale assessment for South America

USGS Publications Warehouse

Vorosmarty, Charles J.; de Guenni, Lelys Bravo; Wollheim, Wilfred M.; Pellerin, Brian A.; Bjerklie, David M.; Cardoso, Manoel; D'Almeida, Cassiano; Colon, Lilybeth

2013-01-01

Extreme weather continues to preoccupy society as a formidable public safety concern bearing huge economic costs. While attention has focused on global climate change and how it could intensify key elements of the water cycle such as precipitation and river discharge, it is the conjunction of geophysical and socioeconomic forces that shapes human sensitivity and risks to weather extremes. We demonstrate here the use of high-resolution geophysical and population datasets together with documentary reports of rainfall-induced damage across South America over a multi-decadal, retrospective time domain (1960–2000). We define and map extreme precipitation hazard, exposure, affectedpopulations, vulnerability and risk, and use these variables to analyse the impact of floods as a water security issue. Geospatial experiments uncover major sources of risk from natural climate variability and population growth, with change in climate extremes bearing a minor role. While rural populations display greatest relative sensitivity to extreme rainfall, urban settings show the highest rates of increasing risk. In the coming decades, rapid urbanization will make South American cities the focal point of future climate threats but also an opportunity for reducing vulnerability, protecting lives and sustaining economic development through both traditional and ecosystem-based disaster risk management systems.

Evaluating the response of Lake Prespa (SW Balkan) to future climate change projections from a high-resolution model

NASA Astrophysics Data System (ADS)

van der Schriek, Tim; Varotsos, Konstantinos V.; Giannakopoulos, Christos

2017-04-01

The Mediterranean stands out globally due to its sensitivity to (future) climate change. Projections suggest that the Balkans will experience precipitation and runoff decreases of up to 30% by 2100. However, these projections show large regional spatial variability. Mediterranean lake-wetland systems are particularly threatened by projected climate changes that compound increasingly intensive human impacts (e.g. water extraction, drainage, pollution and dam-building). Protecting the remaining systems is extremely important for supporting global biodiversity. This protection should be based on a clear understanding of individual lake-wetland hydrological responses to future climate changes, which requires fine-resolution projections and a good understanding of the impact of hydro-climate variability on individual lakes. Climate change may directly affect lake level (variability), volume and water temperatures. In turn, these variables influence lake-ecology, habitats and water quality. Land-use intensification and water abstraction multiply these climate-driven changes. To date, there are no projections of future water level and -temperature of individual Mediterranean lakes under future climate scenarios. These are, however, of crucial importance to steer preservation strategies on the relevant catchment-scale. Here we present the first projections of water level and -temperature of the Prespa Lakes covering the period 2071-2100. These lakes are of global significance for biodiversity, and of great regional socio-economic importance as a water resource and tourist attraction. Impact projections are assessed by the Regional Climate Model RCA4 of the Swedish Meteorological and Hydrological Institute (SMHI) driven by the Max Planck Institute for Meteorology global climate model MPI-ESM-LR under two RCP future emissions scenarios, the RCP4.5 and the RCP8.5, with the simulations carried out in the framework of EURO-CORDEX. Temperature, evapo(transpi)ration and precipitation over the Prespa catchment were simulated with this high horizontal resolution (12 × 12 km) regional climate model. Lake temperatures were derived from surface temperatures based on physical models, while water levels were calculated with the lake water balance model. Climate simulations indicate that annual- and wet season catchment precipitation does not significantly change by the end of the century. The median precipitation decreases, while precipitation variability increases. The percentage of annual precipitation falling in the wet season increases by 5-10%, indicating a stronger seasonality in the precipitation regime. Summer (lake) temperatures and lake surface evaporation will rise significantly under both explored climate change scenarios. Lake impact projections indicate that evaporation changes will cause the water level of Lake Megali Prespa to fall by 5m to 840-839m. The increased precipitation variability will cause large inter-annual water level fluctuations. Average water level may fall even further if: (1) drier summers lead to more water abstraction for irrigation, and (2) there is a reduction in winter snowfall/accumulation and thus less discharge. These findings are of key importance for developing sustainable lake water resource management in a region that is highly vulnerable to future climate change and already experiences significant water stress. Research paves the way for innovative management adaptation strategies focussed on decreasing water abstraction, for example through introducing smart irrigation and selecting more water efficient crops.

Assessing the Impact of Climatic Variability and Change on Maize Production in the Midwestern USA

NASA Astrophysics Data System (ADS)

Andresen, J.; Jain, A. K.; Niyogi, D. S.; Alagarswamy, G.; Biehl, L.; Delamater, P.; Doering, O.; Elias, A.; Elmore, R.; Gramig, B.; Hart, C.; Kellner, O.; Liu, X.; Mohankumar, E.; Prokopy, L. S.; Song, C.; Todey, D.; Widhalm, M.

2013-12-01

Weather and climate remain among the most important uncontrollable factors in agricultural production systems. In this study, three process-based crop simulation models were used to identify the impacts of climate on the production of maize in the Midwestern U.S.A. during the past century. The 12-state region is a key global production area, responsible for more than 80% of U.S. domestic and 25% of total global production. The study is a part of the Useful to Useable (U2U) Project, a USDA NIFA-sponsored project seeking to improve the resilience and profitability of farming operations in the region amid climate variability and change. Three process-based crop simulation models were used in the study: CERES-Maize (DSSAT, Hoogenboom et al., 2012), the Hybrid-Maize model (Yang et al., 2004), and the Integrated Science Assessment Model (ISAM, Song et al., 2013). Model validation was carried out with individual plot and county observations. The models were run with 4 to 50 km spatial resolution gridded weather data for representative soils and cultivars, 1981-2012, to examine spatial and temporal yield variability within the region. We also examined the influence of different crop models and spatial scales on regional scale yield estimation, as well as a yield gap analysis between observed and attainable yields. An additional study was carried out with the CERES-Maize model at 18 individual site locations 1901-2012 to examine longer term historical trends. For all simulations, all input variables were held constant in order to isolate the impacts of climate. In general, the model estimates were in good agreement with observed yields, especially in central sections of the region. Regionally, low precipitation and soil moisture stress were chief limitations to simulated crop yields. The study suggests that at least part of the observed yield increases in the region during recent decades have occurred as the result of wetter, less stressful growing season weather conditions.

Connecting differential responses of native and invasive riparian plants to climate change and environmental alteration.

PubMed

Flanagan, Neal E; Richardson, Curtis J; Ho, Mengchi

2015-04-01

Climate change is predicted to impact river systems in the southeastern United States through alterations of temperature, patterns of precipitation and hydrology. Future climate scenarios for the southeastern United States predict (1) surface water temperatures will warm in concert with air temperature, (2) storm flows will increase and base flows will decrease, and (3) the annual pattern of synchronization between hydroperiod and water temperature will be altered. These alterations are expected to disturb floodplain plant communities, making them more vulnerable to establishment of invasive species. The primary objective of this study is to evaluate whether native and invasive riparian plant assemblages respond differently to alterations of climate and land use. To study the response of riparian wetlands to watershed and climate alterations, we utilized an existing natural experiment imbedded in gradients of temperature and hydrology-found among dammed and undammed rivers. We evaluated a suite of environmental variables related to water temperature, hydrology, watershed disturbance, and edaphic conditions to identify the strongest predictors of native and invasive species abundances. We found that native species abundance is strongly influenced by climate-driven variables such as temperature and hydrology, while invasive species abundance is more strongly influenced by site-specific factors such as land use and soil nutrient availability. The patterns of synchronization between plant phenology, annual hydrographs, and annual water temperature cycles may be key factors sustaining the viability of native riparian plant communities. Our results demonstrate the need to understand the interactions between climate, land use, and nutrient management in maintaining the species diversity of riparian plant communities. Future climate change is likely to result in diminished competitiveness of native plant species, while the competitiveness of invasive species will increase due to anthropogenic watershed disturbance and accelerated nutrient and sediment export.

The Nevada NSF EPSCoR infrastructure for climate change science, education, and outreach project: highlights and progress on investigations of ecological change and water resources along elevational gradients

NASA Astrophysics Data System (ADS)

Saito, L.; Biondi, F.; Fenstermaker, L. F.; Arnone, J.; Devitt, D.; Riddle, B.; Young, M.

2010-12-01

In 2008, the Nevada System of Higher Education received a 5-year, $15 million grant from the National Science Foundation’s (NSF) Experimental Program to Stimulate Competitive Research (EPSCoR). The mission of the project is to create a statewide interdisciplinary program to stimulate transformative research, education, and outreach about the effects of regional climate change on ecosystem services (especially water resources), and support use of this knowledge by policy makers and stakeholders. The overarching question that this effort will address is: how will climate change affect water resources, disturbance regimes and linked ecosystem and human services? While the overall project includes cyberinfrastructure, policy, education and climate modeling, this presentation will focus on the ecological change and water resources components. The goals of these two components are: 1) improving understanding of processes controlling local- and basin-wide impacts of climate on species dynamics, disturbance regimes, and water recharge rates; 2) evaluating interactions between landscape-level processes and biophysical indicators; 3) evaluating interactions between surface and groundwater systems; 4) predicting changes in wildfire regime, primary productivity, and biodiversity (including invasive species); and 5) assessing how interactions between water and ecology will differ under climate change and/or climate variability scenarios. To achieve these goals, the two components will quantify present-day climate variability at multiple temporal and spatial scales, including at multiple elevations within Nevada’s Basin and Range ecosystem continuum. This presentation will discuss key elements for achieving these goals, including the establishment of instrumented transects spanning a range of elevations and vegetation zones in eastern and southern Nevada.

Agriculture and Climate Change in Global Scenarios: Why Don't the Models Agree

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

Nelson, Gerald; van der Mensbrugghe, Dominique; Ahammad, Helal

Agriculture is unique among economic sectors in the nature of impacts from climate change. The production activity that transforms inputs into agricultural outputs makes direct use of weather inputs. Previous studies of the impacts of climate change on agriculture have reported substantial differences in outcomes of key variables such as prices, production, and trade. These divergent outcomes arise from differences in model inputs and model specification. The goal of this paper is to review climate change results and underlying determinants from a model comparison exercise with 10 of the leading global economic models that include significant representation of agriculture. Bymore » providing common productivity drivers that include climate change effects, differences in model outcomes are reduced. All models show higher prices in 2050 because of negative productivity shocks from climate change. The magnitude of the price increases, and the adaptation responses, differ significantly across the various models. Substantial differences exist in the structural parameters affecting demand, area, and yield, and should be a topic for future research.« less

Climate Change, Agricultural Innovation and Exchange across Asia

NASA Astrophysics Data System (ADS)

DAlpoim Guedes, J. A.; Bocinsky, R. K.

2017-12-01

Ancient farmers experienced climate change at the local level: through variations in the yields of their staple crops. However, archaeologists have had difficulty in determining where, when and how changes in climate impacted ancient farmers. We model how several key transitions in climate impacted the productivity of five rain-fed crops across Eurasia. Cooling events between 3750 and 3000 cal. BP lead humans in parts of the Tibetan Plateau and in Central Asia to diversify their crops. A second event at 2000 cal. BP lead farmers in Central China to also diversify their cropping systems and to develop man-made systems that allowed transport of grains from Southern to Northern China. In other areas where crop returns fared even worse, humans reduced their risk by increasing investment in nomadic pastoralism and developing long distance networks of trade that coalesced into the Silk Road. By translating changes in climatic variables into factors that mattered to ancient farmers, we situate the adaptive strategies they developed to deal with variance in crop returns in the context of environmental and climatic changes.

Collaborative Project: Development of an Isotope-Enabled CESM for Testing Abrupt Climate Changes

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

Liu, Zhengyu

One of the most important validations for a state-of-art Earth System Model (ESM) with respect to climate changes is the simulation of the climate evolution and abrupt climate change events in the Earth’s history of the last 21,000 years. However, one great challenge for model validation is that ESMs usually do not directly simulate geochemical variables that can be compared directly with past proxy records. In this proposal, we have met this challenge by developing the simulation capability of major isotopes in a state-of-art ESM, the Community Earth System Model (CESM), enabling us to make direct model-data comparison by comparingmore » the model directly against proxy climate records. Our isotope-enabled ESM incorporates the capability of simulating key isotopes and geotracers, notably δ 18O, δD, δ 14C, and δ 13C, Nd and Pa/Th. The isotope-enabled ESM have been used to perform some simulations for the last 21000 years. The direct comparison of these simulations with proxy records has shed light on the mechanisms of important climate change events.« less

Holocene constraints on simulated tropical Pacific climate

NASA Astrophysics Data System (ADS)

Emile-Geay, J.; Cobb, K. M.; Carre, M.; Braconnot, P.; Leloup, J.; Zhou, Y.; Harrison, S. P.; Correge, T.; Mcgregor, H. V.; Collins, M.; Driscoll, R.; Elliot, M.; Schneider, B.; Tudhope, A. W.

2015-12-01

The El Niño-Southern Oscillation (ENSO) influences climate and weather worldwide, so uncertainties in its response to external forcings contribute to the spread in global climate projections. Theoretical and modeling studies have argued that such forcings may affect ENSO either via the seasonal cycle, the mean state, or extratropical influences, but these mechanisms are poorly constrained by the short instrumental record. Here we synthesize a pan-Pacific network of high-resolution marine biocarbonates spanning discrete snapshots of the Holocene (past 10, 000 years of Earth's history), which we use to constrain a set of global climate model (GCM) simulations via a forward model and a consistent treatment of uncertainty. Observations suggest important reductions in ENSO variability throughout the interval, most consistently during 3-5 kyBP, when approximately 2/3 reductions are inferred. The magnitude and timing of these ENSO variance reductions bear little resemblance to those sim- ulated by GCMs, or to equatorial insolation. The central Pacific witnessed a mid-Holocene increase in seasonality, at odds with the reductions simulated by GCMs. Finally, while GCM aggregate behavior shows a clear inverse relationship between seasonal amplitude and ENSO-band variance in sea-surface temperature, in agreement with many previous studies, such a relationship is not borne out by these observations. Our synthesis suggests that tropical Pacific climate is highly variable, but exhibited millennia-long periods of reduced ENSO variability whose origins, whether forced or unforced, contradict existing explanations. It also points to deficiencies in the ability of current GCMs to simulate forced changes in the tropical Pacific seasonal cycle and its interaction with ENSO, highlighting a key area of growth for future modeling efforts.

Reconstructing Deep Ocean Circulation in the North Atlantic from Bermuda Rise, and Beyond

NASA Astrophysics Data System (ADS)

McManus, J. F.

2016-12-01

The large-scale subsurface circulation of the ocean is an important component of the Earth's climate system, and contributes to the global and regional transport of heat and mass. Assessing how this system has changed in the past is thus a priority for understanding natural climate variability. A long-coring campaign on Bermuda Rise has provided additional abundant high-quality sediments from this site of rapid accumulation in the deep western basin, situated beneath the subtropical gyre of the North Atlantic Ocean. These sediments allow the high-resolution reconstruction of deepwater chemistry and export from this key location throughout the last 150,000 years, covering the entire last glacial cycle in a continuous section of 35 meters in core KNR191-CDH19. The suite of proxy indicators analyzed includes uranium-series disequilibria, neodymium isotopes, and benthic stable isotopes. Combined with multiple previous studies of nearby cores on Bermuda Rise, the published and new proxy data from CDH19 confirm the variability of the deep circulation in the Atlantic Ocean in association with past climate changes. The multiple indicators, along with complementary data from other locations, display coherent evidence for contrasts between deep circulation during glacial and interglacial intervals, with persistent strong, deep ventilation only within the peak interglacial of marine isotope stage 5e (MIS 5e) and the Holocene. In contrast, repeated, dramatic variability in deep ocean circulation accompanied the millennial climate changes of the last glaciation and deglaciation. The largest magnitude circulation shifts occurred at the transitions into stadials associated with the Hudson strait iceberg discharges and between them and the ensuing northern interstadial warmings, significantly exceeding that of the overall glacial-interglacial difference, highlighting the potential oceanographic and climatic importance of short-term perturbations to the deep ocean circulation.

Key landscape ecology metrics for assessing climate change adaptation options: Rate of change and patchiness of impacts

USGS Publications Warehouse

López-Hoffman, Laura; Breshears, David D.; Allen, Craig D.; Miller, Marc L.

2013-01-01

Under a changing climate, devising strategies to help stakeholders adapt to alterations to ecosystems and their services is of utmost importance. In western North America, diminished snowpack and river flows are causing relatively gradual, homogeneous (system-wide) changes in ecosystems and services. In addition, increased climate variability is also accelerating the incidence of abrupt and patchy disturbances such as fires, floods and droughts. This paper posits that two key variables often considered in landscape ecology—the rate of change and the degree of patchiness of change—can aid in developing climate change adaptation strategies. We use two examples from the “borderland” region of the southwestern United States and northwestern Mexico. In piñon-juniper woodland die-offs that occurred in the southwestern United States during the 2000s, ecosystem services suddenly crashed in some parts of the system while remaining unaffected in other locations. The precise timing and location of die-offs was uncertain. On the other hand, slower, homogeneous change, such as the expected declines in water supply to the Colorado River delta, will likely impact the entire ecosystem, with ecosystem services everywhere in the delta subject to alteration, and all users likely exposed. The rapidity and spatial heterogeneity of faster, patchy climate change exemplified by tree die-off suggests that decision-makers and local stakeholders would be wise to operate under a Rawlsian “veil of ignorance,” and implement adaptation strategies that allow ecosystem service users to equitably share the risk of sudden loss of ecosystem services before actual ecosystem changes occur. On the other hand, in the case of slower, homogeneous, system-wide impacts to ecosystem services as exemplified by the Colorado River delta, adaptation strategies can be implemented after the changes begin, but will require a fundamental rethinking of how ecosystems and services are used and valued. In sum, understanding how the rate of change and degree of patchiness of change will constrain adaptive options is a critical consideration in preparing for climate change.

Hydroclimatic Change in the Congo River Basin: Past, Present and Future169

NASA Astrophysics Data System (ADS)

Aloysius, N. R.

2016-12-01

Tropical regions provide habitat for the world's most diverse fauna and flora, sequester more atmospheric carbon and provide livelihood for millions of people. The hydrological cycle provides vital linkages for maintaining these ecosystem functions, yet, the understanding of its spatiotemporal variability is limited. Research on the hydrological cycle of the Congo River Basin (CRB), which encompasses the second largest rainforests, has been largely ignored. Global Climate Models (GCM) show limited skills in simulating CRB's climate and their future projections vary widely. Yet, GCMs provide the most plausible scenarios of future climate, based upon which changes in hydrologic fluxes can be predicted with the aid hydrological models. In order to address the gaps in knowledge and to highlight the research needs, we i) developed a spatially explicit hydrological model suitable for describing key hydrological processes, ii) evaluated the performance of GCMs in simulating precipitation and temperature in the region, iii) developed a set of climate change scenarios for the CRB and iv) developed a simplified modeling framework to quantify water management options for rain-fed agriculture with the objective of achieving the triple goals of sustainable development: food security, poverty alleviation and ecosystem conservation. The hydrology model, which was validated with observed stream flows at 50 locations, satisfactorily characterizes spatiotemporal variability of key fluxes. Our evaluation of 25 GCM outputs reveal that many GCMs poorly simulate regional precipitation. We implemented a statistical bias-correction method to develop precipitation and temperature projections for two future greenhouse gas emission scenarios. These climate forcings were, then, used to drive the hydrology model. Our results show that the near-term projections are not affected by emission scenarios. However, towards the mid-21st century, projections are emission scenario dependent. Available freshwater resources are projected to increase in the CRB, except in the semiarid southeast. Our findings have wider implications for climate change assessment and water resource management, because the region, with high population growth and limited capacity to adapt, are primary targets of land and water grabs. 155

Using global Climate Impact Indicators to assess water resource availability in a Mediterranean mountain catchment: the Sierra Nevada study case (Spain) in the SWICCA platform

NASA Astrophysics Data System (ADS)

José Pérez-Palazón, María; Pimentel, Rafael; Sáenz de Rodrigáñez, Marta; Gulliver, Zacarias; José Polo, María

2017-04-01

Climate services provide water resource managements and users with science-based information on the likely impacts associated to the future climate scenarios. Mountainous areas are especially vulnerable to climate variations due to the expected changes in the snow regime, among others; in Mediterranean regions, this shift involves significant effects on the river flow regime and water resource availability and management. The Guadalfeo River Basin is a 1345 km2 mountainous, coastal catchment in southern Spain, ranging from the Mediterranean Sea coastline to the Sierra Nevada mountains to the north (up to 3450 m a.s.l.) within a 40-km distance. The climate variability adds complexity to this abrupt topography and heterogeneous area. The uncertainty associated to snow occurrence and persistence for the next decades poses a challenge for the current and future water resource uses in the area. The development of easy-to-use local climate indicators and derived decision-making variables is key to assess and face the economic impact of the potential changes. The SWICCA (Service for Water Indicators in Climate Change Adaptation) Platform (http://swicca.climate.copernicus.eu/) has been developed under the Copernicus Climate Change Service (C3S) and provides global climate and hydrology indicators on a Pan-European scale. Different case studies are included to assess the platform development and contents, and analyse the indicators' performance from a proof-of-concept approach that includes end-users feedbacks. The Guadalfeo River Basin is one of these case studies. This work presents the work developed so far to analyse and use the SWICCA Climate Impact Indicators (CIIs) related to river flow in this mountainous area, and the first set of local indicators specifically designed to assess selected end-users on the potential impact associated to different climate scenarios. Different CIIs were extracted from the SWICCA interface and tested against the local information available in the case study. The Essential Climate Variables used were precipitation and flow daily values, obtained at different spatial scales. The analysis led to the use of SWICCA-river flow on a catchment scale as the most suitable global CIIs in this area. Further treatment included local downscaling by means of transfer functions and a final relative anomaly correction. Three final end-users (clients) were identified within the water resource management framework: 1) mini hydropower facilities at the head areas, 2) urban supply at the southern area, and 3) water management decision makers (reservoir operation). From the corrected CIIs, local indicators were defined from the interaction with each client, to tailor water services easily and readily usable. Knowledge brokering from this interaction resulted in a first identification of a set of 4, 3 and 4 indicators for hydropower generation, urban users and water resource decision-makers, respectively, with different time scales. The projections of three future climate scenarios were assessed for each indicator and presented to each client. Local indicators are an efficient tool to assess the potential range of water allocation possibilities in this area on an annual and decadal basis, and get a deeper insight of the seasonal future potential regime of water resource availability. The results are good examples of key information for decision making in the future, and show how to derive local indicators with impact in the short and medium term planning in heterogeneous catchments in this region.

Scaling and contextualizing climate-conflict nexus in historical agrarian China

NASA Astrophysics Data System (ADS)

Lee, Harry F.

2017-04-01

This study examines climate-conflict nexus in historical agrarian China in multi-scalar and contextualized approach, illustrating what and how socio-political factors could significantly mediate the climate-violent link in pre-industrial society. Previous empirical large-N studies show that violent conflict in historical agrarian society was triggered by climate-induced food scarcity. The relationship was valid in China, Europe, and various geographic regions in the Northern Hemisphere in pre-industrial era. Nevertheless, the observed relationship has only been verified at a macro level (long-term variability of the nexus is emphasized and data over large area are aggregated), and somewhat generalized in nature (only physical environmental factors are controlled). Three inter-related issues remain unresolved: First, the key explanatory variable of violent conflicts may change substantially at different spatio-temporal scales. It is necessary to check whether the climate-conflict nexus is valid at a micro level (about short-term variability of the nexus and data in finer spatial resolution), and explore how the nexus changes along various spatio-temporal dimensions. Second, as the climate-conflict nexus has only been demonstrated in a broad sense, it is necessary to check whether and how the nexus is mediated by local socio-political context. More non-climatic factors pertinent to the cause and distribution of conflicts (e.g., governance, adaptive mechanisms, etc.) should be considered. Third, the methodology applied in the previous studies assumes spatially-independent observations and linear relationship, which may simplify the climate-conflict link. Moreover, the solitary reliance on quantitative methods may neglect those non-quantifiable socio-political dynamics which mediates the climate-conflict nexus. I plan to address the above issues by using disaggregated spatial analysis and in-depth case studies, with close attention to local and temporal differences and non-linear nature of the climate-conflict link. China will be chosen as study area. Study period will be delimited to AD1-1911. This study represents pioneering research which systematically examines the climate-conflict nexus in pre-industrial society over extended period in multi-scalar and contextualized perspective. By comparing and evaluating the climate-conflict link along various spatio-temporal dimensions and in different socio-political context, it may help to deepen the theoretical understanding of, and also resolve the current debate over, the climate-conflict relationship. Given the large potential changes in climatic regimes projected in coming decades, the findings in this study may have important implications for the social impact of climate change in tropical countries that are in some ways similar to pre-industrial society.

Interannual Variability of Human Plague Occurrence in the Western United States Explained by Tropical and North Pacific Ocean Climate Variability

PubMed Central

Ari, Tamara Ben; Gershunov, Alexander; Tristan, Rouyer; Cazelles, Bernard; Gage, Kenneth; Stenseth, Nils C.

2010-01-01

Plague is a vector-borne, highly virulent zoonotic disease caused by the bacterium Yersinia pestis. It persists in nature through transmission between its hosts (wild rodents) and vectors (fleas). During epizootics, the disease expands and spills over to other host species such as humans living in or close to affected areas. Here, we investigate the effect of large-scale climate variability on the dynamics of human plague in the western United States using a 56-year time series of plague reports (1950–2005). We found that El Niño Southern Oscillation and Pacific Decadal Oscillation in combination affect the dynamics of human plague over the western United States. The underlying mechanism could involve changes in precipitation and temperatures that impact both hosts and vectors. It is suggested that snow also may play a key role, possibly through its effects on summer soil moisture, which is known to be instrumental for flea survival and development and sustained growth of vegetation for rodents. PMID:20810830

Mapping the potential distribution of the invasive Red Shiner, Cyprinella lutrensis (Teleostei: Cyprinidae) across waterways of the conterminous United States

USGS Publications Warehouse

Poulos, Helen M.; Chernoff, Barry; Fuller, Pam L.; Butman, David

2012-01-01

Predicting the future spread of non-native aquatic species continues to be a high priority for natural resource managers striving to maintain biodiversity and ecosystem function. Modeling the potential distributions of alien aquatic species through spatially explicit mapping is an increasingly important tool for risk assessment and prediction. Habitat modeling also facilitates the identification of key environmental variables influencing species distributions. We modeled the potential distribution of an aggressive invasive minnow, the red shiner (Cyprinella lutrensis), in waterways of the conterminous United States using maximum entropy (Maxent). We used inventory records from the USGS Nonindigenous Aquatic Species Database, native records for C. lutrensis from museum collections, and a geographic information system of 20 raster climatic and environmental variables to produce a map of potential red shiner habitat. Summer climatic variables were the most important environmental predictors of C. lutrensis distribution, which was consistent with the high temperature tolerance of this species. Results from this study provide insights into the locations and environmental conditions in the US that are susceptible to red shiner invasion.

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.

Plio-Pleistocene Sea Surface Temperature Variability As Measured by Different Proxies - A Cautionary Tale

NASA Astrophysics Data System (ADS)

Lawrence, K. T.; Woodard, S. C.; Castañeda, I. S.; deMenocal, P. B.; Peterson, L.; Rosenthal, Y.; Bochner, L.; Gorbey, D. B.; Mauriello, H.

2016-12-01

Conflicting interpretations from the application of different sea surface temperature (SST) proxies seeking to characterize past climate conditions of the same region have given rise to a number of controversies about key elements of Pliocene climate. Thus, a detailed look at whether or not different temperature proxies yield consistent results is warranted. Here, we examine Pliocene climate variability at the orbital scale reporting new alkenone-derived SST estimates from ODP Site 1088 (South Atlantic) and ODP Site 846 (Eastern Equatorial Pacific). Using these novel datasets and previously published records from a variety of different sites in a variety of localities, we further examine the consistency of Plio-Pleistocene SST variability and orbital signatures from faunal, Mg/Ca, and TEX86 SST records relative to Uk'37 SST records. We find that many companion SST records produce very similar mean trends and standard deviations as well as absolute temperature estimates that are generally within error of each other. Our analysis also suggests that many companion records, with a few notable exceptions, capture the same dominant Milankovitch periodicities and produce phase estimates relative to benthic oxygen isotope estimates that are within error of each other. However, marked structural differences occur between different proxy records on glacial-interglacial timescales in Uk'37 versus Mg/Ca comparisons and some Uk'37 versus TEX86 comparisons. Therefore, the temperature estimates of individual glacial-interglacial cycles may vary significantly when a specific time slice is explored. Our preliminary investigation suggests that whether or not climate records derived from different paleothermometers yield consistent results depends on the timescale being explored and the study site, which reflects key factors such as seasonality, ecology, and diagenetic regime. Additional work that explores the underlying causes of the differences observed among proxies and uses a more systematic approach to directly compare the results from different paleothermometers is required. Until we have a better and broader sense of where/when proxies perform consistently, we recommend caution in treating SST records from different proxies as interchangeable.

Paleoenvironmental change in central Chile as inferred from OSL dating of ancient coastal sand dunes

NASA Astrophysics Data System (ADS)

Andrade, Belisario; Garcia, Juan L.; Lüthgens, Christopher; Fiebig, Markus

2013-04-01

To present day, the climatic and geographic expression of glacials and interglacials in the semiarid coast of central Chile remains unclear. The lack of well dated paleoclimatic records has up to now precluded firm conclusions whether maximum glacials evident in the Andes mountain range probably coincide with wetter (e.g., pluvials) or drier conditions at the coast. The natural region locally known as "Norte Chico" represents a transitional semiarid area between the extreme Atacama Desert to the North and the wetter, Mediterranean-like type of climate, to the South. In this semiarid region of Chile several generations of eolian sand dunes, some of them separated by paleosoils, have been preserved. In addition to the occurrence of paleosoils, thick debris flow deposits in some places overly ancient dune bodies, likely indicating significant environmental changes during the formation of these archives. However, the exact timing of these processes within the mid to late Pleistocene and Holocene is still unclear. A key aspect is that some of the ancient dunes are recently hanging above rocky coastlines, where no supply of sand exists today, likely implying their formation during a lower than present, probably glacio-eustatically induced sea level. The location of the research area in a key mid-latitude region of the eastern Pacific in combination with the preserved landform record offers a chance to reconstruct climatic shifts during the Quaternary by studying the variability of morphogenetic conditions throughout time, in order to promote knowledge about possible forcing factors driving climatic variability. Within this pilot study, samples for optically stimulated luminescence (OSL) dating were taken from three different stratigraphic sections that denote a complex environmental variability as indicated by paleosoils and debris flow units intercalated in ancient sand dunes. First dating results inferred from OSL measurements using a post-IR IRSL (pIRIR) protocol for the dating of feldspar will be presented at the conference. Within this project we aim to establish a geochronological framework for the described sedimentary archives in order to unravel their local and regional paleoenvironmental context.

The impact of climate change on the distribution of two threatened Dipterocarp trees.

PubMed

Deb, Jiban C; Phinn, Stuart; Butt, Nathalie; McAlpine, Clive A

2017-04-01

Two ecologically and economically important, and threatened Dipterocarp trees Sal ( Shorea robusta ) and Garjan ( Dipterocarpus turbinatus ) form mono-specific canopies in dry deciduous, moist deciduous, evergreen, and semievergreen forests across South Asia and continental parts of Southeast Asia. They provide valuable timber and play an important role in the economy of many Asian countries. However, both Dipterocarp trees are threatened by continuing forest clearing, habitat alteration, and global climate change. While climatic regimes in the Asian tropics are changing, research on climate change-driven shifts in the distribution of tropical Asian trees is limited. We applied a bioclimatic modeling approach to these two Dipterocarp trees Sal and Garjan. We used presence-only records for the tree species, five bioclimatic variables, and selected two climatic scenarios (RCP4.5: an optimistic scenario and RCP8.5: a pessimistic scenario) and three global climate models (GCMs) to encompass the full range of variation in the models. We modeled climate space suitability for both species, projected to 2070, using a climate envelope modeling tool "MaxEnt" (the maximum entropy algorithm). Annual precipitation was the key bioclimatic variable in all GCMs for explaining the current and future distributions of Sal and Garjan (Sal: 49.97 ± 1.33; Garjan: 37.63 ± 1.19). Our models predict that suitable climate space for Sal will decline by 24% and 34% (the mean of the three GCMs) by 2070 under RCP4.5 and RCP8.5, respectively. In contrast, the consequences of imminent climate change appear less severe for Garjan, with a decline of 17% and 27% under RCP4.5 and RCP8.5, respectively. The findings of this study can be used to set conservation guidelines for Sal and Garjan by identifying vulnerable habitats in the region. In addition, the natural habitats of Sal and Garjan can be categorized as low to high risk under changing climates where artificial regeneration should be undertaken for forest restoration.

Generating High Resolution Climate Scenarios Through Regional Climate Modelling Over Southern Africa

NASA Astrophysics Data System (ADS)

Ndhlovu, G. Z.; Woyessa, Y. E.; Vijayaraghavan, S.

2017-12-01

limate change has impacted the global environment and the Continent of Africa, especially Southern Africa, regarded as one of the most vulnerable regions in Africa, has not been spared from these impacts. Global Climate Models (GCMs) with coarse horizontal resolutions of 150-300 km do not provide sufficient details at the local basin scale due to mismatch between the size of river basins and the grid cell of the GCM. This makes it difficult to apply the outputs of GCMs directly to impact studies such as hydrological modelling. This necessitates the use of regional climate modelling at high resolutions that provide detailed information at regional and local scales to study both climate change and its impacts. To this end, an experiment was set up and conducted with PRECIS, a regional climate model, to generate climate scenarios at a high resolution of 25km for the local region in Zambezi River basin of Southern Africa. The major input data used included lateral and surface boundary conditions based on the GCMs. The data is processed, analysed and compared with CORDEX climate change project data generated for Africa. This paper, highlights the major differences of the climate scenarios generated by PRECIS Model and CORDEX Project for Africa and further gives recommendations for further research on generation of climate scenarios. The climatic variables such as precipitation and temperatures have been analysed for flood and droughts in the region. The paper also describes the setting up and running of an experiment using a high-resolution PRECIS model. In addition, a description has been made in running the model and generating the output variables on a sub basin scale. Regional climate modelling which provides information on climate change impact may lead to enhanced understanding of adaptive water resources management. Understanding the regional climate modelling results on sub basin scale is the first step in analysing complex hydrological processes and a basis for designing of adaptation and mitigation strategies in the region. Key words: Climate change, regional climate modelling, hydrological processes, extremes, scenarios [1] Corresponding author: Email:gndhlovu@cut.ac.za Tel:+27 (0) 51 507 3072

Increasing efficiency of CO2 uptake by combined land-ocean sink

NASA Astrophysics Data System (ADS)

van Marle, M.; van Wees, D.; Houghton, R. A.; Nassikas, A.; van der Werf, G.

2017-12-01

Carbon-climate feedbacks are one of the key uncertainties in predicting future climate change. Such a feedback could originate from carbon sinks losing their efficiency, for example due to saturation of the CO2 fertilization effect or ocean warming. An indirect approach to estimate how the combined land and ocean sink responds to climate change and growing fossil fuel emissions is based on assessing the trends in the airborne fraction of CO2 emissions from fossil fuel and land use change. One key limitation with this approach has been the large uncertainty in quantifying land use change emissions. We have re-assessed those emissions in a more data-driven approach by combining estimates coming from a bookkeeping model with visibility-based land use change emissions available for the Arc of Deforestation and Equatorial Asia, two key regions with large land use change emissions. The advantage of the visibility-based dataset is that the emissions are observation-based and this dataset provides more detailed information about interannual variability than previous estimates. Based on our estimates we provide evidence that land use and land cover change emissions have increased more rapidly than previously thought, implying that the airborne fraction has decreased since the start of CO2 measurements in 1959. This finding is surprising because it means that the combined land and ocean sink has become more efficient while the opposite is expected.

Regional Climate Change Hotspots over Africa

NASA Astrophysics Data System (ADS)

Anber, U.

2009-04-01

Regional Climate Change Index (RCCI), is developed based on regional mean precipitation change, mean surface air temperature change, and change in precipitation and temperature interannual variability. The RCCI is a comparative index designed to identify the most responsive regions to climate change, or Hot- Spots. The RCCI is calculated for Seven land regions over North Africa and Arabian region from the latest set of climate change projections by 14 global climates for the A1B, A2 and B1 IPCC emission scenarios. The concept of climate change can be approaches from the viewpoint of vulnerability or from that of climate response. In the former case a Hot-Spot can be defined as a region for which potential climate change impacts on the environment or different activity sectors can be particularly pronounced. In the other case, a Hot-Spot can be defined as a region whose climate is especially responsive to global change. In particular, the characterization of climate change response-based Hot-Spot can provide key information to identify and investigate climate change Hot-Spots based on results from multi-model ensemble of climate change simulations performed by modeling groups from around the world as contributions to the Assessment Report of Intergovernmental Panel on Climate Change (IPCC). A Regional Climate Change Index (RCCI) is defined based on four variables: change in regional mean surface air temperature relative to the global average temperature change ( or Regional Warming Amplification Factor, RWAF ), change in mean regional precipitation ( , of present day value ), change in regional surface air temperature interannual variability ( ,of present day value), change in regional precipitation interannual variability ( , of present day value ). In the definition of the RCCI it is important to include quantities other than mean change because often mean changes are not the only important factors for specific impacts. We thus also include inter annual variability, which is critical for many activity sectors, such as agriculture and water management. The RCCI is calculated for the above mentioned set of global climate change simulations and is inter compared across regions to identify climate change, Hot- Spots, that is regions with the largest values of RCCI. It is important to stress that, as will be seen, the RCCI is a comparative index, that is a small RCCI value does not imply a small absolute change, but only a small climate response compared to other regions. The models used are: CCMA-3-T47 CNRM-CM3 CSIRO-MK3 GFDL-CM2-0 GISS-ER INMCM3 IPSL-CM4 MIROC3-2M MIUB-ECHO-G MPI-ECHAM5 MRI-CGCM2 NCAR-CCSM3 NCAR-PCM1 UKMO-HADCM3 Note that the 3 IPCC emission scenarios, A1B, B1 and A2 almost encompass the entire IPCC scenario range, the A2 being close to the high end of the range, the B1 close to the low end and the A1B lying toward the middle of the range. The model data are obtained from the IPCC site and are interpolated onto a common 1 degree grid to facilitate intercomparison. The RCCI is here defined as in Giorgi (2006), except that the entire yea is devided into two six months periods, D J F M A M and J J A S O N. RCCI=[n(∆P)＋n(∆σP)+n(RWAF)+n(∆σT)]D...M + [n(∆P)＋n(∆σP)+n(RWAF)+n(∆σT)]J…N (1)

The Medieval Climate Anomaly and Byzantium: A review of the evidence on climatic fluctuations, economic performance and societal change

NASA Astrophysics Data System (ADS)

Xoplaki, Elena; Fleitmann, Dominik; Luterbacher, Juerg; Wagner, Sebastian; Haldon, John F.; Zorita, Eduardo; Telelis, Ioannis; Toreti, Andrea; Izdebski, Adam

2016-03-01

At the beginning of the Medieval Climate Anomaly, in the ninth and tenth century, the medieval eastern Roman empire, more usually known as Byzantium, was recovering from its early medieval crisis and experiencing favourable climatic conditions for the agricultural and demographic growth. Although in the Balkans and Anatolia such favourable climate conditions were prevalent during the eleventh century, parts of the imperial territories were facing significant challenges as a result of external political/military pressure. The apogee of medieval Byzantine socio-economic development, around AD 1150, coincides with a period of adverse climatic conditions for its economy, so it becomes obvious that the winter dryness and high climate variability at this time did not hinder Byzantine society and economy from achieving that level of expansion. Soon after this peak, towards the end of the twelfth century, the populations of the Byzantine world were experiencing unusual climatic conditions with marked dryness and cooler phases. The weakened Byzantine socio-political system must have contributed to the events leading to the fall of Constantinople in AD 1204 and the sack of the city. The final collapse of the Byzantine political control over western Anatolia took place half century later, thus contemporaneous with the strong cooling effect after a tropical volcanic eruption in AD 1257. We suggest that, regardless of a range of other influential factors, climate change was also an important contributing factor to the socio-economic changes that took place in Byzantium during the Medieval Climate Anomaly. Crucially, therefore, while the relatively sophisticated and complex Byzantine society was certainly influenced by climatic conditions, and while it nevertheless displayed a significant degree of resilience, external pressures as well as tensions within the Byzantine society more broadly contributed to an increasing vulnerability in respect of climate impacts. Our interdisciplinary analysis is based on all available sources of information on the climate and society of Byzantium, that is textual (documentary), archaeological, environmental, climate and climate model-based evidence about the nature and extent of climate variability in the eastern Mediterranean. The key challenge was, therefore, to assess the relative influence to be ascribed to climate variability and change on the one hand, and on the other to the anthropogenic factors in the evolution of Byzantine state and society (such as invasions, changes in international or regional market demand and patterns of production and consumption, etc.). The focus of this interdisciplinary study was to address the possible causal relationships between climatic and socio-economic change and to assess the resilience of the Byzantine socio-economic system in the context of climate change impacts.

The Medieval Climate Anomaly and Byzantium: A review of the evidence on climatic fluctuations, economic performance and societal change

NASA Astrophysics Data System (ADS)

Xoplaki, Elena; Fleitmann, Dominik; Luterbacher, Juerg; Wagner, Sebastian; Haldon, John F.; Zorita, Eduardo; Telelis, Ioannis; Toreti, Andrea; Izdebski, Adam

2016-04-01

At the beginning of the Medieval Climate Anomaly, in the ninth and tenth century, the medieval eastern Roman empire, more usually known as Byzantium, was recovering from its early medieval crisis and experiencing favourable climatic conditions for the agricultural and demographic growth. Although in the Balkans and Anatolia such favourable climate conditions were prevalent during the eleventh century, parts of the imperial territories were facing significant challenges as a result of external political/military pressure. The apogee of medieval Byzantine socio-economic development, around AD 1150, coincides with a period of adverse climatic conditions for its economy, so it becomes obvious that the winter dryness and high climate variability at this time did not hinder Byzantine society and economy from achieving that level of expansion. Soon after this peak, towards the end of the twelfth century, the populations of the Byzantine world were experiencing unusual climatic conditions with marked dryness and cooler phases. The weakened Byzantine socio-political system must have contributed to the events leading to the fall of Constantinople in AD 1204 and the sack of the city. The final collapse of the Byzantine political control over western Anatolia took place half century later, thus contemporaneous with the strong cooling effect after a tropical volcanic eruption in AD 1257. We suggest that, regardless of a range of other influential factors, climate change was also an important contributing factor to the socio-economic changes that took place in Byzantium during the Medieval Climate Anomaly. Crucially, therefore, while the relatively sophisticated and complex Byzantine society was certainly influenced by climatic conditions, and while it nevertheless displayed a significant degree of resilience, external pressures as well as tensions within the Byzantine society more broadly contributed to an increasing vulnerability in respect of climate impacts. Our interdisciplinary analysis is based on all available sources of information on the climate and society of Byzantium, that is textual (documentary), archaeological, environmental, climate and climate model-based evidence about the nature and extent of climate variability in the eastern Mediterranean. The key challenge was, therefore, to assess the relative influence to be ascribed to climate variability and change on the one hand, and on the other to the anthropogenic factors in the evolution of Byzantine state and society (such as invasions, changes in international or regional market demand and patterns of production and consumption, etc.). The focus of this interdisciplinary study was to address the possible causal relationships between climatic and socio-economic change and to assess the resilience of the Byzantine socio-economic system in the context of climate change impacts.

Climate Model Diagnostic Analyzer Web Service System

NASA Astrophysics Data System (ADS)

Lee, S.; Pan, L.; Zhai, C.; Tang, B.; Kubar, T. L.; Li, J.; Zhang, J.; Wang, W.

2015-12-01

Both the National Research Council Decadal Survey and the latest Intergovernmental Panel on Climate Change Assessment Report stressed the need for the comprehensive and innovative evaluation of climate models with the synergistic use of global satellite observations in order to improve our weather and climate simulation and prediction capabilities. The abundance of satellite observations for fundamental climate parameters and the availability of coordinated model outputs from CMIP5 for the same parameters offer a great opportunity to understand and diagnose model biases in climate models. In addition, the Obs4MIPs efforts have created several key global observational datasets that are readily usable for model evaluations. However, a model diagnostic evaluation process requires physics-based multi-variable comparisons that typically involve large-volume and heterogeneous datasets, making them both computationally- and data-intensive. In response, we have developed a novel methodology to diagnose model biases in contemporary climate models and implementing the methodology as a web-service based, cloud-enabled, provenance-supported climate-model evaluation system. The evaluation system is named Climate Model Diagnostic Analyzer (CMDA), which is the product of the research and technology development investments of several current and past NASA ROSES programs. The current technologies and infrastructure of CMDA are designed and selected to address several technical challenges that the Earth science modeling and model analysis community faces in evaluating and diagnosing climate models. In particular, we have three key technology components: (1) diagnostic analysis methodology; (2) web-service based, cloud-enabled technology; (3) provenance-supported technology. The diagnostic analysis methodology includes random forest feature importance ranking, conditional probability distribution function, conditional sampling, and time-lagged correlation map. We have implemented the new methodology as web services and incorporated the system into the Cloud. We have also developed a provenance management system for CMDA where CMDA service semantics modeling, service search and recommendation, and service execution history management are designed and implemented.

Correlating regional natural hazards for global reinsurance risk assessment

NASA Astrophysics Data System (ADS)

Steptoe, Hamish; Maynard, Trevor; Economou, Theo; Fox, Helen; Wallace, Emily; Maisey, Paul

2016-04-01

Concurrent natural hazards represent an uncertainty in assessing exposure for the insurance industry. The recently implemented Solvency II Directive requires EU insurance companies to fully understand and justify their capital reserving and portfolio decisions. Lloyd's, the London insurance and reinsurance market, commissioned the Met Office to investigate the dependencies between different global extreme weather events (known to the industry as perils), and the mechanisms for these dependencies, with the aim of helping them assess their compound risk to the exposure of multiple simultaneous hazards. In this work, we base the analysis of hazard-to-hazard dependency on the interaction of different modes of global and regional climate variability. Lloyd's defined 16 key hazard regions, including Australian wildfires, flooding in China and EU windstorms, and we investigate the impact of 10 key climate modes on these areas. We develop a statistical model that facilitates rapid risk assessment whilst allowing for both temporal auto-correlation and, crucially, interdependencies between drivers. The simulator itself is built conditionally using autoregressive regression models for each driver conditional on the others. Whilst the baseline assumption within the (re)insurance industry is that different natural hazards are independent of each other, the assumption of independence of meteorological risks requires greater justification. Although our results suggest that most of the 120 hazard-hazard connections considered are likely to be independent of each other, 13 have significant dependence arising from one or more global modes of climate variability. This allows us to create a matrix of linkages describing the hazard dependency structure that Lloyd's can use to inform their understanding of risk.

Global volcanic aerosol properties derived from emissions, 1990-2014, using CESM1(WACCM): VOLCANIC AEROSOLS DERIVED FROM EMISSIONS

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

Mills, Michael J.; Schmidt, Anja; Easter, Richard

Accurate representation of global stratospheric aerosol properties from volcanic and non-volcanic sulfur emissions is key to understanding the cooling effects and ozone-loss enhancements of recent volcanic activity. Attribution of climate and ozone variability to volcanic activity is of particular interest in relation to the post-2000 slowing in the apparent rate of global average temperature increases, and variable recovery of the Antarctic ozone hole. We have developed a climatology of global aerosol properties from 1990 to 2014 calculated based on volcanic and non-volcanic emissions of sulfur sources. We have complied a database of volcanic SO2 emissions and plume altitudes for eruptionsmore » between 1990 and 2014, and a new prognostic capability for simulating stratospheric sulfate aerosols in version 5 of the Whole Atmosphere Community Climate Model, a component of the Community Earth System Model. Our climatology shows remarkable agreement with ground-based lidar observations of stratospheric aerosol optical depth (SAOD), and with in situ measurements of aerosol surface area density (SAD). These properties are key parameters in calculating the radiative and chemical effects of stratospheric aerosols. Our SAOD climatology represents a significant improvement over satellite-based analyses, which ignore aerosol extinction below 15 km, a region that can contain the vast majority of stratospheric aerosol extinction at mid- and high-latitudes. Our SAD climatology significantly improves on that provided for the Chemistry-Climate Model Initiative, which misses 60% of the SAD measured in situ. Our climatology of aerosol properties is publicly available on the Earth System Grid.« less

Quantifying Key Climate Parameter Uncertainties Using an Earth System Model with a Dynamic 3D Ocean

NASA Astrophysics Data System (ADS)

Olson, R.; Sriver, R. L.; Goes, M. P.; Urban, N.; Matthews, D.; Haran, M.; Keller, K.

2011-12-01

Climate projections hinge critically on uncertain climate model parameters such as climate sensitivity, vertical ocean diffusivity and anthropogenic sulfate aerosol forcings. Climate sensitivity is defined as the equilibrium global mean temperature response to a doubling of atmospheric CO2 concentrations. Vertical ocean diffusivity parameterizes sub-grid scale ocean vertical mixing processes. These parameters are typically estimated using Intermediate Complexity Earth System Models (EMICs) that lack a full 3D representation of the oceans, thereby neglecting the effects of mixing on ocean dynamics and meridional overturning. We improve on these studies by employing an EMIC with a dynamic 3D ocean model to estimate these parameters. We carry out historical climate simulations with the University of Victoria Earth System Climate Model (UVic ESCM) varying parameters that affect climate sensitivity, vertical ocean mixing, and effects of anthropogenic sulfate aerosols. We use a Bayesian approach whereby the likelihood of each parameter combination depends on how well the model simulates surface air temperature and upper ocean heat content. We use a Gaussian process emulator to interpolate the model output to an arbitrary parameter setting. We use Markov Chain Monte Carlo method to estimate the posterior probability distribution function (pdf) of these parameters. We explore the sensitivity of the results to prior assumptions about the parameters. In addition, we estimate the relative skill of different observations to constrain the parameters. We quantify the uncertainty in parameter estimates stemming from climate variability, model and observational errors. We explore the sensitivity of key decision-relevant climate projections to these parameters. We find that climate sensitivity and vertical ocean diffusivity estimates are consistent with previously published results. The climate sensitivity pdf is strongly affected by the prior assumptions, and by the scaling parameter for the aerosols. The estimation method is computationally fast and can be used with more complex models where climate sensitivity is diagnosed rather than prescribed. The parameter estimates can be used to create probabilistic climate projections using the UVic ESCM model in future studies.

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.

Key drivers of ozone change and its radiative forcing over the 21st century

NASA Astrophysics Data System (ADS)

Iglesias-Suarez, Fernando; Kinnison, Douglas E.; Rap, Alexandru; Maycock, Amanda C.; Wild, Oliver; Young, Paul J.

2018-05-01

Over the 21st century changes in both tropospheric and stratospheric ozone are likely to have important consequences for the Earth's radiative balance. In this study, we investigate the radiative forcing from future ozone changes using the Community Earth System Model (CESM1), with the Whole Atmosphere Community Climate Model (WACCM), and including fully coupled radiation and chemistry schemes. Using year 2100 conditions from the Representative Concentration Pathway 8.5 (RCP8.5) scenario, we quantify the individual contributions to ozone radiative forcing of (1) climate change, (2) reduced concentrations of ozone depleting substances (ODSs), and (3) methane increases. We calculate future ozone radiative forcings and their standard error (SE; associated with inter-annual variability of ozone) relative to year 2000 of (1) 33 ± 104 m Wm-2, (2) 163 ± 109 m Wm-2, and (3) 238 ± 113 m Wm-2 due to climate change, ODSs, and methane, respectively. Our best estimate of net ozone forcing in this set of simulations is 430 ± 130 m Wm-2 relative to year 2000 and 760 ± 230 m Wm-2 relative to year 1750, with the 95 % confidence interval given by ±30 %. We find that the overall long-term tropospheric ozone forcing from methane chemistry-climate feedbacks related to OH and methane lifetime is relatively small (46 m Wm-2). Ozone radiative forcing associated with climate change and stratospheric ozone recovery are robust with regard to background climate conditions, even though the ozone response is sensitive to both changes in atmospheric composition and climate. Changes in stratospheric-produced ozone account for ˜ 50 % of the overall radiative forcing for the 2000-2100 period in this set of simulations, highlighting the key role of the stratosphere in determining future ozone radiative forcing.

The future of evapotranspiration: Global requirements for ecosystem functioning, carbon and climate feedbacks, agricultural management, and water resources

NASA Astrophysics Data System (ADS)

Fisher, Joshua B.; Melton, Forrest; Middleton, Elizabeth; Hain, Christopher; Anderson, Martha; Allen, Richard; McCabe, Matthew F.; Hook, Simon; Baldocchi, Dennis; Townsend, Philip A.; Kilic, Ayse; Tu, Kevin; Miralles, Diego D.; Perret, Johan; Lagouarde, Jean-Pierre; Waliser, Duane; Purdy, Adam J.; French, Andrew; Schimel, David; Famiglietti, James S.; Stephens, Graeme; Wood, Eric F.

2017-04-01

The fate of the terrestrial biosphere is highly uncertain given recent and projected changes in climate. This is especially acute for impacts associated with changes in drought frequency and intensity on the distribution and timing of water availability. The development of effective adaptation strategies for these emerging threats to food and water security are compromised by limitations in our understanding of how natural and managed ecosystems are responding to changing hydrological and climatological regimes. This information gap is exacerbated by insufficient monitoring capabilities from local to global scales. Here, we describe how evapotranspiration (ET) represents the key variable in linking ecosystem functioning, carbon and climate feedbacks, agricultural management, and water resources, and highlight both the outstanding science and applications questions and the actions, especially from a space-based perspective, necessary to advance them.

The Future of Evapotranspiration: Global Requirements for Ecosystem Functioning, Carbon and Climate Feedbacks, Agricultural Management, and Water Resources

NASA Technical Reports Server (NTRS)

Fisher, Joshua B.; Melton, Forrest; Middleton, Elizabeth; Hain, Christopher; Anderson, Martha; Allen, Richard; McCabe, Matthew F.; Hook, Simon; Baldocchi, Dennis; Townsend, Philip A.;

Web based visualization of large climate data sets

USGS Publications Warehouse

Alder, Jay R.; Hostetler, Steven W.

2015-01-01

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

On the data-driven inference of modulatory networks in climate science: an application to West African rainfall

NASA Astrophysics Data System (ADS)

González, D. L., II; Angus, M. P.; Tetteh, I. K.; Bello, G. A.; Padmanabhan, K.; Pendse, S. V.; Srinivas, S.; Yu, J.; Semazzi, F.; Kumar, V.; Samatova, N. F.

2015-01-01

Decades of hypothesis-driven and/or first-principles research have been applied towards the discovery and explanation of the mechanisms that drive climate phenomena, such as western African Sahel summer rainfall~variability. Although connections between various climate factors have been theorized, not all of the key relationships are fully understood. We propose a data-driven approach to identify candidate players in this climate system, which can help explain underlying mechanisms and/or even suggest new relationships, to facilitate building a more comprehensive and predictive model of the modulatory relationships influencing a climate phenomenon of interest. We applied coupled heterogeneous association rule mining (CHARM), Lasso multivariate regression, and dynamic Bayesian networks to find relationships within a complex system, and explored means with which to obtain a consensus result from the application of such varied methodologies. Using this fusion of approaches, we identified relationships among climate factors that modulate Sahel rainfall. These relationships fall into two categories: well-known associations from prior climate knowledge, such as the relationship with the El Niño-Southern Oscillation (ENSO) and putative links, such as North Atlantic Oscillation, that invite further research.

On the data-driven inference of modulatory networks in climate science: An application to West African rainfall

DOE PAGES

Gonzalez, II, D. L.; Angus, M. P.; Tetteh, I. K.; ...

2015-01-13

Decades of hypothesis-driven and/or first-principles research have been applied towards the discovery and explanation of the mechanisms that drive climate phenomena, such as western African Sahel summer rainfall~variability. Although connections between various climate factors have been theorized, not all of the key relationships are fully understood. We propose a data-driven approach to identify candidate players in this climate system, which can help explain underlying mechanisms and/or even suggest new relationships, to facilitate building a more comprehensive and predictive model of the modulatory relationships influencing a climate phenomenon of interest. We applied coupled heterogeneous association rule mining (CHARM), Lasso multivariate regression,more » and dynamic Bayesian networks to find relationships within a complex system, and explored means with which to obtain a consensus result from the application of such varied methodologies. Using this fusion of approaches, we identified relationships among climate factors that modulate Sahel rainfall. As a result, these relationships fall into two categories: well-known associations from prior climate knowledge, such as the relationship with the El Niño–Southern Oscillation (ENSO) and putative links, such as North Atlantic Oscillation, that invite further research.« less

Interactions between large-scale modes of climate and their relationship with Australian climate and hydrology

NASA Astrophysics Data System (ADS)

Whan, K. R.; Lindesay, J. A.; Timbal, B.; Raupach, M. R.; Williams, E.

2010-12-01

Australia’s natural environment is adapted to low rainfall availability and high variability but human systems are less able to adapt to variability in the hydrological cycle. Understanding the mechanisms underlying drought persistence and severity is vital to contextualising future climate change. Multiple external forcings mean the mechanisms of drought occurrence in south-eastern Australian are complex. The key influences on SEA climate are El Niño-Southern Oscillation (ENSO), the Indian Ocean Dipole (IOD), the Southern Annular Mode (SAM) and the sub-tropical ridge (STR); each of these large-scale climate modes (LSCM) has been studied widely. The need for research into the interactions among the modes has been noted [1], although to date this has received limited attention. Relationships between LSCM and hydrometeorological variability are nonlinear, making linearity assumptions underlying usual statistical techniques (e.g. correlation, principle components analysis) questionable. In the current research a statistical technique that can deal with nonlinear interactions is applied to a new dataset enabling a full examination of the Australian water balance. The Australian Water Availability Project (AWAP) dataset models the Australian water balance on a fine grid [2]. Hydrological parameters (e.g. soil moisture, evaporation, runoff) are modelled from meteorological data, allowing the complete Australian water balance (climate and hydrology) to be examined and the mechanisms of drought to be studied holistically. Classification and regression trees (CART) are a powerful regression-based technique that is capable of accounting for nonlinear effects. Although it has limited previous application in climate research [3] this methodology is particularly informative in cases with multiple predictors and nonlinear relationships such as climate variability. Statistical relationships between variables are the basis for the decision rules in CART that are used to split the data into increasingly homogeneous groups. CART is applied to the AWAP dataset to identify the hydroclimatic regimes associated with various combinations of LSCM and the importance of each mode in producing the regime. Analysis of the LSCM is conducted on a range of hydroclimatic variables to assess the relative and combined influences of these LSCM on the Australian water balance. This gives information about interactions between LSCM that are vital for specific hydroclimatic states (e.g. drought) and about which combinations of LSCM result in specific regimes. The dominant LSCM in different seasons and the relationships among the climate drivers have been identified. 1. Ummenhofer, C., et al., What causes southeast Australia's worst droughts? Geophysical Research Letters, 2009. 36: p. L04706. 2. Raupach, M., et al., Australian Water Availability Project (AWAP). CSIRO Marine and Atmospheric Research Component: Final Report for Phase 3. 2008. 3. Burrows, W., et al., CART Decision-Tree Statistical Analysis and Prediction of Summer Season Maximum Surface Ozone for the Vancouver, Montreal and Atlantic Regions of Canada. Journal of Applied Meteorology, 1995. 34: p. 1848-1862.

The CSAICLAWPS project: a multi-scalar, multi-data source approach to providing climate services for both modelling of climate change impacts on crop yields and development of community-level adaptive capacity for sustainable food security

NASA Astrophysics Data System (ADS)

Forsythe, N. D.; Fowler, H. J.

2017-12-01

The "Climate-smart agriculture implementation through community-focused pursuit of land and water productivity in South Asia" (CSAICLAWPS) project is a research initiative funded by the (UK) Royal Society through its Challenge Grants programme which is part of the broader UK Global Challenges Research Fund (GCRF). CSAICLAWPS has three objectives: a) development of "added-value" - bias assessed, statistically down-scaled - climate projections for selected case study sites across South Asia; b) investigation of crop failure modes under both present (observed) and future (projected) conditions; and c) facilitation of developing local adaptive capacity and resilience through stakeholder engagement. At AGU we will be presenting both next steps and progress to date toward these three objectives: [A] We have carried out bias assessments of a substantial multi-model RCM ensemble (MME) from the CORDEX South Asia (CORDEXdomain for case studies in three countries - Pakistan, India and Sri Lanka - and (stochastically) produced synthetic time-series for these sites from local observations using a Python-based implementation of the principles underlying the Climate Research Unit Weather Generator (CRU-WG) in order to enable probabilistic simulation of current crop yields. [B] We have characterised present response of local crop yields to climate variability in key case study sites using AquaCrop simulations parameterised based on input (agronomic practices, soil conditions, etc) from smallholder farmers. [C] We have implemented community-based hydro-climatological monitoring in several case study "revenue villages" (panchayats) in the Nainital District of Uttarakhand. The purpose of this is not only to increase availability of meteorological data, but also has the aspiration of, over time, leading to enhanced quantitative awareness of present climate variability and potential future conditions (as projected by RCMs). Next steps in our work will include: 1) future crop yield simulations driven by "perturbation" of synthetic time-series using "change factors from the CORDEX-SA MME; 2) stakeholder dialogues critically evaluating potential strategies at the grassroots (implementation) level to mitigate impacts of climate variability and change on crop yields.

Fish habitat regression under water scarcity scenarios in the Douro River basin

NASA Astrophysics Data System (ADS)

Segurado, Pedro; Jauch, Eduardo; Neves, Ramiro; Ferreira, Teresa

2015-04-01

Climate change will predictably alter hydrological patterns and processes at the catchment scale, with impacts on habitat conditions for fish. The main goals of this study are to identify the stream reaches that will undergo more pronounced flow reduction under different climate change scenarios and to assess which fish species will be more affected by the consequent regression of suitable habitats. The interplay between changes in flow and temperature and the presence of transversal artificial obstacles (dams and weirs) is analysed. The results will contribute to river management and impact mitigation actions under climate change. This study was carried out in the Tâmega catchment of the Douro basin. A set of 29 Hydrological, climatic, and hydrogeomorphological variables were modelled using a water modelling system (MOHID), based on meteorological data recorded monthly between 2008 and 2014. The same variables were modelled considering future climate change scenarios. The resulting variables were used in empirical habitat models of a set of key species (brown trout Salmo trutta fario, barbell Barbus bocagei, and nase Pseudochondrostoma duriense) using boosted regression trees. The stream segments between tributaries were used as spatial sampling units. Models were developed for the whole Douro basin using 401 fish sampling sites, although the modelled probabilities of species occurrence for each stream segment were predicted only for the Tâmega catchment. These probabilities of occurrence were used to classify stream segments into suitable and unsuitable habitat for each fish species, considering the future climate change scenario. The stream reaches that were predicted to undergo longer flow interruptions were identified and crossed with the resulting predictive maps of habitat suitability to compute the total area of habitat loss per species. Among the target species, the brown trout was predicted to be the most sensitive to habitat regression due to the interplay of flow reduction, increase of temperature and transversal barriers. This species is therefore a good indicator of climate change impacts in rivers and therefore we recommend using this species as a target of monitoring programs to be implemented in the context of climate change adaptation strategies.

Estimating daily climatologies for climate indices derived from climate model data and observations

PubMed Central

Mahlstein, Irina; Spirig, Christoph; Liniger, Mark A; Appenzeller, Christof

2015-01-01

Climate indices help to describe the past, present, and the future climate. They are usually closer related to possible impacts and are therefore more illustrative to users than simple climate means. Indices are often based on daily data series and thresholds. It is shown that the percentile-based thresholds are sensitive to the method of computation, and so are the climatological daily mean and the daily standard deviation, which are used for bias corrections of daily climate model data. Sample size issues of either the observed reference period or the model data lead to uncertainties in these estimations. A large number of past ensemble seasonal forecasts, called hindcasts, is used to explore these sampling uncertainties and to compare two different approaches. Based on a perfect model approach it is shown that a fitting approach can improve substantially the estimates of daily climatologies of percentile-based thresholds over land areas, as well as the mean and the variability. These improvements are relevant for bias removal in long-range forecasts or predictions of climate indices based on percentile thresholds. But also for climate change studies, the method shows potential for use. Key Points More robust estimates of daily climate characteristics Statistical fitting approach Based on a perfect model approach PMID:26042192

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).

Modeling climate effects on hip fracture rate by the multivariate GARCH model in Montreal region, Canada.

PubMed

Modarres, Reza; Ouarda, Taha B M J; Vanasse, Alain; Orzanco, Maria Gabriela; Gosselin, Pierre

2014-07-01

Changes in extreme meteorological variables and the demographic shift towards an older population have made it important to investigate the association of climate variables and hip fracture by advanced methods in order to determine the climate variables that most affect hip fracture incidence. The nonlinear autoregressive moving average with exogenous variable-generalized autoregressive conditional heteroscedasticity (ARMAX-GARCH) and multivariate GARCH (MGARCH) time series approaches were applied to investigate the nonlinear association between hip fracture rate in female and male patients aged 40-74 and 75+ years and climate variables in the period of 1993-2004, in Montreal, Canada. The models describe 50-56% of daily variation in hip fracture rate and identify snow depth, air temperature, day length and air pressure as the influencing variables on the time-varying mean and variance of the hip fracture rate. The conditional covariance between climate variables and hip fracture rate is increasing exponentially, showing that the effect of climate variables on hip fracture rate is most acute when rates are high and climate conditions are at their worst. In Montreal, climate variables, particularly snow depth and air temperature, appear to be important predictors of hip fracture incidence. The association of climate variables and hip fracture does not seem to change linearly with time, but increases exponentially under harsh climate conditions. The results of this study can be used to provide an adaptive climate-related public health program and ti guide allocation of services for avoiding hip fracture risk.

Modeling climate effects on hip fracture rate by the multivariate GARCH model in Montreal region, Canada

NASA Astrophysics Data System (ADS)

Modarres, Reza; Ouarda, Taha B. M. J.; Vanasse, Alain; Orzanco, Maria Gabriela; Gosselin, Pierre

2014-07-01

Changes in extreme meteorological variables and the demographic shift towards an older population have made it important to investigate the association of climate variables and hip fracture by advanced methods in order to determine the climate variables that most affect hip fracture incidence. The nonlinear autoregressive moving average with exogenous variable-generalized autoregressive conditional heteroscedasticity (ARMA X-GARCH) and multivariate GARCH (MGARCH) time series approaches were applied to investigate the nonlinear association between hip fracture rate in female and male patients aged 40-74 and 75+ years and climate variables in the period of 1993-2004, in Montreal, Canada. The models describe 50-56 % of daily variation in hip fracture rate and identify snow depth, air temperature, day length and air pressure as the influencing variables on the time-varying mean and variance of the hip fracture rate. The conditional covariance between climate variables and hip fracture rate is increasing exponentially, showing that the effect of climate variables on hip fracture rate is most acute when rates are high and climate conditions are at their worst. In Montreal, climate variables, particularly snow depth and air temperature, appear to be important predictors of hip fracture incidence. The association of climate variables and hip fracture does not seem to change linearly with time, but increases exponentially under harsh climate conditions. The results of this study can be used to provide an adaptive climate-related public health program and ti guide allocation of services for avoiding hip fracture risk.

Attribution of Observed Streamflow Changes in Key British Columbia Drainage Basins

NASA Astrophysics Data System (ADS)

Najafi, Mohammad Reza; Zwiers, Francis W.; Gillett, Nathan P.

2017-11-01

We study the observed decline in summer streamflow in four key river basins in British Columbia (BC), Canada, using a formal detection and attribution (D&A) analysis procedure. Reconstructed and simulated streamflow is generated using the semidistributed variable infiltration capacity hydrologic model, which is driven by 1/16° gridded observations and downscaled climate model data from the Coupled Model Intercomparison Project phase 5 (CMIP5), respectively. The internal variability of the regional hydrologic components using 5100 years of streamflow was simulated using CMIP5 preindustrial control runs. Results show that the observed changes in summer streamflow are inconsistent with simulations representing the responses to natural forcing factors alone, while the response to anthropogenic and natural forcing factors combined is detected in these changes. A two-signal D&A analysis indicates that the effects of anthropogenic (ANT) forcing factors are discernable from natural forcing in BC, albeit with large uncertainties.

Changing Amazon biomass and the role of atmospheric CO2 concentration, climate, and land use

NASA Astrophysics Data System (ADS)

Almeida Castanho, Andrea D.; Galbraith, David; Zhang, Ke; Coe, Michael T.; Costa, Marcos H.; Moorcroft, Paul

2016-01-01

The Amazon tropical evergreen forest is an important component of the global carbon budget. Its forest floristic composition, structure, and function are sensitive to changes in climate, atmospheric composition, and land use. In this study biomass and productivity simulated by three dynamic global vegetation models (Integrated Biosphere Simulator, Ecosystem Demography Biosphere Model, and Joint UK Land Environment Simulator) for the period 1970-2008 are compared with observations from forest plots (Rede Amazónica de Inventarios Forestales). The spatial variability in biomass and productivity simulated by the DGVMs is low in comparison to the field observations in part because of poor representation of the heterogeneity of vegetation traits within the models. We find that over the last four decades the CO2 fertilization effect dominates a long-term increase in simulated biomass in undisturbed Amazonian forests, while land use change in the south and southeastern Amazonia dominates a reduction in Amazon aboveground biomass, of similar magnitude to the CO2 biomass gain. Climate extremes exert a strong effect on the observed biomass on short time scales, but the models are incapable of reproducing the observed impacts of extreme drought on forest biomass. We find that future improvements in the accuracy of DGVM predictions will require improved representation of four key elements: (1) spatially variable plant traits, (2) soil and nutrients mediated processes, (3) extreme event mortality, and (4) sensitivity to climatic variability. Finally, continued long-term observations and ecosystem-scale experiments (e.g. Free-Air CO2 Enrichment experiments) are essential for a better understanding of the changing dynamics of tropical forests.

Understanding the origin of the solar cyclic activity for an improved earth climate prediction

NASA Astrophysics Data System (ADS)

Turck-Chièze, Sylvaine; Lambert, Pascal

This review is dedicated to the processes which could explain the origin of the great extrema of the solar activity. We would like to reach a more suitable estimate and prediction of the temporal solar variability and its real impact on the Earth climatic models. The development of this new field is stimulated by the SoHO helioseismic measurements and by some recent solar modelling improvement which aims to describe the dynamical processes from the core to the surface. We first recall assumptions on the potential different solar variabilities. Then, we introduce stellar seismology and summarize the main SOHO results which are relevant for this field. Finally we mention the dynamical processes which are presently introduced in new solar models. We believe that the knowledge of two important elements: (1) the magnetic field interplay between the radiative zone and the convective zone and (2) the role of the gravity waves, would allow to understand the origin of the grand minima and maxima observed during the last millennium. Complementary observables like acoustic and gravity modes, radius and spectral irradiance from far UV to visible in parallel to the development of 1D-2D-3D simulations will improve this field. PICARD, SDO, DynaMICCS are key projects for a prediction of the next century variability. Some helioseismic indicators constitute the first necessary information to properly describe the Sun-Earth climatic connection.

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

NASA Astrophysics Data System (ADS)

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

2011-12-01

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

Climatic effects on mosquito abundance in Mediterranean wetlands

PubMed Central

2014-01-01

Background The impact of climate change on vector-borne diseases is highly controversial. One of the principal points of debate is whether or not climate influences mosquito abundance, a key factor in disease transmission. Methods To test this hypothesis, we analysed ten years of data (2003–2012) from biweekly surveys to assess inter-annual and seasonal relationships between the abundance of seven mosquito species known to be pathogen vectors (West Nile virus, Usutu virus, dirofilariasis and Plasmodium sp.) and several climatic variables in two wetlands in SW Spain. Results Within-season abundance patterns were related to climatic variables (i.e. temperature, rainfall, tide heights, relative humidity and photoperiod) that varied according to the mosquito species in question. Rainfall during winter months was positively related to Culex pipiens and Ochlerotatus detritus annual abundances. Annual maximum temperatures were non-linearly related to annual Cx. pipiens abundance, while annual mean temperatures were positively related to annual Ochlerotatus caspius abundance. Finally, we modelled shifts in mosquito abundances using the A2 and B2 temperature and rainfall climate change scenarios for the period 2011–2100. While Oc. caspius, an important anthropophilic species, may increase in abundance, no changes are expected for Cx. pipiens or the salt-marsh mosquito Oc. detritus. Conclusions Our results highlight that the effects of climate are species-specific, place-specific and non-linear and that linear approaches will therefore overestimate the effect of climate change on mosquito abundances at high temperatures. Climate warming does not necessarily lead to an increase in mosquito abundance in natural Mediterranean wetlands and will affect, above all, species such as Oc. caspius whose numbers are not closely linked to rainfall and are influenced, rather, by local tidal patterns and temperatures. The final impact of changes in vector abundance on disease frequency will depend on the direct and indirect effects of climate and other parameters related to pathogen amplification and spillover on humans and other vertebrates. PMID:25030527

Uncertainties in Past and Future Global Water Availability

NASA Astrophysics Data System (ADS)

Sheffield, J.; Kam, J.

2014-12-01

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

Assessment of Human Health Vulnerability to Climate Variability and Change in Cuba

PubMed Central

Bultó, Paulo Lázaro Ortíz; Rodríguez, Antonio Pérez; Valencia, Alina Rivero; Vega, Nicolás León; Gonzalez, Manuel Díaz; Carrera, Alina Pérez

2006-01-01

In this study we assessed the potential effects of climate variability and change on population health in Cuba. We describe the climate of Cuba as well as the patterns of climate-sensitive diseases of primary concern, particularly dengue fever. Analyses of the associations between climatic anomalies and disease patterns highlight current vulnerability to climate variability. We describe current adaptations, including the application of climate predictions to prevent disease outbreaks. Finally, we present the potential economic costs associated with future impacts due to climate change. The tools used in this study can be useful in the development of appropriate and effective adaptation options to address the increased climate variability associated with climate change. PMID:17185289

Climate variability drives population cycling and synchrony

Treesearch

Lars Y. Pomara; Benjamin Zuckerberg

2017-01-01

Aim There is mounting concern that climate change will lead to the collapse of cyclic population dynamics, yet the influence of climate variability on population cycling remains poorly understood. We hypothesized that variability in survival and fecundity, driven by climate variability at different points in the life cycle, scales up from...

An analysis of carbon and radiocarbon profiles across a range ecosystems types

NASA Astrophysics Data System (ADS)

Heckman, K. A.; Gallo, A.; Hatten, J. A.; Swanston, C.; Strahm, B. D.; Sanclements, M.

2016-12-01

Soil carbon stocks have become recognized as increasingly important in the context of climate change and global C cycle modeling. As modelers seek to identify key parameters affecting the size and stability of belowground C stocks, attention has been drawn to the mineral matrix and the soil physiochemical factors influenced by it. Though clay content has often been utilized as a convenient and key explanatory variable for soil C dynamics, its utility has recently come under scrutiny as new paradigms of soil organic matter stabilization have been developed. We utilized soil cores from a range of National Ecological Observatory Network (NEON) experimental plots to examine the influence of mineralogical parameters on soil C stocks and turnover and their relative importance in comparison to climatic variables. Results are presented for a total of 11 NEON sites, spanning Alfisols, Entisols, Mollisols and Spodosols. Soils were sampled by genetic horizon, density separated according to density fractionation: light fractions (particulate organics neither occluded within aggregates nor associated with mineral surfaces), occluded fractions (particulate organics occluded within aggregates), and heavy fractions (organics associated with mineral surfaces). Bulk soils and density fractions were measured for % C and radiocarbon abundance (as a measure of C stability). Carbon and radiocarbon abundances were examined among fractions and in the context of climatic variables (temperature, precipitation, elevation) and soil physiochemical variables (% clay and pH). No direct relationships between temperature and soil C or radiocarbon abundances were found. As a whole, soil radiocarbon abundance in density fractions decreased in the order of light>heavy>occluded, highlighting the importance of both surface sorption and aggregation to the preservation of organics. Radiocarbon concentrations of the heavy fraction (mineral adsorbed) were significantly, though weakly, correlated with pH (r2 = 0.35, p = 0.02), though C concentrations were not. Data suggest an important role for both aggregation and soil chemistry in regulating soil C cycling across a diversity of soil orders. The current presented results serve as a preliminary report on a project spanning 40 NEON sites and a range of physiochemical analyses.

The Calibration and Characterization of Earth Remote Sensing and Environmental Monitoring Instruments. Chapter 10

NASA Technical Reports Server (NTRS)

Butler, James J.; Johnson, B. Carol; Barnes, Robert A.

2005-01-01

The use of remote sensing instruments on orbiting satellite platforms in the study of Earth Science and environmental monitoring was officially inaugurated with the April 1, 1960 launch of the Television Infrared Observation Satellite (TIROS) [1]. The first TIROS accommodated two television cameras and operated for only 78 days. However, the TIROS program, in providing in excess of 22,000 pictures of the Earth, achieved its primary goal of providing Earth images from a satellite platform to aid in identifying and monitoring meteorological processes. This marked the beginning of what is now over four decades of Earth observations from satellite platforms. reflected and emitted radiation from the Earth using instruments on satellite platforms. These measurements are input to climate models, and the model results are analyzed in an effort to detect short and long-term changes and trends in the Earth's climate and environment, to identify the cause of those changes, and to predict or influence future changes. Examples of short-term climate change events include the periodic appearance of the El Nino-Southern Oscillation (ENSO) in the tropical Pacific Ocean [2] and the spectacular eruption of Mount Pinatubo on the Philippine island of Luzon in 1991. Examples of long term climate change events, which are more subtle to detect, include the destruction of coral reefs, the disappearance of glaciers, and global warming. Climatic variability can be both large and small scale and can be caused by natural or anthropogenic processes. The periodic El Nino event is an example of a natural process which induces significant climatic variability over a wide range of the Earth. A classic example of a large scale anthropogenic influence on climate is the well-documented rapid increase of atmospheric carbon dioxide occurring since the beginning of the Industrial Revolution [3]. An example of the study of a small-scale anthropogenic influence in climate variability is the Atlanta Land-use Analysis Temperature and Air-quality (ATLANTA) project [4]. This project has found that the replacement of trees and vegetation with concrete and asphalt in Atlanta, Georgia, and its environs has created a microclimate capable of producing wind and thunderstorms. A key objective of climate research is to be able to distinguish the natural versus human roles in climate change and to clearly communicate those findings to those who shape and direct environmental policy.

Winter temperature conditions (1670-2010) reconstructed from varved sediments, western Canadian High Arctic

NASA Astrophysics Data System (ADS)

Amann, Benjamin; Lamoureux, Scott F.; Boreux, Maxime P.

2017-09-01

Advances in paleoclimatology from the Arctic have provided insights into long-term climate conditions. However, while past annual and summer temperature have received considerable research attention, comparatively little is known about winter paleoclimate. Arctic winter is of special interest as it is the season with the highest sensitivity to climate change, and because it differs substantially from summer and annual measures. Therefore, information about past changes in winter climate is key to improve our knowledge of past forced climate variability and to reduce uncertainty in climate projections. In this context, Arctic lakes with snowmelt-fed catchments are excellent potential winter climate archives. They respond strongly to snowmelt-induced runoff, and indirectly to winter temperature and snowfall conditions. To date, only a few well-calibrated lake sediment records exist, which appear to reflect site-specific responses with differing reconstructions. This limits the possibility to resolve large-scale winter climate change prior the instrumental period. Here, we present a well-calibrated quantitative temperature and snowfall record for the extended winter season (November through March; NDJFM) from Chevalier Bay (Melville Island, NWT, Canadian Arctic) back to CE 1670. The coastal embayment has a large catchment influenced by nival terrestrial processes, which leads to high sedimentation rates and annual sedimentary structures (varves). Using detailed microstratigraphic analysis from two sediment cores and supported by μ-XRF data, we separated the nival sedimentary units (spring snowmelt) from the rainfall units (summer) and identified subaqueous slumps. Statistical correlation analysis between the proxy data and monthly climate variables reveals that the thickness of the nival units can be used to predict winter temperature (r = 0.71, pc < 0.01, 5-yr filter) and snowfall (r = 0.65, pc < 0.01, 5-yr filter) for the western Canadian High Arctic over the last ca. 400 years. Results reveal a strong variability in winter temperature back to CE 1670 with the coldest decades reconstructed for the period CE 1800-1880, while the warmest decades and major trends are reconstructed for the period CE 1880-1930 (0.26°C/decade) and CE 1970-2010 (0.37°C/decade). Although the first aim of this study was to increase the paleoclimate data coverage for the winter season, the record from Chevalier Bay also holds great potential for more applied climate research such as data-model comparisons and proxy-data assimilation in climate model simulations.

Quantifying climatic variability in monsoonal northern China over the last 2200 years and its role in driving Chinese dynastic changes

NASA Astrophysics Data System (ADS)

Li, Jianyong; Dodson, John; Yan, Hong; Zhang, David D.; Zhang, Xiaojian; Xu, Qinghai; Lee, Harry F.; Pei, Qing; Cheng, Bo; Li, Chunhai; Ni, Jian; Sun, Aizhi; Lu, Fengyan; Zong, Yongqiang

2017-03-01

Our understanding on the spatial-temporal patterns of climatic variability over the last few millennia in the East Asian monsoon-dominated northern China (NC), and its role at a macro-scale in affecting the prosperity and depression of Chinese dynasties is limited. Quantitative high-resolution, regionally-synthesized palaeoclimatic reconstructions as well as simulations, and numerical analyses of their relationships with various fine-scale, numerical agro-ecological, social-economic, and geo-political historical records during the period of China's history, are presented here for NC. We utilize pollen data together with climate modeling to reconstruct and simulate decadal- to centennial-scale variations in precipitation or temperature for NC during the last 2200 years (-200-2000 AD). We find an overall cyclic-pattern (wet/warm or dry/cold) in the precipitation and temperature anomalies on centennial- to millennial-scale that can be likely considered as a representative for the entire NC by comparison with other related climatic records. We suggest that solar activity may play a key role in driving the climatic fluctuations in NC during the last 22 centuries, with its quasi ∼100, 50, 23, or 22-year periodicity clearly identified in our climatic reconstructions. We employ variation partitioning and redundancy analysis to quantify the independent effects of climatic factors on accounting for the total variation of 17 fine-grained numerical Chinese historical records. We quantitatively illustrate that precipitation (67.4%) may have been more important than temperature (32.5%) in causing the overall agro-ecological and macro-geopolitical shifts in imperial China with NC as the central ruling region and an agricultural heartland over the last 2200 years.

Developing User-Driven Climate Information Services to Build Resilience Amongst Groups at Risk of Drought and Flood in Arid and Semi-Arid Land Counties in Kenya

NASA Astrophysics Data System (ADS)

Githungo, W. N.; Shaka, A.; Kniveton, D.; Muithya, L.; Powell, R.; Visman, E. L.

2014-12-01

The Arid and Semi-Arid Land (ASAL) counties of Kitui and Makueni in Kenya are experiencing increasing climate variability in seasonal rainfall, including changes in the onset, cessation and distribution of the two principal rains upon which the majority of the population's small-holder farmers and livestock keepers depend. Food insecurity is prevalent with significant numbers also affected by flooding during periods of intense rainfall. As part of a multi-partner Adaptation Consortium, Kenya Meteorological Services (KMS) are developing Climate Information Services (CIS) which can better support decision making amongst the counties' principal livelihoods groups and across County Government ministries. Building on earlier pilots and stakeholder discussion, the system combines the production of climate information tailored for transmission via regional and local radio stations with the establishment of a new SMS service. SMS are provided through a network of CIS intermediaries drawn from across key government ministries, religious networks, non-governmental and community groups, aiming to achieve one SMS recipient per 3-500 people. It also introduces a demand-led, premium-rate SMS weather information service which is designed to be self-financing in the long term. Supporting the ongoing process of devolution, KMS is downscaling national forecasts for each county, and providing seasonal, monthly, weekly and daily forecasts, as well as warnings of weather-related hazards. Through collaboration with relevant ministries, government bodies and research institutions, including livestock, agriculture, drought management and health, technical advisories are developed to provide guidance on application of the climate information. The system seeks to provide timely, relevant information which can enable people to use weather and climate information to support decisions which protect life and property and build resilience to ongoing climate variability and future change.

Climate-driven shifts in continental net primary production implicated as a driver of a recent abrupt increase in the land carbon sink

NASA Astrophysics Data System (ADS)

Buermann, Wolfgang; Beaulieu, Claudie; Parida, Bikash; Medvigy, David; Collatz, George J.; Sheffield, Justin; Sarmiento, Jorge L.

2016-03-01

The world's ocean and land ecosystems act as sinks for anthropogenic CO2, and over the last half century their combined sink strength grew steadily with increasing CO2 emissions. Recent analyses of the global carbon budget, however, have uncovered an abrupt, substantial ( ˜ 1 PgC yr-1) and sustained increase in the land sink in the late 1980s whose origin remains unclear. In the absence of this prominent shift in the land sink, increases in atmospheric CO2 concentrations since the late 1980s would have been ˜ 30 % larger than observed (or ˜ 12 ppm above current levels). Global data analyses are limited in regards to attributing causes to changes in the land sink because different regions are likely responding to different drivers. Here, we address this challenge by using terrestrial biosphere models constrained by observations to determine if there is independent evidence for the abrupt strengthening of the land sink. We find that net primary production significantly increased in the late 1980s (more so than heterotrophic respiration), consistent with the inferred increase in the global land sink, and that large-scale climate anomalies are responsible for this shift. We identify two key regions in which climatic constraints on plant growth have eased: northern Eurasia experienced warming, and northern Africa received increased precipitation. Whether these changes in continental climates are connected is uncertain, but North Atlantic climate variability is important. Our findings suggest that improved understanding of climate variability in the North Atlantic may be essential for more credible projections of the land sink under climate change.

Modeled response of the West Nile virus vector Culex quinquefasciatus to changing climate using the dynamic mosquito simulation model

NASA Astrophysics Data System (ADS)

Morin, Cory W.; Comrie, Andrew C.

2010-09-01

Climate can strongly influence the population dynamics of disease vectors and is consequently a key component of disease ecology. Future climate change and variability may alter the location and seasonality of many disease vectors, possibly increasing the risk of disease transmission to humans. The mosquito species Culex quinquefasciatus is a concern across the southern United States because of its role as a West Nile virus vector and its affinity for urban environments. Using established relationships between atmospheric variables (temperature and precipitation) and mosquito development, we have created the Dynamic Mosquito Simulation Model (DyMSiM) to simulate Cx. quinquefasciatus population dynamics. The model is driven with climate data and validated against mosquito count data from Pasco County, Florida and Coachella Valley, California. Using 1-week and 2-week filters, mosquito trap data are reproduced well by the model ( P < 0.0001). Dry environments in southern California produce different mosquito population trends than moist locations in Florida. Florida and California mosquito populations are generally temperature-limited in winter. In California, locations are water-limited through much of the year. Using future climate projection data generated by the National Center for Atmospheric Research CCSM3 general circulation model, we applied temperature and precipitation offsets to the climate data at each location to evaluate mosquito population sensitivity to possible future climate conditions. We found that temperature and precipitation shifts act interdependently to cause remarkable changes in modeled mosquito population dynamics. Impacts include a summer population decline from drying in California due to loss of immature mosquito habitats, and in Florida a decrease in late-season mosquito populations due to drier late summer conditions.

Hydrologic refugia, plants, and climate change.

PubMed

McLaughlin, Blair C; Ackerly, David D; Klos, P Zion; Natali, Jennifer; Dawson, Todd E; Thompson, Sally E

2017-08-01

Climate, physical landscapes, and biota interact to generate heterogeneous hydrologic conditions in space and over time, which are reflected in spatial patterns of species distributions. As these species distributions respond to rapid climate change, microrefugia may support local species persistence in the face of deteriorating climatic suitability. Recent focus on temperature as a determinant of microrefugia insufficiently accounts for the importance of hydrologic processes and changing water availability with changing climate. Where water scarcity is a major limitation now or under future climates, hydrologic microrefugia are likely to prove essential for species persistence, particularly for sessile species and plants. Zones of high relative water availability - mesic microenvironments - are generated by a wide array of hydrologic processes, and may be loosely coupled to climatic processes and therefore buffered from climate change. Here, we review the mechanisms that generate mesic microenvironments and their likely robustness in the face of climate change. We argue that mesic microenvironments will act as species-specific refugia only if the nature and space/time variability in water availability are compatible with the ecological requirements of a target species. We illustrate this argument with case studies drawn from California oak woodland ecosystems. We posit that identification of hydrologic refugia could form a cornerstone of climate-cognizant conservation strategies, but that this would require improved understanding of climate change effects on key hydrologic processes, including frequently cryptic processes such as groundwater flow. © 2017 John Wiley & Sons Ltd.

Interactions between chemical and climate stressors: A role for mechanistic toxicology in assessing climate change risks

USGS Publications Warehouse

Hooper, Michael J.; Ankley, Gerald T.; Cristol, Daniel A.; Maryoung, Lindley A.; Noyes, Pamela D.; Pinkerton, Kent E.

2013-01-01

Incorporation of global climate change (GCC) effects into assessments of chemical risk and injury requires integrated examinations of chemical and nonchemical stressors. Environmental variables altered by GCC (temperature, precipitation, salinity, pH) can influence the toxicokinetics of chemical absorption, distribution, metabolism, and excretion as well as toxicodynamic interactions between chemicals and target molecules. In addition, GCC challenges processes critical for coping with the external environment (water balance, thermoregulation, nutrition, and the immune, endocrine, and neurological systems), leaving organisms sensitive to even slight perturbations by chemicals when pushed to the limits of their physiological tolerance range. In simplest terms, GCC can make organisms more sensitive to chemical stressors, while alternatively, exposure to chemicals can make organisms more sensitive to GCC stressors. One challenge is to identify potential interactions between nonchemical and chemical stressors affecting key physiological processes in an organism. We employed adverse outcome pathways, constructs depicting linkages between mechanism-based molecular initiating events and impacts on individuals or populations, to assess how chemical- and climate-specific variables interact to lead to adverse outcomes. Case examples are presented for prospective scenarios, hypothesizing potential chemical–GCC interactions, and retrospective scenarios, proposing mechanisms for demonstrated chemical–climate interactions in natural populations. Understanding GCC interactions along adverse outcome pathways facilitates extrapolation between species or other levels of organization, development of hypotheses and focal areas for further research, and improved inputs for risk and resource injury assessments.

Determining the relative importance of climatic drivers on spring phenology in grassland ecosystems of semi-arid areas.

PubMed

Zhu, Likai; Meng, Jijun

2015-02-01

Understanding climate controls on spring phenology in grassland ecosystems is critically important in predicting the impacts of future climate change on grassland productivity and carbon storage. The third-generation Global Inventory Monitoring and Modeling System (GIMMS3g) normalized difference vegetation index (NDVI) data were applied to derive the start of the growing season (SOS) from 1982-2010 in grassland ecosystems of Ordos, a typical semi-arid area in China. Then, the conditional Granger causality method was utilized to quantify the directed functional connectivity between key climatic drivers and the SOS. The results show that the asymmetric Gaussian (AG) function is better in reducing noise of NDVI time series than the double logistic (DL) function within our study area. The southeastern Ordos has earlier occurrence and lower variability of the SOS, whereas the northwestern Ordos has later occurrence and higher variability of the SOS. The research also reveals that spring precipitation has stronger causal connectivity with the SOS than other climatic factors over different grassland ecosystem types. There is no statistically significant trend across the study area, while the similar pattern is observed for spring precipitation. Our study highlights the link of spring phenology with different grassland types, and the use of coupling remote sensing and econometric tools. With the dramatic increase in global change research, Granger causality method augurs well for further development and application of time-series modeling of complex social-ecological systems at the intersection of remote sensing and landscape changes.

INTERACTIONS BETWEEN CHEMICAL AND CLIMATE STRESSORS: A ROLE FOR MECHANISTIC TOXICOLOGY IN ASSESSING CLIMATE CHANGE RISKS

PubMed Central

Hooper, Michael J; Ankley, Gerald T; Cristol, Daniel A; Maryoung, Lindley A; Noyes, Pamela D; Pinkerton, Kent E

2013-01-01

Incorporation of global climate change (GCC) effects into assessments of chemical risk and injury requires integrated examinations of chemical and nonchemical stressors. Environmental variables altered by GCC (temperature, precipitation, salinity, pH) can influence the toxicokinetics of chemical absorption, distribution, metabolism, and excretion as well as toxicodynamic interactions between chemicals and target molecules. In addition, GCC challenges processes critical for coping with the external environment (water balance, thermoregulation, nutrition, and the immune, endocrine, and neurological systems), leaving organisms sensitive to even slight perturbations by chemicals when pushed to the limits of their physiological tolerance range. In simplest terms, GCC can make organisms more sensitive to chemical stressors, while alternatively, exposure to chemicals can make organisms more sensitive to GCC stressors. One challenge is to identify potential interactions between nonchemical and chemical stressors affecting key physiological processes in an organism. We employed adverse outcome pathways, constructs depicting linkages between mechanism-based molecular initiating events and impacts on individuals or populations, to assess how chemical- and climate-specific variables interact to lead to adverse outcomes. Case examples are presented for prospective scenarios, hypothesizing potential chemical–GCC interactions, and retrospective scenarios, proposing mechanisms for demonstrated chemical–climate interactions in natural populations. Understanding GCC interactions along adverse outcome pathways facilitates extrapolation between species or other levels of organization, development of hypotheses and focal areas for further research, and improved inputs for risk and resource injury assessments. Environ. Toxicol. Chem. 2013;32:32–48. © 2012 SETAC PMID:23136056

Foraminifera Models to Interrogate Ostensible Proxy-Model Discrepancies During Late Pliocene

NASA Astrophysics Data System (ADS)

Jacobs, P.; Dowsett, H. J.; de Mutsert, K.

2017-12-01

Planktic foraminifera faunal assemblages have been used in the reconstruction of past oceanic states (e.g. the Last Glacial Maximum, the mid-Piacenzian Warm Period). However these reconstruction efforts have typically relied on inverse modeling using transfer functions or the modern analog technique, which by design seek to translate foraminifera into one or two target oceanic variables, primarily sea surface temperature (SST). These reconstructed SST data have then been used to test the performance of climate models, and discrepancies have been attributed to shortcomings in climate model processes and/or boundary conditions. More recently forward proxy models or proxy system models have been used to leverage the multivariate nature of proxy relationships to their environment, and to "bring models into proxy space". Here we construct ecological models of key planktic foraminifera taxa, calibrated and validated with World Ocean Atlas (WO13) oceanographic data. Multiple modeling methods (e.g. multilayer perceptron neural networks, Mahalanobis distance, logistic regression, and maximum entropy) are investigated to ensure robust results. The resulting models are then driven by a Late Pliocene climate model simulation with biogeochemical as well as temperature variables. Similarities and differences with previous model-proxy comparisons (e.g. PlioMIP) are discussed.

Downscaling GCM Output with Genetic Programming Model

NASA Astrophysics Data System (ADS)

Shi, X.; Dibike, Y. B.; Coulibaly, P.

2004-05-01

Climate change impact studies on watershed hydrology require reliable data at appropriate spatial and temporal resolution. However, the outputs of the current global climate models (GCMs) cannot be used directly because GCM do not provide hourly or daily precipitation and temperature reliable enough for hydrological modeling. Nevertheless, we can get more reliable data corresponding to future climate scenarios derived from GCM outputs using the so called 'downscaling techniques'. This study applies Genetic Programming (GP) based technique to downscale daily precipitation and temperature values at the Chute-du-Diable basin of the Saguenay watershed in Canada. In applying GP downscaling technique, the objective is to find a relationship between the large-scale predictor variables (NCEP data which provide daily information concerning the observed large-scale state of the atmosphere) and the predictand (meteorological data which describes conditions at the site scale). The selection of the most relevant predictor variables is achieved using the Pearson's coefficient of determination ( R2) (between the large-scale predictor variables and the daily meteorological data). In this case, the period (1961 - 2000) is identified to represent the current climate condition. For the forty years of data, the first 30 years (1961-1990) are considered for calibrating the models while the remaining ten years of data (1991-2000) are used to validate those models. In general, the R2 between the predictor variables and each predictand is very low in case of precipitation compared to that of maximum and minimum temperature. Moreover, the strength of individual predictors varies for every month and for each GP grammar. Therefore, the most appropriate combination of predictors has to be chosen by looking at the output analysis of all the twelve months and the different GP grammars. During the calibration of the GP model for precipitation downscaling, in addition to the mean daily precipitation and daily precipitation variability for each month, monthly average dry and wet-spell lengths are also considered as performance criteria. For the cases of Tmax and Tmin, means and variances of these variables corresponding to each month were considered as performance criteria. The GP downscaling results show satisfactory agreement between the observed daily temperature (Tmax and Tmin) and the simulated temperature. However, the downscaling results for the daily precipitation still require some improvement - suggesting further investigation of other grammars. KEY WORDS: Climate change; GP downscaling; GCM.

Interactions of Mean Climate Change and Climate Variability on Food Security Extremes

NASA Technical Reports Server (NTRS)

Ruane, Alexander C.; McDermid, Sonali; Mavromatis, Theodoros; Hudson, Nicholas; Morales, Monica; Simmons, John; Prabodha, Agalawatte; Ahmad, Ashfaq; Ahmad, Shakeel; Ahuja, Laj R.

2015-01-01

Recognizing that climate change will affect agricultural systems both through mean changes and through shifts in climate variability and associated extreme events, we present preliminary analyses of climate impacts from a network of 1137 crop modeling sites contributed to the AgMIP Coordinated Climate-Crop Modeling Project (C3MP). At each site sensitivity tests were run according to a common protocol, which enables the fitting of crop model emulators across a range of carbon dioxide, temperature, and water (CTW) changes. C3MP can elucidate several aspects of these changes and quantify crop responses across a wide diversity of farming systems. Here we test the hypothesis that climate change and variability interact in three main ways. First, mean climate changes can affect yields across an entire time period. Second, extreme events (when they do occur) may be more sensitive to climate changes than a year with normal climate. Third, mean climate changes can alter the likelihood of climate extremes, leading to more frequent seasons with anomalies outside of the expected conditions for which management was designed. In this way, shifts in climate variability can result in an increase or reduction of mean yield, as extreme climate events tend to have lower yield than years with normal climate.C3MP maize simulations across 126 farms reveal a clear indication and quantification (as response functions) of mean climate impacts on mean yield and clearly show that mean climate changes will directly affect the variability of yield. Yield reductions from increased climate variability are not as clear as crop models tend to be less sensitive to dangers on the cool and wet extremes of climate variability, likely underestimating losses from water-logging, floods, and frosts.

Climate change and pastoralism: impacts, consequences and adaptation.

PubMed

Herrero, M; Addison, J; Bedelian, C; Carabine, E; Havlík, P; Henderson, B; Van De Steeg, J; Thornton, P K

2016-11-01

The authors discuss the main climate change impacts on pastoralist societies, including those on rangelands, livestock and other natural resources, and their extended repercussions on food security, incomes and vulnerability. The impacts of climate change on the rangelands of the globe and on the vulnerability of the people who inhabit them will be severe and diverse, and will require multiple, simultaneous responses. In higher latitudes, the removal of temperature constraints might increase pasture production and livestock productivity, but in tropical arid lands, the impacts are highly location specific, but mostly negative. The authors outline several adaptation options, ranging from implementing new technical practices and diversifying income sources to finding institutional support and introducing new market mechanisms, all of which are pivotal for enhancing the capacity of pastoralists to adapt to climate variability and change. Due to the dynamism of all the changes affecting pastoral societies, strategies that lock pastoral societies into specified development pathways could be maladaptive. Flexible and evolving combinations of practices and policies are the key to successful pastoral adaptation.

Congo Basin rainfall climatology: can we believe the climate models?

PubMed Central

Washington, Richard; James, Rachel; Pearce, Helen; Pokam, Wilfried M.; Moufouma-Okia, Wilfran

2013-01-01

The Congo Basin is one of three key convective regions on the planet which, during the transition seasons, dominates global tropical rainfall. There is little agreement as to the distribution and quantity of rainfall across the basin with datasets differing by an order of magnitude in some seasons. The location of maximum rainfall is in the far eastern sector of the basin in some datasets but the far western edge of the basin in others during March to May. There is no consistent pattern to this rainfall distribution in satellite or model datasets. Resolving these differences is difficult without ground-based data. Moisture flux nevertheless emerges as a useful variable with which to study these differences. Climate models with weak (strong) or even divergent moisture flux over the basin are dry (wet). The paper suggests an approach, via a targeted field campaign, for generating useful climate information with which to confront rainfall products and climate models. PMID:23878328

Calibration of the Reflected Solar Instrument for the Climate Absolute Radiance and Refractivity Observatory

NASA Technical Reports Server (NTRS)

Thome, Kurtis; Barnes, Robert; Baize, Rosemary; O'Connell, Joseph; Hair, Jason

2010-01-01

The Climate Absolute Radiance and Refractivity Observatory (CLARREO) plans to observe climate change trends over decadal time scales to determine the accuracy of climate projections. The project relies on spaceborne earth observations of SI-traceable variables sensitive to key decadal change parameters. The mission includes a reflected solar instrument retrieving at-sensor reflectance over the 320 to 2300 nm spectral range with 500-m spatial resolution and 100-km swath. Reflectance is obtained from the ratio of measurements of the earth s surface to those while viewing the sun relying on a calibration approach that retrieves reflectance with uncertainties less than 0.3%. The calibration is predicated on heritage hardware, reduction of sensor complexity, adherence to detector-based calibration standards, and an ability to simulate in the laboratory on-orbit sources in both size and brightness to provide the basis of a transfer to orbit of the laboratory calibration including a link to absolute solar irradiance measurements.

A 30+ Year AVHRR LAI and FAPAR Climate Data Record: Algorithm Description, Validation, and Case Study

NASA Technical Reports Server (NTRS)

Claverie, Martin; Matthews, Jessica L.; Vermote, Eric F.; Justice, Christopher O.

2016-01-01

In- land surface models, which are used to evaluate the role of vegetation in the context ofglobal climate change and variability, LAI and FAPAR play a key role, specifically with respect to thecarbon and water cycles. The AVHRR-based LAIFAPAR dataset offers daily temporal resolution,an improvement over previous products. This climate data record is based on a carefully calibratedand corrected land surface reflectance dataset to provide a high-quality, consistent time-series suitablefor climate studies. It spans from mid-1981 to the present. Further, this operational dataset is availablein near real-time allowing use for monitoring purposes. The algorithm relies on artificial neuralnetworks calibrated using the MODIS LAI/FAPAR dataset. Evaluation based on cross-comparisonwith MODIS products and in situ data show the dataset is consistent and reliable with overalluncertainties of 1.03 and 0.15 for LAI and FAPAR, respectively. However, a clear saturation effect isobserved in the broadleaf forest biomes with high LAI (greater than 4.5) and FAPAR (greater than 0.8) values.

Seasonal Drought Prediction: Advances, Challenges, and Future Prospects

NASA Astrophysics Data System (ADS)

Hao, Zengchao; Singh, Vijay P.; Xia, Youlong

2018-03-01

Drought prediction is of critical importance to early warning for drought managements. This review provides a synthesis of drought prediction based on statistical, dynamical, and hybrid methods. Statistical drought prediction is achieved by modeling the relationship between drought indices of interest and a suite of potential predictors, including large-scale climate indices, local climate variables, and land initial conditions. Dynamical meteorological drought prediction relies on seasonal climate forecast from general circulation models (GCMs), which can be employed to drive hydrological models for agricultural and hydrological drought prediction with the predictability determined by both climate forcings and initial conditions. Challenges still exist in drought prediction at long lead time and under a changing environment resulting from natural and anthropogenic factors. Future research prospects to improve drought prediction include, but are not limited to, high-quality data assimilation, improved model development with key processes related to drought occurrence, optimal ensemble forecast to select or weight ensembles, and hybrid drought prediction to merge statistical and dynamical forecasts.

Productivity benefits of warming at regional scale could be offset by detrimental impacts on site level hydrology.

PubMed

Zeng, Qing; Zhang, Yamian; Wen, Li; Li, Zhaxijie; Duo, Hairui; Lei, Guangchun

2017-11-09

Climate change affects the distribution and persistence of wildlife. Broad scale studies have demonstrated that climate change shifts the geographic ranges and phenology of species. These findings are influential for making high level strategies but not practical enough to guide site specific management. In this study, we explored the environment factors affecting the population of Bar-headed Goose in the key breeding site of Qinghai using generalized additive mixed model (GAMM). Our results showed that 1) there were significant increasing trends in climate variables and river flows to the Qinghai Lake; 2) NDVI in the sites decreased significantly despite the regional positive trend induced by the warmer and wetter climate; 3) NDVI at site scale was negatively correlated to lake water level; and 4) the abundance of Bar-headed Goose decreased significantly at all sites. While the abundance was positively related to NDVI at breeding sites, the GAMM revealed an opposite relationship at foraging areas. Our findings demonstrated the multi-facet effects of climate change on population dynamics; and the effect at global/regional scale could be complicated by site level factors.

The Soft Underbelly of System Change: The Role of Leadership and Organizational Climate in Turnover during Statewide Behavioral Health Reform

PubMed Central

Aarons, Gregory A.; Sommerfeld, David H.; Willging, Cathleen E.

2011-01-01

This study examined leadership, organizational climate, staff turnover intentions, and voluntary turnover during a large-scale statewide behavioral health system reform. The initial data collection occurred nine months after initiation of the reform with a follow-up round of data collected 18 months later. A self-administered structured assessment was completed by 190 participants (administrators, support staff, providers) employed by 14 agencies. Key variables included leadership, organizational climate, turnover intentions, turnover, and reform-related financial stress (“low” versus “high”) experienced by the agencies. Analyses revealed that positive leadership was related to a stronger empowering climate in both high and low stress agencies. However, the association between more positive leadership and lower demoralizing climate was evident only in high stress agencies. For both types of agencies empowering climate was negatively associated with turnover intentions, and demoralizing climate was associated with stronger turnover intentions. Turnover intentions were positively associated with voluntary turnover. Results suggest that strong leadership is particularly important in times of system and organizational change and may reduce poor climate associated with turnover intentions and turnover. Leadership and organizational context should be addressed to retain staff during these periods of systemic change. PMID:22229021

Climate Impact of Solar Variability

NASA Technical Reports Server (NTRS)

Schatten, Kenneth H. (Editor); Arking, Albert (Editor)

1990-01-01

The conference on The Climate Impact of Solar Variability, was held at Goddard Space Flight Center from April 24 to 27, 1990. In recent years they developed a renewed interest in the potential effects of increasing greenhouse gases on climate. Carbon dioxide, methane, nitrous oxide, and the chlorofluorocarbons have been increasing at rates that could significantly change climate. There is considerable uncertainty over the magnitude of this anthropogenic change. The climate system is very complex, with feedback processes that are not fully understood. Moreover, there are two sources of natural climate variability (volcanic aerosols and solar variability) added to the anthropogenic changes which may confuse our interpretation of the observed temperature record. Thus, if we could understand the climatic impact of the natural variability, it would aid our interpretation and understanding of man-made climate changes.

Spatial structure of monthly rainfall measurements average over 25 years and trends of the hourly variability of a current rainy day in Rwanda.

NASA Astrophysics Data System (ADS)

Nduwayezu, Emmanuel; Kanevski, Mikhail; Jaboyedoff, Michel

2013-04-01

Climate plays a vital role in a wide range of socio-economic activities of most nations particularly of developing countries. Climate (rainfall) plays a central role in agriculture which is the main stay of the Rwandan economy and community livelihood and activities. The majority of the Rwandan population (81,1% in 2010) relies on rain fed agriculture for their livelihoods, and the impacts of variability in climate patterns are already being felt. Climate-related events like heavy rainfall or too little rainfall are becoming more frequent and are impacting on human wellbeing.The torrential rainfall that occurs every year in Rwanda could disturb the circulation for many days, damages houses, infrastructures and causes heavy economic losses and deaths. Four rainfall seasons have been identified, corresponding to the four thermal Earth ones in the south hemisphere: the normal season (summer), the rainy season (autumn), the dry season (winter) and the normo-rainy season (spring). Globally, the spatial rainfall decreasing from West to East, especially in October (spring) and February (summer) suggests an «Atlantic monsoon influence» while the homogeneous spatial rainfall distribution suggests an «Inter-tropical front» mechanism. What is the hourly variability in this mountainous area? Is there any correlation with the identified zones of the monthly average series (from 1965 to 1990 established by the Rwandan meteorological services)? Where could we have hazards with several consecutive rainy days (using forecasted datas from the Norwegian Meteorological Institute)? Spatio-temporal analysis allows for identifying and explaining large-scale anomalies which are useful for understanding hydrological characteristics and subsequently predicting these hydrological events. The objective of our current research (Rainfall variability) is to proceed to an evaluation of the potential rainfall risk by applying advanced geospatial modelling tools in Rwanda: geostatistical predictions and simulations, machine learning algorithm (different types of neural networks) and GIS. Hybrid models - mixing geostatistics and machine learning, will be applied to study spatial non-stationarity of rainfall fields. The research will include rainfalls variability mapping and probabilistic analyses of extreme events. Key words: rainfall variability, Rwanda, extreme event, model, mapping, geostatistics.

The Copernicus Climate Change Service (C3S): Open Access to a Climate Data Store

NASA Astrophysics Data System (ADS)

Thepaut, Jean-Noel; Dee, Dick

2016-04-01

In November 2014, The European Centre for Medium-range Weather Forecasts (ECMWF) signed an agreement with the European Commission to deliver two of the Copernicus Earth Observation Programme Services on the Commission's behalf. The ECMWF delivered services - the Copernicus Climate Change Service (C3S) and Atmosphere Monitoring Service (CAMS) - will bring a consistent standard to how we monitor and predict atmospheric conditions and climate change. They will maximise the potential of past, current and future earth observations - ground, ocean, airborne, satellite - and analyse these to monitor and predict atmospheric conditions and in the future, climate change. With the wealth of free and open data that the services provide, they will help business users to assess the impact of their business decisions and make informed choices, delivering a more energy efficient and climate aware economy. These sound investment decisions now will not only stimulate growth in the short term, but reduce the impact of climate change on the economy and society in the future. C3S is in its proof of concept phase and through its Climate Data Store will provide • global and regional climate data reanalyses; • multi-model seasonal forecasts; • customisable visual data to enable examination of wide range of scenarios and model the impact of changes; • access to all the underlying data, including climate data records from various satellite and in-situ observations. In addition, C3S will provide key indicators on climate change drivers (such as carbon dioxide) and impacts (such as reducing glaciers). The aim of these indicators will be to support European adaptation and mitigation policies in a number of economic sectors. At the heart of the Service is the provision of open access to a one stop shop (the Climate Data Store) of climate data and modelling, analysing more than 20 Essential Climate Variables to build a global picture of our past, present and future climate and developing customisable climate indicators for key economic sectors, such as energy, water management, agriculture, insurance, health… This talk will focus on the Climate Data Store facility, designed as a distributed system, providing improved access to existing datasets though a unified web interface. This service will accommodate the needs of the highly diverse set of users, from policy makers to expert practitioners and scientists.

Simulating the Past, Present and Future of the Upper Troposphere and Lower Stratosphere

NASA Astrophysics Data System (ADS)

Gettelman, Andrew; Hegglin, Michaela

2010-05-01

A comprehensive assessment of coupled chemistry climate model (CCM) performance in the upper troposphere and lower stratosphere has been conducted with 18 models. Both qualitative and quantitative comparisons of model representation of UTLS dynamical, radiative and chemical structure have been conducted, using a collection of quantitative grading techniques. The models are able to reproduce the observed climatology of dynamical, radiative and chemical structure in the tropical and extratropical UTLS, despite relatively coarse vertical and horizontal resolution. Diagnostics of the Tropical Tropopause Layer (TTL), Tropopause Inversion Layer (TIL) and Extra-tropical Transition Layer (ExTL) are analyzed. The results provide new insight into the key processes that govern the dynamics and transport in the tropics and extra-tropicsa. The presentation will explain how models are able to reproduce key features of the UTLS, what features they do not reproduce, and why. Model trends over the historical period are also assessed and interannual variability is included in the metrics. Finally, key trends in the UTLS for the future with a given halogen and greenhouse gas scenario are presented, indicating significant changes in tropopause height and temperature, as well as UTLS ozone concentrations in the 21st century due to climate change and ozone recovery.

Climate change and viticulture in Mediterranean climates: the complex response of socio-ecosystems. A comparative case study from France and Australia (1955-2040)

NASA Astrophysics Data System (ADS)

Lereboullet, A.-L.; Beltrando, G.; Bardsley, D. K.

2012-04-01

The wine industry is very sensitive to extreme weather events, especially to temperatures above 35°C and drought. In a context of global climate change, Mediterranean climate regions are predicted to experience higher variability in rainfall and temperatures and an increased occurrence of extreme weather events. Some viticultural systems could be particularly at risk in those regions, considering their marginal position in the growth climatic range of Vitis vinifera, the long commercial lifespan of a vineyard, the high added-value of wine and the volatile nature of global markets. The wine industry, like other agricultural systems, is inserted in complex networks of climatic and non-climatic (other physical, economical, social and legislative) components, with constant feedbacks. We use a socio-ecosystem approach to analyse the adaptation of two Mediterranean viticultural systems to recent and future increase of extreme weather events. The present analysis focuses on two wine regions with a hot-summer Mediterranean climate (CSb type in the Köppen classification): Côtes-du-Roussillon in southern France and McLaren Vale in southern Australia. Using climate data from two synoptic weather stations, Perpignan (France) and Adelaide (Australia), with time series running from 1955 to 2010, we highlight changes in rainfall patterns and an increase in the number of days with Tx >35°c since the last three decades in both regions. Climate models (DRIAS project data for France and CSIRO Mk3.5 for Australia) project similar trends in the future. To date, very few projects have focused on an international comparison of the adaptive capacity of viticultural systems to climate change with a holistic approach. Here, the analysis of climate data was complemented by twenty in-depth semi-structured interviews with key actors of the two regional wine industries, in order to analyse adaptation strategies put in place regarding recent climate evolution. This mixed-methods approach allows for a comprehensive assessment of adaptation capacity of the two viticultural systems to future climate change. The strategies of grape growers and wine producers focus on maintaining optimal yields and a constant wine style adapted to markets in a variable and uncertain climate. Their implementation and efficiency depend strongly on non-climatic factors. Thus, adaptation capacity to recent and future climate change depends strongly on adaptation to other non-climatic changes.

Climate-driven vital rates do not always mean climate-driven population.

PubMed

Tavecchia, Giacomo; Tenan, Simone; Pradel, Roger; Igual, José-Manuel; Genovart, Meritxell; Oro, Daniel

2016-12-01

Current climatic changes have increased the need to forecast population responses to climate variability. A common approach to address this question is through models that project current population state using the functional relationship between demographic rates and climatic variables. We argue that this approach can lead to erroneous conclusions when interpopulation dispersal is not considered. We found that immigration can release the population from climate-driven trajectories even when local vital rates are climate dependent. We illustrated this using individual-based data on a trans-equatorial migratory seabird, the Scopoli's shearwater Calonectris diomedea, in which the variation of vital rates has been associated with large-scale climatic indices. We compared the population annual growth rate λ i , estimated using local climate-driven parameters with ρ i , a population growth rate directly estimated from individual information and that accounts for immigration. While λ i varied as a function of climatic variables, reflecting the climate-dependent parameters, ρ i did not, indicating that dispersal decouples the relationship between population growth and climate variables from that between climatic variables and vital rates. Our results suggest caution when assessing demographic effects of climatic variability especially in open populations for very mobile organisms such as fish, marine mammals, bats, or birds. When a population model cannot be validated or it is not detailed enough, ignoring immigration might lead to misleading climate-driven projections. © 2016 John Wiley & Sons Ltd.

Informing Adaptation Decisions: What Do We Need to Know and What Do We Need to Do?

NASA Astrophysics Data System (ADS)

Pulwarty, R. S.; Webb, R. S.

2014-12-01

The demand for improved climate knowledge and information is well documented. As noted in the IPCC Reports (SREX, AR5) and other assessments, this demand has increased pressure for better information to support planning under changing rates of extremes event occurrence. This demand has focused on mechanisms used to respond to past variability and change, including, integrated resource management (watersheds, coasts), infrastructure design, information systems, technological optimization, financial risk management, and behavioral and institutional change. Climate inputs range from static site design statistics (return periods) to dynamic, emergent thresholds and transitions preceded by steep response curves and punctuated equilibria. Tradeoffs are evident in the use of risk-based anticipatory strategies vs. resilience measures. In such settings, annual decision calendars for operational requirements can confound adaptation expectations. Key knowledge assessment questions include: (1) How predictable are potential impacts of events in the context of other stressors, (2) how is action to anticipate such impacts informed, and (3) How often should criteria for "robustness" be reconsidered? To illustrate, we will discuss the climate information needs and uses for two areas of concern for both short and long-term risks (i) climate and disaster risk financing, and (ii) watershed management. The presentation will focus on the climate information needed for (1) improved monitoring, modeling and methods for understanding and analyzing exposure risks, (2) generating risk profiles, (3) developing information systems and scenarios for critical thresholds across climate time and space scales, (4) embedding annual decision calendars in the context of longer-term risk management, (5) gaming experiments to show the net benefits of new information. We will conclude with a discussion of the essential climate variables needed to implement services-delivery and development efforts such as the Global Framework for Climate Services and the Pilot Program on Climate Resilience.

Holocene climate variability in the western Mediterranean through a multiproxy analysis from Padul peat bog (Sierra Nevada, Spain)

NASA Astrophysics Data System (ADS)

Ramos-Román, María J.; Jiménez-Moreno, Gonzalo; Camuera, Jon; García-Alix, Antonio; Anderson, R. Scott; Jiménez-Espejo, Francisco J.; Sachse, Dirk

2017-04-01

The Iberian Peninsula, located in the Mediterranean area, is an interesting location for paleoclimate studies due to its geographic situation between arid and humid climates. Sediments from peat bogs and lakes from Sierra Nevada, in southeastern Iberian Peninsula, have been very informative in terms of how vegetation and wetland environments were impacted by Holocene climate change. These studies are essential if we want to understand the past climate change in the area, which is the key to identify the possible environmental response of the Sierra Nevada ecosystems to future climate scenarios. Padul basin, located in the southwest of the Sierra Nevada mountain range, contains a ca. 100 m-thick peat bog sedimentary sequence that was deposited during the past 1 Ma making this area interesting for paleoenvironmental and paleoclimatic reconstructions. A new 43 m-long sedimentary record has recently been retrieved from the Padul peat bog. In this study we have developed a multiproxy analysis of the Holocene part of the Padul-15-05 core including pollen analysis, XRF-core scanner, magnetic susceptibility and organic geochemistry, supported by an age control based on AMS radiocarbon dates, providing with information about vegetation and climate variability during the past 9.9 cal ka BP. This multiproxy reconstruction of the Padul-15-05 evidences the Mediterranean as a sensitive area with respect to global-scale climate system, showing relevant climate episodes such as the ca. 8, 7.5, 6.5 and 5.5 cal ka BP events during the early and middle Holocene. The trend to aridification to the late Holocene is interrupted by more arid and humid periods as the Iberian Roman Humid Period (from ca. 3 to 1.6 cal ka BP), the Dark Ages (from ca. 1.5 to 1.1 cal ka BP), the Medieval Climate Anomaly (from ca. 1.1 to 1.3 cal ka BP) and the Little Ice Age period (from ca. 500 to 100 cal yr BP).

Interplay between the Westerlies and Asian monsoon recorded in Lake Qinghai sediments since 32 ka

PubMed Central

An, Zhisheng; Colman, Steven M.; Zhou, Weijian; Li, Xiaoqiang; Brown, Eric T.; Jull, A. J. Timothy; Cai, Yanjun; Huang, Yongsong; Lu, Xuefeng; Chang, Hong; Song, Yougui; Sun, Youbin; Xu, Hai; Liu, Weiguo; Jin, Zhangdong; Liu, Xiaodong; Cheng, Peng; Liu, Yu; Ai, Li; Li, Xiangzhong; Liu, Xiuju; Yan, Libin; Shi, Zhengguo; Wang, Xulong; Wu, Feng; Qiang, Xiaoke; Dong, Jibao; Lu, Fengyan; Xu, Xinwen

2012-01-01

Two atmospheric circulation systems, the mid-latitude Westerlies and the Asian summer monsoon (ASM), play key roles in northern-hemisphere climatic changes. However, the variability of the Westerlies in Asia and their relationship to the ASM remain unclear. Here, we present the longest and highest-resolution drill core from Lake Qinghai on the northeastern Tibetan Plateau (TP), which uniquely records the variability of both the Westerlies and the ASM since 32 ka, reflecting the interplay of these two systems. These records document the anti-phase relationship of the Westerlies and the ASM for both glacial-interglacial and glacial millennial timescales. During the last glaciation, the influence of the Westerlies dominated; prominent dust-rich intervals, correlated with Heinrich events, reflect intensified Westerlies linked to northern high-latitude climate. During the Holocene, the dominant ASM circulation, punctuated by weak events, indicates linkages of the ASM to orbital forcing, North Atlantic abrupt events, and perhaps solar activity changes. PMID:22943005

The role of Amundsen-Bellingshausen Sea anticyclonic circulation in forcing marine air intrusions into West Antarctica

NASA Astrophysics Data System (ADS)

Emanuelsson, B. Daniel; Bertler, Nancy A. N.; Neff, Peter D.; Renwick, James A.; Markle, Bradley R.; Baisden, W. Troy; Keller, Elizabeth D.

2018-01-01

Persistent positive 500-hPa geopotential height anomalies from the ECMWF ERA-Interim reanalysis are used to quantify Amundsen-Bellingshausen Sea (ABS) anticyclonic event occurrences associated with precipitation in West Antarctica (WA). We demonstrate that multi-day (minimum 3-day duration) anticyclones play a key role in the ABS by dynamically inducing meridional transport, which is associated with heat and moisture advection into WA. This affects surface climate variability and trends, precipitation rates and thus WA ice sheet surface mass balance. We show that the snow accumulation record from the Roosevelt Island Climate Evolution (RICE) ice core reflects interannual variability of blocking and geopotential height conditions in the ABS/Ross Sea region. Furthermore, our analysis shows that larger precipitation events are related to enhanced anticyclonic circulation and meridional winds, which cause pronounced dipole patterns in air temperature anomalies and sea ice concentrations between the eastern Ross Sea and the Bellingshausen Sea/Weddell Sea, as well as between the eastern and western Ross Sea.

Is the residual vertical velocity a good proxy for stratosphere-troposphere exchange of ozone?

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

Hsu, Juno; Prather, Michael J.

Stratosphere-troposphere exchange (STE) of ozone (O 3) is key in the budget of tropospheric O 3, in turn affecting climate forcing and global air quality. We compare three commonly used diagnostics meant to quantify cross-tropopause O 3 fluxes with a Chemistry-Transport Model driven by two distinct European Centre forecast fields. Here, our reference case calculates accurate, geographically resolved net transport across an isosurface in artificial tracer e90 representing the tropopause. Hemispheric fluxes derived from the ozone mass budget of the lowermost stratosphere yield similar results. Use of the Brewer-Dobson residual vertical velocity as a scaled proxy for ozone flux, however,more » fails to capture the interannual variability. Thus, the common notion that the strength of stratospheric overturning circulation is a good measure for global STE does not apply to O 3. Finally, climatic variability in the modeled O 3 flux needs to be diagnosed directly rather than indirectly through the overturning circulation.« less

Is the residual vertical velocity a good proxy for stratosphere-troposphere exchange of ozone?

DOE PAGES

Hsu, Juno; Prather, Michael J.

2014-12-20

Stratosphere-troposphere exchange (STE) of ozone (O 3) is key in the budget of tropospheric O 3, in turn affecting climate forcing and global air quality. We compare three commonly used diagnostics meant to quantify cross-tropopause O 3 fluxes with a Chemistry-Transport Model driven by two distinct European Centre forecast fields. Here, our reference case calculates accurate, geographically resolved net transport across an isosurface in artificial tracer e90 representing the tropopause. Hemispheric fluxes derived from the ozone mass budget of the lowermost stratosphere yield similar results. Use of the Brewer-Dobson residual vertical velocity as a scaled proxy for ozone flux, however,more » fails to capture the interannual variability. Thus, the common notion that the strength of stratospheric overturning circulation is a good measure for global STE does not apply to O 3. Finally, climatic variability in the modeled O 3 flux needs to be diagnosed directly rather than indirectly through the overturning circulation.« less

Climate change and habitat fragmentation drive the occurrence of Borrelia burgdorferi, the agent of Lyme disease, at the northeastern limit of its distribution

PubMed Central

Simon, Julie A; Marrotte, Robby R; Desrosiers, Nathalie; Fiset, Jessica; Gaitan, Jorge; Gonzalez, Andrew; Koffi, Jules K; Lapointe, Francois-Joseph; Leighton, Patrick A; Lindsay, Lindsay R; Logan, Travis; Milord, Francois; Ogden, Nicholas H; Rogic, Anita; Roy-Dufresne, Emilie; Suter, Daniel; Tessier, Nathalie; Millien, Virginie

2014-01-01

Lyme borreliosis is rapidly emerging in Canada, and climate change is likely a key driver of the northern spread of the disease in North America. We used field and modeling approaches to predict the risk of occurrence of Borrelia burgdorferi, the bacteria causing Lyme disease in North America. We combined climatic and landscape variables to model the current and future (2050) potential distribution of the black-legged tick and the white-footed mouse at the northeastern range limit of Lyme disease and estimated a risk index for B. burgdorferi from these distributions. The risk index was mostly constrained by the distribution of the white-footed mouse, driven by winter climatic conditions. The next factor contributing to the risk index was the distribution of the black-legged tick, estimated from the temperature. Landscape variables such as forest habitat and connectivity contributed little to the risk index. We predict a further northern expansion of B. burgdorferi of approximately 250–500 km by 2050 – a rate of 3.5–11 km per year – and identify areas of rapid rise in the risk of occurrence of B. burgdorferi. Our results will improve understanding of the spread of Lyme disease and inform management strategies at the most northern limit of its distribution. PMID:25469157

Multi-scale Drivers of Variations in Atmospheric Evaporative Demand Based on Observations and Physically-based Modeling

NASA Astrophysics Data System (ADS)

Peng, L.; Sheffield, J.; Li, D.

2015-12-01

Evapotranspiration (ET) is a key link between the availability of water resources and climate change and climate variability. Variability of ET has important environmental and socioeconomic implications for managing hydrological hazards, food and energy production. Although there have been many observational and modeling studies of ET, how ET has varied and the drivers of the variations at different temporal scales remain elusive. Much of the uncertainty comes from the atmospheric evaporative demand (AED), which is the combined effect of radiative and aerodynamic controls. The inconsistencies among modeled AED estimates and the limited observational data may originate from multiple sources including the limited time span and uncertainties in the data. To fully investigate and untangle the intertwined drivers of AED, we present a spectrum analysis to identify key controls of AED across multiple temporal scales. We use long-term records of observed pan evaporation for 1961-2006 from 317 weather stations across China and physically-based model estimates of potential evapotranspiration (PET). The model estimates are based on surface meteorology and radiation derived from reanalysis, satellite retrievals and station data. Our analyses show that temperature plays a dominant role in regulating variability of AED at the inter-annual scale. At the monthly and seasonal scales, the primary control of AED shifts from radiation in humid regions to humidity in dry regions. Unlike many studies focusing on the spatial pattern of ET drivers based on a traditional supply and demand framework, this study underlines the importance of temporal scales when discussing controls of ET variations.

Tropical Pacific variability as a key pacemaker of the global warming staircase

NASA Astrophysics Data System (ADS)

Kosaka, Y.; Xie, S. P.

2016-12-01

Global-mean surface temperature (GMST) has increased since the 19th century with notable interdecadal accelerations and slowdowns, forming the global-warming "staircase". The last step of this staircase is the surface warming slowdown since the late 1990s, for which the transition of the Interdecadal Pacific Oscillation (IPO) from a positive to negative state has been suggested as the leading mechanism. To examine the role of IPO in the entire warming staircase, a long pacemaker experiment is performed with a coupled climate model where tropical Pacific sea surface temperatures are forced to follow the observed evolution since the late 19th century. The pacemaker experiment successfully reproduces the staircase-like global warming remarkably well since 1900. Without the tropical Pacific effect, the same model produces a continual warming from the 1900s to the 1960 followed by rapid warming. The successful reproduction identifies the tropical Pacific decadal variability as a key pacemaker of the GMST staircase. We further propose a method to remove internal variability from observed GMST changes for real-time monitoring of anthropogenic warming.

The carbon cycle in the Australian Community Climate and Earth System Simulator (ACCESS-ESM1) - Part 1: Model description and pre-industrial simulation

NASA Astrophysics Data System (ADS)

Law, Rachel M.; Ziehn, Tilo; Matear, Richard J.; Lenton, Andrew; Chamberlain, Matthew A.; Stevens, Lauren E.; Wang, Ying-Ping; Srbinovsky, Jhan; Bi, Daohua; Yan, Hailin; Vohralik, Peter F.

2017-07-01

Earth system models (ESMs) that incorporate carbon-climate feedbacks represent the present state of the art in climate modelling. Here, we describe the Australian Community Climate and Earth System Simulator (ACCESS)-ESM1, which comprises atmosphere (UM7.3), land (CABLE), ocean (MOM4p1), and sea-ice (CICE4.1) components with OASIS-MCT coupling, to which ocean and land carbon modules have been added. The land carbon model (as part of CABLE) can optionally include both nitrogen and phosphorous limitation on the land carbon uptake. The ocean carbon model (WOMBAT, added to MOM) simulates the evolution of phosphate, oxygen, dissolved inorganic carbon, alkalinity and iron with one class of phytoplankton and zooplankton. We perform multi-centennial pre-industrial simulations with a fixed atmospheric CO2 concentration and different land carbon model configurations (prescribed or prognostic leaf area index). We evaluate the equilibration of the carbon cycle and present the spatial and temporal variability in key carbon exchanges. Simulating leaf area index results in a slight warming of the atmosphere relative to the prescribed leaf area index case. Seasonal and interannual variations in land carbon exchange are sensitive to whether leaf area index is simulated, with interannual variations driven by variability in precipitation and temperature. We find that the response of the ocean carbon cycle shows reasonable agreement with observations. While our model overestimates surface phosphate values, the global primary productivity agrees well with observations. Our analysis highlights some deficiencies inherent in the carbon models and where the carbon simulation is negatively impacted by known biases in the underlying physical model and consequent limits on the applicability of this model version. We conclude the study with a brief discussion of key developments required to further improve the realism of our model simulation.

How resilient are ecosystems in adapting to climate variability

NASA Astrophysics Data System (ADS)

Savenije, Hubert H. G.

2015-04-01

The conclusion often drawn in the media is that ecosystems may perish as a result of climate change. Although climatic trends may indeed lead to shifts in ecosystem composition, the challenge to adjust to climatic variability - even if there is no trend - is larger, particularly in semi-arid or topical climates where climatic variability is large compared to temperate climates. How do ecosystems buffer for climatic variability? The most powerful mechanism is to invest in root zone storage capacity, so as to guarantee access to water and nutrients during period of drought. This investment comes at a cost of having less energy available to invest in growth or formation of fruits. Ecosystems are expected to create sufficient buffer to overcome critical periods of drought, but not more than is necessary to survive or reproduce. Based on this concept, a methodology has been developed to estimate ecosystem root zone storage capacity at local, regional and global scale. These estimates correspond well with estimates made by combining soil and ecosystem information, but are more accurate and more detailed. The methodology shows that ecosystems have intrinsic capacity to adjust to climatic variability and hence have a high resilience to both climatic variability and climatic trends.

North Atlantic summers have warmed more than winters since 1353, and the response of marine zooplankton.

PubMed

Kamenos, Nicholas A

2010-12-28

Modeling and measurements show that Atlantic marine temperatures are rising; however, the low temporal resolution of models and restricted spatial resolution of measurements (i) mask regional details critical for determining the rate and extent of climate variability, and (ii) prevent robust determination of climatic impacts on marine ecosystems. To address both issues for the North East Atlantic, a fortnightly resolution marine climate record from 1353-2006 was constructed for shallow inshore waters and compared to changes in marine zooplankton abundance. For the first time summer marine temperatures are shown to have increased nearly twice as much as winter temperatures since 1353. Additional climatic instability began in 1700 characterized by ∼5-65 year climate oscillations that appear to be a recent phenomenon. Enhanced summer-specific warming reduced the abundance of the copepod Calanus finmarchicus, a key food item of cod, and led to significantly lower projected abundances by 2040 than at present. The faster increase of summer marine temperatures has implications for climate projections and affects abundance, and thus biomass, near the base of the marine food web with potentially significant feedback effects for marine food security.

NOAA Climate Information and Tools for Decision Support Services

NASA Astrophysics Data System (ADS)

Timofeyeva, M. M.; Higgins, W.; Strager, C.; Horsfall, F. M.

2013-12-01

NOAA is an active participant of the Global Framework for Climate Services (GFCS) contributing data, information, analytical capabilities, forecasts, and decision support services to the Climate Services Partnership (CSP). These contributions emerge from NOAA's own climate services, which have evolved to respond to the urgent and growing need for reliable, trusted, transparent, and timely climate information across all sectors of the U.S. economy. Climate services not only enhance development opportunities in many regions, but also reduce vulnerability to climate change around the world. The NOAA contribution lies within the NOAA Climate Goal mission, which is focusing its efforts on four key climate priority areas: water, extremes, coastal inundation, and marine ecosystems. In order to make progress in these areas, NOAA is exploiting its fundamental capabilities, including foundational research to advance understanding of the Earth system, observations to preserve and build the climate data record and monitor changes in climate conditions, climate models to predict and project future climate across space and time scales, and the development and delivery of decision support services focused on risk management. NOAA's National Weather Services (NWS) is moving toward provision of Decision Support Services (DSS) as a part of the Roadmap on the way to achieving a Weather Ready National (WRN) strategy. Both short-term and long-term weather, water, and climate information are critical for DSS and emergency services and have been integrated into NWS in the form of pilot projects run by National and Regional Operations Centers (NOC and ROCs respectively) as well as several local offices. Local offices with pilot projects have been focusing their efforts on provision of timely and actionable guidance for specific tasks such as DSS in support of Coastal Environments and Integrated Environmental Studies. Climate information in DSS extends the concept of climate services to provision of information that will help guide long-term preparedness for severe weather events and extreme conditions as well as climate variability and change GFCS recently summarized examples of existing initiatives to advance provision of climate services in the 2012 publication Climate ExChange. In this publication, NWS introduced the new Local Climate Analysis Tool (LCAT), a tool that is used to conduct local climate studies that are needed to create efficient and reliable guidance for DSS. LCAT allows for analyzing trends in local climate variables and identifying local impacts of climate variability (e.g., ENSO) on weather and water conditions. In addition to LCAT, NWS, working in partnership with the North East Regional Climate center, released xmACIS version 2, a climate data mining tool, for NWS field operations. During this talk we will demonstrate LCAT and xmACIS as well as outline several examples of their application to DSS and its potential use for achieving GFCS goals. The examples include LCAT-based temperature analysis for energy decisions, guidance on weather and water events leading to increased algal blooms and red tide months in advance, local climate sensitivities to droughts, probabilities of hot/cold conditions and their potential impacts on agriculture and fish kills or fish stress.

Persistent drying in the tropics linked to natural forcing.

PubMed

Winter, Amos; Zanchettin, Davide; Miller, Thomas; Kushnir, Yochanan; Black, David; Lohmann, Gerrit; Burnett, Allison; Haug, Gerald H; Estrella-Martínez, Juan; Breitenbach, Sebastian F M; Beaufort, Luc; Rubino, Angelo; Cheng, Hai

2015-07-14

Approximately half of the world's population lives in the tropics, and future changes in the hydrological cycle will impact not just the freshwater supplies but also energy production in areas dependent upon hydroelectric power. It is vital that we understand the mechanisms/processes that affect tropical precipitation and the eventual surface hydrological response to better assess projected future regional precipitation trends and variability. Paleo-climate proxies are well suited for this purpose as they provide long time series that pre-date and complement the present, often short instrumental observations. Here we present paleo-precipitation data from a speleothem located in Mesoamerica that reveal large multi-decadal declines in regional precipitation, whose onset coincides with clusters of large volcanic eruptions during the nineteenth and twentieth centuries. This reconstruction provides new independent evidence of long-lasting volcanic effects on climate and elucidates key aspects of the causal chain of physical processes determining the tropical climate response to global radiative forcing.

Uncertainty in future agro-climate projections in the United States and benefits of greenhouse gas mitigation

DOE PAGES

Monier, Erwan; Xu, Liyi; Snyder, Richard

2016-04-26

Scientific challenges exist on how to extract information from the wide range of projected impacts simulated by crop models driven by climate ensembles. A stronger focus is required to understand and identify the mechanisms and drivers of projected changes in crop yield. In this study, we investigate the robustness of future projections of five metrics relevant to agriculture stakeholders (accumulated frost days, dry days, growing season length, plant heat stress and start of field operations). We use a large ensemble of climate simulations by the MIT IGSM-CAM integrated assessment model that accounts for the uncertainty associated with different emissions scenarios,more » climate sensitivities, and representations of natural variability. By the end of the century, the US is projected to experience fewer frosts, a longer growing season, more heat stress and an earlier start of field operations-although the magnitude and even the sign of these changes vary greatly by regions. Projected changes in dry days are shown not to be robust. We highlight the important role of natural variability, in particular for changes in dry days (a precipitation-related index) and heat stress (a threshold index). The wide range of our projections compares well the CMIP5 multi-model ensemble, especially for temperature-related indices. This suggests that using a single climate model that accounts for key sources of uncertainty can provide an efficient and complementary framework to the more common approach of multi-model ensembles. We also show that greenhouse gas mitigation has the potential to significantly reduce adverse effects (heat stress, risks of pest and disease) of climate change on agriculture, while also curtailing potentially beneficial impacts (earlier planting, possibility for multiple cropping). A major benefit of climate mitigation is potentially preventing changes in several indices to emerge from the noise of natural variability, even by 2100. This has major implications considering that any significant climate change impacts on crop yield would result in nation-wide changes in the agriculture sector. Lastly, we argue that the analysis of agro-climate indices should more often complement crop model projections, as they can provide valuable information to better understand the drivers of changes in crop yield and production and thus better inform adaptation decisions.« less

Uncertainty in future agro-climate projections in the United States and benefits of greenhouse gas mitigation

NASA Astrophysics Data System (ADS)

Monier, Erwan; Xu, Liyi; Snyder, Richard

2016-05-01

Scientific challenges exist on how to extract information from the wide range of projected impacts simulated by crop models driven by climate ensembles. A stronger focus is required to understand and identify the mechanisms and drivers of projected changes in crop yield. In this study, we investigate the robustness of future projections of five metrics relevant to agriculture stakeholders (accumulated frost days, dry days, growing season length, plant heat stress and start of field operations). We use a large ensemble of climate simulations by the MIT IGSM-CAM integrated assessment model that accounts for the uncertainty associated with different emissions scenarios, climate sensitivities, and representations of natural variability. By the end of the century, the US is projected to experience fewer frosts, a longer growing season, more heat stress and an earlier start of field operations—although the magnitude and even the sign of these changes vary greatly by regions. Projected changes in dry days are shown not to be robust. We highlight the important role of natural variability, in particular for changes in dry days (a precipitation-related index) and heat stress (a threshold index). The wide range of our projections compares well the CMIP5 multi-model ensemble, especially for temperature-related indices. This suggests that using a single climate model that accounts for key sources of uncertainty can provide an efficient and complementary framework to the more common approach of multi-model ensembles. We also show that greenhouse gas mitigation has the potential to significantly reduce adverse effects (heat stress, risks of pest and disease) of climate change on agriculture, while also curtailing potentially beneficial impacts (earlier planting, possibility for multiple cropping). A major benefit of climate mitigation is potentially preventing changes in several indices to emerge from the noise of natural variability, even by 2100. This has major implications considering that any significant climate change impacts on crop yield would result in nation-wide changes in the agriculture sector. Finally, we argue that the analysis of agro-climate indices should more often complement crop model projections, as they can provide valuable information to better understand the drivers of changes in crop yield and production and thus better inform adaptation decisions.

Uncertainty in future agro-climate projections in the United States and benefits of greenhouse gas mitigation

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

Monier, Erwan; Xu, Liyi; Snyder, Richard

Scientific challenges exist on how to extract information from the wide range of projected impacts simulated by crop models driven by climate ensembles. A stronger focus is required to understand and identify the mechanisms and drivers of projected changes in crop yield. In this study, we investigate the robustness of future projections of five metrics relevant to agriculture stakeholders (accumulated frost days, dry days, growing season length, plant heat stress and start of field operations). We use a large ensemble of climate simulations by the MIT IGSM-CAM integrated assessment model that accounts for the uncertainty associated with different emissions scenarios,more » climate sensitivities, and representations of natural variability. By the end of the century, the US is projected to experience fewer frosts, a longer growing season, more heat stress and an earlier start of field operations-although the magnitude and even the sign of these changes vary greatly by regions. Projected changes in dry days are shown not to be robust. We highlight the important role of natural variability, in particular for changes in dry days (a precipitation-related index) and heat stress (a threshold index). The wide range of our projections compares well the CMIP5 multi-model ensemble, especially for temperature-related indices. This suggests that using a single climate model that accounts for key sources of uncertainty can provide an efficient and complementary framework to the more common approach of multi-model ensembles. We also show that greenhouse gas mitigation has the potential to significantly reduce adverse effects (heat stress, risks of pest and disease) of climate change on agriculture, while also curtailing potentially beneficial impacts (earlier planting, possibility for multiple cropping). A major benefit of climate mitigation is potentially preventing changes in several indices to emerge from the noise of natural variability, even by 2100. This has major implications considering that any significant climate change impacts on crop yield would result in nation-wide changes in the agriculture sector. Lastly, we argue that the analysis of agro-climate indices should more often complement crop model projections, as they can provide valuable information to better understand the drivers of changes in crop yield and production and thus better inform adaptation decisions.« less

Sensitivity of the East African rift lakes to climate variability

NASA Astrophysics Data System (ADS)

Olaka, L.; Trauth, M. H.

2009-04-01

Lakes in the East African Rift have provided excellent proxies to reconstruct past climate changes in the low latitudes. The lakes occupy volcano-tectonic depressions with highly variable climate and hydrological setting, that present a good opportunity to study the climatic and hydrogeological influences on the lake water budget. Previous studies have used lake floor sediments to establish the sensitivity of the East African rift lakes. This study focuses on geomorphology and climate to offer additional or alternative record of lake history that are key to quantifying sensitivity of these lakes as archives to external and internal climatic forcings. By using the published Holocene lake areas and levels, we analyze twelve lakes on the eastern arm of the East African rift; Ziway, Awassa, Turkana, Suguta, Baringo, Nakuru, Elmenteita, Naivasha, Natron, Manyara and compare with Lake Victoria, that occupies the plateau between the east and the western arms of the rift. Using the SRTM data, Hypsometric (area-altitude) analysis has been used to compare the lake basins between latitude 80 North and 30 South. The mean elevation for the lakes, is between 524 and 2262 meters above sea level, the lakes' hypsometric integrals (HI), a measure of landmass volume above the reference plane, vary from 0.31 to 0.76. The aridity index (Ai), defined as Precipitation/ Evapotranspiration, quantifies the water available to a lake, it encompasses land cover and climatic effects. It is lowest (arid) in the basin between the Ethiopian rift and the Kenyan rift and at the southern termination of the Kenyan Rift in the catchments of lake Turkana, Suguta, Baringo and Manyara with values of 0.55, 0.43, 0.43 and 0.5 respectively. And it is highest (wet) in the catchments of, Ziway, Awassa, Nakuru and Naivasha as 1.33,1.03 and 1.2 respectively, which occupy the highest points of the rift. Lake Victoria has an index of 1.42 the highest of these lakes and receives a high precipitation. We use a simple model written on a Matlab code to illustrate the lake volume and area response to climate of surficialy closed, graben shaped and panshaped lake basins. From preliminary results, lake basins that are sensitive to climate variability have a high HI and high aridity index, which will be presented in this conference

Climate change and the economics of biomass energy feedstocks in semi-arid agricultural landscapes: A spatially explicit real options analysis.

PubMed

Regan, Courtney M; Connor, Jeffery D; Raja Segaran, Ramesh; Meyer, Wayne S; Bryan, Brett A; Ostendorf, Bertram

2017-05-01

The economics of establishing perennial species as renewable energy feedstocks has been widely investigated as a climate change adapted diversification option for landholders, primarily using net present value (NPV) analysis. NPV does not account for key uncertainties likely to influence relevant landholder decision making. While real options analysis (ROA) is an alternative method that accounts for the uncertainty over future conditions and the large upfront irreversible investment involved in establishing perennials, there have been limited applications of ROA to evaluating land use change decision economics and even fewer applications considering climate change risks. Further, while the influence of spatially varying climate risk on biomass conversion economic has been widely evaluated using NPV methods, effects of spatial variability and climate on land use change have been scarcely assessed with ROA. In this study we applied a simulation-based ROA model to evaluate a landholder's decision to convert land from agriculture to biomass. This spatially explicit model considers price and yield risks under baseline climate and two climate change scenarios over a geographically diverse farming region. We found that underlying variability in primary productivity across the study area had a substantial effect on conversion thresholds required to trigger land use change when compared to results from NPV analysis. Areas traditionally thought of as being quite similar in average productive capacity can display large differences in response to the inclusion of production and price risks. The effects of climate change, broadly reduced returns required for land use change to biomass in low and medium rainfall zones and increased them in higher rainfall areas. Additionally, the risks posed by climate change can further exacerbate the tendency for NPV methods to underestimate true conversion thresholds. Our results show that even under severe drying and warming where crop yield variability is more affected than perennial biomass plantings, comparatively little of the study area is economically viable for conversion to biomass under $200/DM t, and it is not until prices exceed $200/DM t that significant areas become profitable for biomass plantings. We conclude that for biomass to become a valuable diversification option the synchronisation of products and services derived from biomass and the development of markets is vital. Copyright © 2017 Elsevier Ltd. All rights reserved.

Geographical and climatic gradients of evergreen versus deciduous broad-leaved tree species in subtropical China: Implications for the definition of the mixed forest.

PubMed

Ge, Jielin; Xie, Zongqiang

2017-06-01

Understanding climatic influences on the proportion of evergreen versus deciduous broad-leaved tree species in forests is of crucial importance when predicting the impact of climate change on broad-leaved forests. Here, we quantified the geographical distribution of evergreen versus deciduous broad-leaved tree species in subtropical China. The Relative Importance Value index (RIV) was used to examine regional patterns in tree species dominance and was related to three key climatic variables: mean annual temperature (MAT), minimum temperature of the coldest month (MinT), and mean annual precipitation (MAP). We found the RIV of evergreen species to decrease with latitude at a lapse rate of 10% per degree between 23.5 and 25°N, 1% per degree at 25-29.1°N, and 15% per degree at 29.1-34°N. The RIV of evergreen species increased with: MinT at a lapse rate of 10% per °C between -4.5 and 2.5°C and 2% per °C at 2.5-10.5°C; MAP at a lapse rate of 10% per 100 mm between 900 and 1,600 mm and 4% per 100 mm between 1,600 and 2,250 mm. All selected climatic variables cumulatively explained 71% of the geographical variation in dominance of evergreen and deciduous broad-leaved tree species and the climatic variables, ranked in order of decreasing effects were as follows: MinT > MAP > MAT. We further proposed that the latitudinal limit of evergreen and deciduous broad-leaved mixed forests was 29.1-32°N, corresponding with MAT of 11-18.1°C, MinT of -2.5 to 2.51°C, and MAP of 1,000-1,630 mm. This study is the first quantitative assessment of climatic correlates with the evergreenness and deciduousness of broad-leaved forests in subtropical China and underscores that extreme cold temperature is the most important climatic determinant of evergreen and deciduous broad-leaved tree species' distributions, a finding that confirms earlier qualitative studies. Our findings also offer new insight into the definition and distribution of the mixed forest and an accurate assessment of vulnerability of mixed forests to future climate change.

Mid-latitude shrub steppe plant communities: Climate change consequences for soil water resources

USGS Publications Warehouse

Palmquist, Kyle A.; Schlaepfer, Daniel R.; Bradford, John B.; Lauenroth, Willliam K.

2016-01-01

In the coming century, climate change is projected to impact precipitation and temperature regimes worldwide, with especially large effects in drylands. We use big sagebrush ecosystems as a model dryland ecosystem to explore the impacts of altered climate on ecohydrology and the implications of those changes for big sagebrush plant communities using output from 10 Global Circulation Models (GCMs) for two representative concentration pathways (RCPs). We ask: 1) What is the magnitude of variability in future temperature and precipitation regimes among GCMs and RCPs for big sagebrush ecosystems and 2) How will altered climate and uncertainty in climate forecasts influence key aspects of big sagebrush water balance? We explored these questions across 1980-2010, 2030-2060, and 2070-2100 to determine how changes in water balance might develop through the 21st century. We assessed ecohydrological variables at 898 sagebrush sites across the western US using a process-based soil water model, SOILWAT to model all components of daily water balance using site-specific vegetation parameters and site-specific soil properties for multiple soil layers. Our modeling approach allowed for changes in vegetation based on climate. Temperature increased across all GCMs and RCPs, while changes in precipitation were more variable across GCMs. Winter and spring precipitation was predicted to increase in the future (7% by 2030-2060, 12% by 2070-2100), resulting in slight increases in soil water potential (SWP) in winter. Despite wetter winter soil conditions, SWP decreased in late spring and summer due to increased evapotranspiration (6% by 2030-2060, 10% by 2070-2100) and groundwater recharge (26% and 30% increase by 2030-2060 and 2070-2100). Thus, despite increased precipitation in the cold season, soils may dry out earlier in the year, resulting in potentially longer drier summer conditions. If winter precipitation cannot offset drier summer conditions in the future, we expect big sagebrush regeneration and survival will be negatively impacted, potentially resulting in shifts in the relative abundance of big sagebrush plant functional groups. Our results also highlight the importance of assessing multiple GCMs to understand the range of climate change outcomes on ecohydrology, which was contingent on the GCM chosen.

THE REGRESSION MODEL OF IRAN LIBRARIES ORGANIZATIONAL CLIMATE

PubMed Central

Jahani, Mohammad Ali; Yaminfirooz, Mousa; Siamian, Hasan

2015-01-01

Background: The purpose of this study was to drawing a regression model of organizational climate of central libraries of Iran’s universities. Methods: This study is an applied research. The statistical population of this study consisted of 96 employees of the central libraries of Iran’s public universities selected among the 117 universities affiliated to the Ministry of Health by Stratified Sampling method (510 people). Climate Qual localized questionnaire was used as research tools. For predicting the organizational climate pattern of the libraries is used from the multivariate linear regression and track diagram. Results: of the 9 variables affecting organizational climate, 5 variables of innovation, teamwork, customer service, psychological safety and deep diversity play a major role in prediction of the organizational climate of Iran’s libraries. The results also indicate that each of these variables with different coefficient have the power to predict organizational climate but the climate score of psychological safety (0.94) plays a very crucial role in predicting the organizational climate. Track diagram showed that five variables of teamwork, customer service, psychological safety, deep diversity and innovation directly effects on the organizational climate variable that contribution of the team work from this influence is more than any other variables. Conclusions: Of the indicator of the organizational climate of climateQual, the contribution of the team work from this influence is more than any other variables that reinforcement of teamwork in academic libraries can be more effective in improving the organizational climate of this type libraries. PMID:26622203

THE REGRESSION MODEL OF IRAN LIBRARIES ORGANIZATIONAL CLIMATE.

PubMed

Jahani, Mohammad Ali; Yaminfirooz, Mousa; Siamian, Hasan

2015-10-01

The purpose of this study was to drawing a regression model of organizational climate of central libraries of Iran's universities. This study is an applied research. The statistical population of this study consisted of 96 employees of the central libraries of Iran's public universities selected among the 117 universities affiliated to the Ministry of Health by Stratified Sampling method (510 people). Climate Qual localized questionnaire was used as research tools. For predicting the organizational climate pattern of the libraries is used from the multivariate linear regression and track diagram. of the 9 variables affecting organizational climate, 5 variables of innovation, teamwork, customer service, psychological safety and deep diversity play a major role in prediction of the organizational climate of Iran's libraries. The results also indicate that each of these variables with different coefficient have the power to predict organizational climate but the climate score of psychological safety (0.94) plays a very crucial role in predicting the organizational climate. Track diagram showed that five variables of teamwork, customer service, psychological safety, deep diversity and innovation directly effects on the organizational climate variable that contribution of the team work from this influence is more than any other variables. Of the indicator of the organizational climate of climateQual, the contribution of the team work from this influence is more than any other variables that reinforcement of teamwork in academic libraries can be more effective in improving the organizational climate of this type libraries.

Potential breeding distributions of U.S. birds predicted with both short-term variability and long-term average climate data.

PubMed

Bateman, Brooke L; Pidgeon, Anna M; Radeloff, Volker C; Flather, Curtis H; VanDerWal, Jeremy; Akçakaya, H Resit; Thogmartin, Wayne E; Albright, Thomas P; Vavrus, Stephen J; Heglund, Patricia J

2016-12-01

Climate conditions, such as temperature or precipitation, averaged over several decades strongly affect species distributions, as evidenced by experimental results and a plethora of models demonstrating statistical relations between species occurrences and long-term climate averages. However, long-term averages can conceal climate changes that have occurred in recent decades and may not capture actual species occurrence well because the distributions of species, especially at the edges of their range, are typically dynamic and may respond strongly to short-term climate variability. Our goal here was to test whether bird occurrence models can be predicted by either covariates based on short-term climate variability or on long-term climate averages. We parameterized species distribution models (SDMs) based on either short-term variability or long-term average climate covariates for 320 bird species in the conterminous USA and tested whether any life-history trait-based guilds were particularly sensitive to short-term conditions. Models including short-term climate variability performed well based on their cross-validated area-under-the-curve AUC score (0.85), as did models based on long-term climate averages (0.84). Similarly, both models performed well compared to independent presence/absence data from the North American Breeding Bird Survey (independent AUC of 0.89 and 0.90, respectively). However, models based on short-term variability covariates more accurately classified true absences for most species (73% of true absences classified within the lowest quarter of environmental suitability vs. 68%). In addition, they have the advantage that they can reveal the dynamic relationship between species and their environment because they capture the spatial fluctuations of species potential breeding distributions. With this information, we can identify which species and guilds are sensitive to climate variability, identify sites of high conservation value where climate variability is low, and assess how species' potential distributions may have already shifted due recent climate change. However, long-term climate averages require less data and processing time and may be more readily available for some areas of interest. Where data on short-term climate variability are not available, long-term climate information is a sufficient predictor of species distributions in many cases. However, short-term climate variability data may provide information not captured with long-term climate data for use in SDMs. © 2016 by the Ecological Society of America.

The Pace of Perceivable Extreme Climate Change

NASA Astrophysics Data System (ADS)

Tan, X.; Gan, T. Y.

2015-12-01

When will the signal of obvious changes in extreme climate emerge over climate variability (Time of Emergence, ToE) is a key question for planning and implementing measures to mitigate the potential impact of climate change to natural and human systems that are generally adapted to potential changes from current variability. We estimated ToEs for the magnitude, duration and frequency of global extreme climate represented by 24 extreme climate indices (16 for temperature and 8 for precipitation) with different thresholds of the signal-to-noise (S/N) ratio based on projections of CMIP5 global climate models under RCP8.5 and RCP4.5 for the 21st century. The uncertainty of ToE is assessed by using 3 different methods to calculate S/N for each extreme index. Results show that ToEs of the projected extreme climate indices based on the RCP4.5 climate scenarios are generally projected to happen about 20 years later than that for the RCP8.5 climate scenarios. Under RCP8.5, the projected magnitude, duration and frequency of extreme temperature on Earth will all exceed 2 standard deviations by 2100, and the empirical 50th percentile of the global ToE for the frequency and magnitude of hot (cold) extreme are about 2040 and 2054 (2064 and 2054) for S/N > 2, respectively. The 50th percentile of global ToE for the intensity of extreme precipitation is about 2030 and 2058 for S/N >0.5 and S/N >1, respectively. We further evaluated the exposure of ecosystems and human societies to the pace of extreme climate change by determining the year of ToE for various extreme climate indices projected to occur over terrestrial biomes, marine realms and major urban areas with large populations. This was done by overlaying terrestrial, ecoregions and population maps with maps of ToE derived, to extract ToEs for these regions. Possible relationships between GDP per person and ToE are also investigated by relating the mean ToE for each country and its average value of GDP per person.

Towards a Local-Scale Climate Service for Colombian Agriculture: Findings and Future Perspectives

NASA Astrophysics Data System (ADS)

Ramirez-Villegas, J.; Prager, S.; Llanos, L.; Agudelo, D.; Esquivel, A.; Sotelo, S.; Guevara, E.; Howland, F. C.; Munoz, A.; Rodriguez, J.; Ordonez, L.; Fernandes, K.

2017-12-01

Globally, interannual climate variability explains roughly a third of the yield variation for major crops. In Colombia, interannual climate variations and specially those driven by ENSO can disrupt production, lower farmers' incomes and increase market prices for both urban and rural consumers alike. Farmers in Colombia, however, often plan for the cropping season based on the immediately prior year's experience, which is unlikely to result in successful crops under high climate variability events. Critical decisions for avoiding total investment loss or to ensure successful harvests, including issues related to planting date, what variety to plant, or whether to plant, are made, at best, intuitively. Here, we demonstrate that the combination of better data, skillful seasonal climate forecasts, calibrated crop models, and a web-based climate services platform tailored to users' needs can prove successful in establishing a sustained climate service for agriculture. Rainfall predictability analyses indicate that statistical seasonal climate forecasts are skillful enough for issuing forecasts reliably in virtually all areas, with dry periods generally showing greater predictability than wet periods. Importantly, we find that a better specification of predictor regions significantly enhances seasonal forecast skill. Rice and maize crop models capture well the growth and development of rice and maize crops in experimental settings, and ably simulate historical (1980-2014) variations in productivity. With skillful climate and crop models, we developed a climate services platform that produces seasonal climate forecasts, and connects these with crop models. A usability study of the forecast platform revealed that, from a population of ca. 200 farmers and professionals, roughly two thirds correctly interpreted information and felt both confident and encouraged to use the platform. Nevertheless, capacity strengthening on key agro-climatology concepts was highlighted by farmers as a crucial need. Challenges also arose in certain zones due to limited access to electricity, computers or Internet. Based on our results, we conclude that for a climate service to be truly sustainable, well-calibrated and skillful models are as critical as the co-creation of the service itself with the stakeholder community.

How do Changes in Hydro-Climate Conditions Alter the Risk of Infection With Fasciolosis?

NASA Astrophysics Data System (ADS)

Beltrame, L.; Dunne, T.; Rose, H.; Walker, J.; Morgan, E.; Vickerman, P.; Wagener, T.

2017-12-01

Fasciolosis is a widespread parasitic disease of livestock and is emerging as a major zoonosis. Since the parasite and its intermediate host live and develop in the environment, risk of infection is directly affected by climatic-environmental conditions. Changes in disease prevalence, seasonality and distribution have been reported in recent years and attributed to altered temperature and rainfall patterns, raising concerns about the effects of climate change in the future. Therefore, it is urgent to understand how changes in climate-environmental drivers may alter the dynamics of disease risk in a quantitative way, to guide parasite control strategies and interventions in the coming decades. In a previous work, we developed and tested a novel mechanistic hydro-epidemiological model for Fasciolosis, which explicitly represents the parasite life-cycle in connection with key environmental processes, allowing to capture the impact of previously unseen conditions. In this study, we use the new mechanistic model to assess the sensitivity of infection rates to changes in climate-environmental factors. This is challenging as processes underlying disease transmission are complex and interacting, and may have contrasting effects on the parasite life-cycle stages. To this end, we set up a sensitivity analysis framework to investigate in a structured way which factors play a key role in controlling the magnitude, timing and spread of infection, and how the sensitivity of disease risk varies in time and space. Moreover, we define synthetic scenarios to explore the space of possible variability of the hydro-climate drivers and investigate conditions that lead to critical levels of infection. The study shows how the new model combined with the sensitivity analysis framework can support decision-making, providing useful information for disease management.

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

NASA Astrophysics Data System (ADS)

Deser, C.

2017-12-01

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

Climate-Driven Crop Yield and Yield Variability and Climate Change Impacts on the U.S. Great Plains Agricultural Production.

PubMed

Kukal, Meetpal S; Irmak, Suat

2018-02-22

Climate variability and trends affect global crop yields and are characterized as highly dependent on location, crop type, and irrigation. U.S. Great Plains, due to its significance in national food production, evident climate variability, and extensive irrigation is an ideal region of investigation for climate impacts on food production. This paper evaluates climate impacts on maize, sorghum, and soybean yields and effect of irrigation for individual counties in this region by employing extensive crop yield and climate datasets from 1968-2013. Variability in crop yields was a quarter of the regional average yields, with a quarter of this variability explained by climate variability, and temperature and precipitation explained these in singularity or combination at different locations. Observed temperature trend was beneficial for maize yields, but detrimental for sorghum and soybean yields, whereas observed precipitation trend was beneficial for all three crops. Irrigated yields demonstrated increased robustness and an effective mitigation strategy against climate impacts than their non-irrigated counterparts by a considerable fraction. The information, data, and maps provided can serve as an assessment guide for planners, managers, and policy- and decision makers to prioritize agricultural resilience efforts and resource allocation or re-allocation in the regions that exhibit risk from climate variability.

Site-specific climate analysis elucidates revegetation challenges for post-mining landscapes in eastern Australia

NASA Astrophysics Data System (ADS)

Audet, P.; Arnold, S.; Lechner, A. M.; Baumgartl, T.

2013-10-01

In eastern Australia, the availability of water is critical for the successful rehabilitation of post-mining landscapes and climatic characteristics of this diverse geographical region are closely defined by factors such as erratic rainfall and periods of drought and flooding. Despite this, specific metrics of climate patterning are seldom incorporated into the initial design of current post-mining land rehabilitation strategies. Our study proposes that a few common rainfall parameters can be combined and rated using arbitrary rainfall thresholds to characterise bioregional climate sensitivity relevant to the rehabilitation these landscapes. This approach included assessments of annual rainfall depth, average recurrence interval of prolonged low intensity rainfall, average recurrence intervals of short or prolonged high intensity events, median period without rain (or water-deficit) and standard deviation for this period in order to address climatic factors such as total water availability, seasonality and intensity - which were selected as potential proxies of both short- and long-term biological sensitivity to climate within the context of post-disturbance ecological development and recovery. Following our survey of available climate data, we derived site "climate sensitivity" indexes and compared the performance of 9 ongoing mine sites: Weipa, Mt. Isa and Cloncurry, Eromanga, Kidston, the Bowen Basin (Curragh), Tarong, North Stradbroke Island, and the Newnes Plateau. The sites were then ranked from most-to-least sensitive and compared with natural bioregional patterns of vegetation density using mean NDVI. It was determined that regular rainfall and relatively short periods of water-deficit were key characteristics of sites having less sensitivity to climate - as found among the relatively more temperate inland mining locations. Whereas, high rainfall variability, frequently occurring high intensity events, and (or) prolonged seasonal drought were primary indicators of sites having greater sensitivity to climate - as found among the semi-arid central-inland sites. Overall, the manner in which these climatic factors are identified and ultimately addressed by land managers and rehabilitation practitioners could be a key determinant of achievable success at given locations at the planning stages of rehabilitation design.

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

PubMed

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

2017-11-01

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

Projected climate and agronomic implications for corn production in the Northeastern United States.

PubMed

Prasad, Rishi; Gunn, Stephan Kpoti; Rotz, Clarence Alan; Karsten, Heather; Roth, Greg; Buda, Anthony; Stoner, Anne M K

2018-01-01

Corn has been a pillar of American agriculture for decades and continues to receive much attention from the scientific community for its potential to meet the food, feed and fuel needs of a growing human population in a changing climate. By midcentury, global temperature increase is expected to exceed 2°C where local effects on heat, cold and precipitation extremes will vary. The Northeast United States is a major dairy producer, corn consumer, and is cited as the fastest warming region in the contiguous U.S. It is important to understand how key agronomic climate variables affect corn growth and development so that adaptation strategies can be tailored to local climate changes. We analyzed potential local effects of climate change on corn growth and development at three major dairy locations in the Northeast (Syracuse, New York; State College, Pennsylvania and Landisville, Pennsylvania) using downscaled projected climate data (2000-2100) from nine Global Climate Models under two emission pathways (Representative Concentration Pathways (RCP) 4.5 and 8.5). Our analysis indicates that corn near the end of the 21st century will experience fewer spring and fall freezes, faster rate of growing degree day accumulation with a reduction in time required to reach maturity, greater frequencies of daily high temperature ≥35°C during key growth stages such as silking-anthesis and greater water deficit during reproductive (R1-R6) stages. These agronomic anomalies differ between the three locations, illustrating varying impacts of climate change in the more northern regions vs. the southern regions of the Northeast. Management strategies such as shifting the planting dates based on last spring freeze and irrigation during the greatest water deficit stages (R1-R6) will partially offset the projected increase in heat and drought stress. Future research should focus on understanding the effects of global warming at local levels and determining adaptation strategies that meet local needs.

Uncertainty and extreme events in future climate and hydrologic projections for the Pacific Northwest: providing a basis for vulnerability and core/corridor assessments

USGS Publications Warehouse

Littell, Jeremy S.; Mauger, Guillaume S.; Salathe, Eric P.; Hamlet, Alan F.; Lee, Se-Yeun; Stumbaugh, Matt R.; Elsner, Marketa; Norheim, Robert; Lutz, Eric R.; Mantua, Nathan J.

2014-01-01

The purpose of this project was to (1) provide an internally-consistent set of downscaled projections across the Western U.S., (2) include information about projection uncertainty, and (3) assess projected changes of hydrologic extremes. These objectives were designed to address decision support needs for climate adaptation and resource management actions. Specifically, understanding of uncertainty in climate projections – in particular for extreme events – is currently a key scientific and management barrier to adaptation planning and vulnerability assessment. The new dataset fills in the Northwest domain to cover a key gap in the previous dataset, adds additional projections (both from other global climate models and a comparison with dynamical downscaling) and includes an assessment of changes to flow and soil moisture extremes. This new information can be used to assess variations in impacts across the landscape, uncertainty in projections, and how these differ as a function of region, variable, and time period. In this project, existing University of Washington Climate Impacts Group (UW CIG) products were extended to develop a comprehensive data archive that accounts (in a reigorous and physically based way) for climate model uncertainty in future climate and hydrologic scenarios. These products can be used to determine likely impacts on vegetation and aquatic habitat in the Pacific Northwest (PNW) region, including WA, OR, ID, northwest MT to the continental divide, northern CA, NV, UT, and the Columbia Basin portion of western WY New data series and summaries produced for this project include: 1) extreme statistics for surface hydrology (e.g. frequency of soil moisture and summer water deficit) and streamflow (e.g. the 100-year flood, extreme 7-day low flows with a 10-year recurrence interval); 2) snowpack vulnerability as indicated by the ratio of April 1 snow water to cool-season precipitation; and, 3) uncertainty analyses for multiple climate scenarios.

Managing fish habitat for flow and temperature extremes ...

EPA Pesticide Factsheets

Summer low flows and stream temperature maxima are key drivers affecting the sustainability of fish populations. Thus, it is critical to understand both the natural templates of spatiotemporal variability, how these are shifting due to anthropogenic influences of development and climate change, and how these impacts can be moderated by natural and constructed green infrastructure. Low flow statistics of New England streams have been characterized using a combination of regression equations to describe long-term averages as a function of indicators of hydrologic regime (rain- versus snow-dominated), precipitation, evapotranspiration or temperature, surface water storage, baseflow recession rates, and impervious cover. Difference equations have been constructed to describe interannual variation in low flow as a function of changing air temperature, precipitation, and ocean-atmospheric teleconnection indices. Spatial statistical network models have been applied to explore fine-scale variability of thermal regimes along stream networks in New England as a function of variables describing natural and altered energy inputs, groundwater contributions, and retention time. Low flows exacerbate temperature impacts by reducing thermal inertia of streams to energy inputs. Based on these models, we can construct scenarios of fish habitat suitability using current and projected future climate and the potential for preservation and restoration of historic habitat regimes th

Potential forcings of summer temperature variability of the southeastern Tibetan Plateau in the past 12 ka

NASA Astrophysics Data System (ADS)

Zhang, Enlou; Chang, Jie; Sun, Weiwei; Cao, Yanmin; Langdon, Peter; Cheng, Jun

2018-06-01

Investigating potential forcing mechanisms of terrestrial summer temperature changes from the Asian summer monsoon influenced area is of importance to better understand the climate variability in these densely populated regions. The results of spectral and wavelet analyses of the published chironomid reconstructed mean July temperature data from Tiancai Lake on the SE Tibetan Plateau are presented. The evidence of solar forcing of the summer temperature variability from the site on centennial timescales where key solar periodicities (at 855 ± 40, 465 ± 40, 315 ± 40 and 165 ± 40 year) are revealed. By using a band-pass filter, coherent fluctuations were found in the strength of Asian summer monsoon, Northern Hemisphere high latitude climate and high elevation mid-latitude (26°N) terrestrial temperatures with solar sunspot cycles since about 7.6 ka. The two abrupt cooling events detected from the Tiancai Lake record, centered at ∼9.7 and 3.5 ka were examined respectively. Coupled with the paleoclimate modeling results, the early Holocene event (9.7 ka) is possibly linked to an ocean-atmospheric feedback mechanism whereas the latter event (3.5 ka) may be more directly related to external forcing.

Soil Carbon Recovery of Degraded Steppe Ecosystems of the Mongolian Plateau

NASA Astrophysics Data System (ADS)

Ojima, D. S.; Togtohyn, C.; Qi, J.

2013-12-01

Mongolian steppe grassland systems are critical source of ecosystem services to societal groups in temperate East Asia. These systems are characterized by their arid and semiarid environments where rainfall tends to be too variable or evaporative losses reduce water availability to reliably support cropping systems or substantial forest cover. These steppe ecosystems have supported land use practices to accommodate the variable rainfall patterns, and seasonal and spatial patterns of forage production displayed by the nomadic pastoral systems practiced across Asia. These pastoral systems are dependent on grassland ecosystem services, including forage production, wool, skins, meat and dairy products, and in many systems provide critical biodiversity and land and water protection services which serve to maintain pastoral livelihoods. Precipitation variability and associated drought conditions experienced frequently in these grassland systems are key drivers of these systems. However, during the past several decades climate change and grazing and land use conversion have resulted in degradation of ecosystem services and loss of soil organic matter. Recent efforts in China and Mongolia are investigating different grazing management practices to restore soil organic matter in these degraded systems. Simulation modeling is being applied to evaluate the long-term benefits of different grazing management regimes under various climate scenarios.

Wildfire disturbance impacts on streamflow from western USA watersheds

NASA Astrophysics Data System (ADS)

Cadol, D.; Wine, M.; Makhnin, O.

2017-12-01

Worldwide rapid changes in climate overlaid on changing land management paradigms have dramatically altered ecological disturbance regimes worldwide including in western North America. Ecological disturbances impacted include woody encroachment, pest pathogen complexes, riparian forest changes, and wildfire. These disturbances impact the hydrologic cycle, though the nature of these impacts has been difficult to quantify. Perhaps the greatest challenge is that most basins worldwide are ungauged. Taking wildfire as a globally relevant example of a key ecological disturbance, even within gauged basins, post-wildfire hydrologic response is spatially and temporally variable, affected by a host of variables including fire frequency, area burned, and recovery trajectory. Hydrologic response to wildfire is further understood to be a non-linear function of watershed characteristics and climate. Here we provide a framework that utilizes remote sensing, statistical modeling, field measurements, and geospatial methods to provide first-order estimates of ecological disturbance hydrologic impacts. We apply this framework to compare ecological disturbance hydrologic impacts amongst selected watersheds in the western USA. Here we show that ecological disturbance impacts on hydrology are highly variable, and in many cases have an effect magnitude similar to that modeled for temperature and precipitation changes.

On climate prediction: how much can we expect from climate memory?

NASA Astrophysics Data System (ADS)

Yuan, Naiming; Huang, Yan; Duan, Jianping; Zhu, Congwen; Xoplaki, Elena; Luterbacher, Jürg

2018-03-01

Slowing variability in climate system is an important source of climate predictability. However, it is still challenging for current dynamical models to fully capture the variability as well as its impacts on future climate. In this study, instead of simulating the internal multi-scale oscillations in dynamical models, we discussed the effects of internal variability in terms of climate memory. By decomposing climate state x(t) at a certain time point t into memory part M(t) and non-memory part ɛ (t) , climate memory effects from the past 30 years on climate prediction are quantified. For variables with strong climate memory, high variance (over 20% ) in x(t) is explained by the memory part M(t), and the effects of climate memory are non-negligible for most climate variables, but the precipitation. Regarding of multi-steps climate prediction, a power law decay of the explained variance was found, indicating long-lasting climate memory effects. The explained variances by climate memory can remain to be higher than 10% for more than 10 time steps. Accordingly, past climate conditions can affect both short (monthly) and long-term (interannual, decadal, or even multidecadal) climate predictions. With the memory part M(t) precisely calculated from Fractional Integral Statistical Model, one only needs to focus on the non-memory part ɛ (t) , which is an important quantity that determines climate predictive skills.

Assessing the combined effects of climatic factors on spring wheat phenophase and grain yield in Inner Mongolia, China

PubMed Central

Pu, Feiyu; Li, Yunpeng; Xu, Jingwen; Li, Ning; Zhang, Yi; Guo, Jianping; Pan, Zhihua

2017-01-01

Understanding the regional relationships between climate change and crop production will benefit strategic decisions for future agricultural adaptation in China. In this study, the combined effects of climatic factors on spring wheat phenophase and grain yield over the past three decades in Inner Mongolia, China, were explored based on the daily climate variables from 1981–2014 and detailed observed data of spring wheat from 1981–2014. Inner Mongolia was divided into three different climate type regions, the eastern, central and western regions. The data were gathered from 10 representative agricultural meteorological experimental stations in Inner Mongolia and analysed with the Agricultural Production Systems Simulator (APSIM) model. First, the performance of the APSIM model in the spring wheat planting areas of Inner Mongolia was tested. Then, the key climatic factors limiting the phenophases and yield of spring wheat were identified. Finally, the responses of spring wheat phenophases and yield to climate change were further explored regionally. Our results revealed a general yield reduction of spring wheat in response to the pronounced climate warming from 1981 to 2014, with an average of 3564 kg·ha-1. The regional differences in yields were significant. The maximum potential yield of spring wheat was found in the western region. However, the minimum potential yield was found in the middle region. The air temperature and soil surface temperature were the optimum climatic factors that affected the key phenophases of spring wheat in Inner Mongolia. The influence of the average maximum temperature on the key phenophases of spring wheat was greater than the average minimum temperature, followed by the relative humidity and solar radiation. The most insensitive climatic factors were precipitation, wind speed and reference crop evapotranspiration. As for the yield of spring wheat, temperature, solar radiation and air relative humidity were major meteorological factors that affected in the eastern and western Inner Mongolia. Furthermore, the effect of the average minimum temperature on yield was greater than that of the average maximum temperature. The increase of temperature in the western and middle regions would reduce the spring wheat yield, while in the eastern region due to the rising temperature, the spring wheat yield increased. The increase of solar radiation in the eastern and central regions would increase the yield of spring wheat. The increased air relative humidity would make the western spring wheat yield increased and the eastern spring wheat yield decreased. Finally, the models describing combined effects of these dominant climatic factors on the maturity and yield in different regions of Inner Mongolia were used to establish geographical differences. Our findings have important implications for improving climate change impact studies and for local agricultural production to cope with ongoing climate change. PMID:29099842

Assessing the combined effects of climatic factors on spring wheat phenophase and grain yield in Inner Mongolia, China.

PubMed

Zhao, Junfang; Pu, Feiyu; Li, Yunpeng; Xu, Jingwen; Li, Ning; Zhang, Yi; Guo, Jianping; Pan, Zhihua

2017-01-01

Understanding the regional relationships between climate change and crop production will benefit strategic decisions for future agricultural adaptation in China. In this study, the combined effects of climatic factors on spring wheat phenophase and grain yield over the past three decades in Inner Mongolia, China, were explored based on the daily climate variables from 1981-2014 and detailed observed data of spring wheat from 1981-2014. Inner Mongolia was divided into three different climate type regions, the eastern, central and western regions. The data were gathered from 10 representative agricultural meteorological experimental stations in Inner Mongolia and analysed with the Agricultural Production Systems Simulator (APSIM) model. First, the performance of the APSIM model in the spring wheat planting areas of Inner Mongolia was tested. Then, the key climatic factors limiting the phenophases and yield of spring wheat were identified. Finally, the responses of spring wheat phenophases and yield to climate change were further explored regionally. Our results revealed a general yield reduction of spring wheat in response to the pronounced climate warming from 1981 to 2014, with an average of 3564 kg·ha-1. The regional differences in yields were significant. The maximum potential yield of spring wheat was found in the western region. However, the minimum potential yield was found in the middle region. The air temperature and soil surface temperature were the optimum climatic factors that affected the key phenophases of spring wheat in Inner Mongolia. The influence of the average maximum temperature on the key phenophases of spring wheat was greater than the average minimum temperature, followed by the relative humidity and solar radiation. The most insensitive climatic factors were precipitation, wind speed and reference crop evapotranspiration. As for the yield of spring wheat, temperature, solar radiation and air relative humidity were major meteorological factors that affected in the eastern and western Inner Mongolia. Furthermore, the effect of the average minimum temperature on yield was greater than that of the average maximum temperature. The increase of temperature in the western and middle regions would reduce the spring wheat yield, while in the eastern region due to the rising temperature, the spring wheat yield increased. The increase of solar radiation in the eastern and central regions would increase the yield of spring wheat. The increased air relative humidity would make the western spring wheat yield increased and the eastern spring wheat yield decreased. Finally, the models describing combined effects of these dominant climatic factors on the maturity and yield in different regions of Inner Mongolia were used to establish geographical differences. Our findings have important implications for improving climate change impact studies and for local agricultural production to cope with ongoing climate change.

Assessing climate impacts

PubMed Central

Wohl, Ellen E.; Pulwarty, Roger S.; Zhang, Jian Yun

2000-01-01

Assessing climate impacts involves identifying sources and characteristics of climate variability, and mitigating potential negative impacts of that variability. Associated research focuses on climate driving mechanisms, biosphere–hydrosphere responses and mediation, and human responses. Examples of climate impacts come from 1998 flooding in the Yangtze River Basin and hurricanes in the Caribbean and Central America. Although we have limited understanding of the fundamental driving-response interactions associated with climate variability, increasingly powerful measurement and modeling techniques make assessing climate impacts a rapidly developing frontier of science. PMID:11027321

A vertical hydroclimatology of the Upper Indus Basin and initial insights to potential hydrological change in the region

NASA Astrophysics Data System (ADS)

Forsythe, Nathan; Kilsby, Chris G.; Fowler, Hayley J.; Archer, David R.

2010-05-01

The water resources of the Upper Indus Basin (UIB) are of the utmost importance to the economic wellbeing of Pakistan. The irrigated agriculture made possible by Indus river runoff underpins the food security for Pakistan's nearly 200 million people. Contributions from hydropower account for more than one fifth of peak installed electrical generating capacity in a country where widespread, prolonged load-shedding handicaps business activity and industrial development. Pakistan's further socio-economic development thus depends largely on optimisation of its precious water resources. Confident, accurate projections of future water resource availability and variability are urgent insights needed by development planners and infrastructure managers at all levels. Correctly projecting future hydrological conditions depends first and foremost on a thorough understanding of the underlying mechanisms and processes of present hydroclimatology. The vertical and horizontal spatial variations in key climate parameters (temperature, precipitation) govern the contributions of the various elevation zones and subcatchments comprising the UIB. Trends in this complex mountainous region are highly varied by season and parameter. Observed changes here often do not match general global trends or even necessarily those found in neighbouring regions. This study considers data from a variety sources in order to compose the most complete picture possible of the vertical hydroclimatology of the UIB. The study presents the observed climatology and trends for precipitation and temperature from local observations at long-record meteorological stations (Pakistan Meteorological Department). These data are compared to characterisations of additional water cycle parameters (humidity, cloud, snow cover and snow-water-equivalent) derived from local short-record automatic weather stations, the ECMWF ‘ERA' reanalysis projects and satellite based observations (AVHRR, MODIS, etc). The potential implications of the vertical (hypsometric) distribution of these parameters are considered. Interlinkages between observed changes in these parameters and the evolution of large-scale circulation indices (ENSO, NAO, local vorticity) are also investigated. In parallel to these climatological considerations, the study presents the typology of the observed UIB hydrological regimes -- glacial, nival and pluvial -- including interannual variability as quantified from the available river gauging record. In order to begin to assess potential implications of future climate change on UIB hydrology, key modes of variability in the climate parameters are identified. The study then analyses in detail the corresponding observed anomalies in UIB discharge for years exemplifying these modes. In conclusion, this work postulates potential impacts of changes in the hydrological variability stemming from continuation of estimated present local climatic trends.

CMIP5-downscaled projections for the NW European Shelf Seas: initial results and insights into uncertainties

NASA Astrophysics Data System (ADS)

Tinker, Jonathan; Palmer, Matthew; Lowe, Jason; Howard, Tom

2017-04-01

The North Sea, and wider Northwest European Shelf seas (NWS) are economically, environmentally, and culturally important for a number of European countries. They are protected by European legislation, often with specific reference to the potential impacts of climate change. Coastal climate change projections are an important source of information for effective management of European Shelf Seas. For example, potential changes in the marine environment are a key component of the climate change risk assessments (CCRAs) carried out under the UK Climate Change Act We use the NEMO shelf seas model combined with CMIP5 climate model and EURO-CORDEX regional atmospheric model data to generate new simulations of the NWS. Building on previous work using a climate model perturbed physics ensemble and the POLCOMS, this new model setup is used to provide first indication of the uncertainties associated with: (i) the driving climate model; (ii) the atmospheric downscaling model (iii) the shelf seas downscaling model; (iv) the choice of climate change scenario. Our analysis considers a range of physical marine impacts and the drivers of coastal variability and change, including sea level and the propagation of open ocean signals onto the shelf. The simulations are being carried out as part of the UK Climate Projections 2018 (UKCP18) and will feed into the following UK CCRA.

Geographic patterns of networks derived from extreme precipitation over the Indian subcontinent

NASA Astrophysics Data System (ADS)

Stolbova, Veronika; Bookhagen, Bodo; Marwan, Norbert; Kurths, Juergen

2014-05-01

Complex networks (CN) and event synchronization (ES) methods have been applied to study a number of climate phenomena such as Indian Summer Monsoon (ISM), South-American Monsoon, and African Monsoon. These methods proved to be powerful tools to infer interdependencies in climate dynamics between geographical sites, spatial structures, and key regions of the considered climate phenomenon. Here, we use these methods to study the spatial temporal variability of the extreme rainfall over the Indian subcontinent, in order to filter the data by coarse-graining the network, and to identify geographic patterns that are signature features (spatial signatures) of the ISM. We find four main geographic patterns of networks derived from extreme precipitation over the Indian subcontinent using up-to-date satellite-derived, and high temporal and spatial resolution rain-gauge interpolated daily rainfall datasets. In order to prove that our results are also relevant for other climatic variables like pressure and temperature, we use re-analysis data provided by the National Center for Environmental Prediction and National Center for Atmospheric Research (NCEP/NCAR). We find that two of the patterns revealed from the CN extreme rainfall analysis coincide with those obtained for the pressure and temperature fields, and all four above mentioned patterns can be explained by topography, winds, and monsoon circulation. CN and ES enable to select the most informative regions for the ISM, providing realistic description of the ISM dynamics with fewer data, and also help to infer geographic pattern that are spatial signatures of the ISM. These patterns deserve a special attention for the meteorologists and can be used as markers of the ISM variability.

Land surface temperature over global deserts: Means, variability, and trends

NASA Astrophysics Data System (ADS)

Zhou, Chunlüe; Wang, Kaicun

2016-12-01

Land surface air temperature (LSAT) has been a widely used metric to study climate change. Weather observations of LSAT are the fundamental data for climate change studies and provide key evidence of global warming. However, there are very few meteorological observations over deserts due to their uninhabitable environment. This study fills this gap and provides independent evidence using satellite-derived land surface temperatures (LSTs), benefiting from their global coverage. The frequency of clear sky from MODerate Resolution Imaging Spectroradiometer (MODIS) LST data over global deserts was found to be greater than 94% for the 2002-2015 period. Our results show that MODIS LST has a bias of 1.36°C compared to ground-based observations collected at 31 U.S. Climate Reference Network (USCRN) stations, with a standard deviation of 1.83°C. After bias correction, MODIS LST was used to evaluate existing reanalyses, including ERA-Interim, Japanese 55-year Reanalysis (JRA-55), Modern-Era Retrospective Analysis for Research and Applications (MERRA), MERRA-land, National Centers for Environmental Prediction (NCEP)-R1, and NCEP-R2. The reanalyses accurately reproduce the seasonal cycle and interannual variability of the LSTs, but their multiyear means and trends of LSTs exhibit large uncertainties. The multiyear averaged LST over global deserts is 23.5°C from MODIS and varies from 20.8°C to 24.5°C in different reanalyses. The MODIS LST over global deserts increased by 0.25°C/decade from 2002 to 2015, whereas the reanalyses estimated a trend varying from -0.14 to 0.10°C/decade. The underestimation of the LST trend by the reanalyses occurs for approximately 70% of the global deserts, likely due to the imperfect performance of the reanalyses in reproducing natural climate variability.

Global Meteorological Drought: A Synthesis of Current Understanding with a Focus on SST Drivers of Precipitation Deficits

NASA Technical Reports Server (NTRS)

Schubert, S.; Stewart, R.; Wang, H.; Barlow, M.; Berbery, H.; Cai, W.; Hoerling, M.; Kanikicharla, K.; Koster, R.; Lyon, B.;

Fire Patterns and Drivers of Fires in the West African Tropical Forest

NASA Astrophysics Data System (ADS)

Dwomoh, F. K.; Wimberly, M. C.

2015-12-01

The West African tropical forest (referred to as the Upper Guinean forest, UGF), is a global biodiversity hotspot providing vital ecosystem services for the region's socio-economic and environmental wellbeing. It is also one of the most fragmented and human-modified tropical forest ecosystems, with the only remaining large patches of original forests contained in protected areas. However, these remnant forests are susceptible to continued fire-mediated degradation and forest loss due to intense climatic, demographic and land use pressures. We analyzed human and climatic drivers of fire activity in the sub-region to better understand the spatial and temporal patterns of these risks. We utilized MODIS active fire and burned area products to identify fire activity within the sub-region. We measured climatic variability using TRMM rainfall data and derived indicators of human land use from a variety of geospatial datasets. We used a boosted regression trees model to determine the influences of predictor variables on fire activity. Our analyses indicated that the spatial and temporal variability of precipitation is a key driving factor of fire activity in the UGF. Anthropogenic effects on fire activity in the area were evident through the influences of agriculture and low-density populations. These human footprints in the landscape make forests more susceptible to fires through forest fragmentation, degradation, and fire spread from agricultural areas. Forested protected areas within the forest savanna mosaic experienced frequent fires, whereas the more humid forest areas located in the south and south-western portions of the study area had fewer fires as these rainforests tend to offer some buffering against fire encroachment. These results improve characterization of UGF fire regime and expand our understanding of the spatio-temporal dynamics of tropical forest fires in response to human and climatic pressures.

Solar Variability in the Context of Other Climate Forcing Mechanisms

NASA Technical Reports Server (NTRS)

Hansen, James E.

1999-01-01

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

Shrub growth response to climate across the North Slope of Alaska

NASA Astrophysics Data System (ADS)

Ackerman, D.; Griffin, D.; Finlay, J. C.; Hobbie, S. E.

2016-12-01

Warmer temperatures at high latitudes are driving the expansion of woody shrubs in arctic tundra, yielding feedbacks to regional carbon cycling. Accounting for these feedbacks in global climate models will require accurate predictions of the spatial extent of shrub expansion within arctic tundra. While dendroecological approaches have proven useful in understanding how shrubs respond to climate, empirical studies to date are limited in spatial extent, often to just one or two sites within a landscape. A recent meta-analysis of such dendroecological studies hypothesizes that soil moisture is a key variable in determining climate sensitivity of arctic shrub growth. We present the first regional-scale empirical test of this hypothesis by analyzing inter-annual radial growth of deciduous shrubs across soil moisture gradients throughout the North Slope of Alaska. Contrary to expectation, riparian shrubs in high-moisture environments showed no climate sensitivity, while shrubs growing in drier upland sites showed a strong positive growth response to summer temperature. These results proved robust to a variety of detrending functions ranging from conservative (negative exponential) to data adaptive (20-year cubic smoothing spline). These findings call into question the role of soil moisture in determining the climate sensitivity of arctic shrubs and further highlight the importance of unified, regional-scale sampling strategies in understanding climate-vegetation links.